This book shows some secure control methods of networked control systems related to linear control system, nonlinear control system, multi-agent system and its applications in power systems. The proposed secure control methods provide some useful results about modeling of network attacks, resilient analysis and synthesis methods, active defense control method.The contents of this book are lists as followings. (1) Modeling of DoS attacks, deception attacks and replay attacks; (2)Secure control methods are proposed by combing delay system method, switched system method and event-based control method. (3) Active control methods are proposed by using model-predictive control and redundant control. (4) The proposed control methods are applied to the security problem of power system.The methods of this book include DoS attacks modeling such as, periodic jamming attack model,model-based average dwell time model, deception attack modeling and relay attack modeling; piece-wise Lyapunov-Krasoviskiifunctional method, stochastic control method; the results including resilient conditions of networked control system and related resilient control design method with linear matrix inequalities(LMIs).From this book, readers can learn about the general network attack modeling methods, resilient analysis and synthesis methods, active control methods from viewpoint of redundancy control, and secure conditions of power systems.Some fundamental knowledge prepared to read this book includes delay system theory, event triggered mechanism, T-S fuzzy system theory and frequency/voltage control of power system.

This book focuses primarily on both technical and business aspects needed to select, design, develop and deploy control application (or product) successfully for multiple components in building systems. Designing and deploying a control application require multiple steps such as sensing, system dynamics modelling, algorithms, and testing. This may involve choosing an appropriate methodology and technique at multiple stages during the development process. Understanding the pros and cons of such techniques, most importantly being aware of practically possible approaches in the entire ecosystem, is critical in choosing the best framework and system application for different parts of building systems. Providing a wide overview of the state-of art in controls and building systems, providing guidance on developing an end-to-end system in relation to business fundamentals (distribution channels, stakeholders, marketing, supply-chain and financial management), the book is ideal for fourth-year control/mechanical/electrical engineering undergraduates, graduate students, and practitioners including business leaders concerned with smart building technology.

Discusses the challenges of automation and automated systems, when humans are left out of the loop, but need to intervene when necessary Provides human control and accepting that humans must handle the unexpected and describes methods to support this Based on recent accident analysis involving autonomous systems and helping to move our understanding forward Supports a more modern view on human errors in order to improve safety in the shipping/marine industry Describes human centered design as a fundamental issue to support the ability of sensemaking

Design of analog multipliers discusses what an analog multiplier and its related types is, how different types of analog multipliers are implemented with analog two to one multiplexers and op-amps, and how the types of analog multipliers are implemented with transistors and op-amps. Describing forty-eight analog multiplier circuits, book explains six building blocks as integrator, comparator, switch, low pass filter, peak detector and sample & hold circuit. All analog multiplier circuits presented in this book use a maximum of four operational amplifiers which will enable the readers to simulate the multipliers with minimum number of components and use for their application at low cost.

The book uses a systems-based approach to show how innovation is pervasive in all facets of endeavors, including business, industrial, government, the military, and even academia. It presents chapters that provide techniques and methodologies for achieving the transfer of science and technology assets for innovation applications. By introducing Innovation, the book and offers different viewpoints, both qualitative and quantitative. It includes the role that systems can play and discusses approaches along technical and process issues. There is a showcase of innovation applications, and coverage on how to manage innovation individually as well as within a team and it also includes how to develop, manage, and sustain innovation in various organizations. Open-ended questions and exercises are included at the end of chapters with no need for a solutions manual. Written for the advance-level textbook market as well as for the professional reader, it targets those within the engineering, business, and management fields.

Provides a structured look, at the unique characteristic for smart sensor networks to resolving the issues of many real-world applications in a broad range of areas such as Smart Healthcare, Engineering, Scientific Research, Social Media, Industrial Automation and more Offers a systematic look at the unique characteristics of AI based wireless sensor networks through their usage in a broad range of areas Delivers recent trends and core concepts in both analytics and application in smart sensor networks using AI Explores the development and application of AI and evolutionary computing as applied to wireless sensor networks Focuses on stepwise discussion, exhaustive literature review, detailed analysis and discussion, rigorous experimentation result and an application-oriented approach.

The aim of this book is to present new computational techniques and methodologies for the analysis of the clinical, epidemiological and public health aspects of SARS-CoV-2 and COVID-19 pandemic. The book presents the use of soft computing techniques such as machine learning algorithms for analysis of the epidemiological aspects of the SARS-CoV-2. This book clearly explains novel computational image processing algorithms for the detection of COVID-19 lesions in lung CT and X-ray images. It explores various computational methods for computerized analysis of the SARS-CoV-2 infection including severity assessment. The book provides a detailed description of the algorithms which can potentially aid in mass screening of SARS-CoV-2 infected cases. Finally the book also explains the conventional epidemiological models and machine learning techniques for the prediction of the course of the COVID-19 epidemic. It also provides real life examples through case studies. The book is intended for biomedical engineers, mathematicians, postgraduate students; researchers; medical scientists working on identifying and tracking infectious diseases.

Addresses real-world challenges in using AI Covers the entire AI process in a holistic manner Explains the technical issues in an easy to use manner Provides real-world examples of AI enablement Addresses the challenges of complex enterprises, coalitions and consortia Avoids the hype, with balanced perspective on benefits and drawbacks of AI

Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards. The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community. In recent years social media has gained significant popularity and has become an essential medium of communication. Such user-generated content provides an excellent scenario for applying the metaphor of mining any information. Transfer learning is a research problem in machine learning that focuses on leveraging the knowledge gained while solving one problem and applying it to a different, but related problem. Features: Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity Presents a detailed study of existing research Provides convergence and complexity analysis of the frameworks Includes algorithms to implement the proposed research work Covers extensive empirical analysis Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community.

Lays out a step-by-step approach to identify relevant tools and methods for UAS data/image acquisition and processing Provides practical hands-on knowledge with visual interpretation, well-organized and designed for a typical, 16-week, UAS course offered on college and university campuses Suitable for all levels of readers and does not require prior knowledge of UAS, remote sensing, digital image processing, or geospatial analytics Includes real-world environmental applications along with data interpretations and software used, often non-proprietary Combines the expertise of a wide range of UAS researchers and practitioners across the geospatial sciences

Optimal Networked Control Systems with MATLAB (R) discusses optimal controller design in discrete time for networked control systems (NCS). The authors apply several powerful modern control techniques in discrete time to the design of intelligent controllers for such NCS. Detailed derivations, rigorous stability proofs, computer simulation examples, and downloadable MATLAB (R) codes are included for each case. The book begins by providing background on NCS, networked imperfections, dynamical systems, stability theory, and stochastic optimal adaptive controllers in discrete time for linear and nonlinear systems. It lays the foundation for reinforcement learning-based optimal adaptive controller use for finite and infinite horizons. The text then: Introduces quantization effects for linear and nonlinear NCS, describing the design of stochastic adaptive controllers for a class of linear and nonlinear systems Presents two-player zero-sum game-theoretic formulation for linear systems in input-output form enclosed by a communication network Addresses the stochastic optimal control of nonlinear NCS by using neuro dynamic programming Explores stochastic optimal design for nonlinear two-player zero-sum games under communication constraints Treats an event-sampled distributed NCS to minimize transmission of state and control signals within the feedback loop via the communication network Covers distributed joint optimal network scheduling and control design for wireless NCS, as well as the effect of network protocols on the wireless NCS controller design An ideal reference for graduate students, university researchers, and practicing engineers, Optimal Networked Control Systems with MATLAB (R) instills a solid understanding of neural network controllers and how to build them.

Systems Thinker's Toolbox: Tools for Managing Complexity provides more than 100 tools based on systems thinking and beyond. Each tool is described, and when necessary, examples are provided of how each of them can be used. Some of the simplest tools can be combined into more complex tools. The tools may be things such as lists, causal loops, and templates, as well as processes and methodologies. Key Features Provides an explanation of the two views of systems thinking; systemic and systematic thinking, and then shows how to perform each of them in a complimentary manner Presents a set of thinking tools that can be used to apply systems thinking to solving problems in project management, engineering, systems engineering, new product development, and business Describes the tools from simple such as lists, and goes on to more complex such as Categorized Requirements in Process (CRIP) charts, and then onto the processes Introduces new tools that have been tested with positive feedback Discusses a set of communication tools that can improve project reviews and communicating innovative ideas

This book describes the methods and algorithms for image pre-processing and recognition. These methods are based on a parallel shift technology of the imaging copy, as well as simple mathematical operations to allow the generation of a minimum set of features to describe and recognize the image. This book also describes the theoretical foundations of parallel shift technology and pattern recognition. Based on these methods and theories, this book is intended to help researchers with artificial intelligence systems design, robotics, and developing software and hardware applications.

Recently, many books on multiobjective programming have been published. However, only a few books have been published, in which multiobjective programming under the randomness and the fuzziness are investigated. On the other hand, several books on multilevel programming have been published, in which multiple decision makers are involved in hierarchical decision situations. In this book, we introduce the latest advances in the field of multiobjective programming and multilevel programming under uncertainty. The reader can immediately use proposed methods to solve multiobjective programming and multilevel programming, which are based on linear programming or convex programming technique. Organization of each capter is summarized as follows. In Chapter 2, multiobjective programming problems with random variables are formulated, and the corresponding interactive algorithms are developed to obtain a satisfactory solution, in which the fuzziness of human's subjective judgment for permission levels are considered. In Chapter 3, multiobjective programming problems with fuzzy random variables are formulated, and the corresponding interactive algorithms are developed to obtain a satisfactory solution, in which not only the uncertainty of fuzzy random variables but also the fuzziness of human's subjective judgment for permission levels are considered. In Chapter 4, multiobjective multilevel programming is discussed, and the interactive algorithms are developed to obtain a satisfactory solution, in which the hierarchical decision structure of multiple decision makers is reflected. In Chapter 5, two kinds of farm planning problems are solved by applying the proposed method, in which cost coefficients of crops are expressed by random variables.

Talks about securing healthcare data using Blockchain and Cryptography Discusses challenges and solutions for Blockchain technology in the healthcare sector Presents digital transformation of the healthcare sector using different technologies Covers the handling of healthcare data/medical records using Blockchain technology Explores managing the medical supply chain using Blockchain technology

Revised chapters from the previous edition, with the inclusion of many additional materials on some important topics, including compress sensing, estimation with convex constraints, the slope estimator, simultaneously low rank and row sparse linear regression, or aggregation of a continuous set of estimators. Three new chapters on iterative algorithms, clustering and minimax lower bounds. Enhanced appendices,minimax lower-bounds mainly with the addition of Davis-Kahan perturbation bound and of two simple versions of Hanson-Wright concentration inequality.

This book focuses on new developments in polytopic projects, particularly on implementation domains and case studies, as well as high-dimensional methodology. Polytopic projects are based on a general reference architecture inspired and shared by the functional organization of organisms and enterprises as informational and cognitive systems, the scientific and engineering methodology and the operational structure of existing self-evolvable and self-sustainable systems.

An up-to-date text designed for undergraduate courses in control systems engineering and principles of automatic controls. The book focuses on design and implementation rather than just the mathematics of control systems. Using a balanced approach, the text presents a unified energy-based approach to modeling; covers analysis techniques for the models presented; and offers a detailed study of digital control and the implementation of digital controllers. Also included are examples and homework problems.

This book gathers high-quality papers presented at International Conference on Science, Technology and Innovation for Society (CITIS 2021), held in Guayaquil, Ecuador, on May 26-28, 2021. This book will present the recent research trends in the fields of software engineering, big data analysis, cloud computing, data engineering, data management and data mining, machine learning, deep learning, artificial intelligence, smart systems, robotics and automation, mechatronic design, and industrial processes design.

This book examines the problems of power systems in fields related to optimization of operating modes of electric power facilities and their control systems, information and measuring systems and metrological support in the electric power industry, ensuring the functioning of the electric power system in the conditions of a competitive market of the electric power. The book is devoted to modern problems ensuring operational reliability and safety of objects integrated power system of Ukraine. It is complex task, solution of which is related to optimization of operating modes of electric power facilities and their control systems, creating diagnostic systems for the electric power industry, ensuring the functioning of the electric power system in the conditions of a competitive market of the electric power. The presented research results in book allow increasing the reliability and efficiency of operation of energy facilities and ensuring the stability of power systems, the introduction of effective methods and tools for forecasting electricity supply, optimize power systems, suggest road map to integrate electricity markets taking into account network constraints in modern conditions of electricity markets. The book includes eight chapters. A book is for researchers, engineers, as well as lecturers and postgraduates of higher education institutions dealing with problems of operation, control, diagnosis and monitoring of integrated power system, power equipment and other.

This book includes selected peer-reviewed papers presented at the International Conference on Modeling, Simulation and Optimization, organized by National Institute of Technology, Silchar, Assam, India, during 3-5 August 2020. The book covers topics of modeling, simulation and optimization, including computational modeling and simulation, system modeling and simulation, device/VLSI modeling and simulation, control theory and applications, modeling and simulation of energy system and optimization. The book disseminates various models of diverse systems and includes solutions of emerging challenges of diverse scientific fields.

Recent progress in artificial intelligence (AI) has revolutionized our everyday life. Many AI algorithms have reached human-level performance and AI agents are replacing humans in most professions. It is predicted that this trend will continue and 30% of work activities in 60% of current occupations will be automated. This success, however, is conditioned on availability of huge annotated datasets to training AI models. Data annotation is a time-consuming and expensive task which still is being performed by human workers. Learning efficiently from less data is a next step for making AI more similar to natural intelligence. Transfer learning has been suggested a remedy to relax the need for data annotation. The core idea in transfer learning is to transfer knowledge across similar tasks and use similarities and previously learned knowledge to learn more efficiently. In this book, we provide a brief background on transfer learning and then focus on the idea of transferring knowledge through intermediate embedding spaces. The idea is to couple and relate different learning through embedding spaces that encode task-level relations and similarities. We cover various machine learning scenarios and demonstrate that this idea can be used to overcome challenges of zero-shot learning, few-shot learning, domain adaptation, continual learning, lifelong learning, and collaborative learning.

The development of computer software for nonlinear control systems has provided many benefits for teaching, research, and the development of control systems design. MATLAB is considered the dominant software platforms for linear and nonlinear control systems analysis. This book provides an easy way to learn nonlinear control systems such as feedback linearization technique and Sliding mode control (Structure variable control) which are one of the most used techniques in nonlinear control dynamical systems; therefore teachers-students and researchers are all in need to handle such techniques; and since they are too difficult for them to handle such nonlinear controllers especially for a more complicated systems such as induction motor, satellite, and vehicles dynamical models. Thus, this document it is an excellent resource for learning the principle of feedback linearization and sliding mode techniques in an easy and simple way: Provides a briefs description of the feedback linearization and sliding mode control strategies Includes a simple method on how to determine the right and appropriate controller (P-PI-PID) for feedback linearization control strategy. A Symbolic MATLAB Based function for finding the feedback linearization and sliding mode controllers are developed and tested using several examples. A simple method for finding the approximate sliding mode controller parameters is introduced Where the program used to construct the nonlinear controller uses symbolic computations; such that the user should provide the program with the necessary functions f(x), g(x) and h(x) using the symbolic library.

Many governments around the world are calling for the use of biometric systems to provide crucial societal functions, consequently making it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system security may prove to be inadequate for large-scale applications to process millions of users at a high rate of throughput. This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security-related issues. The book will present a computational perspective, identify challenges, and cover new problem-solving strategies, offering solved problems and case studies to help with reader comprehension and deep understanding. This book is written for researchers, practitioners, both undergraduate and post-graduate students, and those working in various engineering fields such as Systems Engineering, Computer Science, Information Technology, Electronics, and Communications.

This book presents two nonlinear control strategies for complex dynamical networks. First, sliding-mode control is used, and then the inverse optimal control approach is employed. For both cases, model-based is considered in Chapter 3 and Chapter 5; then, Chapter 4 and Chapter 6 are based on determining a model for the unknow system using a recurrent neural network, using on-line extended Kalman filtering for learning. The book is organized in four sections. The first one covers mathematical preliminaries, with a brief review for complex networks, and the pinning methodology. Additionally, sliding-mode control and inverse optimal control are introduced. Neural network structures are also discussed along with a description of the high-order ones. The second section presents the analysis and simulation results for sliding-mode control for identical as well as non-identical nodes. The third section describes analysis and simulation results for inverse optimal control considering identical or non-identical nodes. Finally, the last section presents applications of these schemes, using gene regulatory networks and microgrids as examples.