Tensors for Data Processing: Theory, Methods and Applications presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data processing. This reference is ideal for students, researchers and industry developers who want to understand and use tensor-based data processing theories and methods. As a higher-order generalization of a matrix, tensor-based processing can avoid multi-linear data structure loss that occurs in classical matrix-based data processing methods. This move from matrix to tensors is beneficial for many diverse application areas, including signal processing, computer science, acoustics, neuroscience, communication, medical engineering, seismology, psychometric, chemometrics, biometric, quantum physics and quantum chemistry.

The Beginnings of Electron Microscopy - Part 1, Volume 220 in the Advances in Imaging and Electron Physics series highlights new advances in the field, with this new volume presenting interesting chapters on Electron-optical Research at the AEG Forschungs-Institut 1928-1940, On the History of Scanning Electron Microscopy, of the Electron Microprobe, and of Early Contributions to Transmission Electron Microscopy, Random Recollections of the Early Days, Early History of Electron Microscopy in Czechoslovakia, Personal Reminiscences of Early Days in Electron, Megavolt Electron Microscopy, Cryo-Electron Microscopy and Ultramicrotomy: Reminiscences and Reflections, and much more.

Deep Reinforcement Learning for Wireless Communications and Networking Comprehensive guide to Deep Reinforcement Learning (DRL) as applied to wireless communication systems Deep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while providing fundamental knowledge about theories, formulation, design, learning models, algorithms and implementation of DRL together with a particular case study to practice. The book also covers diverse applications of DRL to address various problems in wireless networks, such as caching, offloading, resource sharing, and security. The authors discuss open issues by introducing some advanced DRL approaches to address emerging issues in wireless communications and networking. Covering new advanced models of DRL, e.g., deep dueling architecture and generative adversarial networks, as well as emerging problems considered in wireless networks, e.g., ambient backscatter communication, intelligent reflecting surfaces and edge intelligence, this is the first comprehensive book studying applications of DRL for wireless networks that presents the state-of-the-art research in architecture, protocol, and application design. Deep Reinforcement Learning for Wireless Communications and Networking covers specific topics such as: Deep reinforcement learning models, covering deep learning, deep reinforcement learning, and models of deep reinforcement learning Physical layer applications covering signal detection, decoding, and beamforming, power and rate control, and physical-layer security Medium access control (MAC) layer applications, covering resource allocation, channel access, and user/cell association Network layer applications, covering traffic routing, network classification, and network slicing With comprehensive coverage of an exciting and noteworthy new technology, Deep Reinforcement Learning for Wireless Communications and Networking is an essential learning resource for researchers and communications engineers, along with developers and entrepreneurs in autonomous systems, who wish to harness this technology in practical applications.

All over the world, educational institutions confronted emergency policy changes caused by the COVID-19 pandemic. Due to this, academic activities were provided mostly by remote teaching and learning solutions. The transition to emergency remote teaching and learning raised some challenges regarding technical, pedagogical, and organizational issues. It is important for higher education institutions to prepare themselves to deal with future emergency scenarios, promoting an in-depth reflection about the future challenges in the post-pandemic era. Developing Curriculum for Emergency Remote Learning Environments supports creating and promoting an education-as-a-business strategy for higher education institutions by sharing possible business models. It provides a collection of different approaches to online education in the perspective of the future of education environments. Covering topics such as distance learning experiences, online practice improvement, and remote testing, this premier reference source is an excellent resource for educators and administrators of higher education, pre-service educators, IT professionals, librarians, researchers, and academicians.

Smart Cities Cybersecurity and Privacy examines the latest research developments and their outcomes for safe, secure, and trusting smart cities residents. Smart cities improve the quality of life of citizens in their energy and water usage, healthcare, environmental impact, transportation needs, and many other critical city services. Recent advances in hardware and software, have fueled the rapid growth and deployment of ubiquitous connectivity between a city's physical and cyber components. This connectivity however also opens up many security vulnerabilities that must be mitigated. Smart Cities Cybersecurity and Privacy helps researchers, engineers, and city planners develop adaptive, robust, scalable, and reliable security and privacy smart city applications that can mitigate the negative implications associated with cyber-attacks and potential privacy invasion. It provides insights into networking and security architectures, designs, and models for the secure operation of smart city applications.

Structured Light for Optical Communication highlights principles and applications in the rapidly evolving field of structured light in wide-ranging contexts, from classical forms of communication to new frontiers of quantum communication. Besides the basic principles and applications, the book covers the background of structured light in its most common forms, as well as state-of-the-art developments. Structured light has been hailed as affording outstanding prospects for the realization of high bandwidth communication, enhanced tools for more highly secure cryptography, and exciting opportunities for providing a reliable platform for quantum computing. This book is a valuable resource for graduate students and other active researchers, as well as others who may be interested in learning about this cutting-edge research field.

Cardiovascular and Coronary Artery Imaging, Volume One covers state-of-the-art approaches for automated non-invasive systems in early cardiovascular disease diagnosis. The book includes several prominent imaging modalities, such as MRI, CT and PET technologies. A special emphasis is placed on automated imaging analysis techniques, which are important to biomedical imaging analysis of the cardiovascular system. This is a comprehensive, multi-contributed reference work that details the latest developments in spatial, temporal and functional cardiac imaging.

Advances in Imaging and Electron Physics, Volume 219, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains.

Blockchain and artificial intelligence (AI) in industrial internet of things is an emerging field of research at the intersection of information science, computer science, and electronics engineering. The radical digitization of industry coupled with the explosion of the internet of things (IoT) has set up a paradigm shift for industrial and manufacturing companies. There exists a need for a comprehensive collection of original research of the best performing methods and state-of-the-art approaches in this area of blockchain, AI, and the industrial internet of things in this new era for industrial and manufacturing companies. Blockchain and AI Technology in the Industrial Internet of Things compares different approaches to the industrial internet of things and explores the direct impact blockchain and AI technology have on the betterment of the human life. The chapters provide the latest advances in the field and provide insights and concerns on the concept and growth of the industrial internet of things. While including research on security and privacy, supply chain management systems, performance analysis, and a variety of industries, this book is ideal for professionals, researchers, managers, technologists, security analysts, executives, practitioners, researchers, academicians, and students looking for advanced research and information on the newest technologies, advances, and approaches for blockchain and AI in the industrial internet of things.

AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-based data analytics and IoT for predictability of crop, soil, and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management, and smart farming. The book provides an overarching focus on sustainable environment and sustainable economic development through smart and e-agriculture. Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture and data mining researchers around the world provide foundational insights. The book provides practical application opportunities for the resolution of real-world problems, including contributions from the data mining, data analytics, Edge of Things, and cloud research communities working in the farming production sector. The book offers broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT-based agriculture, Edge of Things and cloud-based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture toward smart farming.