Electronics and communications engineering Books

Book SynopsisMost physical problems can be written in the form of mathematical equations (differential, integral, etc.). Mathematicians have always sought to find analytical solutions to the equations encountered in the different sciences of the engineer (mechanics, physics, biology, etc.). These equations are sometimes complicated and much effort is required to simplify them. In the middle of the 20th century, the arrival of the first computers gave birth to new methods of resolution that will be described by numerical methods. They allow solving numerically as precisely as possible the equations encountered (resulting from the modeling of course) and to approach the solution of the problems posed. The approximate solution is usually computed on a computer by means of a suitable algorithm. The objective of this book is to introduce and study the basic numerical methods and those advanced to be able to do scientific computation. The latter refers to the implementation of approaches adapted to the treatment of a scientific problem arising from physics (meteorology, pollution, etc.) or engineering (structural mechanics, fluid mechanics, signal processing, etc.) .Table of ContentsPreface xi Part 1 Introduction 1 Chapter 1 Review of Linear Algebra 3 1.1. Vector spaces 3 1.1.1. General definitions 3 1.1.2. Free families, generating families and bases 4 1.2. Linear mappings 5 1.3. Matrices 7 1.3.1. Operations on matrices 7 1.3.2. Change-of-basis matrices 8 1.3.3. Matrix notations 9 1.4. Determinants 10 1.5. Scalar product 12 1.6. Vector norm 12 1.7. Matrix eigenvectors and eigenvalues 13 1.7.1. Definitions and properties 13 1.7.2. Matrix diagonalization 15 1.7.3. Triangularization of matrices 15 1.8 Using Matlab 16 Chapter 2 Numerical Precision 21 2.1. Introduction 21 2.2. Machine representations of numbers 22 2.3. Integers 23 2.3.1. External representation 23 2.3.2. Internal representation of positive integers 24 2.4. Real numbers 25 2.4.1. External representation 25 2.4.2. Internal encoding of real numbers 25 2.5. Representation errors 26 2.5.1. Properties of computer-based arithmetic 27 2.5.2. Operation of subtraction 28 2.5.3. Stability 29 2.6. Determining the best algorithm 29 2.7 Using Matlab 30 2.7.1. Definition of variables 30 2.7.2. Manipulating numbers 30 Part 2 Approximating Functions 35 Chapter 3 Polynomial Interpolation 37 3.1. Introduction 37 3.2. Interpolation problems 37 3.2.1. Linear interpolation 38 3.3. Polynomial interpolation techniques 38 3.4. Interpolation with the Lagrange basis 39 3.4.1. Polynomial interpolation error 43 3.4.2. Neville–Aitken method 46 3.5. Interpolation with the Newton basis 46 3.6. Interpolation using spline functions 48 3.6.1. Hermite interpolation 50 3.6.2. Spline interpolation error 55 3.7 Using Matlab 58 3.7.1. Operations on polynomials 58 3.7.2. Manipulating polynomials 59 3.7.3. Evaluation of polynomials 60 3.7.4. Linear and nonlinear interpolation 60 3.7.5. Lagrange function 63 3.7.6. Newton function 64 Chapter 4 Numerical Differentiation 67 4.1. First-order numerical derivatives and the truncation error 67 4.2. Higher-order numerical derivatives 70 4.3. Numerical derivatives and interpolation 71 4.4. Studying the differentiation error 73 4.5. Richardson extrapolation 77 4.6. Application to the heat equation 78 4.7 Using Matlab 81 Chapter 5 Numerical Integration 83 5.1. Introduction 83 5.2. Rectangle method 84 5.3. Trapezoidal rule 84 5.4. Simpson’s rule 87 5.5. Hermite’s rule 90 5.6. Newton–Côtes rules 91 5.7. Gauss–Legendre method 92 5.7.1. Problem statement 92 5.7.2. Legendre polynomials 94 5.7.3 Choosing the αi and xi (i = 0, . . . , n) 99 5.8 Using Matlab 100 5.8.1. Matlab functions for numerical integration 100 5.8.2. Trapezoidal rule 101 5.8.3. Simpson’s rule 103 Part 3 Solving Linear Systems 107 Chapter 6 Matrix Norm and Conditioning 109 6.1. Introduction 109 6.2. Matrix norm 109 6.3. Condition number of a matrix 113 6.3.1 Approximation of K(A) 116 6.4. Preconditioning 116 6.5 Using Matlab 117 6.5.1. Matrices and vectors 117 6.5.2. Condition number of a matrix 119 Chapter 7 Direct Methods 123 7.1. Introduction 123 7.2. Method of determinants or Cramer’s method 123 7.2.1. Matrix inversion by Cramer’s method 124 7.3. Systems with upper triangular matrices 124 7.4. Gaussian method 125 7.4.1. Solving multiple systems in parallel 129 7.5. Gauss–Jordan method 129 7.5.1. Underlying principle 129 7.5.2. Computing the inverse of a matrix with the Gauss–Jordan algorithm 131 7.6. LU decomposition 132 7.7. Thomas algorithm 133 7.8. Cholesky decomposition 134 7.9 Using Matlab 136 7.9.1. Matrix operations 136 7.9.2. Systems of linear equations 138 Chapter 8 Iterative Methods 147 8.1. Introduction 147 8.2. Classical iterative techniques 148 8.2.1. Jacobi method 149 8.2.2. Gauss–Seidel method 151 8.2.3. Relaxation method 152 8.2.4. Block forms of the Jacobi, Gauss–Seidel and relaxation methods 154 8.3. Convergence of iterative methods 155 8.4. Conjugate gradient method 157 8.5 Using Matlab 159 8.5.1. Jacobi method 159 8.5.2. Relaxation method 160 Chapter 9 Numerical Methods for Computing Eigenvalues and Eigenvectors 163 9.1. Introduction 163 9.2. Computing det (A − λI) directly 164 9.3. Krylov methods 166 9.4. LeVerrier method 167 9.5. Jacobi method 168 9.6. Power iteration method 171 9.6.1. Deflation algorithm 172 9.7. Inverse power method 173 9.8. Givens–Householder method 174 9.8.1. Givens algorithm 175 9.9 Using Matlab 176 9.9.1. Application to a buckling beam 177 Chapter 10 Least-squares Approximation 185 10.1. Introduction 185 10.2. Analytic formulation 185 10.3. Algebraic formulation 191 10.3.1. Standard results on orthogonality 191 10.3.2. Least-squares problem 191 10.3.3. Solving by orthogonalization 192 10.4. Numerically solving linear equations by QR factorization 193 10.4.1. Householder transformations 193 10.4.2. QR factorization 193 10.4.3. Application to the least-squares problem 193 10.5. Applications 194 10.5.1. Curve fitting 194 10.5.2. Approximations of derivatives 195 10.6 Using Matlab 195 Part 4 Appendices 199 Appendix 1 Introduction to Matlab 201 Appendix 2 Introduction to Optimization 209 Bibliography 215 Index 217

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Book SynopsisThis book covers various modern theoretical, technical, practical and technological aspects of computerized numerical control and control systems of deterministic and stochastic dynamical processes. Readers will discover: A review of the fundamentals and results of the theory of analogue control systems A clear and detailed presentation on the experimental modeling of dynamic processes Frequency synthesis techniques and in the state space of digital control systems Concrete applications of deterministic and stochastic optimal regulation laws New multimedia platforms, training and experimental automated research Various topologies and creation strategies, computer-aided telecontrol regulation systems, as well as a prototype of an automated laboratory that can be remotely operated via the Internet Simple Matlab programs to reproduce, where necessary, the main numerical and graphical results presented Many exercises corrected at the end of each chapter Detailed studies of practical automation projects, aimed at consolidating the skills of the automation profession acquired in the book Table of ContentsPreface ix Introduction xiii Part 1. Analog Feedback Control Systems 1 Chapter 1. Models of Dynamic Processes 3 1.1. Introduction to dynamic processes 3 1.1.1. Definition, hypotheses and notations 3 1.1.2. Implications of hypotheses 4 1.1.3. Dynamic model: an automation perspective 5 1.2. Transfer functions 6 1.2.1. Existence conditions 6 1.2.2. Construction 6 1.2.3. General structure of a transfer function 8 1.2.4. Tools for the analysis of the properties of transfer functions 8 1.2.5. First- and second-order transfer functions 8 1.3. State models 12 1.3.1. Definition 12 1.3.2. Illustrative example 13 1.3.3. General structure of the state model 14 1.4. Linear state models with constant parameters 15 1.4.1. Linearization-based construction 15 1.4.2. Structure of a linear state model with constant parameters 16 1.4.3. Properties of a model without pure input delay (τ0 = 0) 18 1.5. Similarity transformation 20 1.6. Exercises and solutions 21 Chapter 2. Experimental Modeling Approach of Dynamic Processes 39 2.1. Introduction to experimental modeling 39 2.1.1. Problem statement 39 2.1.2. Principle of experimental modeling 39 2.1.3. Experimental modeling methodology 40 2.2. Step response-based modeling 44 2.2.1. Model of order 1 44 2.2.2. Under-damped model of order 2 (ξ < 1) 44 2.2.3. Damped model of order ≥ 2 (Strejc method) 46 2.3. Frequency response-based modeling 50 2.4. Modeling based on ARMA model 52 2.4.1. ARMA model 52 2.4.2. Parameter estimation of an ARMA model 54 2.5. Matlab-aided experimental modeling 56 2.6. Exercises and solutions 58 Chapter 3. Review of Analog Feedback Control Systems 73 3.1. Open-loop analog control 73 3.1.1. Principle 73 3.1.2. Open-loop control 74 3.2. Analog control system 74 3.3. Performances of an analog control system 75 3.3.1. Closed-loop transfer functions 75 3.3.2. Performance quantities 76 3.4. Simple analog controllers 76 3.5. PID/PIDF controllers 77 3.5.1. Structure and role of the parameters of a PID/PIDF controller 77 3.5.2. Ziegler–Nichols methods for parameter calculation 79 3.5.3. Calculation of parameters by pole placement 79 3.5.4. Direct calculation of optimal PID parameters 81 3.5.5. LQR-based indirect calculation of optimal PID parameters 85 3.5.6. Implementation of analog controllers 85 3.6. Controllers described in the state space 86 3.6.1. Principle and block diagram of a linear state feedback 86 3.6.2. Techniques for calculating the state feedback gain 87 3.6.3. Integral action state feedback 88 3.6.4. State feedback with integral action and observer 90 3.6.5. State feedback with output error compensator 92 3.7. Principle of equivalence between PID and LQR controllers 92 3.7.1. Proof of the equivalence principle 93 3.7.2. Equivalence relation 96 3.7.3. Case study 96 3.8. Exercises and solutions 99 Part 2. Synthesis and Computer-aided Simulation of Digital Feedback Control Systems 123 Chapter 4. Synthesis of Digital Feedback Control Systems in the Frequency Domain 125 4.1. Synthesis methodology 125 4.2. Transfer function G(z) of a dynamic process 125 4.2.1. Sampled dynamic model 125 4.2.2. Discretization of Gc(p) if input delay τ0 = 0 126 4.2.3. Discretization of Gc(s) if input delay τ0 # 0 128 4.2.4. Examples of calculation of G(z) by discretization of Gc(s) 132 4.3. Transfer function D(z): discretization method 136 4.3.1. Interest of discretization 136 4.3.2. Discretization of Dc(s) by invariance methods 137 4.3.3. Discretization of Dc(s) by transformation methods 139 4.3.4. z-Transfer functions of simple controllers 142 4.3.5. General structure of D(z) and recurrence equation 144 4.3.6. Discretization of transfer functions with Matlab 145 4.4. Transfer function D(z): model method 146 4.4.1. Principle of the model method 146 4.4.2. Examples of direct design of digital controllers 146 4.4.3. Conditions for the use of model approach 148 4.4.4. Practical rules for using the model approach 149 4.5. Discrete block diagram of digital control 150 4.5.1. Closed-loop characteristic transfer functions 151 4.5.2. Sampling frequency 152 4.6. Exercises and solutions 154 Chapter 5. Computer-aided Simulation of Digital Feedback Control Systems 177 5.1. Approaches to computer-aided simulation 177 5.2. Programming of joint recurrence equations 178 5.2.1. Formulation 178 5.2.2. Example of Matlab® programming 179 5.3. Simulation using Matlab macro programming 183 5.4. Graphic simulation 186 5.5. Case study: simulation of servomechanisms 187 5.5.1. Simulation of a speed servomechanism 187 5.5.2. Simulation of a position servomechanism 191 5.6. Exercises and solutions 194 Chapter 6. Discrete State Models of Dynamic Processes 199 6.1. Discretization of the state model of a dynamic process 199 6.1.1. Discretization of a state model 200 6.1.2. Discretization of a state model with input delay 201 6.2. Calculation of {A, B, C, D} parameters of a discrete state model 204 6.2.1. Calculation of A = eAT 204 6.2.2. Calculation of B 206 6.2.3. Calculation of C and D 208 6.3. Properties of a discrete state model {A, B, C, D} 208 6.3.1. Infinity of state models of one dynamic process 208 6.3.2. Stability 209 6.3.3. Controllability and stabilizability 209 6.3.4. Observability and detectability 210 6.4. Exercises and solutions 210 Appendices 215 Appendix 1. Table of Z-transforms 217 Appendix 2. Matlab® Elements Used in This Book 219 Bibliography 223 Index 227

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Book SynopsisThis book introduces an original fractional calculus methodology (‘the infinite state approach’) which is applied to the modeling of fractional order differential equations (FDEs) and systems (FDSs). Its modeling is based on the frequency distributed fractional integrator, while the resulting model corresponds to an integer order and infinite dimension state space representation. This original modeling allows the theoretical concepts of integer order systems to be generalized to fractional systems, with a particular emphasis on a convolution formulation.Table of Contents1. The Fractional Integrator. 2. Frequency Approach to the Synthesis of the Fractional Integrator. 3. Comparison of Two Simulation Techniques. 4. Fractional Modeling of the Diffusive Interface. 5. Modeling of Physical Systems with Fractional Models: an Illustrative Example. 6. The Distributed Model of the Fractional Integrator. 7. Modeling of FDEs and FDSs. 8. Fractional Differentiation. 9. Analytical Expressions of FDS Transients. 10. Infinite State and Fractional Differentiation of Functions.

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Book SynopsisFollowing the rapid development of connected technologies, which are now highly sophisticated and spread across the globe, Society 5.0 has emerged and brought with it a dramatic societal shift. In 1998, Kodak, the world leader in photographic film, had 170,000 employees. It thus seemed unthinkable that just 3 years later, the majority of people would stop taking photographs to paper film and that Kodak would have disappeared. These are the stakes of this new society that is taking shape. This book, which does not seek to critique current politics, management or marketing literature, aims to fight against the excesses of this often-misunderstood Society 5.0 and to present the ideas and associated technologies that comprise it, all working towards societal improvement. Among these technologies, artificial intelligence, robotics, digital platforms and 3D printing are undoubtedly the most important, and thus receive the greatest focus. Table of ContentsForeword xv Preface xvii Introduction xix Chapter 1. Society 5.0, Its Logic and Its Construction 1 1.1. The origins of society 5.0 1 1.2. The ancient ages 6 1.3. Cybernics or cyber-physical systems 7 1.4. The Council on Competitiveness-Nippon (COCN) 8 1.5. The lessons of history 8 1.6. The decision variables of society 5.0 9 1.6.1. Which role for information? 9 1.6.2. Which role for time? 11 1.6.3. Which role for nature? 11 1.6.4. Which role for distraction? 12 1.6.5. Which role for identity? 13 1.6.6. Which role for alienation? 16 1.6.7. Which role for action? 17 1.7. The contribution of the first revolution 18 1.8. Humanity 2.0 and society 5.0 18 1.9. The new role of society 5.0: a return to bio? 19 1.10. Growing sectors and lagging sectors 19 1.11. The elements of society 5.0 20 Chapter 2. From Society 5.0 to Its Associated Policies 23 2.1. The place of politics in organizations 23 2.1.1. The three levels: strategic, tactical, operational 23 2.1.2. Politics and ethics 24 2.1.3. The relationship between the strategic, tactical and operational levels, and the organization’s functions and tasks 25 2.2. The implementation of national policies 25 2.3. The notion of walls 27 2.3.1. Different types of walls 27 2.3.2. The “NIMBY” wall 28 2.3.3. The wall between private individuals and professionals 29 2.4. New political attitudes 30 2.4.1. Vetocracy 30 2.4.2. Ultrademocracy 33 2.5. The role of governments 34 2.5.1. The protection of national industry 34 2.5.2. The limitations required by governments 35 2.5.3. The question of public orders 36 2.5.4. New cultural policies 36 Chapter 3. Industry 4.0 at the Core of Society 5.0 37 3.1. Business in society 5.0 38 3.1.1. The recent history of the decline of industry 38 3.1.2. The impact of political choices 39 3.1.3. Pierre Musso’s perspective 40 3.2. The firm: a general theory 41 3.2.1. The management of a firm 41 3.2.2. The definition of a market 43 3.2.3. The concept of productive activity 43 3.2.4. The fundamental structures of the firm 44 3.2.5. The question of the appearance of improved structures 46 3.2.6. The usefulness of the concept of profit center 48 3.2.7. The difference between functions and structures 49 3.2.8. The relationship between environment, strategy and structure 49 3.3. The determinants of the factory of the future 50 3.3.1. The main determinants 50 3.3.2. The place of digital 52 3.3.3. Direct manufacturing 53 3.4. The different types of factories of the future 53 3.4.1. Factory 4.0: “integrated logistics chain” 54 3.4.2. The Key-Technology factory: “a highly differentiating process” 54 3.4.3. The Craft-Industrial factory: “tailor-made industrialized production” 54 3.4.4. The Client Drive factory: “the customer operates the process” 54 3.4.5. The Low Cost factory: “in Open Source” 55 3.5. The regulatory determinants of the factory of the future 56 3.6. The main questions regarding the factory of the future 56 3.6.1. The location of the factory of the future 58 3.6.2. Production cycles 58 3.6.3. Finances in the factory of the future 59 3.6.4. The conditions of its emergence 60 3.7. Changes related to the factory of the future 60 3.7.1. Actions for favoring the advent of the factory of the future 61 3.7.2. The notion of industrial revolution 61 3.8. Daily management 62 3.9. Additive manufacturing technologies 62 3.9.1. CNC tools 62 3.9.2. The notion of CPPS 62 3.10. The example of the textile industry 63 Chapter 4. The City and Mobility 3.0 67 4.1. Research 67 4.1.1. The city in motion 67 4.1.2. Transit-City program 68 4.1.3. Research on smart vehicles 69 4.2. The link between smart vehicles and road infrastructure 70 4.2.1. Smart vehicles’ levels 71 4.2.2. Current examples of autonomous vehicles 73 4.2.3. The challenges of the road environment 73 4.2.4. The smart and mobile habitat 74 Chapter 5. Information Technology 2.0, the Foundation of Society 5.0 75 5.1. The reference to Jean-Paul Sartre 75 5.2. The “Sartrian” man in the digital world 77 5.3. Schemata 79 5.4. Data in their environment 79 5.4.1. The sources of data 79 5.4.2. Regulations on data use 80 5.5. The impact of the digital world 81 5.6. The digital shift of organizations 82 5.6.1. Organizations where the digital shift has been a failure 82 5.6.2. Organizations that made the digital shift early 82 5.6.3. Organizations blocked at ICT 1.0 83 5.7. ICT infrastructure 84 5.8. Primitive technologies 84 5.8.1. Text analysis 84 5.8.2. Voice recognition 85 5.8.3. The mobile phone as an inclusive technology 85 5.9. Recent technologies 86 5.9.1. Robotics and automation 86 5.9.2. Virtual reality 87 5.9.3. Computer-aided design 87 5.9.4. Artificial intelligence 89 Chapter 6. Society 5.0 and the Management of the Future 91 6.1. The firm from the managerial viewpoint 91 6.1.1. The definition of management 91 6.1.2. Management’s contents 92 6.2. The definition of market 92 6.3. Marketing 93 6.3.1. Marketing is an approach which only makes sense in a certain context 93 6.3.2. The four historical periods of marketing.95 6.3.3. The features of the different phases 96 6.4. The logics: need, desire, expectation and demand 99 6.4.1. The Lacanian perspective applied to marketing 99 6.4.2. The place of marketing 100 6.5. New managerial skills 102 6.6. Boredom comes from repetition 103 6.7. Customer satisfaction 103 6.8. Resistance to consumption 104 6.9. Recovery, gleaning, etc 105 6.10. Customer relationship management: an essential tool 105 6.11. The holistic approach to management 106 6.11.1. Sociocracy 106 6.11.2. Holacracy 107 6.12. The hacker’s position 108 6.12.1. Corporate hacking 108 6.12.2. Managing a hacking session 111 6.12.3. Human resources management 112 6.13. Feeble signals for understanding evolution 114 6.14. The generations 115 6.14.1. The Beta generation 115 6.14.2. The more “ecological” consumption of new generations 115 6.14.3. The middle-class generation 116 6.15. Skills and generations 117 6.15.1. The distinctive skills of a firm 117 6.15.2. The history of Low and Less 117 6.15.3. The cashless generation 117 6.15.4. Changes in commercialization and in business 118 6.15.5. Changes in the market 118 Chapter 7. The Consequences of the End of Major Innovations 121 7.1. The end of the major innovations: some observations 121 7.2. Marketing philosophy as a vehicle for enhancing technology 123 7.2.1. Why do we mention a marketing philosophy? 123 7.2.2. The example of Intel processors 124 7.2.3. Innovation balance 124 7.3. The new forms of innovation 125 7.4. The globalization of research 126 7.4.1. The globalization of science does not really exist 126 7.4.2. Scientific globalization is only real for mathematics, physics and health 127 7.4.3. The key point is European research 127 7.5. The globalization of scientific publications 128 7.5.1. Scientific communication: publish or perish 128 7.5.2. The solution, to expand the scope of “publications” 129 7.6. The role of bureaucracy in research 129 7.7. The role of China 130 7.8. The solution: to restore philosophy, poetry and morality to science and innovation 131 7.9. The new research in society 5.0 132 7.10. Innovation related to opportunities 132 7.11. The paradigm of innovation 134 7.12. Design thinking 135 7.12.1. Stage 1: identifying a problem and understanding its environment, “observation phase” 135 7.12.2. Stage 2: finding the concept or idea that will make it possible to find a solution, “ideation” phase.136 7.12.3. Stage 3: designing 136 7.12.4. Stage 4: building a model and a prototype 136 7.12.5. Stage 5: the assessment phase or “evaluation” 137 7.13. The risks of innovation 138 7.14. The lessons of Thomas Edison 139 7.15. Methods for innovating 140 7.15.1. The preliminary questions related to the genesis of a product or a service 141 7.15.2. The choice on whether to innovate a product-service or to innovate a process 142 7.16. Man in innovation 142 7.16.1. The human resources of the innovative firm 142 7.16.2. The answer to the society of boredom 142 7.17. The different forms of boredom 143 7.18. The transgression phenomenon and the transcendence one 144 7.19. Boredom comes from the ugly 145 7.19.1. The risk of uniformity 145 7.19.2. The search for harmony 146 7.20. The search for equilibrium 147 7.21. Design as a technical answer 147 7.21.1. Industrial aesthetics and design laws 147 7.21.2. The evolution of design needs 149 7.21.3. The use of a former theoretical approach in design 150 7.21.4. The aesthetic components 152 7.21.5. The impact of the sociometrics and homology 154 7.22. The sources and forms of design 155 7.23. The other criteria for innovating a product or a service 156 Chapter 8. Innovation in Society 5.0 157 8.1. The innovative product service 157 8.1.1. Losses during the innovation process 158 8.1.2. The question on the validation of a new product or a service 159 8.1.3. Improving a product 160 8.2. The paradigm shift 160 8.3. Mash-up forms 162 8.4. “Co” society 163 8.5. The sharing of information 163 8.6. Social networks, Internet and innovation 164 8.7. The collaborative forms 164 8.8. Innovation ecosystems 165 8.8.1. Resource centers 165 8.8.2. The concept of the Digital Innovation Hub 166 8.9. The evolution of former innovation organizations 168 8.10. Innovation in human resources 168 Chapter 9. “Co” Society 171 9.1. “Co” society 171 9.2. The evolution from prosthetic man to the current man 171 9.2.1. Types of bored men 172 9.2.2. Prosthetic man 172 9.2.3. Civilized man 173 9.2.4. Rational man. 173 9.2.5. Information society man 174 9.2.6. Augmented or improved man 174 9.3. The split between boredom and innovation 174 9.4. New innovative strategies 175 9.4.1. Innovation must be everywhere 175 9.4.2. The end of the dynamics of jealous marketing 175 9.4.3. “Co” society as a means for understanding the consumer 176 9.5. Porter’s strategic model 176 9.5.1. The notion of strategy and of strategic model 176 9.5.2. The concept of value chain 177 9.5.3. Porter’s three basic strategies 178 9.5.4. Cost strategic advantage 179 9.5.5. Differentiation advantage 179 9.5.6. Focus strategy 180 9.5.7. Development pathways 181 9.5.8. The origins of market massification 181 9.5.9. The vision through differentiation 182 9.6. Useful partnerships 183 9.7. Different types of alliances 184 9.7.1. The conditions of alliances 184 9.7.2. Strategic alliance through fusion 185 9.7.3. Strategic alliances involved via the execution of an agreement 185 9.7.4. Alliances through the integration of products.186 9.7.5. Determinants of an alliance 187 9.8. Typology of firms (according to Kotler) 188 9.8.1. The leader’s strategy 188 9.8.2. The challenger’s strategy 189 9.8.3. The follower’s strategy 189 9.8.4. The specialist’s strategy 190 Chapter 10. The Challenges of Localization, the Market, Skills and Knowledge 191 10.1. Localization is increasingly losing its interest 191 10.2. New practices related to the lack of importance of localization 192 10.3. The importance of reconstruction 193 10.4. Changes in market shares: why and how? 193 10.5. The issue of skills and knowledge 194 10.6. The notion of intellectual capital 194 10.7. Changes in operational marketing 196 10.8. Intrusive marketing 197 10.9. The use of acquired knowledge 198 10.10. Identification of regulations in documents 199 10.11. Identification of forms of commitment 200 10.12. Implementation of normalization 200 10.13. Organizational consequences 201 10.13.1. The norm as an agent for contextual change 201 10.13.2. The norm and machines 202 10.14. The impact of change on data 203 10.15. Changes in programs and processes 203 10.16. Organizational evolution 204 10.17. The challenge of generating trust 206 10.17.1. Specialized marketplaces 206 10.17.2. Rating, the representation of trust 206 10.17.3. Commitment as an ingredient of trust 207 10.17.4. The necessary confidence for inviting financing 207 Chapter 11. On-Demand Society 209 11.1. Does boredom have any influence on need, desire, expectation and demand? 209 11.1.1. Collective neurosis and diverted uses 209 11.1.2. The theory of diverted uses and the role of boredom 210 11.1.3. Examples of diverted uses 211 11.2. “Servitization”, the products and services of revolution 5.0 212 11.3. The notion of “servitization” 213 11.4. The nature of “servitization” 213 11.4.1. Servicizing 214 11.4.2. The different forms of servicizing 214 11.4.3. “Servuction” 215 11.4.4. Competitive advantage 215 11.5. The paths toward “servitization” 216 11.5.1. The formation of value 217 11.5.2. “XaaS” logic 218 11.5.3. The “rental” rather than the “purchase” logic 219 11.6. Enterprise manufacturing services 220 11.6.1. The fabless 220 11.6.2. Original design manufacturers 221 11.6.3. The example of the EMS of electronics 221 11.7. The key points of “servitization”: visualization and virtualization 222 11.8. Recent developments 223 11.8.1. Tokyo University of Technology 224 11.8.2. The SPREE project 224 11.8.3. The example of the firm Komatsu 224 Chapter 12. The Economy of Society 5.0 227 12.1. The new economies 228 12.2. The problems in the age of connectivity 230 12.3. Evolution of economy 230 12.3.1. Hunting and gathering economy 231 12.3.2. Bartering economy 231 12.3.3. Souk economy or the basis of market economy. 232 12.3.4. Production economy 232 12.3.5. Mass distribution economy 233 12.3.6. Market economy 234 12.3.7. Environmental economy 234 12.3.8. Intangible economy 234 12.4. Economy related to digital tools 235 12.5. The power of platforms 237 12.5.1. The concept of platform 237 12.5.2. The role of trust in platforms 237 12.5.3. The different types of platforms 238 12.5.4. The State as platform 239 12.5.5. Platform as a service 242 12.5.6. Marketing platforms 243 12.6. The limits of platforms 243 12.7. Free economy 244 12.7.1. The characteristics of free economy 245 12.7.2. The example of the “free” newspaper market 245 12.8. The fight against large firms 245 12.9. The notion of data visualization 246 12.10. Technology creating new resources 247 Conclusion 249 Bibliography 251 Index 269

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Book SynopsisDue to their special properties, organic semiconductors enable the development of large-area, low-cost devices, paving the way for flexible and nomadic applications that advantageously replace those made with traditional semiconductors. This book describes the properties and deposition methods of organic semiconductors, transparent conductive materials or metals which are used in the fabrication of organic devices. The physical processes (optical, electrical and interface) that control the mechanisms in the formation and transport of the charge carriers of the materials are studied and explained in detail. Organic Electronics 1 introduces the fundamental and applied aspects of the field of organic electronics. It is intended for researchers and students in university programs or engineering schools specializing in electronics, energy and materials.Table of ContentsIntroduction ix Chapter 1. Semiconductor Theory 1 1.1. Introduction 1 1.2. Review of the basic concepts of crystalline semiconductors 3 1.2.1. Intrinsic semiconductors 4 1.2.2. Extrinsic semiconductors 5 1.2.3. Fermi level 7 1.2.4. Charge transport in semiconductors 7 1.3. P–N junction 9 1.3.1. Space charge region 9 1.3.2. Junction capacitance 11 1.4. Impurities and defects 11 1.4.1. Traps and recombination centers 12 1.5. Metal/semiconductor contact 20 1.5.1. Parameters of metal/semiconductor contacts 20 1.5.2. Formation of metal/semiconductor contacts 21 1.5.3. Width λ of the space charge region 23 1.5.4. Junction capacitance 23 1.5.5. Schottky effect 24 1.5.6. Schottky diode 25 1.6. Semiconductors under non-equilibrium conditions 27 1.6.1. Parameters of a semiconductor under non-equilibrium conditions 27 1.6.2. Recombination of carriers via recombination centers (Shockley–Read–Hall theory) 29 1.6.3. Transient relaxation current 31 1.7. Space charge current 34 1.7.1. The case of an ideal semiconductor 35 1.7.2. Trap-filled limit voltage 37 1.7.3. Discrete traps and trap distribution 37 1.8. Hopping conduction 38 Chapter 2. Materials 41 2.1. Introduction 41 2.2. Organic materials 42 2.2.1. Binding and hybridization of carbon 46 2.3. Conjugated polymers 48 2.3.1. Polyacetylene 49 2.3.2. Benzene 51 2.3.3. Deposition of polymer films 52 2.4. Energy bands 53 2.4.1. Concepts of solitons and polarons 55 2.4.2. Concept of doping 58 2.5. Small molecules 61 2.6. Design and engineering of organic materials 63 2.7. Hybrid materials or nanocomposites 65 2.7.1. Polymer matrix nanocomposites 67 2.7.2. Nanocomposites with nanomaterials 67 2.7.3. Preparation of nanocomposites 68 2.8. Transparent and conductive materials 73 2.8.1. Indium tin oxide 73 2.8.2. Fluorine-doped tin oxide 74 2.8.3. Other transparent oxide conductors 75 2.8.4. Other transparent conductive materials 75 2.9. Materials for encapsulation 78 2.9.1. Glass slides 78 2.9.2. Hybrid multilayers 79 Chapter 3. Optical Processes 81 3.1. Introduction 81 3.2. Interaction between light and molecules 81 3.2.1. Electronic transitions 81 3.2.2. Selection rules 82 3.3. Optical processes 84 3.3.1. Light absorption 84 3.3.2. Light emission 88 3.3.3. Perrin–Jablonski diagram 91 3.3.4. Quenching 91 3.4. Excitons 99 3.4.1. Classification of excitons 100 3.4.2. Binding energy of excitons 101 3.4.3. Movement of excitons 103 3.4.4. Dissociation of excitons 103 3.5. Experimental techniques 104 3.5.1. UV–visible absorption spectroscopy 104 3.5.2. Photoluminescence spectroscopy 106 3.5.3. Infrared and Raman spectroscopy 110 Chapter 4. Electronic Processes 115 4.1. Introduction 115 4.2. Charge carrier injection process 116 4.2.1. Injection mechanisms 117 4.2.2. Hole or electron devices 119 4.2.3. Transport layers 121 4.3. Charge transport process 123 4.3.1. Hopping mechanisms 124 4.3.2. Space-charge limited conduction 133 4.3.3. Defects and traps in organic semiconductors 140 Chapter 5. Interface Processes 155 5.1. Introduction 155 5.2. Formation of organic semiconductor/metal interfaces 155 5.2.1. Vacuum-level alignment model: Mott–Schottky theory 156 5.2.2. Interface dipole model: Bardeen’s theory 156 5.2.3. Characteristics of organic semiconductor/metal interfaces 158 5.2.4. Fermi-level pinning 160 5.2.5. Integer charge transfer process 162 5.3. Surface characterization techniques 166 5.3.1. Atomic force microscopy 166 5.3.2. X-ray photoelectron spectroscopy 167 5.3.3. UV photoelectron spectroscopy 168 5.4. Interface engineering 169 5.4.1. Inverted structure devices 170 5.4.2. Self-assembled monolayers 172 5.5. Conclusion 174 List of Acronyms 175 References 183 Index 191

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Book SynopsisIn the last few decades, metamaterials have revolutionized the ways in which waves are controlled, and applied in physics and practical situations. The extraordinary properties of metamaterials, such as their locally resonant structure with deep subwavelength band gaps and their ranges of frequency where propagation is impossible, have opened the way to a host of applications that were previously unavailable. Acoustic metamaterials have been able to replace traditional treatments in several sectors, due to their better performance in targeted and tunable frequency ranges with strongly reduced dimensions. This is a training book composed of nine chapters written by experts in the field, giving a broad overview of acoustic metamaterials and their uses. The book is divided into three parts, covering the state-of-the-art, the fundamentals and the real-life applications of acoustic metamaterials.Table of ContentsPart 1. Overview of the Current Research in Acoustic 1. Visco-thermal Effects in Acoustic Metamaterials Based on Local Resonances, José Sanchez-Dehesa and Vincente Cutanda Henriquez. 2. Locally Resonant Metamaterials for Plate Waves: the Respective Role of Compressional Versus Flexural Resonances of a Dense Forest of Vertical Rods, Martin Lott and Philippe Roux. 3. Slow Sound and Critical Coupling to Design Deep Sub wave length Acoustic Metamaterials for Perfect Absorption and Efficient Diffusion, Vincente Romero-Garcìa, Noé Jiménez and Jean-Philippe Groby. Part 2. Principles and Fundamentals of Acoustic Metamaterials 4. Homogenization of Thin 3D Periodic Structures in the Time Domain – Effective Boundary and Jump Conditions, Agnès Maurel, Kim Pham and Jean-Jacques Marigo. 5.The Plane Wave Expansion Method, Jérôme Vasseur. 6. Introduction to Multiple Scattering Theory, Logan Schwan and Jean-Philippe Groby. Part 3. Applications of Acoustic Metamaterials 7. Acoustic Metamaterials for Industrial Applications, Clément Lagarrigue and Damien Lecoq. 8. Elastic Metamaterials for Radio Frequency Applications, Sarah Benchabane and Alexandre Reinhardt. 9. Acoustic Metamaterials and Underwater Acoustics Applications, Christian Audoly.

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Book SynopsisThroughout history, engineers have been defined as those who bring technological innovation to society. However, the concept of innovation and the role of the engineer are now changing as a result of globalization, the digital revolution, growing inequalities and environmental concerns. Training Engineers for Innovation therefore analyzes the ways in which the educational systems for engineers are adapting to these new demands, as well as the conditions in which this training has developed. This book brings together the works of a consortium of researchers dedicated to the subject area as part of the Innov’Ing 2020 project. Its contributors present various means to devise effective pedagogies adapted to a holistic approach to innovation which incorporates the technical, economic, social, ethical and environmental dimensions of engineering.Table of ContentsPart 1. Innovation Design and Expectations toward Training 1. From Technological Innovation to “Situated” Innovation: Improving the Adaptation of Engineering Training to the Societal Challenges of the 21st Century, Emmanuel Cardona Gil, Linda Gardelle and Brad Tabas. 2. Responding to an Event: Innovation of the Contemporary Engineer?, Frédéric Huet, Hugues Choplin, Isabelle Cailleau and Pierre Steiner. 3. Innovation within Companies: Changes and Impacts on Our Student Engineer Training Models, Christiane Gillet and Klara Kövesi. 4. Skills and Competencies for Innovators: New Priorities and Requirements for Engineering Graduates, Klara Kövesi and Péter Csizmadia. Part 2. New Skills and Adaptation to Training Systems 5. The Training of Innovators between Skill Acquisition and Construction of an Individual Socioprofessional Identity, Tiphaine Liu. 6. Innovation Training and Entrepreneurship in French Engineering Higher Education Institutions: An Investigation of the Commission des Titres d’Ingénieur, Anne-Marie Jolly and Julie Nolland. 7. Determinants of Skill Matching among Young Hungarian Engineers, Péter Csizmadia and Zsuzsanna Veroszta. Part 3. Pedagogies of Innovation 8. Swimming with Sharks without Being Eaten: How Engineering Students can Learn Creativity, Entrepreneurial Thinking and Innovation, Claudius Terkowsky, Tobias Haertel, Anna-Lena Rose, Liudvika Leisyte and Dominik May. 9. Engaging with Heritage to Promote Innovative Thinking in Engineering Management Education, Jane Andrews and Robin Clark. 10. How Do Graduate Engineering Schools Train for Innovation? Study of the Curricula of Three French Schools, Denis Lemaître and Christophe Morace. 11. Developing Methods and Programs for Teaching Innovation to Engineers: Toward Eco-Innovation?, Catherine Adam and Serge Coco.

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Book SynopsisThis book is dedicated to the application of metaheuristic optimization in trajectory generation and control issues in robotics. In this area, as in other fields of application, the algorithmic tools addressed do not require a comprehensive list of eligible solutions to effectively solve an optimization problem. This book investigates how, by reformulating the problems to be solved, it is possible to obtain results by means of metaheuristics. Through concrete examples and case studies – particularly related to robotics – this book outlines the essentials of what is needed to reformulate control laws into concrete optimization data. The resolution approaches implemented – as well as the results obtained – are described in detail, in order to give, as much as possible, an idea of metaheuristics and their performance within the context of their application to robotics.Table of ContentsPreface ix Introduction xiii Chapter 1. Optimization: Theoretical Foundations and Methods 1 1.1. The formalization of an optimization problem 1 1.2. Constrained optimization methods 5 1.2.1. The method of Lagrange multipliers 9 1.2.2. Method of the quadratic penalization 11 1.2.3. Methods of interior penalties 12 1.2.4. Methods of exterior penalties 13 1.2.5. Augmented Lagrangian method 14 1.3. Classification of optimization methods 15 1.3.1. Deterministic methods 16 1.3.2. Stochastic methods 18 1.4. Conclusion 21 1.5. Bibliography 22 Chapter 2. Metaheuristics for Robotics 27 2.1. Introduction 27 2.2. Metaheuristics for trajectory planning problems 28 2.2.1. Path planning 29 2.2.2. Trajectory generation 43 2.3. Metaheuristics for automatic control problems 45 2.4. Conclusion 50 2.5. Bibliography 50 Chapter 3. Metaheuristics for Constrained and Unconstrained Trajectory Planning 53 3.1. Introduction 53 3.2. Obstacle avoidance 54 3.3. Bilevel optimization problem 58 3.4. Formulation of the trajectory planning problem 59 3.4.1. Objective functions 60 3.4.2. Constraints 62 3.5. Resolution with a bigenetic algorithm 63 3.6. Simulation with the model of the Neuromate robot 66 3.6.1. Geometric model of the Neuromate robot 67 3.6.2. Kinematic model of the Neuromate robot 71 3.6.3. Simulation results 72 3.7. Conclusion 83 3.8. Bibliography 83 Chapter 4. Metaheuristics for Trajectory Generation by Polynomial Interpolation 87 4.1. Introduction 87 4.2. Description of the problem addressed 88 4.3. Formalization 91 4.3.1. Criteria 91 4.3.2. Constraints 92 4.4. Resolution 94 4.4.1. Augmented Lagrangian 95 4.4.2. Genetic operators 97 4.4.3. Solution coding 99 4.5. Simulation results 100 4.6. Conclusion 116 4.7. Bibliography 118 Chapter 5. Particle Swarm Optimization for Exoskeleton Control 121 5.1. Introduction 121 5.2. The system and the problem under consideration 123 5.2.1. Representation and model of the system under consideration 123 5.2.2. The problem under consideration 125 5.3. Proposed control algorithm 126 5.3.1. The standard PSO algorithm 126 5.3.2. Proposed control approach 128 5.4. Experimental results 135 5.5. Conclusion 142 5.6. Bibliography 143 Conclusion 147 Index 153

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Book SynopsisIn recent years, there has been a proliferation of opinion-heavy texts on the Web: opinions of Internet users, comments on social networks, etc. Automating the synthesis of opinions has become crucial to gaining an overview on a given topic. Current automatic systems perform well on classifying the subjective or objective character of a document. However, classifications obtained from polarity analysis remain inconclusive, due to the algorithms' inability to understand the subtleties of human language. Automatic Detection of Irony presents, in three stages, a supervised learning approach to predicting whether a tweet is ironic or not. The book begins by analyzing some everyday examples of irony and presenting a reference corpus. It then develops an automatic irony detection model for French tweets that exploits semantic traits and extralinguistic context. Finally, it presents a study of portability in a multilingual framework (Italian, English, Arabic).Table of ContentsPreface ix Introduction xi Chapter 1. From Opinion Analysis to Figurative Language Treatment 1 1.1. Introduction 1 1.2. Defining the notion of opinion 3 1.2.1. The many faces of opinion 3 1.2.2. Opinion as a structured model 4 1.2.3. Opinion extraction: principal approaches 5 1.3. Limitations of opinion analysis systems 7 1.3.1. Opinion operators 8 1.3.2. Domain dependency 9 1.3.3. Implicit opinions 10 1.3.4. Opinions and discursive context above phrase level 11 1.3.5. Presence of figurative expressions 12 1.4. Definition of figurative language 13 1.4.1. Irony 13 1.4.2. Sarcasm 18 1.4.3. Satire 20 1.4.4. Metaphor 21 1.4.5. Humor 22 1.5. Figurative language: a challenge for NLP 23 1.6. Conclusion 23 Chapter 2. Toward Automatic Detection of Figurative Language 25 2.1. Introduction 25 2.2. The main corpora used for figurative language 27 2.2.1. Corpora annotated for irony/sarcasm 28 2.2.2. Corpus annotated for metaphors 33 2.3. Automatic detection of irony, sarcasm and satire 36 2.3.1. Surface and semantic approaches 36 2.3.2. Pragmatic approaches 39 2.4. Automatic detection of metaphor 51 2.4.1. Surface and semantic approaches 52 2.4.2. Pragmatic approaches 53 2.5. Automatic detection of comparison 58 2.6. Automatic detection of humor 58 2.7. Conclusion 61 Chapter 3. A Multilevel Scheme for Irony Annotation in Social Network Content 63 3.1. Introduction 63 3.2. The FrIC 65 3.3. Multilevel annotation scheme 66 3.3.1. Methodology 66 3.3.2. Annotation scheme 69 3.4. The annotation campaign 79 3.4.1. Glozz 79 3.4.2. Data preparation 80 3.4.3. Annotation procedure 81 3.5. Results of the annotation campaign 83 3.5.1. Qualitative results 83 3.5.2. Quantitative results 84 3.5.3. Correlation between different levels of the annotation scheme 89 3.6. Conclusion 93 Chapter 4. Three Models for Automatic Irony Detection 95 4.1. Introduction 95 4.2. The FrICAuto corpus 97 4.3. The SurfSystem model: irony detection based on surface features 99 4.3.1. Selected features 99 4.3.2. Experiments and results 101 4.4. The PragSystem model: irony detection based on internal contextual features 104 4.4.1. Selected features 104 4.4.2. Experiments and results 109 4.4.3. Discussion 116 4.5. The QuerySystem model: developing a pragmatic contextual approach for automatic irony detection 118 4.5.1. Proposed approach 118 4.5.2. Experiments and results 122 4.5.3. Evaluation of the query-based method 123 4.6. Conclusion 124 Chapter 5. Towards a Multilingual System for Automatic Irony Detection 127 5.1. Introduction 127 5.2. Irony in Indo-European languages 128 5.2.1. Corpora 128 5.2.2. Results of the annotation process 130 5.2.3. Summary 139 5.3. Irony in Semitic languages 140 5.3.1. Specificities of Arabic 142 5.3.2. Corpus and resources 143 5.3.3. Automatic detection of irony in Arabic tweets 146 5.4. Conclusion 149 Conclusion 151 Appendix 155 References 169 Index 189

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Book SynopsisMathematical morphology has developed a powerful methodology for segmenting images, based on connected filters and watersheds. We have chosen the abstract framework of node- or edge-weighted graphs for an extensive mathematical and algorithmic description of these tools.Volume 2 proposes two physical models for describing valid flooding on a node- or edge-weighted graph, and establishes how to pass from one to another. Many new flooding algorithms are derived, allowing parallel and local flooding of graphs. Watersheds and flooding are then combined for solving real problems. Their ability to model a real hydrographic basin represented by its digital elevation model constitutes a good validity check of the underlying physical models. The last part of Volume 2 explains why so many different watershed partitions exist for the same graph. Marker-based segmentation is the method of choice for curbing this proliferation. This book proposes new algorithms combining the advantages of the previous methods which treated node- and edge-weighted graphs differently.Table of ContentsNotations xi Introduction xxv Part 1. Flooding 1 Chapter 1. Modelling Flooding in Edgeor Node-weighted Graphs 3 1.1. Summary of the chapter 3 1.2. The importance of flooding 4 1.2.1. Flooding creates lakes 4 1.2.2. Flooding for controlling watershed segmentation 4 1.2.3. Flooding, razing, leveling and flattening 5 1.3. Description of the flood covering a topographic surface 6 1.3.1. Observing the same flooding on two levels of abstraction 6 1.3.2. Modeling the two scales of flooding: at the pixel level or at the region level 7 1.3.3. Modeling a flooded topographic surface as a node-weighted graph 8 1.3.4. Modeling an edge-weighted graph as a tank network 15 1.4. The relations between n-floodings and e-floodings 19 1.4.1. Modeling flooding on two scales: the equivalence of both models 19 1.5. Flooding a flowing graph 21 1.5.1. Flowing graphs: reminder 21 1.5.2. Starting from an edge-weighted graph G[nil, η] 22 1.5.3. Starting from a node-weighted graph G[ν, nil] 24 1.5.4. Summarizing 24 Chapter 2. Lakes and Regional Minima 27 2.1. Summary of the chapter 27 2.2. Lakes from e-floodings and n-floodings 27 2.2.1. e-flooding of graphs G[nil, η] 27 2.2.2. n-flooding of graphs G[ν, nil] 28 2.3. Regional minimum lakes and full lakes 29 2.3.1. e-floodings of graphs G[nil, η] 29 2.3.2. n-floodings of graphs G[ν, nil] 30 2.4. Coherence between the definitions of lakes in G[ν, nil] and in G[nil, δenν] 31 Chapter 3. Among all Possible Floodings, Choosing One 33 3.1. Summary of the chapter 33 3.2. Various mechanisms for selecting a particular flooding 34 3.2.1. Dominated flooding in node- and edge-weighted graphs 34 3.2.2. Dominated flooding in node- and edge-weighted graphs 36 3.2.3. Dominated flooding as a function of the ceiling function 37 3.3. The topography of dominated flooding 37 3.3.1. The regional minima of dominated flooding in an edge-weighted graph G[nil, η] 38 3.3.2. The regional minima of dominated n-flooding in node-weighted graphs G[ν, nil] 39 3.3.3. Algorithmic consequences 41 3.4. Computing dominated flooding by local adjustments 43 3.4.1. The case of edge-weighted graphs G[nil, η] 43 3.4.2. The case of node-weighted graphs G[ν, nil] 44 3.4.3. Software or hardware implementation of Berge’s algorithm 45 Chapter 4. Flooding and Flooding Distances 49 4.1. Summary of the chapter 49 4.2. Flooding distances 49 4.2.1. The flooding distance associated with the lakes of node- or edge-weighted graphs 49 4.2.2. Characterization of the flooding distance 50 4.2.3. Flooding distances on a graph or a tree 52 4.2.4. The shortest flooding distances 53 4.2.5. Dominated flooding and flooding distances 56 4.3. The shortest path algorithms for computing dominated flooding 66 4.3.1. Computing the shortest flooding distance with the Moore–Dijkstra algorithm 66 4.4. The flooding core-expanding algorithm 75 4.4.1. The first version of the core-expanding algorithm applied to the augmented graph G 76 4.4.2. The second version of the core-expanding algorithm applied to the initial graph G 78 4.4.3. The third version of the core-expanding algorithm applied to the initial graph G 79 4.5. Marker-based segmentation 81 4.5.1. The case of a node-weighted graph G(ν, nil) 81 Chapter 5. Graph Flooding via Dendrograms 83 5.1. Summary of the chapter 83 5.2. Introduction 84 5.3. Dendrograms: reminder 86 5.3.1. The structure associated with an order relation 86 5.3.2. Dendrograms 87 5.3.3. Stratification index and partial ultrametric distances (PUD) 88 5.4. The hierarchy of lake zones 89 5.4.1. The lake zones of an edge-weighted graph G(nil, η) 89 5.4.2. The hierarchy of lake zones, i.e. the closed balls of χ 92 5.4.3. Representing of hierarchy of lake zones 94 5.5. The law of communicating vessels 98 5.5.1. The flooding levels in connected subgraphs and closed balls 99 5.6. Dominated flooding on the dendrogram of lake zones 100 5.6.1. Notations 100 5.6.2. Incidence of the ceiling function on the dendrogram flooding levels 100 5.6.3. Finding the flooding level of a leaf 102 5.6.4. Parallel processing for flooding the dendrogram 105 5.6.5. Strategies for flooding the dendrogram of lake zones 106 5.7. Constructing and flooding a binary dendrogram 111 5.7.1. Two dendrograms representing the same hierarchy 111 5.7.2. Constructing a binary dendrogram representing a hierarchy 112 5.7.3. Flooding a binary dendrogram 113 5.8. A derived algorithm for dominated flooding 113 5.8.1. Algorithm “ancestor-flood without constructing the dendrogram” 117 5.8.2. Illustration 117 Part 2. Modeling a Real Hydrographic Basin 119 Chapter 6. The Hydrographic Basin of a Digital Elevation Model 121 6.1. Summary of the chapter 121 6.2. Preprocessing the digital elevation model 121 6.2.1. Suppressing the spurious regional minima 121 6.2.2. Creating an ∞ − steep digraph 123 6.2.3. Local pruning for extracting marked rivers 126 6.2.4. Extracting all rivers 128 6.2.5. Labeling sources and rivers 129 6.2.6. Detection of crest lines 131 6.2.7. Detecting the upstream of sources 132 6.2.8. Analyzing the tree structure of rivers 133 6.2.9. Constructing the catchment zones of riverlets 137 Part 3. Watershed Partitions 139 Chapter 7. Minimum Spanning Forests and Watershed Partitions 141 7.1. Summary of the chapter 141 7.2. Flooding distance, minimum spanning trees and forests 142 7.2.1. Flooding distances 142 7.2.2. Flooding distance on the minimum spanning tree of the graph G(nil, η) 143 7.2.3. Characterizing the MST 145 7.3. Minimum spanning forests rooted in markers 146 7.3.1. Constructing the minimum spanning forest 147 7.3.2. Converting the minimum spanning forest into a minimum spanning tree 149 7.4. Watershed partitions of weighted graphs 150 7.4.1. Catchment basins and watershed partitions 150 7.4.2. Flowing paths and catchment basins 151 7.5. Minimum spanning forests rooted in the regional minima 151 7.5.1. A minimum spanning forest corresponds to each watershed partition 151 7.5.2. Inversely, each watershed partition spans a minimum spanning forest 154 7.5.3. A rather unexpected watershed partition 156 7.6. A manifold of different watershed partitions 159 7.6.1. Catchment zones and catchment basins 159 7.7. Reducing the number of watershed partitions 160 7.7.1. Minimum spanning forests of k – steep or ∞ − steep graphs 163 7.7.2. The waterfall hierarchy 168 7.7.3. Usefulness of the waterfall hierarchy 171 Chapter 8. Marker-based Segmentation 175 8.1. Dominated flooding and minimum spanning forests 177 8.1.1. Dominated flooding 177 8.1.2. Minimum spanning forests 177 8.1.3. Illustration 178 8.1.4. Minimum spanning forests and dominated flooding 179 8.2. Constructing a minimum spanning forest rooted in the markers 183 8.2.1. Algorithms for constructing a minimum spanning forest 183 8.2.2. Increasing the selectiveness of Prim’s algorithm 186 8.2.3. Marker-based segmentation of node-weighted graphs 187 8.2.4. Derived algorithms 190 8.3. Marker-based segmentation after flooding the graph 194 8.3.1. Segmenting the dominated flooding of a graph 194 8.3.2. The case of an edge-weighted graph 194 8.3.3. Constructing a k – steep or ∞ − steep watershed partition for a node-weighted graph G(ν, nil) 200 8.4. Directly constructing a marker-based ∞ − steep watershed partition with the core expanding algorithm 201 8.5. The early days of marker-based segmentation 202 8.5.1. The level-by-level construction of a watershed 203 8.6. A two scale marker-based segmentation 205 8.7. Instant marker-based segmentation 205 8.7.1. Why and when we need instant marker-based segmentation 205 8.7.2. The reef and cascade distance 206 8.7.3. Computing the reef and cascade distance for all pairs of nodes in G(nil, η) 209 8.7.4. Computing the smallest reef and cascade distances between all couples of nodes in a graph 212 Conclusion 217 Appendix 227 References 239 Index 241

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Book SynopsisRecent advances in the disciplines of computer science (e.g., quantum theory, artificial intelligence), biotechnology and nanotechnology have deeply modified the structures of knowledge from which military capabilities are likely to develop. This book discusses the implications of disruptive technologies for the defence innovation ecosystem. Two complementary dimensions of the defence innovation ecosystem are highlighted: the industrial and intra-organizational. On the industrial scale, there is a shift in the ecology of knowledge underpinning the defence industrial and technological base (DITB). At the intra-organizational level, it is the actors’ practices that change and, through them, their skills and the processes by which they are acquired and transferred. In this context, the sources and legitimacy of innovation are being transformed, in turn requiring sometimes radical adaptations on the part of the various actors, including companies, military services, research communities and governmental agencies, which make up the defence innovation ecosystem.Table of ContentsIntroduction xiPierre BARBAROUX Part 1. Transformation of the Innovation Organization Model in the Defence Sector 1 Chapter 1. Innovation Dynamics in Defence Industries 3Jean BELIN and Marianne GUILLE 1.1. Introduction 3 1.2. Transformation of the defence industry’s innovation environment 4 1.2.1. Changes in the science and technology system 5 1.2.2. Intensifying competition and increasing complexity of the knowledge mobilized 10 1.2.3. Less dependence on defence financing 14 1.3. Opening of the defence sector 19 1.3.1. Development of duality 19 1.3.2. More cooperation 21 1.3.3. New institutions and stronger links with academic research 23 1.4. Conclusion 26 1.5. References 27 Chapter 2. Evolution of the Aerospace and Defence Innovation Model: Intensifying Science and Technology Relationships 31Cécile FAUCONNET 2.1. Introduction 31 2.2. Reflection framework 33 2.2.1. Defence innovation 33 2.2.2. Knowledge-based innovation 35 2.3. Methodology 37 2.3.1. Bibliometric approach 37 2.3.2. Data source and analysis 39 2.4. Results 43 2.4.1. Descriptive analysis 43 2.4.2. Scientific knowledge and quality of technological innovation 47 2.5. Conclusion 50 2.6. Appendices 50 2.7. References 53 Chapter 3. Identification of Defence Technological Knowledge Systems: A Tool for Duality Analysis 59François-Xavier MEUNIER 3.1. Introduction 59 3.2. Definition of a TKS and defence innovation 60 3.3. Data 63 3.4. Methodology 66 3.5. Results 70 3.6. Conclusion 76 3.7. References 77 Chapter 4. Defence Aerospace Firms: What Are the Technological Coherence of Their R&D? 81Cécile FAUCONNET, Didier LEBERT, Célia ZYLA and Sylvain MOURA 4.1. Introduction 81 4.2. Assumptions on the relatedness and technological coherence of DA firms 83 4.3. Measuring technological coherence 86 4.4. The data: scope and content 89 4.5. Main results 96 4.6. Conclusion 100 4.7. References 100 Chapter 5. Innovation and Legitimacy: The Case of Remotely Piloted Aircraft Systems 105Pierre BARBAROUX 5.1. Introduction 105 5.2. Technological innovation and legitimacy 108 5.3. The ecosystem of RPAS in France 110 5.4. The role of the French Air Force RPAS Center of Excellence (CED) in legitimizing RPAS systems 114 5.5. Implications and conclusion 117 5.6. References 119 Part 2. Transformation of Skills and Uses Induced by Innovations 121 Chapter 6. Man–machine Teaming: Towards a New Paradigm of Man–machine Collaboration? 123Vincent FERRARI 6.1. The challenges of collaboration 123 6.2. The sharing of human–machine authority: the premises of collaboration 125 6.3. Expert systems and human–system collaboration 128 6.4. AI and collaboration between human and artificial agents 129 6.4.1. The omnipresence of weak AI 130 6.4.2. The opacity of weak AI 130 6.4.3. A mistrust of weak AI 132 6.4.4. Strong AI for human–system collaboration? 133 6.5. Seeing beyond cognition to innovate 134 6.6. Conclusion 135 6.7. References 136 Chapter 7. Perspectives and Ambitions of the Maintenance in Operational Condition Renovated at the Heart of the Armament Programs: Illustrations in the Terrestrial Environment 139Nicolas HUÉ, Walter ARNAUD and Christophe GRANDEMANGE 7.1. Introduction 139 7.2. Context and future challenges of the MCO 140 7.2.1. End-to-end construction, from upstream phases to the in-service use phase 140 7.2.2. The necessary awareness of stakeholder responsibilities 141 7.2.3 What are the support mechanisms for better industrial accountability? 142 7.2.4. The influence of the environment 143 7.2.5. Financial issues that are central to the work 144 7.3. Innovations for the MCO of the future: the prerequisite for digitization 144 7.3.1. The necessary digitization of the MCO 144 7.3.2. The foundation of digitization: RFID, HUMS and interoperability. 145 7.4. Innovations for the MCO of the future: research and innovation challenges 150 7.4.1. Predictions of optimal maintenance plans: artificial intelligence and big data 150 7.4.2. Augmented and virtual reality (AR/VR) 151 7.4.3. 3D printing 151 7.4.4. Remote maintenance 152 7.5. Some safeguards 152 7.5.1. Technology at the service of humans 152 7.5.2. Jobs and skills that need to be managed in symbiosis 153 7.5.3. A strategic challenge for the DITB 153 7.6. Prospects for the future 154 Chapter 8. Technological Change and Individual Competencies: The Influence of Glass-cockpit Aircraft on French Air Force Pilots Training and Skills 155Cyril CAMACHON and Pierre BARBAROUX 8.1. Introduction 155 8.2. The pilot training model: epistemological foundations and typology of skills 157 8.3. Research context 159 8.3.1. Data sources and analyses 159 8.3.2. The initial training phase at Salon-de-Provence 161 8.4. Digitization of glass cockpits: what are the implications for pilot training? 163 8.4.1. The basic technical skills revisited 163 8.4.2. Reconfiguring the training toolset? The role of embedded simulation 169 8.5. Discussion and conclusion 174 8.6. References 177 Chapter 9. Towards the Advent of High-Altitude Pseudo-Satellites (HAPS) 181Bertrand KIRSCH and Olivier MONTAGNIER 9.1. Introduction 181 9.2. Capability issues: observation and telecommunications. 184 9.3. Solar flight history: projects, records and accidents 185 9.4. Resolution of a scientific and technological paradox 191 9.4.1. Solar energy: unlimited? 192 9.4.2. The keys to endurance 193 9.4.3. A technological challenge: the aeroelasticity of flexible wings 194 9.4.4. An alternative way to remedy flutter: aeroelastic weaving 197 9.5. Conclusion 199 9.6. References 200 Conclusion 203Pierre BARBAROUX List of Authors 209 Index 211

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Book SynopsisThe aim of the book is to analyse and understand the impacts of artificial intelligence in the fields of national security and defense; to identify the political, geopolitical, strategic issues of AI; to analyse its place in conflicts and cyberconflicts, and more generally in the various forms of violence; to explain the appropriation of artificial intelligence by military organizations, but also law enforcement agencies and the police; to discuss the questions that the development of artificial intelligence and its use raise in armies, police, intelligence agencies, at the tactical, operational and strategic levels.Table of ContentsIntroduction ix Chapter 1. On the Origins of Artificial Intelligence 1 1.1. The birth of artificial intelligence (AI) 1 1.1.1. The 1950s–1970s in the United States 1 1.1.2. AI research in China 7 1.1.3. AI research in Russia 9 1.1.4. AI research in Japan 12 1.1.5. AI research in France 14 1.2. Characteristics of AI research 16 1.3. The sequences of AI history 19 1.4. The robot and robotics 23 1.5. Example of AI integration: the case of the CIA in the 1980s 27 1.5.1. The CIA’s instruments and methods for understanding and appropriating AI adapted to its needs 29 1.5.2. Focus groups, research, coordination 35 1.5.3. The network of interlocutors outside the intelligence community 36 1.5.4. What AI applications for what intelligence needs? 42 Chapter 2. Concepts and Discourses 45 2.1. Defining AI 47 2.1.1. AI 47 2.1.2. Expert systems 54 2.1.3. Machine learning and deep learning 56 2.1.4. The robot, robotics 57 2.2. Types of AI 60 2.3. Evolution of the themes over time 62 2.3.1. Google Trends 62 2.3.2. The AAAI magazine 63 2.4. The stories generated by artificial intelligence 67 2.4.1. The transformative power of AI 67 2.4.2. The absolute superiority of human intelligence over the machine 75 2.4.3. The replacement of humans by machines 76 2.4.4. AI as an existential threat 77 2.4.5. The place of AI and robotics in fiction: the example of Japan 80 2.5. Political considerations 82 2.5.1. National strategies for artificial intelligence 85 2.5.2. U.S. policy 97 Chapter 3. Artificial Intelligence and Defense Issues 105 3.1. Military policies and doctrines for AI: the American approach 105 3.1.1. American defense AI policy 105 3.1.2. AI in American military doctrines 114 3.2. Military AI in Russia 128 3.3. AI and the art of warfare 136 3.3.1. Manuel de Landa: war in the age of intelligent machines 136 3.3.2. AI announcing a new RMA? 139 3.3.3. Applications of AI in the military field 143 3.3.4. Expert systems in military affairs 146 3.3.5. Autonomous weapons 148 3.3.6. Robotics and AI 151 3.4. AI and cyber conflict 155 3.4.1. Malware, cybersecurity and AI 157 3.4.2. AI and cyberweapons 162 3.4.3. Offensive–defensive/security configurations 163 3.4.4. Adversarial AI and adversarial Machine Learning 171 3.4.5. AI and information warfare 173 3.4.6. Example 1: the war in Syria 179 3.4.7. Example 2: events in Hong Kong in 2019 181 3.4.8. Example 3: malicious AI attacks 183 3.4.9. Example 4: swarming attacks 184 3.4.10. Example 5: crossing universes with AI and without AI 185 Conclusion 187 Appendices 195 Appendix 1. A Chronology of AI 197 Appendix 2. AI in Joint Publications (Department of Defense, United States) 207 Appendix 3. AI in the Guidelines and Instructions of the Department of Defense (United States) 209 Appendix 4. AI in U.S. Navy Instructions 211 Appendix 5. AI in U.S. Marine Corps Documents 213 Appendix 6. AI in U.S. Air Force Documents 215 References 217 Index 235

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Book SynopsisOptimization is central to any problem involving decision-making in engineering. Optimization theory and methods deal with selecting the best option regarding the given objective function or performance index. New algorithmic and theoretical techniques have been developed for this purpose, and have rapidly diffused into other disciplines. As a result, our knowledge of all aspects of the field has grown even more profound. In Optimization for Engineering Problems, eminent researchers in the field present the latest knowledge and techniques on the subject of optimization in engineering. Whereas the majority of work in this area focuses on other applications, this book applies advanced and algorithm-based optimization techniques specifically to problems in engineering. Table of ContentsPreface ix Chapter 1. Review of some Constrained Optimization Schemes 1Jonnalagadda SRINIVAS 1.1. Introduction 1 1.2. Constrained optimization problems 3 1.3. Direct solution techniques 4 1.3.1. Complex search method 4 1.3.2. Random search techniques 6 1.3.3. Method of feasible directions 7 1.4. Indirect solution techniques 8 1.4.1. Penalty function approach 8 1.4.2. Multipliers method 10 1.4.3. Simulated annealing search 10 1.5. Constrained multi-objective optimization 12 1.6. Conclusions 14 1.7. References 14 Chapter 2. Application of Flower Pollination Algorithm for Optimization of ECM Process Parameters 17Bappa ACHERJEE, Debanjan MAITY, Arunanshu S. KUAR and Manoj K. DUTTA 2.1. Introduction 17 2.2. Flower pollination algorithm 21 2.3. Optimization of the ECM process: results and discussions 23 2.3.1. Experimental data and empirical models 24 2.3.2. Single-objective optimization 25 2.3.3. Multi-objective optimization 31 2.4. Conclusion 34 2.5. References 35 Chapter 3. Machinability and Multi-response Optimization of EDM of Al7075/SIC/WS2 Hybrid Composite Using the PROMETHEE Method 39Mohan Kumar PRADHAN and Brajpal SINGH 3.1. Introduction 40 3.1.1. Overview of metal matrix composites 41 3.1.2. CNC EDM machine 42 3.2. Literature review 49 3.2.1. Metal removing rate 51 3.2.2. Tool wear process 53 3.2.3. Radial overcut 54 3.2.4. Surface topography or surface finish 54 3.3. Optimization process 55 3.3.1. Analytic hierarchy process method 55 3.3.2. PROMETHEE method 60 3.3.3. Ranking relations for improved PROMETHEE 63 3.4. Result and discussion 66 3.4.1. The effect of EDM parameters on machining characteristics of EDM machine 66 3.4.2. Optimization of EDM parameters 71 3.5. Conclusion 71 3.6. References 72 Chapter 4. Optimization of Cutting Parameters during Hard Turning using Evolutionary Algorithms 77Vahid POURMOSTAGHIMI and Mohammad ZADSHAKOYAN 4.1. Introduction 78 4.2. Genetic programming 83 4.3. Particle swarm optimization 86 4.4. Materials and methods 89 4.4.1. Experimental setup 89 4.4.2. Optimization procedure 90 4.5. Results 92 4.5.1. Experimental results 92 4.5.2. GP results 93 4.5.3. Optimization results 95 4.6. Conclusion 96 4.7. References 96 Chapter 5. Development of a Multi-objective Salp Swarm Algorithm for Benchmark Functions and Real-world Problems 101Sushant P. MHATUGADE, Ganesh M. KAKANDIKAR, Omkar K. KULKARNI and Vilas M. NANDEDKAR 5.1. Introduction 101 5.2. Salp swarm algorithm 105 5.2.1. Single-objective salp swarm algorithm (SSA) 107 5.2.2. Multi-objective salp swarm algorithm (MSSA) 109 5.3. Constraint handling techniques 113 5.4. Experimental results and discussion 114 5.4.1. Single-objective unconstrained test functions 115 5.4.2. Single-objective constrained test functions 117 5.4.3. Multi-objective unconstrained test functions 120 5.4.4. Multi-objective constrained test functions 122 5.4.5. Real-world application 125 5.5. Conclusion 127 5.6. References 128 Chapter 6. Water Quality Index: is it Possible to Measure with Fuzzy Logic? 131Alexandre CHOUPINA, Elisabeth T. PEREIRA, Samara Silva SOARES, Poliana ARRUDA, Francis Lee RIBEIRO and Paulo Sérgio SCALIZE 6.1. Introduction 131 6.2. Data and methodology 134 6.2.1. Data and description of the case study 134 6.2.2. Parameters 135 6.2.3. Water quality index 136 6.2.4. Construction of the water quality index by fuzzy logic (WQF) 144 6.3. Results and discussion 148 6.3.1. Water quality analysis 148 6.3.2. Index validation 150 6.4. Conclusions 154 6.5. Appendix 155 6.6. References 156 List of Authors 161 Index 163

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Book SynopsisMobile Robotics presents the different tools and methods that enable the design of mobile robots; a discipline booming with the emergence of flying drones, underwater mine-detector robots, robot sailboats and vacuum cleaners. Illustrated with simulations, exercises and examples, this book describes the fundamentals of modeling robots, developing the concepts of actuators, sensors, control and guidance. Three-dimensional simulation tools are also explored, as well as the theoretical basis for the reliable localization of robots within their environment. This revised and updated edition contains additional exercises and a completely new chapter on the Bayes filter, an observer that enhances our understanding of the Kalman filter and facilitates certain proofs.Table of ContentsIntroduction ix Chapter 1. Three-dimensional Modeling 1 1.1. Rotation matrices 1 1.1.1. Definition 2 1.1.2. Lie group 3 1.1.3. Lie algebra 4 1.1.4. Rotation vector 5 1.1.5. Adjoint 6 1.1.6. Rodrigues rotation formulas 7 1.1.7. Coordinate system change 8 1.2. Euler angles 11 1.2.1. Definition 11 1.2.2. Rotation vector of a moving Euler matrix 13 1.3. Inertial unit 14 1.4. Dynamic modeling 17 1.4.1. Principle 17 1.4.2. Modeling a quadrotor 18 1.5. Exercises 20 1.6. Corrections 37 Chapter 2. Feedback Linearization 65 2.1. Controlling an integrator chain 65 2.1.1. Proportional-derivative controller 66 2.1.2. Proportional-integral-derivative controller 67 2.2. Introductory example 68 2.3. Principle of the method 69 2.3.1. Principle 69 2.3.2. Relative degree 71 2.3.3. Differential delay matrix 72 2.3.4. Singularities 73 2.4. Cart 75 2.4.1. First model 75 2.4.2. Second model 76 2.5. Controlling a tricycle 78 2.5.1. Speed and heading control 78 2.5.2. Position control 80 2.5.3. Choosing another output 81 2.6. Sailboat 82 2.6.1. Polar curve 83 2.6.2. Differential delay 83 2.6.3. The method of feedback linearization 84 2.6.4. Polar curve control 87 2.7. Sliding mode 87 2.8. Kinematic model and dynamic model 90 2.8.1. Principle 90 2.8.2. Example of the inverted rod pendulum 91 2.8.3. Servo-motors 94 2.9. Exercises 95 2.10. Corrections 107 Chapter 3. Model-free Control 133 3.1. Model-free control of a robot cart 134 3.1.1. Proportional heading and speed controller 134 3.1.2. Proportional-derivative heading controller 136 3.2. Skate car 137 3.2.1. Model 138 3.2.2. Sinusoidal control 140 3.2.3. Maximum thrust control 140 3.2.4. Simplification of the fast dynamics 142 3.3. Sailboat 145 3.3.1. Problem 145 3.3.2. Controller 146 3.3.3. Navigation 152 3.3.4. Experiment 153 3.4. Exercises 155 3.5. Corrections 168 Chapter 4. Guidance 183 4.1. Guidance on a sphere 183 4.2. Path planning 187 4.2.1. Simple example 187 4.2.2. Bézier polynomials 188 4.3. Voronoi diagram 189 4.4. Artificial potential field method 191 4.5. Exercises 192 4.6. Corrections 201 Chapter 5. Instantaneous Localization 221 5.1. Sensors 221 5.2. Goniometric localization 225 5.2.1. Formulation of the problem 225 5.2.2. Inscribed angles 226 5.2.3. Static triangulation of a plane robot 228 5.2.4. Dynamic triangulation 229 5.3. Multilateration 230 5.4. Exercises 231 5.5. Corrections 236 Chapter 6. Identification 243 6.1. Quadratic functions 243 6.1.1. Definition 243 6.1.2. Derivative of a quadratic form 244 6.1.3. Eigenvalues of a quadratic function 245 6.1.4. Minimizing a quadratic function 245 6.2. The least squares method 246 6.2.1. Linear case 246 6.2.2. Nonlinear case 248 6.3. Exercises 250 6.4. Corrections 253 Chapter 7. Kalman Filter 263 7.1. Covariance matrices 263 7.1.1. Definitions and interpretations 263 7.1.2. Properties 266 7.1.3. Confidence ellipse 267 7.1.4. Generating Gaussian random vectors 268 7.2. Unbiased orthogonal estimator 269 7.3. Application to linear estimation 274 7.4. Kalman filter 275 7.5. Kalman–Bucy 279 7.6. Extended Kalman filter 282 7.7. Exercises 283 7.8. Corrections 298 Chapter 8. Bayes Filter 329 8.1. Introduction 329 8.2. Basic notions of probabilities 329 8.3. Bayes filter 332 8.4. Bayes smoother 334 8.5. Kalman smoother 335 8.5.1. Equations of the Kalman smoother 335 8.5.2. Implementation 336 8.6. Exercises 337 8.7. Corrections 345 References 359 Index 361

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Book SynopsisThis book – the first of two volumes – explores the syntactical constructs of the most common programming languages, and sheds a mathematical light on their semantics, while also providing an accurate presentation of the material aspects that interfere with coding. Concepts and Semantics of Programming Languages 1 is dedicated to functional and imperative features. Included is the formal study of the semantics of typing and execution; their acquisition is facilitated by implementation into OCaml and Python, as well as by worked examples. Data representation is considered in detail: endianness, pointers, memory management, union types and pattern-matching, etc., with examples in OCaml, C and C++. The second volume introduces a specific model for studying modular and object features and uses this model to present Ada and OCaml modules, and subsequently Java, C++, OCaml and Python classes and objects. This book is intended not only for computer science students and teachers but also seasoned programmers, who will find a guide to reading reference manuals and the foundations of program verification.Table of ContentsForeword xi Preface xiii Chapter 1. From Hardware to Software 1 1.1. Computers: a low-level view 1 1.1.1. Information processing 1 1.1.2. Memories 2 1.1.3. CPUs 3 1.1.4. Peripheral devices 7 1.2. Computers: a high-level view 8 1.2.1. Modeling computations 9 1.2.2. High-level languages 9 1.2.3. From source code to executable programs 10 Chapter 2. Introduction to Semantics of Programming Languages 15 2.1. Environment, memory and state 16 2.1.1. Evaluation environment 16 2.1.2. Memory 18 2.1.3. State 20 2.2. Evaluation of expressions 21 2.2.1. Syntax 21 2.2.2. Values 22 2.2.3. Evaluation semantics 24 2.3. Definition and assignment 26 2.3.1. Defining an identifier 26 2.3.2. Assignment 29 2.4. Exercises 31 Chapter 3. Semantics of Functional Features 35 3.1. Syntactic aspects 35 3.1.1. Syntax of a functional kernel 35 3.1.2. Abstract syntax tree 36 3.1.3. Reasoning by induction over expressions 39 3.1.4. Declaration of variables, bound and free variables 39 3.2. Execution semantics: evaluation functions 42 3.2.1. Evaluation errors 42 3.2.2. Values 43 3.2.3. Interpretation of operators 45 3.2.4. Closures 46 3.2.5. Evaluation of expressions 47 3.3. Execution semantics: operational semantics 54 3.3.1. Simple expressions 55 3.3.2. Call-by-value 56 3.3.3. Recursive and mutually recursive functions 60 3.3.4. Call-by-name 61 3.3.5. Call-by-value versus call-by-name 62 3.4. Evaluation functions versus evaluation relations 64 3.4.1. Status of the evaluation function 64 3.4.2. Induction over evaluation trees 65 3.5. Semantic properties 69 3.5.1. Equivalent expressions 69 3.5.2. Equivalent environments 71 3.6. Exercises 71 Chapter 4. Semantics of Imperative Features 77 4.1. Syntax of a kernel of an imperative language 77 4.2. Evaluation of expressions 81 4.3. Evaluation of definitions 86 4.4. Operational semantics 89 4.4.1. Big-step semantics 89 4.4.2. Small-step semantics 93 4.4.3. Expressiveness of operational semantics 95 4.5. Semantic properties 96 4.5.1. Equivalent programs 96 4.5.2. Program termination 98 4.5.3. Determinism of program execution 100 4.5.4. Big steps versus small steps 103 4.6. Procedures 109 4.6.1. Blocks 109 4.6.2. Procedures 112 4.7. Other approaches 118 4.7.1. Denotational semantics 118 4.7.2. Axiomatic semantics, Hoare logic 129 4.8. Exercises 134 Chapter 5. Types 137 5.1. Type checking: when and how? 139 5.1.1. When to verify types? 139 5.1.2. How to verify types? 140 5.2. Informal typing of a program Exp2 141 5.2.1. A first example 141 5.2.2. Typing a conditional expression 142 5.2.3. Typing without type constraints 142 5.2.4. Polymorphism 143 5.3. Typing rules in Exp2 143 5.3.1. Types, type schemes and typing environments 143 5.3.2. Generalization, substitution and instantiation 146 5.3.3. Typing rules and typing trees 151 5.4. Type inference algorithm in Exp2 154 5.4.1. Principal type 154 5.4.2. Sets of constraints and unification 155 5.4.3. Type inference algorithm 159 5.5. Properties 167 5.5.1. Properties of typechecking 167 5.5.2. Properties of the inference algorithm 167 5.6. Typechecking of imperative constructs 168 5.6.1. Type algebra 168 5.6.2. Typing rules 169 5.6.3. Typing polymorphic definitions 171 5.7. Subtyping and overloading 172 5.7.1. Subtyping 173 5.7.2. Overloading 175 Chapter 6. Data Types 179 6.1. Basic types 179 6.1.1. Booleans 179 6.1.2. Integers 181 6.1.3. Characters 186 6.1.4. Floating point numbers 187 6.2. Arrays 191 6.3. Strings 194 6.4. Type definitions 194 6.4.1. Type abbreviations 195 6.4.2. Records 196 6.4.3. Enumerated types 200 6.4.4. Sum types 202 6.5. Generalized conditional 205 6.5.1. C style switch/case 205 6.5.2. Pattern matching 208 6.6. Equality 216 6.6.1. Physical equality 217 6.6.2. Structural equality 218 6.6.3. Equality between functions 220 Chapter 7. Pointers and Memory Management 223 7.1. Addresses and pointers 223 7.2. Endianness 225 7.3. Pointers and arrays 225 7.4. Passing parameters by address 226 7.5. References 229 7.5.1. References in C++ 229 7.5.2. References in Java 233 7.6. Memory management 234 7.6.1. Memory allocation 234 7.6.2. Freeing memory 237 7.6.3. Automatic memory management 239 Chapter 8. Exceptions 243 8.1. Errors: notification and propagation 243 8.1.1. Global variable 245 8.1.2. Record definition 245 8.1.3. Passing by address 245 8.1.4. Introducing exceptions 246 8.2. A simple formalization: ML-style exceptions 247 8.2.1. Abstract syntax 247 8.2.2. Values 248 8.2.3. Type algebra 248 8.2.4. Operational semantics 248 8.2.5. Typing 250 8.3. Exceptions in other languages 250 8.3.1. Exceptions in OCaml 251 8.3.2. Exceptions in Python 251 8.3.3. Exceptions in Java 253 8.3.4. Exceptions in C++ 254 Conclusion 257 Appendix: Solutions to the Exercises 259 List of Notations 287 Index of Programs 289 References 293 Index 295

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Book SynopsisThe ability of wireless communication devices to transmit reliable information is fundamentally limited by sources of noise related to the electronic components in use. Noise in Radio-Frequency Electronics and its Measurement has five chapters that address the theoretical aspects of this subject, and concludes with a series of exercises and solutions. The book examines the origin and sources of noise inside electronic radio-frequency circuits, their impact in telecommunications, their modeling and their measurement. Particular attention is dedicated to the origins, establishment and significance of formulas that are used when the noise characteristics of an electronic circuit are modeled or measured. This book instructs the reader in the application of the examined methods and their adaptation to solving problems, as well as how to comfortably use the presented formulas.Table of ContentsPreface ix List of Symbols xi Introduction xv Chapter 1. Background Noise in Electronics 1 1.1. Introduction 1 1.2. Spontaneous fluctuations in electronic components 2 1.2.1. Introduction 2 1.2.2. Thermal noise 2 1.2.3. Shot noise 7 1.2.4. Generation / recombination noise 7 1.2.5. Excess noise 8 1.3. Noise factor 9 1.3.1. Definition 9 1.3.2. Reference temperature for the noise factor 11 1.3.3. Importance of the noise factor in telecommunications 12 1.4. Noise in two-ports 13 1.4.1. Representation of noise in two-ports 13 1.4.2. Expression of the noise factor of a two-port 15 1.4.3. Minimum noise factor of a two-port 16 1.4.4. Inverse relations 19 1.5. Characterization of noise in a two-port 20 1.6. Conclusion 22 Chapter 2. Friis Formula 23 2.1. Introduction 23 2.2. Calculation method 24 2.3. Calculation of the admittance parameters of the Q1, Q2 association in cascade 26 2.4. Contribution of noise generators e1, i1, e2 and i2 to I1 and I4 27 2.4.1. Introduction 27 2.4.2. Contribution of the noise generator e1 27 2.4.3. Contribution of the noise generator i1 28 2.4.4. Contribution of the noise generator e2 28 2.4.5. Contribution of the noise generator i2 29 2.5. eTot and iTot identification 30 2.6. Calculation of F12(YS) 30 2.7. Friis Formula 31 2.7.1. Introduction 31 2.7.2. Transducer power gain 32 2.7.3. Available power gain 34 2.8. Conclusion 35 Chapter 3. Adapted Attenuator and Noise Factor 37 3.1. Introduction 37 3.2. Calculation of Y and S parameters 38 3.3. General representation of noise in two-ports 39 3.4. Equivalent noise generators at the input of the adapted attenuator 40 3.5. Noise factor on 50 Ω of the adapted attenuator 41 3.6. Using Bosma’s theorem 43 3.7. Consequences on the structure of a receiver 46 3.8. Equivalent noise resistance and noise conductance at the input 47 3.9. Conclusion 48 Chapter 4. Noise Factor Measurement on 50 Ω 51 4.1. Introduction 51 4.2. Noise factor measurement by Y factor 52 4.3. Second stage correction 54 4.4. Measurement procedure and calculation of the noise factor of the DUT 55 4.5. Available power gain and insertion power gain of the DUT 57 4.6. Sample results 60 4.7. Conclusion 62 Chapter 5. Characterization in Noise 65 5.1. Introduction 65 5.2. The tuner 67 5.2.1. Tuner constitution 67 5.2.2. Noise behavior of the noise diode + tuner assembly 68 5.2.3. Tuner calibration procedure 71 5.3. Characterization in noise of the noise measurement chain 73 5.4. Characterization in S parameters of the device under test 74 5.5. Noise characterization of the device under test 74 5.6. Validation of a noise characterization bench 75 5.6.1. Introduction 75 5.6.2. 2.5 dB adapted attenuator 76 5.6.3. Coaxial cable 78 5.7. Conclusion 79 Chapter 6. Exercises and Answers 81 6.1. Exercises 81 6.2. Solutions 91 Conclusion 117 Appendix 1 119 Appendix 2 125 Appendix 3 135 Appendix 4 149 Bibliography 163 Index 165

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Book SynopsisSince its commercialization in 1971, the microprocessor, a modern and integrated form of the central processing unit, has continuously broken records in terms of its integrated functions, computing power, low costs and energy saving status. Today, it is present in almost all electronic devices. Sound knowledge of its internal mechanisms and programming is essential for electronics and computer engineers to understand and master computer operations and advanced programming concepts. This book in five volumes focuses more particularly on the first two generations of microprocessors, those that handle 4- and 8- bit integers. Microprocessor 1 – the first of five volumes – presents the computation function, recalls the memory function and clarifies the concepts of computational models and architecture. A comprehensive approach is used, with examples drawn from current and past technologies that illustrate theoretical concepts, making them accessible.Table of ContentsQuotation vii Preface ix Introduction xiii Chapter 1. The Function of Computation 1 1.1. Beginnings 2 1.2. Classes of computers 10 1.3. Analog approach 36 1.4. Hardware–software relationship 37 1.5. Integration and its limits 43 1.6. Conclusion 47 Chapter 2. The Function of Memory 49 2.1. Definition 50 2.2. Related concepts 56 2.2.1. A story of endianness 56 2.2.2. Alignment 56 2.3. Modeling 57 2.4. Classification 59 2.5. Conclusion 61 Chapter 3. Computation Model and Architecture: Illustration with the von Neumann Approach 63 3.1. Basic concepts 64 3.1.1. The idea of a program 64 3.1.2. Control and data flows and mechanisms 65 3.1.3. Models of computation 67 3.1.4. Architectures 72 3.1.5. The semantic gap 80 3.2. The original von Neumann machine 81 3.2.1. von Neumann’s computation model 81 3.2.2. von Neumann’s (machine) architecture 82 3.2.3. Control 89 3.3. Modern von Neumann machines 90 3.3.1. Abstraction level 91 3.3.2. Base execution outline 97 3.3.3. Possible transfers 100 3.3.4. Summary: advantages and disadvantages of this model 102 3.4. Variations on a theme 104 3.4.1. Classification by bus 104 3.4.2. Harvard architectures 111 3.4.3. Parallelism 113 3.5. Instruction set architecture 117 3.5.1. Storage components 118 3.5.2. Data format and type 126 3.5.3. Instruction set 126 3.5.4. Memory model 127 3.5.5. Execution modes 128 3.5.6. Miscellaneous 128 3.6. Basic definitions for this book 128 3.7. Conclusion 129 Conclusion of Volume 1 131 Exercises 133 Acronyms 135 References 153 Index 173

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Book SynopsisThe book is intended for students in engineering school or university, young engineers or newcomers in the automotive industry or aeronautics. The objective is to describe in a simple and clear way the problem of energy and motorization for the automobile, helicopters or airplanes. The front-end treatment of these industrial sectors makes it possible to analyze in an original way the similarities and differences of these different means of transport. For this, and based on current technologies and tomorrow, it specifically describes the problem of the energy requirement of cars and aircraft. The result is a search for an ideal motorization associated with the behavior of these different means of transport followed by the analysis of the performances of the various types of engines by covering gas turbines, internal combustion engines and electric motors. Transmission elements such as aerospace gearboxes or gearboxes are described as well as a chapter on energy storage means and their performance including batteries, supercapacitors, inertial or pneumatic storage, hydrogen or fuels from fossil fuels. A final chapter shows the interest and prospects of energy hybridization and electrification for the progressive replacement of fossil fuels. Beyond the technological descriptions, the book focuses on proposing basic sizing rules in order to justify certain performances and to give the reader the means to appropriate the basic know-how of these industrial sectors.Table of ContentsForeword ix Preface xi Introduction xv Chapter 1. Motorization and Reflection on Ideal Engines 1 1.1. Motorization for an aircraft 1 1.1.1. Helicopters 1 1.1.2. Aircraft 19 1.1.3. Compound formulas 22 1.2. Motorization for an automobile 25 1.2.1. Determining tractive force and useful power 25 1.2.2. Definition of ideal transportation powertrain 30 1.3. Conclusion 33 Chapter 2. Engine Technologies 35 2.1. Introduction 35 2.2. Gas turbines 36 2.2.1. General operating principles 36 2.2.2. Improvement of gas turbines 79 2.3. Electric motors 87 2.3.1. Introduction to electric motors 87 2.3.2. Use of electric motors and mission profile 93 2.3.3. Electric motor technologies for propulsion 101 2.3.4. Examples of specific propulsion systems and applications 105 2.4. Internal combustion engine pistons 111 2.4.1. Theoretical thermodynamic cycles 111 2.4.2. Real cycles 128 2.5. Conclusion 142 Chapter 3. Power Transmission Elements 145 3.1. Transmission system for rotating wings 145 3.1.1. Conventional helicopters 145 3.1.2. The case of multi-rotor structures 151 3.2. Transmission system for aircraft 152 3.2.1. Propeller aircraft cases 152 3.2.2. Turbojet aircraft 153 3.3. Transmission system for the automotive industry 154 3.3.1. Gasoline or diesel internal combustion engines 154 3.3.2. The case of electric motors 167 3.4. Conclusion 168 Chapter 4. Energy Storage 171 4.1. Classification of energy sources 171 4.1.1. Primary energy sources 171 4.1.2. Energy carrier concept 173 4.1.3. Use of different energy sources in automotive and aeronautical transport 174 4.2. Energy storage for transport 178 4.2.1. Different forms of energy storage 178 4.2.2. Different energy storage technologies 179 4.3. Forms of hydrogen storage 186 4.3.1. Storage in gaseous form 187 4.3.2. Storage in liquid form 188 4.3.3. Storage in solid form 189 4.3.4. Comparison of diesel fuel tanks and automotive batteries 213 4.4. Conclusion 217 Chapter 5. Hybridization 219 5.1. Hybridization of electric motors: range extender 221 5.1.1. Application examples for the automotive industry 222 5.1.2. Application examples for aeronautics 229 5.2. Hybridization of combustion engines: improving energy efficiency 232 5.2.1. Interest in parallel hybridization 232 5.2.2. Classification of electrical hybridization: the case of the automobile 234 5.2.3. Implementation of hybridization in the case of the automobile 255 5.3. Conclusion 263 References 265 Index 269

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Book SynopsisThe book deals with requirements engineering in the context of System Engineering. He proposes a method to guide this activity engineering. The method is supported by the SysML modeling language. A first chapter aims to present the context and the associated definitions, to position the requirements engineering in the processes system engineering, to define the modeling and its contributions, and to make the link with the management of IS projects. The second chapter is devoted to the proposed method for implementing the requirements engineering subprocesses. Each of the 8 activities the component is first described before specifying how the SysML language can be exploited to achieve it effectively. Proposal for a book Please fill out the questionnaire below and send it back to Chantal Menascé: c.menasce@iste.co.uk The 3rd chapter is an application of the method to define the needs of the stakeholders of a system. The example is built on the basis of the RobAFIS'2018 competition. The 4th chapter continues the application of the method in the continuity of the IS processes to define the requirements of the same system. The appendices present at the same time a toolbox to realize the engineering of the requirements but also the complete results of engineering in Chapters 3 and 4.Table of ContentsForeword ix Preface xiii Part 1. Requirements Engineering 1 Chapter 1. The Requirements Engineering Process 3 1.1. Background and main definitions 3 1.2. Requirements engineering process 10 1.2.1. Requirements engineering and ISO 15288 processes 11 1.2.2. Requirements engineering and ISO 29110 processes 14 1.2.3. Problem versus solution 18 1.3. Requirements engineering process and modeling 19 1.4. Engineering processes and project management 26 Chapter 2. A Method for Requirements Engineering 31 2.1. Proposal of a requirements engineering method 31 2.1.1. Requirement diagram 36 2.1.2. Block definition diagram 38 2.1.3. Use case diagram 38 2.1.4. State machine diagram 39 2.1.5. Sequence diagram 39 2.1.6. Activity diagram 40 2.2. Define the system framework 40 2.2.1. Goal 40 2.2.2. Define the system framework using SysML 41 2.2.3. Systematization and verification 43 2.3. Define the system life cycle 43 2.3.1. Goal 43 2.3.2. Define the system life cycle using SysML 44 2.3.3. Systematization and verification 45 2.4. Define contexts45 2.4.1. Goal 45 2.4.2. Define contexts using SysML 45 2.4.3. Systematization and verification 47 2.5. Define uses 47 2.5.1. Goal 47 2.5.2. Define uses using SysML 49 2.5.3. Systematization and verification 52 2.6. Describe the use scenarios 53 2.6.1. Goal 53 2.6.2. Describe the use scenarios using SysML 53 2.6.3. Systematization and verification 62 2.7. Define functional requirements 62 2.7.1. Goal 62 2.7.2. Define functional requirements using SysML 65 2.7.3. Systematization and verification 67 2.8. Define non-functional requirements 67 2.8.1. Goal 67 2.8.2. Define non-functional requirements using SysML 68 2.8.3. Systematization and verification 70 2.9. Ensure traceability 72 2.9.1. Goal 72 2.9.2. Ensure traceability using SysML 72 2.9.3. Systematization and verification 75 2.10. Conclusion 75 Part 2. Case Study, Application of the Method 77 Chapter 3. Definition of Stakeholders’ Needs 79 3.1. Case study 79 3.1.1. Context of the case study 80 3.1.2. Structure of the SysML project 81 3.1.3. Presentation of the results 84 3.2. Definition of needs 85 3.2.1. Define the system framework 85 3.2.2. Define the system life cycle 86 3.2.3. Define contexts 87 3.2.4. Define uses 89 3.2.5. Describe the use scenarios 92 3.2.6. Define functional requirements 92 3.2.7. Define non-functional requirements 95 3.2.8. Ensure traceability 95 3.3. Stakeholder needs definition documents 98 3.3.1. Use a document template 98 3.3.2. Use a list of needs 119 Chapter 4. System Requirements Engineering 125 4.1. Case study 125 4.1.1. Structure of the SysML project 125 4.1.2. Presentation of the results 126 4.2. Definition of system requirements 126 4.2.1. Define the system framework 126 4.2.2. Define the system life cycle 127 4.2.3. Define contexts 127 4.2.4. Define uses 128 4.2.5. Describe the use scenarios 132 4.2.6. Define functional requirements 135 4.2.7. Define non-functional requirements 136 4.2.8. Ensure traceability 136 4.3. System requirements analysis document 139 4.4. Requirements management 161 4.4.1. Fundamental elements 162 4.4.2. Management workflows 168 4.4.3. Use in student projects 173 Chapter 5. Integration with Other Methods 175 5.1. Context 175 5.2. Integration with the Harmony SE method 175 5.2.1. Modification of the project structure 176 5.2.2. The Harmony SE method and requirements engineering 176 5.2.3. Definition of stakeholders’ needs 178 5.2.4. Analysis of system requirements 179 5.2.5. Conclusion 180 5.3. Integration with the Arcadia method 180 5.3.1. The Arcadia method and requirements engineering 181 5.3.2. Definition of stakeholders’ needs 182 5.3.3. Analysis of system requirements 183 5.3.4. Conclusion 185 5.4. Integration with the CESAM method 186 5.4.1. The CESAM method and requirements engineering 186 5.4.2. Definition of stakeholders’ needs 187 5.4.3. Analysis of system requirements 189 5.4.4. Conclusion 189 References 191 Index 195

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Book SynopsisSince the early 2000s, energy and environmental issues have led to a marked increase in electricity production from renewable energy sources. Sustainable development and concern for future generations constantly challenge us to develop new technologies for energy production, as well as new energy usage patterns. Their rapid emergence can make these new technologies difficult to understand and can thus affect perceptions.Directed towards a broad audience, this book contributes to a better understanding of new electricity generation technologies. It presents the issues, sources and means of conversion using a general approach, while developing scientific concepts to understand their main technical characteristics.This revised and extended second edition presents current data characterizing the development of these renewable energy sources, covering emerging photovoltaic and tidal technologies, offshore wind power, and recent developments on the integration of these sources into the electricity grid. The emergence of self-production and self-consumption is also addressed. In addition, several exercises provide the reader with an opportunity to evaluate their understanding.Table of ContentsForeword xiBernard MULTON Introduction xiiiBenoît ROBYNS Chapter 1. Electricity Production from Renewable Energy 1Benoît ROBYNS 1.1. Decentralized or centralized production? 1 1.1.1. Decentralized production 1 1.1.2. Centralized production 2 1.2. The issue of renewable energies 3 1.2.1. Observations 3 1.2.2. The sustainable development context 6 1.2.3. Commitments and perspectives 7 1.3. Renewable energy sources 10 1.3.1. Wind energy 10 1.3.2. Solar energy 11 1.3.3. Hydraulics 12 1.3.4. Geothermal energy 13 1.3.5. Biomass 13 1.3.6. Contribution of the various renewable energies 14 1.4. Production of electricity from renewable energies 15 1.4.1. Electricity supply chains 15 1.4.2. Efficiency factor 18 1.5. Self-production and self-consumption of energy 19 1.6. References 20 Chapter 2. Solar Photovoltaic Power 21Arnaud DAVIGNY 2.1. Introduction 21 2.2. Characteristics of the primary resource 23 2.3. Photovoltaic conversion 29 2.3.1. Introduction 29 2.3.2. Photovoltaic effect 29 2.3.3. Photovoltaic cells 32 2.3.4. Cell association 56 2.4. Maximum electric power extraction 62 2.5. Power converters 66 2.5.1. Introduction 66 2.5.2. Structure of the photovoltaic conversion chains 67 2.5.3. Choppers 69 2.5.4. Inverters 73 2.6. Adjustment of the active and reactive power 78 2.7. Solar power stations 79 2.7.1. Introduction 79 2.7.2. Autonomous power stations 79 2.7.3. Power stations connected to the network 81 2.8. Exercises 84 2.8.1. Characteristics of a photovoltaic panel 84 2.8.2. Sizing an autonomous photovoltaic installation 86 2.9. References 89 Chapter 3. Wind Power 93Bruno FRANÇOIS and Benoît ROBYNS 3.1. Characteristic of the primary resource 93 3.1.1. Variability 93 3.1.2. The Weibull distribution 94 3.1.3. The effect of relief 97 3.1.4. Loading rate 98 3.1.5. Compass card 99 3.2. Kinetic wind energy 100 3.3. Wind turbines 102 3.3.1. Horizontal axis wind turbines 102 3.3.2. Vertical axis wind turbines 109 3.3.3. Comparison of the various turbine types 113 3.4. Power limitation by varying the power coefficient 114 3.4.1. The “pitch” or variable pitch angle system 114 3.4.2. The “stall” or aerodynamic stall system 116 3.5. Mechanical couplings between the turbine and the electric generator 117 3.5.1. Connection between mechanical speed, synchronous speed and electrical network frequency 117 3.5.2. “Direct drive” wind turbines (without a multiplier) 119 3.5.3. Use of a speed multiplier 119 3.6. Generalities on induction and mechanical electric conversion 120 3.7. “Fixed speed” wind turbines based on induction machines 122 3.7.1. Physical principle 122 3.7.2. Constitution of induction machines 123 3.7.3. Modeling 124 3.7.4. Conversion system 128 3.7.5. Operational characteristics 130 3.8. Variable speed wind turbine 131 3.8.1. Issues 131 3.8.2. Classification of the structures according to machine technologies 132 3.8.3. Principle of element sizing 135 3.8.4. Adjustment of active and reactive powers 136 3.8.5. Aerogenerators based on a doubly-fed induction machine 141 3.8.6. Aerogenerators based on a synchronous machine 147 3.9. Offshore wind turbines 154 3.9.1. Advantages of offshore wind 154 3.9.2. Types of offshore wind turbines 156 3.10. Wind farms 158 3.10.1. Architecture 158 3.10.2. Abundance 160 3.11. Exercises 161 3.11.1. Fixed speed wind turbines 161 3.11.2. Characterization of a turbine and estimate of the generated power 163 3.11.3. High power variable speed wind turbines 168 3.12. References 170 Chapter 4. Terrestrial and Marine Hydroelectricity 173Benoît ROBYNS and Antoine HENNETON 4.1. Run-of-the-river hydraulics 173 4.1.1. Hydroelectricity 173 4.1.2. Small hydraulics 176 4.1.3. Hydraulic turbines 178 4.1.4. Electromechanical conversion for small hydroelectricity 185 4.1.5. Exercise: small hydroelectric run-of-the-river power station 187 4.2. Hydraulic power of the sea 202 4.2.1. Wave power 202 4.2.2. Energy of the continuous ocean currents 207 4.2.3. Tidal energy 209 4.2.4. Wave production, wave-power generator 215 4.2.5. Production by sea currents 238 4.2.6. Tidal production 251 4.2.7. Exercise: estimation of the production of a simple effect tidal power 265 4.3. References 266 Chapter 5. Thermal Power Generation 273Jonathan SPROOTEN 5.1. Introduction 273 5.2. Geothermal power 273 5.2.1. Introduction 273 5.2.2. The resource 274 5.2.3. Fluid characteristics 275 5.2.4. The principle of geothermal power plants 277 5.2.5. Thermodynamic conversion 279 5.2.6. Steam turbine 284 5.2.7. The alternator 286 5.3. Thermodynamic solar power generation 292 5.3.1. Introduction 292 5.3.2. The principle of concentration 292 5.3.3. Cylindro-parabolic design 297 5.3.4. The solar tower 300 5.3.5. Parabolic dish design 301 5.3.6. Comparison of solar thermodynamic generations 303 5.4. Cogeneration by biomass 304 5.4.1. Origin of biomass – energy interests 304 5.4.2. Cogeneration principle 305 5.5. References 307 Chapter 6. Integration of Decentralized Production into the Electrical Network 309Benoît ROBYNS and Jonathan SPROOTEN 6.1. From a centralized network to a decentralized network 309 6.1.1. The transmission network 309 6.1.2. The distribution network 311 6.1.3. Services for the electric system 312 6.1.4. Actors of a liberalized system 317 6.1.5. Roles of decentralized production in network management 318 6.2. Connection constraints and usage checks 318 6.2.1. Voltage management 318 6.2.2. Frequency control 322 6.2.3. Quality of the electric wave 325 6.2.4. Protection and short-circuiting of the electrical system 327 6.2.5. Decoupling protection 327 6.2.6. Other limitations 327 6.3. The challenges of integrating decentralized power generation 328 6.3.1. Defense and infrastructure reconstruction plan for the electricity system 328 6.3.2. Production forecasting for extreme weather conditions 329 6.3.3. Network hosting capacity and protection 330 6.4. Perspectives for better integration into networks 332 6.4.1. Actions at the source level 332 6.4.2. Actions at the network level 334 6.4.3. Actions at the consumer level 341 6.5. References 343 List of Authors 347 Index 349

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Book SynopsisThe book has a dual purpose. The first is to expose a general methodology to solve problems of electromagnetism in geometries constituted of angular regions. The second is to bring the solutions of some canonical problems of fundamental importance in modern electromagnetic engineering with the use of the Wiener-Hopf technique. In particular, the general mathematical methodology is very ingenious and original. It is based on sophisticated and attractive procedures exploiting simple and advanced properties of analytical functions. Once the reader has acquired the methodology, she/he can easily obtain the solution of the canonical problems reported in the book. The book can be appealing also to readers who are not directly interested in the detailed mathematical methodology and/ or in electromagnetics. In fact the same methodology can be extended to acoustics and elasticity problems. Moreover, the proposed practical problems with their solutions constitute a list of reference solutions and can be of interests in engineering production in the field of radio propagations, electromagnetic compatibility and radar technologies.Table of ContentsPreface ix Introduction xiii Chapter 4. Exact Solutions for Electromagnetic Impedance Wedges 1 4.1. Introduction 1 4.2. A list of the impedance wedge problems amenable to exact WH solutions 9 4.3. Cases involving classical WH equations 10 4.3.1. WH formulation of the diffraction by an impedance half-plane 11 4.3.2. Exact solutions of the diffraction by an impedance half-plane 18 4.3.3. Exact solution for the full-plane junction at skew incidence 37 4.3.4. Exact solution of the penetrable half-plane problem (the jump) 39 4.3.5. Exact solution of the right-angled wedge scattering problem 40 4.4. Exact solutions for impedance wedge problems with the GWHE form of section 3.5 – form #1 51 4.4.1. The WH solution of the Malyuzhinets problem 52 4.4.2. Diffraction at skew incidence ( αo ≠ 0 ) by a wedge with a PEC and a PMC face 58 4.4.3. Diffraction at skew incidence ( αo ≠ 0 ) by a wedge with a PEC face and the other face with diagonal Zb with one null element 60 4.5. Exact solutions for the impedance wedge problems with the GWHEs written in an alternative form – form #2 62 4.5.1. Exact factorization with diagonal polynomial matrices P a,b (m) 64 4.5.2. Anisotropic symmetric impedance wedges at normal incidence 67 4.5.3. Non-symmetric wedges at normal incidence with commuting Pa and Pb 68 4.5.4. Non-symmetric wedges at skew incidence 70 4.5.5. Two particular wedge problems amenable to exact solutions 72 4.6. A general form of the GWHEs to study the arbitrary face impedance wedges – form #3 76 Appendix 4.A. Some important formulas of decomposition for wedge problems 79 Chapter 5. Fredholm Factorization Solutions of GWHEs for the Electromagnetic Impedance Wedges Surrounded by an Isotropic Medium 87 5.1. Introduction 87 5.2. Generalized Wiener-Hopf equations for the impenetrable wedge scattering problem of an electromagnetic plane wave at skew incidence 88 5.3. Fredholm factorization solution in the η plane of GWHEs 92 5.4. Fredholm factorization solution in the w plane of GWHEs 95 5.5. Approximate solution of FIEs derived from GWHEs 97 5.6. Analytic continuation of approximate solutions of GWHEs 101 5.7. Far-field computation 103 5.8. Criteria for the examples 110 5.9. Example 1: Symmetric isotropic impedance wedge at normal incidence with Ez polarization 111 5.10. Example 2: Non-symmetric isotropic impedance wedge at normal incidence with Hz polarization and surface wave contribution 119 5.11. Example 3: PEC wedge at skew incidence 121 5.12. Example 4: Arbitrary impedance half-plane at skew incidence 124 5.13. Example 5: Arbitrary impedance wedge at skew incidence 126 5.14. Example 6: Arbitrary impedance concave wedge at skew incidence 128 5.15. Discussion 132 Appendix 5.A. Fredholm properties of the integral equation (5.3.1) 132 Chapter 6. Diffraction by Penetrable Wedges 135 6.1. Introduction 135 6.2. GWHEs for the dielectric wedge at normal incidence (Ez-polarization) 140 6.3. Reduction of the GWHEs for the dielectric wedge at Ez-polarization to Fredholm integral equations 142 6.4. Analytic continuation for the solution of the dielectric wedge at Ez-polarization 154 6.5. Some remarks on the Fredholm integral equations (6.3.24), (6.3.26) and numerical solutions 159 6.6. Field evaluation in any point of the space 162 6.7. The dielectric wedge at skew incidence 165 6.8. Criteria for examples of the scattering by a dielectric wedge at normal incidence (Ez-polarization) 176 6.9. Example: the scattering by a dielectric wedge at normal incidence (Ez-polarization) 177 6.10. Discussion 186 Appendix 6.A. Fredholm factorization applied to (6.3.2)–(6.3.5) 186 Appendix 6.B. Source term ηi (η) 188 References 199 Index 205 Summary of Volume 1 209

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Book SynopsisArchiving has become an increasingly complex process. The challenge is no longer how to store the data but how to store it intelligently, in order to exploit it over time, while maintaining its integrity and authenticity. Digital technologies bring about major transformations, not only in terms of the types of documents that are transferred to and stored in archives, in the behaviors and practices of the humanities and social sciences (digital humanities), but also in terms of the volume of data and the technological capacity for managing and preserving archives (Big Data). Archives in The Digital Age focuses on the impact of these various digital transformations on archives, and examines how the right to memory and the information of future generations is confronted with the right to be forgotten; a digital prerogative that guarantees individuals their private lives and freedoms.Table of ContentsPreface ix Introduction xi Chapter 1. Digital Archives: Elements of Definition 1 1.1. Key concepts of digital archives 1 1.1.1. Archives 1 1.1.2. Archive management 2 1.1.3. Archival management tools 4 1.1.4. Digital archives 7 1.2. Electronic Records Management 7 1.2.1. ERM: elements of definition 7 1.2.2. ERM: implementation steps 10 1.3. Records management 18 1.3.1. Structure of standard 15489 19 1.3.2. Content of the standard 20 1.3.3. Design and implementation of an RM project according to the standard 22 1.3.4. MoReq: the added value of RM 25 1.4. EDRMS: merging ERM and RM 26 1.5. ECM: the overall data management strategy 27 1.6. Conclusion 30 Chapter 2. Digital Archiving: Methods and Strategies 31 2.1. Introduction 31 2.2. Digital archiving: elements of definition 31 2.3. Digital archiving: the essential standards 34 2.3.1. NF Z 42-013/ISO 14641 standard 36 2.3.2. NF 461: electronic archiving system 38 2.3.3. OAIS (ISO 14721): Open Archival Information System 39 2.3.4. ISO 19905 (PDF/A) 42 2.3.5. ISO 30300, ISO 30301 and ISO 30302 series of standards 44 2.3.6. ISO 23081 44 2.4. Methodology for setting up a digital archiving process 46 2.4.1. Qualifying and classifying information 46 2.4.2. Classification scheme 47 2.4.3. Retention schedule or retention standard 51 2.4.4. Metadata 52 2.4.5. Archiving processes and procedures 55 2.5. Archiving of audiovisual documents 58 2.5.1. Definition of audiovisual archives 58 2.5.2. Treatment of audiovisual archives 60 2.5.3. Migration of audiovisual documents 62 2.5.4. Digital archiving of audiovisual documents 63 2.6. Email archiving 65 2.6.1. Email archiving and legislation 66 2.6.2. Why archive emails? 67 2.7. Conclusion 69 Chapter 3. Archives in the Age of Digital Humanities 71 3.1. Introduction 71 3.2. History of the digital humanities 72 3.2.1. “Literary and Linguistic Computing”: 1940–1980 72 3.2.2. “Humanities computing”: 1980–1994 74 3.2.3. “Digital humanities”: since 1994 77 3.3. Definitions of the digital humanities 78 3.4. Archives in the age of the digital humanities 80 3.4.1. Digital archive platforms 81 3.4.2. Software managing digital archives 84 3.4.3. Digital humanities at the heart of long-term preservation 89 3.4.4. Digital humanities and the liberation of the humanities: access and accessibility 107 3.5. Conclusion 112 Chapter 4. Digital Archiving and Big Data 113 4.1. Introduction 113 4.2. Definition of Big Data 115 4.3. Big Data issues 119 4.4. Big Data: challenges and areas of application 120 4.5. Data archiving in the age of Big Data 122 4.5.1. Management and archiving of Big Data 122 4.5.2. Big Data technologies and tools 125 4.5.3. Blockchain, the future of digital archiving of Big Data 137 4.6. Conclusion 147 Chapter 5. Preservation of Archives versus the Right to be Forgotten 149 5.1. Introduction 149 5.2. Forgetting 150 5.3. The right to be forgotten 150 5.3.1. Limits to the right to be forgotten 150 5.3.2. European Directive on the protection of personal data 151 5.3.3. General Data Protection Regulation 153 5.3.4. The right to dereferencing: common criteria 156 5.4. Effectiveness of the right to be forgotten 156 5.4.1. Technical challenge of the effectiveness of the right to be forgotten 157 5.4.2. Legal challenge of the effectiveness of the right to be forgotten 160 5.5. The right to digital oblivion: a controversial subject 163 5.6. Public archives versus the right to be forgotten 165 5.6.1. Archives: exemptions from the right to be forgotten 167 5.6.2. Online publication of archives and finding aids containing personal data 168 5.6.3. Private digital archives and the right to be forgotten 171 5.6.4. Web archiving and the right to be forgotten 172 5.7. Google and the right to be forgotten 173 5.8. Conclusion 178 Conclusion 181 List of Acronyms 185 References 193 Index 207

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Book SynopsisSmart zero-energy buildings and communities have a major role to play in the evolution of the electric grid towards alignment with carbon neutrality policies. The goal to reduce greenhouse gas emissions in the built environment can be pursued through a holistic approach, including the drastic reduction of buildings’ energy consumption.The state-of-the-art in this field relates, on the one hand, to design methodologies and innovative technologies which aim to minimize the energy demand at the building level. On the other hand, the development of information and communication technologies, along with the integration of renewable energy and storage, provide the basis for zero and positive energy buildings and communities that can produce, store, manage and exchange energy at a local level.This book provides a structured and detailed insight of the state-of-the-art in this context based on the analysis of real case studies and applications.Table of ContentsPreface xiNikos KAMPELIS List of Acronyms xvNikos KAMPELIS Chapter 1 The Role of Smart Grids in the Building Sector 1Denia KOLOKOTSA 1.1 Smart and zero-energy buildings 2 1.1.1 Smart metering 3 1.1.2 Demand response (DR) 4 1.1.3 Distributed systems 6 1.2 Smart and zero-energy communities 6 1.3 Conclusion and future prospects 10 Chapter 2 Integrated Design (ID) Towards Smart Zero-energy Buildings and Smart Grids 13Theoni KARLESSI, Pietro MURATORE, Luca VENEZIA, Laura STANDARDI, Klemens LEUTGÖB and Anne Sigrid NORDBY 2.1 Introduction 15 2.2 Methodology 16 2.3 Integrated design in smart and zero-energy buildings 17 2.4 ID process principles and guidelines 19 2.4.1 Benefits 22 2.4.2 Barriers 23 2.5 Scope of services 24 2.6 Remuneration models 26 2.7 Application of evaluation tools 28 2.8 Sustainability certification 29 2.9 Consultancy and quality assurance 30 2.10 Measurement of design quality criteria 31 2.11 Defining a client’s objectives 33 2.11.1 Capital cost reduction 34 2.11.2 Delivery risk reduction 35 2.12 Defining the tenant’s objectives 35 2.12.1 Operational cost reduction 36 2.12.2 Building unsuitability risk reduction 36 2.13 Best practice sites 37 2.13.1 Alexandros N Tombazis and Associates Architects S.A office building 37 2.13.2 APIVITA Commercial and Industrial S.A 42 2.13.3 Stavros Niarchos Foundation Cultural Center 46 2.13.4 Karelas Office Park 50 Chapter 3 Data Analysis and Energy Modeling in Smart and Zero-energy Buildings and Communities 55Nikos KAMPELIS, Konstantinos GOBAKIS, Vagias VAGIAS, Denia KOLOKOTSA, Laura STANDARDI, Daniela ISIDORI, Cristina CRISTALLI, Fabio Maria MONTAGNINO, Filippo PAREDES, Pietro MURATORE, Luca VENEZIA, Marina Kyprianou DRACOU, Alaric MONTENON, Andri PYRGOU, Theoni KARLESSI and Mat SANTAMOURIS 3.1 Energy signature for the NTL of Cyprus Institute 55 3.2 Athalassa Campus and the NTL building 57 3.2.1 Methodology 61 3.2.2 Description of the Novel Technology case study 63 3.2.3 Data exploration 68 3.2.4 Correlation matrix 71 3.2.5 Regression model 72 3.3 Linear Fresnel solar collector at the NTL building, Cyprus Institute 85 3.3.1 Development of the NTL model 90 3.3.2 Energy performance analysis in the NTL 92 3.3.3 Discussion 100 3.4 Conclusion 101 Chapter 4 On the Comparison of Occupancy in Relation to Energy Consumption and Indoor Environmental Quality: A Case Study 103Margarita Niki ASSIMAKOPOULOS, Nikolaos BARMPARESOS, Alexandros PANTAZARAS, Theoni KARLESSI and Siew Eang LEE 4.1 Introduction 103 4.2 Methodology 104 4.3 Description of the case building 105 4.4 Description of the experimental procedure 105 4.5 Results 106 4.5.1 Investigation of energy consumption and indoor air quality 106 4.5.2 Days of special interest – high occupancy 110 4.5.3 Days of special interest – increased energy consumption 112 4.6 Discussion and concluding remarks 112 Chapter 5 Indoor Environmental Quality and Energy Consumption Assessment and ANN Predictions for an Integrated Internet-based Energy Management System Towards a Zero-energy Building 115Denia KOLOKOTSA 5.1 Introduction 115 5.2 Description of the SDE buildings 116 5.2.1 General information 116 5.2.2 Monitoring activities for SDE 3 118 5.3 The power loads and hourly energy consumption 118 5.4 Indoor environmental quality 118 5.4.1 Thermal comfort assessment – time series analysis 127 5.4.2 Indoor air quality 129 5.4.3 The indoor illuminance levels 129 5.5 Cross correlation 135 5.6 Prediction using artificial neural networks (ANN) 136 5.6.1 Prediction of outdoor temperature 137 5.6.2 Prediction of relative humidity 138 5.6.3 Prediction of power loads 139 5.7 Specifications for an integrated internet-based energy management system toward a zero-energy building 141 5.7.1 The phases of the internet-based energy management system for SDE 142 5.7.2 Integration of software and prediction algorithms 149 5.8 Conclusion 149 Chapter 6 Objective and Subjective Evaluation of Thermal Comfort in the Loccioni Leaf Lab, Italy 151 Marina LASKARI, Francesco CARDUCCI, Daniela ISIDORI, Martina SENZACQUA, Laura STANDARDI and Cristina CRISTALLI6.1 Introduction 151 6.2 Background information 152 6.3 Methodology 153 6.3.1 Subjective measurements 154 6.3.2 Objective measurements 154 6.3.3 Combined analysis of objective and subjective measurements 155 6.3.4 User preferences and satisfaction with internal conditions 157 6.4 Collection of building background data 157 6.5 Collection of monitored data 160 6.6 Right-Now questionnaire survey 162 6.7 Results 166 6.7.1 Analysis of MyLeaf measurements 167 6.7.2 Analysis of Comfort Meter measurements 173 6.7.3 Analysis of Right-Now survey responses 176 6.7.4 Respondent characteristics and thermal comfort 184 6.7.5 Combined analysis of objective and subjective measurements 187 6.7.6 Correlation analysis for MyLeaf and Right-Now survey measurements 190 6.7.7 Correlation analysis for objective and subjective measurements (Research for Innovation office space) 191 6.7.8 Comparison between objective and subjective thermal sensation measurements 195 6.7.9 Determination of acceptable and unacceptable conditions 196 6.8 Conclusion 197 Chapter 7 Smart Meters and User Engagement in the Leaf House 199Niki GAITANI 7.1 Introduction 199 7.2 Methodology 200 7.3 Analysis of user engagement 201 7.3.1 Development of the questionnaire 201 7.3.2 Leaf House case study 203 7.4 Results 210 7.4.1 Demographics, socioeconomics 210 7.4.2 Physiological, social and behavioral aspects 212 7.4.3 Information level 214 7.4.4 Health and comfort 215 7.4.5 Living situation 217 7.5 Conclusion 218 Chapter 8 Integration of Energy Storage in Smart Communities and Smart Grids 221Denia KOLOKOTSA, Nikos KAMPELIS, Angeliki MAVRIGIANNAKI, Marco GENTILOZZI, Filippo PAREDES, Fabio Maria MONTAGNINO and Luca VENEZIA 8.1 Energy storage systems in smart grids 223 8.1.1 Electrical and electrochemical energy storage in smart grids 223 8.1.2 Mechanical energy storage in smart grids 228 8.1.3 Thermal energy storage in smart grids 231 8.2 Energy storage and smart grids: case studies 234 8.2.1 Case study 1: the Leaf Community smart grid energy storage system 234 8.2.2 Case study 2: energy storage of CSP and integration with smart grids 244 8.3 Conclusion and future prospects 261 Conclusion and Recommendations 263Nikos KAMPELIS References 267 List of Authors 283 Index 287

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Book SynopsisOur transition towards a cleaner and more sustainable future has seen an increase in the use of electrical energy in the functioning of our society. This implies the need to develop tools and methods which allow us to study electromagnetic devices and ensure their functioning for as long as possible. This requires us to use these tools to understand their behavior, not just as one component, but also in the entire systems in which they can be found, throughout their life cycle. This book provides electrical engineering students and researchers with the resources to analyze how synchronous machines behave over their entire field of operation, particularly focusing on hybrid excited synchronous machines (HESMs). The field of HESMs, although not a fundamental problem in the strict sense of the term, provides answers to a range of fundamental problems: the flux weakening of permanent magnet machines, energy optimization, and lastly the increasing costs of rare-earths permanent magnets.Table of ContentsForeword vii Introduction ix Chapter 1 Hybrid Excited Synchronous Machines: Principles and Structures 1 1.1 Introduction 1 1.2 Interest in hybrid excitation 3 1.2.1 Motoring mode operation 4 1.2.2 Generation mode operation 10 1.3 Hybrid excited structures 12 1.3.1 Classification criteria 13 1.3.2 Structures and classification 19 1.4 Conclusions and perspectives 28 Chapter 2 Control of Hybrid Excited Synchronous Machines 31 2.1 Introduction 31 2.2 Modeling of hybrid excited synchronous machines 32 2.2.1 The nature of the equations 35 2.2.2 Control modes 39 2.3 Torque characteristics and basic control laws 41 2.3.1 Torque characteristics as a function of I and ψ 42 2.3.2 Torque characteristics as a function of V and δ 44 2.3.3 Notion of stability for an open loop and the consequences of closed-loop operations 45 2.3.4 Fundamental control laws 51 2.3.5 Temporary overloaded motor operation 56 2.4 Setting the speed of HESMs (maximal characteristics/envelopes) 58 2.4.1 Low-speed operations 59 2.4.2 Operation at high speeds/the notion of flux weakening 72 2.5 Operations on the entire “torque/speed” plane 111 2.5.1 Efficiency optimization algorithms on the entire “torque/speed” plane 113 2.5.2 Normalized model with losses and the calculation of V n max 118 2.5.3 Machines with non-salient poles (ρ = 1) 121 2.5.4 Machines with salient poles (ρ ≠ 1) 125 2.5.5 Validity of the tools developed and the contribution towards hybrid excitation 131 2.6 Conclusions and perspectives 148 Chapter 3 Experimental Studies of Hybrid Excited Synchronous Machines 153 3.1 Introduction 153 3.2 Machine 1 154 3.2.1 Structure and operating principles 155 3.2.2 Construction 159 3.2.3 Experimental study 162 3.3 Machine 2 170 3.3.1 Structure and operating principle 172 3.3.2 Construction 179 3.3.3 Experimental study 186 3.4 Conclusions and perspectives 194 Conclusion 197 References 199 Index 211

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Book SynopsisThis book offers a new perspective to uncover the keys to accident and disaster avoidance. Created with a working group, it presents research and understanding on the root causes of disasters. Indeed, beyond technical failures, human beings are at the heart of organizations and, through the exchange of data and information, influential relationships inevitably emerge such as conflicts of interest and cooperation.With examples selected from multiple accidents and disasters, this book demonstrates that analyzing the causal chain that leads to an accident is not sufficient if we wish to truly understand it. The role of operational and managerial actors and the complexities they generate are also explored.Cindynics, The Science of Danger helps readers develop their ability to identify gaps, deficits, dissonances, disjunctions, degenerations and blockages, which are the real dangers in inevitably evolving activity situations. With an easily-understandable approach, this book offers new perspectives in several fields (health, crisis management and conflict resolution).Table of ContentsAcknowledgments ix Presentation of the Institut pour la Maîtrise des Risques (French Institute for Risk Management) xi Foreword xiiiAndré LANNOY Preface xvii Chapter 1. Understanding Cindynics 1 1.1. The approach 3 1.2. The method 4 1.3. The tools 6 1.4. Processes 7 Chapter 2. The Usefulness of the Cindynics Approach and Method 9 2.1. The situation, the founding concept of cindynics 9 2.2. Characterizing an activity situation 10 2.3. Qualifying a dangerous situation within an activity situation 12 2.3.1. Notion of a dangerous situation 13 2.3.2. Qualifying the dangerousness of a situation 15 Chapter 3. The Usefulness of Cindynics Tools 17 3.1. Qualification grid for risk sources that are not easily identifiable 17 3.2. Describing this type of risk source 18 3.2.1. At the global organization level 19 3.2.2. At the level of stakeholder groups 23 3.2.3. At the level of the individual actor 23 Chapter 4. Reducing Risk Sources 25 Chapter 5. A Comparative View Between Dependability and Cindynics 29 5.1. Introduction 29 5.1.1. Dependability 29 5.1.2. The cindynics approach 29 5.1.3. Dependability and cindynics seem to ignore or even compete with each other 30 5.2. What is a complex system? 30 5.3. Dependability approach – its strengths and limitations 30 5.3.1. The scope of dependability 30 5.3.2. Description of the system and its components 31 5.3.3. Functional analysis 31 5.3.4. Process hazard analysis 31 5.3.5. Technological choices 31 5.3.6. Identification of failures – analyzing risks 32 5.3.7. Strengths and limitations of the approach 32 5.4. The cindynics approach 32 5.4.1. The cindynic situation and its scope 32 5.4.2. Strengths and limitations of the approach 33 5.5. Conflict or complementarity of the two approaches 34 5.6. Conclusion 35 Chapter 6. Perspectives 37 Conclusion 41 Examples of Approaches 45 Appendix 1. Current Risk Management and its Shortcomings 99 Appendix 2. Notions of Interaction and Complexity 105 Appendix 3. The Grounded Theorization Method 109 Appendix 4. Notions of Quantum Theory 111 Appendix 5. Summary of CSDs 115 Appendix 6. Archeocindynic Study 117 Appendix 7. Bhopal Study 137 Appendix 8. More Information About Bhopal 143 Appendix 9. Collection of Information on the Queen Mary II Gangway Accident 149 Appendix 10. Queen Mary Accident Cause Tree 157 Appendix 11. Collection of Information on the Deepwater Horizon Oil Rig Accident 159 Appendix 12. Synthesis Note of the Work of IMdR–AFPCN: “Vulnerability of Networks and Natural Disasters” 165 Appendix 13. The New Cindynics Concepts Training Course 167 Postface 169 Glossary 173 References 179 Index 185

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Book SynopsisThis book presents interdisciplinary approaches to help buildings, electrical energy networks and their users contribute to the energy and societal transition. Smart Grids and Buildings for Energy and Societal Transition examines the technologies, uses and imaginaries involved in implementing smart buildings and smart grids. Production and consumption forecasts, modeling of stakeholder involvement and self-consumption within a renewable energy community exploiting blockchain technology are examples developed with a view to fostering the emergence of smart grids. The potential of smart buildings, taking into account user comfort while increasing energy efficiency, is identified. Full-scale demonstrators are used to test the proposed solutions, and to ensure that users take full advantage of the potential for electrical flexibility.

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Book SynopsisAs a society today, we are so dependent on systems-of-systems that any malfunction has devastating consequences, both human and financial. Their technical design, functional complexity and numerous interfaces justify a significant investment in testing in order to limit anomalies and malfunctions. Based on more than 40 years of practice, this book goes beyond the simple testing of an application – already extensively covered by other authors – to focus on methodologies, techniques, continuous improvement processes, load estimates, metrics and reporting, which are illustrated by a case study. It also discusses several challenges for the near future. Pragmatic and clear, this book displays many examples and references that will help you improve the quality of your systemsof-systems efficiently and effectively and lead you to identify the impact of upstream decisions and their consequences. Advanced Testing of Systems-of-Systems 2 deals with the practical implementation and use of the techniques and methodologies proposed in the first volume.Table of ContentsDedication and Acknowledgments xiii Preface xv Chapter 1 Test Project Management 1 1.1 General principles 1 1.1.1 Quality of requirements 2 1.1.2 Completeness of deliveries 3 1.1.3 Availability of test environments 3 1.1.4 Availability of test data 4 1.1.5 Compliance of deliveries and schedules 5 1.1.6 Coordinating and setting up environments 6 1.1.7 Validation of prerequisites – Test Readiness Review (TRR) 6 1.1.8 Delivery of datasets (TDS) 7 1.1.9 Go-NoGo decision – Test Review Board (TRB) 7 1.1.10 Continuous delivery and deployment 8 1.2 Tracking test projects 9 1.3 Risks and systems-of-systems 10 1.4 Particularities related to SoS 11 1.5 Particularities related to SoS methodologies 11 1.5.1 Components definition 12 1.5.2 Testing and quality assurance activities 12 1.6 Particularities related to teams 12 Chapter 2 Testing Process 15 2.1 Organization 17 2.2 Planning 18 2.2.1 Project WBS and planning 19 2.3 Control of test activities 21 2.4 Analyze 22 2.5 Design 23 2.6 Implementation 24 2.7 Test execution 25 2.8 Evaluation 26 2.9 Reporting 28 2.10 Closure 29 2.11 Infrastructure management 29 2.12 Reviews 30 2.13 Adapting processes 31 2.14 RACI matrix 32 2.15 Automation of processes or tests 33 2.15.1 Automate or industrialize? 33 2.15.2 What to automate? 33 2.15.3 Selecting what to automate 34 Chapter 3 Continuous Process Improvement 37 3.1 Modeling improvements 37 3.1.1 PDCA and IDEAL 38 3.1.2 CTP 39 3.1.3 SMART 41 3.2 Why and how to improve? 41 3.3 Improvement methods 42 3.3.1 External/internal referential 42 3.4 Process quality 46 3.4.1 Fault seeding 46 3.4.2 Statistics 46 3.4.3 A posteriori 47 3.4.4 Avoiding introduction of defects 47 3.5 Effectiveness of improvement activities 48 3.6 Recommendations 50 Chapter 4 Test, QA or IV&V Teams 51 4.1 Need for a test team 52 4.2 Characteristics of a good test team 53 4.3 Ideal test team profile 54 4.4 Team evaluation 55 4.4.1 Skills assessment table 56 4.4.2 Composition 58 4.4.3 Select, hire and retain 59 4.5 Test manager 59 4.5.1 Lead or direct? 60 4.5.2 Evaluate and measure 61 4.5.3 Recurring questions for test managers 62 4.6 Test analyst 63 4.7 Technical test analyst 64 4.8 Test automator 65 4.9 Test technician 66 4.10 Choose our testers 66 4.11 Training, certification or experience? 67 4.12 Hire or subcontract? 67 4.12.1 Effective subcontracting 68 4.13 Organization of multi-level test teams 68 4.13.1 Compliance, strategy and organization 69 4.13.2 Unit test teams (UT/CT) 70 4.13.3 Integration testing team (IT) 70 4.13.4 System test team (SYST) 70 4.13.5 Acceptance testing team (UAT) 71 4.13.6 Technical test teams (TT) 71 4.14 Insourcing and outsourcing challenges 72 4.14.1 Internalization and collocation 72 4.14.2 Near outsourcing 73 4.14.3 Geographically distant outsourcing 74 Chapter 5 Test Workload Estimation 75 5.1 Difficulty to estimate workload 75 5.2 Evaluation techniques 76 5.2.1 Experience-based estimation 76 5.2.2 Based on function points or TPA 77 5.2.3 Requirements scope creep 79 5.2.4 Estimations based on historical data 80 5.2.5 WBS or TBS 80 5.2.6 Agility, estimation and velocity 81 5.2.7 Retroplanning 82 5.2.8 Ratio between developers – testers 82 5.2.9 Elements influencing the estimate 83 5.3 Test workload overview 85 5.3.1 Workload assessment verification and validation 86 5.3.2 Some values 86 5.4 Understanding the test workload 87 5.4.1 Component coverage 87 5.4.2 Feature coverage 88 5.4.3 Technical coverage 88 5.4.4 Test campaign preparation 89 5.4.5 Running test campaigns 89 5.4.6 Defects management 90 5.5 Defending our test workload estimate 91 5.6 Multi-tasking and crunch 92 5.7 Adapting and tracking the test workload 92 Chapter 6 Metrics, KPI and Measurements 95 6.1 Selecting metrics 96 6.2 Metrics precision 97 6.2.1 Special case of the cost of defaults 97 6.2.2 Special case of defects 98 6.2.3 Accuracy or order of magnitude? 98 6.2.4 Measurement frequency 99 6.2.5 Using metrics 99 6.2.6 Continuous improvement of metrics 100 6.3 Product metrics 101 6.3.1 FTR: first time right 101 6.3.2 Coverage rate 102 6.3.3 Code churn 103 6.4 Process metrics 104 6.4.1 Effectiveness metrics 104 6.4.2 Efficiency metrics 107 6.5 Definition of metrics 108 6.5.1 Quality model metrics 109 6.6 Validation of metrics and measures 110 6.6.1 Baseline 110 6.6.2 Historical data 111 6.6.3 Periodic improvements 112 6.7 Measurement reporting 112 6.7.1 Internal test reporting 113 6.7.2 Reporting to the development team 114 6.7.3 Reporting to the management 114 6.7.4 Reporting to the clients or product owners 115 6.7.5 Reporting to the direction and upper management 116 Chapter 7 Requirements Management 119 7.1 Requirements documents 119 7.2 Qualities of requirements 120 7.3 Good practices in requirements management 122 7.3.1 Elicitation 122 7.3.2 Analysis 123 7.3.3 Specifications 123 7.3.4 Approval and validation 124 7.3.5 Requirements management 124 7.3.6 Requirements and business knowledge management 125 7.3.7 Requirements and project management 125 7.4 Levels of requirements 126 7.5 Completeness of requirements 126 7.5.1 Management of TBDs and TBCs 126 7.5.2 Avoiding incompleteness 127 7.6 Requirements and agility 127 7.7 Requirements issues 128 Chapter 8 Defects Management 129 8.1 Defect management, MOA and MOE 129 8.1.1 What is a defect? 129 8.1.2 Defects and MOA 130 8.1.3 Defects and MOE 130 8.2 Defect management workflow 131 8.2.1 Example 131 8.2.2 Simplify 132 8.3 Triage meetings 133 8.3.1 Priority and severity of defects 133 8.3.2 Defect detection 134 8.3.3 Correction and urgency 135 8.3.4 Compliance with processes 136 8.4 Specificities of TDDs, ATDDs and BDDs 136 8.4.1 TDD: test-driven development 136 8.4.2 ATDD and BDD 137 8.5 Defects reporting 138 8.5.1 Defects backlog management 139 8.6 Other useful reporting 141 8.7 Don’t forget minor defects 141 Chapter 9 Configuration Management 143 9.1 Why manage configuration? 143 9.2 Impact of configuration management 144 9.3 Components 145 9.4 Processes 145 9.5 Organization and standards 146 9.6 Baseline or stages, branches and merges 147 9.6.1 Stages 148 9.6.2 Branches 148 9.6.3 Merge 148 9.7 Change control board (CCB) 149 9.8 Delivery frequencies 149 9.9 Modularity 150 9.10 Version management 150 9.11 Delivery management 151 9.11.1 Preparing for delivery 153 9.11.2 Delivery validation 154 9.12 Configuration management and deployments 155 Chapter 10 Test Tools and Test Automation 157 10.1 Objectives of test automation 157 10.1.1 Find more defects 158 10.1.2 Automating dynamic tests 159 10.1.3 Find all regressions 160 10.1.4 Run test campaigns faster 161 10.2 Test tool challenges 161 10.2.1 Positioning test automation 162 10.2.2 Test process analysis 162 10.2.3 Test tool integration 162 10.2.4 Qualification of tools 163 10.2.5 Synchronizing test cases 164 10.2.6 Managing test data 164 10.2.7 Managing reporting (level of trust in test tools) 165 10.3 What to automate? 165 10.4 Test tooling 166 10.4.1 Selecting tools 167 10.4.2 Computing the return on investment (ROI) 169 10.4.3 Avoiding abandonment of tools and automation 169 10.5 Automated testing strategies 170 10.6 Test automation challenge for SoS 171 10.6.1 Mastering test automation 171 10.6.2 Preparing test automation 173 10.6.3 Defect injection/fault seeding 173 10.7 Typology of test tools and their specific challenges 174 10.7.1 Static test tools versus dynamic test tools 175 10.7.2 Data-driven testing (DDT) 176 10.7.3 Keyword-driven testing (KDT) 176 10.7.4 Model-based testing (MBT) 177 10.8 Automated regression testing 178 10.8.1 Regression tests in builds 178 10.8.2 Regression tests when environments change 179 10.8.3 Prevalidation regression tests, sanity checks and smoke tests 179 10.8.4 What to automate? 180 10.8.5 Test frameworks 182 10.8.6 E2E test cases 183 10.8.7 Automated test case maintenance or not? 184 10.9 Reporting 185 10.9.1 Automated reporting for the test manager 186 Chapter 11 Standards and Regulations 187 11.1 Definition of standards 189 11.2 Usefulness and interest 189 11.3 Implementation 190 11.4 Demonstration of compliance – IADT 190 11.5 Pseudo-standards and good practices 191 11.6 Adapting standards to needs 191 11.7 Standards and procedures 192 11.8 Internal and external coherence of standards 192 Chapter 12 Case Study 195 12.1 Case study: improvement of an existing complex system 195 12.1.1 Context and organization 196 12.1.2 Risks, characteristics and business domains 198 12.1.3 Approach and environment 200 12.1.4 Resources, tools and personnel 210 12.1.5 Deliverables, reporting and documentation 212 12.1.6 Planning and progress 213 12.1.7 Logistics and campaigns 216 12.1.8 Test techniques 217 12.1.9 Conclusions and return on experience 218 Chapter 13 Future Testing Challenges 223 13.1 Technical debt 223 13.1.1 Origin of the technical debt 224 13.1.2 Technical debt elements 225 13.1.3 Measuring technical debt 226 13.1.4 Reducing technical debt 227 13.2 Systems-of-systems specific challenges 228 13.3 Correct project management 229 13.4 DevOps 230 13.4.1 DevOps ideals 231 13.4.2 DevOps-specific challenges 231 13.5 IoT (Internet of Things) 232 13.6 Big Data 233 13.7 Services and microservices 234 13.8 Containers, Docker, Kubernetes, etc 235 13.9 Artificial intelligence and machine learning (AI/ML) 235 13.10 Multi-platforms, mobility and availability 237 13.11 Complexity 238 13.12 Unknown dependencies 238 13.13 Automation of tests 239 13.13.1 Unrealistic expectations 240 13.13.2 Difficult to reach ROI 241 13.13.3 Implementation difficulties 242 13.13.4 Think about maintenance 243 13.13.5 Can you trust your tools and your results? 244 13.14 Security 245 13.15 Blindness or cognitive dissonance 245 13.16 Four truths 246 13.16.1 Importance of Individuals 247 13.16.2 Quality versus quantity 247 13.16.3 Training, experience and expertise 248 13.16.4 Usefulness of certifications 248 13.17 Need to anticipate 249 13.18 Always reinvent yourself 250 13.19 Last but not least 250 Terminology 253 References 261 Index 267 Summary of Volume 1 269

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Book SynopsisSystems and Uses of Digital Sciences for Knowledge Organization is a large-scale scientific work that brings together researchers and R&D professionals to discuss ideas and actions in the organization of knowledge. The main objective of this book is to define collaborative strategies, use advanced technologies in multiple research fields and outline applications of knowledge organization and its cultural, education, economic and industrial potential.The organization of knowledge and advanced technologies (OCTA) asks the following questions: How can we strengthen alliances between multi-disciplinary and trans-disciplinary studies? How can we broaden our skills surrounding common objects of study? How can we innovate the solutions found and propose sustainable development to society confidently? This book is a result of intensive and collaborative work between highly respected scientific authors. The nine chapters that have been selected for this book have been peer-reviewed by the OCTA program committee, both as written submissions and when presented during the OCTA multi-conference on organization.Table of ContentsIntroduction xiSahbi SIDHOM and Amira KADDOUR Chapter 1 Multi-Agent System and Ontology to Manage Ideas and Represent Knowledge: Creativity Challenge 1Pedro Chávez BARRIOS, Davy MONTICOLO and Sahbi SIDHOM 1.1 Introduction 1 1.2 Multi-agent system (MAS) and ontology 3 1.2.1 MAS and ontology 3 1.2.2 MAS methodologies 5 1.2.3 Methodologies to design ontologies 6 1.3 MAS and ontology: our approach proposal 7 1.3.1 MAS methodology GAIA 7 1.3.2 Applying the ontology, Uschold’s ontology 8 1.4 Results 9 1.4.1 Multi-agent system results 9 1.4.2 Ontology results 13 1.5 Conclusion 16 1.6 Appendices 16 1.7 References 22 Chapter 2 Comparative Study of Educational Process Construction Supported by an Intelligent Tutoring System 27Walid BAYOUNES, Inès BAYOUDH S ADI and Hénda BEN GHÉZALA 2.1 Introduction 27 2.2 New view of educational process 28 2.2.1 Psycho-pedagogical level 30 2.2.2 Didactic level 30 2.2.3 Situational level 30 2.2.4 Online level 30 2.3 Definition framework 30 2.3.1 Didactic domain world 31 2.3.2 Instructional design world 32 2.3.3 Learning environment world 33 2.3.4 Learning situation world 34 2.4 Comparative study 34 2.4.1 Study scope 34 2.4.2 Description of systems 35 2.4.3 Specification of approaches 36 2.4.4 Study results and discussion 50 2.5 Conclusion and future works 51 2.6 References 52 Chapter 3 Multi-Criteria Decision-Making Recommender System Based on Users’ Reviews 55Mariem BRIKI, Sabrine BEN ABDRABBAH and Nahla BEN AMOR 3.1 Introduction 55 3.2 Multi-criteria decision-making 56 3.3 Basics of recommendation systems and related work 58 3.3.1 Recommender systems 58 3.3.2 Text mining-based recommendation systems 59 3.3.3 Multi-criteria recommender systems 60 3.4 New multi-criteria text-based recommendation system 62 3.4.1 Primary criterion-based recommendation system 62 3.4.2 Multi-criteria text mining-based recommendation system 66 3.5 Experimental study 67 3.5.1 Dataset and metrics 67 3.5.2 Evaluation metrics 68 3.5.3 Experimental protocol 69 3.5.4 Experimental results 70 3.6 Conclusion 71 3.7 References 72 Chapter 4 Spammer Detection Relying on Reviewer Behavior Features Under Uncertainty 75Malika BEN KHALIFA, Zied ELOUEDI and Eric LEFÈVRE 4.1 Introduction 75 4.2 Background 78 4.2.1 The belief function theory 78 4.2.2 Evidential K-nearest neighbors 80 4.3 Spammer detection relying on the reviewers’ behavioral features 81 4.3.1 Step 1: Features extraction 82 4.3.2 Step 2: Initialization and learning phase 87 4.3.3 Step 3: Distinguishing between innocent and spammer reviewers 88 4.4 Experimental study 89 4.4.1 Evaluation protocol 90 4.4.2 Results and discussion 91 4.5 Conclusion and future work 92 4.6 References 92 Chapter 5 Social Networking Application, Connections Between Visual Communication Systems and Personal Information on the Web 97Marilou KORDAHI 5.1 Introduction 97 5.2 Related published works 100 5.3 Pattern for the SignaComm, first approach 101 5.3.1 SignaComm’s context 102 5.3.2 SignaComm’s pattern 103 5.4 From text phrases to signagrams for the protection of personal data 107 5.4.1 Automatic translation 107 5.4.2 Dictionary of signagrams 109 5.5 SignaComm’s first technical test 110 5.5.1 Interface pattern 110 5.5.2 User profile pattern 111 5.5.3 Machine translation pattern 111 5.5.4 Activity pattern 113 5.6 Discussion and conclusion 113 5.7 Acknowledgment 114 5.8 References 114 Chapter 6 A New Approach of Texts and Writing Normalization for Arabic Knowledge Organization 119Hammou FADILI 6.1 Introduction 119 6.2 Motivation 120 6.3 Using a machine learning model 120 6.4 Technological elements integration 124 6.5 Corpus and dataset 126 6.6 Experiences and evaluations 127 6.6.1 Results 129 6.7 Conclusion 130 6.8 References 131 Chapter 7 Ebola Epidemic in the Congo 2018–2019: How Does Twitter Permit the Monitoring of Rumors? 137Marc TANTI 7.1 Introduction 137 7.2 Materials and methods 139 7.3 Results 143 7.3.1 Regarding the general public, the citizens 143 7.3.2 Regarding the experts 145 7.3.3 Regarding the media 146 7.3.4 Regarding the politicians 148 7.4 Conclusion 149 7.5 Acknowledgment 150 7.6 References 150 Chapter 8 From Human and Social Indexing to Automatic Indexing in the Era of Big Data and Open Data 153Nabil KHEMIRI and Sahbi SIDHOM 8.1 Introduction 153 8.2 Indexing definition 154 8.3 Manual indexing 155 8.4 Automatic indexing 156 8.4.1 Statistical indexing methods 156 8.4.2 Linguistic indexing methods 157 8.4.3 Semantic indexing 158 8.4.4 Social indexing 159 8.5 Indexing methods for Big Data and Open Data 159 8.6 Conclusion 161 8.7 References 161 Chapter 9 Strategies for the Sustainable Use of Digital Technology by the AWI in the Management of Knowledge and Cultural Communication on the “Arab World” 165Asma ABBASSI 9.1 Introduction 165 9.2 The Arab World Institute and the construction of knowledge around the “Arab World” in the West 166 9.3 The AWI’s digital communication strategies 168 9.4 The images built by the AWI and the question of feedback 176 9.5 The role of digital tools in sustainability and durability in the management of knowledge and communication at the AWI 178 9.6 Conclusion 180 9.7 References 181 List of Authors 185 Index 187

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Book SynopsisNumerical modeling now plays a central role in the design and study of electromagnetic systems. In the field of devices operating in low frequency, it is the finite element method that has come to the fore in recent decades. Today, it is widely used by engineers and researchers in industry, as well as in research centers. This book describes in detail all the steps required to discretize Maxwell's equations using the finite element method. This involves progressing from the basic equations in the continuous domain to equations in the discrete domain that are solved by a computer. This approach is carried out with a constant focus on maintaining a link between physics, i.e. the properties of electromagnetic fields, and numerical analysis. Numerous academic examples, which are used throughout the various stages of model construction, help to clarify the developments.

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Book SynopsisModel-based Systems Architecting is a key tool for designing complex industrial systems. It is dedicated to the working systems architects, engineers and modelers, in order to help them master the complex integrated systems that they are dealing with in their day-to-day professional lives. It presents the CESAMES Systems Architecting Method (CESAM), a systems architecting and modeling framework which has been developed since 2003 in close interaction with many leading industrial companies, providing rigorous and unambiguous semantics for all classical systems architecture concepts. This approach is practically robust and easy-to-use: during the last decade, it was deployed in more than 2,000 real system development projects within the industry, and distributed to around 10,000 engineers around the globe.Table of ContentsPreface ix Acknowledgments xv Introduction xvii Chapter 1 Introduction to CESAM 1 1.1 CESAM: a mathematically sound system modeling framework 1 1.2 CESAM: a framework focused on complex integrated systems 8 1.3 CESAM: a collaboration-oriented architecting framework 12 1.4 CESAM: a business-oriented framework 16 Chapter 2 Why Architecting Systems? 19 2.1 Product and project systems 19 2.2 The complexity threshold 22 2.3 Addressing systems architecting becomes key 25 2.4 The value of systems architecting 31 2.5 The key role of systems architects 34 2.6 How to analyze a systems architect profile? 36 Chapter 3 CESAM Framework 39 3.1 Elements of systemics 39 3.1.1 Interface 39 3.1.2 Environment of a system 41 3.2 The three architectural visions 42 3.2.1 Architectural visions definition 42 3.2.2 Architectural visions overview 46 3.2.3 Relationships between the three architectural visions 52 3.2.4 Organization of a system model 55 3.3 CESAM systems architecture pyramid 57 3.3.1 The three key questions to ask 57 3.3.2 The last question that shall not be forgotten 59 3.4 More systems architecture dimensions 60 3.4.1 Descriptions versus expected properties 60 3.4.2 Descriptions 62 3.4.3 Expected properties 73 3.5 CESAM systems architecture matrix 78 Chapter 4 Identifying Stakeholders: Environment Architecture 83 4.1 Why identify stakeholders? 83 4.2 The key deliverables of environment architecture 85 4.2.1 Stakeholder hierarchy diagram 85 4.2.2 Environment diagram 87 Chapter 5 Understanding Interactions with Stakeholders: Operational Architecture 91 5.1 Why understand interactions with stakeholders? 91 5.2 The key deliverables of operational architecture 94 5.2.1 Need architecture diagram 94 5.2.2 Lifecycle diagram 95 5.2.3 Use case diagrams 97 5.2.4 Operational scenario diagrams 99 5.2.5 Operational flow diagram 101 Chapter 6 Defining What the System Shall Do: Functional Architecture 103 6.1 Why understand what the system does? 103 6.2 The key deliverables of functional architecture 105 6.2.1 Functional requirement architecture diagram 106 6.2.2 Functional mode diagram 108 6.2.3 Functional breakdown and interaction diagrams 109 6.2.4 Functional scenario diagrams 111 6.2.5 Functional flow diagram 112 Chapter 7 Deciding How the System Shall be Formed: Constructional Architecture 115 7.1 Understanding how the system is formed? 115 7.2 The key deliverables of constructional architecture 117 7.2.1 Constructional requirement architecture diagram 118 7.2.2 Configuration diagram 120 7.2.3 Constructional breakdown and interaction diagram 121 7.2.4 Constructional scenario diagram 123 7.2.5 Constructional flow diagram 124 Chapter 8 Taking into Account Failures: Dysfunctional Analysis 127 8.1 Systems do not always behave as they should 127 8.2 The key deliverables of dysfunctional analysis 134 8.2.1 Dysfunctional analysis from an operational perspective 135 8.2.2 Dysfunctional analysis from a functional perspective 136 8.2.3 Dysfunctional analysis from a constructional perspective 138 Chapter 9 Choosing the Best Architecture: Trade-off Techniques 141 9.1 Systems architecting does not usually lead to a unique solution 141 9.2 Trade-off techniques 143 9.2.1 General structure of a trade-off process 143 9.2.2 Managing trade-offs in practice 145 Conclusion 149 Appendices 157 Appendix 1 System Temporal Logic 159 Appendix 2 Classical Engineering Issues 163 Appendix 3 Example of System Model Managed with CESAM 177 Appendix 4 Implementing CESAM through a SysML Modeling Tool 199 Appendix 5 Some Good Practices in Systems Modeling 209 References 211 Index 219

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Book SynopsisSmart power integration is at the crossroads of different fields of electronics such as high and low power, engine control and electrothermal studies of devices and circuits. These circuits are complex and are heavily influenced by substrate coupling, especially where 3D integration is concerned. This book provides an overview of smart power integration, including high voltage devices, dedicated and compatible processes, as well as isolation techniques.Two types of integration are highlighted: modular or hybrid integration, together with compatible devices such as the insulated gate bipolar transistor (IGBT); and monolithic integration, specifically through the paradigm of functional integration. Smart Power Integration outlines the main MOS devices for high voltage integrated circuits, and explores into the fields of codesign, coupling hardware and software design, including applications to motor control. Studies focusing on heat pipes for electronics cooling are also outlined.Table of ContentsPreface ix Chapter 1. Overview of Smart Power Integration 1 1.1. Introduction 1 1.2. Smart PIC applications 2 1.2.1. Flat panel displays 4 1.2.2. Computer power supplies and disk drivers 4 1.2.3. Variable speed motor drives 4 1.2.4. Factory automation 4 1.2.5. Telecommunications 5 1.2.6. Appliance controls 5 1.2.7. Consumer electronics 5 1.2.8. Lighting controls 5 1.2.9. Smart homes 6 1.2.10. Aircraft electronics (Avionics) 6 1.2.11. Automotive electronics 6 1.3. Historical view of the MOS power devices 6 1.4. Smart PIC fabrication processes 9 1.4.1. Dedicated processes 9 1.4.2. Compatible processes 10 1.5. Insulation techniques 10 1.5.1. Self-insulation 10 1.5.2. Dielectric insulation 11 1.5.3. Junction insulation 11 1.5.4. Advanced junction insulation techniques 12 1.6. Motivation of the book 13 Chapter 2. Modular or Hybrid Integration 17 2.1. Introduction 17 2.2. IGBT technology evolution 18 2.2.1. IGBT presentation 18 2.2.2. Epitaxial structure with buffer layer and reduction of carrier lifetime 30 2.2.3. Homogeneous structure with control of load injection 36 2.2.4. Silicon direct bonding-IGBT 38 2.2.5. IGBT trench 39 2.2.6. Lateral IGBT 39 2.3. Assembly technology 40 2.4. Thermal aspect 41 2.4.1. Thermal impedance 43 2.5. Applications fields 45 2.5.1. IGBT power modules for electric traction applications 45 2.5.2. IPM for low- and medium-power applications 48 Chapter 3. Monolithic Integration 51 3.1. Functional integration and smart power 51 3.2. Transition from low-voltage technology (CMOS) to high voltage 52 3.2.1. Introduction 52 3.2.2. A typical CMOS technology 62 3.2.3. Breakdown voltage of a microelectronics structure 63 3.2.4. Improved junctions breakdown by guard techniques 68 3.2.5. Improvement using electrical insulation techniques 73 3.2.6. Review of the main MOS devices for high-voltage integrated circuits 75 3.3. Combining analog and digital (mixed) 82 3.3.1. Analog: basic functional blocks in CMOS technology and basic analog structures 82 3.3.2. Reminder on the general structure of the operational amplifier 88 3.3.3. Digital 96 3.3.4. The notion of codesign 96 3.3.5. Assessment 99 Chapter 4. Technology for Simulating Power Integrated Systems 101 4.1. Introduction 101 4.2. Hardware and software design of engine control 102 4.2.1. Functional specification 105 4.2.2. Exploring the space of solutions: the partitioned specification model 106 4.2.3. Mixed synthesis, hardware and software code 107 4.2.4. Model functional testing 110 4.2.5. Synthesis of the approach and related tools of the functional model 111 4.3. Proposed design stream: related tools 112 4.3.1. Accuracy 113 4.3.2. Resources and system architecture 113 4.3.3. Realization 120 4.4. Conclusion 123 Chapter 5. 3D Electrothermal Integration 125 5.1. Introduction 125 5.2. Electrothermal modeling of substrate 126 5.2.1. Brief introduction to mathematical tools 127 5.2.2. Simulation results by using Green/TLM 132 5.2.3. Thermal management in a 3D-integrated figure 146 5.2.4. Thermo-mechanical design 156 5.2.5. Thermal modeling of the connectors 157 5.3. Heat analysis for 3D ICs 157 5.3.1. 3D IC heat transfer compact model without TSVs 157 5.3.2. IC model for analyzing the temperature of the chip of the top layer taking into account the TSVs 159 5.3.3. 3D IC thermal modeling result 161 5.3.4. Electrothermal (ET) modeling of very large scale circuits 166 5.3.5. Electrical modeling of very large scale 167 5.3.6. Thermal modeling of very large scale circuits 170 5.3.7. Electrothermal modeling of very large scale circuits 171 5.4. Conclusion 184 5.5. Heat pipe 185 5.6. Conclusion 203 Chapter 6. Substrate Coupling in Smart Power Integration 205 6.1. Introduction 205 6.2. Part I: smart power integration using the DTI technique 205 6.2.1 DTI technology 205 6.2.2 DTI structure 206 6.2.3. LDMOSFET performance with DTI 207 6.2.4. Parasitic suppression in 2D smart power ICs with deep trench 211 6.2.5. HV dynamic signal impact on CMOS devices 215 6.2.6. Mixed-mode CMOS-substrate coupling simulation 227 6.3. Part II: smart power integration using stacked 3D technology 232 6.3.1. From 2D planar integration to 3D integration 232 6.3.2. 3D smart power integration 234 6.3.3. TSV-CMOS mixed-mode coupling 253 6.3.4. Electromagnetic impact of TSV in RF range 264 Conclusion 271 Appendix: Semiconductor Physical Models 275 References 299 Index 301

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Book SynopsisThis book pioneers the synergy between state-of-the-art edge computing technologies and the power of operations research. It comprehensively explores real-world applications, demonstrating how various operations'' research techniques enhance edge computing's efficiency, reliability and resource allocation. Innovative solutions for dynamic task scheduling, load balancing and data management, all tailored to the unique challenges of edge environments, are displayed. Starting with operation research methodologies with foundations, applications and research challenges in edge computing and an overview of digital education, this book continues with an exploration of applications in the health sector using IoT, intelligent payment procedures and performance measurement of edge computing, using edge computing and operation research. Smart or AI-based applications are also explored further on and the book ends with insight into ultralightweight and security protocols with solutions f

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Book SynopsisAt the end of the Second World War, a new technological trend was born: integrated electronics. This trend relied on the enormous rise of integrable electronic devices. Analog Devices and Circuits is composed of two volumes: the first deals with analog components, and the second with associated analog circuits. The goal here is not to create an overly comprehensive analysis, but rather to break it down into smaller sections, thus highlighting the complexity and breadth of the field. This first volume, after a brief history, describes the two main devices, namely bipolar transistors and MOS, with particular importance given to the modeling aspect. In doing so, we deal with new devices dedicated to radio frequency, which touches on nanoelectronics. We will also address some of the notions related to quantum mechanics. Finally, Monte Carlo methods, by essence statistics, will be introduced, which have become more and more important since the middle of the twentieth

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Book SynopsisThe Ondes Martenot is one of the precursors of electronic musical instruments, and is today considered, with the desire for a return to analogue, as a cult instrument. This book, which is the result of several years of research, sheds light on the intrinsic functioning of the Ondes Martenot. Based on the study of numerous prototypes, the authors trace the historical evolution of the different techniques used: additive, multiplicative and relaxation syntheses. Often, the analysis of the functioning of these instruments demonstrates atypical technological choices, underpinned by a logic that places artistic creation at the forefront. Several models and simulations are built, so as to understand the functioning of each of the different sub-assemblies (keyboard, ribbon, intensity key, timbre filter...). At the end of the book, the complete construction of an Onde (copy of model no. 208) is described in detail. This practical realization of a facsimile is an opportunity to explore the knowhow of the electronic luthier Maurice Martenot.Table of ContentsForeword xi Hugues GENEVOIS Photo Credits xiii Introduction xv Chapter 1 Ondes 1928 1 1.1 Presentation 1 1.2 Principle of operation 3 1.3 The diagram 4 1.4 Construction of a model of the “1928” ondes 8 1.4.1 The box 8 1.4.2 Construction 9 1.4.3 The tuning capacitor controlled by a wire 10 1.4.4 The intensity key 14 1.5 Tests 18 1.5.1 Energy sources 18 1.5.2 The wiring 18 1.5.3 Tuning capacitor calibration 20 1.5.4 Adjusting the instrument 21 1.6 Perspectives of evolution 22 Chapter 2 Ondes No. 15 (1930) 23 2.1 Introduction 23 2.2 Presentation 23 2.3 Organization of the instrument 24 2.4 The heterodyne system + mixer-preamplifier + amplifier 27 2.4.1 General organization 27 2.4.2 Heterodynes 31 2.4.3 The mixer-preamplifier 34 2.4.4 The amplifier 35 2.5 The drawer 37 2.6 The diffuser 41 2.7 Power supplies 43 2.8 Trials 48 2.8.1 Preparations 48 2.8.2 Measurements 53 2.8.3 Measurement results 55 Chapter 3 Ondes No. 169 (1937) 63 3.1 Presentation of the instrument 63 3.2 Organization of the instrument 63 3.3 The heterodyne system + mixer + LF audio amplifier+ power amplifier 65 3.3.1 General organization 65 3.3.2 Heterodynes 67 3.3.3 The mixer–amplifier 79 3.3.4 The amplifier 81 3.4 The drawer 88 3.4.1 Description 88 3.4.2 Circuit diagram 89 3.4.3 Functional study 94 3.4.4 The intensity key 96 3.5 The diffuser 101 3.6 The power supply module 108 3.7 Model 112 3.7.1 Presentation 112 3.7.2 Realization 112 3.7.3 Tests and measurements 121 Chapter 4 Model ‘47 125 4.1 Presentation 125 4.2 Synoptic diagram 125 4.3 Operation analysis 125 4.3.1 Heterodynes 125 4.3.2 The mixer 130 4.3.3 First LF 131 4.3.4 The T9 timbre 136 4.3.5 LF power stage 137 4.3.6 Power module 142 4.4 The intensity key, ribbon capacitor and keyboard 142 Chapter 5 Ondes No. 208 (1953) 145 5.1 Introduction 145 5.2 Functional descriptions 146 5.2.1 The unit 146 5.2.2 The block diagram 150 5.2.3 Mechanical/electrical arrangement 150 5.3 Operation analysis 153 5.3.1 Oscillators 153 5.3.2 The fixed-frequency oscillator 154 5.3.3 The variable-frequency oscillator 157 5.4 The ribbon capacitor 161 5.4.1 General provisions 161 5.4.2 Sizing 164 5.4.3 Comments 179 5.5 Keyboard inductors 180 5.5.1 General provisions 180 5.5.2 Sizing 182 5.5.3 The register change 188 5.6 The mixer 190 5.7 1st LF 193 5.8 LF power stage 196 5.9 Timbre filters 198 5.10 Diffusers 209 5.11 Power supply 209 Chapter 6 Building an Ondes with Vacuum Tubes 213 6.1 Introduction 213 6.2 The electrical schematic 213 6.3 The chassis 214 6.4 The wiring 217 6.5 Special devices 217 6.5.1 The high register tuning capacitor 217 6.5.2 The diapason capacitor 218 6.5.3 The variable tuning inductor of the low register 219 6.5.4 Capacitors for timbre 7 219 6.5.5 HF inductors 220 6.6 The LF output transformer 225 6.7 Generic components 225 6.8 The drawer 225 6.8.1 Introduction 225 6.8.2 The box 225 6.8.3 Switches 227 6.8.4 The quarter-tone control buttons 228 6.8.5 The T8 timbre control knob 230 6.8.6 The power control knob 231 6.8.7 The needle block 232 6.8.8 The intensity key 232 6.8.9 The wiring 232 6.9 The keyboard/ribbon system 234 6.9.1 Introduction 234 6.9.2 The ribbon capacitor 234 6.9.3 The keyboard 241 6.10 The accessories 248 6.10.1 Command buttons 248 6.10.2 Other accessories 250 6.11 Calibration and tuning 254 6.11.1 Introduction 254 6.11.2 Ribbon capacitor calibration 254 6.11.3 Calibrating the keyboard coils 256 6.11.4 Tuning setting 257 6.11.5 The tuning procedure 259 6.12 Some photographs of ondes 2208 260 Chapter 7 Manufacture of the Leather Bag of the Intensity Key and the Ribbon 263 7.1 The intensity key 263 7.2 The mercury key 264 7.2.1 Description 264 7.2.2 Operating constraints 264 7.2.3 Realization 266 7.3 The powder key, first version 268 7.3.1 Abandonment of the mercury key 268 7.3.2 Description 268 7.3.3 Operating constraints 269 7.3.4 Realization 269 7.4 The powder key, second version 270 7.4.1 Description 270 7.4.2 Operating constraints 271 7.4.3 Realization 271 7.5 The powder key, third version 272 7.5.1 Description 272 7.5.2 Operating constraints 272 7.5.3 Realization 273 7.6 The powder key, fourth version 275 7.6.1 Description 275 7.6.2 Operating constraints 276 7.6.3 Realization 276 7.7 Other powder bags 277 7.7.1 Introduction 277 7.7.2 The pedal 277 7.7.3 The knee lever 278 7.8 Intensity key and gesture control 280 7.9 Manufacturing a powder bag 282 7.9.1 Introduction 282 7.9.2 Problem 283 7.9.3 Manufacturing the mixture 283 7.9.4 Manufacturing the powder bag 285 7.10 Ribbon manufacturing 288 7.10.1 Introduction 288 7.10.2 Problem 291 7.10.3 Ribbon manufacturing 291 Chapter 8 Transistorization 297 8.1 Introduction 297 8.2 The support 297 8.3 The problems of transistorization 299 8.4 Compatible transistor experimental ondes 301 8.4.1 Introduction 301 8.4.2 Diagram of the HF sub-assembly 301 8.4.3 The LF subset 302 8.4.4 Power supplies 303 8.5 Tests 304 References 305 Index 307

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Book SynopsisWind energy conversion systems are subject to many different types of faults and therefore fault detection is highly important to ensure reliability and safety. Monitoring systems can help to detect faults before they result in downtime. This book presents efficient methods used to detect electrical and mechanical faults based on electrical signals occurring in the different components of a wind energy conversion system. For example, in a small and high power synchronous generator and multi-phase generator, in the diode bridge rectifier, the gearbox and the sensors. This book also presents a method for keeping the frequency and voltage of the power grid within an allowable range while ensuring the continuity of power supply in the event of a grid fault. Electrical and Mechanical Fault Diagnosis in Wind Energy Conversion Systems presents original results obtained from a variety of research. It will not only be useful as a guideline for the conception of more robust wind turbines systems, but also for engineers monitoring wind turbines and researchersTable of ContentsIntroduction ixMonia BEN KHADER BOUZID and Gérard CHAMPENOIS Chapter 1 Accurate Electrical Fault Detection in the Permanent Magnet Synchronous Generator and in the Diode Bridge Rectifier of a Wind Energy Conversion System 1Monia BEN KHADER BOUZID and Gérard CHAMPENOIS 1.1 Introduction 1 1.2 Description of the system under study and the used fault detection method 2 1.3 Fundamental notions of the symmetrical components 5 1.4 Development of the analytical expressions of the NSV in the case of the different considered faults 7 1.4.1 Analytical expression of 2 V in the case of simultaneous faults 7 1.4.2 Analytical expression of 2 V in the case of ITSCF in the PMSG 12 1.4.3 Analytical expression of 2 V in the case of OCDF in the rectifier 14 1.5 Analytical study of the indicators of the different faults 15 1.5.1 Analytical study in the case of ITSCF 16 1.5.2 Analytical study in the case of OCDF in the rectifier 19 1.5.3 Analytical study in the case of SF 24 1.6 Experimental validation of the proposed fault indicators 25 1.6.1 Description of the tests process 25 1.6.2 Experimental results in the case of healthy operation 26 1.6.3 Experimental results in the case of ITSCF in the PMSG 27 1.6.4 Experimental results in the case of an OCDF fault in the rectifier 29 1.6.5 Experimental results in the case of SF in the system considered 31 1.7 Description of the method proposed 32 1.8 Conclusion 37 1.9 References 37 Chapter 2 Control and Diagnosis of Faults in Multiphase Permanent Magnet Synchronous Generators for High-Power Wind Turbines 39Sérgio CRUZ and Pedro GONÇALVES 2.1 Introduction 39 2.2 Wind energy conversion systems 40 2.3 Multiphase electric drives on WECS 41 2.4 Model of a six-phase PMSG drive 43 2.4.1 Natural reference frame 44 2.4.2 Synchronous reference frame 48 2.5 Control strategies 51 2.5.1 Introduction 51 2.5.2 Field-oriented control 51 2.5.3 Direct torque control 52 2.5.4 Finite control set model predictive control 54 2.6 Fault diagnosis in multiphase drives 71 2.6.1 Introduction 71 2.6.2 Interturn short-circuit faults 73 2.6.3 High-resistance connections and open-phase faults 76 2.6.4 Permanent magnet faults 78 2.6.5 Current sensor faults 79 2.6.6 Speed sensor faults 80 2.7 Conclusion 81 2.8 References 82 Chapter 3 Gearbox Fault Monitoring Using Induction Machine Electrical Signals 89Khmais BACHA and Walid TOUTI 3.1 Introduction 89 3.2 Motor stator current signature approach 90 3.2.1 Air gap magnetic flux density-based approach 90 3.2.2 Magnetizing current approach 97 3.3 Wound rotor current signature approach 99 3.4 Experimental results 101 3.4.1 MCSA for geared motor fault diagnosis 101 3.4.2 MCSA for WT gearbox 103 3.4.3 WT generator current processing 104 3.4.4 Current transformations for geared motor fault diagnosis 106 3.5 Conclusion 116 3.6 Acknowledgments 116 3.7 References 117 Chapter 4 Control of a Wind Distributed Generator for Auxiliary Services Under Grid Faults 119Youssef KRAIEM and Dhaker ABBES 4.1 Introduction 119 4.2 Description of the renewable distributed generator 123 4.3 Control of the distributed generator 124 4.3.1 Control of the wind generator 124 4.3.2 Control of the hybrid storage system 128 4.3.3 Control of the DC bus voltage 130 4.4 Power management algorithm 132 4.4.1 Specifications 132 4.4.2 Determination of inputs/outputs 133 4.4.3 Determination of membership functions 133 4.4.4 Inference engine for energy management 136 4.5 Detection and control of the grid faults 138 4.5.1 Fuzzy logic islanding detection 141 4.5.2 Fuzzy droop control technique for the adjustment of the grid frequency and voltage 144 4.6 Simulation results 146 4.6.1 Control and power management of the distributed generator 147 4.6.2 Detection and correction of the grid voltage and frequency variations at the PCC 150 4.7 Conclusion 154 4.8 References 154 Chapter 5 Fault-Tolerant Control of Sensors and Actuators Applied to Wind Energy Systems 159Elkhatib KAMAL and Abdel AITOUCHE 5.1 Introduction 159 5.2 Objective 161 5.3 RFFTC of WES with DFIG 163 5.3.1 TS fuzzy model with parameter uncertainties and fuzzy observer 164 5.3.2 Proposed RFFTC based on FPIEO and FDOS 167 5.3.3 Proposed RFFTC stability and robustness analysis 170 5.3.4 WES with DFIG application 171 5.3.5 Simulations and results 174 5.4 RFSFTC of WES with DFIG subject to sensor and actuator faults 178 5.4.1 TS fuzzy plant model with actuator faults, sensor faults and parameter uncertainties 179 5.4.2 Proposed RFSFTC algorithm based on FPIEO and FDOS 180 5.4.3 Derivation of the stability and robustness conditions 181 5.4.4 WES with DFIG application and simulations and results 183 5.5 RDFFTC of hybrid wind-diesel storage system subject to actuator and sensor faults 186 5.5.1 Fuzzy observer scheme for the uncertain system with sensor and actuator faults 187 5.5.2 Proposed RDFFTC, reference model and stability analysis 188 5.5.3 HWDSS application and simulations and results 191 5.6 Conclusion 197 5.7 References 198 List of Authors 203 Index 205

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Book SynopsisThe energy sector is undergoing unprecedented change. Twenty years ago, the main concern was having enough oil and gas, whereas today, political leaders are faced with the need to reduce the CO2 emissions produced by still-dominant fossil fuels, without being able to totally rely on renewable energies, which are intermittent and whose share in energy production remains low. Geopolitics and Energy Transition 1 presents the technical aspects of energy and its main characteristics, and outlines the challenges of the energy transition, the conditions for the development of renewable energies and the geopolitical stakes of this transition. It also describes the various energy markets and the consequences of liberalization policies, not forgetting to analyze the structures of the different sectors, while pointing out the fundamental problems of supply security and ways of strengthening it.

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Book SynopsisNetworks are now embedded in daily life thanks to smaller, faster, inexpensive components that are more powerful and increasingly connected. Parallel to this quantitative explosion of communication networks, technology has become more complex. This development comes with challenges related to management and control, and it has become necessary to manage the service level demands of the client to which the service provider commits. Different approaches to managing one or more service level components in different emerging environments are explored, such as: the Internet of Things, the Cloud, smart grids, e-health, mesh networking, D2D (Device to Device), smart cities and even green networking. This book therefore allows for a better understanding of the important challenges and issues relating to Quality of Service (QoS) management, security and mobility in these types of environment.Table of ContentsPreface xi Chapter 1. Service Level Management in the Internet of Things (IoT) 1Ahmad KHALIL, Nader MBAREK and Olivier TOGNI 1.1. Introduction 1 1.2. IoT: definitions 2 1.3. IoT: an overview 3 1.3.1. IoT architectures 3 1.3.2. Application fields of the IoT 6 1.4. Security management and privacy protection in the IoT 8 1.4.1. Motivations and challenges 8 1.4.2. Security services in the IoT environment 10 1.4.3. Privacy protection and trust in the IoT 18 1.5. QoS management for IoT services 21 1.5.1. Motivations and challenges 21 1.5.2. Guaranteeing QoS in IoT 22 1.6. QBAIoT: QoS-based access method for IoT environments 28 1.6.1. Service level guarantee in the IoT 28 1.6.2. The QBAIoT process in the IoT 31 1.6.3. QBAIoT performance evaluation 36 1.7. Conclusion 38 1.8. References 39 Chapter 2. Service Level Management in the Cloud 45Nader MBAREK 2.1. Introduction 45 2.2. The Cloud environment 46 2.2.1. Cloud Computing 46 2.2.2. Cloud Networking 50 2.2.3. Inter-Cloud 52 2.3. Service level and self-management in the Cloud 54 2.3.1. Quality of Service in a Cloud environment 54 2.3.2. Security in a Cloud environment 57 2.3.3. Self-management of Cloud environments 60 2.4. QoS guarantee in Cloud Networking 63 2.4.1. Cloud Networking architectures 63 2.4.2. Performance evaluation 68 2.5. Conclusion 75 2.6. References 75 Chapter 3. Managing Energy Demand as a Service in a Smart Grid Environment 83Samira CHOUIKHI, Leila MERGHEM-BOULAHIA and Moez ESSEGHIR 3.1. Introduction 83 3.2. The Smart Grid environment 84 3.2.1. Smart microgrids 85 3.2.2. Information and communication infrastructure 86 3.3. Demand management: fundamental concepts 87 3.3.1. Predicting loads 87 3.3.2. DR – demand response 88 3.4. Demand-side management 89 3.4.1. The architectures and components of DSM platforms 90 3.4.2. Classifying DSM approaches 91 3.4.3. Deterministic approaches for individual users 92 3.4.4. Stochastic approaches for individual users 93 3.4.5. Deterministic approaches for consumer communities 94 3.4.6. Stochastic approaches for consumer communities 94 3.5. Techniques and methods for demand scheduling 96 3.5.1. Game theory 97 3.5.2. Multiagent systems 98 3.5.3. Machine learning 99 3.6. Conclusion 100 3.7. References 101 Chapter 4. Managing Quality of Service and Security in an e-Health Environment 107Mohamed-Aymen CHALOUF 4.1. Introduction 107 4.2. e-health systems 109 4.2.1. Architecture 110 4.2.2. Characteristics 111 4.3. QoS in e-health systems 114 4.3.1. e-health services and QoS 114 4.3.2. QoS management in e-health systems 117 4.4. Security of e-health systems 124 4.4.1. Threats and attacks specific to e-health systems 124 4.4.2. Security management in e-health systems 127 4.5. Conclusion 130 4.6. References 131 Chapter 5. Quality of Service Management in Wireless Mesh Networks 139Hajer BARGAOUI, Nader MBAREK and Olivier TOGNI 5.1. Introduction 139 5.2. WMNs: an overview 140 5.2.1. Definition of a WMN 140 5.2.2. Architecture of a radio mesh wireless network 140 5.2.3. Characteristics of a WMN environment 142 5.2.4. Standards for WMNs 143 5.2.5. Domains of applications 144 5.3. QoS in WMNs 146 5.3.1. QoS in networks 146 5.3.2. QoS constraints in WMNs 146 5.3.3. QoS mechanisms in WMNs 147 5.3.4. Research projects on QoS in WMNs 150 5.4. QoS-based routing for WMNs 152 5.4.1. Routing requirements in WMNs 152 5.4.2. Routing metrics in WMNs 153 5.4.3. QoS-based routing protocols in WMNs 154 5.5. HQMR: QoS-based hybrid routing protocol for mesh radio networks 157 5.5.1. Description of the HQMR protocol 157 5.5.2. How the HQMR protocol works 160 5.5.3. Validation of the HQMR protocol 162 5.6. Conclusion 168 5.7. References 168 Chapter 6. Blockchain Based Authentication and Trust Management in Decentralized Networks 175Axel MOINET and Benoît DARTIES 6.1. Introduction 175 6.1.1. Challenges and motivations, the state of the art 177 6.1.2. Blockchain, a support for authentication and trust 181 6.2. The Blockchain Authentication and Trust Module (BATM) architecture 184 6.2.1. Context and development 184 6.2.2. Managing identities and authentication 185 6.2.3. Calculating trust and reputation using the MLTE algorithm 188 6.3. Evaluating BATM 197 6.3.1. Simulation plan 197 6.3.2. Results and interpretation 198 6.4. Conclusion 201 6.5. References 202 Chapter 7. How Machine Learning Can Help Resolve Mobility Constraints in D2D Communications 205Chérifa BOUCETTA, Hassine MOUNGLA and Hossam AFIFI 7.1. Introduction 205 7.2. D2D communication and the evolution of networks 207 7.2.1. The discovery phase in D2D communications 208 7.2.2. The data exchange phase in D2D communications 209 7.2.3. Investigations into future mobile networks 210 7.3. The context for machine learning and deep learning 210 7.3.1. Overview of deep learning and its application 212 7.3.2. Types of machine learning 213 7.3.3. Linear regression and classification 213 7.4. Dynamic discovery 215 7.4.1. Real-time prediction of user density 216 7.4.2. The dynamic discovery algorithm 217 7.5. Experimental results 218 7.5.1. General hypotheses 218 7.5.2. Traffic with low user density 219 7.5.3. Traffic with high user density 219 7.6. Conclusion 222 7.7. References 222 Chapter 8. The Impact of Cognitive Radio on Green Networking: The Learning-through-reinforcement Approach 227Mohammed Salih BENDELLA and Badr BENMAMMAR 8.1. Introduction 227 8.2. Green networking 228 8.2.1. Why should we reduce energy consumption? 228 8.2.2. Where can we reduce energy consumption? 228 8.2.3. Definition and objectives of green networking 229 8.3. Green strategies 230 8.3.1. Consolidation of resources 230 8.3.2. Selective connectivity 231 8.3.3. Virtualization 231 8.3.4. Energy-proportional computing 231 8.4. Green wireless networks 233 8.4.1. Energy efficiency in wireless networks 235 8.4.2. Controlling transmission power 236 8.5. How CR contributes to green networking 238 8.5.1. The principle behind CR 238 8.5.2. The cognition cycle 238 8.5.3. Green networking in CR networks 240 8.6. Learning through reinforcement by taking into account energy efficiency during opportunistic access to the spectrum 243 8.6.1. Formulating the problem 245 8.6.2. Comparison between CR and Q_learning enabled CR 247 8.7. Conclusion 248 8.8. References 249 List of Authors 253 Index 255

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Book SynopsisElectromagnetic Waves 1 examines Maxwell’s equations and wave propagation. It presents the scientific bases necessary for any application using electromagnetic fields, and analyzes Maxwell’s equations, their meaning and their resolution for various situations and material environments. These equations are essential for understanding electromagnetism and its derived fields, such as radioelectricity, photonics, geolocation, measurement, telecommunications, medical imaging and radio astronomy. This book also deals with the propagation of electromagnetic, radio and optical waves, and analyzes the complex factors that must be taken into account in order to understand the problems of propagation in a free and confined space. Electromagnetic Waves 1 is a collaborative work, completed only with the invaluable contributions of Ibrahima Sakho, Hervé Sizun and JeanPierre Blot, not to mention the editor, Pierre-Noël Favennec. Aimed at students and engineers, this book provides essential theoretical support for the design and deployment of wireless radio and optical communication systems.Table of ContentsPreface ix Chapter 1. Maxwell’s Equations 1Ibrahima SAKHO 1.1. Maxwell’s equations in a vacuum 1 1.1.1. Electrostatics 1 1.1.2. Magnetostatics 17 1.1.3. Electromagnetic induction 33 1.1.4. Maxwell’s equations 54 1.2. Maxwell equations in material media 85 1.2.1. Electric field and potential in macroscopic dielectric media 86 1.2.2. Homogeneous linear dielectric media 95 1.2.3. Magnetic media 98 1.2.4. Maxwell equations in a polarized and magnetic medium 111 1.3. References 117 Chapter 2. The Propagation of Optical and Radio Electromagnetic Waves 119Hervé SIZUN 2.1. Introduction 119 2.2. Maxwell’s equations 121 2.2.1. Maxwell-Gauss equation 121 2.2.2. Maxwell-Thompson equation 122 2.2.3. Maxwell-Faraday equation 123 2.2.4. Maxwell-Ampère equation 123 2.3. Solving Maxwell’s equations 124 2.4. Characteristics of electromagnetic waves 125 2.4.1. Propagation speed 125 2.4.2. Wavelength and/or frequency 126 2.4.3. The characteristic impedance of the propagation medium 127 2.4.4. Poynting vector 127 2.4.5. The refractive index 128 2.4.6. Polarization 129 2.4.7. Transpolarization 131 2.4.8. Different propagation paths 132 2.4.9. Fresnel zones 133 2.4.10. Fundamental properties of the propagation channel 134 2.5. Propagation modeling 146 2.5.1. Tropospheric propagation 147 2.5.2. Propagation in rural, suburban and urban areas 172 2.5.3. Propagation within buildings 184 2.5.4. Broadband propagation 196 2.5.5. Ultra-wideband propagation 200 2.6. The propagation of visible and infrared waves in the Earth’s atmosphere 207 2.6.1. Introduction 207 2.6.2. The propagation of light in the atmosphere 208 2.6.3. The different models 214 2.6.4. Experimental results 222 2.6.5. Fog and mist 225 2.6.6. Sandstorms 226 2.6.7. Meteorological optical range 227 2.6.8. Applications 231 2.7. Conclusion 232 2.8. Recommendations ITU-R 233 2.9. References 233 Appendix 1 239 Appendix 2 243 Appendix 3 261 Appendix 4 269 Appendix 5 273 List of Acronyms and Constants 275 List of Authors 277 Index 279

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Book SynopsisThe management and control of networks can no longer be envisaged without the introduction of artificial intelligence at all stages. Intelligent Network Management and Control deals with topical issues related mainly to intelligent security of computer networks, deployment of security services in SDN (software-defined networking), optimization of networks using artificial intelligence techniques and multi-criteria optimization methods for selecting networks in a heterogeneous environment. This book also focuses on selecting cloud computing services, intelligent unloading of calculations in the context of mobile cloud computing, intelligent resource management in a smart grid-cloud system for better energy efficiency, new architectures for the Internet of Vehicles (IoV), the application of artificial intelligence in cognitive radio networks and intelligent radio input to meet the on-road communication needs of autonomous vehicles.Table of ContentsIntroduction xiiiBadr BENMAMMAR Part 1. AI and Network Security 1 Chapter 1. Intelligent Security of Computer Networks 3Abderrazaq SEMMOUD and Badr BENMAMMAR 1.1. Introduction 3 1.2. AI in the service of cybersecurity 5 1.3. AI applied to intrusion detection 8 1.3.1. Techniques based on decision trees 9 1.3.2. Techniques based on data exploration 9 1.3.3. Rule-based techniques 10 1.3.4. Machine learning-based techniques 11 1.3.5. Clustering techniques 13 1.3.6. Hybrid techniques 14 1.4. AI misuse 15 1.4.1. Extension of existing threats 16 1.4.2. Introduction of new threats 16 1.4.3. Modification of the typical threat character 17 1.5. Conclusion 17 1.6. References 18 Chapter 2. An Intelligent Control Plane for Security Services Deployment in SDN-based Networks 25Maïssa MBAYE, Omessaad HAMDI and Francine KRIEF 2.1. Introduction 25 2.2. Software-defined networking 27 2.2.1. General architecture 27 2.2.2. Logical distribution of SDN control 29 2.3. Security in SDN-based networks 32 2.3.1. Attack surfaces 33 2.3.2. Example of security services deployment in SDN-based networks: IPSec service 34 2.4. Intelligence in SDN-based networks 40 2.4.1. Knowledge plane 41 2.4.2. Knowledge-defined networking 41 2.4.3. Intelligence-defined networks 42 2.5. AI contribution to security 43 2.5.1. ML techniques 43 2.5.2. Contribution of AI to security service: intrusion detection 47 2.6. AI contribution to security in SDN-based networks 48 2.7. Deployment of an intrusion prevention service 49 2.7.1. Attack signature learning as cloud service 50 2.7.2. Deployment of an intrusion prevention service in SDN-based networks 52 2.8. Stakes 55 2.9. Conclusion 56 2.10. References 56 Part 2. AI and Network Optimization 63 Chapter 3. Network Optimization using Artificial Intelligence Techniques 65Asma AMRAOUI and Badr BENMAMMAR 3.1. Introduction 65 3.2. Artificial intelligence 66 3.2.1. Definition 66 3.2.2. AI techniques 67 3.3. Network optimization 73 3.3.1. AI and optimization of network performances 73 3.3.2. AI and QoS optimization 74 3.3.3. AI and security 75 3.3.4. AI and energy consumption 77 3.4. Network application of AI 77 3.4.1. ESs and networks 77 3.4.2. CBR and telecommunications networks 79 3.4.3. Automated learning and telecommunications networks 79 3.4.4. Big data and telecommunications networks 80 3.4.5. MASs and telecommunications networks 82 3.4.6. IoT and networks 84 3.5. Conclusion 85 3.6. References 85 Chapter 4. Multicriteria Optimization Methods for Network Selection in a Heterogeneous Environment 89Fayssal BENDAOUD 4.1. Introduction 89 4.2. Multicriteria optimization and network selection 91 4.2.1. Network selection process 92 4.2.2. Multicriteria optimization methods for network selection 94 4.3. “Modified-SAW” for network selection in a heterogeneous environment 99 4.3.1. “Modified-SAW” proposed method 100 4.3.2. Performance evaluation 104 4.4. Conclusion 113 4.5. References 113 Part 3. AI and the Cloud Approach 117 Chapter 5. Selection of Cloud Computing Services: Contribution of Intelligent Methods 119Ahmed Khalid Yassine SETTOUTI 5.1. Introduction 119 5.2. Scientific and technical prerequisites 120 5.2.1. Cloud computing 120 5.2.2. Artificial intelligence 126 5.3. Similar works 129 5.4. Surveyed works 131 5.4.1. Machine learning 131 5.4.2. Heuristics 133 5.4.3. Intelligent multiagent systems 135 5.4.4. Game theory 137 5.5. Conclusion 140 5.6. References 140 Chapter 6. Intelligent Computation Offloading in the Context of Mobile Cloud Computing 145Zeinab MOVAHEDI 6.1. Introduction 145 6.2. Basic definitions 147 6.2.1. Fine-grain offloading 147 6.2.2. Coarse-grain offloading 149 6.3. MCC architecture 151 6.3.1. Generic architecture of MCC 151 6.3.2. C-RAN-based architecture 154 6.4. Offloading decision 154 6.4.1. Positioning of the offloading decision middleware 155 6.4.2. General formulation 156 6.4.3. Modeling of offloading cost 158 6.5. AI-based solutions 161 6.5.1. Branch and bound algorithm 161 6.5.2. Bio-inspired metaheuristics algorithms 164 6.5.3. Ethology-based metaheuristics algorithms 165 6.6. Conclusion 165 6.7. References 166 Part 4. AI and New Communication Architectures 169 Chapter 7. Intelligent Management of Resources in a Smart Grid-Cloud for Better Energy Efficiency 171Mohammed Anis BENBLIDIA, Leila MERGHEM-BOULAHIA, Moez ESSEGHIR and Bouziane BRIK 7.1. Introduction 171 7.2. Smart grid and cloud data center: fundamental concepts and architecture 172 7.2.1. Network architecture for smart grids 173 7.2.2. Main characteristics of smart grids 174 7.2.3. Interaction of cloud data centers with smart grids 178 7.3. State-of-the-art on the energy efficiency techniques of cloud data centers 180 7.3.1. Energy efficiency techniques of non-IT equipment of a data center 180 7.3.2. Energy efficiency techniques in data center servers 181 7.3.3. Energy efficiency techniques for a set of data centers 182 7.3.4. Discussion 184 7.4. State-of-the-art on the decision-aiding techniques in a smart grid-cloud system 185 7.4.1. Game theory 186 7.4.2. Convex optimization 187 7.4.3. Markov decision process 187 7.4.4. Fuzzy logic 187 7.5. Conclusion 188 7.6. References 189 Chapter 8. Toward New Intelligent Architectures for the Internet of Vehicles 193Léo MENDIBOURE, Mohamed Aymen CHALOUF and Francine KRIEF 8.1. Introduction 193 8.2. Internet of Vehicles 195 8.2.1. Positioning 195 8.2.2. Characteristics 196 8.2.3. Main applications 197 8.3. IoV architectures proposed in the literature 197 8.3.1. Integration of AI techniques in a layer of the control plane 199 8.3.2. Integration of AI techniques in several layers of the control plane 199 8.3.3. Definition of a KP associated with the control plane 200 8.3.4. Comparison of architectures and positioning 200 8.4. Our proposal of intelligent IoV architecture 201 8.4.1. Presentation 202 8.4.2. A KP for data transportation 203 8.4.3. A KP for IoV architecture management 205 8.4.4. A KP for securing IoV architecture 207 8.5. Stakes 209 8.5.1. Security and private life 210 8.5.2. Swarm learning 210 8.5.3. Complexity of computing methods 210 8.5.4. Vehicle flow motion 211 8.6. Conclusion 211 8.7. References 212 Part 5. Intelligent Radio Communications 217 Chapter 9. Artificial Intelligence Application to Cognitive Radio Networks 219Badr BENMAMMAR and Asma AMRAOUI 9.1. Introduction 219 9.2. Cognitive radio 222 9.2.1. Cognition cycle 222 9.2.2. CR tasks and corresponding challenges 223 9.3. Application of AI in CR 223 9.3.1. Metaheuristics 223 9.3.2. Fuzzy logic 229 9.3.3. Game theory 230 9.3.4. Neural networks 231 9.3.5. Markov models 231 9.3.6. Support vector machines 232 9.3.7. Case-based reasoning 233 9.3.8. Decision trees 233 9.3.9. Bayesian networks 234 9.3.10. MASs and RL 234 9.4. Categorization and use of techniques in CR 236 9.5. Conclusion 237 9.6. References 237 Chapter 10. Cognitive Radio Contribution to Meeting Vehicular Communication Needs of Autonomous Vehicles 245Francine KRIEF, Hasnaâ ANISS, Marion BERBINEAU and Killian LE PAGE 10.1. Introduction 245 10.2. Autonomous vehicles 246 10.2.1. Automation levels 246 10.2.2. The main components 247 10.3. Connected vehicle 251 10.3.1. Road safety applications 251 10.3.2. Entertainment applications 252 10.4. Communication architectures 253 10.4.1. ITS-G5 256 10.4.2. LTE-V2X 257 10.4.3. Hybrid communication 258 10.5. Contribution of CR to vehicular networks 258 10.5.1. Cognitive radio 259 10.5.2. CR-VANET 260 10.6. SERENA project: self-adaptive selection of radio access technologies using CR 264 10.6.1. Presentation and positioning 265 10.6.2. General architecture being considered 266 10.6.3. The main stakes 269 10.7. Conclusion 270 10.8. References 270 List of Authors 275 Index 277

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Book SynopsisA Multi-Processor System-on-Chip (MPSoC) is the key component for complex applications. These applications put huge pressure on memory, communication devices and computing units. This book, presented in two volumes – Architectures and Applications – therefore celebrates the 20th anniversary of MPSoC, an interdisciplinary forum that focuses on multi-core and multi-processor hardware and software systems. It is this interdisciplinarity which has led to MPSoC bringing together experts in these fields from around the world, over the last two decades. Multi-Processor System-on-Chip 1 covers the key components of MPSoC: processors, memory, interconnect and interfaces. It describes advance features of these components and technologies to build efficient MPSoC architectures. All the main components are detailed: use of memory and their technology, communication support and consistency, and specific processor architectures for general purposes or for dedicated applications.Table of ContentsForeword xiiiAhmed JERRAYA Acknowledgments xvLiliana ANDRADE and Frédéric ROUSSEAU Part 1. Processors 1 Chapter 1. Processors for the Internet of Things 3Pieter VAN DER WOLF and Yankin TANURHAN 1.1. Introduction 3 1.2. Versatile processors for low-power IoT edge devices 4 1.2.1. Control processing, DSP and machine learning 4 1.2.2. Configurability and extensibility 6 1.3. Machine learning inference 8 1.3.1. Requirements for low/mid-end machine learning inference 10 1.3.2. Processor capabilities for low-power machine learning inference 14 1.3.3. A software library for machine learning inference 17 1.3.4. Example machine learning applications and benchmarks 20 1.4. Conclusion 23 1.5. References 24 Chapter 2. A Qualitative Approach to Many-core Architecture 27Benoît DUPONT DE DINECHIN 2.1. Introduction 28 2.2. Motivations and context 29 2.2.1. Many-core processors 29 2.2.2. Machine learning inference 30 2.2.3. Application requirements 32 2.3. The MPPA3 many-core processor 34 2.3.1. Global architecture 34 2.3.2. Compute cluster 36 2.3.3. VLIW core 38 2.3.4. Coprocessor 39 2.4. The MPPA3 software environments 42 2.4.1. High-performance computing 42 2.4.2. KaNN code generator 43 2.4.3. High-integrity computing 46 2.5. Conclusion 47 2.6. References 48 Chapter 3. The Plural Many-core Architecture – High Performance at Low Power 53Ran GINOSAR 3.1. Introduction 54 3.2. Related works 55 3.3. Plural many-core architecture 55 3.4. Plural programming model 56 3.5. Plural hardware scheduler/synchronizer 58 3.6. Plural networks-on-chip 61 3.6.1. Schedule rNoC 61 3.6.2. Shared memory NoC 61 3.7. Hardware and software accelerators for the Plural architecture 62 3.8. Plural system software 63 3.9. Plural software development tools 65 3.10. Matrix multiplication algorithm on the Plural architecture 65 3.11. Conclusion 67 3.12. References 67 Chapter 4. ASIP-Based Multi-Processor Systems for an Efficient Implementation of CNNs 69Andreas BYTYN, René AHLSDORF and Gerd ASCHEID 4.1. Introduction 70 4.2. Related works 71 4.3. ASIP architecture 74 4.4. Single-core scaling 75 4.5. MPSoC overview 78 4.6. NoC parameter exploration 79 4.7. Summary and conclusion 82 4.8. References 83 Part 2. Memory 85 Chapter 5. Tackling the MPSoC Data Locality Challenge 87Sven RHEINDT, Akshay SRIVATSA, Oliver LENKE, Lars NOLTE, Thomas WILD and Andreas HERKERSDORF 5.1. Motivation 88 5.2. MPSoC target platform 90 5.3. Related work 91 5.4. Coherence-on-demand: region-based cache coherence 92 5.4.1. RBCC versus global coherence 93 5.4.2. OS extensions for coherence-on-demand 94 5.4.3. Coherency region manager 94 5.4.4. Experimental evaluations 97 5.4.5. RBCC and data placement 99 5.5. Near-memory acceleration 100 5.5.1. Near-memory synchronization accelerator 102 5.5.2. Near-memory queue management accelerator 104 5.5.3. Near-memory graph copy accelerator 107 5.5.4. Near-cache accelerator 110 5.6. The big picture 111 5.7. Conclusion 113 5.8. Acknowledgments 114 5.9. References 114 Chapter 6. mMPU: Building a Memristor-based General-purpose In-memory Computation Architecture 119Adi ELIAHU, Rotem BEN HUR, Ameer HAJ ALI and Shahar KVATINSKY 6.1. Introduction 120 6.2. MAGIC NOR gate 121 6.3. In-memory algorithms for latency reduction 122 6.4. Synthesis and in-memory mapping methods 123 6.4.1. SIMPLE 124 6.4.2. SIMPLER 126 6.5. Designing the memory controller 127 6.6. Conclusion 129 6.7. References 130 Chapter 7. Removing Load/Store Helpers in Dynamic Binary Translation 133Antoine FARAVELON, Olivier GRUBER and Frédéric PÉTROT 7.1. Introduction 134 7.2. Emulating memory accesses 136 7.3. Design of our solution 140 7.4. Implementation 143 7.4.1. Kernel module 143 7.4.2. Dynamic binary translation 145 7.4.3. Optimizing our slow path 147 7.5. Evaluation 149 7.5.1. QEMU emulation performance analysis 150 7.5.2. Our performance overview 151 7.5.3. Optimized slow path 153 7.6. Related works 155 7.7. Conclusion 157 7.8. References 158 Chapter 8. Study and Comparison of Hardware Methods for Distributing Memory Bank Accesses in Many-core Architectures 161Arthur VIANES and Frédéric ROUSSEAU 8.1. Introduction 162 8.1.1. Context 162 8.1.2. MPSoC architecture 163 8.1.3. Interconnect 164 8.2. Basics on banked memory 165 8.2.1. Banked memory 165 8.2.2. Memory bank conflict and granularity 166 8.2.3. Efficient use of memory banks: interleaving 168 8.3. Overview of software approaches 170 8.3.1. Padding 170 8.3.2. Static scheduling of memory accesses 172 8.3.3. The need for hardware approaches 172 8.4. Hardware approaches 172 8.4.1. Prime modulus indexing 172 8.4.2. Interleaving schemes using hash functions 174 8.5. Modeling and experimenting 181 8.5.1. Simulator implementation 182 8.5.2. Implementation of the Kalray MPPA cluster interconnect 182 8.5.3. Objectives and method 184 8.5.4. Results and discussion 185 8.6. Conclusion 191 8.7. References 192 Part 3. Interconnect and Interfaces 195 Chapter 9. Network-on-Chip (NoC): The Technology that Enabled Multi-processor Systems-on-Chip (MPSoCs) 197K. Charles JANAC 9.1. History: transition from buses and crossbars to NoCs 198 9.1.1.NoC architecture 202 9.1.2. Extending the bus comparison to crossbars 207 9.1.3. Bus, crossbar and NoC comparison summary and conclusion 207 9.2. NoC configurability 208 9.2.1. Human-guided design flow 208 9.2.2. Physical placement awareness and NoC architecture design 209 9.3. System-level services 211 9.3.1. Quality-of-service (QoS) and arbitration 211 9.3.2. Hardware debug and performance analysis 212 9.3.3. Functional safety and security 212 9.4. Hardware cache coherence 215 9.4.1. NoC protocols, semantics and messaging 216 9.5. Future NoC technology developments 217 9.5.1. Topology synthesis and floorplan awareness 217 9.5.2. Advanced resilience and functional safety for autonomous vehicles 218 9.5.3. Alternatives to von Neumann architectures for SoCs 219 9.5.4. Chiplets and multi-die NoC connectivity 221 9.5.5. Runtime software automation 222 9.5.6. Instrumentation, diagnostics and analytics for performance, safety and security 223 9.6. Summary and conclusion 224 9.7. References 224 Chapter 10. Minimum Energy Computing via Supply and Threshold Voltage Scaling 227Jun SHIOMI and Tohru ISHIHARA 10.1. Introduction 228 10.2. Standard-cell-based memory for minimum energy computing 230 10.2.1. Overview of low-voltage on-chip memories 230 10.2.2. Design strategy for area- and energy-efficient SCMs 234 10.2.3. Hybrid memory design towards energy- and area-efficient memory systems 236 10.2.4. Body biasing as an alternative to power gating 237 10.3. Minimum energy point tracking 238 10.3.1. Basic theory 238 10.3.2. Algorithms and implementation 244 10.3.3. OS-based approach to minimum energy point tracking 246 10.4. Conclusion 249 10.5. Acknowledgments 249 10.6. References 250 Chapter 11. Maintaining Communication Consistency During Task Migrations in Heterogeneous Reconfigurable Devices 255Arief WICAKSANA, OlivierMULLER, Frédéric ROUSSEAU and Arif SASONGKO 11.1. Introduction 256 11.1.1. Reconfigurable architectures 256 11.1.2. Contribution 257 11.2. Background 257 11.2.1. Definitions 258 11.2.2. Problem scenario and technical challenges 259 11.3. Related works 261 11.3.1. Hardware context switch 261 11.3.2. Communication management 262 11.4. Proposed communication methodology in hardware context switching 263 11.5. Implementation of the communication management on reconfigurable computing architectures 266 11.5.1. Reconfigurable channels in FIFO 267 11.5.2. Communication infrastructure 268 11.6. Experimental results 269 11.6.1. Setup 269 11.6.2. Experiment scenario 270 11.6.3. Resource overhead 271 11.6.4. Impact on the total execution time 273 11.6.5. Impact on the context extract and restore time 275 11.6.6. System responsiveness to context switch requests 276 11.6.7. Hardware task migration between heterogeneous FPGAs 280 11.7. Conclusion 282 11.8. References 283 List of Authors 287 Authors Biographies 291 Index 299

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Book SynopsisA Multi-Processor System-on-Chip (MPSoC) is the key component for complex applications. These applications put huge pressure on memory, communication devices and computing units. This book, presented in two volumes – Architectures and Applications – therefore celebrates the 20th anniversary of MPSoC, an interdisciplinary forum that focuses on multi-core and multi-processor hardware and software systems. It is this interdisciplinarity which has led to MPSoC bringing together experts in these fields from around the world, over the last two decades. Multi-Processor System-on-Chip 2 covers application-specific MPSoC design, including compilers and architecture exploration. This second volume describes optimization methods, tools to optimize and port specific applications on MPSoC architectures. Details on compilation, power consumption and wireless communication are also presented, as well as examples of modeling frameworks and CAD tools. Explanations of specific platforms for automotive and real-time computing are also included.Table of ContentsForeword xiAhmed JERRAYA Acknowledgments xiiiLiliana ANDRADE and Frédéric ROUSSEAU Part 1. MPSoC for Telecom 1 Chapter 1. From Challenges to Hardware Requirements for Wireless Communications Reaching 6G 3Stefan A. DAMJANCEVIC, Emil MATUS, Dmitry UTYANSKY, Pieter VAN DER WOLF and Gerhard P. FETTWEIS 1.1. Introduction 4 1.2. Breadth of workloads 6 1.2.1. Vision, trends and applications 6 1.2.2. Standard specifications 8 1.2.3. Outcome of workloads 13 1.3. GFDM algorithm breakdown 14 1.3.1. Equation 15 1.3.2. Dataflow processing graph and matrix representation 15 1.3.3. Pseudo-code 16 1.4. Algorithm precision requirements and considerations 18 1.5. Implementation 21 1.5.1. Implementation considerations 23 1.5.2. Design space exploration 23 1.5.3. Measurements for low-end and high-end use cases 26 1.6. Conclusion 28 1.7. Acknowledgments 29 1.8. References 29 Chapter 2. Towards Tbit/s Wireless Communication Baseband Processing: When Shannon meets Moore 33Matthias HERRMANN and Norbert WEHN 2.1. Introduction 34 2.2. Role of microelectronics 36 2.3. Towards 1 Tbit/s throughput decoders 37 2.3.1. Turbodecoder 39 2.3.2. LDPC decoder 41 2.3.3. Polar decoder 41 2.4. Conclusion 43 2.5. Acknowledgments 43 2.6. References 43 Part 2. Application-specific MPSoC Architectures 47 Chapter 3. Automation for Industry 4.0 by using Secure LoRaWAN Edge Gateways 49Marcello COPPOLA and George KORNAROS 3.1. Introduction 50 3.2. Security in IIoT 52 3.3. LoRaWAN security in IIoT 53 3.4. Threatmodel 55 3.4.1. LoRaWAN attack model 55 3.4.2. IIoT node attack model 56 3.5. Trusted boot chain with STM32MP1 57 3.5.1. Trust base of node 57 3.5.2. Trusted firmware inSTM32MP1 57 3.5.3. Trusted execution environments and OP-TEE 58 3.5.4. OP-TEE scheduling considerations 60 3.5.5. OP-TEEmemorymanagement 60 3.5.6. OP-TEE clientAPI 61 3.5.7.TEE internal coreAPI 62 3.5.8. Root and chain of trust 62 3.5.9. Hardware unique key 62 3.5.10. Secure clock 63 3.5.11. Cryptographic operations 63 3.6. LoRaWAN gateway withSTM32MP1 64 3.7. Discussion and future scope 65 3.8. Acknowledgments 66 3.9. References 66 Chapter 4. Accelerating Virtualized Distributed NVMe Storage in Hardware 69Julian CHESTERFIELD and Michail FLOURIS 4.1. Introduction 70 4.1.1. Virtualization and traditional hypervisors 71 4.1.2. Hyperconverged versus disaggregated cloud architectures 72 4.1.3. NVMe flash storage 74 4.2. Motivation:NVMe storage for the cloud 75 4.2.1. Motivation for a new hypervisor 75 4.2.2. Motivation for accelerating disaggregated storage 76 4.3. Design 77 4.3.1. Optimizing the hypervisor I/O operations 77 4.3.2. Design of accelerated disaggregated storage 80 4.4. Implementation 86 4.4.1. The NexVisor platform 87 4.4.2. Accelerated disaggregated storage 87 4.5. Results 90 4.5.1. Sequential reads 90 4.5.2. Sequentialwrites 90 4.5.3. Sequential reads on one NVMe drive 92 4.5.4. Networkperformance 92 4.6. Conclusion 93 4.7. References 93 Chapter 5. Modular and Open Platform for Future Automotive Computing Environment 95Raphaël DAVID, Etienne HAMELIN, Paul DUBRULLE, Shuai LI, Philippe DORE, Alexis OLIVEREAU, Maroun OJAIL, Alexandre CARBON and Laurent LE GARFF 5.1. Introduction 96 5.2. Outline of this approach 98 5.2.1. Centralized computation, distributed data 98 5.2.2. Modularity and heterogeneity 99 5.2.3. Tools for specification, configuration and integration 101 5.3. Results 102 5.3.1. Hardware platform 103 5.3.2. FACE SW architecture 108 5.3.3. FACE Tool Suite 112 5.4. Use case 116 5.4.1. Adaptive braking system 116 5.5. Conclusion 118 5.6. References 119 Chapter 6. Post-Moore Datacenter Server Architecture 123Babak FALSAFI 6.1. Introduction 124 6.2. Background: today’s blades are from the desktops of the 1980s 125 6.3. Memory-centricserverdesign 127 6.4. Data management accelerators 129 6.5. Integrated network controllers 130 6.6. References 131 Part 3. Architecture Examples and Tools for MPSoC 135 Chapter 7. SESAM: A Comprehensive Framework for Cyber–Physical System Prototyping 137Amir CHARIF, AriefWICAKSANA, Salah-Eddine SAIDI, Tanguy SASSOLAS, Caaliph ANDRIAMISAINA and Nicolas VENTROUX 7.1. Introduction 138 7.2. An overview of the SESAM platform 138 7.2.1. Multi-abstraction system prototyping 139 7.2.2. Assessing extra-functional system properties 140 7.3. VPSim: fast and easy virtual prototyping 140 7.3.1. Writing peripherals in Python 141 7.3.2. The Model Provider interface 142 7.3.3. QEMU support 144 7.3.4. Online simulation monitoring 146 7.3.5. Acceleration methods 146 7.4. Hybrid prototyping 147 7.4.1. Co-simulationmode 148 7.4.2. Co-emulationmode 149 7.4.3. Runtime performance analysis and debugging features 149 7.5.FMI for co-simulation 150 7.5.1. Functional mock-up interface 151 7.5.2. VPSim integration inFMI co-simulation 152 7.6. Conclusion 155 7.7. References 155 Chapter 8. StaccatoLab: A Programming and Execution Model for Large-scale Dataflow Computing 157Kees VAN BERKEL 8.1. Introduction 158 8.2. Static dataflow 161 8.2.1. Synchronous dataflow 162 8.2.2. Cyclo-static dataflow 166 8.2.3. Dataflow graph transformations 167 8.3. Dynamic dataflow 168 8.3.1. Data-dependentdataflow 168 8.3.2. Non-determinatedataflow 172 8.4. Dataflow execution models 175 8.4.1. A brief review of dataflow theory 175 8.4.2. The StaccatoLab execution model 177 8.5. StaccatoLab 180 8.5.1. Dataflow graph description and analysis 180 8.5.2. Verilog synthesis 180 8.6. Large-scale dataflow computing? 182 8.6.1. What kind of applications? 182 8.6.2. Why effective? 183 8.6.3. Why efficient? 184 8.7. Acknowledgments 185 8.8. References 185 Chapter 9. Smart Cameras and MPSoCs 189Marilyn WOLF 9.1. Introduction 189 9.2. Early VLSI video processors 190 9.3. Video signal processors 191 9.4. Accelerators 193 9.5. From VSP to MPSoC 195 9.6. Graphics processing units 197 9.7. Neural networks and tensor processing units 197 9.8. Conclusion 199 9.9. References 199 Chapter 10. Software Compilation and Optimization Techniques for Heterogeneous Multi-core Platforms 203Weihua SHENG, Jeronimo CASTRILLON and Rainer LEUPERS 10.1. Introduction 204 10.2. Dataflow modeling 207 10.2.1. General concepts 207 10.2.2. Process networks 208 10.2.3. Cfor process networks 209 10.3. Source-to-source-based compiler infrastructure 214 10.3.1.Design rationale 214 10.3.2. Implementation strategy 216 10.4. Software distribution 218 10.4.1. KPNanalysis 219 10.4.2. Static KPN mapping 220 10.4.3. Hybrid KPN mapping 221 10.5. Results 222 10.5.1.Applications and experiences 222 10.5.2. Retargetability 229 10.6. Conclusion 230 10.7. References 231 List of Authors 237 Author Biographies 241 Index 251

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Book SynopsisThe challenges associated with the environmental impact of renewable energies are formidable and multiple. The exploitation of diffuse forms of energy will require us to reshape our lifestyles and infrastructures. Reducing their environmental impact is imperative and requires the mobilization of all available levers of action.Beyond the analysis of these challenges, this book presents an overview of the levers of action that should allow us to meet them, by crossing the fields of the human sciences, geosciences and engineering. The levers of action examined are both technical (through the substitution or use of low technology) and economic and social (through the development of recycling or decoupling). The book also addresses the question of their effectiveness and their overall impact.Table of ContentsIntroduction xiFlorian FIZAINE and Xavier GALIÈGUE Part 1. Stakes 1 Chapter 1. Toward a New Geopolitics of Raw Materials in the Energy Transition 3Emmanuel HACHE, Gondia SOKHNA SECK, Charlène BARNET, Samuel CARCANAGUE and Fernanda GUEDES 1.1. Introduction 3 1.2. Measuring the criticality of raw materials and geopolitical risk 5 1.2.1. Criticality, strategic materials and risks 5 1.2.2. The absence of a homogeneous theoretical framework 6 1.2.3. Criticality matrices 7 1.3. The geopolitics and geo-economics of raw materials in the energy transition 11 1.3.1. From measuring pressures on reserves to taking geopolitics into account in measuring criticality 12 1.3.2. Fear of cartelization or monopoly in commodity markets 13 1.4. How can we manage strategic materials supply risk? 24 1.4.1. The role of public policies 25 1.4.2. The issue of strategic stocks 27 1.4.3. Foreign investment through national companies 28 1.4.4. The logic of the Chinese barter 30 1.5. Conclusion: toward a new resource nationalism? 30 1.6. References 32 Chapter 2. Legal Issues Regarding the Sustainable Management of Territorial and Extraterritorial Mineral Resources 39Stephanie REICHE-DE VIGAN 2.1. National law regarding territorial mineral resources: the decisive issue of ownership 42 2.1.1. Ownership over mineral resources at the core of mineral law 42 2.1.2. A form of mineral ownership that may limit the government’s capacity to regulate the extractive sector for environmental reasons 47 2.2. International law regarding territorial mineral resources: the central role of state sovereignty 52 2.2.1. The principle of permanent sovereignty over natural resources for the benefit of international trade 52 2.2.2. A principle challenged by indigenous peoples’ rights to lands, territories and resources 55 2.3. International law regarding extraterritorial mineral resources: exploitation “for the benefit of mankind as a whole” 56 2.3.1. The legal status of the seabed and the subsoil, determined by states’ interests in the exploitation of mineral resources 57 2.3.2. The legal framework for the exploitation of Antarctic mineral resources, determined by ecological considerations 63 2.4. For a sustainable management of mineral resources 65 2.5. References 68 Chapter 3. Mining and Societies 71Michel DESHAIES 3.1. Introduction 71 3.2. Mines as a factor of settlement and landscape transformation 72 3.2.1. Mining and the population 72 3.2.2. Mines, landscapes and the environment in pre-industrial times 74 3.3. Mining in the Industrial Age 76 3.3.1. The transformations of the industrial energy system 76 3.3.2. Birth and development of coalfields 78 3.3.3. Conquest and development of new metal deposits 79 3.4. Contemporary mining transformations and challenges 81 3.4.1. Geographic trends in mining 81 3.4.2. Decline and changes in former mining regions 82 3.4.3. Extraction boom and risks in new mining regions 85 3.4.4. The limits of “responsible” mining 92 3.5. Conclusion 95 3.6. References 96 Part 2. Action Levers 101 Chapter 4. Maintaining or Even Developing the Mining of Mineral Resources in Europe: The Case of Wallonia (Belgium) 103Johan YANS 4.1. Introduction 103 4.2. Geological resources in Wallonia 104 4.2.1. Extraction of mineral materials other than metals 104 4.2.2. Metal extraction: a problem on several spatiotemporal scales 105 4.3. Extension of sites/quantity of mining? 106 4.3.1. Exploit existing and well-characterized metal resources/reserves 106 4.3.2. Promoting a short circuit 107 4.3.3. Promoting alternatives to the sometimes deplorable extraction conditions in some regions of the world 108 4.3.4. Stimulating the local economy/employment 108 4.3.5. (Re)discovering a degree of supply independence for the industry 108 4.3.6. Creating the “substitution threat”: knowing that local potential exists 109 4.4. Decrease in sites/quantity of operations 109 4.4.1. Lack of local skills (being addressed) 109 4.4.2. NIMBY syndrome 110 4.5. Some levers for action 115 4.5.1. Responsible extraction 115 4.5.2. Popularizing 115 4.5.3. Strengthening the administration and defining a clear public strategy 116 4.5.4. Consulting 117 4.5.5. Collaborating (private–public) 118 4.6. Conclusion 118 4.7. References 119 Chapter 5. Substitution: Promises, Principles and Main Constraints 121Florian FIZAINE 5.1. Introduction 121 5.2. Main economic foundations of substitution 122 5.2.1. The demand curve 123 5.2.2. The horizons of substitution: short, medium and long term 124 5.2.3. The shortcomings of the classical demand curve 125 5.3. Elements, components, systems: what are we really substituting? 125 5.3.1. Altenpohl hierarchy and principal forms of technical substitution 126 5.3.2. Normative substitution: what to substitute for? 127 5.4. The main obstacles to substitution 129 5.4.1. Technical obstacles 129 5.4.2. Economic obstacles 130 5.4.3. Barriers related to the physical availability of the resource 131 5.4.4. Cultural and historical barriers 132 5.4.5. Regulatory barriers 133 5.5. Other aspects to be taken into account 134 5.5.1. Impact of competition and industrial strategies 134 5.5.2. Is economic substitution also an ecological substitution? 135 5.6. References 136 Chapter 6. Resource Consumption and Decoupling 139Thierry LEFÈVRE 6.1. Introduction 139 6.2. Global use of resources 142 6.3. Material consumption indicators 145 6.4. Decoupling the economy from resource consumption 149 6.4.1. Evidence of decoupling 149 6.4.2. Saturation of resource use 152 6.5. Responsibility for resource consumption 154 6.6. Conclusion 156 6.7. References 159 Chapter 7. The Economics of Recycling: Ambitions, Myths and Constraints 163Alain GELDRON 7.1. The recycling economy, an ancient history 163 7.2. Geological and urban mines, similarities and differences in logic 165 7.3. Understand the definitions and indicators of recycling in order to express its performance 167 7.4. A limited deposit because we can only recycle what we have consumed 170 7.5. Multiple factors influencing recycling and its effectiveness 173 7.6. The technical constraints of metal recycling 176 7.6.1. Preparation of materials 177 7.6.2. Recycling of base metals 178 7.6.3. Recycling of specialty metals 179 7.7. Environmental benefits of recycling 181 7.8. Conclusion 182 7.9. References 183 Chapter 8. Low-tech: A Path Toward the Necessary Metallic Sobriety? 187Philippe BIHOUIX 8.1. Cornucopians versus doomsdayers 187 8.2. The circular economy, mission impossible? 190 8.2.1. Invisible dematerialization 191 8.2.2. The systemic issue between energy and resources 193 8.2.3. The constraints of recycling 194 8.3. Toward a metallic frugality 195 8.3.1. Sobriety above all 196 8.3.2. “Advanced” eco-design 198 8.3.3. Moderate mechanization 199 8.4. A possible and desirable transition 200 8.4.1. The role of the public authority, at all scales 200 8.4.2. Finding the right scale 202 8.4.3. Humans, the key to “repairability” and optimal recycling 203 8.4.4. Positive impacts 204 8.4.5. A “happy” transition or nothing 205 8.5. References 206 Conclusion 209Florian FIZAINE and Xavier GALIÈGUE List of Authors 221 Index 223

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Book SynopsisGraph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of graph signal processing – extending traditional Fourier analysis tools such as transforms and wavelets to handle data on irregular graph kernels – provides new flexible computational tools to analyze and process these varied types of imaging data. Recent methods combine graph signal processing ideas with deep neural network architectures for enhanced performances, with robustness and smaller memory requirements.The book is divided into two parts. The first is centered on the fundamentals of graph signal processing theories, including graph filtering, graph learning and graph neural networks. The second part details several imaging applications using graph signal processing tools, including image and video compression, 3D image compression, image restoration, point cloud processing, image segmentation and image classification, as well as the use of graph neural networks for image processing.Table of ContentsIntroduction to Graph Spectral Image Processing xiGene CHEUNG and Enrico MAGLI Part 1. Fundamentals of Graph Signal Processing 1 Chapter 1. Graph Spectral Filtering 3Yuichi TANAKA 1.1. Introduction 3 1.2. Review: filtering of time-domain signals 4 1.3. Filtering of graph signals 5 1.3.1. Vertex domain filtering 6 1.3.2. Spectral domain filtering 8 1.3.3. Relationship between graph spectral filtering and classical filtering 10 1.4. Edge-preserving smoothing of images as graph spectral filters 11 1.4.1. Early works 11 1.4.2. Edge-preserving smoothing 12 1.5. Multiple graph filters: graph filter banks 15 1.5.1. Framework 16 1.5.2. Perfect reconstruction condition 17 1.6. Fast computation 20 1.6.1. Subdivision 20 1.6.2. Downsampling 21 1.6.3. Precomputing GFT 22 1.6.4. Partial eigendecomposition 22 1.6.5. Polynomial approximation 23 1.6.6. Krylov subspace method 26 1.7. Conclusion 26 1.8. References 26 Chapter 2. Graph Learning 31Xiaowen DONG, Dorina THANOU, Michael RABBAT and Pascal FROSSARD 2.1. Introduction 31 2.2. Literature review 33 2.2.1. Statistical models 33 2.2.2. Physically motivated models 35 2.3. Graph learning: a signal representation perspective 36 2.3.1. Models based on signal smoothness 38 2.3.2. Models based on spectral filtering of graph signals 43 2.3.3. Models based on causal dependencies on graphs 48 2.3.4. Connections with the broader literature 50 2.4. Applications of graph learning in image processing 52 2.5. Concluding remarks and future directions 55 2.6. References 57 Chapter 3. Graph Neural Networks 63Giulia FRACASTORO and Diego VALSESIA 3.1. Introduction 63 3.2. Spectral graph-convolutional layers 64 3.3. Spatial graph-convolutional layers 66 3.4. Concluding remarks 71 3.5. References 72 Part 2. Imaging Applications of Graph Signal Processing 73 Chapter 4. Graph Spectral Image and Video Compression 75Hilmi E. EGILMEZ, Yung-Hsuan CHAO and Antonio ORTEGA 4.1. Introduction 75 4.1.1. Basics of image and video compression 77 4.1.2. Literature review 78 4.1.3. Outline of the chapter 79 4.2. Graph-based models for image and video signals 79 4.2.1. Graph-based models for residuals of predicted signals 81 4.2.2. DCT/DSTs as GFTs and their relation to 1D models 87 4.2.3. Interpretation of graph weights for predictive transform coding 88 4.3. Graph spectral methods for compression 89 4.3.1. GL-GFT design 89 4.3.2. EA-GFT design 92 4.3.3. Empirical evaluation of GL-GFT and EA-GFT 97 4.4. Conclusion and potential future work 100 4.5. References 101 Chapter 5. Graph Spectral 3D Image Compression 105Thomas MAUGEY, Mira RIZKALLAH, Navid MAHMOUDIAN BIDGOLI, Aline ROUMY and Christine GUILLEMOT 5.1. Introduction to 3D images 106 5.1.1. 3D image definition 106 5.1.2. Point clouds and meshes 106 5.1.3. Omnidirectional images 107 5.1.4. Light field images 109 5.1.5. Stereo/multi-view images 110 5.2. Graph-based 3D image coding: overview 110 5.3. Graph construction 115 5.3.1. Geometry-based approaches 117 5.3.2. Joint geometry and color-based approaches 121 5.3.3. Separable transforms 125 5.4. Concluding remarks 126 5.5. References 128 Chapter 6. Graph Spectral Image Restoration 133Jiahao PANG and Jin ZENG 6.1. Introduction 133 6.1.1. A simple image degradation model 133 6.1.2. Restoration with signal priors 135 6.1.3. Restoration via filtering 137 6.1.4. GSP for image restoration 140 6.2. Discrete-domain methods 141 6.2.1. Non-local graph-based transform for depth image denoising 141 6.2.2. Doubly stochastic graph Laplacian 142 6.2.3. Reweighted graph total variation prior 145 6.2.4. Left eigenvectors of random walk graph Laplacian 150 6.2.5. Graph-based image filtering 155 6.3. Continuous-domain methods 155 6.3.1. Continuous-domain analysis of graph Laplacian regularization 156 6.3.2. Low-dimensional manifold model for image restoration 163 6.3.3. LDMM as graph Laplacian regularization 165 6.4. Learning-based methods 167 6.4.1. CNN with GLR 169 6.4.2. CNN with graph wavelet filter 171 6.5. Concluding remarks 172 6.6. References 173 Chapter 7. Graph Spectral Point Cloud Processing 181Wei HU, Siheng CHEN and Dong TIAN 7.1. Introduction 181 7.2. Graph and graph-signals in point cloud processing 183 7.3. Graph spectral methodologies for point cloud processing 185 7.3.1. Spectral-domain graph filtering for point clouds 185 7.3.2. Nodal-domain graph filtering for point clouds 188 7.3.3. Learning-based graph spectral methods for point clouds 189 7.4. Low-level point cloud processing 190 7.4.1. Point cloud denoising 191 7.4.2. Point cloud resampling 193 7.4.3. Datasets and evaluation metrics 198 7.5. High-level point cloud understanding 199 7.5.1. Data auto-encoding for point clouds 199 7.5.2. Transformation auto-encoding for point clouds 206 7.5.3. Applications of GraphTER in point clouds 211 7.5.4. Datasets and evaluation metrics 211 7.6. Summary and further reading 213 7.7. References 214 Chapter 8. Graph Spectral Image Segmentation 221Michael NG 8.1. Introduction 221 8.2. Pixel membership functions 222 8.2.1. Two-class problems 222 8.2.2. Multiple-class problems 226 8.2.3. Multiple images 227 8.3. Matrix properties 230 8.4. Graph cuts 232 8.4.1. The Mumford–Shah model 234 8.4.2. Graph cuts minimization 235 8.5. Summary 237 8.6. References 237 Chapter 9. Graph Spectral Image Classification 241Minxiang YE, Vladimir STANKOVIC, Lina STANKOVIC and Gene CHEUNG 9.1. Formulation of graph-based classification problems 243 9.1.1. Graph spectral classifiers with noiseless labels 243 9.1.2. Graph spectral classifiers with noisy labels 246 9.2. Toward practical graph classifier implementation 247 9.2.1. Graph construction 247 9.2.2. Experimental setup and analysis 249 9.3. Feature learning via deep neural network 255 9.3.1. Deep feature learning for graph construction 258 9.3.2. Iterative graph construction 260 9.3.3. Toward practical implementation of deep feature learning 262 9.3.4. Analysis on iterative graph construction for robust classification 267 9.3.5. Graph spectrum visualization 269 9.3.6. Classification error rate comparison using insufficient training data 270 9.3.7. Classification error rate comparison using sufficient training data with label noise 270 9.4. Conclusion 271 9.5. References 272 Chapter 10. Graph Neural Networks for Image Processing 277Giulia FRACASTORO and Diego VALSESIA 10.1. Introduction 277 10.2. Supervised learning problems 278 10.2.1. Point cloud classification 278 10.2.2. Point cloud segmentation 281 10.2.3. Image denoising 283 10.3. Generative models for point clouds 286 10.3.1. Point cloud generation 286 10.3.2. Shape completion 291 10.4. Concluding remarks 294 10.5. References 294 List of Authors 299 Index 301

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Book SynopsisThe Internet of Things (IoT) has contributed greatly to the growth of data traffic on the Internet. Access technologies and object constraints associated with the IoT can cause performance and security problems. This relates to important challenges such as the control of radio communications and network access, the management of service quality and energy consumption, and the implementation of security mechanisms dedicated to the IoT.In response to these issues, this book presents new solutions for the management and control of performance and security in the IoT. The originality of these proposals lies mainly in the use of intelligent techniques. This notion of intelligence allows, among other things, the support of object heterogeneity and limited capacities as well as the vast dynamics characterizing the IoT.Table of ContentsChapter 1 Multicriteria Selection of Transmission Parameters in the IoT 1Sinda BOUSSEN, Mohamed-Aymen CHALOUF and Francine KRIEF 1.1 Introduction 1 1.2 Changing access network in the IoT 2 1.3 Spectrum handoff in the IoT 3 1.4 Multicriteria decision-making module for an effective spectrum handoff in the IoT 4 1.4.1 General architecture 4 1.4.2 Decision-making flowchart 9 1.4.3 Performances evaluation 15 1.5 Conclusion 22 1.6 References 22 Chapter 2 Using Reinforcement Learning to Manage Massive Access in NB-IoT Networks 27Yassine HADJADJ-AOUL and Soraya AIT-CHELLOUCHE 2.1 Introduction 27 2.2 Fundamentals of the NB-IoT standard 29 2.2.1 Deployment and instances of use 29 2.2.2 Transmission principles 30 2.2.3 Radio resource random access procedure 33 2.3 State of the art 37 2.4 Model for accessing IoT terminals 39 2.5 Access controller for IoT terminals based on reinforcement learning 42 2.5.1 Formulating the problem 42 2.5.2 Regulation system for arrivals 44 2.6 Performance evaluation 46 2.7 Conclusion 51 2.8 References 51 Chapter 3 Optimizing Performances in the IoT: An Approach Based on Intelligent Radio 57Badr BENMAMMAR 3.1 Introduction 57 3.2 Internet of Things (IoT) 58 3.2.1 Definition of the IoT 58 3.2.2 Applications of the IoT 59 3.2.3 IoT challenges 60 3.2.4 Enabling technologies in the IoT 61 3.3 Intelligent radio 64 3.3.1 Definition of intelligent radio 64 3.3.2 Motivations for using intelligent radio in the IoT 66 3.3.3 Challenges in using intelligent radio in the IoT 68 3.4 Conclusion 71 3.5 References 73 Chapter 4 Optimizing the Energy Consumption of IoT Devices 77Ahmad KHALIL, Nader MBAREK and Olivier TOGNI 4.1 Introduction 77 4.2 Energy optimization 78 4.2.1 Definitions 78 4.3 Optimization techniques for energy consumption 79 4.3.1 The A* algorithm 79 4.3.2 Fuzzy logic 80 4.4 Energy optimization in the IoT 82 4.4.1 Characteristics of the IoT 82 4.4.2 Challenges in energy optimization 84 4.4.3 Research on energy optimization in the IoT 84 4.5 Autonomous energy optimization framework in the IoT 86 4.5.1 Autonomous computing 86 4.5.2 Framework specification 89 4.6 Proposition of a self-optimization method for energy consumption in the IoT 90 4.6.1 Fuzzy logic model 91 4.6.2 Decision-making algorithm 95 4.6.3 Evaluating energy self-optimization in the IoT 97 4.7 Conclusion 101 4.8 References 101 Chapter 5 Toward Intelligent Management of Service Quality in the IoT: The Case of a Low Rate WPAN 105Guillaume LE GALL, Georgios Z PAPADOPOULOS, Mohamed-Aymen CHALOUF and Olivier TOGNI 5.1 Introduction 106 5.2 Quick overview of the IoT 108 5.2.1 The micro-IPv6 stack 108 5.2.2 Technologies for the IoT 110 5.2.3 IoT and quality of service 114 5.3 IEEE 802.15.4 TSCH approach 115 5.4 Transmission scheduling 117 5.4.1 General considerations 117 5.4.2 Scheduling in the literature 118 5.5 Routing and RPL 120 5.5.1 Routing 120 5.5.2 RPL 121 5.5.3 Multipath 122 5.6 Combined approach based on 802.15.4 TSCH and multipath RPL 123 5.6.1 Automatic Repeat reQuest 125 5.6.2 Replication and Elimination 125 5.6.3 Overhearing 127 5.7 Conclusion 127 5.8 References 128 Chapter 6 Adapting Quality of Service of Energy-Harvesting IoT Devices 133Matthieu GAUTIER and Olivier BERDER 6.1 Toward the energy autonomy of sensor networks 135 6.1.1 Energy harvesting and management 135 6.1.2 State-of-the-art energy managers 138 6.2 Fuzzyman: use of fuzzy logic 141 6.2.1 Design of Fuzzyman 141 6.2.2 Evaluating Fuzzyman 145 6.2.3 Conclusion 146 6.3 RLMan: using reinforcement learning 148 6.3.1 Formulating the problem of managing the harvested energy 148 6.3.2 RLMan algorithm 150 6.3.3 Evaluation of RLMan 153 6.3.4 Conclusion 155 6.4 Toward energy autonomous LoRa nodes 155 6.4.1 Multisource energy-harvesting architecture 157 6.4.2 Applying energy management to LoRa nodes 157 6.5 Conclusion 157 6.6 References 160 Chapter 7 Adapting Access Control for IoT Security 163Ahmad KHALIL, Nader MBAREK and Olivier TOGNI 7.1 Introduction 163 7.2 Defining security services in the IoT 164 7.2.1 Identification and authentication in the IoT 164 7.2.2 Access control in the IoT 165 7.2.3 Confidentiality in the IoT 166 7.2.4 Integrity in the IoT 166 7.2.5 Non-repudiation in the IoT 167 7.2.6 Availability in the IoT 167 7.3 Access control technologies 168 7.4 Access control in the IoT 172 7.4.1 Research on the extension of access control models for the IoT 172 7.4.2 Research on adapting access control systems and technologies for the IoT 173 7.5 Access control framework in the IoT 176 7.5.1 IoT architecture 177 7.5.2 IoT-MAAC access control specification 179 7.6 Conclusion 193 7.7 References 194 Chapter 8 The Contributions of Biometrics and Artificial Intelligence in Securing the IoT 197Amal SAMMOUD, Omessaad HAMDI, Mohamed-Aymen CHALOUF and Nicolas MONTAVONT 8.1 Introduction 197 8.2 Security and privacy in the IoT 198 8.3 Authentication based on biometrics 199 8.3.1 Biometrics 199 8.3.2 Biometric techniques 199 8.3.3 The different properties of biometrics 200 8.3.4 Operating a biometric system 201 8.3.5 System performances 202 8.4 Multifactor authentication techniques based on biometrics 202 8.4.1 Multifactor authentication 203 8.4.2 Examples of multifactor authentication approaches for securing the IoT 204 8.4.3 Presentation of the approach of Sammoud et al (2020c) 205 8.5 Authentication techniques based on biometrics and machine learning 213 8.5.1 Machine learning algorithms 213 8.5.2 Examples of authentication approaches based on biometrics and machine learning 214 8.5.3 Authentication approaches based on ECG and machine learning 215 8.6 Challenges and limits 217 8.6.1 Quality of biometric data 217 8.6.2 Non-revocability of biometric data 218 8.6.3 Security of biometric systems 218 8.7 Conclusion 218 8.8 References 218 Chapter 9 Dynamic Identity and Access Management in the IoT: Blockchain-based Approach 223Léo MENDIBOURE, Mohamed-Aymen CHALOUF and Francine KRIEF 9.1 Introduction 223 9.2 Context 224 9.2.1 Intelligent identity and access management 225 9.2.2 Blockchain 226 9.3 Blockchain for intelligent identity and access management 227 9.3.1 A new architecture integrating blockchain 228 9.3.2 The different benefits 229 9.4 Challenges 234 9.4.1 Scaling up 235 9.4.2 Blockchain security 235 9.4.3 Energy consumption 236 9.4.4 Definition of consensus algorithms based on artificial intelligence 236 9.5 Conclusion 237 9.6 References 237 Chapter 10 Adapting the Security Level of IoT Applications 243Tidiane SYLLA, Mohamed-Aymen CHALOUF and Francine KRIEF 10.1 Introduction 243 10.2 Definitions and characteristics 244 10.2.1 Definitions 244 10.2.2 Characteristics 244 10.3 IoT applications 246 10.4 IoT architectures 246 10.5 Security, trust and privacy protection in IoT applications 247 10.5.1 General remarks 248 10.5.2 Security services 248 10.5.3 Communication security 251 10.5.4 Trust 252 10.5.5 Privacy 253 10.6 Adapting the security level in the IoT 254 10.6.1 Context-awareness 255 10.6.2 Context-aware security 256 10.6.3 Context-aware security architecture and privacy protection designed using the “as a service” approach 258 10.7 Conclusion 261 10.8 References 261 Chapter 11 Moving Target Defense Techniques for the IoT 267Renzo E NAVAS, Laurent TOUTAIN and Georgios Z PAPADOPOULOS 11.1 Introduction 268 11.2 Background 269 11.2.1 Brief chronology of Moving Target Defense 269 11.2.2 Fundamental technical and taxonomic principles of MTD 270 11.3 Related works 271 11.3.1 Surveys on MTD techniques 271 11.3.2 Frameworks for IoT systems linked to the concept of MTD 271 11.4 LMTD for the IoT: a qualitative survey 272 11.4.1 Data: MTD mechanism against side-channel channel attacks based on renegotiating cryptographic keys 272 11.4.2 Software 272 11.4.3 Runtime environment 273 11.4.4 Platform: diversifying by reconfiguring the IoT node firmware 275 11.4.5 Networks 275 11.4.6 Section summary 278 11.5 Network components in the IoT: a vast domain for MTD 279 11.5.1 Physical layer 280 11.5.2 Link layer 281 11.5.3 OSI network layer 281 11.5.4 Transport layer 282 11.5.5 Application layer 283 11.5.6 Section summary 284 11.6 An MTD framework for the IoT 284 11.6.1 Proposition: components 284 11.6.2 Instantiation: UDP port hopping 286 11.7 Discussion and avenues for future research 287 11.8 Conclusion 288 11.9 References 288 List of Authors 293 Index 295

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Book SynopsisFace analysis is essential for a large number of applications such as human-computer interaction or multimedia (e.g. content indexing and retrieval). Although many approaches are under investigation, performance under uncontrolled conditions is still not satisfactory. The variations that impact facial appearance (e.g. pose, expression, illumination, occlusion, motion blur) make it a difficult problem to solve.This book describes the progress towards this goal, from a core building block – landmark detection – to the higher level of micro and macro expression recognition. Specifically, the book addresses the modeling of temporal information to coincide with the dynamic nature of the face. It also includes a benchmark of recent solutions along with details about the acquisition of a dataset for such tasks.Table of ContentsPreface xiRomain BELMONTE and Benjamin ALLAERT Part 1. Facial Landmark Detection 1 Introduction to Part 1 3Romain BELMONTE, Pierre TIRILLY, IoanMarius BILASCO, Nacim IHADDADENE and Chaabane DJERABA Chapter 1. Facial Landmark Detection 13Romain BELMONTE, Pierre TIRILLY, IoanMarius BILASCO, Nacim IHADDADENE and Chaabane DJERABA 1.1. Facial landmark detection in still images 14 1.1.1.Generativeapproaches 14 1.1.2.Discriminative approaches 18 1.1.3.Deep learningapproaches 24 1.1.4.Handlingchallenges 34 1.1.5.Summary 40 1.2.Extendingfacial landmarkdetectionto videos 41 1.2.1.Trackingby detection 41 1.2.2.Box, landmarkand pose tracking 43 1.2.3.Adaptive approaches 45 1.2.4. Joint approaches 46 1.2.5. Temporal constrained approaches 47 1.2.6.Summary 49 1.3.Discussion 50 1.4.References 52 Chapter 2. Effectiveness of Facial Landmark Detection 67Romain BELMONTE, Pierre TIRILLY, IoanMarius BILASCO, Nacim IHADDADENE and Chaabane DJERABA 2.1.Overview 68 2.2.Datasets and evaluationmetrics 69 2.2.1. Image and videodatasets 69 2.2.2. Face preprocessing and data augmentation 73 2.2.3.Evaluationmetrics 75 2.2.4.Summary 77 2.3. Image andvideobenchmarks 77 2.3.1. Compiled results on 300W 77 2.3.2. Compiled results on 300VW 79 2.4.Cross-dataset benchmark 80 2.4.1.Evaluationprotocol 80 2.4.2.Comparisonof selected approaches 82 2.5.Discussion 86 2.6.References 88 Chapter 3. Facial Landmark Detection with Spatio-temporal Modeling 93Romain BELMONTE, Pierre TIRILLY, IoanMarius BILASCO, Nacim IHADDADENE and Chaabane DJERABA 3.1.Overview 94 3.2.Spatio-temporalmodelingreview 95 3.2.1.Hand-craftedapproaches 95 3.2.2.Deep learningapproaches 97 3.2.3.Summary 103 3.3.Architecturedesign 104 3.3.1. Coordinate regression networks 104 3.3.2.Heatmapregressionnetworks 106 3.4.Experiments 107 3.4.1.Datasets andevaluationprotocols 107 3.4.2. Implementationdetails 108 3.4.3.EvaluationonSNaP-2DFe 109 3.4.4. Evaluation on 300VW 111 3.4.5.Comparisonwith existingmodels 112 3.4.6. Qualitative results 112 3.4.7.Propertiesof the networks 114 3.5.Design investigations 114 3.5.1.Encoder-decoder 115 3.5.2. Complementarity between spatial and temporal information 117 3.5.3. Complementarity between local and global motion 119 3.6.Discussion 122 3.7.References 123 Conclusion to Part 1 133Romain BELMONTE, Pierre TIRILLY, IoanMarius BILASCO, Nacim IHADDADENE and Chaabane DJERABA Part 2. Facial Expression Analysis 147 Introduction to Part 2 149Benjamin ALLAERT, IoanMarius BILASCO and Chaabane DJERABA Chapter 4. Extraction of Facial Features 157Benjamin ALLAERT, IoanMarius BILASCO and Chaabane DJERABA 4.1. Introduction 157 4.2.Face detection 158 4.2.1.Point-of-interestdetectionalgorithms 160 4.2.2.Face alignment approaches 162 4.2.3.Synthesis 166 4.3.Face normalization 166 4.3.1.Dealingwith headpose variations 167 4.3.2.Dealingwith facial occlusions 170 4.3.3.Synthesis 172 4.4.Extractionof visual features 172 4.4.1.Facial appearancefeatures 172 4.4.2.Facial geometric features 174 4.4.3. Facial dynamics features 175 4.4.4.Facial segmentationmodels 177 4.4.5.Synthesis 179 4.5. Learning methods 179 4.5.1.Classification versus regression 180 4.5.2.Fusionmodel 182 4.5.3.Synthesis 184 4.6.Conclusion 185 4.7.References 186 Chapter 5. Facial Expression Modeling 191Benjamin ALLAERT, IoanMarius BILASCO and Chaabane DJERABA 5.1. Introduction 191 5.2.Modelingof the affective state 192 5.2.1.Categoricalmodeling 192 5.2.2.Dimensionalmodeling 194 5.2.3.Synthesis 196 5.3. The challenges of facial expression recognition 197 5.3.1. The variation of the intensity of the expressions 197 5.3.2.Variationof facialmovement 199 5.3.3.Synthesis 200 5.4.The learningdatabases 201 5.4.1. Improvementof learningdata 201 5.4.2. Comparison of learning databases 203 5.4.3.Synthesis 205 5.5. Invariance to facial expression intensities 206 5.5.1.Macro-expression 206 5.5.2.Micro-expression 208 5.5.3.Synthesis 209 5.6. Invarianceto facialmovements 211 5.6.1. Pose variations (PV) and large displacements (LD) 211 5.6.2.Synthesis 214 5.7.Conclusion 215 5.8.References 216 Chapter 6. Facial Motion Characteristics 223Benjamin ALLAERT, IoanMarius BILASCO and Chaabane DJERABA 6.1. Introduction 223 6.2.Characteristics of the facialmovement 225 6.2.1. Local constraint of magnitude and direction 226 6.2.2. Local constraint of the motion distribution 228 6.2.3.Motionpropagationconstraint 230 6.3.LMP 232 6.3.1. Local consistency of the movement 233 6.3.2.Consistencyof local distribution 236 6.3.3. Coherence in the propagationof themovement 238 6.4.Conclusion 241 6.5.References 242 Chapter 7. Micro- and Macro-Expression Analysis 243Benjamin ALLAERT, IoanMarius BILASCO and Chaabane DJERABA 7.1. Introduction 243 7.2. Definition of a facial segmentation model 244 7.3.Feature vector construction 247 7.3.1.Motionfeaturesvector 247 7.3.2.Geometric featuresvector 248 7.3.3.Features fusion 249 7.4. Recognition process 250 7.5. Evaluation on micro- and macro-expressions 251 7.5.1.Learningdatabases 252 7.5.2. Micro-expression recognition 253 7.5.3. Macro-expressions recognition 255 7.5.4. Synthesis of experiments on micro- and macro-expressions 258 7.6. Same expression with different intensities 260 7.6.1.Data preparation 260 7.6.2.Fractional time analysis 263 7.6.3.Analysis on a different time frame 264 7.6.4. Synthesis of experiments on activation segments 265 7.7.Conclusion 265 7.8.References 266 Chapter 8. Towards Adaptation to Head Pose Variations 271Benjamin ALLAERT, IoanMarius BILASCO and Chaabane DJERABA 8.1. Introduction 271 8.2.Learningdatabase challenges 273 8.3. Innovative acquisition system (SNaP-2DFe) 274 8.4. Evaluation of face normalization methods 276 8.4.1. Does the normalization preserve the facial geometry? 277 8.4.2. Does normalization preserve facial expressions? 280 8.5.Conclusion 283 8.6.References 284 Conclusion to Part 2 287Benjamin ALLAERT, IoanMarius BILASCO and Chaabane DJERABA List of Authors 293 Index 295

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Book SynopsisA major transformation in the world of networks is underway, as the focus shifts from physical technology to software-based solutions. In this book, the authors present this new generation of networks that are based in the Cloud by detailing the transition from a complex environment to a simple digital infrastructure. This infrastructure brings together connected devices, the antennas that collect radio waves, the optical fibers that carry signals and the data center that handles all of the different processes. From this perspective, the data center becomes the brain, managing network services, controls, automation, intelligence, security and other applications. This architecture is relevant to carrier networks, the Internet of Things, enterprise networks and the global networks of the major Internet companies. Cloud and Edge Networking further discusses developments at the border of networks, the Edge, where data is processed as near as possible to the source. Over the next ten years, the Edge will become a major strategic factor.Table of ContentsPreface xi Chapter 1 Introduction to Edge and Cloud Networking 1 1.1 Introduction to the digital infrastructure 1 1.2 Cloud services 7 1.3 Cloud Networking 9 1.4 Network Functions Virtualization 14 1.5 Conclusion 16 1.6 References 16 Chapter 2 The Cloud Continuum 19 2.1 Cloud Continuum levels 19 2.2 Cloud Continuum Networks 22 2.3 The Cloud Continuum and the digitization of companies 23 2.4 Example of digital infrastructure 25 2.5 Conclusion 28 2.6 References 28 Chapter 3 Digital Infrastructure Architecture 31 3.1 The evolution of enterprise information system architectures 31 3.2 The Open Infrastructure Foundation architecture 36 3.3 The Cloud Native Computing Foundation architecture 42 3.4 Gaia-X 49 3.5 Conclusion 54 3.6 References 54 Chapter 4 Open-Source Architectures for Edge and Cloud Networking 57 4.1 Organizations and the main open sources 57 4.2 The main open-source projects 57 4.3 Conclusion 69 4.4 References 70 Chapter 5 Software-Defined Networking (SDN) 73 5.1 Introduction to Software-Defined Networking 73 5.2 ONF architecture 74 5.3 Southbound interfaces and controllers 80 5.4 The northbound interface and the application plan 82 5.5 Conclusion 84 5.6 References 85 Chapter 6 Edge and Cloud Networking Commercial Products 87 6.1 Introduction to SDN products 87 6.2 Fabric control 87 6.2.1 NSX from VMware 89 6.2.2 Cisco Application Centric Infrastructure 92 6.2.3 OpenContrail and Juniper 94 6.2.4 Nokia SDN Architecture 95 6.3 Software-Defined Wide Area Network 96 6.3.1 The basics of SD-WAN 96 6.3.2 SD-WAN 2.0 101 6.3.3 SD-Branch 102 6.4 Secure Access Service Edge 103 6.5 Virtual Customer Premises Equipment 105 6.6 vWi-Fi 107 6.7 Virtual Radio Access Network 109 6.8 Virtual Evolved Packet Core and virtual 5GCore 110 6.9 Conclusion 111 6.10 References 111 Chapter 7 OpenFlow, P4, Opflex and I2RS 113 7.1 OpenFlow signaling 113 7.2 P4 120 7.3 OpFlex 121 7.4 I2RS 122 7.5 Conclusion 123 7.6 References 124 Chapter 8 Edge and Cloud Networking Operators 127 8.1 Edge Networking in 5G architecture 127 8.2 Cloud RAN 130 8.3 Cloud Networking at the heart of 5G 132 8.4 The Cloud and the new Ethernet and Wi-Fi generations 134 8.5 Enterprise 5G Edge Networks 136 8.6 Conclusion 138 8.7 References 138 Chapter 9 Cloud Networking Protocols 141 9.1 Low-level protocols 142 9.1.1 Radio over Fiber 143 9.1.2 Ethernet over Fiber 144 9.2 Virtual extensible LAN 144 9.3 Network Virtualization using Generic Routing Encapsulation 146 9.4 Ethernet MEF 146 9.5 Ethernet Carrier Grade 147 9.6 Transparent Interconnection of Lots of Links 150 9.7 Locator/Identifier Separation Protocol 152 9.8 Conclusion 153 9.9 References 153 Chapter 10 Edge and Cloud Networking in the IoT 155 10.1 Internet of Things networks 156 10.2 Low Power Wide Area Networks 158 10.3 PAN and LAN networks for the IoT 162 10.4 Telecommunications operator networks for the IoT 166 viii Cloud and Edge Networking 10.5 Platform for the IoT 169 10.6 Conclusion 178 10.7 References 178 Chapter 11 Cloud Continuum in Vehicular Networks 181 11.1 ETSI ITS-G5 183 11.2 5G standardization 185 11.2.1 5G vehicular networks 185 11.2.2 C-V2X technology overview 187 11.3 Visible light communication 189 11.4 The architecture of vehicular networks 190 11.5 Conclusion 193 11.6 References 193 Chapter 12 The Cloud Continuum and Industry 4.0 199 12.1 The features needed to achieve Industry 4.0 201 12.2 Technical specifications for 5G 203 12.3 Cloud and Edge for Industry 4.0 205 12.4 Conclusion 207 12.5 References 208 Chapter 13 AI for Cloud and Edge Networking 211 13.1 The knowledge plane 211 13.2 Artificial intelligence and Software-Defined Networking 214 13.3 AI and Cloud Networking management 217 13.4 AI through digital twins 218 13.5 Conclusion 221 13.6 References 223 Chapter 14 Cloud and Edge Networking Security 229 14.1 The Security Cloud 229 14.2 SIM-based security 230 14.3 Blockchain and Cloud 233 14.4 Cloud Networking security 234 14.5 Edge Networking security 241 14.5.1 Security of 5G MEC 241 14.5.2 Threats to Network Functions Virtualization 242 14.5.3 Fog security 243 14.5.4 Protection of intelligent processes in the Edge 244 14.5.5 Client security through the use of HSM 245 14.6 Conclusion 246 14.7 References 247 Chapter 15 Accelerators 253 15.1 The DPDK accelerator 254 15.2 The FD.io accelerator 258 15.3 Hardware virtualization 260 15.4 Conclusion 263 15.5 References 263 Chapter 16 The Future of Edge and Cloud Networking 267 16.1 5G continuity 269 16.2 Fully distributed networks 272 16.3 Cloud Continuum-based networks 275 16.4 Edge and Cloud properties 276 16.5 Conclusion 278 16.6 References 278 Conclusion 283 List of Authors 285 Index 287

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Book SynopsisHow can atmospheric variables such as temperature, wind, rain and ozone be measured by satellites? How are these measurements taken and what has been learned since the first measurements in the 1970s? What data are currently available and what data are expected in the future? The second volume of this encyclopedic book presents each field of application – meteorology, atmospheric composition and climate – with its main aims as well as the specific areas which can be addressed through the use of satellite remote sensing. This book presents the satellite products used for operational purposes as well as those that allow for the advancement of scientific knowledge. The instruments that are at their origin are described, as well as the processing, delivery times and the knowledge they provide. This book is completed by a glossary and appendices with a list of supporting instruments already in use.Table of ContentsAcknowledgments xiii List of Acronyms xv Introduction xxxiiiThierry PHULPIN Part 1 Meteorology 1 Introduction to Part 1 3Hervé ROQUET Chapter 1 Operational Sounding of Thermodynamic Variables in the Atmosphere 9Thomas AUGUST 1.1 Introduction 9 1.2 Operational use of TIR and MW sounders 11 1.2.1 Satisfying ever-more demanding users 11 1.2.2 Clouds: an obstacle to sounding and a very useful geophysical product 17 1.2.3 Demonstrating and maintaining product quality 19 1.2.4 Different operational algorithmic strategies 22 1.2.5 Application perspectives 25 1.3 Acknowledgments 26 1.4 References 27 Chapter 2 Wind Observations 31Régis BORDE and Jean PAILLEUX 2.1 Introduction 31 2.2 AMVs 34 2.2.1 Extraction of AMVs 34 2.2.2 Current production and outlook 35 2.3 3D winds derived from hyperspectral sounders 37 2.4 Measuring wind from space using Doppler lidar 39 2.4.1 Introduction 39 2.4.2 Measurements from ALADIN lidar onboard Aeolus 40 2.4.3 Culmination of a long process 41 2.4.4 Situation in 2022 and outlook 42 2.5 References 43 Chapter 3 Surface Variables 47Jean-François MAHFOUF 3.1 Observation of the Earth’s surface from space 47 3.2 Energy balances at the surface and at the top of the atmosphere 49 3.3 Ocean surfaces 50 3.3.1 Surface temperature 50 3.3.2 Surface wind 52 3.3.3 Sea ice 54 3.4 Continental surfaces 56 3.4.1 Surface temperature 56 3.4.2 Water content of soil 57 3.4.3 Surface albedo 61 3.4.4 Vegetation properties 62 3.5 Snow-covered surfaces 64 3.5.1 Spatial coverage and albedo 64 3.5.2 Equivalent water content 65 3.6 Expected changes 65 3.7 References 66 Chapter 4 The Assimilation of Satellite Data in Numerical Weather Prediction Systems 69Bill BELL, Jean-Noël THÉPAUT and John EYRE 4.1 Introduction 69 4.2 Early meteorological satellites 71 4.3 Assimilation of satellite soundings 1970–2000 71 4.3.1 Early sounding instruments 71 4.3.2 Assimilation experience: 1970s 73 4.3.3 Assimilation experience: early 1980s 73 4.3.4 Problems arising in the late 1980s 74 4.4 Relevant aspects of data assimilation theory 75 4.5 The modern era (2000 to present) 77 4.5.1 Assimilation strategies 77 4.5.2 Advanced infrared sounders 79 4.5.3 Microwave sounders and imagers 81 4.5.4 Radiative transfer modeling 83 4.5.5 Observation uncertainties 83 4.5.6 Atmospheric motion vectors (AMVs) 84 4.5.7 Scatterometers 86 4.5.8 Radio occultation observations 87 4.5.9 Impacts 89 4.5.10 Reanalyses 91 4.6 Summary and conclusion 91 4.7 References 92 Chapter 5 Nowcasting 97Thibaut MONTMERLE 5.1 Introduction 97 5.2 Satellite data for nowcasting 99 5.2.1 Polar-orbiting satellites 99 5.2.2 Geostationary satellites 100 5.3 Observed phenomena 104 5.3.1 Air mass instability 104 5.3.2 Convective systems 104 5.3.3 Characteristics of clouds 108 5.3.4 Hydrometeors 109 5.3.5 Wind 110 5.4 Nowcasting of detected phenomena 111 5.4.1 Method based on the tracking of structures 111 5.4.2 Method based on image extrapolation 112 5.4.3 Method based on artificial intelligence 112 5.4.4 Use of numerical forecasting 114 5.4.5 OBS-NWP fusion 115 5.4.6 Probabilistic forecast 115 5.5 Perspectives 116 5.6 References 116 Chapter 6 Observation and Monitoring of Tropical Cyclones from Space 119Frank ROUX 6.1 Introduction 119 6.2 Visible and infrared imagery 120 6.3 Microwave imaging 122 6.4 Microwave sounding 125 6.5 Surface wind measurements 126 viii Satellites for Atmospheric Sciences 2 6.6 Ocean parameters 130 6.7 Climatology of cyclones 131 6.8 Conclusion 132 6.9 References 133 Part 2 Atmospheric Composition 137 Introduction to Part 2 Air Composition and the Contribution from Satellite Observations 139Thierry PHULPIN and Claude CAMY-PEYRET Chapter 7 Reactive Tropospheric Chemistry 143Sarah SAFIEDDINE and Camille VIATTE 7.1 Introduction 143 7.2 Methane 144 7.3 Reactive organic species 144 7.3.1 Isoprene 146 7.3.2 Other non-methane volatile organic compounds 146 7.4 Reactive inorganic species 148 7.5 Conclusion 150 7.6 Acknowledgment 150 7.7 References 150 Chapter 8 Major Pollutants: Ozone and Fine Particulate Matter 153Juan CUESTA and Gaëlle DUFOUR 8.1 Introduction 153 8.2 Tropospheric ozone 154 8.2.1 Beginnings of satellite-based tropospheric ozone observations 154 8.2.2 Current capabilities for tropospheric ozone monitoring 155 8.2.3 Multi-wavelength synergy for ozone pollution monitoring 157 8.3 Pollution aerosols 158 8.3.1 Optical thickness of pollution aerosols 159 8.3.2 Altitude of pollution aerosols 161 8.4 References 163 Chapter 9 Desert Dust 167Juan CUESTA 9.1 Introduction 167 9.2 Qualitative satellite detection of desert dust 168 9.3 Satellite observation of the optical depth of desert dust 170 9.4 Vertical profiles of desert dust by spaceborne lidar 171 9.5 3D distribution of desert dust by infrared spectrometer 173 9.6 Conclusion 175 9.7 References 176 Chapter 10 Species Emitted by Fires 179Camille VIATTE and Pasquale SELLITTO 10.1 Introduction 179 10.2 Biomass burning gases 181 10.2.1 Greenhouses gases 181 10.2.2 Carbon monoxide (CO) 181 10.2.3 Volatile organic compounds (VOCs) 182 10.2.4 Ammonia (NH3) 183 10.2.5 Nitrous acid (HONO) 183 10.3 Biomass burning aerosols 183 10.3.1 AOD observations with nadir-viewing instruments 183 10.3.2 Extinction observations with limb-viewing instruments 184 10.3.3 Lidar profiles observations 184 10.4 Fire detection systems from space 184 10.5 Conclusion 185 10.6 Acknowledgments 185 10.7 References 185 Chapter 11 Stratospheric Chemistry 189Claude CAMY-PEYRET and Sarah SAFIEDDINE 11.1 Introduction 189 11.2 Stratospheric ozone chemistry 189 11.2.1 Polar ozone depletion 190 11.2.2 Antarctic ozone distribution 192 11.2.3 Arctic ozone distribution 193 11.3 Stratospheric chemistry of other species 193 11.3.1 Chemistry of the stratosphere and models 194 11.3.2 Radical processes and cycles for the major families 196 11.3.3 The example of methane in the stratosphere 197 11.4 Satellite measurements of trace species in the stratosphere 198 11.5 Conclusion 200 11.6 Acknowledgments 200 11.7 References 200 Part 3 Atmosphere and climate 203 Introduction to Part 3 Atmosphere and Climate and the Contribution of Space 205Paul POLI Chapter 12 Climate Monitoring 209Paul POLI and Jörg SCHULZ 12.1 General concepts about the climate 209 12.1.1 What is climate? 209 12.1.2 Is climate limited to atmospheric phenomena? 211 12.1.3 A question for Nobel Prize laureates: is the climate stable? 213 12.2 From space-based measurements to climate products 215 12.2.1 Sensing the environment 215 12.2.2 The role of space-based observations 217 12.2.3 The concept of essential climate variables 218 12.2.4 Observation-based products 220 12.2.5 Model-assisted climate products 221 12.3 Climate data records and uncertainty estimates 223 12.3.1 Why reprocessing? 223 12.3.2 Calibration 224 12.3.3 Uncertainty 226 12.4 The usage of climate data records in science and services 228 12.5 Looking ahead 230 12.6 References 231 12.7 References of the data sources cited in Figure 12.1 232 Chapter 13 Anthropogenic Greenhouse Gases: CO2 and CH4 235Cyril CREVOISIER 13.1 Monitoring anthropogenic greenhouse gases 236 13.1.1 Biogeochemical cycles 236 13.1.2 Determination of gas sources and sinks 236 13.1.3 The global observation network 237 13.2 Contribution of spatial observation of greenhouse gases 238 13.2.1 Specificities of greenhouse gas observation 238 13.2.2 Particularly rich spatial programming 241 13.3 Measurement techniques 242 13.3.1 Passive observations in the infrared range 243 13.3.2 Passive observations by solar reflection 245 13.3.3 Passive observations by solar occultation 247 13.3.4 Active observations using lidar 247 13.4 From radiation measurement to gas flux at the surface 248 13.4.1 From radiation measurement to gas concentrations 248 13.4.2 From concentration to fluxes 250 13.4.3 Main limitations 251 13.5 Challenges for the future 252 13.5.1 Towards the observation of anthropogenic emissions by spatial imagery 253 13.5.2 Reducing spatio-temporal sampling biases 253 13.5.3 Towards an operational greenhouse gas monitoring service 254 13.6 References 255 Chapter 14 Clouds and Water Vapor 259Hélène BROGNIEZ, Laurence PICON and Dominique BOUNIOL 14.1 Atmospheric water cycle and climate 259 14.2 Observations of water vapor 260 14.2.1 Passive sensors 263 14.2.2 Active sensors 265 14.2.3 Homogenization and intercomparison 266 14.3 Observation of cloud properties 267 14.3.1 Observations using passive instruments 270 14.3.2 Observations using active instruments 273 14.3.3 Multi-instrument synergy for the establishment of cloud climatologies 277 14.4 References 282 Chapter 15 Precipitation 287Vincenzo LEVIZZANI and Christopher KIDD 15.1 Need for global precipitation measurements 287 15.2 Satellite observation of rainfall 289 15.2.1 Visible/Infrared 290 15.2.2 Passive microwave 291 15.2.3 Radar 294 15.2.4 Merged products 295 15.3 Observation of solid precipitation 298 15.4 Precipitation and the Earth water cycle 300 15.5 References 303 Appendices 307 Appendix 1 309Claude CAMY-PEYRET Appendix 2 317Claude CAMY-PEYRET Appendix 3 327 Appendix 4 341 Glossary 347 List of Authors 361 Index 365 Summary of Volume 1 369

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