This book bridges fundamental gaps between control theory and formal methods. Although it focuses on discrete-time linear and piecewise affine systems, it also provides general frameworks for abstraction, analysis, and control of more general models. The book is self-contained, and while some mathematical knowledge is necessary, readers are not expected to have a background in formal methods or control theory. It rigorously defines concepts from formal methods, such as transition systems, temporal logics, model checking and synthesis. It then links these to the infinite state dynamical systems through abstractions that are intuitive and only require basic convex-analysis and control-theory terminology, which is provided in the appendix. Several examples and illustrations help readers understand and visualize the concepts introduced throughout the book.

This book presents a comprehensive analysis and modelling of demand, capacity, quality of services, economics, and sustainability of the air transport system and its main components - - airports, airlines, and ATC/ATM (Air Traffic Control/Management). Airports consist of the airside and landside area characterized by their capacities for handling demand such as aircraft, air passengers, and air freight/cargo shipments. Regarding spatial configuration, airlines generally operate hub-and-spoke (conventional or legacy airlines) and point-to-point (LCCs - Low Cost Carriers) air route networks. Their fleets consisting of different aircraft types provide transport capacity for serving demand including air passengers and freight/cargo shipments. The ATC/ATM includes the controlled airspace, traffic management and control facilities and equipment on the ground, space, and on board aircraft, and the ATC Controllers). They all provide capacity to handle demand consisting of the flights between origin and destination airports carried out by airline aircraft. The outcome from the interrelationships between demand and capacity at these components materializes as the quality of services. At airports and airlines this is generally expressed by congestion and delays of aircraft, air passengers, and freight/cargo shipments. At ATC/ATM, this is expressed by delays, horizontal and vertical in-efficiency, and safety of flights. Economics of each component relate to its revenues, costs, and profits from handling demand, i.e., providing services of given quality. The sustainability of air transport system has become increasingly important issue for many internal and external actors/stakeholders involved to deal with. This has implied increasing the system's overall social-economic effects/benefits while reducing or maintaining constant impacts/costs on the environment and society at both global and regional/local scale under conditions of continuous medium- to long term growth.

Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders' attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system's ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world.

This congress proceedings provides recent research on leading-edge manufacturing processes. The aim of this scientific congress is to work out diverse individual solutions of "production in the border area" and transferable methodological approaches. In addition, guest speakers with different backgrounds will give the congress participants food for thoughts, interpretations, views and suggestions. The manufacturing industry is currently undergoing a profound structural change, which on the one hand produces innovative solutions through the use of high-performance communication and information technology, and on the other hand is driven by new requirements for goods, especially in the mobility and energy sector. With the social discourse on how we should live and act primarily according to guidelines of sustainability, structural change is gaining increasing dynamic. It is essential to translate politically specified sustainability goals into socially accepted and marketable technical solutions. Production research is meeting this challenge and will make important contributions and provide innovative solutions from different perspectives.

This present book provides valuable insights on the technical, societal and legal challenges posed by the use of artificial intelligent systems in a plethora of different applications, from embodied robotic systems to ML algorithms. Engaging with concerns about equity, privacy, surveillance and respect for human dignity, "Towards Trustworthy Artificial Intelligent Systems" highlights the fundamental factors on which stakeholders' trust relies, identifying benchmarking, standardisation and certification as milestones grounding and consolidating that future trust. The multidisciplinary approach followed will make this book a valuable resource for all those involved in the production and deployment of AIs, as well as for academia and legal practitioners.

This book is intended for researchers, graduate students and engineers in the fields of structure-borne sound, structural dynamics, and noise and vibration control. Based on vibration differential equations, it presents equations derived from the exponential function in the time domain, providing a unified framework for structural vibration analysis, which makes it more regular and normalized. This wave propagation approach (WPA) divides structures at "discontinuity points," and the waves show characteristics of propagation, reflection, attenuation, and waveform conversion. In each segment of the system between two "discontinuity points," the governing equation and constraint are expressed accurately, allowing the dynamic properties of complex systems to be precisely obtained. Starting with basic structures such as beams and plates, the book then discusses theoretical research on complicated and hybrid dynamical systems, and demonstrates that structural vibration can be analyzed from the perspective of elastic waves by applying WPA.

With the growing use of feedback controls, "hard" nonlinearities have become ubiquitous in engineering practice despite their rare treatment in academic texts. This book introduces a unified adaptive inverse approach for the control of systems with unknown nonlinearities and settles long-standing engineering problems posed by imperfections of actuators and sensors.

Focusing on dead-zone, backlash, and hysteresis, the authors show how real-time computations can counteract the effects of these nonlinearities. In many applications their approach avoids the need for costly and specialized hardware.

This easy-to-use, self-contained presentation of the entirely new adaptive inverse design is geared towards practicing engineers, researchers, and graduate students.

Adaptive Control of Systems with Actuator and Sensor Nonlinearities features:

• Systematic treatment for actuator and sensor nonlinearities.
• Examples of dead-zone, backlash, and hysteresis models and their inverses.
• Broad coverage that ranges from satellite antennas and piezo-positioners to industrial automation and consumer electronics.
• Step-by-step instructions for adaptive inverse design and implementation.
• Unified continuous- and discrete-time presentation.
• A concise review of model reference adaptive control theory.
• Extensive illustrations of system performance improvement.
• Over ninety figures and design examples.

The book presents a significant expansion in depth and breadth of the previous edition. It includes substantially more numerical illustrations and copious supporting MATLAB code that the reader can use to replicate illustrations or build his or her own. The code is deliberately written to be as simple as possible and easy to edit. The book is an excellent starting point for any researcher to gain a solid grounding in MPC concepts and algorithms before moving into application or more advanced research topics. Sample problems for readers are embedded throughout the chapters, and in-text questions are designed for readers to demonstrate an understanding of concepts through numerical simulation.

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

Explains the basis of Brain Computer Interface and how it can be established using different EEG signal characteristics Covers the detail classification of different types of EEG signals with respect to their physical characteristics Explains detection and diagnosis of epileptic seizures from EEG data of a subject Reviews design and development a low cost and robust EEG acquisition system Provides mathematical analysis of EEG including MATLAB codes for students to experiment with EEG data

This textbook is a concise yet precise supplement to traditional books on Signals and Systems, focusing exclusively on the continuous-time case. Students can use this guide to review material, reinforce their understanding, and see how all the parts connect together in a uniform treatment focused on mathematical clarity. Readers learn the "what", "why" and "how" about the ubiquitous Fourier and Laplace transforms encountered in the study of linear time-invariant systems in engineering: what are these transforms, why do we need them, and how do we use them? Readers will come away with an understanding of the gradual progression from time-domain analysis to frequency-domain and s-domain techniques for continuous-time linear time-invariant systems. This book reflects the author's experience in teaching this material for over 25 years in sophomore- and junior-level required engineering courses and is ideal for undergraduate classes in electrical engineering.

This book contains all refereed papers accepted during the tenth edition of the conference that took place at the Cite Internationale Universitaire de Paris on December 12-13, 2019. Mastering complex systems requires an integrated understanding of industrial practices as well as sophisticated theoretical techniques and tools. This explains the creation of an annual go-between forum in Paris dedicated to academic researchers & industrial actors working on complex industrial systems architecture, modeling & engineering. These proceedings cover the most recent trends in the emerging field of Complex Systems, both from an academic and a professional perspective. A special focus is put on "Systems Engineering through the ages". The CSD&M Paris 2019 conference is organized under the guidance of CESAM Community. It has been developed since 2010 by the non-profit organization CESAMES Association to organize the sharing of good practices in Enterprise and Systems Architecture and to certify the level of knowledge and proficiency in this field through CESAM certification.

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.

Mathematical modeling is a powerful craft that requires practice. The more practice the better one will become in executing the art. The authors wrote this book to develop the craft of mathematical modeling and to foster a desire for lifelong learning, habits of mind and develop competent and confident problem solvers and decision makers for the 21st century. This book offers a problem-solving approach. The authors introduce a problem to help motivate the learning of a particular mathematical modeling topic. The problem provides the issue or what is needed to solve using an appropriate modeling technique. Then principles are applied to the problem and present the steps in obtaining an appropriate model to solve the problem. Modeling Change and Uncertainty: Covers both linear and nonlinear models of discrete dynamical systems. Introduces statistics and probability modeling. Introduces critical statistical concepts to handle univariate and multivariate data. Establishes a foundation in probability modeling. Uses ordinary differential equations (ODEs) to develop a more robust solution to problems. Uses linear programming and machine learning to support decision making. Introduces the reality of uncertainty and randomness that is all around us. Discusses the use of linear programing to solve common problems in modern industry. Discusses he power and limitations of simulations. Introduces the methods and formulas used in businesses and financial organizations. Introduces valuable techniques using Excel, MAPLE, and R. Mathematical modeling offers a framework for decision makers in all fields. This framework consists of four key components: the formulation process, the solution process, interpretation of the solution in the context of the actual problem, and sensitivity analysis. Modeling Change and Uncertainty will be of interest to mathematics departments offering advanced mathematical modeling courses focused on decision making or discrete mathematical modeling and by undergraduate, graduate students and practitioners looking for an opportunity to develop, practice, and apply the craft of mathematical modeling. Table of Contents 1. Perfect Partners: Combining Models of Change and Uncertainty with Technology 2. Modeling Change: Discrete Dynamical Systems (DDS) and Modeling Systems of DDS 3. Statistical and Probabilistic Models 4. Modeling with Probability 5. Differential Equations 6. Forecasting with Linear Programming and Machine Learning 7. Stochastic Models and Markov Chains 8. Linear Programming 9. Simulation of Queueing Models 10. Modeling of Financial Analysis 11. Reliability Models 12. Machine Learning and Unconstrained Optimal Process Dr. William P. Fox is currently a visiting professor of Computational Operations Research at the College of William and Mary. He is an emeritus professor in the Department of Defense Analysis at the Naval Postgraduate School and teaches a three-course sequence in mathematical modeling for decision making. He received his Ph.D. in Industrial Engineering from Clemson University. He has taught at the United States Military Academy for twelve years until retiring and at Francis Marion University where he was the chair of mathematics for eight years. He has many publications and scholarly activities including twenty plus books and one hundred and fifty journal articles. Colonel (R) Robert E. Burks, Jr., Ph.D. is an Associate Professor in the Defense Analysis Department of the Naval Postgraduate School (NPS) and the Director of the NPS' Wargaming Center. He holds a Ph.D. in Operations Research from the Air Force Institute of Technology. He is a retired logistics Army Colonel with more than thirty years of military experience in leadership, advanced analytics, decision modeling, and logistics operations who served as an Army Operations Research analyst at the Naval Postgraduate School, TRADOC Analysis Center, United States Military Academy, and the United States Army Recruiting Command. Other book by William P. Fox and Robert E. Burks: Advanced Mathematical Modeling with Technology, 2021, CRC Press. Other books by William P. Fox from CRC Press: Mathematical Modeling in the Age of the Pandemic, 2021, CRC Press. Advanced Problem Solving Using Maple: Applied Mathematics, Operations Research, Business Analytics, and Decision Analysis (w/William Bauldry), 2020, CRC Press. Mathematical Modeling with Excel (w/Brian Albright), 2020, CRC Press. Nonlinear Optimization: Models and Applications, 2020, CRC Press. Advanced Problem Solving with Maple: A First Course (w/William Bauldry), 2019. CRC Press. Mathematical Modeling for Business Analytics, 2018, CRC Press.

This book provides cutting edge insight into systems dynamics, as applied to engineering systems including control systems. The coverage is intended for both students and practicing engineers. Updated throughout in the second edition, it serves as a firm foundation to develop expertise in design, simulation, prototyping, control, instrumentation, experimentation, and performance analysis.

Providing a clear discussion of system dynamics, the book enables students and professionals to both understand and subsequently model mechanical, thermal, fluid, electrical, and multi-physics systems in a systematic, unified and integrated manner, which leads to a "unique" model. Concepts of through-and across-variables are introduced and applied, alongside tools of modeling and model-representation such as linear graphs and block diagrams. The book uses and illustrates popular software tools such as SIMULINK, throughout, and additionally makes use of innovative worked examples and case studies, alongside problems and exercises based on practical situations.

The book is a crucial companion to undergraduate and postgraduate mechanical engineering and other engineering students, alongside professionals in the field. Complete solutions to end-of-chapter problems are provided in a Solutions Manual that is available to instructors.

Table of Contents

Chapter 1 Introduction to Modeling

Chapter 2 Basic Model Elements

Chapter 3 Analytical Modeling

Chapter 4 Model Linearization

Chapter 5 Linear Graphs

Chapter 6 Frequency-Domain Models

Chapter 7 Transfer-Function Linear Graphs

Appendix A: Graph-Tree Concepts for Linear Graphs

Appendix B: MATLAB Toolbox for Linear Graphs

A powerful, yet easy-to-use design methodology for the control of nonlinear dynamic systems

A key issue in the design of control systems is proving that the resulting closed-loop system is stable, especially in cases of high consequence applications, where process variations or failure could result in unacceptable risk. Adaptive control techniques provide a proven methodology for designing stable controllers for systems that may possess a large amount of uncertainty. At the same time, the benefits of neural networks and fuzzy systems are generating much excitement—and impressive innovations—in almost every engineering discipline.

Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques brings together these two different but equally useful approaches to the control of nonlinear systems in order to provide students and practitioners with the background necessary to understand and contribute to this emerging field.

The text presents a control methodology that may be verified with mathematical rigor while possessing the flexibility and ease of implementation associated with "intelligent control" approaches. The authors show how these methodologies may be applied to many real-world systems including motor control, aircraft control, industrial automation, and many other challenging nonlinear systems. They provide explicit guidelines to make the design and application of the various techniques a practical and painless process.

Design techniques are presented for nonlinear multi-input multi-output (MIMO) systems in state-feedback, output-feedback, continuous or discrete-time, or even decentralized form. To help students and practitioners new to the field grasp and sustain mastery of the material, the book features:

• Background material on fuzzy systems and neural networks
• Step-by-step controller design
• Numerous examples
• Case studies using "real world" applications
• Homework problems and design projects

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.

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.

Articulates a series of scientific and technological developments described in a didactic way Shows a broad view of biometrics in several contexts: Current cases of study in five different areas Provides experimental results in different environments (availability of data and computer code to reproduce the experiments) Includes transdisciplinary approaches and discussions for each chapter Innovation as part of the final cases of study: developments are already affecting the new businesses of the digital age and the era of the brain

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

This book explores the design of optimal trajectories for space maneuver vehicles (SMVs) using optimal control-based techniques. It begins with a comprehensive introduction to and overview of three main approaches to trajectory optimization, and subsequently focuses on the design of a novel hybrid optimization strategy that combines an initial guess generator with an improved gradient-based inner optimizer. Further, it highlights the development of multi-objective spacecraft trajectory optimization problems, with a particular focus on multi-objective transcription methods and multi-objective evolutionary algorithms. In its final sections, the book studies spacecraft flight scenarios with noise-perturbed dynamics and probabilistic constraints, and designs and validates new chance-constrained optimal control frameworks. The comprehensive and systematic treatment of practical issues in spacecraft trajectory optimization is one of the book's major features, making it particularly suited for readers who are seeking practical solutions in spacecraft trajectory optimization. It offers a valuable asset for researchers, engineers, and graduate students in GNC systems, engineering optimization, applied optimal control theory, etc.

The texts presented in Proportion Harmonies and Identities (PHI) Creating Through Mind and Emotions were compiled to establish a multidisciplinary platform for presenting, interacting, and disseminating research. This platform also aims to foster the awareness and discussion on Creating Through Mind and Emotions, focusing on different visions relevant to Architecture, Arts and Humanities, Design and Social Sciences, and its importance and benefits for the sense of identity, both individual and communal. The idea of Creating Through Mind and Emotions has been a powerful motor for development since the Western Early Modern Age. Its theoretical and practical foundations have become the working tools of scientists, philosophers, and artists, who seek strategies and policies to accelerate the development process in different contexts.

Dynamics is what characterizes virtually all phenomenae we face in the real world, and processes that proceed in practically all kinds of inanimate and animate systems, notably social systems. For our purposes dynamics is viewed as time evolution of some characteristic features of the phenomenae or processes under consideration. It is obvious that in virtually all non-trivial problems dynamics can not be neglected, and should be taken into account in the analyses to, first, get insight into the problem consider, and second, to be able to obtain meaningful results.

A convenient tool to deal with dynamics and its related evolution over time is to use the concept of a dynamic system which, for the purposes of this volume can be characterized by the input (control), state and output spaces, and a state transition equation. Then, starting from an initial state, we can find a sequence of consecutive states (outputs) under consecutive inputs (controls). That is, we obtain a trajectory. The state transition equation may be given in various forms, exemplified by differential and difference equations, linear or nonlinear, deterministic or stochastic, or even fuzzy (imprecisely specified), fully or partially known, etc. These features can give rise to various problems the analysts may encounter like numerical difficulties, instability, strange forms of behavior (e.g. chaotic), etc.

This volume is concerned with some modern tools and techniques which can be useful for the modeling of dynamics. We focus our attention on two important areas which play a key role nowadays, namely automation and robotics, and biological systems. We also add some new applications which can greatly benefit from the availability of effective and efficient tools for modeling dynamics, exemplified by some applications in security systems.

The proceedings collect the latest research trends, methods and experimental results in the field of electrical and information technologies for rail transportation. The topics cover intelligent computing, information processing, communication technology, automatic control, and their applications in rail transportation etc. The proceedings can be a valuable reference work for researchers and graduate students working in rail transportation, electrical engineering and information technologies.

Are Amazon Alexa and Google Home limited to our bedrooms, or can they be used in hospitals? Do you envision a future where physicians work hand-in-hand with voice AI to revolutionize healthcare delivery? In the near future, clinical smart assistants will be able to automate many manual hospital tasks-and this will be only the beginning of the changes to come. Voice AI is the future of physician-machine interaction and this Focus book provides invaluable insight on its next frontier. It begins with a brief history and current implementations of voice-activated assistants and illustrates why clinical voice AI is at its inflection point. Next, it describes how the authors built the world's first smart surgical assistant using an off-the-shelf smart home device, outlining the implementation process in the operating room. From quantitative metrics to surgeons' feedback, the authors discuss the feasibility of this technology in the surgical setting. The book then provides an in-depth development guideline for engineers and clinicians desiring to develop their own smart surgical assistants. Lastly, the authors delve into their experiences in translating voice AI into the clinical setting and reflect on the challenges and merits of this pursuit. The world's first smart surgical assistant has not only reduced surgical time but eliminated major touch points in the operating room, resulting in positive, significant implications for patient outcomes and surgery costs. From clinicians eager for insight on the next digital health revolution to developers interested in building the next clinical voice AI, this book offers a guide for both audiences.