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24 articles for “Web 1.0”
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A study on order of authorship to discover the degree of authorship
Abstract: Bibliographical details of research papers of faculty members and research scholars of University of Mysore covered in Web of Science were analyzed to identify the order of authorship and to discover the degree of authorship. Findings of the study reveal that the majority of the authors in overall publications belong to University of Mysore representing 55.81% and the remaining 44.19% of authors from different Universities and Institutions across the world …
Published in Journal of Advancements in Library Sciences · Vol. 5, Issue 3, 2018 · pp. 1–4 Read article
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A Bio-Bibliometric Analysis of Dr. Suprabhat Mukherjee, a Pioneer of Innovative Approach for Colon Cancer Treatment Using Fluids of Custard Apple (Annona Reticulata) Seeds
Abstract: Dr. Suprabhat Mukherjee, associated with Kazi Nazrul University (KNU), West Bengal, India, is a globally recognized immunobiologist, and a celebrated Indian scientist cum researcher for his contributions in Corona Vaccine, and Colon Cancer. This study covers his 154 research publications in various forms of published documents during 2010–2024. Personal information and data about research contributions, have been collected from the bibliographic databases like Google Scholar (GS), Research Gate (RG), and …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 1, 2025 · pp. 50–68 Read article
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Smart SwitchBoard With Auto Safety Control
Abstract: The Intelligent Smart Switch Board, with Automatic Safety Control, is designed as an IoT-based intelligent power management system to enhance electrical safety by providing the user with real-time monitoring of electrical energy consumption and the ability to remotely control electrical loads in their home or small industrial facility. The Smart Switch Board is built around an ESP32 Microcontroller and uses a PZEM-004T Energy Meter Module to accurately measure voltage, current, …
Published in Journal of Microcontroller Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 16–23 Read article
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A Privacy-Preserving and Performance-Optimized Machine Learning Framework for Personalized E-Commerce User Experience
Abstract: In contemporary e-commerce websites, merchant suggestions are the most outstanding way to boost customer satisfaction and conversion levels. Nevertheless, the growing dependence on user data provokes significant concerns over the protection of privacy and efficiency in computation. In this paper, we have suggested a privacy-preserving and performance-optimized machine learning framework that allows customized e-commerce experiences and protects the sensitive information of users. The framework incorporates the concepts of federated learning …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 2, 2026 · pp. 1–8 Read article