Chandra Singh – författare

MODELING and OPTIMIZATION of OPTICAL COMMUNICATION NETWORKS Optical networks are an integral part of many of the technologies that we use every day. It is a constantly changing and evolving area, with new materials, processes, and applications coming online almost daily. This book provides a basis for discussing open principles, methods and research problems in the modeling of optical communication networks. It also provides a systematic overview of the state-of-the-art research efforts and potential research directions dealing with optical communication metworks. It also simultaneously focuses on extending the limits of currently used systems encompassing optical and wireless domains and explores novel research on wireless and optical techniques and systems, describing practical implementation activities, results and issues. A handbook on applications for both academia and industry, this exciting new volume includes detailed discussions on real-world case studies on trends and emerging technologies associated with modeling of optical communication networks. This book also describes several numerical models and algorithms for simulation and optimization of optical communication networks. Modeling and optimization presents several opportunities for automating operations and introducing intelligent decision making in network planning and in dynamic control and management of network resources, including issues like connection establishment, self-configuration, and self-optimization, through prediction and estimation by utilizing present network state and historical data. It focuses on extending the limits of currently used systems encompassing optical and wireless domains, and explores the latest developments in applications like photonics, high speed communication systems and networks, visible light communication, nano-photonics, wireless, and MIMO systems.

SELF-POWERED CYBER PHYSICAL SYSTEMS This cutting-edge new volume provides a comprehensive exploration of emerging technologies and trends in energy management, self-powered devices, and cyber-physical systems, offering valuable insights into the future of autonomous systems and addressing the urgent need for energy-efficient solutions in a world that is increasingly data-driven and sensor-rich. This book is an attempt to aim at a very futuristic vision of achieving self-powered cyber-physical systems by applying a multitude of current technologies such as ULP electronics, thin film electronics, ULP transducers, autonomous wireless sensor networks using energy harvesters at the component level and energy efficient clean energy for powering data centers and machines at the system level. This is the need of the hour for cyber-physical systems since data requires energy when it is stored, transmitted, or converted to other forms. Cyber-physical systems will become energy hungry since the industry trend is towards ubiquitous computing with massive deployment of sensors and actuators. This is evident in using blockchain technologies such as Bitcoin or running epochs for artificial intelligence (AI) applications. Hence, there is a need for research to understand energy patterns and distribution in cyber-physical systems and adopt new technologies to transcend to self-powered cyber-physical systems. This book explores the recent trends in energy management, self-powered devices, and methods in the cyber-physical world. Written and edited by a team of experts in the field, this book tackles a multitude of subjects related to cyber physical systems (CPSs), including self-powered sensory transducers, ambient energy harvesting for wireless sensor networks, actuator methods and non-contact sensing equipment for soft robots, alternative optimization strategies for DGDCs to improve task distribution and provider profits, wireless power transfer methods, machine learning algorithms for CPS and IoT applications, integration of renewables, electric vehicles (EVs), smart grids, RES micro-grid and EV systems for effective load matching, self-powered car cyber-physical systems, anonymous routing and intrusion detection systems for VANET security, data-driven pavement distress prediction methods, the impact of autonomous vehicles on industries and the auto insurance market, Intelligent transportation systems and associated security concerns, digital twin prototypes and their automotive applications, farming robotics for CPS farming, self-powered CPS in smart cities, self-powered CPS in healthcare and biomedical devices, cyber-security considerations, societal impact and ethical concerns, and advances in human-machine interfaces and explore the integration of self-powered CPS in industrial automation. Whether for the veteran engineer or student, this volume is a must-have for any library.

Explore the power of machine learning to revolutionize signal processing and optimization with cutting-edge techniques and practical insights in this outstanding new volume from Scrivener Publishing. Modeling and Optimization of Signals using Machine Learning Techniques is designed for researchers from academia, industries, and R&D organizations worldwide who are passionate about advancing machine learning methods, signal processing theory, data mining, artificial intelligence, and optimization. This book addresses the role of machine learning in transforming vast signal databases from sensor networks, internet services, and communication systems into actionable decision systems. It explores the development of computational solutions and novel models to handle complex real-world signals such as speech, music, biomedical data, and multimedia. Through comprehensive coverage of cutting-edge techniques, this book equips readers with the tools to automate signal processing and analysis, ultimately enhancing the retrieval of valuable information from extensive data storage systems. By providing both theoretical insights and practical guidance, the book serves as a comprehensive resource for researchers, engineers, and practitioners aiming to harness the power of machine learning in signal processing. Whether for the veteran engineer, scientist in the lab, student, or faculty, this groundbreaking new volume is a valuable resource for researchers and other industry professionals interested in the intersection of technology and agriculture.

Digital Convergence in Intelligent Mobility Systems gives a comprehensive understanding of how digital technologies are revolutionizing transportation, equipping you with the insights needed to navigate the future of intelligent mobility systems. The rapid evolution of digital technologies has transformed the landscape of intelligent mobility systems, ushering in a new era of innovation and convergence. The integration of digital technologies into various aspects of mobility systems, such as autonomous vehicles, smart transportation networks, and advanced traffic management systems, has the potential to revolutionize how we move people and goods. Digital Convergence in Intelligent Mobility Systems is a comprehensive guide that explores the intersection of digital convergence and intelligent mobility systems. This book aims to provide an in-depth understanding of the state-of-the-art technologies, methodologies, and applications that are reshaping the future of transportation. It will serve as a valuable resource for researchers, engineers, policymakers, and students interested in the field of intelligent mobility.

Harness the future of automation with this comprehensive guide, offering an in-depth look at how next-generation mobile robotics are driving the transition to a human-centered and sustainable Industry 5.0. Design and Optimization of Mobile Robotics for Industry 5.0 delivers an in-depth, interdisciplinary look at how next-generation mobile robotic systems are enabling the evolution from Industry 4.0 to a more human-centered, resilient, and sustainable Industry 5.0. This book addresses the technical, ethical, and societal dimensions of robotics technologies, from design principles and autonomous navigation to human-robot interaction and AI integration. It brings together cutting-edge research and real-world case studies across smart manufacturing, agriculture, healthcare, and industrial automation. Readers will explore topics such as digital twins, IoT-enhanced robotics, sensor fusion, and collaborative robotics. With contributions from leading global experts, this volume serves as a comprehensive guide for those involved in designing, deploying, or studying robotics systems that align with the goals of Industry 5.0.

Vast manpower and resources are needed to investigate cybercrimes. The use of new advanced technologies, such as machine learning combined with automation, are effective in providing significant additional support in prevention of cyber-attacks, in the speedy recovery of data, and in reducing human error. This new volume offers a comprehensive study of the advances that have been made in cybercrime investigations and digital forensics, highlighting the most up-to-date tools that help to mitigate cyber-attacks and to extract digital evidence for forensic investigations to recover lost, purposefully deleted, or damaged files. The chapters look at technological cybersecurity tools such as artificial intelligence, machine learning, data mining, and others for mitigation and investigation.