Proceedings of the International Conference on Advanced Communications with Modern Circuits and Systems Technologies
Description
This book provides an up-to-date overview of recent advances in advanced communications, modern circuits, and systems technologies, addressing key challenges and emerging trends in contemporary electrical and electronic engineering.
Bringing together selected, peer-reviewed contributions from the International Conference on Advanced Communications with Modern Circuits and Systems Technologies (ACMCST'25), the book covers a broad spectrum of topics including intelligent and connected systems, embedded and energy systems, power electronics, artificial intelligence for engineering applications, and next-generation communication technologies. Organized by the MISET Research Team, the conference gathered researchers and professionals from academia and industry to exchange ideas and present innovative solutions.
This book is intended for researchers, graduate students, engineers, and practitioners seeking a comprehensive reference on modern electronic systems, intelligent technologies, and advanced communication solutions.
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Content
Cross-Shaped Patch Antenna with Parallelogram Exten-sions for IoT and Mobile Applications.- User Perception-Driven Energy Scheduling: A Human-Centered Strategy for Moroccan Households.- Optimal adaptive neural network based PID using evolutionary strategy optimization for autonomous vehicle.- Skin Disease Classification Using Transfer Learning techniques.- Modeling of an energy management system for AC-DC microgrid using rule-based strategy.- Photocatalytic Potential of Double Perovskite Hydrides Cs2CaCdH6 and Rb2CaCdH6: A Continuation of a DFT-Based Study.- Isolated Sign Recognition from Pose Sequences: An Empirical Evaluation of ML and DL Models.- Comparative Evaluation of LCL Filter Damping Strategies in Bidirectional EV Onboard Chargers.- TUBER-ENSEMBLE: An Ensemble of Deep Convolutional Neural Networks for Tuberculosis Detection from Chest X-rays.- A Deep Learning-Based System for Pulmonary Disease Classification Using Chest X-Rays and Respiratory Sounds.
