Intelligent Image and Video Compression: Communicating Pictures, Second Edition explains the requirements, analysis, design and application of a modern video coding system. It draws on the authors' extensive academic and professional experience in this field to deliver a text that is algorithmically rigorous yet accessible, relevant to modern standards and practical. It builds on a thorough grounding in mathematical foundations and visual perception to demonstrate how modern image and video compression methods can be designed to meet the rate-quality performance levels demanded by today's applications and users, in the context of prevailing network constraints. "David Bull and Fan Zhang have written a timely and accessible book on the topic of image and video compression. Compression of visual signals is one of the great technological achievements of modern times, and has made possible the great successes of streaming and social media and digital cinema. Their book, Intelligent Image and Video Compression covers all the salient topics ranging over visual perception, information theory, bandpass transform theory, motion estimation and prediction, lossy and lossless compression, and of course the compression standards from MPEG (ranging from H.261 through the most modern H.266, or VVC) and the open standards VP9 and AV-1. The book is replete with clear explanations and figures, including color where appropriate, making it quite accessible and valuable to the advanced student as well as the expert practitioner. The book offers an excellent glossary and as a bonus, a set of tutorial problems. Highly recommended!" --Al Bovik

Advances in Computers, Volume 123 presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on Downlink Resource Allocations of Satellite-Airborne-Terrestrial Networks Integration, Evaluating Software Testing Techniques: A Systematic Mapping Study, The Screening Phase in Systematic Reviews: Can we speed up the process?, A Survey on Cloud-Based Video Streaming Services, and User Behavior-Ensemble Learning based Improving QoE Fairness in HTTP Adaptive Streaming over SDN approach.

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.

Dieses Werk, das sich umfassend mit der Einfuhrung von maschinellem Lernen, KI und dem IoT im Gesundheitswesen beschaftigt, richtet sich an Forschende, Fachkrafte im Gesundheitswesen, Wissenschaftler und Technologen. Die Nutzung von maschinellem Lernen und kunstlicher Intelligenz im Internet der Dinge (IoT) fur Anwendungen im Gesundheitswesen sowie die damit einhergehenden Herausforderungen werden ausfuhrlich eroertert. Das IoT erzeugt gewaltige Datenmengen von unterschiedlicher Qualitat. Die intelligente Verarbeitung und Analyse dieser Datenmengen sind der Schlussel zur Entwicklung intelligenter IoT-Anwendungen, wodurch Raum fur die Nutzung des maschinellen Lernens (ML) geschaffen wird. Mit ihren Recheninstrumenten, die bei der Erledigung bestimmter Aufgaben die menschliche Intelligenz ersetzen koennen, macht es die kunstliche Intelligenz (KI) moeglich, dass Computer aus Erfahrung lernen, sich an neue Eingaben anpassen und bisher von Menschen durchgefuhrte Aufgaben ubernehmen. Da IoT-Plattformen eine Schnittstelle bieten, um Daten von unterschiedlichen Geraten zusammenzutragen, lassen sie sich leicht mit AI/ML-Systemen verbinden. Vor diesen Hintergrund besteht der Wert der KI in ihrer Fahigkeit, schnell Erkenntnisse aus Daten zu gewinnen, automatisch Muster zu erkennen und Anomalien in den von intelligenten Sensoren und Geraten erzeugten Daten zu erkennen ? aus Angaben zu Temperatur, Druck, Luftfeuchtigkeit, Luftqualitat, Schwingungen und Gerauschen ? die fur eine schnelle Diagnose extrem hilfreich sein koennen.

Advances in Imaging and Electron Physics, Volume 218 merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features 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. Specific chapters in this release cover Phase retrieval methods applied to coherent imaging, X-ray phase-contrast imaging: a broad overview of some fundamentals, Graphene and borophene as nanoscopic materials for electronics - with review of the physics, and more.

This book takes the reader through the actual manufacturing process of making a typical chip, from start to finish, including a detailed discussion of each step, in plain language. The evolution of today's technology is added to the story, as seen through the eyes of the engineers who solved some of the problems. The authors are well suited to that discussion since they are three of those same engineers. They have a broad exposure to the industry and its technology that extends all the way back to Shockley Laboratories, the first semiconductor manufacturer in Silicon Valley.
The CMOS (Complementary Metal-Oxide-Semiconductor) process flow is the focus of the discussion and is covered in ten chapters. The vast majority of chips made today are fabricated using this general method. In order to ensure that all readers are comfortable with the vocabulary, the first chapter carefully and clearly introduces the science concepts found in later chapters. A chapter is devoted to pointing out the differences in other manufacturing methods, such as the gallium arsenide technology that produces chips for cell phones. In addition, a chapter describing the nature of the semiconductor industry from a business perspective is included.
"The entire process of making a chip is surprisingly easy to understand. The part of the story that defies belief is the tiny dimensions: the conducting wires and other structures on a chip are more than a hundred times thinner than a hair - and getting thinner with every new chip design."
* Included CD gives the reader a much greater comprehension of the process than a strictly print book with static illustrations provides
* Authors are actual engineers who have a broad range of exposure and experience with chip technology
* Contains a unique chapter describing the nature of the semiconductor industry from a business perspective

Quantitative Atomic-Resolution Electron Microscopy, Volume 217, the latest release in the Advances in Imaging and Electron Physics series 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. Chapters in this release include Statistical parameter estimation theory, Efficient fitting algorithm, Statistics-based atom counting , Atom column detection, Optimal experiment design for nanoparticle atom-counting from ADF STEM images, and more.

Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks. This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning.

Wireless communication is continuously evolving to improve and be a part of our daily communication. This leads to improved quality of services and applications supported by networking technologies. We are now able to use LTE, LTE-Advanced, and other emerging technologies due to the enormous efforts that are made to improve the quality of service in cellular networks. As the future of networking is uncertain, the use of deep learning and big data analytics is a point of focus as it can work in many capacities at a variety of levels for wireless communications. Implementing Data Analytics and Architectures for Next Generation Wireless Communications addresses the existing and emerging theoretical and practical challenges in the design, development, and implementation of big data algorithms, protocols, architectures, and applications for next generation wireless communications and their applications in smart cities. The chapters of this book bring together academics and industrial practitioners to exchange, discuss, and implement the latest innovations and applications of data analytics in advanced networks. Specific topics covered include key encryption techniques, smart home appliances, fog communication networks, and security in the internet of things. This book is valuable for technologists, data analysts, networking experts, practitioners, researchers, academicians, and students.

Professor Judea Pearl won the 2011 Turing Award "for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning." This book contains the original articles that led to the award, as well as other seminal works, divided into four parts: heuristic search, probabilistic reasoning, causality, first period (1988-2001), and causality, recent period (2002-2020). Each of these parts starts with an introduction written by Judea Pearl. The volume also contains original, contributed articles by leading researchers that analyze, extend, or assess the influence of Pearl's work in different fields: from AI, Machine Learning, and Statistics to Cognitive Science, Philosophy, and the Social Sciences. The first part of the volume includes a biography, a transcript of his Turing Award Lecture, two interviews, and a selected bibliography annotated by him.

Predictive Filtering for Microsatellite Control Systems introduces technological design, modeling, stability analysis, predictive filtering, state estimation problem and real-time operation of spacecraft control systems in aerospace engineering. The book gives a systematically and almost self-contained description of the many facets of envisaging, designing, implementing or experimentally exploring predictive filtering for spacecraft control systems, along with the adequate designs of integrated modeling, dynamics, state estimation, and signal processing of spacecrafts and nonlinear systems.

Quantum computing is radically different from the conventional approach of transforming bits strings from one set of 0's and 1's to another. With quantum computing, everything changes. The physics that we use to understand bits of information and the devices that manipulate them are totally different. The way in which we build such devices is different, requiring new materials, new design rules and new processor architectures. Finally, the way we program these systems is entirely different. Quantum engineering is a revolutionary approach to quantum technology. It encompasses both fundamental physics and the broad engineering skill-set necessary to meet the practical challenges of the future. The proposed book will cover the high-quality reviewed book chapters on original research & innovations and compelling insights in Quantum Computing and Engineering. Data scientists, Engineers, Industry, researchers and students working in the field of quantum computing and its allied research will benefit greatly from this publication.

Advances in Delay-Tolerant Networks: Architecture and Enhanced Performance, Second Edition provides an important overview of delay-tolerant networks (DTNs) for researchers in electronics, computer engineering, telecommunications and networking for those in academia and R&D in industrial sectors. Part I reviews the technology involved and the prospects for improving performance, including different types of DTN and their applications, such as satellite and deep-space communications and vehicular communications. Part II focuses on how the technology can be further improved, addressing topics, such as data bundling, opportunistic routing, reliable data streaming, and the potential for rapid selection and dissemination of urgent messages. Opportunistic, delay-tolerant networks address the problem of intermittent connectivity in a network where there are long delays between sending and receiving messages, or there are periods of disconnection.

Intelligent machines are populating our social, economic and political spaces. These intelligent machines are powered by Artificial Intelligence technologies such as deep learning. They are used in decision making. One element of decision making is the issue of rationality. Regulations such as the General Data Protection Regulation (GDPR) require that decisions that are made by these intelligent machines are explainable. Rational Machines and Artificial Intelligence proposes that explainable decisions are good but the explanation must be rational to prevent these decisions from being challenged. Noted author Tshilidzi Marwala studies the concept of machine rationality and compares this to the rationality bounds prescribed by Nobel Laureate Herbert Simon and rationality bounds derived from the work of Nobel Laureates Richard Thaler and Daniel Kahneman. Rational Machines and Artificial Intelligence describes why machine rationality is flexibly bounded due to advances in technology. This effectively means that optimally designed machines are more rational than human beings. Readers will also learn whether machine rationality can be quantified and identify how this can be achieved. Furthermore, the author discusses whether machine rationality is subjective. Finally, the author examines whether a population of intelligent machines collectively make more rational decisions than individual machines. Examples in biomedical engineering, social sciences and the financial sectors are used to illustrate these concepts.

Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly caused by a bacteria or a virus. The prime targets of this infectious disease are children below the age of 5 and adults above the age of 65, mostly due to their poor immunity and lower rates of recovery. Globally, pneumonia has prevalent footprints and kills more children as compared to any other immunity-based disease, causing up to 15% of child deaths per year, especially in developing countries. Out of all the available imaging modalities, such as computed tomography, radiography or X-ray, magnetic resonance imaging, ultrasound, and so on, chest radiographs are most widely used for differential diagnosis between Normal and Pneumonia. In the CAC system designs implemented in this book, a total of 200 chest radiograph images consisting of 100 Normal images and 100 Pneumonia images have been used. These chest radiographs are augmented using geometric transformations, such as rotation, translation, and flipping, to increase the size of the dataset for efficient training of the Convolutional Neural Networks (CNNs). A total of 12 experiments were conducted for the binary classification of chest radiographs into Normal and Pneumonia. It also includes in-depth implementation strategies of exhaustive experimentation carried out using transfer learning-based approaches with decision fusion, deep feature extraction, feature selection, feature dimensionality reduction, and machine learning-based classifiers for implementation of end-to-end CNN-based CAC system designs, lightweight CNN-based CAC system designs, and hybrid CAC system designs for chest radiographs. This book is a valuable resource for academicians, researchers, clinicians, postgraduate and graduate students in medical imaging, CAC, computer-aided diagnosis, computer science and engineering, electrical and electronics engineering, biomedical engineering, bioinformatics, bioengineering, and professionals from the IT industry.

The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing.

Online high school education is challenging with limited resources for teachers to turn to. In most cases, teachers rely on trial-and-error. This research-based and practitioner-focused text provides best practice techniques and utilizes analogies from brick-and-mortar education to provide a conceptual framework to a better understanding of how online education functions and how to be engage students and how to build and maintain a positive digital culture. This book provides real-world solutions to online and hybrid educators. The aim of this is to train educators to develop online culture, healthy and inclusive communication, and how to use the online classroom environment in parallel or stand-alone with a face-to-face classroom. Engagement strategies will be discussed as well as the use of multi-tiered systems of support to engage students. The desired impact is to increase learning, growth and to prepare high school students for the next step in their academic career.