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This proceedings book offers a refined and comprehensive exploration of cutting-edge advancements in communication networks, computational intelligence, and smart applications, seamlessly blending theoretical insights with practical solutions. Each paper outlines objectives, challenges, proposed solutions, and key findings, enabling swift comprehension of complex topics. By adopting a problem-solving approach and including case studies, the book effectively demonstrates the application of advanced techniques in domains such as industry, healthcare, and smart cities. Addressing the demands of an evolving digital landscape, it highlights emerging technologies like artificial intelligence (AI), the Internet of Things (IoT), and autonomous systems, ensuring its relevance to both current challenges and future innovations. Covering a wide spectrum of topics, including network security, AI applications, IoT ecosystems, and smart technologies, the book serves as a comprehensive resource for understanding the innovations shaping the future of communication and computing. Targeted at graduate students, researchers, professors, and industry professionals, it functions as both an educational tool and a reference guide for those seeking to remain at the forefront of technological advancements. Featuring state-of-the-art research contributions, the book introduces new techniques, algorithms, and solutions to real-world challenges, complemented by structured insights into objectives, problems, and results. Practical applications are brought to life through successful case studies in key areas like smart cities and healthcare, illustrating the tangible impact of these innovations. With contributions reviewed by a distinguished editorial team of leading researchers, engineers, and academics, the book ensures credibility, academic rigor, and relevance. By blending theoretical depth, practical utility, and expert validation, this proceedings book is an indispensable resource for navigating the rapidly evolving fields of computing and communication technologies, equipping readers with the knowledge and tools to excel in an increasingly digital and interconnected world.
Inhaltsverzeichnis
.- 1 Enhancing the Prediction and Classification Performance of Alzheimer Diseases using Voting Rule of Ensemble Learning.- 2 Deep Learning based AI Diagnostic Open API Architecture for Healthcare Applications.- 3 Mathematical Model-Driven Multi-Channel Matrix-based ECG Signal Features Transformation: Impact on Deep Learning Classification of Cardiac Arrhythmia.- 4 Enhancing Lung Disease Detection using DCGAN-Augmented Chest X-Ray Images for CNN Training.- 5 Transforming Multi-Lead ECG Signals into Gramian Angular Field Images for Enhanced Cardiovascular Disease Classification with Hybrid Deep Learning Models: A Case Study on Arrhythmia, etc.
