The book discusses the latest developments and outlines future trends in the fields of microelectronics, electromagnetics, and telecommunication. It contains original research works presented at the International Conference on Microelectronics, Electromagnetics and Telecommunication (ICMEET 2024), organized by Department of Electronics and Communication Engineering, National Institute of Technology Mizoram, India, during 19–20 December 2024. The book is divided into four volumes, and it covers papers written by scientists, research scholars, and practitioners from leading universities, engineering colleges, and R&D institutes from all over the world and shares the latest breakthroughs in and promising solutions to the most important issues facing today’s society.
Forecasting Energy Production at Solar Substations Using LSTM Networks
Optimized by Adaptive Metaheuristics.- Various Power Efficient Adiabatic
Logics for Low Power VLSI Circuits.- Optimizing Local Storage by Implementing
Hash-Based Deduplication to Reduce File Size and Improve Storage Efficiency.-
An Overview of Underwater Optical, Acoustic, and Hybrid Modems: Design
Challenges, Recent Developments, and Obstacles in Underwater Communication.-
Memory based Parallel FFT Architecture for High Speed Applications.-
Evaluating Frequency and Predication Based Word Embedding Models for Natural
Language Processing.- Real Time Driver Drowsiness Detection for Safe
Driving.- Implementation of SecureNet AdaptShield for Network Security using
GNS3.- Deep Learning for Parkinsons Detection Through DatScan imaging and
voice Data.- A Distinctive review of Brushless Doubly Fed Reluctance Machine
(BDFRM) based Wind turbine system.- Alzhiemer Disease Detection using
MobileNetV2 Integrated with Vision Transformer.- ANN Based Loss Estimation of
Power Networks at Different Load Variations.- Multimodal Diagnostics for
Wilsons Disease Bridging Object Detection, Large Language Model and Speech
Synthesis.- A Robust Heart Disease Prediction System using SVM Classifier
Deep Learning.- Hybrid Machine Learning Model for Fault Detection in
Electrical Grids.- Efficient Flood Detection via Deep Ensemble Learning
Methods.- Enhanced Crop Classification Using Remote Sensing and Machine
Learning Techniques: A Study Leveraging Sentinel-1, Sentinel-2, and Google
Earth Engine.- Dual Tuned Absorber and Linear to Cross Polarization Converter
using Graphene and Vanadium Dioxide Metasurface.- Predicting Cardiovascular
Syndrome Using Machine Learning Techniques: A Comparative Analysis.-
Optimizing Traffic Flow in Traffic Signal Controlling System with AI ML.-
Detection of Cardiovascular Disease by ECG Images Using LSTM.- DeepMango:
Understanding and Analysis of Deep Models in Mango Leaf Disease Detection.-
Smart Agriculture: Real-Time Plant Disease Classification with CNN and
ResNet.- Enhanced CNN Model Techniques for Classification of Brain Tumor and
Approaches.- A Hybrid Algorithm to Predict Parkinson's Disease Using Freezing
of Gait.- Quantum Enhanced Vickrey Clarke Groves Auction for Optimal Resource
Allocation in Mobile Adhoc Networks.- The Role of Artificial Intelligence in
Modernizing Arbitration: Opportunities and Challenges.- Chronic Kidney
Disease Prediction: A Study of Encrypted Datasets.- VisionGrip:
Revolutionizing Motor Functionality in Carpal Tunnel Syndrome and Radial
Nerve Palsy Patients Through EOG-Controlled Robotic Claw.- Advancing
Underwater Trash Detection: A Hybrid Approach with ESRGAN and YOLOv11.-
Reinforcement learning-based traffic signal control.- Lora-IoT based
efficient data prediction model for agricultural applications using Deep
Maxout Neural Network.- Machine Learning for Optical Network: A Survey.-
Adoption Strategies and Perceptions of Data Mining Techniques Among Data
Scientists: An Exploratory Study.- Assessing Public Awareness and
Vulnerability to Crypto currency Scams: A Qualitative Study.- Diabetes
prediction using IoT and Bagging Classifier.- Skin Disease Detection Using
Resnet-50 and Machine Learning Based Enhanced Random Forest Approach.-
IoT-Enhanced Predictive Models for Brain Stroke Care using Machine Learning.-
Pick and Place Robotic Vehicle with Arm.- A Machine Learning Approach for
Early Detection of Diabetes.- Deep learning-based hand gesture classification
via sequential and ensemble EMG denoising: Devising a potential pathway for
BCI-fostered motor rehabilitation system.- Comprehensive Insights into Deep
Learning Techniques for Biomedical Image Processing.- Sales Prediction for
Solving Food Wastage with Machine Learning Algorithms on French Bakery Shop.-
A Comparative Study of Deep Learning Models for Breast Cancer Diagnosis.-
Fortifying Cloud Security: A Reliable Multi-Level Encryption Framework for
Safeguarding Data.- Fuzzy Logic-Based Recruitment for Software Engineering
Domain: A Modified Mamdani Model.- Enhancing Efficiency and Economic Impact
of Public Transportation in Malaysia through Ubiquitous Computing
Integration.- Enhancing Life Quality for People Who Stutter through an
AI-Driven Interactive Website - Assistance for People Who Stutter (AFPWS).-
Integrating Cloud-based Crowdsourcing and Interactive Learning for Enhanced
Code Smell Identification and Resolution.
Vikrant Bhateja is associate professor in Department of Electronics Engineering, Faculty of Engineering and Technology (UNSIET), Veer Bahadur Singh Purvanchal University, Jaunpur, Uttar Pradesh, India. He is also serving as Head: Computer Sc. Engg. & Information Technology in the same university. He holds a doctorate in ECE (Bio-Medical Imaging) with a total academic teaching experience of 21 years with around 190 publications in reputed international conferences, journals and online book chapter contributions; out of which 40 papers are published in SCIE indexed high impact factored journals. One of his papers published in Review of Scientific Instruments (RSI) Journal (under American International Publishers) has been selected as Editor Choice Paper of the Issue'' in 2016. Among the international conference publications, five papers have received Best Paper Award''. He has been instrumental in chairing/co-chairing around 30 international conferences in India and abroad as Publication/TPC chair and edited 55 book volumes from Springer-Nature as a corresponding/co-editor/author on date. He has delivered nearly 25 keynotes, invited talks in international conferences, ATAL, TEQIP and other AICTE sponsored FDPs and STTPs. He has been Editor-in-Chief of IGI Global--International Journal of Natural Computing and Research (IJNCR) journal from 2017-22. He is guest editor in journals like: Elsevier: Measurement, Springer: Evolutionary Intelligence. He is Senior Member of IEEE and Life Member of CSI. published research has a current h-index of 35 on google scholar.
Zaid Omar (Senior Member, IEEE) received the masters degree in data communications from The University of Sheffield and the Ph.D. degree in electrical engineering from the Imperial College London, in 2012. He is currently an Associate Professor with Universiti Teknologi Malaysia. His research interests include computer vision, medical imaging, and image fusion. Dr. Omar was crowned the best science communicator for FameLab Malaysia 2017-- one of the biggest science communication competitions in the world organised by British Council.
Dr. Anumoy Ghosh has obtained his PhD degree from the Dept. of Electronics and Telecommunication Engineering in IIEST Shibpur in 2018. Since 2014, he is working in the Dept. of Electronics and Communication Engineering in NIT Mizoram and is currently holding the position of Assistant Professor Gr-I. He has 46 publications in reputed SCI journals and international conferences. His research group has 10 PhD scholars working in various domains of microwave and millimeter wave engineering. He has served as a reviewer for various SCI journals under the publications house of IEEE, Wiley, Radioengineering and Taylor & Francis. He has given several expert lectures in various institutes on microwave engineering and awareness about microwave technologies. His research interests include Antennas, MIMO technology, RFID, Microwave Energy Harvesting, Frequency Selective Surfaces and THz technology.
Sarika Shrivastava is B.E. in Electrical Engineering, MBA in Marketing, M. Tech. in Power System and Ph.D. in Engineering. She is Director & Professor, Ashoka Institute of Technology & Management, Varanasi, India. She has got 25 years of academic & research experience. She serves as the Advisor to Uravu Lab in Bengaluru, India. She is Member of Examination Committee and Borad of Studies of AKTU. She is a Fellow of The Institution of Engineers, a member of IEEE & System Dynamics Society. Her research contributions include publications in international journals, conference proceedings, and book chapters. Her research areas are sustainability, leadership, power system operation and control, wind energy technology, electric vehicle technologies, grid integration, and the application of artificial intelligence in healthcare and energy.
