Inventive Communication and Computational Technologies
Description
This book gathers selected papers presented at the 9th International Conference on Inventive Communication and Computational Technologies (ICICCT 2025), held on June 5-6, 2025, at Sree Sakthi Engineering College, Coimbatore, India. The book covers 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 working as a Principal in Sri Ramakrishna College of Engineering, Perambalur, India. He has done his PhD in the Faculty of Information and Communication Engineering from Anna University, Chennai in the year 2013. His research thesis was in the area of Biomedical Signal Processing. He has a total of 30+ years of experience both in industry, teaching and research. He has guided several project works for many UG and PG Students in the areas of Biomedical 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 Referee for many reputed International Journals published by Elsevier, Springer, Taylor and Francis, etc. He has membership in various professional bodies like ISTE, IAENG etc., and has actively involved himself in organizing various international and national level conferences, symposiums, seminars etc.
Dr. George A. Papakostas received the diploma in Electrical and Computer Engineering in 1999, and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas currently serves as a full Professor in the Department of Computer and Informatics Engineering, Eastern Macedonia and Thrace Institute of Technology, Greece. He has (co)authored more than 70 publications in indexed journals, international conferences and book chapters. His research interests include pattern recognition, computer/machine vision, computational intelligence, machine learning, feature extraction, evolutionary optimization, signal and image processing. Dr. Papakostas served as a reviewer in numerous journals and conferences and he is a member of the IAENG, MIR Labs, EUCogIII and the Technical Chamber of Greece (TEE).
Dr. Álvaro Rocha holds Habilitation in Information Science, PhD in Information Systems and Technologies, MSc in Information Management, and BCs in Computer Science. He is Professor of Information Systems and Software Engineering at University of Coimbra, researcher at CISUC (Centre for Informatics and Systems of the University of Coimbra) and a collaborator researcher at LIACC (Laboratory of Artificial Intelligence and Computer Science) and at CINTESIS (Center for Research in Health Technologies and Information Systems). His main research interests are Information Systems Planning and Management, Maturity Models, Information Systems Quality, Online Service Quality, Intelligent Information Systems, Software Engineering, e-Government, e-Health, and Information Technology in Education
Content
Analytical Approach of False Products and Complaint System Development Using Blockchain Technology.- Efficient Korean text classification algorithm based on optimized attention-based LSTM model.- Anomaly Detection in High-Frequency Trading Data: A GNN-TCN Hybrid Approach.- System-Agnostic Fault Detection Using Machine Learning-Based Vibration Analysis.- Video Summarizer Using Audio to Text Conversion and Natural Language Processing.- Integrated Solutions for System Security: Scanning, Password Management, and Incident Response.- A Novel Framework for Fake Visual Content Detection Through Hybrid Intelligent Techniques.- A Real-Time AI-Driven Framework for Personalized Prenatal Nutrition Using Multi-Algorithm Learning and Genetic Insights.- Deep Learning with Augmentation for Accurate Coconut Leaf Disease Classification in Scenarios with Limited Data.- When Large Language Models Meet Customer Feedback.- Lightweight Data Encryption on EdgeAI Platforms.- Implementation of XGBoost time series model for statistical analysis of renewable and traditional fuel energy with future perspective.- Underwater Image Enhancement Hybrid Using Res-UNet Model.- An XLNet-based Deep Reinforcement Learning for Solving the Traveling Salesman Problem.- Analysis of Methods for Detecting Vulnerabilities in Web Servers.- Automatic segmentation of lung lesions from medical imaging.- Comparative Performance Analysis of Machine Learning Models for Agricultural Crop Prediction.- Deep Learning in Healthcare: A Futuristic Approach of Enhancement.- Comparative Analysis of Standard vs. Curriculum-Based Proximal Policy Optimization in High-Dimensional Quadrupedal Locomotion.- Deep Learning for Alzheimer's Disease Classification.- Harnessing the wildlife animal detection using proposed CNN and ResNet50 deep learning model.-Cyber Defense with Predictive Analysis and Compliance Using LSTM and Swarm Intelligence in Indian Cyberspace.- Occluded Face Reconstruction based on GANs for Realistic 3D Avatars in Virtual Reality.- An Optimized Deep Learning Based Framework for Cognitive State Classification Using Brain-Computer Interface Technologies.- Algorithm for conducting information security audits in organizations based on a multilevel model based on graph theory.- End-to-End Air Quality Forecasting with Refined Architecture and Low-Code Big Data Framework.- A Hybrid Deep Learning Framework for Landslide Detection and Severity Analysis.- Harnessing Supervised Machine Learning (ML) Principles for Enhanced Early-Stage Diagnosis of Parkinson's Disease.- PCOS Detection and Classification using Deep Learning Approach.- Improving Water Quality Prediction using Robust Outlier Detection and RankGenForestStacking Classifier Approach.- Blockchain-Enabled Patient Consent System for Secure Healthcare Data Management.- Assessing YouTube Title-Content Alignment using NLP Framework.- Cascaded Energy Management System with ANN Controlled DC Microgrid Systems.- AI Based Malware Detection Using Machine Learning, Random Forest, Extra Tree Algorithms.- SweetPick: Leveraging AI to Predict Apple Sweetness.- Cataract Detection Using Deep Learning Leveraging Fundus and Anterior Eye Images.- Blockchain-Enabled Communication for Sustainable Fashion.- A Multi-layered Architecture for Email Classification.- Integrating OpenCV and Mediapipe.