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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
