This graduate-level textbook elucidates low-risk and fail-safe systems in mathematical detail. It addresses, in particular, problems where mission-critical performance is paramount, such as in aircraft, missiles, nuclear reactors and weapons, submarines, and many other types of systems where "failure" can result in overwhelming loss of life and property. The book is divided into four parts: Fundamentals, Electronics, Software, and Dangerous Goods. The first part on Fundamentals addresses general concepts of system safety engineering that are applicable to any type of system. The second part, Electronics, addresses the detection and correction of electronic hazards. In particular, the Bent Pin Problem, Sneak Circuit Problem, and related electrical problems are discussed with mathematical precision. The third part on Software addresses predicting software failure rates as well as detecting and correcting deep software logical flaws (called defects). The fourth part on Dangerous Goods presents solutions to three typical industrial chemical problems faced by the system safety engineer during the design, storage, and disposal phases of a dangerous goods' life cycle.

This book presents the proceedings of the 17th Chinese Intelligent Systems Conference, held in Fuzhou, China, on Oct 16-17, 2021. It focuses on new theoretical results and techniques in the field of intelligent systems and control. This is achieved by providing in-depth study on a number of major topics such as Multi-Agent Systems, Complex Networks, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles and so on. The book is particularly suited for readers who are interested in learning intelligent system and control and artificial intelligence. The book can benefit researchers, engineers, and graduate students.

The purpose of this edited book is to provide the relevant technologies and case studies in a concise format that will simplify and streamline the processing of blockchain. The goal is for the contents of this book to change the way business transformations are conducting in economic and social systems. The book examines blockchain technology, the transaction attributes, and its footprint in various fields. It offers fundamentals and terminologies used in blockchain, architecture, and various consensus mechanisms that can be deployed in areas such as healthcare, smart cities, and supply chain management. The book provides a widespread knowledge into the deployment of security countermeasures that can be implemented for a blockchain network and enables the reader to consider the management of business processes and the implementation process in detail. The book highlights the challenges and provides various e-business case studies of security countermeasures. The book serves researchers and businesses by providing a thorough understanding of the transformation process using blockchain technology.

This book provides an overview of distributed control and distributed optimization theory, followed by specific details on industrial applications to smart grid systems. It discusses the fundamental analysis and design schemes for developing actual working smart grids and covers all aspects concerning the conventional and nonconventional methods of their use. Hybrid Intelligence for Smart Grid Systems provides an overview of a smart grid, along with its needs, benefits, challenges, and existing structure and describes the inverter topologies adopted for integrating renewable power, and provides an overview of its needs, benefits, challenges, and possible future technologies. This pioneering book is a must-read for researchers, engineering professionals, and students, giving them the tools needed to move from the concept of a smart grid to its actual design and implementation. Moreover, it will enable regulators, policymakers, and energy executives to understand the future of energy delivery systems towards safe, economical, high-quality power delivery in a dynamic and demanding environment.

Convergence of Blockchain, AI, and IoT: Concepts and Challenges discusses the convergence of three powerful technologies that play into the digital revolution and blur the lines between biological, digital, and physical objects. This book covers novel algorithms, solutions for addressing issues in applications, security, authentication, and privacy. The book provides an overview of the clinical scientific research enabling smart diagnosis equipment through AI. It presents the role these technologies play in augmented reality and blockchain, covers digital currency managed with bitcoin, and discusses deep learning and how it can enhance human thoughts and behaviors. Targeted audiences range from those interested in the technical revolution of blockchain, big data and the Internet of Things, to research scholars and the professional market.

Examines the recent research trends and the future of Cyber-Physical systems, IoT, and Autonomous Systems as it relates to Industry 4.0 Investigates various challenges across multiple sectors and different industries Offers a discussion on the recent advancements in Industry 4.0 technological developments for operations and supply chain management Explores the potential for the IoT, Autonomous and Cyber-Physical Systems to replace the current mechanical, people-based systems in various sectors Discusses additional topics such as Machine Learning and Cloud Computing

As the sister book to "Introduction to Multicopter Design and Control," published by Springer in 2017, this book focuses on using a practical process to help readers to deepen their understanding of multicopter design and control. Novel tools with tutorials on multicopters are presented, which can help readers move from theory to practice. Experiments presented in this book employ: (1) The most widely-used flight platform - multicopters - as a flight platform; (2) The most widely-used flight pilot hardware - Pixhawk - as a control platform; and (3) One of the most widely-used programming languages in the field of control engi-neering - MATLAB + Simulink - as a programming language. Based on the current advanced development concept Model-Based Design (MBD)process, the three aspects mentioned above are closely linked. Each experiment is implemented in MATLAB and Simulink, and the numerical simula-tion test is carried out on a built simulation platform. Readers can upload the controller to the Pixhawk autopilot using automatic code generation technology and form a closed loop with a given real-time simulator for Hardware-In-the-Loop (HIL) testing. After that, the actual flight with the Pixhawk autopilot can be performed. This is by far the most complete and clear guide to modern drone fundamentals I've seen.It covers every element of these advanced aerial robots and walks through examples and tutorials based on the industry's leading open-source software and tools. Read this book, and you'll be well prepared to work at the leading edge of this exciting new industry. Chris Anderson, CEO 3DR and Chairman, the Linux Foundation's Dronecode Project The development of a multicopter and its applications is very challenging in the robotics area due to the multidomain knowledge involved. This book systematically addresses the design, simulation and implementation of multicopters with the industrial leading workflow - Model-Based Design, commonly used in the automotive and aero-defense industries. With this book, researchers and engineers can seamlessly apply the concepts, workflows, and tools in other engineering areas, especially robot design and robotics ap-plication development. Dr. Yanliang Zhang, Founder of Weston Robot, EX-product Manager of Robotics System Toolbox at the MathWorks

Covers the fundamentals of shape feature extraction from images Discusses different applications of image shape feature in the field of content based image retrieval Includes polygonal approximation techniques of shape features Details moment based, scale space and geometric shape features Different approaches for extracting image shape features are reviewed affecting image retrieval from a large database

In practice, many different people with backgrounds in many different disciplines contribute to the design of an enterprise. Anyone who makes decisions to change the current enterprise to achieve some preferred structure is considered a designer. What is problematic is how to use the knowledge of separate aspects of the enterprise to achieve a globally optimized enterprise. The synthesis of knowledge from many disciplines to design an enterprise defines the field of enterprise engineering. Because enterprise systems are exceedingly complex, encompassing many independent domains of study, students must first be taught how to think about enterprise systems. Specifically written for advanced and intermediate courses and modules, Design of Enterprise Systems: Theory, Architecture, and Methods takes a system-theoretical perspective of the enterprise. It describes a systematic approach, called the enterprise design method, to design the enterprise. The design method demonstrates the principles, models, methods, and tools needed to design enterprise systems. The author uses the enterprise system design methodology to organize the chapters to mimic the completion of an actual project. Thus, the book details the enterprise engineering process from initial conceptualization of an enterprise to its final design. Pedagogical tools available include: For instructors: PowerPoint (R) slides for each chapter Project case studies that can be assigned as long-term projects to accompany the text Quiz questions for each chapter Business Process Analyzer software available for download For students: Templates, checklists, forms, and models to support enterprise engineering activities The book fills a need for greater design content in engineering curricula by describing how to design enterprise systems. Inclusion of design is also critical for business students, since they must realize the import their decisions may have on the long-term design of the enterprises they work with. The book's practical focus and project-based approach coupled with the pedagogical tools gives students the knowledge and skills they need to lead enterprise engineering projects.

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine. It will combine the design and problem-solving skills of engineering with health sciences, in order to advance healthcare treatment. The book will include areas such as diagnosis, monitoring, and therapy. The book will provide real-world case studies, gives a detailed exploration of applications in healthcare systems, offers multiple perspectives on a variety of disciplines, while also letting the reader know how to avoid some of the consequences of old methods with data sharing. The book can be used as a reference for practitioners, researchers and for students at basic and intermediary levels in Computer Science, Electronics and Communications.

Coefficient of Variation (CV) is a unit free index indicating the consistency of the data associated with a real-world process and is simple to mold into computational paradigms. This book provides necessary exposure of computational strategies, properties of CV and extracting the metadata leading to efficient knowledge representation. It also compiles representational and classification strategies based on the CV through illustrative explanations. The potential nature of CV in the context of contemporary Machine Learning strategies and the Big Data paradigms is demonstrated through selected applications. Overall, this book explains statistical parameters and knowledge representation models.

The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed. Along with focusing on the research trends, challenges and future of AI in Data Science, the book explores the potential for integration of advanced AI algorithms, addresses the challenges of Data Science for Industry 4.0, covers different security issues, includes qualitative and quantitative research, and offers case studies with working models. This book also provides an overview of AI and Data Science algorithms for readers who do not have a strong mathematical background. Undergraduates, postgraduates, academicians, researchers, and industry professionals will benefit from this book and use it as a guide.

New prospects for biomedical and healthcare engineering are being created by the rapid development of Robotic and Artificial Intelligence techniques. Innovative technologies such as Artificial Intelligence, Deep Learning, Robotics, and IoT are currently under huge influence in today's modern world. For instance, a micro-nano robot allows us to study the fundamental problems at a cellular scale owing to its precise positioning and manipulation ability; the medical robot paves a new way for the low-invasive and high-efficient clinical operation, and rehabilitation robotics is able to improve the rehabilitative efficacy of patients. This book aims at exhibiting the latest research achievements, findings, and ideas in the field of robotics in biomedical and healthcare engineering, primarily focusing on the walking assistive robot, telerobotic surgery, upper/lower limb rehabilitation, and radiosurgery. As a result, a wide range of robots are being developed to serve a variety of roles within the medical environment. Robots specializing in human treatment include surgical robots and rehabilitation robots. The field of assistive and therapeutic robotic devices is also expanding rapidly. These include robots that help patients rehabilitate from severe conditions like strokes, empathic robots that assist in the care of older or physically/mentally challenged individuals, and industrial robots that take on a variety of routine tasks, such as sterilizing rooms and delivering medical supplies and equipment, including medications. The objectives of the book are in terms of advancing the state-of-the-art of robotic techniques and addressing the challenging problems in biomedical and healthcare engineering. This book Lays a good foundation for the core concepts and principles of robotics in biomedical and healthcare engineering, walking the reader through the fundamental ideas with expert ease. Progresses on the topics in a step-by-step manner and reinforces theory with a full-fledged pedagogy designed to enhance students' understanding and offer them a practical insight into the applications of it. Features chapters that introduce and cover novel ideas in healthcare engineering like Applications of Robots in Surgery, Microrobots and Nanorobots in Healthcare Practices, Intelligent Walker for Posture Monitoring, AI-Powered Robots in Biomedical and Hybrid Intelligent Systems for Medical Diagnosis, and so on. Deepak Gupta is an Assistant Professor at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India. Moolchand Sharma is an Assistant Professor at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India. Vikas Chaudhary is a Professor at the JIMS Engineering Management Technical Campus, GGSIPU, Greater Noida, India. Ashish Khanna currently works at the Maharaja Agrasen Institute of Technology, GGSIPU, Delhi, India.

This book is for everyone interested in systems and the modern practice of engineering. The revolution in engineering and systems that has occurred over the past decade has led to an expansive advancement of systems engineering tools and languages. A new age of information-intensive complex systems has arrived with new challenges in a global business market. Science and information technology must now converge into a cohesive multidisciplinary approach to the engineering of systems if products and services are to be useful and competitive. For the non-specialist and even for practicing engineers, the subject of systems engineering remains cloaked in jargon and a sense of mystery. This need not be the case for any reader of this book and for students no matter what their background is. The concepts of architecture and systems engineering put forth are simple and intuitive. Readers and students of engineering will be guided to an understanding of the fundamental principles of architecture and systems and how to put them into engineering practice. This book offers a practical perspective that is reflected in case studies of real-world systems that are motivated by tutorial examples. The book embodies a decade of research and very successful academic instruction to postgraduate students that include practicing engineers. The material has been continuously improved and evolved from its basis in defence and aerospace towards the engineering of commercial systems with an emphasis on speed and efficiency. Most recently, the concepts, processes, and methods in this book have been applied to the commercialisation of wireless charging for electric vehicles. As a postgraduate or professional development course of study, this book will lead you into the modern practice of engineering in the twenty-first century. Much more than a textbook, though, Essential Architecture and Principles of Systems Engineering challenges readers and students alike to think about the world differently while providing them a useful reference book with practical insights for exploiting the power of architecture and systems.

From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies." ---Sartaj Sahni, University of Florida, USA "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields. --Hai Jin, Huazhong University of Science and Technology, China Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems. The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions. The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.

The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass human performance. While the success of this approach has transformed the engineering methods of machine learning in artificial intelligence, the significance of these achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic Representation looks at the application of a variety of deep learning systems to several cognitively interesting NLP tasks. It also considers the extent to which this work illuminates our understanding of the way in which humans acquire and represent linguistic knowledge. Key Features: combines an introduction to deep learning in AI and NLP with current research on Deep Neural Networks in computational linguistics. is self-contained and suitable for teaching in computer science, AI, and cognitive science courses; it does not assume extensive technical training in these areas. provides a compact guide to work on state of the art systems that are producing a revolution across a range of difficult natural language tasks.

Intelligent Support for Computer Science Education presents the authors' research journey into the effectiveness of human tutoring, with the goal of developing educational technology that can be used to improve introductory Computer Science education at the undergraduate level. Nowadays, Computer Science education is central to the concerns of society, as attested by the penetration of information technology in all aspects of our lives; consequently, in the last few years interest in Computer Science at all levels of schooling, especially at the college level, has been flourishing. However, introductory concepts in Computer Science such as data structures and recursion are difficult for novices to grasp. Key Features: Includes a comprehensive and succinct overview of the Computer Science education landscape at all levels of education. Provides in-depth analysis of one-on-one human tutoring dialogues in introductory Computer Science at college level. Describes a scalable, plug-in based Intelligent Tutoring System architecture, portable to different topics and pedagogical strategies. Presents systematic, controlled evaluation of different versions of the system in ecologically valid settings (18 actual classes and their laboratory sessions). Provides a time-series analysis of student behavior when interacting with the system. This book will be of special interest to the Computer Science education community, specifically instructors of introductory courses at the college level, and Advanced Placement (AP) courses at the high school level. Additionally, all the authors' work is relevant to the Educational Technology community, especially to those working in Intelligent Tutoring Systems, their interfaces, and Educational Data Mining, in particular as applied to human-human pedagogical interactions and to user interaction with educational software.

The fourth edition of this bestselling textbook explains the principles of artificial intelligence (AI) and its practical applications. Using clear and concise language, it provides a solid grounding across the full spectrum of AI techniques, so that its readers can implement systems in their own domain of interest. The coverage includes knowledge-based intelligence, computational intelligence (including machine learning), and practical systems that use a combination of techniques. All the key techniques of AI are explained-including rule-based systems, Bayesian updating, certainty theory, fuzzy logic (types 1 and 2), agents, objects, frames, symbolic learning, case-based reasoning, genetic algorithms and other optimization techniques, shallow and deep neural networks, hybrids, and the Lisp, Prolog, and Python programming languages. The book also describes a wide range of practical applications in interpretation and diagnosis, design and selection, planning, and control. Fully updated and revised, Intelligent Systems for Engineers and Scientists: A Practical Guide to Artificial Intelligence, Fourth Edition features: A new chapter on deep neural networks, reflecting the growth of machine learning as a key technique for AI A new section on the use of Python, which has become the de facto standard programming language for many aspects of AI The rule-based and uncertainty-based examples in the book are compatible with the Flex toolkit by Logic Programming Associates (LPA) and its Flint extension for handling uncertainty and fuzzy logic. Readers of the book can download this commercial software for use free of charge. This resource and many others are available at the author's website: adrianhopgood.com. Whether you are building your own intelligent systems, or you simply want to know more about them, this practical AI textbook provides you with detailed and up-to-date guidance.

The book investigates the role of artificial input delay in approximating unknown system dynamics, referred to as time-delayed control (TDC), and provides novel solutions to current design issues in TDC. Its central focus is on designing adaptive-switching gain-based robust control (ARC) for a class of Euler-Lagrange (EL) systems with minimal or no knowledge of the system dynamics parameters. The newly proposed TDC-based ARC tackles the commonly observed over- and under-estimation issues in switching gain. The consideration of EL systems lends a practical perspective on the proposed methods, and each chapter is supplemented by relevant experimental data. The book offers a unique resource for researchers in the areas of ARC and TDC alike, and covers the state of the art, new algorithms, and future directions.

This Newnes manual provides a practical introduction to the standard methods and techniques of assembly and wiring of electrical and electromechanical control panels and equipment. Electricians and technicians will find this a useful reference during training and a helpful memory aid at work. This is a highly illustrated guide, designed for ready use. The contents are presented in pictures and checklists. Each page has a series of 'how-to' instructions and illustrations. In this way the subject is covered in a manner which is easy to follow. Each step adds up to a comprehensive course in control panel wiring.This new edition includes extra underlying theory to help the technician plus application notes and limitations of use. Simple programmable logic controllers (PLCs) are covered, as well as new information about EMC/EMI regulations and their impact.

Viability theory designs and develops mathematical and algorithmic methods for investigating the adaptation to viability constraints of evolutions governed by complex systems under uncertainty that are found in many domains involving living beings, from biological evolution to economics, from environmental sciences to financial markets, from control theory and robotics to cognitive sciences. It involves interdisciplinary investigations spanning fields that have traditionally developed in isolation. The purpose of this book is to present an initiation to applications of viability theory, explaining and motivating the main concepts and illustrating them with numerous numerical examples taken from various fields.

Metaheuristics for Resource Deployment under Uncertainty in Complex Systems analyzes how to set locations for the deployment of resources to incur the best performance at the lowest cost. Resources can be static nodes and moving nodes while services for a specific area or for customers can be provided. Theories of modeling and solution techniques are used with uncertainty taken into account and real-world applications used. The authors present modeling and metaheuristics for solving resource deployment problems under uncertainty while the models deployed are related to stochastic programming, robust optimization, fuzzy programming, risk management, and single/multi-objective optimization. The resources are heterogeneous and can be sensors and actuators providing different tasks. Both separate and cooperative coverage of the resources are analyzed. Previous research has generally dealt with one type of resource and considers static and deterministic problems, so the book breaks new ground in its analysis of cooperative coverage with heterogeneous resources and the uncertain and dynamic properties of these resources using metaheuristics. This book will help researchers, professionals, academics, and graduate students in related areas to better understand the theory and application of resource deployment problems and theories of uncertainty, including problem formulations, assumptions, and solution methods.

The textbook, Introduction to Wavelet Transforms provides basics of wavelet transforms in a self-contained manner. Applications of wavelet transform theory permeate our daily lives. Therefore it is imperative to have a strong foundation for this subject. Features No prior knowledge of the subject is assumed. Sufficient mathematical background is provided to complete the discussion of different topics. Different topics have been properly segmented for easy learning. This makes the textbook pedagogical and unique. Notation is generally introduced in the definitions. Relatively easy consequences of the definitions are listed as observations, and important results are stated as theorems. Examples are provided for clarity and to enhance reader's understanding of the subject. Each chapter also has a problem section. A majority of the problems are provided with sufficient hints. The textbook can be used either in an upper-level undergraduate or first-year graduate class in electrical engineering, or computer science, or applied mathematics. It can also be used by professionals and researchers in the field who would like a quick review of the basics of the subject. About the Author Nirdosh Bhatnagar works in both academia and industry in Silicon Valley, California. He is also the author of a comprehensive two-volume work: Mathematical Principles of the Internet, published by the CRC Press in the year 2019. Nirdosh earned M.S. in Operations Research, and M.S. and Ph.D. in electrical engineering, all from Stanford University, Stanford, California.

This book is for everyone interested in systems and the modern practice of engineering. The revolution in engineering and systems that has occurred over the past decade has led to an expansive advancement of systems engineering tools and languages. A new age of information-intensive complex systems has arrived with new challenges in a global business market. Science and information technology must now converge into a cohesive multidisciplinary approach to the engineering of systems if products and services are to be useful and competitive. For the non-specialist and even for practicing engineers, the subject of systems engineering remains cloaked in jargon and a sense of mystery. This need not be the case for any reader of this book and for students no matter what their background is. The concepts of architecture and systems engineering put forth are simple and intuitive. Readers and students of engineering will be guided to an understanding of the fundamental principles of architecture and systems and how to put them into engineering practice. This book offers a practical perspective that is reflected in case studies of real-world systems that are motivated by tutorial examples. The book embodies a decade of research and very successful academic instruction to postgraduate students that include practicing engineers. The material has been continuously improved and evolved from its basis in defence and aerospace towards the engineering of commercial systems with an emphasis on speed and efficiency. Most recently, the concepts, processes, and methods in this book have been applied to the commercialisation of wireless charging for electric vehicles. As a postgraduate or professional development course of study, this book will lead you into the modern practice of engineering in the twenty-first century. Much more than a textbook, though, Essential Architecture and Principles of Systems Engineering challenges readers and students alike to think about the world differently while providing them a useful reference book with practical insights for exploiting the power of architecture and systems.

Proposes an integrative approach combining Human Factors Expertise with Automotive Engineering Develops an in-depth case study of design a fuel-efficient driving intervention Offers an examination of an innovative study of feed-forward eco-driving advice based on current vehicle and road environment status Presents lessons and insights gained from the current work and can be applied across domains Utilizes a documented scientific and research lead approach to designing novel speed advisory and fuel use minimisation systems suitable for combustion vehicles, hybrids, and electric vehicles