Security, privacy, and trust in the Internet of Things (IoT) and CPS (Cyber-Physical Systems) are different from conventional security as concerns revolve around the collection and aggregation of data or transmission of data over the network. Analysis of cyber-attack vectors and the provision of appropriate mitigation techniques are essential research areas for these systems. Adoption of best practices and maintaining a balance between ease of use and security are, again, crucial for the effective performance of these systems. Recent Advances in Security, Privacy and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS) discusses and presents techniques and methodologies, as well as a wide range of examples and illustrations, to effectively show the principles, algorithms, challenges, and applications of security, privacy, and trust for IoT and CPS. Book features: Introduces new directions for research, development, and engineering security, privacy, and trust of IoT and CPS Includes a wealth of examples and illustrations to effectively demonstrate the principles, algorithms, challenges, and applications Covers most of the important security aspects and current trends not present in other reference books This book will also serve as an excellent reference in security, privacy, and trust of IoT and CPS for professionals in this fast-evolving and critical field. The chapters present high-quality contributions from researchers, academics, and practitioners from various national and international organizations and universities.

Formal Verification: An Essential Toolkit for Modern VLSI Design, Second Edition presents practical approaches for design and validation, with hands-on advice to help working engineers integrate these techniques into their work. Formal Verification (FV) enables a designer to directly analyze and mathematically explore the quality or other aspects of a Register Transfer Level (RTL) design without using simulations. This can reduce time spent validating designs and more quickly reach a final design for manufacturing. Building on a basic knowledge of SystemVerilog, this book demystifies FV and presents the practical applications that are bringing it into mainstream design and validation processes. New sections cover advanced techniques, and a new chapter, The Road To Formal Signoff, emphasizes techniques used when replacing simulation work with Formal Verification. After reading this book, readers will be prepared to introduce FV in their organization to effectively deploy FV techniques that increase design and validation productivity.

Using the implementation of a deep learning framework as an example, C++ Template Metaprogramming in Practice: A Deep Learning Framework explains the application of metaprogramming in a relatively large project and emphasizes ways to optimize systems performance. The book is suitable for developers with a basic knowledge of C++. Developers familiar with mainstream deep learning frameworks can also refer to this book to compare the differences between the deep learning framework implemented with metaprogramming and compile-time computing with deep learning frameworks using object-oriented methods. Consisting of eight chapters, the book starts with two chapters discussing basic techniques of metaprogramming and compile-time computing. The rest of the book's chapters focus on the practical application of metaprogramming in a deep learning framework. It examines rich types and systems, expression templates, and writing complex meta-functions, as well as such topics as: Heterogeneous dictionaries and policy templates An introduction to deep learning Type system and basic data types Operations and expression templates Basic layers Composite and recurrent layers Evaluation and its optimization Metaprogramming can construct flexible and efficient code. For C++ developers who are familiar with object-oriented programming, the main difficulty in learning and mastering C++ metaprogramming is establishing the thinking mode of functional programming. The meta-programming approach involved at compile time is functional, which means that the intermediate results of the construction cannot be changed, and the impact may be greater than expected. This book enables C++ programmers to develop a functional mindset and metaprogramming skills. The book also discusses the development cost and use cost of metaprogramming and provides workarounds for minimizing these costs.

Get up to speed on Apache Spark, the popular engine for large-scale data processing, including machine learning and analytics. If you're looking to expand your skill set or advance your career in scalable machine learning with MLlib, distributed PyTorch, and distributed TensorFlow, this practical guide is for you. Using Spark as your main data processing platform, you'll discover several open source technologies designed and built for enriching Spark's ML capabilities. Scaling Machine Learning with Spark examines various technologies for building end-to-end distributed ML workflows based on the Apache Spark ecosystem with Spark MLlib, MLFlow, TensorFlow, PyTorch, and Petastorm. This book shows you when to use each technology and why. If you're a data scientist working with machine learning, you'll learn how to: Build practical distributed machine learning workflows, including feature engineering and data formats Extend deep learning functionalities beyond Spark by bridging into distributed TensorFlow and PyTorch Manage your machine learning experiment lifecycle with MLFlow Use Petastorm as a storage layer for bridging data from Spark into TensorFlow and PyTorch Use machine learning terminology to understand distribution strategies

The Internet of Things (IoT) has made revolutionary advances in the utility grid as we know it. Among these advances, intelligent medical services are gaining much interest. The use of Artificial Intelligence (AI) is increasing day after day in fighting one of the most significant viruses, COVID-19. The purpose of this book is to present the detailed recent exploration of AI and IoT in the COVID-19 pandemic and similar applications. The integrated AI and IoT paradigm is widely used in most medical applications, as well as in sectors that deal with transacting data every day. This book can be used by computer science undergraduate and postgraduate students; researchers and practitioners; and city administrators, policy makers, and government regulators. It presents a smart and up-to-date model for COVID-19 and similar applications. Novel architectural and medical use cases in the smart city project are the core aspects of this book. The wide variety of topics it presents offers readers multiple perspectives on a variety of disciplines. Prof. Dr. Fadi Al-Turjman received his PhD in computer science from Queen's University, Kingston, Ontario, Canada, in 2011. He is a full professor and research center director at Near East University, Nicosia, Cyprus.

This book aims to provide the latest research developments and results in the domain of AI techniques for smart cyber ecosystems. It presents a holistic insight into AI-enabled theoretic approaches and methodology in IoT networking, security analytics using AI tools and network automation, which ultimately enable intelligent cyber space. This book will be a valuable resource for students, researchers, engineers and policy makers working in various areas related to cybersecurity and privacy for Smart Cities. This book includes chapters titled "An Overview of the Artificial Intelligence Evolution and Its Fundamental Concepts, and Their Relationship with IoT Security", "Smart City: Evolution and Fundamental Concepts", "Advances in AI-Based Security for Internet of Things in Wireless Virtualization Environment", "A Conceptual Model for Optimal Resource Sharing of Networked Microgrids Focusing Uncertainty: Paving Path to Eco-friendly Smart Cities", "A Novel Framework for a Cyber Secure Smart City", "Contemplating Security Challenges and Threats for Smart Cities", "Self-Monitoring Obfuscated IoT Network", "Introduction to Side Channel Attacks and Investigation of Power Analysis and Fault Injection Attack Techniques", "Collaborative Digital Forensic Investigations Model for Law Enforcement: Oman as a Case Study", "Understanding Security Requirements and Challenges in the Industrial Internet of Things: A Review", "5G Security and the Internet of Things", "The Problem of Deepfake Videos and How to Counteract Them in Smart Cities", "The Rise of Ransomware Aided by Vulnerable IoT Devices", "Security Issues in Self-Driving Cars within Smart Cities", and "Trust-Aware Crowd Associated Network-Based Approach for Optimal Waste Management in Smart Cities". This book provides state-of-the-art research results and discusses current issues, challenges, solutions and recent trends related to security and organization within IoT and Smart Cities. We expect this book to be of significant importance not only to researchers and practitioners in academia, government agencies and industries, but also for policy makers and system managers. We anticipate this book to be a valuable resource for all those working in this new and exciting area, and a "must have" for all university libraries.

This book covers the technology of digital image processing in various fields with big data and their applications. Readers will understand various technologies and strategies used in digital image processing as well as handling big data, using machine-learning techniques. This book will help to improve the skills of students and researchers in such fields as engineering, agriculture, and medical imaging. There is a need to be able to understand and analyse the latest developments of digital image technology. As such, this book will cover: * Applications such as biomedical science and biometric image processing, content-based image retrieval, remote sensing, pattern recognition, shape and texture analysis * New concepts in color interpolation to produce the full color from the sub-pattern bare pattern color prevalent in today's digital cameras and other imaging devices * Image compression standards that are needed to serve diverse applications * Applications of remote sensing, medical science, traffic management, education, innovation, and analysis in agricultural design and image processing * Both soft and hard computing approaches at great length in relation to major image processing tasks * The direction and development of current and future research in many areas of image processing * A comprehensive bibliography for additional research (integrated within the framework of the book) This book focuses not only on theoretical and practical knowledge in the field but also on the traditional and latest tools and techniques adopted in image processing and data science. It also provides an indispensable guide to a wide range of basic and advanced techniques in the fields of image processing and data science.

Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science. All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry. While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility. A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides. Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book.

This unique survey of the career of Michael Dudok de Wit discusses all of his works and offers a glimpse into his private life. The biography of this European master of 2D animation, born in the Netherlands and based in London, is the first complete overview of the well-defined and canonic opus of this humble genius. Visually and thematically, Dudok de Wit's poetic and singular style of animation differs from the rest of contemporary independent animation production. This book reveals what still challenges and thrills Dudok de Wit in the art of animation and why he persistently continues to believe in the beauty of hand-drawn animation. Key Features The complete animation production of Michael Dudok de Wit, never-before reviewed in one volume An all-embracing approach regarding this auteur, unavailable elsewhere in one place (his biography, his peculiar method of work, his extracurricular activities) An ad hoc glossary of animation written by Michael Dudok de Wit and a critical reception of his body of work with a wide contribution of his colleagues and collaborators Filmography and bibliography Author Andrijana Ruzic graduated in History and Criticism of Art at the Universita degli Studi in Milan, Italy, where she fell in love with the medium of animation. She specialised in the History of Animated Film under Giannalberto Bendazzi's mentorship. For the past six years, she has curated the section dedicated to animated films at the International Comics Festival in Belgrade, Serbia. She is a member of the Selection Board of Animafest Scanner, the symposium for Contemporary Animation Studies at the World Festival of Animated Film held annually in Zagreb, Croatia. She writes about animation and art for the Belgrade weekly magazine Vreme.

The use of Electronic Health Records (EHR)/Electronic Medical Records (EMR) data is becoming more prevalent for research. However, analysis of this type of data has many unique complications due to how they are collected, processed and types of questions that can be answered. This book covers many important topics related to using EHR/EMR data for research including data extraction, cleaning, processing, analysis, inference, and predictions based on many years of practical experience of the authors. The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data. Key Features: Written based on hands-on experience of contributors from multidisciplinary EHR research projects, which include methods and approaches from statistics, computing, informatics, data science and clinical/epidemiological domains. Documents the detailed experience on EHR data extraction, cleaning and preparation Provides a broad view of statistical approaches and machine learning prediction models to deal with the challenges and limitations of EHR data. Considers the complete cycle of EHR data analysis. The use of EHR/EMR analysis requires close collaborations between statisticians, informaticians, data scientists and clinical/epidemiological investigators. This book reflects that multidisciplinary perspective.

This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking.

This volume offers a critical overview of digital reading practices and scholarly efforts to analyze and understand reading in the mediatized landscape Building on research about digital reading, born digital literature, and digital audiobooks, The Digital Reading Condition explores reading as part of a broader cultural shift encompassing many forms of media and genres Bringing together research from media and literary studies, digital humanities, scholarship on reading and learning, as well as sensory studies and research on multimodal and multisensory media reception, the authors address and challenge print-biased conceptions of reading that are still prevalent in research, whether the reading medium is print or digital They argue that the act of reading itself is changing, and rather than rejecting digital media as not suitable for sustained or focused reading practices, argue that the complex media landscape challenges us to rethink how to define reading as a mediated practice Presenting a truly interdisciplinary perspective on digital reading practices, this volume will appeal to scholars and graduate students in communication, media studies, new media and technology, literature, digital humanities, literacy studies, composition, and rhetoric

*Covers not just the basics of storytelling with data but also the more complex issues of data searching, cleaning and scraping from a journalist's, rather than a computer scientist's, perspective. *Data Journalism courses are taught at BA and MA level on most Journalism degrees around the world, both as compulsory and elective modules. *Mike Reilley is a leading authority in this area- he founded the Journalist's Toolbox newsletter which shares digital and data tools and has over 51k followers on Twitter, so his name will draw a lot of attention to this book.

This book is an important collection for scholars and students interested in the critical analysis of digital games, and will be of interest across several disciplines including game studies, game design and development, internet studies, visual studies, cultural studies, communication studies, and media studies, as well as disability studies The book explores the opportunities and challenges people with disabilities experience in the context of digital games from the perspective of three related areas: representation, access and inclusion, and community Drawing on key concerns in disability media studies, the book brings together scholars from disability studies and game studies, alongside game developers, educators, and disability rights activists, to reflect upon the increasing visibility of disabled characters in digital games Chapters explore the contemporary gaming environment as it relates to disability on platforms such as Twitch, Minecraft, and Tingyou, while also addressing future possibilities and pitfalls for people with disabilities within gaming given the rise of virtual reality applications, and augmented games such as Pokemon Go The book also asks how game developers can attempt to represent diverse abilities, taking games such as BlindSide and Overwatch as examples

The Home in the Digital Age is a set of multidisciplinary studies exploring the impact of digital technologies in the home, with a shift of emphasis from technology to the people living and using this in their homes. The book covers a wide variety of topics on the design, introduction and use of digital technologies in the home, combining the technological dimension with the cognitive, emotional, cultural and symbolic dimensions of the objects that incorporate digital technologies and project them onto people's lives. It offers a coherent approach, that of the home, which gives unity to the discussion. Scholars of the home, the house and the family will find here the connection with the problems derived from the use of domestic robots and connected devices. Students of artificial intelligence, machine learning, robotics, big data and other branches of digital technologies will find ideas and arguments to apply their disciplines to the home and participate fruitfully in forums where digital technologies are built and negotiated in the home. Experts from various disciplines psychologists and sociologists; philosophers, epistemologists and ethicists; economists; engineers, architects, urban planners and designers and so on and also those interested in developing policies for the home and family will find this book contains well-founded and useful ideas to focus their work.

Placing contemporary technological developments in their historical context, this book argues for the importance of law in their regulation. Technological developments are focused upon overcoming physical and human constraints. There are no normative constraints inherent in the quest for ongoing and future technological development. In contrast, law proffers an essential normative constraint. Just because we can do something, does not mean that we should. Through the application of critical legal theory and jurisprudence to pro-actively engage with technology, this book demonstrates why legal thinking should be prioritised in emerging technological futures. This book articulates classic skills and values such as ethics and justice to ensure that future and ongoing legal engagements with socio-technological developments are tempered by legal normative constraints. Encouraging them to foreground questions of justice and critique when thinking about law and technology, the book addresses law students and teachers, lawyers and critical thinkers concerned with the proliferation of technology in our lives.

This book provides an authoritative resource on the topic of intelligent robots, artificial intelligence and the ethical implications of these revolutionary innovations. It examines the moral and ethical problems that arise in relation to the development, design and use of intelligent robots, which are capable of autonomous or semi-autonomous decision-making. These problems might relate, for example, to medical robots, driverless cars, intelligent military drones, pedagogical robots, police robots, legal robots and many others. The main question addressed in this book is how we can understand, explain and apply the concept of ethics in relation to intelligent robots and artificial intelligence. In each chapter, the author examines a different aspect of this question. The author also questions how we can ensure that intelligent robots are of service to humans and under what conditions intelligent robots could become more ethical than humans. The book employs an original approach to examining this cutting-edge research question, combining different research areas, and offers a wealth of practical relevance and real-world examples, illustrated through vivid case studies. With its jargon free approach and a dedicated chapter on relevant concepts at the end, this book is also accessible to readers without prior knowledge on intelligent robots and the Fourth Industrial Revolution. By providing a general account of this debate, and of the consequences of the innovations resulting from these trends, the book serves as an important contribution to the discussion and will find a natural readership among scholars and students of the innovation economy and those concerned with the ethical considerations arising in the wake of the Fourth Industrial Revolution

SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems. Features: The book covers emerging trends, issues and solutions in the direction of Edge-cloud interplay It highlights the research advances in on SDN, edge, and IoT architecture for smart cities, and software-defined internet of vehicles It includes detailed discussion has made of performance evaluations of SDN controllers, scalable software-defined edge computing, and AI for edge computing Applications areas include machine learning and deep learning in SDN-supported edge-cloud systems Different use cases covered include smart health care, smart city, internet of drones, etc This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.

The proposed title intends to provide a comprehensive view of emerging paradigms of computer science. The initial chapters will introduce various emerging paradigms and discuss research challenges related to them. Then some of the chapters will focus on the research solutions to address the identified challenges. The last few chapters will provide a discussion on future research directions.

In bringing to the readers the book 5G Multimedia Communication: Technology, Multiservices and Deployment, the aim is to present current work and direction on the challenging subject of multimedia communications, with theoretical and practical roots. The past two decades have witnessed an extremely fast evolution of mobile cellular network technology. The fifth generation of mobile wireless systems has achieved the first milestone toward finalization and deployment by 2020. This is vital to the development of future multimedia communications. Also, it is necessary to consider 5G technology from the performance point of view by analyzing network capabilities to the operator and to the end user in terms of data rate, capacity, coverage, energy efficiency, connectivity and latency. The book is divided into three major parts with each part containing four to seven chapters: * Critical enabling technology * Multiservices network * Deployment scenarios The first part discusses enabling technologies, such as green communication, channel modeling, massive and distributed MIMO and ML-based networks. In the second part, different methodologies and standards for multiservices have been discussed. Exclusive chapters have been dedicated to each of the open research challenges such as multimedia operating in 5G environment, network slicing optimization, mobile edge computing, mobile video multicast/broadcast, integrated satellite and drone communication. The third part paved the way to deployment scenarios for different innovative services including integration of a multienergy system in smart cities, intelligent transportation systems, 5G connectivity in the transport sector, healthcare services, 5G edge-based video surveillance and challenges of connectivity for massive IoT in 5G and beyond systems. The book is written by experts in the field who introduced scientific and engineering concepts, covering the 5G multimedia communication areas. The book can be read cover-to-cover or selectively in the areas of interest for the readers. Generally, the book is intended for novel readers who could benefit from understanding general concepts, practitioners who seek guidance into the field and senior-level as well as graduate-level engineering students in understanding the process of today's wireless multimedia communications.

This book focuses on environmental sustainability by employing elements of engineering and green computing through modern educational concepts and solutions. It visualizes the potential of artificial intelligence, enhanced by business activities and strategies for rapid implementation, in manufacturing and green technology. This book covers utilization of renewable resources and implementation of the latest energy-generation technologies. It discusses how to save natural resources from depletion and illustrates facilitation of green technology in industry through usage of advanced materials. The book also covers environmental sustainability and current trends in manufacturing. The book provides the basic concepts of green technology, along with the technology aspects, for researchers, faculty, and students.

Cognitive Computing for Internet of Medical Things (IoMT) offers a complete assessment of the present scenario, role, challenges, technologies, and impact of IoMT-enabled smart healthcare systems. It contains chapters discussing various biomedical applications under the umbrella of the IoMT. Key Features Exploits the different prospects of cognitive computing techniques for the IoMT and smart healthcare applications Addresses the significance of IoMT and cognitive computing in the evolution of intelligent medical systems for biomedical applications Describes the different computing techniques of cognitive intelligent systems from a practical point of view: solving common life problems Explores the technologies and tools to utilize IoMT for the transformation and growth of healthcare systems Focuses on the economic, social, and environmental impact of IoMT-enabled smart healthcare systems This book is primarily aimed at graduates, researchers and academicians working in the area of development of the application of the of the application of the IoT in smart healthcare. Industry professionals will also find this book helpful.

This book provides cutting-edge research in the growing areas of Audio Education and Popular Music Pedagogy Offers an ideal blend of theory and practice as well as acknowledging the practical elements of music production pedagogy A variety of international viewpoints are included, making it accessible to educators in the US, UK, Australia and beyond

The Audio Expert is a comprehensive reference book covering all aspects of audio, with both practical and theoretical explanations. It is written for people who want to understand audio at the deepest, most technical level, but without needing an engineering degree. The Audio Expert explains how audio really works in much more depth than usual, using common sense plain-English explanations and mechanical analogies, with minimal math. It uses an easy to read conversational tone, and includes more than 400 figures and photos to augment the printed text. However, this book goes beyond merely explaining how audio works. It brings together the concepts of audio, aural perception, musical instrument physics, acoustics, and basic electronics, showing how they're intimately related. It also describes in great detail many practices and techniques used by recording and mixing engineers, including video production and computers. This book is meant for intermediate to advanced recording engineers and audiophiles who want to become experts. There's plenty for beginners too. One unique feature is explaining how audio devices such as equalizers, compressors, and A/D converters work internally, and how they're spec'd and tested, rather than merely describing how to use them. There's plenty of myth-busting and consumerism too. The book doesn't tell readers what brand power amplifier to buy, but it explains in great detail what defines a good amplifier so people can choose a first-rate model wisely without over-paying. Most explanations throughout the book are platform-agnostic, applying equally to Windows and Mac computers, and to most software and hardware. Many audio and video examples are included to enhance the written text. The new edition offers many updates and improvements throughout. New sections on coding an equalizer, comparing microphone preamps, testing results of loudspeaker isolation devices, new online video content on music theory, plus incorporated chapters on MIDI basics, computers, video production, plus new myth-busters, and much more!

With the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations. Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models. The crux of the book is four industry use cases. They describe how an enterprise can access, assess, and perform analytics on data by way of discovering data, defining key metrics that enable the same, defining governance rules, and activating metadata for AI/ML recommendations. Explaining the implementation specifics of each of these four use cases by way of using various AI-enabled machine learning and deep learning algorithms, this book provides complete code for each of the implementations, along with the output of the code, supplemented by visuals that aid in BI-enabled decision making. Concluding with a brief discussion of the cognitive computing aspects of AI, the book looks at future trends, including augmented analytics, automated and autonomous BI, and security and governance of AI-powered BI.