STM Journals Peer-reviewed research from Consortium e-Learning Network

3 publications

  • Published Subscription Review Article

    Leveraging Biosensors for Enhanced Family Dynamics: Strategies for Mental Health and Well-being in the Digital Age

    By Ushaa Eswaran, Vivek Eswaran, Keerthna Murali, Vishal Eswaran

    Abstract: This study investigates the integration of biosensors as innovative solutions for optimizing family dynamics and promoting mental health and well-being in the digital era. By exploring the intersection of biosensor technology with family interactions, communication patterns, and conflict resolution strategies, this study offers practical insights and recommendations for leveraging biosensors to strengthen familial relationships and support individual mental health. Through a multidisciplinary approach, combining psychology, sociology, and biosensor engineering, this …

    Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 9–18 Read article

  • Published Subscription Review Article

    Advancements in Data Structures: Bridging the Gap Between Theory and Real-world Applications

    By Ushaa Eswaran, Vivek Eswaran, Keerthna Murali, Vishal Eswaran

    Abstract: In the rapidly advancing landscape of computer science, this study unfolds a comprehensive exploration of Data Structures, spanning from foundational principles to cutting-edge innovations. Data structures form the backbone of computational processes, and this study aims to dissect and illuminate their pivotal role. Beginning with fundamental concepts such as Arrays, Linked Lists, Stacks, and Queues, the narrative progresses to intricate structures like Trees, Graphs, and Hash Tables. Practical applications in …

    Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article

  • Published Subscription Review Article

    Unveiling Fairness: A Quest for Ethical Artificial Intelligence and Bias Mitigation

    By Ushaa Eswaran, Vivek Eswaran, Keerthna Murali, Vishal Eswaran

    Abstract: Artificial intelligence (AI) systems have become ubiquitous across areas like finance, healthcare, employment, and criminal justice. However, they suffer from issues of unfair bias, lack of transparency, and broad ethical implications impacting vulnerable societal groups disproportionately. This paper reviews key challenges around AI ethics and bias while proposing data-driven guidelines mitigating such algorithmic harms through rigorous statistical testing, predictive modeling ensembles adjusting distortion vectors and AI audits by domain experts …

    Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 28–31 Read article

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