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
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.
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.
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.
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.
Authors - Azran Ahmad, Naziffa Raha Md. Nasir, Azlan Yusof, Aslina Mat Asli, Fazlina Mohd Ali, Surya Sumarni Hussein Abstract - 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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
