Introduces edge computing, hardware for edge computing AI, edge virtualization techniques Explores edge intelligence and deep learning applications, training and optimization Explains machine learning algorithms for edge Reviews AI on IoT Discusses future edge computing needs

This text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing. It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems. The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology. This book: * Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis. * Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems. * Presents the application of evolutionary computations for fractal visualization of sequence data. * Explores the use of genetic algorithms for pair-wise and multiple sequence alignments. * Examines the roles of efficient computational techniques in biology.

Cyber Physical System (CPS) is an integration of computation, networking, and physical processes: the combination of several systems ofdifferent nature whose main purpose is tocontrol a physical process and, through feedback, adapt itself to new conditions, in real time.Cyber Physical System: Concepts and Applications includes an in-depth coverage of the latestmodels and theories that unify perspectives. It expresses the interacting dynamics of the computational and physical components of asystem in a dynamic environment. Covers automatic application of software countermeasures against physical attacks and impact of cyber physical system on industry 4.0 Explains how formal models provide mathematical abstractions to manage the complexity of a system design Offers a rigorous and comprehensive introduction to the principles of design,specification, modelling, and analysis of cyber physicalsystems Discusses the multiple domains where Cyber Physical system has a vital impact and provides knowledge about different models thatprovide mathematical abstractions tomanage the complexity of a system design Provides the rapidly expanding field of cyber-physical systems with a Long-needed foundational text by an established authority This book is primarily aimed at advanced undergraduates, graduates of computer science. Engineers will also find this book useful.

Coding for Channels with Feedback presents both algorithms for feedback coding and performance analyses of these algorithms, including analyses of perhaps the most important performance criterion: computational complexity. The algorithms are developed within a single framework, termed the compressed-error-cancellation framework, where data are sent via a sequence of messages: the first message contains the original data; each subsequent message contains a source-coded description of the channel distortions introduced on the message preceding it. Coding for Channels with Feedback provides an easily understood and flexible framework for deriving low-complexity, practical solutions to a wide variety of feedback communication problems. It is shown that the compressed-error-cancellation framework leads to coding schemes with the lowest possible asymptotic order of growth of computations and can be applied to discrete memoryless channels, finite state channels, channels with memory, unknown channels, and multiple-access channels, all with complete noiseless feedback, as well as to channels with partial and noisy feedback. This framework leads to coding strategies that have linear complexity and are capacity achieving, and illustrates the intimate connection between source coding theory and channel coding theory. Coding for Channels with Feedback is an excellent reference for researchers and communication engineers in the field of information theory, and can be used for advanced courses on the topic.

The Internet gives the consumer almost unlimited choice in products. At the same time, it causes a globalization of consumer habits and tastes. One important question that arises is: Does the Internet and the World Wide Web offer the same opportunities for choice of services as they do for products? Service Customization Using Web Technologies aims to advance our understanding of Web-related concepts, approaches, and technologies revolving around the core theme of e-service customization. Limitless e-service choice can become possible on the Web only through customization. Understanding such customization on the Web, applied at a mass market level, in a cost efficient manner, will present an unprecedented opportunity for both the industry and the consumers. For both researchers and practitioners, understanding that as service customization accelerates through other types of industries and consumers, we will experience, the benefits of service customization in many more areas of everyday life.

Blockchain for IoT provides the basic concepts of Blockchain technology and its applications to varied domains catering to socio-technical fields. It also introduces intelligent Blockchain platforms by way of infusing elements of computational intelligence into Blockchain technology. With the help of an interdisciplinary approach, it includes insights into real-life IoT applications to enable the readers to assimilate the concepts with ease. This book provides a balanced approach between theoretical understanding and practical applications. Features: A self-contained approach to integrating the principles of Blockchain with elements of computational intelligence A rich and novel foundation of Blockchain technology with reference to the internet of things conjoined with the tenets of artificial intelligence in yielding intelligent Blockchain platforms Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Information presented in an accessible way for research students of computer science and information technology, as well as software professionals who can inherit the much-needed developmental ideas to boost up their computing knowledge on distributed platforms This book is aimed primarily at undergraduates, postgraduates, and researchers studying Blockchain.

The methods are more practical than the common probabilistic based algorithms, since these can be appiled in unknown but bounded noisy environment.

The methods are more practical than the common probabilistic based algorithms, since these can be appiled in unknown but bounded noisy environment.

This book reviews and presents several approaches to advanced decision-making models for safety and risk assessment. Each introduced model provides case studies indicating a high level of efficiency, robustness, and applicability, which allow readers to utilize them in their understudy risk-based assessment applications. The book begins by introducing a novel dynamic DEMATEL for improving safety management systems. It then progresses logically, dedicating a chapter to each approach, including advanced FMEA with probabilistic linguistic preference relations, Bayesian Network approach and interval type-2 fuzzy set, advanced TOPSIS with spherical fuzzy set, and advanced BWM with neutrosophic fuzzy set and evidence theory. This book will be of interest to professionals and researchers working in the field of system safety and reliability and postgraduate and undergraduate students studying applications of decision-making tools and expert systems.

For courses in Programmable Logic Controllers where the Allen/Bradley programmable logic controller is the controller of choice. This text focuses on the theory and operation of PLC systems with an emphasis on program analysis and development. The book is written in easy-to-read and understandable language with many crisp illustrations and practical examples. It describes the PLC instructions for the Allen-Bradley PLC 5, SLC 500, and Logix processors with an emphasis on the SLC 500 system using numerous figures, tables, and example problems. The text features a new two-column and four-color interior design that improves readability and figure placement. The book's organization also has improved; all the chapter questions and problems are listed in one convenient location in Appendix D with page locations for all chapter references in the questions and problems. This book describes the technology in a clear, concise style that is effective in helping students who have no previous experience in PLCs or discrete and analog system control. For additional resources, visit these web sites: http: //plctext.com/ http: //plcteacher.c

Data Science: A First Introduction focuses on using the R programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. The text emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. All source code is available online, demonstrating the use of good reproducible project workflows. Based on educational research and active learning principles, the book uses a modern approach to R and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The book will leave readers well-prepared for data science projects. The book is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates in the University of British Columbia's DSCI100: Introduction to Data Science course.

This book explores various intelligent algorithms including evolutionary algorithms, swarm intelligence-based algorithms for analysis and control of dynamical systems. Both single-input-single-output (SISO) and multi-input-multi-output (MIMO) systems are explored for analysis and control purposes. The applications of intelligent algorithm vary from approximation to optimal control design. The applications of intelligent algorithms not only improve understanding of a dynamical system but also enhance the control efficacy. The intelligent algorithms are now readily applied to all fields of control including linear control, nonlinear control, digital control, optimal control, etc. The book also discusses the main benefits attained due to the application of algorithms to analyze and control.

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.

Covers fundamental concepts and framework of CPS Reviews CPS and construction project management Reviews CPS applications in construction sector Covers CPS and IoT integrated network Reviews challenges and security aspects of construction CPS

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.

Features Contains ready-to-use coding recipes allowing fast prototyping and solving of mathematical problems using FEM. Suitable for upper-level undergraduates and graduates in applied mathematics, science, or engineering. Both MATLAB and Python programming codes are provided to give readers more flexibility in the practical framework implementation.

Unique selling point: Combines theory with practice and applications for advanced intelligent healthcare informatics Core audience: Researchers and academics in healthcare informatics and machine learning Place in the market: Reference work

Covers different technologies like AI, IoT and Signal Processing in the context of biomedical applications Reviews medical image analysis, disease detection, and prediction Comprehends the advantage of recent technologies for medical record keeping through electronics health records (EHRs) Presents state of art research in the field of biomedical engineering using various physiological signals Explores different Bio Sensors used in Healthcare Applications using IoT

This monograph presents controllability and stabilization methods in control theory that solve parabolic boundary value problems. Starting from foundational questions on Carleman inequalities for linear parabolic equations, the author addresses the controllability of parabolic equations on a variety of domains and the spectral decomposition technique for representing them. This method is, in fact, designed for use in a wider class of parabolic systems that include the heat and diffusion equations. Later chapters develop another process that employs stabilizing feedback controllers with a finite number of unstable modes, with special attention given to its use in the boundary stabilization of Navier-Stokes equations for the motion of viscous fluid. In turn, these applied methods are used to explore related topics like the exact controllability of stochastic parabolic equations with linear multiplicative noise. Intended for graduate students and researchers working on control problems involving nonlinear differential equations, Controllability and Stabilization of Parabolic Equations is the distillation of years of lectures and research. With a minimum of preliminaries, the book leaps into its applications for control theory with both concrete examples and accessible solutions to problems in stabilization and controllability that are still areas of current research.

Control networks span a wide range of application areas. These networks are put into action in the `Digital Home', industrial applications, commercial buildings, transportation systems, gas stations, security systems, and they are found in most instances where smart sensors and smart actuators are used to exchange information. The authors of this volume provide an overview of various control network protocols and discuss LonTalk (R) protocol, Neuron (R) chip, programming model, network structures, network management, interoperability between nodes, application profiles, development and maintenance tools, performance analysis, and standardization activities. Open Control Networks: LonWorks/EIA 709 Technology will be an important resource for advanced students of control systems and embedded systems, engineers designing distributed networks, systems designers and architects, and others developing smart buildings and intelligent transportation systems.

Optimal Impulsive Control explores the class of impulsive dynamic optimization problems-problems that stem from the fact that many conventional optimal control problems do not have a solution in the classical setting-which is highly relevant with regard to engineering applications. The absence of a classical solution naturally invokes the so-called extension, or relaxation, of a problem, and leads to the notion of generalized solution which encompasses the notions of generalized control and trajectory; in this book several extensions of optimal control problems are considered within the framework of optimal impulsive control theory. In this framework, the feasible arcs are permitted to have jumps, while the conventional absolutely continuous trajectories may fail to exist. The authors draw together various types of their own results, centered on the necessary conditions of optimality in the form of Pontryagin's maximum principle and the existence theorems, which shape a substantial body of optimal impulsive control theory. At the same time, they present optimal impulsive control theory in a unified framework, introducing the different paradigmatic problems in increasing order of complexity. The rationale underlying the book involves addressing extensions increasing in complexity from the simplest case provided by linear control systems and ending with the most general case of a totally nonlinear differential control system with state constraints. The mathematical models presented in Optimal Impulsive Control being encountered in various engineering applications, this book will be of interest to both academic researchers and practising engineers.

This book has been created on the basis of contributions to the 54th International Conference of Machine Design Departments that was held for the 60th anniversary of Technical University of Liberec. This international conference which follows a tradition going back more than 50 years is one of the longest-running series of conferences held in central Europe, dealing with methods and applications inmachine design. The main aim of the conference was to provide an international forum where experts, researchers, engineers and industrial practitioners, managers and Ph.D. students could meet, share their experiences and present the results of their efforts in the broad field of machine design and related fields.

The book has seven chapters which focus on new knowledge of machine design, optimization, tribology, experimental methods and measuring, engineering analyses and product innovation. Authors presented new design methods of machine parts and more complex assemblies with the help of numerical methods such as FEM. Research, measurements and studies of new materials, including composites for energy-efficient constructions are also described. The book also includes solutions and results useful for optimization and innovation of complex design problems in various industries."

This book presents recent advances in fault diagnosis and fault-tolerant control of dynamic processes. Its impetus derives from the need for an overview of the challenges of the fault diagnosis technique and sustainable control, especially for those demanding systems that require reliability, availability, maintainability, and safety to ensure efficient operations. Moreover, the need for a high degree of tolerance with respect to possible faults represents a further key point, primarily for complex systems, as modeling and control are inherently challenging, and maintenance is both expensive and safety-critical. Diagnosis and Fault-tolerant Control 2 also presents and compares different fault diagnosis and fault-tolerant schemes, using well established, innovative strategies for modeling the behavior of the dynamic process under investigation. An updated treatise of diagnosis and fault-tolerant control is addressed with the use of essential and advanced methods including signal-based, model-based and data-driven techniques. Another key feature is the application of these methods for dealing with robustness and reliability.

This monograph develops a framework for time-optimal control problems, focusing on minimal and maximal time-optimal controls for linear-controlled evolution equations. Its use in optimal control provides a welcome update to Fattorini's work on time-optimal and norm-optimal control problems. By discussing the best way of representing various control problems and equivalence among them, this systematic study gives readers the tools they need to solve practical problems in control. After introducing preliminaries in functional analysis, evolution equations, and controllability and observability estimates, the authors present their time-optimal control framework, which consists of four elements: a controlled system, a control constraint set, a starting set, and an ending set. From there, they use their framework to address areas of recent development in time-optimal control, including the existence of admissible controls and optimal controls, Pontryagin's maximum principle for optimal controls, the equivalence of different optimal control problems, and bang-bang properties. This monograph will appeal to researchers and graduate students in time-optimal control theory, as well as related areas of controllability and dynamic programming. For ease of reference, the text itself is self-contained on the topic of time-optimal control. Frequent examples throughout clarify the applications of theorems and definitions, although experience with functional analysis and differential equations will be useful.

The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs. The simulation results that appear in each chapter include rigorous mathematical analyses, based on the Lyapunov approach, to establish its properties. The book contains two sections: the first focuses on the analyses of control techniques; the second is dedicated to illustrating results of real-time applications. It also provides solutions for the output trajectory tracking problem of unknown nonlinear systems based on sliding modes and inverse optimal control scheme. "This book on Discrete-time Recurrent Neural Control is unique in the literature, with new knowledge and information about the new technique of recurrent neural control especially for discrete-time systems. The book is well organized and clearly presented. It will be welcome by a wide range of researchers in science and engineering, especially graduate students and junior researchers who want to learn the new notion of recurrent neural control. I believe it will have a good market. It is an excellent book after all." - Guanrong Chen, City University of Hong Kong "This book includes very relevant topics, about neural control. In these days, Artificial Neural Networks have been recovering their relevance and well-stablished importance, this due to its great capacity to process big amounts of data. Artificial Neural Networks development always is related to technological advancements; therefore, it is not a surprise that now we are being witnesses of this new era in Artificial Neural Networks, however most of the developments in this research area only focuses on applicability of the proposed schemes. However, Edgar N. Sanchez author of this book does not lose focus and include both important applications as well as a deep theoretical analysis of Artificial Neural Networks to control discrete-time nonlinear systems. It is important to remark that first, the considered Artificial Neural Networks are development in discrete-time this simplify its implementation in real-time; secondly, the proposed applications ranging from modelling of unknown discrete-time on linear systems to control electrical machines with an emphasize to renewable energy systems. However, its applications are not limited to these kind of systems, due to their theoretical foundation it can be applicable to a large class of nonlinear systems. All of these is supported by the solid research done by the author." - Alma Y. Alanis, University of Guadalajara, Mexico "This book discusses in detail; how neural networks can be used for optimal as well as robust control design. Design of neural network controllers for real time applications such as induction motors, boost converters, inverted pendulum and doubly fed induction generators has also been carried out which gives the book an edge over other similar titles. This book will be an asset for the novice to the experienced ones." - Rajesh Joseph Abraham, Indian Institute of Space Science & Technology, Thiruvananthapuram, India