Weiwei Jiang – författare

The rapid digital transformation of healthcare has created unprecedented opportunities for improving patient outcomes, operational efficiency, and accessibility of medical services. At the same time, the increasing reliance on connected devices, cloud infrastructures, and data-driven decision-making has introduced significant challenges related to security, privacy, trust, and regulatory compliance. Emerging technologies such as artificial intelligence, machine learning, blockchain, federated learning, post-quantum cryptography, and neuromorphic computing are playing a pivotal role in addressing these challenges while enabling the next generation of intelligent healthcare systems. Their potential extends from secure data sharing and privacy-preserving analytics to predictive diagnostics, personalized medicine, remote patient monitoring, and autonomous healthcare applications.The book is intended for undergraduate and postgraduate students, researchers, academicians, healthcare professionals, cybersecurity practitioners, AI engineers, data scientists, and industry experts working in the fields of artificial intelligence, cybersecurity, healthcare informatics, medical data analytics, blockchain technologies, Internet of Things (IoT), and intelligent healthcare systems. It also serves as a valuable reference for professionals seeking to understand the practical implementation of advanced computational and security technologies in modern healthcare environments.Key Features: Explores novel cutting-edge techniques for the protection of health data.Provides a better understanding and analysis of the telemedicine applications with these techniques.Discusses the integration of intelligent systems with cutting edge techniques for e- health care management.Reviews the development of the different state of the art techniques for social good.Examines how the developed techniques will result in better remote health care services with improved and efficient diagnosis.

A comprehensive guide to 6G wireless systems and AI-powered smart antennas, this book explores how artificial intelligence can transform antenna design, optimize, and deploy next-generation networks. Readers will gain practical insights into integrating AI with advanced antenna technologies for ultra-fast, energy-efficient, and adaptive 6G networks. It combines theory with hands-on simulation, real-world use cases, and open-source resources, covering topics like beamforming, RIS, terahertz antennas, and edge AI.Key Features:Effectively bridges the gap between AI theory and practical smart antenna design for 6G networks.Comprehensively covers terahertz antennas, RIS, edge AI, and real-world deployment scenarios.Includes supplementary materials such as Python/MATLAB code, CST/HFSS simulation files, and curated datasets via a dedicated GitHub repository for reproducibility and practical learning.Ideal for graduate students, researchers, and industry professionals in wireless communications, antenna engineering, and AI applications.Also suited for instructors developing advanced courses on 6G, IoT, and smart antenna systems.

Cyber-Physical Resilience: Cultivating Symbiotic Architectures Beyond Traditional Control introduces a revolutionary paradigm shift in Cyber-Physical Systems (CPS) design, challenging conventional wisdom that treats physical components as passive elements controlled by computation. Instead, it proposes CPS as symbiotic relationships where cyber and physical elements co-evolve harmoniously, creating inherently resilient systems. Based on three years of international research across multiple sectors, this book delivers both a theoretical foundation and a practical methodology for adaptive systems that thrive amid complexity and uncertainty.The Symbiotic System presents a groundbreaking CPS design approach that transforms traditional hierarchical control into harmonious cyber-physical relationships through five key principles: mutual adaptation (reducing downtime 67%), context-responsive distributed intelligence, selective boundary permeability, co-evolutionary learning, and adaptive strengthening. The book's empirical studies demonstrate these systems achieve 43% greater energy efficiency and 78% faster recovery than conventional approaches. This comprehensive framework integrates engineering, computer science, and socio-technical theory, with the author's validated models quantifying performance advantages under various stress conditions across manufacturing, energy, agriculture, and healthcare sectors.This book targets an international audience at the technology development-implementation intersection, including systems engineers, computer scientists, and automation specialists seeking resilient infrastructure approaches. Academic researchers will appreciate its theoretical depth and methodological rigor, while technology strategists and policymakers will find evidence-based guidance for regulatory frameworks.