Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human-robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: Introduces several new contributions to the representation and management of humans in autonomous robotic systems; Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; Engages with the potential repercussions of cognitive computing and HRI in the real world.

During the COVID-19 era, the functions of social policy and public administration have undergone a meaningful change, especially with the advancement of digital elements and online and virtual functions. Cyber developments, cyber threats, and the effects of cyberwar on the public administrations of countries have become critical research subjects, and it is important to have resources that can introduce and guide users through the current best practices, laboratory methods, policies, protocols, and more within cyber public administration and social policy. The Handbook of Research on Cyber Approaches to Public Administration and Social Policy focuses on the post-pandemic changes in the functions of social policy and public administration. It also examines the implications of the cyber cosmos on public and social policies and practices from a broad perspective. Covering topics such as intersectional racism, cloud computing applications, and public policies, this major reference work is an essential resource for scientists, laboratory technicians, professionals, technologists, computer scientists, policymakers, students, educators, researchers, and academicians.

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.

Inclusive Radio Communication Networks for 5G and Beyond is based on the COST IRACON project that consists of 500 researchers from academia and industry, with 120 institutions from Europe, US and the Far East involved. The book presents state-of-the-art design and analysis methods for 5G (and beyond) radio communication networks, along with key challenges and issues related to the development of 5G networks. This book is Open Access and was funded by: CNIT - Consorzio Nazionale Interuniversitario per le Telecomunicazioni European Association for Communications and Networking (EURACON), AISBL

The Internet of Medical Things (IoMT) allows clinicians to monitor patients remotely via a network of wearable or implantable devices. The devices are embedded with software or sensors to enable them to send and receive data via the internet so that healthcare professionals can monitor health data such as vital statistics, metabolic rates or drug delivery regimens, and can provide advice or treatment plans based on this real-world, real-time data. This edited book discusses key IoT technologies that facilitate and enhance this process, such as computer algorithms, network architecture, wireless communications, and network security. Providing a systemic review of trends, challenges and future directions of IoMT technologies, the book examines applications such as breast cancer monitoring systems, patient-centric systems for handling, tracking and monitoring virus variants, and video-based solutions for monitoring babies. The book discusses machine learning techniques for the management of clinical data and includes security issues such as the use of blockchain technology. Written by a range of international researchers, this book is a great resource for computer engineering researchers and practitioners in the fields of data mining, machine learning, artificial intelligence and the IoT in the healthcare sector.

In the implementation of smart cities, sensors and actuators that produce and consume enormous amounts of data in a variety of formats and ontologies will be incorporated into the system as a whole. The data produced by the participating devices need to be adequately categorized and connected to reduce duplication and conflicts. Newer edge computing techniques are needed to manage enormous amounts of data quickly and avoid overloading the cloud infrastructure. Cyber-Physical System Solutions for Smart Cities considers the most recent developments in several crucial software services and cyber infrastructures that are important to smart cities. Covering key topics such as artificial intelligence, smart data, big data, and computer science, this premier reference source is ideal for industry professionals, government officials, policymakers, scholars, researchers, academicians, instructors, and students.

Artificial intelligence is headline news with the launch of the latest ChatGPT and Google Bard. But when did we start making computers mimic the human mind? And what is the reality of the capabilities of AI now, and in the future?

AI has always stirred emotions and caused great excitement and concern. Since the launch of large language models such as ChatGPT, the scope and capabilities of AI look set to transform our technology, in both good and bad ways. AI can help teach us how to write better or help us generate amazing artwork. But in the wrong hands, AI can create fake images and fake information that can be used to damage our societies.

A new addition to the popular Bite-sized Chunks series, this expert-led book will explore how AI has developed from humble beginnings in the 1950s to today’s extraordinary AIs with more neurons than the human brain. Focusing on specific AIs and their creators over the years, it explains the science and engineering behind each AI, discusses ethical issues, and covers all the most fascinating information about one of the most important and contentious developments in human technology (including the latest on generative AI/ChatGPT), as well as what we can expect to see in the future of this field – all in short, accessible bite-sized chunks.

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.

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.

Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.

Big Data in Psychiatry and Neurology provides an up-to-date overview of achievements in the field of big data in Psychiatry and Medicine, including applications of big data methods to aging disorders (e.g., Alzheimer's disease and Parkinson's disease), mood disorders (e.g., major depressive disorder), and drug addiction. This book will help researchers, students and clinicians implement new methods for collecting big datasets from various patient populations. Further, it will demonstrate how to use several algorithms and machine learning methods to analyze big datasets, thus providing individualized treatment for psychiatric and neurological patients. As big data analytics is gaining traction in psychiatric research, it is an essential component in providing predictive models for both clinical practice and public health systems. As compared with traditional statistical methods that provide primarily average group-level results, big data analytics allows predictions and stratification of clinical outcomes at an individual subject level.

Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general. This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent Systems and Learning Data Analytics in Online Education shares stimulating theoretical and practical research from leading international experts. This publication provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners to evaluate and apply.

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value.