BEGIN:VCALENDAR VERSION:2.0 X-WR-CALNAME:5thworldconferenceoninformations X-WR-CALDESC:Event Calendar METHOD:PUBLISH CALSCALE:GREGORIAN PRODID:-//Sched.com 5th World Conference on Information Systems for Business Management//EN X-WR-TIMEZONE:UTC BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T160000Z DTEND:20261017T164500Z SUMMARY:Registration with Networking Tea / Coffee DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:36546c415c3c8898a3269d947d34c3d0 URL:http://5thworldconferenceoninformations.sched.com/event/36546c415c3c8898a3269d947d34c3d0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T164500Z DTEND:20261017T170000Z SUMMARY:Pre Conference Discussion DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:2c1c37291c1825106a0f7a370f2bc6e8 URL:http://5thworldconferenceoninformations.sched.com/event/2c1c37291c1825106a0f7a370f2bc6e8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T170000Z DTEND:20261017T171000Z SUMMARY:Welcome Address By DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:0a55162c22a96976135e8b2f83ac93f8 URL:http://5thworldconferenceoninformations.sched.com/event/0a55162c22a96976135e8b2f83ac93f8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T171000Z DTEND:20261017T172500Z SUMMARY:Address By Invited Guest & Keynote Speaker DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:426271d47250fa2bf422d66d851377a2 URL:http://5thworldconferenceoninformations.sched.com/event/426271d47250fa2bf422d66d851377a2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T172500Z DTEND:20261017T174000Z SUMMARY:Address By Invited Guest & Keynote Speaker DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:770fcfa5737fb6f2087382831d16f31a URL:http://5thworldconferenceoninformations.sched.com/event/770fcfa5737fb6f2087382831d16f31a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T174000Z DTEND:20261017T175500Z SUMMARY:Address By Invited Guest & Keynote Speaker DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:26c54a6c282e2368514e746e2f7b4351 URL:http://5thworldconferenceoninformations.sched.com/event/26c54a6c282e2368514e746e2f7b4351 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T175500Z DTEND:20261017T181000Z SUMMARY:Address By Invited Guest & Keynote Speaker DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:966ea9e263fea883b1ddc7069a4fb82e URL:http://5thworldconferenceoninformations.sched.com/event/966ea9e263fea883b1ddc7069a4fb82e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T181000Z DTEND:20261017T182500Z SUMMARY:Address By Special Guest DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:465aec7fd22a94e91800f92c892b0870 URL:http://5thworldconferenceoninformations.sched.com/event/465aec7fd22a94e91800f92c892b0870 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T182500Z DTEND:20261017T183000Z SUMMARY:Vote of Appreciation DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:75e47ac90e377c531303c8a6ed3213b3 URL:http://5thworldconferenceoninformations.sched.com/event/75e47ac90e377c531303c8a6ed3213b3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T183000Z DTEND:20261017T184000Z SUMMARY:Felicitation & Group Photograph DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:dcee37ddab16af42e63325a581ce497f URL:http://5thworldconferenceoninformations.sched.com/event/dcee37ddab16af42e63325a581ce497f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T184000Z DTEND:20261017T190000Z SUMMARY:Networking Tea / Coffee & Snack DESCRIPTION: CATEGORIES:INAUGURAL SESSION LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:bfea9b90f7fbec4a3e78dbb91778e6ed URL:http://5thworldconferenceoninformations.sched.com/event/bfea9b90f7fbec4a3e78dbb91778e6ed END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T190000Z DTEND:20261017T191500Z SUMMARY:Blockchain-Enhanced Federated Learning for Privacy-Preserving Model Training in Cloud Computing Systems DESCRIPTION:Authors - Nitin Varshney\, Harsh Nagar\, Dhaval Pambhar\, Krunal Vaghela Abstract - Federated Learning (FL) lets multiple devices work together to train a model while keeping data private. However\, it has problems with managing trust\, keeping the model’s integrity\, and finding malicious participants in cloud environments. This article suggests TrustFLChain\, a block-chain based FL framework that combines a decentralized trust management system with a scheme for collecting models based on deep learning. TrustFLChain uses a consortium blockchain to make sure that model updates can’t be changed\, that participants’ trust is evaluated in a strong way using a hybrid identity-behavior trust model\, and that the Proof-of-Trust (PoT) consensus mechanism works well. Trust scoring and the fraudulent detection updates are both automated by the use of smart contracts. Testing done on variety of datasets like the CIFAR-10\, MNIST\, and ImageNet shows that TrustFLChain is 6.5% more accurate\, 38% faster to identify harmful updates\, 28% faster at reaching a consensus\, and 22% less energy-hungry than the current best methods. Significant improvements are supported by statistical studies (p < 0.01). TrustFLChain provides a flexible\, safe\, and private way to use trusted AI in cloud systems\, perfect for a wide range of uses. CATEGORIES:PHYSICAL TECHNICAL SESSION 1A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:f25825dbb6a8a44d343b71f1ac24b306 URL:http://5thworldconferenceoninformations.sched.com/event/f25825dbb6a8a44d343b71f1ac24b306 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T190000Z DTEND:20261017T191500Z SUMMARY:Encoding for Topic Modeling: Comparing Quality of Encoding Models for Topic Mining in Unstructured Textual Data DESCRIPTION:Authors - \;Ivan Blekanov\, Svetlana S. Bodrunova\, Li Jing\, Mohsin Hassan Khan\nAbstract - \;Traditional data mining techniques\, while effective for structured nu-merical data\, struggle with the complexity\, ambiguity\, and dynamic nature of natural language. To address these challenges\, topic models have emerged as a powerful tool for uncovering latent topic structures in text\, enabling applications such as trend analysis\, recommendation systems\, and decision support. These models are particularly valuable in social network content analysis\, where they help reveal user behavior\, information dissemination patterns\, and social dynam-ics by identifying implicit topic distributions. The linguistic diversity of text data lowers the quality of the topic models. To overcome this shortcoming\, Trans-former-based text encoding is applied. However\, benchmarks for text encoding are not set\, and the models have not been properly compared in terms of dimen-sionality/noise reduction. We conduct comparative analysis of five neural-net-work encoding models based on the Transformer architecture\, integrating them with clustering methods for efficient topic detection. We employ a dataset of COVID-related discussions from Twitter collected between November 24\, 2021\, and January 23\, 2022. The methodology pipeline includes text encoding\, dimen-sionality reduction\, and clustering\, with detailed steps and results discussed in the respective sections. The results show that the encoding models differ substan-tially in how they help in topic detection\, with the general text embedding (GTE) model providing for the best quality. Our findings highlight the models’ differing efficiency in topic detection\, offering insights for future research and practical applications in text analysis and knowledge discovery. CATEGORIES:PHYSICAL TECHNICAL SESSION 1B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:53ecf8c18aed8a0ae1063fed0efe8dd0 URL:http://5thworldconferenceoninformations.sched.com/event/53ecf8c18aed8a0ae1063fed0efe8dd0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T190000Z DTEND:20261017T191500Z SUMMARY:The Multivariate Impacts of ESG Practices on Logistics Business Sustainability in Southeast Asia: The Mediating Role of Time-Critical Logistics DESCRIPTION:Authors - Truong Cong Hau\, Nguyen Quoc Cuong\, Tran Tat Dat\, Duong Ngoc Anh\, Nguyen Son Duong Abstract - In an era of increasing environmental awareness and social accountability\, ESG (Environment\, Social\, and Governance) practices have become a strategic priority for logistics enterprises in Southeast Asia. This study aims to model the multivariate impacts of ESG implementation on firm sustainability\, with a particular focus on the mediating role of Time-Critical Logistics (TCL). ESG integration is expected to enhance environmental performance\, social responsibility\, and governance transparency\, while TCL supports the efficiency of time-critical logistics operations. Using a quantitative approach and Structural Equation Modeling (SEM)\, the study analyzes data from 369 from major logistics enterprises in Southeast Asia. Findings are anticipated to confirm the positive influence of ESG on sustainability\, with TCL playing a key mediating role. CATEGORIES:PHYSICAL TECHNICAL SESSION 1C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:23bdc76f18b5fc2a6a1da3a2b9bd6cc1 URL:http://5thworldconferenceoninformations.sched.com/event/23bdc76f18b5fc2a6a1da3a2b9bd6cc1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T190000Z DTEND:20261017T191500Z SUMMARY:Enhancing Resource Management in Dyeing Industry Supply Chain Using Artificial Intelligence DESCRIPTION:Authors - Palash Sontakke\, Pankaj Chandre\, Prashant Dhotre\, Ganesh Pathak Abstract - The dyeing segment of textile manufacturing faces pressing demands to curb water\, energy and chemical consumption while maintaining colour con-sistency and fast throughput. This paper presents a layered edge‑to‑cloud archi-tecture that employs artificial‑intelligence techniques to manage resources dy-namically across the entire dyeing supply chain. IoT sensors on each dyeing machine stream high‑frequency telemetry to an AI cloud where data are curated in a scalable lake and enriched through feature engineering. Deep‑learning models forecast short‑term demand\, yields and process drifts\, enabling proac-tive recipe adjustments. A digital‑twin simulation engine mirrors every dye bath and tank\, permitting insilico experimentation of eco‑friendly formulas without risking live production. Reinforcement‑learning agents\, trained against the twin\, generate near‑optimal job schedules and set‑points that minimise water and chemical footprints while respecting delivery constraints. All recommendations pass through an explainable‑AI module that surfaces the key factors driving each decision to foster operator trust and regulatory compliance. A blockchain ledger records batch‑level resource transactions\, ensuring tamper‑proof tracea-bility for audits and sustainability certifications. The architecture integrates seamlessly with existing ERP/MES systems\, closing the loop between predic-tive intelligence and shop‑floor actuation. Proof‑of‑concept results from a mid‑scale dye house show up to 18 % water savings and 12 % energy reduction\, with payback achieved in under nine months. Collectively\, the proposed framework demonstrates how advanced AI and Industry 4.0 technologies can deliver both economic and environmental gains in dyeing operations. CATEGORIES:PHYSICAL TECHNICAL SESSION 1D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:90a671f18f90400359c5ee5e80cec929 URL:http://5thworldconferenceoninformations.sched.com/event/90a671f18f90400359c5ee5e80cec929 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T191500Z DTEND:20261017T193000Z SUMMARY:Advancements in Machine Learning: Algorithms\, Applications\, and Emerging Research Directions DESCRIPTION:Authors - Harsh Nagar\, Nitin Varshney\, Twinkal Chavda\, Krunal Vaghela Abstract - Machine learning (ML) produce a huge impact in the Fourth Industrial Revolution that will change everything. ML makes systems very precise and efficient in many sectors like as cyber security\, healthcare\, smart cities\, and farming that is good for the environment. This article examines the different aspects and advancements in machine learning since 2021. It cover wide area which gives more details and fill gaps in crucial fields like ethical AI\, real-time processing\, energy efficiency\, explainability\, federated learning\, and adversarial stability. We investigate supervised\, unsupervised\, semi-supervised\, reinforcement\, and deep learning algorithms\, supported by solid theoretical frameworks\, mathematical formulations\, and empirical evaluations on extensive benchmark datasets (e.g.\, MNIST\, CIFAR-10\, NSL-KDD\, UCI datasets). These contributions include deep study of performance evaluations\, visual representations crafted with Python\, and architectural frameworks for hybrid machine learning systems. These diverse results shows that how things work and implement in the real world and mark the difficulties like bias\, scalability\, and latency. The future will be about ML solutions that are precise\, accurate\, adaptable\, and durable. This publication offers scholars and practitioners a technological framework that fosters innovation in the Fourth Industrial Revolution (4IR). CATEGORIES:PHYSICAL TECHNICAL SESSION 1A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:0321c2f9c2449161d05e592bb00111aa URL:http://5thworldconferenceoninformations.sched.com/event/0321c2f9c2449161d05e592bb00111aa END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T191500Z DTEND:20261017T193000Z SUMMARY:Investment Preferences and Risk Appetite— A Financial Behavior Study Between Generation Z and Generation Y Investors DESCRIPTION:Authors - Irappa Alagur\, Prayag Gokhale Abstract - Managing finance is an important skill that differs across the generations\, influenced by their investment preference and risk-taking ability. This study is an explorative study that reveals the investment preference\, awareness\, participation and risk tolerance among Generation Z and Generation Y. Thes research is undertaken with the objectives to examine the investment awareness amongst Gen Z and Gen Y investors\, their future investment choices and assess their risk tolerance level. For the study\, convenience sampling technique is used with structured questionnaire for data collection from 100 respondents confined to Bangalore\, the silicon city of India. The questionnaire is designed to include 15 questions\; all are set in google form and distributed amongst the intended audience on selective bases fulfilling the criteria and requirement. The responses are captured and presented in pictorial diagrams. The authors analyzed all the responses separately. The findings of the study revealed that Generation Zs are risk-taking investors\, and they prefer to have investment in high liquid funds and unfamiliar markets where outcome is hard to predict to leverage risk with return. It is also found that Gen Zs are very volatile in keeping their investment in a particular fund and rollover frequently to satisfy their short-term requirements. In contrast\, it is observed from the analysis that Generation Y investors are risk-avoidable and prefer to invest in stable and long-term assets like fixed deposits and commodities. They prefer to invest in a familiar market with low volatility where risk is minimum with constant return. CATEGORIES:PHYSICAL TECHNICAL SESSION 1B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:1b07cbc1ab69a3c3c2dec10ca85a55af URL:http://5thworldconferenceoninformations.sched.com/event/1b07cbc1ab69a3c3c2dec10ca85a55af END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T191500Z DTEND:20261017T193000Z SUMMARY:Enterprise Intrusion Detection Using Ensemble CNN-LSTM-GBM: Cross Scale Performance Analysis DESCRIPTION:Authors - Tam Nguyen Minh\, Tai Vu Thanh\, Quynh Chi Truong\, Thi Ai Thao Nguyen Abstract - The growing reliance of enterprises on internal and information systems has led to an increased risk of cyber attacks\, which pose serious threats to the confidentiality\, integrity and availability of data. Intrusion Detection Systems (IDS) are essential for identifying malicious activities\; however\, conventional IDS approaches often struggle with evolving and sophisticated attack vectors. Recent advances in machine learning (ML) offer new opportunities to enhance IDS capabilities through adaptive and data-driven models. This study proposes a hybrid architecture that integrates convolutional neural networks (CNN)\, long-short-term memory (LSTM)\, and gradient boosting machines (GBM)\, leveraging both supervised learning and advanced feature representation techniques\, addressing key challenges such as limited labeled data\, diverse traffic patterns\, and resource constraints in small and medium enterprises (SMEs). The proposed approach includes an end-to-end pipeline for data collection\, preprocessing\, feature extraction\, and data labeling\, combined with aug-mentation techniques to improve model generalization. Experimental evaluation across different network scales demonstrates the effectiveness of the method in detecting both known and novel attack types\, while maintaining computational efficiency. The findings contribute to a practical and scalable solution for enter-prise network security\, with implications for real-world IDS deployment and fu-ture research in ML-driven cybersecurity. CATEGORIES:PHYSICAL TECHNICAL SESSION 1C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:b7bb7ee99197272ed3c5cbfe0069172a URL:http://5thworldconferenceoninformations.sched.com/event/b7bb7ee99197272ed3c5cbfe0069172a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T191500Z DTEND:20261017T193000Z SUMMARY:ENVIRONMENTAL\, SOCIAL AND GOVERNANCE DISCLOSURE & PRICE SYNCHRONICITY: A STUDY OF AUSTRALIAN MINING COMPANIES DESCRIPTION:Authors - Princessa Natasya Kwang\, Yanthi Hutagaol-Martowidjojo Abstract - This research analyzes the effect of ESG disclosure scores on stock price synchronicity among Australian mining companies\, exploring each pillar's contribution. The final sample consists of 275 firm-year observations of Australian listed mining companies covering the period from 2020 to 2024. Data was collected from Bloomberg and Factset. This study adopts the price synchronicity model proposed by Hutagaol-Martowidjojo et al. (2023) and panel data regression is employed to analyse and test the research hypotheses. The study concludes that ESG disclosure is significantly associated with higher price synchronicity\, implying that while ESG disclosure scores enhance overall market visibility\, they may simultaneously reduce the uniqueness of firm-specific information. CATEGORIES:PHYSICAL TECHNICAL SESSION 1D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:2164af0c0d1d6e3e4241adce9d585797 URL:http://5thworldconferenceoninformations.sched.com/event/2164af0c0d1d6e3e4241adce9d585797 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T193000Z DTEND:20261017T194500Z SUMMARY:Smart and Secure Electronic Voting Machine DESCRIPTION:Authors - \;Mayur Rajendra Badiger\, Tejasvi Bellubbi\, Aditya Holla\, Jayanth H T\, Kavitha Devi CS\nAbstract - \;India\, as the world’s largest democracy\, faces the ongoing challenge of low voter turnout\, with recent national elections recording a participation rate of just 65.79%. This issue is exacerbated by the existing electoral requirement that voters be physically present in their registered constituencies\, effectively disenfranchising millions of migrant workers and citizens residing away from home. The proposed Smart and Secure Electronic Voting System addresses this critical gap by enabling inter-state voting\, allowing eligible voters to cast ballots for their home constituencies from any location across the country. Built on an Arduino Uno platform\, the system integrates biometric fingerprint authentication to ensure secure and unique voter identification\, while an LCD interface displays constituency-specific candidate lists. Votes are securely transmitted and stored in a cloud-based database via a WiFi module\, using the ThingSpeak server for real-time\, tamper-resistant data management. The system prevents multiple voting attempts by locking out voters after a successful ballot submission\, thereby upholding electoral integrity. By combining IoT technologies and robust biometric verification\, this solution not only simplifies the voting process for the floating population but also strengthens the inclusivity\, accessibility\, and representativeness of the Indian democratic process. CATEGORIES:PHYSICAL TECHNICAL SESSION 1A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:05c2831969989135d8d2a54592ae944a URL:http://5thworldconferenceoninformations.sched.com/event/05c2831969989135d8d2a54592ae944a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T193000Z DTEND:20261017T194500Z SUMMARY:Do mergers create value? An empirical study between merged and non-merged public sector banks in India DESCRIPTION:Authors - Trilochan Jena\, Pradipta Kumar Sanyal Abstract - A key role of mergers and acquisitions (M&A) is to help businesses grow rapidly in competitive markets. Foreign companies entering the Indian market have made it tough for small businesses. Using mergers and acquisitions (M&A) and restructuring has become a standard practice to ensure a company’s survival\, advancement\, and competitiveness. A significant number of bank mergers have occurred in India over the past decade\, prompting many to wonder whether they have been efficient in adding value for bank owners. The analysis pairs four public sector banks post-merger—SBI\, PNB\, BOB\, and Canara Bank—with four other public sector banks that did not merge—IOB\, UCB\, BOI\, and CBI—all based on their market capitalization. To measure organic growth\, Current Ratio\, Advance to Deposit Ratio\, NPA to Advance Ratio\, Capital Adequacy Ratio\, Operating Profit Ratio\, Net Profit Ratio\, Interest Coverage Ratio\, EPS\, and Dividend Payout Ratio are reviewed. We analyze inorganic growth using the Standard Event Study Methodology in a period from -200 to +30 days. Financial and operational results were better for merged banks than for non-merged banks following the merger. Although the AR and CAR results for mergers were mainly positive\, they did not reach a level of statistical significance. Each merged bank displayed sound financial performance based on its Altman Z-score (>2.6). Overall\, M&As help shareholders\, and yet banks that haven’t merged take care of the remaining issues proactively. CATEGORIES:PHYSICAL TECHNICAL SESSION 1B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:66506c556710ee389d794e7f6646b174 URL:http://5thworldconferenceoninformations.sched.com/event/66506c556710ee389d794e7f6646b174 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T193000Z DTEND:20261017T194500Z SUMMARY:Hybrid Machine Learning Framework for Burnout and Retention Modeling in Urban Indian IT Employees DESCRIPTION:Authors - Niranjan C Kundur\, Anil B C\, Sreenatha M\, Jayasimha S R Abstract - A hybrid machine learning framework designed to predict burnout levels and employee retention among IT professionals in urban India a sector increasingly challenged by mental health issues\, high attrition\, and work-life imbalance. The proposed framework integrates Gradient Boosting Regression for continuous burnout score prediction and Random Forest Classification for binary retention outcomes. Data were collected from 300 IT employees across five metropolitan firms\, encompassing cross-sectional and temporal variables related to work conditions\, wellness policies\, and demographic profiles. Rigorous preprocessing\, feature encoding\, and 5-fold cross-validation ensured robust model performance. The burnout prediction model achieved an R² score of 0.87 and a Mean Absolute Error (MAE) of 4.12\, while the retention classifier yielded an accuracy of 85%\, F1-score of 0.82\, and AUC-ROC of 0.88. Key predictors included flexible hours\, remote work options\, and job satisfaction\, with gender emerging as a significant moderating factor—female employees demonstrated 12% greater sensitivity to burnout-related outcomes. The findings highlight the utility of predictive analytics in identifying high-risk employees and guiding personalized wellness and retention strategies. This hybrid framework offers HR leaders a scalable\, data-driven tool to optimize workforce well-being and reduce attrition in the evolving landscape of Indian IT workplaces. CATEGORIES:PHYSICAL TECHNICAL SESSION 1C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:e8414859cbcd2b643b498c35b758fb2c URL:http://5thworldconferenceoninformations.sched.com/event/e8414859cbcd2b643b498c35b758fb2c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T193000Z DTEND:20261017T194500Z SUMMARY:A Machine Learning – Genetic Algorithm Based Media Mix Modeling DESCRIPTION:Authors - \;Thejan Dulara\, Indra Mahakalanda\, Prasanga Jayathunga\nAbstract - \;Media budget allocation remains a major challenge in the advertising industry. Inefficient spending and biased budgeting decisions often cause un-derperforming campaigns. It is a challenge for advertisers to strike the right balance between traditional media like TV\, radio\, press and the digital media. This not only wastes resources but reduces campaign impact. Media mix problem revolves around media performance and return on investment. This study develops a data-driven media mix determination model using machine learning and genetic algorithms. The goal is to maximize audience reach while minimizing costs. The model focuses on key quantitative factors such as cost-effectiveness\, media efficiency\, and saturation points. The use of data collected from the Sri Lankan market ensures the practical relevance of the study. Supervised machine learning models such as decision trees\, random forests\, XGBoost\, and LightGBM are tested to understand the complex\, non-linear behavior of media performance. The above models predict how different channels respond to increased spending. Curve smoothing enables the identification of saturation point and efficiency levels. A genetic algorithm deployed to identify the optimal budget allocation across media platforms. The result provides a practical media mix for the Sri Lankan advertising industry where advertising planners can allocate budgets more effectively with minimum overspends to achieve higher campaign success. Although the models were learned using a country specific data set\, they can be used for similar scale markets. This study contributes to the existing literature by developing an efficient method for me-dia advertising planning. CATEGORIES:PHYSICAL TECHNICAL SESSION 1D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:f42422d1859dc05713404bff246e9777 URL:http://5thworldconferenceoninformations.sched.com/event/f42422d1859dc05713404bff246e9777 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T194500Z DTEND:20261017T200000Z SUMMARY:Integrating Financial Therapy with Financial Literacy Programs DESCRIPTION:Authors - Niranjan Kulkarni\, Suma MN Abstract - This paper introduces an integrated model that couples financial literacy training with financial therapy to enhance financial knowledge as well as behavioural results. Basing its argument on existing literature\, this study employs a mixed-methods methodology to assess the effectiveness of pilot programs that blend therapeutic interventions like cognitive-behavioural therapy (CBT) and financial counselling with standard financial education. The study unveils the need for an integrated financial education approach\, providing a model for the development of more effective financial literacy programs that consider cognitive as well as affective dimensions of financial well-being. CATEGORIES:PHYSICAL TECHNICAL SESSION 1A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:b3666dd5a48de001fcce2b83d2485d1c URL:http://5thworldconferenceoninformations.sched.com/event/b3666dd5a48de001fcce2b83d2485d1c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T194500Z DTEND:20261017T200000Z SUMMARY:A Low-Cost Obstacle Avoidance System Prototype for Autonomous Wheelchairs Using a Servo-Mounted Ultrasonic Sensor DESCRIPTION:Authors - Wirote Jongchanachavawat\, Noppon Mingmuang\, Chayut Ployjirapas\, Kwanchai Nanan\, Kamonwan Oiumekha\, Noppong Cheychuen\, Wannatham Noyklay\, Polaphat Laima\, Suphat Bunyarittikit Abstract - This research presents the development of a low-cost obstacle avoidance prototype designed for mobile robotic applications\, with a potential use case in autonomous wheelchairs. The system utilizes a single ultrasonic sensor mounted on a servo motor to perform multi-directional distance scanning\, allowing the robot to detect and avoid obstacles in real time. An Arduino-based control algorithm interprets distance measurements at four predefined angles (30°\, 60°\, 120°\, and 150°)\, enabling the robot to make navigation decisions including forward movement\, turns\, and retreating actions.The system was tested under various conditions: with obstacles in front\, in front-left\, and in all directions (front\, left\, and right). Results showed a 100% success rate in the simple frontal obstacle scenario\, 80% in the front - left obstacle case\, and 60% in the most complex environment with obstacles on three sides. The primary cause of failure was the sensor's limitation in detecting very close objects (less than 2 cm).The findings confirm the feasibility of implementing this single-sensor approach in low-cost assistive mobility devices. The prototype demonstrates effective navigation capabilities and provides a practical foundation for future development of intelligent obstacle-avoidance systems for autonomous wheelchairs. CATEGORIES:PHYSICAL TECHNICAL SESSION 1B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:0a9f5b382c1e28c6827cd12c5782d032 URL:http://5thworldconferenceoninformations.sched.com/event/0a9f5b382c1e28c6827cd12c5782d032 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T194500Z DTEND:20261017T200000Z SUMMARY:Customer Segmentation Meets Strategy: Unlocking the Competitive Value of Natural Products in Hospitality Industry DESCRIPTION:Authors - Albrecht Kati\, Vilko Jyri Abstract - Restaurants and their customers value natural food products (NFPs)\, and demand for them is growing steadily due to product qualities such as taste and freshness\, as well as support for sustainable development. However\, the availability of natural food products from suppliers can be challenging. Availa-bility challenges mean that the market for natural food products is inefficient. This also makes it difficult for restaurants to define their competitive strategies. Local restaurants are often small\, entrepreneur-driven businesses with a few dozen employees. In small restaurants\, resources are spent on daily operations\, and systematic long-term development is often given less attention. However\, systematic operations require clear\, planned customer segmentation and\, through this\, the development of competitive strategies as a means of creating value. The main objective of the study is to increase understanding of the link between cus-tomer segmentation and competitive strategies in business and the added value they generate. In addition\, the study aims to guide restaurants towards more sys-tematic business development. The data was collected through qualitative re-search and in-depth interviews with restaurant owners and managers in Finland. The research was based on thematic analysis\, and the results were documented using NVivo software. Restaurants were found to have insufficient knowledge of how NFTs can be used to create value-added business and how customers can be segmented using competitive strategies. CATEGORIES:PHYSICAL TECHNICAL SESSION 1C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:e28d8782d2acd54498f4e3268323ba89 URL:http://5thworldconferenceoninformations.sched.com/event/e28d8782d2acd54498f4e3268323ba89 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T194500Z DTEND:20261017T200000Z SUMMARY:A Mixed Integer Linear Programming Based Television Media Scheduling Optimization DESCRIPTION:Authors - \;Thejan Dulara\, Indra Mahakalanda\, Prasanga Jayathunga\nAbstract - \;Efficient media scheduling plays a vital role in advertising campaign success. Among media platforms\, television remains a key channel for audience engagement. However\, allocating advertisements across programs\, times\, and channels is a complex task. The number of possible combinations exceeds human evaluation capacity. Advertisers often face challenges in allocating spots effectively while minimizing plan cost. This study implements a Mixed Integer Linear Programming (MILP) model to optimize spot allocation across TV programs. The objective is to minimize the Cost Per Rating Point (CPRP)\, a key efficiency metric. The model maximizes the normalized gross rating point (GRP)\, subject to constraints such as total budget\, program slot availability\, and fair commercial distribution. By transforming a nonlinear objective into a solvable MILP framework\, the model ensures practical feasibility and scalability. The results demonstrate improved CPRP performance and significant time savings under realistic constraints. This approach supports advertisers in making data-driven\, cost-effective media scheduling decisions. The study offers a replicable framework for optimizing television advertising plans in dynamic markets. CATEGORIES:PHYSICAL TECHNICAL SESSION 1D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:a4f63904f69e84b5ff0703cdb04c57ab URL:http://5thworldconferenceoninformations.sched.com/event/a4f63904f69e84b5ff0703cdb04c57ab END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T200000Z DTEND:20261017T201500Z SUMMARY:Footballer Player Recommendation Model using Graph Convolutional Networks DESCRIPTION:Authors - W Saib\, T Moodley Abstract - In modern football\, smart recruitment is essential in building successful teams. Traditional scouting methods\, though effective in identifying player mentalities\, often fall short due to the team’s budget restrictions and the need to fit the head coach’s strategy. Teams frequently lose top targets to wealthier clubs\, sign players who do not fit with the coach’s strategy and overlook affordable and stylistically similar players. To address this\, we propose a novel player recommendation system\, which first clusters players and then leverages the Graph Convolutional Networks (GCNs) ability to generate rich node embeddings from a player-similarity graph constructed via cosine distance. Using data from FBref\, we refine the scope to only central midfielders and on the Graph Convolutional Network where the target variables are the labels from K-Means clustering of which we obtained 49% accuracy with all neighbours but a perfect 100% with shared-label aggregation introduced in this paper. It was observed that there were significant visual differences (obtained via t-SNE) in the clusters formed. Graph Convolutional Networks are primarily used for node classification on academic citation datasets\, and the proposed method in this research outperformed on the Cora (88%) and Pubmed (84%) Datasets\, respectively. CATEGORIES:PHYSICAL TECHNICAL SESSION 1A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:ce506f021c7197e5413f5f649c907460 URL:http://5thworldconferenceoninformations.sched.com/event/ce506f021c7197e5413f5f649c907460 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T200000Z DTEND:20261017T201500Z SUMMARY:An Adaptive approach for SDN-based containerized applications on raspberry Pi using STGP DESCRIPTION:Authors - \;Bimlendu Shahi\, V. Pushparajesh\nAbstract - \;The rise of Software defined network-based containerized applications has driven the need for efficient resource management and network optimization\, especially in constrained environments for Raspberry Pi. This paper highlights the AI driven approach in optimizing Raspberry Pi-based container setups using Strongly typed genetic programming (STGP). This generative AI driven approach is followed by the prompt engineering aspects for implementation of adaptive approach in SDN Network. The proposed approach improves task success rates\, reduces latency\, and min-imizes resource contention based on real-time network metrics using CPU usage\, Memory utilization and Network consumption. Experimental results demonstrate the effectiveness of STGP in maintaining optimal performance in highly dynamic network environments. The proposed model allows more precise and adaptable solutions for resource-constrained SDN environments on distributed systems of Raspberry Pi. CATEGORIES:PHYSICAL TECHNICAL SESSION 1B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:ec564fd5172a9e37ec5bb3be229bbe54 URL:http://5thworldconferenceoninformations.sched.com/event/ec564fd5172a9e37ec5bb3be229bbe54 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T200000Z DTEND:20261017T201500Z SUMMARY:Guidelines for Addressing the Non-compliance to Cybersecurity Policies Among Healthcare Workers DESCRIPTION:Authors - Ervine de Vasconcellos\, Tapiwa Gundu Abstract - The rising acceptance of digital technology to improve patient care has made cybersecurity one of the biggest issues for healthcare workers. Having an urgent need to fully understand accepted cybersecurity standards and the main causes of non-compliance. Knowing how healthcare workers see cybersecurity policies becomes essential as a result of the following interruptions in services and more complex assaults that target hospitals and clinical environments. The objective of the research was to provide guidelines for addressing the non-com-pliance with cybersecurity policies by healthcare workers in South Africa. A lit-erature review was carried out to determine the current status of cybersecurity policies in healthcare and a systematic literature review was done to determine the causes of healthcare workers non-compliance with cybersecurity policies. The systematic literature review provided some themes which were then analysed and guidelines were created based on them. CATEGORIES:PHYSICAL TECHNICAL SESSION 1C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:e574b711c7b7c63f6236aeb6492b43d1 URL:http://5thworldconferenceoninformations.sched.com/event/e574b711c7b7c63f6236aeb6492b43d1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T200000Z DTEND:20261017T201500Z SUMMARY:Women in the Future Driven by AI: Using Generative AI to Create Inclusive Systems DESCRIPTION:Authors - Aishwarya Anand Arora\, Charu Gupta Abstract - The explosive growth of artificial intelligence (AI)\, particularly generative AI\, poses opportunities and challenges gender equality. AI has the capacity to shatter cultural boundaries and build inclusive systems\, yet latent algorithmic bias and gender inequality in its composition can exacerbate existing divisions. This overview delves into the ways generative AI can both perpetuate or decrease gender bias\, contingent upon how responsibly it is created and deployed. AI systems tend to reflect the biases of the society they are designed from. For instance\, AI recruitment tools have tended to select more male candidates because of gender-biased historical data. Generative AI\, too\, tends to underrepresent women in leadership positions and perpetuate stereotypes. If unregulated\, these systems stand a chance of perpetuating gender imbalance across industries. In this paper\, we have discussed how AI also has the potential to advance fairness. Resume-anonymizing tools\, huge data set analysis to detect biased tendencies\, and individualized learning plans can promote gender inclusiveness. AI can help bridge STEM access disparities for women and provide supportive mentoring networks in education. To harness these benefits\, responsible AI governance is critical. Fairness audits\, diverse datasets\, transparency\, and accountability should guide AI development. Increasing women’s participation in AI research and policymaking is also key to creating more equitable systems. Ethical AI guidelines must ensure that AI use is inclusive\, fair\, and non-discriminatory. Generative AI has the potential to be an effective catalyst of gender equality when coupled with ethical governance\, representative data\, and representation diversity\, leading towards a more equitable\, AI-powered world. CATEGORIES:PHYSICAL TECHNICAL SESSION 1D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:60fdb14e3a9d68b274acb15bd0bd003a URL:http://5thworldconferenceoninformations.sched.com/event/60fdb14e3a9d68b274acb15bd0bd003a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T201500Z DTEND:20261017T203000Z SUMMARY:Real-Time South African Sign Language interpretation using computer vision methods DESCRIPTION:Authors - \;Precious Magodi\, Tevin Moodley\nAbstract - \;Vision-based sign language recognition significantly advances communication within the deaf community\, enhancing accessibility and inclusion for those who are deaf or hard of hearing. This paper presents a system developed for real-time recognition of South African Sign Language (SASL) using Google’s MediaPipe framework for spatial feature extraction and a long short-term memory (LSTM) network for temporal modelling.We utilise a subset of the ASL Citizen dataset\, focusing on five classes: “SCHOOL\,” “TIMEOUT\,” “MORNING\,” “THANK YOU\,” and “I LOVE YOU\,” which serve as proxies for SASL vocabulary. Keypoint sequences from both hands and body pose are extracted via MediaPipe and fed into a two-layer LSTM for classification. Trained with a Tensor- Flow TFRecord pipeline\, our model achieves a test accuracy of 35.5% and highlights the challenges posed by limited data and variability among signers. This work demonstrates the potential of combining MediaPipe and LSTM for real-time sign recognition and emphasises the need for larger\, language-specific datasets to improve accuracy. CATEGORIES:PHYSICAL TECHNICAL SESSION 1A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:f2187bfc79466b1499b4e2f6eac59f52 URL:http://5thworldconferenceoninformations.sched.com/event/f2187bfc79466b1499b4e2f6eac59f52 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T201500Z DTEND:20261017T203000Z SUMMARY:DeepCart: Smart Cart Security with GAN-Based Anomaly Detection and DBN Classification DESCRIPTION:Authors - \;Rohan Anantapur\, Pranav Rao Pernankil\, Animesh Giri\nAbstract - \;The emergence of smart carts in the retail and shopping industry has introduced questions regarding the safety and security of these autonomous guided vehicles. While smart carts enhance the shopping experience through automation and real-time transaction processing\, they are susceptible to various risks that can compromise their functionality and user data. Many existing cyberattack detection systems fail to consider a well-rounded set of features\, leaving smart cart networks exposed to sophisticated threats. This approach enhances the resilience of smart cart systems by detecting and mitigating security breaches effectively. In this paper\, we introduce DeepCart\, a cyberattack detection and classification system that focuses on violations in smart cart networks. DeepCart leverages Generative Adversarial Networks (GAN) to identify cyberattack data patterns and employs Deep Belief Networks (DBN) for accurate classification of detected threats. CATEGORIES:PHYSICAL TECHNICAL SESSION 1B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:ec882ba23530a4dd2feb17ff8c95b99e URL:http://5thworldconferenceoninformations.sched.com/event/ec882ba23530a4dd2feb17ff8c95b99e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T201500Z DTEND:20261017T203000Z SUMMARY:Coping Mechanisms Toward the Philippine Creditable Withholding Tax on Electronic Marketplace Transactions: An Analysis Across Tax Policy Dimensions and Demographic Profiles DESCRIPTION:Authors - Jonalyn Echano\, Carla Dayne N. Ferreras\, Jhaniella Anne T. Ganuelas\, Maria Angela P. Obsuna\, Regienald G. Obina Abstract - As digital commerce continues to thrive\, the Philippine government has implemented the Creditable Withholding Tax on Electronic Marketplace Transactions to ensure tax compliance among online sellers. This study explores how online sellers in Quezon City cope with the challenges brought by this regulation. Specifically\, it examines their coping mechanisms in relation to the complexity of tax laws\, perceived fairness of the tax system\, quality of tax admin-istration\, effectiveness of enforcement measures\, and the level of penalties and sanctions. A quantitative research design was employed\, using a structured survey distributed via email and social media. The study gathered responses from 113 online sellers operating within Quezon City. Statistical tools such as frequency distribution\, weighted mean\, and ANOVA were used to analyze the data. Findings revealed that while most sellers perceived the tax system as generally fair and the administration as responsive\, they struggled with the complexity of the laws. Many sellers acknowledged the effectiveness of enforcement and the influence of penalties in motivating compliance. However\, differences in coping mechanisms were significantly evident only when sellers were grouped by busi-ness experience and perceived fairness—while factors like capitalization and business category showed no major influence. The results highlight the need for clearer guidelines\, simplified tax processes\, and continuous education efforts. This research contributes to a deeper understanding of how small digital entre-preneurs adapt to evolving tax policies\, offering insights for policy improvements that support voluntary compliance and fairness in the growing e-commerce sec-tor. CATEGORIES:PHYSICAL TECHNICAL SESSION 1C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:bda8b9caaeb709cb1670747969915273 URL:http://5thworldconferenceoninformations.sched.com/event/bda8b9caaeb709cb1670747969915273 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T201500Z DTEND:20261017T203000Z SUMMARY:Integrating Super-Resolution and Deep Inpainting for High-Quality Visual Restoration DESCRIPTION:Authors - Pujari Suresh Kumar\, Sushama Rani Dutta Abstract - Image Inpainting is the field that reconstructs the missing regions with high-quality image restoration. The image restoration addresses the loss of conditional details and distortion of visual quality in damaged images. In this paper\, a Scale-Variant Learning (SVL) model is presented that combines super-resolution and deep image inpainting for the restoration of missing or damaged regions\, resulting in increased image clarity and high resolution. The proposed SVL consists of a super-resolution network that first recovers high-frequency details from low-quality input and an inpainting module that fills in missing re-gions by leveraging both contextual and structural information. To generate photo-realistic output\, a multi-scale feature fusion\, attention mechanisms\, and adversarial learning are used to enable the model learns the global semantics and local texture consistency. The pre-trained model DeepFill v1\, with transfer learning applied to large-scale high-resolution datasets (CelebA-HQ and Plac-es2)\, shows competitive performance compared to existing techniques in both quantitative evaluations and visual appearance. This pre-trained model fills the gap between missing content and accurate regions\, from image restoration and editing to historical image repair and computer vision tasks that require fine-grained representation. CATEGORIES:PHYSICAL TECHNICAL SESSION 1D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:fe74480c7c4b8f3a75c99f1d52556e01 URL:http://5thworldconferenceoninformations.sched.com/event/fe74480c7c4b8f3a75c99f1d52556e01 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T213000Z DTEND:20261017T214500Z SUMMARY:Tracking Social Capital Evolution in Commercial Districts via Social Network Analysis DESCRIPTION:Authors - \;Yuya Ieiri\, Tengfei Shao\, Osamu Yoshie\nAbstract - \;Social capital is recognized as an important concept for revitalizing commercial districts. However\, the dynamics of social capital within these dis-tricts remain largely unexplored. As an initial step toward addressing this gap\, this study conceptualizes changes in the social network of a commercial district community as shifts in social capital. Furthermore\, it investigates the impact of information sharing within the community on this social capital. The study developed a framework to examine the relationship between social capital and so-cial networks. An empirical investigation involving ten participants and three experiments was conducted over three weeks. Results indicated that participants' subjective evaluations of store importance are influenced by the mode of information sharing within the community. Furthermore\, the findings suggest that structured\, repeated information sharing can strengthen interpersonal rela-tionships within the network. From a social-capital perspective\, these findings imply that information sharing within interactive groups can potentially foster its development. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:5ce9fca8796c72b6e9802c3bd967858b URL:http://5thworldconferenceoninformations.sched.com/event/5ce9fca8796c72b6e9802c3bd967858b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T213000Z DTEND:20261017T214500Z SUMMARY:Feasibility Study of Digital Passes for Human Access Control in Data Centers DESCRIPTION:Authors - Ryo Itokawa\, Eisuke Ito Abstract - With the widespread adoption of smartphones\, digital credential presentation systems such as the EUDIWallet and ISO-compliant mobile driver’s licenses􀊕are being deployed worldwide. In contrast\, human access control at data centers still primarily relies on a combination of physical IC cards and biometric authentication. This creates a considerable burden for engineers who frequently need to access multiple facilities\, as they must manage several physical IC cards. To address this issue\, this study investigates the feasibility of introducing a digital access pass based on the Verifiable Credentials (VC) framework\, currently being standardized by the W3C. Building on the experience gained through the development of a VC-based digital student ID system at Kyushu University\, we propose a conceptual system that enables the issuance\, presentation\, and verification of credentials via smartphones. In this paper\, we outline the current operational practices and challenges of human access control in data centers. We also present a conceptual model of a VC-based digital access pass\, followed by a discussion of future directions and challenges for implementation. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:14fadb1a4132703e646c28ffb0d3a0ab URL:http://5thworldconferenceoninformations.sched.com/event/14fadb1a4132703e646c28ffb0d3a0ab END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T213000Z DTEND:20261017T214500Z SUMMARY:Breaking Integer Factorization using Shor’s Algorithm: A Practical Approach with IBM Qiskit DESCRIPTION:Authors - Anand Ghugare\, Atharva Rajoba\, Dinesh Kumar Saini Abstract - Quantum computers poses a significant threat to traditional cryptography systems\, which depend on integer factorization. Theoretically\, Shor’s algorithm\, a quantum polynomial-time algorithm\, allows quick factorization of huge semiprimes\, compromising the RSA protocol. This paper shows hardware-based execution by implementing Shor’s algorithm using IBM’s quantum resource and Qiskit framework to factor the number 221. The study examines the success probability and performance limitations of implementation on noisy quantum hardware. Our results provide valuable insights into effective quantum cryptanalysis and pave the path for scaling such approaches for larger numbers. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:238bf6515929f8f0620aee0d88952c1d URL:http://5thworldconferenceoninformations.sched.com/event/238bf6515929f8f0620aee0d88952c1d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T213000Z DTEND:20261017T214500Z SUMMARY:Password Hygiene Guidelines for SMEs in South Africa: A Systematic Literature Review DESCRIPTION:Authors - Tapiwa Gundu\, Nangamso Mmango Abstract - Small and Medium Enterprises (SMEs) in South Africa face signifi-cant cybersecurity challenges due to poor password hygiene practices. Employees and managers frequently experience password fatigue\, leading to dangerous security shortcuts such as password reuse\, weak credential creation\, and physical recording of passwords. While comprehensive cybersecurity frameworks exist for large enterprises\, SMEs lack practical\, tailored solutions that account for their limited resources and technical expertise. This study conducts a systematic literature review (SLR) to analyze existing research on password security challenges in SMEs\, with particular focus on the South African context. The review identifies key vulnerabilities and synthesizes evidence-based recommendations into actionable password hygiene guidelines specifically designed for SME environ-ments. The proposed guidelines emphasize usability alongside security\, offering realistic strategies to improve authentication practices without overwhelming staff. Findings highlight the critical need for simplified policies\, appropriate tech-nological tools\, and continuous security awareness training in resource-constrained SME settings. CATEGORIES:PHYSICAL TECHNICAL SESSION 2D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:67785847979c280534f0f93cd6f212c9 URL:http://5thworldconferenceoninformations.sched.com/event/67785847979c280534f0f93cd6f212c9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T214500Z DTEND:20261017T220000Z SUMMARY:Front-End Web Developer Hiring Trends in the Philippines: Implications for University Curricula DESCRIPTION:Authors - Nirel Marie M. Ibarra Abstract - The fast changes in front-end web development technologies have widened the gap between what schools teach and what businesses need in the Philippines. This paper offers the first systematic study of developer job postings in the country\, using a new approach that combines web scraping\, LLM-based classification\, and statistical analysis. By examining hiring needs across small\, mid-sized\, and large companies\, the study highlights apparent differences in technology preferences\, range of skills\, and business practices. The findings indicate that smaller firms look for adaptable generalists\, while larger organizations focus on specialized skills and organized processes. There are also early signs of a demand for AI knowledge in various settings. These insights form a Minimum Viable Skill Set (MVSS) that includes technical skills like React\, JavaScript/TypeScript\, HTML\, CSS\, Git/GitHub workflows\, and basic DevOps. It also includes the ability to adjust to different work environments. The results aim to guide curriculum changes in Philippine universities and act as a model for other ASEAN countries. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:7f72d18aef56f86a76a1df5f3bf03b5f URL:http://5thworldconferenceoninformations.sched.com/event/7f72d18aef56f86a76a1df5f3bf03b5f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T214500Z DTEND:20261017T220000Z SUMMARY:Improving the Accuracy of Individual Excitement Level Curve Generation Based on Subjective Emotion Evaluation During Sightseeing DESCRIPTION:Authors - Keishin Asakura\, Yuya Ieiri\, Hiroki Sasayama\, Osamu Yoshie Abstract - Recently\, the importance of designing tourism routes based on a com-prehensive evaluation of tourist experiences has been increasingly recognized. One common approach for such an evaluation involves the use of electrodermal activity (EDA) data\, a physiological indicator of emotional arousal. However\, owing to the high cost and complexity associated with collecting and analyzing EDA data\, their use in real-world tourism settings remains limited. Consequently\, this study focused on the individual excitement level (IEL) curve as a subjective and cost-effective alternative for visualizing emotional transitions during sight-seeing. Building on previous studies\, we developed a web-based application that allows tourists to self-report their emotional responses with greater granularity. Unlike previous methods that use only three levels\, the proposed system supports both a five-level positive scale (1 to 5) and an extended ten-level scale (-5 to +5) that incorporate negative emotions. We conducted a field experiment in Mojiko\, Kitakyushu City\, where participants used the application while engaging in actual sightseeing. The results demonstrated that IEL curves based on five- and ten-point evaluations exhibited stronger alignment with the EDA data than those based on a three-point evaluation. In particular\, the inclusion of negative evalua-tions on a ten-point scale enabled a more comprehensive representation of emo-tional fluctuations. These findings suggest that the proposed method enhances the expressive capacity for emotional self-reporting and supports the practical implementation of data-driven tourism route planning. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:59a848b69d87ed58da877fe21585fa08 URL:http://5thworldconferenceoninformations.sched.com/event/59a848b69d87ed58da877fe21585fa08 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T214500Z DTEND:20261017T220000Z SUMMARY:Strategic Planning for Sustainable Urban Transport: A Conceptual Framework Integrating Artificial Intelligence and Enterprise Architecture DESCRIPTION:Authors - Alma Delia Torres-Rivera\, Laura Alma Diaz-Torres\, Mario Leonardo Nieto Antolinez Abstract - This study proposes a theoretical framework for integrating artificial intelligence into sustainable business models for urban public transport. Drawing on a literature review and two in-depth expert interviews (in data analytics and operations)\, it identifies key structural challenges in the sector\, including fragmented concession models\, rising costs\, declining demand\, environmental pressures\, and weak alignment with national policies such as the National Policy for Urban Collective Public Transport. The findings indicate that artificial intelligence alone is insufficient to achieve sustainability\; it must be integrated with robust enterprise architecture and adaptive strategic planning. To support this integration\, the study presents a six-phase roadmap: structural diagnosis\, enterprise architecture redesign\, strategic planning\, AI integration\, training and change management\, and continuous evaluation. This roadmap offers a practical and ethical pathway for digital transformation aligned with the Sustainable Development Goals. Ultimately\, artificial intelligence can improve efficiency\, resilience\, and sustainability—provided its deployment is context-sensitive and supported by institutional leadership\, organizational capacity\, and cross-sector collaboration. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:894f2031a9cf9de91fffeb1ed374bcf7 URL:http://5thworldconferenceoninformations.sched.com/event/894f2031a9cf9de91fffeb1ed374bcf7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T214500Z DTEND:20261017T220000Z SUMMARY:Parallel Deep Convolutional Neural Network with Gaussian Error Linear Unit based Efficient Facial Expression Recognition DESCRIPTION:Authors - Shruthi S\, Manjula Y Abstract - Automated emotion detection through facial analysis represents a cru-cial technological advancement for interpreting human expressions from digital images. Current classification approaches face challenges in achieving precise accuracy because they extract insufficient distinguishing characteristics needed to differentiate various emotional states. To address these issues\, we introduce a Parallel Deep Convolutional Neural Network (PDCNN) incorporating Gaussian Error Linear Unit (GELU) activation for enhanced emotion classification performance. Our methodology utilizes two established benchmark collections: FER-2013 and Japanese Female Facial Expression (JAFFE) databases\, which undergo preprocessing through Contrast Limited Adaptive Histogram Equalization (CLAHE) and dataset balancing via Generative Adversarial Network (GAN) based augmentation techniques. Subsequently\, the enhanced dataset undergoes feature extraction using DenseNet-121 architecture\, which captures representa-tions through densely connected layers before processing through our dual-stage classification framework. This system leverages both localized and comprehen-sive facial characteristics\, integrating them via a fusion mechanism for precise emotional categorization. Our experimental validation demonstrates that the PDCNN with GELU approach achieves superior performance with 94.67% ac-curacy on FER-2013 and 99.10% on JAFFE datasets\, outperforming traditional CNN\, Convolutional Relational Network (CRN)\, ResNet-50\, Wavelet DCNN\, and Three Channel-CNN methodologies. CATEGORIES:PHYSICAL TECHNICAL SESSION 2D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:97ec573854dec1848ee03e2508fcbb4e URL:http://5thworldconferenceoninformations.sched.com/event/97ec573854dec1848ee03e2508fcbb4e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T220000Z DTEND:20261017T221500Z SUMMARY:SVM-Based Predictive Correlation (S2C): A Detailed Theoretical and Empirical Investigation DESCRIPTION:Authors - Suthawan Prukumpai\, TzeHoung Lee\, Patrick Ghali Abstract - Traditional correlation metrics like Pearson correlation capture only linear and symmetric relationships between variables\, potentially obscuring meaningful dependencies in financial systems where nonlinearities and lead-lag effects are common. This paper introduces SVMBased Predictive Correlation (S2C)\, a novel approach that redefines correlation in terms of predictive power rather than mere association. S2C accommodates nonlinearities and directional structures within data\, allowing practitioners to better gauge risk and properly size allocations. We develop the mathematical foundations of S2C within the context of kernel methods and reproducing kernel Hilbert spaces (RKHSs)\, then present an empirical study involving financial and macroeconomic time series with different update frequencies. Our analysis demonstrates that S2C can recover both linear and nonlinear relationships\, is more robust to irregular sampling than standard correlation measures\, and captures directionality by revealing how one variable can predict another. We conclude with implications for portfolio construction and risk management\, particularly addressing the ”volatility washing” problem in portfolios containing illiquid alternative investments. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:cc29bcd7b740a09caae7ade55ff5701d URL:http://5thworldconferenceoninformations.sched.com/event/cc29bcd7b740a09caae7ade55ff5701d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T220000Z DTEND:20261017T221500Z SUMMARY:ENotaryo: A Foundational ID-based Document Notarization System DESCRIPTION:Authors - Victor Edwin Reyes\, Joele Althea Manansala\, Wilson M. Tan Abstract - The process of document notarization in the Philippines is vulnerable to institutional corruption due to a lack of a centralized source of truth. Recent initiatives by the Philippine government to introduce a digital-ready national ID system allow for an e-government-based approach to tackle this problem. This paper proposes an institutional and technical framework for such an approach\, describes the implementation of a minimal viable system\, and provides recommendations based on its performance under test loads. Such a framework must minimally comprise of institutional support\, a storage for documents and notarization records\, a mechanism for identity validation\, and a physical information format along with a reader of this format. This proposed framework was implemented minimally and tested. Recommendations based on these tests were made with an emphasis on improving performance and technical rigor. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:d266abc6b6551b35e530db14a5f4184b URL:http://5thworldconferenceoninformations.sched.com/event/d266abc6b6551b35e530db14a5f4184b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T220000Z DTEND:20261017T221500Z SUMMARY:Assessing Drivers of Lifestyle-Based Entrepreneurship in Natural Products Field DESCRIPTION:Authors - Markus Heikkila\, Alisa Misukka\, Ilkka Kero\, Kati Albrecht\, Jyri Vilko Abstract - Entrepreneurship in the natural product field is growing\, founded in the utiliza-tion of sustainable natural resources and entrepreneur’s personal values and motives. Natural product field offers interesting perspectives for entrepreneurship where business activity is shaped by financial targets\, personal value system and relationships with nature. The field’s immatureness\, heterogeneity\, and undeveloped supply chains highlight the decisions independent entrepreneurs make regarding their business strategy. This research explores the path towards entrepreneurship of two entrepreneurs within the natural product field regarding entre-preneurship motivation and commercialization strategies in the form of an extreme case study. It addresses that entrepreneurship within natural product field is driven by passion\, customer entered approach\, and willingness to combine per-sonal values with business activity. Case companies differ from one another re-garding their willingness to grow\, educational background\, and brand building. However\, similarities can be found regarding valuing quality\, customer feedback\, and self-directed information seeking. The results expand previous understanding about entrepreneurship motives\, indicating how strategic make or buy decisions are tied into entrepreneur’s identity\, values and resource acquisition. Specifically in natural product entrepreneurship\, commercialization is not only a technical process but rather based on entrepreneur’s value system\, covering product origin\, authenticity and ethical grounds. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:c49de64c5f3ce54b58afb63d509de9d7 URL:http://5thworldconferenceoninformations.sched.com/event/c49de64c5f3ce54b58afb63d509de9d7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T220000Z DTEND:20261017T221500Z SUMMARY:A Machine Learning Approach to Analyzing the Impact of Environmental\, Social\, and Governance (ESG) Indictors on Financial Performance DESCRIPTION:Authors - Sneha Warrier\, Umesh Mahtani\, Smitha Rao Abstract - This study makes a novel attempt using ensemble Machine Learning (ML) techniques to analyze the impact of various Environmental\, Social\, and Governance (ESG) indicators on the financial performance of publicly listed entities in India. The findings highlight the importance of looking beyond the ESG score and assessing the most important ESG indicators that impact firms’ finan-cial performance. The main findings establish a relationship between Tobin’s Q (firm value) and individual ESG indicators. The study shows that ESG indicators have comparatively less impact on the internal accounting measures of Return on Total Assets (ROA) and Return on Net Worth (RONW). The results list the following key ESG indicators: energy intensity and consumption\, equal and mini-mum wages to employees\, turnover rate\, as those having impact on Tobin’s Q across the various ML models explored. These research findings would assist corporations\, investors\, and policymakers in identifying key ESG indicators that impact financial performance of companies. CATEGORIES:PHYSICAL TECHNICAL SESSION 2D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:4b12ec1af004ba7d78abec6e6e2da950 URL:http://5thworldconferenceoninformations.sched.com/event/4b12ec1af004ba7d78abec6e6e2da950 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T221500Z DTEND:20261017T223000Z SUMMARY:Hybrid Multi-Model Ensemble System for Effective Intrusion Detection and Prevention in Cloud Environment Using Hypergraph DESCRIPTION:Authors - \;Gokulraj G\, Bose S\, Danya S\, Maheswaran N\, Illakiya Varshini C\, Pradeep Kumar M\nAbstract - \;Cloud computing environments increasingly face sophisticated cyber threats due to their distributed and open-access nature\, demanding robust security solutions for data integrity. To address these challenges\, this work proposes a Hybrid Multi-Model Ensemble System that uses advanced hypergraph techniques for comprehensive intrusion detection and prevention. The system combines models such as Hypergraph Neural Networks (HNN)\, Variational Autoencoders (VAE)\, and Graph Attention Networks (GAT) to boost detection precision for complex attack patterns. An Adversarial Module with ZOO Model (Zeroth Order Optimization) boosting generates challenging attack samples\, strengthening the pipeline’s resilience against evolving threats. Real-time protection is reinforced through an SNORT-powered Intrusion Prevention Module that blocks intrusions proactively with adaptive policies. Experiments show that the proposed ensemble achieves detection accuracy above 90%\, surpassing single-model approaches. This strong accuracy\, along with reliable recall and precision\, confirms the hybrid architecture minimizes false positives while accurately classifying diverse intrusion types. Overall\, the system’s advanced modeling and adaptability offer a scalable solution for securing cloud infrastructures against known and novel attacks. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:e7b9a25e80c94871bd388b0e97df6e0b URL:http://5thworldconferenceoninformations.sched.com/event/e7b9a25e80c94871bd388b0e97df6e0b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T221500Z DTEND:20261017T223000Z SUMMARY:A Coherent Solution of dataset crisis using GAN based transfer learning approach for leaf image classification & Disease Prediction DESCRIPTION:Authors - Monu Bhagat\, Sunil Kumar Abstract - Recently\, the identification and classification of illnesses from images of plant leaves have been an ongoing problem in agricultural research. There is a dearth of proper dataset to be able to use modern deep learning-based disease detection algorithms for plant disease detection. We may rely less on farmers to take precautions to ensure the safety of their crops if they can use image-processing techniques to identify plant illnesses. For better use of these advancements mobile applications need to be developed\, where farmers directly can upload the images and get desired feedback for his crop/plant. In this work we have developed such a solution where we attempted to solve the dataset crisis by using cycleGAN and used the generated synthetic dataset for leaf disease detection. For classification\, we used transfer learning model EfficientNetB3 and achieved classification accuracy 93.33%. Finally\, these developments are implemented in a mobile application for easy and scalable use for farmers. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:f8c2d5c1b76d8208db2eca2da8119c82 URL:http://5thworldconferenceoninformations.sched.com/event/f8c2d5c1b76d8208db2eca2da8119c82 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T221500Z DTEND:20261017T223000Z SUMMARY:Implementation of a Neural Network-Based Approach for Recognizing American Sign Language (ASL) Letters DESCRIPTION:Authors - Nasir Ansari\, Amit Kumar Sharma Abstract - A significant challenge in human-computer interaction is enabling effective communication for individuals with hearing impairments. This research addresses the need for accessible solutions by implementing a neural network-based system for recognizing American Sign Language (ASL) letters from images captured via a standard webcam. The primary objective is to reduce the communication barrier between the deaf and hearing communities by leveraging machine learning techniques for hand gesture classification. A Convolutional Neural Network (CNN) was utilized for both feature extraction and classification tasks. The model was trained on a publicly available Kaggle dataset comprising 87\,000 images across 29 ASL alphabet classes. Experimental results demonstrate that the proposed model achieves high classification accuracy\, indicating its potential applicability in real-time ASL translation systems. When we sit down to plan the next phase of the project\, well add real-time gesture tracking\, mix in voice and touch data\, and shrink the whole model so it runs smoothly on phones and tablets. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:7e2708c06498729df398ede6e710b47e URL:http://5thworldconferenceoninformations.sched.com/event/7e2708c06498729df398ede6e710b47e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T221500Z DTEND:20261017T223000Z SUMMARY:Novel IoT Node Concept in IoT Platform for Intelligent and Dynamic Remote Patient Monitoring DESCRIPTION:Authors - \;Siham Beloualid\, Abderrahim BAJIT\, Hicham Essamri\, Youness Zahid\, Nabil Srifi\, Rachid Elbouayadi\, Aya Essafini\, Salaheddine Zezaan\nAbstract - \;The growing demand for intelligent healthcare systems emphasizes the need for advanced technologies that support continuous\, non-intrusive patient monitoring in clinical environments. This paper presents a comprehensive solution that integrates both static and mobile IoT nodes\, coupled with AI-driven perception and analytics\, to enhance monitoring capabilities within hospital settings. The proposed system incorporates three core components: autonomous navigation\, computer vision–based health assessment\, and machine learning–enabled sensor analysis. Static nodes are deployed at each patient’s bedside to collect physiological and environmental data in real time using embedded sensors\, while simultaneously capturing visual data through fixed cameras. Sensor data is analyzed using machine learning models that predict missing values in case of sensor malfunction or loss\, ensuring reliable and uninterrupted monitoring. In addition to static setup\, a mobile robot navigates autonomously through hospital wards\, executing monitoring routines based on user-defined schedules or clinical priorities. During its rounds\, the robot collects visual data of patients and surgical sites. Deep learning models\, applied to extract subjective information\, are employed to analyze patient posture\, wound healing progress\, and to detect essential items such as medicine containers and water bottles. These models also support autonomous navigation by enabling path recognition and action planning. The system integrates insights from both static and mobile nodes into structured\, real-time reports that assist in the early detection of clinical issues and timely informed medical decisions. This solution provides a scalable and objective approach to continuous patient assessment. It improves monitoring quality services\, reduces reliance on subjective manual evaluations\, enhances staff efficiency\, and fosters a more responsive\, data-informed hospital environment. CATEGORIES:PHYSICAL TECHNICAL SESSION 2D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:e1d68adda2e600e1d405f040505b264f URL:http://5thworldconferenceoninformations.sched.com/event/e1d68adda2e600e1d405f040505b264f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T223000Z DTEND:20261017T224500Z SUMMARY:Multi-task Cascaded Convolutional Neural Networks for Thermal Face Detection DESCRIPTION:Authors - \;Patil Pratima\, Deshpande Deepa\nAbstract - \;This paper presents a real-time thermal face detection and recogni-tion system based on an enhanced Multi-task Cascaded Convolutional Neural Network (MTCNN) framework. Unlike visible-light methods\, thermal imaging introduces domain-specific challenges such as low spatial resolution\, high noise\, and intensity variance due to temperature fluctuations. To address these\, we propose a dedicated preprocessing pipeline including normalization\, contrast enhancement\, and channel replication to adapt single-channel thermal images for CNN-based processing. The modified MTCNN is fine-tuned on thermal datasets to accurately detect facial regions and landmarks. Aligned faces are then processed through a thermal-optimized feature embedding network trained with tri-plet loss to produce identity-preserving descriptors. Recognition is performed us-ing a lightweight classifier over the feature space. The system is optimized for real-time performance using GPU acceleration and quantized inference. Experi-mental results on publicly available thermal face datasets demonstrate the effec-tiveness of our approach in terms of detection accuracy\, recognition rate\, and processing speed\, making it suitable for surveillance and biometric applications under low-light or no-light conditions. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:cc030248c23232f0fd4daddf5059ebcd URL:http://5thworldconferenceoninformations.sched.com/event/cc030248c23232f0fd4daddf5059ebcd END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T223000Z DTEND:20261017T224500Z SUMMARY:Bridging the Gap: Perceptual Differences Between Physical and Virtual Tours in 360 Maynila DESCRIPTION:Authors - Laila D. Malabanan\, Apolinar P. Datu\, Annaliza C. Sinfuego\, Dawn Nari S. Condez\, Jessica Rose P. Enriquez\, Lexus P. Mon-tenegro\, Ana Celine G. Esquierdo\, Chona S. Lajom Abstract - Bridging the Gap: Perceptual Differences Between Physical and Vir-tual Tours in 360 Maynila takes a closer look at how people experience culture and history in today’s digital age. With virtual tours becoming more accessible through platforms like 360 Maynila\, this study compares how audiences perceive traditional\, in-person tours versus immersive virtual ones. Using surveys\, the re-searchers gathered insights from individuals who experienced both formats. Re-sults show that while physical tours create a stronger emotional connection and allow for richer sensory engagement\, virtual tours offer convenience\, accessibil-ity\, and a modern twist that appeals to tech-savvy audiences. Interestingly\, many participants found that virtual tours sparked curiosity but lacked the depth and atmosphere of being physically present. The study suggests that instead of re-placing one with the other\, a blend of both can offer a more inclusive and dynamic cultural experience. By understanding these perceptual differences\, cultural in-stitutions and tourism organizers can create more engaging and adaptable ways for people to connect with heritage\, no matter where they are. This research high-lights the growing role of technology in storytelling and encourages thoughtful innovation in how we share and preserve our cultural identity. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:1750e7937366ab05693f6d9191e8ac8e URL:http://5thworldconferenceoninformations.sched.com/event/1750e7937366ab05693f6d9191e8ac8e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T223000Z DTEND:20261017T224500Z SUMMARY:Development Of English-Assamese Machine Translation System Using NMT DESCRIPTION:Authors - Saptarshi Paul\, Pratul Kalita\, Abu Ahmed Waliullah Mazumder\, Saurav Paul Abstract - With the rise of multilingual technology and the growing demand for inclusive language tools\, there remains a significant gap when it comes to resources and research dedicated to Assamese\, one of the major languages spoken in North east India. The core objective is to bridge that gap by leveraging recent advances in deep learning—specifically the Transformer architecture—to build a translation model that is both accurate and adaptable. The system is implemented using the OpenNMT-py framework which supports flexible training of encoder- decoder models with attention mechanisms. To train the model\, a parallel corpus consisting of approximately 124\,000English-Assamese sentence pairs was sourced from the Samanantar dataset available on Kaggle. The data was prepared using a machine translation (MT) preprocessing script\, which utilizes Sentence Piece to perform sub word tokenization. This step ensures that rare and compound words are broken down into more frequently occurring subunits\, thereby improving the model’s ability to learn patterns in low-resource language settings. The trained model was evaluated using the BLEU score\, which is used to compare the overlap between machine-generated outputs and human reference translations. The evaluation results indicated that the Transformer-based approach provides promising performance\, particularly in producing fluent and contextually relevant translations\, despite the limited size of the dataset. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:0a75459a3b57da51b041c9583758ab23 URL:http://5thworldconferenceoninformations.sched.com/event/0a75459a3b57da51b041c9583758ab23 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T223000Z DTEND:20261017T224500Z SUMMARY:Innovating An Autonomous Mobile Node for Plant Imagery and Health Monitor in Agricultural Greenhouse DESCRIPTION:Authors - \;Siham BELOUALID\, Abderrahim BAJIT\, Alae ELFOURCHI\, Youness ZAHID\, Emile SEMAKO\, Hicham ESSAMRI\nAbstract - \;The increasing complexity of greenhouse agriculture requires integrated\, scalable platforms capable of precise monitoring\, real-time decision-making\, and sustainable management. This work presents an intelligent greenhouse system that transitions from static IoT networks to a multi-agent architecture combining mobile sensing units\, autonomous robots\, and deep learning-powered computer vision. Environmental parameters such as temperature\, humidity\, and soil moisture are continuously collected through embedded sensors\, while high-resolution visual data enables detailed plant health assessment. Machine learning models analyze these multimodal datasets to predict crop conditions\, detect anomalies\, and enable early intervention. A tri-modal vision system ensures complete coverage: static wide-angle cameras for global monitoring\, mobile units with CNN-based analysis for close-range inspections\, and robot-mounted cameras for real-time tasks. Autonomous robots\, equipped with SLAM and path planning algorithms\, perform precision operations such as targeted harvesting and disease removal. The fusion of robotics\, AI\, and sensor networks provides high-resolution monitoring\, optimizes resource usage\, and enhances crop management. Additionally\, onboard edge computing enables fast\, localized data processing\, reducing latency and improving system autonomy. CATEGORIES:PHYSICAL TECHNICAL SESSION 2D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:bccbf86921b753c7915700176e330af3 URL:http://5thworldconferenceoninformations.sched.com/event/bccbf86921b753c7915700176e330af3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T224500Z DTEND:20261017T230000Z SUMMARY:Stress Detection and Prediction Using Wearable Sensors and Machine Learning: A Data-Driven Approach DESCRIPTION:Authors - Asma Shahin\, Deepa Deshpande Abstract - The prevalence of stress in modern life demands innovative solutions to monitor and mitigate its effects on individual well-being. This study explores stress detection through a robust dataset derived from wearable devices\, analysing physiological signals\, perceived stress scores\, and task performance metrics. Given the widespread impact of stress across diverse populations\, this research seeks to unravel the complexities of stress responses\, paving the way for personalized interventions and enhancing our understanding of the physiological mechanisms underlying stress. On the Stress Predict dataset\, the accuracy by Random Forest was the highest at 83% as compared to Logistic regression - 54% and SVM - 82%. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:5cc2f566db7f1aab8b627a57c60210a8 URL:http://5thworldconferenceoninformations.sched.com/event/5cc2f566db7f1aab8b627a57c60210a8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T224500Z DTEND:20261017T230000Z SUMMARY:EXAMINING THE PROMOTIONAL STRATEGIES OF PHILIPPINE FESTIVALS IN ATTRACTING TOURISTS DESCRIPTION:Authors - Jhon Eric D. Punzalan\, Apolinar P. Datu\, Jonas A. Jaro\, Andro Isao T. Aquino\, Jubilee Anne C. Del Rosario\, Khen Karlo A. Ocampo\, Paulo M. Gabagat\, Earl John Z. Alba\, Marivic P. Mojica\, Rizza May G. Tandog Abstract - This study examines the promotional strategies employed by Philippine festivals to attract both local and international tourists. Festivals in the Philippines are not only vibrant expressions of cultural heritage but also vital drivers of tourism and economic activity. With increasing global competition and changing tourist behavior\, effective promotion is essential to maintaining their relevance and appeal. The research gathered responses from a diverse group of participants\, analyzing demographics\, engagement patterns\, and perceptions of various promotional approaches. Findings reveal that festival attendees are predominantly young adults\, male\, students\, and largely international tourists\, particularly from Asia and Europe. Respondents strongly agree that festivals across national\, regional\, and city levels are widely attended and culturally significant. Promotional efforts using a mix of traditional media\, experiential marketing\, and digital platforms such as YouTube\, TikTok\, and social media are seen as highly effective\, especially among younger\, tech-savvy audiences. Promotional content is perceived as credible and culturally authentic\, contributing to high satisfaction and repeat attendance. However\, key challenges such as budget constraints\, inconsistent branding\, and limited digital marketing expertise persist. Respondents support strategies focused on enhancing digital engagement\, extending festival durations\, and maintaining cultural authenticity. The study concludes that a well-integrated\, inclusive\, and globally oriented marketing approach is essential for sustaining and expanding the appeal of Philippine festivals. It recommends strategic investments in capacity building\, digital tools\, and culturally grounded storytelling to strengthen the Philippines’ position as a leading cultural tourism destination in Southeast Asia. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:d807058c9506b477757aaf8f332c92af URL:http://5thworldconferenceoninformations.sched.com/event/d807058c9506b477757aaf8f332c92af END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T224500Z DTEND:20261017T230000Z SUMMARY:On Non-Timber Forest Products processing in the food supply chains DESCRIPTION:Authors - Homayoun Rabiei Pour\, Jyri Vilko Abstract - Non-timber forest products (NTFPs) are wild products harvested from the forest\, except timber\, there’s a significant potential for application in the food supply chains. This systematic literature review evaluates the process potential of various NTFPs based on the feasibility and technological aspects of these un-derutilized natural resources for food processing. By using Web of Science\, pub-lications were retrieved with a specific search strategy of keywords mainly con-sisting of food\, non-timber forest products\, processing\, and cost. After screening based on defined inclusion criteria\, relevant articles were selected for analysis. The results contained different applications of NTFPs such as wild fruits\, shea butter\, bamboo shoots\, and plant-derived polysaccharides in food manufacturing\, preservation\, and nutritional enhancement. Different processing methods such as drying\, extraction\, fermentation\, and enzyme treatment were documented with corresponding evaluations of safety\, functional properties\, and economic viabil-ity. While interest in sustainable and local foods is increasing\, there are also large gaps related to scale-up feasibility\, market integration\, and cost analysis. The re-view concludes with recommendations for future research\, particularly empha-sizing innovation in food-grade processing and value-added product develop-ment from NTFPs. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:74166bb79baefb1a4a102f7303ce419f URL:http://5thworldconferenceoninformations.sched.com/event/74166bb79baefb1a4a102f7303ce419f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T224500Z DTEND:20261017T230000Z SUMMARY:mVR-REAL: Virtual Reality Applications Based on Social Emotional Learning for Emotion Regulation in Malaysian Adolescents DESCRIPTION:Authors - \;Irna Hamzah\, Ely Salwana\, Hameedur Rahman\nAbstract - \;Virtual reality (VR) is swiftly evolving into a transformative tool in education\, offering immersive environments that facilitate social-emotional learning (SEL) and enhance emotional regulation\, particularly among adolescents. This study intends to explore the application of a VR design framework specifically customized for the Malaysian context\, with the objective of strengthening social-emotional learning and establishing emotional regulation skills in adolescents. The study collects and analyses data through the VR application named mVR-REAL utilizing a VRSEL framework\, which encompasses essential design principles such as user interface (UI)\, presentation layer (PL)\, and brain activity (BA) in the execution of VR-based social-emotional learning (SEL) interventions\, highlighting the opportunities and constraints within Malaysian educational settings. The data analysis is performed utilizing SPSS. A total of 127 students from four secondary schools were enrolled in this study. Majority of the respondents were female (51.2%\, n=65). All respondents answered usability instrument and the emotional questionnaire. Overall\, the data suggests that the system has strong usability\, with most users rating it as good. The mean score above 86% and the high proportion of good ratings reflect positively on the user experience. However\, the presence of some users with scores below 80% highlights opportunities to further enhance usability for all users. CATEGORIES:PHYSICAL TECHNICAL SESSION 2D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:eb4a379291c62ea0a6e9018d19077f0d URL:http://5thworldconferenceoninformations.sched.com/event/eb4a379291c62ea0a6e9018d19077f0d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T230000Z DTEND:20261017T231500Z SUMMARY:Spatial Optimization for Emergency Centers in Industrial Zones DESCRIPTION:Authors - Ornurai Sangsawang Abstract - Industrial chemical emergencies\, such as leaks\, fires\, and explosions\, are major risks that affect life\, property\, the environment\, and infrastructure security\, especially in areas with high factory density. This research aims to develop a spatial emergency response station placement model by applying the Maximal Covering Location Problem (MCLP) model in two case studies: (1) the placement of the Industrial Emergency Response Center (I-ERC) using factory location data in Rayong Province\, and (2) the placement of the Chemical Emergency Response Station (CERS) using historical chemical accidents. The results of the study compared the locations of 21 existing EMS stations and found that the MCLP model can significantly increase the coverage of the risk areas. In the I-ERC case\, the coverage level increased from 87.09% to 99.46%\, and in the CERS case\, the risk points can be covered 100% with an appropriate number of stations. The results of this study can be applied to support strategic planning for emergency response systems in high-risk industrial areas. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:4048c2d6c88c7dcc115fcd49e7586cc8 URL:http://5thworldconferenceoninformations.sched.com/event/4048c2d6c88c7dcc115fcd49e7586cc8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T230000Z DTEND:20261017T231500Z SUMMARY:Process over Technology: Developing an Analytical Platform Concept that is Attractive to Jobseekers DESCRIPTION:Authors - \;Takashi Miyata\, Noriaki Takemura\, Takumi Kato\, Kazuhiko Tsuda\nAbstract - \;In the field of internal marketing\, concern exists that advanced technology may be perceived as a negative target in employee attitudes. This is because new technology will completely change the processes that employees have accumulated and put their employment at risk. Therefore\, to help employees understand the value of advanced technology\, the technology concept is important. By targeting an organization’s big data analysis infrastructure\, we verified a concept that is attractive to potential job-changers. A randomized controlled trial of 500 people in Japan revealed that potential job-changers are attracted to a workplace through the appeal of the presence of high-speed internal processes rather than high technical performance. This effect was more pronounced than concepts that promoted risk management such as personal information leaks\, or that promoted management of business domain knowledge. The background to this is that close collaboration with business departments is essential for data scientists to function effectively. The factors that cause data science projects to fail are more prominent in the aspects of internal processes and organizational friction than in technical aspects. Having an internal environment that solves these problems is very attractive to employees. By analyzing employees’ needs and developing a concept\, employees will have a positive attitude toward advanced technology. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:5d3ecb454ad30d3516f804881dd5768f URL:http://5thworldconferenceoninformations.sched.com/event/5d3ecb454ad30d3516f804881dd5768f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T230000Z DTEND:20261017T231500Z SUMMARY:ANALYSIS OF SKIN CANCER DETECTION AND CLASSIFICATION USING VISION TRANSFORMER DESCRIPTION:Authors - R. Kowsalya\, S. Ravi\, C. Manusha\, A. Saranya\, T. Kalaichelvi Abstract - A significant obstacle to early skin cancer detection is the diversity of skin types and colors. Compared to convolutional neural networks (CNNs)\, Vision Transformers (ViTs) are a powerful alternative. By applying self-attention mechanisms to model global dependencies within an image\, ViTs can capture long-range contextual information more effectively than traditional CNNs that use local convolutions to capture spatial patterns. A study describes how Vision Transformers perform better on large-scale image datasets than CNNs when trained with enough training data to achieve maximum performance. Additionally\, hybrid architectures are investigated\, which combine the advantages of CNNs and transformers strategies to improve generalization and training efficiency. It will help researchers learn about the latest deep-learning techniques and comparative analysis. It will also be helpful to know which type of Transformer is most suitable for accurately detecting the early stage of skin cancer classification and detection. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:7b3da20f21f4872dc182b5a13e6835ab URL:http://5thworldconferenceoninformations.sched.com/event/7b3da20f21f4872dc182b5a13e6835ab END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T230000Z DTEND:20261017T231500Z SUMMARY:Transforming healthcare with natural language processing DESCRIPTION:Authors - \;Rajneeshkaur Sachdeo Bedi\, Pankaj Chandre\, Pallavi Bhujbal\, Bhagyashree Shendkar\nAbstract - \;Transforming healthcare with Natural Language Processing (NLP) is revolutionizing how medical data is analyzed\, interpreted\, and utilized. This paradigm shift is fueled by NLP's ability to process diverse healthcare data sources such as medical research articles\, imaging reports\, electronic health records\, clinical notes\, and patient feedback. Key NLP tasks like text summarization\, information extraction\, named entity recognition\, sentiment analysis\, and question answering are at the core of enabling advanced applications in healthcare. These include medical research acceleration\, administrative task automation\, clinical decision support systems (CDSS)\, and patient care enhancement. Despite its promise\, challenges such as limited annotated datasets\, biases in models\, integration with legacy systems\, and ensuring data privacy and security persist. The integration of NLP-driven solutions into healthcare systems has immense potential to enhance efficiency\, improve patient outcomes\, and optimize decision-making processes. Addressing these challenges through innovation and collaboration will ensure the sustainable growth of NLP in smart healthcare systems. CATEGORIES:PHYSICAL TECHNICAL SESSION 2D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:e7d9d547d6b235279a25f7dfb48dbef6 URL:http://5thworldconferenceoninformations.sched.com/event/e7d9d547d6b235279a25f7dfb48dbef6 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T231500Z DTEND:20261017T233000Z SUMMARY:Bridging Languages\, Time Zones\, and Fatigue: A Hybrid RCPSP-GA-CP Framework for Multilingual IT Contact Center Optimization DESCRIPTION:Authors - Arnold Aguilar\, Ronaldo Polancos Abstract - Multilingual IT contact centers serve as vital operational structures for global corporations\, facilitating engagement with geographically dispersed clientele across diverse languages\, temporal zones\, and technical complexities. Excluding their strategic significance\, the mechanisms for scheduling and task allocation within these contexts have remained inadequately investigated within the classical project scheduling literature. Conventional frameworks addressing the resource-constrained project scheduling problem (RCPSP) neglect to incorporate dynamic constraints such as agent fatigue\, linguistic alignment\, shift-based availability\, or the demands of strategic escalation. This systematic literature review integrates more than twenty years of advancements in RCPSP\, leveraging hybrid metaheuristic methodologies—specifically Genetic Algorithms (GA) and Constraint Programming (CP)—to propose an innovative trajectory tailored to multilingual service operations. A case study is employed to corroborate the proposed model\, demonstrating its potential to enhance SLA compliance\, agent workload distribution\, and language-specific support efficacy. This research provides a dedicated conceptual and algorithmic foundation for multilingual support scheduling—an area that has been predominantly preoccupied from the mainstream RCPSP discourse—thereby establishing a basis for forthcoming empirical validation and implementation in high-demand support environments. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:d70f5a7094e023b9be6f0b40c865f90c URL:http://5thworldconferenceoninformations.sched.com/event/d70f5a7094e023b9be6f0b40c865f90c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T231500Z DTEND:20261017T233000Z SUMMARY:The Impact of Digitalization on Total Quality Management and Supply Chain Performance: Evidence from the Manufacturing Sector in a Developing Country DESCRIPTION:Authors - Luay Jum’a Abstract - This study examined the impact of digitalization on total quality management (TQM) practices and examines how both digitalization and TQM practices influ-ence supply chain performance (SCP) within the manufacturing sector in Jordan\, a developing country. Using the resource-based view and dynamic capabilities theory\, the study conceptualizes digitalization as a dynamic enabler that rein-forces internal quality capabilities. Data were collected through a self-adminis-tered survey targeting managers in Jordanian manufacturing firms\, resulting in 74 valid responses. Established measurement scales were used\, and the data were analyzed using multiple linear regression via SPSS. The findings reveal that dig-italization significantly enhances the implementation of TQM practices\, particu-larly by improving process visibility\, data integration\, and quality control. Amongst the six TQM dimensions examined\, only process management and em-ployee involvement demonstrated a significant positive impact on SCP. Addi-tionally\, digitalization was found to have a direct and positive effect on SCP\, reinforcing its strategic role in enhancing responsiveness and efficiency in supply chains. The study contributes to literature by incorporating digital transformation with quality and supply chain in the context of Jordan as a developing economy. It additionally offers actionable suggestions for managers in pursuit of aligning digital initiatives with quality-driven practices to improve supply chain out-comes. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:2385d513af9abd36a47aec05aafc0536 URL:http://5thworldconferenceoninformations.sched.com/event/2385d513af9abd36a47aec05aafc0536 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T231500Z DTEND:20261017T233000Z SUMMARY:Natural Language Processing for Business Insight - Sentiment Analysis of E-Hailing Driver Reviews in South Africa Using Ensemble and Probabilistic Learning Methods DESCRIPTION:Authors - Shane Maluleke\, Tebatso Gorgina Moape\, Ernest Mnkandla Abstract - The exponential growth of consumer and service provider reviews on digital platforms has generated substantial big data online\, creating both opportunities and challenges for business analytics. Businesses often use these reviews to evaluate customer satisfaction\, service quality\, and overall brand perception. Due to the vast amount of data generated\, traditional analysis methods are often inadequate for efficient processing. Hence\, most companies employ sentiment analysis techniques to analyze substantial volumes of data from reviews. Sentiment analysis is a subset of natural language processing that enables the automatic classification of text-based feedback according to the emotional tone expressed. In this paper\, sentiment analysis is conducted on the Uber driver app\, a ride e-hailing service\, within the South African context. This study intentionally focused on driver reviews instead of customer reviews\, as most research predominantly focuses on passenger satisfaction\, service quality\, and pricing strategies\, while driver perspectives remain understudied. The methodology employed in the paper involved a systematic data mining process\, followed by text pre-processing\, thematic code analysis of the collected data\, and the application of Naïve Bayes and Random Forest algorithms to classify the Uber driver app reviews. The Random Forest model outperformed the Naïve Bayes classifier\, with an accuracy of 0.9023\, while Naïve Bayes achieved an accuracy of 0.8333. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:5f3871b6ae53ee641befb14f5b3ed9a8 URL:http://5thworldconferenceoninformations.sched.com/event/5f3871b6ae53ee641befb14f5b3ed9a8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T231500Z DTEND:20261017T233000Z SUMMARY:A Hybrid LSTM-Transformer-Based MPC Framework for Efficient Greenhouse Climate Forecasting and Control DESCRIPTION:Authors - Khalid BOUALI\, Abderrahim BAJIT\, Hamza BENZZINE\, Ibtissam EL AOUNI\, Hicham ESSAMRI\, Siham BELOUALID\, Rachid EL BOUAYADI Abstract - The transition towards intelligent greenhouse agriculture is driven by the need to optimize resource efficiency and manage climate variability. Classical control methods\, such as PID and open-loop control systems\, have shown limi-tations in precision and in handling the nonlinearities. To address these chal-lenges\, advanced automation and predictive control strategies like Model Predic-tive Control (MPC) have gained attention. However\, achieving accurate forecasts of meteorological parameters remains critical for maintaining optimal growing conditions and reducing energy consumption. This paper proposes a hybrid deep learning model that integrates Long Short-Term Memory (LSTM) networks with Transformer architecture within an MPC framework to improve forecasting of key meteorological parameters\, including temperature\, humidity\, and solar irra-diance. By combining memory and attention mechanisms\, the model captures both short- and long-term dependencies in time series data. Experiments were conducted with varying input window sizes\, and performance was evaluated us-ing mean absolute error (MAE)\, root mean squared error (RMSE)\, and symmetric mean absolute percentage error (SMAPE). Results show that the proposed hybrid model outperforms standard LSTM models in both accuracy and inference time\, highlighting its potential to support intelligent greenhouse climate management and promote sustainable agriculture. CATEGORIES:PHYSICAL TECHNICAL SESSION 2D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:5eb5adabb7a45ab613f76feceabbc94e URL:http://5thworldconferenceoninformations.sched.com/event/5eb5adabb7a45ab613f76feceabbc94e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T233000Z DTEND:20261017T234500Z SUMMARY:AI in E-Business: A Comprehensive Analysis of AI Applications in Shopify’s Platform DESCRIPTION:Authors - Kayode Daniel Akilo\, Rhulani Maluleka\, Abelwe Maluleka Abstract - The introduction of Artificial Intelligence (AI) in revolutionizing e-business environments has considerably automated operational efficiency with ease. The induction of AI has increased consumer engagement and business suc-cess across the e-commerce landscape. Concerning this\, this research examines the application\, operation\, and various impacts and challenges of the adoption of artificial intelligence across e-commerce operations and platforms. Primarily focusing on Shopify as a case study\, this allows for an effective and efficient analysis of AI adoption. This research utilizes SWOT analysis and comprehensive academic literature in evaluating AI environments and AI adoption\, such as intelligent chatbots\, personalization engines\, and security systems. Through this analysis\, this research extends to how these implementations transform both small and medium-sized enterprises (SMEs). The research identifies the barriers to implementation\, strategic approaches in effective AI adoption\, and factors that are to be attributed to success. Additionally\, this research contributes to the competitive advantages through an established platform\, such as Shopify\, for a more grounded approach. This paper evaluates the AI adoption in the e-commerce landscape and addresses the economic infrastructure. Allowing effective solu-tions for SMEs in practical\, technical\, and ethical ways. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:2cf9b8479e269b8091574f5759a1a7f2 URL:http://5thworldconferenceoninformations.sched.com/event/2cf9b8479e269b8091574f5759a1a7f2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T233000Z DTEND:20261017T234500Z SUMMARY:Elucidating the mechanism of consumer behavior in tourism DESCRIPTION:Authors - \;M.Akashi\, M.Nagano\, Y.Ieiri\, O.Yoshie\nAbstract - \;Recently\, the number of tourists engaging in walking tourism at various destinations has increased\, presenting new opportunities for local economic activity. However\, the mechanisms underlying consumer behavior in walking tourism remain unclear\, and effective methods for designing such tourism have not been established. This study aims to elucidate the mechanism of consumer behavior by integrally analyzing eye-tracking data\, conversation data\, and electrodermal activity (EDA) data collected during walking tours. Empirical experiments were conducted in Otaru City and Atami City\, with data analyzed from multiple perspectives. The analysis revealed that eye-tracking data\, conversation data\, and EDA data can effectively identify triggers of consumer behavior during walking tourism. Furthermore\, the increase in EDA highlights the potential to extract consumer behavior in walking tourism. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:ad5fa0719e7a1554cebebfc11a2a4aac URL:http://5thworldconferenceoninformations.sched.com/event/ad5fa0719e7a1554cebebfc11a2a4aac END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T233000Z DTEND:20261017T234500Z SUMMARY:Impact of the Internet of Things on Smart Logistics Management: A Bibliometric Analysis DESCRIPTION:Authors - Mathew Philip\, Ruksana Banu\, Amala Nirmal Doss Savari\, Mimy Mathew\, Ahmed Aboualam Abstract - The rapid progress of Internet of Things (IoT) technology and digitalisation is transforming the logistics sector into more efficient operational processes and data-informed decision-making. This shift is driven by evolving market demands\, sustainability imperatives\, and the emergence of innovative business models. This study aims to identify and analyse current research trends in the application of IoT in smart logistics management\, and to understand how these technologies address existing research gaps in traditional logistics systems. The study presents a bibliometric analysis and examines the concept of smart logistics. It also reviews and analyses IoT-based smart Logistics Management (SLM) research\, demonstrating how IoT influences smart logistics. The study reveals that the most prominent area\, based on Scopus research from 2017 to 2025\, was IoT\, which is regarded as a key revolution. Terms like efficiency\, visibility\, and responsiveness highlight the operational priorities IoT technologies seek to optimise within logistics and supply chain contexts. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:a4137fc35a361b0e3f74024a7f611945 URL:http://5thworldconferenceoninformations.sched.com/event/a4137fc35a361b0e3f74024a7f611945 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T233000Z DTEND:20261017T234500Z SUMMARY:Edge AI-Enhanced Nodes for Intelligent Agricultural Greenhouse Microclimate Control DESCRIPTION:Authors - Khalid BOUALI\, Abderrahim BAJIT\, Hamza BENZZINE\, Siham BELOUALID\, Youness ZAHID\, Mohamed Nabil SRIFI\, Rachid EL BOUAYADI Abstract - With the rapid advancement of the Internet of Things (IoT)\, smart de-vices have become integral to various sectors\, including healthcare\, transporta-tion\, smart homes\, and industrial systems. In agriculture\, these technologies have driven a shift toward automation and data-driven decision-making through the adoption of smart sensing systems. However\, most existing systems remain con-strained by their reliance on centralized cloud infrastructure\, resulting in latency\, increased computational costs\, and limited real-time capabilities. This work pro-poses an optimized microclimate sensor node architecture that incorporates edge computing abilities to enable real-time processing of sensor data and localized decision-making. These nodes are enhanced with Edge Artificial Intelligence to offer prediction analysis capacities at the edge. In this study\, we focused on the prediction of missing sensor data using the intercorrelation between microclimate features\, including temperature\, humidity\, CO₂\, and light intensity. The study evaluates three supervised regression models\, including Random Forest (RF)\, Extreme Gradient Boosting (XGBoost)\, and Artificial Neural Network (ANN)\, based on R²\, RMSE\, and MAE metrics. Experimental results demonstrate the superior performance of the RF model in learning the patterns between the mi-croclimate parameters\, achieving R² scores of 98.88 % in predicting temperature\, 95.60 % for humidity\, 94.67 % for CO₂\, and 97.40 % for light intensity. The results present the effectiveness of the model in predicting the missing parameters using the available ones. By enabling predictive inference at the edge\, this ap-proach optimizes the monitoring systems\, reduces the dependency on the cloud servers\, and contributes to sustainable agriculture\, generally offering a scalable solution for resilient\, intelligent\, and real-time monitoring in precision agricul-ture. CATEGORIES:PHYSICAL TECHNICAL SESSION 2D LOCATION:Benchasiri 4\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:1275b0a44edb4893a7e5491fb5a45106 URL:http://5thworldconferenceoninformations.sched.com/event/1275b0a44edb4893a7e5491fb5a45106 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T234500Z DTEND:20261018T000000Z SUMMARY:First General Meetings and the Handover Process: An Analysis of Developers Compliance with South African Sectional Title Schemes DESCRIPTION:Authors - Balebetse H. Skele\, Partson Paradza\, Benita G. Zulch\, Joseph A. Yacim Abstract - In South Africa\, Section 2 of the Sectional Title Schemes Management Act of 2011 (the Act) requires developers to attend the First General Meeting (FGM) and present necessary documentation to the corporate body. However\, non- compliance with standards and incomplete submissions by developers often lead to the postponement of the FGM. This results in financial burdens for the body corporate and the signing of long-term contracts without proper oversight. The impact of this non-compliance has not been investigated\, highlighting the need for further investigation to improve handover procedures under the Act. Thus\, this study aims to inform current policies and contribute to the literature on the handover process of residential sectional title properties. Adopting a case study approach\, the research integrates mixed methods to collect data from seven sectional title schemes in the Western Cape and Gauteng Provinces. Findings reveal that developers' non-attendance at FGMs causes communication breakdowns with Body Corporate\, rendering FGMs ineffective. This paper provides valuable insights for policy on sectional title purchases in South Africa. It also contributes to the litera-ture by examining the challenges in the handover processes of sectional title properties in South Africa. CATEGORIES:PHYSICAL TECHNICAL SESSION 2A LOCATION:Benchasiri 1\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:f3ea205de0ef35e81fb5bfa295c20829 URL:http://5thworldconferenceoninformations.sched.com/event/f3ea205de0ef35e81fb5bfa295c20829 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T234500Z DTEND:20261018T000000Z SUMMARY:Sustainable Optimization of Industrial Plant Layouts: A Systematic Review of Methodologies\, Tools\, and Indicators DESCRIPTION:Authors - Anthony Garces L\, Pablo Flores-Siguenza\, Lorena Siguenza-Guzman\, Piera Maresca\, Rodrigo Guaman Abstract - In a global landscape increasingly driven by competitiveness and sus-tainability\, manufacturing companies face significant challenges in adopting sustainable practices—often due to financial limitations\, limited technical training\, and inadequate policy support. This study presents a systematic literature review focused on methodologies\, tools\, and performance indicators used to optimize industrial plant layout\, with a particular emphasis on enhancing operational efficiency and environmental sustainability. Using Fink’s methodology\, 46 peer-reviewed articles published between 2014 and 2024 were rigorously analyzed through a three-tier bibliometric approach: meta-analysis\, keyword clustering\, and descriptive sample analysis. The findings highlight the effectiveness of hybrid strategies that integrate systematic layout planning (SLP)\, advanced simulation platforms (FlexSim\, Arena\, ProModel)\, and multi-criteria decision-making techniques (AHP\, NSGA-III). These approaches demonstrate clear improvements in workflow efficiency\, bottleneck reduction\, and environmental impact mitigation. Key performance indicators identified include material flow\, travel distance\, cycle time\, inventory levels\, and carbon footprint. The study under-scores the importance of integrated methodologies that align operational and sus-tainability objectives\, offering valuable insights for decision-making in industrial engineering and facility planning goals. CATEGORIES:PHYSICAL TECHNICAL SESSION 2B LOCATION:Benchasiri 2\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:ac1a4005db3c8291a15f2add27459a66 URL:http://5thworldconferenceoninformations.sched.com/event/ac1a4005db3c8291a15f2add27459a66 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261017T234500Z DTEND:20261018T000000Z SUMMARY:A Comparative Study of Machine Learning and Deep Learning Models for Technology Stock Price Prediction using News Sentiment and Economic Indicators DESCRIPTION:Authors - \;Pornpimol Chaiwuttisak\nAbstract - \;This study developed predictive models for the closing prices of five leading technology stocks: GOOGL\, MSFT\, AAPL\, NVDA\, and META by employing five advanced machine learning and deep learning techniques: Light Gradient Boosting Machine (LightGBM)\, Extreme Gradient Boosting (XGBoost)\, Recurrent Neural Network (RNN)\, Gated Recurrent Unit (GRU)\, and Long Short-Term Memory (LSTM). The modeling framework integrated sentiment scores derived from financial news articles specific to each stock us-ing the VADER Sentiment Analysis tool\, in conjunction with a range of macro-economic indicators. Model performance was evaluated separately for each stock using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) as primary metrics. To determine whether statistically significant dif-ferences existed among the predictive performance of the models across all stocks\, the Friedman test was employed\, followed by the Wilcoxon signed-rank test for post-hoc pairwise comparisons. The empirical results indicated that XGBoost achieved superior predictive accuracy for MSFT and AAPL\, GRU outperformed other models for NVDA and META\, while RNN yielded the most accurate forecasts for GOOGL. CATEGORIES:PHYSICAL TECHNICAL SESSION 2C LOCATION:Benchasiri 3\, Bangkok Marriott Hotel Sukhumvit\, Thailand SEQUENCE:0 UID:321c26de54b808f6c10f7e22eb1ba451 URL:http://5thworldconferenceoninformations.sched.com/event/321c26de54b808f6c10f7e22eb1ba451 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T162800Z DTEND:20261018T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:a811676f7032179dbb064c1aa130cd0f URL:http://5thworldconferenceoninformations.sched.com/event/a811676f7032179dbb064c1aa130cd0f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T162800Z DTEND:20261018T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:0132dcb3a306673591c13ba01b733226 URL:http://5thworldconferenceoninformations.sched.com/event/0132dcb3a306673591c13ba01b733226 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T162800Z DTEND:20261018T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:868f32c33100063a817f4143eb2a9402 URL:http://5thworldconferenceoninformations.sched.com/event/868f32c33100063a817f4143eb2a9402 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T162800Z DTEND:20261018T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:6c9a1c2d919fd95053d9b2778dac1e70 URL:http://5thworldconferenceoninformations.sched.com/event/6c9a1c2d919fd95053d9b2778dac1e70 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T162800Z DTEND:20261018T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:448320991159c1a4046376c938e3ee36 URL:http://5thworldconferenceoninformations.sched.com/event/448320991159c1a4046376c938e3ee36 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T162800Z DTEND:20261018T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:f973e234a762a42b12dc04ab16236bf0 URL:http://5thworldconferenceoninformations.sched.com/event/f973e234a762a42b12dc04ab16236bf0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Agribusiness Transformation Towards a Green Economy: The Role of Policies\, Innovation\, and Sector Collaboration in Enhancing Sustainability DESCRIPTION:Authors - Reinardus Dwi Prio Christianto\, Nur Wening\, Abdul Wahab Samad\, Ranthy Pancasasti\, Sujoko Abstract - This study explores the role of transitioning to a green economy within the agribusiness sector\, encompassing agriculture\, fisheries\, livestock\, forestry\, agro-processing industries\, and renewable energy. Using advanced theoretical and practical approaches\, the primary focus is to investigate policies and innovations that facilitate green economy implementation\, while emphasizing behavioral stress management among stakeholders facing structural and technological shifts. Data were collected through surveys assessing eco-friendly policy adoption\, technological innovations\, and stakeholders' perceptions of psychological stress\, adaptation pressures\, and behavioral resilience during the transition. Data analysis was conducted using NVIVO 14 through coding techniques to identify key themes\, such as resource efficiency\, carbon emission reduction\, and coping mechanisms for stress. The findings reveal that policies fostering cross-sectoral collaboration and green technology adoption not only enhance agribusiness efficiency and sustainability but also mitigate behavioral stress induced by the demands of change. Visual tools such as word clouds and frequency distribution charts illustrate the levels of policy acceptance and emerging psychosocial adaptation patterns. This study contributes significantly to understanding the intersection of green policy\, technological innovation\, and stress management strategies in accelerating sustainable transformation within the agribusiness sector CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:3f265d8bd4e90715c2d257bfcc63f193 URL:http://5thworldconferenceoninformations.sched.com/event/3f265d8bd4e90715c2d257bfcc63f193 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:An Innovative Secured Spectrum Management Technologies in CRN: A Review DESCRIPTION:Authors - Reshma C R\, ArunKumar B R Abstract - The wireless communication impacts any application in accordance with the security model. This research paper focuses on the transmission technologies to access the unused portion of the spectrum among primary user and secondary user in cognitive radio networks. The users ensure trust models are implemented for the identity of the user\, later the verification process are involved to assign the spectrum to the secondary users. The security threats are experiential for both the users i.e. Primary User and Secondary User. The prevention measures need to be adapted to perform the hand-off for spectrum management in CRN. This research work\, encompasses the different transmission technologies for spectrum utilization. The security model with zero knowledge proof\, blind signature and zero trust security model for identity and access management in cognitive radio network are addressed to manage the spectrum securely. The system performs various stage verification to determine the identity of the user. CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:dcaf3000b078b3b2bdf7bee0b82f8e73 URL:http://5thworldconferenceoninformations.sched.com/event/dcaf3000b078b3b2bdf7bee0b82f8e73 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Evaluating the Effectiveness and Challenges of Software in Paediatric Healthcare DESCRIPTION:Authors - Bhagyashree Thakur\, Shailesh Gahane\, Deepak S. Sharma\, Pankajkumar Anawade Abstract - The pediatricians and other health workers manage and treat children has been modified through the introduction of software into children's medicine. Clinical decision support systems (CDSS)\, telemedicine platforms\, electronic health records (EHRs)\, and patient management systems are imperative for optimizing patient outcomes\, eliminating administrative overhead\, and optimizing the delivery of care. This research examines the advantages and disadvantages of using technology in a pediatric health facility. Among the ways these technologies work are more accurate diagnosis\, more efficient chronic disease management\, more effective caregivers and providers communication\, and monitoring patient progress remotely. For instance\, telemedicine has been extremely beneficial in rural and underserved communities But using software in the pediatric clinic does pose several challenges. Software system compatibility\, training needs for healthcare personnel\, and data privacy concerns especially in maintaining the confidentiality of sensitive information on children are significant challenges. The complexity of pediatric care and its specific requirements\, such as tracking children's growth and evaluating development\, also make integrating generic healthcare software a challenge.\, offering specialty care that would not otherwise be available. In spite of these issues\, there are still possible advantages to the use of software in pediatric healthcare delivery. As technology continues to evolve\, software will have to overcome security\, training\, and system integration issues in order to be as helpful as possible for enhancing pediatric healthcare outcomes. CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:d7278ffb030d576473a43f78aaf714c5 URL:http://5thworldconferenceoninformations.sched.com/event/d7278ffb030d576473a43f78aaf714c5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Investigating the Key Factors Influencing Software Developer Productivity in Developing Regions DESCRIPTION:Authors - Rafid Al Ahsan\, Rifat Ara Rouf\, Farzana Sadia\, Mahady Hasan\, Saadia Binte Alam\, M. Rokonuzzaman Abstract - Software developer productivity is a critical factor influencing the efficiency and success of software projects. However\, understanding the key factors that impact developer productivity remains a challenge\, particularly in region-specific contexts such as Bangladesh. This study aims to identify the primary factors affecting developer productive and analyze how these factors vary across companies and experience levels. To achieve this\, a survey was conducted among software developers working in Bangladesh. The survey sent out to 168 software developers working across 38 different software firms. The survey yield 44 responses. Statistical analysis was employed to determine the most influential factors. The findings suggest that autonomy in decision-making\, task variety\, and using the best practices\, software and tool are the strongest factors affecting productivity. While some factors\, such as task variety\, remain consistent across companies\, other\, such as remote work policies and communication styles\, vary significantly. Additionally\, beginner developer prioritize learning\, and tool adoption\, mid-level developers face challenges with tight deadlines\, and senior developer focus more on leadership\, collaboration and decision-making autonomy. CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:25d626de550cca53f3dddce4c6e28d9b URL:http://5thworldconferenceoninformations.sched.com/event/25d626de550cca53f3dddce4c6e28d9b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Learning to Lead with Social Mission: The Role of Social Entrepreneurship Education DESCRIPTION:Authors - T.A. Alka\, M. Suresh Abstract - The study aims to map the current trends in social entrepreneurship education (SEE) research through a bibliometric analysis of 119 papers\, followed by the PRISMA protocol analysed through the Biblioshiny package and the VOSViewer to investigate the themes and the collaboration patterns of countries\, and to propose the research implications. This research contributes to the current knowledge through a systematic analysis of the existing SEE research guide\, through the research questions\, and a comprehensive analysis. Themes identified in this research are: the foundation of pedagogy for sustainable and value-based education\, ecosystem support for the SEE\, student-oriented perspective\, and the social capital in SEE\, etc. From the cluster analysis\, the most emerging topics are: the role of innovation and design thinking for sustainability\, entrepreneurship pedagogy development for inclusive social entrepreneurship knowledge management\, experiential and service learning in the SEE\, and the social innovation in the SEE for system-level metamorphosis to create responsible entrepreneurs. The collaboration dynamics reveal that the five clusters are in the southern and northern countries in the practice and context-based research in the SEEs\, East Asia\, and the central Europe or eastern Europe countries on the innovation\, policy\, and Anglo-Asia-Pacific collaboration in the scholarship of the policy in SEEs. The major limitation of the study is purely based on secondary data and lacks empirical understanding. The study offers further research scope on combining data-bases\, and the mixed method research by integrating qualitative insights into more quantitative analysis through methods like BERTopic modelling\, etc\, integrated with hypothesis testing. CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:586070944a8c91375d03c3691feb9851 URL:http://5thworldconferenceoninformations.sched.com/event/586070944a8c91375d03c3691feb9851 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Literature Review on Conceptual Understanding in Programming: Foundations for a Validated Assessment Instrument DESCRIPTION:Authors - \;Azran Ahmad\, Naziffa Raha Md. Nasir\, Azlan Yusof\, Aslina Mat Asli\, Fazlina Mohd Ali\, Surya Sumarni Hussein\nAbstract - \;As programming education evolves\, enhancing conceptual under-standing among novice learners remains a critical challenge. This literature review synthesizes key pedagogical innovations from 2015 to 2025 that inform the development of a validated assessment instrument for programming conceptual understanding. Five major approaches are explored: conceptual metaphors\, robotics and interactive tools\, prototype theory\, physical programming tools\, and ontology-based frameworks. These strategies collectively aim to scaffold abstract reasoning\, reduce cognitive load\, and foster deeper learner engagement. Conceptual metaphors provide intuitive cognitive bridges between everyday experiences and abstract programming constructs. Robotics and physical tools offer tangible\, multimodal learning environments that enhance motivation and comprehension. Prototype theory emphasizes relatable exemplary to support categorization and knowledge transfer\, while ontology-based learning structures promote metacognitive reflection and conceptual integration. The review high-lights a growing consensus that multimodal\, metaphorical\, and structured pedagogies significantly improve computational thinking and problem-solving skills. This synthesis supports the design of the Programming Conceptual Understanding Test (PCUT)\, a novel assessment tool grounded in cognitive science and validated through mixed-methods research. The review concludes by identifying future research directions\, including cultural adaptability\, scalability\, and integration with adaptive technologies to personalize learning. These insights offer a foundation for a more inclusive\, effective\, and engaging programming education CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:d7c0c05a164ff467f77c46dba7c08798 URL:http://5thworldconferenceoninformations.sched.com/event/d7c0c05a164ff467f77c46dba7c08798 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Plant Disease detection using Deep Learning Techniques DESCRIPTION:Authors - Ch V S Satyamurty\, Ch Srikarthik Abstract - Plant diseases are of numerous kinds. Recognizing each one of them would be a tedious task for a human being\, but a machine can solve this issue. Farmers used to take a small cutting of an infected plant to a local garden centre\, which includes plant pathologists who can often help to identify the disease manually. Later Machine learning algorithms came into existence and its usage gave the accurate results. Machine Learning deals with classification and used to classify plants based on health like unhealthy and healthy plants. "Classification" is the key concept used here. Classification of the plant leaves done centred around morphological features. Classification can be done by using decision tree\, k- means clustering\, neural network etc. We are proposing a web application which helps in identifying the disease type for the given input from a trained data set using "Convolutional Neural Network"\, a deep learning algorithm. CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:7ee9971faf5beaafcc3d2b587c1f9c9e URL:http://5thworldconferenceoninformations.sched.com/event/7ee9971faf5beaafcc3d2b587c1f9c9e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Real-Time Posture Monitoring for Sitting Activities Using MediaPipe DESCRIPTION:Authors - Herry Rojivadiya\, Priyanka Patel Abstract - In today’s digital-driven lifestyle\, individuals across various sectors—including students\, office employees\, and remote workers—spend extended hours seated in front of screens. Prolonged sedentary behavior often results in poor postural habits\, leading to musculoskeletal discomfort and decreased productivity. This research presents a real-time posture monitoring system utilizing MediaPipe BlazePose for keypoint detection. By analyzing the spatial relationships between body landmarks\, the system identifies postures such as slouching\, leaning\, and improper arm or leg positioning. Immediate feedback is provided to encourage healthier sitting habits across diverse environments\, from classrooms to offices and home workstations. CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:967072f777d29b01994c814494a9984d URL:http://5thworldconferenceoninformations.sched.com/event/967072f777d29b01994c814494a9984d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Strategic Integration of RPA\, BPM\, and Digital Transformation in Industry 5.0 DESCRIPTION:Authors - Truong Bui Quang\, Huu Dang Quoc\, Van Nguyen Thi Cam\, Anh Nguyen Duc Abstract - This paper examines the interaction between Robotic Process Automation (RPA)\, Business Process Management (BPM)\, and Digital Transformation (DT) - three critical components in improving operational efficiency and driving business modernization. RPA automates repetitive tasks\, reduces errors\, accelerates processing\, and optimizes resource use. When combined with Artificial Intelligence (AI) and Machine Learning (ML)\, it further enhances data analysis and decision-making. BPM focuses on analyzing\, designing\, and optimizing business processes to ensure organizational agility. DT provides a technological foundation for broader innovation in processes and structures. The paper contributes a comprehensive and updated perspective on how RPA\, BPM\, and DT interrelate—not only functioning independently but also reinforcing one another to create greater business value. It emphasizes that their integration is a strategic approach to improving performance\, responsiveness\, and continuous innovation. Importantly\, the research is relevant to both Industry 4.0 and Industry 5.0. While Industry 4.0 prioritizes automation and data-driven systems\, Industry 5.0 highlights human–technology collaboration for more adaptive and human-centric organizations. This study enriches theoretical insights and offers practical guidance for building effective and sustainable digital transformation strategies. CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:3cf6a6ea509af05baa9cb26fb66d6dcf URL:http://5thworldconferenceoninformations.sched.com/event/3cf6a6ea509af05baa9cb26fb66d6dcf END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:WEARABLE SENSORS TO SELF-MONITORING DEVICES: TRANSFORMING PERSONAL HEALTH MANAGEMENT DESCRIPTION:Authors - Anupama Ugemuge\, Shubham Kishor Kadam\, Utkarsha Wanjari Abstract - This paper highlights the transformative potential of wearables and the importance of ongoing innovation and research in this dynamic field. Self-monitoring devices and wearable sensors are changing the way people can maintain their health independently by enabling the instant tracking of some important bodily parameters. Such technologies enable continual monitoring that facilitates early identification of health problems and fosters proactive healthcare involvement. From fitness trackers to glucose monitors\, these wearables are primarily used to help patients manage chronic conditions\, achieve fitness goals\, and maintain general well-being. They provide important advantages such as lowering costs\, personalized health information\, and compatibility with other mobile applications. Nevertheless\, issues such as data accuracy\, privacy\, and user acceptance are still good fields for further research and development. With the rapid progress in artificial intelligence and sensor technology\, we stand on the brink of a generation of wearable health devices that will reshape the landscape of healthcare\, offering predictive health analytics and widening access to healthcare around the globe. CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:3c054011da9e1eff0ca85b9fc9d93058 URL:http://5thworldconferenceoninformations.sched.com/event/3c054011da9e1eff0ca85b9fc9d93058 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:A Dual-Branch DeepMF Framework Enhanced by NLP for Intelligent Tutoring Systems DESCRIPTION:Authors - Nguyen Xuan Ha Giang\, Lam Thanh-Toan\, Nguyen Thai-Nghe Abstract - This study introduces a novel dual-branch Deep Matrix Factorization (DeepMF) framework enhanced by NLP techniques for predicting student performance in the Intelligent Tutoring Systems. Building on previous research\, the proposed approach adopts a fundamentally different modeling strategy by transforming discrete educational features-such as learner ID\, exercise\, question\, skill group\, session start time\, and repeated attempts-into structured sentences that capture both temporal and sequential information. These inputs are processed through two complementary branches. The first branch employs pre-trained GloVe embeddings\, followed by a self-attention layer that captures intra-sequence dependencies before passing the representations into a DeepMF module. The second branch leverages a BERT-based model to extract contextualized language features. To address the issue of class imbalance\, Focal Loss is applied during training on both the KDDCup 2010 and Assistment 2017 datasets. Experimental results demonstrate substantial improvements in prediction accuracy: RMSE is reduced from 0.418 to 0.167 (a 60.1% reduction) on KDDCup 2010\, and from 0.472 to 0.186 on Assistment 2017 (representing a 60.6% relative improvement). These findings confirm the effectiveness of integrating contextual\, sequential\, and temporal modeling with DeepMF in educational data mining. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:5f7125ac6c615383c0121dfd7e66f3af URL:http://5thworldconferenceoninformations.sched.com/event/5f7125ac6c615383c0121dfd7e66f3af END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:An Overview of India's Policy Measures from Gender Perspective: During and After the COVID-19 Pandemic DESCRIPTION:Authors - \;Hariprasad Rai M\, Shankar Lingam. M\nAbstract - \;The COVID-19 pandemic has had profound and multifaceted impacts on global economies\, with gender disparities becoming increasingly apparent. This paper explores the gendered effects of India's policy measures in response to the pandemic\, focusing on the socio-economic challenges faced by women. It assesses the policy interventions implemented by the Indian government to mitigate these impacts\, such as cash transfers\, healthcare support\, and social security measures. Drawing from data collected through the COVID-19 Global Gender Response Tracker\, the study highlights the gendered dimensions of these policies and their effectiveness in addressing the unique needs of women during the crisis. The analysis underscores the need for gender-sensitive economic and social policies to ensure equitable recovery and resilience for women in future crises. By critically examining the intersection of gender\, policy\, and pandemic response\, this paper contributes to a deeper understanding of the importance of gender-inclusive strategies in man-aging global health emergencies. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:aa47bc085c68f5bfdf2444682c3f47e9 URL:http://5thworldconferenceoninformations.sched.com/event/aa47bc085c68f5bfdf2444682c3f47e9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Customer Behavior\, Adoption and Retention in Software Markets: An AI-Based Analysis for Strategic Growth of Software Business. DESCRIPTION:Authors - Md Mahbub Alam\, Sabrina Sultana Prithul\, Md. Sajjad Hossain Abstract - Understanding and predicting customer behavior is essential for sustaining growth and profitability in the software market. This study proposes an AI-driven framework for analyzing customer adoption patterns and churn risk through the integration of clustering and classification techniques. Using real-world behavioral data\, the research first applies K-Means clustering to segment users into distinct behavioral groups. Four meaningful segments were identified\, each characterized by varying engagement levels\, contract types\, and churn tendencies. Subsequently\, supervised machine learning models—Logistic Regression\, Random Forest\, and XGBoost—were employed to predict churn. Among these\, XGBoost achieved the highest performance\, with an accuracy of 87.1% and an ROC-AUC score of 0.91. Feature importance analysis highlighted tenure\, contract type\, and monthly charges as critical churn predictors. The findings offer practical insights into personalized retention strategies and pricing interventions\, emphasizing the utility of AI in customer analytics. This work contributes to the field by bridging behavioral segmentation with predictive modeling\, providing a scalable and interpretable approach to managing customer lifecycle challenges in software-based services. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:6a2a20937f414af937cd850995a25fa2 URL:http://5thworldconferenceoninformations.sched.com/event/6a2a20937f414af937cd850995a25fa2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Cyber Security For Mobile Applications Using Artificial Intelligence DESCRIPTION:Authors - S. Rajaprakash\, G. Sujatha\, S. Kavitha\, Vivek Darsi\, Mohith Sai Kurakalva\, Srikar Reddy Palapati Abstract - The growth of mobile applications has reached extraordinary levels because they provide users better features and convenience for daily needs. Massive mobile application expansion resulted in fresh security issues creating an in-creased number of cyber threats throughout the market. The number of cyber risks increases in Germany since malicious applications both harm device integrity and illegally obtain user information to threaten individual privacy together with organizational security measures. The development of strong auto- mated security systems with locating and removal capabilities of threats remains an urgent matter. Cybersecurity systems at present base their protection on fixed rule systems alongside traditional machine learning approaches. The implemented security methods deliver protection however they demonstrate reduced performance during changes in cyber threat patterns. The system exposes sever-al entry points which hackers can leverage for attack purposes. An innovative cyber- security framework has been developed which incorporates the RF algorithm with PCA through this project to address existing limitations. The system uses mobile application metadata preprocessing to accomplish three tasks through PCA: elimination of unneeded data and retention of important features along with feature selection. This procedure simultaneously maintains data authenticity as well as enhances processing speed. Random Forest becomes operational to classify mobile applications between malicious and safe categories within the framework. RF algorithm and PCA form a flexible and scalable system which enables handling extensive datasets along with security adaptation towards the latest threats. The system has a user-friendly interface which enables users to enter mobile app metadata and get prompt predictions along with performance scores. Mobile app users benefit from predictions which help them decide about the safety of apps through confidence scoring. The system maintains strict vali- dation procedures across unidentified datasets which confirm its dependable and practical functionality during actual use. Evaluation of the model effectiveness depends on performance metrics that include accuracy together with precision\, recall and F1-score. The system delivers complete performance information which allows end-users to receive practical insights and enable greater transparency. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:50986a2bbfcb90060683aae0666619ab URL:http://5thworldconferenceoninformations.sched.com/event/50986a2bbfcb90060683aae0666619ab END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Impact of Quality\, Accessibility and Affordability on Patient Satisfaction in Healthcare Services DESCRIPTION:Authors - Gaurav Kamble\, Chetan Parlikar Abstract - This study explores the impact of the quality of healthcare services\, their accessibility\, and affordability on patient satisfaction. With patient satisfaction becoming a crucial determinant of healthcare quality\, it is important to establish drivers of patient satisfaction in order to empower healthcare providers to improve service delivery. Specifically\, the study seeks to establish the level to which healthcare service quality\, accessibility of healthcare services\, and their affordability independently influence patient satisfaction. A survey of 206 respondents was conducted\, and data on respondents' perceptions and experiences of healthcare services were collected. The study analyses the interaction among the three drivers and patient satisfaction with a view to providing actionable in-sights into the improvement of healthcare outcomes. With the onset of greater emphasis on patient-centred care\, this study provides timely and relevant evidence capable of guiding policy and strategy towards enhancing the quality\, accessibility\, and affordability of healthcare services. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:b7889fc6b079635547af867f94b67f1b URL:http://5thworldconferenceoninformations.sched.com/event/b7889fc6b079635547af867f94b67f1b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Minimalist Human Oversight for Trustworthy Multi-Agent Systems DESCRIPTION:Authors - Jay Prakash Thakur\, Akshata Kishore Moharir Abstract - Multi Agent Systems (MAS) face a critical challenge to maintain trustworthiness alongside operational efficiency as they move from theoretical development to practical implementation in essential domains. Human-in-the-loop approaches create operational bottlenecks that limit scalability\, but fully autonomous systems face the risk of catastrophic failures. The proposed framework in the paper introduces a new approach to minimal human oversight through strategic intervention points that use intelligent triggers that assess risk and quantify uncertainty\, detect novelty\, and analyze consensus. The framework achieves scalable oversight of complex MAS through optimized information flow and reduced cognitive load that maintains critical safety guarantees.This position paper conducts a theoretical analysis of the impact of system performance while presenting applications for autonomous transportation\, critical infrastructure management\, and financial systems. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:40d5ffa2d5af3fb1d5a7d42635396b05 URL:http://5thworldconferenceoninformations.sched.com/event/40d5ffa2d5af3fb1d5a7d42635396b05 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Statistical Computing for Variance Zero-inflated Two-parameter Rayleigh Distribution DESCRIPTION:Authors - Sasipong Kijsason\, Sa-Aat Niwitpong\, Suparat Niwitpong Abstract - Parameter variance is used to measure the dispersion of data or the deviation of individual data points from the mean. A high variance indicates that the data are widely spread around the mean\, reflecting greater variability within the dataset. This study introduces four novel methods for constructing confidence intervals for the variance of the Zero-Inflated two-Parameter Rayleigh distribution. These include the percentile bootstrap\, the bootstrap method with standard error\, the standard method based on a large sample\, and generalized confidence interval approaches. A simulation-based comparison was conducted using coverage probability and expected length as performance criteria. The findings indicate that the generalized confidence interval and standard method achieved coverage probabilities closest to the nominal confidence level. Among these methods\, the generalized confidence interval demonstrated the highest efficiency. Additionally\, the proposed methods were applied to real-world data on COVID-19 mortality rates in Malaysia during September 2021. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:54110e849db510dcdff69f7cb06a0484 URL:http://5thworldconferenceoninformations.sched.com/event/54110e849db510dcdff69f7cb06a0484 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Time-Sensitive Networking for Industrial Automation: A Hands-on Approach DESCRIPTION:Authors - Eshwari V. Kadu\, Sudhir Agarmore Abstract - An IEEE family of standards called Time-Sensitive Networking (TSN) builds upon Ethernet to facilitate determinism over communications with guaranteed low latency\, low jitter\, and high dependability. Providing synchronized\, deterministic network operation on prevalent Ethernet equipment\, TSN finds itself at the center of essential enabler support for emerging applications such as industrial automation\, self-driving vehicles\, and smart grid\, all which necessitate deterministic\, real-time sharing of information. Time-sensitive scheduling\, traffic priority\, redundancy\, and perfect time synchronization are only a few of the most important aspects of TSN discussed in depth in this paper\, which also follows the development of the technology from ordinary Ethernet and identifies the necessity for time-sensitive communication. Besides\, we examine the challenges of deploying TSN\, summarize real-world applications across various industries\, and discuss emerging trends such as integrating TSN with wireless networks and edge computing. As part of ensuring TSN has the ability to meet the demands of future-time-critical systems\, we identified open research avenues and directions as part of our research. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:600a457b13223c4507b95ee02371a2de URL:http://5thworldconferenceoninformations.sched.com/event/600a457b13223c4507b95ee02371a2de END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Travel Without Touch: Motivation Factors\, Drivers of Virtual Tourism in the Post-Pandemic Time DESCRIPTION:Authors - Thanaporn Phattanaviroj\, Massoud Moslehpour\, Princy Pappachan\, Mosiur Rahaman\, Jirapong Pomnoi\, Rinruedee Pattaradej Abstract - The tourism industry has undergone significant transformations following the COVID-19 pandemic\, particularly through the adoption of digital technologies such as virtual tours. This study investigates the motivational factors influencing individuals' intention to adopt virtual tours\, using Protection Motivation Theory (PMT) as the theoretical framework. It identifies two key components: threat appraisal (perceived travel and health risks) and coping appraisal (enjoyment\, perceived cost-effectiveness\, and sustainability motivation). Data was collected through a designed questionnaire and analyzed by applying Partial Least Squares Structural Equation Modeling\, with 122 respondents. The findings indicate that threat and coping appraisals have a significant influence on the intention to adopt virtual tours. The research provides insight into the evolving behavior of tourism consumers in a post-pandemic context. It highlights the potential of virtual tourism as a sustainable and attractive alternative to physical travel. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:10e2bf3e5cc31d592630a151b850db37 URL:http://5thworldconferenceoninformations.sched.com/event/10e2bf3e5cc31d592630a151b850db37 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:What drives earnings in Digital Labour Markets: College Degrees or Five-Star ratings? DESCRIPTION:Authors - Anju Kamal\, Rajiv Prasad Abstract - The emergence of technology driven gig economy and digital labor platforms has transformed the methods of sourcing\, assessing\, and remunerating work. This study examines how traditional credentials like educational degrees and platform-specific ratings like Top Rated and Top-Rated Plus affect freelancer earnings in digital labor marketplaces. We use regression analysis to compare the explanatory power of ratings given by the platform and educational levels to determine whether platform ratings are more strongly associated with hourly earnings than formal education credentials for 146 freelancers on a prominent digital labor platform. Based on signaling theory\, we found that platform-assigned ratings that acts as signals predict hourly earnings better than formal education. The findings indicate that digital labor marketplaces value platform signals like innovative reputation systems. The results show the association between traditional educational credentials that serve as labor market indicators and platform-specific signals in evaluating value in digital marketplaces. The study demonstrate labor signaling is changing in the era of digital work with implications for freelancers\, platform developers and human resource management practices. It further challenges the traditional human capital development and raises questions about the role of traditional educational credentials in the future of digitally mediated work. CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:34c341f8002c3157e37d82b787e71e61 URL:http://5thworldconferenceoninformations.sched.com/event/34c341f8002c3157e37d82b787e71e61 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Automatic Speech Recognition for Gujarati Language: A Review and Scope of Orthographic correction DESCRIPTION:Authors - Twinkle K. Patel\, Ankit Bhavsar\, Arpit Jain Abstract - Automatic Speech Recognition (ASR) systems have become essential tools for the communication in natural human-computer communication across various languages. The growing need for effective communication in public and private sector has increased the need of Natural Language Processing. Gujarat is one of the prominent state in India where most of the official communication takes place in Gujarati language. ASR for Gujarati language has its own importance due to the high usage of Gujarati language. This paper\, highlights the emergence of ASR for Gujarati language from the early days of creating ASR commercially to more modern advancement approaches such as deep learning\, end-to-end (E2E)\, and various other methods. Traditional ASR systems utilized statistical methods\, most commonly Hidden Markov Models (HMM) and Gaussian Mixture Model (GMM) which often reported low accuracy. With the emergence of deep learning models\, including CNN\, BiLSTM\, and transformer-based models such as Wav2Vec 2.0 and XLSR-53\, the recognition accuracy has significantly increased\, especially in noisy and spontaneous speech contexts. The paper also provide the comparative study of the work done by various researchers in the field of Gujarati ASR\, highlighting that the use of spell correctors as well as hybrid feature extraction methods have reduced phonetic ambiguities and diacritic errors in Gujarati language. The study strongly emphasizes the need for morphological analysis and contextual modeling to adequately address the complexity in the homophones and diacritics of Gujarati language. The paper also reviews the various methods applied to Gujarati ASR and their reported Word Error Rates. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:6126ce3f9c6cdf7567479d9dfee71c8c URL:http://5thworldconferenceoninformations.sched.com/event/6126ce3f9c6cdf7567479d9dfee71c8c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Code reviews using traditional methods vs Hybrid models DESCRIPTION:Authors - Prathilothamai M\, Nitin Ravi\, Rishi Pradeepkumar\, Sajith Rajan P\, Anurag Nagilla Abstract - Code analysis ensures software quality\, readability\, and maintenance. Traditional methods such as Static Analysis Tools (SAT) and SZZ algorithms recognize errors and analyze contributions based on predefined rules and historical trends. However\, complex code semantics are difficult to understand and often lead to overlooked issues and limited feedback. Despite its benefits\, LLM is not practical in some business environments\, facing challenges such as high computing costs\, slower processing\, and data protection concerns. Hybrid models may provide scalable and inexpensive solutions for large enterprise projects. This study contrasts SATs and LLMs\, focusing on capabilities to detect bugs and maintain code quality\, by investigating hybrid models that fuse the contextual strength of LLMs with the efficiency of SATs. In evaluations with 30 participants\, the hybrid model consistently received the highest scores across accuracy\, clarity\, relevance\, and usability (average ratings >8.5/10)\, outperforming both SATs and AI-alone approaches. Hybrid models may thus provide a scalable and cost-effective solution for problems arising in large-scale corporate enterprise projects. This study supports the use of case studies and benchmarks to assess the effectiveness\, cost\, and scalability of these various approaches. The findings aim to give practical suggestions for improving traditional code review processes\, helping balance rule-based tools with AI-powered insights to enhance software development workflows. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:4b7ddbabc23d2594a4798bd0d24ef567 URL:http://5thworldconferenceoninformations.sched.com/event/4b7ddbabc23d2594a4798bd0d24ef567 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Driving Change for People and Planet: A Systematic Literature Review on the Interplay Between Social Innovation and Sustainable Entrepreneurship DESCRIPTION:Authors - T. A. Alka\, M. Suresh Abstract - The study aims to examine the link between social innovation (SI) and sustainable entrepreneurship (SE). The major focus is to explore how SI is promoted by the SE and what the Sustainable Development Goals (SDGs) are covered by the sustainable entrepreneurship through promoting social innovation identified through a research gap by adopting the TCCM framework. The study is a systematic literature review on the publications in the Scopus database identified through keywords relevant to the theme by adopting the SPAR-4-SLR protocol. The result indicates that the sustainable entrepreneurs promoting SI innovation through innovative business models ensure social well-being. The SI is not only the technological but also non-technological aspects\, which are responsible and impactful\, having innovative approaches\, social practices\, and processes. The SEs are developing business models that are socially and sustainability purpose-driven\, offering financial advantage and ensuring the social cohesion and the empowerment of the community through their participatory approaches and ensuring the local level stakeholders’ engagement. SE develops partnerships and collaboration among the different actors\, which will create knowledge sharing and collaborative innovation. While mapping of SDGs to SI by SEs\, the study identifies that the major SDGs covered are: SDG 1\, SDG 4\, SDG 5\, SDG 8\, SDG 9\, SDG 10\, etc. The study offers implications to practitioners\, policymakers for actionable strategies to enhance the SI-driven SE ecosystem. This systematic review lacks empirical findings and relies purely on the published works. The limitations will open future research scope avenues by covering more databases\, keywords\, etc. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:c7403a885893a81543d740931c7f485c URL:http://5thworldconferenceoninformations.sched.com/event/c7403a885893a81543d740931c7f485c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Integrated Lift-Toilet System for Enhanced Accessibility in High-Density Urban Housing DESCRIPTION:Authors - Shaveta Thakral\, JyotiVerma\, Pratima Manhas\, Shankar Amalraj\, Neha Shahare\, Monali Tingane\, Aparna Mahesh Torade Abstract - Urbanization and increasing housing density have necessitated innovative solutions to address both space constraints and accessibility for individuals with limited mobility. This paper presents a novel concept of an integrated lift-toilet system\, designed specifically for elderly and disabled individuals living in multi-story buildings. By merging the functionalities of vertical transportation and sanitary facilities\, the proposed system aims to provide dignity\, convenience\, and emergency usability\, particularly in high-rise residences and healthcare environments. The research encompasses a multidisciplinary approach\, including mechanical design\, sanitary engineering\, user-centric ergo-nomics\, and real-world application assessments. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:06908552377d2c0ef89e7cd2ff2f2d1c URL:http://5thworldconferenceoninformations.sched.com/event/06908552377d2c0ef89e7cd2ff2f2d1c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Machine Learning in Intelligent Transportation Systems: A study based on emerging trends DESCRIPTION:Authors - Jyotika R. Yadav\, Arpit A. Jain\, Ankit Bhavsar Abstract - Efficient traffic management is a major focus in smart city projects. Intelligent Transportation Systems (ITS) are revolutionize the way transportation networks are managed\, to improve safety\, efficiency\, and sustainability. Machine learning (ML) has been developed as a powerful means for advancing ITS by enabling data-driven decision-making\, real-time traffic management\, predictive analytics\, and automation. This paper offers a thorough summary of the current trends and advancements in the utilization of ML techniques in ITS. It explores key areas such as traffic flow prediction\, autonomous vehicles\, congestion management\, smart mobility solutions\, and road anomaly detection. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:7ca38527d7e2e6f26d466a3fed0bee93 URL:http://5thworldconferenceoninformations.sched.com/event/7ca38527d7e2e6f26d466a3fed0bee93 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Smart Food Labels: A Systematic Literature Review DESCRIPTION:Authors - Saranya P.\, Rejikumar G. Abstract - This study employs a systematic literature review (SLR) to investigate the changing landscape of smart labelling in the food industry. As Customer demand for transparency\, traceability\, and ethical consumption increases\, conventional food labels are evolving into interactive communication instruments. Smart labels facilitated by technologies such as QR codes\, RFID\, and intelligent packaging are now integral to real time customer interaction and business decision making. Despite increasing scholarly interest\, a thorough delineation of research trends\, deficiencies\, and prospective directions has been absent. To tackle this\, adoption of SPAR-4-SLR protocol was done to examine 43 peer reviewed papers (2015-2025) from Scopus utilizing Biblioshiny and Vosviewer. The investigation identified few predominant topics like food safety\, customer behaviors\, and technological integration while also highlighting under discovered topics like RFID and packaging designs. Result indicated a shift from a compliance orientated labeling to an interactive digital approach that foster consumer trust. This review provides essential in-sights for scholars\, legislators\, and industry executives seeking to create data-driven\, customer-focused labelling systems in the digital era. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:eb5956a47244b3bb031d46e605616de7 URL:http://5thworldconferenceoninformations.sched.com/event/eb5956a47244b3bb031d46e605616de7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Stock Price Forecasting Using Machine Learning Models: A Comprehensive Analysis DESCRIPTION:Authors - Abhishek Passwan\, Srushti Karki\, B M Bandgar Abstract - Accurately predicting stock prices remains a challenging task\, primarily due to the volatile\, dynamic\, and non-linear nature of financial markets. This study introduces a robust deep learning-based framework designed to forecast the closing prices of companies listed on the Nifty 50 index. We explore and compare the predictive performance of several state-of-the-art neural network architectures\, including Long Short-Term Memory (LSTM)\, Gated Recurrent Unit (GRU)\, Recurrent Neural Networks (RNN)\, and Convolutional Neural Networks (CNN)\, alongside two novel hybrid models: StockAugNet-f and StockAugNet-c. Historical stock data were retrieved from Yahoo Finance and pre-processed using Min-Max normalization. To effectively model temporal dependencies\, we applied a sliding window technique for sequence construction during training. Model performance was assessed using key evaluation metrics: Root Mean Square Error (RMSE)\, Mean Absolute Error (MAE)\, and Mean Absolute Percentage Error (MAPE). To enhance usability and support real-time forecasting\, we developed an interactive Streamlit-based application\, allowing users to dynamically visualize model outputs. Experimental findings indicate that the GRU and RNN model give better accuracy over the hybrid models accuracy and resilience for the NIFTY 50 index stocks. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:d5a39ee361b98ca6cd52b5f94646344d URL:http://5thworldconferenceoninformations.sched.com/event/d5a39ee361b98ca6cd52b5f94646344d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:The Evolution of Network Architecture: From Traditional Models to 5G\, IoT\, and Quantum Networking DESCRIPTION:Authors - Kumar Gaurav\, Sudhir Agarmore\, Akshay Kumar\, Akshat Jha\, Edidiong Akpabio\, Chandan Kumar Abstract - Network architecture is examined in-depth in terms of the structural design or the underlying protocols that help in the facilitation of data transmission between networks. The paper discusses the classic models of network architecture\, which include P2P\, client-server\, and hybrid models\, and outlines the latest advancements in cloud computing\, edge computing\, and IoT. The paper further discusses the different types of network topologies and other devices\, such as the OSI and TCP/IP models\, in the shaping of data communication. This also encompasses new emerging trends\, such as 5G\, IoT\, quantum networking\, and zero-trust security\, among many others. These will detail discussions of the concepts involved as well as their impacts on network protocols and architecture. As demand for faster\, more secure\, and scalable networks grows\, the integration of these modern technologies opens the way to new opportunities and challenges of future network infrastructure. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:8c45d59f942272728105fd9089fed0bd URL:http://5thworldconferenceoninformations.sched.com/event/8c45d59f942272728105fd9089fed0bd END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:The Gratitude Gap in Leadership: What We Know and What We’ve Missed DESCRIPTION:Authors - Janani Vijayan\, Bala Subramanian R Abstract - This study explores the growing body of research on leader’s gratitude\, emphasizing its significance in organizational settings. Gratitude\, a complex and multifaceted positive emotion\, plays a crucial role in enhancing interpersonal relationships\, promoting well-being\, and fostering prosocial behavior. The review categorizes gratitude into trait\, state\, and collective forms\, examining their unique characteristics and implications. It highlights key theoretical frameworks such as the Find-Remind-and-Bind Theory\, Broaden-and-Build Theory\, and Cognitive Emotion Theory to explain how gratitude functions within leadership dynamics. The review further delves into the antecedents of leader’s gratitude\, including team error management\, feedback\, and appreciation programs and its consequences\, such as enhanced social intelligence\, team innovation\, improved leader-member relationships\, and increased organizational commitment. Moreover\, the paper discusses the broader social impacts of leader gratitude\, showing how it fosters a positive work culture. Identified limitations include the scarcity of causal studies and underrepresentation of cultural factors. Future research directions are proposed\, such as exploring gender differences in gratitude expression\, cultural variations\, and the effectiveness of different gratitude expressions. Overall\, the review underscores that leader’s gratitude is a powerful yet underutilized tool in cultivating effective leadership and healthy organizational environments. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:ec959d3e3ae49e240f9b192c7e8c5bbb URL:http://5thworldconferenceoninformations.sched.com/event/ec959d3e3ae49e240f9b192c7e8c5bbb END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:VOICE: A Smart Grievance Handling System for Issue Classification and Resolution DESCRIPTION:Authors - \;S. Kirthica\, K. Subha\, S. Arul Murugan\, V. Deepak Kumar\, M. Dhivagar\, S. Kanishka \nAbstract - \;In contemporary society\, effective grievance redressal is vital for transparency\, accountability\, and public trust. Traditional systems often face issues like manual processing\, delays\, and poor user engagement. To overcome these challenges\, we propose VOICE\, an AI-driven grievance management platform that automates the complaint lifecycle—from classification and similarity detection to assignment and tracking. Leveraging natural language processing (NLP)\, speech-to-text\, and automated prioritization\, VOICE reduces human intervention and improves response times. It also incorporates community-driven upvoting\, real-time notifications\, and performance monitoring to enhance user engagement and system transparency. Designed for scalability and ease of use\, VOICE can be deployed across institutions\, communities\, and national systems. By combining automation\, intelligence\, and user-centric features\, VOICE represents a significant advancement in modern grievance redressal. CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:b7536293cc904912a3cec519aabb760b URL:http://5thworldconferenceoninformations.sched.com/event/b7536293cc904912a3cec519aabb760b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:A Hybrid Deep Learning Framework for Test Case Prioritisation using Semantic and Structured Features DESCRIPTION:Authors - Siqabukile Ndlovu\, Ernest Mkandla Abstract - This paper presents a novel approach to improve test case prioritisation in continuous integration environments by integrating semantic features derived from test case descriptions. The approach uses a Convolutional Neural Network (CNN) model that considers both structured and semantic features. The target variable for prioritisation is defined using a threshold on calculated priority values\, helping to identify the most critical test cases. We further engineer interaction and polynomial terms with the semantic feature to capture complex relationships. These polynomial terms allows the model to capture non-linear relationships. For example\, a small change in the semantic feature might not matter much in the middle range\, but a large implicit_prob (e.g.\, above 0.9) might have a disproportionately strong effect on the priority. Through a 5-fold crossvalidation\, our results demonstrate that while the semantic features do not statistically significantly improve overall F1-score\, they yield a statistically significant enhancement in Average Percentage of Fault Detection (APFD) (pvalue = 0.0055). This indicates that incorporating semantic understanding enables the model to effectively reorder test cases\, leading to earlier detection of critical faults and increased efficiency in testing efforts within live CI/CD environments. CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:83d3d3f2aa4525d9cc5ef4465cd8f57b URL:http://5thworldconferenceoninformations.sched.com/event/83d3d3f2aa4525d9cc5ef4465cd8f57b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:AI-Driven Precision Farming: Leveraging Environmental and Soil Parameters for Accurate Crop Yield Prediction DESCRIPTION:Authors - Juhi Patel\, Tejaskumar Bhatt Abstract - Growing realization of the need for sustainable agriculture has seen Artificial Intelligence (AI) applications implemented in precision agriculture\, advocating for sustainable use of resources and enhanced yields in crops. The authors present an AI-driven model that employs multi-modal data of soil attributes\, weather\, and vegetation indices to predict crop yield. It develops a model with satisfactory test prediction accuracy based on starting from a Linear Regression model (MSE of 0.0835 and R² score of 0.9714). This shows that the model can potentially capture linear trends for big meteorological change influence on crop yields. Feature correlation analysis determines NDVI and soil moisture as the most significant predictors\, with the important roles of monitoring vegetation health and effective water management yielding better agricultural results. Although Linear Regression is a robust starting point\, this research also paves the way for integrating sophisticated AI techniques like Neural Networks and Ensemble Learning models to tackle non-linear relationships and interactions. In comparative analysis\, we have confirmed the utility of interpretable models for scalability\, reliability and applicability in smallholder farming. Implications: The result fills the void between the abstract AI structures and the usable application\, providing a widely replicable artifact to improve decision-making in precision agriculture. In addition to prediction accuracy\, the study also emphasizes on scalability and ethical consideration\, the latter coupled with the area of application of IOT based AI empowered systems and data privacy. Further studies will seek to evaluate the model in different agricultural regions\, explore new machine learning methods\, and implement real time decision support systems. This study contributes to global efforts towards achieving sustainable agriculture\, ensuring food security\, and limiting the environmental impact of agriculture by providing knowledge that can be used directly. CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:bc4f66fc0b441fa21cbb0a20c9f7819b URL:http://5thworldconferenceoninformations.sched.com/event/bc4f66fc0b441fa21cbb0a20c9f7819b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:DeepFakeGuard: Detection of Face-Swap Based Deepfake Images and Videos DESCRIPTION:Authors - Bhumi Patel\, Mann Patel\, Aum Mehta\, Nishat Shaikh\, Priteshkumar Prajapati Abstract - Deepfake generation techniques have advanced rapidly in recent years\, posing significant risks for misinformation and privacy. In this paper\, we propose an ensemble-based deepfake detection framework that leverages EfficientNet-B4 as the backbone architecture for both image and video analysis. By incorporating attention mechanisms and siamese training strategies\, our system enhances feature discrimination and improves robustness against subtle manipulation artifacts. The framework is trained and evaluated on two widely adopted benchmarks—the Deep- Fake Detection Challenge (DFDC) and FaceForensics++ datasets. Experimental results demonstrate that the ensemble approach outperforms individual models\, achieving higher accuracy and improved log-loss metrics\, while also providing interpretability via attention maps. We further discuss the integration of temporal consistency analysis to better handle video data\, and outline future directions for real-time deepfake forensic systems. CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:e3085aeac86bc68d087c18417ebe486a URL:http://5thworldconferenceoninformations.sched.com/event/e3085aeac86bc68d087c18417ebe486a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Examine The Role of SAKTI and MONSAKTI in Public Sector Accounting: A Case Study of BRIN (National Research and Innovation Agency of Indonesia) DESCRIPTION:Authors - Putri Haryani\, Sinatria Arka Daniswara\, Randany Zevanya Sihombing\, Gavikal Hanif Pasopati\, Ridho Rambu Bassae\, Andhika Hendra Adi Wibisono Abstract - This study investigates the implementation of the Institutional Financial Application System (SAKTI) in digitalizing public sector accounting within Indonesia’s National Research and Innovation Agency (BRIN). Recently\, BRIN is a newly formed government institution resulting from the merger of several institutions. It manages budgets from various sources and operates within a complex organizational structure. BRIN faces significant challenges in achieving accurate and timely financial reporting. Using a qualitative case study method\, data were collected through semi-structured interviews and observations at BRIN’s Bureau of Planning and Finance. The findings reveal that SAKTI\, alongside the MONSAKTI monitoring system\, plays a pivotal role in supporting accrual-based financial reporting in compliance with Government Regulation No. 71/2010. Despite progress in automation and integration\, several challenges persist\, including limited system performance\, partial manual processing\, and constrained operational budgets. The study highlights the strategic importance of aligning digital infrastructure\, internal controls\, and human resource capacity to sustain accountability and reporting quality. These insights are expected to inform similar public institutions undergoing digital financial transformation amid structural complexity. CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:80f55b7641b9706504f69d495cb28b73 URL:http://5thworldconferenceoninformations.sched.com/event/80f55b7641b9706504f69d495cb28b73 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Human-Computer Interaction to Global Patients Trust: an HCI and URT approach in Medical Tourism DESCRIPTION:Authors - Dina Sekar Vusparatih\, Handy Martinus\, Eshaby Mustafa\, Ahmad Hidayat Ahmad Ridzuan Abstract - Malaysia has become the primary destination for Indonesian patients over the past two decades. However\, international medical tourism carries significant risks due to limited information\, restricted communication access caused by distance and language barriers\, while the industry heavily relies on trust for critical health-related decision-making. This study focuses on how Island Hospital implements technology strategies to reduce uncertainty in making informed decisions. A qualitative approach using a case study method was employed to gather the necessary data. Interviews were conducted with Indonesian patients and their family members at the hospital\, as well as with Indonesian government representatives in Penang\, Malaysia. To enrich the findings\, participant and documentation observations were also applied. The results indicate that the hospital integrates Human-Computer Interaction (HCI) using four approaches in designing its web-site/portal and mobile application. This enables patients to communicate with healthcare providers despite existing barriers\, and supports them in planning both pre- and post-treatment procedures. CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:1f2e10fa23b3e4868a62b2494c29a990 URL:http://5thworldconferenceoninformations.sched.com/event/1f2e10fa23b3e4868a62b2494c29a990 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Influence of Store Attributes on Purchase Intention and Customer Satisfaction in Philippine Supermarkets DESCRIPTION:Authors - Gweneaella Lyrika R. Aguinaldo\, Nellisa F. Cortez\, Jocelle Marie S. Dador\, Kathleen Kaye L. Getonzo\, Loran Ann G. Gonzaga\, Angela B. Navarro\, Remelyn J. Vicente\, Manuel J. Logatoc\, John Kenneth M. Arcayos Abstract - This study examines how key store attributes influence shoppers’ purchase intentions and\, ultimately\, customer satisfaction in five selected supermarkets in Cavite\, Philippines. Store attributes—defined as accessibility and cleanliness\, product assortment\, promotion\, price\, and customer relations—are hypothesized to drive the likelihood that a customer will buy (purchase intention) and feel satisfied. Employing a quantitative correlational design\, the researchers ad-ministered an adaptive\, 45-item Likert-scale questionnaire (4-point) both face-to-face and online to 380 supermarket patrons. Instrument reliability was con-firmed via Cronbach’s alpha coefficients between 0.8740 and 0.9379 (good–excellent). Respondent demographics indicated a predominantly young (18–28 years\, 75.5 %) and female (62.4 %) sample\, with over half (51.6 %) reporting a monthly income below ₱10\,000. Descriptive analysis (frequency\, percentage\, weighted mean\, and standard deviation) revealed that accessibility and cleanliness received the highest effectiveness rating (mean = 3.44\, SD = 0.43)\, while customer relations scored lowest. Inferential analysis using Spearman’s rank-order correlation showed a moderate positive relationship between purchase intention and customer satisfaction (ρ = 0.549\, p < 0.001). Among individual attributes\, promotion correlated most strongly with purchase intention (ρ = 0.507)\, and price exhibited the highest link to customer satisfaction (ρ = 0.567). These findings suggest that supermarkets seeking to boost sales\, and loyalty should prioritize promotional strategies to drive purchase intent and calibrate pricing structures to enhance satisfaction. Optimizing accessibility\, cleanliness\, and other in-store factors can further improve customer experience\, yielding competitive advantage in the retail sector. CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:756052ed5f2a31b010d53fb587fe262b URL:http://5thworldconferenceoninformations.sched.com/event/756052ed5f2a31b010d53fb587fe262b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Intelligent Access Control Schemes for the Internet of Everything: A Survey of Techniques\, Challenges\, and Future Directions DESCRIPTION:Authors - Pradnya H Desai\, Parikshit Mahalle\, Pankaj Chandre Abstract - The exponential growth of the Internet of Everything (IoE) demands secure\, intelligent access control mechanisms to manage data flow and device interaction efficiently. This paper proposes a novel architecture that integrates post-quantum cryptography\, federated learning\, and explainable AI to ensure privacy- preserving\, real-time decision-making for resource-constrained IoE environments. The edge nodes\, equipped with lightweight cryptographic engines and context-aware training modules\, perform preliminary data processing and secure communication via GG-ULL and PQCrypto protocols. The cloud leverages federated learning to train distributed models and uses a multi-agent policy engine for dynamic access decisions. Blockchain-backed audit trails ensure accountability\, while the explainable AI module enhances transparency in access control. The system supports mission-critical services like SCADA and health data lakes\, guaranteeing secure and interpretable decision flows. This architecture paves the way for resilient\, scalable\, and intelligent access control frameworks suitable for next-generation IoE ecosystems. CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:bbd076bb53826d2c937aaa93c025dafc URL:http://5thworldconferenceoninformations.sched.com/event/bbd076bb53826d2c937aaa93c025dafc END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Real-time Objection Detection Using YOLOv5 DESCRIPTION:Authors - Deepika K M\, Rohith H P\, Srinivas D B\, Lakshmi H Abstract - The need for real-time object recognition is growing in a few applications\, including robotics\, surveillance\, and autonomous vehicles. Modern object recognition technique YOLOv5 achieves high accuracy while maintaining real-time performance. This paper proposes a real-time\, highly accurate object recognition method using YOLOv5. The system\, which was created using PyTorch and Python\, is trained and evaluated using the COCO dataset. The proposed system enables fast object detection and achieves outstanding precision and recall rates using single-shot detector architecture. Additionally\, the detection accuracy is greatly improving with the introduction of YOLO and its architectural descendants. YOLOs are frequently employed in a variety of contexts\, mostly because of their speedy conclusion rather than due to the accuracy of their detection. The YOLO detection accuracy\, for instance\, ranges between 63.4 and 70. The suggested system is ideal for real-time object detection applications since experimental findings demonstrate that it performs better than current object detection systems in terms of accuracy and speed. CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:18c77b26778ce3d0f1f038420a6857fd URL:http://5thworldconferenceoninformations.sched.com/event/18c77b26778ce3d0f1f038420a6857fd END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:The Impact of Hospital Leadership Styles on Staff Performance and Patient Satisfaction DESCRIPTION:Authors - Asra Fatema Zakir Baig\, Amol Mashankar Abstract - Hospital leadership styles are crucial determinants of employee performance and patient satisfaction. In this research\, secondary research findings are integrated to explore the influence of transformational\, transactional\, and laissez-faire leadership styles on healthcare delivery. Transformational leadership is always linked with greater staff engagement\, job satisfaction\, and better patient care outcomes. Transactional leadership is less consistent in its findings\, typically enhancing short-term efficiency but with little developmental impact over the long term. Laissez-faire leadership has typically been associated with negative organizational performance because of the lack of direction and responsibility. The literature highlights the requirement for healthcare managers to embrace transformational styles as a means to create a safe work environment as well as an improved patient experience. Emotional intelligence\, communication skills\, and encouraging teamwork should feature prominently in any future leadership programs aimed at enabling sustainable healthcare greatness. (Alilyyani\, B.\, Wong\, C. A.\, & Cummings\, G. G.\, 2018)\, Effective hospital leadership has a profound impact on the performance of staff as well as patient satisfaction. The current paper integrates evidence from research studies to explore how the transformational\, transactional\, and laissez-faire styles of leadership influence healthcare. The review emphasizes the significance of leadership in creating an optimistic workplace culture\, improving staff participation\, and finally enhancing patient care.(Wong\, C. A.\, & Cummings\, G. G. (2013)) CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:4e1de4f4cc49e12023c683e795cb4218 URL:http://5thworldconferenceoninformations.sched.com/event/4e1de4f4cc49e12023c683e795cb4218 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:What Are the Real Challenges of Being a Freelancer? DESCRIPTION:Authors - Najah Najmia Halim\, Okta Bayu Prihatma Putra Abstract - This paper uncovers the system-level challenges confronting freelancers in emerging markets\, framing freelancing as a form of digital entrepreneurship with significant social implications. Through a systematic literature review of 23 peer‑reviewed studies (2020–2024) using the PRISMA protocol\, we identified five critical challenge domains: opaque algorithmic management that limits freelancer autonomy\, financial instability due to irregular income and weak social protection\; regulatory ambiguity that erodes trust in digital platforms\, technical barriers including limited infrastructure and digital literacy\, and career development gaps marked by burnout and isolation. These challenges disproportionately affect freelancers in developing regions\, highlighting structural inequalities within the global digital labor market. By synthesizing literature across geography and sector\, this study positions freelancing not just as a labor trend\, but as a pressing issue of digital inclusion and social sustainability. The findings inform policymakers\, platform designers\, and support institutions about intervention points to foster equitable\, resilient freelance ecosystems. Future research must explore how technology\, policy\, and cross-sector partnerships can create inclusive innovation frameworks that sustain independent digital work. CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:8ea575ed1ef202ac4a1a9e935cef7e6e URL:http://5thworldconferenceoninformations.sched.com/event/8ea575ed1ef202ac4a1a9e935cef7e6e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:A Secure and Efficient Implementation of TLS and QUIC for Secure Satellite Based Communication in UAVs DESCRIPTION:Authors - Ankush Soni\, Sanjay K. Sahay Abstract - The integration of unmanned aerial vehicles (UAVs) into remote and beyond-visual-line-of-sight missions has increased the demand for secure\, efficient\, and low-latency communication systems\, particularly in scenarios where satellite connectivity is the only viable option. However\, high-latency satellite links and constrained onboard resources pose significant challenges to traditional cryptographic protocols. In this paper\, we present a lightweight\, symmetric key-based authentication and secure communication protocol designed specifically for satellite-driven UAV applications. Our protocol replaces resource-intensive public key operations with a pre-shared key approach and incorporates AESHA3\, a variant of AES that leverages SHA-3 for key scheduling\, along with SHA2-512 for hashing. We implement this design within the TLS and QUIC frameworks\, adapting their internal packet structures to accommodate constrained environments. Experimental evaluations on Raspberry Pi testbeds reveal that our proposed QUIC implementation significantly outperforms TLS in encryption speed\, handshake latency\, and overall protocol execution time. The results demonstrate the suitability of the proposed system for real-time mission-critical UAV operations over satellite links\, highlighting the benefits of integrating optimized symmetric cryptography into modern transport protocols. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:27782a3efdfc2c49d61790524c672c85 URL:http://5thworldconferenceoninformations.sched.com/event/27782a3efdfc2c49d61790524c672c85 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:A System for Advanced Customer Predictive Analytics for Marketing Automation and Market Accountability DESCRIPTION:Authors - Reena (Mahapatra) Lenka\, Jaya Chitranshi\, Vanishree Pabalkar Abstract - Marketing automation with the use of data-driven insights will help in anticipating customer-behavior. It will enable personalized campaigns\, improve the process of decision-making\, and ensure market-accountability by measuring effectiveness of the system and help in optimizing strategies This will ultimately drive customer engagement\, loyalty\, and higher-returns on investment in the competitive business environments. The present invention relates to a method and a system for customer predictive analysis for marketing automation and market accountability. The present invention attempts to develop a layout for the job of marketing-computerization (MA) in estimating the return on displaying exercises and the difficulties related with arriving at responsibility in marketing. To explore the goal of the assessment\, the creators took on a subjective methodology\, leading an exploratory review among ten key witnesses. Based on the aftereffects of the subjective investigation\, an applied system was proposed\, which incorporates both key and functional level elements fully intent on making a worth based plan. In this plan\, leaders\, for example the Chief Marketing Officer. arise as worth makers\, encouraging business versatility\, what further contentions can be given to legitimize spending plan portion to MA exercises. Through cautious examination of the components that describe the peculiarity under study\, the present invention eventually adds to a superior comprehension of MA and responsibility inside the current business worldview. Focusing on the marketing setting\, an organized conversation of how AI can recognize the objective clients exactly in spite of their various practices was introduced in this contemporary invention. The uses of AI in client focusing and the extended viability all through the unique periods of client lifecycle were similarly inspected. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:80a0426e936c9002229499126195c4c9 URL:http://5thworldconferenceoninformations.sched.com/event/80a0426e936c9002229499126195c4c9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:An HRM Decision-making Model in an MNC using Predictive Analytics DESCRIPTION:Authors - Reena (Mahapatra) Lenka\, Jaya Chitranshi\, Vanishree Pabalkar Abstract - The systems and regulations that control human behaviour are the main emphasis of HRM. Finding the greatest talent from around the world\, training them\, evaluating their performance\, rewarding them\, and creating a positive work atmosphere are all part of the HRM field's magnificent duty. Developing a framework that accurately forecasts the need for talent and workforce skills becomes crucial because every organization's strategy depends\, in part or in full\, on its skill sets. When the human resource data is accessed for study of the higher cognitive processes involved\, a variety of techniques may be used to extract the most useful information from the dataset. A common strategy for using data to inform decisions is data processing. On the other side\, "state-of-the-art accuracy" in decisions is what predictive analytics is known for. The goal of this study is to provide a strategic decision-making model for "human resource management (HRM)." The study develops a decision-making framework based on data processing and predictive analytics for decisions pertaining to human resources. Given that HRM has a significant impact on an organization's longevity and efficacy\, the model was created for global corporations. The suggested approach will be useful in enhancing HR systems' effectiveness\, which could have a favourable impact on business results. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:165fe4844f236e6c85d16045e2a3d798 URL:http://5thworldconferenceoninformations.sched.com/event/165fe4844f236e6c85d16045e2a3d798 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Brand Vulnerability in Digital Age: Effects of Negative Publicity on Purchase Intention DESCRIPTION:Authors - Bryna Meivitawanli\, Liu Fen Phaw\, Daniella Maria Natalia Abstract - The increasing influence of social media and user generated con-tent has significantly transformed consumer behavior\, with negative publicity emerging as a critical factor affecting brand perception and purchase intention. This study aims to investigate the impact of negative publicity on the purchase intentions of Generation Z consumers in Indonesia\, focusing on the mediating roles of brand advocacy and brand betrayal. A quantitative research approach was employed\, utilizing a structured questionnaire distributed to 158 respond-ents. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test four hypotheses regarding the relationships be-tween negative publicity\, brand advocacy\, brand betrayal\, and purchase intention. The findings indicate that negative publicity significantly reduces purchase intention\, with brand advocacy mitigating its adverse effects\, while brand betrayal amplifies the negative impact. These results underscore the importance of managing brand reputation in the digital age\, highlighting the need for brands to adopt ethical marketing strategies and proactive reputation management to counter the detrimental effects of negative publicity. This research contributes to the understanding of how digital media influences consumer behavior\, offering valuable insights for marketers seeking to enhance brand loyalty and mitigate the risks associated with negative publicity. The findings are particularly relevant for businesses targeting Generation Z in emerging markets like Indonesia\, where social media plays a pivotal role in shaping consumer decisions. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:8d5b0e0c3019008dfac716b64e54648c URL:http://5thworldconferenceoninformations.sched.com/event/8d5b0e0c3019008dfac716b64e54648c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Emotion Classification in News Headlines of Operation Sindoor Using Machine Learning: A Comparative Study of Logistic Regression and SVM DESCRIPTION:Authors - Sateesh Kumar TK\, Vishnu Achutha Menon\, Juby Thomas\, Lijo P Thomas Abstract - This study examines emotion classification in news headlines related to Operation Sindoor\, a precision military response initiated by India in May 2025 following the Pahalgam terrorist attack. The operation’s symbolic naming\, reflecting cultural mourning and national resolve\, resulted in emotionally charged media coverage. To analyze the emotional framing within these head-lines\, a dataset from multiple news outlets was compiled and annotated with six emotion categories: anger\, fear\, joy\, sadness\, surprise\, and neutral. Preprocessing involved TF‑IDF vectorization with unigram and bigram features\, followed by classification using Logistic Regression and Support Vector Machines (SVM). Model performance was evaluated using accuracy\, precision\, recall\, and F1-score\, with macro-averaging to address class imbalance. Both models achieved an overall accuracy of 54%\, with SVM yielding a higher macro‑F1 score (0.40) compared to Logistic Regression (0.22). The results indicate that SVM performed better in identifying dominant emotions such as fear and sur-prise\, while both models struggled with underrepresented categories like joy and disgust. The findings suggest the need for advanced approaches such as deep learning architectures or data augmentation methods to improve classification of minority emotions in crisis reporting contexts. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:114224e0ff50d3174be55cc99ddb76b0 URL:http://5thworldconferenceoninformations.sched.com/event/114224e0ff50d3174be55cc99ddb76b0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Examining the mediating role of Self Efficacy and Student engagement between Student’s Digital Competence and their Academic Performance DESCRIPTION:Authors - \;Ananth Chiravuri\nAbstract - \;Prior studies have indicated a positive effect of a student’s digital competence on their academic performance in higher education institutes. However\, the relationship between variables such as digital competence and academic performance may not be direct. There are other variables such as student engagement and self-efficacy that could mediate the role between digital competence and academic performance\, warranting a further investigation Specifically\, this research investigates whether students' digital skills/literacy influence their academic success through the mediating factors of self-efficacy and engagement. Findings from the study aim to emphasize the importance of empowering students with digital literacy skills to enhance their learning experiences and achievements. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:9cefa0ef559e6d7e0c5c7d0da813999b URL:http://5thworldconferenceoninformations.sched.com/event/9cefa0ef559e6d7e0c5c7d0da813999b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Exploring YOLOv12 for Multi-Camera People Tracking with BoT-SORT\, ResNet50-IBN and Cluster Self-Refinement DESCRIPTION:Authors - Cu Quoc Le\, Huy Khanh Hua\, Nguyen Viet Ngo\, Tien Trung Bach\, Hoang Ngoc Tran Abstract - This paper presents an improved multi-camera people tracking pipeline with a focus on enhancing object detection to improve overall tracking performance. The system integrates object detection\, singlecamera tracking\, re-identification\, and multi-camera matching. We evaluate five versions of the YOLO model\, from YOLOv8 to YOLOv12 in the same tracking pipeline to ensure a fair comparison. Part of Track 1 data from AIC2024 dataset is used for both training and inference purposes. For each frame\, detected objects are tracked using a Kalman filter and matched via the Hungarian algorithm based on both spatial and appearance features. Inter-camera identity association is achieved through cluster-based matching\, followed by refinement steps to improve consistency. Tracking performance is assessed using the MOTA metric. Experimental results demonstrate that stronger detection models significantly improve tracking accuracy\, with YOLOv12 achieving the highest MOTA score. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:7b1b5527c514ac180568737da7cef68d URL:http://5thworldconferenceoninformations.sched.com/event/7b1b5527c514ac180568737da7cef68d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Metaverse Entrepreneurship: Pathways of opportunities\, challenges\, and directions for future research DESCRIPTION:Authors - T. A. Akshaya\, M. Suresh Abstract - This study is a journey to identify the opportunities\, challenges\, and future research scope in the metaverse entrepreneurship based on a systematic literature review. The Scopus database is employed for the selection of documents. For review\, 25 documents are selected through the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. The study identified the opportunities in metaverse entrepreneurship connected with the technological enablers of entrepreneurship\, innovative business and market opportunities\, transformation of education and entrepreneurial learning\, economic growth and social inclusion\, and further development in metaverse entrepreneurship. The major challenges of the metaverse in entrepreneurship encompass economic\, technological\, regulatory\, security\, and skill-based aspects. Metaverse entrepreneurship is a galaxy waiting to be explored. This study represents the first attempt to synthesize the existing research through a systematic literature review methodology. To policymakers\, this study guides to creation regulatory framework in social\, economic\, and legal dimensions. To entrepreneurs\, this study helps to identify opportunities in metaverse entrepreneurship not just as a marketplace but as an ocean for innovation and ideation. To educators\, this study is a light into the rethinking in redesigning of the curriculum and the pedagogical approach to integrating metaverse tools and entrepreneurship education to create a generation with immense knowledge in digital entrepreneurship. The limitation of this in-depth study is\, it only included the documents from the Scopus database till August 2025. The novelty of the study is to the theory by informing future research possibilities in this evolving domain by highlighting current research trends. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:3c23f79cccf3e6647a48dd07e260097d URL:http://5thworldconferenceoninformations.sched.com/event/3c23f79cccf3e6647a48dd07e260097d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Mining Strategic Business Insights from Online Reviews: A Case Study in the Southern Coast of Sri Lanka DESCRIPTION:Authors - Chirani Perera\, Uvini Ranaweera\, Indra Mahakalanda Abstract - This study investigates tourist perceptions of seven southern beaches in Sri Lanka using Google Reviews. With the increasing influence of online plat-forms in travel decision-making\, analyzing review content provides valuable in-sights into tourist experiences and preferences. The research employs trans-former-based models from Hugging Face for sentiment analysis and topic modeling\, offering a modern\, data-driven approach to textual review interpretation. Word clouds and bigram visualizations are used to highlight common positive and negative expressions associated with each beach. The findings reveal themes such as cleanliness\, natural beauty\, surfing opportunities\, crowd\, and local ser-vice quality as key themes associated with the southern coastline of Sri Lanka. Sentiment patterns vary across beaches\, with some consistently rated positively while others receive mixed feedback. This analysis offers practical insights for stakeholders in the field of tourism to improve destination management and marketing strategies. The study demonstrates the effectiveness of modern-day NLP techniques in understanding tourist experiences and provides a scalable frame-work for future such analysis that centres around the user responses. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:e5e10156fb6c809e219b3f0916f0c966 URL:http://5thworldconferenceoninformations.sched.com/event/e5e10156fb6c809e219b3f0916f0c966 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:XenSense-V.1: A Survey and Proposed Framework for Video Segmentation and Object Detection in Autonomous Vehicles DESCRIPTION:Authors - Mayanka Gupta\, Ayman Amjad\, Arjun Prabhakaran\, Bhanoday Kurma\, Bhanu Prakash M\, Kiran Agarwal Gupta\, Chaitra Ravi\, Sindhoor N Abstract - Despite significant progress in autonomous driving\, detecting and segmenting obstacles under poor conditions remains a major challenge. This paper reviews deep learning models that tackle real-world difficulties like occlusion\, fog\, motion blur\, and uneven road surfaces such as potholes and broken speed bumps—factors that heavily impact safety and detection accuracy. Over ten recent models are analyzed\, including prompt-based approaches like Semantic-SAM and EPCFormer\, memory-augmented ones like OOSIS and XMem\, and task-specific detectors such as DR-YOLO\, D-YOLO\, and motion-aware YOLO variants. Each model type comes with trade-offs: prompt-based systems are flexible but depend on large vision-language datasets\, while memory-based methods offer temporal consistency at the cost of increased computation. A key focus is on handling unstructured and uncertain road conditions\, especially common in countries like India\, where irregular infrastructure and unpredictable traffic are everyday challenges. Models trained solely on structured data often fail in these environments. To address this\, the survey includes detailed comparisons and benchmark tests under difficult traffic and weather conditions. These insights inform the design of XenSense-V.1\, a real-time deep learning framework using optical f low\, temporal reasoning\, and efficient segmentation to handle occlusion\, weather issues\, and complex road scenarios—particularly suited to Indian driving conditions. CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:eb44e36327d6ccd7ae05efd9b56e2812 URL:http://5thworldconferenceoninformations.sched.com/event/eb44e36327d6ccd7ae05efd9b56e2812 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Assessing Strategic Alignment for Green Finance Adoption in Manufacturing MSMEs for Green Growth DESCRIPTION:Authors - Sivakami B U\, M. Suresh Abstract - In a world racing toward net-zero emissions\, how can MSMEs strategically align their business operations to adopt green finance? Despite MSMEs’ growing recognition of sustainable development\, they continue to face persistent challenges in aligning their strategies with green finance adoption due to financial\, regulatory\, and knowledge-related barriers. The extant literature provides limited insights into the strategic alignment for adopting green finance. To ad-dress this gap\, the study develops a Fuzzy Logic-based assessment framework to evaluate alignment levels and identify weaker attributes. The framework specifies five criteria and nineteen attributes. Findings reveal a state of “moderately aligned” with four among nineteen attributes requiring immediate attention. The framework offers MSMEs a structured pathway to assess their alignment and strategically position themselves for green finance adoption and sustainable growth. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:8a9422861e417861d0d958e44302f28c URL:http://5thworldconferenceoninformations.sched.com/event/8a9422861e417861d0d958e44302f28c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:ECGGoDevice: A Low-Cost Multifunctional Wearable for Integrated Real-Time Cardiac and Mobility Monitoring DESCRIPTION:Authors - Premchand\, Jayant Kalra\, Ajoy Kumar\, Sahil Sankhyan\, Varun Dutt Abstract - Cardiovascular diseases (CVDs) continue to be the globe's leading cause of death\, and therefore\, there is a need for low-cost\, long-term cardiac monitoring technologies especially in low-resource environments. Current wearable ECG technologies are limited by cost\, proprietary design\, and single functionality. We introduce ECG Go Device\, a low-cost\, portable\, multifunctional\, wearable device with real-time ECG monitoring\, heart rate variability (HRV) analysis\, fall detection\, and step counting in one platform. The system utilizes a high-fidelity analog front-end and inertial sensing to provide mobility aware cardiac monitoring. A 44-subject validation trial compared ECG Go Device with a clinical-grade Shimmer3 ECG system and the Fitbit Sense 2 on 12 standard time-domain HRV measures and 10-day step count. The ECG Go Device demonstrated good agreement (all p > .05\; r > .93) with Shimmer3\, and high correlation in step count measure (r = .94). With clinically robust signal quality\, real-time wireless transmission\, and safety alert capability\, ECG Go Device provides a scalable solution for longitudinal cardiac and mobility monitoring especially for eldercare and underserved communities. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:fa9e4671e79ed4da315bdaef51700365 URL:http://5thworldconferenceoninformations.sched.com/event/fa9e4671e79ed4da315bdaef51700365 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:ERP–SCM Integration in the Digital Era: A Bibliometric–Systematic Review and Framework for Technical\, Organisational\, and Strategic Alignment DESCRIPTION:Authors - Sarath M\, M Suresh Abstract - Enterprise Resource Planning systems and Supply Chain Management systems shape how organizations plan\, coordinate\, and deliver goods and services. When they function together\, they improve efficiency\, visibility\, and decision making. Research on this integration\, however\, is scattered across industries and viewpoints\, making it hard to see the full picture. This study clarifies that picture through a Bibliometric Systematic Literature Review (B-SLR). A PRISMA-based review identified and screened relevant studies with clear criteria to ensure transparency. Ninety-nine publications from the Scopus database\, covering 2020 to 2025\, were retrieved. From these\, twenty studies were selected for qualitative synthesis\, while the full set underwent bibliometric analysis to map the field through performance metrics\, collaboration networks\, keyword co-occurrence\, and thematic clusters. The results show a rising focus on ERP and SCM integration\, driven by digital transformation and the demand for resilient supply chains. The analysis high-lights five recurring dimensions: scope\, enabling technologies\, outcomes\, success factors\, and barriers. These insights form a Five-Dimensional ERP and SCM Integration Framework that links theory with practice and provides a foundation for future research and implementation. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:061728f2b693c845e77a3e332abec6c5 URL:http://5thworldconferenceoninformations.sched.com/event/061728f2b693c845e77a3e332abec6c5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Extended Lifelong Sustainable Inquiry-based Community Learning (LSiCL) for Human-LLM Learning Based on Eduinformatics DESCRIPTION:Authors - Kunihiko Takamatsu\, Sayaka Matsumoto\, Katsuhiko Murakami\, Hidehiko Kamei\, Kazuya Tsuruta\, Naoya Honda\, Yumi Ishige\, Shimpei Matsumoto\, Hiroya Kawasaki\, Ikuhiro Noda\, Kenya Bannaka\, Tetsuhiro Gozu\, Tomoyuki Sakai\, Ryosuke Kozaki\, Aoi Kishida\, Hibiki Ito\, Koichi Akashi\, Sayaka Hama\, Gerald Prescott\, Masahiro Uchida\, Akira Nakamura\, Yasuhiro Kozaki\, Tamotsu Mori\, Shintaro Tajiri\, Naruhiko Shiratori\, Shotaro Imai\, Kenichiro Mitsunari\, Yasuo Nakata\, Sachio Hirokawa\,Masao Mori Abstract - This paper extends the Lifelong Sustainable Inquiry-based Community Learning (LSiCL) framework\, based on Edu in formatics\, to address challenges and opportunities presented by the rise of Large Language Models (LLMs) in education. LLMs like ChatGPT are fundamentally transforming education\, with human-LLM and inter-LLM learning relationships opening new frontiers. This research explores whether the traditional human-to-human LSiCL can be meaningfully extended to encompass human-LLM and LLM-LLM interactions while retaining its core principle of collaborative inquiry. Our analysis demonstrates that LSiCL principles are applicable across all these configurations\, paving the way for sustainable and scalable Human-LLM Learning ecosystems. This frame-work is crucial for improving resource efficiency\, promoting educational equity\, and enhancing global educational sustainability. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:6df98ab05c31e395686d707aa6326f29 URL:http://5thworldconferenceoninformations.sched.com/event/6df98ab05c31e395686d707aa6326f29 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Preparing and Making Digital Video Lectures for e-Learning – A Case Study DESCRIPTION:Authors - Nakhoon Baek Abstract - Since the computers are introduced\, there have been many meaningful attempts to use computers as education tools. Additionally\, the wide use of web servers on the internet makes video-on-demand services available especially in the entertainment area. They also developed digital video lectures\, which record video lectures as digital contents\, and provide them also as parts of video-on-demand services. During the COVID-19 pandemic in the year of 2020\, almost all schools around the world provided digital video lectures. Since the digital video lectures can provide high-quality lectures to lots of people at relatively-low costs\, it is now expected to be much actively used in near future. In this paper\, we will present more details of what preparations and choices are possible\, what to do\, and what to avoid\, in the process of providing digital video lectures\, especially in the field of computer science. At this time\, these kinds of literature surveys are seriously lacking\, and thus\, our case studies will be used to further improve the overall quality of digital video lectures and expand the e-learning markets. This paper will be a good starting point for providing check points and reference items to lecturers who prepare and provide digital video lectures. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:00482b3d101c408da70e2cd562652c03 URL:http://5thworldconferenceoninformations.sched.com/event/00482b3d101c408da70e2cd562652c03 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:reKYC for Fintech Security: A Privacy-Preserving Approach to Digital Wallet Verification DESCRIPTION:Authors - Ikram Ahamed Mohamed\, Hafiz Abdulla\, Mohaideen Mohamed Mohabilasha\, Fiyaz Ahmed\, Pankaj Chandre\, Parikshit Mahalle Abstract - With the surge in digital wallet usage across fintech platforms\, secure and privacy preserving Know Your Customer (KYC) mechanisms have become increasingly critical. This survey reviews the current state of digital identity verification frameworks\, emphasizing the challenges posed by centralized KYC models\, including data breaches\, lack of user consent\, and regulatory fragmentation. We systematically analyze more than 50 recent studies and industry practices addressing privacy-preserving identity protocols\, decentralized identity (DID) systems\, cryptographic techniques (such as zero-knowledge proofs)\, and access control architectures. The paper proposes a reference architecture reKYC based on common patterns found in the literature\, integrating layered components for identity verification\, access governance\, trust evaluation\, and regulatory compliance. We classify existing approaches by their trust model\, cryptographic basis\, and consent mechanisms. Key gaps identified include limited regulatory interoperability\, weak user-centric control models\, and lack of scalable trust frameworks. This survey concludes with open research directions and a future outlook for secure\, privacy-aligned digital wallet verification. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:14307ad734e77615e053ae6526ae5d4b URL:http://5thworldconferenceoninformations.sched.com/event/14307ad734e77615e053ae6526ae5d4b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Reviving Indian knowledge systems: implementation\, execution\, and impact on modern education DESCRIPTION:Authors - Ujwala Kshirsagar\, Asmita Dani Abstract - The National Education Policy 2020 (NEP 2020) encourages the inclusion of an Indian Knowledge System (IKS) in the Higher education curriculum. In traditional Indian philosophy\, the search for knowledge wisdom and truth was always seen as the highest goal of human life. The scholars made significant contributions in many fields likes mathematics\, medicine\, astronomy\, engineering\, surgery\, architecture\, navigation\, shipbuilding\, arts\, yoga\, and even chess. These valuable traditions and contributions should be preserved\, studied\, developed\, and used in new ways through our education system to benefit future generations This paper focused on strategies for implementing IKS Indian Knowledge System into curriculum of higher education institutes\, to roadmap efficient execution of IKS and impact of addition of IKS on modern syllabus. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:4825d7e62d07c65cafc8ba39d1cd44f4 URL:http://5thworldconferenceoninformations.sched.com/event/4825d7e62d07c65cafc8ba39d1cd44f4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Scenario-based Crowdfunding Framework to Accelerate Corporate Social Responsibility and Empower Employees in Society 5.0 DESCRIPTION:Authors - Vikas Shah\, Aarav Shah\, Aarush Shah Abstract - The crowdfunding landscape\, positioned at the intersection of entrepreneurship and technological innovation\, compels organizations to address rising competitiveness while embedding corporate social responsibility (CSR) and advancing employee empowerment. Traditional crowdfunding approaches often struggle to meet the primary objectives due to inconsistent mechanisms to ac-count for regulatory changes\, cultural diversity\, and the demand for measurable social impact. A persistent limitation of existing practices is the absence of standardized frameworks and measurable indicators capable of capturing the organizational and societal value of crowdfunding. The paper introduces a Scenario-based Crowdfunding Framework (SCRF) that categorizes scenarios and defines actionable objectives to enhance alignment between CSR and employee empowerment. SCRF is a lightweight and adaptable methodology incorporating elementary mechanisms to evaluate\, refine\, and strengthen the social and organizational impact of crowdfunding. An empirical case study of crowdfunding for Artificial Intelligence (AI) initiatives and programs is performed\, providing evidence of how scenario-based initiatives can serve as a strategic lever for CSR and employee empowerment in the context of Society 5.0. The research identifies key determinants influencing crowdfunding effectiveness and examines their implications for CSR integration and organizational engagement with scenario-driven analysis\, governance cycle\, and impact evaluations. The study ex-amines and contributes to accelerating CSR initiatives\, positioning employees as empowered change agents\, and advancing the broader societal vision of So-ciety 5.0. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:acc994814944bfd61b65bcd0ad8f793b URL:http://5thworldconferenceoninformations.sched.com/event/acc994814944bfd61b65bcd0ad8f793b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:The Repercussions of the Chinese Business Culture on the Motivations of Generation-Y to Work in Chinese-Owned Garment Companies DESCRIPTION:Authors - Nurianna Thoha\, Stephen Wijaya Abstract - The purpose of this research is to explore the motivational factors of Generation Y (Gen Y) to work in Chinese-owned garment companies and to analyze how these factors are linked to Herzberg’s theory of motivation and the Chinese business culture since based on the previous research many companies do not properly motivate Gen Y employees. A qualitative method by utilizing exploratory study was applied for this research. In-depth semi-structured inter-views with 25 Gen Y employees were conducted in two Chinese-owned garment companies in the Greater Jakarta area of Indonesia\, to collect the primary data. The interviews were recorded\, and the data was used to develop the transcripts\, which were then analyzed using thematic data analysis. The research results showed that Herzberg’s theory of motivation and Guanxi are not always aligned with the motivations of Gen Y employees to work in Chinese-owned garment companies. For example\, quality of relationship and status are aligned with Guanxi but not aligned with Herzberg’s theory of motivation. However\, several Guanxi factors are aligned with Herzberg’s theory of motivation\, such as trust and responsibility\, and recognition. In conclusion\, there is a connection between motivations\, Chinese business culture\, and generation cohort which is GenY employees who are currently working in both garment companies in the Greater Jakarta area of Indonesia. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:69e5050d502b99f2df40a863b8132533 URL:http://5thworldconferenceoninformations.sched.com/event/69e5050d502b99f2df40a863b8132533 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T163000Z DTEND:20261018T183000Z SUMMARY:Transforming Plant Disease Classification through AI and Methodological Integration DESCRIPTION:Authors - \;Akash Patel\, Hardik kumar Jayswal\, Rishi Patel\, Prem Trivedi \nAbstract - \;This paper provides an in-depth analysis of various methods and concluding things for plant disease detection and classification\, utilizing combinations of machine learning and deep learning approaches. The literature review highlights three primary methods: computer vision-based ML models\, DL architectures\, and spectroscopy-based techniques. While computer vision methods\, including segmentation and manual feature extraction\, have been extensively used\, they are time-consuming and less effective for datasets with minimal visible symptoms. Deep learning\, with its capability for automatic feature extraction\, demonstrates significant potential\, although challenges such as high computational costs and overfitting persist. Spectroscopy methods present alternative strategies\, yet they are not universally applicable across all types of plant diseases. Our analysis suggests that optimized methodologies\, capable of handling diverse datasets and overcoming the limitations of visual-based techniques\, are essential for the timely and accurate classification of plant diseases. Future research must ad-dress these challenges to develop more robust\, scalable\, and efficient disease detection systems. CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:48f986d18ffbf4fdd790569aac469ef0 URL:http://5thworldconferenceoninformations.sched.com/event/48f986d18ffbf4fdd790569aac469ef0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183000Z DTEND:20261018T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:e560a435cbb62cc0cc43872716154eab URL:http://5thworldconferenceoninformations.sched.com/event/e560a435cbb62cc0cc43872716154eab END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183000Z DTEND:20261018T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:68de41b424dc61fb1e62dd3b164dd9d2 URL:http://5thworldconferenceoninformations.sched.com/event/68de41b424dc61fb1e62dd3b164dd9d2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183000Z DTEND:20261018T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:082612eea8bec0a7a071556405df66c3 URL:http://5thworldconferenceoninformations.sched.com/event/082612eea8bec0a7a071556405df66c3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183000Z DTEND:20261018T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:127b3eb27198c69685d6eed1f2cdf615 URL:http://5thworldconferenceoninformations.sched.com/event/127b3eb27198c69685d6eed1f2cdf615 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183000Z DTEND:20261018T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:f560bb73d8e4eb9d65f3f229e96febc8 URL:http://5thworldconferenceoninformations.sched.com/event/f560bb73d8e4eb9d65f3f229e96febc8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183000Z DTEND:20261018T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:bc76a723514f5436da9fe7f2883c57c4 URL:http://5thworldconferenceoninformations.sched.com/event/bc76a723514f5436da9fe7f2883c57c4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183200Z DTEND:20261018T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:173b4dc3759ccb9380ecedf4a04af7ea URL:http://5thworldconferenceoninformations.sched.com/event/173b4dc3759ccb9380ecedf4a04af7ea END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183200Z DTEND:20261018T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:1ca1cb8a905153dfb71f18c6ab9691d7 URL:http://5thworldconferenceoninformations.sched.com/event/1ca1cb8a905153dfb71f18c6ab9691d7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183200Z DTEND:20261018T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:0ee7384176928bf904b04ff1571f0384 URL:http://5thworldconferenceoninformations.sched.com/event/0ee7384176928bf904b04ff1571f0384 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183200Z DTEND:20261018T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:59320a3425a9576e54e27e7a27404fdb URL:http://5thworldconferenceoninformations.sched.com/event/59320a3425a9576e54e27e7a27404fdb END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183200Z DTEND:20261018T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:2f47a097c05c5372bc40bc786f3a4dab URL:http://5thworldconferenceoninformations.sched.com/event/2f47a097c05c5372bc40bc786f3a4dab END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T183200Z DTEND:20261018T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 4F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:201ec584ee1f7e5b1569e41b5feec9b2 URL:http://5thworldconferenceoninformations.sched.com/event/201ec584ee1f7e5b1569e41b5feec9b2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191300Z DTEND:20261018T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:0557f0ea0cfe31c2e7d3ef4ca7a9aebc URL:http://5thworldconferenceoninformations.sched.com/event/0557f0ea0cfe31c2e7d3ef4ca7a9aebc END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191300Z DTEND:20261018T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:20ba8cd845770a136c17c3cb0a04a9b7 URL:http://5thworldconferenceoninformations.sched.com/event/20ba8cd845770a136c17c3cb0a04a9b7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191300Z DTEND:20261018T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:2d14ce31dbe0d24ff2dd77610dcd2a59 URL:http://5thworldconferenceoninformations.sched.com/event/2d14ce31dbe0d24ff2dd77610dcd2a59 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191300Z DTEND:20261018T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:4b3e8581947a627cc5e260df01d42bee URL:http://5thworldconferenceoninformations.sched.com/event/4b3e8581947a627cc5e260df01d42bee END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191300Z DTEND:20261018T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:e4fb29d430df1634f28c2584de5e9acb URL:http://5thworldconferenceoninformations.sched.com/event/e4fb29d430df1634f28c2584de5e9acb END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191300Z DTEND:20261018T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:24100c6b43b0849f333e41d1c686fcb8 URL:http://5thworldconferenceoninformations.sched.com/event/24100c6b43b0849f333e41d1c686fcb8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:A Systematic Review on Real-Time Liveness Detection against 3D Mask and Media-Based Spoofing Attacks in Face Biometric Systems DESCRIPTION:Authors - G Baby Lakshmi Prasanna\, R. Pradeep Kumar Reddy Abstract - In a time of increasing dependence on digital identity\, facial biometric systems have become important for access control and authentication. However\, their vulnerability to advanced presentation attacks is especially 3D masks and media -based (photos\, videos and replay’s like gif) reflects serious security threats. Due to liveness detection will show some impact on the major threats which are unseen attacks. This literature survey systematically examines the development of real -time detection techniques developed to combat these challenges. We analyze deep learning methods and hybrid models such as classic texture-based methods\, 3D depth and thermal sensing\, CNN and VITs\, customized distribution on edge units. The paper data set discusses availability\, real -time performance\, generality of the domain and hardware efficiency. Research intervals have been highlighted in adapting cross -film\, unfavorable strength and distribution of low resources. This review serves as a basis for researchers and doctors\, who aim to develop flexible\, real-time anti-spoofing systems for safe biometric authentication. Apart from this some of review highlights the importance of standardized evaluation protocols\, privacy-preserving deployment and fairness across demographics groups. CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:d4a1c07c73da14df3510ff2a6bf23075 URL:http://5thworldconferenceoninformations.sched.com/event/d4a1c07c73da14df3510ff2a6bf23075 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Customer Loyalty Formation in the Digital Era: A Mediated-Moderated Model of Satisfaction\, Trust\, Brand Image\, Engagement\, and Perceived Value DESCRIPTION:Authors - Ch Sahyaja\, D. Harsha\, G. Sruthi\, Ch Shankar Abstract - The digital marketplace presents significant challenges for firms\, making customer loyalty a crucial strategic goal for sustained success. This study develops and tests a mediated-moderated structural model to uncover the mechanisms behind customer loyalty formation. Drawing on Relationship Marketing Theory and Customer Engagement Theory\, the model examines Customer Engagement (CE) as a mediator between Customer Satisfaction (CS)\, Trust (TR)\, and Brand Image (BI)\, with Perceived Value (PV) moderating the CE–Customer Loyalty (CL) relationship. Data from 406 digital consumers were analyzed using Structural Equation Modeling (SEM) and moderation analysis. Results reveal that CE significantly mediates the effects of satisfaction\, trust\, and brand image on loyalty\, accounting for up to 47% of the relationship. Additionally\, PV moderates the engagement–loyalty link\, enhancing the impact of engagement on loyalty in online contexts. The constructions demonstrated strong reliability and validity. These findings highlight the central role of engagement in converting relational drivers into loyalty and emphasize the importance of perceived value in strengthening this effect\, offering valuable insights for firms seeking to build enduring digital customer relationships. CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:d099389fe3d10f643f7984473ae073f4 URL:http://5thworldconferenceoninformations.sched.com/event/d099389fe3d10f643f7984473ae073f4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Digital Transformation in GST: A Comparative Study of Tax Compliance Systems in South Indian States DESCRIPTION:Authors - Sreesankar R S\, Durgalashmi C V Abstract - This study examines the year-on-year percentage change in Goods and Services Tax (GST) collections across five South Indian states—Karnataka\, Kerala\, Tamil Nadu\, Telangana\, and Andhra Pradesh—from 2017–2018 to 2023–2024. Employing a comparative and trend analysis framework\, the research traces the initial post-implementation surge\, the pandemic-induced contraction\, and the subsequent recovery and deceleration phases. While all states experienced robust growth immediately after the introduction of GST\, the subsequent trends reveal significant divergence. Karnataka consistently outperformed its peers\, benefiting from digital readiness and administrative efficiency\, whereas Andhra Pradesh\, despite an early lead\, now lags. The findings highlight the influence of state-specific economic structures\, governance models\, and digital infrastructure on tax performance. CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:3285e1d95121c1b230e24be3e83e4adc URL:http://5thworldconferenceoninformations.sched.com/event/3285e1d95121c1b230e24be3e83e4adc END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Impact of Leather and Non-Leather Footwear on Foot Health and Comfort DESCRIPTION:Authors - D.K. Chaturvedi\, Sachin Diwaker Abstract - Footwear is critical in maintaining foot health\, comfort\, and overall well-being. Leather and non-leather materials are widely used in footwear manufacturing\, each with distinct properties affecting breathability\, durability\, and foot support. This study examines the impact of leather and non-leather footwear on foot health and comfort by analyzing existing research\, material properties\, and biomechanical factors. Findings indicate that leather footwear generally offers superior breathability and ergonomic support\, whereas non-leather alternatives provide cost-effective and ethical advantages but may lead to foot discomfort over prolonged use. Future research should focus on developing sustainable yet comfortable alternatives. CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:d5d462de1822971a5cd6f9d7865ee568 URL:http://5thworldconferenceoninformations.sched.com/event/d5d462de1822971a5cd6f9d7865ee568 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Managing Educational Processes Using Blockchain Technology: The Example of Stackable Micro-Credentials Acquisition DESCRIPTION:Authors - Oleksii Shapoval Abstract - Stackable micro-credentials have a significant potential for making the study process more flexible and personalized. The paper introduces an approach for managing educational processes related to the acquisition of stackable micro-credentials with the use of blockchain technology. The approach allows learners to build verifiable personalized skill trees with cryptographic provenance of their progression. The paper first outlines related works in the fields of micro-credentials\, stackable credentials\, and the application of blockchain technology in education and knowledge certification. Then\, the approach is described\, starting with a high-level overview\, elaboration on incorporated technologies\, and a description of the main processes. The contextualization of the work is then provided\, elaborating on implications and practical advantages of the presented approach. The research contributes to the field of knowledge management by providing a practical blueprint for how blockchain technology can be applied for personalization of learning process. This approach can be applied for a number of use-cases\, from small-scale workshops to online courses and education institution environments. CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:3950220861f63992002a1f42ec8d5102 URL:http://5thworldconferenceoninformations.sched.com/event/3950220861f63992002a1f42ec8d5102 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Media Mix Determination Model using MCDA DESCRIPTION:Authors - Sandali Tharumini\, Indra Mahakalanda\, Prasanga Jayathunga Abstract - Advertising is a major element in the promotional mix that plays a crucial role in both brand development and success. Advertising messages reach end customers through multiple mediums like television\, radio\, digital media\, outdoor display advertising (OOH)\, and print publications. The selection of an optimal media mix serves as one of the critical aspects. This research addresses the issue of the absence of a structured methodology for media mix selection in the advertising industry\, which generally leads to inefficient media planning. Applying the Multi-Criteria Decision Analysis (MCDA) technique\, Fuzzy Analytic Hierarchy Process\, the study evaluates five qualitative criteria to determine the optimal media mix. By using a real-world relaunch campaign\, "My Zesta Story" from the Sri Lankan tea brand "Zesta"\, the study provides a campaign-specific framework for media mix optimization. The analysis reveals that learning effectiveness is the most influencing criterion in media selection\, and overall\, in terms of performance\, digital media and TV are the best performers. Digital is slightly leading due to its affordability\, learning effectiveness\, and campaign fit. TV outperforms on communication fit and competitiveness CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:1455dfd97bd99416920f5d3dc8f2c973 URL:http://5thworldconferenceoninformations.sched.com/event/1455dfd97bd99416920f5d3dc8f2c973 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:SEM Generates Good Ideas! Differences in the Quality of Concept Planning Depending on the Method of Visualizing Consumer Attitude Factors DESCRIPTION:Authors - Takumi Kato\, Ryosuke Ikeda\, Emiko Yamada\, Kenta Kasahara Abstract - In the current big data era\, excessively rich data may cause information overload in employees\, resulting in reduced productivity. Therefore\, this study seeks to address the question: "Is it more effective to generate ideas by showing factors at the factor level\, as with structural equation modeling (SEM)\, rather than showing the effects of a large number of individual variables\, as with multiple regression analysis (MRA)?" We randomly assigned 131 students to use the brand image factors of 10 sports in Japan as reference data for ideas. We provided the control group with the MRA analysis results and the treatment group with the SEM analysis results\, and asked them to plan a new gym concept. As a result of a randomized controlled trial conducted on 2\,521 people in their 20s to 60s\, 29.1% (control group: MRA analysis) and 36.2% (treatment group: SEM analysis) found the concept attractive (quality of the concept)\; a significant difference was detected. However\, the amount of concepts was fewer in the treatment group. Presumably\, the motivation to generate more ideas decreases once a good idea is generated through SEM. Therefore\, SEM should be actively adopted for data analysis within a company to reveal employees’ idea-creating abilities. Additionally\, the motivation to produce more ideas decreases once a good idea is produced\; hence\, managers should not easily demand large amounts of output from their subordinates. This study is novel since it demonstrates the impact of the comprehensive analytical results of aggregated information from SEM on human creativity. CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:8468014c98da502e2bb7003874dd5e99 URL:http://5thworldconferenceoninformations.sched.com/event/8468014c98da502e2bb7003874dd5e99 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Solving Complex EOQ Models Using Finite Difference and Iterative Numerical Methods DESCRIPTION:Authors - Patel Nirmal Rajnikant\, Ritu Khanna Abstract - The relevance of conventional Economic Order Quantity (EOQ) models to today's manufacturing systems with varying and unpredictable parts demand is small\, as they often use closed-form analytical approaches with constant demand. In this paper\, we propose a numerical scheme that integrates Newton-Raphson iterative techniques with finite difference methods to address complex EOQ models with variable demand. To achieve this\, the EOQ problem is reformulated into a nonlinear minimization problem of a total cost model where a non-linear first-order condition needs to be solved to find the order quantity. Due to the variability of demand\, it is often impossible to analytically derive the cost function’s gradient\, thus the finite difference method is employed within the Newton-Raphson iteration process to approximate the gradient.To assess the method's effectiveness\, several manufacturing case scenarios with different demand profiles are used. The results show that the proposed hybrid procedure finds accurate solutions even for non-linear and non-stationary demand. The paper fills the gap between the theory of optimization and actual inventory management in the dynamic production environment by providing a flexible and widely applicable solution procedure for EOQ models with advanced elements. CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:61b043c0871b6c11a1b962f99a678ea5 URL:http://5thworldconferenceoninformations.sched.com/event/61b043c0871b6c11a1b962f99a678ea5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Sustainable EOQ Model with Carbon Emission Caps and Renewable Sourcing in Inventory Decisions DESCRIPTION:Authors - Patel Nirmal Rajnikant\, Ritu Khanna Abstract - We provide a rationale on how businesses can adapt inventory control techniques and simultaneously integrate sustainability strategies to reach economic goals. An up-to-date version of the Economic Order Quantity (EOQ) model is developed with sustainability prerequisites around the greenhouse gas emissions limit and the ratio of renewable resources used during procurement\, aiming to lower total inventory cost while observing the legal green compliance requisites. These prerequisites focus on the scope of emissions generated and emissions reduction efforts undertaken by the business. Subordinate to emissions caps\, we set forth a decision variable proportional to renewably sourced material per order. Valuable analytical responses to questions related to the impact of cap levels and renewably sourcing on order size\, frequency and cost are presented. Numerical example based on business of a medium-sized manufacturing company is implemented. Outcomes reveal that investments for strengthening renewably sourced materials to drive green purchasing significantly improve environmental footprint measurements at reduced cost. Such awareness significantly boosts operation planning cost sustainability objectives. CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:5644039d8ad235caecffaa854e9a550d URL:http://5thworldconferenceoninformations.sched.com/event/5644039d8ad235caecffaa854e9a550d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Understanding Customer Views in the Evolving Insurance Industry: Conventional Methods versus Technology-Enabled Sustainable InsurTech DESCRIPTION:Authors - Adwaitha K Raj\, Pranesh P\, Durga Lashmi C.V\, Taramol K.G Abstract - The sale of insurance products through the bancassurance channel has rapidly gained popularity in India. Consumers who make use of joint services provided by banks and insurance companies weigh different considerations when making purchases and evaluate different standards to gauge their degree of satisfaction. This study examines the factors that influence customer purchasing behaviour and satisfaction with bancassurance\, using a sample of 150 respondents from three districts in Kerala. The findings suggest that after purchasing insurance through agents\, banks are emerging as the next best option\, due to their commitment\, cost savings and return on investment. Majority clients prefer to buy future insurance policies through bancassurance\, citing advantages like current policy information\, fast premium payments\, and efficient claims processing. Therefore\, the future of bancassurance in India looks promising if partnering companies effectively channel their efforts to meet the customers' needs. CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:dec611b71db75d6484f3f96fcf5c45a4 URL:http://5thworldconferenceoninformations.sched.com/event/dec611b71db75d6484f3f96fcf5c45a4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:An Efficient Technique to Design Carry Skip Adder Using Reversible Logic Gate DESCRIPTION:Authors - Md. Mizanur Rahman\, Ankan Roy\, Shovan Kumar Paul\, Anupam Singha Abstract - Nowadays\, energy or power dissipation has become a major concern in digital integrated circuit design. This high-density design of the chip increases power dissipation. One of the primary causes of energy dissipation is irreversible computation\, necessitating improved power optimisation techniques. Consequently\, the reversible logic methodology provides an efficient means to minimise energy dissipation in the circuit. Addition is a fundamental arithmetic operation that underpins other regularly utilised operations\, including multiplication\, division\, and subtraction. In computing systems\, adders\, which are digital circuits that add numbers\, are a fundamental component. With the continuous development of technology\, the need for efficient and high-performance processing units has become inevitable\, and these must be made from reversible logic elements. The Carry Skip Adder(CSA) is among the most efficient adders utilised in numerous data processing units to do swift arithmetic operations. This study introduces a design that is effective of a CSA utilising reversible logic gates and evaluates its performance. The proposed design achieves notable improvements over existing works by reducing garbage outputs\, optimizing constant inputs\, minimizing delay\, enhancing quantum cost efficiency\, and decreasing the overall gate count. Additionally\, the performance of the suggested adder surpasses that of others in terms of transistor count and power dissipation. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:0fd4932c632d1d04c881e19fde81465a URL:http://5thworldconferenceoninformations.sched.com/event/0fd4932c632d1d04c881e19fde81465a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Autonomous Healthcare Monitoring via IoT-Edge Computing: Adaptive Power Optimization (Solar/SMPS)\, Predictive Analytics\, and Blynk-Enabled Telemedicine for Chronic Disease Management DESCRIPTION:Authors - Badrun Nahar Luna\, Nazifa Jerin Reshni\, Shefat-E-Ara Khan\, Md. Munna Khan\, Md. Rakibul Hasan Antor\, Sadah Anjum Shanto Abstract - This autonomous healthcare monitoring system enhances patient care by tracking vital signs and automating essential needs via IoT-Edge computing. It uses MAX30100 and DS18B20 sensors to measure heart rate\, oxygen levels\, and body temperature\, with real-time data displayed on an LCD screen and transmitted to the Blynk app for remote monitoring. The system automates food and medicine dispensing using a servo motor\, ensuring timely intake through Blynk notifications for caregivers. To maintain uninterrupted operation\, a hybrid power system integrates solar panels\, battery storage\, and an SMPS\, with a relay switch enabling automatic transitions based on power availability. The Blynk app also monitors the voltage and efficiency\, comparing the solar and SMPS performance. Paired NodeMCU microcontrollers power the system\, making it extensible and sustainable. Anticipated for hospitals\, clinics\, and home healthcare\, this smart monitoring system leverages IoT technology to strengthen patient safety\, accommodation\, and authenticity while reducing manual interference. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:b3bea20b61410cb1d09906900e85994c URL:http://5thworldconferenceoninformations.sched.com/event/b3bea20b61410cb1d09906900e85994c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Blockchain in Training Management DESCRIPTION:Authors - Suruchi Pandey\, Hemlata Gaikwad\, Vatsala Saxena\, Sweta Rani\, Sonal Kumari Abstract - The fast pace of development in blockchain technology is transforming corporate Learning and Development (L&D) by addressing challenges related to credential verification\, transparency in training\, compliance tracking\, and work-force mobility. Current training management systems are typically plagued by inefficiencies in the form of manual verification\, data security breaches\, and lack of interoperability with Learning Management Systems (LMS). This research explores how blockchain can enhance training management through decentralized\, tamper-evident learning records\, providing trust\, security\, and efficiency for corporate training programs. The study utilises a secondary data research design\, scrutinizing industry reports\, peer-reviewed scholarly articles\, firm case studies\, and government policy documents. Results indicate that blockchain enables secure credentialing\, time-real skill verification\, automated compliances verification\, and easy transfer of certification from one company to another. The study employs the ADDIE Model to assess the use of blockchain in L&D for effective training program analysis\, design\, development\, implementation\, and evaluation. This study concludes that blockchain will play an important role in the future of business education but requires standardized models\, policy backing\, and scalable integration models to achieve large-scale adoption. Companies must leverage blockchain-based AI learning systems to enhance workforce training\, compliance automation\, and global credential recognition in the digital economy. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:7dfa082e2beffd9fa68a9cb14501a167 URL:http://5thworldconferenceoninformations.sched.com/event/7dfa082e2beffd9fa68a9cb14501a167 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:DisasterComm: A Severity-Aware Big Data Communication Framework for Effective Disaster Notification DESCRIPTION:Authors - Anika Yadav\, Ananya V Holla\, Animesh Giri Abstract - With the growing use of connected devices\, geographic barriers diminish\, enabling communication of critical data in near real-time. As the frequency of natural disasters increases\, timely communication forms the backbone of efficient disaster management. With the number of recipients varying based on the population density\, any disaster notification framework must be highly scalable. Big Data technologies like Apache Kafka\, Apache Flink\, RabbitMQ\, Apache Spark\, and Apache Hadoop can be employed to enhance scalability. This study proposes a hybrid framework that classifies disasters based on severity and then routes them through one of three pipelines. This approach ensures that the Quality of Service requirements for each disaster severity type are satisfied. The pipeline assigned to handle high-severity traffic demonstrates notification delivery with latency in the order of 0.88 seconds on average across the disaster types. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:cd8b392129cfac3e0f216b48e638bb4d URL:http://5thworldconferenceoninformations.sched.com/event/cd8b392129cfac3e0f216b48e638bb4d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Fuzzy Meta-Goal Programming for Wind-Solar Hybrid Systems: Optimizing Renewable Synergies in Arid and Coastal Environments DESCRIPTION:Authors - Chauhan Priyank Hasmukhbhai\, Ritu Khanna Abstract - The integration of wind-solar hybrid systems presents a transformative pathway to bolster renewable energy resilience\, yet their optimal deployment in geographically diverse environments remains hindered by spatiotemporal intermittency\, conflicting stakeholder priorities\, and dynamic ecological constraints. This study proposes a novel fuzzy meta-goal programming (FMGP) framework to reconcile techno-economic\, environmental\, and social objectives in wind-solar hybridization\, with a focus on arid and coastal ecosystems—regions characterized by contrasting meteorological volatility and land-use sensitivities. By embedding fuzzy set theory into meta-goal structures\, the model quantifies uncertainties in renewable resource availability (e.g.\, wind shear variability\, solar irradiance fluctuations) while balancing antagonistic criteria such as levelized energy cost minimization\, carbon footprint reduction\, and biodiversity preservation. The FMGP approach uniquely incorporates synergistic complementarity metrics to exploit temporal offsetting between wind and solar generation cycles\, enhancing grid stability in resource-erratic zones. Empirical validation through case studies in a hyper-arid desert and a storm-prone coastal region reveals Pareto-optimal solutions that achieve up to 23% improvement in annual energy yield reliability and 18% reduction in land-use conflicts compared to conventional multi-objective models. Furthermore\, the framework introduces a stochastic acceptability index to evaluate policy robustness under climate change scenarios\, demonstrating adaptive capacity in mitigating energy-water nexus pressures in arid areas and storm resilience trade-offs in coastal grids. This research advances sustainable hybrid system design by harmonizing multi-scale environmental governance with precision energy planning\, offering policymakers a decision-centric tool to navigate the socio-ecological complexities of the renewable transition. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:89cd15acd4a659182f610258c304c9c1 URL:http://5thworldconferenceoninformations.sched.com/event/89cd15acd4a659182f610258c304c9c1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Mapping Dropouts: A Comparative Analysis of State- Specific Influences on Skill Development Programs in India DESCRIPTION:Authors - Kala V Krishnan\, Ramanathan P V Abstract - India is currently experiencing a demographic dividend\, with the youngest working population predicted to remain until 2050. Scholars emphasize that this demographic advantage alone cannot guarantee the economic growth of the country unless accompanied by effective policy interventions. Skill development has thus emerged as a national priority to harness this opportunity\, leading to large-scale initiatives such as the Pradhan Mantri Kaushal Vikas Yojana (PMKVY). As India’s flagship skill certification scheme\, PMKVY aims to provide industry-relevant training to youth. Despite its magnificent scale and substantial investment\, the program faces a major challenge of high dropout rates among participants\, which warns its long-term effectiveness and results in significant economic and social costs. Existing research highlights the need for analysing these dropout trends\, especially at the state level\, where disparities may reflect underlying regional and structural factors. This study adopts a quantitative cross-sectional comparative approach to assess the dropout rates of PMKVY across Indian states and examine the impact of selected state-specific factors: poverty rate\, literacy rate\, population density\, and industrial development. The objective is to identify the extent of regional variation and analyse the relationship between these state-specific factors and program attrition. By doing so\, the study aims to generate insights that can inform policy reforms and targeted interventions to improve retention and enhance the efficiency of government-supported skill development programs in India. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:96d24ba88a164f40c376859f594b0e63 URL:http://5thworldconferenceoninformations.sched.com/event/96d24ba88a164f40c376859f594b0e63 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Optimization of Marine Oil Extraction and Resource Allocation Using Fuzzy Logic and Nonlinear Goal Programming DESCRIPTION:Authors - Chauhan Priyank Hasmukhbhai\, Ritu Khanna Abstract - The strategic allocation of marine oil resources involves complex trade-offs between economic performance\, operational efficiency\, and environmental sustainability—often under significant uncertainty. This paper develops a robust decision-support framework that integrates Fuzzy Logic with Nonlinear Goal Programming (NLGP) to address the multi-objective optimization problem inherent in marine oil extraction and resource allocation. Uncertainty in key parameters— such as extraction costs\, production yields\, and environmental impact limits—is modeled using fuzzy sets\, enabling a more flexible representation of real-world ambiguity. The model simultaneously optimizes multiple nonlinear and conflicting goals\, including profit maximization\, cost minimization\, and ecological risk reduction. To efficiently solve the resulting nonlinear programming problem\, a hybrid solution approach is proposed that combines fuzzy goal programming techniques with metaheuristic optimization\, specifically a tuned Genetic Algorithm. The framework is applied to a representative offshore oil field scenario\, demonstrating superior performance in solution quality and robustness compared to traditional linear and crisp optimization methods. The results underscore the potential of fuzzy NLGP models in supporting high-stakes operational decisions in uncertain and dynamic environments. This work contributes to the growing body of operations research methods that address multi-criteria decision-making under uncertainty\, with direct implications for energy resource planning and sustainable marine operations. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:8e1512d8d4421a9b6d2769452bbc0031 URL:http://5thworldconferenceoninformations.sched.com/event/8e1512d8d4421a9b6d2769452bbc0031 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Role of ICT in E-Governance Problems and Acceptability DESCRIPTION:Authors - Smita Kalokar\, Ritesh Sule\, Dinesh Mirkute Abstract - A nation's progress is supported by its effective administration. To ensure the betterment of the country the governments of all the world has accepted the sustainable development goals which is announced by United Nation Development programme (UNDP) in 2015\,as acceptable target by the member country.The transformation in digital Technology has introduced a new focus for government in India. Nowadays\, Information and Communication Technology (ICT) is essential. In particular\, for developing nations\, it is viewed as vital for economic\, social\, and political progress. The introduction of low-cost smart phones and the lowest-priced data packages have increased the opportunities for both citizens and government equipment to take advantage of e-Government's advantages. In recent years\, e-Governance initiatives in India have shown their effectiveness in reducing processing expenses\, enhancing transparency\, and fostering economic growth through income-generating activities\, increased agricultural output\, and advancements in health and education sectors. These improvements collectively enhance the quality of life for Indian citizens. Nevertheless\, e-Governance has not fully reached all demographics\, particularly in rural areas. In rural India\, there are specific basic and cultural challenges that hinder the achievement of e-Governance objectives. Consequently\, the government must address these issues and ensure that service delivery mechanisms are user-friendly for these communities. This paper will explore ICT and Governance in India\, along with the fundamental challenges and acceptance of e-Governance. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:1af096795541abf03c4d778d9148c483 URL:http://5thworldconferenceoninformations.sched.com/event/1af096795541abf03c4d778d9148c483 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Synergizing Goal Programming and Neural Network AI for Real-Time Virtual Reality Model Optimization: A Framework for Multi-Objective Decision-Making in Dynamic Systems DESCRIPTION:Authors - Chauhan Priyank Hasmukhbhai\, Ritu Khanna Abstract - Real-time optimization of virtual reality (VR) models in dynamic systems demands adaptive decision-making frameworks capable of reconciling conflicting objectives such as computational efficiency\, latency reduction\, and user experience fidelity. While traditional optimization techniques often struggle with the non-linear\, high-dimensional\, and time-sensitive nature of VR environments\, this paper introduces a novel hybrid framework that synergizes Goal Programming (GP) and Neural Network Artificial Intelligence (NN-AI) to address these challenges. The proposed methodology leverages GP to formalize multi-objective decision-making under constraints\, while a dynamically trained neural network predicts and prioritizes system states in real time\, enabling context-aware adjustments to VR model parameters. By integrating GP’s structured optimization with NN-AI’s predictive adaptability\, the framework achieves Pareto-optimal solutions that balance competing objectives across fluctuating operational conditions. The study validates the framework through a series of simulated and real-world VR scenarios\, including immersive gaming and industrial training systems\, where dynamic variables such as user interactions\, environmental complexity\, and hardware limitations are present. Results demonstrate a 22–35% improvement in rendering efficiency and a 40% reduction in latency compared to conventional single-objective optimization approaches\, without compromising visual quality. Furthermore\, the system exhibits robust generalization capabilities\, adapting to unseen scenarios within 5–10 iterations. This research bridges a critical gap in real-time multi-objective optimization for VR\, offering a scalable\, AI-driven solution for industries reliant on immersive technologies. The framework’s ability to harmonize human-centric objectives with computational constraints positions it as a transformative tool for next-generation dynamic systems in entertainment\, healthcare\, and Industry 4.0 applications. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:a4668f889aa884895052ce16d877bf43 URL:http://5thworldconferenceoninformations.sched.com/event/a4668f889aa884895052ce16d877bf43 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Time To Failure Prediction for Industrial Ovens Using Machine Learning and Deep Learning DESCRIPTION:Authors - Thuan Nguyen Dinh\, Truong Nguyen Xuan Abstract - In this paper\, the authors suggest and compare models for industrial oven Time-to-Failure (TTF) prediction within a critical 60-minute timeframe using sensor data. They compare traditional methods such as LSTM\, GRU + Attention\, and XGBoost with a new hybrid approach: CNN-Autoencoder + XGBoost (CNN-AE+XGBoost). Experimental outcomes\, in terms of RMSE\, MAE\, and R²\, confirm the performance superiority of the proposed system. For the complete dataset\, R² for the hybrid model was 0.89\, well ahead of LSTM (0.27)\, GRU + Attention (0.47)\, and XGBoost (0.83). Importantly\, for the focused TTF ≤ 60 minutes frame\, it also had a low Mean Absolute Error (MAE) of 6.57. These results present the CNN-AE+XGBoost model as an effective predictive maintenance tool for curbing production downtime within the food processing sector. CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:2908112e6e4460ba8f5f1d05ee7bf3b2 URL:http://5thworldconferenceoninformations.sched.com/event/2908112e6e4460ba8f5f1d05ee7bf3b2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Emerging Themes and Bibliographic Analysis of Smart Waste Bin as an Inputs to Cost-Effective\, Automated Waste Management DESCRIPTION:Authors - And Julie D. Rosal Abstract - This study checks on emerging research trends and conducts a bibliographic analysis on smart waste bins as foundational elements for cost-effective\, automated waste management solutions. The escalating urbanization and environmental pressures necessitate advanced waste management technologies\, where smart trash bins equipped with IoT (Internet of Things)\, AI (Artificial Intelligence)\, and robotics offer transformative solutions such as automated segregation\, real-time monitoring\, and optimized collection routes. Employing a systematic literature review facilitated by Scopus AI\, the study identifies consistent\, rising\, and novel themes in smart bin research. IoT-enabled systems consistently emerged\, underscoring their role in operational efficiency and sustainability. Rising trends prominently featured AI integration\, robotic automation\, and advanced waste segregation methods\, indicating a clear shift towards intelligent automation. Security and privacy issues constitute novel themes\, reflecting the growing importance of ensuring trust and reliability in technology adoption. The bibliometric analysis revealed significant global research contributions with notable peaks aligning with heightened global sustainability goals. Additionally\, the study proposes a conceptual prototype integrating sensors\, AI-driven categorization\, and autonomous collection mechanisms\, validated through simulation testing. Findings demonstrated improved operational efficiency\, higher recycling accuracy\, and substantial cost savings. Addressing integration challenges\, infrastructure compatibility\, and public acceptance\, the study provides critical insights for urban planners\, policymakers\, and stake-holders. This work significantly contributes to the discourse on sustainability and smart city initiatives\, highlighting technological innovation as pivotal in solving contemporary environmental management issues. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:ea49aeb498aa8f92e8e6aa2174fdda9e URL:http://5thworldconferenceoninformations.sched.com/event/ea49aeb498aa8f92e8e6aa2174fdda9e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Enhancing Trust in the Cloud: A New Reputation-Based Model Outperforms Existing Solutions DESCRIPTION:Authors - Akheel Mohammed\, Sameera Khanam\, Ayesha\, Mohammed Shah Alam Rasool Khan Abstract - The proliferation of cloud computing presents a significant challenge for enterprises: entrusting mission-critical data to remote service providers. The widespread adoption of cloud services is fundamentally hampered by a lack of robust and reliable trust evaluation mechanisms. To address this critical obstacle\, this paper introduces a novel reputation-based trust model designed to accurately assess the trustworthiness of Cloud Service Providers (CSPs). Our proposed model uniquely integrates three key metrics: direct customer feedback\, historical server rejection rates\, and real-time server workload. A specialized trust evaluation algorithm processes these inputs to generate a comprehensive reputation score. Experimental results validate the efficacy of our approach\, demonstrating a more efficient and accurate evaluation of CSP trustworthiness compared to existing models. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:297bd747b071c2341c020a21969ced95 URL:http://5thworldconferenceoninformations.sched.com/event/297bd747b071c2341c020a21969ced95 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Fog Computing through the lens of ResearchRabbit - A Citation-Based Literature Mapping Tool DESCRIPTION:Authors - Ashwini Matange\, Jibi Abraham Abstract - Major component of research is searching for relevant publications in the domain of research from varied sources\, exploring them\, organizing them and finding interconnections between them. Different platforms ranging from Google Scholar\, PubMed\, IEEE Xplore\, ScienceDirect\, Springer are to be visited and explored to find research papers in the relevant field of the researchers. Research Rabbit is a free to use literature mapping tool that provides a one stop venue to locate papers of interest effortlessly with effective visualizations and smooth navigation. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:7862461217d43c76f5301400648437ff URL:http://5thworldconferenceoninformations.sched.com/event/7862461217d43c76f5301400648437ff END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Improving Fruit Detection and Counting using RetinaNet Model DESCRIPTION:Authors - Seema Shrawne\, Aishwarya Jadhav\, Saniya Gupte\, Sayali Panch\, Sakshi Thombre\, Vaibhav Dhore\, Vijay Sambhe Abstract - Accurately detecting and counting fruits is crucial for improving yield estimates in Precision Agriculture. However\, challenges such as varying fruit types\, overlapping objects\, and cluttered backgrounds make this task difficult. In this study\, we use RetinaNet\, a deep learning model known for detecting dense objects\, to address these issues. By replacing its ResNet50 backbone with SEResNet18\, we improve both accuracy and speed\, increasing mAP by 1.65%at IoU 0.5 and 1.79%at IoU 0.7. We also fine-tune the model using Differential Evolution to optimize anchors\, further boosting mAP by 0.61% and 7.3% at IoU 0.5 and 0.7\, respectively. Our enhanced model performs better on KFuji apples\, mangoes\, and holly fruits\, while the default model slightly outperforms ours on strawberries and oranges at higher IoU thresholds. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:a78ea62f90f699e525277d4de301f398 URL:http://5thworldconferenceoninformations.sched.com/event/a78ea62f90f699e525277d4de301f398 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:PathoVision: Multimodal Deep Learning for Advancing Pathology Imaging with Explainable Artificial Intelligence DESCRIPTION:Authors - \;Meeradevi\, Maria Rufina P\, Prathik B\, C S Parthasarathy\, Janya V\, Neeha Ritvika Mandava\nAbstract - \;PathoVision is an AI-powered framework that enhances cancer diagnosis by integrating histopathology images with clinical text using multimodal learning. Unlike traditional systems focused solely on image analysis\, it employs the PLIP model to generate combined visual-text embeddings for more accurate and contextual understanding. A custom decoder pro- cesses these embeddings to classify cancer subtypes\, while Grad- CAM provides interpretable heatmaps\, ensuring transparency in decision-making. Designed for use in clinical diagnostics\, research\, and education\, PathoVision addresses the limitations of manual pathology—such as subjectivity and time constraints—by offering a reliable\, interpretable\, and accessible solution. This framework represents a significant advancement in computational pathology\, blending modern AI with traditional diagnostics to support expert pathologists and improve patient outcomes. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:211b8e102332c78cc021d3925d326e91 URL:http://5thworldconferenceoninformations.sched.com/event/211b8e102332c78cc021d3925d326e91 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Quality Assurance in Focus: Implementation of Quality Culture in a Pangasinan State University DESCRIPTION:Authors - And Julie D. Rosal\, David Livingstone T. Ramos\, Randy Joy M. Ventayen Abstract - This study explores the quality assurance (QA) practices of Pangasinan State University (PSU) from 2016 to 2025\, emphasizing key strategies that enhanced its national and global reputation. Using a multi-method approach—including literature review\, surveys\, and interviews\, examines stake-holder perceptions\, institutional challenges\, and achievements in quality assurance recognition\, and improved international rankings. The findings highlight the importance of strong leadership\, continuous improvement\, faculty development\, and stakeholder engagement in fostering a culture of quality. These elements have strengthened PSU’s quality management system and its responsive-ness to academic and institutional demands. As a forward strategy\, the study presents a five-year roadmap for 2026–2030 focused on sustaining quality through digital transformation\, global benchmarking\, research-driven planning\, and performance-based evaluation. This roadmap is intended to solidify PSU’s status as a globally competitive university and offers practical insights for other state universities aiming to institutionalize QA and improve their academic standing at both national and international levels. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:22c317841b22a83e262831bff52b94ba URL:http://5thworldconferenceoninformations.sched.com/event/22c317841b22a83e262831bff52b94ba END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Quality Assurance Information System for State Universities and Colleges in the Philippines DESCRIPTION:Authors - David Livingstone T. Ramos Abstract - Quality assurance (QA) in higher education is a critical mechanism for promoting academic excellence\, institutional ac-countability\, and societal impact. State Universities and Colleges (SUCs) in the Philippines serve as gateways to education for under-served regions but face significant challenges in maintaining and im-proving quality due to the absence of standardized frameworks\, reliance on manual processes\, and limited technological integration. These issues hinder their efficiency\, compliance with accreditation standards\, and ability to respond to evolving educational demands. This study examines the role of a Quality Assurance Information System (QAIS) as a solution for addressing these challenges. Employing a literature review methodology\, it evaluates current QA practices in SUCs and identifies gaps\, such as fragmented processes\, inconsistent standards\, and insufficient data management capabilities. The research emphasizes the potential of QAIS to streamline processes\, automate routine tasks\, and provide real-time data for evidence-based decision-making. Key components of an effective QAIS include modular design for scalability\, compliance with international standards\, user-friendly interfaces\, and robust analytics for monitoring and continuous improvement. By implementing QAIS\, SUCs can align their practices with global benchmarks\, enhance stakeholder engagement\, and improve institutional performance. The study also highlights challenges in adopting QAIS\, including resource limitations and resistance to change\, and proposes strategies to mitigate these barriers. The findings offer actionable recommendations for SUCs to implement and scale QAIS effectively\, aligning with national and international quality standards while addressing local needs. By leveraging QAIS\, SUCs can enhance their competitive-ness\, improve educational outcomes\, and contribute to broader national development goals. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:f55ea2423ade56e319c63b1f778e5ede URL:http://5thworldconferenceoninformations.sched.com/event/f55ea2423ade56e319c63b1f778e5ede END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:ROLE OF FIN-TECH IN IT AND CORPORATE SECTOR AND SUSTAINABLE DEVELOPMENT DESCRIPTION:Authors - Pravitha N R\, Sumedha N Varma Abstract - This study reflects the pivotal role of financial technology (Fin-tech) in reshaping the IT and Corporate sectors while playing a role in achieving sustainable development. Fintech has evolved into a significant role as a game changer\, driving innovation in financial contribution through digital platforms\, blockchain technology\, artificial technology\, and big data analytics. In the IT sector\, Fintech facilitates secure\, efficient transactions and enhances digital infrastructure\, leading to improved service delivery and client engagement. Within the corporate domain\, it streamlines operations\, increases financial inclusion\, and supports strategic decision-making. In addition\, the integration of Fintech services with principles of sustainability is enhancing green finance and promoting efficient digital solutions. This paper studies the factors affecting the adoption of fin-tech services and how sustainable development goals are achieved by adopting fin-tech services. By using regression analysis\, the study expresses that Digital Financial Literacy and Perceived Performance Expectancy have a positive impact on the Behavioural Intention in adopting fintech services. The analysis further states that the actual use of fin-tech services plays a vital role in promoting sustainable development. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:5bbc2448635eca4070268a8d3f0d73f1 URL:http://5thworldconferenceoninformations.sched.com/event/5bbc2448635eca4070268a8d3f0d73f1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Supervised Machine Learning-based Optimal Media Mix Modelling to Evaluate the Sales Performance DESCRIPTION:Authors - Sasini Gandhari Dabare\, Indra Mahakalanda\, Prasanga Jayathunga\, Nathali Fernando Abstract - Media Mix Modeling (mMM) is a data-driven analytical approach that quantifies the influence of multiple advertising channels on sales performance while adjusting for external factors such as seasonality and economic conditions. This study explores machine learning-based mMM to predict weekly sales performance in the Sri Lankan home appliances industry by combining ad spending variables with external factors such as exchange rates and holidays. The study applies time series decomposition\, ad stock transformation\, and data normalization to capture delayed and nonlinear media effects. TimeSeriesSplit cross-validation was used to test four predictive models: Linear Regression\, XGBoost Regression\, Support Vector Regression (SVR)\, and Bayesian Ridge Regression\, along with key metrics for performance (MSE\, RMSE\, R² Score\, MAPE). The tuned XGBoost model had the best accuracy (R² = 0.9145\; MAPE = 2.87%)\, making it most useful for predicting. The findings demonstrate the importance of machine learning-enhanced MMM as an effective strategy for optimizing media spending and increasing advertising efficiency in competitive\, budget-constrained markets. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:71329f9bd621decee132c6e84a711820 URL:http://5thworldconferenceoninformations.sched.com/event/71329f9bd621decee132c6e84a711820 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Tax Compliance and Core Tax Administration System (CTAS) for MSMEs: Insights from a Qualitative Study DESCRIPTION:Authors - Hera Khairunnisa\, Nayla Nandhita Nuril Hadi\, Surya Anugrah\, Rochma Sudiati\, Windy Permata Suyono Abstract - First objective of this study is evaluating MSMEs tax compliance with Strengths\, Weaknesses\, Opportunities\, and Threats (SWOT) analysis. Second objective of this study is evaluating the role of Core Tax Administration System (CTAS) for MSME. The study uses a descriptive qualitative approach\, with semi-structured interviews with three tax consultants with extensive experience in MSME taxation. This study also employs the literature review approach. From the interview\, this study shows that MSMEs typically have straightforward cost structures given their simple business operations. Government support\, such as the reduction of the final tax rate for MSMEs from 1% to 0.5%\, is viewed as an opportunity in taxation. However\, the study highlights ongoing challenges in MSME operators' tax competence\, particularly their understanding of recent tax regulations and literacy in tax matters. This study also shows that the implementation of the Core Tax System serves as a strategic advancement in enhancing tax administration for MSMEs in Indonesia. By leveraging digital integration and automation\, the system aims to promote greater efficiency\, transparency\, and ac-countability in tax processes. CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:89ee71a893ea0b9ed052951a056c23fc URL:http://5thworldconferenceoninformations.sched.com/event/89ee71a893ea0b9ed052951a056c23fc END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:AI-Generated Music and Its Acceptance on Distribution Platforms: An Experiment from Production to Business Monetization DESCRIPTION:Authors - David Livingstone T. Ramos\, And Julie D. Rosal\, Randy Joy M. Ventayen\, Timothy Joshua M. Ventayen Abstract - This study look into the practical acceptance and compliance of AI-generated music on major digital distribution platforms\, including Spotify\, Apple Music\, and other popular online music stores. Leveraging advanced generative AI tools such as Udio and Suno\, the researchers created original musical tracks and submitted them for distribution. Although many platforms have explicit policies against the use or upload of AI-generated content\, all tracks produced through these tools were accepted without issue and made publicly avail-able through the distribution systems. This outcome reveals critical gaps in the enforcement of platform policies\, raising serious questions about the current ability of digital platforms to detect and regulate AI-generated content. The findings bring to light the ethical\, legal\, and economic challenges posed by the growing presence of generative AI in the music industry. In response\, the study recommends the implementation of more robust detection technologies\, trans-parent labeling of AI-generated works\, and the development of consistent regulatory frameworks to address the complexities of AI-driven creativity in the evolving digital music ecosystem. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:eafa4e4feedb12b94e2b3c5dba51a9e8 URL:http://5thworldconferenceoninformations.sched.com/event/eafa4e4feedb12b94e2b3c5dba51a9e8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:An Empirical Analysis of MCDM Techniques in Stock Market-Nifty 50 DESCRIPTION:Authors - Masood Ahmed Shariff\, Sushma R Abstract - In today’s complex financial environment\, identifying optimal stock investments is challenging. This study applies Multi-Criteria Decision-Making (MCDM) techniques to evaluate NIFTY 50 stocks using nine financial indica-tors\, including returns\, P/E ratio\, dividend yield\, and market capitalization. Daily data from April 2020 to March 2025\, sourced from the Prowess database\, was analyzed. The Entropy Weighting Method ensured objective assignment of metric importance. Four MCDM models—TOPSIS\, VIKOR\, SAW\, and COPRAS—were used to rank stocks. Ranking discrepancies led to the development of a hybrid model combining normalized ranks with entropy-based weights\, creating a composite ranking. Spearman’s rank correlation helped compare the models. The hybrid approach enhances ranking consistency and supports data-driven investment decisions. This methodology can also be ap-plied to sectoral or global equity markets\, offering a flexible tool for portfolio evaluation and financial analysis. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:4b435ca58c43e001aa9cb6118e380fc1 URL:http://5thworldconferenceoninformations.sched.com/event/4b435ca58c43e001aa9cb6118e380fc1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Bibliometric Analysis:E-Commerce Platform in Chemical Supply Chains DESCRIPTION:Authors - Tawsif Hasan Kirkire\, Smita Mehendale\, Ashish Thatte Abstract - This paper is bibliometric analysis of the academic literature related to e-commerce platforms within the chemical supply chain. From the 17 documents published between 2000 and 2025\, this study identifies inconsistent\, but off late accelerating\, research journey\, with a notable rise in publications and citations post-2020\, most likely influenced by the global imperative for digital transformation. Co-word analysis reveals "electronic commerce" as a central thematic node\, connecting traditional "sales" and "chemical industry" applications with emergent areas like "learning systems" and "chemical activation." The analysis highlights China's dominant intellectual contribution\, suggesting a concentrated epistemic center. Inspite of recent contributions from diverse sources\, the field displays significant temporal and thematic gaps\, particularly regarding sustainability and resilient practices\, alongside a uneven collaborative network. This study outlines critical future research directions\, promoting for the integration of AI/ML applications\, exploration of chemical manufacturing\, diversification into Global South economies\, and the adoption of enhanced methodological rigor to foster a more mature\, interconnected\, and impactful interdisciplinary research domain. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:a4ab98b5601fdae854a8f312ff4d831d URL:http://5thworldconferenceoninformations.sched.com/event/a4ab98b5601fdae854a8f312ff4d831d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Design\, Development\, and Acceptability of a Small-Scale Salt Vibrating Screen Classifier for Artisanal Salt Production DESCRIPTION:Authors - Juanito P. Maneclang Jr. Abstract - The Philippine salt industry\, particularly in culturally significant regions like Pangasinan\, has faced a steep decline due to a reliance on antiquated\, laborintensive production methods. This study addresses this challenge through a three-part objective-driven approach: (1) identifying the technological gaps in artisanal salt production through a comprehensive literature review and needs analysis\; (2) developing a prototype salt vibrating screen classifier with an integrated grinder to address these gaps\; and (3) evaluating the prototype's acceptability among experts and end-users. The methodology involved a systematic re-view of academic and industry literature\, which pinpointed a lack of appropriate-scale post-harvest machinery. A prototype\, fabricated from stainless steel and powered by a 5-horsepower motor\, was subsequently developed. The machine's acceptability was determined through a mixed-method evaluation with technical experts and salt farmers. The results from the evaluation demonstrated high acceptability\, with participants confirming the machine's robust performance\, efficiency in grinding and classifying salt\, and significant practical advantages over traditional methods. The study concludes that the developed prototype is a highly acceptable and viable technological solution that directly addresses the needs identified in the literature\, offering a means to enhance productivity and quality for Filipino salt farmers. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:46486bddb577968bcfc3f1b88de94374 URL:http://5thworldconferenceoninformations.sched.com/event/46486bddb577968bcfc3f1b88de94374 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Dynamic SLA Enforcement in Cloud Environments via ML\, Privacy Risk Scoring\, and NLP-Based Clause Generation DESCRIPTION:Authors - R. Komala\, B. R. Arun Kumar\, A. Shreyas Abstract - Service Level Agreements (SLAs) are essential for defining performance and compliance expectations in cloud computing ecosystems. However\, traditional SLA models often lack adaptability\, failing to address dynamic workloads\, evolving regulatory demands\, and rising cybersecurity threats. This study presents an adaptive SLA governance architecture driven by Machine Learning (ML)\, enabling predictive violation detection\, real-time compliance monitoring\, and dynamic policy adjustments. The system integrates legal frameworks such as GDPR\, ISO/IEC 27001\, NIST\, and India's DPDPA\, embedding enforceable standards into SLA logic. Our framework employs ML techniques including violation forecasting\, unsupervised anomaly detection\, privacy risk quantification\, and NLP-based clause synthesis\, creating self-adjusting\, legally resilient SLAs. In simulations with cloud workload datasets\, the system achieved 94% prediction accuracy for SLA breaches\, 98% anomaly detection\, and over 91% success in automated clause alignment. While promising\, broader testing in real-world deployments is needed to validate generalizability. This framework bridges regulatory obligations and dynamic service delivery through explainable\, transparent SLA orchestration. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:0ee04e5385f75d5c97ef8398e28644d1 URL:http://5thworldconferenceoninformations.sched.com/event/0ee04e5385f75d5c97ef8398e28644d1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Enhancing Cybersecurity Posture Through Comprehensive Threat Intelligence: Methods\, Challenges\, and Future Trends DESCRIPTION:Authors - Akshay Kumar\, Sudhir Agarmore\, Kumar Gaurav\, Edidiong Akpabio\, Akshat Jha Abstract - Cyber threats now come in an advanced form and\, therefore\, call for a proactive rather than a passive cybersecurity strategy. Threat intelligence helps to complement security defences through methodical acquisition\, analysis\, and utilization of information regarding competitors and new risks. This article gives an insightful review of the approaches to threat intelligence\, covering open-source intelligence (OSINT)\, closed-source intelligence\, monitoring of the dark web\, and live feeds of intelligence. We classify threat intelligence into strategic\, tactical\, operational\, and technical levels\, explaining their functions in cyber security architectures. Particular emphasis is given to the incorporation of artificial intelligence (AI) and machine learning (ML) in the automation of threat identification and intelligence analysis. In addition\, we address challenges of implementation\, including data glut\, verification\, and ethics. To provide real-world practicality\, we examine actual case studies demonstrating practical threat intelligence implementations in reducing ransomware\, blocking phishing\, and countering supply chain attacks. We also recommend enhancing intelligence sharing\, predictive analytics\, and automation to strengthen future threat intelligence systems. Through the integration of dynamic threat intelligence into security operations\, organizations are able to effectively detect\, analyze\, and block cyber threats beforehand\, ultimately fortifying their cybersecurity resilience as a whole. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:dfbc90c1f9d71a664a06d2224d5c838b URL:http://5thworldconferenceoninformations.sched.com/event/dfbc90c1f9d71a664a06d2224d5c838b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Harnessing Technology in Professional Education: An Inquiry into Pedagogical Practices and Governance Per-spectives in State Universities and Colleges in the Philip-pines DESCRIPTION:Authors - Romary Reyes Lincod Abstract - This paper provides an review of the pedagogical practices and governance perspectives related to technology integration in Philippine State Universities and Colleges (SUCs). The global pandemic served as a catalyst\, accelerating a system-wide shift from emergency remote teaching to a strategic push for sustained flexible learning\, underpinned by national policies from the Commission on Higher Education (CHED) and cross-agency collaborations. However\, a significant gap persists between ambition and institutional reality. This review examines four key domains: institutional governance and leadership\, pedagogical practices in the digital classroom\, the human element of faculty and student experiences\, and the foundational pillars of infrastructure and finance. Findings reveal a governance paradox where strategic planning is robust\, but leadership needs to translate vision into faculty competency. Pedagogically\, technology adoption outpaces deep integration\, with tools often used to replicate traditional methods. Faculty and students are caught in a "Cycle of Unpreparedness\," marked by skill gaps\, anxiety\, and infrastructural barriers. Foundational weaknesses\, including a pervasive digital divide and unstable funding models\, create a mismatch between the vision for digital transformation and the capacity for implementation. The paper concludes with multi-level strategic recommendations for policymakers\, SUC administrators\, and future research\, aimed at creating a more resilient\, equitable\, and innovative digital education ecosystem. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:0cf7c4491d0433b3fe8d9e027af7f565 URL:http://5thworldconferenceoninformations.sched.com/event/0cf7c4491d0433b3fe8d9e027af7f565 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Pangasinan Culture of Arts in Fabrics: A Beginning of a Cultural Identity and Technological Innovation in Fabrics DESCRIPTION:Authors - Caren C. Orlanda-Ventayen\, Renato E. Salcedo Abstract - The tangible heritage of a region\, particularly its textile traditions\, of-ten serves as a primary marker of its cultural identity. This literature review studies the role of fabric arts in the cultural expression of Pangasinan province in the Philippines. A systematic review of historical backgrounds\, cultural publications\, and recent news archives reveals a notable absence of a deeply rooted\, continuous\, and widespread indigenous textile weaving tradition for clothing in the province. Historically\, Pangasinan's material culture was characterized by non-textile crafts and a reliance on imported fabrics obtained through extensive trade networks. This historical context makes the contemporary situation particularly compelling. As of mid-2025\, Pangasinan is the site of new\, institution-ally-driven initiatives aimed at establishing a local textile industry. These projects are twofold: a technology-focused hub for developing bamboo-based textile fibers and a culturally-focused center for reviving the transplanted hand-loom weaving traditions of Cordilleran migrant communities. This paper argues that Pangasinan is not merely preserving a dormant craft but is actively designing a new and evolving cultural identity in fabric\, one that is uniquely shaped by the confluence of technological innovation\, cultural migration\, and institutional support. The findings suggest that Pangasinan offers a unique case study in the contemporary construction of cultural heritage. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:0ed0a1b3dcca5fb059e697a6fe14d35b URL:http://5thworldconferenceoninformations.sched.com/event/0ed0a1b3dcca5fb059e697a6fe14d35b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Technological Intervention by AutoCAD Teachers Implementing Online and Modular Learning DESCRIPTION:Authors - Claro S. Sison Jr. Abstract - The rapid shift to remote education has compelled a significant trans-formation in the teaching methodologies for technical subjects like AutoCAD. This paper investigates the technological interventions implemented by Auto-CAD instructors in response to the challenges of online and modular learning environments. The study adopts a mixed-methods approach\, beginning with a systematic literature review to identify prevalent challenges and technological solutions documented in academic and technical sources. This is followed by a local survey of 30 AutoCAD teachers in the Schools Division of Pangasinan I\, Philippines\, to assess the available technological resources\, their utilization rates\, and the specific challenges faced in a developing country context. Key findings from the literature indicate that while a plethora of advanced software\, platforms\, and tools are available\, their effective implementation is often hindered by issues such as the digital divide\, lack of institutional support\, and the inherent difficulty of teaching hands-on skills remotely. The local survey corroborates these findings\, revealing a heavy reliance on personal resources\, unstable internet connectivity\, and underutilization of advanced CAD-specific tools. The study reveals that successful interventions often involve a blend of synchronous and asynchronous technologies\, including video tutorials\, cloud-based CAD solutions\, and virtual reality simulations. A strong positive correlation (r = 0.785) was found be-tween the level of technological intervention and teachers' perceived instructional effectiveness. This research concludes by synthesizing the findings to provide a holistic view of the current state of AutoCAD education\, offering recommendations for educators\, institutions\, and policymakers to enhance the quality of technical instruction in remote settings. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:29643d5a907716897fa31219ef0420ec URL:http://5thworldconferenceoninformations.sched.com/event/29643d5a907716897fa31219ef0420ec END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:The Universal Power Elixir: A Techno-Economic Review and User-Centric Case Study of the USB-Integrated Laptop Charger Adapter DESCRIPTION:Authors - Corlito P. Cruz Abstract - The proliferation of portable computing devices has historically been accompanied by an equally diverse and incompatible array of proprietary power adapters\, creating significant issues for consumers and contributing to a growing electronic waste crisis. This scientific review charts the rise of the USB integrated laptop charger adapter as a pivotal solution to this long-standing issue. It presents an in-depth analysis of the technological underpinnings\, centered on the USB Power De-livery (USB-PD) specification\, that enable a universal charging standard. Key enabling technologies\, most notably the material science advancements of Gallium Nitride (GaN) wide-bandgap semiconductors\, are analyzed for their role in creating a new generation of compact\, highly efficient\, and intelligent power adapters. To ground this technological analysis in practical application\, this paper further presents a targeted case study involving a survey of Bachelor of Industrial Technology (BIT) students to identify tangible user needs. The results of this survey\, which indicated a strong demand for integrated USB ports on laptop chargers\, led to the development of a functional proof-of concept prototype\, validating the broader market trends dis-cussed. The paper examines the technical evolution of the USB-IF standards\, the current technoeconomic landscape\, and the persistent challenges in engineering and usability\, including protocol fragmentation and safety compliance. Finally\, this re-view looks to the future\, assessing the impact of the 240W Extended Power Range (EPR) of USB-PD 3.1 and the trajectory toward a truly universal and intelligent power ecosystem. It concludes that the USB-integrated adapter represents a critical\, user-driven inflection point in consumer electronics\, moving the industry from a fragmented past to a standardized\, efficient\, and interconnected future. CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:0267111353849a5e76e8d543432461c5 URL:http://5thworldconferenceoninformations.sched.com/event/0267111353849a5e76e8d543432461c5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:A Novel Machine Learning Ensemble Approach for Corrupt Data Packet Identification DESCRIPTION:Authors - Ramesh Chandra Poonia\, Vishal Singh Rathore\, Ajay Kumar Abstract - In contemporary network infrastructures\, ensuring the fidelity of data transmission is paramount for robust communication and security. The intrusion of corrupted data packets can severely degrade network efficiency\, resulting in critical data loss\, exploitable security gaps\, and suboptimal resource allocation. This paper indicates the significantly increase detection accuracy and system resilience by synergistically using the predictive capability of many machine learning paradigms especially. This paper employs sophisticated feature engineering to extract discriminative attributes from network packet headers and payloads\, followed by a refined ensemble learning strategy that leverages both stacking and boosting techniques for optimal classification performance. Compared to conventional single-model techniques\, evaluated on real-world network traffic datasets our model shows a significant increase in key performance measures. Here a pioneering hybrid machine learning ensemble framework designed for the precise identification and mitigation of corrupted data packets. Notably\, the ensemble framework excels in minimizing false positives\, enabling real-time packet analysis and bolstering network security. This study contributes to the evolution of intelligent\, adaptive network defense mechanisms\, providing a scalable and high-performance solution for safeguarding data integrity and mitigating the deleterious effects of corrupted data packets in modern\, high-throughput communication environments. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:cf5a160b9b86c3a9d5193d0ba5405a29 URL:http://5thworldconferenceoninformations.sched.com/event/cf5a160b9b86c3a9d5193d0ba5405a29 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:CNN-Powered Emotion Detection from Audio Recordings DESCRIPTION:Authors - Smit Patel\, Priyanka Patel Abstract - Speech Emotion Recognition (SER) plays a vital role in enhancing human-computer interaction by enabling machines to interpret and respond to human emotions. This study focuses on SER using the RAVDESS dataset\, emphasizing speech-only modalities. A comprehensive set of audio features including MFCCs\, chroma\, spectral contrast\, tonnetz\, and wavelet transforms is extracted\, and the performance of four deep learning models— CNN\, LSTM\, BiLSTM\, and CNN-LSTM—is evaluated. Among them\, CNN achieves the highest accuracy (68.37%)\, with strong F1-scores across several emotion classes. The results underscore the effectiveness of spatial feature extraction in emotion classification and suggest further enhancements using attention mechanisms and transformer-based models. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:95fafeb650a8883babeb9dfda847e4d0 URL:http://5thworldconferenceoninformations.sched.com/event/95fafeb650a8883babeb9dfda847e4d0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Combinatorial Analysis of Multi-Domain Feature Sets for Regional Monsoon Rainfall Prediction DESCRIPTION:Authors - Sundar S\, Prathilothamai M Abstract - Accurate prediction of monsoon rainfall remains a persistent challenge due to the intricate interplay among meteorological conditions\, oceanic influences\, and broader climatic patterns. While significant effort has been devoted to improving model architectures\, the effect of input feature composition on prediction accuracy has received relatively less attention. This study addresses that gap by conducting an extensive empirical evaluation of 2\,047 feature group combi-nations\, systematically derived from eleven curated sets of climate-related variables. Using a hyperparameter-tuned XGBoost model\, each configuration was evaluated independently to assess the predictive contribution of domains such as lagged climate indices\, cyclical temporal encodings\, and event-based indicators. The results show that model performance improved significantly from an R² of 0.5801 (RMSE: 10.8999 mm\, MAE: 4.9009 mm) using only meteorological features to an R² of 0.7606 (RMSE: 8.2297 mm\, MAE: 3.8752 mm) when combined with oceanic and climatic inputs\, particularly lagged MJO and ENSO indices and temporal signals. These insights reinforce the value of domain-informed feature fusion and provide a replicable approach to enhancing monsoon prediction models through thoughtful feature group design and empirical validation. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:b73e9092f7310e4ac65dc17a6faae077 URL:http://5thworldconferenceoninformations.sched.com/event/b73e9092f7310e4ac65dc17a6faae077 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Detecting Bank Frauds: A unified solution in a fragmented domain DESCRIPTION:Authors - Atharva Godkhindi\, Anjali Naik Abstract - Fraud detection in financial transactions presents a persistent challenge due to extreme class imbalance and evolving attack patterns. While several machine learning (ML) and deep learning (DL) methods have shown promise\, these solutions are fragmented and use traditional methods to address the severe class imbalance\, leading to models with inflated metrics and poor generalization. In this study\, we propose a unified ML-DL-XAI pipeline that integrates Variational Autoencoders (VAE) not only for data augmentation but also for feature engineering. Unlike traditional resampling\, the VAE enables representation learning that preserves underlying data distributions while mitigating overfitting. Our pipeline incorporates interpretable machine learning models alongside neural networks to ensure both high performance and explainability. Empirical evaluations on a large-scale financial dataset demonstrate superior and reliable performance\, that achieves an accuracy of 99.6%\, a precision of 92%\, and a recall of 85%\, outperforming several recent benchmarks. By combining augmentation\, feature engineering\, and explainability in a single pipe-line\, this work offers a robust and practical answer for real-world fraud detection applications. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:bf1b3bba10159e1c48234f7d8c36e67c URL:http://5thworldconferenceoninformations.sched.com/event/bf1b3bba10159e1c48234f7d8c36e67c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:From Prompt to Pedagogy: A Conceptual Framework for Structured AI Dialogue and Value-Based Learning DESCRIPTION:Authors - Gitanjali S. Poothuvallil\, Dhanya Manayath Abstract - This paper explores the use of generative AI in social entrepreneurship education through the REFLECT model—a justice-informed ethics framework emphasizing participatory\, empathic\, and power-sensitive reasoning. Using ChatGPT\, we simulated context-rich dialogues based on real-life renewable energy cases to examine ethical dilemmas\, systemic failures\, and power dynamics. Through iterative refinement\, we developed a prompt template capable of producing realistic\, grounded dialogues. These were evaluated on three criteria: depth of empathy\, systems complexity\, and presence of ethical tension. Findings suggest that integrating the REFLECT framework enhanced the pedagogical quality of AI-generated cases\, aligning them more closely with the aims of values-based social entrepreneurship education. The approach demonstrates how generative AI can foster critical thinking and ethical reflection\, helping students engage with complex social justice and sustainability issues. Our study presents a novel application of AI in the classroom\, showing its potential to ad-vance pedagogy in socially responsible entrepreneurship. The paper concludes by exploring the future potential of integrating AI into educational pedagogy\, highlighting both its ethical implications and the ongoing need for refinement in its application to ensure responsible and effective use in teaching and learning environments. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:018322bcd4c6515f419abbacf513496a URL:http://5thworldconferenceoninformations.sched.com/event/018322bcd4c6515f419abbacf513496a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Graph-NIDS: Detecting Network Intrusions via HGT-based Edge Classification on Network Traffic Graphs DESCRIPTION:Authors - Bharateesha lvn\, J Vignesh\, Jabez Lawrence G\, Bhaskarjyoti Das Abstract - The emergence of sophisticated cyber threats calls for the evolution of sophisticated Network Intrusion Detection Systems (NIDS). Even though graph-based approaches have been promising\, they have mostly was concerned with node classification to determine the bad actors. This paper provides a new framework that recontextualizes the NIDS challenge as a marginal concern classification problem on a heterogeneous graph. We assume that classifying the boundaries (relations) between network objects as harmful or benign offers a more timely and efficient means of intrusion detection. In order to achieve this\, we build a heterogeneous graph from network flow data and employs a Heterogeneous Graph Transformer (HGT) model\, which is designed to maintain the integrity of instructional and semantic detail formation present in such graphs. The model is trained and tested on a large dataset from the UNSW-NB15 dataset. Our experiments show that the edge classification method greatly outperforms a conventional node classification baseline\, achieving superior accuracy\, precision\, and recall. These results illustrate the potential of edge-centric GNN models for constructing more efficient and complete network intrusion detection systems. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:d43e088e2f41597cefe0692ad4581dc1 URL:http://5thworldconferenceoninformations.sched.com/event/d43e088e2f41597cefe0692ad4581dc1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Impact of Cryptocurrency in this Digital World: A Bibliometric Analysis DESCRIPTION:Authors - Poojitha Panchakarla\, Sarvani Kocherlakota Abstract - Cryptocurrency has emerged as a prominent research topic in recent decades\, with numerous findings published in leading international journals. To investigate its current research landscape and emerging trends\, we conduct a Bibliometric analysis by using R software 4.5.0\, and VOSviewer to identify the research trend\, emerging topics\, and collaborations among countries\, authors\, documents and the contributing academic journals during the study period. Lecture Notes in Networks and Systems is having the highest publications and IEEE Access is having the most cited document. Kumar A is the most contributing author and Song H is the most cited author. India is the most cited country and contributing country. By research gap analysis\, the future direction in the domain of cryptocurrency can be machine language forecasts\, sustainable energy\, and regulatory framework. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:4124938957bb2c40310ec48cb28702e4 URL:http://5thworldconferenceoninformations.sched.com/event/4124938957bb2c40310ec48cb28702e4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Optimisation of Scheduling the Production of EV Batteries on Parallel Processors DESCRIPTION:Authors - Jiri David\, Jan Fabry\, Josef Bradac Abstract - With the growing importance of electromobility\, the efficient planning in the production of lithium-ion batteries has become a critical factor in maintaining competitiveness. This article focuses on the optimisation of batch scheduling on parallel processors – an essential challenge in a complex manufacturing environment characterised by hybrid (sequential-parallel) processes\, technological dependencies\, and high variability. Based on a formal mathematical model of the P|batch\, rj \, sj | Cmax type\, a method is proposed that integrates batch planning\, nonlinear setup times\, multi-objective optimisation\, and robust scenariobased control. The model was implemented in the AMPL (A Mathematical Programming Language) environment and tested using real production data from battery manufacturing at the famous production company. The results demonstrate significant improvements over conventional methods (e.g.\, FCFS\, LPT)\, including a reduction in production time of up to 10%\, a 6% decrease in setup operations\, and an increase in capacity utilisation (OEE) by more than 10%. Moreover\, reductions in energy consumption and enhanced schedule predictability were observed. The model is designed to be integrable with MES/ERP systems and offers both scalability and adaptability across varying production scenarios. The findings confirm that the combination of a rigorously defined optimisation model and operationally validated data can significantly enhance planning efficiency in battery system manufacturing for electric vehicles. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:d53400453c6f4055ec91cbefe6082c5b URL:http://5thworldconferenceoninformations.sched.com/event/d53400453c6f4055ec91cbefe6082c5b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Public Sector Accounting Student’s Views on Nonprofit Organizations Accounting Information System Using IS Success Model DESCRIPTION:Authors - Etty Gurendrawati\, Hera Khairunnisa\, Aji Ahmadi Sasmi\, Andrew Saw Tek Wei\, Nayla Nandhita Nuril Hadi\, Rohadatul Aisy\, Shoofiyah Nur Aliifah Abstract - This study examines how Information Quality (IQ)\, System Quality (SQ)\, and Service Quality (SeQ) influence Use (U) and User Satisfaction (US). It also investigates the impact of U on US\, and how both US and U affect Net Benefit (NB) among Public Sector Accounting students at an Indonesian State University. Data from 114 student questionnaires were analysed using SEM PLS by SMART PLS 4. Seven of nine hypotheses were supported. SQ significantly impacted U and US\, while SeQ significantly affected U. Both U and US positively influenced NB\, with US having the strongest effect. The insignificant role of IQ suggests students prioritize system functionality and support over data output. These findings emphasize that enhancing system and service quality drives user satisfaction and use\, ultimately boosting the perceived net benefits of nonprofit accounting information systems. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:ed5568b2fac10e9574837b65a9d6be77 URL:http://5thworldconferenceoninformations.sched.com/event/ed5568b2fac10e9574837b65a9d6be77 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Understanding Consumer Behavior in Sustainable Avia-tion: An Integrated Theoretical Model Examining Envi-ronmental Values\, Technology Acceptance\, and Travel Context DESCRIPTION:Authors - Rhytheema Dulloo\, Kirti Biradar\, Srijaa M Abstract - The aviation industry faces mounting pressure to achieve net-zero carbon emissions by 2050\, yet passenger adoption of sustainable aviation practices remains inconsistent\, highlighting the urgent need to understand the psychological and behavioral factors influencing passenger decision-making in sustainable aviation contexts. This study develops and tests an integrated theoretical framework combining Theory of Planned Behavior (TPB)\, Value-Belief-Norm (VBN) theory\, and Technology Acceptance Model (TAM) to explore how environmental values\, technology perceptions\, and travel context shape attitudes\, intentions\, and behaviors. A quantitative cross-sectional study of 847 airline passengers across seven metropolitan hubs in India was conducted. Environmental values emerged as the strongest predictor of attitudes toward sustainable aviation behavior (β = 0.42\, p < 0.001)\, while the integrated model explained 62% of variance in behavioral intentions and 34% in actual behavior. Perceived usefulness and ease of use were found to significantly affect sustainable aviation technology acceptance and TPB constructs effectively predicted behavioral intention and actual behavior towards sustainable aviation\, with per-sonal norms adding further explanatory power. Significant differences were found between business and leisure travelers\, with leisure travelers showing stronger relationships between environmental values and attitudes (p = 0.032) and between intentions and behavior (p = 0.007)\, while the intention-behavior gap was more pronounced among business travelers\, highlighting structural barriers to sustainable aviation adoption. The findings suggest that airlines should adopt differentiated strategies\, with sustainability messaging emphasizing personal environmental responsibility for leisure travelers\, while structural interventions such as corporate partnerships and policy changes are needed for business travelers to address organizational barriers. This study provides the first comprehensive integration of TPB\, VBN\, and TAM theories in sustainable aviation contexts\, offering novel insights into travel context moderation effects and actionable guidance for industry stakeholders seeking to enhance passenger adoption of sustainable aviation practices. CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:0d0c56e2914df3c0fa4a4cd9f71f70b4 URL:http://5thworldconferenceoninformations.sched.com/event/0d0c56e2914df3c0fa4a4cd9f71f70b4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:A Holistic Review of Deep Learning Methods in Speech Emotion Recognition DESCRIPTION:Authors - Shital Khaparde\, Rakesh Verma Abstract - In the field of Speech Emotion Recognition (SER) the research is gaining more attention\, with the ability to augment human-computer interaction by allowing systems to recognize emotional states from speech. The research area has evolved significantly\, with most of the advancements being due to deep models of learning which are particularly good at extracting subtle patterns from raw audio data directly. The review discussed the current research\, with focus on the use of prevalent deep learning architectures—e.g.\, Long Short-Term Memory networks (LSTM)\, Recurrent Neural Networks (RNN)\, Convolutional Neural Networks (CNN)\, \, and hybrid models like CNN-BiLSTM—for SER tasks. The area of research has come a long way\, some of the major challenges still persist. The design of dependable SER systems is still beset by issues such as imbalanced datasets\, the ongoing difficulty of effective feature selection\, noise sensitivity\, and computational efficiency problems. Although deep learning has advanced remarkably\, the review emphasizes that significant obstacles must still be overcome before the area can provide consistently trustworthy performance in actual situations. This paper proposes several future research including broadening and diversifying datasets\, increasing the cross-linguistic strength of the model\, and better real-time system performance. CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:23179b417e51b3aed2dc981ac87faf2b URL:http://5thworldconferenceoninformations.sched.com/event/23179b417e51b3aed2dc981ac87faf2b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:AI-Enabled Resource Synergy Model (AI-RSM): A Novel Framework for Resource Resilience for Smart Cities DESCRIPTION:Authors - Sharon Elizuba Koshy\, Shyam A.V\, Padmadas Sundaram\, Sofia Rani Shaik Abstract - The growing complexity of urban ecosystems\, fueled by rapid population expansion\, is intensifying the challenges cities face in achieving sustainability\, circularity\, and resilience. This evolving landscape demands innovative management approaches that integrate technological advancements and resource optimization strategies to support resilient urban development. This research proposes a management-oriented framework for Artificial Intelligence enabled Industrial Symbiosis networks within smart cities\, focusing on enhancing resource recovery and establishing closed-loop systems. By leveraging AI technologies of predictive analytics\, dynamic matchmaking\, and optimization algorithms\, the framework aims to identify\, coordinate\, and scale symbiotic partnerships among industries\, utilities\, and municipal stakeholders. Rather than emphasizing the technical development of AI algorithms\, the study addresses strategic governance models\, stakeholder engagement mechanisms\, and policy interventions that facilitate the effective integration of AI in managing industrial symbiosis networks. Drawing on principles of the circular economy and smart infrastructure governance\, this research highlights how AI can drive adaptive and resilient resource flows within urban environments. By bridging technological innovation with strategic management practices\, the study contributes to the evolving discourse on sustainable smart city development and offers actionable insights for policymakers\, city planners\, and infrastructure managers. CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:06847046a2aa30c095d4532d1cc4c8e3 URL:http://5thworldconferenceoninformations.sched.com/event/06847046a2aa30c095d4532d1cc4c8e3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Breaking the TAM Barrier: How Personal Innovativeness Enhances ICT Acceptance Among University Students DESCRIPTION:Authors - Mohar Banerjee Biswas\, Srikant Das Abstract - Individuals display different levels of innovativeness towards technology and this innovativeness is a crucial personality trait to understand adoption behavior. Personal Innovativeness in Information Technology (PIIT) has emerged as a strong personality trait that influences the adoption behavior towards Information and Communication Technologies (ICT) in higher education. This research analyses the influence of PIIT on the perception of utility and simplicity of ICT by higher education students. The study extends the Technology Acceptance Model (TAM) by adding PIIT and analyses how it affects the perceived usefulness (PU)\, perceived ease of use (PEOU) and subsequent behavior intention (BI) towards ICT adoption. For the data collection\, 493 sample data were obtained from university students using an online structured questionnaire and was processed using Structural Equation Modeling (SEM). The findings of the study reveal that PIIT significantly impacts the PU and PEOU\, indicating that students who are more innovative will view ICT as beneficial to their academic task and will find it easy to use. PIIT also has an indirect influence on BI via the construct of PU and PEOU\, emphasizing its mediating role. The findings propose that developing PIIT amongst learners can improve students' preparedness to adopt ICT in academics. The research has important implications for stakeholders in developing specialized interventions\, training\, and curriculum designs that nurture creative mindsets\, thus enabling stronger integration of technology in learning. CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:53aaae915d486201abb8da96b2b6ef9c URL:http://5thworldconferenceoninformations.sched.com/event/53aaae915d486201abb8da96b2b6ef9c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Deconstructing Barriers to Digital Well-Being Among Gen Z DESCRIPTION:Authors - Santanu Mandal\, Srinija M\, Sukruthi M Abstract - This study investigates the structural barriers hindering digital well-being among Generation Z (Gen Z) through an integrated lens of Self-Determination Theory (SDT) and Cognitive Load Theory (CLT). Using a cross-sectional survey conducted between June and July 2025\, 126 valid responses were collected from Indian Gen Z participants\, comprising students and early-career employees. Ten barriers—including lack of awareness\, absence of digital literacy\, mixed media messages\, platform design addiction\, and peer pressure—were examined for their interrelationships using Interpretive Structural Modelling (ISM) and MICMAC analysis. Results reveal that foundational barriers such as lack of awareness\, absence of digital literacy\, and mixed media messages act as high-driving factors\, creating cascading effects on dependent barriers like inconsistent sleep patterns\, low perceived control\, and productivity guilt. From the SDT perspective\, these drivers undermine autonomy and competence\, while CLT explains how cognitive overload from addictive design features exacerbates maladaptive digital behaviours. The findings highlight the need for multi-stakeholder interventions—spanning policy\, education\, workplace culture\, and ethical platform design—to address root causes and promote sustainable digital wellness. This research advances theoretical integration between SDT and CLT\, offering a diagnostic framework for targeted\, systemic interventions aligned with SDG 3 and SDG 12. CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:b7b104e7aafb0c571099a5bda274e5c4 URL:http://5thworldconferenceoninformations.sched.com/event/b7b104e7aafb0c571099a5bda274e5c4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Dependency of Sentiment on its aspect using Large Language Model DESCRIPTION:Authors - Rupsa Sarkar\, Jaydev Mishra Abstract - Natural language processing (NLP) has several key applications\, including sentiment analysis (SA). SA can bed escribed as a procedure that identifies the polarity of a sentence as well as its goal through analysis. SA is now the most active NLP research area. Aspect-based sentiment analysis\, which is a subset of SA\, is the process of examining a sentence's structure and determining its polarity. This field has been grown because now people feel free to share their thoughts\, opinions\, expressions. Internet\, social media are now the massive resource of opinion assuming. In this paper\, we have used Sem Eval 2014 task 4 dataset to focus on Aspect-based Sentiment Analysis (ABSA) problem. We have focused on previous work Based on Aspect-based Sentiment Analysis and Some work of Sentiment Analysis based on conversational data. We have used GPT2 for this task. CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:f71c39a636e8a10866087a6f4458f46e URL:http://5thworldconferenceoninformations.sched.com/event/f71c39a636e8a10866087a6f4458f46e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:EVALUATING THE APPROPRIATENESS OF STATISTICAL TECHNIQUES IN GRADUATE RESEARCH: A DIAGNOSTIC APPROACH DESCRIPTION:Authors - Mark Anthony C. Ochoa\, Aloysius J. Aurelio\, Stephan Kupsch Abstract - This sub-study evaluates the application of descriptive and inferential statistics in graduate research at DMMMSU-CGS. Findings show that while nominal and interval/ratio scales are often treated with appropriate measures (frequency counts and means)\, ordinal data is frequently misrepresented using the mean instead of median or mode. Such lapses compromise validity and highlight gaps in statistical literacy. This misuse underscores the need for statistical diagnostics prior to test selection and the inclusion of assumption checks in research guidelines. Moreover\, analysis of appropriateness and accuracy revealed that while proper methods generally produce accurate results\, some accuracy still arises from misapplied tools due to compensating factors. These findings stress the importance of enhanced statistical training and methodological rigor. . . . CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:4fb732716fe31a452b6c1481d30f62b7 URL:http://5thworldconferenceoninformations.sched.com/event/4fb732716fe31a452b6c1481d30f62b7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:From Prompts to Persuasion: Parameter-Efficient Adaptation of Open LLMs for Privacy-Aware Email Marketing DESCRIPTION:Authors - Jordan Cardenas\, Fabian Cardenas\, Marcos Levano\, Billy Peralta Abstract - In today’s digital economy\, where personalization has become a cornerstone of effective marketing strategies\, companies face the dual challenge of increasing advertising impact while safeguarding sensitive customer information. Despite the rapid progress of large language models (LLMs)\, existing commercial solutions often neglect the integration of synthetic data to reduce privacy risks and enhance adaptability\, leaving organizations dependent on external providers. To address this gap\, our work fine-tunes open-source LLMs (LlaMa2\, Mistral\, and Zephyr) with synthetic datasets generated via GPT\, aiming to produce customized marketing emails tailored to demographic and behavioral features. This thesis demonstrates not only the feasibility but also the competitiveness of such models by evaluating outputs with standard metrics (BLEU\, ROUGE) and human-like scoring through GPT-4\, showing that open-source models can approximate the performance of proprietary alternatives at significantly lower cost. The results confirm that fine-tuned LLMs with synthetic data represent a viable solution for enterprises seeking efficiency\, personalization\, and internal control of data. CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:0e3b5bcd55dd4e489f24def4bdd7ea4b URL:http://5thworldconferenceoninformations.sched.com/event/0e3b5bcd55dd4e489f24def4bdd7ea4b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Liberty to Equality: Hotel Management Application Level of Diversity Management in Selected Department of Tourism Accredited Hotels in Pangasinan DESCRIPTION:Authors - Rricky Tim Solomon Sison\, Romary Reyes Lincod Abstract - Diversity management has become a strategic priority in the hospitality industry\, particularly in regions marked by increasing demographic variation. This study investigates the perceived effects of diversity management on the work environment in Department of Tourism (DOT) accredited hotels in Western Pangasinan\, Philippines. It also examines the relationship between administrative diversity management application and employees’ experiential perceptions. This quantitative-descriptive research employed an adapted and expert validated instrument\, refined through pilot testing. Using purposive and stratified sampling\, data were collected from 53 participants (10 supervisors/managers and 43 employees) across five DOT-accredited hotels. Four sub-variables were examined: employee engagement\, creativity and innovation\, stereotyping and bias\, and employee retention. Analytical tools included mean\, average weighted mean (AWM)\, one-way ANOVA\, and Pearson correlation. The study revealed that diversity management was perceived to be highly effective\, particularly in fostering stronger employee engagement and enhancing creativity in the work-place. Overall\, its impact on the organizational environment was regarded as very positive. Nevertheless\, the findings also indicated that administrative strategies showed a weak and statistically non-significant relationship with employee perceptions\, suggesting that structural approaches alone may not be sufficient to shape employees’ views. Among the demographic factors considered\, marital status emerged as the only variable with a meaningful influence\, highlighting its relevance in understanding how diversity initiatives are experienced within the hospitality context. The study suggests a disconnect between diversity policies and their perceived impact\, highlighting the need for inclusive implementation. Limitations include the small\, localized sample. The findings emphasize the im-portance of participatory diversity planning\, inclusive leadership training\, and institutional mechanisms to ensure meaningful and sustainable diversity out-comes in hotel organizations. CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:e09ef546367317bd49588d58e7abc764 URL:http://5thworldconferenceoninformations.sched.com/event/e09ef546367317bd49588d58e7abc764 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Terra INVicta: A browser-based adaptive game for cognitive training DESCRIPTION:Authors - Sebastian Carrasco\, Pablo Schwarzenberg\, Marcos Levano\, Carla Taramasco\, Billy Peralta Abstract - In an era where rapid\, accurate keyboarding underpins virtually every academic\, professional and everyday digital interaction\, conventional drill-based tutors still struggle to sustain user engagement and to adapt difficulty in real time. Addressing this gap\, we present Terra INVicta\, a browser-native serious game that defends Earth from procedurally generated “cosmic” threats only when the player types their associated words correctly\, thereby combining cognitive processing and motor skills practice in an engaging and accesible way. This paper details the game’s design workflow and a first-round evaluation of its gameplay mechanics and adaptive-difficulty engine\, which modulates challenge through a mixed time–score progression factor. Initial tests indicate that Terra INVicta delivers fluid animation\, near-instant keystroke-to-action responsiveness\, and sustains a “flow” state across diverse player abilities\, confirming its viability as a cognitive training game. Beyond validating its educational value\, we highlight lessons learned and propose future work—including their application as a tool for cognitive assessment and improvement of cognitive and motor-skills in older adults. An interactive prototype is available at https://inverosimilitudes.github.io/ TerraINVicta/. CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:a0b0e4689ead9fb8c3bdb120f4476b66 URL:http://5thworldconferenceoninformations.sched.com/event/a0b0e4689ead9fb8c3bdb120f4476b66 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T191500Z DTEND:20261018T211500Z SUMMARY:Unmanned Aerial Vehicle Navigation Using Map-Based Localization DESCRIPTION:Authors - Sanjeeb Prasad Panday\, Ravi Gautam\, Basanta Joshi\, Aman Shakya\, Anunaya Pandey Abstract - The proposed approach focuses on autonomous UAV (Unmanned Aerial Vehicle) navigation and obstacle detection using only visual sensors specifically\, the on-board front camera. Unlike traditional methods that rely on multiple sensors (e.g.\, LiDAR\, radar\, or GPS)\, this vision-based system aims to reduce hardware complexity and cost while maintaining robust performance in diverse environments. By leveraging computer vision and deep learning techniques\, the UAV processes real-time camera feed data to detect obstacles\, map surroundings\, and plan collision-free paths. Key challenges include handling dynamic environments\, varying lighting conditions\, and real-time processing constraints. The system employs feature extraction\, depth estimation\, and semantic segmentation to interpret visual data\, enabling the UAV to navigate autonomously without external aids. Advantages of this approach include reduced sensor dependency\, lower power consumption\, and improved adaptability in GPS denied or cluttered spaces (e.g.\, indoor settings or dense urban areas). However\, limitations may arise in low-visibility conditions (e.g.\, fog or darkness) or with texture-less surfaces that complicate depth perception. The method aligns with advancements in lightweight AI models optimized for edge computing\, ensuring efficient onboard processing. Future enhancements could integrate multi-camera setups or hybrid sensor fusion for increased reliability. Overall\, this vision only navigation strategy offers a scalable and cost-effective solution for UAV autonomy\, particularly in applications like surveillance\, inspection\, and disaster response where simplicity and agility are critical. CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:7d22551893ebc6f1ff3969bf08c3b6db URL:http://5thworldconferenceoninformations.sched.com/event/7d22551893ebc6f1ff3969bf08c3b6db END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211500Z DTEND:20261018T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:61e6965dd55435753a30f19f5f64ddcb URL:http://5thworldconferenceoninformations.sched.com/event/61e6965dd55435753a30f19f5f64ddcb END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211500Z DTEND:20261018T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:0f1e03c62588cdd669e0133813ea17a5 URL:http://5thworldconferenceoninformations.sched.com/event/0f1e03c62588cdd669e0133813ea17a5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211500Z DTEND:20261018T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:fe7c38d2d81db2d2ee9f37f8c09567e0 URL:http://5thworldconferenceoninformations.sched.com/event/fe7c38d2d81db2d2ee9f37f8c09567e0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211500Z DTEND:20261018T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:78b2e3a08d61b3ef26a708d23630f82c URL:http://5thworldconferenceoninformations.sched.com/event/78b2e3a08d61b3ef26a708d23630f82c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211500Z DTEND:20261018T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:85c6bb7db4886ca1491b5ac47ff144f1 URL:http://5thworldconferenceoninformations.sched.com/event/85c6bb7db4886ca1491b5ac47ff144f1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211500Z DTEND:20261018T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:252352c4c3d166a7114840d981353917 URL:http://5thworldconferenceoninformations.sched.com/event/252352c4c3d166a7114840d981353917 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211700Z DTEND:20261018T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:fc6bb28a2068b31678ab766d3a582f2d URL:http://5thworldconferenceoninformations.sched.com/event/fc6bb28a2068b31678ab766d3a582f2d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211700Z DTEND:20261018T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:db093d4dc324b33ae79de85d9366a23a URL:http://5thworldconferenceoninformations.sched.com/event/db093d4dc324b33ae79de85d9366a23a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211700Z DTEND:20261018T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:4527ed61289bef5465cd1df7b6cbba5f URL:http://5thworldconferenceoninformations.sched.com/event/4527ed61289bef5465cd1df7b6cbba5f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211700Z DTEND:20261018T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:f209b648c46b929f4b34638cf51a84a2 URL:http://5thworldconferenceoninformations.sched.com/event/f209b648c46b929f4b34638cf51a84a2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211700Z DTEND:20261018T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:6ffecdf003181e708b6302d28c9af513 URL:http://5thworldconferenceoninformations.sched.com/event/6ffecdf003181e708b6302d28c9af513 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T211700Z DTEND:20261018T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 5F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:a2264a41e4f23fb1573d2f36930e4750 URL:http://5thworldconferenceoninformations.sched.com/event/a2264a41e4f23fb1573d2f36930e4750 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T215800Z DTEND:20261018T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:a36f13c95e55d0d86cf3722a7fc3d25c URL:http://5thworldconferenceoninformations.sched.com/event/a36f13c95e55d0d86cf3722a7fc3d25c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T215800Z DTEND:20261018T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:de1a91cd7964e49c7cc7b7069c6933f9 URL:http://5thworldconferenceoninformations.sched.com/event/de1a91cd7964e49c7cc7b7069c6933f9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T215800Z DTEND:20261018T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:142b02059f440ef42d243590a17f7f55 URL:http://5thworldconferenceoninformations.sched.com/event/142b02059f440ef42d243590a17f7f55 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T215800Z DTEND:20261018T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:5940cf4dd1d7ded247253e5c8d7fd109 URL:http://5thworldconferenceoninformations.sched.com/event/5940cf4dd1d7ded247253e5c8d7fd109 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T215800Z DTEND:20261018T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:75b6460889e39725c9724a6001f301c9 URL:http://5thworldconferenceoninformations.sched.com/event/75b6460889e39725c9724a6001f301c9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T215800Z DTEND:20261018T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:74fe84c97dd3fc785504685ae557598e URL:http://5thworldconferenceoninformations.sched.com/event/74fe84c97dd3fc785504685ae557598e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:A comprehensive study on work life balance of dual career couples DESCRIPTION:Authors - Smita Kalokar\, Ritesh Sule\, Dinesh Mirkute Abstract - Demographic dividend is an economic theory that suggests a potential for growth when a population has a higher ratio of working-age people. This concept highlights the economic advantages that can arise from shifts in a society's age structure. In India\, there has been a growing trend of dual-career couples\, where both partners are employed. This phenomenon has emerged as a response to escalating inflation and elevated living standards\, necessitating both partners to work concurrently. While this arrangement contributes to financial stability and social standing\, it also presents numerous challenges. These challenges encompass psychological strain on the couples\, difficulties in child-rearing\, struggles with work-life balance\, inadequate support from organizations and families when required\, insufficient spousal aid in home responsibilities and career development\, and disruptions in personal life. Women\, who often shoulder the primary responsibility for childcare and family matters\, face additional pressure when entering the workforce as they must juggle job duties with familial obligations. The research seeks to investigate the challenges encountered by dual-career couples and their strategies for managing the demands of work and personal responsibilities. The paper examines these issues and suggests various strategies at both individual and organizational levels to address and manage these concerns. This study utilizes a descriptive methodology\, drawing upon an analysis of existing scholarly literature and direct observations in the field CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:148d47ce89b7d57801f3022f394a4eec URL:http://5thworldconferenceoninformations.sched.com/event/148d47ce89b7d57801f3022f394a4eec END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:An Empirical Validation of DevOps Critical Success Factors in Developing Countries DESCRIPTION:Authors - Rivu Bhattacharjee\, Ramisa Nawar\, Farzana Sadia\, Mahady Hasan\, Rifat Ara Rouf\, M. Rokonuzzaman Abstract - The core idea of DevOps is to integrate development and operations teams to improve software delivery\, yet existing Critical Success Factor (CSF) frameworks remain largely untested in emerging economies where resource constraints exist and organizational cultures differ substantially. This study seeks to quantitatively validate and refine existing CSF models within the developing countries’ software industries. A cross-sectional survey of 23 DevOps professionals from leading software firms mapped 19 prior CSFs against perceived project success. Multiple linear regression analysis evaluated model explanatory strength\, checked multicollinearity via Variance Inflation Factors (VIFs)\, and applied two-tailed t-tests to identify predictive factors. The regression model explained 95.6% of the variance in DevOps project success\, identifying five key CSFs: regular DevOps events\, collaborative team culture\, complex performance engineering integration\, build automation\, and CI/CD pipe-line challenge mitigation. Regular DevOps events\, collaborative culture\, and streamlined automation emerged as primary success drivers. Results confirm core CSF frameworks while providing empirically grounded recommendations for resource-constrained contexts. Future research should employ larger multi-regional samples and qualitative methods. CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:4bbf492b9ec0596eb4bf4b761327e116 URL:http://5thworldconferenceoninformations.sched.com/event/4bbf492b9ec0596eb4bf4b761327e116 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Feasibility Analysis for the Construction of Civil Works in the Western Zone of the City of Loja Based on the Bearing Capacity of Its Soils DESCRIPTION:Authors - Jose Luis Chavez Torres\, KunYong Zhang\, Tyrone Alexander Guarderas Cabrera\, Camila Nickole Fernandez Morocho\, Ulises Edison Ruiz Mendoza Abstract - The main objective of this study was to create a Geomechanical Zoning Map for a polygon located in the northwestern area of Loja\, based on the soil bearing capacity derived from lithological and topographic surveys\, at a 1:6000 scale. The lithological map identified six zones with different soil classifications. DCP tests were conducted at six demonstration points\, including one comparison point\, to evaluate the bearing capacity. Results showed varying soil strengths\, with the highest CBR value of 79.36% in the center of the polygon (ML lithology) and the lowest CBR value of 18.1% in the upper left margin (OH lithology). Overall\, the soils ranged from good to acceptable in bearing capacity. It was also noted that approximately 70% of the polygon area is already urbanized. CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:08669eef6f6ef80c565bde59e72022ef URL:http://5thworldconferenceoninformations.sched.com/event/08669eef6f6ef80c565bde59e72022ef END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Integrated Geotechnical Assessment and Slope Stabilization of the Punzara Hillside in Loja\, Ecuador: A Case Study Using Topographic\, Laboratory\, and Numerical Modeling Techniques DESCRIPTION:Authors - Jose Luis Chavez Torres\, KunYong Zhang\, Tyrone Alexander Guarderas Cabrera\, Camila Nickole Fernandez Morocho Abstract - This study presents an integrated geotechnical analysis to evaluate the slope stability of a critical sector located along the lateral road of Ángel Felicisimo Rojas\, near the Punzara lagoon in Loja\, Ecuador. The site\, characterized by steep slopes and weak lithological units such as silty sands\, sandy clays\, and weathered conglomerates\, was identified as highly susceptible to landslides. A comprehensive methodological framework was employed\, combining field surveys\, geophysical profiling using the dipole-dipole method\, laboratory soil classification\, and shear strength testing. Mechanical properties such as cohesion and internal friction angle were determined and used to model slope stability under static and pseudo-static conditions using GEO5 software. The initial safety factor was found to be below recommended limits\, indicating severe geotechnical risk. Through the evaluation of stratigraphic profiles and failure modes\, the study out-lines the potential failure mechanisms and proposes slope reinforcement strategies to mitigate hazards. This research underscores the importance of integrating geological\, geomorphological\, and geotechnical data to support informed engineering decisions in landslide-prone Andean environments. CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:7af88666c73517f62a984b516b6d54b4 URL:http://5thworldconferenceoninformations.sched.com/event/7af88666c73517f62a984b516b6d54b4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Oversight of Autonomous Organizational Systems (AOS) Decision Making DESCRIPTION:Authors - Grant Royd Howard Abstract - Oversight of autonomous organizational systems (AOS) decision making is imperative for the betterment of and the prevention of harm to humanity. Human decision making oversight literature is extensive across many disciplines\, but little exists about AOS decision making oversight. This was the research problem addressed\, guided by the question\, what fundamental concepts are essential for AOS decision making oversight? The question was answered by developing an original conceptual framework. To this end\, a conceptual research design was applied to answer the research question. Conceptual research is effective for generating new knowledge using intellectual tools\, logical argumentation and assimilation of interdisciplinary empirical research. The framework exposed fundamental oversight concepts for overseeing decision making in AOS\, namely governance framework\, delegation and autonomy\, human involvement\, transparency\, traceability and explainability\, accountability\, ethical and legal compliance\, risk management\, and feedback\, adaptation and improvement. The framework is important for all AOS and artificial intelligence (AI) scientists\, academics\, programmers and organizations for averting vulnerabilities\, threats\, failures\, stagnant models\, opaque decisions\, auditing difficulties\, undetected biases\, responsibility vacuums\, unclear liability\, unethical behavior\, ethical violations\, erosion of trust\, business continuity risk\, legal and regulatory non‑compliance\, and missed learning opportunities. Furthermore\, the framework advances AOS and AI oversight and governance research\, establishing fundamental concepts for theory development and knowledge progression in the domain of AOS decision making oversight. CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:6f703a76ca146090d8d89dbc445be79f URL:http://5thworldconferenceoninformations.sched.com/event/6f703a76ca146090d8d89dbc445be79f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:QUANTUM COMPUTING AND BEHAVIORAL ANALYTICS IN HR: THE NEXT FRONTIER IN TALENT MANAGEMENT DESCRIPTION:Authors - Shiwani Wagh\, Shubham Kishor Kadam\, Utkarsha Wanjari Abstract - The coupling of quantum computing and behavioural analytics signals broader opportunities for human resource management (HRM) and\, in particular\, talent management. In an age where we are using massive\, multidimensional data sets simply for workforce planning and retention strategies\, traditional HR approaches falter too frequently beneath the weight of such complexity. Moreover\, that brings us to the flip side of the coin: quantum computing\, the trading depth of behavioural analytics\, for qubits for data processing power. This research explores how these technologies con-fluence to provide new solutions for Recruitment\, Employee retention\, Workforce development\, Organisation Planning\, etc. By combining predictive analytics and personalized interventions to make treatment decisions\, quantum-enhanced behavioural analytics can support a targeted approach to behavioural analytics. Additional applications include pipeline optimization\, attrition risk prediction\, and alignment of development programs with business goals. On the other hand\, while we have these new frontiers\, we also have technical limitations\, ethical concerns about data privacy\, and the potential for biases in decision-making. To address these\, they need to be driven by robust governance\, ethical frameworks and upskilling of our HR professionals. The potential synergy with this is brought out in this paper\, with a recommendation for its ethically implemented use in HR practices. The next frontier in HRM includes quantum computing and behavioural analytics\, which will aid in the bolstering of workforce engagement and organizational success through data-driven\, human-centred strategies. CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:23106b10b4253390e193c463afd4e6e6 URL:http://5thworldconferenceoninformations.sched.com/event/23106b10b4253390e193c463afd4e6e6 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:The Role of DEI Strategies in Organizational Management and Performance Enhancement DESCRIPTION:Authors - Priyanka Patel\, Priyanshi Desai Abstract - This research examines the relationship between Diversity\, Equity\, and Inclusion (DEI) strategies and organizational performance across global business environments. Through extensive analysis of empirical studies\, international corporate case examples\, and industry best practices\, this study demonstrates that effectively implemented DEI initiatives contribute significantly to enhanced organizational outcomes\, including increased innovation\, improved financial performance\, higher employee engagement\, and expanded market reach. The paper addresses implementation challenges with particular focus on leadership accountability frameworks and strategies to prevent diversity fatigue while main- training long-term employee engagement. This analysis provides valuable insights for business leaders seeking to leverage DEI as a strategic advantage while navigating cultural and regulatory differences across inter- national markets. CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:c98058b8402e2c3af1449eed502458f2 URL:http://5thworldconferenceoninformations.sched.com/event/c98058b8402e2c3af1449eed502458f2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Towards Smarter Diagnosis: A Survey of CNN-Based Hybrid Models in Breast Cancer Detection DESCRIPTION:Authors - Anurag Agarwal\, Mahesh Jangid\, Prashant Vats Abstract - Breast cancer starts as a problem with breast cells that multiply too fast\, forming growths called lumps. Breast cancer commonly appears in milk ducts before advancing to other body parts\, if found too late. The sooner doctors find and diagnose breast cancer\, the better patients respond to treatment and survive longer. Better breast cancer detection comes from using large collections of imaging data through AI technology\, especially machine learning and deep learning. With transfer learning tools and hybrid networks combined with CNNs sophisticated systems achieve strong results in breast cancer evaluation and characterization. Through their use of artificial intelligence\, medical researchers are developing better diagnostic tools and creating wider accessible healthcare systems for worldwide needs. CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:6edf350157807edef65fe5a039d6dfc8 URL:http://5thworldconferenceoninformations.sched.com/event/6edf350157807edef65fe5a039d6dfc8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Using Cognitivist Theory to Effect Learning and Engagement in Higher Education: A Process Control Engineering Case Study DESCRIPTION:Authors - Rangith B. Kuriakose Abstract - Learning is a complex process shaped by psychological and social factors. Psychological theories examine mental processes like memory and problem-solving\, while sociological theories analyze how culture and societal structures influence education. Key psychological perspectives include behaviorism\, which emphasizes reinforcement\, and cognitivism focusing on knowledge construction and active learning. Vygotsky’s constructivism highlights social inter-action and the Zone of Proximal Development (ZPD)\, where guidance enhances learning. Sociologically\, functionalism (Parsons) sees education as promoting social cohesion\, whereas conflict theory (Marx\, Freire) critiques its role in perpetuating inequality. Freire’s Pedagogy of the Oppressed advocates for empowering\, reflective education. This paper explores cognitivism’s application in higher education\, using an Electrical Engineering module as a case study. It identifies learning challenges ("learning knots") and proposes chunking\, a cognitivist strategy\, as an intervention. A comparative study (control vs. test groups over five tutorials) evaluates the method’s effectiveness in fostering meaningful\, sustained learning. The paper bridges theory and practice\, offering insights into curriculum design and findings suggest structured knowledge segmentation improves comprehension\, demonstrating cognitivism’s practical relevance in technical education. CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:a214484d3b115d9b7a117b7962552302 URL:http://5thworldconferenceoninformations.sched.com/event/a214484d3b115d9b7a117b7962552302 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:YOLO Assisted SAM: A Two-Stage Deep Learning Framework for Automated PCB Defect Detection and Segmentation DESCRIPTION:Authors - Mageshwari A. J.\, Jothi Prabha R.\, Karthiga N.\, Lekshmi R. R. Abstract - Ensuring the quality of printed circuit boards is crucial for the reliability of electronic devices. Traditional manual inspection methods are laborintensive and prone to errors\, underscoring the need for automated solutions. This study presents an automated deep learning-based approach for printed circuit board inspection and defect detection by leveraging segmentation and object detection models. The investigation focuses on the performance of the SAM and an integrated YOLO-SAM pipeline. A high-resolution dataset com-prising PCB images annotated with six common defect types—missing hole\, mouse bite\, open circuit\, short\, spur\, and spurious copper—is collected and preprocessed for training and evaluation. Initial experiments with SAM reveal limitations in segmenting defects without guided prompts\, particularly board with missing holes. To address this\, YOLO is integrated with SAM to provide localized bounding box prompts\, enhancing segmentation accuracy. The YOLO-SAM model is trained for 100 epochs and evaluated using precision\, recall\, F1-score\, mean average precision\, Intersection over Union\, and Dice score. Results demonstrate that the YOLO-SAM pipeline significantly outperforms standalone SAM\, achieving more accurate and robust detection across multiple folds. This two-stage approach offers a reliable solution for automated\, high-precision printed circuit boards’ defect analysis. CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:a87faa701d7b2145ec991c59c9be909b URL:http://5thworldconferenceoninformations.sched.com/event/a87faa701d7b2145ec991c59c9be909b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Adoption and User Experience of AI-Enabled Food Kiosks in Quick Service Restaurants: Insights from College Students DESCRIPTION:Authors - Ronald C. Barriga\, Dan Jeward Rubis\, Arlene A. San Pablo\, Rochelle Joy S. Tagle\, Helinor Y. Medina Abstract - This study investigates the influence of AI-enabled self-service food kiosks on customer satisfaction and their intention to use such technology in quick service restaurants. Utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) framework\, the research examines key factors such as convenience\, efficiency\, security\, and enjoyment that mediate customer perceptions. Findings indicate that positive experiences with AI kiosks significantly enhance customer satisfaction\, suggesting that strategic implementation of AI technologies can lead to improved operational efficiency and customer engagement in the food service industry. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:667a62dee878b4fea23bbfa8ddf3329f URL:http://5thworldconferenceoninformations.sched.com/event/667a62dee878b4fea23bbfa8ddf3329f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Burnout among healthcare professionals: implications for job performance and organizational sustainability DESCRIPTION:Authors - Michael Savariapitchai\, Priyanka S. Dhore Abstract - This study investigates the levels of burnout among healthcare professionals\, its impact on job performance\, and its relationship with organizational sustainability. The research employs a descriptive and correlational design\, utilizing a sample of 101 healthcare workers from various roles and organizations. A structured questionnaire with Likert-scale questions was used to collect data\, which was then analyzed using descriptive and inferential statistics\, including correlation analysis. The findings reveal moderate levels of burnout across dimensions such as emotional exhaustion\, physical fatigue\, and motivation. Burnout significantly affects job performance\, including quality of patient care\, concentration\, efficiency\, and job satisfaction. Furthermore\, burnout is perceived to contribute to organizational challenges\, including employee turnover and decreased organizational sustainability. Although there is some recognition of burnout’s impact\, respondents indicated that organizational support systems are inadequate in addressing these issues. The study underscores the need for comprehensive burnout prevention strategies\, including improved workload management\, employee well-being programs\, and enhanced support systems to promote both individual and organizational health. Recommendations include enhancing leadership initiatives\, fostering work-life balance\, and strengthening mental health support within healthcare organizations. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:c37711019cab7818a10897bc441b6d0a URL:http://5thworldconferenceoninformations.sched.com/event/c37711019cab7818a10897bc441b6d0a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:CerviScan: CNN-Powered Early Diagnosis of Cervical Cancer Through Multiclass Cell Classification DESCRIPTION:Authors - Moksha Patel\, Anuradha Desai\, Happy Patel Abstract - Despite advancements in health care\, cervical cancer is still one of the most prevalent causes of death amongst women globally. This highlights the importance of early diagnosis\, which significantly improves the chances of positive treatment outcomes. Traditionally\, the Pap sample screening has been used\; however\, its interpretation is human-dependent\, which causes variability and prospective delays in patient treatment. To address these issues\, this study offers a model called CerviScan\, which utilizes Convolutional Neural Net-works\, specifically InceptionV3\, to automatically multiclass cervical cell image classification. The SIPaKMeD dataset\, containing 5 different types of cervical cell images\, served as the training dataset for our model. Through transfer learning and extensive augmentation\, we sought to improve generalization capability. As a result\, CerviScan was able to surpass a classification threshold of 96.8%\, exhibiting remarkable accuracy and recall for all cell type categories. Concerning this medical imaging problem\, InceptionV3\, along with fine-tuning techniques\, has deeply enhanced classification performance owing to its deep feature extraction capabilities. This system is highly accurate\, cost-effective\, and efficient\, which offers remarkable assistance in eliminating repetitive tasks for pathologists and thereby accelerating the diagnosis process. Adapting deep learning methodologies to enhance the early detection of cervical cancer\, as discussed in CerviScan\, demonstrates the potential it has to improve cervix cancer detection and healthcare equality on a global scale. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:a71b689528b859bf546dac5f3b7270e9 URL:http://5thworldconferenceoninformations.sched.com/event/a71b689528b859bf546dac5f3b7270e9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Enhancing User Experience with Lightning Web Components DESCRIPTION:Authors - \;Bhargav Dhengre\, Reena Satpute\nAbstract - \;Lightning Web Components (LWC) is a new\, ambient framework for creating dynamic and responsive user interfaces for the Salesforce ecosystem. LWC is built on web standards and uses these standards to enhance user experience (UX) through improved performance\, customizability\, accessibility\, and integration. This report outlines the areas in which LWC enhances UX through faster rendering (through Virtual DOM\, lazy loading)\, reusable and themeable components\, and ARIA support/semantic HTML for accessibility. In addition to accessibility\, LWC is built for seamless integration with Salesforce data and third-party libraries\, as well as other developer-friendly tools that speed up application development while being consistent and scalable. Use cases for LWC have already shown tremendous improvements in existing applications\, enhanced e-commerce platforms\, enhanced load speeds\, packaging checkout information to streamline checkout\, and responsiveness for all mobile devices. The modularity or components in LWC can help decrease the effort to maintain components while increasing engagement\, session creation\, and conversion rates. The future of LWC has great potential in terms of AI integration\, more and more component libraries\, and added compatibility with cross-platform applications in the Salesforce ecosystem. LWC is likely to become a key technology for Salesforce development. Organizations that adopt LWC are likely to provide users with a fast and intuitive application to satisfy users and help organizations operate more efficiently in their business operations. For that reason\, Salesforce is and will continue to be an elite leader in the development of enterprise CRM technologies. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:0a3f6012ed3e78fda1932eb0530f4b80 URL:http://5thworldconferenceoninformations.sched.com/event/0a3f6012ed3e78fda1932eb0530f4b80 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Evaluating the Effectiveness of Core Tax Administration System (CTAS) in Digital Tax Education: A Pre-Experimental Study Among Accounting Students DESCRIPTION:Authors - Rochma Sudiati\, Ayatulloh Michael Musyaffi\, Eka Ary Wibawa\, Dinda Rahma Tiara\, Putri Haryani\, Ellis Annisa\, Hera Khairunnisa\, Eka Septariana Puspa\, Surya Anugrah Abstract - Digital transformation in tax administration\, particularly through the implementation of the Core Tax Administration System (CTAS)\, has brought significant changes in the way taxes are managed and reported in Indonesia. This study points to assess the viability of using CTAS in learning tax collection for bookkeeping understudies. The most center of this study is to analyze students' state of mind towards advanced system-based learning innovation and survey their level of fulfillment after utilizing CTAS. The inquire about strategy utilized is pre-experimental with a one gather pre-test and post-test plan\, where understudies take after a recreation of utilizing CTAS to report charges carefully. Information were collected through multiple-choice questions and a Likert scale-based survey to degree students' understanding\, attitude\, and fulfillment with the utilize of the framework. The comes about appeared that in spite of the fact that there was a slight decrease in positive attitude towards advanced learning\, students' fulfillment level expanded altogether after taking part within the recreation utilizing CTAS. This consider concludes that although innovation encompasses a positive impact on understudy learning fulfillment\, its impact on learning demeanor isn't exceptionally noteworthy. Therefore\, there's a require for change in learning strategies to extend students engagement with charge innovation\, as well as guaranteeing that advanced learning can be more effective in making strides students' understanding and aptitudes in tax assessment. This inquire gives understanding into the significance of innovation integration in taxation instruction to form graduates who are ready to confront challenges in an progressively digitized world of work. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:50b5f114bf67069cb69ed6b901b1c348 URL:http://5thworldconferenceoninformations.sched.com/event/50b5f114bf67069cb69ed6b901b1c348 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Evolution of internal competition within organizational boundaries: A comprehensive literature review DESCRIPTION:Authors - Harsh Chauhan\, Henrijs Kalkis Abstract - To analyze the process of internal competition within organization’s structure\, the concentration is on employee’s perspective of internal social comparison followed by intra-organizational competition developing between subordinates. The organization’s perspective of internal competition is subjected to intra-organizational evolution for developing competitiveness in business operations. For evaluation of internal competition in organization a comprehensive literature review has been developed in 2 parts. Part 1: “Intra-organizational competition”: Intra-organizational competition is the resultant of Internal social comparison. Not all employees are competition ready. Employees benchmark their performance and contribution against each other. They compare remuneration and work behavior. Part 2: “Intra-organizational evolution”: Based on ‘Variation’ associated with decentralization of command\, ‘Selection’ in terms of allocating scares resources and ‘Retention’ depending on managerial ability for implementing organizational strategy for exhibiting internal competition. Scientific database such as Google Scholar\, Emerald Insight\, EBSCO host and Science Direct has been researched. 37 research papers includes internal social comparison and intra-organizational competition\, similarly 23 research papers are selected for intra-organizational evolution. Methodology of selecting papers is based on PRISMA 2020. The literature review emphasize on treating co-workers as competitors\, however organizations management focuses on increasing productivity by developing internal competition. A conceptual framework of internal competition has been developed. The level of competition and control between employees and business management derives the span and scale of internal competition within the organization’s boundaries. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:6c1df80daabd7035683de206a4d46759 URL:http://5thworldconferenceoninformations.sched.com/event/6c1df80daabd7035683de206a4d46759 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Improving Soil Geomechanical Properties with Vetiver Grass for Bioengineering Applications DESCRIPTION:Authors - Jose Luis Chavez Torres\, KunYong Zhang\, Camila Nickole Fernandez Morocho\, Tyrone Alexander Guarderas Cabrera Abstract - This study investigates the ability of vetiver grass (Chrysopogon zizanioides) to improve the geomechanical characteristics of fine soils in the province of Loja\, Ecuador. Given the problem of erosion and slope instability in the region\, the effect of the vetiver root system on soil shear resistance was experimentally evaluated. Undisturbed soil samples were extracted\, both with the presence of vetiver and control (without vetiver)\, at depths between 0.80 and 1.5 meters. Laboratory tests included physical characterization of the soil and geomechanical tests such as the undrained consolidated triaxial test (CU) and the direct shear test (CD). The results obtained demonstrate a notable increase in the apparent cohesion and shear resistance of the samples with vetiver roots compared to the control samples. The presence of vetiver markedly enhanced the soil's shear resistance capacity\, reflected in a considerably greater apparent cohesion in the reinforced samples. These findings validate vetiver grass as an effective and sustainable bioengineering solution for slope stabilization and mitigation of erosive processes in soils with characteristics similar to those studied. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:f1bbdcadc751ac5c05bec4569948f05e URL:http://5thworldconferenceoninformations.sched.com/event/f1bbdcadc751ac5c05bec4569948f05e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:IOT Based Automatic Medicine Dispenser DESCRIPTION:Authors - Sunil Sangve\, Prathmesh Kalaskar\, Yash Kathoke\, Tejas Joshi\, Amartya Khandare\, Anish Kadu Abstract - Elderly individuals and those with chronic illnesses often struggle to stick to their medication schedules\, especially when they do not have someone around to help. To address this challenge\, this paper introduces an IoT-based medicine dispenser designed to automatically dispense medication at specific times of the day—morning\, noon\, and night. The system is built using an Arduino microcontroller\, servo motors\, LEDs\, an LCD display\, and a buzzer to provide clear visual and audio reminders. The design of the medicine dispenser facilitates easy management of medication regimens. A basic cardboard container holds three compartments designed for medication at different times of the day. The servo motor operates the dispensing system to deliver medications at the correct times. Through a app users and caregivers can effortlessly manage medication schedules which enhances medication adherence and leads to better health results. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:2d97805ba2a1a97a7e8f67bd673f1d17 URL:http://5thworldconferenceoninformations.sched.com/event/2d97805ba2a1a97a7e8f67bd673f1d17 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Optimized EfficientNetB4 Architecture for Breast Cancer Classification: A Deep Learning Approach DESCRIPTION:Authors - Happy Patel\, Anuradha Desai\, Moksha Patel Abstract - Breast cancer can be considered one of the fatal disorders distinguished by unusual and uncontrolled development of breast cells\, which requires early and precise detection in order to be effectively treated. Ultrasound image is frequently used for breast cancer screening as it is widely available and non- invasive. Diagnostic difficulties may arise from the subjective and variable manual interpretation of ultrasound pictures. In this work\, we suggest a Deep Learning Model utilizing EfficientNetB4 for automated classification of ultrasound images of breast cancer. There are 647 images in the collection that have been categorized as either benign or malignant. Binary masking\, histogram equalization\, and grayscale conversion are some of the steps to improve feature extraction. The proposed model outperforms traditional CNN architectures achieving an accuracy of 90.24% on the testing dataset after being trained with a transfer learning approach. The model indicates exceptional sensitivity in identifying malignant cases\, decreased the rate of false-negative outcomes\, and increased diagnosis accuracy. To ensure efficient model training\, accurate iterative improvement\, and consistent performance improvement\, learning rate scheduling and check pointing are used. The experimental results demonstrate how well EfficientNetB4 performs feature extraction and classification\, making it a potentially useful tool to help radiologists diagnose breast cancer. By providing a better approach for identifying and categorizing breast cancer\, this research promotes the use of deep learning in the field of medical imaging. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:fcdc9eb0e070f37dec56fabddeb89d5c URL:http://5thworldconferenceoninformations.sched.com/event/fcdc9eb0e070f37dec56fabddeb89d5c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Security\, Privacy\, and Trust in Internet of Everything: Challenges and the Way Forward DESCRIPTION:Authors - Prince Kelvin Owusu\, Philomina Pomaah Ofori\, Moses Aggor Ofori\, Dzordzoe Koffie-Ocloo\, Gibson Afriyie Owusu\, Martins Larweh Nuertey Abstract - The Internet of Everything (IoE) extends traditional IoT by integrating people\, processes\, data\, and things into a highly dynamic and context-sensitive ecosystem. This convergence introduces complex security\, privacy\, and trust challenges that cannot be effectively addressed using static or device-centric models. In this paper\, we propose CAT-M\, a novel Context-Aware Trust Management framework that integrates dynamic trust evaluation\, semantic policy enforcement\, and context-sensitive privacy controls to secure heterogeneous IoE environments. CAT-M leverages fuzzy logic\, semantic translation\, and lightweight cryptography to ensure scalable\, interoperable\, and human-centric security. Through simulation in a smart healthcare scenario\, we demonstrate the framework’s effectiveness in reducing privacy leakage\, improving trust accuracy\, and enabling real-time access control. The results highlight CATM’s potential as a unified approach to building secure and trustworthy IoE systems\, while paving the way for future enhancements through intelligent trust prediction and cross-domain interoperability. CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:f3d6d0f908318bb2e74b9091dd0569ea URL:http://5thworldconferenceoninformations.sched.com/event/f3d6d0f908318bb2e74b9091dd0569ea END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Advancement and Challenges in Chatbot Technology: A Deep Dive into AI-Powered Conversations DESCRIPTION:Authors - Samiksha Andeo\, Supriya Narad Abstract - How we've been interacting with technology has altered with the presence of chatbots\, which have now become a part of our digital society. These artificially intelligent virtual personal assistants are being applied on a vast scale in customer services\, health care\, and education sectors since they are capable of answering the customers\, addressing their queries\, and directing them in real-time. In relation to their application in healthcare\, in this research study\, the his-tory of chatbots is discussed\, the technology employed by them\, their real-world applications\, and the problems faced by them. Modern-day chatbots can understand human language\, learn from past conversations\, and communicate in a customized way by employing Natural Language Processing (NLP)\, Machine Learning (ML)\, and Artificial Intelligence (AI). They may be anything from AI-based chatbots able to engage in meaningful\, dynamic conversations to rule-based assistants that utilize pre-defined scripts. With the advent of technology\, chatbots are increasingly being applied in the field of health care such as patient assistance\, mental assistance\, and diet and nutrition guidance\, all of which enhance access to health care services. However\, despite all their benefits\, their potential is also hindered by limitations such as privacy\, ethical concerns\, and the inability to understand human feelings. As the future of deep learning\, IoT connectivity\, and more interactive AI is on the horizon\, chatbots appear to have a very bright future. The purpose of this research is to give an authoritative and illuminating perspective on how chatbots are changing various businesses and the future of AI communication. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:26e70bbe0625aea25f6d1b3744eea976 URL:http://5thworldconferenceoninformations.sched.com/event/26e70bbe0625aea25f6d1b3744eea976 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:AgroTrust: A Blockchain-Enabled AI-Powered Organic Product Certification System DESCRIPTION:Authors - Sadman Hafiz\, Md. Ataur Rahman\, Tahmid Zamee\, Md Sacklain Hossain\, Marufa Akter\, Ahmad Mostofa Kamal\, Mahady Hasan\, M. Rokonuzzaman\, Farzana Sadia Abstract - The organic agriculture sector in Bangladesh faces significant challenges due to the absence of a national organic product certification system. As a result\, local producers are often forced to rely on expensive international certification agencies\, creating barriers to market entry\, increasing costs and limiting consumer trust. To solve this\, our proposed system is a blockchain-enabled\, AI-powered web platform designed to establish a secure\, transparent\, and efficient organic product certification system tailored for the Bangladeshi context. A key innovation is its hash-based file verification to minimize gas fees to store data on the chain. Farmers or producers submitted product data like images\, videos\, and documents\, which are encrypted (AES-256) and stored locally\, while cryptographic hashes (SHA-256) are saved on-chain. Any alteration in a file changes its hash\, and QR-code scanning will instantly flag tampering\, ensuring product integrity. It also integrates tokenized payment systems using ERC-20 tokens alongside SSLCOMMERZ payment gateway\, ensuring secure\, traceable\, and accessible transactions for all stakeholders. Key features include smart contract automation\, real-time certification tracking\, a decentralized dispute resolution mechanism\, and QR code-based traceability for consumers. This project\, therefore\, aims to democratize organic product certification\, lower operational costs\, and build consumer trust\, while aligning with global trends in digital food supply chains. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:8926a449f5139bae2a4b07fc55d61ac9 URL:http://5thworldconferenceoninformations.sched.com/event/8926a449f5139bae2a4b07fc55d61ac9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:AI-Driven Road Accident Image Processing\, Annotation\, and Reporting Framework Using Advanced Machine Learning Model DESCRIPTION:Authors - Wani Tejaswi\, Pawar Suvarna Abstract - The number and intensity of car accidents around the world are rising\, which makes it even more important to have smart systems that can quickly and correctly process accident pictures. We need more advanced systems to quickly find accidents\, label data\, and record them. Manual methods take a long time\, are prone to mistakes\, and are not good enough for real-time apps. This paper tries to solve these problems by suggesting a system that uses advanced machine learning (ML) models to automatically process\, label\, and report images of car accidents. Convolutional Neural Networks (CNNs) are used for feature extraction\, YOLOv8 is used for real-time accident recognition\, and Transformer-based models are used for complex multi-object labeling Global Road Accidents Dataset is much better at generalizing models than the Car Crash Dataset and the Road Traffic Accidents Dataset\, which are more focused on crash types and vehicle damage. This is because it has more images and a wider range of features\, such as location\, severity\, and weather. It was tested and found that the proposed hybrid model is more accurate than the CNN- based and YOLO-only methods\, which got 94.5% and 93.7% accuracy and precision\, re-spectively\, on the Global Road Accidents Dataset. The combination model also has better accuracy for annotations and fewer fake hits. Comparative research shows that combining Transformer designs with object recognition models makes it easier to understand features and make reports. Findings from this study show that the AI-driven framework can be used to automate accident investigation processes. This is a big step towards smart traffic control and emergency response systems. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:5f4374442e713ab4a344e6c7bad45bd1 URL:http://5thworldconferenceoninformations.sched.com/event/5f4374442e713ab4a344e6c7bad45bd1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:An In-Depth Analysis of IAQ in Educational Settings using ML DESCRIPTION:Authors - Hasin Mahir\, Tahfizul Hasan Zihan\, Md. Shirazim Munir\, Khondkar Ayaz Rabbani\, Rifat Ara Rouf\, Ferdows Zahid\, Mahady Hasan\, Md. Tarek Habib Abstract - Indoor air quality (IAQ) is critical for health\, comfort\, and cognitive performance in classrooms. Yet\, many classrooms in lowermiddle-income countries (e.g.\, Bangladesh) rely on natural ventilation and lack any warning system for impending air-quality guideline breaches. This study is motivated by the need to maintain healthy learning environments in resource-constrained settings\, where students and teachers are often exposed to elevated CO2 and particulate levels. To address this\, we present the first comparative evaluation of three forecasting models: Prophet\, Random Forest (RF)\, and Long Short-Term Memory (LSTM)\, on daily PM2.5 and CO2 time series covering six months of continuous operation in Dhaka\, Bangladesh. Our goal is to anticipate IAQ deterioration to enable proactive ventilation or filtration interventions. The nonlinear machine-learning models substantially outperform the Prophet baseline. Random Forest performed best for PM. (RMSE 1.87 μg/m³\, R² 0.992)\, showing its ability to capture complex pollutant dynamics. LSTM excelled at forecasting peak CO2 (RMSE 159.7 ppm\, R² 0.693)\, which is critical for timely interventions. These findings demonstrate the feasibility of accurate\, low-cost IAQ forecasting in resource-constrained classrooms and underscore the potential of data-driven forecasting to maintain healthier learning environments. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:87587b44e7124611339093c3b3bb3c8b URL:http://5thworldconferenceoninformations.sched.com/event/87587b44e7124611339093c3b3bb3c8b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Embedding Self-Attention Blocks into Deep Neural Networks for Early Rice Yield Prediction DESCRIPTION:Authors - Thuy-Vi Thi Ha\, Phuoc-Hung Vo\, Thanh-Nghi Do Abstract - In this paper\, we propose an enhanced deep learning approach for early-stage rice yield prediction by embedding self-attention layers into established deep neural networks (DNNs) such as VGG-16\, DenseNet\, MobileNet\, ResNet\, Inception\, and Xception. The addition of self-attention significantly improves the models’ ability to capture longrange dependencies and global context\, which traditional convolutional layers often fail to represent adequately due to their inherently local receptive fields. We evaluate the proposed method on a dataset of 18\,642 RGB images collected from 47 rice field plots spanning over 28 hectares in An Giang and Tra Vinh provinces. The images were acquired using digital cameras\, smartphones\, and fixed-wing UAVs during the heading stage of rice growth. Experimental results demonstrate that DNNs enhanced with self-attention layers consistently outperform their original fine-tuned counterparts. Furthermore\, these hybrid models also achieve higher prediction accuracy compared to Vision Transformers (ViT)\, highlighting the effectiveness of integrating self-attention into conventional DNN architectures for agricultural yield forecasting. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:c79690fd41372b6790cfd52b09b4e587 URL:http://5thworldconferenceoninformations.sched.com/event/c79690fd41372b6790cfd52b09b4e587 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Enhancing Weather Prediction For Agriculture DESCRIPTION:Authors - Soham Paithankar\, Khushi Khedkar\, Supriya Narad Abstract - In this research paper\, there is a new forecast on the programme that will be able to predict the weather for agriculture. Enhanced by the Internet-connected weather and climate models\, earth observation data\, and artificial intelligence algorithms\, the system returns to farmers accurate\, location-based outlook. It does this by factoring preceding day’s temperature data and other factors to determine the needed plant growth\, therefore offering comprehensive and precise directions. Furthermore\, the alarm systems help in giving the farmers a prior indication of any future possible weather-related incidents that cause a threat to human and their stock’s safety so that measures could be taken accordingly. It also uses real information especially in agriculture sector thus transmits present information to the farmers. The main objective that the system has for farmers is to provide them with information on crops during a favourable time for crop production and the main idea of achieving this is to boost agriculture sustainability and productivity\, this is because climatic conditions are very volatile thus would have a great negative impact on farming. Also\, the expected audience becomes more diverse and can principally grow\, as we would like to consider farmers\, who may not even have a basic computer knowledge\, empowered by the platform. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:16a0f5b18ea9e6d61ef1b2af3728de05 URL:http://5thworldconferenceoninformations.sched.com/event/16a0f5b18ea9e6d61ef1b2af3728de05 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Ethical Considerations and the Impact of Large Language Models on Automated Feedback Generation and Data Analysis DESCRIPTION:Authors - Ankit Shah\, Roshni Rawal Abstract - Artificial intelligence-powered learning analytics (LA) shows great results for assisting teachers with the time-consuming task of providing feedback in context to ethical consideration\, leads to fairness\, maintaining privacy and transparency in feedback. The study investigated two GPT model versions (3.5 and 4) that produce evaluation advice on students' writing assessment based on assignments in context of data science subject. Researchers evaluated GPT generated advice in comparison with human instructions on the basics of effective-ness\, readability\, and reliability. The paper concludes that both versions could constantly produce more decipherable advice in comparison with human instructions\, but GPT-4 performed much better than GPT 3.5 and human instructors. Researchers talked about the unique blend of ethical contemplation and the impact of LLM’s on automated feedback and data analysis provides a perfect match to the LLMs to achieve ethical horizons and set a new height to be achieved for upcoming generations. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:85f55664376c1a8a8cb25ec5486f6ac1 URL:http://5thworldconferenceoninformations.sched.com/event/85f55664376c1a8a8cb25ec5486f6ac1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:The Need for Sustainable AI-Based Green Technology for Soil Management in Agriculture DESCRIPTION:Authors - Shalini S\, Mamatha A\, S. Sheela\, Mala B A\, Nagaraj M Lutimath\, Koustav Biswas Abstract - Sustainable soil management is essential for ensuring food quality\, environmental health and climate resilience. This systematic survey examines the evolution and integration of Artificial Intelligence (AI) and Machine Learning (ML) within green agricultural technologies aimed at enhancing soil health. This paper focuses on sensor networks\, remote sensing\, Internet of Things (IoT)\, robotics and data-driven decision-support systems to assess their efficiency in precision soil diagnostics\, fertility management and resource conservation. While these green AI technologies show promising benefits\, improved resource efficiency\, reduced environmental footprint\, regenerative soil practices challenges persist\, including uneven soil data availability\, high implementation costs and limited interpretability of models and lack of standardization. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:d3184a00838b0ffcf28e5fef0ffb4d74 URL:http://5thworldconferenceoninformations.sched.com/event/d3184a00838b0ffcf28e5fef0ffb4d74 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Tolerance to DDOS attacks in SDN Networks By Dedicating A Controller to Packet-in Messages DESCRIPTION:Authors - Aida Ouedraogo/Rakissga\, P Justin Kouraogo Abstract - We're interested of the control plane's fault tolerance and the solution we're proposing is proactive thanks to its modularity. Our solution proposes a distributed SDN (Software-Defined Networking) architecture\, comprising a controller specifically dedicated to processing packet_in messages and a generic controller in charge of other network management functions. The goal is to prove the effectiveness of this role specialization with regard to performance in message processing and the ability to resist failures. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:6df3fb063c1c71654a8f02011c2fe40b URL:http://5thworldconferenceoninformations.sched.com/event/6df3fb063c1c71654a8f02011c2fe40b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Unified Tour Insights: Linking Tourists and Businesses in Tourism Industry DESCRIPTION:Authors - Shyamali Thasale\, Seema Kedar\, Rutuja Khedkar\, Kartik Naphade\, Prajakta Gaikwad\, Vijay Kale Abstract - Sentiment analysis of tourist reviews examines common points of view to help users choose destinations\, accommodations\, and services. Provides businesses with information on customer satisfaction and helps travelers make better choices based on a variety of common experiences. The proposed method uses a mix of the Skip-Gram models and Continuous Bag of Words in addition to Word2Vec vectorization to transform textual data into numerical values. This method maintains the sentiment of the text and also captures the context and word relationships. Convolutional neural networks boost the accuracy of classification and feature extraction. Along with CNN\, models like Random Forest\, AdaBoost\, LSTM and CNN-BiLSTM have also been used in order to hold a comparison between them. Among these\, the CNN model showed the highest accuracy of 96.3 %. This system provides users with specific recommendations for vacation spots\, accommodations\, and activities. CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:bee17fa242f5abd2aa32981bf46e9aec URL:http://5thworldconferenceoninformations.sched.com/event/bee17fa242f5abd2aa32981bf46e9aec END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:A Comprehensive Review of Communication Protocols: Wired\, Wireless\, IoT\, and Beyond DESCRIPTION:Authors - Vedansh Verdia\, Upesh Patel\, Trushit Upadhyaya Abstract - In this paper\, we take a look into the world of communication protocols from the ones we've relied on for years like the Ethernet\, to newer technologies made just for the Internet of Things (IoT)\, and even those that are just starting to emerge. As our need for faster\, more reliable\, secure\, and energy-efficient communication keeps growing\, these protocols have continued to evolve. We look at how they work\, what they're built on\, and how well they perform in real-world situations. Along the way\, we break down their strengths\, their drawbacks\, and where they’re best used. Our review spans a broad spectrum—from classic wired systems to wireless options like Wi-Fi and cellular networks\, as well as industrial communication setups and cutting-edge technologies like Time-Sensitive Networking. We break down how these protocols compare in terms of speed\, ease of implementation\, and security\, helping readers understand which ones are best suited for different needs and situations. Finally\, we talk about the big questions researchers are still trying to answer\, and where things might be headed especially when it comes to making systems smarter\, more unified\, and ready for future challenges like quantum-safe communication. This paper is meant to be a helpful guide for anyone researchers\, engineers\, or tech enthusiasts—trying to make sense of today’s complex communication landscape. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:f12df8fa1412df19cd5032a5b2774a39 URL:http://5thworldconferenceoninformations.sched.com/event/f12df8fa1412df19cd5032a5b2774a39 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Charting Crime: Opportunities and Challenges in the Age of Predictive Analytics DESCRIPTION:Authors - Vikas Sihag\, Kanika Panwar Abstract - Predictive analytics is reshaping crime mapping and policing by leveraging tools like GIS\, machine learning\, and big data. This paper reviews current techniques and real-world applications\, highlighting their potential to identify crime hotspots and inform proactive strategies. It also examines key challenges\, including biased data\, ethical concerns\, and privacy risks. Through case studies analysis and literature review\, the research outlines the limitations of existing systems. The study stresses the importance of fairness\, transparency\, and accountability. Furthermore\, the paper presents a current state of challenges and solutions advocated in research\, thus supporting responsible and effective crime prevention practices. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:5796b8a8b1050ccd1815e12763e348b4 URL:http://5thworldconferenceoninformations.sched.com/event/5796b8a8b1050ccd1815e12763e348b4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Cybersecurity in the Age of Artificial Intelligence: Emerging Challenges for South African SMEs: A Scoping Review DESCRIPTION:Authors - Moses Moyo\, Hanifa Abdullah Abstract - This scoping review was conducted to have an overview of how Artificial Intelligence (AI) influenced cybersecurity posture in South African small and medium enterprises (SMES) utilizing cloud computing technologies. The study extract 57 articles from six electronic databases. After rigorous screen\, only eighteen studies were eligible for analysis. Of the eighteen remaining studies\, eight were empirical and ten desktops. A qualitative thematic approach was used to extract relevant data from the study to understand the current state of cyberse-curity in SMEs. The study found that South African SMEs were using AI but did not harness opportunities it can offer in cybersecurity. The level of cybersecurity among the SMEs was very low due to lack of proper knowledge about threats that AI technologies could bring about if used by criminals. The study concluded SMEs were poorly prepared for AI use in general and in cybersecurity. The study was limited due to lack of literature related to the research questions. Therefore\, it is recommended that a longitudinal empirical study be conducted with South African SMEs to have deeper understanding standing of how the adoption of AI is influencing their cybersecurity posture. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:7efd1e5d96fd63fbfe89288396f8dfa3 URL:http://5thworldconferenceoninformations.sched.com/event/7efd1e5d96fd63fbfe89288396f8dfa3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Digital Public Infrastructure as a Driver of Innovation: Global Lessons from the India Stack Experience DESCRIPTION:Authors - Aswathi Mary Varghese\, Jisha K Abstract - Digital public infrastructure (DPI) denotes foundational digital systems that serve as essential enablers for delivering digital services at scale across society. It has emerged as a key enabler of innovation in developing countries by reducing systemic entry barriers and fostering an inclusive digital ecosystem. DPI serves as a vital connective tissue within the digital ecosystem. Bridging the gap between physical infrastructure—such as internet connectivity\, devices\, data centers\, and the cloud—and a diverse landscape of applications\, DPI empowers societies to deploy innovative solutions across sectors like e-commerce\, social protection\, re-mote education\, and telehealth. Real-world illustrations abound: India’s Aadhaar system has revolutionized digital identification\, Brazil’s Pix has made fast\, real-time payments accessible nationwide\, and Australia’s Consumer Data Right is pioneering user-centric data sharing. By enabling dynamic\, cross-sectoral innovation\, DPI stands as the engine powering the next generation of digital transformation. This paper analyses the evolution and impact of India Stack\, focusing on how its layers enable innovation across sectors such as fintech\, health\, and e-commerce. By mapping the structural features of India Stack against the outcomes in financial inclusion\, digital health\, and market decentralization\, the paper offers a conceptual framework to assess the role of public policy in driving innovation. The findings indicate that when government platforms are built as public goods with interoperable standards and strong institution-al backing\, they can create an enabling environment for grassroots and enterprise-level innovation. The India Stack model\, while context-specific\, holds valuable lessons for other nations seeking to integrate public policy with digital transformation goals. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:2955e3ec0b61b3d4fe93975e28a25816 URL:http://5thworldconferenceoninformations.sched.com/event/2955e3ec0b61b3d4fe93975e28a25816 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Explainable AI for Time Series: A Systematic Review of Robust and Efficient Detection of Stealthy Adversarial Attacks DESCRIPTION:Authors - Mohammed Hashim Kalam\, Guhanathan Poravi Abstract - Time-series data has been increasingly utilized in critical domains making it vulnerable to stealthy adversarial attacks. Explainable AI (XAI) has made major enhancements to model transparency specifically in non-sequential domains (Image\, NLP and tabular) but is less researched in time series data due to complexity of temporal dependency in sequential data. This paper systematically reviews around 60 studies published up to June 2025\, examining XAI-based approaches for time series\, as well as recent XAI extensions tailored for time series data. Various attack types are discussed in terms of their effectiveness\, and the performance of recent detection frameworks against these attacks is analyzed\, with particular focus on XAI-integrated systems\, including SHAP\, LIME\, LRP\, and formal verifications. Despite their usage\, most XAI-enhanced approaches\, especially those relying on SHAP\, face challenges in efficiency and risk explanation instability under noise\, with limited evaluation against subtle partial adversarial attacks. While LRP offers computational efficiency vital for high stakes domain real-time detection\, its architectural dependency restricts its adaptability across diverse models. This review highlights major unsolved limitations and concludes with prioritizing the need for efficient\, robust\, temporally aware\, and architecture-agnostic frameworks\, possibly extending LRP\, tailored specifically for time series data. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:4d77100526aff7a481168ae82b41bb23 URL:http://5thworldconferenceoninformations.sched.com/event/4d77100526aff7a481168ae82b41bb23 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Financial Literacy\, Inclusion\, and Empowerment of Rural Women Entrepreneurs: A Bibliometric Review on the Role of Incubation Centers DESCRIPTION:Authors - Shalini Singh\, Amala Siby Abstract - In the last twenty years\, efforts have been made to address how financial literacy and inclusion can empower rural women entrepreneurs. However\, one essential factor tends to be left behind—the contribution of incubation centers to enabling these women to succeed. This research examines the academic landscape in closer detail through a bibliometric analysis of 2\,012 peer-reviewed articles between 2005 and mid-2025 based on the Scopus database. Using tools such as Biblioshiny and VOSviewer\, we delve into how the discourse on financial capability\, women entrepreneurship\, and economic empowerment has progressed throughout time. The research indicates a meteoric increase in interest following 2020\, fueled primarily by vulnerabilities uncovered with the COVID-19 pandemic. Despite expansion\, however\, something is certain: there remains relatively little research linking incubation assistance to rural women directly or financial literacy programs. Our analyses of keywords and co-authorships indicate a splintered discipline with ample space for richer\, more holistic research. This article not only charts what is known but also reveals what is lacking\, presenting new directions for researchers and policymakers dedicated to building stronger safety nets for rural women entrepreneurs. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:16d3cb854e847cc19746276007b230b7 URL:http://5thworldconferenceoninformations.sched.com/event/16d3cb854e847cc19746276007b230b7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:FPGA Implementation of AES Algorithm DESCRIPTION:Authors - Manupriya P\, Rajeshwari.Mattimani\, Haripriya G\, Hema B\, Saroja.V.Siddamal\, Vijay H M\, Suhas Shirol\, Ganga I Abstract - At present\, encryption is key to safeguard confidential information from unauthorized access. It means using special algorithms and encryption keys to change readable data into unreadable data. AES is symmetric encryption algorithm adopted by the U.S.Government as a replacement of DES algorithm. AES supports 3-key sizes: 128 bit\, 192 bit and 256 bit\, with AES -128 being the most commonly used due to its balance of security and performance. Because it is fast and simple\, symmetric key encryption which uses a single key for both encryption and decryption\, is used in many cases. Advanced Encryption Standard (AES) is a symmetric block cipher that is used extensively in the encryption of electronic data. Out of its various implementations\, AES-128 is the most commonly used\, with a 128-bit key size and encrypting 128-bit-sized blocks of data and to get 128-bit cipher text. The encryption process goes through 10 rounds of processes like SubBytes\, ShiftRows\, MixColumns\, and AddRoundKey\, which are computed to have high confusion and diffusion properties. AES-128 is optimally balanced in terms of security\, efficiency\, and performance and thus finding use in hardware and software in various industries. Due to its strength and immunity against known attacks on electronic data\, passwords etc. AES-128 has been the standard for encrypting data in commercial and government systems worldwide. AES algorithm has many applications such as online banking\, ATM machines and military and government communication. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:f50dc7889943d8bc713e374a67a90bf8 URL:http://5thworldconferenceoninformations.sched.com/event/f50dc7889943d8bc713e374a67a90bf8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Product Market Response Evaluation Applying User Data Analytics: A Study on Breast Feeding Equipment DESCRIPTION:Authors - Anirban Chowdhury\, Parul Sachdeva Abstract - This study explores the product-market response to breastfeeding equipment by leveraging user data analytics to evaluate consumer behavior\, preferences\, and satisfaction. As maternal health awareness grows and parenting practices evolve\, breastfeeding products have seen significant innovation in design\, functionality\, and accessibility. However\, market success relies not only on product features but also on understanding real-world user experience and response. The research employs a quantitative method\, from user ratings sales metrics to get insights from data collected from amazon.in. Findings reveal key determinants influencing user acceptance\, including ergonomic design\, portability\, ease of use\, and aesthetics. The study also identifies gaps between user expectations and product performance that affect repeat purchases despite of product brand. By contextualizing user experience data within broader market trends\, the research highlights the role of user-centered design and feedback loops in enhancing product relevance and competitiveness. The outcomes of this study can inform product developers\, marketers\, and health professionals in creating more effective\, user-aligned breastfeeding solutions that support ma- ternal well-being and infant health outcomes. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:0f050c736b5b0875853534e70ffb2418 URL:http://5thworldconferenceoninformations.sched.com/event/0f050c736b5b0875853534e70ffb2418 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Signaling or Symbolism? Reassessing the Link Between Risk Disclosure and ESG Performance DESCRIPTION:Authors - I Gusti Ketut Agung Ulupui\, Gentiga Muhammad Zairin\, Septi Nurmalita\, Hera Khairunnia\, Dwi Kismayanti Respati\, Eka Septariana Puspa Abstract - This study examines the relationship between voluntary risk disclosure and Environmental\, Social\, and Governance (ESG) performance among Indonesian publicly listed companies. While ESG metrics have become central to investment evaluations\, the influence of narrative risk reporting on ESG scores remains unclear\, particularly in emerging markets where such disclosures are not standardized. Utilizing content analysis of 2022 annual reports and ESG ratings provided by Sustainalytics through the Indonesia Stock Exchange\, this study investigates whether risk disclosure serves as a credible signal of corporate sustainability. The findings reveal that risk disclosure does not significantly influence ESG performance\, suggesting that investors and ESG rating agencies may discount voluntary disclosures when they lack precision or strategic alignment. In contrast\, firm-specific characteristics\, namely profitability (ROA)\, leverage\, and firm size—are positively associated with ESG scores. These results indicate that internal financial and structural factors may offer more reliable indicators of ESG commitment than unregulated disclosure narratives. The study contributes to the ESG literature by questioning the signaling power of voluntary disclosures and highlights the need for stronger disclosure standards in emerging markets to enhance ESG credibility and comparability. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:92e83423a8b87bec99ecf7e78f805d49 URL:http://5thworldconferenceoninformations.sched.com/event/92e83423a8b87bec99ecf7e78f805d49 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:User Data Analytics for Prediction of Business Impact due to Cybercrimes in India: Learnings from Literature and Metadata DESCRIPTION:Authors - Devanjan Khuntia\, Anirban Chowdhury\, Subhra Chakraborty Abstract - Cybercrime poses a significant threat to India’s business environment\, disrupting economic ecosystems\, revenue growth\, innovation\, and employee well-being. As digital adoption accelerates\, sectors like banking\, e-commerce\, and manufacturing face escalating vulnerabilities. This study analyses cyber crime’s multifaceted impact\, revealing projected losses of ₹20\,000 crore in 2025\, with banking (₹8\,200 crore) and retail (₹5\,800 crore) hardest hit. Beyond financial damage\, attacks erode trust\, delay deliveries (30% of manufacturers)\, and slow AI/cloud adoption (40%). Intellectual property theft affects 22% of firms\, while SMEs struggle with weak defences (73% prioritize cybersecurity). Employees face data breaches (32% via PUPs) and stress (45%). The paper advocates for stronger policies (e.g.\, enhancing I4C)\, AI-driven security\, and workforce training to build resilience. A holistic approach—combining regulation\, public-private collaboration\, and awareness—is critical to safeguarding India’s digital economy. CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:d0b1497d0a5afbd0e8fc7a8e3faa97d8 URL:http://5thworldconferenceoninformations.sched.com/event/d0b1497d0a5afbd0e8fc7a8e3faa97d8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Adaptive Ambient Intelligence: Machine Learning Models for Context Prediction in Ubiquitous Systems DESCRIPTION:Authors - GGS Pradeep\, Thrilok. Kolla\, Rajesh Sharma R\, Akey Sungheetha\, N Vijayalakshmi\, Pellakuri Vidyullatha Abstract - Ambient Intelligence (AmI) systems are intended to support responsive and adaptive services by understanding the context of their users. The present paper proposes a machine learning framework for context prediction in ubiquitous environments on the basis of multi-sensor ambient data. The method classifies user activity into four high-level contexts: Sleeping\, Working\, Cooking\, and Outdoors\, exploiting features like Temperature\, Light\, Sound\, Motion\, and Time. The model described here consists of three steps: Preprocessing\, Normalization\, and Classification based on Random Forests. Visualization techniques\, such as KDE plots\, correlation matrices\, and 3D scatter analysis\, are used for the interpretation of contextual separability and the influence of features. Experimental results show that outdoor activity strongly dominates the dataset\, while other contexts are almost neglected. The proposed framework shows high predictive accuracy with interpretable insights into context-dependent behavioral patterns. This work thus contributes to the design of such adaptive\, context-aware systems that can find a home in intelligent environments\, especially in the realms of smart homes and assistive technologies. The abstract makes it abundantly clear how crucial Ambient Intelligence systems are to contemporary ubiquitous surroundings\, particularly for assistive technology and smart houses. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:07fd4661a57a82fd53ef9da0d35c20f3 URL:http://5thworldconferenceoninformations.sched.com/event/07fd4661a57a82fd53ef9da0d35c20f3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:AMPERE: A Hierarchical Multi-Agent Deep Reinforcement Learning and Evolutionary Algorithm Framework for Optimising Smart Grid Electricity Distribution DESCRIPTION:Authors - Adrian Diepeveen\, Siphesihle Sithungu Abstract - Traditional electricity grid networks have approached critical resilience thresholds\, with archaic grid architectures demonstrating inadequate capacity to accommodate volatile demand fluctuations. South Africa's current energy crisis\, characterised by unpredictable power outages and extensive economic losses from electricity outages\, emphasises the need for novel optimisation frameworks. This re-search proposes a framework named AMPERE (Autonomous Multi-Agent Predictive Electricity Reinforcement Learning Engine)\, a dual-phase solution which com-bines hierarchical multi-agent deep reinforcement learning (MADRL) and evolutionary algorithms (EAs) in order to address electricity distribution challenges through decentralised multi-agent coordination. A significant gap exists in research integrating distributed hierarchical knowledge-sharing MADRL with EAs at both regional and national levels\, since current approaches focus on singular artificial intelligence (AI) methodologies or non-hierarchical frameworks. Ultimately\, AMPERE introduces a novel three-tier hierarchical agent architecture consisting of smart grid national agents\, smart home regional agents\, and smart home battery agents\, utilising Pecan Street's real-world Internet of Things (IoT) time-series datasets. The Centralised Training with Decentralised Execution (CTDE) paradigm enables effective multi-agent coordination across regional and national scales\, subsequently enhancing smart grid stability and scalability while minimising electricity lost in distribution. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:a6410852085abb7c2adcd90d98d9d186 URL:http://5thworldconferenceoninformations.sched.com/event/a6410852085abb7c2adcd90d98d9d186 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:From Stress to Burnout: Effects of Misinformation on Indian Healthcare Professionals During a Public Health Emergency DESCRIPTION:Authors - Jayan V\, Sreejith Alathur Abstract - The COVID-19 pandemic not only strained global healthcare systems but also exposed healthcare professionals to unprecedented psychological challenges. Among the various stressors\, the rapid spread of misinformation on social media emerged as a significant contributor to emotional distress\, confusion\, and burnout among frontline workers. This study explores the impact of social media misinformation on the mental health of healthcare professionals in India during the pandemic\, using qualitative interviews with 41 public sector healthcare workers. Guided by the honeycomb social media framework and stress coping models\, the re-search examines how misinformation intensifies psychological stress and how individuals and institutions respond to it. Findings reveal that misinformation created confusion in clinical protocols\, fueled public panic\, and intensified professional anxiety. Participants emphasized the need for verified communication channels\, stronger digital literacy\, and mental health support systems. The study underscores the critical role of individual responsibility\, institutional action\, and policy reform in combating the "infodemic" and protecting the well-being of healthcare workers. Recommendations include the establishment of centralized information platforms\, community-driven myth-busting initiatives\, and proactive involvement of enforcement agencies. This research calls for a multi-stakeholder approach to address misinformation as a public health risk in its own right. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:0bcc1049b77079b25be5a18644b091c5 URL:http://5thworldconferenceoninformations.sched.com/event/0bcc1049b77079b25be5a18644b091c5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Genetic Algorithm-Driven Parameter Optimization for Practical Torus Fully Homomorphic Encryption DESCRIPTION:Authors - John Paul C. Masuhay\, Reynaldo R. Corpuz Abstract - This piece of work\, setting up a new stage\, introduces a novel optimization approach for Torus Fully Homomorphic Encryption (TFHE) using Genetic Algorithms (GA). TFHE protects data privacy by facilitating calculations on encrypted data. The study integrates GA with TFHE to optimize key parameters\, such as LWE dimension\, decomposition level\, and security level\, aiming to achieve an optimal trade-off between encryption accuracy\, bootstrapping time\, ciphertext size\, and security. The GA optimization uses a multi-objective fitness function\, in which performance metrics are derived from synthetic datasets such as text\, alphanumeric\, and special characters for simulation. The results indicate that the GA framework using DEAP was effectively integrated with TFHE. After five generations\, the optimization process attained a best fitness value of 0.9691\, marking significant enhancements in system performance. Specifically\, the GA optimization improved TFHE parameters\, such as increasing the LWE dimension from 1024 to 1514.02 by reducing the noise standard deviation from 3.2 to 2.53 and improving the security level from 128 bits to 242.57 bits. The decomposition level was adjusted from 4 to 2\, optimizing computational performance while slightly reducing security. Variation in bootstrapping times across datasets reflects how efficiently the optimization balances efficiency and performance. These remarkable findings suggest that GA could potentially be applied to im-prove TFHE parameters\, making it a more efficient and secure method to perform privacy-preserving computations\, particularly within edge computing environments. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:c27353d90c50b6c85b1d6083fef31e65 URL:http://5thworldconferenceoninformations.sched.com/event/c27353d90c50b6c85b1d6083fef31e65 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Grass Quality Analysis with Unsupervised Gabor-K-Means++ and Advanced Gabor Denoising Techniques DESCRIPTION:Authors - Alpa R. Barad\, Ankit R. Bhavsar Abstract - A good quality of forage is essential to feed cattle to improve its health and productivity. Quality of grass has been affected by various factors such as weather condition\, leaf disease\, and diverse species with texture similarity. Over multiple species of grass and variation over sessions leads quality recognition more complex and difficulty. Proposed study uses unsupervised approach to reduce dependence of annotation over multiple species of grass. Proposed work uses median and fast denoising algorithm to enhance input image. Article present novel approach with integration of Gabor filter with k-means++ model. Gabor filters helps to identify optimized features over texture similarity problem of grass. Simulation of proposed study also measures denoising input grass image with 0.72 SSIM. Simulation of proposed study also finds remarkable performance with 79.86% accuracy with median and Gabor filter. Simulation of study also explore possible variations with hybrid unsupervised approach to enhance performance of the model. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:923554ddca7d92cbaf9936f76439b2e4 URL:http://5thworldconferenceoninformations.sched.com/event/923554ddca7d92cbaf9936f76439b2e4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Pattern Discovery in Genomic Sequences Using Advanced Data Mining Algorithms DESCRIPTION:Authors - GGS Pradeep\, Thrilok. Kolla\, N Vijayalakshmi\, U Ananthanagu\, Rajesh Sharma R Abstract - The booming volume of genomic data requires computational techniques that will allow the efficient extraction of biologically meaningful patterns. This work investigates advanced data mining algorithms for extracting frequent patterns and motifs in DNA and RNA sequences based on k-mer analysis. The nucleotide sequences are divided into shorter pieces called k-mers\, where frequent pattern mining\, positional frequency mapping\, and dimensionality reduction techniques are applied to expose conserved motifs and structural characteristics. The proposed methodology employs Apriori for mining\, followed by Principal Component Analysis (PCA) and a variation of a sequence logo style for visualization\, which exposes latent relationships and biologically relevant sequence patterns. The experimental data show uniformly distributed occurrences of dominant k-mers and positionally clustered functional motifs like the “ATG” codon. The PCA projections in 2D and 3D space further highlight the structural diversity and possible clustering of sequences according to k-mer profiles. This research extends the frontier of bioinformatics by aiding in the interpretation of genomic sequences\, with applications in genome annotation\, disease-associated gene prediction\, and regulatory motif identification. It serves the purpose of informing about the methods being brought together under k-mer analysis\, frequent pattern mining\, PCA\, and motif visualization. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:a95b629ebc8d545d5c0ef06a9d6a25a7 URL:http://5thworldconferenceoninformations.sched.com/event/a95b629ebc8d545d5c0ef06a9d6a25a7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Project-Based Learning: Comparing the Results of Group and Individual Projects in Undergraduate Program of Information Systems DESCRIPTION:Authors - Zlatinka Kovacheva\, Kalinka Kaloyanova\, Ina Naydenova\, Mariana Trifonova Abstract - This paper concerns project-based learning. The aim of the study is to compare the results of group and individual projects of undergraduate students studying Information systems. The research is based on statistical inference and hypotheses tests. A hypothesis test is presented regarding a difference between means of two dependent samples for quantitative indicators that have a normal distribution. The result analysis is based on 3-years experiments with student pro-jects. For all experiments\, the null hypothesis is rejected\, and in both methods of assessment (group and individual projects)\, different results are obtained. For the majority of the groups involved in the experiments\, the marks of the group project are higher than the average marks of the individual project but there are also exceptions. The results show that students who performed better on the individual project often received lower grades on the group project. Also\, students with low individual grades received higher scores on the group assessment. As a conclusion\, we can recommend applying both methods – group and individual projects for students’ assessment\, paying attention at their advantages and disadvantages. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:e4a527dd1c75bd53554fb1dcbab2576a URL:http://5thworldconferenceoninformations.sched.com/event/e4a527dd1c75bd53554fb1dcbab2576a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Robust Face Recognition System using Stable Diffusion and Synthetic Data DESCRIPTION:Authors - Nguyen Hoang Kha\, Su Truong Phuc\, Huynh Tu Anh\, Ha Cao Vi\, Tran Quoc Hao\, Vinh Dinh Nguyen Abstract - Face recognition tasks often suffer from poor performance when limited real training data is available per class. To address this\, we propose a novel pipeline that combines LoRA-based fine-tuning of a generative model with synthetic image generation and YOLOv8 classifier training. Our method fine-tunes Stable Diffusion using just a few real face images per identity\, then generates realistic\, identity-preserving synthetic images to augment the training dataset. The augmented dataset is then used to train a YOLOv8n classifier for face recognition. We evaluate our pipeline on a 31-class face dataset and achieve a Top-1 classification accuracy of 80.05%\, significantly outperforming the baseline YOLOv8n model trained only on resized real images (60.94%). These results demonstrate the effectiveness of our method in low-resource settings for face recognition. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:6156871bd50372aa0bd48374c7a63c7c URL:http://5thworldconferenceoninformations.sched.com/event/6156871bd50372aa0bd48374c7a63c7c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:StockVisionX: Leveraging Financial News Sentiment and Technical Indicators for Stock Movement Prediction DESCRIPTION:Authors - Keshav Dudani\, Nischay Jain\, Rishi Raj\, Nitesh Patnaik\, Vishal Meena Abstract - Stock market volatility and the effect of financial trends and external news perspectives are reasons why predicting the direction of the stock market is so intrinsically tough. Conventional models may fail to provide accurate forecasts when they fail to react to the quick changes in the marketplace. Our proposed method boosts the success of predicting by employing StockVisionX\, which constructs classifications by combining past stock movements and sentiment analysis of financial news sources. The sentiment polarity that is integrated into StockVisionX delivers a more thorough market movement projection\, thereby forecasting whether a stock will gain or drop in price. StockVisionX adds even more strength in its predictability with the usage of vital technical indicators such as SMA\, EMA\, RSI\, MACD\, ATR\, and OBV. Supplementing these criteria with sentiment analysis ensures a better and evidence-based manner of categorizing stock movement. The model is trained and tested on diverse datasets to analyze sentiment and forecast prices\, and task-specific optimization is seen. Our Naive Bayes technique is 54.5% more accurate when compared to Vader sentiment categorization. Our Prophet + XGBoost model\, which has been trained on non-correlated real-world data\, outsmarts ARIMA and LSTM by 49.0% and 29.6%\, respectively\, when predicting price\; however\, it is hard to determine if these models would work better with highly correlated data. This is evidence of the power and generalizability of our process. StockVisionX is efficient and precise in its classification model on predicting stock movement through the meticulous integrating of sentiment-related information with the trend history. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:ef995adacc2d3174a9e4e6875bcca6d8 URL:http://5thworldconferenceoninformations.sched.com/event/ef995adacc2d3174a9e4e6875bcca6d8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Temporal Pattern Recognition in IoT Sensor Streams Using Spatio-Temporal Reasoning DESCRIPTION:Authors - GGS Pradeep\, Thrilok. Kolla\, Rajesh Sharma R\, Akey Sungheetha\, N Vijayalakshmi\, Pellakuri Vidyullatha Abstract - The ever-increasing implementation of IoT sensor networks in smart environments has created a multitude of multivariate spatiotemporal data streams. The effective identification of temporal patterns and anomalies in those streams becomes necessary to ensure environmental awareness and operational integrity. This paper proposes an elaborate framework for temporal pattern recognition in IoT sensor data through the integration of spatiotemporal reasoning\, statistical modeling\, and anomaly detection. The approach uses statistical descriptors\, kernel density estimation\, correlation matrices\, and spatiotemporal visualization to capture local anomalies as well as trends prevalent in aggregation over distributed sensors in order to illustrate its strengths in analyzing the data. One of the case studies depicts the environmental awareness based on monitoring temperature: deviation detection\, inter-sensor coherence\, and a conceptual view of anomaly propagation. The results indicate the potential of establishing a system capable of real-time and interpretable monitoring in dynamically evolving IoT settings. This work contributes toward more adaptive and transparent sensing architectures capable of operating under uncertainty and environmental variability. The abstract is coherently structured\, flowing from motivation to case study\, methodology\, results\, and contribution. It also accurately frames the rationale for the study and successfully defines the fundamental difficulty in IoT sensor networks\, which is the recognition of temporal patterns and abnormalities. CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:a2d567efc87fccfc128ab6fde136ff1c URL:http://5thworldconferenceoninformations.sched.com/event/a2d567efc87fccfc128ab6fde136ff1c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:A COMPREHENSIVE BENCHMARK FOR EVALUATION INFERENCE STRATEGIES ON LARGE SCALE TABULAR DATASETS DESCRIPTION:Authors - Tushaar Yenduri\, S S R Subramanya Hemant Konduri\, Kalyan Netti Abstract - This study examines three inference strategies—serial\, multi-core parallel (Joblib)\, and distributed memory (MPI)—to address scalability challenges in applying machine learning models to large tabular datasets. Using the HIGGS dataset as a representative benchmark of high-volume scientific data\, a Random Forest classifier was trained and validated with performance metrics of 73.3% accuracy and 81.25% ROC-AUC. The results offer concrete guidance on selecting appropriate inference backends based on system architecture and dataset size\, particularly for practitioners in high-performance computing and scientific machine learning domains. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:5fc08cc5feb53544c77745d457d1e207 URL:http://5thworldconferenceoninformations.sched.com/event/5fc08cc5feb53544c77745d457d1e207 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Advanced Planning for Lean\, Circular and Sustainable Decision-Making in Textile Manufacturing company: A TOPSIS Approach DESCRIPTION:Authors - Kevin De la Cruz\, Alberto Taza\, Edgar Ramos\, Donovan Fuqua Abstract - The textile industry is facing growing pressure to transition toward production systems that are sustainable\, efficient\, and aligned with circular economy principles. This study develops a structured multi-criteria decision-making framework designed to integrate lean practices\, circularity\, and sustainability into strategic planning for textile manufacturing. The methodology applies the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach to evaluate and rank key operational practices considering their environmental\, operational\, and economic impacts. Results indicate that prioritizing lean initiatives with embedded circularity practices provides a dual advantage: improving short-term efficiency while simultaneously supporting broader sustainability goals. The proposed model offers decision-makers in the textile sector a practical and evidence-based tool to address challenges of competitiveness\, environmental regulation\, and sustainable value creation. Ultimately\, this research contributes to advancing integrated planning approaches that strengthen the ongoing transition toward sustainable manufacturing systems. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:647224e91f81a831782d40871b5d05be URL:http://5thworldconferenceoninformations.sched.com/event/647224e91f81a831782d40871b5d05be END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:AI-Driven Stakeholder-Centered Curriculum Design for Global Media Innovation: A Case Study from Thailand DESCRIPTION:Authors - Matana Charoenwongsa\, Sangkama Sarawat\, Laknara Chandraramya\, Waralak Vongdoiwang Siricharoen\, Thirachit Saenphon Abstract - The global media landscape is experiencing a profound shift\, shaped by the rise of artificial intelligence (AI)\, growing cross-cultural content demands\, and evolving patterns of work. This study investigates how active stakeholder participation can guide the development of an AI-integrated curriculum within global media education. Emphasis is placed on nurturing technological fluency\, interdisciplinary perspectives\, and ethically grounded innovation. Drawing on a curriculum design initiative from Thailand’s Global Media Industry and Innovation Master’s Programme\, the research explores how AI-driven tools\, media production technologies\, and entrepreneurial approaches are brought together in educational practice. Insights were collected from over 50 stakeholders—including media entrepreneurs\, policymakers\, educators\, and students—and examined through thematic content analysis. The research highlights three core priorities that shaped the curriculum design: strengthening technological fluency\, deepening global media literacy\, and encouraging social innovation through entrepreneurship. It proposes a collaborative model that addresses technological change while centring human agency\, with practical implications for curriculum reform and the future of sustainable media ventures in an AI-influenced era. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:b2be4dc2920d7e7c2688b4eea846725f URL:http://5thworldconferenceoninformations.sched.com/event/b2be4dc2920d7e7c2688b4eea846725f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:An Innovative Hybrid Approach to Image Steganography:Combining Non-Linear Cost Functions with Structured MatrixOperations for Enhanced Security DESCRIPTION:Authors - \;Chethana N S\, Anithadevi M D\nAbstract - \;We introduce a groundbreaking steganographic technique that merges non-linear cost evaluationmethods with binary triangular matrix structures to achieve superior data concealment in color images.Our approach tackles the inherent weaknesses of conventional linear cost models by implementing amultiplicative framework that more effectively maintains the statistical characteristics of images whileoptimizing embedding performance. The integration of structured binary matrices enables intelligentposition selection through organized randomization\, preserving both visual fidelity and cryptographicsecurity. Our methodology incorporates sophisticated texture evaluation\, self-adjusting parameter tuning\, andmulti-channel analysis to deliver outstanding results across various image categories. Through rigoroustesting\, we demonstrate remarkable improvements over current leading methods\, achieving averagePSNR values of 52.34 dB and SSIM scores of 0.9847 across standardized test collections from multipleimage databases. The system exhibits substantially enhanced resilience against contemporarysteganalysis tools while supporting high embedding rates up to 0.8 bits per pixel with strengthenedsecurity assurances. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:f68c1e6552cacdf22edc150768096b56 URL:http://5thworldconferenceoninformations.sched.com/event/f68c1e6552cacdf22edc150768096b56 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:BIG DATA-DRIVEN CORRECTION COEFFICIENTS IN THE 360-DEGREE FEEDBACK METHOD DESCRIPTION:Authors - YURY MIKHEEV\, URSULA PODOSENIN\, SERGEY V. SYCHOV Abstract - This study investigates the reliability and validity of the 360-degree feedback method by focusing on three primary sources of bias: respondent roles\, interpersonal relationships\, and individual evaluative styles. Drawing on data from over 15\,000 respondents across multiple organizations\, it applies a Python-based statistical algorithm to quantify the impact of these biases on competency ratings. Findings reveal that such factors can account for up to half of the variance in assessments. Mitigation approaches include evaluator anonymity\, structured training\, and correction coefficients. With these measures in place\, 360-degree feedback continues to serve as an effective tool for fair and accurate performance appraisal\, supporting personnel decisions and sustainable talent management. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:03eae4fb5cfbdd24d7fffdddc40374cf URL:http://5thworldconferenceoninformations.sched.com/event/03eae4fb5cfbdd24d7fffdddc40374cf END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Comprehensive Assessment of Deep and Traditional ML Approaches for Multiclass Skin Disease Recognition DESCRIPTION:Authors - Zarif Wasif Bhuiyan\, Zaed Bin Monir Atib\, Mahady Hasan\, Farhad Alam\, Md. Tarek Habib Abstract - Early and accurate identification of common skin conditions is essential for appropriate therapy and better clinical outcomes. However\, diagnostic expertise is often limited in resource-constrained healthcare or remote settings. We present a robust deep learning approach based on a custom convolutional neural network (CNN) to automatically classify five prevalent skin diseases (acne\, contact dermatitis\, nail fungus\, scabies\, and urticaria) from clinical images. A curated dataset of 8\,900 clinical images (1\,780 per class) was compiled\, with standardized resizing\, normalization\, and extensive augmentation applied to simulate real-world variability and enhance generalization. The CNN architecture consists of five sequential convolutional blocks with progressively increasing filters to extract high-level features\, accompanied by dropout layers to mitigate overfitting\, and includes a fully connected layer prior to the SoftMax output. On evaluation\, the model achieved an overall classification accuracy of 99%\, demonstrating robust performance and high diagnostic precision across all categories. It notably outperformed conventional machine learning classifiers as well as state-of-the-art pretrained deep networks on the same task. This exceptional performance\, combined with strong generalization capabilities\, underscores the model’s reliability and suitability for deployment in real-world clinical practice and tele dermatology settings. In such scenarios\, rapid and accurate screening for multiple skin conditions can significantly improve patient care and enable earlier interventions. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:0fcd2acac37398268708c6b5d897fc00 URL:http://5thworldconferenceoninformations.sched.com/event/0fcd2acac37398268708c6b5d897fc00 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Enhancing Open-Source Software Security Through Intelligent Monitoring of Community-Sourced Code Snippets DESCRIPTION:Authors - Amruta Khanaj\, Sourabh Khanaj\, Smita S. Sangewar Abstract - This research investigates the security implications of reusing code snippets of Stack Overflow in open-source software projects. We present a novel framework that proactively identifies and mitigates security risks associated with outdated Stack Overflow code snippets. Our methodology combines static code analysis techniques\, continuous monitoring of Stack Overflow post changes\, and an automated developer notification system. We analyzed 1.5 million code snippets from Stack Overflow approximately across 5000 popular open-source GitHub projects\, focusing on programming codes. Our observations reveal that there are a significant number of reused snippets becoming outdated over time\, with developers often missing critical security updates made to the original Stack Overflow posts. We showcase the effectiveness of our framework in detecting potential vulnerabilities and alerting developers to security relevant updates in reused code. The research emphasizes the need for continuous monitoring of community-sourced code and suggests solutions to ensure its secure integration in software development practices. Our work contributes to the broader understanding of software supply chain security and the evolving nature of code reuse in the open-source ecosystem. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:b788ea9a06e8836e1523eaf89af732c5 URL:http://5thworldconferenceoninformations.sched.com/event/b788ea9a06e8836e1523eaf89af732c5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Grading\, Packaging\, and Real-Time Transport Management System of Agriculture DESCRIPTION:Authors - Mst.Sadia Siddika\, Sherin Sultana\, Md. Tarek Habib\, Sabrina Alam\, Md. Mahbub Alam\, Mahady Hasan Abstract - Agricultural products are graded based on their quality and adherence to standards. Managing the grading\, packaging\, and transportation of products\, especially perishable items like food\, is crucial for maintaining freshness and safety. Packaged goods are transferred to storage facilities and prepared for transportation. To maintain product freshness\, a well-organized and traceable supply chain is essential. This study demonstrates how technologies such as the Internet of Things (IoT) can facilitate an agricultural supply chain system that uses maps\, computer vision\, smart packaging\, and smart barcodes. These technologies help track products in real-time\, ensure data security via databases\, and streamline supply chain operations through web-based platforms. Using an app-based system\, the solution highlights traceability\, automation\, and user-friendly interfaces to optimize efficiency from farm to market. The app also provides automated alerts and real-time inventory updates for both customers and sellers. Additionally\, the system should integrate IoT-based temperature and humidity monitoring to maintain the quality of perishable goods. Overall\, this study suggests that combining these advanced technologies into a unified system can address challenges in traditional methods\, such as delays and product quality loss. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:7ea0084567c3c881261b0c8f73a93bd9 URL:http://5thworldconferenceoninformations.sched.com/event/7ea0084567c3c881261b0c8f73a93bd9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Intelligent information system for proactive management of a printing enterprise DESCRIPTION:Authors - Kostaryev D.B.\, Tevyashev A.D.\, Sizova N.D.\, Tkachenko V.P. Abstract - An intelligent information system for proactive management of a printing enterprise based on artificial intelligence is proposed. Approaches to proactive enterprise management grounded in Industry 4.0/5.0 are substantiated\, including the use of relevant scientific methods and mathematical models. The architecture of the information system\, based on mathematical models and scientific principles\, has been developed. The results of evaluating the effective-ness of implementing and using this intelligent information system at a printing enterprise are presented. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:ac1c00ad3325c91a5e04ef878ea24917 URL:http://5thworldconferenceoninformations.sched.com/event/ac1c00ad3325c91a5e04ef878ea24917 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261018T220000Z DTEND:20261019T000000Z SUMMARY:Rural Bangladesh Before COVID: Baseline Trends and District Forecasts from the Life in the Field Program DESCRIPTION:Authors - Zarif Wasif Bhuiyan\, MD. Humayun Kabir\, Paramita Saha\, Md Mahbub Alam\, Mahady Hasan Abstract - Urban–rural evidence in Bangladesh is often fragmented or short-lived\, limiting its value for tracking change. This study leverages the Life in the Field Experience at Independent University\, Bangladesh to build a pre-COVID baseline from eight annual waves of student-collected surveys spanning 2013–2020 across six districts: Jessore\, Bogra\, Mymensingh\, Sylhet\, Barishal\, and Dinajpur. Heterogeneous spreadsheets are harmonized into standardized sector indices for education\, medications and health service use\, employment\, marital history\, acute morbidity\, and chronic morbidity. A transparent pipeline handles header inconsistencies\, variable shifts\, and missingness\, producing comparable annual series. ARIMA models are estimated for Jessore to generate five-year projections and are interpreted alongside cross-district benchmarking using z-scores. Results show steady gains in education that level off\, an employment dip followed by recovery\, rising medication use\, low and stable acute morbidity\, a gradual increase in chronic morbidity\, and largely stable marital patterns. Forecasts are framed as extensions of pre-COVID dynamics with explicit uncertainty. The pipeline provides a reusable template for short annual series and supports policy diagnosis at district level. Future work will extend forecasting to all districts\, incorporate structural-break tests and hierarchical models\, and enrich indices with external covariates and administrative validation. CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:c890006c3ae4efd17dca754a892481bf URL:http://5thworldconferenceoninformations.sched.com/event/c890006c3ae4efd17dca754a892481bf END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000000Z DTEND:20261019T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:49e238ed68a1ecd001ed84d262fa680e URL:http://5thworldconferenceoninformations.sched.com/event/49e238ed68a1ecd001ed84d262fa680e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000000Z DTEND:20261019T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:ded0d2b6f428339d8895d952d3118e9a URL:http://5thworldconferenceoninformations.sched.com/event/ded0d2b6f428339d8895d952d3118e9a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000000Z DTEND:20261019T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:f560c297f60e5da7909a1791e563e35b URL:http://5thworldconferenceoninformations.sched.com/event/f560c297f60e5da7909a1791e563e35b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000000Z DTEND:20261019T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:34a2907d2084bffbc16a69795ed8ea2a URL:http://5thworldconferenceoninformations.sched.com/event/34a2907d2084bffbc16a69795ed8ea2a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000000Z DTEND:20261019T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:f5e7ae072756770cc1a69fd771846bf2 URL:http://5thworldconferenceoninformations.sched.com/event/f5e7ae072756770cc1a69fd771846bf2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000000Z DTEND:20261019T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:2d41856809144e58c2a5b3c05ab0d2ea URL:http://5thworldconferenceoninformations.sched.com/event/2d41856809144e58c2a5b3c05ab0d2ea END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000200Z DTEND:20261019T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:73fe8e4a94e6c71a91b950099edf6b63 URL:http://5thworldconferenceoninformations.sched.com/event/73fe8e4a94e6c71a91b950099edf6b63 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000200Z DTEND:20261019T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:bf816c512c452b570b8710e8e8557645 URL:http://5thworldconferenceoninformations.sched.com/event/bf816c512c452b570b8710e8e8557645 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000200Z DTEND:20261019T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:9240faa0f99142a230059de4d33b2a0b URL:http://5thworldconferenceoninformations.sched.com/event/9240faa0f99142a230059de4d33b2a0b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000200Z DTEND:20261019T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:e3a7665052d3a446b50b6c27e5f53b27 URL:http://5thworldconferenceoninformations.sched.com/event/e3a7665052d3a446b50b6c27e5f53b27 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000200Z DTEND:20261019T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:72e0881ba23952ce5ef4e23c788e8b96 URL:http://5thworldconferenceoninformations.sched.com/event/72e0881ba23952ce5ef4e23c788e8b96 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T000200Z DTEND:20261019T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 6F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:1fb3c7a28105b9787798510bb4e44990 URL:http://5thworldconferenceoninformations.sched.com/event/1fb3c7a28105b9787798510bb4e44990 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T162800Z DTEND:20261019T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:4d8b4e8a4190f947505efb91589766b7 URL:http://5thworldconferenceoninformations.sched.com/event/4d8b4e8a4190f947505efb91589766b7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T162800Z DTEND:20261019T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:55eed99d30c9132dbf1651d37c854859 URL:http://5thworldconferenceoninformations.sched.com/event/55eed99d30c9132dbf1651d37c854859 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T162800Z DTEND:20261019T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:9294e744419bc1ceda8af4e421c9382c URL:http://5thworldconferenceoninformations.sched.com/event/9294e744419bc1ceda8af4e421c9382c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T162800Z DTEND:20261019T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:45c9e9bf55e064da4bf3f1dcac52ddbc URL:http://5thworldconferenceoninformations.sched.com/event/45c9e9bf55e064da4bf3f1dcac52ddbc END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T162800Z DTEND:20261019T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:d14260a902792cdd481bf0abbab7afb0 URL:http://5thworldconferenceoninformations.sched.com/event/d14260a902792cdd481bf0abbab7afb0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T162800Z DTEND:20261019T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:e8699f61fc45d666a84b7961be316a6b URL:http://5thworldconferenceoninformations.sched.com/event/e8699f61fc45d666a84b7961be316a6b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T162800Z DTEND:20261019T163000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:b652959ae3c360ccb810321f5c5daaa4 URL:http://5thworldconferenceoninformations.sched.com/event/b652959ae3c360ccb810321f5c5daaa4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:A Comparative Review of Employee Engagement and Retention Strategies in Public and Private Sector Banks DESCRIPTION:Authors - Sapna B. Warghane\, Ajay Pethe Abstract - Modern banking institutions recognize employee engagement and retention as critical to achieving long-term goals. These elements influence productivity\, innovation\, and customer satisfaction. Public and private sector banks adopt different strategies shaped by political culture\, regulatory environments\, and competitive dynamics. Public Sector Banks (PSBs) offer job security\, structured career growth\, and welfare benefits\, fostering stability and long-term com-mitment. These factors contribute to employee motivation and consistent performance but may limit agility and innovation. In contrast\, Private Sector Banks (PvSBs) emphasize performance-based incentives\, career mobility\, and a dynamic work environment. While these strategies enhance engagement and drive results\, they can also lead to stress and higher employee turnover. Organizational culture\, compensation\, career development\, work-life balance\, and employee well-being play significant roles in shaping these outcomes. This review compares engagement and retention strategies across both sec-tors\, identifying the strengths and challenges of each. A hybrid approach—combining financial rewards\, career development opportunities\, and wellness initiatives—is recommended to enhance satisfaction and commitment across the board. By refining these strategies\, both PSBs and PvSBs can develop a more engaged and resilient workforce\, ultimately supporting long-term organizational success and stability. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:c5eaf144beff7d4a7d812abb13e30937 URL:http://5thworldconferenceoninformations.sched.com/event/c5eaf144beff7d4a7d812abb13e30937 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:A SYSTEMATIC LITERATURE REVIEW: SAAS MARKETING STRATEGY DESCRIPTION:Authors - Jannat Khair Chowdhury\, S. M. Saikat Hossain\, Farzana Sadia\, Mahady Hasan\, M. Rokonuzzaman\, Marufa Akter Abstract - Developing an effective marketing strategy is crucial for the success of Software-as-a-Service (SaaS) businesses\, given the dynamic and competitive nature of the market. This systematic literature review looks at major tactics including pricing structures\, client acquisition and retention\, and digital technologies. It emphasizes the problems of transferring academic findings to industry\, with an emphasis on data-driven solutions such as hybrid pricing\, freemium models\, and tailored content. The report provides recommendations for optimizing SaaS marketing to promote scalable\, long-term growth. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:b0bf3f5a5e9c7a21e146fcf308a4b756 URL:http://5thworldconferenceoninformations.sched.com/event/b0bf3f5a5e9c7a21e146fcf308a4b756 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Advanced Supply Chain Planning Model to Boost Resilience and Sustainability: Evidence of a Pharmaceutical Supply Chain DESCRIPTION:Authors - Juan Mejia\, Valentino Galindo\, Edgar Ramos\, Donovan Fuqua Abstract - This study proposes a conceptual model that integrates advanced supply chain planning to enhance supply chain resilience and sustainability. Drawing from previous literature\, the study explores how such planning approaches contribute to strengthening supply chains and improving long-term operational stability. The model is developed through a structured review of academic sources and expert perspectives\, with an emphasis on theoretical alignment and systemic relevance. Using the Best-Worst Method (BWM) as a decision-making framework\, the paper outlines key factors that may influence effective resource allocation and disruption management. While no empirical validation is conducted\, the study highlights potential criteria for improving operations\, particularly in terms of reducing disruptions and optimizing resource use. This work offers a foundation for future empirical research and supports ongoing discussions on resilient and sustainable supply chain strategies. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:899d1d5317e674c8bbdab9a9548c205c URL:http://5thworldconferenceoninformations.sched.com/event/899d1d5317e674c8bbdab9a9548c205c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:BERT-Based Text Classification Pipeline for Categorising Mental Health Statements DESCRIPTION:Authors - Divya Saleela\, Reshma Lucos\, Reji R\, Teena Joseph\, Shyna A\, Chinchu M S\, Hashna Rasheed\, Arjun Rajesh Panicker Abstract - The automatic classification of mental health-related textual data is essential for enabling scalable and proactive psychological support. This study employs a fine-tuned BERT-base transformer model categorise statements into seven clinically relevant mental health conditions. The model was evaluated using a publicly available dataset from Kaggle and assessed with standard performance metrics\, including accuracy\, precision\, recall\, specificity\, and F1-score. Achieving an overall accuracy of 90.00 per cent\, the model demonstrated strong generalisability across a linguistically diverse and imbalanced corpus. The highest classification performance was achieved in the Normal\, Depression\, and Suicidal categories\, with satisfactory results obtained for less frequent classes. These findings highlight the effectiveness of transformer-based architectures in mental health text classification and support their potential application in digital screening and early intervention systems. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:ba73c92706718e1436f291de6685da4d URL:http://5thworldconferenceoninformations.sched.com/event/ba73c92706718e1436f291de6685da4d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Driving change: Analyzing visual advertisements of Tata EV cars through Archetypal Branding through sustainable advertising DESCRIPTION:Authors - Gokul B\, Arumugam Balasubramanian Abstract - Climate change and sustainable ecosystem are gaining momentum in the public domain. Innovative technology is steering towards environmental protection enabled products and processes. Tata motors have captured the public imagination by lining up green vehicles with clean fuel. In order to accelerate the adoption of this innovative product they have embarked on an advertising campaign that not only caters to product marketing but also satisfies their inner desire towards contributing their might in the green initiatives. To this end\, content analysis is used as a methodological tool to examine whether archetypal advertising strategies align with Tata Motors’ goal of promoting innovation in a sustainable manner. Analysis has come out quite clearly that archetypal advertising strategy are put to effective use to successfully kindle their desire and satisfy the consumers motivation towards adopting automotive innovation in the context of green commerce. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:5f90cbf295d1a1ad96a5f6e14c7f5178 URL:http://5thworldconferenceoninformations.sched.com/event/5f90cbf295d1a1ad96a5f6e14c7f5178 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Empowering Women in Business Leadership Challenges\, Opportunity and Strategies for Advancement DESCRIPTION:Authors - Asra Fatema Zakir Baig\, Amol Mashankar Abstract - Women in business leadership must be empowered through promotion of diversity\, innovation\, and sustainable growth. Conceding that there have been noticeable gains\, women remain way behind in their quest for leadership positions\, due to multifaceted barriers\, such as systemic biases\, limited access to their networks\, and societal expectation\; this paper discusses the organizational culture and its gender-based stereotypes and the lack of mentorship\, which hold back women's advancement in business leadership. Further\, it goes on discussing the various opportunities that now come forth from women's leadership empowerment\, further focusing on the advantages of a diverse leadership team: better decision-making and improved performance for companies. Through real examples of best practices\, the authors demonstrate which organizations have applied some of the best diversity and inclusion strategies followed by positive results from investing in women's leadership development. The paper speaks to actionable strategies an organization can employ in addressing the challenges and seizing the opportunities available. It focuses first on creating an inclusive workplace culture followed by starting out with mentorship and sponsorship programs\, targeted training and development. And finally work arrangements and others that also involve policies that support work-life balance and equal pay and works continually in amplifying the need for systemic change in creating an environment that avails women's advancement. Finally\, women's empowerment in business leadership is more about equity and strategic advantage as a group for organizations to leverage benefits. In the end\, embracing diversity in leadership can help unlock potential\, drive innovation\, and develop a resilient workforce for businesses. This paper\, therefore\, calls for collective efforts from stakeholders across all levels to advance women's leadership and pave the way for unlocking the silos of barriers in the business world. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:b4e497c044a99c07fd18274159fcb86c URL:http://5thworldconferenceoninformations.sched.com/event/b4e497c044a99c07fd18274159fcb86c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Harnessing Social Media to Advance Social Entrepreneurship in Bangladesh: A Qualitative Study DESCRIPTION:Authors - Sazzad Hussain Farhaan\, Tanvir Hussain Himel\, Ahsanul Kaiser\, Md. Nayon Ali Abstract - Utilising digital technology is more crucial than ever\, especially social media\, to address urgent societal issues and encourage creative solutions. Since traditional infrastructures and resources may be few in underdeveloped nations like Bangladesh\, social media provides an affordable and easily accessible avenue for impact\, creativity\, and collaboration. This strategy continues the heritage of Grameen Bank and Dr. Muhammad Yunus\, who pioneered creative social entrepreneurship through microfinance. The use of social media to promote social entrepreneurship in Bangladesh is examined in this qualitative study. Based on 20 in-depth interviews with people involved in social entrepreneurship\, the study explores how digital platforms may support social transformation\, especially in environments with limited resources. Purposive sampling was used to choose participants\, guaranteeing that they had at least a year of experience utilising social media for social entrepreneurship. Social media is a vital tool for outreach\, community involvement\, fundraising\, and creating awareness\, according to the findings. By overcoming conventional obstacles\, it enables business owners to reach a larger audience and rally support for social causes. Future research can be done on digital infrastructure\, and community participation affect social media’s ability to promote social entrepreneurship. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:20b6f37565cb548b878f3f48bd10cf11 URL:http://5thworldconferenceoninformations.sched.com/event/20b6f37565cb548b878f3f48bd10cf11 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Impact Analysis of Incubates Funded Under Government Scheme DESCRIPTION:Authors - Radhika V. Kulkarni\, Spandan Papade\, Yash Paryani\, Saniya Patil\, Rahul Madhawani\, Prakash Sharma Abstract - Governments worldwide actively support entrepreneurs tackling pressing social issues\, aiming to boost economic opportunities for all\, generate employment\, and accelerate tech-driven progress. Unfortunately\, some recipients exploit these funds for personal gain\, sidelining projects that could otherwise drive fair governance\, community welfare\, and environmentally conscious industries. Manually tracking thousands of funded startups is inefficient\, allowing dis-honest actors to slip through the cracks. This study introduces an AI-powered solution to bridge this gap. The system scans public data—such as LinkedIn activity and online footprints—to identify red flags\, like founders holding jobs un-related to their funded ventures. Advanced language analysis and pattern recognition techniques assess how closely a founder’s current work aligns with their original proposal\, simplifying oversight while fostering synergy between public programs and modern technology platforms. By promoting fairness\, transparency\, and accountability\, the system supports several United Nations Sustainable Development Goals\, including SDG 8: Decent Work and Economic Growth\, SDG 9: Industry\, Innovation\, and Infrastructure\, and SDG 16: Justice\, and Strong Institutions. It enables governments to channel resources more effectively to innovators committed to creating lasting social value. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:f9512b63c05968c3e1cb1603f3a0de51 URL:http://5thworldconferenceoninformations.sched.com/event/f9512b63c05968c3e1cb1603f3a0de51 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Instagram motivations towards sustainable fashion apparel purchase: understanding the dynamics of consumer identities and sustainability related psychological and behavioural constructs DESCRIPTION:Authors - Ashiqha Sultana\, Kalyani Suresh Abstract - Sustainable fashion apparel purchase on Instagram has utmost importance in recent times\, as Indian consumers are currently influenced by many factors that finally lead them to purchase intention. This paper tries to examine and explore the Indian consumer mindset towards sustainable fashion apparel on Instagram and the connection between demographics and consumer identity of the consumers with the sustainable constructs. Responses were taken from 100 respondents using snowball sampling from different parts of India. Results of the study show that there is a significant association between demographics\, patterns of interacting with sustainable fashion apparel on Instagram\, and Consumer Identity. The study also reveals the strong connection between Indian consumers and purchase intention\, consumer identity\, sustainable constructs\, purchase behaviour\, and Instagram motivation. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:aea06b582c536b730ea1179d1561355c URL:http://5thworldconferenceoninformations.sched.com/event/aea06b582c536b730ea1179d1561355c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:The Impact of Artificial Intelligence on Business Decision-Making: Opportunities\, Challenges\, and Strategic Implications DESCRIPTION:Authors - Sapna B. Warghane\, Ajay Pethe Abstract - Artificial Intelligence (AI) has had a significant effect on decision-making in business by providing data-driven decision-making\, improving efficiencies and decision-making accuracy. This literature review will elaborate on the impact of Artificial Intelligence on decision-making in business and its various components\, such as predictive analytics\, automation\, risk management\, marketing personalization\, strategy\, etc. It will also explore issues\, ethics\, and future prospects of AI in business-related decision-making. AI has already been adopted in various industries\, including finance\, healthcare\, retail\, and manufacturing\, to increase efficiencies and optimize operations while attempting to optimize the customer experience. On the other side of AI\, increasing utilization creates other challenges about bias\, security\, and regulatory compliance must be considered in the sustainable growth of AI in business. CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:b6dd3ccb41e41fcfb572062683ba13e2 URL:http://5thworldconferenceoninformations.sched.com/event/b6dd3ccb41e41fcfb572062683ba13e2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:A Novel Design of Miniaturized Heptagonal Koch Fractal Wide Band Antenna for 5G mmWave Applications DESCRIPTION:Authors - J. Silamboli\, Divya Rani M S\, G Dhivyasri\, Nagesh H\, J Ajayan\, Manaswini R\, Kalyandurg Rafeeq Ahmed\, M Manikandan Abstract - This article uses Koch fractals to demonstrate a compact heptagonal wideband antenna for 5G mm-wave applications. This antenna is designed with defective ground planes to enhance impedance matching and employs Koch fractal geometry for wideband characteristics. In terms of performance and wideband features\, fractal antennas prove to be more effective than other antennas. This antenna is designed to achieve greater gain and improved bandwidth characteristics while also minimizing interference at higher frequencies. A peak realized gain of 5dBi at 27.58 GHz is observed for the antenna\, which offers a bandwidth between 26.5 and 40 GHz. Millimeter-wave integration is well suited to the proposed flexible antenna. A similar response can be found both in the measured results and in the simulated results. It is a compact antenna with a size of 9 mm by 9 mm. With a bandwidth of 7.42GHz\, the VSWR for the whole frequency spectrum is less than 2 is achieved with the HFSS Tool. Experiments and simulations yield a good radiation pattern. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:28b91baf16fc403bf2950e453daa2bb1 URL:http://5thworldconferenceoninformations.sched.com/event/28b91baf16fc403bf2950e453daa2bb1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:A Novel Financial Market Prediction Framework Based on Deep Learning for Accurate Trend Forecasting DESCRIPTION:Authors - Priya Shirley Muller\, Yadala Sucharitha\, Shilpa Kottapally\, Gulshodakhon Ismoilova\, Lola Rakhimova\, Pundru Chandra Shaker Reddy Abstract - Many scholars worry about the stock market\, a key economic component. Many experts are exploring how to forecast stock prices and market trends. Previous prediction methods centered on geometric and neural network models\, which have become admired. Although not typically utilized in financial time series\, deep learning offers excellent learning abilities and is ideal for complex timeseries. Due to its cyclic structure\, the LSTM network has long-term memory\, making it perfect for financial timeseries anticipation. A new stock closing price anticipation framework yields better predictions than standard models in the study. Data pre and postprocessing use empirical-wavelet-transform (EWT) and outlier-resilient-extreme learning-machine (ORELM) models. Dropout strategy and particle swarm optimization (PSO) method optimize the mixed frame's primary component\, an LSTM predictor. Each hybrid framework algorithm can maximize its functionalities to improve prediction ac-curacy. Three hard datasets are used for predicting trials to test the model. To demonstrate the framework's efficacy\, some comparison models are chosen. Investigational results reveal that the hybrid approach proposed in the study has the best anticipation accuracy and may be used for stock market data investigation. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:3a83d41853cbe6307f1cbc5be3a5685a URL:http://5thworldconferenceoninformations.sched.com/event/3a83d41853cbe6307f1cbc5be3a5685a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Enhancing Personal Financial Decision-Making in the Digital Era: Awareness\, Adoption\, and Influence of Digital Personal Finance Tools DESCRIPTION:Authors - Chandana M C\, Roshna Rahim\, Aarathy K Sudhakaran Abstract - In the current situation where technology is getting an important part of our day-to-day life\, digital money management is an important necessity and convenience. This study examines the role of digital personal finance literacy and how it influences people’s financial behaviors\, decision-making\, and overarching stability. It looks at how aware people are of digital financial tools\, how they feel about digital versus traditional methods\, and the outcomes of certain investing techniques. The research highlights how digital tools can make people financially empowered but also acknowledgeable hurdles such as lack of access and know-how. Skills\, to create economically successful and knowledgeable communities and in this way fosters social inclusion. It focuses on enhancing digital finance literacy to contribute to building economically strong and sustainable communities in this dynamically evolving digital period. The study will require 156 people to gain factual results\, including those from various backgrounds and locations. A structured questionnaire will be filled through a google form to collect data. The questions will cover areas such as awareness of digital financial services\, changes in behavior due to these services\, preference for digital or traditional platforms\, and long-term economic impacts. The questionnaire will be a set of close-ended questions comprising mostly multiple-choice options\, with a few examples using a Likert scale so that it can be analyzed in an easy and evident way. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:bb6834b147ec67f7bd2b6e1a36d89800 URL:http://5thworldconferenceoninformations.sched.com/event/bb6834b147ec67f7bd2b6e1a36d89800 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:HomeCookSL: A Digital Approach to Addressing Food Insecurity through Empowering Home-Based Food Businesses with focus to Nutrition\, Hygiene and Business Sustainability DESCRIPTION:Authors - Achala Fernando\, Shyani Siriwardene\, Salitha Dinushika Abstract - "Food Insecurity" is a widespread global challenge that significantly impacts individuals\, particularly students and working professionals living away from home. This issue extends beyond mere access to food\, encompassing the quality\, nutrition\, and hygiene of the available options. Home-based food (HBF) vendors often face difficulties in establishing and sustaining their presence in the competitive food market\, further complicating consumers' access to nutritious and hygienic meals. This research aims to address these challenges through HomeCookSL\, a digital platform designed to empower HBF vendors by enabling them to effectively showcase their recipes while providing users with comprehensive nutritional information and meals tailored to their dietary preferences. By facilitating informed meal decisions and promoting healthy eating habits\, HomeCookSL not only enhances consumer satisfaction but also fosters the growth and sustainability of local HBF businesses\, contributing to a more resilient food ecosystem. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:edcce1b886106d4195ab929a46ef77b4 URL:http://5thworldconferenceoninformations.sched.com/event/edcce1b886106d4195ab929a46ef77b4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:MasquerAge: Anonymous Age Verification Using the Modular Open Source Identity Platform DESCRIPTION:Authors - Ivan Cassidy A. Cadiang\, Jared L. Hechanova\, Wilson M. Tan Abstract - Traditional identity verification methods pose significant challenges to user privacy and security\, often requiring individuals to disclose more personal information than necessary for manual verification. As the country advances toward a digital economy\, the Philippine Identification System (PhilSys) provides an opportunity to shift from physical document checks to a unified and secure digital identity framework. This paper introduces MasquerAge\, an age verification system leveraging the Modular Open Source Identity Platform (MOSIP). The system utilizes MOSIP-based IDs\, containing QR codes aligned with PhilSys specifications\, to perform secure age verification. A web application was developed to facilitate scanning QR codes and authenticating users via MOSIP APIs. Performance testing showed the system to be generally efficient\; however\, cryptographic processes required by MOSIP introduced noticeable latency. The results highlight the viability of a privacy-preserving age verification system while identifying areas for optimizations and security enhancements in real-world implementations. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:24f6ff6f3caf7fda8fbb6665ebcafdf4 URL:http://5thworldconferenceoninformations.sched.com/event/24f6ff6f3caf7fda8fbb6665ebcafdf4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Optimizing banks' decision-making architecture in the context of corporate and business-oriented BI Models DESCRIPTION:Authors - Efrem MBAKI LUZAYISU Abstract - The aim is to analyze the possibilities of optimizing decision-making systems in financial institutions\, essentially based on a comparison of two models: centralized (corporate) BI and decentralized (business) BI under four do-mains — decision-making efficiency\, data governance\, agility and user satisfaction — The article evaluates the advantages and limitations of each approach. The study is based on a qualitative methodology combining semi-structured interviews and documentary analysis\, applied to two major European banks. Based on concrete indicators (reporting time\, adoption of BI tools\, GDPR compliance\, satisfaction)\, the article puts into perspective the trade-offs between centralization and autonomy\, and proposes avenues towards hybrid architectures reconciling rigor\, flexibility and innovation. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:bd227d74f23a930a6a2e2cae5a4d133b URL:http://5thworldconferenceoninformations.sched.com/event/bd227d74f23a930a6a2e2cae5a4d133b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Psychological Capital and Entrepreneurial Passion: The Moderating Role of Environmental Dynamism in Chinese Nascent Entrepreneurs DESCRIPTION:Authors - Mo Xiao\, Chatchai Chatpunyakulr\, Sarist Gulthawatvichai Abstract - This study investigates how psychological capital (PsyCap) influences nascent entrepreneurial behavior in China's dynamic economic environment\, with a focus on passion mediation and environmental contingencies. Drawing on social cognitive theory and planned behavior frameworks\, we propose an integrated model testing (1) PsyCap direct effects on passion and venture activity\, (2) passion's mediating role\, and (3) environmental dynamism's moderating effects. Using stratified sampling across three Chinese innovation hubs (N=387)\, we employ mixed methods combining SEM with fuzzy-set qualitative analysis. Findings reveal industry-specific boundary conditions where regulatory turbulence amplifies PsyCap impact in tech sectors but attenuates effects in policy-sensitive domains. The study contributes a cognition-anchored PsyCap measurement model while informing adaptive training protocols for nascent entrepreneurs facing institutional voids. Future research should examine cultural contingencies in emerging economies through longitudinal designs. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:1730b67f99308fc0d02bbba1bc41ee1b URL:http://5thworldconferenceoninformations.sched.com/event/1730b67f99308fc0d02bbba1bc41ee1b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Smart Business: AI Applications in Entrepreneurship DESCRIPTION:Authors - Nitin Prakash\, Kajal P. Salampuriya Abstract - Significant progress has been made in integrating artificial intelligence (AI) with entrepreneurship\, which has changed conventional business structures. AI is used by entrepreneurs to improve automation\, predictive analytics\, and decision- making\, which increases operational effectiveness and fosters creativity. This abstract examines the various applications of artificial intelligence (AI) in entrepreneurship\, emphasising how these applications can revolutionise strategic planning\, consumer involvement\, and the development of flexible and adaptable businesses. The adoption of AI technology by entrepreneurs confers a competitive advantage in navigating intricate markets and promoting sustainable growth\, hence highlighting the critical role of AI in defining the trajectory of entrepreneurial endeavours. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:6d1251620fcf5f9d4e6f63e7e2f1bf4a URL:http://5thworldconferenceoninformations.sched.com/event/6d1251620fcf5f9d4e6f63e7e2f1bf4a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:The Psychology of Digital Brand Engagement: Understanding Consumer Responses to UGC\, BGC and AIGC DESCRIPTION:Authors - Ioseb Gabelaia Abstract - In the digital attention economy\, brands are increasingly utilizing diverse content strategies\, including user-generated content (UGC)\, brand-generated content (BGC)\, and AI-generated content (AIGC)\, to engage consumers and shape their brand perception. This research investigates the psychological mechanisms that influence consumer engagement with these three content forms\, utilizing cognitive processing theory (CPT). The research insights are based on a survey of 291 respondents\, which measured engagement behaviors\, emotional responses\, and perceived authenticity. Moreover\, 17 marketing professionals\, through semi-structured interviews\, provided insights into content reception\, trust dynamics\, and platform-specific interaction patterns. Results indicate that UGC produced the highest levels of perceived authenticity and emotional resonance\, positively influencing engagement and brand trust. BGC was associated with consistent brand identity but yielded moderate emotional impact. AIGC\, while efficient and scalable\, generated uncertain responses\, valued for personalization yet questioned for credibility. Thematic analysis of the interviews underscored the growing strategic integration of AIGC in marketing while also highlighting consumer sensitivity to transparency and ethical content sourcing. This research contributes to the knowledge of digital marketing by examining how psychological responses to different content origins influence digital brand engagement. Moreover\, the practical implications highlight the need for content hybridization strategies that strike a balance between authenticity\, control\, and scalability. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:b823f6abfa7dc61b4794b132547d6223 URL:http://5thworldconferenceoninformations.sched.com/event/b823f6abfa7dc61b4794b132547d6223 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:The Role of Agriculture in the Food Industry and Global Trade: Challenges and Opportunities DESCRIPTION:Authors - Kajal P. Salampuriya\, Deepak S. Sharma Abstract - Agriculture forms the foundation of the global food industry\, ensuring food security and contributing significantly to economies worldwide. The agriculture contributes half of the india’s population it is the backbone of the nation’s economy. Agriculture encomposses of different activities like crop cultivation\, livestrock breeding\, poultry farming\, cattle husbandry and aquaculture. This paper explores the interrelation between agriculture\, the food industry\, and international trade\, highlighting the challenges such as climate change\, supply chain disruptions\, and trade barriers. It also investigates opportunities for growth through technological advancements\, sustainable practices\, and global market expansion. This study concludes by emphasizing policy recommendations for enhancing agricultural productivity and export capabilities to meet the growing global food demand. With a diverse climate supporting cultivation of various crops\, India ranks among the world’s top producers of agricultural and food products in financial year 2021-22\, the agricultural sector grew at an estimate rate of 3.9%\, exceeded the previous year’s growth rate 3.6% respectively. Globalization has amplified the necessity for the countries to actively engage in international trade\, merging the national market into a competative global economy. Rapid technological advancements and scientific progress continue to redefine agricultural practices\, including machinization and chemical innovations\, it helps to increase productivity and international competitiveness. This article highlights the challenging role of agriculture in economy and the growing importance of technical advancements\, globalization\, trade and the different opportunities. CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:bc65029dd3a2507effd85793d197e0de URL:http://5thworldconferenceoninformations.sched.com/event/bc65029dd3a2507effd85793d197e0de END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:A Study on The Adoption of UPI Applications in Kerala Among Generation X DESCRIPTION:Authors - Syamanarayanaprabha S S\, Abymon A\, Aarathy K Sudhakaran Abstract - Digital transactions in India have increased significantly since the National Payments Coperation of India introduced the Unified Payments Interface (UPI) in 2016. This study focuses on Generation X (ages 45-60) in Kerala\, a state known for its high level of digital literacy\, whereas adoption studies have mostly focused on younger generations like Millennials and Gen Z. The results\, which are based on responses from 132 participants\, show that security\, transaction speed and convenience of use are important element that promote UPI adoption within this demographic. However\, technological difficulties and security-related worries still serve as obstacles. To increase UPI acceptance in this group\, the study emphasizes the need of more user-friendly application designs\, focused digital education initiatives\, and calculated interventions. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:eb8612e6702fc0b779bc9ec269a87559 URL:http://5thworldconferenceoninformations.sched.com/event/eb8612e6702fc0b779bc9ec269a87559 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Accelerating AI Agent Development through a Domain-Specific Programming Language DESCRIPTION:Authors - Salvatore Vella\, Fatima Hussain\, Salah Sharieh\, Murrium Zaheer\, Alex Ferworn Abstract - Artificial Intelligence (AI) using Large Language Models (LLMs) is now used to automate simple knowledge worker tasks such as creating communications and summarizing documents. This paper presents a domain-specific language for creating agents\, which we call ContentCreator (CC)\, to perform common knowledge worker tasks and mimic the behaviour of knowledge workers and their workflows. An interpreter has been built to execute and automate these workflows. In the same way that computer languages have progressed from assembly language to increasingly higher-level languages\, CC enables the high-level programming of workflows that utilize large language models. CC is a simple language that non-programmers can use and understand. We use several use cases to demonstrate the ability of ContentCreator to automate workflows across multiple tasks. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:a3df635619fb929219a304938f07310f URL:http://5thworldconferenceoninformations.sched.com/event/a3df635619fb929219a304938f07310f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Adopting smart tools in the mango leagile supply chain for enhancing the circular supply chain DESCRIPTION:Authors - Bryan Atunca\, Henry Coico\, Edgar Ramos\, Araceli Macassi\, Donovan Fuqua Abstract - The adoption of digital technologies and intelligent systems is significantly enhancing efficiency and safety across the global agri-food industry. Integrating Industry 4.0 objectives with circular economy principles offers effective solutions to challenges such as resource scarcity and environmental impact. This study proposes a leagile supply chain model—combining lean and agile method-ologies—to optimize mango supply chains worldwide. By leveraging Cyber-Physical Systems (CPS) in postharvest processes such as drying and storage\, the model enables remote monitoring and control of key environmental parameters. CPS technologies\, through sensors\, actuators\, and data-driven algorithms\, provide real-time feedback\, minimize human error\, and support precision in decentralized processing units. Findings show a reduction in total supply chain time from 41 to 30 days (26.8%)\, with efficiency gains of 25% in harvesting and 28.5% in storage. The integration of CPS strengthens circular supply chain practices\, reduces losses\, and enhances sustainability\, profitability\, and system resilience across global mango supply chains. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:cf921e6582dd220ae59a186c87efb239 URL:http://5thworldconferenceoninformations.sched.com/event/cf921e6582dd220ae59a186c87efb239 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:An Attention-Based Deep Learning Framework for Gold Price Prediction using Time Series Data DESCRIPTION:Authors - Abhijit T. Somnathe\, Parameshwari M\, Sampurnima Pattem\, Sridhar N Koka\, Shokhida Abdurakhmanova\, Pundru Chandra Shaker Reddy Abstract - Gold prices are non-linear\, unexpected\, volatile\, and unregulated\, making prediction difficult. Numerous studies have anticipated gold prices because they affect international economic and monetary systems. However\, linear relationship studies rarely explain gold price changes. Gold price time series data is unpredictable\, nonlinear\, and volatile\, making prediction difficult. Classical statistics and machine-learning (ML) approaches like Random-Forests\, CNNs\, and RNNs offer excellent accuracy but limits. A model that combines Temporal-Convolutional-Networks(TCN) with Query (Q) and Keys (K) attention-mechanisms (TCN-QV) is presented to improve gold price forecasts. The model extracts temporal properties from sequence data using stacked dilated causal convolution layers in the TCN architecture. To adapt weight distribution to information features\, an attention mechanism is introduced. Finally\, dense layers give projected results. This approach predicts Shanghai gold price time-series. The optimised model reduces Mean Absolute Error (MAE) by 5.47% in the least favorable case and 33.69% in the most favorable case across four investigational datasets compared to the baseline model. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:85424c9efd6b2ebfe56df9f0340f7104 URL:http://5thworldconferenceoninformations.sched.com/event/85424c9efd6b2ebfe56df9f0340f7104 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:ArogyaMind-NER: Benchmarking a Mental Health NER Dataset for Marathi DESCRIPTION:Authors - Pooja Anil Patil\, Yashodhara Haribhakta Abstract - Named Entity Recognition (NER) is a core task in Natural Language Processing (NLP) with applications in conversational AI\, healthcare analytics\, and search systems. It enables structured extraction of key entities from text\, supporting clinical decision-making and automated diagnosis. While NER resources for high-resource languages like English are widely available\, low-resource languages such as Marathi lack domain-specific datasets\, particularly in the mental health sector. This work introduces ArogyaMINDNER\, a Marathi mental health-specific NER dataset\, designed to enhance entity recognition for diseases\, symptoms\, and treatments. The dataset is manually annotated using BIO tagging\, ensuring linguistic accuracy and contextual consistency across formal and conversational text. Annotation policies account for psychiatric terminology nuances\, accommodating Marathi’s morphological richness and linguistic diversity. To assess performance\, ArogyaMIND-NER is benchmarked using classical machine learning models (SVM\, Naïve Bayes\, XGBoost\, LightGBM\, Random Forest)\, deep learning architectures (CNN\, BiLSTM\, BiLSTM-CRF)\, and transformer-based models (mBERT\, XLMRoBERTa\, IndicBERT\, MahaBERT\, MahaMarathi-7B). Comparative evaluation reveals MahaMarathi-7B and Marathi-Social-NER as topperforming models\, achieving higher precision and recall in disease recognition\, while classical models struggle with contextual understanding. This dataset and trained models establish benchmarks for Marathi NLP research\, contributing to mental health analytics\, clinical applications\, and low-resource language processing. The findings advocate for finetuning transformer architectures for domain-specific NER\, ensuring better entity identification in Marathi mental health texts. The dataset and models will be made available for further research and development. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:ccadd817af1425f35ce88793facf23b7 URL:http://5thworldconferenceoninformations.sched.com/event/ccadd817af1425f35ce88793facf23b7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Design of E-Learning System for College Student DESCRIPTION:Authors - Navin Barde\, Deepak S. Sharma Abstract - Good E-Learning system for colleges would ensure student learning to be flexible\, accessible\, and interactive for being remote learning option in the Post COVID-19 times. The most important aspects are an intuitive and easy to use GUI to easily browse on any device\, the interactive content such as video lectures\, simulations\, quizzes\, forum to improve the engagement. Customized learning paths\, progress tracking\, grade management\, and instant communication features enhance learning. We take security very seriously\, we encrypt all of your data while storing it and ensure that students privacy is maintained with strong user authentication. Laying particular emphasis on usability\, interactivity\, personalization\, and security\, such systems create a convincing and flexible learning environment\, which encourages life long learning. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:81c34e80fdfc19bf0f22addb8890cb60 URL:http://5thworldconferenceoninformations.sched.com/event/81c34e80fdfc19bf0f22addb8890cb60 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Enhancing Full-Stack Application Development with Generative AI-Powered Conversational User Interfaces DESCRIPTION:Authors - Mohit Menghnani Abstract - The increasing expenses and shortage of qualified developers have driven many to look to software development with an eye toward the incorporation of Artificial Intelligence (AI). Full-stack development facilitates the web application process\, from the interface to the server-side functionality that powers it. AI has changed the tasks for many software developments services\, and full-stack is one of them. The integration of Generative AI (GAI) into full-stack applications presents a transformative opportunity for healthcare assistance by enhancing conversational user interfaces. This study explores the development of an AI-powered healthcare assistant using a React.js frontend\, a Node.js/Express.js backend\, and Google GAI for symptom analysis and response generation. The aim is to assess the feasibility\, performance\, and effectiveness of Generative AI in providing real-time medical suggestions. A process of repeating development occurs and the system continuously improves through testing alongside user engagement. Users can maintain safe communication between systems through Jason Web Token (JWT) authentication and HyperText Transfer Protocol Secure (HTTPS) encryption features in addition to multi-language compatibility. Test results show that symptoms processed by the AI-enabled chatbot require 1.5 to 2.5 seconds before providing recommendations with 85-90% accuracy which surpasses traditional rule-based chatbots. The obtained results indicate how GAI shows promise to expand healthcare availability to wider populations. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:68e4d8f492107371c20eab80997bb02e URL:http://5thworldconferenceoninformations.sched.com/event/68e4d8f492107371c20eab80997bb02e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Ensemble Deep Learning Framework for Pneumonia Detection in Chest X-rays Using the RSNA Dataset DESCRIPTION:Authors - Aneri Pandya\, Killol Pandya\, Hemant Yadav Abstract - Convolutional Neural Networks (CNNs) play a crucial role in medical image analysis\, particularly in the detection of pneumonia\, by facilitating accurate diagnosis and treatment planning. This paper presents a robust approach to pneumonia classification using the publicly available RSNA Pneumonia Detection Challenge dataset. The proposed method employs an ensemble-based CNN framework that integrates multiple pre-trained architectures\, specifically MobileNetV2\, InceptionV3\, and ResNet152V2\, through a combination of stacking techniques and soft voting. This ensemble strategy aims to leverage the individual strengths of each model for improved performance. All models are trained and evaluated exclusively on the RSNA dataset\, and their effectiveness is assessed using AUC\, accuracy\, and F1-score metrics. The results demonstrate that the ensemble consistently outperforms individual models in terms of prediction stability and classification accuracy. This work highlights the potential of deep model aggregation techniques to enhance diagnostic reliability in clinical pneumonia screening systems. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:7f103170de9505a45478b72752b1dd7f URL:http://5thworldconferenceoninformations.sched.com/event/7f103170de9505a45478b72752b1dd7f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:From Algorithms To Assurance: Understanding The Link Between AI-Based Personalization And Consumer Trust In Beauty Products DESCRIPTION:Authors - Sana S Santhosh\, Ashitha Mohan\, Vishnu N Abstract - Artificial Intelligence (AI) has transformed the cosmetics market by providing tailored suggestions based on client interests and behaviors. This study investigates the correlation between AI-driven personalization and consumer trust\, emphasizing critical elements such as the precision of AI recommendations\, transparency\, and the degree of customization. Research indicates that AI-driven customisation markedly improves client trust\, therefore influencing consumer pleasure and brand loyalty. Trust development in AI-driven recommendations is contingent upon perceived reliability\, security\, and transparency. The review emphasizes that AI transparency techniques\, including explainable AI (XAI)\, enhance customer confidence\, whereas excessive personalization may provoke privacy issues. Moreover\, the precision of AI recommendations is strongly linked to consumer happiness and intents to repurchase\, enhancing perceived expertise and diminishing decision-making anxiety. Brands utilizing AI-generated cosmetic advice must equilibrate customisation\, openness\, and security to cultivate enduring consumer trust. Future research ought to investigate the ethical ramifications of AI personalization and analyze the evolution of confidence in AI-driven cosmetic brands over time. With the ongoing advancement of AI technology\, it is imperative to optimize algorithms for precision and ethical concerns to maintain client confidence in the beauty sector. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:c95b965f0e16f25a977d6245d824b2e8 URL:http://5thworldconferenceoninformations.sched.com/event/c95b965f0e16f25a977d6245d824b2e8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Towards Bioacoustic Insect Recognition: Spectro-Temporal Attention Networks for Fine-Grained Insect Classification DESCRIPTION:Authors - Amarnath K R\, Nandini Nayakudi\, Lekha S Nair Abstract - Accurate and timely identification of insect species is a foundational requirement for precision agriculture\, ecological monitoring\, and integrated pest management. This paper presents a novel deep learning architecture for fine-grained acoustic classification of insect species using multichannel wingbeat recordings. Targeting critical agricultural use cases\, the model is designed to differentiate between two morphologically and acoustically similar pest species\, Halyomorpha halys and Nezara viridula\, and a beneficial pollinator\, Episyrphus balteatus. The proposed approach utilizes log-Mel and Per-Channel Energy Normalization (PCEN) spectrograms as input features and integrates a residual convolutional backbone with Squeeze and Excite blocks and Transformer inspired self-attention modules to enhance spectro-temporal representation learning. Evaluation on a curated subset of the InsectSound1000 dataset demonstrates a classification accuracy of 88.73% and a macro averaged F1 score of 88.78%. Class wise analysis reveals that the model effectively captures subtle differences in wingbeat harmonics\, achieving an AUC of 1.00 and AP of 0.99 for the pollinator class. The results suggest strong discriminative power across ecologically distinct classes and highlight the model’s potential for deployment in automated\, non-invasive insect monitoring systems for real-time agricultural decision-making. CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:89f0944a9d40816765e56f4d5b3b7c7f URL:http://5thworldconferenceoninformations.sched.com/event/89f0944a9d40816765e56f4d5b3b7c7f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:A Study on the Commercialization Path and Sustainable Development Model of Integrating Health Qigong with the Modern Health Management Industry DESCRIPTION:Authors - XIAOLIN HE\, CHUANCHEN BI Abstract - With the rapid development of the global health management industry and the growing awareness of personal well-being\, traditional wellness practices are provided with significant opportunities for modern transformation. As an important component of traditional Chinese health culture\, Health Qigong—featuring the integration of body movement\, breath regulation\, and mental focus—has demonstrated notable advantages in chronic disease prevention\, psychological regulation\, and overall health promotion. However\, integration of Health Qigong into the modern health management industry continues to encounter multiple obstacles\, such as insufficient standardization\, limited market recognition\, and a lack of diversified business models. These challenges constrain its commercialization and sustainable development. This study adopts a qualitative research approach based on secondary data and case analysis to explore emerging trends\, practical models\, and key barriers in the commercialization of Health Qigong. By applying Business Model Canvas (BMC) and Creating Shared Value (CSV) framework\, the study proposes sustainable business pathways for Health Qigong\, including course standardization\, digital dissemination\, membership subscriptions\, corporate health partnerships\, and integration with health tourism. The findings indicate that establishing standardized curricula\, utilizing digital platforms\, and fostering cross-sectoral cooperation can support the formation of viable commercialization models that align with contemporary health industry demands. This\, in turn\, may enable the global expansion of Health Qigong as a sustainable health intervention. The results not only offer theoretical support for the modern promotion of Health Qigong but also provide practical insights for the commercialization of traditional cultural products within the health sector. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:5aec6e40121c0d712a58d2805e6af703 URL:http://5thworldconferenceoninformations.sched.com/event/5aec6e40121c0d712a58d2805e6af703 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:AI Powered Text to Video Generation DESCRIPTION:Authors - Aditya Dere\, Bharati Dixit Abstract - The world of AI is has gone through tremendous advancements in over last decade. AI journey started from Algorithmic Intelligence and Linguistic Intelligence\, and is moving towards Imaginative intelligence. This generative AI’s historical journey is focused on generating realistic texts and images through the means of early models like autoencoders and variational autoencoders (VAEs). From creating simple and coherent images from basic textual descriptions using Generative Adversarial Networks (GANs) and models like DALL-E in text to image generation\, the AI leaped towards generating coherent frames which aligned for improving video quality\, length\, and the ability to generate more complex scenes in video with natural transitions in the field of text to video generation. The T2V models made use of models such as diffusion model\, transformer model and the latest and the best one which is diffusion transformer model (DiT model). This paper basically gives us the overview of text to image and text to video generation models and their advancement in the field of generative AI. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:c6eb6de340d40aac0aa66af4eafff17a URL:http://5thworldconferenceoninformations.sched.com/event/c6eb6de340d40aac0aa66af4eafff17a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Assessing The Degree of Contribution of IoT Integration in the Hotel Supply Chain: 4Rs Framework DESCRIPTION:Authors - Lyndon Avendano Abstract - The Philippine tourism sector significantly contributes to the national GDP\, hence continuous improvements is necessary to achieve competitive advantage within the region\, evidently the hotel industry plays an integral role in this objective. Several studies posits that effective Supply Chain Management (SCM) is crucial for competitive advantage and customer satisfaction in the hotel industry. Given today's technological advancements\, integrating technology into SC operations is imperative. This study investigates the nuances of Internet of Things (IoT) integration within Hotel Supply Chain and its perceived contribution to supply chain performance from the perspective of various SC functions. This research posits that IoT integration can foster competitive advantage in hotel supply chains\, enhancing their reliability\, responsiveness\, realignment\, and resilience against disruptions. The analysis revealed a consistent\, moderate perceived contribution of IoT integration across all four SC performance dimensions: Responsiveness\, Reliability\, Realignment\, and Resilience. Further analysis indicated: Logistics demonstrated the highest overall perceived IoT contribution particularly strong in resilience\, highlighting IoT's role in tracking and disruption management. Demand Planning showed the highest mean for realignment suggesting IoT's strength in data analytics for market adaptation. A significant difference was also noted for resilience across functions. These findings emphasize understanding each supply chain function's unique needs for effective IoT implementation. The results offer valuable insights for hotel operations aiming to strategically leverage IoT to optimize supply chain performance and gain a sustained competitive advantage in the dynamic hotel industry. Future research should delve deeper into factors driving these functional variations and explore tailored IoT applications. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:a426a7c8b0803f27fe0cd251fd4feacd URL:http://5thworldconferenceoninformations.sched.com/event/a426a7c8b0803f27fe0cd251fd4feacd END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:From Awareness to Enterprise: A Participatory Innovation Framework for Vulture Safe Zones in the Nilgiri Biosphere DESCRIPTION:Authors - Bharathidasan\, Dhivyalakshumi\, Vasanthi Abstract - This paper investigates an innovative\, community-driven model of vulture conservation developed by Arulagam\, an environmental NGO operating within the Nilgiri Biosphere Reserve in Tamil Nadu\, India. Declination of vulture population due to the misuse of non-steroidal anti-inflammatory drugs (NSAIDs) in veterinary care\, has been observed in recent decades. This study examines how Arulagam's interdisciplinary approach combines scientific outreach\, cultural engagement\, and stakeholder collaboration has evolved into a replicable model for sustainable ecological entrepreneurship. Using qualitative methods\, including in-depth interviews\, field observation\, and campaign-based ethnography\, this study documents how interventions such as pharmacist sensitisation\, ethno-veterinary advocacy\, school programs\, and mobile awareness drives have contributed to the formation of Vulture Safe Zones (VSZs). It highlights how creative mediums like shadow puppetry\, murals\, and mythological storytelling have shifted negative public perceptions of vultures and introduced conservation ethics within local communities. This paper also explores entrepreneurial pathways emerging from the conservation framework\, including eco-tourism\, ethical livestock branding\, and native plant nurseries. Emphasizing on the principles of nature-based solutions and aligned with SDG 15 (Life on Land)\, this study proposes a measurable intervention model that merges biodiversity protection with livelihood generation\, offering policy-relevant insights for governing conservation in other biodiversity hotspots. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:54924c4b8054447976a02bb3b539d5a8 URL:http://5thworldconferenceoninformations.sched.com/event/54924c4b8054447976a02bb3b539d5a8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Impact of Social Media Marketing on Customer Behaviour Outcomes in Bangladesh DESCRIPTION:Authors - Md Shahim Uddin Saba\, Mohitul Shafir\, Md Zahid Hasan\, Md Asfaqur Rahman\, Farhan Khan\, Mahady Hasan\, Farzana Sadia Abstract - Social media has reshaped customer engagement\, leading to widespread use of digital marketing. However\, the effects of specific social media marketing practices on purchase decisions\, participation\, and brand loyalty remain underexplored. This study investigates the impact of social media marketing activities on consumer behaviour in Bangladesh’s technology product sector. Based on a quantitative survey and Structural Equation Modeling (SEM) using SmartPLS 4\, the results show that both social media marketing and customer experience significantly influence behavioural outcomes. The findings provide strategic guidance for brands that seek to strengthen engagement in competitive digital markets. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:8ef5fff7c8ca47439a26a38a9890484d URL:http://5thworldconferenceoninformations.sched.com/event/8ef5fff7c8ca47439a26a38a9890484d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Integral Model for the Management and Mitigation of Credit Risk in the Colombian Solidarity Sector DESCRIPTION:Authors - Jasleidy Astrid Prada Segura\, Efren Danilo Ariza\, Maria del Pilar Corredor Garcia\, Eduard Ricardo Espinosa Armero Abstract - The objective of this research is to design a comprehensive model aimed at reducing credit risk in the solidarity sector. This effort seeks a substantial improvement in the efficiency of the recovery of non-performing loans\, considering that this process involves a significant level of risk. It is an applied and mixed research in terms of its sources of information\, the scope is exploratory and explanatory\, and the approach is quantitative. The model contains crucial parameters for effective risk mitigation. It should be noted that\, as additional support\, information from the sectoral analysis of the cooperatives in the report of the Superintendencia Solidaria and portfolio balances by city and entity with cutoff to 2021 and 2022 generated by the Superintendencia Solidaria will be used to support the current situation of the portfolio in the solidarity sector in Colombia. The methodology developed in this research can be extrapolated and applied in other regional contexts and economic sectors\, offering a valuable tool to address credit risk and strengthen the solidarity economy in Colombia. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:a5ced6cb7200dd22c52137715f3c5038 URL:http://5thworldconferenceoninformations.sched.com/event/a5ced6cb7200dd22c52137715f3c5038 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Medical Ethics and Medico-Legal Issues for Storing Electronic Health Records in India Using Blockchain Technology DESCRIPTION:Authors - Neha A. Samsir\, Arpit A. Jain Abstract - With the pandemic taking a serious impact\, it is becoming progressively clearer that India needs to boost funding and develop its healthcare system. The integration of Information and Communication Technology (ICT) into the healthcare sector is transforming healthcare systems worldwide by improving patient access to and availability of healthcare services. A basic requirement for utilizing ICT in healthcare is having an electronic health record. It is a digital record that combines patient health information and is utilized for handling data\, educational purposes\, research\, and reference purposes. Cloud-based electronic health records are constantly evolving and have transparency\, trust\, and confidentiality\, they are vulnerable to several security and privacy threats. In the new Digital India\, digital health (DH) plays a big role in healthcare. Utilizing technology\, the audacious goal of offering universal health coverage—first to 500 million citizens with low incomes— is being accomplished. The widespread adoption of electronic health records (EHRs) has presented several obstacles\, even though they have transformed healthcare by facilitating rapid access to patient information. The implementation of EHRs raises ethical and legal concerns\, which are examined in this study with a specific emphasis on the Indian healthcare system. The implementation of EHRs should be guided by ethical issues\, including medical beneficence\, fairness\, autonomy for patients\, confidentiality\, and beneficence. Strong regulations and security measures are essential considering legal difficulties such as medical errors\, data breaches\, and billing discrepancies. This paper aims to analyze all the legalities and medical issues of storing EHR using Blockchain Technology. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:c24a8bf11d2bc5043ae0300aadabdf57 URL:http://5thworldconferenceoninformations.sched.com/event/c24a8bf11d2bc5043ae0300aadabdf57 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Optimizing LAN Performance: Key Determinants and Algorithmic Solutions DESCRIPTION:Authors - Sudhir B.Agarmore\, Hemant S.Mahalle Abstract - This research paper analyses the key determinants affecting LAN performance and articulates algorithmic solutions for improving the efficiency of such networks. Elaborating on factors like bandwidth\, latency\, packet loss\, and congestion\, against the backdrop of cutting-edge algorithmic interventions\, inclusive of dynamic routing\, congestion control\, and traffic engineering\, this current research offers a comprehensive insight into the augmentation of LAN performance. A local area network is a major part of any modern computing infrastructure. The user experience and productivity depend to a great degree on their performance\; at the same time\, the overall network efficiency depends on them. This paper explores the main factors of LAN performance and examines algorithmic solutions to optimize these factors. Such factors that will be discussed are the impact of network topology\, traffic patterns\, hardware capabilities\, software configuration\, and their effective combinations on LAN performance. We will also investigate some higher-level algorithms\, such as those for congestion control\, routing protocols\, and QoS mechanisms\, which help increase network throughput\, reduce latency\, and deal with reliability in data transmission. Proper understanding of these determining factors and implementing the relevant algorithmic solutions significantly improve performance and reliability in organizational LANs. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:8c24f18bfa7c4b2acdae4b88b34fe37b URL:http://5thworldconferenceoninformations.sched.com/event/8c24f18bfa7c4b2acdae4b88b34fe37b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Smart Hormone Monitoring: Sensors\, Wearables and AI Powered Detection Techniques DESCRIPTION:Authors - Shaily Sharma\, Disha Shah Abstract - Hormone level fluctuation is connected with several health problems affecting human beings. To properly managing and diagnosing hormone levels\, it is essential to understand hormonal imbalance and its detection. Commonly the levels of hormones were detected with the help of laboratory tests like chromatographic methods and immunoassays which gives accurate results but are very slow process and there is no real time detection proficiency. Hormone monitoring is crucial and wearable devices are progressing very effectively with the help of biosensors to monitor hormones to provide better understanding of health control. This review paper is focusing on the theory of hormones\, hormonal imbalance indicators\, and detection approaches which are available. Several tests for diagnosing hormone level imbalance were investigated including chromatographic techniques (HPLC\, GC-MS)\, biosensors and immunoassays (ELISA\, RIA) while also focusing on machine learning including deep learning algorithms\, pattern recognition\, regression\, classification to provide customized treatment. Deep learning approaches like CNN (Convolutional Neural Networks) and Supervised learning approaches like SVM (Support Vector Machine) and Random Forests have demonstrated encouraging uses in real-time monitoring and the prediction of hormone related diseases. The review also highlights wearable devices available for hormonal levels monitoring\, comparison of wearable sensors like electrochemical\, optical and microfluidic systems. By empowering real-time surveillance of hormone level imbalances and promoting early detection\, diagnosing and illness prevention\, these advancements have improved conveniency. According to the research\, combining Machine learning (ML) algorithms with wearable biosensors can transform monitoring of hormone levels may result in better results and can provide early medication. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:b4bcf01f70dc263592fc0dcaba0cfb1c URL:http://5thworldconferenceoninformations.sched.com/event/b4bcf01f70dc263592fc0dcaba0cfb1c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:TRENDS IN VENTURE CAPITAL: A BIBLIOMETRIC REVIEW DESCRIPTION:Authors - Sneha Sarah Alex\, Jains P Chacko Abstract - This study explores the evolution of venture capital (VC) research through a bibliometric analysis of 2\,577 journal articles from 1972 to 2022\, using Scopus\, VOSviewer\, and Biblioshiny. It identifies five key research clusters: private equity and IPOs\, entrepreneurship\, innovation\, human capital\, and institutional factors. Highly cited works highlight VC’s impact on firm performance\, governance\, and innovation. Emerging themes include syndication\, decision-making dynamics\, globalization\, and sectoral shifts like biotech. Grounded in agency\, human capital\, and institutional theories\, this study provides insights for researchers\, investors\, and policymakers\, while also suggesting broader future research directions. CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:0570fb7a8888de29e1abc920d440f72d URL:http://5thworldconferenceoninformations.sched.com/event/0570fb7a8888de29e1abc920d440f72d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:A Machine Learning and Data-Driven Analysis of English Anxiety Among Rural High School Students in Bangladesh DESCRIPTION:Authors - Md. Najmus Sakib Sourov\, Md. Ataur Rahman\, Urmi Ghosh\, Sabera Sultana\, Mahady Hasan\, Md. Tarek Habib Abstract - English Language Anxiety represents a prevalent issue among learners\, significantly affecting their capacity to communicate and acquire knowledge effectively. The study uses machine learning models to offer insights into how anxiety affects students' general well-being and academic performance. English language anxiety among rural high school students in Bangladesh is investigated using machine learning techniques to determine its sources and effects on aca-demic performance. Machine learning techniques like k-Nearest Neighbors (k-NN)\, Support Vector Machine (SVM)\, Naïve Bayes\, Decision Tree\, and Gradient Boosting were used to analyze data from several rural schools\, including student scores and qualitative insights on their perceptions of English. The results showed that SVM was the most accurate model\, with an accuracy of 99.43%. The study reveals major anxiety patterns and predictions\, with a focus on the interaction between academic pressure\, English complexity\, and student mental health. The findings will guide educators and policymakers in designing focused interventions to relieve English subject anxiety and establish a supportive learning environment. CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:ecb407f9b7400d09a2decbadd428e9de URL:http://5thworldconferenceoninformations.sched.com/event/ecb407f9b7400d09a2decbadd428e9de END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:CHARACTER RECOGNITION OF NEPALI NUMBER PLATE DESCRIPTION:Authors - Satyasa Khadka\, Sandhya Baral\, Sudip Tiwari\, Sharad Kumar Ghimire Abstract - This paper presents a robust Automatic Number Plate Recognition (ANPR) system tailored for Nepali license plates written in Devanagari script. In this paper\, a pipelined model was used that integrates YOLO-based models for license plate and character detection\, followed by a CNN classifier trained on 34 Devanagari characters. Two publicly available data sets were used that incorporate diverse lighting\, fonts\, and structural variations. Data augmentation and additional training on embossed plates enhanced the generalizability of the model. The system achieved a recognition accuracy of up to 93%\, demonstrating strong performance under real-world conditions and providing a scalable solution for traffic management in Nepal. CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:2f6fc542821dc7a6e84df38ea5d54dc9 URL:http://5thworldconferenceoninformations.sched.com/event/2f6fc542821dc7a6e84df38ea5d54dc9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:CHARACTERIZATION AND ANALYSIS OF BADMINTON RACKET USING SINGLE WALLED AND MULTIWALLED CARBON NANOTUBES DESCRIPTION:Authors - K. Vidyasagar\, G. Lakshminarayana\, B. Surya Prasada Rao\, K. Vijaychandra\, P. Suresh babu Abstract - Nanoscience is the emerging technology to strengthen the devices that are more essential to human life. This chapter discussed structural design considerations of a badminton racket. The stress-strain relationship\, modulus of elasticity\, bending modulus\, and moment of inertia are studied to improve the shaft deflections while smashing the shuttle with high force. Carbon nanotubes are elected for badminton rackets to withstand both rapid forward and side deflections. This paper discussed the physical characteristics of armchairs\, Zig-Zag Single-walled carbon nanotubes and double-walled carbon nanotubes (DWCNT). The length of the carbon nanotube is fixed to 200 A. The C-C bond length is considered as 1.4210 A. The stretch factor is considered as ‘1’ for both single-walled and carbon nanotubes (SWCNT). And the ellipse ratio is also considered as ‘1’ for both SWCNT and DWCNT. The screw distortion and bending angle are varied from 00 to 900 for single-walled carbon nanotubes\, and the physical elastic properties of the SWCNT and DWCNT are investigated. Finite element analysis is used to analyse SWCNT and DWCNT structures. Nano tube modeler is used to simulate the SWCNT and DWCNT structures. CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:9dc85a512ef1f6d2c33ad496686f8e08 URL:http://5thworldconferenceoninformations.sched.com/event/9dc85a512ef1f6d2c33ad496686f8e08 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Cross-Modal Attention Transformer for Multi-SKU Demand Forecasting in Retail Environments DESCRIPTION:Authors - Sabar Aritonang Rajagukguk\, Eileen Heriyanni\, Ahmad Fikron Maulida\, Enina Putri Abstract - Multi-SKU demand forecasting poses considerable challenges for re-tail operations due to intricate interdependencies among products\, seasonal fluctuations\, and external market influences. Conventional forecasting approaches often fail to model these complexities effectively\, resulting in poor inventory management and financial inefficiencies. This paper proposes a novel Cross-Modal Attention Transformer (CMAT) architecture for addressing multi-SKU demand prediction in retail contexts. The model employs a dual-attention mechanism to capture temporal patterns within individual SKU time series as well as cross-SKU relationships via an inter-product attention layer. It further integrates multimodal external variables such as promotional campaigns\, weather data\, and economic indicators using dedicated feature encoders. Evaluation on a large-scale retail dataset comprising 15\,847 SKUs across 12 product categories shows a 23.4% reduction in Mean Absolute Percentage Error (MAPE) compared to standard transformer models and a 31.2% improvement over traditional statistical methods. The results indicate potential for improving supply chain efficiency and reducing inventory-related costs through more accurate multi-horizon demand predictions. CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:bc2eeeb2a19f8b35179d44a1dc1f6bd6 URL:http://5thworldconferenceoninformations.sched.com/event/bc2eeeb2a19f8b35179d44a1dc1f6bd6 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Detection of Advanced Persistent Threats Using Swift-KNN DESCRIPTION:Authors - Kshitij Gupte\, Kunj Patel\, Krisha Desai\, Dhrumi Patel\, Anjali Jivani Abstract - Advanced Persistent Threats (APTs) pose a serious challenge to cybersecurity due to their stealthy and prolonged nature. Detecting these attacks early is critical\, yet traditional methods often fail to catch subtle patterns or require extensive resources. This study investigates the effectiveness of several machine learning algorithms including Logistic Regression\, Random Forest\, Naive Bayes\, and K-Nearest Neighbors (KNN) to identify APT behavior from system and network activity data. A significant focus was placed on reducing the complexity of the detection system without compromising accuracy. Dimensionality reduction using Linear Discriminant Analysis (LDA) was applied to transform high-dimensional data into a more manageable format\, and data cleansing techniques were used to handle null and infinite values. The results showed that the KNN algorithm not only achieved the highest detection accuracy but also maintained performance even when trained on just 10% of the dataset. This approach offers a lightweight\, high-precision method for APT detection that can minimize processing overhead while improving real-time responsiveness helping organizations enhance their security posture without sacrificing efficiency. CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:fe4ea99adb5777cd75eab2d70af926b1 URL:http://5thworldconferenceoninformations.sched.com/event/fe4ea99adb5777cd75eab2d70af926b1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Integrating Climate Action into Business Operations: Perspectives from City SMEs in the Philippines DESCRIPTION:Authors - Justin Q. Cabellon\, Ashley MJ A. Andrade\, Dave P. Bautista\, Kenshin Z. Gutierrez\, Dorothy Joy B. Nabo\, Angel Anne R. Nuarin\, Manuel J. Logatoc\, Rexieden N. Barrera Abstract - This study examines the perceptions of small and medium enterprises (SMEs) toward United Nations Sustainable Development Goal 13 (Climate Action). Employing a quantitative survey across multiple industries\, it captures numeric data to identify patterns in SMEs’ attitudes and evaluates whether demo-graphic factors— length of operation\, nature of business\, number of employees\, or type of ownership—influence these perceptions. Respondents rated statements on a five-point Likert scale (1 = Strongly Disagree to 5 = Strongly Agree) across five business dimensions: product\, service\, process\, network\, and model. Results reveal high overall support for climate-action initiatives\, with mean scores indicating positive engagement in each dimension. Statistical analysis shows no significant variation in perceptions among SMEs grouped by any demographic criterion\, suggesting a shared recognition of climate action’s importance irrespective of firm characteristics. These findings underscore the uniform commitment within the SME sector to integrate climate considerations into core operations. By illuminating SMEs’ supportive stance and the absence of demographic dis-parities\, this research highlights the sector’s potential contributions to global cli-mate objectives. Insights from this study can inform policymakers and practitioners aiming to tailor interventions that bolster SME participation in sustainable development and foster resilient economic growth. CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:cf9f9a89816962a460a58aa38f2d4a8f URL:http://5thworldconferenceoninformations.sched.com/event/cf9f9a89816962a460a58aa38f2d4a8f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Model Confidentiality in AI-as-a-Service: Challenges and Cryptographic Solutions DESCRIPTION:Authors - Parikshit Mahalle\, Pradnya H Desai\, Pankaj Chandre Abstract - With the widespread adoption of AI-as-a-Service (AIaaS)\, enterprises increasingly rely on cloud platforms to deploy and access powerful machine learning models. This shift offers scalability and cost-efficiency but also introduces significant security and privacy concerns. Protecting the confidentiality of AI models and user data has become a critical requirement in this outsourced computing paradigm. However\, AIaaS platforms face numerous threats\, including model inversion\, membership inference\, extraction attacks\, and data poisoning. Traditional security mechanisms are insufficient to address the unique confidentiality risks associated with remote AI model hosting and inference. Furthermore\, balancing performance\, privacy\, and deployment feasibility remains a core challenge. This paper proposes a comprehensive confidentiality-focused architecture for AIaaS\, integrating multiple cryptographic techniques and secure hardware layers. The design leverages Homomorphic Encryption\, Secure Multiparty Computation\, Trusted Execution Environments\, and Federated Learning with Secure Aggregation\, supported by a centralized Management & Compliance layer. Threat vectors are explicitly addressed across client\, cloud\, and edge layers\, while performance and auditability are maintained. In conclusion\, our architecture provides a layered and resilient defense against modern AI threats while maintaining functionality and scalability. It offers a blueprint for deploying privacy-preserving AIaaS infrastructures. Future work will focus on optimizing hybrid models and advancing quantum-resistant protections. CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:70da284bed2f6723682443d8d0a68d22 URL:http://5thworldconferenceoninformations.sched.com/event/70da284bed2f6723682443d8d0a68d22 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Multi-Label Fake News Detection with Transformer: A Study on the LIAR Dataset DESCRIPTION:Authors - Mridul Das Joshe\, Shyja Rafeek S\, Aji Sivanandan Abstract - Fake news has become a critical research area due to the expanding spread of misinformation on digital platforms. As social media becomes a main news source for millions\, confirming the authenticity of online material is crucial. This research addresses the problem using a multi-label text classification method\, which better identifies the complex nature of misinformation that may fall into multiple categories. In our research\, we used the LIAR dataset\, a bench-mark collection of 12.8k short political statements labeled with six fine-textured truthfulness classes. A transformer-based architecture\, notably a fine-tuned BERT model\, is proposed including both textual context and metadata to enhance better classification output. The model achieved an accuracy of 0.7351\, presenting superior results than those reported earlier research using the LIAR dataset. Confirming the robustness of the approach across different classes with evaluation metrics and per-label precision and recall. The findings illustrate the potency of transformer-based architectures in identifying different degrees of falsehood. This research adds an extensible and practical solution for real-time fake news detection to support information. CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:086165199b0eed8e2a9b9f3964d8a5d5 URL:http://5thworldconferenceoninformations.sched.com/event/086165199b0eed8e2a9b9f3964d8a5d5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:The Role of ICT in Empowering Women-Led MSMEs: Analysing WhatsApp Commerce as a Catalyst for SDG 5 & SDG 8 in Tier-3 India DESCRIPTION:Authors - Agna S. Nath\, Arun Kumar V N\, Aswathi K.B Abstract - This study investigates the role of WhatsApp Commerce—the use of WhatsApp for business transactions—in empowering women-led Micro\, Small\, and Medium Enterprises (MSMEs) in Tier-3 cities of India\, while advancing Sustainable Development Goals (SDGs) 5 (Gender Equality) and 8 (Economic Growth). Despite India’s digital revolution\, gender disparities persist\, with women leading only 20% of MSMEs and facing barriers like digital exclusion and sociocultural constraints. Grounded in Kabeer’s Empowerment Theory and Davis’s Technology Acceptance Model\, the research employs a mixed-methods approach\, combining surveys of 400 women entrepreneurs and 20 case studies across four Tier-3 cities (Bareilly\, Jalgaon\, Dibrugarh\, Erode). Key findings reveal that WhatsApp usage intensity correlates with a 27% revenue increase (β=0.27\, *p* CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:55b664db2f8d17cf7267d300ac4f7ad2 URL:http://5thworldconferenceoninformations.sched.com/event/55b664db2f8d17cf7267d300ac4f7ad2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Uncovering Consumer Patterns: The RN-Algorithm for Market Basket Analysis DESCRIPTION:Authors - Kingkar Prosad Ghosh\, Ankan Roy\, Anupam Singha\, Tabassum Tajin Ratry\, Nafisha Hossain Abstract - Market Basket Analysis (MBA) identifies co-occurring products for pricing\, cross-selling\, and placement. This paper reviews Apriori and FP-Growth and introduces the RN-Algorithm\, a method that focuses on rules with high lift and confidence by measuring pairwise item co-occurrence. In retail-style transactions\, RN provides competitive or superior performance in identifying the top rules while remaining simple to distribute. This study examines RN’s complexity\, how its runtime scales with the number of unique items and basket width\, and offers a practitioner-oriented comparison of algorithms. We also address RN’s limitations (e.g.\, pair growth in wide baskets) and propose mitigations\, including minimum item support\, top-K selection\, and distributed counting. The paper concludes with actionable guidance on when to prefer RN over FP-Growth or Apriori in modern e-commerce applications. CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:676ee577d3997d09912cef61bb98a576 URL:http://5thworldconferenceoninformations.sched.com/event/676ee577d3997d09912cef61bb98a576 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:A Framework to Safeguard Electronic Health Records and Ensure Privacy in Cloud Storage DESCRIPTION:Authors - T. Sruthi\, Martha Sheshikala Abstract - Cloud computing has brought significant benefits to healthcare systems\, especially when it comes to improving data access and storage efficiency. However\, it also rais-es major concerns around privacy and security\, particularly for Electronic Health Records (EHRs). In this paper\, we propose a new framework designed to protect EHRs in cloud environments. The framework uses a combination of symmetric and asymmetric encryption techniques to ensure that data stays private during both storage and transmission. It also includes advanced access control measures that regulate who can access the data based on established policies. Our tests show that the framework successfully reduces the risk of unauthorized access while keeping system performance intact. These results highlight the importance of using strong privacy protections to safeguard sensitive health data in cloud-based healthcare applications. This research builds on Dutta et al.'s (2023) work\, which explored hybrid encryption techniques to improve the security of health data in the cloud. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:6c730db912e6e4f58b12336f0fa6e0bd URL:http://5thworldconferenceoninformations.sched.com/event/6c730db912e6e4f58b12336f0fa6e0bd END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Artificial Intelligent: An Effective Tool for Knowledge Management in Higher Education DESCRIPTION:Authors - Sanasam Bimol\, Mutum Indrakumar Meetei Abstract - In higher education\, knowledge management (KM) is important for encouraging innovation\, helping students learn better\, and making university management more effective. However\, traditional ways of handling knowledge face problems like too much information\, poor systems for finding content\, and not enough personalized learning experiences. Using artificial intelligence (AI) can help by automating data handling\, making information easier to retrieve and more accurate and offering customized learning paths. This paper looks at how AI can be used in KM within higher education\, focusing on its ability to improve the creation\, sharing\, organization\, and decision-making processes of knowledge. It also examines issues like the AI infrastructure needed for KM\, compares different approaches\, discusses strategies for development\, and addresses the challenges and ethical questions that come with using AI in educational settings. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:53b223f7d29fa9ba6279d782d552565e URL:http://5thworldconferenceoninformations.sched.com/event/53b223f7d29fa9ba6279d782d552565e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Integrating AI and Behavioral Analytics for Advanced Insider Threat Detection: A Cross-Disciplinary Approach Combining Cybersecurity and Cognitive Science DESCRIPTION:Authors - Praveen Savarapu\, Shankar Lingam. M Abstract - Insider threats pose significant risks to organizational cybersecurity\, often arising from complex human behaviors that traditional detection systems struggle to identify (Smith & Johnson\, 2023). This study proposes a novel\, cross-disciplinary approach in-tegrating artificial intelligence (AI) and behavioral analytics to enhance insider threat detection. By combining machine learning techniques with cognitive science principles\, the framework captures nuanced behavioral patterns and psychological indicators that precede malicious insider activities (Lee et al.\, 2022). This work contributes to advancing proactive risk mitigation strategies by bridging technical cybersecurity defenses with human behavioral insights\, for both researchers and practitioners. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:fbe7d8df30876859ed418cd49580c6ef URL:http://5thworldconferenceoninformations.sched.com/event/fbe7d8df30876859ed418cd49580c6ef END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Linking System Effectiveness to Workforce Productivity: A Study on the Use of Electronic Accounting Systems DESCRIPTION:Authors - Mark Anthony A. Gavino\, Rafaela Medilane A. Gonzales\, Queenie Marie E. Manilag\, Angeline G. Reyes\, Rey Mark C. Sadoy\, Lester P. Acoba Abstract - With the rapid advancement of technology\, traditional manual accounting methods are increasingly being replaced by Electronic Accounting Systems (EAS) to improve organizational efficiency and decision-making. This study aimed to examine the perceived effectiveness of EAS and its impact on the productivity of accounting personnel in Makati City. Utilizing a quantitative-descriptive research design\, data were collected from 152 finance officers and accountants with at least six months of experience using EAS through a structured Likert-scale questionnaire. The study assessed EAS effectiveness across five dimensions—speed\, accuracy\, security\, reliability of information\, and decision-making—and evaluated productivity based on motivation\, satisfaction\, performance\, absenteeism\, and turnover. Using partial least squares-structural equation modeling (PLS-SEM)\, results revealed a strong and statistically significant relationship between perceived effectiveness and productivity. Reliability and validity analyses confirmed the robustness of the measurement model. The findings indicate that effective EAS use significantly enhances both system performance and employee productivity. The study concludes that investing in well-implemented EAS can lead to improved efficiency and workforce outcomes. Practical recommendations include providing continuous user training\, choosing secure and adaptable systems\, integrating EAS into business strategies\, and regularly evaluating system impact. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:450d61a2f76a249da87ac5457239b278 URL:http://5thworldconferenceoninformations.sched.com/event/450d61a2f76a249da87ac5457239b278 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Modelling the Barriers to Gen Z Adoption of Privacy-Preserving AI-Enabled Health Apps DESCRIPTION:Authors - Payel Das\, Uditaa K\, Hariprasad Abstract - Artificial Intelligence (AI) is redefining healthcare through enhanced diagnostics\, personalized interventions\, and preventive monitoring. Privacy-preserving AI-enabled health applications—leveraging technologies such as federated learning and differential privacy—hold the potential to protect sensitive health data while delivering actionable insights. Yet\, adoption among Generation Z (Gen Z) remains inconsistent\, hindered by complex and interlinked barriers. This study identifies and models ten critical barriers—Awareness Deficit\, Data Misuse Anxiety\, AI Credibility Doubt\, Surveillance Concern\, UX–UI Friction\, Digital Health Knowledge Gap\, Regulatory Ambiguity\, Human Displacement Fear\, Perceived Health Irrelevance\, and Eco–Ethical Concerns—through a survey of 142 Gen Z respondents in India. Using Interpretive Structural Modeling (ISM) and MICMAC analysis\, the research reveals a hierarchical structure were foundational drivers cascade into immediate deterrents\, demonstrating that isolated interventions may be insufficient. By integrating Protection Motivation Theory (PMT) and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2)\, the study offers a dual lens capturing both resistance (security–privacy dimension) and adoption (utility–experience dimension) dynamics. Findings provide actionable guidance for developers\, policy-makers\, educators\, and healthcare providers to address root causes\, bridge knowledge gaps\, enhance trust\, and align solutions with Gen Z’s values\, fostering informed and sustained adoption. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:00a647b673827ef473f6e36dce89b05e URL:http://5thworldconferenceoninformations.sched.com/event/00a647b673827ef473f6e36dce89b05e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Prompt Engineering Intervention for Enhancing Proficiency and AI Self-Efficacy in Undergraduate Management Education DESCRIPTION:Authors - Vijay Makwana Abstract - The rapid integration of artificial intelligence (AI) into business necessitates a curricular shift in management education toward practical AI literacy. This study addresses the gap between the availability of AI tools and students' ability to leverage them effectively. It evaluates a structured prompt engineering intervention designed to improve undergraduate business students' AI self-efficacy\, foundational AI knowledge\, and practical prompting skills. Using a mixed-methods\, pre-test/post-test design\, the study included 78 undergraduate business administration students at a university in Gujarat\, India. Participants engaged in a workshop that introduced advanced prompting strategies for business applications. Data were collected via a validated AI Self-Efficacy Scale\, an AI Knowledge Assessment\, and a Prompt Engineering Skill Rubric. The findings show statistically significant improvements in AI knowledge and self-efficacy\, corroborated by qualitative evidence of enhanced prompt sophistication. The results underscore the intervention's efficacy in cultivating essential AI competencies. This research offers a replicable pedagogical framework for integrating prompt engineering into business curricula\, providing key insights for educators seeking to prepare future professionals for an AI-driven land-scape. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:2b881a70ede224ac0d9b82510367e004 URL:http://5thworldconferenceoninformations.sched.com/event/2b881a70ede224ac0d9b82510367e004 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Robust Face Recognition Under Occlusion Using Attention-Enhanced Angular Margin Loss DESCRIPTION:Authors - Chau Huy Thuan\, Nguyen Dac Thanh Phuoc\, Bui Chau Sao\, Le Phu Thanh\, Tong Van Dinh\, Hung Nguyen-Huu\, Vinh Dinh Nguyen Abstract - The widespread use of facial masks poses a major challenge for face recognition systems\, often leading to drastic performance degradation. This paper presents a systematic\, multi-stage framework to build a highly robust face recognition model against such occlusions. We perform extensive ablation experiments by gradually introducing three main enhancements over a strong Triplet Loss baseline: (1) Mask-Aware Sampling to explicitly learn cross-mask invariances\; (2) a Spatial Attention module to adaptively focus on un-occluded facial regions\; and (3) the state-of-the-art ArcFace loss to maximize the embedding's discrimination power. Extensive experiments demonstrate that our final model not only achieves an outstanding F1-score exceeding 97% across all verification scenarios (unmasked-unmasked\, masked-masked\, and cross-mask) but\, more critically\, exhibits exceptional robustness\, reducing the performance variance between the easiest and hardest scenarios from 5.9% in the baseline to a mere 2.0%. Furthermore\, we evaluate our models also on the Labeled Faces in the Wild (LFW) which is a standard face benchmark and our final model achieved an efficient improvement of +8.9% accuracy improvement over the baseline in the general case of LFW\, demonstrating that our model acts effectively in general when it may not be necessarily occlusive situation as well. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:08f4ac2e175afebb8ef62b7e4e715a41 URL:http://5thworldconferenceoninformations.sched.com/event/08f4ac2e175afebb8ef62b7e4e715a41 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Role of Digital marketing in the era of Artificial Intelligence DESCRIPTION:Authors - Sarvani Kocherlakota\, Lavanya Goura\, Poojitha Panchakarla\, Thupakula Kushwanth\, Jangala Venkata Shanmukha Abstract - The impact of artificial intelligence in digital marketing has emerged as a prominent research topic in recent decades\, with numerous findings published in leading international journals. To investigate its current research landscape and emerging trends\, we conduct a bibliometric analysis by using R software 4.5.0\, and VOSviewer to identify the research trend\, emerging topics\, collaborations among countries\, authors\, documents and the contributing academic journals during the study period. Lecture Notes in Networks and Systems journal is having the highest publications and Journal of Operations Management is having the most cited document. Sharma A is the most contributing author to the literature. India is the most contributing country with around 12.5% of total publications. By research gap analysis\, the future direction in the domain of artificial intelligence in digital marketing can be green marketing\, ethical AI\, personalization\, automation and prediction. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:03ac2d980c68b766940e4a5fe76feca7 URL:http://5thworldconferenceoninformations.sched.com/event/03ac2d980c68b766940e4a5fe76feca7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Understanding the Drivers of Financial Literacy and Digital Investment Behaviour among Generation Z DESCRIPTION:Authors - Nandgopan R\, Pavan Shankar R\, Santanu Mandal Abstract - This research investigates the interconnected factors of financial literacy and digitised investment behaviour of Generation Z inhabiting the financial ecosystem in India that is increasingly becoming digitised. The study examines nine significant drivers through the lens of a cross-sectional survey involving 115 respondents aged 18–27 years\, including financial knowledge\, trust in digital finance platforms\, digital literacy\, social media and peer effect\, perceived financial risk\, consumer experience and design of the application\, financial socialization by parents\, awareness of regulations\, and the perception of uncertainty in the economy. ISM is used for the identification of hierarchal relationships between all the variables\, whereas MICMAC analysis is used for classifying the variables on the basis of driving power and dependence power. Our results indicate that regulatory awareness\, perception of economic uncertainty\, and financial socialization by parents are the exogenous high-driving determinants of the intermediate enablers of financial literacy and digital literacy\, and the intermediate determinants of the dependent factors like trust\, perceived risk\, and user experience. This hierarchy demonstrates that policy and practice must build on higher-ordered enablers before approaching determinants of behaviours at lower order levels. The study contributes theoretically by integrating the Theory of Planned Behaviour and Technology Acceptance Model\, and offers practical recommendations for policymakers\, educators\, and fintech designers to foster sustainable financial literacy and digital investment participation among Gen Z. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:de19761db343abafe2375839996c462a URL:http://5thworldconferenceoninformations.sched.com/event/de19761db343abafe2375839996c462a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Website Defacement Detection using Machine Learning Technique DESCRIPTION:Authors - Liladhar P. Dhake\, Jayashree Katti\, Sapana Kolambe Abstract - Website defacement attacks have been a significant threat to both private and public organizations’ websites and web portals. Such attacks can have severe repercussions for website owners\, disrupting website operations and tarnishing their reputation\, potentially resulting in substantial financial losses. With our approach\, we examined SVM\, which is a type of machine learning for detecting website defacement. Our approach applied machine learning methods to develop classifiers that distinguish web pages into normal and attacked classes. Moreover\, we collected a large number of features from the website's content and metadata to train and test the algorithms. This method is applicable to both static and dynamic websites\; through training\, it can learn to adjust to a wide range of page types. The use of an algorithm from machine learning to obtain results has shown that our approach achieves very high detection accuracy with a very low rate of false positives. Additionally\, it should be noted that our approach does not require it to depend on massive computational capabilities. CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:7e2cf98aef0bf1b3f7bb18ae805b7bce URL:http://5thworldconferenceoninformations.sched.com/event/7e2cf98aef0bf1b3f7bb18ae805b7bce END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:AARA: An AI Registration Assistant DESCRIPTION:Authors - John Jenq Abstract - An Artificial Intelligence (AI) agent is an expert that can handle tasks efficiently and accurately\, and can execute specific tasks automatically. In this paper\, we develop an AI class scheduling assistant system. This system consists of a large language model (LLM) which serves as an interface to the user\, and an agent. This agent contains several sub-agents to perform the scheduling task. The data used by the agent was acquired from the University website. It was pre-processed and stored on an excel file that is accessible to the agent. One of the sub-agents will load the file and convert it into Python Pandas data frame. Another sub-agent has the function of finding all the available class sections based on the user’s input from the data frame. This available section information can be used later\, along with the user’s data by other sub-agents. OpenAI GPT-4 model is used for the LLM. We implemented the system using Python programming language. According to our experimental results\, the agent workflow runs smoothly and quickly\, and the system performs the scheduling task accurately. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:6a81bb0bb68a342f2115dead559f4d93 URL:http://5thworldconferenceoninformations.sched.com/event/6a81bb0bb68a342f2115dead559f4d93 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Adapting Large Language Models for Customer Service: A Comparative Study of RAG\, RAFT and DoRA DESCRIPTION:Authors - Anh Truong\, An Nguyen\, Huy Le\, Thang Pham Abstract - Large language models (LLMs) are being increasingly deployed in customer-service chatbot applications. While traditional fine-tuning approaches often suffer from hallucinations or require computationally expensive retraining\, emerging retrieval-based and parameter-efficient methods are increasingly regarded as promising alternatives. However\, comprehensive evaluation of these paradigms in a customer-service context remains limited. To address this gap\, we conduct a comprehensive comparison of three fine-tuning paradigms - Retrieval-Augmented Generation (RAG)\, Retrieval-Augmented Fine-Tuning (RAFT)\, and Weight-Decomposed Low-Rank Adaptation (DoRA) - for customer-service chatbot applications. All methods share a common backbone and are evaluated on the Bitext customer-support dataset. RAG method achieves strong factual consistency at the cost of higher inference latency. RAFT delivers the best overall balance of intent-classification accuracy\, coverage\, and low hallucination with moderate latency overhead. DoRA extends LoRA (Low Rank Adaptation) by decomposing weight updates into magnitude and directional components for precise low-rank adaptation. On Bitext\, DoRA’s end-to-end fine-tuning not only achieves medium accuracy and coverage but also suffers a higher hallucination rate due to limited training data. In larger-scale settings (e.g.\, SQuAD + 400K-row FAQ)\, DoRA demonstrates surprising low hallucination and high BLEU/ROUGE\, proving that dataset size significantly influences its performance. The results highlight trade-offs between latency\, accuracy\, and factual reliability\, while emphasizing the importance of data scale and retrieval grounding in deploying scalable\, trustworthy LLM-based customer-service systems. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:f1614d048a11dca5a680f4f8dd625b31 URL:http://5thworldconferenceoninformations.sched.com/event/f1614d048a11dca5a680f4f8dd625b31 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:An IoT-Enabled Real-Time Monitoring\, Alerting\, and Cloud Data Management System for Optimized Water Quality Control in Recirculating Aquaculture Systems (RAS) DESCRIPTION:Authors - Tahfizul Hasan Zihan\, Hana Sultan Chowdhury\, Shirazim Munir Deap\, Rubayed Mehedi\, Farhad Alam\, A. M. Shahabuddin\, Mahady Hasan Abstract - Recirculating Aquaculture Systems (RAS) have increasingly gained attention in Bangladesh due to their efficient water use. However\, maintaining real-time water quality is challenging\, as delayed anomaly detection often causes economic loss and compromises fish health. To address this\, we developed a low-cost IoT-based monitoring and alert system that integrates industry-standard sensors to track key water parameters (pH\, turbidity\, dissolved oxygen\, temperature\, oxidation-reduction potential\, total dissolved solids\, and electrical conductivity) using Arduino microcontrollers and ESP8266 Wi-Fi modules. The total hardware cost was under USD 700\, an order of magnitude cheaper than commercial systems. Sensor readings were published every 15 seconds via MQTT to the Thing Speak cloud platform\, enabling real-time visualization and WhatsApp-based alerts for immediate intervention. Experimental deployment demonstrated the system’s capability to maintain optimal conditions consistently\, identifying critical events such as abnormal water quality drops efficiently. Clear daily and monthly trends were observed\, enabling predictive adjustments and informed automated decision-making. This IoT approach significantly improves operational efficiency and reliability in resource-limited aquaculture settings typical of Bangladesh\, ensuring sustained fish productivity and welfare. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:e800a23dfe5587f952dc703a5531f0f4 URL:http://5thworldconferenceoninformations.sched.com/event/e800a23dfe5587f952dc703a5531f0f4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Citizens’ Perceptions of AI Government Chatbot Adoption DESCRIPTION:Authors - Ayman Alarabiat\, Yousef Alarabiat\, Mahmoud AlZuabi\, Mamoun Shakatreh Abstract - Governments are increasingly leveraging artificial intelligence (AI) Chatbots to enhance e-service accessibility. However\, Chatbots adoption among citizens’ remains low\, limiting their intended benefits. This study explores citizens’ perspectives on government Chatbots adoption. A quantitative correlational research approach was employed\, collecting 358 responses from Jordani-an citizens who had used government Chatbots in the last 6 to 12 months. An online survey measured ten key constructs: low complexity\, relative advantage\, compatibility\, trialability\, observability\, trust\, responsiveness\, perceived intelligence\, anthropomorphism\, and Chatbot adoption. Data analysis using SPSS 24 revealed low willingness to adopt Chatbots\, primarily due to concerns about Chatbot intelligence\, responsiveness\, and trust. Additionally\, low observability and limited perceived relative advantage further hinder adoption. These findings provide insights for policymakers\, government agencies\, and Chatbot developers to enhance Chatbot functionality and user experience. Key recommendations include improving Chatbot intelligence and responsiveness\, increasing public awareness\, and fostering greater trust in the Chatbot. Addressing these factors can drive greater adoption\, maximizing the efficiency and impact of AI-driven public services. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:92a33ac392a23babd1c001a75af4765d URL:http://5thworldconferenceoninformations.sched.com/event/92a33ac392a23babd1c001a75af4765d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Collegial Supervision as a Catalyst for Digital Transformation: Insights from a Rural Indonesian Secondary Schools DESCRIPTION:Authors - Maisyaroh\, Agus Timan\, Mustiningsih\, Maulana Amirul Adha\, Indra Lesmana\, Rudy Ansar\, Novia Putri Arianti Abstract - Digital learning transformation in rural schools faces various challenges\, including limited infrastructure and low digital literacy among teachers. This study aims to explore the contribution of collegial supervision in supporting this transformation. Using a descriptive qualitative approach\, data were collected through in-depth interviews\, observations\, and documentation at a high-performing private secondary school in a rural area. The findings reveal that collegial supervision is grounded in values of trust\, equality\, shared reflection\, and communal cooperation. This approach provides a collaborative space for teachers to exchange best practices\, enhance their technological competencies\, and develop effective digital teaching strategies. Despite challenges related to time\, resources\, and varying levels of understanding\, collegial supervision has proven effective in fostering an innovative school culture that supports digital-era teaching and learning. This study contributes to the literature on educational supervision by offering context-specific insights and practical strategies for teacher development in resource-constrained schools. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:1278e7ca834812c781bbfeddb0bfdb48 URL:http://5thworldconferenceoninformations.sched.com/event/1278e7ca834812c781bbfeddb0bfdb48 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Deep Learning in Oncology: A Multi-Modality Survey of Diagnostic and Prognostic Models DESCRIPTION:Authors - Nishat Shaikh\, Parth Shah\, Bimal Patel Abstract - Deep learning has revolutionized oncology by enabling unprecedent-ed integration of multimodal data for cancer diagnosis and prognosis. This comprehensive survey presents the first systematic analysis of deep learning architectures across four major cancer types (lung\, breast\, skin\, and brain) through three critical data modalities: medical imaging\, histopathology\, and genomics. Our unique contribution lies in providing a structured taxonomy of multimodal fusion strategies and identifying critical architectural innovations that have emerged in the 2021-2025 period. We systematically analyze 60+ recent studies\, revealing that attention-based mechanisms and Transformer architectures demonstrate superior performance in handling heterogeneous cancer data compared to traditional CNN approach-es. Our analysis uncovers three key research gaps: (1) limited interpretability frameworks for clinical deployment\, (2) insufficient standardization across institutions\, and (3) scalability challenges for real-world implementation. This survey uniquely bridges the gap between theoretical deep learning advances and practical oncological applications by proposing a unified framework for multimodal cancer analysis. We provide actionable insights for researchers and clinicians\, establishing clear directions for future development in AI-driven cancer care that addresses both technical innovation and clinical translation requirements. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:6fa28c08c3362be2a76caea4719bced4 URL:http://5thworldconferenceoninformations.sched.com/event/6fa28c08c3362be2a76caea4719bced4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Fostering Resilience strategies through Smart Manufacturing\, Innovation and Circularity in Agri-food supply chain DESCRIPTION:Authors - Esthefano Palomino\, Rodrigo Condor\, Edgar Ramos\, Ludwig Tocto\, Victor Pimentel Abstract - Agri-food supply chains are increasingly exposed to climate variability\, resource constraints\, and disruptive shocks\, requiring strategies that enhance resilience and sustainability. This study applies the Best–Worst Method (BWM) to assess and prioritize four strategic dimensions: resilience\, smart manufacturing\, innovation\, and circularity. The results indicate that resilience is the most critical enabler\, while smart manufacturing and innovation provide significant complementary support\, with circularity ranking lowest. These findings emphasize the central role of resilience in safeguarding agri-food systems and demonstrate how technology and innovation can strengthen long-term sustainability. The study contributes by offering a structured decision-making framework that helps managers and policymakers focus on the most impactful dimensions when designing more adaptive and sustainable agri-food supply chains. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:82fb8c224e0c57ac4468f75d63314828 URL:http://5thworldconferenceoninformations.sched.com/event/82fb8c224e0c57ac4468f75d63314828 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:GENERATIVE ADVERSARIAL NETWORKS FOR MEDICAL IMAGE AUGMENTATION: A COMPREHENSIVE STUDY DESCRIPTION:Authors - Sarika Pabalkar(Wagh)\, Kirti Jain Abstract - Generative adversarial networks\, or GANs\, are strong tools for improving medical pictures because they can make high-quality virtual images that can be used to solve problems like limited datasets\, image unpredictability\, and poor diagnosis accuracy. This research looks at all the ways that GAN can be used in medical imaging and highlights the most important improvements in the process of segmentation reconstruction\, disease identification\, and cross-modal synthesis. A structured methodology based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) was employed to identify\, screen\, and analyze 42 peer-reviewed articles published between 2020 and 2025 across databases such as PubMed\, Scopus\, IEEE\, and ScienceDirect. The review compares widely used GAN architectures—including CycleGAN\, Pix2Pix\, DCGAN\, and ProGAN— evaluating their strengths\, limitations\, and suitability for different imaging modalities such as MRI\, CT\, X-ray\, ultrasound\, and mammography. There are significant problems\, including mode collapse\, instability in training\, no consistent evaluation standard\, and few opportunities for clinical validation. The results show the increasing importance of GANs in generating clinically useful data for rare disease information and for cross-modality tasks. The discussion also indicated future interventions that would focus on model stability\, ethical use\, clinical incorporation\, and generalization across populations. The aim of the review is to help fellow researchers and practitioners through assessing state-of-the-art GAN approaches and defining gaps that will need to be addressed prior to more adaptation of GANs in medical imaging. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:f41b76149fd2f4f2842532705c7bac40 URL:http://5thworldconferenceoninformations.sched.com/event/f41b76149fd2f4f2842532705c7bac40 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Understanding and Mitigating Bias in Artificial Intelligence Systems: An Ontological Perspective DESCRIPTION:Authors - Om Roy\, Dhruv Shingala\, Priyanka Patel Abstract - Bias within Artificial Intelligence (AI) systems constitutes a profound challenge with substantial implications for fairness\, accountability\, and societal equity. This paper presents an exhaustive examination of the ontology of bias in AI\, delving deeply into its conceptual underpinnings and exploring the intricate algorithmic consequences arising from biased data and models. By establishing a comprehensive and nuanced framework that categorizes diverse manifestations of bias and elucidates their origins\, this study aims to foster a profound understanding of how bias permeates AI systems. Integrating interdisciplinary perspectives drawn from philosophy\, sociology\, and computer science\, the ontology of bias is meticulously dissected to reveal its multifaceted nature. Furthermore\, the paper investigates the profound impacts of these biases on critical decision-making processes and proposes multifaceted strategies for mitigating bias through ethical design\, advanced algorithmic techniques\, and stringent regulatory frameworks. Through detailed case studies and empirical analysis\, this research highlights the inherent complexities in addressing bias and underscores the imperative for collaborative endeavors to cultivate equitable AI technologies. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:98dbd548b1a05fa72bc8d65716ae3695 URL:http://5thworldconferenceoninformations.sched.com/event/98dbd548b1a05fa72bc8d65716ae3695 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T163000Z DTEND:20261019T183000Z SUMMARY:Using ChatGPT for Sustainable Development Education: Potentials\, Risks\, and Governance Needs DESCRIPTION:Authors - Payel Das\, Tejaswini Seelam\, Rajeswari Annam Abstract - This study investigates the intersection between generative AI\, sustainable development and education by conducting a systematic review on the utilization of ChatGPT and other Large Language Models (LLMs) in relation to Sustainable Development Goals (SDGs)\, focusing on SDG 4 and SDG 12. The article explores how technology-enhanced learning and LLMs are challenging pedagogical traditions\, practices\, even ethical dilemmas\, and calls for responsible governance. There were 59 peer-reviewed articles included between 2023-2025 which provided data synthesis. Three core clusters were discerned using the VOS viewer keyword co-occurrence map: (1) educational impact and learning outcomes\, (2) stakeholder ethics and governance perspectives\, and (3) integrity Challenges of AI-assisted instruction. The study also raises alarms about threats that could emerge from misinformation\, academic cheating\, algorithmic bias and unequal ac-cess. It also underscores the lesser-known environmental footprint of AI tools. CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:16f9ca9540c29e4150c59efc82be0acb URL:http://5thworldconferenceoninformations.sched.com/event/16f9ca9540c29e4150c59efc82be0acb END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183000Z DTEND:20261019T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:4ad28d7c31ae96fac88101231ae990fa URL:http://5thworldconferenceoninformations.sched.com/event/4ad28d7c31ae96fac88101231ae990fa END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183000Z DTEND:20261019T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:41a7142a333af292d728d3d338938969 URL:http://5thworldconferenceoninformations.sched.com/event/41a7142a333af292d728d3d338938969 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183000Z DTEND:20261019T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:e197f5415689afb2e227523a7ed84ac6 URL:http://5thworldconferenceoninformations.sched.com/event/e197f5415689afb2e227523a7ed84ac6 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183000Z DTEND:20261019T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:e33350b7676319b2b10b408e39cbaa65 URL:http://5thworldconferenceoninformations.sched.com/event/e33350b7676319b2b10b408e39cbaa65 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183000Z DTEND:20261019T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:cdaf501a2983cc3f5b3a3dfcd1a76d1a URL:http://5thworldconferenceoninformations.sched.com/event/cdaf501a2983cc3f5b3a3dfcd1a76d1a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183000Z DTEND:20261019T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:f6cb57fa3880c505c68c11b618d5d6f9 URL:http://5thworldconferenceoninformations.sched.com/event/f6cb57fa3880c505c68c11b618d5d6f9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183000Z DTEND:20261019T183200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:a0774bf209a18b3794516da0bbbc5dda URL:http://5thworldconferenceoninformations.sched.com/event/a0774bf209a18b3794516da0bbbc5dda END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183200Z DTEND:20261019T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:03ef4cd0dc2665ed58220897d7bfead5 URL:http://5thworldconferenceoninformations.sched.com/event/03ef4cd0dc2665ed58220897d7bfead5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183200Z DTEND:20261019T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:13b0824308db654c0e1ce9107de7f597 URL:http://5thworldconferenceoninformations.sched.com/event/13b0824308db654c0e1ce9107de7f597 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183200Z DTEND:20261019T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:3c052b3910da25b25c30078748cd0dac URL:http://5thworldconferenceoninformations.sched.com/event/3c052b3910da25b25c30078748cd0dac END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183200Z DTEND:20261019T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:971e797dbd4034d2151b480bf3c86dc0 URL:http://5thworldconferenceoninformations.sched.com/event/971e797dbd4034d2151b480bf3c86dc0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183200Z DTEND:20261019T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:16322fb90180e279ad9d30e2b7e0aeaf URL:http://5thworldconferenceoninformations.sched.com/event/16322fb90180e279ad9d30e2b7e0aeaf END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183200Z DTEND:20261019T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:e9618400c658a3fb5642e6179db992a4 URL:http://5thworldconferenceoninformations.sched.com/event/e9618400c658a3fb5642e6179db992a4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T183200Z DTEND:20261019T183500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 7G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:458784d174251eeb40c459bc169a63bb URL:http://5thworldconferenceoninformations.sched.com/event/458784d174251eeb40c459bc169a63bb END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191300Z DTEND:20261019T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:f21e4669dfb05ee2a36d4728ef78d884 URL:http://5thworldconferenceoninformations.sched.com/event/f21e4669dfb05ee2a36d4728ef78d884 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191300Z DTEND:20261019T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:5da8133e57f6828e9dd5fbb58f8de03f URL:http://5thworldconferenceoninformations.sched.com/event/5da8133e57f6828e9dd5fbb58f8de03f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191300Z DTEND:20261019T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:f3dd521d9c082d6ebabe11051cd94a22 URL:http://5thworldconferenceoninformations.sched.com/event/f3dd521d9c082d6ebabe11051cd94a22 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191300Z DTEND:20261019T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:1c8d64e493da69f266dc71070c82efcc URL:http://5thworldconferenceoninformations.sched.com/event/1c8d64e493da69f266dc71070c82efcc END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191300Z DTEND:20261019T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:e132dd25aa77573a8cba4b03d8d88766 URL:http://5thworldconferenceoninformations.sched.com/event/e132dd25aa77573a8cba4b03d8d88766 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191300Z DTEND:20261019T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:9b26d4931ee48bc3a14487bc0df5e574 URL:http://5thworldconferenceoninformations.sched.com/event/9b26d4931ee48bc3a14487bc0df5e574 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191300Z DTEND:20261019T191500Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:38994eb2e9175662d8150d9674c1aad9 URL:http://5thworldconferenceoninformations.sched.com/event/38994eb2e9175662d8150d9674c1aad9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Deep Learning Architectures for Voice Recognition: A Comparative Analysis and Future Directions DESCRIPTION:Authors - Seema Tripathi\, Nikita Bhardwaj\, Shivani Bansal Abstract - Voice recognition technology has evolved into a cornerstone in contemporary applications\, from virtual assistants and intelligent homes to biometric security and healthcare. Its potential to facilitate unobstructed human-computer interaction has hastened the need for more precise and more robust systems. GMM and HMM traditionally paved the way for voice processing. However\, deep learning architectures—namely Convolutional Neural Networks (CNNs)\, Recurrent Neural Networks (RNNs)\, and Transformer-based models—have revolutionized the field by achieving unprecedented performance and flexibility. This research paper provides a comparative study of major deep learning models for voice recognition\, critically evaluating their design rationales\, merits\, and shortcomings Some major challenges like scarcity of data\, noise tolerance\, computational efficiency\, and interpretability of models are discussed. The paper also offers the perspectives of the future trends in work like the inclusion of self-supervised learning\, light-weight models for edge devices\, and multimodal systems that will influence the next voice recognition generation. The goal of this work is to offer an end-to-end perspective of what exists currently and stimulate future work in this very dynamic field. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:1ea53ab8e6be7acee5e6ef6f2d1b3430 URL:http://5thworldconferenceoninformations.sched.com/event/1ea53ab8e6be7acee5e6ef6f2d1b3430 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Emerging Research Themes in AI-Based Supply Chains\, Transportation and Logistics: A Bibliometric Analysis DESCRIPTION:Authors - Vipul Lanjewar\, Sourish Joshi\, Sujata Joshi\, Menachem Domb Abstract - AI is changing supply chain\, transport\, and logistics using neural net-works to improve decisions. It helps with real-time analysis\, route planning\, and demand prediction. A bibliometric analysis with Scopus data was performed\, using VOSviewer and Biblioshiny to track trends\, citations\, and new themes in AI for these fields. The focus was on areas like warehouse automation\, self-driving logistics\, and smart transportation\, while also tackling data security and ethical issues. By finding key research and gaps\, this paper shows how AI can shape the future of these industries. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:af6b8fec208a331165e496c1c3072281 URL:http://5thworldconferenceoninformations.sched.com/event/af6b8fec208a331165e496c1c3072281 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Internal Conflicts: Examining the influence of arms and armed forces DESCRIPTION:Authors - Anshika Srivastava\, Rojalin Patri Abstract - This study explores whether arms and armed forces increase the probability of armed conflict within a country. Though several studies in literature have highlighted the cases where arms and armed forces have influenced armed conflict within a country\, none of them have provided empirical evidence to support this phenomenon. This study attempts to bridge the gap by providing a quantitative analysis across 45 countries over 28 years and further substantiates the arguments laid in qualitative studies. Random effect panel logistic estimates and year-wise logistic estimates have been used to capture the overall as well as year-wise significance of arms and armed forces on armed conflict within the country\, respectively. Similarly\, when the number of armed forces increase by one million\, the odds for armed conflict becomes 3.97 times more and when military expenditure increase by 1%\, the odds for armed conflict becomes 9.06 times more than before. These insights point towards the fact that arms\, armed forces and militarism don’t necessarily help reduce violence. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:46a46c248aa68d3550304a7bd1070027 URL:http://5thworldconferenceoninformations.sched.com/event/46a46c248aa68d3550304a7bd1070027 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Managing Professional and Personal Life A Study on Work-Life Balance Among Working Professionals DESCRIPTION:Authors - Kalyani Yede\, Deepak Sharma Abstract - Work-life balance is of utmost importance to career workers managing the challenges of contemporary work environments and family duties. This research employs secondary data to investigate the determinants of work-life balance\, its impact on worker satisfaction\, productivity\, and health\, and organizational support as a facilitator of balance. The study finds that flexible work arrangements\, supportive management\, and organizational policies all contribute strongly to helping employees balance work and personal life. Excessive workload and a lack of support\, on the other hand\, lead to job dissatisfaction and stress. The study emphasizes a need for cooperative efforts between employers and employees to create a good work-life balance. This study offers useful insights to organizations that want to enhance organizational performance and employee well-being by implementing focused work-life balance programs. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:16e413babbb3566d1d442a1cd872d9f0 URL:http://5thworldconferenceoninformations.sched.com/event/16e413babbb3566d1d442a1cd872d9f0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:OPTIMIZING VIDEO SUMMARIZATION USING DEEP REINFORCEMENT LEARNING WITH DIVERSITY REPRESENTATIVE REWARD DESCRIPTION:Authors - Namrata Patil\, Pravin Desai\, Ashvini Patil\, Pragati Patil Abstract - In the context of multimedia content of huge scale\, effective and efficient video summarization has become more and more important for improving web browsing experiences and information overload. In this paper\, we introduce a new video summarization method by modeling it as a sequential decision-making problem. A Deep Summarization Network (DSN) is proposed for predicting the probability of considering each video frame in terms of its possible contribution to the final summary. For training the DSN\, we suggest an end-to-end deep reinforcement learning system that works in a fully unsupervised way\, without requiring annotated labels or human intervention. Our approach has its foundation in a well-crafted reward function that assesses generated summaries along two primary dimensions: diversity and representativeness. These elements are designed to ensure that the chosen frames not only convey the main content of the video but also encompass a good number of visual and contextual variations. The DSN is trained to maximize these rewards\, resulting in brief\, informative\, and non-redundant summaries. Extensive experiments are performed on two standard datasets to confirm the efficacy of the new method. The experimental results show that our method is capable of rendering competitive performance compared with state-of-the-art methods\, especially under unsupervised scenarios\, thus revealing excellent potential to be applied in real-world systems for large-scale video analysis and multimedia retrieval. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:d47983037d497d44955782a874627ef6 URL:http://5thworldconferenceoninformations.sched.com/event/d47983037d497d44955782a874627ef6 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Predicting Esophageal Cancer with Machine Learning: An Automated Approach DESCRIPTION:Authors - Janwale Asaram Pandurang\, Minal Dutta\, Savita Mohurle Abstract - The machine learning algorithms used for the automated predction of esophageal cancer\, a highly destructive disease that frequently exhibits at an advanced stage because it lacks early symptoms\, is examined in this work. A huge dataset including clinical\, demographic\, and diagnostic information is used in the study to relate the classification algorithms of logistic regression and decision trees. With a incredible accuracy of 99.75% compared to 64.87%\, the Decision Tree model clearly beaten Logistic Regression. Its capability to recognise complex\, non-linear relationships in the data is responsible for Decision Tree's better performance\, which makes it a useful tool for early cancer detection. The study identifies the need for validation on a variety of datasets and techniques to reduce overfitting\, even as the results illustrate how machine learning may improve diagnostic accuracy. Improved clinical processes and better patient outcomes are made possible by us research's successful development of scalable\, interpretable\, and effective diagnostic tools. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:cc89562b4ce813cd814db77c9a7363fc URL:http://5thworldconferenceoninformations.sched.com/event/cc89562b4ce813cd814db77c9a7363fc END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Recommendation of Research Papers using KNN and Universal Sentence Encoder DESCRIPTION:Authors - Jatin Kumar Sangewar\, Chandan Kumar Sangewar\, Gaurav Kumawat\, Chirag Joshi Abstract - In this research paper\, we introduce a novel approach to improving research paper recommendation systems using the Universal Sentence Encoder (USE) to analyze and understand the textual content of academic papers\, such as their title\, abstract\, and publication year. Our ultimate objective in the proposed methodology is to greatly enhance the accuracy and personalization of paper recommendations in favor of scholars\, researchers\, and students. Our research provides a thorough system architecture review\, extensive experimentation with regard to state-of-the-art benchmarks\, as well as an assessment of its probable impact on the world of academia. In addition to the technicalities of our method\, we explore the larger research paper recommendation system context. This involves a close look at the issues that plague these systems\, including data sparsity and the cold start problem\, and the potential directions they offer for enhancing academic discovery. We also look at possible futures for the discipline\, including the incorporation of user profiling\, collaborative filtering methods\, and ethical considerations into the building of these systems. The goal of this study is to push the field of research paper recommendations into a new generation based on the use of state-of-the-art Natural Language Processing and Machine Learning methods while ensuring a commitment to enhancing the academic experience. The new use of the USE model in this system offers intriguing possibilities for making more accurate and user-specific recommendations\, which will eventually enable a more productive and efficient academic experience for users in general. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:0aec5f769044d1140e2a4017121b688a URL:http://5thworldconferenceoninformations.sched.com/event/0aec5f769044d1140e2a4017121b688a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Smart Water Temperature Modulation Bottle DESCRIPTION:Authors - Naina Kokate\, Aoudumber D. Londhe\, Priyanka Swapnil Raikar\, Nikeeta Pande\, Sanjana Sanjiv Nikam\, Nethra Nadar\, Indranil Nayak\, Rhia Nevgi\, Neil Oswal Abstract - This project demonstrates about working of Peltier module with an new approach\, we have tried making a smart way of using it by making a smart water temperature modulation bottle. The targets we wanted to achieve through this project was to make it energy efficient along with cost effective. the dual purpose of heating and cooling to be done as per our wishes. the main components which are used in this project are TEC1-12706 Peltier module\, W1209 digital thermostat\, two heatsinks and two fans. the project can be used for personal as well as professional fulfilling of needs such as getting water to a certain temperature or maintaining a medicine at a given temperature. the project can work on both battery and electricity. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:ea44b3978350acab94ed63a633279065 URL:http://5thworldconferenceoninformations.sched.com/event/ea44b3978350acab94ed63a633279065 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Statistical Analysis of the Israeli-Palestinian Conflict: Patterns and Dynamics DESCRIPTION:Authors - Ketaki Paranjape\, Rajasi Barapatre\, Sandhya Arora Abstract - This study conducts a statistical analysis of the Israeli-Palestinian conflict to uncover patterns and relationships that characterize the dynamics of hostilities. The research examines critical questions about the association between event location\, age\, citizenship\, and types of ammunition\, employing statistical methods such as Z-scores\, Chi-square tests\, and F-tests on a comprehensive dataset. Key findings include significant regional variations in participation in hostilities\, with Gaza showing the highest levels of engagement\, and the predominance of the 21–30 age group in active involvement. Additionally\, asymmetrical impacts were observed\, with Palestinian civilians primarily affected by Israeli security forces\, and Israeli civilians targeted by Palestinian actors. Analysis of ammunition usage reveals targeted engagement against younger age groups and highlights the varied means of violence in the conflict. These findings provide valuable insights into the conflict's demographic and regional dimensions\, offering a foundation for data-driven conflict resolution strategies and humanitarian interventions. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:6b705283bc82f754538e652d6652cc11 URL:http://5thworldconferenceoninformations.sched.com/event/6b705283bc82f754538e652d6652cc11 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Work-Life Balance among Employee in IT Parks in Pune: A Research Study DESCRIPTION:Authors - Kalyani Yede\, Deepak Sharma Abstract - This study looks into the effect of work-life balance on IT professionals in Pune\, India\, through analysis of determinants that affect this balance and measures to enhance it. A thorough review of literature demarcates important areas for study\, such as the organizational policy\, socio-cultural determinants\, and perceptions. The research will fill the gap between research and practice by presenting culturally responsive suggestions to organizations looking to improve employees' job satisfaction and productivity. The research will\, with a mixed-methods design\, offer insights for policy-making and enhancing the quality of life of IT professionals. CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:be0baafa2f067f2041e377951c0ac14c URL:http://5thworldconferenceoninformations.sched.com/event/be0baafa2f067f2041e377951c0ac14c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:A Lightweight Framework for Implementing ISO/IEC 26550 in Small and Medium-sized Software Enterprises in Bangladesh DESCRIPTION:Authors - Sayeda Rahnuma Akthar\, Fatima Ibrahim\, Muhammad Rezaul Islam\, Marzan Binte Hasan\, Md. Ataur Rahman\, Zinia Hafiz\, Farzana Sadia\, Mahady Hasan\, M. Rokonuzzaman Abstract - This study explores the challenges faced by Bangladeshi software Small and Medium-sized Enterprises (SMEs) in adopting ISO/IEC 26550 for Software Process Improvement (SPI). Data collected from 12 SMEs revealed uneven implementation across key process areas\, with high familiarity in domain requirements (up to 95\%) but limited engagement in testing and validation practices. To address these gaps\, the study proposes a lightweight PDCA (Plan–Do–Check–Act) framework tailored to the unique resource constraints of SMEs. Un-like traditional models such as CMMI or ISO/IEC 12207\, the proposed approach emphasizes simplicity\, cost-effectiveness\, and role-based adaptability\, making it more practical for SMEs in emerging economies. The framework supports scalable and gradual process improvement\, enhances quality assurance\, and facilitates stronger alignment with ISO/IEC 26550 in resource-limited environments. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:5815d1ce87ee13ea83f3b746a32c908f URL:http://5thworldconferenceoninformations.sched.com/event/5815d1ce87ee13ea83f3b746a32c908f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Air quality prediction using Computational Intelligence DESCRIPTION:Authors - Sushmitha\, Vijayalaxmi Abstract - This paper provides prediction of air quality using computational intelligence techniques. The study employs various Computational Intelligence techniques to evaluate the data associated with environmental pollution and hence to predict the air quality focusing on PM2.5 and PM10 concentrations. The performance of each model is assessed with standard evaluation metrics. Through a series of simulations\, it is observed that the results suggest that computational intelligence techniques play an essential role in improving the accuracy of air quality prediction models. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:a2652338e3e2bc370e4095750f27364f URL:http://5thworldconferenceoninformations.sched.com/event/a2652338e3e2bc370e4095750f27364f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:An Extensive Examination of the Development of Financial Technology in the Banking Sector: The Role of Trust as an Entry Barrier DESCRIPTION:Authors - Jaride Chama\, Hajraoui Kenza\, Zaidane Kaoutar\, Benabdelkrim El Filali Yasmine Abstract - With technological developments and the digitalization of business processes in the banking sector\, physical and virtual environments are complementing each other. Electronic channels are no longer considered as additional or less costly way of interacting with customers. Today\, they represent a considerable and constantly growing part of the activities of bank institutions world-wide. The aim of this work is to assess the impact of trust in the development of fintech banking through a transnational analysis. The results of this work can be used to map the countries that studied this topic. The findings of this study reveal that\, despite the fact that research in this field has been carried out in a wide variety of economic and cultural contexts (45 countries were surveyed)\, the previous studies agreed on the strong presence of trust as an entry barrier for the development of financial technology in the banking sector. In addition to trust\, other adoption factors appear to be essential for consumers. The vulnerability resulting from digitalization in the banking sector has enabled us to formulate some suggestions for further investigations. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:fb9cd4ad8b1f53d8de5d01dde856eba1 URL:http://5thworldconferenceoninformations.sched.com/event/fb9cd4ad8b1f53d8de5d01dde856eba1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:An In-depth Analysis of the Impact of Feature Transformation Learning on Classification Matrix in Driver Identification DESCRIPTION:Authors - Md. Abbas Ali Khan\, Md. Musfique Anwar\, Mohammad Hanif Ali\, Touhid Bhuiyan\, Md. Ataur Rahman Abstract - Personalized driving assistance\, security\, and usage-based insurance models all depend on driver identification in intelligent transportation systems. Conventional techniques for identifying drivers primarily rely on biometric or manually engineered feature data\, which may not adequately capture the nuances of unique driving actions. Using time-series driving data\, including vehicle speed\, steering angle\, and acceleration\, we present a unique contrastive learning-based method for driver identification in this study. The suggested model uses contrastive learning to compare driving sessions from the same driver to those of other drivers to learn how to distinguish between them. Rather than requiring manual feature extraction\, our method automatically extracts strong\, high-dimensional representations of driving behavior. Concerning driving sequences\, the contrastive learning framework aims to minimize the similarity between sequences from different drivers and maximize the similarity between sequences from the same driver. When applied to situations with various driving behaviors and a small amount of labeled data\, our strategy outperforms more conventional classification techniques in accuracy. The suggested model offers a scalable and effective solution for real-world applications\, as demonstrated by experimental findings on driving publicly available datasets. This model also greatly increases driver identification performance. We applied seven machine learning classification models. The Random Forest Classifier obtained the highest accuracy of 93.57%. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:875768c28472337487ff7bf8267332c4 URL:http://5thworldconferenceoninformations.sched.com/event/875768c28472337487ff7bf8267332c4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Content Marketing and Corporate Brand Awareness in the Philippines: A Structural Equation Model (SEM) DESCRIPTION:Authors - Ronald C. Barriga\, Dan Jeward Rubis\, Arlene A. San Pablo\, Helinor Y. Medina Abstract - Content video marketing has become vital in the world of marketing for the past few years\, in which companies are into it using content creators to expand brand awareness. The use of different social media platforms makes all this possible technological advancement like 5G connectivity that makes the connection faster\, the continuous and fast innovation in the electronic industry has made everything easy to access. These make content marketing more vital in establishing corporate brand awareness. Brand recall\, recognition and dominance through content video marketing has a significant impact to brand awareness\, where brand recall essentially a dominant contributor to Brand Awareness. Furthermore\, the model Structural Equation Modeling (SEM) shows that for content video marketing to be effective\, the quality of each content must be given importance with consideration also to Knowledge Opinion Leader (KOL) and the Electronic Word of Mouth (eWOM) to strengthen brand awareness. Lastly\, SEM positively indicates how significant the three factors mentioned are to brand awareness. The SEM model has a very good fit for the data\, explaining a large portion of the variance in brand awareness. The results suggest that to improve brand awareness\, strategies that enhance brand recognition\, recall\, and dominance should be prioritized. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:a72dd8bfe8c21926547b1abaddd9eb04 URL:http://5thworldconferenceoninformations.sched.com/event/a72dd8bfe8c21926547b1abaddd9eb04 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:CyberShield AI: A Cyber-Bullying Detection Tool DESCRIPTION:Authors - Dev Parekh\, Jay Patel\, Keshvi Patel\, Dhaval Patel\, Priteshkumar Prajapati Abstract - This paper presents CyberShieldAI\, a novel framework that leverages BERT (Bidirectional Encoder Representations from Transformers) models to detect cyberbullying in online text communications. Our approach harnesses BERT’s contextual understanding capabilities to identify subtle linguistic patterns\, emotional undertones\, and semantic structures commonly associated with cyberbullying content. By fine-tuning BERT on carefully curated datasets of online interactions\, CyberShieldAI can effectively distinguish between harmless communications and those containing bullying\, harassment\, or other harmful content. The framework analyzes text bidirectionally\, capturing crucial contextual relationships that traditional text classification methods might overlook. Experimental evaluations demonstrate that our BERT-based system achieves significant improvements in cyberbullying detection accuracy\, sensitivity\, and specificity compared to conventional machine learning approaches. This paper details the system architecture\, implementation methodology\, dataset preparation challenges\, and performance metrics that validate the effectiveness of our strategy. CyberShieldAI represents a significant advancement in automated content moderation systems\, which can help create safer online environments\, particularly for vulnerable user populations\, such as children and adolescents. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:d428d28195bfec51204a9d80a1ac00a9 URL:http://5thworldconferenceoninformations.sched.com/event/d428d28195bfec51204a9d80a1ac00a9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:DESIGN AND DEVELOPMENT OF A SYSTEM FOR UNVEILING INAUTHENTICITY IN AUDIO CONTENT DESCRIPTION:Authors - Swati Kale\, Jyoti Tipale\, Shilpa Sonawane\, Kshitij Mulay\, Gaurav Patil\, Nikita Khumkar Abstract - This paper presents a novel multi-modal speech analysis system that integrates deep learning architectures and “Natural Language Processing (NLP)” techniques to address the limitations of traditional speech evaluation approaches. The proposed system combines a custom “Long Short-Term Memory (LSTM)” based neural network for temporal pattern analysis\, TF-IDF vectorization for keyword extraction\, real-time spectrogram analysis for acoustic feature extraction\, and a dynamic content fetching system from Wikipedia datasets. The system demonstrates enhanced accuracy in content relevance detection\, real-time processing with minimal latency\, and a scalable architecture suitable for diverse ap-plications\, including educational\, professional\, and research contexts. The study highlights the system's ability to bridge the difference in the theoretical abilities of speech analysis and their practical implementation. The proposed methodology contributes to the advancement of speech analysis by addressing the challenges of insufficient integration between acoustic and semantic analysis\, static reference materials\, and limited scalability. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:cf49b175755ea4b488cd20eb901dfcce URL:http://5thworldconferenceoninformations.sched.com/event/cf49b175755ea4b488cd20eb901dfcce END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Impact of Complex Engineering Problem Segment under Outcome-Based Education (OBE) in the Context of Engineering Education DESCRIPTION:Authors - Md. Ataur Rahman\, Sabrina Alam\, Saadia Binte Alam\, Mahady Hasan Abstract - Outcomes-based education (OBE) is reshaping engineering education\, with an emphasis on complex engineering problem solving\, with clear outcomes directly related to industry needs. This study assessed the impact of including complex engineering problem-solving in the engineering curriculum within OBE on student skills. Through qualitative and quantitative research methods\, including course curriculum analysis\, student feedback\, questionnaires\, and student achievement. We collect 3 years of data. Data collected over a three-year research period (2022\, 2023\, and 2024) at Independent University\, Bangladesh (IUB)\, this study assessed the improvement in skills such as critical thinking\, application of advanced tools\, sustainability awareness\, professional ethics\, teamwork\, communication\, project management\, lifelong learning\, and entrepreneurship. There are barriers to implementation\, such as resource allocation\, training of faculty members\, and curriculum restructuring\, with evidence of positive improvements in these categories. This study strongly recommends greater application of advanced engineering problem-solving techniques in OBE to match educational outcomes to professional engineering requirements better\, ultimately producing graduates more adept at solving problems in the real world. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:e09a63dcb98496bc7c21498f0303c4e5 URL:http://5thworldconferenceoninformations.sched.com/event/e09a63dcb98496bc7c21498f0303c4e5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Leveraging Large Language Models for Enhanced URL Phishing Detection DESCRIPTION:Authors - Rohit Yadav\, Rohini Bhosale\, Rahul Rathod\, Prashant Dhotre\, Yashraj Salunkhe Patil Abstract - Phishing continues to be a prevalent threat in cybersecurity\, using deceptive URLs to undermine user information and system integrity. Conventional machine learning methods\, though effective when handcrafted features are used\, tend to perform poorly in generalizing against more obfuscated patterns of attacks. This paper presents an effective phishing URL detection system that takes advantage of the contextual strengths of quantized Large Language Models (LLMs)—namely Mistral-7B and Mixtral-8x7B—combined with interpretable gradient boosting models like CatBoost. The LLMs are employed with prompt-based inference for semantic URL evaluation\, whereas the CatBoost model employs lexical and statistical features for structured classification. Tested on a balanced dataset of more than 2.28 mil-lion URLs\, the system has high accuracy and low false positive rates. SHAP-based visualizations are employed to offer transparent explanations for model decisions. The findings prove the real-world feasibility of integrating effective LLM reasoning with conventional ML in real-time phishing defense systems\, particularly in resource-limited settings. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:99a03b9737e3ec731ec4af997d588d51 URL:http://5thworldconferenceoninformations.sched.com/event/99a03b9737e3ec731ec4af997d588d51 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:When Reality Blurs: The Impact of Deepfakes on Psychology and Society DESCRIPTION:Authors - Aryan G. Kale\, Kajal P. Salampuriya\, Nitin Prakash Abstract - The ascent of artificial intelligence technologies\, particularly the generative application of GANs\, has changed the landscape of media production into a milieu that easily allows - creation of hyper-realistic yet deceptive content. While deepfakes have indeed been misused from entertaining\, educative\, and access provisions\, their abuse causes dreadful threats to mental well-being and social harmony. This study explores the psychological effects of deepfakes\, such as anxiety owing to identity theft\, impersonation\, trust erosion in digital media\, cognitive dissonance because of the inability to tell the difference between real and fake content\, and social isolation due to cyberbullying and non-consensual pornography.On the social front\, deepfakes add to the pool of misinformation spreading\, fake news politically entering the narratives\, and a myriad of ethical dilemmas\, adding to general confusion\, anxiety\, and distrust among the public at large in institutions. The economic designs revolve around hiring specialists to thwart deepfake manipulation and attending to its legal and psychological aftermath.To ameliorating this\, the study points out a projective need for strategies of intervention. These would include developing an AI detecting tool that identifies and flags deepfakes\, launching public awareness campaigns to increase digital literacy and critical thinking\, instituting solid legal scaffolding with added ethical principles\, and other support systems including counseling services supporting the victims of deepfake assaults.The study is primarily inclined toward discussing how integrated management approaches shall serve to address the issues faced concerning deepfakes\, while the positives remain intact. Future research is necessary to explore the cultural and demographic nuances of deepfake impacts\, understand the influence of the COVID- 19 pandemic on mental health in the context of deepfake exposure\, and evaluate the effectiveness of emerging prevention and mitigation strategies. CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:e879bf12232bfc92c3e81a194509f09d URL:http://5thworldconferenceoninformations.sched.com/event/e879bf12232bfc92c3e81a194509f09d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Advanced Supply Chain Planning through the Human- Center to Foster Resilience and Sustainable Agrifood Supply Chain 5.0 DESCRIPTION:Authors - Nathalia Zacarias\, Denys Huacanca\, Edgar Ramos\, Ines Tarazona\, Donavan Fuqua Abstract - Supply Chain Planning in agri-food supply chains faces increasing challenges due to global disruptions and resource constraints. Supply Chain 5.0\, driven by human-centered approaches\, enhances resilience and sustainability by aligning dynamic demand strategies with technological advancements in uncertain environments. To address these complexities\, this study applies the Best- Worst Method (BWM) to prioritize key strategic criteria across four dimensions\, enabling consistent and structured decision-making. The results emphasize the relevance of advanced supply chain planning and human-centered innovation in fostering adaptive resilience and shaping a more sustainable supply chain. These findings support the transition toward resilient\, sustainable\, and human-driven agri-food supply chains aligned with the Supply Chain 5.0 framework. CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:f340f90a727367bba0cdf716768d75c9 URL:http://5thworldconferenceoninformations.sched.com/event/f340f90a727367bba0cdf716768d75c9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Advancing Audit Effectiveness through AI-Driven Digital Audits and Auditor Competency: The Moderating Role of Technological Infrastructure DESCRIPTION:Authors - Windy Permata Suyono\, Marsellisa Nindito\, Dwi Handarini\, Hera Khairunnisa\, Eka Septariana Puspa\, Surya Anugrah\, Rochma Sudiati\, Rio Firnanda\, Sabo Hermawan\, Septi Nurmalita Abstract - The transformation of auditing through Artificial Intelligence (AI) has redefined the way auditors perform their tasks in the digital era. This study aims to examine the role of digital audit and auditor competence in enhancing audit effectiveness\, with technological infrastructure as a moderating variable. Using a systematic literature review approach\, findings show that both digital audit and auditor competence have a significant positive impact on audit effectiveness. However\, technological infrastructure exhibits a dual moderating role. It negatively moderates the relationship between digital audit and audit effectiveness\, suggesting that inadequate infrastructure may hinder the benefits of digitalization. Conversely\, it positively moderates the relationship between auditor competence and audit effectiveness\, indicating that skilled auditors perform better when supported by robust infrastructure. These findings emphasize the need for a holistic strategy that combines advanced technology\, auditor upskilling\, and infrastructure readiness. This study contributes to the body of knowledge on audit digitalization and supports Sustainable Development Goal 9 (SDG 9) by promoting industry innovation and resilient infrastructure. CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:bee0e2c77c3ac3fbf41e370485d6dacd URL:http://5thworldconferenceoninformations.sched.com/event/bee0e2c77c3ac3fbf41e370485d6dacd END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:ARTIFICIAL INTELLIGENCE POWERED CREDIT SCORING MODELS: ADVANCING FINANCIAL INCLUSION AMIDST LEGAL AND ETHICAL CHALLENGES IN INDIA DESCRIPTION:Authors - Amita Verma\, Simran Sankhyayan\, Kritika Sheoran\, Rukhsaar Dhaliwal Abstract - Artificial Intelligence has evolved the operation and functioning of every sector and banking is no exception to it. The inclusion of AI has revolutionized banking operations to a significant extent\, following the introduction of Automated Teller Machines and Online Banking\, transforming traditional banking practices in India. This contribution intends to unravel the complex yet pressing intersections between technology and Banking. This paper examines how AI-powered credit scoring systems\, compared to conventional methods\, are utilized by banks and financial institutions to accurately assess credit scores and predict credit risks. Credit scoring has been completely transformed by artificial intelligence\, which offers sophisticated models and predictive analytics that promise increased efficiency and accuracy. This paper discusses the benefit of leveraging AI technology in credit scoring in terms of financial inclusion of underserved populations of the country paving the way for the establishment of an equitable society. Nevertheless\, there are drawbacks and restrictions of using Algorithm technology in credit scoring. This paper highlights the main legal issues and challenges\, with particular attention to issues with interpretability\, data privacy\, data breaches\, etc. The principles of fairness\, accountability\, and transparency are invoked\, and the possibility of unintentional biases is called into question by this lack of explainability in AI credit scoring tools. All such issues are then weighed in the context of the existing legal framework in India which eventually highlights the grey areas in the legal realm that the concerned authorities like the legislature\, RBI\, and financial institutions should ponder upon to ensure the balance between innovation and justice. CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:799104b37375420a58356fe08bce72c4 URL:http://5thworldconferenceoninformations.sched.com/event/799104b37375420a58356fe08bce72c4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Chicken Disease Image Classification Using modern CNNs and Vision Transformers DESCRIPTION:Authors - Howard Prioleau\, Saurav K. Aryal\, Jeremy Blackstone Abstract - This study contributes to ongoing efforts in agricultural technology by advancing the application of artificial intelligence in poultry disease classification\, crucial for sustaining agriculture amidst global demographic changes. Focusing on the Chicken Disease Image Classification task\, the research evaluates and finetunes state-of-the-art Convolutional Neural Networks (CNNs) like EfficientNet and ConvNeXT\, alongside Vision Transformers (ViTs) such as DeiT and Swin Transformer. These models\, pretrained on ImageNet\, are adapted to classify various poultry diseases from chicken fecal matter images\, representing conditions like Coccidiosis\, Healthy\, New Castle Disease\, and Salmonella. The study juxtaposes these advanced models with traditional machine learning approaches to assess their relative efficacy in handling class imbalances and complexities inherent in the dataset. Through a comprehensive evaluation using Precision-Recall curves and Confusion Matrices\, the research sheds light on the nuances of model performance in disease identification. The findings underscore the challenges posed by imbalanced datasets and emphasize the need for balanced data in training machine learning models for disease classification. This work showcases the capabilities of current state of the art AI in agricultural settings\, aiming to enhance early disease detection tools for poultry health management\, especially beneficial in resource-limited environments. CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:2ecb0bb51f533183ec75ff93d218bc04 URL:http://5thworldconferenceoninformations.sched.com/event/2ecb0bb51f533183ec75ff93d218bc04 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:E-Commerce in Sustainable Supply Chain Management: A Bibliometric Analysis Approach DESCRIPTION:Authors - Sarvani Kocherlakota\, Poojitha Panchakarla\, Padmanabhuni Venkata Sai Rushikesh Vardhan\, Vecha Guhana Naga Gayathri Abstract - E-commerce and supply chain management has emerged as a prominent research topic in recent decades\, with numerous findings published in leading international journals. To investigate its current research landscape and emerging trends\, we conduct a Bibliometric analysis by using R software 4.5.0\, and VOSviewer to identify the research trend\, emerging topics\, and collaborations among countries\, authors\, documents and the contributing academic journals during the study period. Sustainability (Switzerland) journal is having the highest publications and Journal of Operations Management is having the most cited document. Zhang X is the most contributing author and Sun Y is the most cited author. China is the most contributing country with around 45% of total publications and also has high international collaborations. By research gap analysis\, the future direction in the domain of supply chain management can be integration of live-streaming\, emerging technologies\, disruption risks\, and consumer behavioral preferences. CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:c29672e8cc654a4bd6927ae3815b73df URL:http://5thworldconferenceoninformations.sched.com/event/c29672e8cc654a4bd6927ae3815b73df END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:ECONOMIC BENEFITS OF NMT IMPLEMENTATION ON HEALTH AND ENVIRONMENT DESCRIPTION:Authors - Jaskaran Singh Saini\, Dinesh Kumar Saini\, Bhawna Chahar Abstract - Smart non-motorized transportation is crucial for the sustainable development of urban areas. An astronomical rise in the number of motorized vehicles\, particularly in metropolitan cities\, has compromised air quality and traffic conditions. NMT\, as an effective mode of transport\, is often neglected due to a lack of understanding of the long-term negative consequences of internal combustion engines (ICE) by policymakers and transport planners. The rising fuel costs and demand have inflated India's import bills and are expected to surge further until corrective measures are taken. NMT is a low-hanging fruit that can be implemented in urban hotspots at a relatively lower capital expenditure. It can help reduce the demand for fossil fuels and save the state enormous sums that would otherwise have been spent on capital-intensive carbon sequestration technologies. This study aims to highlight the significant economic benefits of NMT\, based on data collected from 599 respondents in New Delhi and Chandigarh. The analysis reveals that\, in addition to establishing the complex infrastructure of NMT\, transport planners and policymakers must foster attitudinal change among citizens\, i.e.\, the soft infrastructure. CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:fc03a8d66f1f118b9ef6840662793c73 URL:http://5thworldconferenceoninformations.sched.com/event/fc03a8d66f1f118b9ef6840662793c73 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Financial Inclusion Through Health Insurance Literacy of Middle-Aged Class DESCRIPTION:Authors - Adithi Varma PC\, Venugopal J S\, Mayadevi Thampatty PC Abstract - This paper explores the intricate relationship between financial literacy and health insurance as key determinants in fostering financial inclusion among middle-aged class. By examining the mutual connections and co-influence between these concepts\, the study aims to uncover how enhancing the health literacy to facilitate greater financial inclusion. Financial Literacy empowers individuals to make sound decisions regarding health insurance\, risk management\, healthcare cost\, and insurance coverage. Conversely\, Adequate health insurance which suits your health plan act as financial safety net\, reducing huge health-related expenditures and promote financial stability. This study is conducted using a descriptive and analytical design\, surveyed 101 respondents in Kozhikode District via convenient sampling through interview schedule. Data analysis involved mean scores\, Chi-square\, and t-tests. This research proposes that by integrating financial education with health literacy programs we can a create a synergistic effect that leading to an improved health outcome and enhanced financial well-being. This study will facilitate the development of comprehensive strategies that address the financial and health challenges faced by individuals and thereby promoting financial inclusion. CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:bf2873625641d07e85aebe7ad810e3b9 URL:http://5thworldconferenceoninformations.sched.com/event/bf2873625641d07e85aebe7ad810e3b9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Improving Lattice-Based Cryptography for Post Quantum Security in IoT and Block Chain Communications DESCRIPTION:Authors - Selvamani K\, Kanimozhi S\, Muthusundar SK\, Saranraj G\, Jagadeesh K Abstract - With the advancement of quantum computing\, conventional cryptographic approaches are losing strength against possible attacks\, showing the necessity of secure alternatives such as lattice-based cryptography\, especially for block chain and IoT implementations. Although lattice-based cryptography provides strong quantum resistance\, its practical application is hindered by high computational overhead\, intricate key management\, and power consumption in resource-constrained IoT devices. Additionally\, using it in block chain demands secure signature schemes and authentication protocols without compromising performance. Existing solutions compromise between security and efficiency at the expense of power consumption and higher latency. In an effort to solve these challenges\, we present a more robust latticebased cryptographic scheme that enhances aggregate signatures for low communication overhead without compromising security. Our solution also provides a light-weight key exchange mechanism specific to IoT devices\, enhancing scalability and energy consumption. Adaptive security elements are also included to counter potential post-quantum threats. Performance tests indicate that our framework substantially minimizes computational complexity while improving security compared to currently available alternatives. The findings attest to its capability to secure block chain-based IoT networks while providing efficient cryptographic operations. By overcoming the major shortcomings of lattice-based cryptography\, our research provides a scalable\, quantum-resistant solution for IoT and block chain application security in the post-quantum age. CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:eb9e76beb1911159e3168a649e853ff1 URL:http://5thworldconferenceoninformations.sched.com/event/eb9e76beb1911159e3168a649e853ff1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Understanding and Mitigating Emerging Social Engineering Cyber Attacks: A Vulnerability Analysis Approach DESCRIPTION:Authors - Selvamani K\, Kanimozhi S\, Muthusundar SK\, Saranraj S\, Raju S Abstract - In the contemporary digital environment\, organizations across all industries are increasingly dependent on online services to enhance convenience\, streamline operations\, and boost overall efficiency. While this digital transformation offers undeniable benefits\, it simultaneously exposes users and institutions to significant cyber security threats. Malicious actors constantly seek out vulnerabilities in these systems\, employing sophisticated methods to gain unauthorized access to sensitive data. One of the most alarming and effective tactics used by cybercriminals is social engineering. Rather than targeting technological flaws\, social engineering exploits human behavior\, manipulating individuals through deception\, coercion\, or the illusion of trust to bypass even the most advanced technical security controls. As traditional cyber security defenses such as multi-layered encryption\, firewalls\, and vulnerability patches grow more robust\, attackers are shifting their focus to the human element\, which is often the weakest link in the security chain. Unlike technical attacks that require in-depth knowledge of systems and code\, social engineering preys on emotions like fear\, urgency\, curiosity\, or helpfulness. These psychological manipulations make it easier for attackers to extract confidential data or financial information without triggering alarms. This paper explores the most common forms of Social Engineering (SE) attacks\, including phishing\, pretexting\, baiting\, and tailgating. It also delves into the psychological principles behind these tactics and outlines essential preventative strategies to mitigate the growing threat of social engineering in today’s cyber landscape. CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:c6202f198de63a89b6a901cbdc783366 URL:http://5thworldconferenceoninformations.sched.com/event/c6202f198de63a89b6a901cbdc783366 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Vulnerable Brain Region Identification in Early Stage of Alzheimer’s Disease (AD) using Magnetic Resonance Images (MRI): A Novel Unsupervised Feature Selection Algorithm DESCRIPTION:Authors - Iroshan Aberathne\, Don Kulasiri\, Sandhya Samarasinghe Abstract - Manual techniques are not yet capable of tracking such tiny abnormalities in the early stages of AD due to the inherent complex nature of the structural changes in the brain. Therefore\, we propose a novel model agnostic unsupervised feature selection algorithm called Prominent Feature Selection (PFS) to identify significant or vulnerable brain regions via volumetric measurements extracted from MRI images. Features selected by PFS are evaluated in two aspects. First\, we compare the results with several other feature selection methods to assess the interpretability of the selected features against age and gender. The experimental results show that the PFS results better describe the structural changes in brain regions against age and gender. Secondly\, binary class classification is performed to observe the discriminative power of the selected features against Cognitive Normal (CN) vs. Early Mild Cognitive Impairment (EMCI) subjects. Binary class classification performance measures demonstrate the significance of PFS. It has higher F1 score values despite a lower number of features compared to other feature selection methods. Since\, PFS can identify and rank the most significant brain regions at early the stage of AD\, diagnosis may become more specific. PFS can also be used as an effective feature selection technique not only to enhance the model performance but also to extend the model’s interpretability which would improve personalized evaluation in areas like eXplainable Artificial Intelligence (XAI). CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:74ba584fa103f6a2c7d2f767263455ab URL:http://5thworldconferenceoninformations.sched.com/event/74ba584fa103f6a2c7d2f767263455ab END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:A Decade of AI in Personal Financial Management: A Bibliometric Analysis of Trends\, Intellectual Structures\, and Research Opportunities DESCRIPTION:Authors - Ayatulloh Michael Musyaffi\, Rida Prihartini\, Muhammad Ikhwan\, Rochma Sudiati\, Diah Armeliza\, Maulana Amirul Adha\, Maudy Shinta Maychella Abstract - Over the past decade\, the integration of Artificial Intelligence (AI) into personal financial management has emerged as a strategic trend\, transforming how individuals approach budgeting\, investing\, retirement planning\, and debt management. Although academic interest in this area has grown\, systematic mapping of publication trends\, intellectual structures\, and research gaps remains limited. This study conducts a bibliometric analysis of 624 Scopus-indexed publications from 2015 to 2024 using the Biblioshiny platform. The findings indicate a marked increase in publications following the COVID-19 pandemic\, with most contributions originating from institutions in Asia\, while Western countries produced the most highly cited works. Author keyword analysis and Multiple Correspondence Analysis (MCA) mapping identified three major thematic dimensions: algorithmic decision support\, behavioral finance applications\, and experimental AI methodologies. Additionally\, several underexplored yet promising areas were identified\, including demographic personalization\, the integration of ethical considerations\, and behavioral-based AI design. This study provides a comprehensive knowledge map and offers actionable insights for advancing research in AI-driven personal finance. CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:8f76fef9bfb3e7297adc073cba2330bf URL:http://5thworldconferenceoninformations.sched.com/event/8f76fef9bfb3e7297adc073cba2330bf END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:A Structural Equation Modeling Approach to Assess Project-Based Learning and Student Achievement in Higher Education DESCRIPTION:Authors - S Anupama Kumar\, Vijayalakshmi M N\, Divya T L\, Narasimha Swamy S Abstract - Recent advancements in the Higher Education have led to the adoption of diverse learning approaches across the globe. The current educational frame-work incorporates multiple techniques\, such as collaborative learning\, active learning\, cognitive learning\, and more to improve the performance of the student. Experiential learning is one of the promising approaches\, enabling students to experiment with concepts and learn through practical application. This paper explores the effectiveness of Project-Based Learning (PBL)\, an experiential learning approach\, in a higher education course to improve student learning outcome. This research focuses on understanding the relationship between PBL\, Collaborative Learning (CL)\, Iterative Learning (IL)\, Authentic Learning (AL)\, Disciplinary Course Learning . The research contributes towards the effectiveness of PBL in improving the student learning outcome. Structural equation model is used to attain the findings. A positive relation is found between the PBL\, collaborative learning\, disciplinary course learning\, iterative learning\, and authentic learning. This relation in large has improved the learning outcome of the student to a greater extent. Hence PBL is found to be an effective technique to be adopted in higher education and enable the students to acquire new knowledge using various methods. This in turn will improve the learning outcome of the students. CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:16c217ca30b37530414d7b0e9ddbebf4 URL:http://5thworldconferenceoninformations.sched.com/event/16c217ca30b37530414d7b0e9ddbebf4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:An Intelligent Framework for Non-Parametric Test Prediction and Execution Using Machine Learning DESCRIPTION:Authors - Dhvani Shah\, Disha Chandaria\, Harshil Shah\, Janhavi Patel\, Abhijit Joshi Abstract - Non-parametric tests are important in statistical analysis where data fails to meet assumptions like normality or homogeneity of variance. Nevertheless\, choosing and implementing the right test is frequently statistical in nature\, which is a limitation for most users. Therefore\, we suggest an intelligent framework that automates the selection and running of non-parametric tests through machine learning. A well-curated dataset of statistical problems is fed into a Decision Tree Classifier\, which is labeled as the best model with 93.4 percent accuracy to identify the most appropriate non-parametric test\, such as the Runs Test\, Wilcoxon Signed-Rank Test\, and Mann-Whitney U Test. After prediction\, the identified test is run automatically\, and outputs are produced in a well-structured\, interpretable manner. This method increases accessibility\, enhances statistical analysis efficiency\, and opens the way to further application of non-parametric testing in data-driven inquiry. CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:5e8b2b803dd6045833b1b09f02edd34c URL:http://5thworldconferenceoninformations.sched.com/event/5e8b2b803dd6045833b1b09f02edd34c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Attaining Sustainability in Circular Economy: A Bibliometric Analysis DESCRIPTION:Authors - Sarvani Kocherlakota\, Poojitha Panchakarla\, Vellore Vandana\, Buchi Harika Abstract - Circular economy is gaining momentum in the field of production and consumption to achieve sustainable goals in this digital era. Many strategies have been evolved in functioning the digital technologies to enhance the circular economy. But out of these technologies\, we are not aware which technology could be used to emerge circular economy to a great extent. Entrepreneurship represents a key factor in capturing new circular business opportunities. To investigate its current research landscape and emerging trends\, we conducted a Bibliometric analysis by using R software 4.5.0\, and VOSviewer to identify the research trend\, emerging topics\, collaborations among countries\, authors\, documents and the contributing academic journals during the study period. Journal of Cleaner Production is having the highest publications and Resources\, Conservation and Recycling is having the most cited document. Kumar A is the most contributing author in publications and Kumar V is the most cited author. Netherlands is the most contributing affiliation for publications and United Kingdom high international references. CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:2be6d3df253f1dd93c68d140dab38629 URL:http://5thworldconferenceoninformations.sched.com/event/2be6d3df253f1dd93c68d140dab38629 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Enabling SME Participation in Cybersecurity Information Sharing: A Human-centric\, Socio-technical Model DESCRIPTION:Authors - Matipa Ricky Ngandu\, Ntima Mabanza\, Gardner Mwansa Abstract - Cybersecurity Information Sharing (CIS) among Small and Medium-sized Enterprises (SMEs) is increasingly recognized as essential for collective threat mitigation\, yet participation remains low due to complex human\, social\, and organizational barriers. Underpinned by Social Cognitive Theory (SCT) this study explores how human factors such as trust\, leadership engagement\, awareness levels\, and communication practices influence CIS participation within SME ecosystems. Drawing on academic literature and analysis of primary quantitative and qualitative data\, we present a socio-technical model that conceptualizes CIS as a form of digital crowdsourcing\, embedded within informal and semi-formal social networks. Our findings indicate that SME participation in CIS is significantly enhanced when trust-building practices\, cultural alignment\, and role-specific awareness are actively supported through peer in-fluence and community-based engagement mechanisms. The proposed model identifies the conditions under which SMEs are most likely to share security intelligence\, including personalization of tools\, clear governance structures\, and inter-organizational trust scaffolding. This work emphasizes the role of social structures and crowdsourcing dynamics in driving effective cybersecurity engagement\, offering practical implications for designing inclusive\, scalable\, and human-aware CIS platforms tailored for resource-constrained SMEs. This work contributes to broader efforts in boosting cyber resilience through socially grounded\, technology-supported approaches. CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:ac2b65719529d1b57f1ee1622137f328 URL:http://5thworldconferenceoninformations.sched.com/event/ac2b65719529d1b57f1ee1622137f328 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Energy Sector in India: Studying Environmental Sustainability through BRSR Reporting DESCRIPTION:Authors - Bhupinder Kaur\, Shivani Gupta\, Kritika Sheoran Abstract - The corporate world is increasingly becoming aware of the dynamic nature of its laws and policies\, and has actively started functioning towards it. The observance of ESG goals by corporations is a de-novo approach towards the achievement of SDGs\, and is an improvement over the already existing concept of CSR. Even credit rating agencies are considering ESG factors while assessing the creditworthiness of corporates\, because under the ESG regime\, corporations are responsible for their Environmental\, Social and Governance initiatives\, towards a better and sustainable tomorrow. This paper studies the environmental sustainability of various industries of the energy sector that have been filing their BRSR reports while following their environmental policy. Studying energy sector is important\, because ultimately\, one of the prominent parameters of every BRSR report is the amount of energy consumed in the industrial process. Herein\, a comparative study shall be made taking regard to amount of energy generated and the various other parameters reported in a BRSR report. The study reveals that BRSR reporting is an effective and reliable method to access the actual compliance of environmental policy regulations by corporations. Further\, the paper also enlists various shortcomings in the BRSR reporting system. CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:79a37382696e59c07c5a2f86e399cebd URL:http://5thworldconferenceoninformations.sched.com/event/79a37382696e59c07c5a2f86e399cebd END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Harmonization of Financial Reporting and Accounting Standards in the Merger of Indonesian State-Owned Enterprises DESCRIPTION:Authors - Eka Septariana Puspa\, Laode Arahman Nasir\, Dwi Handarini\, Gentiga Muhammad Zairin\, Surya Anugrah\, Windy Permata Suyono\, Septi Nurmalita\, Rochma Sudiati\, Irima Rahmadani\, Nazwa Febriyani Abstract - This study explores the harmonization of financial reporting and accounting standards in the merger of two Indonesian state-owned enterprises (SOEs)\, Perum X and Perum Y. Employing a qualitative case study approach\, the research investigates the systemic differences in accounting policies\, financial information systems\, and reporting structures that pose significant challenges in the post-merger integration process. Data were collected through in-depth interviews\, document analysis\, and observation of the integration process. The findings reveal disparities in Chart of Accounts (COA) structure\, PSAK implementation—particularly PSAK 16 and PSAK 71—and the use of financial systems\, with X operating an ERP-based system while Y remains reliant on Excel-based processes. Regulatory interventions\, such as asset restatement and capital participation adjustments\, are also discussed as critical factors influencing harmonization efforts. A conceptual framework is proposed to guide future SOE mergers in aligning accounting systems and policies. The harmonization process enhances financial transparency\, managerial decision-making\, and auditability\, but also highlights the need for national guidelines and institutional coordination. This study contributes to the literature on public sector accounting by providing practical insights and policy recommendations for improving the consistency and integrity of financial reporting in SOE mergers. It also opens avenues for further research on long-term outcomes and cross-sector comparisons of accounting harmonization in public enterprises. CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:6115810b5b24c0aa3088e273507b481a URL:http://5thworldconferenceoninformations.sched.com/event/6115810b5b24c0aa3088e273507b481a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Post-ERP Performance Shift in HRM: Evidence from FMCG Firms in Bangladesh DESCRIPTION:Authors - Mohima Rahman\, Mehzabul Hoque Nahid\, Khandakar Tahurul Islam\, Erfan Ovee Nomaan\, Kazi Tareq Ullah Abstract - This study investigates the critical factors influencing the post-ERP performance shift of Huamn Resource Management (HRM) in the Fast-Moving Consumer Goods (FMCG) organizations in Bangladesh\, utilizing the Technology–Organization–Environment (TOE) framework. Drawing on the empirical evidence\, the research evaluates the impact of five determinants\, Competitive Environment\, Perceived Compatibility\, Perceived Efficiency\, Top Management Support\, and Training\, on post-ERP performance shift in HRM. The findings re-veal that Competitive Environment\, Perceived Compatibility\, Perceived Efficiency\, and Top Management Support significantly enhance post-ERP performance\, whereas Training does not show a statistically significant effect. These results underscore the importance of aligning ERP systems with organizational processes\, supported by effective leadership\, system fit\, and external responsiveness. The study also emphasizes the need for fostering an innovation-driven culture\, strengthening vendor partnerships\, and ensuring system scalability and compliance in the post-ERP phase. By addressing these strategic and operational factors\, HR departments can improve efficiency\, agility\, and data integrity\, ultimately enhancing organizational competitiveness. The research contributes to the growing discourse on digital transformation in HRM and offers actionable insights for practitioners\, policymakers\, and enterprise system stake-holders in emerging market contexts. CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:00d735184419ba98ca46b0cf70c2870b URL:http://5thworldconferenceoninformations.sched.com/event/00d735184419ba98ca46b0cf70c2870b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:The Impact of Digital Tax Education and Financial App Use on Tax Literacy and Compliance Intention among E-Commerce MSMEs in Indonesia DESCRIPTION:Authors - Dwi Handarini\, Eka Septariana Puspa\, Nuramalia Hasanah\, Ratna Anggraini\, Surya Anugrah\, Windy Permata Suyono\, Septi Nurmalita\, Rochma Sudiati \, Sabo Hermawan\, Stefany Indiraguna Joka Abstract - The rapid growth of Indonesia’s digital economy has brought millions of Micro\, Small\, and Medium Enterprises (MSMEs) into online marketplaces such as Shopee\, Tokopedia\, and TikTok Shop. However\, despite their economic significance\, MSME tax compliance remains critically low due to limited tax literacy and weak financial administration. This study examines the impact of digital tax education and financial application usage on tax literacy and tax compliance intention among e-commerce MSMEs. Drawing on the Theory of Planned Behavior (TPB)\, a quantitative explanatory approach was employed using data from 100 MSME respondents in Indonesia. Structural Equation Modeling (PLS-SEM) was applied to test direct and mediating effects. The results show that both digital tax education and financial app usage significantly improve tax literacy\, which in turn strongly predicts tax compliance intention. Tax literacy also mediates the relationship between digital interventions and compliance behavior. These findings offer theoretical contributions by integrating digital behavioral factors into tax compliance models\, and practical implications for policymakers to develop integrated strategies that combine tax education with financial technology empowerment. Strengthening digital literacy and promoting fintech adoption can increase voluntary compliance\, expand the tax base CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:a97db6993354c79bcbbb9308dc13d422 URL:http://5thworldconferenceoninformations.sched.com/event/a97db6993354c79bcbbb9308dc13d422 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Voice-Enabled Chess: A Speech-Driven Approach to Interactive Gameplay DESCRIPTION:Authors - Harsh Sobhashana\, Jiya Bera\, Margin Ankola\, Nishat Shaikh Abstract - Voice-Enabled Chess is an innovative Python-based application that enhances traditional chess gameplay with modern voice recognition technology. Designed for accessibility and engagement\, the system allows players to exe-cute moves using voice commands\, providing an intuitive and hands-free gaming experience. The application integrates speech-to-text conversion via the Speech Recognition library\, while AI- driven decision-making ensures a challenging opponent. A graphical user interface (GUI) enhances usability\, and Docker deployment simplifies distribution across platforms. This project targets a diverse audience\, including chess enthusiasts\, individuals with disabilities\, and technology enthusiasts interested in voice-controlled applications. By leveraging Python’s extensive ecosystem\, including NumPy\, Pandas\, and the Chess library\, the system efficiently manages game logic and interactions. Through the fusion of traditional chess mechanics with modern artificial intelligence and speech recognition\, Voice-Enabled Chess pro- motes inclusivity and innovation in digital game development. CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:c82e2b6adb8458f3204ef0a7ad8abf7e URL:http://5thworldconferenceoninformations.sched.com/event/c82e2b6adb8458f3204ef0a7ad8abf7e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:An Expository Deep Learning Approach for Network Intrusion Detection in Software Defined Networking DESCRIPTION:Authors - E. C. Nwokorie\, D. O. Njoku\, M. E. Nwanga\, S. A. Okolie\, C. D. Anyiam\, J. E. Jibiri\, C. G. Onukwugha\, I. H. Ajunwa\, C. O. Amadi\, F. O. Nwokoma\, A. I. Otuonye\, U. C. Onyemauche Abstract - This research investigates the application of TabNet\, a deep learning model optimized for tabular data\, for binary classification of Software Defined Networking (SDN) traffic. Using a combination of normal and Open vSwitch (OVS) traffic datasets\, the model was trained to differentiate between benign and potentially anomalous traffic patterns. The preprocessing pipeline included feature selection\, normalization\, and encoding\, followed by model training using PyTorch TabNet. The classifier achieved a high validation accuracy of 99.51%\, with strong precision and recall\, highlighting its capability for real-time anomaly detection in SDN environments. Visualizations such as ROC curves\, precision-recall plots\, confusion matrices\, and PCA projections further validated the model’s effectiveness and interpretability. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:958a8ea189a484391241f300d8b66c01 URL:http://5thworldconferenceoninformations.sched.com/event/958a8ea189a484391241f300d8b66c01 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Blockchain-Enabled Trust Platforms for Home-to-Home Shared Accommodation Services: A Quantitative Study in Tourism Management DESCRIPTION:Authors - Tiurida Lily Anita\, Arif Zulkarnain\, Abdul Rauf Ridzuan Abstract - The integration of blockchain technology into digital tourism platforms has sparked interest in how such innovations influence user trust and behavioral intentions. This study investigates the impact of digital value\, smart contracts\, and security-transparency on users’ intention to use blockchain-based services\, with perceived trust as a mediating variable. A quantitative survey involving 200 Traveloka users was conducted using structured questionnaires. The analysis employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to validate the measurement and structural models. Results reveal that digital value and perceived trust significantly influence users’ intention to use Traveloka's blockchain-enabled services. Moreover\, digital value and smart contracts positively affect perceived trust. However\, the direct impact of security-transparency on perceived trust was found to be statistically insignificant. The mediation effect of perceived trust is confirmed only in the relationship between digital value and intention to use\, while its mediating roles between smart contract and intention\, and between security-transparency and intention\, are not supported. These findings suggest that enhancing digital value and reinforcing trustworthy smart contract features are key to fostering trust and increasing user adoption. This study offers practical insights for digital tourism platforms aiming to deploy blockchain technology and contributes to the theoretical understanding of trust-based technology acceptance in the tourism domain. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:1df88d1aa3c95a67cb1b43f3f52da194 URL:http://5thworldconferenceoninformations.sched.com/event/1df88d1aa3c95a67cb1b43f3f52da194 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Business Intelligence Impacts in Small and Medium Enterprises Performance: A Literature Review DESCRIPTION:Authors - Zainab Shalehah\, Santy Abstract - Small and Medium Enterprises (SMEs) face increasing pressure to remain competitive in rapidly evolving markets. Business Intelligence (BI) has emerged as a strategic tool that supports data-driven decision-making and improves organizational performance. This study aims to explore the impacts\, benefits\, and challenges of BI implementation in SMEs through a systematic literature review (SLR) of relevant academic sources. Literature was collected from databases such as Scopus and Google Scholar and analyzed using thematic categorization based on BI usage and its performance outcomes in SMEs. The findings highlight that BI positively contributes to decision-making quality\, operational efficiency\, and financial performance. However\, SMEs often face challenges such as high implementation costs\, lack of skilled personnel\, and integration difficulties. The success of BI adoption is highly influenced by contextual factors\, including data quality\, financial capacity\, and strategic planning. This review concludes that while BI offers significant advantages for SMEs\, a careful\, well-planned approach is necessary to overcome adoption barriers. Further research is recommended to explore industry-specific BI solutions that address the unique needs of SMEs. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:e33bbade5aa15d64b68759ec57f9b2fc URL:http://5thworldconferenceoninformations.sched.com/event/e33bbade5aa15d64b68759ec57f9b2fc END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Comparative evaluation of open-source Automatic speech recognition tools for mathematical speech recognition DESCRIPTION:Authors - Sadhana Mishra\, Poonam Dang Abstract - Automatic speech recognition (ASR) is increasingly being applied in various fields such as healthcare\, Education and accessibility. However\, ASR of mathematical expressions presents a unique challenge due to the symbolic\, structured and hierarchical nature of math language. Accurate transcription of such expressions is essential for digital learning\, documentation and computational processing. This paper presents a comparative study of four open-source ASR tools— Whisper\, DeepSpeech\, Vosk and PocketSphinx — focusing on their ability to recognize spoken mathematical expressions accurately. The study uses a dataset of several mathematical categories\, such as algebra\, trigonometry\, calculus\, and vectors\, recorded by six speakers\, to assess each tool's performance based on Word error rate (WER) and processing time. According to the results\, Vosk processes information the quickest\, whereas Whisper performs better in terms of accuracy. The findings provide insights into tool selection for educational or assistive technology applications involving math speech transcriptions. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:c4557f6294d37bfd721fc1bb0c7668e3 URL:http://5thworldconferenceoninformations.sched.com/event/c4557f6294d37bfd721fc1bb0c7668e3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Decentralized Public Donation Pools Covering Fees for Free Blockchain Protocols Usage DESCRIPTION:Authors - Serhii Kozlov\, Nazar Matsko\, Yaroslava Chopa\, Volodymyr Dubinin\, Dmytro Nishchemenko Abstract - This article proposes a solution to the problem of free decentralized protocol usage for a group of users who want to participate in the protocol without paying transaction fees and/or do not have a wallet with a key pair (Externally Owned Account). The proposed solution is a public donation pool that enables users to interact with any decentralized protocol during a specific event without owning a wallet and/or incurring blockchain gas fees. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:747a491266ac51e5f2026018c4d3c1de URL:http://5thworldconferenceoninformations.sched.com/event/747a491266ac51e5f2026018c4d3c1de END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Determinants of User Satisfaction in Digital Payment System Transactions: A Philippine Perspective DESCRIPTION:Authors - Andrea Dannielle Mayuga\, KC A. Berdin\, Mary Faith F. Lagmay\, Love Joyce A. Mortel\, Lovely M. Penafiel\, Ashley D. Sacayanan\, Manuel J. Logatoc\, Steven C. Jocson Abstract - This study evaluates the level of satisfaction with digital payment systems among residents in the Philippines. In an era where rapid technological advancement reshapes business transactions\, digital payment platforms have emerged as critical drivers of efficiency and convenience. Employing data from survey questionnaires and pertinent digital‐literacy studies\, the research applies Davis’s Technological Acceptance Model (TAM)\, with perceived usefulness (PU) and perceived ease of use (PEOU) as central predictors of users’ behavioral intentions toward mobile payments. The analysis explores three dimensions: users’ overall satisfaction\, the most frequently used digital payment platforms\, and variations across socio‐demo-graphic profiles. Findings indicate that respondents maintain a uniformly positive attitude toward digital payment systems\, deeming them useful for everyday trans-actions and expressing strong willingness to recommend these platforms over traditional methods. Ease of use emerged as a key factor driving continued adoption intentions. Among socio‐demographic variables\, gender and monthly in-come show significant correlations with satisfaction levels\; in contrast\, age\, civil status\, and highest educational attainment exhibit no notable influence. These results suggest that while digital payment systems enjoy broad acceptance across diverse user groups\, targeted strategies that address gender\, and income‐based preferences may further enhance user satisfaction. Policymakers and service providers can leverage these insights to refine platform design\, optimize user education initiatives\, and foster more inclusive adoption of digital payment technologies. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:a360f64addb046a66226dcc8b3988a6d URL:http://5thworldconferenceoninformations.sched.com/event/a360f64addb046a66226dcc8b3988a6d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Identifying the Role of ESG in the Global Capital Market DESCRIPTION:Authors - Sarvani Kocherlakota\, Poojitha Panchakarla\, Ajay Amjuri\, Sannakalla Sai Sree Charan Abstract - Economic\, Social and Governance is playing a predominant role in the capital markets to increase the awareness Global investments and to acquire knowledge on the investment avenues available across the world. To investigate its current research landscape and emerging trends\, we conduct a bibliometric analysis by using R software 4.5.0\, and VOSviewer to identify the research trend\, emerging topics\, and collaborations among countries\, authors\, documents and the contributing academic journals during the study period. Finance research letters is having the highest publications and Review of Accounting Studies is having the most cited document. Li Y is the most contributing author and Christensen HB\, Hail L and Leuz C are the most cited author. China is the most cited country. Further research may happen in this area from the perspective of various countries like BRICS\, various quantative techniques and scope of the study may be limited to individual country and so on. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:2c9ffe0d6798bcfed893385d1fc0e67b URL:http://5thworldconferenceoninformations.sched.com/event/2c9ffe0d6798bcfed893385d1fc0e67b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Parametric Evaluation of State of The Art For Pesticide Recommendation and Diseases Detection System in Cotton Plant DESCRIPTION:Authors - Rajkumar Patil\, Vivek S. Deshpande\, Nilesh P. Sable Abstract - Pests pose a significant threat to cotton yields\, leading to economic losses for farmers. This paper conducted a comprehensive literature review\, examining the various types of pests affecting cotton crops both globally and specifically in India. We analyzed the actual yield losses ascribed to these pests as well. Furthermore\, we reviewed a variety of literature on pesticide recommendations and cotton disease detection. In this paper we have chosen four Deep Learning (DL) models—VGG19\, ResNet50\, ResNet152V2\, and Incep-tionV3 selection of this model was based on literature review. These models were trained and tested on a dataset of 2\,293 images comprising affected and non-affected cotton plants and leaves. The output of our evaluation demonstrates how useful these models are in detecting diseases in cotton plants. Ultimately\, the AI-based automated recommendation system allows farmers to use this information to make informed decisions about using pesticides resulting in better crop health and higher yield of cotton. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:499c8064f63731e8c0474bb01a2a7862 URL:http://5thworldconferenceoninformations.sched.com/event/499c8064f63731e8c0474bb01a2a7862 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Positive Work-Life Balance in Women: A Strategic Driver of Mental Health and Empowerment in Academic Organizations DESCRIPTION:Authors - Ronil Manohar\, Melita Simoes\, Arogyaswamy Karadi Abstract - Today’s competitive jobs demand a sturdy balance between personal and professional life. Women are an integral part of the current workforce including academics wherein achieving a sustainable work-life integration is a critical challenge in the ever evolving dynamic workplaces despite institutional reforms\, growing attention to gender equity and women empowerment. This study highlights the role of work-life balance\, mental well-being\, and organizational support structures among 103 women professionals that include teaching and non teaching fraternity in educational institutions across Hubli-Dharwad. According to reports\, a substantial proportion of respondents\, mostly Millennials and Generation Z\, struggle to maintain balance\, resulting in medical illnesses\, stress\, burnout\, and disturbances in family life. These issues frequently result in lower productivity\, job satisfaction and can hamper career progression and leadership aspirations\, emphasizing the critical need for effective measures to help women achieve a sustainable work-life balance. This study employs a quantitative approach that made use of a structured data collection through a well drafted questionnaire which aims to explore the perception of women on work-life balance\, mental health\, and personal empowerment along with understanding the role of equitable policies\, anti-harassment frameworks\, as well as the implementation of flexible and inclusive work environments that promote a gender-balanced leadership wherein the needs and voice of women employees are addressed. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:7b13d44406e3f67367fd43b5f898508e URL:http://5thworldconferenceoninformations.sched.com/event/7b13d44406e3f67367fd43b5f898508e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Socioeconomic Indicator-Based Crime Prediction in Pakistan Using Machine Learning Techniques DESCRIPTION:Authors - Usman Ali\, Tariq Hussain\, Muhammad Mujeeb Akbar\, Shahzad Ali\, Sajid Abstract - In Pakistan\, crime is always a significant economic and social issue affecting governance and public safety. Religious issues\, poverty\, and political instability have a very high contribution to increasing crime in the country. Despite highly effective efforts of authorities and prevention techniques\, crimes are often inconsistent and lack effectiveness in determining crimes across the country. This study aims to analyze national crimes in Pakistan using machine learning and structured datasets to support more effective decision-making and understanding of crime rates across the country. Through the proposed framework\, linear regression\, the Decision Tree\, and the Random Forest are applied to historical data obtained from the Kaggle repository. With different evaluation matrices and cost functions\, the proposed model is interpreted and evaluated. The Evaluation metric includes R²\, and the cost functions include MSE\, MAE\, and RMSE. Linear Regression works effectively in comparison to others\, providing the highest R²\, i.e.\, 99.9%. By using this framework\, crimes from 2030 to 2050 are predicted with a difference of 5 years. These algorithms help to identify different types of crimes across the country based on different factors. Unlike traditional methods and black-box models\, this research underscores the comprehensibility\, making insights understandable for both law and policy makers. The study explains how interpretable frameworks can help authorities to find high-risk area predictions. In the future\, the aim is to use deep learning techniques with explainable AI (XAI) for enhancement in this study\, which can support the development of more public safety systems across the country. CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:12f8609929ddcb290402fa7a86f916a7 URL:http://5thworldconferenceoninformations.sched.com/event/12f8609929ddcb290402fa7a86f916a7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:A Case Study on an Inexperienced Team Using Waterfall for Game Development DESCRIPTION:Authors - Sajidur Rahman\, Md. Ataur Rahman\, Saymadeen Tabassum\, Farhad Alam\, Mahady Hasan\, Towsif Zahin Khan Abstract - Our work explores the application of the Waterfall model in game development through a case study involving an inexperienced team developing a Space Invaders clone. While Agile methodologies are widely favored in modern game development for their flexibility\, the structured\, phase-based nature of Waterfall presents certain advantages for teams with limited experience in iterative processes. We investigate how clearly defined stages- requirement analysis\, design\, implementation\, testing\, and maintenance-provide direction\, minimize scope creep\, and can support systematic progress and project success despite the team’s inexperience. Key findings suggest that Waterfall was effective in maintaining project control\, with clear documentation and milestone tracking helping reduce ambiguity. However\, the model also posed challenges in managing late-stage design changes and balancing creativity within a rigid structure. The paper compares these findings with insights from the literature on Agile and hybrid methodologies\, especially in the context of novice teams. The case study concludes that although Waterfall’s predictability can benefit inexperienced developers\, its success relies heavily on disciplined planning\, well-defined roles\, and the ability to adapt within a structured framework. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:2096acfb2086f8b440d64a6581ea502c URL:http://5thworldconferenceoninformations.sched.com/event/2096acfb2086f8b440d64a6581ea502c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Developing LINE Application to prevent COVID-19 in Pregnant Women DESCRIPTION:Authors - Krit Chaiwong\, Wirote Jongchanachavawat\, Ittipat Roopkom\, Boonchart Kativat Abstract - This research and development aimed to create a LINE application to prevent COVID-19 among pregnant women and to evaluate its effectiveness and user satisfaction. The study was conducted in four stages: (1) assessing the situation\, needs\, related factors\, and feasibility of the LINE application\; (2) developing the LINE application for COVID-19 prevention\; (3) implementing a quasi-experimental study\; and (4) refining and evaluating the application’s effectiveness. The research instruments included: (1) in-depth interview questions with content validity index (CVI) values ranging from 0.88 to 0.90\; (2) field notes\; (3) a questionnaire on COVID-19 prevention among pregnant women\, comprising a knowledge assessment (KR-20 = 0.72) and a behavior assessment (Cronbach’s alpha = 0.93)\; and (4) a satisfaction survey for the LINE application (Cronbach’s alpha = 0.89). Data were analyzed using content analysis\, frequency\, percentage\, mean\, standard deviation\, and paired t-tests. Results indicated that after using the LINE application\, participants demonstrated significantly higher knowledge and improved preventive behaviors compared to pre-intervention levels (p < 0.001). Participants also reported a high level of satisfaction with the application. These findings suggest that the LINE application is an effective and well-received tool for promoting COVID-19 prevention among pregnant women. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:d47b98a0f711c1f4c50999810d558ca3 URL:http://5thworldconferenceoninformations.sched.com/event/d47b98a0f711c1f4c50999810d558ca3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Disease Prediction in Sericulture and Automation DESCRIPTION:Authors - Seema V Kedar\, Shabana Pirjade\, Avinash Chhabu Shelar\, Dheeraj Sharma\, Harshita Daftari\, Rushikesh Manoj Gholap Abstract - Around 9.76 million peoples in the rural and semi-urban area are depend on the sericulture for their livelihood. Monitoring the health and environment of silk worm is a crucial factor of sericulture industry. Which is done manually by farmers or care taker by monitoring them time to time and keeping track of their environmental conditions which are favourable temperature and humidity. By automating this process lot of time\, work and labour cost of farmers can be saved and utilized for other work. For doing so Arduino will be used which will be connected to temperature sensor\, and humidity sensor which will be used for taking input signal from the system and define the current environment conditions of the system. The current environmental conditions will be compared by threshold values which will be which will be predefined. If the value of temperature is greater than threshold the fan which is another component will be switched on to cool down the temperature. If the temperature is lower than the threshold the bulb will be switched on to rise the temperature. All the status report of the system will be given send to famers phone by using the GSM module. Throughout the process of monitoring the health of silk worm always had a front foot. Cause one diseased worm can make another worm ill. Hence\, to avoid this a disease detection system which will detect diseases silk worm will help farmers. For doing so CNN and Image processing algorithms are used for disease detection on time This model will classify the diseased silkworm in different diseases based on which it is suffering from. CNN is trained with its auto generated features. An average accuracy of 85%\, 75% and 59% for classification of healthy and diseased silkworms. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:193ddb07a3cdd62aac3c8ecef7e99fb3 URL:http://5thworldconferenceoninformations.sched.com/event/193ddb07a3cdd62aac3c8ecef7e99fb3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Empowering Road Safety Analysis: State-wise Accident Data Visualization with Power BI DESCRIPTION:Authors - Parth Modhvadiya\, Harshil Kothiya\, Nishat Shaikh\, Jalpesh Vasa Abstract - The main goal of this paper is to study and examine accident data in India on a national\, state\, and major city level between 2017 and 2021. It focuses on identifying patterns\, key factors\, and differences across regions. Road accidents have been a serious issue in India for a long time. Research indicates that injuries resulting from road accidents remain a significant challenge for public health\, affecting both the economy and society. These accidents are particularly common in states like Tamil Nadu\, Maharashtra\, and Uttar Pradesh. The paper uses data from various sources\, including government reports\, to better under-stand the scale of the problem\, regional variations\, key risk factors\, and possible ways to prevent accidents. One of the main reasons for road accidents in India is careless driving. Furthermore\, the rapid increase in vehicle ownership has played a key role in the rising number of accidents. Data from the Ministry of Road Transport and Highways indicates that registered motor vehicles in India grew from 24.8 crore in 2017 to 28.9 crore in 2020\, marking an approximate 16.5% rise. This surge in vehicles has caused more traffic congestion\, making it harder for drivers to travel safely. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:0c4160133cc31327878ffedbc22b4e07 URL:http://5thworldconferenceoninformations.sched.com/event/0c4160133cc31327878ffedbc22b4e07 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Exploring Large Language Models to Assist Finite Element Analysis DESCRIPTION:Authors - Hector Rafael Morano Okuno Abstract - Nowadays\, Large Language Models (LLMs) are utilized in various fields of knowledge to assist users in performing tasks after being prompted with a question. However\, further exploration is needed to determine their scope\, as they are constantly being trained to improve and enhance their capabilities. This article investigates an LLM to decide whether or not it can assist users in interpreting results from finite element analyses and whether it can suggest modifications to the analyzed parts to improve the results of said analyses. This work was conducted during the Cyber-Physical Systems course\, held in the August-December 2024 semester\, with students of mechatronics\, robotics\, and computational systems engineering. Among the results\, it was found that LLMs are capable of recognizing images with beam diagrams featuring different types of support and loads\, as well as correctly interpreting finite element analysis results generated by software tool applications\, with the potential to provide recommendations for improving these results. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:ccc16d6816cbdb59d24cb97d307c7be4 URL:http://5thworldconferenceoninformations.sched.com/event/ccc16d6816cbdb59d24cb97d307c7be4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Forecasting inflation and stock prices in India’s energy sector: a comparative analysis of classical and deep learning models DESCRIPTION:Authors - Hetansh Shah\, Hitarth Bhatt\, Jay Topiwala\, Hitanshu Shah\, Pradnya Saval\, Shruti Mathur Abstract - This paper compares classical and deep models for forecasting stock prices of India’s top energy stocks (ONGC\, NTPC\, RELI) under inflation stress measured by the Energy Price Index (EPI). Although classical models like Prophet and Holt-Winters accurately forecast the inflation series\, an LSTM network with an Attention mechanism forecasts much better for stock price forecasting\, especially for volatile stocks. The paper further demonstrates that pure-energy stocks (ONGC\, NTPC) are more inflation-sensitive than diversified RELI. The findings have pragmatic implications for investors and policymakers on risk management in the energy market. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:7a4700c46bb1d33d676c3dab767ceff0 URL:http://5thworldconferenceoninformations.sched.com/event/7a4700c46bb1d33d676c3dab767ceff0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:From Perception to Adoption: A Model of Trust and Intention to Use for Digital Payment Solutions DESCRIPTION:Authors - Stanny Dewanty Rehatta\, Meta Bara Berutu\, Inkreswari Retno Hardini\, Gita Safitri Abstract - The rapid growth of Buy Now\, Pay Later (BNPL) services in Indonesia\, especially Shopee PayLater\, has created new patterns in consumer behavior and technology adoption in digital finance. While these services offer practical benefits and financial flexibility\, they also raise concerns related to data privacy\, potential misuse of personal information\, and system security. This study investigates the factors influencing users’ behavioral intention to use Shopee PayLater by extending the Technology Acceptance Model (TAM). The proposed model includes six key variables: Perceived Ease of Use\, Perceived Usefulness\, Perceived Risk\, Perceived Security\, User Trust\, and Intention to Use. A quantitative method was applied by distributing a structured online questionnaire to Shopee users in Indonesia. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that Perceived Ease of Use positively influences both User Trust and Intention to Use\, although its effect on intention is not statistically significant. Perceived Risk negatively affects both Trust and Intention\, with a significant impact on Trust. Perceived Security unexpectedly has a negative but marginally significant effect on Intention to Use. User Trust is found to be a strong and significant predictor of Intention to Use\, indicating its central role in mediating other variables in the model. These findings suggest that\, beyond ease and usefulness\, users' trust and risk perceptions significantly affect adoption. Strengthening security assurance and reducing perceived risk are essential strategies to improve trust and drive continued use of BNPL services such as Shopee PayLater in the Indonesian digital finance environment. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:ae8b5ec8b5d7ab1a5270b3e46941a140 URL:http://5thworldconferenceoninformations.sched.com/event/ae8b5ec8b5d7ab1a5270b3e46941a140 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Machine Learning-Based Clustering for Tuberculosis Patient Segmentation by Risk Factors and Symptom Profiles: A Case Study of Ngao District\, Lampang DESCRIPTION:Authors - Budsaba Inkiew\, Wongpanya S. Nuankaew\, Thapanapong Sararat\, Pratya Nuankaew Abstract - Tuberculosis (TB) remains a global health threat\, especially in low- and middle-income countries like Thailand\, where rural areas have limited healthcare resources. This study uses a machine learning–based clustering framework to stratify TB patients and screening data in Ngao District\, Lampang Province. It combines data sources—including a registry of 899 TB cases and 15\,318 chest X-rays—and addresses challenges like data heterogeneity\, missing values\, and inconsistent formats through cleaning\, imputation\, and feature engineering. Using the k-means algorithm\, evaluation metrics such as Silhouette Score\, Davies–Bouldin Index\, and Calinski–Harabasz Index confirmed three optimal clusters. Each cluster shows distinct demographic\, clinical\, and epidemiological features\, highlighting TB risk diversity. The findings demonstrate machine learning's potential to support targeted public health interventions\, optimize resources\, and improve TB prevention and control. This scalable framework offers insights for other regions facing similar infectious disease challenges\, integrating AI into public health systems. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:2d9d6ccad283c99055537a18d29326c7 URL:http://5thworldconferenceoninformations.sched.com/event/2d9d6ccad283c99055537a18d29326c7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Mapping Resistance to AI in Education: A Structural Analysis of Gen Z Adoption Barriers DESCRIPTION:Authors - Aishwini VR\, Aravindan B\, Santanu Mandal Abstract - The integration of Artificial Intelligence (AI) in education offers unprecedented opportunities for personalization\, efficiency\, and innovation\, yet resistance to adoption persists among Generation Z learners. This study investigates the structural interplay of ten key barriers to AI adoption in higher education\, integrating the Technology Acceptance Model\, Resistance to Innovation Theory\, and Cognitive Load Theory. Using Interpretive Structural modelling (ISM) and MICMAC analysis on survey data from 118 Gen Z respondents\, the research identifies lack of trust in AI\, data privacy concerns\, and algorithmic bias as high-driving factors\, influencing dependent barriers such as low perceived usefulness and poor user experience. Digital fatigue and cognitive overload emerge as central linkage variables\, mediating relationships between upstream drivers and downstream disengagement. Findings highlight the pivotal role of faculty support and pedagogical integration in shaping adoption attitudes. The study reframes resistance not as reluctance\, but as a signal of systemic misalignment between learner expectations\, institutional practices\, and AI design. Practical implications call for transparent\, inclusive\, and cognitively considerate AI tools\, robust governance frameworks\, and AI literacy initiatives to foster equitable and sustainable adoption. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:9e9c05e445d376b2d1ce38151bbfac14 URL:http://5thworldconferenceoninformations.sched.com/event/9e9c05e445d376b2d1ce38151bbfac14 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Unveiling Barriers to Sustainable Fashion Consumption Among Gen Z DESCRIPTION:Authors - Prabhuram S P\, B Sathish Kumar\, Santanu Mandal Abstract - The global fashion industry’s environmental footprint has heightened the urgency for sustainable fashion adoption\, yet Generation Z (Gen Z)—despite high sustainability awareness—shows limited engagement. This study investigates the systemic barriers impeding sustainable fashion consumption among urban\, digitally active Indian Gen Z consumers. Drawing on the Theory of Planned Behaviour and Resistance to Innovation Theory\, the research identifies ten interlinked barriers\, including lack of awareness\, limited availability\, price sensitivity\, trend obsession\, peer influence\, greenwashing confusion\, low perceived impact\, convenience bias\, brand loyalty\, and inconsistent messaging. A mixed qualitative–quantitative approach employing Interpretive Structural Modelling (ISM) and MICMAC analysis was applied to 137 valid responses collected in June–July 2025. Findings reveal that lack of awareness and limited availability are foundational drivers shaping intermediate constraints—such as price sensitivity and low perceived impact—which ultimately influence entrenched behaviours like brand loyalty and trend fixation. The ISM hierarchy underscores the multi-level nature of resistance\, while MICMAC classification highlights critical driving factors for targeted interventions. The study contributes to sustainable consumption theory by mapping structural interdependencies and offers actionable insights for policymakers\, educators\, and brands seeking to align Gen Z fashion choices with Sustainable Development Goals 12 and 13. CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:7acf9e89e439dde549672776db8261a0 URL:http://5thworldconferenceoninformations.sched.com/event/7acf9e89e439dde549672776db8261a0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Adaptability of 5G\, IoT\, and AI in Philippine Digital Infrastructure: Comparative Insights from ASEAN and Global Leaders DESCRIPTION:Authors - Mary Anne Q. Zheng\, Gerry Paul C. Genove Abstract - This paper presents a global benchmarking analysis to evaluate the Philippines’ infrastructure adaptability to 5G\, IoT\, and AI. Based on a systematic literature review of 35 peer-reviewed studies\, industry analyses\, and government reports from 2018 to 2025\, it evaluates the current state of deployment\, identifies key barriers\, and proposes actionable strategies for alignment with international best practices. Results indicate that 5G coverage is expanding in metropolitan areas\, IoT applications are emerging in sectors such as utilities and agriculture\, and AI integration is concentrated in enterprise and pilot projects. However\, socioeconomic inequality\, an archipelagic geography\, bureaucratic inefficiencies\, and fragmented governance emerge as primary constraints on broader adaptability and inclusivity. Comparative analysis against global leaders and selected ASEAN peers\, including Japan\, South Korea\, the United States\, Germany\, Malaysia\, Vietnam\, Thailand\, and Singapore\, highlights the importance of regulatory coherence\, coordinated infrastructure investment\, and integration with socioeconomic strategies. Policy lessons from peer nations demonstrate how centralized spectrum management\, regulatory sandboxes\, rural inclusion programs\, and digital upskilling initiatives can accelerate adaptation. The findings highlight the need for coherent policies\, shared infrastructure models\, and capacity-building frameworks to align the Philippines with international best practices. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:05043ac43a031d274e1ddf43673faf39 URL:http://5thworldconferenceoninformations.sched.com/event/05043ac43a031d274e1ddf43673faf39 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Beyond Engineering to Order: Embracing Leagile in Smart Manufacturing Planning for Boost Sustainability DESCRIPTION:Authors - Monica Pilco\, Lisset Ugaz\, Edgar Ramos\, Donovan Fuqua Abstract - The volatility and complexity of the marketplace require planning approaches that balance efficiency and adaptability in engineer-to-order (ETO) manufacturing environments. This study brings together lean\, agile (Leagile) principles and smart manufacturing planning to improve responsiveness without compromising operational performance. Using the Fuzzy Analytic Hierarchy Process (F-AHP) methodology\, this study combines a comprehensive literature review with the evaluation of strategies and drivers in a manufacturing case study. The results highlight the importance of Digital Integration\, Digital Value Stream\, and Integrated Planning to achieve leagile and sustainable operations. Conclusively\, this study offers practical suggestions for leveraging digital drivers to strengthen resilience and long-term sustainable smart manufacturing. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:5b704bae83c200c2298f0469744ae4a2 URL:http://5thworldconferenceoninformations.sched.com/event/5b704bae83c200c2298f0469744ae4a2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Conceptualizing Islamic Social Enterprise and Islamic Social Entrepreneurship: Insights from a Systematic Literature Review DESCRIPTION:Authors - Wahyu Wastuti Abstract - This study conducts a Systematic Literature Review (SLR) of 30 Scopus-indexed articles published between 2016 and 2025 to examine the conceptualization and development of Islamic Social Enterprise (ISE) and Islamic Social Entrepreneurship (ISEn). The review reveals that ISE is predominantly framed as an organizational form integrating Islamic principles into governance\, accountability\, and social welfare structures\, while ISEn emphasizes individual-driven innovation and entrepreneurial behavior aligned with sharī‘ah values. Despite their differences\, both models converge in their pursuit of financial sustainability\, social justice\, and community empowerment. Thematic analysis identifies four recurring domains in the literature: governance\, innovation\, sustainability\, and maqāṣid al-sharī‘ah. Governance studies highlight ac-countability\, transparency\, and stakeholder trust\, while research on ISEn emphasizes digitalization\, creative financing\, and entrepreneurial intention. Sustainability is viewed not only in terms of economic viability but also as encompassing ethical and social commitments\, with maqāṣid al-sharī‘ah providing a normative framework that guides decision-making and ensures alignment with faith-based objectives. The findings reveal that the conceptual boundaries be-tween ISE and ISEn remain blurred but complementary\, suggesting their integration offers both institutional stability and entrepreneurial dynamism. This study contributes to the academic discourse by clarifying definitions\, synthesizing thematic trends\, and identifying research gaps. Practically\, the results offer implications for policymakers in designing supportive ecosystems\, for practitioners in building hybrid models\, and for academics in advancing theoretical clarity. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:4c90b1e4eba9a720132a9a243d7348c4 URL:http://5thworldconferenceoninformations.sched.com/event/4c90b1e4eba9a720132a9a243d7348c4 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Enhancing Intrusion Detection with Hybrid Deep Learning(CNN-LSTM) and Tree-Based Models with XGBoost\, and LightGBM DESCRIPTION:Authors - Jaimin Dave\, Chintan Shah\, Premal Patel Abstract - Intrusion Detection Systems (IDS) have been instrumental in preventing emerging threats from compromising a network. One of the key challenges in the field is to design an IDS with high detection coverage and low false positives. This study investigates the potential of hybrid deep learning systems to address this challenge. We developed a CNN+LSTM model that leverages the spatial feature extraction power of CNN and the temporal sequence learning capacity of LSTM. Experimental results demonstrate that the proposed CNN-LSTM model consistently outperforms LightGBM and XGBoost\, achieving the highest accuracy (92.7%)\, precision (89.5%)\, recall (81.8%)\, and F1-score (84.3%)\, thereby confirming its robustness and effectiveness for intrusion detection. Additionally\, comprehensive assessments indicate that for more complex and hidden attack patterns\, the CNN+LSTM model is more advanced in terms of detection availability and effectiveness. The relevance of this work emphasises the need to modernise IDS systems by using hybrid deep learning techniques. Furthermore\, the combination of convolutional neural networks with LSTM improves detection capacity and supports feature-level detail for new hazards. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:6a9358a03cb81a42e3ca7973f8d201ed URL:http://5thworldconferenceoninformations.sched.com/event/6a9358a03cb81a42e3ca7973f8d201ed END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Implementing Zero Trust Architecture in SMEs: Readiness\, Barriers\, and Tailored Support Strategies – Evidence from the Czech Republic DESCRIPTION:Authors - Lukas Herout\, Arvind Panwar Abstract - This paper explores the adoption of Zero Trust Architecture (ZTA) in small and medium-sized enterprises (SMEs) in the Czech Republic\, aiming to identify key barriers\, enabling factors\, and readiness levels for its implementation. Drawing on survey data from 230 SME respondents\, we investigate aware-ness of ZTA principles\, current security practices\, and the perceived value of specific support measures. The study is guided by clearly defined research questions and hypotheses. We construct a composite readiness index based on technical and organizational measures and analyze its relationship with firm size\, security maturity\, and training frequency. Key findings indicate that while ZTA awareness is relatively low (only 43.4% had heard of the term)\, many companies have already implemented foundational elements aligned with ZTA. Security readiness is significantly higher among firms with formal security policies and regular employee training. Medium-sized enterprises show notably greater implementation levels than micro and small firms. The most frequently requested forms of support include practical implementation guides\, financial aid\, and consultations with experts. These preferences vary by firm size\, with smaller firms emphasizing financial support and larger ones favoring professional services. The paper concludes with a roadmap for SME-oriented ZTA adoption\, emphasizing the need for scalable\, low-barrier solutions and targeted support. Our findings provide empirical insights to inform policy design\, training programs\, and vendor strategies for secure digital transformation in the SME sector. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:fe1745d9b42875a2986f80027e49fe57 URL:http://5thworldconferenceoninformations.sched.com/event/fe1745d9b42875a2986f80027e49fe57 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:On-Device Tree-Based IAQ Forecasting on ESP32: A Comparative Evaluation DESCRIPTION:Authors - Hasin Mahir\, Tahfizul Hasan Zihan\, Md. Shirazim Munir\, M. M. Kamal\, Mahady Hasan\, Md. Tarek Habib Abstract - Accurate Indoor Air Quality (IAQ) forecasting can support affordable and privacy-conscious interventions in classrooms and workplaces. However\, most existing systems depend on cloud-based inference\, which introduces additional cost\, network dependency\, and reliability issues. In this work\, we present a comparative evaluation of three ensemble tree models—Random Forest\, XGBoost\, and LightGBM—implemented directly on an ESP32-S3 microcontroller for edge-based IAQ prediction of CO2 and PM2.5. A unified feature extraction strategy was employed\, combining temporal encodings\, lagged variables\, and short rolling aggregates. Models were trained offline\, converted into C\, and embedded into the device firmware. Their performance was assessed with respect to (i) forecasting accuracy\, using MAPE and RMSPE\, and (ii) resource efficiency\, including flash storage\, RAM usage\, and inference latency. Experimental results indicate that boosted methods (XGBoost and LightGBM) provide higher accuracy than Random Forest while staying within the strict memory and timing limits of the ESP32. This demonstrates the feasibility of fully self-contained IAQ forecasting on ultra-low-cost hardware\, without reliance on cloud resources. Furthermore\, we outline trade-offs between model complexity and efficiency\, and provide a reproducible toolchain for exporting tree ensembles into deployable ESP32 firmware\, highlighting their practicality for resource-constrained IAQ monitoring. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:302c93168bf61f760cc703dc2322e36c URL:http://5thworldconferenceoninformations.sched.com/event/302c93168bf61f760cc703dc2322e36c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Quantum-Enhanced Hybrid Intelligence: Fuzzy Logic Meets Neural Networks in Data-Driven Systems DESCRIPTION:Authors - Amogh Kotha Nagaraj\, Rajesh Eswarawaka\, Aadi B Kumar\, Sujay D Abstract - This paper will examine the synthesis of fuzzy logic\, neural network applications and hybrid computational techniques with quantum computing for data-driven system improvement. The intersection of these innovations will provide exciting directions for intelligent decision-making\, adaptive learning\, and effective data processing. Fuzzy logic offers a mechanism for dealing with uncertainty\, whereas these hybrid techniques blend the powers of multiple paradigms of computation. Neural networks provide the capability of deep learning\, and quantum computing provides new means for optimization and parallelism. In this work\, the theoretical background\, real-world applications\, and prospects of quantum-assisted hybrid intelligence systems are presented. The results imply that combined approaches can greatly enhance performance in high-complexity data environments\, opens up opportunities for future intelligent systems. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:feb4f044b48304a933e648d0ca18a197 URL:http://5thworldconferenceoninformations.sched.com/event/feb4f044b48304a933e648d0ca18a197 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Securing Systems Through Log Anomaly Detection: From Traditional Learning to LLMs DESCRIPTION:Authors - Pimal Khanpara\, Prasham Shah\, Sharada Valiveti\, Gaurang Raval Abstract - This article examines recent advancements in log anomaly detection\, a key factor in ensuring system reliability and security. Research is categorized into four main approaches like traditional machine learning\, deep learning\, transformer-based models\, and other emerging methods leveraging large language models (LLMs). Evaluations across benchmark datasets such as HDFS\, BGL\, Thunderbird\, and Spirit reveal a steady progression in detection capabilities\, with LLM-based approaches generally outperforming earlier methods. Techniques like LogRAG\, LLMeLog\, and EagerLog achieve F1-scores above 99% on certain datasets\, marking substantial improvements over traditional baselines. Current research trends include multimodal analysis\, few-shot and zeroshot learning\, explainable AI\, lightweight models\, and deeper semantic understanding of logs. These directions are increasingly important as modern systems generate massive\, diverse log volumes that demand more scalable and intelligent anomaly detection solutions. However\, persistent challenges like log parsing accuracy\, effective feature extraction\, and model adaptability to evolving log formats continue to limit performance in real-world applications. This review provides a structured overview of current methods\, highlights the strengths of LLM-based techniques\, and outlines promising areas for future research to advance the field of log anomaly detection. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:4aa18e887f4518760f2dcf005326fb24 URL:http://5thworldconferenceoninformations.sched.com/event/4aa18e887f4518760f2dcf005326fb24 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Simulation and Analysis of DDoS Attacks using ML on MAVLink protocol in UAV Communication DESCRIPTION:Authors - Sudarshan Sharma\, Amita Chauhan\, Sakshi Kaushal Abstract - Unmanned Aerial Vehicles (UAVs) have revolutionized industries such as defense\, agriculture\, and logistics due to their adaptability and ease of deployment. However\, their growing dependence on wireless communication protocols\, including MAVLink\, UAVCAN\, and UranusLink\, introduces significant security challenges. This research offers a comprehensive security evaluation of the MAVLink protocol through experimental simulations in Software-In- The-Loop (SITL) environments. The study simulates Distributed Denial-of-Service (DDoS) attacks at both the Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) layers to identify protocol vulnerabilities. Captured network traffic is compiled into a structured dataset and analyzed using machine learning algorithms\, specifically Support Vector Machine (SVM)\, Random Forest (RF)\, and K-Nearest Neighbor (KNN) algorithms\, to differentiate between normal and malicious packets. The findings highlight critical security weaknesses in MAVLink communications and introduce a robust simulation and classification pipeline designed to enhance the effective detection of attacks\, thereby improving UAV security. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:7e1f44d0f94cd5771dd3254b52e9623f URL:http://5thworldconferenceoninformations.sched.com/event/7e1f44d0f94cd5771dd3254b52e9623f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T191500Z DTEND:20261019T211500Z SUMMARY:Transforming Capital Markets through Blockchain Technology: Research Trends\, Challenges\, and Regulatory Insights DESCRIPTION:Authors - Suparna Ray\, Sushruthan Babu\, Niranjan Babu Abstract - Our study explores the transformative role of Blockchain Technology (BCT) in capital markets (CM) employing a mixed-method research design. We synthesize extant research and analyse global regulatory case studies\, particularly focusing on the Indian context. Utilising both bibliometric analysis and qualitative case study research\, our paper highlights the evolution of academic dis-course\, publication trends\, and practical applications of Distributed Ledger Technology (DLT) across equities\, debt\, and derivatives markets. Our findings indicate that while BCT promises efficiency\, transparency\, decentralization\, and cost reduction\, its large-scale adoption remains constrained by regulatory uncertainty\, scalability concerns\, and institutional resistance. This paper emphasizes the emerging regulatory frameworks in the US\, EU\, and Asia-Pacific\, acknowledging diverse approaches ranging from innovation-friendly sandboxes to cautious restrictions. We find limited empirical evidence on systemic risk\, tokenization\, liquidity\, and ESG-linked instruments\; hence\, we propose future research avenues that integrate finance\, law\, computer science\, and public policy. Through coherent mapping of the global regulatory landscape and reviewing scholarly contributions\, our paper contributes to understanding how BCT is reshaping CM infrastructure and provides pathways for policymakers\, regulators\, and market participants toward responsible and sustainable digital transformation. CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:1b4fc660a6487abf8fa4e0cbdcdd4395 URL:http://5thworldconferenceoninformations.sched.com/event/1b4fc660a6487abf8fa4e0cbdcdd4395 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211500Z DTEND:20261019T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:dfc52f73e364d9a366dc0119d34b5af8 URL:http://5thworldconferenceoninformations.sched.com/event/dfc52f73e364d9a366dc0119d34b5af8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211500Z DTEND:20261019T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:811dcdf864d2523a145229e4403c400c URL:http://5thworldconferenceoninformations.sched.com/event/811dcdf864d2523a145229e4403c400c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211500Z DTEND:20261019T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:1f476f5b19afb58320e8eb523802dfeb URL:http://5thworldconferenceoninformations.sched.com/event/1f476f5b19afb58320e8eb523802dfeb END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211500Z DTEND:20261019T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:fedd5625501c3a5c7c705fe43b168f57 URL:http://5thworldconferenceoninformations.sched.com/event/fedd5625501c3a5c7c705fe43b168f57 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211500Z DTEND:20261019T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:81e1c4d10e94ed4cf1a2b5593ce0d4eb URL:http://5thworldconferenceoninformations.sched.com/event/81e1c4d10e94ed4cf1a2b5593ce0d4eb END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211500Z DTEND:20261019T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:3b91454479f3cd0b2dc502a6527f59c1 URL:http://5thworldconferenceoninformations.sched.com/event/3b91454479f3cd0b2dc502a6527f59c1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211500Z DTEND:20261019T211700Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:d5b4d1addc3ae732df2163ae4ccd80d0 URL:http://5thworldconferenceoninformations.sched.com/event/d5b4d1addc3ae732df2163ae4ccd80d0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211700Z DTEND:20261019T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:9a83813dc1c6853e961658f87ade72c8 URL:http://5thworldconferenceoninformations.sched.com/event/9a83813dc1c6853e961658f87ade72c8 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211700Z DTEND:20261019T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:3ec3e704f81f6cf38bcb4b6d85bd2318 URL:http://5thworldconferenceoninformations.sched.com/event/3ec3e704f81f6cf38bcb4b6d85bd2318 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211700Z DTEND:20261019T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:2bcded96291e2e3421f9e3fae710ac42 URL:http://5thworldconferenceoninformations.sched.com/event/2bcded96291e2e3421f9e3fae710ac42 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211700Z DTEND:20261019T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:10f3c64e41c802017a185bd397801c9e URL:http://5thworldconferenceoninformations.sched.com/event/10f3c64e41c802017a185bd397801c9e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211700Z DTEND:20261019T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:9f50dd020d2a93db3e65532fc1cf0462 URL:http://5thworldconferenceoninformations.sched.com/event/9f50dd020d2a93db3e65532fc1cf0462 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211700Z DTEND:20261019T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:be499059cb85b17fbd95566749510c03 URL:http://5thworldconferenceoninformations.sched.com/event/be499059cb85b17fbd95566749510c03 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T211700Z DTEND:20261019T212000Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 8G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:e99619156e2f059216fd6b6ce9d7fdba URL:http://5thworldconferenceoninformations.sched.com/event/e99619156e2f059216fd6b6ce9d7fdba END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T215800Z DTEND:20261019T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:03ef52c70fd8353161fdfdff95921023 URL:http://5thworldconferenceoninformations.sched.com/event/03ef52c70fd8353161fdfdff95921023 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T215800Z DTEND:20261019T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:de3868d1ee78b871cea5b476839cfbce URL:http://5thworldconferenceoninformations.sched.com/event/de3868d1ee78b871cea5b476839cfbce END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T215800Z DTEND:20261019T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:bb8e7a05d15a21a0efb0e61036777cd6 URL:http://5thworldconferenceoninformations.sched.com/event/bb8e7a05d15a21a0efb0e61036777cd6 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T215800Z DTEND:20261019T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:c2704940b48d60a772cf2e8b5bdd736f URL:http://5thworldconferenceoninformations.sched.com/event/c2704940b48d60a772cf2e8b5bdd736f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T215800Z DTEND:20261019T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:50331c9e48f3f87a878b78b467b3313e URL:http://5thworldconferenceoninformations.sched.com/event/50331c9e48f3f87a878b78b467b3313e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T215800Z DTEND:20261019T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:d520de1605cb00f885f4da82cc78a2b3 URL:http://5thworldconferenceoninformations.sched.com/event/d520de1605cb00f885f4da82cc78a2b3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T215800Z DTEND:20261019T220000Z SUMMARY:Opening Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:255f967f6e7a28eae72aa545b73917ff URL:http://5thworldconferenceoninformations.sched.com/event/255f967f6e7a28eae72aa545b73917ff END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Agriculture with IoT-Enabled Smart Sensors: A new era of Agriculture Sustainability DESCRIPTION:Authors - Shamama Kamal\, Shailesh Saxena Abstract - This paper examines the transformative impact of Internet of Things (IoT) technologies on agriculture\, highlighting their role in enhancing efficiency\, productivity\, and sustainability. By integrating sensor devices\, data analytics\, and real-time connectivity\, IoT enables precision farming practices and interconnected farming ecosystems. Key components include soil monitoring\, crop health analysis\, and smart irrigation systems\, optimizing resource management and enhancing crop yields. Despite challenges like data security and interoperability\, the potential benefits of IoT in agriculture\, such as resource optimization and sustainable practices\, underscore its significance. In conclusion\, IoT emerges as a vital enabler for sustainable and efficient farming practices\, promising a more resilient agricultural sector and contributing to global food security. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:a6ecfd9772bf0a3686c5df1663780b39 URL:http://5thworldconferenceoninformations.sched.com/event/a6ecfd9772bf0a3686c5df1663780b39 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Detecting Malicious Android Apps through Static Features using Machine Learning DESCRIPTION:Authors - Priteshkumar Prajapati\, Jugal Mehta\, Prince Tadhani\, Parth Shah\, Amit Thakkar\, Dipak Dabhi Abstract - In the current era of mobile technology\, Android’s widespread use and customisation by developers have also made it simpler for hackers to identify and exploit security flaws. Android malware continues to evolve\, and one of the biggest concerns is how it quietly exploits app permissions and runs in the background to carry out harmful tasks without users even being aware of it. To address this emerging issue\, the research proposes a static analysis-based solution for Android malware detection\, utilising features derived from application permissions and API call behaviour. The study investigated a range of machine learning algorithms\, including traditional methods such as Logistic Regression\, SVM\, and KNN\, as well as more advanced approaches like Neural Networks and ensemble techniques like Random Forest\, XGBoost\, and CatBoost. We trained and tested the models using a well-organised set of Android app datasets and then measured their performance by analysing the results with a confusion matrix\, focusing on key metrics such as accuracy\, precision\, recall\, and F1-score. The confusion matrix clearly shows where our approach performs well\, especially in real-world situations where there’s an uneven number of malicious and safe apps. Our results highlight the effectiveness of ensemble learning methods in enhancing mobile security while also providing a clear comparison of how different algorithms approach the task of detecting Android malware. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:d4389336fc79dafc45c4229b11aaeab2 URL:http://5thworldconferenceoninformations.sched.com/event/d4389336fc79dafc45c4229b11aaeab2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Enhancing Athletic Performance Through an AI-Based Sports Application DESCRIPTION:Authors - Nayan Suresh Patil\, Shabana Pirjade\, Yash Dattatray Londhe\, Yogeshwar Anil Patil\, Tej Tushar Jadhav Abstract - This study presents an AI-powered mobile application designed to enhance athletic performance and promote active lifestyles. By evaluating existing sports applications\, it explores their roles in boosting user engagement\, motivation\, and achievement of fitness goals. Challenges such as user consistency and data privacy are also considered. The findings suggest that well-designed sports apps\, supported by responsive feedback systems\, can play a significant role in personal training. To address the difficulties faced by aspiring athletes\, especially in urban settings\, this project introduces a feature-rich platform that connects users to nearby sports academies and offers structured guidance across various disciplines like cycling\, athletics\, and running. A key innovation is the integration of IoT-based monitoring devices\, which provide real-time feedback through sensor-based data analysis. This facilitates accurate performance tracking and injury prevention\, empowering users with personalized insights for continuous improvement. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:670db986fa7e9560437c5837544ad751 URL:http://5thworldconferenceoninformations.sched.com/event/670db986fa7e9560437c5837544ad751 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Founder Verifier: An AI-Driven System for Automated Startup Founder Reputation Analysis and Verification DESCRIPTION:Authors - Radhika V. Kulkarni\, Gaurav Sulsule\, Sanika Kolawale\, Urmila Kakarwal\, Prathmesh Deshmukh\, Prakash Sharma Abstract - The burgeoning startup ecosystem necessitates robust and efficient methods for evaluating the credibility and historical performance of founders and their ventures. Traditional due diligence processes are often manual\, time-consuming\, and susceptible to information overload and inherent biases. This paper presents "Founder Verifier\," an Artificial Intelligence (AI) driven web application designed to automate and enhance the initial stages of founder reputation analysis. The system integrates web scraping capabilities with Natural Language Processing (NLP) techniques to provide a multifaceted assessment. Key functionalities include sentiment analysis of web-derived text using the NLTK VADER lexicon\, Named Entity Recognition (NER) for geographical context ex-traction via spaCy\, keyword-based potential controversy detection\, and assimilation of failure/industry insights. These analyses culminate in a consolidated web report featuring a heuristically derived reputation score\, categorized sentiment snippets\, links to relevant external profiles\, and downloadable PDF summaries. An operational dashboard further provides analytics on system usage and observed trends. This paper details the system's architecture\, the methodologies employed for data acquisition and multi-modal analysis\, the formulation of the reputation score\, and discusses the structure and utility of its outputs. The Founder Verifier aims to provide a rapid\, data-driven preliminary assessment tool for stakeholders in the startup ecosystem. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:cb0b8ab35e8e982119e4174931daa521 URL:http://5thworldconferenceoninformations.sched.com/event/cb0b8ab35e8e982119e4174931daa521 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Greening the Workforce: A Systematic and Bibliometric Review of Green Human Resource Management Literature (2000–2025) DESCRIPTION:Authors - Ch Sahyaja\, Gorripotu Eekshitha Bhagavathi\, Karthick.M\, Ch Shankar Abstract - This study presents a comprehensive\, systematic\, and bibliometric review of Green Human Resource Management (GHRM) literature from 2000 to 2025\, highlighting key trends\, influential authors\, research clusters\, and emerging themes. Using Scopus as the primary data source\, a total of 137 articles were analyzed with tools including VOSviewer\, R (Biblioshiny)\, and Excel. The findings reveal a significant growth in GHRM publications\, especially after 2020\, with South and Southeast Asian countries leading in research output and collaboration. Co-authorship and co-citation analyses revealed some well-known contributors\, including Ramayah T.\, Yusliza M.Y.\, and Jabbour C.J.C.\, and important publication outlets such as the Journal of Cleaner Production and IJHRM. From the keyword co-occurrence mapping\, we observe dominant research themes surrounding sustainability\, environmental performance\, green behavior\, and innovation. Besides\, this study provides a roadmap for future studies by outlining areas of theoretical void\, emergent domains of study and a call to an interdisciplinary and empirical approach. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:38dcdcb0b8c67f850154a50b8cb7d7a3 URL:http://5thworldconferenceoninformations.sched.com/event/38dcdcb0b8c67f850154a50b8cb7d7a3 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Multi-Class Crop Prediction Based on Soil and Climate Parameters Using Random Forest\, XGBoost\, and MLP DESCRIPTION:Authors - Aishwarya V. Kadu\, KTV Reddy Abstract - This research investigates the effectiveness of machine learning and deep learning models in multi-class crop classification using an agricultural dataset comprising 3\,450 records from the Wardha district of Maharashtra\, India. The dataset includes essential soil and climatic parameters such as pH\, nitrogen (N)\, phosphorus (P)\, potassium (K)\, Mn\, Fe\, Cu\, Zn\, S i.e Nutrients and micronutrients temperature\, humidity\, wind speed\, Cloud and rainfall\, covering 11 crop types. Data preprocessing involved label encoding for su-pervised learning tasks. The study developed and evaluated three predictive models: Random Forest\, XGBoost\, and Multi-Layer Perceptron (MLP). Model performance was assessed using classification metrics like accuracy and confusion matrix\, as well as regression metrics such as MAE\, MSE\, RMSE\, and R-squared. Feature importance analysis was performed to deter-mine the influence of input variables on model predictions. XGBoost showed the highest classification accuracy\, while MLP demonstrated strong learning capability. The findings emphasize the value of combining predictive performance and interpretability\, highlighting the applicability of AI-driven methods in enhancing crop recommendation systems and advancing precision agriculture across varied agro climatic zones. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:fe27f9f5c8f095d99f70da660563747b URL:http://5thworldconferenceoninformations.sched.com/event/fe27f9f5c8f095d99f70da660563747b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Predicting Diabetic Retinopathy using Convolutional Neural Networks DESCRIPTION:Authors - Purva Agarwal\, Somya R. Goyal Abstract - Diabetic Retinopathy (DR) is a widespread stage of diabetes that influences the retina and\, if untreated\, can lead to blindness. DR is one of the primary reasons for blindness\, especially among working-age populations in developing countries. Treatment can solely assist in preserving vision due to the irreversible nature of the disease. Timely identification and intervention substantially diminish the likelihood of blindness. Manual diabetic retinopathy diagnosis with retinal images is costly\, time-consuming\, and labor-intensive. The automatic detection of diabetic retinopathy disease can be possible using deep leaning methods specially CNN. In this paper\, several diabetic retinopathy detection methods based on deep learning are evaluated. The accuracy of the suggested method is 94.04%. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:bf7b27f01300770f4824b30a3b7c10ae URL:http://5thworldconferenceoninformations.sched.com/event/bf7b27f01300770f4824b30a3b7c10ae END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:QUANTUM COMPUTING AND WORKFORCE MANAGEMENT: REVOLUTIONIZING HR ANALYTICS DESCRIPTION:Authors - Damini Wankhede\, Shubham Kishor Kadam\, Utkarsha Wanjari Abstract - Quantum computing is a ground-breaking new technology\, and its disruptive potential can affect workforce management and HR analytics. This paper talks about its prominent role in addressing new challenges\, including workforce honing\, talent management\, employee retention\, cobalt matrix personalization\, and diversity management. Organizations can leverage quantum algorithms to optimize their allocation of resources\, recruitment and finding patterns in multidimensional datasets for better decision-making. These innovations are not only improving operational efficiencies — they are also facilitating more personalized and equitable approaches to the workforce. However\, the addition of quantum computing to HR systems poses its own set of problems. Technical roadblocks\, like high infrastructure costs and a shortage of skilled workers\, prevent wider adoption. HR schedules powered by automation can lead to biased results when data privacy and fairness of algorithms-related ethical concerns are addressed. Implementing such technology is beset by further complications like organizational readiness and change resistance needing to be effectively planned for and managed. The paper recommends actionable recommendations for HR leaders\, including phased integration\, investment in quantum literacy\, and the establishment of pilot projects. Further studies should employ realistic architectures that prioritize scalability\, cost-efficiency\, and the reduction of algorithmic biases that make quantum solutions more widely accessible and equitable. Because of that\, quantum computing can change the way HR analytics are performed\, and new opportunities for diverse industries emerge. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:f43dda8f1c5ea658f97080594a1170e9 URL:http://5thworldconferenceoninformations.sched.com/event/f43dda8f1c5ea658f97080594a1170e9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:The Role of Hospital Administrators in Enhancing Healthcare Quality through Leadership and Quality Improvement Initiatives DESCRIPTION:Authors - Rohini Chavhan\, Michael Savariapitchai\, Priyanka S. Dhore Abstract - Hospital administrators contribute substantially to healthcare quality advancement through their dual performance as operational managers and strategic leaders who drive changes. This study examines the multifaceted responsibilities of hospital administrators who enhance patient care quality by implementing leadership roles and executing policies and managing resources and developing their workforce. This study surveyed healthcare workers across the Sawangi region through 104 structured questionnaires which measured training delivery and resource distribution along with communication channels and leadership activities. The analysis of administrative behaviors against quality improvement outcomes utilized Spearman's Rank Correlation with Independent Samples t-tests. The research demonstrates that standardized staff workshops together with adequate financial resources and well-defined communication goals lead to improved staff involvement as well as superior patient security alongside superior clinical outcomes. Administrators who underwent formal training displayed superior abilities to lead continuous quality improvement efforts. The study demonstrates how hospital administrators drive patient-centered and safe healthcare delivery systems through strategic leadership execution which connects organization objectives to evidence-backed procedures. Strong leadership development along with policy support stands essential for maintaining quality care at high levels within transforming healthcare systems. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:053bbb79aaad8838e7a20eb47b3e5d46 URL:http://5thworldconferenceoninformations.sched.com/event/053bbb79aaad8838e7a20eb47b3e5d46 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:UPI Usage Among Migrant Workers in Tamil Nadu: An Analysis of Awareness and Challenges DESCRIPTION:Authors - Pranesh P\, Adwaitha K Raj\, Durga Lashmi C.V Abstract - Many individuals are interested in the Unified Payments Interface (UPI) technology since it is secure\, user-friendly\, and widely used in India. UPI (Unified Payments Interface) is incredibly popular in India\, with millions of users and billions of transactions processed daily. This study explains about the UPI usage and the awareness about the migrant workers in Tamil Nadu. This study consists of 100 responses from the migrant workers\, and their opinion towards the UPI usage. Most of the people think that the UPI usage is convenient for them to use in their smartphone. This study also examines the UPI preference of the respondents and their purposes. It also has the dominant results that all the respondents are aware of the UPI systems and pursuing it. This study has also consisted an insight of the digital literacy of the migrant workers. It also brings us the challenges that are faced by the people at the time of using UPI. UPI\, the Unified Payments Interface\, has been experiencing intermittent technical issues leading to partial transaction declines\, according to the National Payments Corporation of India (NPCI). These issues can cause problems with fund transfers\, payments\, and app functionality. CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:0099fc43a35cec88e1fd817785ec155a URL:http://5thworldconferenceoninformations.sched.com/event/0099fc43a35cec88e1fd817785ec155a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:AI-GHRM Integration Model (AGIM): A Multi layered Framework for Sustainable and Secure Workforce Analytics in Hospitality DESCRIPTION:Authors - Anubrata Dhar Chaudhuri\, Raj Chakraborty Abstract - The hospitality sector faces increasing pressure to integrate sustainability into operations while maintaining high productivity. Green Human Re-source Management (GHRM) practices have proven to enhance employee engagement and promote eco-friendly organizational citizenship behavior. How-ever\, traditional GHRM frameworks lack the digital\, real-time analytics needed to respond dynamically to workforce changes and sustainability goals. This research work proposes the AI-GHRM Integration Model (AGIM)\, a novel conceptual framework that extends the classical Stimulus-Organism-Response (SOR) paradigm into a dynamic feedback loop powered by artificial intelligence (AI). AGIM consists of a multi-layered architecture incorporating AI-based predictive analytics for attrition and engagement forecasting\, NLP-driven sentiment analysis of employee well-being\, IoT-enabled automation of sustainability compliance\, and privacy-preserving security mechanisms. This paper outlines the AGIM conceptual model\, compares its dimensions with traditional GHRM\, and presents a hypothesis matrix linking AI-powered interventions to employee and sustainability outcomes. A mixed-method research methodology is discussed\, blending qualitative case studies with quantitative analytics. Use case scenarios illustrate AGIM’s implementation phases in a hotel setting. The discussion highlights theoretical contributions (extending SOR with AI feed-back) and practical implications for business information systems in “smart secure systems”. Future work includes empirical validation and expansion to other service industries. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:e5167cce7fc27f72744c85fd24093b4d URL:http://5thworldconferenceoninformations.sched.com/event/e5167cce7fc27f72744c85fd24093b4d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Confidence intervals for Difference between the Percentiles of the Delta-Rayleigh Distributions DESCRIPTION:Authors - Nerisa Thornsr\, Sa-Aat Niwitpong\, Suparat Niwitpong Abstract - The delta-Rayleigh distribution comprises a mixture of zero and non-negative values following the Rayleigh distribution. Percentiles are practical tools for describing skewed data and are widely used in several fields. The purpose of this study is to construct confidence intervals for different percentiles of the delta-Rayleigh distributions using generalized confidence interval (GCI)\, normal approximation (NA)\, method of variance estimates recovery (MOVER)\, percentile bootstrap confidence interval (PBCI)\, and Bayesian methods. Monte Carlo simulations were conducted to evaluate the performance of these methods using coverage probabilities and average widths. The results indicate that the GCI method outperformed others. For a real-world data application\, we utilized a dataset on CO concentration to assess the performance of the presented methods. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:62d740e7583e62c50e4e093d54851a76 URL:http://5thworldconferenceoninformations.sched.com/event/62d740e7583e62c50e4e093d54851a76 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Evaluating the Effectiveness of Indonesia’s Core Tax Administration System: Challenges\, Early Impacts\, and Lessons for Digital Tax Reform DESCRIPTION:Authors - Surya Anugrah\, Sabo Hermawan\, Christian Wiradendi Wolor\, Eka Septariana Puspa\, Windy Permata Suyono\, Dwi Handarini Abstract - Indonesia’s bold leap toward digital tax reform culminated in the 2025 launch of its Core Tax Administration System (CTAS) a centralized platform aimed at streamlining taxpayer services\, boosting compliance\, and modernizing revenue administration. This study critically evaluates the early- stage implementation of CTAS using a dual-theoretical lens: the Technology Acceptance Model (TAM) and Institutional Theory. Drawing on government documents\, user surveys\, and media analysis\, findings reveal a paradox while users widely acknowledge CTAS’s potential to simplify tax filing\, technical glitches\, complex interfaces\, and poor system responsiveness undermine its usability and acceptance. Moreover\, institutional misalignments such as inadequate training\, low digital literacy\, and resistance to change pose structural barriers to reform success. By integrating behavioral insights with systemic analysis\, this research highlights the multilevel challenges of digital transformation in public finance. The paper concludes with actionable lessons for emerging economies navigating the tension between technological innovation and institutional readiness in the digital era. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:738df447b194a4e0dd3a785ccfed2746 URL:http://5thworldconferenceoninformations.sched.com/event/738df447b194a4e0dd3a785ccfed2746 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Intelligent Resume Evaluation Using LLMs: Skill Gap Identification and Job Compatibility Scoring DESCRIPTION:Authors - Krishna Saurabh Soni\, Pranshi Talati\, Jash Mandani\, Dweepna Garg\, Parth Goel Abstract - Recruitment has become a lot more complicated with a surge in the number of applicants for each job. Traditional resume screening methods are time-consuming and subjective—and that leads to inefficiencies and biases in candidate selection. What we need is a more efficient\, fair and accurate way to evaluate resumes. That’s where a new resume screening system comes in. By using Retrieval-Augmented Generation (RAG) with the Gemini API\, we can improve the accuracy\, efficiency and fairness of resume evaluation. That system pulls out the most relevant information from resumes\, compares a candidate’s skills to the job description and gives you a selection probability score-complete with reasoning. We combined Natural Language Processing (NLP)\, machine learning and a resume dataset from Kaggle to refine the evaluation process. The experiments show the model can identify missing skills\, match candidate qualifications to job requirements and give job seekers valuable insights. Integrating RAG into the hiring process can make a real difference to recruitment outcomes-and reduce bias and manual workload. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:93b9b741b5588d388cc92eea200ac0db URL:http://5thworldconferenceoninformations.sched.com/event/93b9b741b5588d388cc92eea200ac0db END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Kinecharge: A smart kinetic energy to electric eco energy generation from cycling motion for smart device charging DESCRIPTION:Authors - Naina Kokate\, Supriya Gorde\, Rashmi Kale\, Sayali Mulik\, Kashmira Naik\, Kartik Mundwadkar\, Atharva Navale\, Piyush Nakade Abstract - The rapid increase in portable electronic device usage has intensified the demand for sustainable and self-sufficient energy solutions. KineCharge addresses this need by innovatively harvesting kinetic energy generated during cycling and converting it into usable electrical power. The system uses a DC motor directly connected to a bicycle wheel\, which produces electricity as the wheel rotates. This generated electrical energy is regulated through a diode to ensure proper current flow and is managed via a battery charging module. The harvested energy can be stored in a rechargeable battery for later use or accessed immediately through a USB output to charge smartphones and other portable devices. This design offers an environmentally friendly and costeffective alternative to traditional power sources\, particularly benefiting cyclists\, outdoor enthusiasts\, and individuals in remote or off-grid locations. KineCharge promotes clean energy utilization while providing a practical means to keep devices powered during travel. By leveraging mechanical energy from cycling\, it reduces reliance on conventional electrical grids and supports the adoption of sustainable energy practices. Additionally\, the project serves as an educational tool that demonstrates principles of energy conversion and renewable power generation. Designed for easy installation on most bicycles\, KineCharge offers a portable and green energy solution adaptable to a variety of users. It exemplifies innovative thinking in renewable energy and contributes to fostering energy independence and environmental sustainability in everyday life. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:9568bb14c3a187e8a9c91ae07e2c6ba9 URL:http://5thworldconferenceoninformations.sched.com/event/9568bb14c3a187e8a9c91ae07e2c6ba9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Optimizing Tax Revenue to Support the Achievement of SDG 13: Mitigating Climate Change through Carbon Tax Policy DESCRIPTION:Authors - Surya Anugrah\, Rochma Sudiati\, Eka Septariana Puspa\, Windy Permata Suyono\, Sabo Hermawan\, Septi Nurmalita Abstract - Carbon tax policies have been widely adopted as instruments for climate change mitigation\; however\, their implementation in developing countries continues to face significant structural and political challenges. This study aims to analyze the influence of per capita carbon emissions and tax revenue on carbon tax rates in ten developing countries during the period 2021-2023. Utilizing a panel data regression approach with fixed effects models\, this research examines the causal relationship between environmental and fiscal factors and the determination of carbon tax rates. The estimation results reveal that per capita carbon emissions have a negative and statistically significant effect on carbon tax rates\, with a coefficient of -6.09 (p0.05)\, suggesting that fiscal considerations are not yet a primary determinant in the design of carbon tax policies in developing economies. The policy implications of this study highlight the need for more progressive and integrated carbon tax reforms aligned with sustainable development agendas\, particularly in support of Sustainable Development Goal (SDG) 13. This study contributes novel empirical evidence to the green fiscal literature in developing countries and offers strategic recommendations for policymakers to optimize the role of carbon taxation in global emissions reduction efforts. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:e813de2a161fead250263347c8d991a1 URL:http://5thworldconferenceoninformations.sched.com/event/e813de2a161fead250263347c8d991a1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Promoting Sustainable Futures through Quality Education DESCRIPTION:Authors - Navya H\, Ananthavalli Thangam Abstract - Education is an important tool in empowering people with the required knowledge and influencing their perspective and attitude for transforming the society. This assumes more importance in the context of the goal of lifelong learning. Achieving goals require behaviour change at multiple levels. This study is an attempt to assess the impact of education on the perspectives of people in promoting eco-friendly behaviour. Quality education is invariably connected with certain goals such as reducing poverty and promoting gender equality. As we drive towards the targets of SDGs\, a closer look at the intricate relation of education with the goals of zero hunger\, gender equality and poverty reduction points towards the urgency in using education not merely as a goal in itself but a catalyst for attaining the desired goals. Equipped with the necessary skills\, education provides opportunities for employment. Coupled with the awareness of sustainable development\, the goals of economic advancement can be attained with less damage to the environment. Inclusive education with provision of equal opportunities for women leads to gender equality and participation of women in progress. A cross-sectional survey was taken to assess the perspective of the role of education as a catalyst to promote the SDGs. The results strongly indicated the need to provide quality education with the right strategy and policy interventions. There are economic and social challenges to overcome. The role of institutions is to be emphasized. Concerted efforts by academicians\, corporates and the government can strengthen the pillars of economy\, environment and equity. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:146df8ed15efecccb17830c8c0d243f2 URL:http://5thworldconferenceoninformations.sched.com/event/146df8ed15efecccb17830c8c0d243f2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Research and analyze stock trends in Vietnam's banking industry based on real data DESCRIPTION:Authors - Tran Phuong Duy\, Nguyen Gia Tuan Anh Abstract - This study aims to evaluate the trend of stock price fluctuations in the Vietnamese banking industry in the period of 2019-2023 by integrating real-world data with quantitative models and modern machine learning techniques. Data is collected from reputable sources such as HOSE\, Vietstock and CafeF\, including financial indicators (EPS\, ROE\, P/E\, ROA)\, macroeconomic factors (operating interest rates\, exchange rates\, foreign cash flows) and market sentiment index (Vietnam VIX). The applied analytical models include linear regression\, logistic regression\, GARCH\, VAR\, VaR and Random Forest. The research results show that the VIX index has a clear impact on bank stock prices\, and the proposed system is capable of supporting investors in determining the appropriate trading time\, classifying stocks according to risk and expected return. The article not only provides a quantitative perspective but also provides an effective visualization tool\, contributing to improving the quality of investment decisions in the Vietnamese stock market. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:119b9f80077aaface03ad5cb92417105 URL:http://5thworldconferenceoninformations.sched.com/event/119b9f80077aaface03ad5cb92417105 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Role-Specific Gender Differences in Employee Attrition: Evidence from a Multi-Method Workforce Study DESCRIPTION:Authors - Usha Sadhani\, Melita Simoes\, A M Kadakol Abstract - In today’s dynamic work environment\, employee attrition is a crucial challenge for organizations that are impacted by demographic and job-related factors. This study examines the role of gender in attrition across different job roles and encompasses a multi-method approach taking into consideration 1\,470 employees. The analysis found that there is no significant influence of gender in the attrition rates. Job satisfaction and tenure of an employee within an organization emanated as stronger predictors of attrition than gender\, aligning with the established theories that highlighted the preference of job-related factors over demographic characteristics that helps in the retention of an employee. The logistic regression model showed a statistically significant result but was not very effective at predicting who leaves\, highlighting the complexity of attrition and the role of factors not included in the study. Overall\, the findings suggest that gender alone is insufficient to explain attrition patterns\, highlighting the importance of contextual factors such as job role and employee satisfaction. This research contributes to the ongoing dialogue on diversity and retention by demonstrating that effective talent management should consider the nuanced interactions between job characteristics and individual experiences rather than relying on broad demographic generalizations. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:2efb388bd95143de3ad3b97306ff7fea URL:http://5thworldconferenceoninformations.sched.com/event/2efb388bd95143de3ad3b97306ff7fea END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:The role of leadership styles in preventing burnout and promoting a sustainable work environment in healthcare organizations DESCRIPTION:Authors - Priyanka S. Dhore\, Michael Savariapitchai\, Rohini Chavhan Abstract - Repeatedly\, being burnt out\, constitutes a severe health issue\, affecting employee welfare\, and negatively impacting the long-term sustainability of health organizations. It revolves around different types of management styles that don't burn an employee out\, but instead create an environment conducive to work\, given health institutions. Exploring the work of four different dimensions of leadership: transformational\, ethical\, health-promoting\, and resilient\; would be towards reducing burning out and improving employee well-being\, as well as creating a positive organizational culture. The study adopted a quantitative approach wherein close-ended survey questionnaires were used to collect data from a sample of 101 healthcare employees. Results revealed that empathic\, supportive\, and team-focused behavior of leaders has considerable impact on the burnout and job satisfaction levels of workers. In addition\, interventions such transformational and health-promoting leadership have been found to have a positive influence on organizational health\, supportive policies\, and retention of employees\, among others. Workplace leadership praise the productivity and balance. Leadership helps to focus Tasks. It encourages the distribution of workloads. It sets up mental health projects and it backs employee welfare. Healthcare leadership requires listening to concerns raised by employees\, creating a work-life balance\, and enforcing fair policies to prevent burnout. There is evidence in favor of having an enlightened discussion for healthcare leaders that improves the environment balancing conditions between burnout-prevention and better performance of the organization. CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:90738a5de99ae642a66999ef98bda80c URL:http://5thworldconferenceoninformations.sched.com/event/90738a5de99ae642a66999ef98bda80c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:A Federated Learning Framework for Secure Crop Disease Detection in Decentralized Agricultural Environments DESCRIPTION:Authors - Mohammad Nasar\, Mohammad Abu Kausar\, Md. Abu Nayyer Abstract - Smart farming technologies\, particularly image-based crop disease detection systems\, are significantly transforming agriculture by enabling farmers to respond promptly to emerging threats. However\, deploying centralized AI models in remote or rural farming communities remains challenging due to limited internet connectivity\, heterogeneous data sources\, and privacy concerns. This paper presents a federated learning (FL) framework designed to support secure and privacy-preserving crop disease detection in decentralized agricultural environments. In the proposed approach\, lightweight convolutional neural networks (CNNs) are trained locally on crop images captured by drones or field sensors\, ensuring that sensitive data remains at the source. Instead of transmit-ting raw data\, only model updates are shared with a central server\, which aggregates them using the Federated Averaging (FedAvg) algorithm. To enhance security and model integrity\, a cosine similarity-based filter is incorporated to detect and discard malicious or corrupted updates. Additionally\, an attention-based heatmap module is introduced to visually highlight disease-affected regions in the crop images\, improving system transparency and building user trust. Experimental evaluations on the PlantVillage dataset and real-world drone imagery of wheat and tomato crops demonstrate that the framework achieves an average 4.8% improvement in F1-score under non-IID data conditions com-pared to centralized models\, alongside a 9.3% reduction in communication overhead at 50 nodes. This solution is well-suited for resource-constrained rural settings and contributes to scalable\, intelligent\, and sustainable agricultural digitization. CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:e5b618a1f6bee65084d9464be79edc7a URL:http://5thworldconferenceoninformations.sched.com/event/e5b618a1f6bee65084d9464be79edc7a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Active Directory – Attacks and Defense DESCRIPTION:Authors - Makrand Kadam\, Prashant Dhotre Abstract - Active Directory (AD)\, created by Microsoft\, plays a central role in how most organizations manage user identities\, access\, and system permissions. Because of its importance in controlling access across enterprise networks\, it’s a prime target for cyber attackers. This paper takes a closer look at how AD is structured\, highlighting key vulnerabilities and common methods used by attackers—like stealing credentials\, escalating privileges\, using Pass-the-Hash\, or creating Golden Tickets. It also examines real-life security breaches to show just how critical AD security has become. Beyond identifying threats\, the paper outlines practical defenses such as improved auditing\, network segmentation\, hardening of domain controllers\, and adopting zero trust models. By bringing together current research and best practices from the field\, this study offers cybersecurity professionals and system administrators a clear\, actionable guide to better protect their AD setups against today’s increasingly sophisticated threats. CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:04c1d9993f3bdb4218405a7192d53320 URL:http://5thworldconferenceoninformations.sched.com/event/04c1d9993f3bdb4218405a7192d53320 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:AI and Inner Peace: AI-Powered Mental Wellness through the Teachings of the Bhagavad-Gita DESCRIPTION:Authors - Rajeshwari S B\, Sajini G\, Jagadish S Kallimani Abstract - In today's fast-paced world\, people frequently experience high levels of emotional stress and struggle to access personalized mental health support. Traditional mental health services often face challenges such as limited accessibility and a generalized approach\, which can overlook individual emotional nuances. This one-size-fits-all method may fail to address the specific needs of individuals. The need for more responsive and individualized mental health resources has never been greater\, highlighting the importance of innovative solutions that offer contextually relevant and personalized care. The Srimad Bhagavad Gita\, a timeless spiritual text\, offers profound teachings on managing emotions\, finding purpose and maintaining balance in life. This project aims to develop a Mental Health Conversational Assistant that provides users with motivational responses rooted in the wisdom of the Bhagavad Gita. This chatbot lever-ages NLP and NLU to detect both the emotional state and the intent behind user queries. It uses advanced techniques like emotion detection and semantic understanding to analyze user input and respond with relevant verses from the Bhagavad Gita. By integrating Hugging Face's emotion detection models and sentence-transformer embeddings\, chatbot is capable of providing tailored\, contextually relevant verses from Bhagavad Gita that match both the user’s emotions and the meaning of their queries. CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:bf2740bc0715279deaddf3c6a50b9b50 URL:http://5thworldconferenceoninformations.sched.com/event/bf2740bc0715279deaddf3c6a50b9b50 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:AI-Driven Disease Surveillance and Outbreak Response: A Transparent Informatics Framework for Resource-Limited Healthcare Systems DESCRIPTION:Authors - Reena S. Satpute\, Nura Muhammad Sani Abstract - Effective disease surveillance and outbreak response are high public health priorities\, particularly in resource-limited healthcare systems facing significant challenges with data collection\, predictive modeling\, and coordinated intervention strategies. It hence proposes an integrated AI-driven framework responding to these challenges and strengthening the capacity of public health authorities to better manage infectious disease outbreaks. This framework will integrate real-time data from different sources such as electronic health records\, syndromic surveillance\, environmental indicators\, and social media in a harmonious way into one centralized repository for the enablement of advanced predictive modeling techniques. It mainly comprises a disease forecasting model\, an outbreak detection algorithm\, and an intervention optimization tool integrated to provide early warning\, accurate prediction\, and data-driven decision support. An extensive performance evaluation of the framework was conducted using accuracy\, sensitivity\, specificity\, and area under the ROC curve as some of the metrics. The results are very satisfactory\, while the overall accuracy is 94.8% (95% CI: 93.2%-96.4%) with an AUC-ROC of 0.967 (95% CI: 0.951 - 0.983). Comparative performance analysis using state-of-the-art deep learning architectures further establishes the superiority of the proposed hybrid model. Transparency and explainability in the framework were guaranteed up to an extent that allows understanding the models and decision-making process by the public health authorities. CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:25e477b2e5fb46a684b6c9b713a51d81 URL:http://5thworldconferenceoninformations.sched.com/event/25e477b2e5fb46a684b6c9b713a51d81 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Forecasting Cryptocurrency Trends: Applying ARIMA and Machine Learning to Predict XRP and Bitcoin Prices DESCRIPTION:Authors - Adulfo R. Arevalo\, Ronald L. Pancho Abstract - This study examines the forecasting performance of three prominent models— Autoregressive Integrated Moving Average (ARIMA)\, Support Vector Regression (SVR)\, and Random Forest (RF)—in predicting the short-term price movements of Bitcoin (BTC) and XRP using real daily closing price data from January to June 2024. The research aims to determine which model delivers the most accurate forecasts by applying each technique to actual market data and evaluating their predictive outputs using three standard accuracy metrics: Mean Absolute Error (MAE)\, Mean Absolute Percentage Error (MAPE)\, and Root Mean Squared Error (RMSE). Results show that ARIMA consistently outperformed both SVR and Random Forest in forecasting accuracy\, recording the lowest average errors across all metrics for BTC and XRP. While SVR performed poorly in capturing XRP's volatility\, Random Forest showed moderate results but lagged behind ARIMA. These findings highlight ARIMA's robustness and practicality as a forecasting tool for short-term cryptocurrency price movements. The study concludes with model-specific recommendations\, encouraging the use of ARIMA for near-term price prediction and suggesting further exploration into hybrid and deep learning models for future research. CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:9b807788f301af4225d356faaf7302a9 URL:http://5thworldconferenceoninformations.sched.com/event/9b807788f301af4225d356faaf7302a9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Gesture and Speech Enabled Virtual Mouse for Assistive Human-Computer Interaction DESCRIPTION:Authors - Rajeshwari S B\, Jagadish S Kallimani Abstract - In the realm of human-computer interaction\, the development of input devices accommodating diverse user needs is paramount. Traditional peripherals like mice and keyboards\, though effective in typical settings\, often falter in specialized conditions such as low-light environments. Addressing these constraints\, this study introduces a novel gesture and voice-controlled mouse system. By leveraging real-time video and audio inputs\, the system interprets user gestures and voice commands\, eliminating reliance on conventional input tools. Additionally\, it tackles unresolved interface design issues\, striving to optimize user experience and broaden computing resource accessibility. Key to its functionality is the integration of MediaPipe for precise gesture recognition and natural language processing for voice command interpretation. Utilizing standard webcam and microphone hardware enables hands-free cursor control and command execution\, particularly aiding users with mobility limitations. Methodologically\, the system blends foundational theoretical principles with innovative design concepts for practical realization. Rigorous testing demonstrates a 90% accuracy rate in gesture recognition and a notable 60% accuracy in low-light conditions. Voice command interpretation achieves an impressive 95% accuracy across various accents and speech patterns\, with a significant reduction in task completion time com-pared to conventional setups. This research underscores the potential of an affordable and adaptable technology\, promising enhanced digital accessibility through ubiquitous webcam and microphone integration. CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:6b17946aeb32da9c780b263e6ed02be5 URL:http://5thworldconferenceoninformations.sched.com/event/6b17946aeb32da9c780b263e6ed02be5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Habit and Perceived Safety on E–Wallet Adoption in Vietnam DESCRIPTION:Authors - Thanh D. Nguyen\, Anh T. N. Nguyen Abstract - This study examines how habitual behavior and users’ perceptions of security influence their intention to adopt and use e-wallet services. Building upon the original Technology Acceptance Model (TAM)\, the research integrates elements from both the Unified Theory of Acceptance and Use of Technology (UTAUT) and its extended version\, UTAUT2. Data were collected from 265 valid respondents via an online survey and analyzed using reliability testing\, exploratory factor analysis (EFA)\, confirmatory factor analysis (CFA)\, and structural equation modeling (SEM). The findings reveal that perceived security\, general privacy concerns\, and habit all positively affect the intention to adopt e-wallets. Further-more\, this intention significantly influences actual usage behavior. CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:8fc3c2e345fe8debc3032423bf42fedf URL:http://5thworldconferenceoninformations.sched.com/event/8fc3c2e345fe8debc3032423bf42fedf END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:MACHINE LEARNING ALGORITHMS FOR DETECTING FAKE NEWS ON SOCIAL MEDIA DESCRIPTION:Authors - Nureni Ayofe Azeez\, Solomon Akinboro\, Isiekwene Chinyere Chioma\, Charles Van der Vyver\, Awoseemo Babajide Abstract - The propagation of fake news in the digital age has raised momentous concerns about the integrity of information dissemination. This research aims to carry out a comparative assessment of machine learning algorithms for identifying fake news in social media. To achieve this\, an attempt was made to collect a wide-ranging dataset of news articles\, encompassing both real and fake sources. In the initial phase of the research\, we preprocess the news data\, extracting relevant features such as text content\, metadata\, and source credibility. Leveraging a wealth of labelled data\, these models learn to differentiate between genuine and fake news articles\, while also providing insights into the characteristics that contribute to their classification. In a world where information authenticity is paramount\, the implementation of this system provides a valuable tool for discerning consumers of news and enables the swift identification of misinformation sources. The models were trained using four different datasets. Several machine learning algorithms were used for carrying out comparative assessment in terms of their efficiency and accuracy to detect fake news. Selected metrics were chosen for a comparative assessment. At the end of the experiments\, for Dataset 1\, the Passive Aggressive Algorithm had the highest accuracy of 0.8333\, while for Dataset 2\, the Passive Aggressive Algorithm had the highest accuracy of 0.914285. However\, for Dataset 3\, the AdaBoostClassifier Algorithm had the highest accuracy of 0.9142857. Furthermore\, in Dataset 4\, several algorithms which including Logistic Regression\, Passive Aggressive\, Ridge Classifier\, SGD Classifier\, AdaBoost Classifier\, Bagging Classifier\, Extra Tree Classifier\, Gradient Classifier\, Random Forest\, NUSVC\, Linear SVC\, Decision Tree\, BernoulliNB\, and GaussianNB\, all had the highest accuracy of 1.0000000. A bar chart was used to represent the results graphically\, showing the minimum\, maximum\, and quartile range. CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:4d23630718865e143b03c7c102f8f8cc URL:http://5thworldconferenceoninformations.sched.com/event/4d23630718865e143b03c7c102f8f8cc END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Real-Time Deepfake Audio Detection Using Lightweight CNNs DESCRIPTION:Authors - Akash Karale\, Pratvina Talele Abstract - With the rapid advancement of deepfake audio technology\, producing artificial voices that sound remarkably realistic is now simpler than ever. As this becomes available In addition to opening up new creative possibilities\, it also poses grave security\, disinformation\, and fraud concerns. Although many of the deepfake audio detection tools available today are accurate\, their application in real-time situations is limited by their high processing overhead. In this work\, we introduce a Convolutional Neural Network (CNN)-based lightweight deepfake audio detection model. Our model can detect AI-generated speech accurately and with minimal processing demands by utilizing Mel-Spectrogram features and an effective CNN architecture. The model works well with high accuracy and low latency\, according to tests on standard datasets\, which makes it appropriate for real-world uses like media verification and voice authentication. Looking ahead\, we aim to improve the model's ability to withstand adversarial attacks and adapt to new types of deepfake generation techniques. In the future\, we would like to improve the model's robustness against hostile attacks and make it more flexible to accommodate new deepfake generation techniques CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:e0527a56151b0bcdf8be7848c62d38d0 URL:http://5thworldconferenceoninformations.sched.com/event/e0527a56151b0bcdf8be7848c62d38d0 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Recognizing Manipulated Images Using Deep Learning in Flask DESCRIPTION:Authors - Ram Joshi\, Rutuja Khedkar\, Prema Sahane\, Shantanu Totewad\, Nikhil Tarate\, Prajodeep Patil\, Kedarnath Zunjare Abstract - Deepfakes are manipulated or AI-generated images and videos that appear authentic but are not. A decade ago\, detecting deepfakes was relatively straightforward due to the limitations of the technology. However\, recent advancements in AI\, machine learning\, and deep learning have made deepfakes nearly undetectable. Although this technology is often used for entertainment\, it is increasingly being used for malicious purposes. The widespread availability of AI tools has further facilitated the creation of convincing deepfakes by fraudsters. Given that people tend to trust what they see and hear\, they are particularly susceptible to the influence of realistic deepfakes. CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:d199f8b7a64bb1991033c134872387f1 URL:http://5thworldconferenceoninformations.sched.com/event/d199f8b7a64bb1991033c134872387f1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:A Novel System to Capture and Create DIACOM and PACS Database DESCRIPTION:Authors - Kantharaju\, Srinidhi G A Abstract - Healthcare institutions worldwide are increasingly adopting digital im-aging solutions to replace traditional film-based radiological systems. This re-search presents the development of an advanced Picture Archiving and Communication System (PACS) designed to address current limitations in medical image management. Our proposed system focuses on seamless integration of legacy im-aging equipment through innovative format conversion capabilities\, specifically transforming proprietary image formats into standardized DICOM files. The implementation demonstrates significant improvements in storage efficiency\, trans-mission speed\, and overall workflow optimization within hospital environments. Through comprehensive testing and validation\, we established that our solution successfully bridges the gap between older imaging modalities and modern digital infrastructure requirements. The system architecture incorporates robust security measures\, user-friendly interfaces\, and scalable database management to support growing institutional needs. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:1bf15011c43fa6f352ceefd9273ded92 URL:http://5thworldconferenceoninformations.sched.com/event/1bf15011c43fa6f352ceefd9273ded92 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Advancing E-Governance in the Philippines: Strategies for Optimizing Components and Enhancing Digital Public Service Performance DESCRIPTION:Authors - Ronald L. Pancho\, Maria Teresa N. Pancho\, Roland M. Simbre Abstract - Using digital technologies to enhance government operations and e-service delivery\, e-governance encompasses diverse components crucial for improving digital initiatives and government e-service performance. This study examines how various elements of e-governance influence the effectiveness and efficiency of e-government e-services. The Philippines has actively pursued e-governance initiatives to encourage citizen participation\, provide access to information and service delivery\, enhance transparency and accuracy\, and promote communication and interaction. In this context\, the government's e-service performance becomes pivotal in assessing the effectiveness and efficiency of digital initiatives undertaken by the government. There were six hundred eighty-three (683) government e-services users to whom the respondents replied through Google Forms. The study used a self-made survey questionnaire and employed Cronbach's Alpha to test reliability and internal consistency. The experts conducted content validation\, and non-probability purposive sampling techniques were used in which respondents were directly involved. The finding reveals that e-governance components positively correlate with government e-services' performance in effectiveness and efficiency. The study relates how the use of e-governance components affects e-services performance. The idea suggests that increasing e-governance practices enhances government e-services performance. Therefore\, optimizing the e-governance components and enhancing their performance are essential in improving digital public service initiatives. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:379d46f3b5f49a3eabe873986e79305c URL:http://5thworldconferenceoninformations.sched.com/event/379d46f3b5f49a3eabe873986e79305c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Evaluating AI-Optimized Mobile Design: A Mixed-Method Study on Bootstrap Performance and ChatGPT Text Analysis for MSME Websites DESCRIPTION:Authors - Sabo Hermawan\, Ryna Parlyna\, Surya Anugrah\, Inkreswari Retno Hardini\, Ferry Setyadi Atmadja\, Fajri Hamdani\, Alifah Nur Rahmawati\, Cornellius Seno Adriano Abstract - This study examines the effectiveness of combining AI-optimized mobile design with Bootstrap performance improvements and ChatGPT-driven text analysis for Micro\, Small\, and Medium Enterprise (MSME) websites. A mixed-methods approach was utilized to assess the effects of these interventions. Performance measures\, particularly Largest Contentful Paint (LCP)\, exhibited a significant 40% enhancement following modification. Simultaneously\, text analysis performed with ChatGPT-4 attained an accuracy of 86.7% in detecting significant content concerns. This research fills a notable vacuum in the literature by offering a comprehensive analysis of technical and AI-based solutions for enhancing the online presence of MSMEs. The results highlight the capability of AI to improve the technical performance and content quality of mobile-optimized websites\, providing practical insights for MSME digital strategies. Subsequent research will investigate wider geographical contexts. These findings are further contextualized within the Technology Acceptance Model (TAM)\, emphasizing the perceived usefulness and ease of use of AI-enhanced mobile websites. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:4e40d6a7431f3ed52a934fd9437f52ac URL:http://5thworldconferenceoninformations.sched.com/event/4e40d6a7431f3ed52a934fd9437f52ac END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Exploring Satellite Imaging: From Technology to Landsat Image Creation with Raw Data DESCRIPTION:Authors - Veena N D\, Anithadevi M D Abstract - This investigation examines contemporary satellite imaging method-ologies and their implementation in Earth observation applications. We analyze the operational principles of various sensing platforms\, data acquisition techniques\, and processing algorithms used in modern remote sensing applications. Our research focuses on spectral band optimization and image reconstruction methodologies using actual satellite datasets. A comprehensive case study utilizing Kilauea Volcano imagery from Hawaii demonstrates practical applications of multi-band data processing techniques. Through systematic analysis of seven spectral channels from Landsat-7 Enhanced Thematic Mapper Plus sensor\, we evaluate the effectiveness of different wavelength combinations for terrain characterization. Our experimental results indicate optimal spectral configurations for various surface feature identification tasks. The study concludes with an assessment of current technological capabilities and operational constraints affecting satellite-based Earth observation systems. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:5e55e5b534521067c0f965b6ac739f00 URL:http://5thworldconferenceoninformations.sched.com/event/5e55e5b534521067c0f965b6ac739f00 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Opioid Disease Mortality Rate Analysis in United States using AI DESCRIPTION:Authors - Sanjay Yadav\, Sanjay Kumar\, Sakshi\, Aaryan Abstract - Artificial Intelligence (AI) is revolutionizing healthcare by enhancing diagnostics\, optimizing treatment plans\, and enabling datadriven public health strategies. This paper focuses on the application of AI to combat the opioid overdose crisis in the United States\, utilizing machine learning techniques—particularly reinforcement learning—to inform policy interventions. We explore the use of deep Q-networks (DQN) trained on CDC opioid mortality data to simulate optimal intervention strategies across states\, demonstrating a potential reduction of 15% in projected deaths. Additionally\, we apply clustering and trend analysis on multi-year overdose data to uncover regional dynamics and emerging hotspots. The study also examines key ethical considerations\, data privacy solutions\, and integration challenges within AI-driven healthcare systems. By combining algorithmic insights with epidemiological realities\, this work offers a scalable and explainable AI framework to support equitable healthcare policy design. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:de170405ee6974428ccfaddb004b7253 URL:http://5thworldconferenceoninformations.sched.com/event/de170405ee6974428ccfaddb004b7253 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Redefining Audit Practices in the Digital Era: A Systematic Review on Blockchain Integration DESCRIPTION:Authors - Septi Nurmalita\, Surya Anugrah\, Gentiga Muhammad Zairin\, Rochma Sudiati\, Eka Septariana Puspa\, Windy Permata Suyono\, Hera Khairunnia Abstract - In the era of accelerated digital transformation\, blockchain has emerged as a disruptive force in the auditing profession. This study presents a Systematic Literature Review (SLR) of 20 peer-reviewed articles from Scopusindexed journals (2020–2025)\, critically examining the opportunities and challenges of blockchain adoption in auditing. The review finds that blockchain enhances audit quality through real-time data access\, immutable transaction records\, and automation via smart contracts—leading to improved transparency\, fraud detection\, and operational efficiency. However\, adoption remains limited due to regulatory uncertainty\, high implementation costs\, technical interoperability issues\, and organizational resistance within traditional audit firms. Emerging concerns such as private key vulnerabilities\, ethical ambiguities\, and role conflicts in interdisciplinary audit teams further complicate adoption. Despite these barriers\, recent literature highlights new opportunities\, including collaborative audit ecosystems and the rise of Audit 4.0\, where blockchain is integrated with AI and IoT for predictive\, real-time assurance. The study calls for global regulatory harmonization\, cross-platform audit standards\, and empirical validation of blockchain-based audit systems. It also proposes a future research agenda centered on the convergence of blockchain and artificial intelligence to enhance risk detection\, audit automation\, and digital accountability. The findings offer actionable insights for regulators\, auditors\, and scholars navigating the evolving nexus of technology and assurance. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:142b1d9c4647211d71e2dd583a92703b URL:http://5thworldconferenceoninformations.sched.com/event/142b1d9c4647211d71e2dd583a92703b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Smart Campus Experience: Integrating Web-Based ERP\, Big Data Analytics\, and AI-Powered Dashboards to Enhance Student Engagement in International Programs DESCRIPTION:Authors - Sabo Hermawan\, Surya Anugrah\, Ryna Parlyna\, Windy Permata Suyono\, Eka Septariana Puspa Abstract - This study investigates the impact of integrating web-based Enterprise Resource Planning (ERP) systems\, Big Data Analytics (BDA)\, and AI-powered dashboards to create a Smart Campus environment that enhance student engagement in international programs. Employing a mixed-methods approach over one academic semester\, the research incorporates system log analysis\, surveys\, inter-views\, and focus groups. The findings reveal a significant improvement in aca-demic engagement (mean score = 7.8\, σ = 1.1)\, student satisfaction (68% positive feedback)\, and retention rates among international students. AI dashboards enabled early interventions for at-risk students\, while ERP and BDA supported administrative efficiency and personalized services. These outcomes contribute to Sustainable Development Goal (SDG) 4: Quality Education\, by promoting inclusivity\, efficiency\, and digital transformation in higher education. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:4d2ce57ac9609843a02e0f997c293977 URL:http://5thworldconferenceoninformations.sched.com/event/4d2ce57ac9609843a02e0f997c293977 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Smart Grip on a Budget: Designing a Cost-Effective EMG- Driven Prosthetic Arm DESCRIPTION:Authors - Ketaki Patil\, Om Nalagune\, Shravani Patil\, Sangita Bavkar Abstract - This paper presents the design and construction of a low-cost\, Arduino Nano-based myoelectric prosthetic arm to increase access to assistive technology to underprivileged populations. The system leverages surface electromyography (sEMG) signals recorded from non- invasive Ag/AgCl electrodes to signal voluntary muscle contraction. The signals are interpreted by a simple threshold-based control algorithm\, eschewing the use of advanced machine learning in favor of reliable and responsive performance. Upon exceeding a calibrated threshold\, servo motors built into a 3D-printed PLA arm are actuated to mimic simple hand movements like opening and closing. The use of open-source hardware\, low-cost materials\, and additive manufacturing processes like FDM 3D printing guarantees a low-cost manufacturing process\, permitting simple assembly\, repair\, and modification. The prosthesis is energy efficient\, modular\, and lightweight\, ideal for educational use\, rural hospitals\, and prototyping. Experimental testing confirms consistent performance and real-time responsiveness to muscle activity. In summary\, this paper demonstrates a low-cost\, accessible\, and scalable approach to functional prosthetic limb design\, closing the gap between advanced biomedical solutions and those communities in need of them. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:1ff32dfc77fb99eaaa8048193a3628fe URL:http://5thworldconferenceoninformations.sched.com/event/1ff32dfc77fb99eaaa8048193a3628fe END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Sustainable Business Model for BUMDes Wukirsari: A Study on Circular Economy Approach DESCRIPTION:Authors - Unggul Purwohedi\, Sabo Hermawan\, Ria Rahma Nida\, Yeti Lastuti Abstract - This study proposes a sustainable business model for BUMDes (Village-Owned Enterprises) Wukirsari\, specifically examining a circular economy approach integrated with information systems to support Sustainable Development Goal 12 (Responsible Consumption and Production). The research ad-dresses the gap of limited circular economy adoption and digital integration in rural enterprises. Utilizing a mixed-methods approach\, the study involved 18 respondents and employed tools such as Business Model Canvas\, SWOT analysis\, and Circular Mapping. Google Sheets\, Forms\, and Drive were integrated as the core information system for data tracking and management\, demonstrating a practical application of information systems for business management in a rural context. Validation was achieved through triangulation of data sources and expert review. The results identify key circular units\, including composting\, recycled crafts\, and eco-tourism\, integrated into a comprehensive circular model with digital tracking mechanisms. The proposed model demonstrates improved efficiency\, enhanced transparency\, and local feasibility\, offering a replicable frame-work for other rural enterprises. This research contributes to the novelty of tech-enabled circularity in rural contexts\, providing a practical pathway for BUMDes to enhance sustainability and economic resilience through a robust business model. While the study's limitations include a small sample size and single-site focus\, it lays a foundational understanding for future broader implementations of sustainable circular business models. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:f679ee4f0a2ed2edbbce71fecc8cf933 URL:http://5thworldconferenceoninformations.sched.com/event/f679ee4f0a2ed2edbbce71fecc8cf933 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Words-to-Fly: A Function-Based Approach to Voice-Controlled UAVs DESCRIPTION:Authors - Rama Satish K V\, Hemavathi J\, Shrihari Kulkarni\, V.V Sathya Sai Likhith\, Balasubramani A\, Shashaank Raj CS Abstract - The integration of AI-driven voice-controlled systems is transforming human-drone interaction\, enabling intuitive and efficient UAV operation. This paper presents a novel approach for voice-commanded drone navigation using a fine-tuned T5 model\, ensuring structured execution through predefined flight functions. The system incorporates Whisper for speech-to-text conversion and AirSim for high-fidelity simulation via its Python API. By leveraging NLP and real-time processing\, the model accurately maps user commands to drone actions while maintaining execution safety. Experimental results demonstrate 97% accuracy in function mapping\, highlighting the system’s reliability and responsive-ness. This work advances AI-powered UAV control\, enabling applications in search-and-rescue\, autonomous inspections\, and hands-free drone operations. CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:21b70069c85fc81a7b8c3277d698bae5 URL:http://5thworldconferenceoninformations.sched.com/event/21b70069c85fc81a7b8c3277d698bae5 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Advancements in Sentiment Analysis: A Comprehensive Survey of Techniques\, Models\, and Real-World Applications DESCRIPTION:Authors - Unnati Parmar\, Jatin Modh Abstract - Sentiment Analysis\, or opinion mining\, is the computational study of opinions\, sentiments\, emotions\, and attitudes expressed in texts. Due to the rapid expansion of social media\, e-commerce platforms\, and digital communication\, huge amount of opinion rich information is generated daily. This tremendous surge has also substantially increased the importance of sentiment analysis for understanding public opinion\, monitoring brand image\, forecasting market trend and enhancing customer relations. This paper also offers a detailed survey of SA methods\, from classic lexicon-based methods to recent deep learning models and transformers such as BERT and RoBERTa. We test their effectiveness on bench-mark datasets with empirical experiments and discuss their pros and cons in various real-world scenarios. Beyond these popular approaches\, we present a range of domain-specialized techniques\, multilingual processing\, and hybrid architectures synthesizing symbolic and statistical methods. We empirically show that the transformer models outperform LR\, SVM\, LSTM and BERT on the IMDB dataset in achieving better understanding of context-specific nuances. We next provide a number of problematic applications of sentiment analysis including sarcastic expression detection\, domain adaptation\, data unbalance and sentiment ambiguity. Various application scenarios in marketing\, healthcare\, finance and politics are also included in the paper. Finally\, we describe future research avenues focusing on explainable sentiment models\, real-time analysis systems\, and multimodal fusion approaches that take into account text\, audio and visual features.The goal of this study is to provide researchers and practitioners with a fundamental framework for creating sentiment analysis systems that are intelligent\, scalable\, and reliable. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:a43533c0b8a4c86d563b70b4419f1857 URL:http://5thworldconferenceoninformations.sched.com/event/a43533c0b8a4c86d563b70b4419f1857 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:AI-Driven Sustainable Marketing in the Metaverse and Consumer Purchase Intentions: A TPB Analysis DESCRIPTION:Authors - Rhytheema Dulloo\, Aditi Singh\, Vinay Kiran Abstract - The convergence of artificial intelligence\, sustainability conscious-ness\, and immersive metaverse technologies has created unprecedented opportunities for transformative marketing communications that influence consumer behavior in virtual environments. Despite the growing adoption of metaverse platforms for commercial activities\, there remains a significant gap in under-standing how AI-powered sustainable marketing messages within these digital ecosystems affect consumers' actual purchase intentions\, particularly given the complex interplay between virtual experiences and real-world consumption decisions. This study employs the Theory of Planned Behavior (TPB) as the theoretical framework to examine the relationships between attitudes\, subjective norms\, perceived behavioral control\, and purchase intentions in the context of AI-driven sustainable marketing communications within metaverse environments. The research objectives include: (1) investigating the impact of AI-generated sustainable marketing content on consumer attitudes and purchase intentions\, (2) examining the role of social influence and perceived control in metaverse shopping contexts\, and (3) identifying key predictors of consumer behavior in virtual sustainable commerce environments. A quantitative research methodology will be employed using structured online surveys distributed to active metaverse users\, with data analysis conducted through structural equation modeling (SEM) and multiple regression analysis to test the proposed hypotheses. Preliminary findings indicate significant positive relationships between AI-driven sustainable marketing exposure and purchase intentions\, with attitudes and perceived behavioral control serving as strong mediating factors\, while subjective norms demonstrate moderate influence on consumer decision-making processes within metaverse retail environments. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:0e88a5f2f2590801a219727f3a2c0df1 URL:http://5thworldconferenceoninformations.sched.com/event/0e88a5f2f2590801a219727f3a2c0df1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:AI-Driven Underwriting in Life Insurance: Transforming Risk Assessment in e-Business DESCRIPTION:Authors - Sonaly Maharaj\, Rhulani Maluleka\, Abelwe Maluleka Abstract - Life insurance is not immune to the transformative impact of artificial intelligence (AI). AI offers unprecedented levels of precision\, speed\, and customization in a field historically reliant on laborious manual procedures and statistical assumptions. This paper investigates how AI-driven underwriting can be incorporated into life insurers’ digital business strategy\, using Momentum’s in-app screening tool as a primary case study. The study proposes a theoretical AI underwriting architecture that maximizes risk assessment and policy issuance by leveraging machine learning algorithms\, biometric information\, and behavioral insights. The advantages\, disadvantages\, opportunities\, and threats of adopting AI underwriting are analyzed through a SWOT analysis\, highlighting ethical and legal considerations around algorithmic bias\, regulatory compliance\, and explainability. The findings suggest that while AI underwriting can provide insurers a competitive edge in a crowded market\, its implementation requires robust frameworks\, ethical design\, and regulatory alignment. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:1ede59b9d489500da3df9ecf6ab50746 URL:http://5thworldconferenceoninformations.sched.com/event/1ede59b9d489500da3df9ecf6ab50746 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Decoding Career Hesitations in Online Discourse: Topic Modeling Analysis of Social Media Posts on Managerial Roles DESCRIPTION:Authors - Suresh Panampilly\, Murale Venugopalan Abstract - Despite the prestige associated with leadership roles\, many employees are reluctant to become managers. This poses challenges for organizations aiming to strengthen their managerial pipeline to meet long-term strategic goals. In this study\, managerial reluctance is studied by analyzing candid posts on Reddit. LDA topic modelling using 15 posts revealed 6 themes. The themes uncover psychological\, organizational and ethical factors. Some results align with established theories (e.g. Expectancy\, equity and role theories). Others highlight unexplored areas such as ethical dilemmas and identity conflicts. This study confirms that topic modelling on social media data can give valuable insights into managerial reluctance. By using data from online discourses to draw theoretical insights\, this study offers conceptual contributions and practical in-sights which can be used to develop inclusive managerial talent in organizations. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:876c447528338f684aaf7036475f0573 URL:http://5thworldconferenceoninformations.sched.com/event/876c447528338f684aaf7036475f0573 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Dialogic Knowledge in AI Systems DESCRIPTION:Authors - Otmane Azeroual Abstract - This paper introduces Dialogic Artificial Intelligence (DAI)—a conceptual and computational framework for modeling how AI systems engage with human epistemic preferences in processes of knowledge retrieval and semantic representation. Grounded in Wittgenstein’s theory of language games\, DAI facilitates context-sensitive interpretation of user intent through dialogical interaction. Using multiverse hypergraphs and a mechanism called Dispute Learning (DL)\, the framework maps diverse queries onto epistemic subgraphs that reflect over-lapping but distinct knowledge communities. Unlike existing preference-matching models\, DAI emphasizes pluralism\, transparency\, and contestability in meaning construction. Real-world applications include academic search\, semantic interoperability\, and policy analysis—pointing toward a more dialogical paradigm in knowledge-driven AI systems. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:3c705e9906a3b796aaf312f03751ff8b URL:http://5thworldconferenceoninformations.sched.com/event/3c705e9906a3b796aaf312f03751ff8b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Enhancing Tax Compliance among E-Commerce MSMEs: The Impact of Digital Financial Technology and Tax Knowledge with Digital Trust as a Moderating Vari-able DESCRIPTION:Authors - Windy Permata Suyono\, Dwi Handarini\, Nuramalia Hasanah\, Ratna Anggraini\, Rio Firnanda\, Surya Anugrah\, Eka Septariana Puspa\, Septi Nurmalita Abstract - The digital transformation of Micro\, Small\, and Medium Enterprises (MSMEs) in the e-commerce sector has created significant opportunities to enhance tax compliance through the adoption of digital financial technology. De-spite these advancements\, tax compliance remains relatively low in many developing countries. This study investigates the impact of digital financial technology adoption and tax knowledge on the tax compliance behavior of e-commerce-based MSMEs\, with digital trust examined as a moderating variable. A quantitative approach was employed\, utilizing survey data from 120 MSME actors operating on major e-commerce platforms such as Tokopedia\, Shopee\, Lazada\, Blibli\, and Bukalapak. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that both digital financial technology and tax knowledge significantly influence tax compliance. Moreover\, digital trust positively moderates these relationships\, amplifying the effects of digital financial technology and tax knowledge on compliance behavior. These results highlight the critical role of a trustworthy digital ecosystem and comprehensive tax literacy programs in promoting voluntary tax compliance among MSMEs. The study provides meaningful insights for policymakers\, tax authorities\, and FinTech developers\, contributing to the growing body of literature on digitalization and tax governance in emerging economies. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:50ecddc7e8f481a0f45edd737b0e8e73 URL:http://5thworldconferenceoninformations.sched.com/event/50ecddc7e8f481a0f45edd737b0e8e73 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Hybrid Kernel SVM and Boosting Approaches for Accurate Autism Spectrum Disorder Screening DESCRIPTION:Authors - Usman Ali\, Shaiza Shahid\, Misbah\, Shahzad Ali\, Sheraz Aslam\, Kainat Mustafa Abstract - Autism Spectrum Disorder (ASD) is a neurocognitive condition that affects social connection\, expressive abilities\, and behavioral patterns. This study aims to diagnose ASD using machine learning (ML) techniques based on behavioral and demographic data. The dataset sourced from Kaggle includes features such as age\, gender\, ethnicity\, social interaction behaviors\, and responses to standardized screening questionnaires. To improve accuracy\, various ML models are implemented\, including NB\, AdaBoost\, SVM\, LightGBM\, KNN\, and XGBoost. Additionally\, advanced Ensemble Methods are applied\, such as Hybrid Kernel SVM\, a boosting classifier\, and a stacking classifier. Among all methods\, the stacking classifier delivered the best performance\, achieving 99.74% accuracy with the minimum MSE of 0.2. This result supports the development of an intelligent system to aid in early autism diagnosis and intervention planning. Future research could enhance this approach by integrating neuroimaging biomarkers\, generative AI\, or more advanced ML frameworks\, aiming for even greater precision and robustness in a real-world clinical setting. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:4dca058e014ade1f77268ae66a3ab549 URL:http://5thworldconferenceoninformations.sched.com/event/4dca058e014ade1f77268ae66a3ab549 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:ICT as a Teaching Tool for Understanding the Complexity of Strategic Management DESCRIPTION:Authors - Martina Beranek Abstract - Industry and services are undergoing fundamental changes in connection with new technologies\, the advent of AI\, global competition and at the same time the contradictory process of partial deglobalization\, changing markets\, material shortages\, local regulations and changing trade barriers\, especially in the form of tariffs. The already difficult situation is complicated by major military conflicts in the Middle East\, Ukraine and some regions of Africa. These aspects place high demands on the work of managers at all levels of management. It is therefore essential for university students to prepare for the above facts and to understand the complexity of strategic management as best as possible. ICT in the form of business simulations is a very suitable tool to teach students system thinking and explain the principles and principles of a strategic approach in business. Empirical research shows that students prefer project-based learning using ICT tools to classic frontal teaching and that this form of teaching based on the use of not only ICT but also AI promotes adaptability of learning\, contributes to digital literacy and leads to a much higher level of readiness for future professions. Business simulation not only allows the development of the entrepreneurial spirit but also leads to the improvement of soft skills. Finally\, it has been proven that thanks to the feedback provided by the simulation\, students see the impact of their decisions more or less immediately and can thus understand the complexity and complexity of the decision-making process at the strategic level of business management. The document recommends expanding the use of strategic simulations in higher education to meet the demands of a rapidly evolving and changing business environment. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:66e456d668a9d54e781453befdce178d URL:http://5thworldconferenceoninformations.sched.com/event/66e456d668a9d54e781453befdce178d END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Orchestrating Organizational Sustainability: The Impact of Green Recruitment\, Training\, Performance Management\, Involvement & Reward Systems through Green Leadership DESCRIPTION:Authors - Ch Sahyaja\, Ch Shankar\, Madhuri. K\, Jaswanthi Guda Abstract - The paper evaluates how the integrated Green Human Resource Management (GHRM) practices\, such as the green recruitment and selection of employees\, green sustainability training\, green performance management\, employee engagement and green compensation and rewards\, play a role in green leadership leading to sustainability capacity of organizations. The research was based on Ability Motivation Opportunity (AMO) and resource-based view (RBV) conceptualizations\, and the analysis was done using partial least squares SEM on 205 HR and the line managers of the manufacturing and service-based organization\, upon using the questionnaires issued to the mentioned managers in ADANCO 2.2.1. Findings reveal that green recruitment and selection (E = 0.303)\, employee involvement (E = 0.350) and green compensation (E = 0.250) do play a significant role in influencing the green leadership with a combinational effect of 60.3 per cent (R2 = .603). Green leadership plays an important role in exerting a favourable impact on sustainability (BR2 = .543) and helps to mediate among all three GHRM practices (Sustainability-mediated effects). Green leadership mediates between the GHRM behaviours of sustainability (.189)\, recruiting (.218) and promoting (.155) in direct effect (p < .005). Although organizational green culture positively affects sustainability (156)\, it does not have such an effect on the connection between leadership and sustainability. This brings out the point that green leadership holds the key to sustainability. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:814300e9fdaf1e440947648011ae7414 URL:http://5thworldconferenceoninformations.sched.com/event/814300e9fdaf1e440947648011ae7414 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Social Media in Promoting Sustainable Marketing: A Systematic Literature Review DESCRIPTION:Authors - Md Faiz Ahmad\, Md Asadul Haque\, Ananya Chowdary Muppana\, Aasritha Malineedi\, Dharani Gudivaka\, Sri Krishna Surya Putta Abstract - The present study offers a systematic literature review (SLR) providing insights on the role of social media in promoting sustainable marketing. The SLR is carried out to gain an understanding of the phenomenon. Scopus database was used to identify\, extract\, select and review related articles using search keywords. A total of 27 articles were deemed fit for this study. This SLR recognizes current research avenues related to social media in sustainable marketing using TCCM framework. The study used co-citation and keyword occurrence analyses to explore the nuances of the field under consideration. The study yields valuable insights for academia\, government\, green marketers to practically implement strategies and suggesting future opportunities for research. CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:ef8850b381d722a130a4122da7eead70 URL:http://5thworldconferenceoninformations.sched.com/event/ef8850b381d722a130a4122da7eead70 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Efficient Car Logo Detection via YOLOv8 and Attention Mechanism Fusion DESCRIPTION:Authors - Nhat Minh Nguyen\, Tu Anh Nguyen\, Huy Thai Hinh\, Quang Nhat Nguyen\, Thong Minh Phuc Nguyen\, Vinh Dinh Nguyen Abstract - Car logo detection is crucial for intelligent transportation systems. This paper compares attention mechanisms integrated into YOLOv8m for car logo detection\, evaluating Efficient Channel Attention (ECA)\, SimAM\, and their combination against a baseline YOLOv8m (95.2% mAP@0.5\, 48.6% mAP@0.5:0.95\, 79.3 GFLOPs). On a dataset of 5372 images\, ECA achieves 94.5% mAP@0.5 and 50.2% mAP@0.5:0.95 with 79.1 GFLOPs\, SimAM reaches 96.1% mAP@0.5 and 50.0% mAP@0.5:0.95 with 79.1 GFLOPs\, and the combined approach attains 95.3% mAP@0.5 and 50.1% mAP@0.5:0.95 with 79.3 GFLOPs. All variants maintain real-time performance with inference speeds of 29.29 FPS (ECA)\, 28.69 FPS (SimAM)\, and 27.95 FPS (combined)\, compared to the baseline’s 28.32 FPS on an NVIDIA RTX 3050 laptop GPU. These results demonstrate that integrating lightweight attention mechanisms can substantially enhance detection performance in data-constrained scenarios while preserving real-time efficiency. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:516e8dd9a05d388419db9b6c4ce38f4f URL:http://5thworldconferenceoninformations.sched.com/event/516e8dd9a05d388419db9b6c4ce38f4f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Empowering Auditor Performance Through Digital Access and IT Infrastructure: The Mediating Role of Auditor Competence DESCRIPTION:Authors - Windy Permata Suyono\, Dwi Handarini\, Eka Septariana Puspa\, Surya Anugrah\, Wida Aristanti\, Rio Firnanda Abstract - This study investigates the influence of digital access and IT infra-structure on auditor performance\, with auditor competence as a mediating variable. Grounded in the Technology–Organization–Environment (TOE) and Task–Technology Fit (TTF) frameworks\, data were collected from 110 auditors in Jakarta and West Java using a structured online survey. Structural Equation Modelling with Partial Least Squares (SEM-PLS) was employed to analyse the relationships. The results reveal that while digital access does not have a direct effect on auditor performance\, it significantly influences auditor competence\, which in turn enhances performance. IT infrastructure shows both direct and indirect effects through auditor competence. These findings underscore the critical role of auditor competence in leveraging technological resources to achieve optimal performance. The study provides practical insights for audit institutions aiming to enhance audit effectiveness through digital capability development and infra-structure investment. It also contributes to the growing literature on digital trans-formation in the auditing profession\, especially within the context of emerging economies. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:ac73555eecd2bcb8e2b9651ede3eb1d2 URL:http://5thworldconferenceoninformations.sched.com/event/ac73555eecd2bcb8e2b9651ede3eb1d2 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Fine-Tuning BART for Multi-Label ICD-9 Prediction from Clinical Discharge Summaries DESCRIPTION:Authors - Ch Geethika Gayatri\, P Lavanya\, S Manvitha Reddy\, Nikitha K Abstract - Accurate and automated assignment of ICD-9 codes from clinical narratives is essential for healthcare analytics\, and clinical decision support. However\, the task remains complex due to the high dimensionality of the label space\, variability in clinical language\, and the multi-label nature of diagnostic documentation. This paper presents a novel deep learning framework for multi-label ICD-9 code prediction from discharge summaries using a fine-tuned Bidirectional and Auto-Regressive Transformers(BART). Targeting real-world clinical documentation scenarios\, the proposed approach models unstructured medical narratives using a sequence-to-sequence architecture that captures both global context and fine-grained semantic cues. Each discharge summary is tokenized and encoded using BART’s bidirectional encoder and autoregressive decoder\, enabling robust multi-label classification across the top 20 most frequent ICD-9 codes. Evaluation on the MIMIC-III dataset demonstrates strong performance\, achieving a F1 score of 71%\, while also showing balanced precision-recall behavior across high and low-frequency codes. ROC-AUC confirms the model’s discriminative capability across imbalanced labels. These results validate the model’s capability to handle complex\, multi-label classification scenarios common in clinical documentation. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:db5c3a9bbddd5864cafc8109790e43e9 URL:http://5thworldconferenceoninformations.sched.com/event/db5c3a9bbddd5864cafc8109790e43e9 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Formative Assessment of Spoken English Using Large Language Models in a Controlled Intervention Study DESCRIPTION:Authors - Mahimaben Panjabi\, Vijay Makwana Abstract - This study investigated the efficacy of Large Language Models (LLMs) for providing formative assessment of spoken English within a mixed-methods\, one-group pre-test/post-test design. The research involved 30 intermediate English as a Second Language (ESL) learners and five expert faculty members. The design integrated quantitative pre-test/post-test data with qualitative analysis of AI-generated feedback\, student reflections\, and faculty interviews. During the intervention\, all students used LLM tools (ChatGPT and Google Gemini) for practice and feedback. To ensure a robust\, triangulated assessment\, a coder-based framework was implemented where human experts evaluated spoken tasks against linguistic criteria. A paired-samples t-test revealed a statistically significant improvement in speaking proficiency from pre-test to post-test. Thematic analysis of qualitative data indicated that LLM-generated feedback was perceived as useful\, accessible\, and effective in reducing learner anxiety. This multi-faceted approach affirms that LLMs can be effective supplementary tools in language education and offers a holistic model for their integration into formative assessment practices. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:4e5fb3242d91fa0e37b1ef167787194a URL:http://5thworldconferenceoninformations.sched.com/event/4e5fb3242d91fa0e37b1ef167787194a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Nonlinear Classification on MiniRocket Architecture for Fish-Freshness Prognostics DESCRIPTION:Authors - Raghavan Vaidhyaraman\, Aryavardhan Modi\, Jayakumar Kaliappan Abstract - This paper aims to evaluate the performance of multiple non-linear classification techniques. Time-series classification has become central to many sensor-driven applications\, where capturing temporal patterns efficiently and accurately is critical. In this paper\, we evaluate and extend the proposed MiniRocket framework for classifying multivariate sensor data\, focusing on a practical “Fish Freshness” monitoring use case. Precise quantification of post-harvest fish freshness underpins foodsafety compliance and public-health protection while curbing spoilageinduced economic losses across the cold-chain. In operational practice\, high-fidelity freshness classification enables dynamic inventory routing\, just-in-time processing\, and trustworthy quality labelling\, thereby reducing food waste and reinforcing consumer confidence throughout seafood supply networks. MiniRocket is a highly efficient convolution-based feature extractor that transforms each raw time series into a fixed-length vector of pattern-frequency features (Proportion of Positive Values). We demonstrate that\, when paired with a simple linear classifier such as Ridge Classifier\, MiniRocket achieves state-of-the-art accuracy while requiring orders of magnitude less computation than deep-learning alternatives. We have demonstrated that combining MiniRocket with Random Forest Classifier yields greater than or equal to 90% classification accuracy\, particularly improving performance on ambiguous classes like ”Semi-Fresh.” The model’s simplicity\, scalability\, and efficiency make it suitable for real-time applications. Our findings validate MiniRocket as a practical solution for robust\, low-latency time-series classification in resource-constrained environments. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:27de63584bbfb0a4d573a034c81e5e40 URL:http://5thworldconferenceoninformations.sched.com/event/27de63584bbfb0a4d573a034c81e5e40 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Optimizing Feature Selection for Medical Diagnosis Systems Using Differential Evolution DESCRIPTION:Authors - GGS Pradeep\, Thrilok. Kolla\, N Vijayalakshmi\, Rajesh Sharma R Abstract - Machine learning has aided the improvement of medical diagnostic systems that help to detect diseases accurately in the present era. The work gave a mathematical and algorithmic handbook for characteristic selection with a binary Genetic Algorithm (GA) of particular use to jobs involving medical diagnosis. Clinical datasets usually have many dimensions and redundancy\, which most time affects model performance and increases computational complexity. In this study is presented a mathematical and algorithmic guide for selecting features through a binary Genetic Algorithm (GA)\, especially suitable for medical diagnostic tasks. The proposed method seeks to obtain the most informative subset of features by optimizing a fitness function that balances between classification accuracy and dimensionality reduction. The work develops a thorough mathematical model that incorporates data preprocessing\, binary encoding of feature subsets\, and repetitive evolutionary optimization. The metric used in testing the classification model is standard performance metrics-accuracy\, sensitivity\, specificity\, and F1 score\, summarized using a confusion matrix. Understanding feature selection stability across generations is also examined and visualized in a multidimensional performance space. The results would indicate a direct convergence of the model into high-performing feature configurations while avoiding risk for overfitting. An interpretative paradigm\, speed-up in computations\, as well as high reliability in diagnosis\, therefore pushing this method as a tool of great value in clinical decision support systems. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:d9e74a5ac6dbfe43219869cc45d4711f URL:http://5thworldconferenceoninformations.sched.com/event/d9e74a5ac6dbfe43219869cc45d4711f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Optimizing Multi-Agent and Functional Architectures for Enhanced Financial Trading Performance: VinTradeAgent Case Study DESCRIPTION:Authors - An Dinh Van\, Anh Nguyen Thi Linh\, Phuong Pham Nguyen Hien\, Hung Nguyen Gia\, Trinh Tran Thi Kieu\, Hung Nguyen Quang Abstract - This study proposes and evaluates a hybrid framework that integrates multi-agent systems and functional architecture for automated financial trading in Vietnam. The framework assigns specialized roles - fundamental\, technical\, news\, market\, trader and risk agents - operating over multimodal stock market data (OHLCV\, technical indicators\, firm fundamentals\, and textual news). Agents interact via structured horizontal debates and vertical risk gating to produce auditable trading proposals. Experimental results demonstrate improved risk-adjusted returns and enhanced explainability\, while modular design supports deployment for back-office automation (e.g.\, report generation and opportunity identification). The study contributes a methodology for combining agentic large language model (LLMs) with disciplined functional pipelines and provides practical guidance for deploying such systems in emerging markets characterized by high volatility and limited liquidity. Implications for FinTech adoption and regulatory alignment in Vietnam are discussed. Vin-Trade-Agent is available at https://github.com/thanhENC/Vin-Trade-Agent. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:2b2ee2d1135e4ed37768aac6dd27b7ca URL:http://5thworldconferenceoninformations.sched.com/event/2b2ee2d1135e4ed37768aac6dd27b7ca END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Predictive Modeling of Customer Churn and Personalized Subscription Recommendations for OTT Platforms DESCRIPTION:Authors - Kavitha Dhanushkodi\, Uma Sankary A Abstract - With the explosive growth of Over-the-Top (OTT) plat- forms\, reducing subscriber churn has emerged as a central problem for service providers. This paper introduces a single framework for churn pre- diction and customized subscription plan recommendation\, capitalizing on the advantages of Graph Neural Networks (GNN) and Reinforcement Learning (RL). Churn prediction was carried out on four models: Random Forest\, XGBoost\, Long Short-Term Memory (LSTM)\, and GNN\, with the GNN model showing better ability to detect potential churners by being able to model rich relationships in user data. For personalized recommendations\, both Cosine Similarity-based and Deep Q-Learning (DQN)-based approaches were utilized\, with DQN providing dynamic\, user-specific plan recommendations. The model was trained and tested on a balanced dataset with 147\,269 training samples and 25\,000 test samples\, and performance was gauged using accuracy\, recall\, F1-score\, and AUC-ROC. Analysis shows that the use of GNN for churn prediction and DQN for recommendation enhances the efficacy of retention mechanisms and increases user satisfaction. The technique empowers OTT providers with an effective means of proactive user interaction and churn prevention. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:f8db469353256a39c44d7357b26bbaaa URL:http://5thworldconferenceoninformations.sched.com/event/f8db469353256a39c44d7357b26bbaaa END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Strategic Media Insights on Video-on-Demand (VoD) Platforms through Graph Analytics DESCRIPTION:Authors - Ghanem Ghanem Binhamooda AlDhaheri\, Khalifa Mohamed Abdulla Alansi\, Hazza Meqbel Ali Alameri\, Gurdal Ertek\, Ananth Chiravuri Abstract - In today’s digital entertainment landscape\, video-on-demand (VoD) streaming platforms are essential for accessing a broad range of content. This study examines the content of extensive media catalogs available on some of the major streaming platforms\, namely Amazon\, Apple\, Disney\, HBO\, Netflix\, and Paramount. We used a structured dataset and custom-developed a graph analytics methodology that provided a thorough analysis of the data. The sample collection of algorithmically generated graph visualizations help draw basic and in-depth insights\, targeted to support informed decision-making for content creators\, platform managers\, and viewers alike. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:4a089c2a4be7eda0a63223610c7e10b6 URL:http://5thworldconferenceoninformations.sched.com/event/4a089c2a4be7eda0a63223610c7e10b6 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:The 'Grammarly Effect': A Mixed-Methods Study on the Impact of Instantaneous AI Feedback on Student Writing Anxiety and Revision Processes DESCRIPTION:Authors - Kinjal Bhatia Abstract - The integration of AI-powered writing assistants like Grammarly into academic life has fundamentally altered the writing landscape. While these tools provide immediate feedback\, their influence on the psychological and procedural aspects of student writing is not well understood. This paper introduces the "Grammarly Effect\," examining it through a sequential explanatory mixed-methods study. The research investigated how real-time AI suggestions affect the writing anxiety and revision habits of undergraduate students. In the quantitative phase (N=124)\, a quasi-experimental de-sign using pre- and post-task surveys found a significant decrease in anxiety associated with surface-level correctness (e.g.\, grammar\, spelling). However\, the qualitative phase\, involving think-aloud protocols and interviews with a subset of students (n=15)\, revealed a more nuanced situation. While anxiety over superficial errors di-minished\, a reliance on the tool fostered a different anxiety related to authorial originality and self-trust. Analysis of revision behaviors showed a consistent pattern of uncritical acceptance of AI suggestions\, prioritizing surface-level fixes over deep\, rhetorical engagement. The study concludes that the "Grammarly Effect" is a paradoxical phenomenon\, highlighting a critical need for pedagogical approaches that foster AI literacy\, empowering students to use these tools as aids rather than oracles. CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:838e5d3e663d473fe56457af05abd55a URL:http://5thworldconferenceoninformations.sched.com/event/838e5d3e663d473fe56457af05abd55a END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:A Survey on Image Forgery Detection Techniques Using Error Level Analysis and Convolutional Neural Networks DESCRIPTION:Authors - D. S. Vangao\, Pallavi Khatri Abstract - Image forgeries have become much more common due to the widespread use of sophisticated digital image manipulation tools\, which makes it difficult to independently confirm authenticity in domains like social media\, digital forensics\, and journalism. This survey study paper offers a thorough analysis of the most recent methods for identifying image modifications including copy-move and splicing forgeries\, with an emphasis on combining Convolutional Neural Networks (CNNs) with Error Level Analysis (ELA). We evaluate important approaches from recent literature based on their architectures\, datasets\, and performance metrics. We do so via methodically analyzing both contemporary deep learning techniques and traditional methods that rely on handcrafted features. Our investigation shows that hybrid ELA-CNN techniques routinely beat alternative techniques\, attaining accuracy rates exceeding 90% on common datasets such as CASIA. More reliable\, real-time solutions are required\, nevertheless\, as problems like identifying subtle tampering and increasing computational effectiveness continue to arise. We wrap up by discussing the present state of the field's limits and potential avenues for future research in digital image forensics. CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:10cd677a4068d7b0ca948fdfe36ce8f7 URL:http://5thworldconferenceoninformations.sched.com/event/10cd677a4068d7b0ca948fdfe36ce8f7 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Analysing Current Cyber Threats using the Advanced Statistical Techniques DESCRIPTION:Authors - Chethana R.M.\, S.P. Manikandan Abstract - Organisations around the world face never-before-seen difficulties as a result of the quickly changing cybersecurity landscape\, which calls for advanced analytical techniques to recognise and anticipate threat trends. In order to analyse current cyberthreats and their organisational impact\, this study uses sophisticated statistical techniques such as ANOVA\, regression analysis\, machine learning classification\, and clustering algorithms. We examine threat distribution patterns\, financial impact correlations\, and predictive modeling capabilities for ten key threat categories malware\, phishing\, social engineering\, ransomware\, insider threats\, supply chain attacks\, DoS/DDoS attacks\, zero-day exploits\, credential theft\, and AI-powered attacks by thoroughly analysing 360 cyber security incidents that occurred across several Indian cities between 2019 and 2024. The most significant predictor of financial impact\, according to our statistical analysis\, is incident type (F=4.58\, p CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:d2038eeeb60d35cadb22d372403a18ed URL:http://5thworldconferenceoninformations.sched.com/event/d2038eeeb60d35cadb22d372403a18ed END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Enhancing Query Understanding Using Deep Contextual Embeddings in Information Retrieval Systems DESCRIPTION:Authors - GGS Pradeep\, Thrilok. Kolla\, Rajesh Sharma R\, Akey Sungheetha\, U Ananthanagu\, Pellakuri Vidyullatha Abstract - This paper outlines a holistic framework for improving query comprehension in information retrieval (IR) systems through deep contextual embeddings. Using Sentence-BERT\, we transform the queries and documents into dense semantic representations and then calculate cosine similarity for the relevance measure. We especially emphasize interpretability by adding various statistical and visualization techniques\, like heatmaps\, KDE plots\, UMAP projection\, dendrograms\, and box plots\, to identify and analyze latent semantic patterns and keep close tabs on the inner workings of how different documents relate to such varied query formulations. We also follow an avenue of the interquartile dispersion and distributional behavior of similarity scores to understand the embedding consistency and discriminative power. This methodology\, therefore\, encompasses both retrieval accuracy and explainability as it provides visible insights into improving query reformulation\, semantic search\, and content recommendation. Experimental visualizations have further demonstrated their effectiveness towards deep semantic alignment\, especially during the processing of complex multi-topic corpora. The abstract is technically solid and easily comprehensible because it is rationally structured and clearly states the research’s methodology\, instruments\, and objectives. CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:ac08fe96622ab4aea9d74371256ae18c URL:http://5thworldconferenceoninformations.sched.com/event/ac08fe96622ab4aea9d74371256ae18c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Evolutionary Multi-Objective Optimization of Neuro-Fuzzy Systems in Non-Stationary Time Series Forecasting DESCRIPTION:Authors - GGS Pradeep\, Thrilok. Kolla\, U Ananthanagu\, Akey Sungheetha\, Rajesh Sharma R Abstract - Predicting non-stationary time series is still a tough nut to crack: the statistical properties may vary\, and so will the temporal dynamics. In this context\, a robust and interpretable approach involving the integration of a Takagi–Sugeno neuro-fuzzy inference system and evolutionary multi-objective optimization is proposed. The NSGA-II optimization procedure minimizes prediction accuracy alongside model complexity\, evolving the fuzzy rule base and membership parameters and the linear consequents. Contrary to the conventional opaque models\, a neuro-fuzzy architecture affords some degree of transparency\, letting one see how the functional temporal patterns have been learned. Results of the experiments conducted demonstrate the ability of the system to adapt to structural changes in the data\, with a corresponding better capability of reducing residual errors and increasing model compactness using a synthetic non-stationary dataset. Further\, residual oscillations and fuzzy rule surfaces\, alongside the convergence behavior and the Pareto optimality\, present powerful evidence in support of the proposed model’s effectiveness and interpretability. The proposed framework represents a potent alternative for real-time adaptive forecasting in dynamic environments where precision and explainability are both crucial. Simulated non-stationary time series will be good enough to justify the approach of lag-embedding. Thoughtful integration of interpretable fuzzy logic and adaptive learning via evolutionary optimization would strengthen the contribution. CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:32475ca7ef0a2d141ad330cecb589499 URL:http://5thworldconferenceoninformations.sched.com/event/32475ca7ef0a2d141ad330cecb589499 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Exploring the potential of 5G: A new era in wireless communication DESCRIPTION:Authors - Ritu Raut\, Sudhir Agarmore Abstract - The kick to stride the new era in wireless communication begins once 5G technologies holding the promises of speeds previously unheard of and extremely low latency with the capacity to connect a large number of devices at once [4]. This article reviews the potential of 5G in transforming such industries as healthcare\, driverless cars\, smart cities\, and the Internet of Things. It discusses enabling technologies such as millimeter waves\, massive MIMO (Multiple Input Multiple Output)\, and network slicing [1]\, among others\, and also its infrastructure\, security\, and the possibility of availability of the frequency spectrum. For this purpose\, this research aimed to provide an inclusive overview of how this new generation of wireless technology may impinge upon the future of worldwide communication and connectivity by assessing both the benefits and challenges that emanate from 5G. CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:a4bf3b0a3a443eefd9ee2deee75c6b5f URL:http://5thworldconferenceoninformations.sched.com/event/a4bf3b0a3a443eefd9ee2deee75c6b5f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Exposing Digital Deception: Evaluating the Power of Image Forensics Tools DESCRIPTION:Authors - D. S. Vangao\, Pallavi Khatri\, Diya Khatri Abstract - In the digital age\, the proliferation of image manipulation has raised significant concerns regarding the authenticity and integrity of visual content. This study\, explores the critical role of image forensic tools in detecting digital forgeries and ensuring the credibility of photographic evidence. A comprehensive evaluation of a range of widely used image forensic tools—including but not limited to FotoForensics\, JPEG snoop\, Izitru\, Forensically\, and Amped Authenticate—assessing their performance in identifying various types of tampering\, such as splicing\, cloning\, resampling\, and compression artifacts is done in this work. Each tool is evaluated on the basis of criteria such as detection accuracy\, supported forgery type\, user interface\, automation capabilities\, and analysis depth. The comparative analysis reveals strengths and limitations unique to each tool\, offering insights into their suitability for different investigative scenarios. Our findings highlight that no single tool excels universally\; rather\, a combination of tools often yields more reliable results. This study underscores the necessity for cybersecurity professionals\, digital investigators\, and media analysts to adopt a multitool strategy for robust image authentication. CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:70dfed75ab75e0b72da63a8703341c4e URL:http://5thworldconferenceoninformations.sched.com/event/70dfed75ab75e0b72da63a8703341c4e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Fuzzy-Neural Hybrid Models for Early Detection of Neurodegenerative Disorders Using Multimodal Medical Data and Temporal Pattern Analysis DESCRIPTION:Authors - GGS Pradeep\, Thrilok. Kolla\, Rajesh Sharma R\, Akey Sungheetha\, N Vijayalakshmi\, Pellakuri Vidyullatha Abstract - The early identification of neurodegenerative diseases\, like Alzheimer’s and Parkinson’s disease\, is crucial for their management\, although difficult due to subtle\, heterogeneous\, and evolutionarily conditioned clinical patterns. In this paper\, we present a fuzzy-neural hybrid that incorporates the beneficial properties of fuzzy inference systems and temporal deep learning toward improved early diagnosis. Our model analyzes longitudinal multimodal medical data (neuroimaging and clinical scores)\, combining fuzzy rule-based feature encoding with Long Short- Term Memory (LSTM) networks for temporal pattern extraction. Interpretability is provided by assigning Gaussian membership functions\, while the LSTM component encodes the dynamics of disease progression. The proposed system is validated on synthetic and benchmark datasets\, showing robust classification performance and excellent temporal tracking of patient trajectories. Interpretations of internal representations are provided through visualizations such as confusion matrices\, t-SNE embeddings\, and 3D PCA trajectories. The results indicate that the hybrid approach provides both powerful predictions and transparent operation\, making it an excellent option for clinical decision support in neurodegenerative diagnostics. The authors propose a hybrid diagnostic system that uses Gaussian fuzzy membership functions for interpretable feature encoding and LSTM networks for temporal sequence modeling of multimodal medical data. The authors validated their method with synthetic data as well as benchmark datasets\, achieving perfect binary classification in their experimental results. CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:bc52e9011981cdf39cee054fd1a48563 URL:http://5thworldconferenceoninformations.sched.com/event/bc52e9011981cdf39cee054fd1a48563 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Green Digital School Management as Technology-Driven Strategies for Achieving Sustainable and Eco-Friendly School Governance DESCRIPTION:Authors - Agus Timan\, Maisyaroh\, Maulana Amirul Adha\, Indra Lesmana\, Anabelie Villa Valdez\, Arum Sri Banowati Abstract - The urgency of climate change\, environmental degradation\, and the need for sustainable development has placed education at the forefront of global transformation. As schools evolve into eco-conscious institutions\, there is growing interest in integrating digital technologies to enhance sustainability-driven governance. This has led to the emergence of Green Digital School Management (GDSM)\, a model that synergizes environmental responsibility with technology-based school leadership. This study aims to systematically explore the core com-ponents\, implementation challenges\, and effective strategies of GDSM by con-ducting a Systematic Literature Review (SLR) based on PRISMA guidelines. An initial pool of 892 articles was screened\, 87 high-quality studies were selected for thematic analysis. The findings indicate that GDSM encompasses digital environmental policies\, IoT-based monitoring\, and participatory platforms that engage school communities in green practices. Despite significant barriers\, including infrastructure gaps\, limited digital-environmental literacy\, and policy frag-mentation\, several innovative strategies have emerged\, such as digital teacher training\, cross-sector partnerships\, and gamified environmental education tools. This review contributes to the conceptual development of GDSM and provides actionable recommendations for policymakers\, educators\, and technology providers seeking to build smart\, green\, and sustainable school ecosystems. CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:3f58011ab39b067c4349b68feea64e66 URL:http://5thworldconferenceoninformations.sched.com/event/3f58011ab39b067c4349b68feea64e66 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:New Method to Construct a Database and Design a Business Process from Intuitional Document Using Generative AI DESCRIPTION:Authors - Tsunenori Inakura\, Shotaro Imai\, Kunihiko Takamatsu\, Sayaka Matsumoto\, Masao Mori Abstract - Institutional Research (IR) in universities needs data from many different systems\, but it is often hard to know what data is stored and where. To solve this\, it is important to design both databases and business processes together. In this study\, categorical databases\, ontology logs (ologs)\, and event driven process chains (EPCs) are used to connect institutional documents with data and process design. Ologs describe concepts and their functional relations in a formal but also readable way\, while EPCs show how events and functions go step by step in the real processes. Generative AI was used to support both tasks. The AI helps to read documents\, to extract concepts and functions\, and to check consistency. By comparing ologs and EPCs\, both sides can be improved and give a unified view of data and processes. This makes it possible to design information systems for IR with more consistency and less effort. CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:2cbedd291471bf993cd50c033bac7478 URL:http://5thworldconferenceoninformations.sched.com/event/2cbedd291471bf993cd50c033bac7478 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261019T220000Z DTEND:20261020T000000Z SUMMARY:Tomato Ripeness Evaluation through Cutting-Edge Deep Learning Models DESCRIPTION:Authors - Vijay Siva\, Vijayakumar Ponnusamy Abstract - According to the United Nations\, global population will rise from 7 billion currently to 9 billion in 2050. The world will need far more food\, and agriculture will face remarkable pressure to meet demand. Emerging application of deep learning in agriculture includes ripeness detection of tomato which harvest tomato in appropriate time and prevents rotten of tomato. This saves the framer from loss. Tomato was classified as ripe\, half-ripe\, and unripe\, based on maturity stage of fruit. Various deep learning methodologies were analyzed for maturity detection of tomato. Multimodal approach for maturity detection is suggested for enhanced accuracy in ripeness detection. CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:362334dd1b6c935d661451014b434108 URL:http://5thworldconferenceoninformations.sched.com/event/362334dd1b6c935d661451014b434108 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000000Z DTEND:20261020T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:97b129aa77943d1d718cf48c3f93bf6c URL:http://5thworldconferenceoninformations.sched.com/event/97b129aa77943d1d718cf48c3f93bf6c END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000000Z DTEND:20261020T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:0c940abf285ee0ed2d203767a4078e05 URL:http://5thworldconferenceoninformations.sched.com/event/0c940abf285ee0ed2d203767a4078e05 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000000Z DTEND:20261020T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:5a69d874f697ee72bd32d83129dd8636 URL:http://5thworldconferenceoninformations.sched.com/event/5a69d874f697ee72bd32d83129dd8636 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000000Z DTEND:20261020T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:b5aea8e88267c716ed4b6992e334d922 URL:http://5thworldconferenceoninformations.sched.com/event/b5aea8e88267c716ed4b6992e334d922 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000000Z DTEND:20261020T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:3347f36770b1c2fb2a15f62b8de3084e URL:http://5thworldconferenceoninformations.sched.com/event/3347f36770b1c2fb2a15f62b8de3084e END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000000Z DTEND:20261020T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:36cbd6898c52224a8571181d73b00ed1 URL:http://5thworldconferenceoninformations.sched.com/event/36cbd6898c52224a8571181d73b00ed1 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000000Z DTEND:20261020T000200Z SUMMARY:Session Chair Concluding Remarks DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:f313c8c4fe594f06cd141c78c6c6e498 URL:http://5thworldconferenceoninformations.sched.com/event/f313c8c4fe594f06cd141c78c6c6e498 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000200Z DTEND:20261020T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9A LOCATION:Virtual Room A\, Bangkok\, Thailand SEQUENCE:0 UID:bde4fc0a31dc06fc3d9ffe01e1f83887 URL:http://5thworldconferenceoninformations.sched.com/event/bde4fc0a31dc06fc3d9ffe01e1f83887 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000200Z DTEND:20261020T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9B LOCATION:Virtual Room B\, Bangkok\, Thailand SEQUENCE:0 UID:38d2ae0c4978944330e9726a03a18f75 URL:http://5thworldconferenceoninformations.sched.com/event/38d2ae0c4978944330e9726a03a18f75 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000200Z DTEND:20261020T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9C LOCATION:Virtual Room C\, Bangkok\, Thailand SEQUENCE:0 UID:e55b39054eb9b28a7b8a580c23b0da2f URL:http://5thworldconferenceoninformations.sched.com/event/e55b39054eb9b28a7b8a580c23b0da2f END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000200Z DTEND:20261020T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9D LOCATION:Virtual Room D\, Bangkok\, Thailand SEQUENCE:0 UID:eca47716a9d92d4ea63c28433e73b692 URL:http://5thworldconferenceoninformations.sched.com/event/eca47716a9d92d4ea63c28433e73b692 END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000200Z DTEND:20261020T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9E LOCATION:Virtual Room E\, Bangkok\, Thailand SEQUENCE:0 UID:63c8e6b1f1d791ffb93f7d2836a387cf URL:http://5thworldconferenceoninformations.sched.com/event/63c8e6b1f1d791ffb93f7d2836a387cf END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000200Z DTEND:20261020T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9F LOCATION:Virtual Room F\, Bangkok\, Thailand SEQUENCE:0 UID:52ceb76285ef2ee227d37048ea08296b URL:http://5thworldconferenceoninformations.sched.com/event/52ceb76285ef2ee227d37048ea08296b END:VEVENT BEGIN:VEVENT DTSTAMP:20260820T134456Z DTSTART:20261020T000200Z DTEND:20261020T000500Z SUMMARY:Session Closing and Information To Authors DESCRIPTION: CATEGORIES:VIRTUAL ROOM 9G LOCATION:Virtual Room G\, Bangkok\, Thailand SEQUENCE:0 UID:127b9959d2e6286d06f1b0c702e291c6 URL:http://5thworldconferenceoninformations.sched.com/event/127b9959d2e6286d06f1b0c702e291c6 END:VEVENT END:VCALENDAR