Inventive Communication and Computational Technologies
Description
This book gathers selected papers presented at the 8th International Conference on Inventive Communication and Computational Technologies (ICICCT 2024), held on June 14-15, 2024, at Sree Sakthi Engineering College, Coimbatore, India. The book covers the topics such as Internet of things, social networks, mobile communications, big data analytics, bio-inspired computing, and cloud computing. The book is exclusively intended for academics and practitioners working to resolve practical issues in this area.
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Persons
Dr. G. Ranganathan is working as a principal in Sree Sakthi Engineering College, Coimbatore, India. He has done his Ph.D. in the Faculty of Information and Communication Engineering from Anna University, Chennai, in the year 2013. His research thesis was in the area of bio-medical signal processing. He has a total of 30+ years of experience in industry, teaching, and research. He has guided several project works for many UG and PG students in the areas of bio-medical signal processing. He has published more than 35 research papers in international and national journals and conferences. He has also co-authored many books in electrical and electronics subjects. He has served as a referee for many reputed international journals published by Elsevier, Springer, Taylor and Francis, etc.
George A. Papakostas received the Diploma, M.Sc., and Ph.D. degrees in electrical and computer engineering from the Democritus University of Thrace (DUTh), Greece, in 1999, 2002, and 2007, respectively. Currently, he is a tenured Full Professor with the Department of Informatics, DUTh, Kavala, Greece. He has 15 years of experience in large-scale systems design, as a senior software engineer and a technical manager. He is also the Head of the Machine Learning and Vision (MLV) Research Group. He has (co)authored more than 250 publications in indexed journals, international conferences, and book chapters, one book (in Greek), two edited books, and eight journal special issues. His publications have more than 4900 citations with H-index 38 (Google Scholar). His research interests include machine learning, computer/machine vision, pattern recognition, and computational intelligence. He is a member of the IAENG, MIR Labs, EUCogIII, and the Technical Chamber of Greece (TEE). He served as a reviewer for numerous journals and conferences.
Dr. Yong Shi currently is working as an associate/tenured professor of Computer Science at Kennesaw State University, and director/coordinator of the Master of Computer Science. He is the responsible for directing the Master of Computer Science program and reviewing applications for the Master of Computer Science. He has published more than 50 articles in national and international journals. He acted as an editor, reviewer, editorial board member, and program committee member in many reputed journals and conferences. His research interest includes cloud computing, big data, and cybersecurity.
Content
Enhancing Attack Detection on IoT Devices using a Hybrid Deep Learning Model.- Analysis of Routing Protocols in VANETs with Different Pause Times.- Performance Insights of Attention-free Language Models in Sentiment Analysis: A Case Study for E-commerce Platforms in Vietnam.- An AutoML Approach Integrated with Live Weather Data in Rain Forecasting System (RFS).- Decentralized Identity Management using Self-Sovereign Identity Approach through Blockchain.- Stock Price Prediction Model using Enhanced LSTM and Arima.- Prefetching Mechanism for Distributed Cache Architecture: Trends and Challenges.- A Concise Review of Crop Disease Identification: Integrating Conventional and Deep Learning Feature Extraction for Effective Diagnosis and Mitigation Strategies.- Fortifying Healthcare Data Security in Cloud Environments.- Review on the Enhancement of 5G Communications using LEO Satellites.- Design and Implementation of a Python-Based GUI Tool for Eye-Hand Coordination Analysis.- Detection of Strabismus using Convolutional Neural Network based Classification Models.- Video Anomaly Detection using Liquid Neural Networks.- A Blockchain Solution to Counterfeiting in the Semiconductor Supply Chain.