Covers applications of various image processing techniques in thermal imaging applications for diagnosis of different medical conditions Describes the development of a computer diagnostics system (CAD) based on thermographic data Discusses customized deep learning models for accurate diagnosis of various diseases Includes new aspects in rheumatoid arthritis and diabetes research with usage of advanced analytical tools Reviews application of feature fusion algorithms and feature reduction algorithms for accurate classification of images

By proposing and forming a mobile manipulator for modern multi-floor buildings, A Robotic Framework for the Mobile Manipulator: Theory and Application helps readers visualize an end-to-end workflow for making a robot system work in a targeted environment. From a product-oriented viewpoint, this book is considered as a bridge from theories to real products, in which robotic software modules and the robotic system integration are mainly concerned. In the end, readers will have an overview of how to build and integrate various single robotic modules to execute a list of designed tasks in the real world, as well as how to make a robot system work independently, without human interventions. With references and execution guidelines provided at the end of each chapter, the book will be a useful tool for developers and researchers looking to expand their knowledge about the robotics and the robotic software.

'Real science can be far stranger than science fiction, and much more satisfying' Will artificial intelligence outsmart us? Is there other intelligent life in the universe? Throughout his extraordinary career, Stephen Hawking expanded our understanding of the universe and unravelled some of its greatest mysteries. Will Artificial Intelligence Outsmart Us? considers the threat of artificial super-intelligence - as well as the likelihood of intelligent life beyond our planet. 'Modest, profound and sometimes very funny' Sunday Times Brief Answers, Big Questions: this stunning paperback series offers electrifying essays from one of the greatest minds of our age, taken from the original text of the No. 1 bestselling Brief Answers to the Big Questions.

Today, raw data on any industry is widely available. With the help of artificial intelligence (AI) and machine learning (ML), this data can be used to gain meaningful insights. In addition, as data is the new raw material for today's world, AI and ML will be applied in every industrial sector. Industry 4.0 mainly focuses on the automation of things. From that perspective, the oil and gas industry is one of the largest industries in terms of economy and energy. Applications of Artificial Intelligence (AI) and Machine Learning (ML) in the Petroleum Industry analyzes the use of AI and ML in the oil and gas industry across all three sectors, namely upstream, midstream, and downstream. It covers every aspect of the petroleum industry as related to the application of AI and ML, ranging from exploration, data management, extraction, processing, real-time data analysis, monitoring, cloud-based connectivity system, and conditions analysis, to the final delivery of the product to the end customer, while taking into account the incorporation of the safety measures for a better operation and the efficient and effective execution of operations. This book explores the variety of applications that can be integrated to support the existing petroleum and adjacent sectors to solve industry problems. It will serve as a useful guide for professionals working in the petroleum industry, industrial engineers, AI and ML experts and researchers, as well as students.

1. Provides a toolkit of templates for common VR interactions, as well as practical advice on when to use them and how to tailor them for specific use cases; 2. Includes case studies detailing the practical application of interaction theory discussed in each chapter; 3. Presents tables of guidelines for practicing VR developers, for reference during software development; 4. Covers procedures for Interface Evaluation - formulas and testing methodologies to ensure that VR interfaces are effective, efficient, engaging, error-tolerant, and easy to learn; 5. Non-linear organisation - chapters of the book on different concepts can be read to gain knowledge on a single topic, without requiring other chapters to be read beforehand; 6. Includes ancillaries - PowerPoint slides, 3D models, videos, and a teacher's guide

This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence

Blockchain technology has been penetrating every aspect of Information and Communications Technology (ICT), and its use has been growing rapidly in recent years. The interest and development of this technology has primarily been driven by the enormous value growth of cryptocurrencies and large investments of venture capital in blockchain start-ups. Blockchain for Smart Systems: Computing Technologies and Applications is intended to clarify and define, in simple terms, the technology behind blockchain. It provides a deep dive into the core fundamentals of blockchain: hashing algorithm behind each block, distributed technology, smart contracts, and private vs. public blockchain. Features Discusses fundamental theories of practical and sophisticated applications of blockchain technology Includes case studies Discusses the concepts with illustrations, appropriate figures, tables, and simple language This book is primarily aimed at undergraduates, graduates, research scholars, academicians, and industry and technology enthusiasts working in various aspects of blockchain technology.

- Centers artificial intelligence as a pathway for media studies students, scholars and practitioners to navigate the broad terrain of software practice. - Examines the impact of software on everyday life as it traces the industrial development and migrations of AI and the connectedness of play to broader cultural, social and economic forces. - Connects history and theory to practice through a number of illustrative, culturally relevant media objects and case studies that will be familiar and engaging to many students. - With its focus on applied artificial intelligence in popular and public culture, it bridges the fields of software studies, science and technology studies, and video game studies.

Auditory Interfaces explores how human-computer interactions can be significantly enhanced through the improved use of the audio channel. Providing historical, theoretical and practical perspectives, the book begins with an introductory overview, before presenting cutting-edge research with chapters on embodied music recognition, nonspeech audio, and user interfaces. This book will be of interest to advanced students, researchers and professionals working in a range of fields, from audio sound systems, to human-computer interaction and computer science.

All the topics that a professional AI programmer needs are covered within Each topic is accompanied by an example game, where the reader simply adds their own code and see the effects their changes have Covers complex topics but in an easy to read manner and with conversational delivery

Explores text mining and IoT applications for monitoring and controlling smart industrial systems Describes the key principles and techniques for Big-data analytics, security, and optimization for industrial applications. Provides context-aware insights, human-centric industry, smart computing for next-generation industry

The book is concerned with contemporary methodologies used for automatic text summarization. It proposes interesting approaches to solve well-known problems on text-summarization using computational intelligence (CI) techniques including cognitive approaches. A better understanding of the cognitive basis of the summarization task is still an open research issue, an extent of its use in text summarization is highlighted for further exploration. With the ever-growing text and people on research has little time to spare for extensive reading, where, summarized information helps for a better understanding of the context at a shorter time. This book helps students and researchers to automatically summarize the text documents in an efficient and effective way. The computational approaches and the research techniques presented guides to achieve text summarization at ease. The summarized text generated supports readers to learn the context or the domain at a quicker pace. The book is presented with reasonable amount of illustrations and examples convenient for the readers to understand and implement for their use. The book is not to make readers understand what text summarization is, but for people to perform text summarization using various approaches. This also describes measures that can help to evaluate, determine and explore the best possibilities for text summarization to analyse and use for any specific purpose. The illustration is based on social media and healthcare domain, which shows the possibilities to work with any domain for summarization. The new approach for text summarization based on cognitive intelligence is presented for further exploration in the field.

1. Provides a comprehensive introduction to the interdisciplinary field of Cognitive Science. 2. Features extended case studies throughout to illustrate key concepts from across different fields. 3. Uniquely adopts a cognitive psychology structure throughout, addressing key issues for each, unlike rival texts which are more thematically based.

Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing. From object recognition to image classification for diagnostics, deep learning has shown the power of artificial deep neural networks in solving real world visual computing problems with super-human accuracy. The introduction of deep learning into the field of visual computing has meant to be the death of most of the traditional image processing and computer vision techniques. Today, deep learning is considered to be the most powerful, accurate, efficient and effective method with the potential to solve many of the most challenging problems in visual computing. This book provides an insight into deep machine learning and the challenges in visual computing to tackle the novel method of machine learning. It introduces readers to the world of deep neural network architectures with easy-to-understand explanations. From face recognition to image classification for diagnosis of cancer, the book provides unique examples of solved problems in applied visual computing using deep learning. Interested and enthusiastic readers of modern machine learning methods will find this book easy to follow. They will find it a handy guide for designing and implementing their own projects in the field of visual computing.

The aim of this book is to present and analyse theoretical advances and also emerging practical applications of swarm and evolutionary intelligence. It comprises nine chapters. Chapter 1 provides a theoretical introduction of the computational optimization techniques regarding the gradient-based methods such as steepest descent, conjugate gradient, newton and quasi-Newton methods and also the non-gradient methods such as genetic algorithm and swarm intelligence algorithms. Chapter 2, discusses evolutionary computation techniques and genetic algorithm. Swarm intelligence theory and particle swarm optimization algorithm are reviewed in Chapter 3. Also, several variations of particle swarm optimization algorithm are analysed and explained such as Geometric PSO, PSO with mutation, Chaotic PSO with mutation, multi-objective PSO and Quantum mechanics - based PSO algorithm. Chapter 4 deals with two essential colony bio-inspired algorithms: Ant colony optimization (ACO) and Artificial bee colony (ABC). Chapter 5, presents and analyses Cuckoo search and Bat swarm algorithms and their latest variations. In chapter 6, several other metaheuristic algorithms are discussed such as: Firefly algorithm (FA), Harmony search (HS), Cat swarm optimization (CSO) and their improved algorithm modifications. The latest Bio-Inspired Swarm Algorithms are discussed in chapter 7, such as: Grey Wolf Optimization (GWO) Algorithm, Whale Optimization Algorithm (WOA), Grasshopper Optimization Algorithm (GOA) and other algorithm variations such as binary and chaotic versions. Chapter 8 presents machine learning applications of swarm and evolutionary algorithms. Illustrative real-world examples are presented with real datasets regarding neural network optimization and feature selection, using: genetic algorithm, Geometric PSO, Chaotic Harmony Search, Chaotic Cuckoo Search, and Evolutionary Algorithm and also crime forecasting using swarm optimized SVM. In chapter 9, applications of swarm intelligence on deep long short-term memory (LSTM) networks and Deep Convolutional Neural Networks (CNNs) are discussed, including LSTM hyperparameter tuning and Covid19 diagnosis from chest X-Ray images. The aim of the book is to present and discuss several state-of-theart swarm intelligence and evolutionary algorithms together with their variances and also several illustrative applications on machine learning and deep learning.

Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area-including healthcare, finance, manufacturing, and marketing-could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy. This is the first such book that provides a comprehensive overview of integrating both cyber security and data science and discusses both theory and practice in secure data science. After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media. This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science.

Reviews different machine learning and deep learning techniques with a biomedical perspective Provides the relevant case studies that demonstrate applicability of different AI techniques Explain different kinds of inputs like various image modalities, biomedical signals types, etc. Covers the latest trends of AI-based biomedical domains including IoT, drug discovery, biomechanics, robotics, electronic health records, etc. Discusses the research challenges and opportunities in AI and biomedical domain

This foundational text examines the intersection of AI, psychology, and ethics, laying the groundwork for the importance of ethical considerations in the design and implementation of technologically supported education, decision support, and leadership training. AI already affects our lives profoundly, in ways both mundane and sensational, obvious and opaque. Much academic and industrial effort has considered the implications of this AI revolution from technical and economic perspectives, but the more personal, humanistic impact of these changes has often been relegated to anecdotal evidence in service to a broader frame of reference. Offering a unique perspective on the emerging social relationships between people and AI agents and systems, Hampton and DeFalco present cutting-edge research from leading academics, professionals, and policy standards advocates on the psychological impact of the AI revolution. Structured into three parts, the book explores the history of data science, technology in education, and combatting machine learning bias, as well as future directions for the emerging field, bringing the research into the active consideration of those in positions of authority. Exploring how AI can support expert, creative, and ethical decision making in both people and virtual human agents, this is essential reading for students, researchers, and professionals in AI, psychology, ethics, engineering education, and leadership, particularly military leadership.

Provides for the first time a comprehensive, state-of-the-art overview of the different types of healthcare robots and the advances that AI brings them. Provides, in an easy and accessible way, essential basic information about the autonomy levels of surgery robots, which is novel. As such, could be very valuable to a broad community that ranges from legal scholars, ethicists, developers, policymakers, students, or non-specialists curious about the topic.

Artificial Intelligence in Information and Communication Technologies, Healthcare and Education: A Roadmap Ahead is designed as a reference text and discusses inter-dependability, communication and effective control for the betterment of services through artificial intelligence (AI), as well as the challenges and path ahead for AI in computing and control across different domains of business and human life. The book accommodates technologies and application domains including backbone hardware, systems and methods for deployment, which help incorporating intelligence through different supervised and probabilistic learning approaches. Features The book attempts to establish a connection between hardware, software technologies and algorithmic intelligence for data analysis and decision support in domains such as healthcare, education and other aspects of business and mobility. It presents various recent applications of artificial intelligence in information and communication technologies such as search and optimization methods, machine learning, data representation and ontologies, and multi-agent systems. The book provides a collection of different case studies with experimentation results than mere theoretical and generalized approaches. Covers most of the applications using the trending technologies like machine learning (ML), data science (DS), Internet of Things (IoT), and underlying information and communication technologies. The book is aimed primarily at advanced undergraduates and postgraduate students studying computer science, computer applications, and information technology. Researchers and professionals will also find this book useful.

What existential threats does humanity face? And how can we secure our future? 'The Precipice is a powerful book . . . Ord's love for humanity and hope for its future is infectious' Spectator 'Ord's analysis of the science is exemplary . . . Thrillingly written' Sunday Times We live during the most important era of human history. In the twentieth century, we developed the means to destroy ourselves - without developing the moral framework to ensure we won't. This is the Precipice, and how we respond to it will be the most crucial decision of our time. Oxford moral philosopher Toby Ord explores the risks to humanity's future, from the familiar man-made threats of climate change and nuclear war, to the potentially greater, more unfamiliar threats from engineered pandemics and advanced artificial intelligence. With clear and rigorous thinking, Ord calculates the various risk levels, and shows how our own time fits within the larger story of human history. We can say with certainty that the novel coronavirus does not pose such a risk. But could the next pandemic? And what can we do, in our present moment, to face the risks head on? A major work that brings together the disciplines of physics, biology, earth and computer science, history, anthropology, statistics, international relations, political science and moral philosophy, The Precipice is a call for a new understanding of our age: a major reorientation in the way we see the world, our history, and the role we play in it.

This carefully designed, multi-authored textbook covers a broad range of theoretical issues in cognitive science, psychology, and neuroscience. With accessible language, a uniform structure, and many pedagogical features, Mind, Cognition, and Neuroscience: A Philosophical Introdution is the best high-level overview of this area for an interdisciplinary readership of students. Written specifically for this volume by experts in their fields who are also experienced teachers, the book's thirty chapters are organized into the following parts: I. Background Knowledge II. Classical Debates III. Consciousness IV. Crossing Boundaries Each chapter starts with relevant key words and definitions and a chapter overview, then presents historical coverage of the topic, explains and analyzes contemporary debates, and ends with a sketch of cutting edge research. A list of suggested readings and helpful discussion topics conclude each chapter. This uniform, student-friendly design makes it possible to teach a cohort of both philosophy and interdisciplinary students without assuming prior understanding of philosophical concepts, cognitive science, or neuroscience. Key Features: Synthesizes the now decades-long explosion of scientifically informed philosophical research in the study of mind. Expands on the offerings of other textbooks by including chapters on language, concepts and non-conceptual content, and animal cognition. Offers the same structure in each chapter, moving the reader through an overview, historical coverage, contemporary debates, and finally cutting-edge research. Packed with pedagogical features, like defined Key Terms, Suggested Readings, and Discussion Questions for each chapter, as well as a General Glossary. Provides readers with clear, chapter-long introductions to Cognitive Neuroscience, Molecular and Cellular Cognition, Experimental Methods in Cognitive Neuroscience, Philosophy of Mind, Philosophy of Science, Metaphysical Issues, and Epistemic Issues.

This book proposes a new critical relationship between computation and architecture, developing a history and theory of representation in architecture to understand and unleash potential means to open up creativity in the field. Historically, architecture has led spatial representation. Today, computation has established new representational paradigms that can be compared to spatial representations, such as the revolution of perspective in the Renaissance. Architects now use software, robotics, and fabrication tools with very little understanding and participation in how these tools influence, revolutionize, and determine both architecture and its construction today. Why does the discipline of architecture not have a higher degree of authorship in the conception and development of computational technologies that define spatial representation? This book critically explores the relationship between history, theory and cultural criticism. Lorenzo-Eiroa positions new understandings through parallel historical sections and theories of many revolutionary representational architecture canons displaced by conventional spatial projection. He identifies the architects, artists, mathematicians, and philosophers that were able to revolutionise their disciplines through the development of new technologies, new systems of representation, and new lenses to understand reality. This book frames the discussion by addressing new means to understand and expand architecture authorship in relation to survey, information, representation, higher dimensional space, Big Data, and Artificial Intelligence - in the pursuit of activating an architecture of information. This will be important reading for upper-level students and researchers of architecture and architectural theory, especially those with a keen interest in computational design and robotic fabrication.

The book describes state-of-the-art advances in simulators and emulators for quantum computing. It introduces the main concepts of quantum computing, defining q-bits, explaining the parallelism behind any quantum computation, describing measurement of the quantum state of information and explaining the process of quantum bit entanglement, collapsed state and cloning. The book reviews the concept of quantum unitary, binary and ternary quantum operators as well as the computation implied by each operator. It provides details of the quantum processor, providing its architecture, which is validated via execution simulation of some quantum instructions.

Electronic device usage has increased considerably in the past two decades. System configurations are continuously requiring upgrades; existing systems often become obsolete in a matter of 2–3 years. Green computing is the complete effective management of design, manufacture, use, and disposal, involving as little environmental impact as possible. This book intends to explore new and innovative ways of conserving energy, effective e-waste management, and renewable energy sources to harness and nurture a sustainable eco-friendly environment. This book: • Highlights innovative principles and practices using effective e-waste management and disposal • Explores artificial intelligence based sustainable models • Discovers alternative sources and mechanisms for minimizing environmental hazards • Highlights successful case studies in alternative sources of energy • Presents solid illustrations, mathematical equations, as well as practical in-the-field applications • Serves as a one-stop reference guide to stakeholders in the domain of green computing, e-waste management, renewable energy alternatives, green transformational leadership including theory concepts, practice and case studies • Explores cutting-edge technologies like internet of energy and artificial intelligence, especially the role of machine learning and deep learning in renewable energy and creating a sustainable ecosystem • Explores futuristic trends in renewable energy This book aims to address the increasing interest in reducing the environmental impact of energy as well as its further development and will act as a useful reference for engineers, architects, and technicians interested in and working with energy systems; scientists and engineers in developing countries; industries, manufacturers, inventors, universities, researchers, and interested consultants to explain the foundation to advanced concepts and research trends in the domain of renewable energy and sustainable computing. The content coverage of the book is organized in the form of 11 clear and thorough chapters providing a comprehensive view of the global renewable energy scenario, as well as how science and technology can play a vital role in renewable energy.