Electronics and communications engineering Books

Book SynopsisDynamic System Modeling & Analysis with MATLAB & Python A robust introduction to the advanced programming techniques and skills needed for control engineering In Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers, accomplished control engineer Dr. Jongrae Kim delivers an insightful and concise introduction to the advanced programming skills required by control engineers. The book discusses dynamic systems used by satellites, aircraft, autonomous robots, and biomolecular networks. Throughout the text, MATLAB and Python are used to consider various dynamic modeling theories and examples. The author covers a range of control topics, including attitude dynamics, attitude kinematics, autonomous vehicles, systems biology, optimal estimation, robustness analysis, and stochastic system. An accompanying website includes a solutions manual as well as MATLAB and Python example code. Dynamic System Modeling & Analysis with MATLABTable of ContentsPreface xiii Acknowledgements xv Acronyms xvii About the Companion Website xix 1 Introduction 1 1.1 Scope of the Book 1 1.2 Motivation Examples 2 1.2.1 Free-Falling Object 2 1.2.1.1 First Program in Matlab 4 1.2.1.2 First Program in Python 10 1.2.2 Ligand–Receptor Interactions 14 1.3 Organization of the Book 21 Exercises 21 Bibliography 22 2 Attitude Estimation and Control 23 2.1 Attitude Kinematics and Sensors 23 2.1.1 Solve Quaternion Kinematics 26 2.1.1.1 MATLAB 26 2.1.1.2 Python 29 2.1.2 Gyroscope Sensor Model 33 2.1.2.1 Zero-Mean Gaussian White Noise 33 2.1.2.2 Generate Random Numbers 34 2.1.2.3 Stochastic Process 40 2.1.2.4 MATLAB 41 2.1.2.5 Python 45 2.1.2.6 Gyroscope White Noise 49 2.1.2.7 Gyroscope RandomWalk Noise 50 2.1.2.8 Gyroscope Simulation 53 2.1.3 Optical Sensor Model 57 2.2 Attitude Estimation Algorithm 64 2.2.1 A Simple Algorithm 64 2.2.2 QUEST Algorithm 65 2.2.3 Kalman Filter 66 2.2.4 Extended Kalman Filter 75 2.2.4.1 Error Dynamics 76 2.2.4.2 Bias Noise 77 2.2.4.3 Noise Propagation in Error Dynamics 78 2.2.4.4 State Transition Matrix, Φ 84 2.2.4.5 Vector Measurements 84 2.2.4.6 Summary 86 2.2.4.7 Kalman Filter Update 86 2.2.4.8 Kalman Filter Propagation 87 2.3 Attitude Dynamics and Control 88 2.3.1 Dynamics Equation of Motion 88 2.3.1.1 MATLAB 91 2.3.1.2 Python 94 2.3.2 Actuator and Control Algorithm 95 2.3.2.1 MATLAB Program 98 2.3.2.2 Python 101 2.3.2.3 Attitude Control Algorithm 103 2.3.2.4 Altitude Control Algorithm 105 2.3.2.5 Simulation 106 2.3.2.6 MATLAB 107 2.3.2.7 Robustness Analysis 107 2.3.2.8 Parallel Processing 110 Exercises 113 Bibliography 115 3 Autonomous Vehicle Mission Planning 119 3.1 Path Planning 119 3.1.1 Potential Field Method 119 3.1.1.1 MATLAB 122 3.1.1.2 Python 126 3.1.2 Graph Theory-Based Sampling Method 126 3.1.2.1 MATLAB 128 3.1.2.2 Python 129 3.1.2.3 Dijkstra’s Shortest Path Algorithm 130 3.1.2.4 MATLAB 130 3.1.2.5 Python 131 3.1.3 Complex Obstacles 134 3.1.3.1 MATLAB 135 3.1.3.2 Python 141 3.2 Moving Target Tracking 145 3.2.1 UAV and Moving Target Model 145 3.2.2 Optimal Target Tracking Problem 148 3.2.2.1 MATLAB 149 3.2.2.2 Python 151 3.2.2.3 Worst-Case Scenario 153 3.2.2.4 MATLAB 157 3.2.2.5 Python 159 3.2.2.6 Optimal Control Input 164 3.3 Tracking Algorithm Implementation 167 3.3.1 Constraints 167 3.3.1.1 Minimum Turn Radius Constraints 167 3.3.1.2 Velocity Constraints 169 3.3.2 Optimal Solution 172 3.3.2.1 Control Input Sampling 172 3.3.2.2 Inside the Constraints 175 3.3.2.3 Optimal Input 177 3.3.3 Verification Simulation 180 Exercises 182 Bibliography 182 4 Biological System Modelling 185 4.1 Biomolecular Interactions 185 4.2 Deterministic Modelling 185 4.2.1 Group of Cells and Multiple Experiments 186 4.2.1.1 Model Fitting and the Measurements 188 4.2.1.2 Finding Adaptive Parameters 190 4.2.2 E. coli Tryptophan Regulation Model 191 4.2.2.1 Steady-State and Dependant Parameters 194 4.2.2.2 Padé Approximation of Time-Delay 195 4.2.2.3 State-Space Realization 196 4.2.2.4 Python 205 4.2.2.5 Model Parameter Ranges 206 4.2.2.6 Model Fitting Optimization 213 4.2.2.7 Optimal Solution (MATLAB) 221 4.2.2.8 Optimal Solution (Python) 223 4.2.2.9 Adaptive Parameters 226 4.2.2.10 Limitations 226 4.3 Biological Oscillation 227 4.3.1 Gillespie’s Direct Method 231 4.3.2 Simulation Implementation 234 4.3.3 Robustness Analysis 241 Exercises 245 Bibliography 246 5 Biological System Control 251 5.1 Control Algorithm Implementation 251 5.1.1 PI Controller 251 5.1.1.1 Integral Term 252 5.1.1.2 Proportional Term 253 5.1.1.3 Summation of the Proportional and the Integral Terms 253 5.1.1.4 Approximated PI Controller 253 5.1.1.5 Comparison of PI Controller and the Approximation 254 5.1.2 Error Calculation: ΔP 260 5.2 Robustness Analysis: 𝜇-Analysis 269 5.2.1 Simple Examples 269 5.2.1.1 𝜇 Upper Bound 272 5.2.1.2 𝜇 Lower Bound 275 5.2.1.3 Complex Numbers in MATLAB/Python 278 5.2.2 Synthetic Circuits 280 5.2.2.1 MATLAB 281 5.2.2.2 Python 281 5.2.2.3 𝜇-Upper Bound: Geometric Approach 290 Exercises 291 Bibliography 292 6 FurtherReadings295 6.1 Boolean Network 295 6.2 Network Structure Analysis 296 6.3 Spatial-Temporal Dynamics 297 6.4 Deep Learning Neural Network 298 6.5 Reinforcement Learning 298 Bibliography 298 Appendix A Solutions for Selected Exercises 301 A.1 Chapter 1 301 Exercise 1.4 301 Exercise 1.5 301 A.2 Chapter 2 302 Exercise 2.5 302 A.3 Chapter 3 302 Exercise 3.1 302 Exercise 3.6 303 A.4 Chapter 4 303 Exercise 4.1 303 Exercise 4.2 303 Exercise 4.7 304 A.5 Chapter 5 304 Exercise 5.2 304 Exercise 5.3 304 Index 307

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Book SynopsisTable of ContentsPREFACE TO THE FOURTH EDITION PART 1 INTRODUCTION 1 THE IMPORTANCE OF SAFETY AND HEALTH 2 SAFETY AND HEALTH PROFESSIONS 3 FUNDAMENTAL CONCEPTS AND TERMS PART 2 LEGAL ASPECTS OF SAFETY AND HEALTH 4 UNITED STATES LAWS, REGULATIONS, STANDARDS AND FEDERAL AGENCIES 5 LOCAL, INTERNATIONAL AND VOLUNTARY LAWS, REGULATIONS AND STANDARDS 6 WORKERS’ COMPENSATION 7 PRODUCTS LIABILITY 8 RECORD KEEPING AND REPORTING PART 3 HAZARDS AND THEIR CONTROL 9 GENERAL PRINCIPLES OF HAZARD CONTROL 10 MECHANICS AND STRUCTURES 11 WALKING AND WORKING SRUFACES 12 ELECTRICAL SAFETY 13 TOOLS AND MACHINES 14 TRANSPORTATION 15 MATERIALS HANDLING 16 FIRE PROTECTION AND PREVENTION 17 EXPLOSIONS AND EXPLOSIVES 18 HEAT AND COLD 19 PRESSURE 20 VISUAL ENVIRONMENT 21 NON-IONIZING RADIATION 22 IONIZING RADIATION 23 NOISE AND VIBRATION 24 CHEMICALS 25 VENTILATION 26 BIOHAZARDS 27 HAZARDOUS WASTE 28 PERSONAL PROTECTIVE EQUIPMENT 29 EMERGENCIES AND SECURITY 30 FACILITY PLANNING, DESIGN AND MAINTENANCE PART 4 THE HUMAN ELEMENT 31 HUMAN BEHAVIOR AND PERFORMANCE IN SAFETY AND HEALTH 32 PROCEDURES, RULES, AND TRAINING 33 ERGONOMICS PART 5 MANAGING SAFETY AND HEALTH 34 RISK, RISK ASSESSMENT AND RISK MANAGEMENT 35 SAFETY AND HEALTH MANAGEMENT 36 SYSTEM SAFETY 37 SAFETY AND HEALTH DATA, ANALYSIS AND MANAGEMENT INFORMATION 38 SAFEY AND HEALTH PLANS AND PROGRAMS INDEX

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Book SynopsisTable of ContentsPreface Chapter 1: Overview 1.0 Introduction 1.1 Understanding Project Management 1.2 Defining Project Success 1.3 Trade-Offs and Competing Constraints 1.4 The Entry-Level Project Manager 1.5 The Talent Triangle 1.6 Technology-Based Projects 1.7 The Project Manager–Line Manager Interface 1.8 Defining the Project Manager’s Role 1.9 Defining the Functional Manager’s Role 1.10 Defining the Functional Employee’s Role 1.11 Defining the Executive’s Role 1.12 Working with Executives 1.13 Committee Sponsorship/Governance 1.14 The Project Manager as the Planning Agent 1.15 Project Champions 1.16 Project-Driven Versus Non–Project-Driven Organizations 1.17 Marketing in the Project-Driven Organization 1.18 Classification of Projects 1.19 Location of the Project Manager 1.20 Differing Views of Project Management 1.21 Public-Sector Project Management 1.22 International Project Management 1.23 Concurrent Engineering: A Project Management Approach 1.24 Added Value 1.25 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: Williams Machine Tool Company Chapter 2: Project Management Growth: Concepts and Definitions 2.0 Introduction 2.1 The Evolution of Project Management: 1945–2021 2.2 Resistance to Change 2.3 Systems, Programs, and Projects: A Definition 2.4 Projects versus Operations 2.5 Product versus Project Management: A Definition 2.6 Maturity and Excellence: A Definition 2.7 Informal Project Management: A Definition 2.8 The Many Faces of Success 2.9 The Many Faces of Failure 2.10 Causes of Project Failure 2.11 Degrees of Success and Failure 2.12 Project Health Checks 2.13 The Stage-Gate Process 2.14 Project Life Cycles 2.15 Gate Review Meetings (Project Closure) 2.16 Engagement Project Management 2.17 Project Management Methodologies: A Definition 2.18 From Enterprise Project Management Methodologies to Frameworks 2.19 Growth of Strategic Project Management 2.20 Business Models 2.21 Methodologies Can Fail 2.22 Lean Project Management 2.23 Organizational Change Management and Corporate Cultures 2.24 Benefits Harvesting and Cultural Change 2.25 Agile and Adaptive Project Management Cultures 2.26 Project Management Intellectual Property 2.27 Systems Thinking 2.28 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: Creating a Methodology Chapter 3: Organizational Structures 3.0 Introduction 3.1 Organizational Work Flow 3.2 Traditional (Classical) Organization 3.3 Pure Product (Projectized) Organization 3.4 Matrix Organizational Form 3.5 Modification of Matrix Structures 3.6 The Strong, Weak, or Balanced Matrix 3.7 Project Management Offices 3.8 Selecting the Organizational Form 3.9 Strategic Business Unit (SBU) Project Management 3.10 Transitional Management 3.11 Seven Fallacies That Delay Project Management Maturity 3.12 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Chapter 4: Organizing and Staffing the Project Office and Team 4.0 Introduction 4.1 The Staffing Environment 4.2 Selecting the Project Manager: An Executive Decision 4.3 Skill Requirements for Project and Program Managers 4.4 Special Cases in Project Manager Selection 4.5 Today’s Project Managers 4.6 Duties and Job Descriptions 4.7 The Organizational Staffing Process 4.8 The Project Office 4.9 The Functional Team 4.10 The Project Organizational Chart 4.11 Selecting the Project Management Implementation Team 4.12 Mistakes Made by Inexperienced Project Managers 4.13 Studying Tips for the PMI®Project Management Certification Exam Answers Problems Chapter 5: Management Functions 5.0 Introduction 5.1 Controlling 5.2 Directing 5.3 Project Authority 5.4 Interpersonal Influences 5.5 Barriers to Project Team Development 5.6 Suggestions for Handling the Newly Formed Team 5.7 Team Building as an Ongoing Process 5.8 Leadership in a Project Environment 5.9 Value-Based Project Leadership 5.10 Transformational Project Management Leadership 5.11 Organizational Impact 5.12 Employee–Manager Problems 5.13 General Management Pitfalls 5.14 Time Management Pitfalls 5.15 Management Policies and Procedures 5.16 Human Behavior Education 5.17 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: The Trophy Project Case Study: McRoy Aerospace Case Study: The Poor Worker Case Study: The Prima Donna Case Study: The Reluctant Workers Case Study: Leadership Effectiveness (A) Case Study: Leadership Effectiveness (B) Chapter 6: Communications Management 6.0 Introduction 6.1 Modeling the Communications Environment 6.2 The Project Manager as a Communicator 6.3 Project Review Meetings 6.4 Project Management Bottlenecks 6.5 Active Listening 6.6 Communication Traps 6.7 Project Problem Solving 6.8 Using Action Items 6.9 Brainstorming 6.10 Predicting the Outcome of a Decision 6.11 Facilitation 6.12 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: Communication Failures Case Study: The Team Meeting Chapter 7: Conflicts 7.0 Introduction 7.1 The Conflict Environment 7.2 Types of Conflicts 7.3 Conflict Resolution 7.4 The Management of Conflicts 7.5 Conflict Resolution Modes 7.6 Understanding Superior, Subordinate, and Functional Conflicts 7.7 Studying Tips for the PMI® Project Management Certification Exam Problems Case Study: Facilities Scheduling at Mayer Manufacturing Case Study: Telestar International Case Study: Handling Conflict in Project Management Chapter 8: Special Topics 8.0 Introduction 8.1 Performance Measurement 8.2 Financial Compensation and Rewards 8.3 Effective Project Management in the Small Business Organization 8.4 Mega Projects 8.5 Morality, Ethics, and the Corporate Culture 8.6 Professional Responsibilities 8.7 Internal and External Partnerships 8.8 Training and Education 8.9 Integrated Product/Project Teams 8.10 Virtual Project Teams 8.11 Managing Innovation Projects 8.12 Agile Project Management 8.13 Artificial Intelligence 8.14 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: Is It Fraud? Chapter 9: The Variables for Success 9.0 Introduction 9.1 Predicting Project Success 9.2 Project Management Effectiveness 9.3 Expectations 9.4 Lessons Learned 9.5 Understanding Best Practices 9.6 Downside Risks of Best Practices 9.7 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: Radiance International Chapter 10: Working with Executives 10.0 Introduction 10.1 The Project Sponsor 10.2 Handling Disagreements with the Sponsor 10.3 The Collective Belief 10.4 The Exit Champion 10.5 The In-House Representatives 10.6 Stakeholder Relations Management 10.7 Project Portfolio Management 10.8 Politics 10.9 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: The Prioritization of Projects Case Study: The Irresponsible Sponsors Case Study: Selling Executives on Project Management Chapter 11: Planning 11.0 Introduction 11.1 Business Case 11.2 Validating the Assumptions 11.3 Validating the Objectives 11.4 General Planning 11.5 Life-Cycle Phases 11.6 Life-Cycle Milestones 11.7 Kickoff Meetings 11.8 Understanding Participants’ Roles 11.9 Establishing Project Objectives 11.10 The Statement of Work 11.11 Project Specifications 11.12 Data Item Milestone Schedules 11.13 Work Breakdown Structure 11.14 WBS Decomposition Problems 11.15 Work Breakdown Structure Dictionary 11.16 Project Selection 11.17 Role of the Executive in Planning 11.18 Management Cost and Control System 11.19 Work Planning Authorization 11.20 Why Do Plans Fail? 11.21 Stopping Projects 11.22 Handling Project Phaseouts and Transfers 11.23 Detailed Schedules and Charts 11.24 Master Production Scheduling 11.25 Project Plan 11.26 The Project Charter 11.27 Project Baselines 11.28 Verification and Validation 11.29 Management Control 11.30 Configuration Management 11.31 Enterprise Project Management Methodologies 11.32 Project Audits 11.33 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Chapter 12: Network Scheduling Techniques 12.0 Introduction 12.1 Network Fundamentals 12.2 Graphical Evaluation and Review Technique (GERT) 12.3 Dependencies 12.4 Slack Time 12.5 Network Replanning 12.6 Estimating Activity Time 12.7 Estimating Total Project Time 12.8 Total Pert/CPM Planning 12.9 Crash Times 12.10 PERT/CPM Problem Areas 12.11 Alternative PERT/CPM Models 12.12 Precedence Networks 12.13 Lag 12.14 Scheduling Problems 12.15 The Myths of Schedule Compression 12.16 Project Management Software 12.17 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: The Invisible Sponsor Chapter 13: Pricing and Estimating 13.0 Introduction 13.1 Global Pricing Strategies 13.2 Types of Estimates 13.3 Pricing Process 13.4 Organizational Input Requirements 13.5 Labor Distributions 13.6 Overhead Rates 13.7 Materials/Support Costs 13.8 Pricing out the Work 13.9 Smoothing Out Department Man-Hours 13.10 The Pricing Review Procedure 13.11 Systems Pricing 13.12 Developing the Supporting/Backup Costs 13.13 The Low-Bidder Dilemma 13.14 Special Problems 13.15 Estimating Pitfalls 13.16 Estimating High-Risk Projects 13.17 Project Risks 13.18 The Disaster of Applying the 10 Percent Solution to Project Estimates 13.19 Life-Cycle Costing (LCC) 13.20 Logistics Support 13.21 Economic Project Selection Criteria: Capital Budgeting 13.22 Payback Period 13.23 The Time Value of Money and Discounted Cash Flow (DCF) 13.24 Net Present Value (NPV) 13.25 Internal Rate of Return (IRR) 13.26 Comparing IRR, NPV, and Payback 13.27 Risk Analysis 13.28 Capital Rationing 13.29 Project Financing 13.30 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: The Estimating Problem Chapter 14: Cost Control 14.0 Introduction 14.1 Understanding Control 14.2 The Operating Cycle 14.3 Cost Account Codes 14.4 Budgets 14.5 The Earned Value Measurement System (EVMS) 14.6 Variance and Earned Value 14.7 The Cost Baseline 14.8 Justifying the Costs 14.9 The Cost Overrun Dilemma 14.10 Recording Material Costs Using Earned Value Measurement 14.11 Material Variances: Price and Usage 14.12 Summary Variances 14.13 Status Reporting 14.14 Cost Control Problems 14.15 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: The Bathtub Period Case Study: Franklin Electronics Chapter 15: Metrics 15.0 Introduction 15.1 Project Management Information Systems 15.2 Enterprise Resource Planning 15.3 Project Metrics 15.4 Key Performance Indicators (KPIs) 15.5 Growth of New Metrics and KPIs 15.6 Value-Based Metrics 15.7 Strategic Metrics 15.8 Metrics for Measuring Intangible Assets 15.9 Dashboards and Scorecards 15.10 Metrics Feedback 15.11 Metrics and Customer Relations Management 15.12 Business Intelligence 15.13 Studying Tips for the PMI®Project Management Certification Exam Answers Problems Chapter 16: Trade-off Analysis in a Project Environment 16.0 Introduction 16.1 Methodology for Trade-Off Analysis 16.2 Contracts: Their Influence on Projects 16.3 Industry Trade-Off Preferences 16.4 Project Manager’s Control of Trade-Offs 16.5 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Chapter 17: Risk Management 17.0 Introduction 17.1 Definition of Risk 17.2 Tolerance for Risk 17.3 Definition of Risk Management 17.4 Certainty, Risk, and Uncertainty 17.5 Risk Management Process 17.6 Plan Risk Management 17.7 Risk Identification 17.8 Risk Analysis 17.9 Qualitative Risk Analysis 17.10 Quantitative Risk Analysis 17.11 Plan Risk Response 17.12 Monitor and Control Risks 17.13 Some Implementation Considerations 17.14 The Use of Lessons Learned 17.15 Dependencies between Risks 17.16 The Impact of Risk Handling Measures 17.17 Risk and Concurrent Engineering 17.18 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: Teloxy Engineering (A) Case Study: Teloxy Engineering (B) Case Study: The Risk Management Department Chapter 18: Learning Curves 18.0 Introduction 18.1 General Theory 18.2 The Learning Curve Concept 18.3 Graphic Representation 18.4 Key Words Associated with Learning Curves 18.5 The Cumulative Average Curve 18.6 Sources of Experience 18.7 Developing Slope Measures 18.8 Unit Costs and Use of Midpoints 18.9 Selection of Learning Curves 18.10 Follow-on Orders 18.11 Manufacturing Breaks 18.12 Learning Curve Limitations 18.13 Competitive Weapon 18.14 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Chapter 19: Contract Management 19.0 Introduction 19.1 Procurement 19.2 Plan Procurements 19.3 Conducting the Procurements 19.4 Conduct Procurements: Request Seller Responses 19.5 Conduct Procurements: Select Sellers 19.6 Types of Contracts 19.7 Incentive Contracts 19.8 Contract Type versus Risk 19.9 Contract Administration 19.10 Contract Closure 19.11 Using a Checklist 19.12 Proposal-Contractual Interaction 19.13 Studying Tips for the PMI® Project Management Certification Exam Answers Problems Case Study: To Bid or Not to Bid Case Study: The Management Reserve Chapter 20: Quality Management 20.0 Introduction 20.1 Definition of Quality 20.2 The Quality Movement 20.3 Quality Management Concepts 20.4 The Cost of Quality 20.5 The Seven Quality Control Tools 20.6 Acceptance Sampling 20.7 Implementing Six Sigma 20.8 Quality Leadership 20.9 Responsibility for Quality 20.10 Quality Circles 20.11 Total Quality Management (TQM) 20.12 Studying Tips for the PMI®Project Management Certification Exam Answers Problems Chapter 21: Modern Developments in Project Management 21.0 Introduction 21.1 The Project Management Maturity Model (PMMM) 21.2 Developing Effective Procedural Documentation 21.3 Project Management Methodologies 21.4 Continuous Improvement 21.5 Capacity Planning 21.6 Competency Models 21.7 Managing Multiple Projects 21.8 The Business of Scope Changes 21.9 End-of-Phase Review Meetings Case Study: Honicker Corporation Case Study: Kemko Manufacturing Appendix A: Solution to Leadership Exercise Appendix B: Solutions to the Project Management Conflict Exercise Appendix C: Dorale Products Case Studies Appendix D: Solutions to the Dorale Products Case Studies Appendix E: Alignment of the PMBOK® Guide, 6e to the Text Appendix F: Alignment of the PMBOK® Guide, 7e to the Text Index

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Book SynopsisAGRICULTURE WASTE MANAGEMENT AND BIORESOURCE Comprehensive resource detailing the generation of agricultural waste and providing insight into waste management Agriculture Waste Management and Bioresource provides thorough coverage of the generation of agricultural waste with essential thought leadership about various options in managing the waste, including composting, vermicomposting to form manure, and biogas generation. Readers take a crucial step toward more sustainable development and creating a greener planet. The text includes a wide range of information regarding resource recovery from the waste of the agriculture sector, energy generation, biofuels, reduction in the amount and volume of waste through circular economies, and much more. The authors place particular importance on understanding and managing agricultural waste concerning the sustainability of the environment in the era of global climate change. Topics covered in Agriculture WasteTable of Contents1. Agricultural Waste as a Resource: the lesser travelled road to Sustainability 2. Sustainable Physical Methods Used For The Management Of Agricultural Waste Biomass 3. An overview of Biomass Conversion from Agricultural Waste: Address on Environmental Sustainability 4. Agriculture wastes: Generation and Sustainable management" 5. Microbiological Digestion of Agricultural Biomass: Prospects & Challenges in Generating Clean and Green energy 6. Nothing is “Waste” in Agriculture: From Nanotechnology and Bioprocesses Perspectives 7 Agro-Wastes as Low-Cost Bio-sorbent for Dyes Removal from Wastewater 8 Agricultural waste as source of organic fertilizer and Energy 9 Production of Bioethanol using Agricultural Waste: An Overview 10 Bioethanol production from Lignocellulose Waste of Agricultural waste Biomass 11 Hydrothermal liquefaction of waste agricultural biomass for biofuel and biochar 12 Biogas production through Anaerobic digestion of Agricultural Wastes: State of Benefits and its Future trend 13 Expansion of Agricultural Residues to Bio-Fuel Processing and Production 14 Creating wealth from agro-waste: success stories from India

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Book SynopsisModel-Based Reinforcement Learning Explore a comprehensive and practical approach to reinforcement learning Reinforcement learning is an essential paradigm of machine learning, wherein an intelligent agent performs actions that ensure optimal behavior from devices. While this paradigm of machine learning has gained tremendous success and popularity in recent years, previous scholarship has focused either on theoryoptimal control and dynamic programming or on algorithmsmost of which are simulation-based. Model-Based Reinforcement Learning provides a model-based framework to bridge these two aspects, thereby creating a holistic treatment of the topic of model-based online learning control. In doing so, the authors seek to develop a model-based framework for data-driven control that bridges the topics of systems identification from data, model-based reinforcement learning, and optimal control, as well as the applications of each. This new technique for assesTable of ContentsAbout the Authors xi Preface xiii Acronyms xv Introduction xvii 1 Nonlinear Systems Analysis 1 1.1 Notation 1 1.2 Nonlinear Dynamical Systems 2 1.2.1 Remarks on Existence, Uniqueness, and Continuation of Solutions 2 1.3 Lyapunov Analysis of Stability 3 1.4 Stability Analysis of Discrete Time Dynamical Systems 7 1.5 Summary 10 Bibliography 10 2 Optimal Control 11 2.1 Problem Formulation 11 2.2 Dynamic Programming 12 2.2.1 Principle of Optimality 12 2.2.2 Hamilton–Jacobi–Bellman Equation 14 2.2.3 A Sufficient Condition for Optimality 15 2.2.4 Infinite-Horizon Problems 16 2.3 Linear Quadratic Regulator 18 2.3.1 Differential Riccati Equation 18 2.3.2 Algebraic Riccati Equation 23 2.3.3 Convergence of Solutions to the Differential Riccati Equation 26 2.3.4 Forward Propagation of the Differential Riccati Equation for Linear Quadratic Regulator 28 2.4 Summary 30 Bibliography 30 3 Reinforcement Learning 33 3.1 Control-Affine Systems with Quadratic Costs 33 3.2 Exact Policy Iteration 35 3.2.1 Linear Quadratic Regulator 39 3.3 Policy Iteration with Unknown Dynamics and Function Approximations 41 3.3.1 Linear Quadratic Regulator with Unknown Dynamics 46 3.4 Summary 47 Bibliography 48 4 Learning of Dynamic Models 51 4.1 Introduction 51 4.1.1 Autonomous Systems 51 4.1.2 Control Systems 51 4.2 Model Selection 52 4.2.1 Gray-Box vs. Black-Box 52 4.2.2 Parametric vs. Nonparametric 52 4.3 Parametric Model 54 4.3.1 Model in Terms of Bases 54 4.3.2 Data Collection 55 4.3.3 Learning of Control Systems 55 4.4 Parametric Learning Algorithms 56 4.4.1 Least Squares 56 4.4.2 Recursive Least Squares 57 4.4.3 Gradient Descent 59 4.4.4 Sparse Regression 60 4.5 Persistence of Excitation 60 4.6 Python Toolbox 61 4.6.1 Configurations 62 4.6.2 Model Update 62 4.6.3 Model Validation 63 4.7 Comparison Results 64 4.7.1 Convergence of Parameters 65 4.7.2 Error Analysis 67 4.7.3 Runtime Results 69 4.8 Summary 73 Bibliography 75 5 Structured Online Learning-Based Control of Continuous-Time Nonlinear Systems 77 5.1 Introduction 77 5.2 A Structured Approximate Optimal Control Framework 77 5.3 Local Stability and Optimality Analysis 81 5.3.1 Linear Quadratic Regulator 81 5.3.2 SOL Control 82 5.4 SOL Algorithm 83 5.4.1 ODE Solver and Control Update 84 5.4.2 Identified Model Update 85 5.4.3 Database Update 85 5.4.4 Limitations and Implementation Considerations 86 5.4.5 Asymptotic Convergence with Approximate Dynamics 87 5.5 Simulation Results 87 5.5.1 Systems Identifiable in Terms of a Given Set of Bases 88 5.5.2 Systems to Be Approximated by a Given Set of Bases 91 5.5.3 Comparison Results 98 5.6 Summary 99 Bibliography 99 6 A Structured Online Learning Approach to Nonlinear Tracking with Unknown Dynamics 103 6.1 Introduction 103 6.2 A Structured Online Learning for Tracking Control 104 6.2.1 Stability and Optimality in the Linear Case 108 6.3 Learning-based Tracking Control Using SOL 111 6.4 Simulation Results 112 6.4.1 Tracking Control of the Pendulum 113 6.4.2 Synchronization of Chaotic Lorenz System 114 6.5 Summary 115 Bibliography 118 7 Piecewise Learning and Control with Stability Guarantees 121 7.1 Introduction 121 7.2 Problem Formulation 122 7.3 The Piecewise Learning and Control Framework 122 7.3.1 System Identification 123 7.3.2 Database 124 7.3.3 Feedback Control 125 7.4 Analysis of Uncertainty Bounds 125 7.4.1 Quadratic Programs for Bounding Errors 126 7.5 Stability Verification for Piecewise-Affine Learning and Control 129 7.5.1 Piecewise Affine Models 129 7.5.2 MIQP-based Stability Verification of PWA Systems 130 7.5.3 Convergence of ACCPM 133 7.6 Numerical Results 134 7.6.1 Pendulum System 134 7.6.2 Dynamic Vehicle System with Skidding 138 7.6.3 Comparison of Runtime Results 140 7.7 Summary 142 Bibliography 143 8 An Application to Solar Photovoltaic Systems 147 8.1 Introduction 147 8.2 Problem Statement 150 8.2.1 PV Array Model 151 8.2.2 DC-D C Boost Converter 152 8.3 Optimal Control of PV Array 154 8.3.1 Maximum Power Point Tracking Control 156 8.3.2 Reference Voltage Tracking Control 162 8.3.3 Piecewise Learning Control 164 8.4 Application Considerations 165 8.4.1 Partial Derivative Approximation Procedure 165 8.4.2 Partial Shading Effect 167 8.5 Simulation Results 170 8.5.1 Model and Control Verification 173 8.5.2 Comparative Results 174 8.5.3 Model-Free Approach Results 176 8.5.4 Piecewise Learning Results 178 8.5.5 Partial Shading Results 179 8.6 Summary 182 Bibliography 182 9 An Application to Low-level Control of Quadrotors 187 9.1 Introduction 187 9.2 Quadrotor Model 189 9.3 Structured Online Learning with RLS Identifier on Quadrotor 190 9.3.1 Learning Procedure 191 9.3.2 Asymptotic Convergence with Uncertain Dynamics 195 9.3.3 Computational Properties 195 9.4 Numerical Results 197 9.5 Summary 201 Bibliography 201 10 Python Toolbox 205 10.1 Overview 205 10.2 User Inputs 205 10.2.1 Process 206 10.2.2 Objective 207 10.3 SOL 207 10.3.1 Model Update 208 10.3.2 Database 208 10.3.3 Library 210 10.3.4 Control 210 10.4 Display and Outputs 211 10.4.1 Graphs and Printouts 213 10.4.2 3D Simulation 213 10.5 Summary 214 Bibliography 214 A Appendix 215 A.1 Supplementary Analysis of Remark 5.4 215 A.2 Supplementary Analysis of Remark 5.5 222 Index 223

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Book SynopsisElectromagnetic Radiation, Scattering, and Diffraction Discover a graduate-level text for students specializing in electromagnetic wave radiation, scattering, and diffraction for engineering applications In Electromagnetic Radiation, Scattering and Diffraction, distinguished authors Drs. Prabhakar H. Pathak and Robert J. Burkholder deliver a thorough exploration of the behavior of electromagnetic fields in radiation, scattering, and guided wave environments. The book tackles its subject from first principles and includes coverage of low and high frequencies. It stresses physical interpretations of the electromagnetic wave phenomena along with their underlying mathematics. The authors emphasize fundamental principles and provide numerous examples to illustrate the concepts contained within. Students with a limited undergraduate electromagnetic background will rapidly and systematically advance their understanding of electromagnetic wave theory until they can complete useful and important graduate-level work on electromagnetic wave problems. Electromagnetic Radiation, Scattering and Diffraction also serves as a practical companion for students trying to simulate problems with commercial EM software and trying to better interpret their results. Readers will also benefit from the breadth and depth of topics, such as: Basic equations governing all electromagnetic (EM) phenomena at macroscopic scales are presented systematically. Stationary and relativistic moving boundary conditions are developed. Waves in planar multilayered isotropic and anisotropic media are analyzed. EM theorems are introduced and applied to a variety of useful antenna problems. Modal techniques are presented for analyzing guided wave and periodic structures. Potential theory and Green's function methods are developed to treat interior and exterior EM problems. Asymptotic High Frequency methods are developed for evaluating radiation Integrals to extract ray fields. Edge and surface diffracted ray fields, as well as surface, leaky and lateral wave fields are obtained. A collective ray analysis for finite conformal antenna phased arrays is developed. EM beams are introduced and provide useful basis functions. Integral equations and their numerical solutions via the method of moments are developed. The fast multipole method is presented. Low frequency breakdown is studied. Characteristic modes are discussed. Perfect for graduate students studying electromagnetic theory, Electromagnetic Radiation, Scattering, and Diffraction is an invaluable resource for professional electromagnetic engineers and researchers working in this area.Table of ContentsAbout the Authors xvii Preface xix Acknowledgments xxiii 1 Maxwell’s Equations, Constitutive Relations, Wave Equation, and Polarization 1 1.1 Introductory Comments 1 1.2 Maxwell’s Equations 5 1.3 Constitutive Relations 10 1.4 Frequency Domain Fields 15 1.5 Kramers-Kronig Relationship 19 1.6 Vector and Scalar Wave Equations 21 1.6.1 Vector Wave Equations for EM Fields 21 1.6.2 Scalar Wave Equations for EM Fields 22 1.7 Separable Solutions of the Source-Free Wave Equation in Rectangular Coordinates and for Isotropic Homogeneous Media. Plane Waves 23 1.8 Polarization of Plane Waves, Poincaré Sphere, and Stokes Parameters 29 1.8.1 Polarization States 29 1.8.2 General Elliptical Polarization 32 1.8.3 Decomposition of a Polarization State into Circularly Polarized Components 36 1.8.4 Poincaré Sphere for Describing Polarization States 37 1.9 Phase and Group Velocity 40 1.10 Separable Solutions of the Source-Free Wave Equation in Cylindrical and Spherical Coordinates and for Isotropic Homogeneous Media 44 1.10.1 Source-Free Cylindrical Wave Solutions 44 1.10.2 Source-Free Spherical Wave Solutions 48 References 51 2 EM Boundary and Radiation Conditions 52 2.1 EM Field Behavior Across a Boundary Surface 52 2.2 Radiation Boundary Condition 60 2.3 Boundary Conditions at a Moving Interface 63 2.3.1 Nonrelativistic Moving Boundary Conditions 63 2.3.2 Derivation of the Nonrelativistic Field Transformations 66 2.3.3 EM Field Transformations Based on the Special Theory of Relativity 69 2.4 Constitutive Relations for a Moving Medium 84 References 85 3 Plane Wave Propagation in Planar Layered Media 87 3.1 Introduction 87 3.2 Plane Wave Reflection from a Planar Boundary Between Two Different Media 87 3.2.1 Perpendicular Polarization Case 88 3.2.2 Parallel Polarization Case 93 3.2.3 Brewster Angle θ b 97 3.2.4 Critical Angle θ c 100 3.2.5 Plane Wave Incident on a Lossy Half Space 104 3.2.6 Doppler Shift for Wave Reflection from a Moving Mirror 110 3.3 Reflection and Transmission of a Plane Wave Incident on a Planar Stratified Isotropic Medium Using a Transmission Matrix Approach 112 3.4 Plane Waves in Anisotropic Homogeneous Media 119 3.5 State Space Formulation for Waves in Planar Anisotropic Layered Media 135 3.5.1 Development of State Space Based Field Equations 135 3.5.2 Reflection and Transmission of Plane Waves at the Interface Between Two Anisotropic Half Spaces 139 3.5.3 Transmission Type Matrix Analysis of Plane Waves in Multilayered Anisotropic Media 142 References 143 4 Plane Wave Spectral Representation for EM Fields 144 4.1 Introduction 144 4.2 PWS Development 144 References 155 5 Electromagnetic Potentials and Fields of Sources in Unbounded Regions 156 5.1 Introduction to Vector and Scalar Potentials 156 5.2 Construction of the Solution for A 160 5.3 Calculation of Fields from Potentials 165 5.4 Time Dependent Potentials for Sources and Fields in Unbounded Regions 176 5.5 Potentials and Fields of a Moving Point Charge 185 5.6 Cerenkov Radiation 192 5.7 Direct Calculation of Fields of Sources in Unbounded Regions Using a Dyadic Green’s Function 195 5.7.1 Fields of Sources in Unbounded, Isotropic, Homogeneous Media in Terms of a Closed Form Representation of Green’s Dyadic, G 0 195 5.7.2 On the Singular Nature of G 0 (r|r ′) for Observation Points Within the Source Region 197 5.7.3 Representation of the Green’s Dyadic G 0 in Terms of an Integral in the Wavenumber (k) Space 201 5.7.4 Electromagnetic Radiation by a Source in a General Bianisotropic Medium Using a Green’s Dyadic G a in k-Space 208 References 209 6 Electromagnetic Field Theorems and Related Topics 211 6.1 Conservation of Charge 211 6.2 Conservation of Power 212 6.3 Conservation of Momentum 218 6.4 Radiation Pressure 225 6.5 Duality Theorem 235 6.6 Reciprocity Theorems and Conservation of Reactions 242 6.6.1 The Lorentz Reciprocity Theorem 243 6.6.2 Reciprocity Theorem for Bianisotropic Media 249 6.7 Uniqueness Theorem 251 6.8 Image Theorems 254 6.9 Equivalence Theorems 258 6.9.1 Volume Equivalence Theorem for EM Scattering 258 6.9.2 A Surface Equivalence Theorem for EM Scattering 260 6.9.3 A Surface Equivalence Theorem for Antennas 270 6.10 Antenna Impedance 278 6.11 Antenna Equivalent Circuit 282 6.12 The Receiving Antenna Problem 282 6.13 Expressions for Antenna Mutual Coupling Based on Generalized Reciprocity Theorems 287 6.13.1 Circuit Form of the Reciprocity Theorem for Antenna Mutual Coupling 287 6.13.2 A Mixed Circuit Field Form of a Generalized Reciprocity Theorem for Antenna Mutual Coupling 292 6.13.3 A Mutual Admittance Expression for Slot Antennas 294 6.13.4 Antenna Mutual Coupling, Reaction Concept, and Antenna Measurements 296 6.14 Relation Between Antenna and Scattering Problems 297 6.14.1 Exterior Radiation by a Slot Aperture Antenna Configuration 297 6.14.2 Exterior Radiation by a Monopole Antenna Configuration 299 6.15 Radar Cross Section 308 6.16 Antenna Directive Gain 309 6.17 Field Decomposition Theorem 311 References 313 7 Modal Techniques for the Analysis of Guided Waves, Resonant Cavities, and Periodic Structures 314 7.1 On Modal Analysis of Some Guided Wave Problems 314 7.2 Classification of Modal Fields in Uniform Guiding Structures 314 7.2.1 TEM z Guided waves 315 7.3 TM z Guided Waves 325 7.4 TE z Guided Waves 328 7.5 Modal Expansions in Closed Uniform Waveguides 330 7.5.1 TM z Modes 331 7.5.2 TE z Modes 332 7.5.3 Orthogonality of Modes in Closed Perfectly Conducting Uniform Waveguides 334 7.6 Effect of Losses in Closed Guided Wave Structures 337 7.7 Source Excited Uniform Closed Perfectly Conducting Waveguides 338 7.8 An Analysis of Some Closed Metallic Waveguides 342 7.8.1 Modes in a Parallel Plate Waveguide 342 7.8.2 Modes in a Rectangular Waveguide 350 7.8.3 Modes in a Circular Waveguide 358 7.8.4 Coaxial Waveguide 364 7.8.5 Obstacles and Discontinuities in Waveguides 366 7.8.6 Modal Propagation Past a Slot in a Waveguide 379 7.9 Closed and Open Waveguides Containing Penetrable Materials and Coatings 383 7.9.1 Material-Loaded Closed PEC Waveguide 384 7.9.2 Material Slab Waveguide 388 7.9.3 Grounded Material Slab Waveguide 395 7.9.4 The Goubau Line 395 7.9.5 Circular Cylindrical Optical Fiber Waveguides 398 7.10 Modal Analysis of Resonators 400 7.10.1 Rectangular Waveguide Cavity Resonator 402 7.10.2 Circular Waveguide Cavity Resonator 406 7.10.3 Dielectric Resonators 408 7.11 Excitation of Resonant Cavities 409 7.12 Modal Analysis of Periodic Arrays 411 7.12.1 Floquet Modal Analysis of an Infinite Planar Periodic Array of Electric Current Sources 412 7.12.2 Floquet Modal Analysis of an Infinite Planar Periodic Array of Current Sources Configured in a Skewed Grid 419 7.13 Higher-Order Floquet Modes and Associated Grating Lobe Circle Diagrams for Infinite Planar Periodic Arrays 422 7.13.1 Grating Lobe Circle Diagrams 422 7.14 On Waves Guided and Radiated by Periodic Structures 425 7.15 Scattering by a Planar Periodic Array 430 7.15.1 Analysis of the EM Plane Wave Scattering by an Infinite Periodic Slot Array in a Planar PEC Screen 432 7.16 Finite 1-D and 2-D Periodic Array of Sources 437 7.16.1 Analysis of Finite 1-D Periodic Arrays for the Case of Uniform Source Distribution and Far Zone Observation 437 7.16.2 Analysis of Finite 2-D Periodic Arrays for the Case of Uniform Distribution and Far Zone Observation 444 7.16.3 Floquet Modal Representation for Near and Far Fields of 1-D Nonuniform Finite Periodic Array Distributions 446 7.16.4 Floquet Modal Representation for Near and Far Fields of 2-D Nonuniform Planar Periodic Finite Array Distributions 449 References 451 8 Green’s Functions for the Analysis of One-Dimensional Source-Excited Wave Problems 453 8.1 Introduction to the Sturm-Liouville Form of Differential Equation for 1-D Wave Problems 453 8.2 Formulation of the Solution to the Sturm-Liouville Problem via the 1-D Green’s Function Approach 456 8.3 Conditions Under Which the Green’s Function Is Symmetric 463 8.4 Construction of the Green’s Function G(x|x′) 464 8.4.1 General Procedure to Obtain G(x|x′) 464 8.5 Alternative Simplified Construction of G(x|x′) Valid for the Symmetric Case 466 8.6 On the Existence and Uniqueness of G(x|x′) 483 8.7 Eigenfunction Expansion Representation for G(x|x′) 483 8.8 Delta Function Completeness Relation and the Construction of Eigenfunctions from G(x|x′) = U (x<)T (x>) ∕ W 488 8.9 Explicit Representation of G(x|x′) Using Step Functions 519 References 520 9 Applications of One-Dimensional Green’s Function Approach for the Analysis of Single and Coupled Set of EM Source Excited Transmission Lines 522 9.1 Introduction 522 9.2 Analytical Formulation for a Single Transmission Line Made Up of Two Conductors 522 9.3 Wave Solution for the Two Conductor Lines When There Are No Impressed Sources Distributed Anywhere Within the Line 525 9.4 Wave Solution for the Case of Impressed Sources Placed Anywhere on a Two Conductor Line 527 9.5 Excitation of a Two Conductor Transmission Line by an Externally Incident Electromagnetic Wave 541 9.6 A Matrix Green’s Function Approach for Analyzing a Set of Coupled Transmission Lines 543 9.7 Solution to the Special Case of Two Coupled Lines (N = 2) with Homogeneous Dirichlet or Neumann End Conditions 546 9.8 Development of the Multiport Impedance Matrix for a Set of Coupled Transmission Lines 551 9.9 Coupled Transmission Line Problems with Voltage Sources and Load Impedances at the End Terminals 552 References 553 10 Green’s Functions for the Analysis of Two- and Three-Dimensional Source- Excited Scalar and EM Vector Wave Problems 554 10.1 Introduction 554 10.2 General Formulation for Source-Excited 3-D Separable Scalar Wave Problems Using Green’s Functions 555 10.3 General Procedure for Construction of Scalar 2-D and 3-D Green’s Function in Rectangular Coordinates 566 10.4 General Procedure for Construction of Scalar 2-D and 3-D Green’s Functions in Cylindrical Coordinates 569 10.5 General Procedure for Construction of Scalar 3-D Green’s Functions in Spherical Coordinates 572 10.6 General Formulation for Source-Excited 3-D Separable EM Vector Wave Problems Using Dyadic Green’s Functions 575 10.7 Some Specific Green’s Functions for 2-D Problems 583 10.7.1 Fields of a Uniform Electric Line Source 583 10.7.2 Fields of an Infinite Periodic Array of Electric Line Sources 590 10.7.3 Line Source-Excited PEC Circular Cylinder Green’s Function 591 10.7.4 A Cylindrical Wave Series Expansion 596 10.7.5 Line Source Excitation of a PEC Wedge 598 10.7.6 Line Source Excitation of a PEC Parallel Plate Waveguide 602 10.7.7 The Fields of a Line Dipole Source 606 10.7.8 Fields of a Magnetic Line Source on an Infinite Planar Impedance Surface 608 10.7.9 Fields of a Magnetic Line Dipole Source on an Infinite Planar Impedance Surface 612 10.7.10 Circumferentially Propagating Surface Fields of a Line Source Excited Impedance Circular Cylinder 614 10.7.11 Analysis of Circumferentially Propagating Waves for a Line Dipole Source-Excited Impedance Circular Cylinder 617 10.7.12 Fields of a Traveling Wave Line Source 619 10.7.13 Traveling Wave Line Source Excitation of a PEC Wedge and a PEC Cylinder 620 10.8 Examples of Some Alternative Representations of Green’s Functions for Scalar 3-D Point Source-Excited Cylinders, Wedges and Spheres 623 10.8.1 3-D Scalar Point Source-Excited Circular Cylinder Green’s Function 623 10.8.2 3-D Scalar Point Source Excitation of a Wedge 630 10.8.3 Angularly and Radially Propagating 3-D Scalar Point Source Green’s Function for a Sphere 632 10.8.4 Kontorovich–Lebedev Transform and MacDonald Based Approaches for Constructing an Angularly Propagating 3-D Point Source Scalar Wedge Green’s Function 640 10.8.5 Analysis of the Fields of a Vertical Electric or Magnetic Current Point Source on a PEC Sphere 647 10.9 General Procedure for Construction of EM Dyadic Green’s Functions for Source-Excited Separable Canonical Problems via Scalar Green’s Functions 652 10.9.1 Summary of Procedure to Obtain the EM Fields of Arbitrarily Oriented Point Sources Exciting Canonical Separable Configurations 653 10.10 Completeness of the Eigenfunction Expansion of the Dyadic Green's Function at the Source Point 665 References 669 11 Method of Factorization and the Wiener–Hopf Technique for Analyzing Two- Part EM Wave Problems 670 11.1 The Wiener–Hopf Procedure 670 11.2 The Dual Integral Equation Approach 682 11.3 The Jones Method 691 References 696 12 Integral Equation-Based Methods for the Numerical Solution of Nonseparable EM Radiation and Scattering Problems 697 12.1 Introduction 697 12.2 Boundary Integral Equations 697 12.2.1 The Electric Field Integral Equation (EFIE) 699 12.2.2 The Magnetic Field Integral Equation (MFIE) 700 12.2.3 Combined Field and Combined Source Integral Equations 701 12.2.4 Impedance Boundary Condition 702 12.2.5 Boundary Integral Equation for a Homogeneous Material Volume 703 12.3 Volume Integral Equations 705 12.4 The Numerical Solution of Integral Equations 706 12.4.1 The Minimum Square-Error Method 706 12.4.2 The Method of Moments (MoM) 708 12.4.3 Simplification of the MoM Impedance Matrix Integrals 710 12.4.4 Expansion and Testing Functions 713 12.4.5 Low-Frequency Break-Down 718 12.5 Iterative Solution of Large MoM Matrices 720 12.5.1 Fast Iterative Solution of MoM Matrix Equations 721 12.5.2 The Fast Multipole Method (FMM) 725 12.5.3 Multilevel FMM and Fast Fourier Transform FMM 730 12.6 Antenna Modeling with the Method of Moments 732 12.7 Aperture Coupling with the Method of Moments 734 12.8 Physical Optics Methods 736 12.8.1 Physical Optics for a PEC Surface 736 12.8.2 Iterative Physical Optics 738 References 740 13 Introduction to Characteristic Modes 742 13.1 Introduction 742 13.2 Characteristic Modes from the EFIE for a Conducting Surface 743 13.2.1 Electric Field Integral Equation and Radiation Operator 743 13.2.2 Eigenfunctions of the Electric Field Radiation Operator 743 13.2.3 Characteristic Modes from the EFIE Impedance Matrix 745 13.3 Computation of Characteristic Modes 746 13.4 Solution of the EFIE Using Characteristic Modes 748 13.5 Tracking Characteristic Modes with Frequency 749 13.6 Antenna Excitation Using Characteristic Modes 749 References 750 14 Asymptotic Evaluation of Radiation and Diffraction Type Integrals for High Frequencies 752 14.1 Introduction 752 14.2 Steepest Descent Techniques for the Asymptotic Evaluation of Radiation Integrals 752 14.2.1 Topology of the Exponent in the Integrand Containing a First-Order Saddle Point 753 14.2.2 Asymptotic Evaluation of Integrals Containing a First-Order Saddle Point in Its Integrand Which Is Free of Singularities 756 14.2.3 Asymptotic Evaluation of Integrals Containing a Higher-Order Saddle Point in Its Integrand Which Is Free of Singularities 760 14.2.4 Pauli–Clemmow Method (PCM) for the Asymptotic Evaluation of Integrals Containing a First-Order Saddle Point Near a Simple Pole Singularity 763 14.2.5 Van der Waerden Method (VWM) for the Asymptotic Evaluation of Integrals Containing a First-Order Saddle Point Near a Simple Pole Singularity 773 14.2.6 Relationship Between PCM and VWM Leading to a Generalized PCM (or GPC) Solution 775 14.2.7 An Extension of PCM for Asymptotic Evaluation of an Integral Containing a First-Order Saddle Point and a Nearby Double Pole 777 14.2.8 An Extension of PCM for Asymptotic Evaluation of an Integral Containing a First-Order Saddle Point and Two Nearby First-Order Poles 779 14.2.9 An Extension of VWM for Asymptotic Evaluation of an Integral Containing a First-Order Saddle Point and a Nearby Double Pole 783 14.2.10 Nonuniform Asymptotic Evaluation of an Integral Containing a Saddle Point and a Branch Point 784 14.2.11 Uniform Asymptotic Evaluation of an Integral Containing a Saddle Point and a Nearby Branch Point 789 14.3 Asymptotic Evaluation of Integrals with End Points 791 14.3.1 Watson’s Lemma for Integrals 792 14.3.2 Generalized Watson’s Lemma for Integrals 792 14.3.3 Integration by Parts for Asymptotic Evaluation of a Class of Integrals 792 14.4 Asymptotic Evaluation of Radiation Integrals Based on the Stationary Phase Method 794 14.4.1 Stationary Phase Evaluation of 1-D Infinite Integrals 794 14.4.2 Nonuniform Stationary Phase Evaluation of 1-D Integrals with End Points 795 14.4.3 Uniform Stationary Phase Evaluation of 1-D Integrals with a Nearby End Point 796 14.4.4 Nonuniform Stationary Phase Evaluation of 2-D Infinite Integrals 801 References 816 15 Physical and Geometrical Optics 818 15.1 The Physical Optics (PO) Approximation for PEC Surfaces 818 15.2 The Geometrical Optics (GO) Ray Field 820 15.3 GO Transport Singularities 824 15.4 Wavefronts, Stationary Phase, and GO 828 15.5 GO Incident and Reflected Ray Fields 832 15.6 Uniform GO Valid at Smooth Caustics 840 References 854 16 Geometrical and Integral Theories of Diffraction 855 16.1 Geometrical Theory of Diffraction and Its Uniform Version (UTD) 855 16.2 UTD for an Edge in an Otherwise Smooth PEC Surface 861 16.3 UTD Slope Diffraction for an Edge 872 16.4 An Alternative Uniform Solution (the UAT) for Edge Diffraction 874 16.5 UTD Solutions for Fields of Sources in the Presence of Smooth PEC Convex Surfaces 874 16.5.1 UTD Analysis of the Scattering by a Smooth, Convex Surface 876 16.5.2 UTD for the Radiation by Antennas on a Smooth, Convex Surface 885 16.5.3 UTD Analysis of the Surface Fields of Antennas on a Smooth, Convex Surface 901 16.6 UTD for a Vertex 913 16.7 UTD for Edge-Excited Surface Rays 915 16.8 The Equivalent Line Current Method (ECM) 921 16.8.1 Line Type ECM for Edge-Diffracted Ray Caustic Field Analysis 922 16.9 Equivalent Line Current Method for Interior PEC Waveguide Problems 926 16.9.1 TE y Case 927 16.9.2 TM y Case 932 16.10 The Physical Theory of Diffraction (PTD) 933 16.10.1 PTD for Edged Bodies - A Canonical Edge Diffraction Problem in the PTD Development 936 16.10.2 Details of PTD for 3-D Edged Bodies 937 16.10.3 Reduction of PTD to 2-D Edged Bodies 939 16.11 On the PTD for Aperture Problems 940 16.12 Time-Domain Uniform Geometrical Theory of Diffraction (TD-UTD) 940 16.12.1 Introductory Comments 940 16.12.2 Analytic Time Transform (ATT) 941 16.12.3 TD-UTD for a General PEC Curved Wedge 942 References 945 17 Development of Asymptotic High-Frequency Solutions to Some Canonical Problems 951 17.1 Introduction 951 17.2 Development of UTD Solutions for Some Canonical Wedge Diffraction Problems 951 17.2.1 Scalar 2-D Line Source Excitation of a Wedge 952 17.2.2 Scalar Plane Wave Excitation of a Wedge 958 17.2.3 Scalar Spherical Wave Excitation of a Wedge 960 17.2.4 EM Plane Wave Excitation of a PEC Wedge 965 17.2.5 EM Conical Wave Excitation of a PEC Wedge 968 17.2.6 EM Spherical Wave Excitation of a PEC Wedge 971 17.3 Canonical Problem of Slope Diffraction by a PEC Wedge 974 17.4 Development of a UTD Solution for Scattering by a Canonical 2-D PEC Circular Cylinder and Its Generalization to a Convex Cylinder 978 17.4.1 Field Analysis for the Shadowed Part of the Transition Region 982 17.4.2 Field Analysis for the Illuminated Part of the Transition Region 985 17.5 A Collective UTD for an Efficient Ray Analysis of the Radiation by Finite Conformal Phased Arrays on Infinite PEC Circular Cylinders 991 17.5.1 Finite Axial Array on a Circular PEC Cylinder 992 17.5.2 Finite Circumferential Array on a Circular PEC Cylinder 999 17.6 Surface, Leaky, and Lateral Waves Associated with Planar Material Boundaries 1004 17.6.1 Introduction 1004 17.6.2 The EM Fields of a Magnetic Line Source on a Uniform Planar Impedance Surface 1004 17.6.3 EM Surface and Leaky Wave Fields of a Uniform Line Source over a Planar Grounded Material Slab 1011 17.6.4 An Analysis of the Lateral Wave Phenomena Arising in the Problem of a Vertical Electric Point Current Source over a Dielectric Half Space 1019 17.7 Surface Wave Diffraction by a Planar, Two-Part Impedance Surface: Development of a Ray Solution 1032 17.7.1 TE z Case 1033 17.7.2 TM z Case 1036 17.8 Ray Solutions for Special Cases of Discontinuities in Nonconducting or Penetrable Boundaries 1038 References 1039 18 EM Beams and Some Applications 1042 18.1 Introduction 1042 18.2 Astigmatic Gaussian Beams 1043 18.2.1 Paraxial Wave Equation Solutions 1043 18.2.2 2-D Beams 1044 18.2.3 3-D Astigmatic Gaussian Beams 1047 18.2.4 3-D Gaussian Beam from a Gaussian Aperture Distribution 1048 18.2.5 Reflection of Astigmatic Gaussian Beams (GBs) 1050 18.3 Complex Source Beams and Relation to GBs 1051 18.3.1 Introduction to Complex Source Beams (CSBs) 1051 18.3.2 Complex Source Beam from Scalar Green’s Function 1051 18.3.3 Representation of Arbitrary EM Fields by a CSB Expansion 1054 18.3.4 Edge Diffraction of an Incident CSB by a Curved Conducting Wedge 1056 18.4 Pulsed Complex Source Beams in the Time Domain 1061 Index 1105

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Book SynopsisTable of Contents Introduction xxiii Assessment Test Ivi Answers to Assessment Test lxxvii Chapter 1 Introducing Cloud Computing Configurations and Deployments 1 Introducing Cloud Computing 4 Virtualization 7 Cloud Service Models 10 Cloud Reference Designs and Delivery Models 14 Introducing Cloud Concepts and Components 16 Connecting the Cloud to the Outside World 18 Deciding Whether to Move to the Cloud 18 Selecting Cloud Compute Resources 18 Hypervisor Affinity Rules 19 Validating and Preparing for the Move to the Cloud 19 Choosing Elements and Objects in the Cloud 20 Internet of Things 21 Machine Learning/Artificial Intelligence (AI) 21 Creating and Validating a Cloud Deployment 22 The Cloud Shared Resource Pooling Model 23 Organizational Uses of the Cloud 27 Scaling and Architecting Cloud Systems Based on Requirements 29 Understanding Cloud Performance 29 Delivering High Availability Operations 30 Managing and Connecting to Your Cloud Resources 30 Is My Data Safe? (Replication and Synchronization) 32 Understanding Load Balancers 34 Cloud Testing 35 Verifying System Requirements 36 Correct Scaling for Your Requirements 36 Making Sure the Cloud Is Always Available 37 Remote Management of VMs 39 Monitoring Your Cloud Resources 41 Writing It All Down (Documentation) 41 Creating Baselines 41 Shared Responsibility Model 42 Summary 43 Exam Essentials 43 Written Lab 45 Review Questions 46 Chapter 2 Cloud Deployments 51 Executing a Cloud Deployment 58 Understanding Deployment and Change Management 59 Cloud Deployment Models 65 Network Deployment Considerations 67 Service Level Agreements 77 Matching Data Center Resources to Cloud Resources 78 What Are Available and Proposed Hardware Resources? 78 Templates and Images 81 Physical Resource High Availability 82 Introducing Disaster Recovery 82 Physical Hardware Performance Benchmarks 83 Cost Savings When Using the Cloud 83 Energy Savings in the Cloud 84 Shared vs. Dedicated Hardware Resources in a Cloud Data Center 84 Microservices 84 Configuring and Deploying Storage 86 Identifying Storage Configurations 86 Storage Provisioning 90 Storage Priorities: Understanding Storage Tiers 94 Managing and Protecting Your Stored Data 95 Storage Security Considerations 102 Accessing Your Storage in the Cloud 105 Performing a Server Migration 105 Different Types of Server Migrations 106 Addressing Application Portability 109 Workload Migration Common Procedures 110 Examining Infrastructure Capable of Supporting a Migration 110 Managing User Identities and Roles 111 RBAC: Identifying Users and What Their Roles Are 112 What Happens When You Authenticate? 113 Understanding Federation 113 Single Sign-On Systems 113 Understanding Infrastructure Services 114 Summary 117 Exam Essentials 118 Written Lab 119 Review Questions 120 Chapter 3 Security in the Cloud 125 Cloud Security Compliance and Configurations 128 Establishing Your Company’s Security Policies 130 Selecting and Applying the Security Policies to Your Cloud Operations 130 Some Common Regulatory Requirements 130 Encrypting Your Data 134 Remote Access Protocols 139 Automating Cloud Security 140 Security Best Practices 141 Access Control 144 Accessing Cloud-Based Objects 144 Cloud Service Models and Security 146 Cloud Deployment Models and Security 147 Role-Based Access Control 148 Mandatory Access Control 148 Discretionary Access Control 148 Multifactor Authentication 149 Single Sign-On 149 Summary 149 Exam Essentials 150 Written Lab 151 Review Questions 153 Chapter 4 Implementing Cloud Security 157 Implementing Security in the Cloud 159 Data Classification 159 Segmenting Your Deployment 160 Implementing Encryption 162 Applying Multifactor Authentication 163 Regulatory and Compliance Issues During Implementation 164 Cloud Access Security Broker 165 Automating Cloud Security 165 Automation Tools 166 Techniques for Implementing Cloud Security 168 Security Services 170 Summary 173 Exam Essentials 174 Written Lab 175 Review Questions 177 Chapter 5 Maintaining Cloud Operations 183 Applying Security Patches 187 Patching Cloud Resources 187 Patching Methodologies 189 Patching Order of Operations and Dependencies 193 Updating Cloud Elements 193 Hotfix 193 Patch 194 Version Update 194 Rollback 195 Workflow Automation 195 Continuous Integration and Continuous Deployment 196 Virtualization Automation Tools and Activities 197 Storage Operations 199 Types of Backups 199 Backup Targets 203 Backup and Restore Operations 205 Summary 206 Exam Essentials 207 Written Lab 209 Review Questions 210 Chapter 6 Disaster Recovery, Business Continuity, and Ongoing Maintenance 215 Implementing a Disaster Recovery and Business Continuity Plan 216 Service Provider Responsibilities and Capabilities 217 Disaster Recovery Models and Techniques 219 Business Continuity 225 Establishing a Business Continuity Plan 225 Establishing Service Level Agreements 227 Cloud Maintenance 228 Establishing Maintenance Windows 228 Maintenance Interruptions to Operations 229 Maintenance Automation Impact and Scope 229 Common Maintenance Automation Tasks 229 Summary 233 Exam Essentials 234 Written Lab 235 Review Questions 236 Chapter 7 Cloud Management 241 Cloud Metrics 244 Monitoring Your Deployment 246 Cloud Support Agreements 250 Standard Cloud Maintenance Responsibilities 250 Configuration Management Applications and Tools 251 Change Management Processes 251 Adding and Removing Cloud Resources 252 Determining Usage Patterns 252 Bursting 252 Migrating Between Cloud Providers 252 Scaling Resources to Meet Requirements 253 Extending the Scope of the Cloud 256 Understanding Application Life Cycles 256 Organizational Changes 257 Managing Account Provisioning 258 Account Identification 258 Authentication 259 Authorization 259 Lockout Policies 259 Password Complexity 259 Account Automation and Orchestration 260 Summary 261 Exam Essentials 262 Written Lab 263 Review Questions 264 Chapter 8 Cloud Management Baselines, Performance, and SLAs 269 Measuring Your Deployment Against the Baseline 272 Object Tracking for Baseline Validation 273 Applying Changes to the Cloud to Meet Baseline Requirements 277 Changing Operations to Meet Expected Performance/Capacity Requirements 280 Cloud Accounting, Chargeback, and Reporting 281 Summary 284 Exam Essentials 285 Written Lab 286 Review Questions 287 Chapter 9 Troubleshooting 291 Incident Management 294 Incident Types 294 Logging Incidents 298 Prioritizing Incidents 298 Preparation 299 Templates 300 Time Synchronization 301 Workflow 301 Troubleshooting Cloud Capacity Issues 301 Capacity Boundaries in the Cloud 301 Troubleshooting Automation and Orchestration 304 Process and Workflow Issues 305 Summary 307 Exam Essentials 308 Written Lab 309 Review Questions 310 Chapter 10 Troubleshooting Networking and Security Issues and Understanding Methodologies 315 Troubleshooting Cloud Networking Issues 317 Identifying the Common Networking Issues in the Cloud 318 Network Troubleshooting and Connectivity Tools 324 Remote Access Tools 333 Troubleshooting Security Issues 336 Account Privilege Escalation 336 Network Access Issues 337 Authentication 337 Authorization 337 Federations 338 Certificate Configuration Issues 338 Device- Hardening Settings 338 External Attacks 339 Internal Attacks 339 Maintain Sufficient Security Controls and Processes 339 Network Access Tunneling and Encryption 340 Troubleshooting Methodology 340 Identifying the Problem 341 Establishing a Theory 341 Testing the Theory 343 Creating and Implementing a Plan of Action 344 Verifying the Resolution 344 Documenting the Ordeal 344 Summary 344 Exam Essentials 345 Written Lab 346 Review Questions 347 Index 375

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Book SynopsisThe Technology of Discovery Incisive discussions of a critical mission-enabling technology for deep space missions In The Technology of Discovery: Radioisotope Thermoelectric Generators and Thermoelectric Technologies for Space Exploration, distinguished JPL engineer and manager David Woerner delivers an insightful discussion of how radioisotope thermoelectric generators (RTGs) are used in the exploration of space. It also explores their history, function, their market potential, and the governmental forces that drive their production and design. Finally, it presents key technologies incorporated in RTGs and their potential for future missions and design innovation. The author provides a clear and understandable treatment of the subject, ranging from straightforward overviews of the technology to complex discussions of the field of thermoelectrics. Included is also background on NASA's decision to resurrect the GPHS-RTG and discussion of the future of commercialiTable of ContentsForeward xi Note from the Series Editor xiii Preface xv Authors xix Reviewers xxi Acknowledgments xxiii Glossary xxv List of Acronyms and Abbreviations xxxiii 1 The History of the Invention of Radioisotope Thermoelectric Generators (RTGs) for Space Exploration 1 Chadwick D. Barklay References 5 2 The History of the United States’s Flight and Terrestrial RTGs 7 Andrew J. Zillmer 2.1 Flight RTGs 7 2.1.1 SNAP Flight Program 7 2.1.1.1 Snap-3 8 2.1.1.2 Snap-9 8 2.1.1.3 Snap-19 9 2.1.1.4 Snap-27 11 2.1.2 Transit-RTG 13 2.1.3 Multi-Hundred-Watt RTG 13 2.1.4 General Purpose Heat Source RTG 15 2.1.4.1 General Purpose Heat Source 15 2.1.4.2 GPHS-RTG System 16 2.1.5 Multi-Mission Radioisotope Thermoelectric Generator 17 2.1.6 US Flight RTGs 18 2.2 Unflown Flight RTGs 18 2.2.1.1 Snap-1 18 2.2.1.2 Snap-11 18 2.2.1.3 Snap-13 18 2.2.1.4 Snap-17 22 2.2.1.5 Snap-29 22 2.2.1.6 Selenide Isotope Generator 23 2.2.1.7 Modular Isotopic Thermoelectric Generator 24 2.2.1.8 Modular RTG 24 2.3 Terrestrial RTGs 25 2.3.1 SNAP Terrestrial RTGs 25 2.3.1.1 Snap-7 25 2.3.1.2 Snap-15 26 2.3.1.3 Snap-21 26 2.3.1.4 Snap-23 26 2.3.2 Sentinel 25 and 100 Systems 27 2.3.3 Sentry 28 2.3.4 URIPS-P 1 28 2.3.5 RG-1 29 2.3.6 BUP-500 30 2.3.7 Millibatt-1000 31 2.4 Conclusion 31 References 31 3 US Space Flights Enabled by RTGs 35 Young H. Lee and Brian K. Bairstow 3.1 SNAP-3B Missions (1961) 35 3.1.1 Transit 4A and Transit 4B 35 3.2 SNAP-9A Missions (1963–1964) 36 3.2.1 Transit 5BN-1, 5BN-2, and 5BN-3 36 3.3 SNAP-19 Missions (1968–1975) 38 3.3.1 Nimbus-B and Nimbus III 38 3.3.2 Pioneer 10 and 11 41 3.3.3 Viking 1 and 2 Landers 43 3.4 SNAP-27 Missions (1969–1972) 45 3.4.1 Apollo 12–17 45 3.5 Transit-RTG Mission (1972) 47 3.5.1 TRIAD 47 3.6 MHW-RTG Missions (1976–1977) 48 3.6.1 Lincoln Experimental Satellites 8 and 9 48 3.6.2 Voyager 1 and 2 50 3.7 GPHS-RTG Missions (1989–2006) 52 3.7.1 Galileo 52 3.7.2 Ulysses 53 3.7.3 Cassini 55 3.7.4 New Horizons 57 3.8 MMRTG Missions: (2011-Present (2021)) 59 3.8.1 Curiosity 59 3.8.2 Perseverance 61 3.8.3 Dragonfly–Scheduled Future Mission 62 3.9 Discussion of Flight Frequency 64 3.10 Summary of US Missions Enabled by RTGs 73 References 74 4 Nuclear Systems Used for Space Exploration by Other Countries 77 Christofer E. Whiting 4.1 Soviet Union 77 4.2 China 81 References 82 5 Nuclear Physics, Radioisotope Fuels, and Protective Components 85 Michael B.R. Smith, Emory D. Collins, David W. DePaoli, Nidia C. Gallego, Lawrence H. Heilbronn, Chris L. Jensen, Kaara K. Patton, Glenn R. Romanoski, George B. Ulrich, Robert M. Wham, and Christofer E. Whiting 5.1 Introduction 85 5.2 Introduction to Nuclear Physics 86 5.2.1 The Atom 86 5.2.2 Radioactivity and Decay 88 5.2.3 Emission of Radiation 90 5.2.3.1 Alpha Decay 91 5.2.3.2 Beta Decay 92 5.2.3.3 Photon Emission 92 5.2.3.4 Neutron Emission 93 5.2.3.5 Decay Chains 94 5.2.4 Interactions of Radiation with Matter 94 5.2.4.1 Charged Particle Interactions with Matter 96 5.2.4.2 Neutral Particle Interactions with Matter 97 5.2.4.3 Biological Interactions of Radiation with Matter 100 5.3 Historic Radioisotope Fuels 102 5.3.1 Polonium-210 104 5.3.2 Cerium-144 104 5.3.3 Strontium-90 105 5.3.4 Curium-242 106 5.3.5 Curium-244 106 5.3.6 Cesium-137 107 5.3.7 Promethium-147 107 5.3.8 Thallium-204 108 5.4 Producing Modern PuO2 108 5.4.1 Cermet Target Design, Fabrication, and Irradiation 110 5.4.2 Improved Target Design 111 5.4.3 Post-Irradiation Chemical Processing 112 5.4.4 Waste Management 113 5.4.5 Conversion to Production Mode of Operation 114 5.5 Fuel, Cladding, and Encapsulations for Modern Spaceflight RTGs 115 5.5.1 Evolution of Radioisotope Heat Source Protection 115 5.5.2 General Purpose Heat Source 119 5.5.3 Fine Weave Pierced Fabric (FWPF) 120 5.5.4 Carbon-Bonded Carbon Fiber (CBCF) 121 5.5.5 Heat Transfer Considerations 122 5.5.6 Cladding 122 5.6 Summary 125 References 125 6 A Primer on the Underlying Physics in Thermoelectrics 133 Hsin Wang 6.1 Underlying Physics in Thermoelectric Materials 133 6.1.1 Reciprocal Lattice and Brillouin Zone 135 6.1.2 Electronic Band Structure 135 6.1.3 Lattice Vibration and Phonons 138 6.2 Thermoelectric Theories and Limitations 141 6.2.1 Best Thermoelectric Materials 141 6.2.2 Imbalanced Thermoelectric Legs 143 6.3 Thermal Conductivity and Phonon Scattering 144 6.3.1 Highlights of SiGe 145 References 145 7 End-to-End Assembly and Pre-flight Operations for RTGs 151 Shad E. Davis 7.1 GPHS Assembly 151 7.2 RTG Fueling and Testing 159 7.3 RTG Delivery, Spacecraft Checkout, and RTG Integration for Flight 172 References 181 8 Lifetime Performance of Spaceborne RTGs 183 Christofer E. Whiting and David Friedrich Woerner 8.1 Introduction 183 8.2 History of RTG Performance at a Glance 185 8.3 RTG Performance by Generator Type 189 8.3.1 Snap-3B 189 8.3.2 Snap-9A 189 8.3.3 Snap-19B 191 8.3.4 Snap-27 194 8.3.5 Transit-RTG 196 8.3.6 Snap-19 197 8.3.7 Multi-Hundred Watt RTG 201 8.3.8 General Purpose Heat Source RTG 204 8.3.9 Multi-Mission RTG 207 References 210 9 Modern Analysis Tools and Techniques for RTGs 213 Christofer E. Whiting, Michael B.R. Smith, and Thierry Caillat 9.1 Analytical Tools for Evaluating Performance Degradation and Extrapolating Future Power 213 9.1.1 Integrated Rate Law Equation 214 9.1.2 Multiple Degradation Mechanisms 215 9.1.3 Solving for k′ and x 217 9.1.4 Integrated Rate Equation 220 9.1.5 Analysis of Residuals 220 9.1.6 Rate Law Equations: RTGs versus Chemistry versus Math 221 9.1.6.1 Application to RTG Performance 222 9.2 Effects of Thermal Inventory on Lifetime Performance 222 9.2.1 Analysis of GPHS-RTG 223 9.2.2 Analysis of MMRTG 226 9.3 (Design) Life Performance Prediction 228 9.3.1 RTG’s Degradation Mechanisms 229 9.3.2 Physics-based RTG Life Performance Prediction 233 9.4 Radioisotope Power System Dose Estimation Tool (RPS-DET) 235 9.4.1 Motivation 235 9.4.2 RPS-DET Software Components 236 9.4.3 RPS-DET Geometries 237 9.4.4 RPS-DET Source Terms and Radiation Transport 238 9.4.5 Simulation Results 239 9.4.6 Validation and Verification 240 9.4.7 Conclusion 240 References 241 10 Advanced US RTG Technologies in Development 245 Chadwick D. Barklay 10.1 Introduction 245 10.1.1 Background 246 10.2 Skutterudite-based Thermoelectric Converter Technology for a Potential MMRTG Retrofit 247 Thierry Caillat, Stan Pinkowski, Ike C. Chi, Kevin L. Smith, Jong-Ah Paik, Brian Phan, Ying Song, Joe VanderVeer, Russell Bennett, Steve Keyser, Patrick E. Frye, Karl A. Wefers, Andrew M. Lane, and Tim Holgate 10.2.1 Introduction 247 10.2.2 Thermoelectric Couple and 48-Couple Module Design and Fabrication 248 10.2.3 Performance Testing of Couples and 48-Couple Module 252 10.2.4 Generator Life Performance Prediction 255 10.3 Next Generation RTG Technology Evolution 257 Chadwick D. Barklay 10.3.1 Introduction 257 10.3.2 Challenges to Reestablishing a Production Capability 260 10.3.2.1 Design Trades 260 10.3.2.2 Silicon Germanium Unicouple Production 261 10.3.2.3 Converter Assembly 262 10.3.3 Opportunities for Enhancements 264 10.4 Considerations for Emerging Commercial RTG Concepts 265 Chadwick D. Barklay 10.4.1 Introduction 265 10.4.2 Challenges for Commercial Space RTGs 266 10.4.2.1 Radioisotopes 267 10.4.2.2 Specific Power 267 10.4.2.3 Launch Approval 268 10.4.3 Launch Safety Analyses and Testing 270 10.4.3.1 Modeling Approaches 270 10.4.3.2 Safety Testing 271 10.4.3.3 Leveraging Legacy Design Concepts 271 References 273 Index 277

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Book SynopsisTable of ContentsPreface xvii 1 Introduction to the Internet of Things: Opportunities, Perspectives and Challenges 1 F. Leo John, D. Lakshmi and Manideep Kuncharam 1.1 Introduction 2 1.1.1 The IOT Data Sources 4 1.1.2 IOT Revolution 6 1.2 IOT Platform 8 1.3 IOT Layers and its Protocols 10 1.4 Architecture and Future Problems for IOT Protection 27 1.5 Conclusion 32 References 32 2 Role of Battery Management System in IoT Devices 35 R. Deepa, K. Mohanraj, N. Balaji and P. Ramesh Kumar 2.1 Introduction 36 2.1.1 Types of Lithium Batteries 36 2.1.1.1 Lithium Battery (LR) 37 2.1.1.2 Button Type Lithium Battery (BLB) 37 2.1.1.3 Coin Type Lithium Battery (CLB) 37 2.1.1.4 Lithium-Ion Battery (LIB) 37 2.1.1.5 Lithium-Ion Polymer Battery (LIP) 37 2.1.1.6 Lithium Cobalt Battery (LCB) 38 2.1.1.7 Lithium Manganese Battery (LMB) 38 2.1.1.8 Lithium Phosphate Battery (LPB) 38 2.1.1.9 Lithium Titanate Battery (LTB) 38 2.1.2 Selection of the Battery 38 2.1.2.1 Nominal Voltage 39 2.1.2.2 Operating Time 39 2.1.2.3 Time for Recharge and Discharge 39 2.1.2.4 Cut Off Voltage 39 2.1.2.5 Physical Dimension 39 2.1.2.6 Environmental Conditions 40 2.1.2.7 Total Cost 40 2.2 Internet of Things 41 2.2.1 IoT – Battery Market 43 2.2.2 IoT - Battery Marketing Strategy 44 2.2.2.1 Based on the Type 44 2.2.2.2 Based on the Rechargeability 45 2.2.2.3 Based on the Region 45 2.2.2.4 Based on the Application 45 2.3 Power of IoT Devices in Battery Management System 45 2.3.1 Power Management 46 2.3.2 Energy Harvesting 47 2.3.3 Piezo-Mechanical Harvesting 48 2.3.4 Batteries Access to IoT Pioneers 49 2.3.5 Factors for Powering IoT Devices 49 2.3.5.1 Temperature 50 2.3.5.2 Environmental Factors 50 2.3.5.3 Power Budget 50 2.3.5.4 Form Factor 51 2.3.5.5 Status of the Battery 51 2.3.5.6 Shipment 52 2.4 Battery Life Estimation of IoT Devices 52 2.4.1 Factors Affecting the Battery Life of IoT Devices 53 2.4.2 Battery Life Calculator 53 2.4.3 Sleep Modes of IoT Processors 55 2.4.3.1 No Sleep 55 2.4.3.2 Modem Sleep 55 2.4.3.3 Light Sleep 55 2.4.3.4 Deep Sleep 56 2.4.4 Core Current Consumption 56 2.4.5 Peripheral Current Consumption 59 2.5 IoT Networking Technologies 59 2.5.1 Selection of an IoT Sensor 60 2.5.2 IoT - Battery Technologies 60 2.5.3 Battery Specifications 61 2.5.4 Battery Shelf Life 62 2.6 Conclusion 62 References 63 3 Smart Grid - Overview, Challenges and Security Issues 67 C. N. Vanitha, Malathy S. and S.A. Krishna 3.1 Introduction to the Chapter 68 3.2 Smart Grid and Its Uses 69 3.3 The Grid as it Stands-What’s at Risk? 72 3.3.1 Reliability 73 3.3.2 Efficiency 73 3.3.3 Security 74 3.3.4 National Economy 74 3.4 Creating the Platform for Smart Grid 75 3.4.1 Consider the ATM 76 3.5 Smart Grid in Power Plants 77 3.5.1 Distributed Power Flow Control 78 3.5.2 Power System Automation 79 3.5.3 IT Companies Disrupting the Energy Market 79 3.6 Google in Smart Grid 80 3.7 Smart Grid in Electric Cars 81 3.7.1 Vehicle-to-Grid 82 3.7.2 Challenges in Smart Grid Electric Cars 83 3.7.3 Toyota and Microsoft in Smart Electric Cars 84 3.8 Revisit the Risk 85 3.8.1 Reliability 85 3.8.2 Efficiency 86 3.8.3 Security 87 3.8.4 National Economy 88 3.9 Summary 88 References 88 4 IoT-Based Energy Management Strategies in Smart Grid 91 Seyed Ehsan Ahmadi and Sina Delpasand 4.1 Introduction 92 4.2 Application of IoT for Energy Management in Smart Grids 93 4.3 Energy Management System 94 4.3.1 Objectives of EMS 94 4.3.2 Control Frameworks of EMS 95 4.3.2.1 Centralized Approach 96 4.3.2.2 Decentralized Approach 97 4.3.2.3 Hierarchical Approach 97 4.4 Types of EMS at Smart Grid 98 4.4.1 Smart Home EMS 99 4.4.2 Smart Building EMS 100 4.5 Participants of EMS 103 4.5.1 Network Operator 104 4.5.2 Data and Communication Technologies 105 4.5.3 Aggregators 107 4.6 DER Scheduling 108 4.7 Important Factors for EMS Establishment 111 4.7.1 Uncertainty Modeling and Management Methods 111 4.7.2 Power Quality Management 112 4.7.3 DSM and DR Programs 114 4.8 Optimization Approaches for EMS 115 4.8.1 Mathematical Approaches 117 4.8.2 Heuristic Approaches 118 4.8.3 Metaheuristic Approaches 119 4.8.4 Other Programming Approaches 119 4.9 Conclusion 121 References 121 5 Integrated Architecture for IoTSG: Internet of Things (IoT) and Smart Grid (SG) 127 Malathy S., K. Sangeetha, C. N. Vanitha and Rajesh Kumar Dhanaraj 5.1 Introduction 128 5.1.1 Designing of IoT Architecture 129 5.1.2 IoT Characteristics 132 5.2 Introduction to Smart Grid 134 5.2.1 Smart Grid Technologies (SGT) 136 5.3 Integrated Architecture of IoT and Smart Grid 138 5.3.1 Safety Concerns 140 5.3.2 Security Issues 142 5.4 Smart Grid Security Services Based on IoT 143 References 154 6 Exploration of Assorted Modernizations in Forecasting Renewable Energy Using Low Power Wireless Technologies for IoTSG 157 Logeswaran K., Suresh P., Ponselvakumar A.P., Savitha S., Sentamilselvan K. and Adhithyaa N. 6.1 Introduction to the Chapter 158 6.1.1 Fossil Fuels and Conventional Grid 158 6.1.2 Renewable Energy and Smart Grid 160 6.2 Intangible Architecture of Smart Grid (SG) 161 6.3 Internet of Things (IoT) 164 6.4 Renewable Energy Source (RES)- Key Technology for SG 167 6.4.1 Renewable Energy: Basic Concepts and Readiness 167 6.4.2 Natural Sources of Renewable Energy 169 6.4.3 Major Issues in Following RES to SG 173 6.4.4 Integration of RES with SG 176 6.4.5 SG Renewable Energy Management Facilitated by IoT 177 6.4.6 Case Studies on Smart Grid: Renewable Energy Perception 180 6.5 Low Power Wireless Technologies for IoTSG 181 6.5.1 Role of IoT in SG 181 6.5.2 Innovations in Low Power Wireless Technologies 182 6.5.3 Wireless Communication Technologies for IoTSG 183 6.5.4 Case Studies on Low Power Wireless Technologies Used in IoTSG 186 6.6 Conclusion 188 References 188 7 Effective Load Balance in IOTSG with Various Machine Learning Techniques 193 Thenmozhi K., Pyingkodi M. and Kanimozhi K. I. Introduction 194 II. IoT in Big Data 195 III. IoT in Machine Learning 197 IV. Machine Learning Methods in IoT 199 V. IoT with SG 200 VI. Deep Learning with IoT 201 VII. Challenges in IoT for SG 202 VIII. IoT Applications for SG 202 IX. Application of IoT in Various Domain 204 X. Conclusion 205 References 206 8 Fault and Delay Tolerant IoT Smart Grid 207 K. Sangeetha and P. Vishnu Raja 8.1 Introduction 207 8.1.1 The Structures of the Intelligent Network 209 8.1.1.1 Operational Competence 209 8.1.1.2 Energy Efficiency 209 8.1.1.3 Flexibility in Network Topology 210 8.1.1.4 Reliability 210 8.1.2 Need for Smart Grid 210 8.1.3 Motivation for Enabling Delay Tolerant IoT 211 8.1.4 IoT-Enabled Smart Grid 211 8.2 Architecture 212 8.3 Opportunities and Challenges in Delay Tolerant Network for the Internet of Things 215 8.3.1 Design Goals 215 8.4 Energy Efficient IoT Enabled Smart Grid 219 8.5 Security in DTN IoT Smart Grid 220 8.5.1 Safety Problems 220 8.5.2 Safety Works for the Internet of Things-Based Intelligent Network 221 8.5.3 Security Standards for the Smart Grid 222 8.5.3.1 The Design Offered by NIST 222 8.5.3.2 The Design Planned by IEEE 222 8.6 Applications of DTN IoT Smart Grid 224 8.6.1 Household Energy Management in Smart Grids 224 8.6.2 Data Organization System for Rechargeable Vehicles 224 8.6.3 Advanced Metering Infrastructure (AMI) 225 8.6.4 Energy Organization 226 8.6.5 Transmission Tower Protection 226 8.6.6 Online Monitoring of Power Broadcast Lines 227 8.7 Conclusion 227 References 228 9 Significance of Block Chain in IoTSG - A Prominent and Reliable Solution 235 S. Vinothkumar, S. Varadhaganapathy, R. Shanthakumari and M. Ramalingam 9.1 Introduction 236 9.2 Trustful Difficulties with Monetary Communications for IoT Forum 239 9.3 Privacy in Blockchain Related Work 242 9.4 Initial Preparations 244 9.4.1 Blockchain Overview 244 9.4.2 k-Anonymity 246 9.4.2.1 Degree of Anonymity 246 9.4.2.2 Data Forfeiture 247 9.5 In the IoT Power and Service Markets, Reliable Transactions and Billing 248 9.5.1 Connector or Bridge 250 9.5.2 Group of Credit-Sharing 251 9.5.3 Local Block 251 9.6 Potential Applications and Use Cases 253 9.6.1 Utilities and Energy 253 9.6.2 Charging of Electric Vehicles 253 9.6.3 Credit Transfer 254 9.7 Proposed Work Execution 254 9.7.1 Creating the Group of Energy Sharing 255 9.7.2 Handling of Transaction 255 9.8 Investigation of Secrecy and Trustworthy 259 9.8.1 Trustworthy 259 9.8.2 Privacy-Protection 260 9.8.2.1 Degree of Confidentiality 261 9.8.2.2 Data Forfeiture 263 9.8.3 Evaluation of Results 265 9.9 Conclusion 267 References 267 10 IoTSG in Maintenance Management 273 T.C. Kalaiselvi and C.N. Vanitha 10.1 Introduction to the Chapter 274 10.2 IoT in Smart Grid 276 10.2.1 Uses and Facilities in SG 278 10.2.2 Architectures in SG 280 10.3 IoT in the Generation Level, Transmission Level, Distribution Level 288 10.4 Challenges and Future Research Directions in SG 295 10.5 Components for Predictive Management 296 10.6 Data Management and Infrastructure of IoT for Predictive Management 298 10.6.1 PHM Algorithms for Predictive Management 303 10.6.2 Decision Making with Predictive Management 305 10.7 Research Challenges in the Maintenance of Internet of Things 310 10.8 Summary 315 References 315 11 Intelligent Home Appliance Energy Monitoring with IoT 319 S. Tamilselvan, D. Deepa, C. Poongodi, P. Thangavel and Sarumathi Murali 11.1 Introduction 320 11.2 Survey on Energy Monitoring 320 11.3 Internet of Things System Architecture 322 11.4 Proposed Energy Monitoring System with IoT 323 11.5 Energy Management Structure (Proposed) 324 11.6 Implementation of the System 325 11.6.1 Implementation of IoT Board 325 11.6.2 Software Implementation 325 11.7 Smart Home Automation Forecasts 326 11.7.1 Energy Measurement 326 11.7.2 Periodically Updating the Status in the Cloud 327 11.7.3 Irregularity Detection 328 11.7.4 Finding the Problems with the Device 328 11.7.5 Indicating the House Owner About the Issues 329 11.7.6 Suggestions for Remedial Actions 329 11.8 Energy Reduction Based on IoT 330 11.8.1 House Energy Consumption (HEC) - Cost Saving 330 11.9 Performance Evaluation 330 11.9.1 Data Analytics and Visualization 330 11.10 Benefits for Different User Categories 332 11.11 Results and Discussion with Benefits of User Categories 332 11.12 Summary 334 References 334 12 Applications of IoTSG in Smart Industrial Monitoring Environments 339 Mohanasundaram T., Vetrivel S.C., and Krishnamoorthy V. 12.1 Introduction 340 12.2 Energy Management 342 12.3 Role of IoT and Smart Grid in the Banking Industry 345 12.3.1 Application of IoT in the Banking Sector 346 12.3.1.1 Customer Relationship Management (crm) 347 12.3.1.2 Loan Sanctions 348 12.3.1.3 Customer Service 348 12.3.1.4 Leasing Finance Automation 348 12.3.1.5 Capacity Management 348 12.3.2 Application of Smart Grid in the Banking Sector 349 12.4 Role of IoT and Smart Grid in the Automobile Industry 349 12.4.1 Application of IoT in the Automobile Industry 350 12.4.1.1 What Exactly is the Internet of Things (IoT) Mean to the Automobile Sector? 350 12.4.1.2 Transportation and Logistics 351 12.4.1.3 Connected Cars 351 12.4.1.4 Fleet Management 352 12.4.2 Application of Smart Grid (SG) in the Automobile Industry 354 12.4.2.1 Smart Grid Can Change the Face of the Automobile Industry 355 12.4.2.2 Smart Grid and Energy Efficient Mobility System 357 12.5 Role of IoT and SG in Healthcare Industry 357 12.5.1 Applications of IoT in Healthcare Sector 358 12.5.2 Application of Smart Grid (SG) in Health Care Sector 360 12.6 IoT and Smart Grid in Energy Management - A Way Forward 360 12.7 Conclusion 362 References 363 13 Solar Energy Forecasting for Devices in IoT Smart Grid 365 K. Tamil Selvi, S. Mohana Saranya and R. Thamilselvan 13.1 Introduction 366 13.2 Role of IoT in Smart Grid 368 13.3 Clear Sky Models 370 13.3.1 REST2 Model 370 13.3.2 Kasten Model 370 13.3.3 Polynomial Fit 371 13.4 Persistence Forecasts 372 13.5 Regressive Methods 373 13.5.1 Auto-Regressive Model 373 13.5.2 Moving Average Model 373 13.5.3 Mixed Auto Regressive Moving Average Model 373 13.5.4 Mixed Auto Regressive Moving Average Model with Exogeneous Variables 374 13.6 Non-Linear Stationary Models 374 13.7 Linear Non-Stationary Models 376 13.7.1 Auto Regressive Integrated Moving Average Models 376 13.7.2 Auto-Regressive Integrated Moving Average Model with Exogenous Variables 376 13.8 Artificial Intelligence Techniques 377 13.8.1 Artificial Neural Network 377 13.8.2 Multi-Layer Perceptron 377 13.8.3 Deep Learning Model 380 13.8.3.1 Stacked Auto-Encoder 381 13.8.3.2 Deep Belief Network 382 13.8.3.3 Deep Recurrent Neural Network 383 13.8.3.4 Deep Convolutional Neural Network 384 13.8.3.5 Stacked Extreme Learning Machine 386 13.8.3.6 Generative Adversarial Network 386 13.8.3.7 Comparison of Deep Learning Models for Solar Energy Forecast 387 13.9 Remote Sensing Model 389 13.10 Hybrid Models 389 13.11 Performance Metrics for Forecasting Techniques 390 13.12 Conclusion 391 References 392 14 Utilization of Wireless Technologies in IoTSG for Energy Monitoring in Smart Devices 395 S. Suresh Kumar, A. Prakash, O. Vignesh and M. Yogesh Iggalore 14.1 Introduction to Internet of Things 396 14.2 IoT Working Principle 397 14.3 Benefits of IoT 398 14.4 IoT Applications 399 14.5 Introduction to Smart Home 399 14.5.1 Benefits of Smart Homes 400 14.6 Problem Statement 401 14.6.1 Methodology 401 14.7 Introduction to Wireless Communication 402 14.7.1 Merits of Wireless 402 14.8 How Modbus Communication Works 403 14.8.1 Rules for Modbus Addressing 404 14.8.2 Modbus Framework Description 404 14.8.2.1 Function Code 404 14.8.2.2 Cyclic Redundancy Check 405 14.8.2.3 Data Storage in Modbus 405 14.9 MQTT Protocol 406 14.9.1 Pub/Sub Architecture 406 14.9.2 MQTT Client Broker Communication 407 14.9.3 MQTT Standard Header Packet 407 14.9.3.1 Fixed Header 408 14.10 System Architecture 408 14.11 IoT Based Electronic Energy Meter-eNtroL 410 14.11.1 Components Used in eNtroL 411 14.11.2 PZEM-004t Energy Meter 411 14.11.3 Wi-Fi Module 412 14.11.4 Switching Device 413 14.11.5 230V AC to 5V Dc Converter 414 14.11.6 LM1117 IC- 5V to 3.3V Converter 414 14.12 AC Control System for Home Appliances – Switch2Smart 415 14.12.1 Opto-Coupler- H11AA1 IC 415 14.12.2 TRIAC Driven Opto Isolator- MOC3021M IC 416 14.12.3 Triac, Bt136-600 Ic 416 14.13 Scheduling Home Appliance Using Timer – Switch Binary 417 14.14 Hardware Design 418 14.14.1 Kaicad Overview 418 14.14.2 PCB Designing Using Kaicad 418 14.14.2.1 Designing of eNtroL Board Using Kaicad 418 14.14.2.2 Designing of Switch2smart Board Using Kaicad 420 14.14.2.3 Designing of Switch Binary Board Using Kaicad 421 14.15 Implementation of the Proposed System 422 14.16 Testing and Results 424 14.16.1 Testing of eNtrol 425 14.16.2 Testing of Switch2Smart 427 14.16.3 Testing of SwitchBinary 428 14.17 Conclusion 429 References 429 15 Smart Grid IoT: An Intelligent Energy Management in Emerging Smart Cities 431 R. S. Shudapreyaa, G. K. Kamalam, P. Suresh and K. Sentamilselvan 15.1 Overview of Smart Grid and IoT 432 15.1.1 Smart Grid 432 15.1.2 Smart Grid Data Properties 434 15.1.3 Operations on Smart Grid Data 435 15.2 IoT Application in Smart Grid Technologies 436 15.2.1 Power Transmission Line - Online Monitoring 436 15.2.2 Smart Patrol 437 15.2.3 Smart Home Service 437 15.2.4 Information System for Electric Vehicle 438 15.3 Technical Challenges of Smart Grid 438 15.3.1 Inadequacies in Grid Infrastructure 438 15.3.2 Cyber Security 439 15.3.3 Storage Concerns 439 15.3.4 Data Management 440 15.3.5 Communication Issues 440 15.3.6 Stability Concerns 440 15.3.7 Energy Management and Electric Vehicle 440 15.4 Energy Efficient Solutions for Smart Cities 441 15.4.1 Lightweight Protocols 441 15.4.2 Scheduling Optimization 441 15.4.3 Energy Consumption 441 15.4.4 Cloud Based Approach 441 15.4.5 Low Power Transceivers 442 15.4.6 Cognitive Management Framework 442 15.5 Energy Conservation Based Algorithms 442 15.5.1 Genetic Algorithm (GA) 442 15.5.2 BFO Algorithm 444 15.5.3 BPSO Algorithm 445 15.5.4 WDO Algorithm 447 15.5.5 GWDO Algorithm 447 15.5.6 WBFA Algorithm 450 15.6 Conclusion 451 References 451 Index 455

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Book SynopsisPrepare for success on the AWS SysOps exam, your next job interview, and in the field with this handy and practical guide The newly updated Third Edition ofAWS Certified SysOps Administrator Study Guide: Associate (SOA-C02) Examprepares you forthe Amazon Web Services SysOps Administrator certification and a careerin the deployment, management, and operation of an AWS environment. Whether you're preparing for your first attempt at the challengingSOA-C02Exam,or you want to upgrade your AWS SysOps skills, this practicalStudy Guidedelivers thehands-on skills and best practices instruction you need to succeed on the test and in the field.You'll get: Coverage of all of the SOA-C02 exam's domains, including monitoring, logging, remediation, reliability, business continuity, and moreInstruction that's tailor-made to achieve success on the certification exam, inan AWS SysOps job interview, and in your next role as a SysOps administratorAccess to the Sybex online study tools, with chapter review questions, full-length practice exams, hundreds of electronic flashcards, and a glossary of key terms TheAWS Certified SysOps Administrator Study Guide: Associate (SOA-C02) Examincludesall thedigital and offlinetools you need tosupercharge your career as an AWS Certified SysOps Administrator.

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Book SynopsisTable of ContentsPreface ix Acknowledgements xiii About the Editors xv About the Contributors xvii Part 1 Cloud Computing 1 1 Cloud Computing: Evolution, Research Issues, and Challenges 3Neeraj Gupta and Asha Sohal 2 Cloud IoT: An Emerging Computing Paradigm for Smart World 19Ruchi Bhatnagar, Prof (Dr.) Paramjeet Rawat and Dr. Amit Garg Part 2 Quantum Computing and Its Applications 41 3 Quantum Computing: Principles and Mathematical Models 43Arish Pitchai 4 Quantum Cryptography and Security 63Anukriti and Vandana Niranjan 5 Quantum Machine Learning Algorithms 79Renata Wong, Tanya Garg, Ritu Thombre, Alberto Maldonado Romo, Niranjan PN, Pinaki Sen, Mandeep Kaur Saggi and Amandeep Singh Bhatia Part 3 Computational Intelligence and Its Applications 99 6 Computational Intelligence Paradigms in Radiological Image Processing—Recent Trends and Challenges 101Anil B. Gavade, Rajendra B. Nerli, Ashwin Patil, Shridhar Ghagane and Venkata Siva Prasad Bhagavatula 7 Computational Intelligence in Agriculture 125Hari Prabhat Gupta, Swati Chopade and Tanima Dutta 8 Long-and-Short-Term Memory (LSTM) Networks: Architectures and Applications in Stock Price Prediction 143Jaydip Sen and Sidra Mehtab Part 4 Advances in Wireless Networks 161 9 Mobile Networks: 5G and Beyond 163Pavel Loskot 10 Advanced Wireless Sensor Networks: Research Directions 177Richa Sharma 11 Synergizing Blockchain, IoT, and AI with VANET for Intelligent Transport Solutions 193S.S. Zalte, V.R. Ghorpade and Rajanish K. Kamat Part 5 Blockchain Technology and Cyber Security 211 12 Enterprise Blockchain: ICO Perspectives and Industry Use Cases 213Ashish Seth, Kirti Seth and Himanshu Gupta 13 Blockchain and Cryptocurrencies: Techniques, Applications and Challenges 235Snehlata Barde 14 Importance of Cybersecurity and Its Subdomains 247Parag H. Rughani Index 263

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Book SynopsisAUTONOMOUS AND CONNECTED VEHICLES Discover the latest developments in autonomous vehicles and what the future holds for this exciting technology In Autonomous and Connected Vehicles, networking experts Dominique Paret and Hassina Rebaine deliver a robust exploration of the major technological changes taking place in the field, and describe the different levels of autonomy possible with current technologies and the legal and regulatory contexts in which new autonomous vehicles will circulate. The book also includes discussions of the sensors, including infrared, ultrasound, cameras, lidar, and radar, used by modern autonomous vehicles. Readers will enjoy the intuitive descriptions of Advanced Driver Assistance Systems (ADAS), network architectures (CAN-FD, FlexRay, and Backbone Ethernet), and software that power current and future autonomous vehicles. The authors also discuss how ADAS can be fused with data flowing over newer and faster network architecturTable of ContentsForeword iv Acknowledgments vi About the Authors vii Preface ix Introduction 1 1 The Buzz about Autonomous and Connected Vehicles 3 2 Aspects Relating to Autonomous and Connected Vehicles 23 3 DAS, ADAS, HADAS, and AVs – L3, L4, L5! 81 4 Networks and Architecture 145 5 Ethernet and Automobiles 237 6 Simulations, Applications, and Software Architectures for Automobiles 317 Index 399

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Book SynopsisCybersecurity Risk Management In Cybersecurity Risk Management: Mastering the Fundamentals Using the NIST Cybersecurity Framework, veteran technology analyst Cynthia Brumfield, with contributions from cybersecurity expert Brian Haugli, delivers a straightforward and up-to-date exploration of the fundamentals of cybersecurity risk planning and management. The book offers readers easy-to-understand overviews of cybersecurity risk management principles, user, and network infrastructure planning, as well as the tools and techniques for detecting cyberattacks. The book also provides a roadmap to the development of a continuity of operations plan in the event of a cyberattack. With incisive insights into the Framework for Improving Cybersecurity of Critical Infrastructure produced by the United States National Institute of Standards and Technology (NIST), Cybersecurity Risk Management presents the gold standard in practical guidance for the implementation of risk mTable of ContentsAcademic Foreword xiii Acknowledgments xv Preface – Overview of the NIST Framework xvii Background on the Framework xviii Framework Based on Risk Management xix The Framework Core xix Framework Implementation Tiers xxi Framework Profile xxii Other Aspects of the Framework Document xxiii Recent Developments At Nist xxiii Chapter 1 Cybersecurity Risk Planning and Management 1 Introduction 2 I. What Is Cybersecurity Risk Management? 2 A. Risk Management Is a Process 3 II. Asset Management 4 A. Inventory Every Physical Device and System You Have and Keep the Inventory Updated 5 B. Inventory Every Software Platform and Application You Use and Keep the Inventory Updated 9 C. Prioritize Every Device, Software Platform, and Application Based on Importance 10 D. Establish Personnel Security Requirements Including Third-Party Stakeholders 11 III. Governance 13 A. Make Sure You Educate Management about Risks 13 IV. Risk Assessment and Management 15 A. Know Where You’re Vulnerable 15 B. Identify the Threats You Face, Both Internally and Externally 16 C. Focus on the Vulnerabilities and Threats That Are Most Likely AND Pose the Highest Risk to Assets 17 D. Develop Plans for Dealing with the Highest Risks 18 Summary 20 Chapter Quiz 20 Essential Reading on Cybersecurity Risk Management 22 Chapter 2 User and Network Infrastructure Planning and Management 23 I. Introduction 24 II. Infrastructure Planning and Management Is All about Protection, Where the Rubber Meets the Road 24 A. Identity Management, Authentication, and Access Control 25 1. Always Be Aware of Who Has Access to Which System, for Which Period of Time, and from Where the Access Is Granted 27 2. Establish, Maintain, and Audit an Active Control List and Process for Who Can Physically Gain Access to Systems 28 3. Establish Policies, Procedures, and Controls for Who Has Remote Access to Systems 28 4. Make Sure That Users Have the Least Authority Possible to Perform Their Jobs and Ensure That at Least Two Individuals Are Responsible for a Task 29 5. Implement Network Security Controls on All Internal Communications, Denying Communications among Various Segments Where Necessary 31 A Word about Firewalls 31 6. Associate Activities with a Real Person or a Single Specific Entity 32 7. Use Single- or Multi-Factor Authentication Based on the Risk Involved in the Interaction 33 III. Awareness and Training 34 A. Make Sure That Privileged Users and Security Personnel Understand Their Roles and Responsibilities 35 IV. Data Security 35 A. Protect the Integrity of Active and Archived Databases 35 B. Protect the Confidentiality and Integrity of Corporate Data Once It Leaves Internal Networks 36 C. Assure That Information Can Only Be Accessed by Those Authorized to Do So and Protect Hardware and Storage Media 37 D. Keep Your Development and Testing Environments Separate from Your Production Environment 38 E. Implement Checking Mechanisms to Verify Hardware Integrity 39 V. Information Protection Processes and Procedures 39 A. Create a Baseline of IT and OT Systems 40 B. Manage System Configuration Changes in a Careful, Methodical Way 41 A Word about Patch Management 42 C. Perform Frequent Backups and Test Your Backup Systems Often 43 D. Create a Plan That Focuses on Ensuring That Assets and Personnel Will Be Able to Continue to Function in the Event of a Crippling Attack or Disaster 43 VI. Mainte nance 44 A. Perform Maintenance and Repair of Assets and Log Activities Promptly 45 B. Develop Criteria for Authorizing, Monitoring, and Controlling All Maintenance and Diagnostic Activities for Third Parties 45 VII. Protective Technology 46 A. Restrict the Use of Certain Types of Media On Your Systems 46 B. Wherever Possible, Limit Functionality to a Single Function Per Device (Least Functionality) 47 C. Implement Mechanisms to Achieve Resilience on Shared Infrastructure 48 Summary 49 Chapter Quiz 50 Essential Reading on Network Management 51 Chapter 3 Tools and Techniques for Detecting Cyber Incidents 53 Introduction 54 What Is an Incident? 55 I. Detect 56 A. Anomalies and Events 56 1. Establish Baseline Data for Normal, Regular Traffic Activity and Standard Configuration for Network Devices 57 2. Monitor Systems with Intrusion Detection Systems and Establish a Way of Sending and Receiving Notifications of Detected Events; Establish a Means of Verifying, Assessing, and Tracking the Source of Anomalies 58 A Word about Antivirus Software 60 3. Deploy One or More Centralized Log File Monitors and Configure Logging Devices throughout the Organization to Send Data Back to the Centralized Log Monitor 61 4. Determine the Impact of Events Both Before and After they Occur 61 5. Develop a Threshold for How Many Times an Event Can Occur Before You Take Action 62 B. Continuous Monitoring 62 1. Develop Strategies for Detecting Breaches as Soon as Possible, Emphasizing Continuous Surveillance of Systems through Network Monitoring 63 2. Ensure That Appropriate Access to the Physical Environment Is Monitored, Most Likely through Electronic Monitoring or Alarm Systems 64 3. Monitor Employee Behavior in Terms of Both Physical and Electronic Access to Detect Unauthorized Access 65 4. Develop a System for Ensuring That Software Is Free of Malicious Code through Software Code Inspection and Vulnerability Assessments 65 5. Monitor Mobile Code Applications (e.g., Java Applets) for Malicious Activity by Authenticating the Codes’ Origins, Verifying their Integrity, and Limiting the Actions they Can Perform 66 6. Evaluate a Provider’s Internal and External Controls’ Adequacy and Ensure they Develop and Adhere to Appropriate Policies, Procedures, and Standards; Consider the Results of Internal and External Audits 66 7. Monitor Employee Activity for Security Purposes and Assess When Unauthorized Access Occurs 67 8. Use Vulnerability Scanning Tools to Find Your Organization’s Weaknesses 68 C. Detection Processes 68 1. Establish a Clear Delineation between Network and Security Detection, with the Networking Group and the Security Group Having Distinct and Different Responsibilities 69 2. Create a Formal Detection Oversight and Control Management Function; Define Leadership for a Security Review, Operational Roles, and a Formal Organizational Plan; Train Reviewers to Perform Their Duties Correctly and Implement the Review Process 70 3. Test Detection Processes Either Manually or in an Automated Fashion in Conformance with the Organization’s Risk Assessment 71 4. Inform Relevant Personnel Who Must Use Data or Network Security Information about What Is Happening and Otherwise Facilitate Organizational Communication 71 5. Document the Process for Event Detection to Improve the Organization’s Detection Systems 72 Summary 72 Chapter Quiz 73 Essential Reading for Tools and Techniques for Detecting a Cyberattack 74 Chapter 4 Developing a Continuity of Operations Plan 75 Introduction 77 A. One Size Does Not Fit All 77 I. Response 77 A. Develop an Executable Response Plan 79 B. Understand the Importance of Communications in Incident Response 80 C. Prepare for Corporate-Wide Involvement During Some Cybersecurity Attacks 81 II. Analysis 82 A. Examine Your Intrusion Detection System in Analyzing an Incident 82 B. Understand the Impact of the Event 83 C. Gather and Preserve Evidence 84 D. Prioritize the Treatment of the Incident Consistent with Your Response Plan 84 E. Establish Processes for Handling Vulnerability Disclosures 85 III. Mitigation 86 A. Take Steps to Contain the Incident 86 B. Decrease the Threat Level by Eliminating or Intercepting the Adversary as Soon as the Incident Occurs 87 C. Mitigate Vulnerabilities or Designate Them as Accepted Risk 88 IV. Recover 88 A. Recovery Plan Is Executed During or After a Cybersecurity Incident 89 B. Update Recovery Procedures Based on New Information as Recovery Gets Underway 91 C. Develop Relationships with Media to Accurately Disseminate Information and Engage in Reputational Damage Limitation 92 Summary 92 Chapter Quiz 93 Essential Reading for Developing a Continuity of Operations Plan 94 Chapter 5 Supply Chain Risk Management 95 Introduction 96 I. NIST Special Publication 800-161 96 II. Software Bill of Materials 97 III. NIST Revised Framework Incorporates Major Supply Chain Category 98 A. Identify, Establish, and Assess Cyber Supply Chain Risk Management Processes and Gain Stakeholder Agreement 98 B. Identify, Prioritize, and Assess Suppliers and Third-Party Partners of Suppliers 99 C. Develop Contracts with Suppliers and Third-Party Partners to Address Your Organization’s Supply Chain Risk Management Goals 100 D. Routinely Assess Suppliers and Third-Party Partners Using Audits, Test Results, and Other Forms of Evaluation 101 E. Test to Make Sure Your Suppliers and Third-Party Providers Can Respond to and Recover from Service Disruption 102 Summary 103 Chapter Quiz 103 Essential Reading for Supply Chain Risk Management 104 Chapter 6 Manufacturing and Industrial Control Systems Security 105 Essential Reading on Manufacturing and Industrial Control Security 110 Appendix A: Helpful Advice for Small Organizations Seeking to Implement Some of the Book’s Recommendations 111 Appendix B: Critical Security Controls Version 8.0 Mapped to NIST CSF v1.1 113 Answers to Chapter Quizzes 121 Index 131

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Book Synopsis>IoT-Enabled Smart Healthcare Systems, Services and Applications Explore the latest healthcare applications of cutting-edge technologies In IoT-Enabled Smart Healthcare Systems, Services and Applications, an accomplished team of researchers delivers an insightful and comprehensive exploration of the roles played by cutting-edge technologies in modern healthcare delivery. The distinguished editors have included resources from a diverse array of learned experts in the field that combine to create a broad examination of a rapidly developing field. With a particular focus on Internet of Things (IoT) technologies, readers will discover how new technologies are impacting healthcare applications from remote monitoring systems to entire healthcare delivery methodologies. After an introduction to the role of emerging technologies in smart health care, this volume includes treatments of ICN-Fog computing, edge computing, security and privacy, IoT architecture, vehiTable of ContentsPreface ix Acknowledgments xi About the Editors xiii List of Contributors xvii 1 The Role of Emerging Technologies in Smart Healthcare 1Masooma Zehra Syeda, Dur-e-hassan Syeda, and Himanshi Babbar 1.1 Introduction 1 1.2 Emerging Technologies in Smart Healthcare 3 1.3 Realization of SHC through Emerging Technologies (Applications) 9 1.4 Conclusion 15 Author Biography 15 References 15 2 ICN-Fog Computing for IoT-Based Healthcare: Architecture and Challenges 19Divya Gupta, Shalli Rani, and Syed Hassan Ahmed Shah 2.1 Introduction 19 2.2 ICN in IoT 21 2.3 IoT in Healthcare 24 2.4 Role of Fog Computing in IoT 26 2.5 Fog Computing in Healthcare: A Classification Approach 28 2.6 ICN-Fog Leveraging Healthcare Architecture 30 2.7 Challenges in the Healthcare System 33 2.8 Conclusion 35 References 35 3 Internet of Things (IoT) Enabled Software Defined Networking (SDN) for Load Balancing, Edge, Cloud Computing in Healthcare 39Himanshi Babbar, Shalli Rani, and Neeraj Kumar 3.1 Overview of Software-Defined Networking 39 3.2 Overview of Healthcare 40 3.3 Technologies Used in Software-Defined Networking (SDN) and HealthCare 42 3.4 Use Cases of Software-Defined Networking in Healthcare 52 3.5 Research Directions 55 3.6 Conclusion 55 Key Points 56 Author Biography 57 References 59 4 Security and Privacy Issues in Smart Healthcare System Using Internet of Things 63R. Nidhya, Manish Kumar, R. Maheswar, and D. Pavithra 4.1 Introduction 63 4.2 Overview of Internet of Things in Smart Healthcare Systems 64 4.3 Policies and Legislation Related to Smart Healthcare 66 4.4 Security and Privacy Issues in Smart Healthcare Based on Internet of Things 69 4.5 Issues in Location Privacy 77 4.6 Issues in Privacy of Stored Data and Threats Identity 77 4.7 Conclusion 77 Author Biography 78 References 79 5 An Overview of Architecture and Applications of IoT-Based Health Care Systems 87M. Saravanan, J. Ajayan, R. Maheswar, and E. Parthasarathy 5.1 Introduction 87 5.2 Overview of the Healthcare System 88 5.3 Working Prototype of Healthcare System Using BAN 89 5.4 On-Body Sensors and Sensor Embodiment 93 5.5 Vital Signs Monitoring 97 5.6 Biosensors in M-Health 104 5.7 IoT-Based Rehabilitation System 109 5.8 Future Work 115 5.9 Conclusion 115 Authors’ Biography 115 References 117 6 A Review of e-Healthcare System of India and Thailand 123Shanu Bhardwaj, S.N. Panda, Priyanka Datta, Rajesh Kumar Kaushal, and Naveen Kumar 6.1 Introduction 123 6.2 Literature Review 124 6.3 Problem Statement 134 6.4 Methodology 134 6.5 Discussion 134 6.6 Conclusion 137 References 138 7 WSN-and IoT-Based Smart Surveillance Systems for Patients with Closed-Loop Alarm 143Amit Sundas, Sumit Badotra, Shalli Rani, and Chhabildas Madhukar Gajare 7.1 Introduction 143 7.2 Literature Review 152 7.3 Proposed Work : WSN and IoT-Based Smart Surveillance System for Patients with Closed-Loop Alarm 155 7.4 Implementation and Evaluation of the WSN and IoT-Based Smart Surveillance System for Patients with Closed-Loop Alarm 160 7.5 Conclusion and Future Work 173 References 174 8 An IoMT-Based Smart Remote Monitoring System for Healthcare 177Chetna Kaushal, Md Khairul Islam, Anshu Singla, and Md Al Amin 8.1 Introduction 177 8.2 Literature Review 181 8.3 Methodology 183 8.4 Use Case of Real-Time Remote Monitoring System 191 8.5 Conclusion 193 References 194 9 A Multi-Domain Perspective of Future Directions for VANETs for Emergency Message Dissemination 199Ravneet Kaur, Ramkumar Ketti Ramachandran, Robin Doss, and Lei Pan 9.1 Introduction 199 9.2 Future Directions of Multi-Domain VANETs Emergency Message Dissemination 200 9.3 Role of VANETs in Healthcare Systems 203 9.4 Techniques Used for Fast Delivery of Emergency Message in VANETs to Help the Healthcare System 205 9.5 Current Facilities and Limitations for Implementing the Real-Time Environment 210 9.6 Discussion on Upcoming Trends and Possibilities with Future Readings 211 9.7 Conclusion 214 Notes 214 Author Biography 214 References 216 Index 219

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Book SynopsisTable of ContentsList of Simulation and Hardware Implementation Example and Figures xiii Preface xv Acknowledgment xvii About the Companion Website xix Chapter 1 Power Electronics: An Enabling Technology 1 1.1 Introduction to Power Electronics 1 1.2 Applications and the Role of Power Electronics 2 1.3 Energy and the Environment: Role of Power Electronics in Providing Sustainable Electric Energy 4 1.4 Need for High Efficiency and High Power Density 8 1.5 Structure of Power Electronics Interface 9 1.6 Voltage-Link-Structure 11 1.7 Recent Advances in Solid-State Devices Based on Wide Bandgap (WBG) Materials 16 1.8 Use of Simulation and Hardware Prototyping 16 References 17 Problems 18 Chapter 2 Design of Switching Power-poles 21 2.1 Power Transistors and Power Diodes 21 2.2 Selection of Power Transistors 22 2.3 Selection of Power Diodes 24 2.4 Switching Characteristics and Power Losses in Power Poles 25 2.5 Justifying Switches and Diodes as Ideal 30 2.6 Design Considerations 31 2.7 The PWM IC 34 2.8 Hardware Prototyping 35 References 36 Problems 36 Appendix 2A Diode Reverse Recovery and Power Losses 37 Chapter 3 Switch-mode Dc-dc Converters: Switching Analysis, Topology Selection, and Design 41 3.1 DC-DC Converters 41 3.2 Switching Power-Pole in DC Steady State 41 3.3 Simplifying Assumptions 45 3.4 Common Operating Principles 46 3.5 Buck Converter Switching Analysis in DC Steady State 46 3.6 Boost Converter Switching Analysis in DC Steady State 51 3.7 Buck-Boost Converter Analysis in DC Steady State 57 3.8 Topology Selection 65 3.9 Worst-Case Design 66 3.10 Synchronous-Rectified Buck Converter for Very Low Output Voltages 66 3.11 Interleaving of Converters 71 3.12 Regulation of DC-DC Converters by PWM 71 3.13 Dynamic Average Representation of Converters in CCM 72 3.14 Bi-Directional Switching Power-Pole 74 3.15 Discontinuous-Conduction Mode (DCM) 75 References 86 Problems 86 Appendix 3A Average Representation in Discontinuous- Conduction Mode (DCM) 92 Chapter 4 Designing Feedback Controllers in Switch-mode Dc Power Supplies 97 4.1 Introduction and Objectives of Feedback Control 97 4.2 Review of Linear Control Theory 98 4.3 Linearization of Various Transfer Function Blocks 100 4.4 Feedback Controller Design in Voltage-Mode Control 106 4.5 Peak-Current Mode Control 113 4.6 Feedback Controller Design in DCM 123 References 124 Problems 124 Appendix 4A Bode Plots of Transfer Functions with Poles and Zeros 125 Appendix 4B Transfer Functions in Continuous Conduction Mode (CCM) 128 Appendix 4C Derivation of Parameters of the Controller Transfer Functions 134 Chapter 5 Rectification of Utility Input Using Diode Rectifiers 139 Rectifiers 139 5.1 Introduction 139 5.2 Distortion and Power Factor 140 5.3 Classifying the “Front-End” of Power Electronic Systems 148 Electronic Systems 148 5.4 Diode-Rectifier Bridge “Front-End” 148 5.5 Means to Avoid Transient Inrush Currents at Starting 156 5.6 Front-Ends with Bi-Directional Power Flow 157 References 157 Problems 157 Chapter 6 Power-factor-correction (PFC) Circuits And Designing the Feedback Controller And Designing the Feedback Controller 159 6.1 Introduction 159 6.2 Operating Principle of Single-Phase PFCS 159 6.3 Control of PFCS 162 6.4 Designing the Inner Average-Current-Control Loop 163 6.5 Designing the Outer Voltage-Control Loop 165 6.6 Example of Single-Phase PFC Systems 167 6.7 Simulation Results 168 6.8 Feedforward of the Input Voltage 169 6.9 Other Control Methods for PFCS 169 References 170 Problems 170 Appendix 6A Proof that IˆS3/IˆL2 =1/2 Appendix 6b Proof That V ̃d I ĩ L(s)=1 I 2 Vˆs/Vd R I 2/ 1+ s (R /2)C Chapter 7 Magnetic Circuit Concepts 173 7.1 Ampere-Turns and Flux 173 7.2 Inductance l 174 7.3 Faraday’s Law: Induced Voltage in a Coil Due to Time-Rate of Change of Flux Linkage 176 7.4 Leakage and Magnetizing Inductances 177 7.5 Transformers 179 Reference 182 Problems 182 Chapter 8 Switch-mode Dc Power Supplies 185 8.1 Applications of Switch-Mode DC Power Supplies 185 8.2 Need for Electrical Isolation 186 8.3 Classification of Transformer-Isolated DC-DC Converters 186 8.4 Flyback Converters 186 8.5 Forward Converters 198 8.6 Full-Bridge Converters 204 8.7 Half-Bridge and Push-Pull Converters 209 8.8 Practical Considerations 209 References 210 Problems 211 Chapter 9 Design of High-frequency Inductors and Transformers 215 9.1 Introduction 215 9.2 Basics of Magnetic Design 215 9.3 Inductor and Transformer Construction 216 9.4 Area-Product Method 216 9.5 Design Example of an Inductor 219 9.6 Design Example of a Transformer for a Forward Converter 221 9.7 Thermal Considerations 221 References 222 Problems 222 Chapter 10 Soft-switching in Dc-dc Converters and Half-bridge Resonant Converters 223 10.1 Introduction 223 10.2 Hard-Switching in Switching Power poles 223 10.3 Soft-switching in Switching Power-Poles 225 10.4 Half-Bridge Resonant Converter 228 References 230 Problems 230 Chapter 11 Applications of Switch-mode Power Electronics in Motor Drives, Uninterruptible Power Supplies, And Power Systems 231 11.1 Introduction 231 11.2 Electric Motor Drives 231 11.3 Uninterruptible Power Supplies (UPS) 244 11.4 Utility Applications of Switch-Mode Power Electronics 244 Reference 246 Problems 246 Chapter 12 Synthesis of Dc and Low-frequency Sinusoidal Ac Voltages for Motor Drives, Ups, and Power Systems Applications 249 12.1 Introduction 249 12.2 Bidirectional Switching Power-Pole as the Building Block 250 12.3 Converters for DC Motor Drives (−Vd 12.4 Synthesis of Low-Frequency AC 260 12.5 Single-Phase Inverters 261 12.6 Three-Phase Inverters 266 12.7 Multilevel Inverters 280 12.8 Converters For Bidirectional Power Flow 281 12.9 Matrix Converters (Direct Link System) 283 References 284 Problems 284 Chapter 13 Thyristor Converters 287 13.1 Introduction 287 13.2 Thyristors (SCRs) 287 13.3 Single-phase, Phase-controlled Thyristor Converters 289 13.4 Three-Phase, Full-Bridge Thyristor Converters 294 13.5 Current-Link Systems 300 Reference 301 Problems 301 Chapter 14 Utility Applications of Power Electronics 303 14.1 Introduction 303 14.2 Power Semiconductor Devices and Their Capabilities 304 14.3 Categorizing Power Electronic Systems 305 14.4 Distributed Generation (DG) Applications 306 14.5 Power Electronic Loads 311 14.6 Power Quality Solutions 312 14.7 Transmission and Distribution (T&D) Applications 313 References 317 Problems 317 Index 319

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Book SynopsisHANDBOOK of BIOMASS VALORIZATION for INDUSTRIAL APPLICATIONS The handbook provides a comprehensive view of cutting-edge research on biomass valorization, from advanced fabrication methodologies through useful derived materials, to current and potential application sectors. Industrial sectors, such as food, textiles, petrochemicals and pharmaceuticals, generate massive amounts of waste each year, the disposal of which has become a major issue worldwide. As a result, implementing a circular economy that employs sustainable practices in waste management is critical for any industry. Moreover, fossil fuels, which are the primary sources of fuel in the transportation sector, are also being rapidly depleted at an alarming rate. Therefore, to combat these global issues without increasing our carbon footprint, we must look for renewable resources to produce chemicals and biomaterials. In that context, agricultural waste materials are gaining popularity as cost-effective and abundantly availabl

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Book SynopsisTable of ContentsIntroduction xxi Assessment Test xxx Chapter 1 History of Analytics and Big Data 1 Evolution of Analytics Architecture Over the Years 3 The New World Order 5 Analytics Pipeline 6 Data Sources 7 Collection 8 Storage 8 Processing and Analysis 9 Visualization, Predictive and Prescriptive Analytics 9 The Big Data Reference Architecture 10 Data Characteristics: Hot, Warm, and Cold 11 Collection/Ingest 12 Storage 13 Process/Analyze 14 Consumption 15 Data Lakes and Their Relevance in Analytics 16 What is a Data Lake? 16 Building a Data Lake on AWS 19 Step 1: Choosing the Right Storage – Amazon S3 is the Base 19 Step 2: Data Ingestion – Moving the Data into the Data Lake 21 Step 3: Cleanse, Prep, and Catalog the Data 22 Step 4: Secure the Data and Metadata 23 Step 5: Make Data Available for Analytics 23 Using Lake Formation to Build a Data Lake on AWS 23 Exam Objectives 24 Objective Map 25 Assessment Test 27 References 29 Chapter 2 Data Collection 31 Exam Objectives 32 AWS IoT 33 Common Use Cases for AWS IoT 35 How AWS IoT Works 36 Amazon Kinesis 38 Amazon Kinesis Introduction 40 Amazon Kinesis Data Streams 40 Amazon Kinesis Data Analytics 54 Amazon Kinesis Video Streams 61 AWS Glue 64 Glue Data Catalog 66 Glue Crawlers 68 Authoring ETL Jobs 69 Executing ETL Jobs 71 Change Data Capture with Glue Bookmarks 71 Use Cases for AWS Glue 72 Amazon SQS 72 Amazon Data Migration Service 74 What is AWS DMS Anyway? 74 What Does AWS DMS Support? 75 AWS Data Pipeline 77 Pipeline Definition 77 Pipeline Schedules 78 Task Runner 79 Large-Scale Data Transfer Solutions 81 AWS Snowcone 81 AWS Snowball 82 AWS Snowmobile 85 AWS Direct Connect 86 Summary 87 Review Questions 88 References 90 Exercises & Workshops 91 Chapter 3 Data Storage 93 Introduction 94 Amazon S3 95 Amazon S3 Data Consistency Model 96 Data Lake and S3 97 Data Replication in Amazon S3 100 Server Access Logging in Amazon S3 101 Partitioning, Compression, and File Formats on S3 101 Amazon S3 Glacier 103 Vault 103 Archive 104 Amazon DynamoDB 104 Amazon DynamoDB Data Types 105 Amazon DynamoDB Core Concepts 108 Read/Write Capacity Mode in DynamoDB 108 DynamoDB Auto Scaling and Reserved Capacity 111 Read Consistency and Global Tables 111 Amazon DynamoDB: Indexing and Partitioning 113 Amazon DynamoDB Accelerator 114 Amazon DynamoDB Streams 115 Amazon DynamoDB Streams – Kinesis Adapter 116 Amazon DocumentDB 117 Why a Document Database? 117 Amazon DocumentDB Overview 119 Amazon Document DB Architecture 120 Amazon DocumentDB Interfaces 120 Graph Databases and Amazon Neptune 121 Amazon Neptune Overview 122 Amazon Neptune Use Cases 123 Storage Gateway 123 Hybrid Storage Requirements 123 AWS Storage Gateway 125 Amazon EFS 127 Amazon EFS Use Cases 130 Interacting with Amazon EFS 132 Amazon EFS Security Model 132 Backing Up Amazon EFS 132 Amazon FSx for Lustre 133 Key Benefits of Amazon FSx for Lustre 134 Use Cases for Lustre 135 AWS Transfer for SFTP 135 Summary 136 Exercises 137 Review Questions 140 Further Reading 142 References 142 Chapter 4 Data Processing and Analysis 143 Introduction 144 Types of Analytical Workloads 144 Amazon Athena 146 Apache Presto 147 Apache Hive 148 Amazon Athena Use Cases and Workloads 149 Amazon Athena DDL, DML, and DCL 150 Amazon Athena Workgroups 151 Amazon Athena Federated Query 153 Amazon Athena Custom UDFs 154 Using Machine Learning with Amazon Athena 154 Amazon EMR 155 Apache Hadoop Overview 156 Amazon EMR Overview 157 Apache Hadoop on Amazon EMR 158 EMRFS 166 Bootstrap Actions and Custom AMI 167 Security on EMR 167 EMR Notebooks 168 Apache Hive and Apache Pig on Amazon EMR 169 Apache Spark on Amazon EMR 174 Apache HBase on Amazon EMR 182 Apache Flink, Apache Mahout, and Apache MXNet 184 Choosing the Right Analytics Tool 186 Amazon Elasticsearch Service 188 When to Use Elasticsearch 188 Elasticsearch Core Concepts (the ELK Stack) 189 Amazon Elasticsearch Service 191 Amazon Redshift 192 What is Data Warehousing? 192 What is Redshift? 193 Redshift Architecture 195 Redshift AQUA 198 Redshift Scalability 199 Data Modeling in Redshift 205 Data Loading and Unloading 213 Query Optimization in Redshift 217 Security in Redshift 221 Kinesis Data Analytics 225 How Does It Work? 226 What is Kinesis Data Analytics for Java? 228 Comparing Batch Processing Services 229 Comparing Orchestration Options on AWS 230 AWS Step Functions 230 Comparing Different ETL Orchestration Options 230 Summary 231 Exam Essentials 232 Exercises 232 Review Questions 235 References 237 Recommended Workshops 237 Amazon Athena Blogs 238 Amazon Redshift Blogs 240 Amazon EMR Blogs 241 Amazon Elasticsearch Blog 241 Amazon Redshift References and Further Reading 242 Chapter 5 Data Visualization 243 Introduction 244 Data Consumers 245 Data Visualization Options 246 Amazon QuickSight 247 Getting Started 248 Working with Data 250 Data Preparation 255 Data Analysis 256 Data Visualization 258 Machine Learning Insights 261 Building Dashboards 262 Embedding QuickSight Objects into Other Applications 264 Administration 265 Security 266 Other Visualization Options 267 Predictive Analytics 270 What is Predictive Analytics? 270 The AWS ML Stack 271 Summary 273 Exam Essentials 273 Exercises 274 Review Questions 275 References 276 Additional Reading Material 276 Chapter 6 Data Security 279 Introduction 280 Shared Responsibility Model 280 Security Services on AWS 282 AWS IAM Overview 285 IAM User 285 IAM Groups 286 IAM Roles 287 Amazon EMR Security 289 Public Subnet 290 Private Subnet 291 Security Configurations 293 Block Public Access 298 VPC Subnets 298 Security Options during Cluster Creation 299 EMR Security Summary 300 Amazon S3 Security 301 Managing Access to Data in Amazon S3 301 Data Protection in Amazon S3 305 Logging and Monitoring with Amazon S3 306 Best Practices for Security on Amazon S3 308 Amazon Athena Security 308 Managing Access to Amazon Athena 309 Data Protection in Amazon Athena 310 Data Encryption in Amazon Athena 311 Amazon Athena and AWS Lake Formation 312 Amazon Redshift Security 312 Levels of Security within Amazon Redshift 313 Data Protection in Amazon Redshift 315 Redshift Auditing 316 Redshift Logging 317 Amazon Elasticsearch Security 317 Elasticsearch Network Configuration 318 VPC Access 318 Accessing Amazon Elasticsearch and Kibana 319 Data Protection in Amazon Elasticsearch 322 Amazon Kinesis Security 325 Managing Access to Amazon Kinesis 325 Data Protection in Amazon Kinesis 326 Amazon Kinesis Best Practices 326 Amazon QuickSight Security 327 Managing Data Access with Amazon QuickSight 327 Data Protection 328 Logging and Monitoring 329 Security Best Practices 329 Amazon DynamoDB Security 329 Access Management in DynamoDB 329 IAM Policy with Fine-Grained Access Control 330 Identity Federation 331 How to Access Amazon DynamoDB 332 Data Protection with DynamoDB 332 Monitoring and Logging with DynamoDB 333 Summary 334 Exam Essentials 334 Exercises/Workshops 334 Review Questions 336 References and Further Reading 337 Appendix Answers to Review Questions 339 Chapter 1: History of Analytics and Big Data 340 Chapter 2: Data Collection 342 Chapter 3: Data Storage 343 Chapter 4: Data Processing and Analysis 344 Chapter 5: Data Visualization 346 Chapter 6: Data Security 346 Index 349

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Book SynopsisDesign for Embedded Image Processing on FPGAs Bridge the gap between software and hardware with this foundational design reference Field-programmable gate arrays (FPGAs) are integrated circuits designed so that configuration can take place. Circuits of this kind play an integral role in processing images, with FPGAs increasingly embedded in digital cameras and other devices that produce visual data outputs for subsequent realization and compression. These uses of FPGAs require specific design processes designed to mediate smoothly between hardware and processing algorithm. Design for Embedded Image Processing on FPGAs provides a comprehensive overview of these processes and their applications in embedded image processing. Beginning with an overview of image processing and its core principles, this book discusses specific design and computation techniques, with a smooth progression from the foundations of the field to its advanced principles. Readers of the second edition of Design for Embedded Image Processing on FPGAs will also find: Detailed discussion of image processing techniques including point operations, histogram operations, linear transformations, and moreNew chapters covering Deep Learning algorithms and Image and Video CodingExample applications throughout to ground principles and demonstrate techniques Design for Embedded Image Processing on FPGAs is ideal for engineers and academics working in the field of Image Processing, as well as graduate students studying Embedded Systems Engineering, Image Processing, Digital Design, and related fields.Table of ContentsPreface xiii Acknowledgments xix About the Companion Website xxi 1 Image Processing 1 1.1 Basic Definitions 1 1.2 Image Formation 3 1.2.1 Optics 3 1.2.2 Colour 5 1.3 Image Processing Operations 6 1.4 Real-time Image Processing 8 1.5 Embedded Image Processing 9 1.6 Computer Architecture 10 1.7 Parallelism 11 1.7.1 Temporal or Task Parallelism 12 1.7.2 Spatial or Data Parallelism 13 1.7.3 Logical Parallelism 14 1.7.4 Stream Processing 14 1.8 Summary 15 References 16 2 Field-programmable Gate Arrays 19 2.1 Hardware Architecture of FPGAs 19 2.1.1 Logic 21 2.1.2 DSP Blocks 22 2.1.3 Memory 23 2.1.4 Embedded CPU 23 2.1.5 Interconnect 24 2.1.6 Input and Output 24 2.1.7 Clocking 26 2.1.8 Configuration 26 2.1.9 FPGAs vs. ASICs 27 2.2 Programming FPGAs 28 2.2.1 Register Transfer Level 30 2.2.2 Hardware Description Languages 32 2.2.3 High-level Synthesis 33 2.3 FPGAs and Image Processing 38 2.3.1 Choosing an FPGA or Development Board 39 2.4 Summary 40 References 41 3 Design Process 45 3.1 Problem Specification 45 3.2 Algorithm Development 47 3.2.1 Algorithm Development Process 47 3.2.2 Algorithm Structure 48 3.2.3 FPGA Development Issues 51 3.3 Architecture Selection 51 3.3.1 System Architecture 52 3.3.2 Partitioning Between Hardware and Software 53 3.3.3 Computational Architecture 55 3.4 System Implementation 60 3.4.1 Mapping to FPGA Resources 60 3.4.2 Algorithm Mapping Issues 62 3.5 Testing and Debugging 63 3.5.1 Design 63 3.5.2 Implementation 64 3.5.3 Common Implementation Bugs 64 3.5.4 Timing 66 3.5.5 System Debugging 68 3.5.6 Algorithm Tuning 70 3.5.7 In-field Diagnosis 71 3.6 Summary 72 References 73 4 Design Constraints 77 4.1 Timing Constraints 77 4.1.1 Low-level Pipelining 78 4.1.2 Process Synchronisation 80 4.1.3 Synchronising Between Clock Domains 82 4.1.4 I/O Constraints 83 4.2 Memory Bandwidth Constraints 84 4.2.1 Memory Architectures 84 4.2.2 Caching 86 4.2.3 Row Buffering 87 4.3 Resource Constraints 88 4.3.1 Bit-serial Computation 89 4.3.2 Resource Multiplexing 89 4.3.3 Arbitration 92 4.3.4 Resource Controllers 94 4.3.5 Reconfigurability 95 4.4 Power Constraints 97 4.5 Performance Metrics 98 4.5.1 Speed 99 4.5.2 Resources 99 4.5.3 Power 99 4.5.4 Cost 100 4.5.5 Application Metrics 100 4.6 Summary 101 References 102 5 Computational Techniques 105 5.1 Number Systems 105 5.1.1 Binary Integers 105 5.1.2 Residue Systems 106 5.1.3 Redundant Representations 107 5.1.4 Fixed-point Numbers 107 5.1.5 Floating-point Numbers 108 5.1.6 Logarithmic Number System 110 5.1.7 Posit Numbers 110 5.2 Elementary Functions 111 5.2.1 Square Root 111 5.2.2 Trigonometric Functions 112 5.2.3 Linear CORDIC 116 5.2.4 Hyperbolic Functions 117 5.2.5 Logarithms and Exponentials 118 5.2.6 Lookup Tables 118 5.2.7 Polynomial Approximations 122 5.2.8 Iterative Techniques 123 5.3 Other Computation Techniques 124 5.3.1 Incremental Update 124 5.3.2 Separability 124 5.4 Memory Structures 124 5.4.1 FIFO Buffer 124 5.4.2 Zigzag Buffers 126 5.4.3 Stacks 126 5.4.4 Linked Lists 127 5.4.5 Trees 128 5.4.6 Graphs 129 5.4.7 Hash Tables 129 5.5 Summary 130 References 131 6 Interfacing 135 6.1 Camera Input 135 6.1.1 Analogue Video 136 6.1.2 Direct Digital Interface 137 6.1.3 MIPI Camera Serial Interface 138 6.1.4 Camera Link 139 6.1.5 USB Cameras 139 6.1.6 GigE Vision 139 6.1.7 Camera Processing Pipeline 140 6.2 Display Output 143 6.2.1 Display Driver 143 6.2.2 Display Content 146 6.3 Serial Communication 147 6.3.1 Rs- 232 147 6.3.2 I 2 c 148 6.3.3 Serial Peripheral Interface (SPI) 149 6.3.4 Universal Serial Bus (USB) 150 6.3.5 Ethernet 150 6.3.6 PCI Express 151 6.4 Off-chip Memory 151 6.4.1 Static RAM 152 6.4.2 Dynamic RAM 152 6.4.3 Flash Memory 155 6.5 Processors 155 6.5.1 AXI Interface 155 6.5.2 Avalon Bus 156 6.5.3 Operating Systems 157 6.5.4 Implications for System Design 157 6.6 Summary 157 References 158 7 Point Operations 161 7.1 Point Operations on a Single Image 161 7.1.1 Contrast and Brightness Adjustment 161 7.1.2 Global Thresholding and Contouring 164 7.1.3 Lookup Table Implementation 166 7.2 Point Operations on Multiple Images 167 7.2.1 Image Averaging 168 7.2.2 Image Subtraction 170 7.2.3 Background Modelling 172 7.2.4 Intensity Scaling 175 7.2.5 Masking 175 7.2.6 High Dynamic Range (HDR) Imaging 177 7.3 Colour 179 7.3.1 False Colour 179 7.3.2 Colour Space Conversion 180 7.3.3 Colour Thresholding 192 7.3.4 Colour Enhancement 193 7.3.5 White Balance 194 7.4 Multi-spectral and Hyperspectral Imaging 197 7.4.1 Hyperspectral Image Acquisition 197 7.4.2 Processing Steps 198 7.5 Summary 199 References 199 8 Histogram Operations 203 8.1 Greyscale Histogram 203 8.1.1 Building the Histogram 203 8.1.2 Data Gathering 205 8.1.3 Histogram Equalisation 209 8.1.4 Automatic Exposure 214 8.1.5 Threshold Selection 215 8.1.6 Histogram Similarity 220 8.2 Multidimensional Histograms 220 8.2.1 Triangular Arrays 221 8.2.2 Multidimensional Statistics 222 8.2.3 Colour Segmentation 225 8.2.4 Colour Indexing 228 8.2.5 Texture Analysis 229 8.3 Summary 231 References 231 9 Local Filters 235 9.1 Window Caching 235 9.1.1 Border Handling 237 9.1.2 Filter Latency 239 9.2 Linear Filters 239 9.2.1 Filter Techniques 240 9.2.2 Noise Smoothing 243 9.2.3 Edge Detection 246 9.2.4 Edge Enhancement 248 9.3 Nonlinear Filters 249 9.3.1 Gradient Magnitude 249 9.3.2 Edge Orientation 250 9.3.3 Peak Detection and Non-maximal Suppression 251 9.3.4 Zero-crossing Detection 252 9.3.5 Bilateral Filter 252 9.3.6 Adaptive Thresholding 253 9.3.7 High Dynamic Range Tone Mapping 255 9.4 Rank Filters 256 9.4.1 Sorting Networks 258 9.5 Adaptive Histogram Equalisation 262 9.6 Morphological Filters 262 9.6.1 Binary Morphology 262 9.6.2 Greyscale Morphology 266 9.7 Colour Filtering 268 9.7.1 Colour Morphology and Vector Median 269 9.7.2 Edge Enhancement 269 9.7.3 Bayer Pattern Demosaicing 271 9.7.4 White Balancing 272 9.8 Summary 273 References 274 10 Geometric Transformations 281 10.1 Reverse Mapping 282 10.1.1 Anti-alias Filtering 283 10.1.2 Interpolation 284 10.2 Forward Mapping 291 10.2.1 Separable Mapping 292 10.2.2 Hybrid Approach 296 10.3 Common Mappings 297 10.3.1 Affine Transformation 297 10.3.2 Perspective Mapping 297 10.3.3 Polynomial Mapping 298 10.3.4 Lens Distortion 299 10.3.5 Non-parametric Mappings 302 10.4 Image Registration 302 10.4.1 Feature-based Methods 303 10.4.2 Area-based Methods 307 10.4.3 Applications 314 10.5 Summary 315 References 315 11 Linear Transforms 321 11.1 Discrete Fourier Transform 322 11.1.1 Fast Fourier Transform (FFT) 323 11.1.2 Goertzel’s Algorithm 331 11.1.3 Applications 332 11.2 Discrete Cosine Transform (DCT) 336 11.3 Wavelet Transform 338 11.3.1 Filter Implementations 340 11.3.2 Applications 344 11.4 Summary 345 References 345 12 Image and Video Coding 349 12.1 Compression Techniques 350 12.1.1 Colour Conversion 350 12.1.2 Prediction and Transformation 350 12.1.3 Motion Estimation and Compensation 351 12.1.4 Quantisation 352 12.1.5 Run-length Coding 353 12.1.6 Entropy Coding 354 12.2 DCT-based Codecs 357 12.2.1 DCT Block Processing 357 12.2.2 Jpeg 357 12.2.3 Video Codecs 358 12.3 Wavelet-based Codecs 359 12.4 Lossless Compression 360 12.5 Perceptual Coding 361 12.6 Coding Hyperspectral Images 362 12.7 Summary 362 References 363 13 Blob Detection and Labelling 367 13.1 Bounding Box 367 13.2 Run-length Coding 369 13.3 Chain Coding 369 13.3.1 Sequential Implementation 370 13.3.2 Single-pass Stream Processing Algorithms 370 13.3.3 Feature Extraction 372 13.4 Connected Component Labelling (CCL) 374 13.4.1 Random Access Algorithms 374 13.4.2 Multiple Pass Algorithms 374 13.4.3 Two-pass Algorithms 375 13.4.4 Parallel Algorithms 377 13.4.5 Hysteresis Thresholding 377 13.5 Connected Component Analysis (CCA) 377 13.5.1 Basic Single-pass Algorithm 378 13.5.2 Reducing Memory Requirements 379 13.5.3 Eliminating End-of-row Overheads 379 13.5.4 Parallel Algorithms 380 13.5.5 Further Considerations and Optimisations 381 13.6 Distance Transform 381 13.6.1 Morphological Approaches 381 13.6.2 Chamfer Distance 382 13.6.3 Euclidean Distance 384 13.6.4 Applications 386 13.6.5 Geodesic Distance Transform 386 13.7 Watershed Transform 387 13.7.1 Flow Algorithms 388 13.7.2 Immersion Algorithms 389 13.8 Hough Transform 391 13.8.1 Line Hough Transform 391 13.8.2 Circle Hough Transform 394 13.8.3 Generalised Hough Transform 395 13.9 Summary 396 References 396 14 Machine Learning 403 14.1 Training 403 14.1.1 Loss and Cost Functions 404 14.1.2 Model Optimisation 405 14.1.3 Considerations 406 14.2 Regression 409 14.2.1 Linear Regression 409 14.2.2 Nonlinear Regression 409 14.2.3 Neural Networks 409 14.3 Classification 411 14.3.1 Decision Trees 411 14.3.2 Random Forests 412 14.3.3 Bayesian Classification 412 14.3.4 Quadratic Discriminant Analysis 414 14.3.5 Linear Discriminant Analysis 414 14.3.6 Support Vector Machines 415 14.3.7 Neural Networks 416 14.3.8 Clustering 417 14.4 Deep Learning 418 14.4.1 Building Blocks 419 14.4.2 Architectures and Applications 421 14.4.3 Training 427 14.4.4 Implementation Issues 428 14.5 Summary 433 References 433 15 Example Applications 441 15.1 Coloured Region Tracking 441 15.2 Foveal Sensor 443 15.2.1 Foveal Mapping 444 15.2.2 Using the Sensor 447 15.3 Real-time Produce Grading 448 15.3.1 Software Algorithm 448 15.3.2 Hardware Implementation 450 15.4 Stereo Imaging 453 15.4.1 Rectification 454 15.4.2 Calculating the Depth 456 15.4.3 Stereo Matching Design 457 15.5 Face Detection 459 15.5.1 Design 460 15.6 Summary 461 References 461 Index 465

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Book SynopsisComprehensive resource presenting the fundamentals and state of the art concepts, design examples, relevant components, and technology Slow-wave Microwave and mm-wave Passive Circuits presents the fundamentals and state of the art concepts, design examples, relevant components, and technology of the subject, plus examples of circuit layout optimization using slow-wave circuits. Recent advances in aspects of the slow-wave concept are covered, with potential applications including automotive radars, medical and security applications, and 5G and future 6G for very high-speed communications. The text considers a variety of slow-wave structures and associated concepts which are useful for circuit design, each structure electrically modeled with clear illustration. The highly qualified authors show that the use of the slow-wave concept can, in some cases, improve the performance of passive circuits. The techniques proposed make it possible to reduce the size and/or the performance of the circuits, with a beneficial cost-saving effect on semiconductor materials. Concepts are applied to several technologies, namely CMOS, PCB (Printed Circuit Board) and nanowires. Sample topics covered include: Concepts of energy storage with examples of slow-wave CPW (S-CPW), slow-wave SIW (SW-SIW), and slow-wave microstrip (S-MS),Transmission line topology and application in integrated technologies (CMOS), including possibilities offered by the BEOL (Back-End-Of-Line),Effect of the geometrical dimensions on the transmission line parameters (Zc, a, ereff, and Q) and comparisons between conventional CPW and CPS, and slow-wave CPW and CPS, Performance of slow-wave coupled lines and comparison with conventional microstrip coupled lines. Slow-wave Microwave and mm-wave Passive Circuits is a highly useful resource for graduate students (best complemented with a basic book on microwaves), engineers, and researchers. The text is also valuable for physicists wishing to implement comparable techniques in optics or mechanics.

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Book SynopsisTHE WILEY 5G REF Explore cutting-edge subjects in 5G privacy and security In The Wiley 5G REF: Security, a team of distinguished researchers delivers an insightful collection of articles selected from the online-only The Wiley 5G Reference. The editors introduce the security landscape of 5G, including the significant security and privacy risks associated with 5G networks. They also discuss different security solutions for various segments of the 5G network, like the radio, edge, access, and core networks. The book explores the security threats associated with key network softwarization technologies, like SDN, NFV, NS, and MEC, as well as those that come with new 5G and IoT services. There is also a detailed discussion on the privacy of 5G networks. The included articles are written by leading international experts in security and privacy for telecommunication networks. They offer learning opportunities for everyone from graduate-level students toTable of ContentsForeword List of Contributors 1. 5G Mobile Networks Security Landscape and Major Risks 2. SDMN Security 3. 5G Security – Complex Challenges 4. Physical-Layer Security for 5G and Beyond 5. Security for Handover and D2D Communication in 5G HetNets 6. Authentication and Access Control for 5G 7. 5G-Core Network Security 8. MEC and Cloud Security 9. Security in Network Slicing 10. VNF Placement and Sharing in NFV-Based Cellular Networks 11. Security Monitoring and Management in 5G 12. Security for Vertical Industries 13. Introduction to IoT Security 14. Privacy in the 5G World: The GDPR in a Datafied Society 15. Structural Safety Assessment of 5G Network Infrastructures Index

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Book SynopsisTable of ContentsIntroduction xxiii Part 1 Software Architect Capability Model 1 Chapter 1 Software Architect Capability Model 3 Software Architect Capability Model: Benefits 4 How Should Organizations Utilize the Software Architect Capability Model? 4 Why Create a Personal Software Architect Capability Model? 5 Rudimentary Guiding Principles 6 Software Architect Capability Model Creation Process 6 Requirements Drive Architecture Solutions 7 Requirements Issued by Problem and Solution Domain Entities 7 How Do the Problem and Solution Domains Collaborate? 7 Important Facts to Remember 9 Create a Software Architect Capability Model in Five Steps 9 Step 1: Provide Requirements and Specifications 10 Business Requirements 10 Technical Specifications 11 Ensure Clear Requirements 11 Step 2: Identify Software Architecture Practices 12 Establish Architecture Practices 12 Step 3: Establish Software Architecture Disciplines 13 Apply Architecture Disciplines to Architecture Practices 14 Applying Disciplines to the Application Architecture Practice 14 Applying Disciplines for the Data Architecture Practice 16 Step 4: Add Software Architecture Deliverables 17 About Software Architecture Deliverables 17 Add the Deliverables Section 18 Step 5: Quantify Skill Competencies 21 Quantifying Architecture Skills 22 Measuring the Application Architect Skill Levels 22 Measuring Data Architect Skill Levels 24 Skill Competency Patterns for Architects 25 How Can Organizations Utilize the Skill Competency Pattern? 26 How an Individual Can Utilize the Skill Competency Pattern 27 Interview Questions 28 Part 2 Software Architecture Career Planning 29 Chapter 2 Types of Software Architects 31 Business Needs for Technological Solutions 32 Business Needs for Software Architecture: Strategic Collaboration 32 How Does Software Architecture Respond to Business Needs? 33 Business Needs for Software Architecture: Technological Mediation 33 How Could Technological Mediation Efforts Be Utilized? 34 Business Needs for Software Architecture: Technological Implementation 34 How Does the Implementation of Software Products Meet Business Needs? 34 Organizational Leading Software Architect Levels 35 Ranking Leading Software Architects 35 Collaboration Hierarchy of Leading Software Architects 36 Level I: Enterprise Architect Responsibilities 38 Enterprise Architect Summary of Responsibilities 38 Enterprise Architect Responsibility Table 39 Level II: Solution Architect Responsibilities 40 Solution Architect Summary of Responsibilities 41 Solution Architect Responsibility Table 42 Level III: Application Architect Responsibilities 44 Application Architect Summary of Responsibilities 44 Application Architect Responsibilities Table 46 Comparing Responsibilities of Leading Software Architects 48 Types of Domain Software Architects 49 Data Architect 49 Data Architect Summary of Responsibilities 50 Data Architect Responsibilities Table 51 Cloud Architect 51 Cloud Architect Summary of Responsibilities 54 Cloud Architect Responsibilities Table 55 Security Architect 57 Security Architect Summary of Responsibilities 58 Security Architect Responsibilities Table 60 Business Architect 62 Business Architect Summary of Responsibilities 62 Business Architect Responsibilities Table 63 Collaboration Between Leading Software Architects and Domain Software Architects 65 Use Case I: Collaboration Between an Application Architect and a Data Architect 66 Application Architect and Data Architect Collaboration Table 66 Use Case II: Solution Architect and Security Architect 68 Solution Architect and Security Architect Collaboration Table 68 Use Case III: Business Architect and Enterprise Architect Collaboration 70 Business Architect and Enterprise Architect Collaboration Table 70 Chapter 3 Career Planning for Software Architects: A Winning Strategy 73 Software Architecture Career Planning Process 74 Career Planning Step 1: Conduct Self- Discovery 75 Discovery of Technological and Social Talents 75 Career Planning Self- Discovery Subjects 76 Career Planning Step 2: Pursue Research 76 Formal Education, Training, and Certification 77 Employment Opportunities and Interviews 77 Subjects of Research 77 Career Planning Step 3: Devise an Approach 78 Setting Software Architecture Career Goals 78 Setting Software Architecture Career Milestones 80 Decision- Making 81 Action Planning 82 Career Planning Step 4: Plan Career Execution 85 Use Case I: A Software Architecture Career Execution Plan with Alternative Tasks 85 Use Case II: Optimized Software Architecture Execution Plan 88 Self- Discovery Process: The Six Ws 89 The “Why” 90 The “Who” 91 The “What” 92 Self- Discovery Questions for Software Architecture Candidates 93 Self- Discovery Queries for Software Architects 93 The “Where” 94 The “When” 95 The “How” 96 “How” Self- Queries for Software Architecture Applicants 97 “How” Self- Questions for Practicing Software Architects 97 Carving a Software Architecture Career Path 98 The 4D Software Architecture Career Perspectives 99 Social- Driven Career Perspective 100 Social- Driven Career Chart 100 Carve Out a Social- Driven Career Chart 101 Social- Driven Career Path 102 Create a Social- Driven Career Path 102 Technology- Driven Career Perspective 103 Technology- Driven Career Chart 104 Create a Technology- Driven Career Chart 105 Technical- Driven Career Path 106 Develop a Technical- Driven Career Path 106 Leadership- Driven Career Perspective 107 Leadership- Driven Career Chart 108 Create a Leadership- Driven Career Chart 109 Leadership- Driven Career Path 110 Develop a Leadership- Driven Career Path 110 Strategy- Driven Career Perspective 112 Strategy- Driven Career Chart 112 Create a Strategy- Driven Career Chart 114 Strategy- Driven Career Path 114 Develop a Strategy- Driven Career Path 115 Chapter 4 Self- Assessment for Software Architects 117 Social Intelligence 118 Teamwork 118 Partnership 119 Self- consciousness 119 Communication 120 Networking 120 Soft Skills 120 Trust Building 121 Learning from Others 121 Negotiation 122 Self- presentation 122 Teleworking 123 Fellowship 123 Self- sufficiency 124 Handling Customer Relationships 124 Social Intelligence Skill Assessment 124 Software Architecture Practice 126 Software Architecture Strategy 126 Software Architecture Vision 127 Software Architecture Role 127 System Integration 128 Interoperability 128 Software Reuse 129 Distributed Architecture Model 129 Federated Architecture Model 129 Architecture Styles 130 Architecture and Design Patterns 130 Componentization 130 Software Architecture Frameworks 131 Software Development 131 Software Architecture Practice Skill Assessment 132 Leadership 133 Managing Time 134 Decision- Making 134 Problem-solving 134 Diversity, Equity, and Inclusion 135 Responsibility and Accountability 135 Hiring Preferences 136 Creative Thinking 136 Critical Thinking 136 Being Proactive 137 Establishment of Trust 137 Administrative Duties 138 Coaching and Training 138 Team Building 139 Resolving Conflicts 139 Assessment of Leadership Competencies 140 Strategy 141 Software Architecture Strategy 142 Strategic Thinking 142 Problem Identification 142 Problem-solving 143 Abstraction 143 Generalization 144 Visualization 144 Software Design Approaches 145 Simplification 145 Analytical Capabilities 145 Influencing 146 Promoting Culture 146 Strategy Execution Plan 147 Assessment of Strategic Competencies 147 Part 3 Software Architecture Toolbox 149 Chapter 5 Employing Innate Talents to Provide Potent Organizational Solutions 151 Innate Skills Promote Software Architecture Effectiveness 152 Remember: Survival, Survival, Survival 152 Consequences of Failing to Invoke Innate Talents 153 Employ Chief Innate Talents to Become an Effective Software Architect 154 The Power of Creativity 154 The Benefits of Unleashing Software Architecture Creativity 155 Unleash the Power of Software Architecture Creativity 155 The Potency of Imagination 157 The Benefits of Harnessing Imagination 158 Unleash the Power of Imagination 159 Software Design Aesthetic 162 Technical Proficiency and Aesthetic Talents Drive Software Design 162 The Chief Contribution of Design Aesthetic Talents to Software Architecture 163 Curiosity Attributes 167 The Contribution of Curiosity to Software Architecture 167 The Influencing Facets of Curiosity on Software Architecture Practices 168 Chapter 6 Software Architecture Environment Construction 173 Benefits of the Software Architecture Environment Construction Discipline 174 Must Haves: Problem Statements and Requirements 174 Never Start a Software Design Project Without Understanding the Problems 175 Never Start a Software Design Project Without Requirements 176 Software Architecture Structures 176 Micro Level: Multidimensional Structures of Software Implementations 176 Macro Level: 3D Software Architecture Environment Structure 177 Software Architecture Environment: Driven by an Uncontrolled Quantum Landscape Behavior 178 Software Architecture Environment: An Intelligent Topological Space 179 Deformation Aspects of a Multidimensional Software Architecture Environment 181 Entanglement Effects in a Software Architecture Environment 182 Software Architecture Environment Forces Drive Software Behavior 183 Probability Assessment of Software Operations and Behavior 184 Software Architecture Environment Positive and Negative Forces 184 Software Architecture Environment Gravitational Forces 185 The Impetus for Granting Software Architecture Gravitational Powers to Software Implementations 186 Software Architecture Gravitational Force Intensity 187 The Cost of Unbalanced Software Architecture Environment Gravitational Forces 187 Competing Software Architecture Environment Forces 188 Software Architecture Environment: A Survival Game Space 188 Maintaining a Pragmatic Balance Between Competing Software Architecture Forces 189 Mitigating the Competing Forces Challenge 190 Software Architecture Environment Harmonizing and Disharmonizing Forces 190 Chief Properties of Harmonizing Forces in a Software Architecture Environment 191 Chief Properties of Disharmonizing Forces in a Software Architecture Environment 193 Genetic Encoding of a Software Architecture Environment 194 Difficulties of Restructuring a Software Architecture Environment 194 Encoding a Software Architecture Environment 195 Influences on Social, Behavioral, and Business Goals 195 Software Architecture Environment Construction Life Cycle 196 Software Architecture Environment Construction Process 197 Creating a Software Architecture Environment Construction Balance Table 197 Software Architecture Environment Construction Design Activities 199 Use Case I: Software Architecture Environment Composition and Decomposition Design Activities 201 Design- Time vs. Runtime Environment Composition and Decomposition Design Activities 201 Composition and Decomposition Design Methods 202 Composition and Decomposition Process Outline 203 Use Case II: Software Architecture Environment Integration and Disintegration Design Activities 204 When to Apply Integration and Disintegration Design Activities 205 Integration and Disintegration Design Methods 205 Integration and Disintegration Process Outline 206 Use Case III: Software Architecture Environment Centralization and Decentralization Design Activities 208 When to Employ the Software Environment Centralization and Decentralization Design Activities 208 Centralization and Decentralization Design Methods 209 Software Architecture Environment Centralization and Decentralization Process Outline 210 Use Case IV: Software Architecture Environment Elasticity and Inelasticity Design Activities 211 Chapter 7 When to Employ Elasticity and Inelasticity Design Activities 212 Elasticity and Inelasticity Design Methods 213 Software Architecture Elasticity and Inelasticity Design Process Outline 214 Use Case V: Software Architecture Environment Synchronization and Desynchronization Design Activities 215 When to Employ Environment Synchronization and Desynchronization Design Activities 216 Environment Synchronization and Desynchronization Design Methods 216 Software Architecture Environment Synchronization and Desynchronization Design Process Outline 218 Construction Laws of a Software Architecture Environment 219 Best Practices for Software Architecture Environment Construction 220 Structural Construction of Software Implementations in Multidimensional Environments 223 Software Architecture Solids: Rudimentary Geometrical Design Structures 224 Atomic Solid 225 Composite Solid 227 Monolithic Solid 228 Interface Solid 229 Pipe Solid 230 Inclusive Utilization of Pipe Solids 231 Exclusive Utilization of Pipe Solids 232 Internal Utilization of Pipe Solids 233 Data Solid 234 Software Architecture Solids’ Attribute Summary 236 Software Architecture Dimensional Model 237 Software Architecture: Zero Dimension 238 Software Architecture: One Dimension 239 Software Architecture: Two Dimensions 240 What Impacts the Length and Width Dimensions of a 2D Software Structure? 241 Software Architecture: Three Dimensions 242 Volumes of 3D Software Structures 242 Increase in Software Architecture Level of Specificity in a 3D Computing World 243 Software Population Sustainability in an Architecture Environment Space: A Capacity Planning Challenge 245 Comparative Perspectives in a Software Architecture Space 246 3D Software Structures in a Software Architecture Computing Space 247 The Impetus for Establishing a 3D Software Architecture Space 247 Chief Features of Software Architecture Computing Space 249 Influences of Software Structures on Software Architecture Computing Space 250 Relative Positions in a 3D Software Architecture Computing Space 250 Coordinate Axes: Skeleton of a Software Architecture Computing Space 251 Software Architecture Computing Space Logical Coordinate System 252 Cardinal and Intercardinal Physical Directions in Software Architecture Computing Space 253 Applying Cardinal and Intercardinal Directions to Software Architecture Computing Space 254 Marrying a Logical Coordinate System with Cardinal and Intercardinal Physical Directions System 255 Leveraging the Z- Axis to Create Floors in a Software Architecture Computing Space 256 Distribution Styles of 3D Software Implementations in an Architecture Computing Space 257 Federated Distribution Style 258 Flooring Distribution Style 260 Symmetrical and Asymmetrical Distribution Styles 261 Symmetrical Distribution Style 261 Asymmetrical Distribution Style 263 Construction Life Cycle of Software Implementations 264 Software Construction Process 265 Creating a Software Construction Balance Table 265 Software Construction Design Activities 266 Use Case I: Thicken and Contract Design Activities 267 When to Apply Thicken and Contract Design Activities 268 Thicken and Contract Design Methods 269 Software Structure Thickening and Contracting Process Outline 270 Use Case II: Lengthen and Shorten Design Activities 272 When to Apply the Lengthen and Shorten Design Activities 273 Lengthen and Shorten Design Methods 273 Software Structure Lengthening and Shortening Process Outline 275 Use Case III: Layer and Delayer Design Activities 277 When to Apply Layer and Delayer Design Activities 277 Layer and Delayer Design Methods 278 Layer and Delayer Process Outline 279 Governing Laws for Software Construction in a 3D Computing World 281 Best Practices for Constructing Software Implementations 282 Part 4 Software Architecture Interview Preparations 285 Chapter 8 Preparing for a Software Architecture Interview: A Winning Strategy 287 Software Architecture Job Interview Strategy 288 Preparing a Job Interview Defense Plan 288 Preparing a Job Interview Attack Plan 289 Software Architecture Job Interview Preparation Model 290 Software Architecture Job Interview Defense Plan 291 Study and Analyze the Job Description 291 Start with Identifying the Scope of the Software Architecture Job Requirements 292 Dive Deep into the Software Architect Job Description 293 Start with Analyzing the Summary Portion of the Job Requirements 294 Create a Findings Table Version I for the Job Description 295 Next, Analyze the Responsibilities Portion of the Job Requirements 296 Then, Update the Findings Table Version II of the Job Description 296 Last, Analyze the Software Architect Skills Portion of the Job Requirements 297 Do Not Forget to Update the Findings Table of the Job Description 298 Create a Software Architect Skill Competency Model for the Job Description 299 Skill Competency Model’s Requirements and Practices 300 Skill Competency Model’s Disciplines 301 Design Discipline’s Deliverables 301 Cybersecurity Discipline Deliverables 301 Products Selection and Evaluation Discipline’s Deliverables 302 SDLC Discipline’s Deliverables 302 The Competency Part of the Skill Competency Model 303 Discover the Personal Knowledge Gap Before Attending a Job Interview 303 Assess Whether the Next Software Architecture Job Is a Strategic Career Move 304 Conduct a Software Architecture Mock Interview 305 Prepare a Software Architecture Interview Cheat Sheet 306 Prepare for Possible Software Architecture Interview Questions 307 Software Architecture Job Interview Attack Plan 308 Study the Hiring Organization’s Business 309 Start by Finding Information About the Hiring Organization 309 Chapter 9 Leveraging Business Knowledge During an Interview 311 Understand the Business Model 312 Get Familiar with the Hiring Company’s Culture 314 Conduct a Quick SWOT Analysis 315 Understand the Hiring Organization’s Technology 316 Technological Information Sources 316 Discover the Environment’s Technology Stack 318 Learn About the Development Technology Stack 319 Study the Applications 320 Identify Specific IT Projects 321 Demonstrate Enterprise Architecture Knowledge of the Hiring Organization 321 Adopt Software Architecture Lingo 323 Use Design Patterns Vocabulary 323 Use the Software Architecture Guidelines Lingo to Communicate Solutions 324 Remember Software Architecture Tools 328 Classification of Software Architecture Tools 329 Especially Prepare for Architecture Visualization Tools Questions 332 Get Familiar with Software Architecture Analysis and Evaluation Methods 333 Be Aware of Early Architecture Evaluation Methods 334 Be Aware of Late Architecture Evaluation Methods 335 Talk About Software Architecture Analysis Standards 335 An Outline for Software Architecture Job Interview Questions 337 Behavioral Questions 338 Communication 339 Interpersonal Relationships 340 Software Architecture Leadership 340 Skill Assessment Questions 341 Software Architecture Attributes Questions 342 Software Architecture LifeCycle Questions 343 Software Architecture Concepts Questions 346 Design Building Blocks Concepts 347 Employ Design Building Blocks Concepts to Depict Solutions 347 Prepare for the “How to Design” Interview Questions 348 Software Architecture Environment Concepts 349 Business Concepts 351 Consumer Concepts 352 Architecture Style, Architecture Pattern, and Design Pattern Questions 353 Architecture Patterns vs. Design Patterns 353 Understand Architecture Styles 355 Remember Contextual Hierarchy of Patterns 355 Why Interviewers Ask Architecture and Design Pattern Questions 356 Prepare for Architecture and Design Pattern Questions 357 Problem-solving and decision- making Questions 358 Embrace the Software Architecture Problem- Solving and Decision- Making Process 358 Identifying Business Problems 358 Attend to the Problem- Solving and Decision- Making Process 359 Prepare for Problem- Solving and Decision- Making Questions 360 Data- Related Questions 360 Focus on Data Aspects Related to Software Architecture 361 More Data- Related Interview Questions 361 Production Environment Questions 362 Characteristics of Software Architecture Environment Hosted in Production 363 Production Environment-Related Questions 364 Software Architecture Framework Questions 365 Focus on Array of Framework Contributions 365 Software Architecture Framework Questions 367 Index 369

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Book SynopsisMake your every wishAlexa's commandwith thisin-depth guidetothewildlypopular Amazon smart speaker You might be thinking,All I have to do is plug in my Echo device and start using it! And you'd be right. But if youreallywant to explore what that compact little device can do, thenAlexaForDummiesis your go-to resource.This bookshowsyouhow tocustomize your device to respond to yourrequestsandenhance your life. Alexa For Dummiestakes you on a tour of all things Alexa: its capabilities, tools, settings, and skills.Go beyond the basics ofplaying music, calling friends, reading the news, and checking the weather.You'll learn how to make Alexa private and secure, connect it to your smart home devices, and even make it sound like Samuel L. Jackson, if you feel like it.You can alsoextend its capabilitiesby adding new skills. Customize your device to respond to your voiceTroubleshoot when a light is signaling something's wrongAdd skills to play music and audiobooksCreate routines toturn on lights, adjust the thermostat,set your security alarm, and lock your doorsSync your smart devices throughout your homeUse Alexa to connect to a Zoom meeting or phone call with your friends or family No matter which device you haveEcho, Echo Dot, Echo Show, Echo Studio, Echo Flex, Echo Loop, Echo Buds, or Echo FramesAlexaForDummiesis the perfect companion.Ready to get started? Say Hey,Alexa, orderAlexaForDummies!Table of ContentsIntroduction 1 Part 1: Getting Started with Alexa 5 Chapter 1: Getting to Know Alexa 7 Chapter 2: Setting Up Alexa and Your Devices 21 Chapter 3: Learning Alexa Basics 43 Part 2: Having Fun with Alexa 59 Chapter 4: Playing Media 61 Chapter 5: Communicating with Alexa 89 Chapter 6: Using Alexa at Home 111 Chapter 7: Being More Productive 131 Part 3: Getting More out of Your Relationship with Alexa 149 Chapter 8: Asking Alexa Questions 151 Chapter 9: Adding Skills to Alexa 161 Chapter 10: Making Alexa Accessible 177 Part 4: Controlling Your Smart Home 191 Chapter 11: Setting Up Your Smart Home 193 Chapter 12: Uncovering Some Smarter Smart-Home Techniques 215 Part 5: The Part of Tens 237 Chapter 13: Ten (Times Ten) Ridiculously Fun Alexa Tricks 239 Chapter 14: Ten Things That Can Go Wrong (and How to Fix Them) 247 Chapter 15: Ten Ways to Beef Up Security and Privacy 263 Index

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Book SynopsisTable of ContentsIntroduction 1 Book 1: Getting Started with Electronics 7 Chapter 1: Welcome to Electronics 9 Chapter 2: Understanding Electricity 21 Chapter 3: Creating Your Mad-Scientist Lab 37 Chapter 4: Staying Safe 61 Chapter 5: Reading Schematic Diagrams 71 Chapter 6: Building Projects 85 Chapter 7: The Secrets of Successful Soldering 121 Chapter 8: Measuring Circuits with a Multimeter 133 Chapter 9: Catching Waves with an Oscilloscope 149 Book 2: Working with Basic Electronic Components 161 Chapter 1: Working with Basic Circuits 163 Chapter 2: Working with Resistors 203 Chapter 3: Working with Capacitors 235 Chapter 4: Working with Inductors 261 Chapter 5: Working with Diodes and LEDs 275 Chapter 6: Working with Transistors 301 Book 3: Working with Integrated Circuits 331 Chapter 1: Introducing Integrated Circuits 333 Chapter 2: The Fabulous 555 Timer Chip 345 Chapter 3: Working with Op-Amps 383 Book 4: Beyond Direct Current 403 Chapter 1: Getting into Alternating Current 405 Chapter 2: Building Power Supplies 429 Chapter 3: Understanding Radio 441 Chapter 4: Working with Infrared 467 Book 5: Doing Digital Electronics 485 Chapter 1: Understanding Digital Electronics 487 Chapter 2: Getting Logical 503 Chapter 3: Working with Logic Circuits 523 Chapter 4: Working with Flip-Flops 561 Chapter 5: Introducing Microcontrollers 591 Book 6: Working with Arduino Microprocessors 597 Chapter 1: Introducing Arduino 599 Chapter 2: Creating Arduino Sketches 615 Chapter 3: More Arduino Programming Tricks 647 Chapter 4: An Arduino Proximity Sensor 665 Chapter 5: Adding Sound and Motion to Your Arduino Projects 681 Chapter 6: Keypads and Keyboards 711 Book 7: Working with Raspberry Pi 735 Chapter 1: Introducing Raspberry Pi 737 Chapter 2: Programming in Python 759 Chapter 3: Reading Digital and Analog Input 791 Book 8: Special Effects 813 Chapter 1: Building a Color Organ 815 Chapter 2: Animating Holiday Lights 827 Chapter 3: Building an Animatronic Prop Controller 851 Chapter 4: Re-Creating a Retro Science-Fiction Robot Head 881 Index 893

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Book SynopsisPower Flow Control Solutions for a Modern Grid using SMART Power Flow Controllers Provides students and practicing engineers with the foundation required to perform studies of power system networks and mitigate unique power flow problems Power Flow Control Solutions for a Modern Grid using SMART Power Flow Controllers is a clear and accessible introduction to power flow control in complex transmission systems. Starting with basic electrical engineering concepts and theory, the authors provide step-by-step explanations of the modeling techniques of various power flow controllers (PFCs), such as the voltage regulating transformer (VRT), the phase angle regulator (PAR), and the unified power flow controller (UPFC). The textbook covers the most up-to-date advancements in the Sen transformer (ST), including various forms of two-core designs and hybrid architectures for a wide variety of applications. Beginning with an overview of the origin and development of modern power flow controllers, Table of ContentsAuthors’ Biographies xiii Foreword xv Nomenclature xix Preface xxv Acknowledgments xxix About the Companion Website xxxi 1 Smart Controllers 1 1.1 Why is a Power Flow Controller Needed? 1 1.2 Traditional Power Flow Control Concepts 5 1.3 Modern Power Flow Control Concepts 14 1.4 Cost of a Solution 22 1.4.1 Defining a Cost-Effective Solution 22 1.4.2 Payback Time 24 1.4.3 Economic Analysis 24 1.5 Independent Active and Reactive PFCs 26 1.6 SMART Power Flow Controller (SPFC) 39 1.6.1 Example of an SPFC 40 1.6.2 Justification 41 1.6.3 Additional Information 41 1.7 Discussion 42 2 Power Flow Control Concepts 45 2.1 Power Flow Equations for a Natural or Uncompensated Line 60 2.2 Power Flow Equations for a Compensated Line 63 2.2.1 Shunt-Compensating Voltage 67 2.2.1.1 Power Flow at the Modified Sending End with a Shunt-Compensating Voltage 70 2.2.1.2 Power Flow at the Receiving End with a Shunt-Compensating Voltage 73 2.2.1.3 Exchanged Power by a Shunt-Compensating Voltage 79 2.2.1.4 Representation of a Shunt-Compensating Voltage as a Shunt-Compensating Impedance 79 2.2.2 Series-Compensating Voltage as an Impedance Regulator, Voltage Regulator, and Phase Angle Regulator (Asymmetric) 80 2.2.2.1 Power Flow at the Sending End with a Series-Compensating Voltage 92 2.2.2.2 Power Flow at the Receiving End with a Series-Compensating Voltage 95 2.2.2.3 Power Flow at the Modified Sending End with a Series-Compensating Voltage 100 2.2.2.4 Exchanged Power by a Series-Compensating Voltage 109 2.2.2.5 Additional Series-Compensating Voltages 126 2.2.2.5.1 Phase Angle Regulator (Symmetric) 126 2.2.2.5.2 Reactance Regulator 129 2.2.2.5.2.1 Reactance Control Method 137 2.2.2.5.2.2 Voltage Control Method 139 2.2.2.6 Representation of a Series-Compensating Voltage as a Series-Compensating Impedance 145 2.2.2.6.1 Equivalent Impedance of a Voltage Regulator (VR) 152 2.2.2.6.2 Equivalent Impedance of a Phase Angle Regulator (Asymmetric) 154 2.2.2.6.3 Equivalent Impedance of a Phase Angle Regulator (Symmetric) 157 2.2.2.6.4 Equivalent Impedance of a Reactance Regulator 160 2.2.3 Comparison Between Series- and Shunt-Compensating Voltages 165 2.3 Implementation of Power Flow Control Concepts 168 2.3.1 Voltage Regulation 168 2.3.1.1 Direct Method 168 2.3.1.2 Indirect Method 170 2.3.2 Phase Angle Regulation 173 2.3.2.1 Single-core Phase Angle Regulator 173 2.3.2.2 Dual-core Phase Angle Regulator 176 2.3.3 Series Reactance Regulation 178 2.3.3.1 Direct Method 178 2.3.3.2 Indirect Method 178 2.3.4 Impedance Regulation 179 2.3.4.1 Unified Power Flow Controller (UPFC) 181 2.3.4.2 Sen Transformer (ST) 183 2.4 Interline Power Flow Concept 185 2.4.1 Back-to-Back SSSC 186 2.4.2 Multiline Sen Transformer (MST) 188 2.4.3 Back-to-Back STATCOM 192 2.4.4 Generalized Power Flow Controller 194 2.5 Figure of Merits Among Various PFCs 196 2.5.1 VR 196 2.5.2 PAR (sym) 196 2.5.3 PAR (asym) 198 2.5.4 RR 202 2.5.5 IR 204 2.5.6 RPI, LI, and APR of a PFC 206 2.6 Comparison Between Shunt-Compensating Reactance and Series-Compensating Reactance 228 2.6.1 Shunt-Compensating Reactance 230 2.6.1.1 Restoration of Voltage at the Midpoint of the Line 230 2.6.1.2 Restoration of Voltage at the One-Third and Two-Third Points of the Line 232 2.6.1.3 Restoration of Voltage at the One-Fourth, Half, and Three-Fourth Points of the Line 233 2.6.1.4 Restoration of Voltage at n Points of the Line 235 2.6.2 Series-Compensating Reactance 239 2.7 Calculation of RPI, LI, and APR for a PAR (sym), a PAR (asym), a RR, and an IR in a Lossy Line 242 2.7.1 PAR (sym) 245 2.7.2 PAR (asym) 246 2.7.3 RR 248 2.7.4 IR 249 2.8 Sen Index of a PFC 253 3 Modeling Principles 255 3.1 The Modeling in EMTP 255 3.1.1 A Single-Generator/Single-Line Model 259 3.1.2 A Two-Generator/Single-Line Model 264 3.2 Vector Phase-Locked Loop (VPLL) 277 3.3 Transmission Line Steady-State Resistance Calculator 280 3.4 Simulation of an Independent PFC, Integrated in a Two-Generator/Single-Line Power System Network 281 4 Transformer-Based Power Flow Controllers 297 4.1 Voltage-Regulating Transformer (VRT) 297 4.1.1 Voltage Regulating Transformer (Shunt-Series Configuration) 298 4.1.2 Two-Winding Transformer 315 4.2 Phase Angle Regulator (PAR) 322 4.2.1 PAR (Asymmetric) 322 4.2.2 PAR (Symmetric) 332 5 Mechanically-Switched Voltage Regulators and Power Flow Controllers 341 5.1 Shunt Compensation 341 5.1.1 Mechanically-Switched Capacitor (MSC) 341 5.1.2 Mechanically-Switched Reactor (MSR) 353 5.2 Series Compensation 354 5.2.1 Mechanically-Switched Reactor (MSR) 354 5.2.2 Mechanically-Switched Capacitor (MSC) with a Reactor 363 5.2.3 Series Reactance Emulator 369 6 Sen Transformer 375 6.1 Existing Solutions 377 6.1.1 Voltage Regulation 383 6.1.2 Phase Angle Regulation 385 6.2 Desired Solution 386 6.2.1 ST as a New Voltage Regulator 389 6.2.2 ST as an Independent PFC 392 6.2.3 Control of ST 394 6.2.3.1 Impedance Emulation 395 6.2.3.2 Resistance Emulation 396 6.2.3.3 Reactance Emulation 396 6.2.3.4 Closed-Loop Power Flow Control 397 6.2.3.5 Open-Loop Power Flow Control 398 6.2.4 Simulation of ST Integrated in a Two-Generator/One-Line Power System Network 425 6.2.5 Simulation of ST Integrated in a Three-Generator/Four-Line Power System Network 439 6.2.6 Testing of ST 453 6.2.7 Limited-Angle Operation of ST 485 6.2.8 ST Using LTCs with Lower Current Rating 498 6.2.9 ST with a Two-Core Design 501 6.3 Comparison Among the VRT, PAR, UPFC, and ST 510 6.3.1 Power Flow Enhancement 510 6.3.2 Speed of Operation 511 6.3.3 Losses 512 6.3.4 Switch Rating 512 6.3.5 Magnetic Circuit Design 513 6.3.6 Optimization of Transformer Rating 513 6.3.7 Harmonic Injection into the Power System Network 515 6.3.8 Operation During Line Faults 515 6.4 Multiline Sen Transformer 516 6.4.1 Basic Differences Between the MST and BTB-SSSC 519 6.5 Flexible Operation of the ST 520 6.6 ST with a Shunt-Compensating Voltage 522 6.7 Limited Angle Operation of the ST with Shunt-Compensating Voltages 526 6.8 MST with Shunt-Compensating Voltages 531 6.9 Generalized Sen Transformer 532 6.10 Summary 533 Appendix A Miscellaneous 535 A.1 Three-Phase Balanced Voltage, Current, and Power 535 A.2 Symmetrical Components 538 A.3 Separation of Positive-, Negative-, and Zero-Sequence Components in a Multiple Frequency Composite Variable 544 A.4 Three-Phase Unbalanced Voltage, Current, and Power 547 A.5 d-q Transformation (3-Phase System, Transformed into d-q axes; d-axis Is the Active Component and q-axis Is the Reactive Component) 551 A.5.1 Conversion of a Variable Containing Positive-, Negative-, and Zero-Sequence Components into d-q Frame 556 A.5.2 Calculation of Instantaneous Power into d-q Frame 560 A.5.3 Calculation of Instantaneous Power into d-q frame for a Three-Phase, Three-Wire System 560 A.6 Fourier Analysis 566 A.7 Adams-Bashforth Numerical Integration Formula 569 Appendix B Power Flow Equations in a Lossy Line 571 B.1 Power Flow Equations for a Natural or Uncompensated Line 575 B.2 Power Flow Equations for a Compensated Line 582 B.2.1 Shunt-Compensating Voltage 583 B.2.1.1 Power Flow at the Modified Sending End with a Shunt-Compensating Voltage 584 B.2.1.2 Power Flow at the Receiving End with a Shunt-Compensating Voltage 587 B.2.1.3 Exchanged Power by a Shunt-Compensating Voltage 590 B.2.1.4 Representation of a Shunt-Compensating Voltage as a Shunt-Compensating Impedance 590 B.2.2 Series-Compensating Voltage as an Impedance Regulator, Voltage Regulator, and Phase Angle Regulator (Asymmetric) 591 B.2.2.1 Power Flow at the Sending End with a Series-Compensating Voltage 596 B.2.2.2 Power Flow at the Receiving End with a Series-Compensating Voltage 600 B.2.2.3 Power Flow at the Modified Sending End with a Series-Compensating Voltage 606 B.2.2.4 Exchanged Power by a Series-Compensating Voltage 615 B.2.2.5 Additional Series-Compensating Voltages 624 B.2.2.5.1 Phase Angle Regulator (Symmetric) 624 B.2.2.5 2 Reactance Regulator 628 B.2.2.6 Representation of a Series-Compensating Voltage as a Series-Compensating Impedance 631 B.2.2.6.1 Equivalent Impedance of a Voltage Regulator (VR) 635 B.2.2.6.2 Equivalent Impedance of a Phase Angle Regulator (Asymmetric) 636 B.2.2.6.3 Equivalent Impedance of a Phase Angle Regulator (Symmetric) 638 B.2.2.6.4 Equivalent Impedance of a Reactance Regulator 640 B.2.2.7 RPI, LI, and APR of a PFC 640 B.3 Descriptions of the Examples in Chapter 2 644 Appendix C Modeling of the Sen Transformer in PSS®E 647 C.1 Sen Transformer 647 C.2 Modeling with Two Transformers in Series 648 C.3 Relating the Sen Transformer with the PSSE ® E Model 649 C.4 Chilean Case Study 650 C.5 Limitations – PSS®E Two-Transformer Model 654 C.6 Conclusion 655 References 657 Index 669

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Book SynopsisA practical introduction to microwave plasma for processing applications at a variety of pressures In Microwave Plasma Sources and Methods in Processing Technology, the authors deliver a comprehensive introduction to microwaves and microwave-generated plasmas. Ideal for anyone interested in non-thermal gas discharge plasmas and their applications, the book includes detailed descriptions, explanations, and practical guidance for the study and use of microwave power, microwave components, plasma, and plasma generation. This reference includes over 130 full-color diagrams to illustrate the concepts discussed within. The distinguished authors discuss the plasmas generated at different levels of power, as well as their applications at reduced, atmospheric and higher pressures. They also describe plasmas inside liquids and plasma interactions with combustion flames. Microwave Plasma Sources and Methods in Processing Technology concludes with an inTable of ContentsForeword from the Authors ix 1 Basic Principles and Components in the Microwave Techniques and Power Systems 1 1.1 History in Brief – From Alternating Current to Electromagnetic Waves and to Microwaves 1 1.2 Microwave Generators 3 1.3 Waveguides and Electromagnetic Modes in Wave Propagation 5 1.3.1 The Cut-off Frequency and the Wavelength in Waveguides 7 1.3.2 Waveguides Filled by Dielectrics 9 1.3.3 Wave Impedance and Standing Waves in Waveguides 10 1.3.4 Coaxial Transmission Lines 12 1.3.5 Microwave Resonators 14 1.4 Waveguide Power Lines 14 1.4.1 Magnetron Tube Microwave Generator 16 1.4.2 Microwave Insulators 16 1.4.3 Impedance Tuners 17 1.4.4 Directional Couplers 19 1.4.5 Passive Waveguide Components – Bends, Flanges, Vacuum Windows 20 1.4.6 Tapered Waveguides and Waveguide Transformers 22 1.4.7 Power Loads and Load Tuners 23 1.4.8 Waveguide Phase Shifters 25 1.4.9 Waveguide Shorting Plungers 25 1.4.10 Coupling from Rectangular to Circular Waveguide: Resonant Cavities for Generation of Plasma 26 1.5 Microwave Oven – A Most Common Microwave Power Device 28 References 33 2 Gas Discharge Plasmas 37 2.1 Basic Understanding of the Gas Discharge Plasmas 37 2.2 Generation of the Plasma, Townsend Coefficients, Paschen Curve 40 2.3 Generation of the Plasma by AC Power, Plasma Frequency, Cut-off Density 43 2.4 Space-charge Sheaths at Different Frequencies of the Incident Power 50 2.5 Classification of Gas Discharge Plasmas, Effects of Gas Pressure, Microwave Generation of Plasmas 55 2.5.1 Classification of Gas Discharge Plasmas 55 2.5.2 Effects of the Gas Pressure on Particle Collisions in the Plasma 58 2.5.3 Microwave Generation of Plasmas 61 References 64 3 Interactions of Plasmas with Solids and Gases 67 3.1 Plasma Processing, PVD, and PE CVD 67 3.2 Sputtering, Evaporation, Dry Etching, Cleaning, and Oxidation of Surfaces 72 3.3 Particle Transport in Plasma Processing and Effects of Gas Pressure 75 3.3.1 Movements of Neutral Particles 76 3.3.2 Movements of Charged Particles 77 3.3 Effect of the Gas Pressure on the Plasma Processing 79 3.4 Afterglow and Decaying Plasma Processing 81 References 83 4 Microwave Plasma Systems for Plasma Processing at Reduced Pressures 85 4.1 Waveguide-Generated Isotropic and Magnetoactive Microwave Plasmas 85 4.1.1 Waveguide-Generated Isotropic Microwave Oxygen Plasma for Silicon Oxidation 87 4.1.2 ECR and Higher Induction Magnetized Plasma Systems for Silicon Oxidation 93 4.2 PE CVD of Silicon Nitride Films in the Far Afterglow 105 4.3 Microwave Plasma Jets for PE CVD of Films 111 4.3.1 Deposition of Carbon Nitride Films 115 4.3.2 Surfajet Plasma Parameters and an Arrangement for Expanding the Plasma Diameter 119 4.4 Hybrid Microwave Plasma System with Magnetized Hollow Cathode 122 References 129 5 Microwave Plasma Systems at Atmospheric and Higher Pressures 135 5.1 Features of the Atmospheric Plasma and Cold Atmospheric Plasma (CAP) Sources 136 5.2 Atmospheric Microwave Plasma Sources Assisted by Hollow Cathodes 140 5.2.1 Applications of the H-HEAD Plasma Source in Surface Treatments 144 5.3 Microwave Treatment of Diesel Exhaust 151 5.4 Microwave Plasma in Liquids 154 5.5 Microwave Plasma Interactions with Flames 157 5.6 Microwave Plasmas at Very High Pressures 161 References 162 6 New Applications and Trends in the Microwave Plasmas 169 References 176 7 Appendices 181 7.1 List of Symbols and Abbreviations 181 7.2 Constants and Numbers 188 Index 189

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Book SynopsisFUNDAMENTALS AND APPLICATIONS OF COLOUR ENGINEERING EXPERT OVERVIEW OF THE WORLD OF COLOUR ENGINEERING IN THE 21ST CENTURY, WITH NEW, UPDATED TECHNOLOGIES AND A MATLAB TOOLBOX Fundamentals and Applications of Colour Engineering provides important coverage on topics that hold the power to extend our knowledge of colour reproduction, such as colour measurement and appearance and the methods used, with additional discussion of the technologies responsible for reproducing colour across a wide range of devices, together with the colour management systems that are used to connect devices and exchange information. Composed of 20 chapters, the Editor and his team of expert contributors consider the new ICC.2 architecture, an approach that introduces an evolutionary step in colour engineering, ensuring wider possibilities for technology. The text also considers the emerging applications for advanced colour management, such as processing spectral data, handling HDR images, and the capture and rTable of ContentsSeries Editor's Foreword xvii Preface xix Introductory Notes xxi 1 Instruments and Methods for the Colour Measurements Required in Colour Engineering 1Danny Rich 1.1 Introduction 1 1.2 Visual Colorimetry 3 1.3 Analogue Simulation of Visual Colorimetry 7 1.4 Digital Simulation of Visual Colorimetry 12 1.5 Selecting and Using Colorimeters and Spectrocolorimeters 15 1.6 Geometric Requirements for Colour Measurements 18 1.7 Conclusions and Expectations 22 2 Colorimetry and Colour Difference 27Phil Green 2.1 Introduction 27 2.2 Colorimetry 27 2.3 Normalization 28 2.4 Colour Matching Functions 29 2.5 Illuminants 29 2.6 Data for Observers and Illuminants 30 2.7 Range and Interval 30 2.8 Calculation of Chromaticity 31 2.9 Calculation of CIE 1976 Uniform Colour Spaces 31 2.10 Inversion of CIELAB Equations 34 2.11 Colour Difference 34 2.12 Problems with Using UCS Colour Difference 35 2.13 Uniformity of the Components of Colour Difference 35 2.14 Viewing Conditions 36 2.15 Surface Characteristics 37 2.16 Acceptability of Colour Differences 37 2.17 Overcoming the Limitations of UCS Colour Difference with Advanced Colour Difference Metrics 37 2.18 CIE94 37 2.19 CIEDE2000 39 2.20 Progress on Colour Difference Metrics since CIEDE2000 41 2.21 3D Colour Difference 41 2.22 Colour Difference in High Luminance Conditions 41 2.23 Colour Difference Formulas Based on Colour Appearance Models 41 2.24 Limitations in the Use of Advanced Colour Difference Metrics in Colour Imaging 42 2.25 Basis Conditions 42 2.26 Colour Difference in Complex Images 43 2.27 Acceptability and Perceptibility 44 2.28 Large vs Small Differences 44 2.29 Deriving Colour Difference Tolerances 44 2.30 Sample Preparation 45 2.31 Psychophysical Experiments 45 2.32 Colour Difference Judgements by Observers with a Colour Vision Deficiency 46 2.33 Calculating Colour Tolerances from Experimental Data 46 2.34 Calculation of Discrimination Ellipsoids and Tolerance Distributions 46 2.34.1 Calculation of Parametric Constants in Weightings Functions 47 2.35 Calculation of Acceptability Thresholds 48 2.36 Evaluating Colour Difference Metrics 48 2.37 Conclusion 48 3 Fundamentals of Device Characterization 53Phil Green 3.1 Introduction 53 3.2 Characterization Methods 54 3.3 Numerical Models 57 3.4 Look-Up Tables with Interpolation 63 3.5 Evaluating Accuracy -- Training and Test Data 67 4 Characterization of Input Devices 71Phil Green 4.1 Input Channels 71 4.2 Characterization Goals 72 4.3 Transform Encoding 73 4.4 Dynamic Range 73 4.5 Input Characterization Methods 74 4.5.1 Scanners 74 4.6 Targets 74 4.7 Modelling 74 4.7.1 Digital Cameras 75 4.8 Target-Based Characterization 75 4.9 Targets 75 4.10 Modelling 76 5 Color Processing for Digital Cameras 81Michael S. Brown 5.1 Introduction 81 5.2 Basics of a Camera Sensor 82 5.3 The Camera Pipeline 83 5.4 Multi-Frame Processing 93 5.5 Towards the Neural ISP 94 5.6 Concluding Remarks 95 6 Display Calibration 99Catherine Meininger, Tom Lianza, and Grace Annese 6.1 Introduction 99 6.2 From CRT to Contemporary Display Technologies 99 6.3 The Display Never Sleeps... Merging Television and Computer Display Standards 102 6.4 The Evolution of Display Calibration Capabilities 103 6.5 Measurement Set Requirements 111 6.6 Calibration Validation Methodologies 113 6.7 Low Blue Light Developments 114 6.8 Conclusions 117 7 Characterizing Hard Copy Printers 119Phil Green 7.1 Introduction 119 7.2 Properties of Hard Copy Printers 120 7.3 Substrates and Inks 120 7.4 Colour Gamut 120 7.5 Halftoning 121 7.6 Mechanical Printing Systems 122 7.7 Printing Conditions 122 7.8 Digital Systems 122 7.9 RGB Printers 122 7.10 Test Charts 123 7.11 Printer Models 124 7.12 Block Dye Model 125 7.13 Physical Models 126 7.14 Numerical Models and Look-up Tables 134 7.15 Inverting the Model 137 7.16 Multi-Colour and Spot Colour Characterization 137 7.17 Spectral Characterization 137 7.18 White Ink 138 7.19 Reducing the Frequency of Characterization 138 7.20 Conclusions 138 8 Colour Encodings 143Phil Green 8.1 Introduction 143 8.2 Colour Encoding Components 143 8.3 Colour Spaces 144 8.4 Device and Colour Space Encodings 144 8.5 Colorimetric Interpretation 144 8.6 Image State 145 8.7 Standard 3-Component Colour Space Encodings 146 8.8 Colour Gamut 146 8.8.1 Extended Colour Gamut 147 8.9 Precision and Range 147 8.9.1 High Dynamic Range 148 8.9.2 Negative Values 149 8.10 Luminance/Chrominance Encodings 149 8.11 Conversion to Colorimetry 150 8.12 Implementation Issues 150 8.13 File Formats 152 9 Colour Gamut Communication 155Kiran Deshpande 9.1 Introduction 155 9.2 How to Describe Colour Gamuts 157 9.3 How to Obtain a Colour Gamut of a Printing System 162 9.4 How to Obtain a Colour Gamut of a Display 163 9.5 How to Calculate Gamut Volume 163 9.6 How to Analyse Colour Gamuts 164 9.7 How to Visualize Colour Gamuts 167 9.8 How to Communicate Colour Gamuts 171 9.9 Summary 173 10 The ICC Colour Management Architecture 177Phil Green 10.1 Origins of the ICC 177 10.2 Fundamentals of the ICC Architecture: The PCS, the ICC Profile, Transforms and the CMM 178 10.3 Other CMM Operations 185 10.4 Workflows 187 10.5 Current Status of ICC.1 188 10.6 ICC.2 189 11 iccMAX Color Management -- Philosophy, Overview, and Basics 193Max Derhak 11.1 Background and Philosophy Leading to iccMAX 193 11.2 Overview 194 11.3 Creating Transforms 207 11.4 Specification Subsets via ICSs 209 11.5 Domain Specific Examples 210 11.6 Getting Started with iccMAX (Where Color Engineering Comes to Play) 212 11.7 Conclusion 213 12 Sensor Adjustment 215Phil Green 12.1 Introduction 215 12.2 Aims of Sensor Adjustment 215 12.3 Luminance Adjustment 216 12.4 Chromatic Adaptation 218 12.5 Material-Equivalent Adjustment 220 12.6 Local Adaptation 221 12.7 Incomplete Adaptation 222 13 Evaluating Colour Transforms 227Phil Green 13.1 Introduction 227 13.2 Accuracy 227 13.3 Cost 232 13.4 Subjective Preference 233 14 Appearance Beyond Colour: Gloss and Translucency Perception 239Davit Gigilashvili and Jean-Baptiste Thomas 14.1 Introduction 239 14.2 Gloss Perception 240 14.3 Translucency Perception 244 14.4 Interaction among Appearance Attributes 248 14.5 Impact on Colour Technologies 250 14.6 Conclusion 252 15 Colour Management of Material Appearance 259Tanzima Habib 15.1 Introduction 259 15.2 Material Appearance Modelling 260 15.3 Appearance Support in Colour Management 263 15.4 A Colour Management Workflow for Material Appearance 264 15.5 Conclusion 269 16 Color on the Web 271Chris Lilley 16.1 Early History 271 16.2 Color on the Legacy Web 272 16.3 Wide Color Gamut (WCG) Comes to the Web 277 16.4 Color on the Wide Gamut Web 281 16.5 HDR Comes to the Web 286 17 High Dynamic Range Imaging 293Mekides Assefa Abebe 17.1 Introduction and Background 293 17.2 High Dynamic Range Imaging 296 17.3 Conclusion 308 18 HDR and Wide Color Gamut Display Technologies and Considerations 311Timo Kunkel and Ajit Ninan 18.1 Introduction 311 18.2 Early HDR Display Systems 312 18.3 Transmissive Displays 313 18.4 Emissive Displays 317 18.5 Projection Systems 319 18.6 Reflective Displays 320 18.7 Achieving Wide Color Gamuts 321 18.8 Spatial Display Properties 326 18.9 Temporal Display Properties 327 18.10 Signaling 328 18.11 Characterization and Calibration 330 18.12 Ambient Effects 330 18.13 Conclusion 332 19 Colour in AR and VR 335Michael J. Murdoch 19.1 Introduction 335 19.2 Colour Synthesis in AR and VR Displays 337 19.3 Colour Appearance in AR and VR 342 19.4 Colour Imaging and Graphics in AR and VR 350 19.5 Conclusion 351 20 Colour Engineering Toolbox and Other Open Source Tools 355Phil Green 20.1 Colour Engineering Toolbox 2.0 355 20.2 Polar Calculations 357 20.3 Media-Relative and PCS Scaling 357 20.4 DemoIccMax 360 20.5 Color.js 360 20.6 Little CMS 360 20.7 Argyll 361 20.8 Colour 361 References 361 Index 363

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Book SynopsisSEA ICE The latest edition of the gold standard in sea ice references In the newly revised second edition of Sea Ice: Physics and Remote Sensing, a team of distinguished researchers delivers an in-depth review of the features and structural properties of ice, as well as the latest advances in geophysical sensors, ice parameter retrieval techniques, and remote sensing data. The book has been updated to reflect the latest scientific developments in macro- and micro-scale sea ice research. For this edition, the authors have included high-quality photographs of thin sections from cores of various ice types, as well as a comprehensive account of all major field expeditions that have systematically surveyed sea ice and its properties. Readers will also find: A thorough introduction to ice physics and physical processes, including ice morphology and age-based structural features Practical discussions of radiometric and radar-scattering observatioTable of ContentsPreface xv Acknowledgments and Recognitions xvii 1 Introduction 1 1.1 Background 1 1.2 Canada and the Arctic: Historical and Community Synopsis 4 1.3 The Fascinating Nature of Sea Ice 8 1.4 Sea Ice in Research and Operational Disciplines 12 1.4.1 Sea Ice in Physics 12 1.4.2 Sea Ice in Climatology 13 1.4.3 Sea Ice in Meteorology 14 1.4.4 Sea Ice in Oceanography 15 1.4.5 Sea Ice in Marine Biology 16 1.4.6 Sea Ice in Marine Navigation 17 1.4.7 Sea Ice and Offshore Structures 19 1.4.8 Sea Ice as A Transportation Platform 20 1.4.9 Sea Ice in Relation to Solid Earth Sciences: Rocks and Plate Tectonics 21 1.5 Sea Ice and Remote Sensing 22 1.6 Motivation for the Book Writing 24 1.7 Organization of the Book 25 1.8 References 27 2 Ice Physics and Physical Processes 29 2.1 Prior to Freezing: About Freshwater and Seawater 30 2.1.1 Molecular Composition of Water 30 2.1.2 Seawater Salinity 31 2.1.3 Seawater Density 32 2.2 Phase Diagram of Sea Ice 33 2.3 Initial Ice Formation 33 2.3.1 Freezing Processes in Freshwater and Seawater 33 2.3.2 Initial Formation of Ice Crystals and Frazil Ice 35 2.4 Sea Ice Growth 37 2.4.1 Lateral Ice Growth 37 2.4.2 Vertical Ice Growth (Congelation Ice) 38 2.4.3 Superimposed Ice 39 2.4.4 Thermodynamic Ice Growth 40 2.4.4.1 Simplified Models of Sea Ice Growth 41 2.4.4.2 Effect of Snow On Sea Ice 45 2.4.4.3 Effect of Oceanic Heat Flux 46 2.4.4.4 Effect of Surface Ablation 46 2.5 Processes in Ice 47 2.5.1 Compositional (Constitutional) Supercooling At the Ice–Water Interface 50 2.5.2 Dendritic Ice–Water Interface and Entrapment of Brine Within Sea Ice 51 2.5.3 Grains and Subgrains In Sea Ice 53 2.5.4 Brine Pockets Formation, Contents and Distribution In Sea Ice 54 2.5.5 Salinity Loss During Sea Ice Growth 58 2.5.5.1 Initial Rapid Salt Rejection At the Ice–Water Interface 59 2.5.5.2 Subsequent Slow Salt Rejection from the Bulk Ice 61 2.6 Ice Deformation 67 2.6.1 Rafting of Thin Ice 69 2.6.2 Ridging of Thick Ice 70 2.6.3 Formation of Ice Rubble Field 73 2.6.4 Fractures in Ice Cover 74 2.7 Ice Decay and Aging 76 2.7.1 Ice Decay 76 2.7.2 Ice Aging 80 2.8 Sea Ice Classes 84 2.9 Sea Ice Regimes 85 2.9.1 Polynyas 86 2.9.2 Pancake Ice Regime 90 2.9.3 Marginal Ice Zone and Ice Edge 92 2.9.3.1 Marginal Ice Zone 93 2.9.3.2 Ice Edge 94 2.9.4 Ice of Glacier Origin 95 2.10 References 99 3 Sea Ice Properties: Data and Derivations 107 3.1 Typical Values of Sea Ice and Snow Physical Parameters 107 3.2 Temperature Profiles in Ice and Snow 108 3.3 Bulk Salinity and Salinity Profile 113 3.3.1 Bulk Salinity 115 3.3.2 Salinity profiles 116 3.4 Density of First-Year and Multi-Year Ice 121 3.5 Volume Fraction of Sea Ice Constituents 123 3.5.1 Brine Volume Fraction 123 3.5.2 Solid Salt Volume Fraction 124 3.5.3 Pure Ice Volume Fraction 124 3.5.4 Air Volume Fraction 124 3.5.5 Temperature Dependence of Volume Fractions of Different Components 125 3.6 Thermal Properties 126 3.6.1 Thermal Conductivity of Sea Ice 126 3.6.2 Thermal Conductivity of Snow 129 3.6.3 Specific Heat of Sea Ice 131 3.6.4 Latent Heat of Sea Ice 133 3.7 Dielectric Properties 134 3.7.1 Dielectric Constant of Brine 136 3.7.2 Dielectric Mixing Models 136 3.7.3 Field Measurements of Dielectric Constant 142 3.8 References 146 4 Laboratory Techniques for Revealing the Structure of Polycrystalline Ice 149 4.1 Relevant Optical Properties 151 4.1.1 Polarized Light 151 4.1.2 Birefringence or Double Refraction of Ordinary (Ih) Ice 153 4.1.3 Optical Retardation 155 4.1.4 Interference Colors for White Light 157 4.2 Ice Thin Sectioning Techniques 158 4.2.1 Hot-plate Techniques for Thin Sectioning of Ice 159 4.2.2 Double-Microtoming Technique for Thin Sectioning of Ice 159 4.2.3 Double-Microtoming Technique for Thin Sectioning of Snow 161 4.2.4 Precautions for Thin Sectioning by DMT 163 4.2.5 Optimum Thickness for Thin Sections of Ice and Snow 163 4.3 Viewing and Photographing Ice Thin Sections 164 4.3.1 Laboratory and Hand-Held Polariscope 165 4.3.2 Cross-Polarized versus Parallel-Polarized Light Viewing 168 4.3.3 Scattered Light and Combined Cross-Polarized/Scattered Light Viewing 169 4.3.4 Circularly Polarized Light and Rapid Crystallographic Analysis 172 4.4 Advanced Techniques for Revealing Fine Crystallographic Microstructural Features 173 4.4.1 Sublimation of Ice and Sublimation Pits 173 4.4.2 Etching Processes 176 4.4.2.1 Thermal Etching of Microtomed Ice Surfaces 179 4.4.2.2 Chemical Etching and Replicating Ice Surfaces 183 4.5 References 188 5 Polycrystalline Ice Structure 191 5.1 Terms and Definitions Relevant to Polycrystalline Ice 192 5.1.1 Special Thermal State of Natural Ice 192 5.1.2 General Terms for Structural Aspects of Ice 193 5.1.3 Basic Terms and Definitions 194 5.2 Morphology of Ice 197 5.2.1 Forms of Ice Crystals 197 5.2.2 Miller Indices for Hexagonal Ice 198 5.2.3 Growth Direction of Ice Crystals 199 5.2.4 Ice Density in Relation to Crystalline Structure 199 5.3 Structure- and Texture-Based Crystalline Classification of Natural Ice 200 5.3.1 Freshwater Ice Classification of Michel and Ramseier 200 5.3.2 Extending Crystallographic Classification of Freshwater Ice to Sea Ice 202 5.3.3 Crystallographic Classes of Natural Ice 203 5.3.3.1 Granular or Snow Ice (T1 Ice) 203 5.3.3.2 Randomly Oriented (S4) and Vertically Oriented (S5) Frazil Ice 204 5.3.3.3 Columnar-Grained with c Axis Vertical (S1) Ice 205 5.3.3.4 Columnar-Grained with c Axis Horizontal and Random (S2 Ice) 207 5.3.3.5 Columnar-Grained Ice with c Axis Horizontal and Oriented (S3 Ice) 211 5.3.3.6 Agglomerate Ice with Discontinuous Columnar-Grained (R Type Ice) 211 5.3.3.7 Ice of Land-Based Origin 212 5.3.3.8 Platelet Sea Ice 213 5.3.4 Stereographical Projection (Fabric Diagram) of Natural Polycrystalline Ice 214 5.4 Examples of Crystallographic Structure of Natural Sea Ice 216 5.4.1 Crystallographic Structure of Seasonal Sea Ice 217 5.4.1.1 Frazil Ice (S5 Type) 217 5.4.1.2 Columnar-Grained Ice (S3 Type) 218 5.4.1.3 Agglomeration of Various Crystallographic Structures 220 5.4.1.4 Air Entrapment in Seasonal Ice 220 5.4.2 Crystallographic Structure of Perennial Sea Ice 221 5.4.2.1 Hummock Ice 223 5.4.2.2 Melt Pond Ice 226 5.5 Biomass Accumulation at the Bottom of the Ice 230 5.6 Information Contents in Polycrystalline Ice Structure 232 5.6.1 Geometric Characteristics of Crystalline Structure 232 5.6.2 Geometric Characteristics of Brine Pockets in First-Year Ice 236 5.6.3 Geometric Characteristics of Air Bubbles 242 5.7 References 244 6 Major Field Expeditions to Study Sea Ice 249 6.1 The Arctic Ice Dynamic Joint Experiment (AIDJEX) 250 6.2 Mould Bay Experiments 1981–1984: Stories that Were Never Told 252 6.2.1 Site, Resources, and Logistics 252 6.2.2 Sea Ice Conditions 254 6.2.3 Aging of Sea Ice: from FYI to MYI 259 6.2.4 Interface Between Old and New Ice in Second-Year Ice Profile 260 6.3 High Arctic Experience with Ice of Land Origin 262 6.3.1 Ward Hunt Ice Shelf and Hobson’s Choice Ice Island Experiment 262 6.3.2 Multi-Year Rubble Field Around the Ice Island 265 6.4 Labrador Ice Margin Experiment (LIMEX) 266 6.5 Sea Ice Monitoring and Modeling Site (SIMMS) Program 268 6.6 The Surface Heat Budget of Arctic Ocean (SHEBA) 270 6.7 The Norwegian Young Sea Ice Experiment (N-ICE) 272 6.8 Marginal Ice Zone (MIZ) Experiments 274 6.9 Ice Exercise by Us Navy 277 6.10 The Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) 278 6.11 References 280 7 Remote Sensing Fundamentals Relevant to Sea Ice 283 7.1 General Principles of Satellite Remote Sensing 284 7.2 Electromagnetic Wave Properties and Processes 289 7.2.1 Polarization of EM Wave 290 7.2.2 Reflection, Transmission, Absorption, Scattering, and Emission 292 7.2.2.1 Reflection and Fresnel Model 293 7.2.2.2 Transmission 295 7.2.2.3 Absorption and Scattering Losses 296 7.2.2.4 Emitted Radiation (Re-radiation) 296 7.2.3 Brightness Temperature and Emissivity 297 7.2.4 Penetration Depth 299 7.3 Optical Sensing 300 7.4 Thermal Infrared Sensing 303 7.5 Microwave Remote Sensing 305 7.6 Imaging Radar Sensing 308 7.6.1 Imaging Radar Principles 308 7.6.1.1 Radar Equations and Spatial Resolutions of RAR and SAR 309 7.6.1.2 Coherency and Polarization of Radar Signals 311 7.6.1.3 Radar Scattering Mechanisms 312 7.6.2 Multichannel SAR 313 7.6.3 SAR Polarimetry: Formulation and Derived Parameters 315 7.6.3.1 Formulation of Polarimetric Measurements 316 7.6.3.2 Polarimetric Parameters Derived from the FP SAR Data 317 7.6.3.3 Linking Radar Scattering Mechanisms to Ice Features 320 7.6.3.4 Age-Based versus SAR-Based and Scattering-Based Sea Ice Classification 321 7.7 Scatterometer Systems 322 7.8 Altimeter Systems 323 7.9 Radiative Processes in Relevant Media 325 7.9.1 Atmospheric Influences 325 7.9.1.1 Influences of Atmosphere on Optical and Infrared Observations 325 7.9.1.2 Atmospheric Correction for Passive Microwave Observations 328 7.9.2 Seawater 330 7.9.2.1 Seawater in the Optical and Thermal Infrared Data 330 7.9.2.2 Seawater in the Microwave Data 331 7.9.3 Snow on Sea Ice: Physical and Radiative Processes 333 7.9.3.1 Snow in Optical and Thermal Infrared Data 335 7.9.3.2 Snow in the Microwave Data 336 7.10 References 341 8 Satellite Sensors for Sea Ice Monitoring 349 8.1 Historical Synopsis of Remote Sensing Satellites for Sea Ice 349 8.2 Optical and Thermal Infrared Sensors 352 8.3 Modern Passive Microwave Sensors 353 8.4 Modern Imaging Radar Sensors 355 8.5 Scatterometer Sensors 358 8.6 Altimeter Sensors 359 8.7 References 360 9 Radiometric and Scattering Observations from Sea Ice, Water, and Snow 363 9.1 Optical Reflectance and Albedo Data 364 9.2 Microwave Brightness Temperature Data 370 9.3 Radar Backscatter 376 9.3.1 Backscatter Databases from Single-Channel SAR 378 9.3.2 Dual Polarization Data 384 9.3.3 Fully Polarimetric Data 387 9.4 Emissivity Data in the Microwave Bands 395 9.5 Microwave Penetration Depth 403 9.6 References 407 10 Retrieval of Sea Ice Surface Information 411 10.1 Mechanically Generated Surface Deformation 412 10.1.1 Rafted Ice 412 10.1.2 Ridged, Rubble, and Brash Ice 413 10.1.3 Kinematic Processes: Convergence, Divergence, Shear, and Vorticity 417 10.1.4 Cracks and Leads 421 10.2 Thermally Induced Surface Features 428 10.2.1 Surface Melt 428 10.2.1.1 Optical Observations 428 10.2.1.2 Passive Microwave Observations 432 10.2.1.3 Active Microwave Observations 434 10.2.1.4 Airborne Photography 437 10.2.2 Frost Flowers 438 10.3 Meteorologically Driven Surface Features 442 10.3.1 Polynya Identification and Properties 442 10.3.2 Snow Depth 444 10.4 References 448 11 Retrieval of Sea Ice Geophysical Parameters 453 11.1 Sea Ice Type Classification 454 11.1.1 Ice Classification from Optical and TIR Systems 456 11.1.2 Ice Classification from Passive Microwave Data 457 11.1.3 Ice Classification from SAR 458 11.1.3.1 Ice Classification from Single-Channel SAR 460 11.1.3.2 Ice Classification from Dual-Channel SAR 461 11.1.3.3 Ice Classification from Polarimetric SAR Data 467 11.2 Sea Ice Concentration 471 11.2.1 Ice Concentration from Optical and TIR Images 472 11.2.2 Ice Concentration from Coarse-Resolution Microwave Observations 473 11.2.2.1 NASA TEAM (NT) Algorithm 475 11.2.2.2 The Enhanced NASA Team (NT2) Algorithm 476 11.2.2.3 The ASI Algorithm 478 11.2.2.4 ECICE Algorithm 479 11.2.2.5 Intercomparison of PM Algorithms 486 11.2.2.6 Sources of Error and Sensitivity of Ice Concentration Algorithms 490 11.2.2.7 Assessment of Ice Concentration Results Against Ice Charts 493 11.2.3 Ice Concentration from Fine-Resolution SAR 496 11.3 Sea Ice Extent and Area 498 11.4 Sea Ice Thickness (SIT) 501 11.4.1 SIT from TIR Observations 503 11.4.2 SIT from PM Observations 506 11.4.3 SIT from Altimeter Observations 510 11.4.4 SIT from SAR Observations 514 11.5 Ice Surface Temperature (IST) 517 11.5.1 IST from TIR Observations 517 11.5.2 IST from PM Observations 520 11.6 Sea Ice Age 522 11.7 Sea Ice Motion and Kinematics 524 11.7.1 Methods of Ice Motion Tracking 526 11.7.1.1 Motion Tracking Using Image Features 526 11.7.1.2 Motion Tracking Using Individual Sea Ice Floes 528 11.7.2 Operational Ice Motion Products 532 11.8 References 533 12 Modeling Microwave Emission and Scattering from Snow-Covered Sea Ice 541 By Rasmus Tage Tonboe 12.1 The Need for Modeling Microwave Emission and Scattering from Snow-Covered Sea Ice 541 12.1.1 The ECMWF Workshop and Large-Scale Sea Ice Modeling 542 12.1.2 Gross Features of Forward Models 542 12.2 Radiative Transfer and Modeling Approaches for Sea Ice Thermal Microwave Emission 543 12.2.1 Dense Media Volume Scattering 543 12.2.2 Sea Ice Emission Models 543 12.2.3 Sea Ice Backscatter Models for Level Ice 544 12.2.4 Sea Ice Backscatter Models for Ridged Ice 545 12.3 The Input to a Forward Model 545 12.3.1 Primary Input Parameters 545 12.3.2 Secondary Input Parameters 546 12.3.3 Tertiary Input Parameters, Volume, and Surface Scattering 546 12.4 Example of the Implementation of an Altimeter Model to Study the Impact of Saline Snow on the Backscatter 547 12.5 Example of Combining Atmospheric, Ocean, and Sea Ice Emission Models to Simulate the Noise in Sea Ice Concentration Estimates 548 12.5.1 Snow in the Emission Models 549 12.5.2 The Combined Sea Ice Thermodynamic, Atmospheric, Ocean, and Sea Ice Emission Models 549 12.6 Inverse Modeling 552 12.7 References 553 13 Impacts of Climate Change on Polar Ice 557 13.1 The Inconvenient Truth of Global Warming: How is it Manifested in The Polar Region? 560 13.2 Sea Ice Regimes in the Two Polar Regions 562 13.2.1 Geographic Differences Between the Two Polar Regions and Their Impacts on Sea Ice 562 13.2.2 Differences in Sea Ice Characteristics Between the Two Polar Regions 564 13.3 Changes of Polar Sea Ice in Response to Global Warming 565 13.3.1 The Arctic and Antarctic Ice Extent 565 13.3.2 The Arctic and Antarctic Ice Thickness and Volume 569 13.3.3 The Arctic Sea Ice Age 572 13.3.4 The Arctic Sea Ice Dynamics 575 13.3.5 The Antarctic Icebergs 576 13.4 Coupling Between Polar Sea Ice and Environmental Factors 577 13.4.1 Interaction of the Arctic Sea Ice with the Environment 578 13.4.1.1 Atmospheric Factors that Contribute to Changes in the Arctic Sea Ice 578 13.4.1.2 Enhanced Arctic Warming due to Changes of Sea Ice Cover 578 13.4.1.3 Arctic Warming due to Sea Ice Advection Out of the Arctic Basin 580 13.4.1.4 Interaction of the Arctic Sea Ice with Wind 582 13.4.1.5 Mutual Interactions Between the Arctic Sea Ice Cover and Oceanic Forcing 584 13.4.2 Interaction of the Antarctic Sea Ice with the Environment 585 13.4.2.1 Interaction of the Antarctic Sea ice with Atmospheric Factors 585 13.4.2.2 Interaction of the Antarctic Sea Ice with Oceanic Forcing 586 13.4.2.3 Interaction Between the Antarctic Sea Ice, Ice Shelves, and Icebergs 587 13.5 References 590 Index 595

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Book SynopsisTable of ContentsIntroduction 1 About This Book 1 Foolish Assumptions 3 Icons Used in This Book 3 Beyond the Book 4 Where to Go from Here 4 Part 1: Your Phone in the Android Universe 5 Chapter 1: Why Android? What’s the Deal? 7 A Little Android History 8 The Many Flavors (Versions) of Android 9 Reasons That People Choose Android 10 Why You Need a Google Account 11 Accessing apps and settings 12 Bequeathing your account 12 So Many Choices! 14 Tech support options 15 5G? LTE? 4G? VoLTE? Whaaat? 16 A Word about Privacy and Security 17 Free usually isn’t 17 The terms of service can be tricky 17 Marsha’s sage advice about privacy 18 Chapter 2: Buying Your Android Smartphone and Accessories 21 Investigate First — Then Make a Buying Decision 22 Looking at a phone’s physical features 22 Reviewing before making a decision 26 Considering an older model 27 Choosing where to buy your phone 28 Consider Your Carrier Choice 29 Checking out the carrier’s coverage area 30 Finding senior discounts on carrier service 31 You Need a Few Accessories, Too 32 Power charging blocks — volts and watts matter 32 MicroSD card 33 Phone case 34 Phone Sanitizer 35 Chapter 3: Activating and Connecting Your Phone 37 Unbox Your New Phone 38 Insert a SIM Card 40 Turn On Your Phone for the First Time 41 Connecting to a network 42 Setting up a Google account 42 Setting up a secure lock 44 Restoring data from an older phone 44 Learn Android Smartphone Symbols and Gestures 45 Recognizing common Android icons 45 Meeting the top status bar 47 Exploiting screen navigation and gestures 48 Part 2: Getting Started with Your Android Smartphone 51 Chapter 4: Safety First: Making Your New Phone Private 53 Set Up a Screen Lock 54 Checking out the screen locking options 54 Following the lock screen setup process 56 Establish Data Backup 58 Place Owner Information On the Lock Screen 59 Add Emergency Info 62 Designating Emergency or ICE contacts 62 Providing medical information 63 Chapter 5: Personalizing Your Handset 67 Hardware Buttons and What They Do 68 Power buttons 70 Volume buttons 73 Find and Sort Your Apps 75 Move App Shortcuts to the Home Screen 77 Group Apps into Folders 78 Deal with Preinstalled Applications (or Bloatware) 81 Get the News (and Other Media) You Can Use 82 Customize the Home Screen with Widgets 84 Chapter 6: Android Typing Tricks with Google’s Gboard 87 Make the Keyboard Decision 88 Selecting a keyboard to use 88 Noting keyboard features 89 Exploring keyboards you have (or can have) 93 Check Out Keyboard Contenders 94 Gboard, the official Google keyboard 95 Samsung Keyboard 97 Microsoft SwiftKey keyboard 99 Speak Words with Voice Typing 99 Spell-Check as You Type 100 Extended Keyboard and Special Characters 101 Learn the Emoji Language 102 Delete, Copy, and Paste Text 104 Print Messages, Documents, and Web Pages 105 Chapter 7: Handling Notifications and Google Assistant 109 Meet the Android Notifications Window Shade 110 Recognizing notification types and settings 110 Disabling notifications (or not) 111 Controlling notifications via settings 114 Having fun with notifications, or not 115 Taming Google Discover news feed 117 Manage Your Phone with the Window Shade Quick Settings 119 The first-up Quick Settings 120 The full cast of Quick Settings 121 Get the 411 from Google Assistant 122 Knowing what you can do with Google Assistant 123 Installing or deactivating Google Assistant 124 Part 3: Let’s Start Communicating 127 Chapter 8: Chatting via Voice or Video 129 Make a Voice Call 130 Making international calls from your phone 131 Calling internationally with no contract 132 Check Voicemail 133 Get Voicemail Transcriptions 135 Reply to an Incoming Call by Sending a Text 138 Set a New Ringtone 141 Using a built-in ringtone 141 Downloading a custom ringtone 141 Activating a downloaded ringtone 144 Spend Face Time with Family and Friends 146 Google Duo 146 Google Meet 148 Chapter 9: Keeping Track of Friends and Appointments 149 Establish Your Phone’s Contacts 150 Starting out right with Google Contacts 151 Importing old address books 151 Save Contacts from Email 154 Add a Contact in Other Ways 156 Importing contacts from texts 157 Adding a contact from the call log 158 Type In a Full Contact in the Contacts App 158 Merge Duplicate Contacts 161 Customize, Delete, and Update Contacts 162 Energize Your Calendar App 164 Add Calendar Events from Gmail 166 Chapter 10: Texting with Poise and Character 167 Compare Types of Text Messaging 168 Turning on RCS chat features 170 Using third-party chat apps 172 Dress Up Texts in Google Messages 173 The Text Message Bar and Emoji 176 Find Even More Texting Options 177 Share Photos and Videos in Texts 179 Voice-Type (Dictate) 180 Manipulate the Text in Your Message 181 Schedule a Text Message for Later Delivery 183 Act on Text Messages You Receive 184 Share and Print Documents, Email Messages, and Web Pages 185 Printing from Gmail 186 Printing from a web page 186 Chapter 11: Managing Email with the Gmail App 189 Discover Gmail Features 190 Revealing the Gmail app’s main menu 190 Tending to mailbox organization 191 Scoping out the main mailbox 192 Send a Gmail Email 193 Adding an email signature 196 Creating a Vacation Responder email 196 Perform Basic Gmail tasks 198 A table of common email tasks 199 Printing an email from Gmail 200 Link to Other Apps and Gmail Settings 201 Chapter 12: Choosing and Using a Smartphone Camera 203 Examine Smartphone Cameras and Brands 204 Paying the right amount of attention to reviews 204 Phones with camera brand collaborations 205 Take a Camera-Spec Safari 205 Enough megapixel, but not too much 206 Home in on subjects with zoom 207 Exercise Your Android Camera’s Capabilities 209 Just point-and-shoot either stills or video 210 Add interest with your camera’s tools 210 Expand your reach with Google Lens 212 Access camera features on the scrolling menu 214 Go Pro with Pro Mode 215 Discovering the Pro settings 216 Applying the Pro settings 217 Edit Your Photos 218 Finding editing options 219 Applying the photo editor’s tools 220 Playing with filters, colors, and more 222 Part 4: Exploring Android Apps 225 Chapter 13: Preinstalled Tools You Want to Use 227 Take a Shortcut to Features with Android Quick Settings 228 Customizing the Quick Settings 228 Meeting popular Quick Settings 231 Quick Settings That Offer Valuable Options 234 Opting for Dark mode 234 Maximizing eye comfort 235 Avoiding interruptions 236 Sharing with “close” friends 239 Phone-Resident Android Apps 240 Recording your voice 240 Taking a screen shot 242 Staying on task with Google Calendar 244 Frequenting the Google Play Store 245 Chapter 14: Google Mobile Services Apps for Android 247 Find Popular Google Apps 248 Google Photos 249 Storing and retrieving 250 Syncing and deleting 251 Sharing 251 Searching 252 Google Maps 255 Finding your way to an appointment 255 Employing the Directions screen options 256 Find My Device 258 Take Note(s) with Google Keep 260 Chapter 15: Apps You Might Like in Google Play Store 261 Establish App Privacy Permissions 262 Connect to Radio (Yes, Radio), Podcasts, and Music 264 Configuring your speakers’ volume 264 Making a wired connection 265 Using a Bluetooth connection 266 Find Favorite and Fun Apps — a Consensus 267 Radio, podcasts, and music 268 Video apps 269 Travel 270 Games 270 News 273 Books 274 Engage Social Media 275 Try Out the Android Accessibility Suite 276 Part 5: Android Today and Tomorrow 279 Chapter 16: Marsha’s MUST-DO Things for Your Phone 281 Make the Orientation Decision 282 Configure Do Not Disturb 283 Use Your Home Wi-Fi for Calls and Browsing 284 Practice Safety When Using Public Connections 285 Use a VPN to secure public Wi-Fi connections 285 Beware of charging a phone from a public port 287 Secure Your Power Cables 289 Set Up Emergency Call and SOS 289 Establishing SOS messaging 290 Activating Emergency mode 291 Managing Emergency mode 294 Manage Home Screen App Shortcuts 295 Make Folders of Apps 299 Chapter 17: Android 12 and Beyond: The OS Evolution 301 Find Helpful New Features in Android 12 302 Make purchasing faster with GPay 302 Poke around in Android 12 303 Meet the Soothing Android 12 User Experience 304 Be Ready for the Future 306 Index 307

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Book SynopsisMachine Learning for Business Analytics Machine learningalso known as data mining or data analyticsis a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques and Applications in RapidMiner provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the seventh edition of Machine Learning for Business Analytics, and the first using RapidMiner software. This edition also includes: ATable of ContentsForeword by Ravi Bapna xxi Preface to the RapidMiner Edition xxiii Acknowledgments xxvii PART I PRELIMINARIES CHAPTER 1 Introduction 3 1.1 What Is Business Analytics? 3 1.2 What Is Machine Learning? 5 1.3 Machine Learning, AI, and Related Terms 5 1.4 Big Data 7 1.5 Data Science 8 1.6 Why Are There So Many Different Methods? 9 1.7 Terminology and Notation 9 1.8 Road Maps to This Book 12 1.9 Using RapidMiner Studio 14 CHAPTER 2 Overview of the Machine Learning Process 19 2.1 Introduction 19 2.2 Core Ideas in Machine Learning 20 2.3 The Steps in a Machine Learning Project 23 2.4 Preliminary Steps 25 2.5 Predictive Power and Overfitting 32 2.6 Building a Predictive Model with RapidMiner 37 2.7 Using RapidMiner for Machine Learning 45 2.8 Automating Machine Learning Solutions 47 2.9 Ethical Practice in Machine Learning 52 PART II DATA EXPLORATION AND DIMENSION REDUCTION CHAPTER 3 Data Visualization 63 3.1 Introduction 63 3.2 Data Examples 65 3.3 Basic Charts: Bar Charts, Line Charts, and Scatter Plots 66 3.4 Multidimensional Visualization 75 3.5 Specialized Visualizations 87 3.6 Summary: Major Visualizations and Operations, by Machine Learning Goal 92 CHAPTER 4 Dimension Reduction 97 4.1 Introduction 97 4.2 Curse of Dimensionality 98 4.3 Practical Considerations 98 4.4 Data Summaries 100 4.5 Correlation Analysis 103 4.6 Reducing the Number of Categories in Categorical Attributes 105 4.7 Converting a Categorical Attribute to a Numerical Attribute 107 4.8 Principal Component Analysis 107 4.9 Dimension Reduction Using Regression Models 117 4.10 Dimension Reduction Using Classification and Regression Trees 119 PART III PERFORMANCE EVALUATION CHAPTER 5 Evaluating Predictive Performance 125 5.1 Introduction 125 5.2 Evaluating Predictive Performance 126 5.3 Judging Classifier Performance 131 5.4 Judging Ranking Performance 146 5.5 Oversampling 151 PART IV PREDICTION AND CLASSIFICATION METHODS CHAPTER 6 Multiple Linear Regression 163 6.1 Introduction 163 6.2 Explanatory vs. Predictive Modeling 164 6.3 Estimating the Regression Equation and Prediction 166 6.4 Variable Selection in Linear Regression 171 CHAPTER 7 k-Nearest Neighbors (k-NN) 189 7.1 The k-NN Classifier (Categorical Label) 189 7.2 k-NN for a Numerical Label 200 7.3 Advantages and Shortcomings of k-NN Algorithms 202 CHAPTER 8 The Naive Bayes Classifier 209 8.1 Introduction 209 8.2 Applying the Full (Exact) Bayesian Classifier 211 8.3 Solution: Naive Bayes 213 8.4 Advantages and Shortcomings of the Naive Bayes Classifier 223 CHAPTER 9 Classification and Regression Trees 229 9.1 Introduction 229 9.2 Classification Trees 232 9.3 Evaluating the Performance of a Classification Tree 240 9.4 Avoiding Overfitting 245 9.5 Classification Rules from Trees 255 9.6 Classification Trees for More Than Two Classes 256 9.7 Regression Trees 256 9.8 Improving Prediction: Random Forests and Boosted Trees 259 9.9 Advantages and Weaknesses of a Tree 261 CHAPTER 10 Logistic Regression 269 10.1 Introduction 269 10.2 The Logistic Regression Model 271 10.3 Example: Acceptance of Personal Loan 272 10.4 Logistic Regression for Multi-class Classification 283 10.5 Example of Complete Analysis: Predicting Delayed Flights 286 CHAPTER 11 Neural Networks 305 11.1 Introduction 306 11.2 Concept and Structure of a Neural Network 306 11.3 Fitting a Network to Data 307 11.4 Required User Input 321 11.5 Exploring the Relationship Between Predictors and Target Attribute 322 11.6 Deep Learning 323 11.7 Advantages and Weaknesses of Neural Networks 334 CHAPTER 12 Discriminant Analysis 337 12.1 Introduction 337 12.2 Distance of a Record from a Class 340 12.3 Fisher’s Linear Classification Functions 341 12.4 Classification Performance of Discriminant Analysis 346 12.5 Prior Probabilities 348 12.6 Unequal Misclassification Costs 348 12.7 Classifying More Than Two Classes 349 12.8 Advantages and Weaknesses 351 CHAPTER 13 Generating, Comparing, and Combining Multiple Models 359 13.1 Automated Machine Learning (AutoML) 359 13.2 Explaining Model Predictions 367 13.3 Ensembles 373 13.4 Summary 381 PART V INTERVENTION AND USER FEEDBACK CHAPTER 14 Interventions: Experiments, Uplift Models, and Reinforcement Learning 387 14.1 A/B Testing 387 14.2 Uplift (Persuasion) Modeling 393 14.3 Reinforcement Learning 400 14.4 Summary 405 PART VI MINING RELATIONSHIPS AMONG RECORDS CHAPTER 15 Association Rules and Collaborative Filtering 409 15.1 Association Rules 409 15.2 Collaborative Filtering 424 15.3 Summary 438 CHAPTER 16 Cluster Analysis 445 16.1 Introduction 445 16.2 Measuring Distance Between Two Records 449 16.3 Measuring Distance Between Two Clusters 455 16.4 Hierarchical (Agglomerative) Clustering 457 16.5 Non-Hierarchical Clustering: The k-Means Algorithm 466 PART VII FORECASTING TIME SERIES CHAPTER 17 Handling Time Series 479 17.1 Introduction 480 17.2 Descriptive vs. Predictive Modeling 481 17.3 Popular Forecasting Methods in Business 481 17.4 Time Series Components 482 17.5 Data Partitioning and Performance Evaluation 486 CHAPTER 18 Regression-Based Forecasting 497 18.1 A Model with Trend 498 18.2 A Model with Seasonality 504 18.3 A Model with Trend and Seasonality 508 18.4 Autocorrelation and ARIMA Models 509 CHAPTER 19 Smoothing and Deep Learning Methods for Forecasting 533 19.1 Smoothing Methods: Introduction 534 19.2 Moving Average 534 19.3 Simple Exponential Smoothing 541 19.4 Advanced Exponential Smoothing 545 19.5 Deep Learning for Forecasting 549 PART VIII DATA ANALYTICS CHAPTER 20 Social Network Analytics 563 20.1 Introduction 563 20.2 Directed vs. Undirected Networks 564 20.3 Visualizing and Analyzing Networks 567 20.4 Social Data Metrics and Taxonomy 571 20.5 Using Network Metrics in Prediction and Classification 577 20.6 Collecting Social Network Data with RapidMiner 584 20.7 Advantages and Disadvantages 584 CHAPTER 21 Text Mining 589 21.1 Introduction 589 21.2 The Tabular Representation of Text: Term–Document Matrix and “Bag-of-Words’’ 590 21.3 Bag-of-Words vs. Meaning Extraction at Document Level 592 21.4 Preprocessing the Text 593 21.5 Implementing Machine Learning Methods 602 21.6 Example: Online Discussions on Autos and Electronics 602 21.7 Example: Sentiment Analysis of Movie Reviews 607 21.8 Summary 614 CHAPTER 22 Responsible Data Science 617 22.1 Introduction 617 22.2 Unintentional Harm 618 22.3 Legal Considerations 620 22.4 Principles of Responsible Data Science 621 22.5 A Responsible Data Science Framework 624 22.6 Documentation Tools 628 22.7 Example: Applying the RDS Framework to the COMPAS Example 631 22.8 Summary 641 PART IX CASES CHAPTER 23 Cases 647 23.1 Charles Book Club 647 23.2 German Credit 653 23.3 Tayko Software Cataloger 658 23.4 Political Persuasion 662 23.5 Taxi Cancellations 665 23.6 Segmenting Consumers of Bath Soap 667 23.7 Direct-Mail Fundraising 670 23.8 Catalog Cross-Selling 672 23.9 Time Series Case: Forecasting Public Transportation Demand 673 23.10 Loan Approval 675 Index 685

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Book SynopsisBIOFUEL EXTRACTION TECHNIQUES The energy industry and new energy sources and innovations are rapidly changing and evolving. This new volume addresses the current state-of-the-art concepts and technologies associated with biofuel extraction technologies. Biofuels are a viable alternative to petroleum-based fuel because they are produced from organic materials such as plants and their wastes, agricultural crops, and by-products. The development of cutting-edge technology has increased the need for energy significantly, which has resulted in an overreliance on fossil fuels. Renewable fuels are an important subject of research because of their biodegradability, eco-friendliness, decrease in greenhouse gas (GHG) emissions, and favorable socioeconomic consequences to counteract imitations of fossil fuels. Different extraction techniques are used for the production of biofuel from renewable feedstocks. A good example is biodiesel, a promising biofuel which is produced bTable of ContentsPreface xix 1 Plant Seed Oils and Their Potential for Biofuel Production in India 1L. C. Meher and S. N. Naik 2 Processing of Feedstock in Context of Biodiesel Production 25Durgawati and Rama Chandra Pradhan 3 Extraction Techniques for Biodiesel Production 51Soumya Parida and Subhalaxmi Pradhan 4 Role of Additives on Anaerobic Digestion, Biomethane Generation, and Stabilization of Process Parameters 101Adya Isha, Bhaskar Jha, Tinku Casper D'Silva, Subodh Kumar, Sameer Ahmed Khan, Dushyant Kumar, Ram Chandra and Virendra Kumar Vijay 5 An Overview on Established and Emerging Biogas Upgradation Systems for Improving Biomethane Quality 125Tinku Casper D'Silva, Adya Isha, Subodh Kumar, Sameer Ahmad Khan, Dushyant Kumar, Ram Chandra and Virendra Kumar Vijay 6 Renewable Feedstocks for Biofuels 151Monika Chauhan, Vanshika, Ajay Kumar, Diwakar Chauhan and Arvind Kumar Jain 7 Extraction Techniques of Gas-to-Liquids (GtL) Fuels 177Sonali Kesarwani, Divya Bajpai Tripathy and Pooja Bhadana 8 Second Generation Biofuels and Extraction Techniques 207Prashant Kumar, Praveen Kumar Sharma, Shreya Tripathi, Deepak Kumar, Ashween Deepak Nannaware, Shivani Chaturvedi and Prasant Kumar Rout 9 Bio-Alcohol: Production, Purification, and Analysis Using Analytical Techniques 257Smrita Singh, Susanta Roy, Lalit Prasad and Ashutosh Singh Chauhan 10 Studies on Extraction Techniques of Bio-Hydrogen 291C. S. Madankar, Priti Borde and P. D. Meshram 11 Valorization of By-Products Produced During the Extraction and Purification of Biofuels 307Subodh Kumar, Tinku Casper D'Silva, Dushyant Kumar, Adya Isha, Sameer Ahmad Khan, Ram Chandra, Anushree Malik and Virendra Kumar Vijay 12 Valorization of Byproducts Produced During Extraction and Purification of Biodiesel: A Promising Biofuel 333Gunjan, Radhika Singh and Subhalaxmi Pradhan 13 Biofuel Applications: Quality Control and Assurance, Techno-Economics and Environmental Sustainability 367Sameer Ahmad Khan, Dushyant Kumar, Subodh Kumar, Adya Isha, Tinku Casper D'Silva, Ram Chandra and Virendra Kumar Vijay 14 Role of CO2 Triggered Switchable Polarity Solvents and Supercritical Solvents During Biofuel Extraction 421Anupama Sharma, Pinki Chakraborty, Karthikay Sankhyadhar, Sandeep Kumar and Monisha Singh 15 Efficiency of Catalysts During Biofuel Extraction 441Gajanan Sahu, Sudipta Datta, Sujan Saha, Prakash D. Chavan, Deshal Yadav and Vishal Chauhan 16 Microorganisms as Effective CO2 Assimilator for Biofuel Production 495Chandreyee Saha and Subhalaxmi Pradhan 17 Global Aspects of Biofuel Extraction 523Shilpi Bhatnagar and Shilpi Khurana 18 New Advancements of Biofuel Extractions and Future Trends 543Rita Sharma, Kuldip Dwivedi, Bhavna Sharma and Shashank Sharma References 556 About the Editors 559 Index 561

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Book SynopsisPROTON EXCHANGE MEMBRANE FUEL CELLS Edited by one of the most well-respected and prolific engineers in the world and his team, this book provides a comprehensive overview of hydrogen production, conversion, and storage, offering the scientific literature a comprehensive coverage of this important fuel. Proton exchange membrane fuel cells (PEMFCs) are among the most anticipated stationary clean energy devices in renewable and alternative energy. Despite the appreciable improvement in their cost and durability, which are the two major commercialization barriers, their availability has not matched demand. This is mainly due to the use of expensive metal-catalyst, less durable membranes, and poor insight into the ongoing phenomena inside proton exchange membrane fuel cells. Efforts are being made to optimize the use of precious metals as catalyst layers or find alternatives that can be durable for more than 5000 hours. Computational models are also being developed and studied to get an inTable of ContentsPreface xiii 1 Stationary and Portable Applications of Proton Exchange Membrane Fuel Cells 1 Shahram Mehdipour-Ataei and Maryam Mohammadi 1.1 Introduction 1 1.2 Proton Exchange Membrane Fuel Cells 3 1.2.1 Stationary Applications 3 1.2.2 Portable Applications 5 1.2.3 Hydrogen PEMFCs 6 1.2.4 Alcohol PEMFCs 6 1.2.4.1 Direct Methanol Fuel Cell 6 1.2.4.2 Direct Dimethyl Ether Fuel Cell 7 1.2.5 Microbial Fuel Cells 8 1.2.5.1 Electricity Generation 8 1.2.5.2 Microbial Desalination Cells 9 1.2.5.3 Removal of Metals From Industrial Waste 9 1.2.5.4 Wastewater Treatment 9 1.2.5.5 Microbial Solar Cells and Fuel Cells 10 1.2.5.6 Biosensors 11 1.2.5.7 Biohydrogen Production 11 1.2.6 Micro Fuel Cells 11 1.3 Conclusion and Future Perspective 12 References 13 2 Graphene-Based Membranes for Proton Exchange Membrane Fuel Cells 17 Beenish Saba 2.1 Introduction 18 2.2 Membranes 19 2.3 Graphene: A Proton Exchange Membrane 19 2.4 Synthesis of GO Composite Membranes 20 2.5 Graphene Oxide in Fuel Cells 21 2.5.1 Electrochemical Fuel Cells 22 2.5.1.1 Hydrogen Oxide Polymer Electrolyte Membrane Fuel Cells 22 2.5.1.2 Direct Methanol Fuel Cells 23 2.5.2 Bioelectrochemical Fuel Cells 24 2.6 Characterization Techniques of GO Composite Membranes 25 2.7 Conclusion 26 References 27 3 Graphene Nanocomposites as Promising Membranes for Proton Exchange Membrane Fuel Cells 33 Ranjit Debnath and Mitali Saha 3.1 Introduction 34 3.2 Recent Kinds of Fuel Cells 35 3.2.1 Proton Exchange Membrane Fuel Cells 36 3.3 Conclusion 45 Acknowledgements 45 References 45 4 Carbon Nanotube–Based Membranes for Proton Exchange Membrane Fuel Cells 51 Umesh Fegade and K. E. Suryawanshi 4.1 Introduction 52 4.2 Overview of Carbon Nanotube–Based Membranes PEM Cells 54 References 64 5 Nanocomposite Membranes for Proton Exchange Membrane Fuel Cells 73 P. Satishkumar, Arun M. Isloor and Ramin Farnood 5.1 Introduction 74 5.2 Nanocomposite Membranes for PEMFC 77 5.3 Evaluation Methods of Proton Exchange Membrane Properties 80 5.3.1 Proton Conductivity Measurement 80 5.3.2 Water Uptake Measurement 81 5.3.3 Oxidative Stability Measurement 81 5.3.4 Thermal and Mechanical Properties Measurement 81 5.4 Nafion-Based Membrane 82 5.5 Poly(Benzimidazole)–Based Membrane 86 5.6 Sulfonated Poly(Ether Ether Ketone)–Based Membranes 91 5.7 Poly(Vinyl Alcohol)–Based Membranes 95 5.8 Sulfonated Polysulfone–Based Membranes 98 5.9 Chitosan-Based Membranes 100 5.10 Conclusions 103 References 103 6 Organic-Inorganic Composite Membranes for Proton Exchange Membrane Fuel Cells 111 Guocai Tian 6.1 Introduction 111 6.2 Proton Exchange Membrane Fuel Cell 112 6.3 Proton Exchange Membrane 116 6.3.1 Perfluorosulfonic Acid PEM 117 6.3.2 Partial Fluorine-Containing PEM 117 6.3.3 Non-Fluorine PEM 118 6.3.4 Modification of Proton Exchange Membrane 118 6.4 Research Progress of Organic-Inorganic Composite PEM 120 6.4.1 Inorganic Oxide/Polymer Composite PEM 120 6.4.2 Two-Dimensional Inorganic Material/Polymer Composite PEM 122 6.4.3 Carbon Nanotube/Polymer Composite PEM 124 6.4.4 Inorganic Acid–Doped Composite Film 125 6.4.5 Heteropoly Acid–Doped Composite PEM 126 6.4.6 Zirconium Phosphate–Doped Composite PEM 127 6.4.7 Polyvinyl Alcohol/Inorganic Composite Membrane 127 6.5 Conclusion and Prospection 128 Acknowledgments 130 Conflict of Interest 130 References 130 7 Thermoset-Based Composite Bipolar Plates in Proton Exchange Membrane Fuel Cell: Recent Developments and Challenges 137 Salah M.S. Al-Mufti and S.J.A. Rizvi 7.1 Introduction 138 7.2 Theories of Electrical Conductivity in Polymer Composites 142 7.2.1 Percolation Theory 145 7.2.2 General Effective Media Model 146 7.2.3 McLachlan Model 147 7.2.4 Mamunya Model 148 7.2.5 Taherian Model 149 7.3 Matrix and Fillers 151 7.3.1 Thermoset Resins 151 7.3.1.1 Epoxy 152 7.3.1.2 Unsaturated Polyester Resin 152 7.3.1.3 Vinyl Ester Resins 152 7.3.1.4 Phenolic Resins 153 7.3.1.5 Polybenzoxazine Resins 153 7.3.2 Fillers 153 7.3.2.1 Graphite 156 7.3.2.2 Graphene 157 7.3.2.3 Expanded Graphite 158 7.3.2.4 Carbon Black 158 7.3.2.5 Carbon Nanotube 159 7.3.2.6 Carbon Fiber 160 7.4 The Manufacturing Process of Thermoset-Based Composite BPs 162 7.4.1 Compression Molding 162 7.4.2 The Selective Laser Sintering Process 163 7.4.3 Wet and Dry Method 164 7.4.4 Resin Vacuum Impregnation Method 164 7.5 Effect of Processing Parameters on the Properties Thermoset-Based Composite BPs 166 7.5.1 Compression Molding Parameters 166 7.5.1.1 Pressure 166 7.5.1.2 Temperature 168 7.5.1.3 Time 169 7.5.2 The Mixing Time Effect on the Properties of Composite Bipolar Plates 170 7.6 Effect of Polymer Type, Filler Type, and Composition on Properties of Thermoset Composite BPs 170 7.6.1 Electrical Properties 171 7.6.2 Mechanical Properties 173 7.6.3 Thermal Properties 174 7.7 Testing and Characterization of Polymer Composite-Based BPs 176 7.7.1 Electrical Analysis 176 7.7.1.1 In-Plane Electrical Conductivity 176 7.7.1.2 Through-Plane Electrical Conductivity 189 7.7.2 Thermal Analysis 190 7.7.2.1 Thermal Gravimetric Analysis 190 7.7.2.2 Differential Scanning Calorimetry 190 7.7.2.3 Thermal Conductivity 191 7.7.3 Mechanical Analysis 192 7.7.3.1 Flexural Strength 192 7.7.3.2 Tensile Strength 192 7.7.3.3 Compressive Strength 193 7.8 Conclusions 193 Abbreviations 194 References 195 8 Metal-Organic Framework Membranes for Proton Exchange Membrane Fuel Cells 213 Yashmeen, Gitanjali Jindal and Navneet Kaur 8.1 Introduction 213 8.2 Aluminium Containing MOFs for PEMFCs 216 8.3 Chromium Containing MOFs for PEMFCs 217 8.4 Copper Containing MOFs for PEMFCs 224 8.5 Cobalt Containing MOFs for PEMFCs 225 8.6 Iron Containing MOFs for PEMFCs 227 8.7 Nickel Containing MOFs for PEMFCs 230 8.8 Platinum Containing MOFs for PEMFCs 230 8.9 Zinc Containing MOFs for PEMFCs 232 8.10 Zirconium Containing MOFs for PEMFCs 234 8.11 Conclusions and Future Prospects 239 References 240 9 Fluorinated Membrane Materials for Proton Exchange Membrane Fuel Cells 245 Pavitra Rajendran, Valmiki Aruna, Gangadhara Angajala and Pulikanti Guruprasad Reddy Abbreviations 246 9.1 Introduction 247 9.2 Fluorinated Polymeric Materials for PEMFCs 250 9.3 Poly(Bibenzimidazole)/Silica Hybrid Membrane 250 9.4 Poly(Bibenzimidazole) Copolymers Containing Fluorine-Siloxane Membrane 252 9.5 Sulfonated Fluorinated Poly(Arylene Ethers) 253 9.6 Fluorinated Sulfonated Polytriazoles 255 9.7 Fluorinated Polybenzoxazole (6F-PBO) 257 9.8 Poly(Bibenzimidazole) With Poly(Vinylidene Fluoride-Co-Hexafluoro Propylene) 258 9.9 Fluorinated Poly(Arylene Ether Ketones) 259 9.10 Fluorinated Sulfonated Poly(Arylene Ether Sulfone) (6fbpaqsh-xx) 260 9.11 Fluorinated Poly(Aryl Ether Sulfone) Membranes Cross-Linked Sulfonated Oligomer (c-SPFAES) 261 9.12 Sulfonated Poly(Arylene Biphenylether Sulfone)- Poly(Arylene Ether) (SPABES-PAE) 261 9.13 Conclusion 266 Conflicts of Interest 266 Acknowledgements 267 References 267 10 Membrane Materials in Proton Exchange Membrane Fuel Cells (PEMFCs) 271 Foad Monemian and Ali Kargari 10.1 Introduction 271 10.2 Fuel Cell: Definition and Classification 272 10.3 Historical Background of Fuel Cell 273 10.4 Fuel Cell Applications 274 10.4.1 Transportation 275 10.4.2 Stationary Power 275 10.4.3 Portable Applications 275 10.5 Comparison between Fuel Cells and Other Methods 278 10.6 PEMFCs: Description and Characterization 280 10.6.1 Ion Exchange Capacity–Conductivity 281 10.6.2 Durability 281 10.6.3 Water Management 282 10.6.4 Cost 282 10.7 Membrane Materials for PEMFC 282 10.7.1 Statistical Copolymer PEMs 283 10.7.2 Block and Graft Copolymers 286 10.7.3 Polymer Blending and Other PEM Compounds 289 10.8 Conclusions 296 References 296 11 Nafion-Based Membranes for Proton Exchange Membrane Fuel Cells 299 Santiago Pablo Fernandez Bordín, Janet de los Angeles Chinellato Díaz and Marcelo Ricardo Romero 11.1 Introduction: Background 300 11.2 Physical Properties 302 11.3 Nafion Structure 304 11.4 Water Uptake 307 11.5 Protonic Conductivity 310 11.6 Water Transport 316 11.7 Gas Permeation 319 11.8 Final Comments 324 Acknowledgements 324 References 325 12 Solid Polymer Electrolytes for Proton Exchange Membrane Fuel Cells 331 Nitin Srivastava and Rajendra Kumar Singh 12.1 Introduction 331 12.2 Type of Fuel Cells 334 12.2.1 Alkaline Fuel Cells 334 12.2.2 Polymer Electrolyte Fuel Cells 335 12.2.3 Phosphoric Acid Fuel Cells 337 12.2.4 Molten Carbonate Fuel Cells 338 12.2.5 Solid Oxide Fuel Cells 338 12.3 Basic Properties of PEMFC 339 12.4 Classification of Solid Polymer Electrolyte Membranes for PEMFC 341 12.4.1 Perfluorosulfonic Membrane 341 12.4.2 Partially Fluorinated Polymers 343 12.4.3 Non-Fluorinated Hydrocarbon Membrane 344 12.4.4 Nonfluorinated Acid Membranes With Aromatic Backbone 344 12.4.5 Acid Base Blend 344 12.5 Applications 345 12.5.1 Application in Transportation 346 12.6 Conclusions 347 References 347 13 Computational Fluid Dynamics Simulation of Transport Phenomena in Proton Exchange Membrane Fuel Cells 353 Maryam Mirzaie and Mohamadreza Esmaeilpour 13.1 Introduction 354 13.2 PEMFC Simulation and Mathematical Modeling 356 13.2.1 Governing Equations 359 13.2.1.1 Continuity Equation 359 13.2.1.2 Momentum Equation 360 13.2.1.3 Mass Transfer Equation 360 13.2.1.4 Energy Transfer Equation 362 13.2.1.5 Equation of Charge Conservation 362 13.2.1.6 Formation and Transfer of Liquid Water 362 13.3 The Solution Procedures 363 13.3.1 CFD Simulations 363 13.3.2 OpenFOAM 374 13.3.3 Lattice Boltzmann 381 13.4 Conclusions 389 References 390 Index 395

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Book SynopsisTable of ContentsForeword xix Preface to the Fourth Edition xxi Acknowledgments xxv PART I PRELIMINARIES CHAPTER 1 Introduction 3 CHAPTER 2 Overview of the Machine Learning Process 15 PART II DATA EXPLORATION AND DIMENSION REDUCTION CHAPTER 3 Data Visualization 59 CHAPTER 4 Dimension Reduction 91 PART III PERFORMANCE EVALUATION CHAPTER 5 Evaluating Predictive Performance 115 PART IV PREDICTION AND CLASSIFICATION METHODS CHAPTER 6 Multiple Linear Regression 151 CHAPTER 7 k-Nearest-Neighbors (k-NN) 169 CHAPTER 8 The Naive Bayes Classifier 181 CHAPTER 9 Classification and Regression Trees 197 CHAPTER 10 Logistic Regression 229 CHAPTER 11 Neural Nets 257 CHAPTER 12 Discriminant Analysis 283 CHAPTER 13 Generating, Comparing, and Combining Multiple Models 303 PART V INTERVENTION AND USER FEEDBACK CHAPTER 14 Experiments, Uplift Modeling, and Reinforcement Learning 319 PART VI MINING RELATIONSHIPS AMONG RECORDS CHAPTER 15 Association Rules and Collaborative Filtering 341 CHAPTER 16 Cluster Analysis 369 PART VII FORECASTING TIME SERIES CHAPTER 17 Handling Time Series 401 CHAPTER 18 Regression-Based Forecasting 415 CHAPTER 19 Smoothing Methods 445 PART VIII DATA ANALYTICS CHAPTER 20 Social Network Analytics 467 CHAPTER 21 Text Mining 487 CHAPTER 22 Responsible Data Science 507 PART IX CASES CHAPTER 23 Cases 537 References 575 Data Files Used in the Book 577 Index 579

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Book SynopsisQUANTUM MECHANICS From classical analytical mechanics to quantum mechanics, simulation, foundations & engineering Quantum mechanics is a fundamental and conceptually challenging area of physics. It is usually assumed that students are unfamiliar with Lagrangian and Hamiltonian formulations of classical mechanics and the role played by probability. As a result, quantum physics is typically introduced using heuristic arguments, obscuring synergies with classical mechanics. This book takes an alternative approach by leveraging classical analytical mechanics to facilitate a natural transition to quantum physics. By doing so, a solid foundation for understanding quantum phenomena is provided. Key features of this textbook include: Mathematics and Classical Analytical Mechanics: The necessary mathematical background and classical analytical mechanics are introduced gradually, allowing readers to focus on one conceptual challenge at a time. Deductive Approach: Quantum mechanics is presented on the firm foundation of classical analytical mechanics, ensuring a logical progression of concepts. Pedagogical Features: This book includes helpful notes, worked examples, problems, computational challenges, and problem-solving approaches to enhance understanding. Comprehensive Coverage: Including advanced topics such as open quantum systems, phase-space methods, and computational methods for quantum physics including good programming practice and code design. Much of the code needed to reproduce figures throughout this book is included. Consideration of Foundations: The measurement problem and correspondence principle are addressed, including an open and critical discussion of their interpretation and consequences. Introduction to Quantum Systems Engineering: This is the first book to introduce Quantum Systems Engineering approaches for applied quantum technologies development. This textbook is suitable for undergraduate students in physics and graduate students in mathematics, chemistry, engineering, and materials science.Table of ContentsAcronyms xiii About the Authors xv Preface xvii Acknowledgements xix About the Companion Website xxi Introduction xxiii 1 Mathematical Preliminaries 1 1.1 Introduction 1 1.2 Generalising Vectors 2 1.2.1 Vector Spaces 2 1.2.2 Inner Product 5 1.2.3 Dirac Notation 7 1.2.4 Basis and Dimension 9 1.3 Linear Operators 10 1.3.1 Definition and Some Key Properties of Linear Operators 10 1.3.2 Expectation Value of Random Variables 12 1.3.3 Inverse of Operators 13 1.3.4 Hermitian Adjoint Operators 13 1.3.5 Unitary Operators 15 1.3.6 Commutators 15 1.3.7 Eigenvectors and Eigenvalues 17 1.3.8 Eigenvectors of Commuting Operators 18 1.3.9 Functions of Operators 18 1.3.10 Differentiation of Operators 19 1.3.11 Baker Campbell Hausdorff, Zassenhaus Formulae, and Hadamard Lemma 19 1.3.12 Operators and Basis State – Resolutions of Identity 20 1.3.12.1 Outer Product and Projection 20 1.3.12.2 Resolutions of Identity 21 1.4 Representing Kets as Vectors, and Operators as Matrices and Traces 22 1.4.1 Trace 24 1.4.2 Basis, Representation, and Inner Products 24 1.4.3 Observables 25 1.4.4 Labelling Vectors – Complete Sets of Commuting Observables – CSCO 25 1.5 Tensor Product 26 1.5.1 Setting the Scene: The Cartesian Product 26 1.5.2 The Tensor Product 27 1.6 The Heisenberg Uncertainty Relation 29 1.7 Concluding Remarks 32 2 Notes on Classical Mechanics 35 2.1 Introduction 35 2.2 A Brief Revision of Classical Mechanics 38 2.2.1 Lagrangian Mechanics 38 2.2.2 Hamiltonian Mechanics 41 2.3 On Probability in Classical Mechanics 45 2.3.1 The Liouville Equation 45 2.3.2 Expectation Values 48 2.4 Damping 50 2.5 Koopman–von Neumann (KvN) Classical Mechanics 53 2.6 Some Big Problems with Classical Physics 56 2.6.1 Atoms and Polarisers 56 2.6.2 The Stern–Gerlach Experiment 56 2.6.3 The Correspondence Principle – What It Is and What It Is Not 59 3 The Schrödinger View/Picture 63 3.1 Introduction 63 3.2 Motivating the Schrödinger Equation 64 3.2.1 Ehrenfest’s Theorem, Poisson Brackets, and Commutation Relations 68 3.2.2 The Main Proposition 70 3.2.2.1 Summarising an Issue with the Above Argument 70 3.3 Measurement 71 3.3.1 Introducing Measurement 71 3.3.2 On the Possible Connection Between the State Vector and Probabilities 73 3.3.3 The Time-independent Schrödinger Equation 75 3.3.4 Measurement Outcomes 77 3.4 Representation of Quantum Systems 78 3.4.1 The Position and Momentum Representation 78 3.4.1.1 The One-dimensional Case 78 3.4.1.2 Three Dimensions 83 3.4.2 Spin 85 3.4.3 Spin and Position – The Spinor 88 3.5 Closing Remarks and the Axioms of Quantum Mechanics 89 4 Other Formulations of Quantum Mechanics 93 4.1 Introduction 93 4.2 The Heisenberg Picture 94 4.2.1 Background 94 4.2.2 Motivating the Heisenberg Equation of Motion 95 4.2.3 A Specific Example: the One-dimensional Harmonic Oscillator 100 4.2.4 The State, Representation, and Dynamics 101 4.2.5 Axioms of Quantum Mechanics Revisited 101 4.2.6 The Evolution Operator 102 4.2.7 Connection to the Schrödinger Picture, and Revisiting Issues with Ehrenfest’s Theorem 105 4.3 Wigner’s Phase-space Quantum Mechanics 106 4.3.1 Background 106 4.3.2 Motivating the Phase-space Equation of Motion 107 4.3.3 Quantising Phase Space 108 4.3.4 Joining the Dots 113 4.3.5 The Heisenberg Uncertainty Relation 117 4.3.6 Generalising Wigner Functions to Spins 118 4.3.7 Axioms of Quantum Mechanics Revisited 121 4.4 The Path Integral Formulation of Quantum Mechanics 122 4.5 Closing Remarks 124 5 Vectors and Angular Momentum 127 5.1 Introduction 127 5.2 On Curvilinear Coordinates (Using Spherical Coordinates as an Example) 129 5.2.1 The Coordinate Representation: A Statement of the Problem 129 5.2.2 Canonical Quantisation in Spherical Coordinates 131 5.2.3 Spherical Coordinates, Vectors, and Momenta 132 5.3 The Theory of Orbital and General Angular Momentum 137 5.3.1 From Classical to Quantum Angular Momentum 137 5.3.2 General Properties of Angular Momentum 139 5.3.3 Eigenvalues and Eigenvectors of Angular Momentum 141 5.3.4 Worked Examples of Matrix Construction 143 5.3.5 Orbital Angular Momentum Basis 145 5.4 Addition of Angular Momentum 147 5.4.1 The General Theory 147 5.4.2 Two-particle Systems 148 5.4.3 Example: Addition of Spins 150 6 Some Analytic and Semi-analytic Methods 153 6.1 Introduction 153 6.2 Problems of the Form Ĥ0 + Ŵ 154 6.2.1 The Interaction Picture 154 6.2.2 Time-independent Perturbation Theory 155 6.2.3 Time-dependent Perturbation Theory 159 6.3 The Variational Method 161 6.4 Instantaneous Energy Eigenbasis 161 6.5 Moving Basis 163 6.6 Time periodic Systems and Floquet Theory 164 6.7 Two-level Systems 168 6.7.1 Non-degenerate Uncoupled System 170 6.7.2 Non-degenerate Coupled System 170 6.7.3 Degenerate Coupled System 172 7 Applications and Examples 175 7.1 Introduction 175 7.2 Position Representation Examples of Particles and Potentials 176 7.2.1 The Free Particle 176 7.2.2 Infinitely Deep Potential Well 177 7.2.3 The Finite Potential Barrier 180 7.2.4 Finite Potential Well 183 7.3 The Harmonic Oscillator 186 7.3.1 A Scheme for Creating Ladder Operators 186 7.3.2 Ladder Operators and Some Eigenvalue Properties of the QHO 186 7.3.3 A Walk-through of Repeatedly Applying â † to |0⟩ 188 7.3.4 The General Form of the Action of â and â † on |n⟩ 190 7.3.5 Matrix Representation 192 7.3.6 The Position Representation of Wave-functions 193 7.3.7 Coherent States 197 7.3.7.1 Introduction 197 7.3.7.2 Coherent States in the Number Basis 200 7.3.7.3 Coherent States as Displaced Vacuum States 201 7.3.7.4 The Position Representation 202 7.4 The Hydrogen Atom 203 7.4.1 Introduction 203 7.4.2 Quantum Analysis 206 7.4.2.1 Choosing a Representation 206 7.4.3 Fine Structure of Hydrogen: Spin–Orbit Coupling 211 7.5 The Dihydrogen Ion 212 7.6 The Jaynes–Cummings Model 215 7.6.1 The Hamiltonian 215 7.6.2 The Eigenstates and Eigenvalues 217 7.6.3 Dynamics of the Atomic Inversion 218 7.7 The Stern–Gerlach Experiment 222 8 Computational Simulation of Quantum Systems 227 8.1 Introduction 227 8.2 General Points for Consideration 229 8.2.1 On Code Clarity and Performance 229 8.2.1.1 On Comments 230 8.2.1.2 Clear Code 232 8.2.2 Should I Use Third-party Libraries? 232 8.2.3 Choice of Language 233 8.3 Some Overarching Coding Principles 236 8.3.1 Have Clear Objectives 236 8.3.2 Trust Your Code 236 8.3.3 Plan for the Future 237 8.3.4 Test, Test, Test 238 8.3.5 Object-oriented Design 240 8.3.6 Be a SOLID Scientific Programmer 242 8.3.6.1 The Single-responsibility Principle 242 8.3.6.2 The Open-closed Principle 242 8.3.6.3 The Liskov Substitution Principle 243 8.3.6.4 The Interface Segregation Principle 243 8.3.6.5 The Dependency Inversion Principle 244 8.3.7 Be a Clean Coder 244 8.3.8 Continue to Master Your Craft 245 8.4 A Small Generic Quantum Library 245 8.4.1 Some Swift Basics 246 8.4.1.1 Comments 246 8.4.1.2 Primitive Types and Their Declaration 246 8.4.2 Complex Numbers and the ‘Generic’ Decision 247 8.4.2.1 Introducing Structure and Classes 247 8.4.2.2 A First Look at Generics 249 8.4.2.3 Functions 249 8.4.2.4 Operator Overloading 250 8.4.2.5 Introducing Protocols and Extensions 250 8.4.2.6 An Aside on the Power of Extensions 253 8.4.3 Adding Quantum Structure to the Code 254 8.4.3.1 Spaces 255 8.4.3.2 Vectors 256 8.4.3.3 Operators 260 8.4.4 Quantum Functionality 261 8.4.5 Dynamics 268 8.4.6 Plotting the Output 275 8.5 Concluding Remarks 275 8.6 Appendix I – Some Useful Calculated Quantities 277 8.6.1 Exponentials of the Annihilation and Creation Operators 277 8.6.2 The Pauli Vector: Euler Formula and Other Functions 278 8.6.3 Cosine of the Position Operator 279 8.7 Appendix II – Wigner Function Code 280 9 Open Quantum Systems 281 9.1 Introduction 281 9.1.1 Context 281 9.1.2 Background 281 9.1.3 System Plus Bath Models 283 9.2 Classical Brownian Motion 284 9.2.1 Brownian Motion from Hamiltonian Mechanics 286 9.3 Master Equations 288 9.3.1 The Redfield Master Equations 290 9.3.2 The Caldeira–Leggett Model 294 9.3.2.1 Spectral Density 298 9.3.3 Master Equations of Lindblad Form 301 9.3.4 Low-temperature Regime 306 9.3.5 Lindblads: Strengths and Weaknesses 308 9.3.6 Effective Hamiltonians 309 9.4 Master Equation Approximations and Their Implications 311 9.4.1 The Baker Campbell Hausdorff Approximations 311 9.4.2 The Born Approximation 312 9.4.3 Choice of Spectral Density 313 9.4.4 High Cut-off Limit 315 9.5 A Master Equation Derivation Example 316 9.5.1 Inductive Coupling 318 9.5.2 Introducing Capacitive Coupling 322 9.5.3 Where Does the Model Break Down? 325 9.6 Unravelling the Master Equation 326 10 Foundations: Measurement and the Quantum-to-Classical Transition 331 10.1 Introduction 331 10.2 The Measurement Problem 333 10.3 Refining the Idea of Measurement 336 10.4 My First Foray into Model-based Measurement 339 10.5 Two Other Measurement Devices and Their Classical Limit 344 10.6 The Quantum-to-Classical Transition 348 10.7 A Model-based Approach to Quantum Measurement 354 10.8 Questions for the Reader to Ponder 358 11 Quantum Systems Engineering 361 11.1 Introduction 361 11.2 What Is Systems Engineering? 363 11.2.1 An Overview 363 11.2.2 Notes on Complexity and Interconnectedness 365 11.2.3 Industry Standard Systems Engineering 365 11.3 Quantum Systems Engineering 366 11.3.1 Motivation 366 11.3.2 Modelling and Simulation Challenges 368 11.3.2.1 What Is in a Model? 368 11.3.2.2 Design for Modelability 369 11.3.2.3 Hierarchical Modelling 369 11.3.2.4 An Aside on Standards 370 11.3.2.5 Extensibility 370 11.3.2.6 State of Play 371 11.3.3 Reliability Engineering 371 11.3.4 System-of-interest Boundaries 373 11.3.5 Requirements Analysis 376 11.3.6 Test and Verification 379 11.3.7 Device Characterisation 382 11.3.8 Model-based Systems Engineering 383 11.4 Concluding Remarks 386 Bibliography 387 Index 395

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Book SynopsisDiscover theanalyticalfoundations of electric machine, power electronics, electric drives, and electric power systems InIntroduction to the Analysis of Electromechanical Systems, an accomplished team of engineers deliversan accessible and robust analysis of fundamental topics in electrical systems and electrical machine modelingoriented to their control with power converters. The book begins with an introduction to the electromagnetic variables in rotatory and stationary reference frames before moving ontodescriptions ofelectric machines. The authors discuss direct current, round-rotor permanent-magnet alternating current, and induction machines, as well as brushless direct currentand induction motor drives. Synchronous generators and various other aspects of electric power system engineering are coveredas well, showing readers how to describe the behavior of electromagnetic variables and how to approach their control with modern power converters. Introduction to the Analysis of ElectrTable of ContentsPreface ix About the Authors xi 1 Basic System Analysis 1 1.1 Introduction 1 1.2 Phasor Analysis and Power Calculations 1 1.2.1 Power and Reactive Power 6 1.3 Elementary Magnetic Circuits 8 1.3.1 Field Energy and Coenergy 12 1.4 Stationary Coupled Circuits – The Transformer 16 1.4.1 Magnetically Linear Transformer 17 1.4.2 Field Energy 20 1.5 Two- and Three-phase Systems 23 1.5.1 Two-phase Systems 23 1.5.2 Three-phase Systems 25 1.6 Problems 29 2 Fundamentals of Electric Machine Analysis 31 2.1 Introduction 31 2.2 Coupled Circuits in Relative Motion 32 2.2.1 Field Energy 35 2.3 Electromagnetic Force and Torque 36 2.4 Winding Configurations 42 2.4.1 Concentrated Winding 42 2.4.2 Distributed Windings 46 2.5 Rotating Air-gap mmf – Tesla’s Rotating Magnetic Field 49 2.5.1 Two-pole Two-phase Stator 50 2.5.2 Three-phase Stator 55 2.6 Change of Variables 57 2.6.1 Two-phase Transformation 57 2.6.2 Three-phase Transformation 59 2.7 Stator Voltage Equations in Arbitrary Reference Frame 61 2.8 Instantaneous and Steady-state Phasors 63 2.9 P-pole Machines 65 2.10 Problems 70 References 72 3 Electric Machines 73 3.1 Introduction 73 3.2 Direct-current Machine 73 3.2.1 Commutation 74 3.2.2 Voltage and Torque Equations 77 3.2.3 Permanent-magnet dc Machine 79 3.3 Permanent-magnet ac Machine 82 3.3.1 Two-phase Permanent-magnet ac Machine 82 3.3.2 Reference Frame Analysis of a Permanent-magnet ac Machine 86 3.3.3 Three-phase Permanent-magnet ac Machine 90 3.3.4 Steady-state Analysis 90 3.4 Symmetrical Induction Machines 95 3.4.1 Two-phase Induction Machine 96 3.4.2 Symmetrical Rotor Windings 98 3.4.3 Substitute Variables for Symmetrical Rotating Circuits 101 3.4.4 Torque 105 3.4.5 Phasors and Steady-state Equivalent Circuit 108 3.5 Problems 115 References 117 4 Power Electronics 119 4.1 Introduction 119 4.2 Switching-circuit Fundamentals 120 4.2.1 Power Conversion Principles 120 4.2.2 Switches and Switching Functions 121 4.2.3 Energy Storage Elements 125 4.3 dc–dc Conversion 127 4.3.1 Buck Converter 127 4.3.2 Boost Converter 137 4.3.3 Advanced Circuit Topologies 141 4.4 ac–dc Conversion 141 4.4.1 Half-wave Rectifier 141 4.4.2 Full-wave Rectifier 148 4.5 dc–ac Conversion 156 4.5.1 Single-phase Inverter 156 4.6 Problems 160 References 163 5 Electric Drives 165 5.1 Introduction 165 5.2 dc Drive 165 5.2.1 Average-value Time-domain Block Diagram 168 5.2.2 Torque Control 170 5.3 Brushless dc Drive 172 5.3.1 Operation of Brushless Dc Drive with Φ V = 0 175 5.3.2 Torque Control 177 5.4 Induction Motor Drive 182 5.4.1 Torque Control 187 5.5 Problems 191 References 191 6 Power Systems 193 6.1 Introduction 193 6.2 Three-phase Transformer Connections 193 6.2.1 Wye–Wye Connection 194 6.2.2 Delta–Delta Connection 196 6.2.3 Wye–Delta or Delta–Wye Connection 197 6.2.4 Ideal Transformers 198 6.3 Synchronous Generator 200 6.3.1 Damper Windings 204 6.3.2 Torque 205 6.3.3 Steady-state Operation and Rotor Angle 206 6.4 Reactive Power and Power-Factor Correction 212 6.5 Per Unit System 218 6.6 Discussion of Transient Stability 221 6.6.1 Three-phase Fault 222 6.7 Problems 226 References 227 Appendix A Abbreviations, Constants, Conversions, and Identities 229 Index 233

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Book SynopsisEssentials of Electrical and Computer Engineeringis for an introductory course or course sequence for nonmajors, focused on the essentials of electrical and computer engineering that are required for all engineering students, and to pass the electrical engineering portion of the Fundamentals of Engineering (FE) exam. The text gently yet thoroughly introduces students to the full spectrum of fundamental topics, and the modular presentation gives instructors great flexibility. Special chapters and sections not typically found in nonmajors books: The Electric Power System explains how the components of the Grid work together to produce and deliver electric power. (Ch 8)Load line analysis is integrated with small-signal analysis, providing wide application for enhancing students' understanding of transistor and circuit operation and the options for analysis. (Ch 9)Instrumentation looks at how electrical measurements support the analysis and development of engineering systems. (Ch 13) Modern electronic devices and applications are presented in way useful for all majors, at a level presuming no prior knowledge. Technologies such as MEMS (Microelectromechanical Systems) are included to illustrate how modern technologies are interdisciplinary. This text may also be useful for self-study readers learning the fundamentals of electrical and computer engineering.

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Book SynopsisNUCLEAR ELECTRONICS WITH QUANTUM CRYOGENIC DETECTORS An ideal, comprehensive reference on quantum cryogenic detector instrumentation for the semiconductor and nuclear electronics industries Quantum nuclear electronics is an important scientific and technological field that overviews the development of the most advanced analytical instrumentation. This instrumentation covers a broad range of applications such as astrophysics, fundamental nuclear research facilities, chemical nano-spectroscopy laboratories, remote sensing, security systems, forensic investigations, and more. In the years since the first edition of this popular resource, the discipline has developed from demonstrating the unprecedented energy resolving power of individual devices to building large frame cameras with hundreds of thousands of pixel arrays capable of measuring and processing massive information flow. Building upon its first edition, the second edition of Nuclear Electronics with Quantum Cryogenic Detectors Table of ContentsPREFACE Chapter 1. Interaction of nuclear radiation with detector absorbers Introduction. 1.1. Intrinsic quantum efficiency of radiation detectors. 1.2. Detection of charged particles. 1.2.1. Light charged particles. 1.2.2. Continuous “braking” radiation (bremsstrahlung). 1.2.3. Backscattering of charged particles. 1.2.4. Heavy charged particles. 1.3. Primary interactions of X- and γ-ray photons with solid-state absorbers. 1.3.1. The photoelectric effect. 1.3.2. The Compton scattering. 1.3.3. The pair production. 1.3.4. Attenuation of photon radiation in solid-state detector absorbers 1.4. Detection of neutrons with solid-state radiation sensors. 1.5. Heat generation in athermal absorbers. Chapter 2. Radiation detectors with superconducting absorbers Introduction. 2.1. Selected topics of the superconductivity theory 2.1.1. The electron-phonon interaction and Cooper pairing mechanisms 2.1.2. The behaviour of superconductors in the magnetic field. 2.1.3. The tunnel Josephson junction. 2.1.4. The superconducting transmission line: the kinetic inductance. 2.2. Superconducting absorbers: the down-conversion of particle energy, intrinsic energy resolution. 2.2.1. The energy down-conversion process in superconducting absorbers. 2.2.2. The intrinsic energy resolution of quasi-particle detectors with superconducting absorbers. 2.3. Transport in the non-equilibrium superconductors. Incomplete charge collection mechanisms 2.3.1. The recombination time of quasi-particles in superconducting absorbers 2.3.2. The Rothwarf-Taylor phenomenological framework 2.3.3. The diffusion of quasi-particles in thin-film superconducting absorbers. Incomplete charge collection 2.3.4. Noise Equivalent Power (NEP) of superconducting absorbers 2.4. Quasi-particle radiation detectors with Superconducting Tunnel Junction (STJ) readout 2.4.1. The bandgap engineering and fabrication of STJ detectors. 2.4.2. The Giaever I-V curve of the STJ. 2.4.3. The tunneling mechanisms in STJs. 2.4.4. Pile-up and count rate capability of the STJ detectors. 2.5. Quasi-particle radiation detectors with microwave kinetic inductance sensors (MKID) 2.5.1. The operating principle of microwave kinetic inductance sensors. 2.5.2. The DROID X-ray detector with microwave kinetic inductance sensor readout. 2.6. STJ detectors frequency domain multiplexing with microwave SQUIDs Chapter 3. Radiation detectors with normal metal absorbers Introduction 3.1. Spectrometers based on Transition Edge Sensor (TES) microcalorimeters. 3.1.1. Fundamentals of TES design. 3.1.2. The electro-thermal feedback in TES microcalorimeters. 3.2. TES Microcalorimeters with Microwave SQUID (MSQUID) readout. Imaging cameras 3.3. Hot electron microcalorimeter with the NIS tunnel junction thermometer Chapter 4. Radiation detectors with semiconductor absorbers Introduction 4.1. Semiconductor transport. 4.1.1. Valence bond and energy band models. 4.1.2. Carrier scattering mechanisms and mobility in the semiconductor bulk materials. 4.1.3. Carrier generation and recombination (G-R) processes. 4.1.4. Effects of the G-R transport on the performance of radiation detectors. 4.1.5. Tunneling-assisted transport in semiconductor materials. 4.1.6. Tunneling transport across the thin dielectric barrier. 4.1.7. The semiconductor-vacuum interface. Surface transport 4.2. Macroscopic modelling of semiconductor devices 4.2.1. Microscopic models based on the Schroedinger Equation 4.2.2. The semi-classical transport models 4.2.3. The initial and boundary conditions in device modeling. The Ramo-Shockley theorem 4.3. Front windows in semiconductor radiation detectors 4.3.1. Entrance window based on the Schottky barrier junction 4.3.2. Front window based Metal-Insulator-Semiconductor (MIS) junction 4.3.3. The pn junction based front window in radiation detectors 4.4. Fabrication of semiconductor drift detectors (SDD) 4.4.1. The epitaxially grown ultra-shallow p+n junction entrance windows 4.4.2. The pureB technology for ultra-shallow entrance windows 4.5. Semiconductor drift detectors 4.5.1. Semiconductor detectors: operation principle and performance specifications 4.5.2. The intrinsic energy resolution of semiconductor detectors 4.5.3. Time response of SDDs 4.6. The quantum calorimetric electron-hole detector with semiconductor absorber 4.6.1. The phonon system dynamics in semiconductor materials 4.6.2. The design and performance of the quantum electron-hole detectors Chapter 5. Front End Readout Electronic Circuits for Quantum Cryogenic Detectors. Introduction 5.1 JFET transconductance preamplifiers 5.1.1. Principles of JFET transconductance amplifiers 5.1.2. Settling time of preamplifiers 5.2Dynamic and noise properties of JFET amplifiers 5.2.1. Static and dynamic parameters of JFETs 5.2.2. Noise characteristics of JFETs 5.2.3. PentaFET. High precision reset mechanism 5.2.4. The JFET cascode stage 5.2.5. The source follow-based charge-sensitive preamplifier 5.2.6. The differential stage based on matched JFETs 5.3 High Electron Mobility Transistor (HEMT) low noise amplifiers 5.4. The dc SQUID current amplifiers 5.4.1. The dcSQUID as a superconducting parametric amplifier 5.4.2. The dcSQUID with an intermediary input transformer 5.4.3. The coupled energy resolution of a double transformer dcSQUID 5.4.4. The dcSQUID readout electronics 5.4.5. The dcSQUID with the digital Bode FLL controller 5.4.6. The dcSQUID amplifier in the small-signal limit (noise) 5.4.7. The dcSQUID current amplifier in the large signal limit (dynamics) 5.4.8. The dcSQUID current amplifier in the large signal limit (noise) 5.5dc SQUID current amplifier at ultra low temperature 5.5.1. A double-stage amplifier with a single front ULT dcSQUID 5.5.2. A double stage amplifier with the front ULT SQUID array 5.6 Microwave SQUID parametric amplifier 5.6.1. Operation principle of microwave SQUIDs with external pumping (MSQUIDs) 5.6.2. The non-linearities in the MSQUID readout 5.6.3. The flux-ramp modulation methodology 5.6.4. Performance of MSQUID current amplifier 5.7 Design methodologies of analogue circuitries 5.7.1. The Laplace transform. Transfer functions of electronic networks 5.7.2. Design of analog pulse-shaping filter cells 5.7.3. Design of low-pass filters 5.7.4. Graphical methods of analysis and synthesis in the frequency domain 5.7.5. The describing function of non-linear elements in the frequency domain 5.7.6. Systems with synchronous multipliers Chapter 6. The Energy Resolution of Radiation Spectrometers. Introduction 6.1 Signal-to-noise ratio, equivalent noise charge of radiation spectrometers. General definitions 6.2Energy resolution of quasi-particle detectors (STJs, SDDs) 6.2.1. The tunnel junction coupled to a JFET transconductance amplifier 6.2.2. Energy resolution of STJ sensors read out with SQUID current preamps 6.3Optimal filtration in radiation spectrometers 6.4Energy resolution of TES microcalorimeters 6.5Matrix readout multiplexing of STJ detectors 6.5.1. Matrix readout of STJ sensors with JFET transconductance amplifiers 6.5.2. Matrix readout with SQUID current amplifiers 6.6Time division multiplexing (TDM) 6.7 Frequency division multiplexing (FDM) with microwave SQUIDs (μMUX) 6.8Code division multiplexing (CDM). Spread spectrum modulation (SSM) Chapter 7. Signal processing in radiation spectrometers Introduction 7.1. Signal conditioning units 7.1.1. Overview digital pulse processing architectures 7.1.2. AC coupled digital spectrometers 7.1.3. Digital pulse processing with moving window deconvolution 7.1.4. DC-coupled digital pulse processors 7.1.5. DC-coupled digital pulse processors with a sliding window signal conditioner 7.2.Analogue-to-digital conversion 7.2.1. Analog-to-digital converters. Basic information 7.2.2. The quantisation noise model of ADC 7.2.3. Nonlinearities of ADC 7.2.4. Aperture time of ADCs 7.2.5. Aperture uncertainty of ADCs 7.2.6. Reduction of the differential nonlinearity with the sliding scale method 7.3.Digital filtration 7.3.1. Z-transform methodology 7.3.2. Design of digital filters with z-transform 7.3.3. The stability of digital filters 7.3.4. Trapezoidal pulse shaping digital filter 7.3.5. Moving average pulse processing 7.4.Throughput of digital spectrometers 7.4.1. Pulse recognition channel. Pile up detection 7.4.2. Timing resolution of digital spectrometers 7.4.3. The pile up decoding in digital pulse processors 7.4.4. Digital rise (fall) time discriminators 7.5.Selected topics on the hardware design 7.5.1. Noise reduction in systems with switching power supplies 7.5.2. PCB layout 7.5.3. Layout, decoupling, and grounding of ADCs 7.5.4. Grounding aspects of the system design Chapter 8. Ultra-Low Temperature (ULT) cryogenic arrangement. Introduction 8.1. Cooling technologies for sub-1K temperature 8.1.1. The 3He refrigerator 8.1.2. The adiabatic demagnetisation refrigerator (ADR) 8.1.3. Temperature control in ADRs 8.2.Magnetic shielding at ultra low temperature 8.2.1. The µ-metal shield 8.2.2. The superconducting shielding 8.2.3. Solenoid inside a cylindrical superconducting shield 8.3.Thermal load on ULT stages 8.3.1.Thermal conduction through solids 8.3.2. Thermal conduction through the gas 8.3.3. Thermal radiation 8.4.Cryogenic packaging for the Focal Plane Array (FPA) unit 8.4.1. Design of the FPA unit implementing the TDM technique 8.4.2. The collimation of the FPA unit 8.4.3. Solid angle of the nuclear radiation spectrometer 8.4.4. Focusing poly-capillary optics 8.4.5. Wiring at mK temperatures 8.5.Cryogenic design for detectors with micro-wave frequency division multiplexing 8.6.The collection efficiency of radiation spectrometers Chapter 9. Applications of radiation spectrometers based on quantum cryogenic detectors Introduction 9.1.Nano-analytical chemistry with the SEM electron probe 9.1.1. The SEM-based energy dispersive spectroscopy (EDS) 9.1.2. The dual array TES-based EDS 9.1.3. Complementary techniques in the electron probe nano-analysis: the Auger spectroscopy 9.1.4. Complementary techniques in the electron probe nano-analysis: the wavelength dispersive spectrometers 9.2.Energy dispersive MALDI-TOF mass spectrometry for biochemical analysis Index

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Book SynopsisExplore straightforward drawing skills to help you communicate product ideas exponentially faster than you could with text In Drawing Product Ideas: Fast and Easy UX Drawing for Anyone, RSA Fellow and Google Data Visualization Lead, Kent Eisenhuth delivers a new and exciting guide to effectively communicating product ideas by drawing just two simple things: boxes and lines! In the book, you'll learn why drawing is important and how it supports the design thinking process. You'll also discover how to build your drawing toolkit by exploring your own personal drawing style. The author also includes: Strategies for how to use your drawing to support your solutions to real-world problemsTips and tricks for applying your new drawing skills in a workshop setting, in real-timeAn illuminating foreword by the celebrated Manuel Lima, a Fellow of the Royal Society of Arts An essential volume for engineers, researchers, and product managers, Drawing Product Ideas is also an indispensable blueprint for anyone seeking to improve their public, ad-hoc drawing skills.Table of ContentsForeword ix Preface xi Introduction xv Chapter 1 Why Draw? 1 Explore an Idea 2 Gain a Shared Understanding 5 Improve Collaboration 7 Anyone Can Draw 7 Right Time and Place 10 Chapter 2 Reframing Our Thinking 15 Breaking It Down 17 Introducing the System 19 Common Drawings 23 Chapter 3 Lines and Points 33 Telling Stories with Lines 34 Making Meaning with Points 42 Tools and Materials 45 Chapter 4 Building From Rectangles 47 Creating Diagrams 48 Content Elements 55 Navigation Elements 58 Forms 65 Chapter 5 Building From Circles, Triangles, and More 81 Circular Elements 81 Triangular Elements 89 Advanced Icons and Symbols 92 Representing Interactions 98 Chapter 6 Illustrating Light, Motion, and Other Concepts 103 Shading Techniques 103 Using Accent Marks 105 Looking at Lighting 105 Using Elevation 110 Using Texture 116 Capturing Motion 119 Conveying Luminance 120 Communicating Sound 121 Chapter 7 The System 127 Putting It Together 128 Creating Something New 134 Chapter 8 Using Flows To Tell Stories 139 Starting with the Syntax 139 Showing Interactions 142 Just Enough Information 144 Depicting Transitions 145 Labels and Annotations 147 Being Conscious of Composition 150 Chapter 9 Telling Engaging Stories 157 Real-World Constraints 160 Invoking Emotion 166 Adapting the Visual Language 170 Wayfinding and Landmarks 174 Choreography and Timing 178 Packaging Your Drawings 180 Chapter 10 Moving Forward 183 Works Cited 185 Index 187

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Book SynopsisSOCIAL NETWORK ANALYSIS As social media dominates our lives in increasing intensity, the need for developers to understand the theory and applications is ongoing as well. This book serves that purpose. Social network analysis is the solicitation of network science on social networks, and social occurrences are denoted and premeditated by data on coinciding pairs as the entities of opinion. The book features: Social network analysis from a computational perspective using python to show the significance of fundamental facets of network theory and the various metrics used to measure the social network. An understanding of network analysis and motivations to model phenomena as networks. Real-world networks established with human-related data frequently display social properties, i.e., patterns in the graph from which human behavioral patterns can be analyzed and extracted. Exemplifies information cascades that spread through an undeTable of ContentsPreface xi 1 Overview of Social Network Analysis and Different Graph File Formats 1Abhishek B. and Sumit Hirve 1.1 Introduction—Social Network Analysis 2 1.2 Important Tools for the Collection and Analysis of Online Network Data 3 1.3 More on the Python Libraries and Associated Packages 9 1.4 Execution of SNA in Terms of Real-Time Application: Implementation in Python 13 1.5 Clarity Toward the Indices Employed in the Social Network Analysis 14 1.5.1 Centrality 14 1.5.2 Transitivity and Reciprocity 15 1.5.3 Balance and Status 15 1.6 Conclusion 15 References 15 2 Introduction To Python for Social Network Analysis 19Agathiya Raja, Gavaskar Kanagaraj and Mohammad Gouse Galety 2.1 Introduction 20 2.2 SNA and Graph Representation 21 2.2.1 The Common Representation of Graphs 21 2.2.2 Important Terms to Remember in Graph Representation 23 2.3 Tools To Analyze Network 24 2.3.1 MS Excel 24 2.3.2 Ucinet 26 2.4 Importance of Analysis 26 2.5 Scope of Python in SNA 26 2.5.1 Comparison of Python With Traditional Tools 27 2.6 Installation 27 2.6.1 Good Practices 28 2.7 Use Case 29 2.7.1 Facebook Case Study 30 2.8 Real-Time Product From SNA 32 2.8.1 Nevaal Maps 33 References 34 3 Handling Real-World Network Data Sets 37Arman Abouali Galehdari, Behnaz Moradi and Mohammad Gouse Galety 3.1 Introduction 37 3.2 Aspects of the Network 38 3.3 Graph 41 3.3.1 Node, Edges, and Neighbors 41 3.3.2 Small-World Phenomenon 42 3.4 Scale-Free Network 43 3.5 Network Data Sets 46 3.6 Conclusion 49 References 49 4 Cascading Behavior in Networks 51Vasanthakumar G. U. 4.1 Introduction 51 4.1.1 Types of Data Generated in OSNs 52 4.1.2 Unstructured Data 52 4.1.3 Tools for Structuring the Data 53 4.2 User Behavior 53 4.2.1 Profiling 54 4.2.2 Pattern of User Behavior 54 4.2.3 Geo-Tagging 55 4.3 Cascaded Behavior 56 4.3.1 Cross Network Behavior 56 4.3.2 Pattern Analysis 58 4.3.3 Models for Cascading Pattern 59 References 60 5 Social Network Structure and Data Analysis in Healthcare 63Sailee Bhambere 5.1 Introduction 64 5.2 Prognostic Analytics—Healthcare 64 5.3 Role of Social Media for Healthcare Applications 65 5.4 Social Media in Advanced Healthcare Support 67 5.5 Social Media Analytics 67 5.5.1 Phases Involved in Social Media Analytics 68 5.5.2 Metrics of Social Media Analytics 69 5.5.3 Evolution of NIHR 70 5.6 Conventional Strategies in Data Mining Techniques 71 5.6.1 Graph Theoretic 72 5.6.2 Opinion Evaluation in Social Network 74 5.6.3 Sentimental Analysis 75 5.7 Research Gaps in the Current Scenario 75 5.8 Conclusion and Challenges 77 References 78 6 Pragmatic Analysis of Social Web Components on Semantic Web Mining 83Sasmita Pani, Bibhuprasad Sahu, Jibitesh Mishra, Sachi Nandan Mohanty and Amrutanshu Panigrahi 6.1 Introduction 84 6.2 Background 87 6.2.1 Web 87 6.2.2 Agriculture Information Systems 88 6.2.3 Ontology in Web or Mobile Web 90 6.3 Proposed Model 90 6.3.1 Developing Domain Ontology 91 6.3.2 Building the Agriculture Ontology with OWL-DL 94 6.3.2.1 Building Class Axioms 94 6.3.3 Building Object Property Between the Classes in OWL-DL 95 6.3.3.1 Building Object Property Restriction in OWL-DL 96 6.3.4 Developing Social Ontology 97 6.3.4.1 Building Class Axioms 99 6.3.4.2 Analysis of Social Web Components on Domain Ontology Under Agriculture System 100 6.4 Building Social Ontology Under the Agriculture Domain 100 6.4.1 Building Disjoint Class 100 6.4.2 Building Object Property 103 6.5 Validation 104 6.6 Discussion 104 6.7 Conclusion and Future Work 105 References 106 7 Classification of Normal and Anomalous Activities in a Network by Cascading C4.5 Decision Tree and K-Means Clustering Algorithms 109Gouse Baig Mohammad, S. Shitharth and P. Dileep 7.1 Introduction 110 7.1.1 Cascade Blogosphere Information 111 7.1.2 Viral Marketing Cascades 112 7.1.3 Cascade Network Building 113 7.1.4 Cascading Behavior Empirical Research 113 7.1.5 Cascades and Impact Nodes Detection 114 7.1.6 Topologies of Cascade Networks 114 7.1.7 Proposed Scheme Contributions 117 7.2 Literature Survey 118 7.2.1 Network Failures 122 7.3 Methodology 123 7.3.1 K-Means Clustering for Anomaly Detection 123 7.3.2 C4.5 Decision Trees Anomaly Detection 124 7.4 Implementation 125 7.4.1 Training Phase ZI 125 7.4.2 Testing Phase 126 7.5 Results and Discussion 127 7.5.1 Data Sets 127 7.5.2 Experiment Evaluation 127 7.6 Conclusion 127 References 128 8 Machine Learning Approach To Forecast the Word in Social Media 133R. Vijaya Prakash 8.1 Introduction 133 8.2 Related Works 135 8.3 Methodology 135 8.3.1 TF-IDF Technique 136 8.3.2 Times Series 137 8.4 Results and Discussion 138 8.5 Conclusion 141 References 145 9 Sentiment Analysis-Based Extraction of Real-Time Social Media Information From Twitter Using Natural Language Processing 149Madhuri Thimmapuram, Devasish Pal and Gouse Baig Mohammad 9.1 Introduction 150 9.1.1 Applications for Social Media 153 9.1.2 Social Media Data Challenges 154 9.2 Literature Survey 157 9.2.1 Techniques in Sentiment Analysis 164 9.3 Implementation and Results 166 9.3.1 Online Commerce 166 9.3.2 Feature Extraction 167 9.3.3 Hashtags 167 9.3.4 Punctuations 167 9.4 Conclusion 168 9.5 Future Scope 171 References 171 10 Cascading Behavior: Concept and Models 175Bithika Bishesh 10.1 Introduction 175 10.2 Cascade Networks 177 10.3 Importance of Cascades 178 10.4 Purposes for Studying Cascades 179 10.5 Collective Action 179 10.6 Cascade Capacity 180 10.7 Models of Network Cascades 180 10.7.1 Decision-Based Diffusion Models 181 10.7.2 Probabilistic Model of Cascade 181 10.7.3 Linear Threshold Model 183 10.7.4 Independent Cascade Model 183 10.7.5 SIR Epidemic Model 184 10.8 Centrality 186 10.9 Cascading Failures 189 10.10 Cascading Behavior Example Using Python 189 10.11 Conclusion 192 References 202 11 Exploring Social Networking Data Sets 205Arulkumar N., Joy Paulose, Mohammad Gouse Galety, Manimaran A., S. Saravanan and Saleem Raja A. 11.1 Introduction 206 11.1.1 Network Theory 206 11.1.2 Social Network Analysis 207 11.2 Establishing a Social Network 208 11.2.1 Designing the Symmetric Social Network 208 11.2.2 Creating an Asymmetric Social Network 210 11.2.3 Implementing and Visualizing Weighted Social Networks 212 11.2.4 Developing the Multigraph for Social Networks 213 11.3 Connectivity of Users in Social Networks 214 11.3.1 The Degree to which a Network Exists 214 11.3.2 Coefficient of Clustering 215 11.3.3 The Shortest Routes and Length Between Two Nodes 215 11.3.4 Eccentricity Distribution of a Node in a Social Network 217 11.3.5 Scale-Independent Social Networks 218 11.3.6 Transitivity 218 11.4 Centrality Measures in Social Networks 218 11.4.1 Centrality by Degree 219 11.4.2 Centrality by Eigenvectors 219 11.4.3 Centrality by Betweenness 220 11.4.4 Closeness to All Other Nodes 220 11.5 Case Study of Facebook 221 11.6 Conclusion 226 References 227 Index 229

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Book SynopsisINTRELLIGENT MANUFACTURING MANAGEMENT SYSTEMS The book explores the latest manufacturing techniques in relation to AI and evolutionary algorithms that can monitor and control the manufacturing environment. The concepts that pertain to the application of digital evolutionary technologies in the sphere of industrial engineering and manufacturing are presented in this book. A few chapters demonstrate stepwise discussion, case studies, structured literature review, rigorous experimentation results, and applications. Further chapters address the challenges encountered by industries in integrating these digital technologies into their operational activities, as well as the opportunities for this integration. In addition, the reader will find: Systemic explanations of the unique characteristics of big data, cloud computing, and AI used for decision-making in intelligent production systems; Highlights of the current and highly relevant topics in manufactTable of ContentsPreface xvii Part I: Smart Technologies in Manufacturing 1 1 Smart Manufacturing Systems for Industry 4.0 3 Gaijinliu Gangmei and Polash Pratim Dutta Abbreviations 3 1.1 Introduction 4 1.2 Research Methodology 5 1.3 Pillars of Smart Manufacturing 6 1.3.1 Manufacturing Technology and Processes 6 1.3.2 Materials 7 1.3.3 Data 8 1.3.4 Sustainability 8 1.3.5 Resource Sharing and Networking 9 1.3.6 Predictive Engineering 9 1.3.7 Stakeholders 10 1.3.8 Standardization 10 1.4 Enablers and Their Applications 11 1.4.1 Smart Design 12 1.4.2 Smart Machining 12 1.4.3 Smart Monitoring 13 1.4.4 Smart Control 13 1.4.5 Smart Scheduling 14 1.5 Assessment of Smart Manufacturing Systems 14 1.6 Challenges in Implementation of Smart Manufacturing Systems 15 1.6.1 Technological Issue 16 1.6.2 Methodological Issue 16 1.7 Implications of the Study for Academicians and Practitioners 17 1.8 Conclusion 17 References 18 2 Smart Manufacturing Technologies in Industry 4.0: Challenges and Opportunities 23 S. Deepak Kumar, G. Arun Manohar, R. Surya Teja, P. S. V. Ramana Rao, A. Mandal, Ajit Behera and P. Srinivasa Rao Abbreviations 24 2.1 Introduction to Smart Manufacturing 24 2.1.1 Background of SM 24 2.1.2 Traditional Manufacturing versus Smart Manufacturing 25 2.1.3 Concept and Evolution of Industry 4.0 25 2.1.4 Motivations for Research in Smart Manufacturing 28 2.1.5 Objectives and Need of Industry 4.0 29 2.1.6 Research Methodology 30 2.1.7 Principles of I4. 0 30 2.1.8 Benefits/Advantages of Industry 4.0 31 2.2 Technology Pillars of Industry 4.0 31 2.2.1 Automation in Industry 4.0 33 2.2.1.1 Need of Automation 33 2.2.1.2 Components of Automation 33 2.2.1.3 Applications of Automation 34 2.2.2 Robots in Industry 4.0 34 2.2.2.1 Need of Robots 35 2.2.2.2 Advantages of Robots 35 2.2.2.3 Applications of Robots 37 2.2.2.4 Advances Robotics 37 2.2.3 Additive Manufacturing (AM) 38 2.2.3.1 Additive Manufacturing’s Potential Applications 39 2.2.4 Big Data Analytics 40 2.2.5 Cloud Computing 41 2.2.6 Cyber Security 43 2.2.6.1 Cyber-Security Challenges in Industry 4.0 43 2.2.7 Augmented Reality and Virtual Reality 44 2.2.8 Simulation 46 2.2.8.1 Need of Simulation in Smart Manufacturing 46 2.2.8.2 Advantages of Simulation 47 2.2.8.3 Simulation and Digital Twin 47 2.2.9 Digital Twins 47 2.2.9.1 Integration of Horizontal and Vertical Systems 48 2.2.10 IoT and IIoT in Industry 4.0 48 2.2.11 Artificial Intelligence in Industry 4.0 49 2.2.12 Implications of the Study for Academicians and Practitioners 51 2.3 Summary and Conclusions 51 2.3.1 Benefits of Industry 4.0 51 2.3.2 Challenges in Industry 4.0 52 2.3.3 Future Directions 52 Acknowledgement 53 References 53 3 IoT-Based Intelligent Manufacturing System: A Review 59 Hiranmoy Samanta, Pradip Kumar Talapatra, Kamal Golui and Pritam Chakraborty 3.1 Introduction 60 3.2 Literature Review 60 3.3 Research Procedure 64 3.3.1 The Beginning and Advancement of SM/IM 64 3.3.2 Beginning of SM/IM 64 3.3.3 Defining SM/IM 65 3.3.4 Potential of SM/IM 66 3.3.5 Statistical Analysis of SM/IM 68 3.3.6 Future Endeavour of SM/IM 68 3.3.7 Necessary Components of IoT Framework 69 3.3.8 Proposed System Based on IoT 71 3.3.9 Development of IoT in Industry 4.0 72 3.4 Smart Manufacturing 73 3.4.1 Re-Configurability Manufacturing System 73 3.4.2 RMS Framework Based Upon IoT 75 3.4.3 Machine Control 76 3.4.4 Machine Intelligence 77 3.4.5 Innovation and the IIoT 78 3.4.6 Wireless Technology 78 3.4.7 IP Mobility 78 3.4.8 Network Functionality Virtualization (NFV) 79 3.5 Academia Industry Collaboration 79 3.6 Conclusions 80 References 81 4 3D Printing Technology in Smart Manufacturing Systems for Efficient Production Process 85 Kali Charan Rath, Prasenjit Chatterjee, Pankajkumar Munibara Patro, Polaiah Bojja, Amaresh Kumar and Rashmi Prava Das Abbreviations 86 4.1 Introduction and Literature Reviews 86 4.1.1 Motivation Behind the Study 88 4.1.2 Objective of the Chapter 89 4.2 Network in Smart Manufacturing System 89 4.2.1 Challenges for Smart Manufacturing Industries 90 4.2.2 Smart Manufacturing Current Market Scenario 93 4.3 Data Drives in Smart Manufacturing 93 4.3.1 Benefits of Data-Driven Manufacturing 94 4.4 Manufacturing of Product Through 3D Printing Process 97 4.4.1 3D Printing Technology 99 4.4.2 3D Printing Technologies Classification 100 4.4.3 3D Printer Parameters 101 4.4.4 Significance of Honeycomb Structure 102 4.4.5 Acrylonitrile Butadiene Styrene (ABS) Thermoplastic Polymer Used for Honeycomb Structures Model 103 4.4.6 3D Printing Parameters and Their Descriptions 107 4.5 Conclusion 107 References 109 5 Smart Inventory Control: Proposed Framework on Basis of IoT, RFID, and Supply Chain Management 113 Hiranmoy Samanta and Kamal Golui 5.1 Introduction 114 5.2 Objectives 114 5.3 Research Methodology 114 5.4 Literature Review 115 5.5 Components of SIM 116 5.5.1 Supply Chain Management (SCM) 116 5.5.2 Inventory Management System (IMS) 117 5.5.3 Internet of Things (IoT) 120 5.5.4 RFID System 121 5.5.5 Maintenance, Repair, and Operations 123 5.5.6 Deep Reinforcement Learning 125 5.6 Framework 127 5.7 Optimization 130 5.7.1 Inventory Optimization 130 5.8 Results and Discussion 131 5.9 A Mirror to Researchers and Managers 132 5.10 Conclusions 133 5.11 Future Scope 133 References 134 6 Application of Machine Learning in the Machining Processes: Future Perspective Towards Industry 4.0 141 Bikash Chandra Behera, Bikash Ranjan Moharana, Matruprasad Rout and Kishore Debnath 6.1 Introduction 142 6.2 Machine Learning 143 6.3 Smart Factory 146 6.4 Intelligent Machining 148 6.5 Machine Learning Processes Used in Machining Process 150 6.6 Performance Improvement of Machine Structure Using Machine Learning 152 6.7 Conclusions 153 References 153 7 Intelligent Machine Learning and Deep Learning Techniques for Bearings Fault Detection and Decision-Making Strategies 157 Jagadeesha T., Thutupalli Srinivasa Advaith, Choppala Sarath Wesley, Grandhi Sri Sai Charith and Doppalapudi Manohar Abbreviations 158 7.1 Introduction 158 7.2 Literature Review 159 7.3 Methodology 161 7.3.1 Dataset Preparation 161 7.3.2 CWRU Dataset 161 7.3.3 Methodology Flow Chart 161 7.3.4 Data Pre-Processing 162 7.3.5 Models Deployed 163 7.3.6 Training and Testing 163 7.4 Analysis 164 7.4.1 Datasets 164 7.4.2 Feature Extraction 168 7.4.3 Splitting of Data into Samples 168 7.4.4 Algorithms Used 169 7.4.4.1 Multinomial Logistic Regression 169 7.4.4.2 K-Nearest Neighbors 170 7.4.4.3 Decision Tree 172 7.4.4.4 Support Vector Machine (SVM) 173 7.4.4.5 Random Forest 175 7.5 Results and Discussion 177 7.5.1 Importance of Classification Reports 177 7.5.2 Importance of Confusion Matrices 177 7.5.3 Decision Tree 178 7.5.4 Random Forest 180 7.5.5 K-Nearest Neighbors 182 7.5.6 Logistic Regression 185 7.5.7 Support Vector Machine 185 7.5.8 Comparison of the Algorithms 188 7.5.8.1 Accuracies 188 7.5.8.2 Precision and Recall 188 7.6 Conclusions 191 7.7 Scope of Future Work 191 References 192 8 Smart Vision-Based Sensing and Monitoring of Power Plants for a Clean Environment 195 K. Sujatha, R. Krishnakumar, N.P.G. Bhavani, U. Jayalatsumi, V. Srividhya, C. Kamatchi and R. Vani 8.1 Introduction 196 8.1.1 Color Image Processing 197 8.1.2 Motivation 199 8.1.3 Objectives 199 8.2 Literature Review 200 8.2.1 Gas Turbine Power Plants 200 8.2.2 Artificial Intelligent Methods 201 8.3 Materials and Methods 202 8.3.1 Feature Extraction 202 8.3.2 Classification 203 8.4 Results and Discussion 204 8.4.1 Fisher’s Linear Discriminant Function (FLDA) and Curvelet 204 8.5 Conclusion 219 8.5.1 Future Scope of Work 220 References 221 9 Implementation of FEM and Machine Learning Algorithms in the Design and Manufacturing of Laminated Composite Plate 223 Sidharth Patro, Trupti Ranjan Mahapatra, Romeo S. Fono Tamo, Allu Vikram Kishore Murty, Soumya Ranjan Parimanik and Debadutta Mishra Abbreviations 224 9.1 Introduction 224 9.2 Numerical Experimentation Program 227 9.3 Discussion of the Results 239 9.4 Conclusion 244 Acknowledgements 245 References 245 Part II: Integration of Digital Technologies to Operations 249 10 Edge Computing-Based Conditional Monitoring 251 Granville Embia, Aezeden Mohamed, Bikash Ranjan Moharana and Kamalakanta Muduli 10.1 Introduction 252 10.1.1 Problem Statement 252 10.2 Literature Review 253 10.3 Edge Computing 257 10.4 Methodology 259 10.5 Discussion 263 10.5.1 Predictive Maintenance 263 10.5.2 Energy Efficiency Management 264 10.5.3 Smart Manufacturing 265 10.5.4 Conditional Monitoring via Edge Computing Locally 266 10.5.5 Lesson Learned 266 10.6 Conclusion 267 References 267 11 Optimization Methodologies in Intelligent Manufacturing Systems: Application and Challenges 271 Hiranmoy Samanta, Pradip Kumar Talapatra, Kamal Golui and Atiur Alam 11.1 Introduction 272 11.2 Literature Review 273 11.3 Intelligent Manufacturing System Framework 275 11.3.1 Principles of Developing Industry 4.0 Solutions 277 11.3.2 Quantitative Analysis 279 11.3.2.1 Optimization Characteristics and Requirements of Industry 4.0 279 11.3.3 Optimization Methodologies and Algorithms 281 11.4 Bayesian Networks (BNs) 287 11.4.1 Instance-Based Learning (IBL) 288 11.4.2 The IB1 Algorithm 288 11.4.3 Artificial Neural Networks 289 11.4.4 A Comparison Between Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN) 291 11.5 Problems of Implementing Machine Learning in Manufacturing 293 11.6 Conclusions 293 References 294 12 Challenges of Warehouse Management Towards Smart Manufacturing: A Case of an Indian Consumer Electrical Company 297 Natarajan Ramanathan, Neeraj Vairagi, Sakti Parida, Sushanta Tripathy, Ashok Kumar Sar, Kumar Mohanty and Alisha Lakra 12.1 Introduction 298 12.2 Literature Review 300 12.2.1 Shortage of Space 301 12.2.2 Non-Moving Materials 301 12.2.3 Lack of Action on Liquidation 302 12.2.4 Defective Material from Both Ends 302 12.2.5 Gap Between the Demand and the Supply 302 12.2.6 Multiple Price Revision 303 12.2.7 More Manual Timing for Loading and Unloading 303 12.2.8 Operational Challenges for Seasonal Products 303 12.2.9 Lack of Automation 303 12.2.10 Manpower Balancing Between Peak and Off 304 12.3 The Proposed ISM Methodology 304 12.3.1 Establishment of the Structural Self-Interaction Matrix (SSIM) 306 12.3.2 Creation of the Reachability Matrix 307 12.3.3 Implementation of the Level Partitions 308 12.3.4 Classification of the Selected Challenges 309 12.3.5 Development of the Final ISM Model 310 12.4 Results and Discussion 311 12.5 Practical Implications 312 12.6 Conclusions 313 References 314 13 The Impact of Organizational Ergonomics on Teaching Rapid Prototyping 319 Yaone Rapitsenyane, Patience Erick, Oanthata Jester Sealetsa and Richie Moalosi Abbreviations 320 13.1 Introduction 320 13.2 Organizational Ergonomics 322 13.2.1 Aim of Organizational Ergonomics 323 13.3 Rapid Prototyping and Teaching Rapid Prototyping 323 13.4 Industry 4.0 Factors Associated with Organizational Ergonomics in a Rapid Prototyping/Manufacturing Facility 325 13.4.1 Technology 326 13.4.2 Communication 327 13.4.3 Teamwork 328 13.4.4 Human Resource 328 13.4.5 Quality Management 329 13.5 Implications of Industry 4.0 on Prototyping and Prototyping Facilities in Design Schools 329 13.6 The Influence of Cooperative Working Ergonomics of Distributed Manufacturing in Teaching and Learning Rapid Prototyping 332 13.7 Health and Safety in Rapid Prototyping Laboratories 333 13.7.1 Common Health Hazards in 3D Printing 333 13.7.2 Chemical Hazards 335 13.7.3 Flammable/Explosion Hazards 336 13.7.4 UV and Laser Radiation Hazard 336 13.7.5 Other Hazards 336 13.7.6 Hazard Controls 337 13.7.7 Engineering Controls 337 13.7.8 Administrative Controls 338 13.7.9 Personal Protective Equipment 338 13.8 Impact of Digital/Rapid Prototyping on Organizational Ergonomics 339 13.9 Implications of the Study for Academicians and Practitioners 340 13.10 Conclusions and Future Work 341 References 343 14 Sustainable Manufacturing Practices through Additive Manufacturing: A Case Study on a Can-Making Manufacturer 349 Kiren Piso, Aezeden Mohamed, Bikash Ranjan Moharana, Kamalakanta Muduli and Noorhafiza Muhammad 14.1 Introduction 350 14.2 Literature Review 352 14.3 Research Set Up 354 14.4 Additive Manufacturing Techniques 356 14.4.1 Types of Additive Manufacturing 356 14.4.1.1 Fused Deposition Modelling (FDM) 356 14.4.1.2 Stereolithography (SLA) 356 14.4.1.3 Selective Laser Sintering (SLS) 357 14.4.1.4 Direct Energy Deposition (DED) 357 14.4.1.5 Digital Light Processing (DLP) 358 14.5 Strategies Used by Production Company 358 14.5.1 Maintenance Strategies 358 14.5.1.1 Breakdown Maintenance (BM) 358 14.5.1.2 Preventive Maintenance (PM) 358 14.5.1.3 Periodic Maintenance (Time Based Maintenance – TBM) 359 14.5.1.4 Predictive Maintenance (PM) 359 14.5.1.5 Corrective Maintenance (CM) 359 14.5.1.6 Maintenance Prevention (PM) 359 14.5.2 Inventory Control in Manufacturing 359 14.5.2.1 Inventory Control and Maintenance in Manufacturing 360 14.5.2.2 Warehouse Storages 360 14.5.3 Time Factor in Manufacturing 361 14.5.3.1 Breakdown Time 361 14.5.3.2 Set-Up Time 361 14.5.3.3 Manned Time (Available Time) 361 14.5.3.4 Operating Working Time 361 14.5.3.5 Operating Time 362 14.5.3.6 Production Time 362 14.6 Sustainable Manufacturing 362 14.6.1 Social Aspect of Sustainable Manufacturing 363 14.6.2 Environmental Aspects of Sustainable Manufacturing 364 14.6.3 Economical Aspect of Sustainable Manufacturing 364 14.7 Sustainable Additive Manufacturing 365 14.7.1 Energy 365 14.7.2 Cost 366 14.7.2.1 Downtime Cost 366 14.7.3 Supply Chain 368 14.7.4 Maintenance with Additive Manufacturing 368 14.8 Additive Manufacturing with IFC CMD: A Case Study 369 14.9 Contribution of Additive Manufacturing Towards Sustainability 370 14.10 Limitations of Additive Manufacturing 372 14.11 Conclusions and Recommendations 373 References 373 Index 377

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Book SynopsisTable of ContentsPreface xix Acknowledgements xxiii 1 Self-Powered Sensory Transducers: A Way Toward Green Internet of Things 1Rajeev Ranjan 1.1 Introduction 1 1.2 Need of the Work 3 1.3 Energy Scavenging Schemes in WSAN 4 1.4 Self Powered Systems and Green IoT (G-IoT) 10 1.5 Application Area and Scope of Self-Powered System in G-IoT 11 1.6 Challenges and Future Scope of the Self-Powered G-IoT 22 1.7 Conclusion 27 2 Self-Powered Wireless Sensor Networks in Cyber Physical System 41Srividya P. 2.1 Introduction 42 2.2 Wireless Sensor Networks in CPS 43 2.3 Architecture of WSNs with Energy Harvesting 44 2.4 Energy Harvesting for WSN 44 2.5 Energy Harvesting Due to Mechanical Vibrations 45 2.6 Piezoelectric Generators 46 2.7 Piezoelectric Materials 47 2.8 Types of Piezoelectric Structures 48 2.9 Hybridized Nanogenerators for Energy Harvesting 55 2.10 Conclusion 56 3 The Emergence of Cyber-Physical System in the Context of Self-Powered Soft Robotics 57Darwin S. and Fantin Irudaya Raj E. 3.1 Introduction 58 3.2 Actuators and Its Types 59 3.3 Soft Actuator Electrodes 69 3.4 Sensors 72 3.5 Soft Robotic Structures and Control Methods 74 3.6 Soft Robot Applications 76 3.7 Future Scope 79 3.8 Conclusion 82 4 Dynamic Butterfly Optimization Algorithm-Based Task Scheduling for Minimizing Energy Consumption in Distributed Green Data Centers 91Sengathir Janakiraman and Deva Priya M. 4.1 Introduction 92 4.2 Related Work 94 4.3 Improved Dynamic Butterfly Optimization Algorithm (IDBOA)-Based Task Scheduling (IDBOATS) 99 4.4 Results and Discussion 106 4.5 Conclusion 110 5 Wireless Power Transfer for IoT Applications--A Review 115Sasikala G. and Rajeev Ranjan 5.1 Introduction 116 5.2 Sensors 116 5.3 Actuators 118 5.4 Energy Requirement in Wireless Sensor Networks (WSNs) 119 5.5 Wireless Sensor Network and Green IoT (G-IoT) 121 5.6 Purpose of G-IoT 122 5.7 Motivation 124 5.8 Contribution 124 5.9 Need of the Work 125 5.10 Energy Transferring Schemes in WSAN 126 5.11 Electromagnetic Induction 127 5.12 Inductive Coupling 131 5.13 Resonance Inductive Coupling 132 5.14 Wireless Power Transmission Using Microwaves 133 5.15 Electromagnetic Radiations 135 5.16 Conclusion 135 6 Adaptive Energy Intelligence Using AI/ML Techniques 141Gowthamani R., Sasi Kala Rani K., Manikandan M. and Rohini M. 6.1 Introduction 142 6.2 Evolution of Cyber Physical System 144 6.3 Relationship With Internet of Things 146 6.4 Challenges in Design and Integration of Cyber Physical Systems 147 6.5 Future Challenges and Promises 149 6.6 Machine Learning Models 149 6.7 Estimation of Building Energy Consumption 150 6.8 Development of Artificial Intelligence 150 6.9 Usage of AI/ML in Adaptive Energy Management 151 6.10 Use of Hybrid/Ensemble Machine Learning Algorithm for Better Prediction 152 6.11 Conclusion 155 7 Renewable Energy Smart Grids for Electric Vehicles 159Vishal H. Kanchan, Preethesh B., Hithesh Alen D'Costa, Sohan R. Alva and Rathishchandra Ramachandra Gatti 7.1 Introduction 160 7.2 Integration of Electric Vehicles (EVs) into the Power Grid 161 7.3 EV Charging and Electric Grid Interaction 161 7.4 EVs with V2G System Architecture 163 7.5 EVs and Smart Grid Infrastructure 164 7.6 Renewable Energy Sources Integration With EVs 165 7.7 Application in Transport Sector 167 7.8 Application in Micro-Grid 169 7.9 State-of-the-Art Review 170 7.10 Future Trends 172 8 Recent Advances in Integrating Renewable Energy Micro-Grid Systems With Electric Vehicles 177Hithesh Alen D'Costa, Sohan R. Alva, Vishal H. Kanchan, Preethesh B. and Rathishchandra R. Gatti 8.1 Introduction 178 8.2 Electric Vehicles and Renewable Energy Sources: A General Overview 179 8.3 Microgrid 183 8.4 Interactions Between Cost-Conscious EVs and RESs 186 8.5 Interaction Between Efficiency-Conscious EVs and RESs 188 8.6 Open Problems 190 8.7 Conclusion 191 9 Overview of Fast Charging Technologies of Electric Vehicles 193Sohan R. Alva, Vishal H. Kanchan, Preethesh B., Hithesh Alen D'Costa and Rathishchandra Ramachandra Gatti 9.1 Introduction 194 9.2 Different Levels of Charging Electric Vehicles 194 9.3 State-of-the-Art Fast-Charging Implementation 197 9.4 DC Fast-Charging Structure 199 9.5 Fast Chargers 200 9.6 Today's Situation and Future Needs 201 9.7 Fast-Charging Point Power Requirements 202 9.8 Recent Technologies in Fast Charging, Machine Learning, and Artificial Intelligence 203 9.9 Effect of Fast Charging on EV Powertrain Systems 205 9.10 Grid Impacts Caused by EV Charging 207 9.11 Fast-Charging Technologies on the Self-Powered Automotive Cyber-Physical Systems 208 9.12 Conclusions 209 10 A Survey of VANET Routing Attacks and Defense Mechanisms in Intelligent Transportation System 213Allam Balaram, P. Chandana, Shaik Abdul Nabi and M. SilpaRaj 10.1 Introduction 214 10.2 Attacks in VANET 215 10.3 Impacts of Attacks on VANET Routing 216 10.4 Nonintentional Misbehavior 217 10.5 Intentional Misbehavior 217 10.6 Defence Mechanism of Routing Attacks in VANET Routing 218 10.7 Intrusion Detection Techniques in VANETs 220 10.8 Anonymous Routing in VANETs 221 10.9 Challenges and Future Directions 222 10.10 Conclusion 223 11 ANN-Based Cracking Model for Flexible Pavement in the Urban Roads 227Athiappan K., Kandasamy A., Karthik C. and Rajalakshmi M. 11.1 Introduction 228 11.2 Literature Review 229 11.3 Methodology 230 11.4 Structural Number 234 11.5 Modeling Methodology 235 11.6 Model Validation 238 11.7 Sensitivity Analysis 238 11.8 Conclusions 241 11.9 Limitations 241 11.10 Future Scope of Study 241 12 A Review of Autonomous Vehicles 243Joyston J. D'Costa and Ajith B.S. 12.1 Introduction 244 12.2 History 245 12.3 Degrees in Automation 246 12.4 Benefits and Drawbacks 247 12.5 Working Principle of Autonomous Vehicles 249 12.6 Mechanics Involved 250 12.7 Conclusion 252 13 Meeting Privacy Concerns in Intelligent Transportation Systems 255Sharon D. John 13.1 Introduction 255 13.2 Synopsis of ITS 257 13.3 Future Research Direction 260 13.4 Contributions to this Research 261 13.5 Conclusions 262 14 Feasibility Study of Digital Twin in Automotive Industry--Trends and Challenges 265Preethesh B., Hithesh Alen D'Costa, Sohan R. Alva, Vishal H. Kanchan and Rathishchandra R. Gatti 14.1 Introduction 266 14.2 Industrial Evolution 267 14.3 Influence of IoT on Digital Twin 268 14.4 Digital Twin in CPS Applications 269 14.5 Digital Twin Types 270 14.6 Levels of Digital Twin 271 14.7 Digital Thread 272 14.8 State-of-the-Art Digital Twin Deployment 273 14.9 Benefits of Digital Twin 274 14.10 Digital Twin Life Cycle 275 14.11 Digital Twin in Automotive Industry 276 14.12 Applications of Digital Twinning Technology in the Automotive Industry 277 14.13 Role of Digital Twins in Addressing Current Automotive Challenges 279 14.14 Challenges for Implementing Digital Twin in Automotive Industry 280 14.15 Bridging the Gap 280 15 State-of-the-Art and Future Applications of Farming Robotics 283Badrinath A.R., Abhishek Kamath, Veerishetty Arun Kumar, Nishan Rai and Rathishchandra R. Gatti 15.1 Introduction 283 15.2 Components of Agricultural Robots 285 15.3 Types of Agricultural Robots 288 15.4 Implementation of Robotics in the Agricultural Process 290 15.5 Challenges 294 15.6 Conclusions 295 16 Review on Robot Operating System 297G. Vijeth and Rathishchandra R. Gatti 16.1 Introduction 297 16.2 Nomenclature 301 16.3 ROS Implementation 303 16.4 Conclusion 306 17 An Overview of Collaborative Robots and Their Applications 309Rao S. Krishna and Lawrence J. Fernandes 17.1 Introduction 309 17.2 Art of Study 310 17.3 Implementation of Collaborative Robots 314 17.4 Conclusion 318 18 State-of-the-Art and Future Applications of Powered Exoskeleton 321C.P. Dheeshith, K. Abhijith, A. Shahaas, Rithin B. Nambiar and Rathishchandra R. Gatti 18.1 Introduction 321 18.2 Powered Exoskeleton 323 18.3 State of the Art 324 18.4 Design Parameters to be Considered 325 18.5 Challenges to Tackle 328 18.6 Applications of Powered Exoskeleton 328 18.7 Conclusion 330 19 An Overview of Recent Trends in Consumer Robotics 333Pramod Rao M., Shrihari P.C., Manoj, Shankar Gouda S. and Rathishchandra R. Gatti 19.1 Introduction 333 19.2 Entertainment Robot 334 19.3 Educational Robot 335 19.4 Social Robot 336 19.5 Toy Robot 337 19.6 Conclusion 338 20 Soft Robotics in Waste Management 341S. Rithvik, Vijith Rai, Surya Dornal, Deepak J. and B.C. Pramod 20.1 Introduction 341 20.2 Soft Robotics Insights 342 20.3 Soft Robots in Waste Management 343 20.4 Are Soft Robots the First Step for a Sustainable Future? 346 20.5 Conclusions 347 21 State-of-the-Art Review of Robotics in Crop Agriculture 349A. Shahaas, Rithin, B. Nambiar, C.P. Dheeshith, K. Abhijith and Rathishchandra R. Gatti 21.1 Introduction 349 21.2 Scope 350 21.3 Advantages 351 21.4 Disadvantages 352 21.5 Applications 352 21.6 Automation in Agriculture 354 21.7 Precision Agriculture 356 21.8 Conclusion 357 References 357 Index 359

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Book SynopsisOBJECT DETECTION BY STEREO VISION IMAGES Since both theoretical and practical aspects of the developments in this field of research are explored, including recent state-of-the-art technologies and research opportunities in the area of object detection, this book will act as a good reference for practitioners, students, and researchers. Current state-of-the-art technologies have opened up new opportunities in research in the areas of object detection and recognition of digital images and videos, robotics, neural networks, machine learning, stereo vision matching algorithms, soft computing, customer prediction, social media analysis, recommendation systems, and stereo vision. This book has been designed to provide directions for those interested in researching and developing intelligent applications to detect an object and estimate depth. In addition to focusing on the performance of the system using high-performance computing techniques, a technical overview of certain tools, languages,Table of ContentsPreface xiii 1 Data Conditioning for Medical Imaging 1 Shahzia Sayyad, Deepti Nikumbh, Dhruvi Lalit Jain, Prachi Dhiren Khatri, Alok Saratchandra Panda and Rupesh Ravindra Joshi 1.1 Introduction 2 1.2 Importance of Image Preprocessing 2 1.3 Introduction to Digital Medical Imaging 3 1.3.1 Types of Medical Images for Screening 4 1.3.1.1 X-rays 4 1.3.1.2 Computed Tomography (CT) Scan 4 1.3.1.3 Ultrasound 4 1.3.1.4 Magnetic Resonance Imaging (MRI) 5 1.3.1.5 Positron Emission Tomography (PET) Scan 5 1.3.1.6 Mammogram 5 1.3.1.7 Fluoroscopy 5 1.3.1.8 Infrared Thermography 6 1.4 Preprocessing Techniques of Medical Imaging Using Python 6 1.4.1 Medical Image Preprocessing 6 1.4.1.1 Reading the Image 7 1.4.1.2 Resizing the Image 7 1.4.1.3 Noise Removal 8 1.4.1.4 Filtering and Smoothing 9 1.4.1.5 Image Segmentation 11 1.5 Medical Image Processing Using Python 13 1.5.1 Medical Image Processing Methods 16 1.5.1.1 Image Formation 17 1.5.1.2 Image Enhancement 19 1.5.1.3 Image Analysis 19 1.5.1.4 Image Visualization 19 1.5.1.5 Image Management 19 1.6 Feature Extraction Using Python 20 1.7 Case Study on Throat Cancer 24 1.7.1 Introduction 24 1.7.1.1 HSI System 25 1.7.1.2 The Adaptive Deep Learning Method Proposed 25 1.7.2 Results and Findings 27 1.7.3 Discussion 28 1.7.4 Conclusion 29 1.8 Conclusion 29 References 30 Additional Reading 31 Key Terms and Definition 32 2 Detection of Pneumonia Using Machine Learning and Deep Learning Techniques: An Analytical Study 33 Shravani Nimbolkar, Anuradha Thakare, Subhradeep Mitra, Omkar Biranje and Anant Sutar 2.1 Introduction 33 2.2 Literature Review 35 2.3 Learning Methods 41 2.3.1 Machine Learning 41 2.3.2 Deep Learning 42 2.3.3 Transfer Learning 42 2.4 Detection of Lung Diseases Using Machine Learning and Deep Learning Techniques 43 2.4.1 Dataset Description 43 2.4.2 Evaluation Platform 44 2.4.3 Training Process 44 2.4.4 Model Evaluation of CNN Classifier 46 2.4.5 Mathematical Model 47 2.4.6 Parameter Optimization 47 2.4.7 Performance Metrics 50 2.5 Conclusion 52 References 53 3 Contamination Monitoring System Using IOT and GIS 57 Kavita R. Singh, Ravi Wasalwar, Ajit Dharmik and Deepshikha Tiwari 3.1 Introduction 58 3.2 Literature Survey 58 3.3 Proposed Work 60 3.4 Experimentation and Results 61 3.4.1 Experimental Setup 61 3.5 Results 64 3.6 Conclusion 70 Acknowledgement 71 References 71 4 Video Error Concealment Using Particle Swarm Optimization 73 Rajani P. K. and Arti Khaparde 4.1 Introduction 74 4.2 Proposed Research Work Overview 75 4.3 Error Detection 75 4.4 Frame Replacement Video Error Concealment Algorithm 77 4.5 Research Methodology 77 4.5.1 Particle Swarm Optimization 78 4.5.2 Spatio-Temporal Video Error Concealment Method 78 4.5.3 Proposed Modified Particle Swarm Optimization Algorithm 79 4.6 Results and Analysis 83 4.6.1 Single Frame With Block Error Analysis 85 4.6.2 Single Frame With Random Error Analysis 86 4.6.3 Multiple Frame Error Analysis 88 4.6.4 Sequential Frame Error Analysis 91 4.6.5 Subjective Video Quality Analysis for Color Videos 93 4.6.6 Scene Change of Videos 94 4.7 Conclusion 95 4.8 Future Scope 97 References 97 5 Enhanced Image Fusion with Guided Filters 99 Nalini Jagtap and Sudeep D. Thepade 5.1 Introduction 100 5.2 Related Works 100 5.3 Proposed Methodology 102 5.3.1 System Model 102 5.3.2 Steps of the Proposed Methodology 104 5.4 Experimental Results 104 5.4.1 Entropy 104 5.4.2 Peak Signal-to-Noise Ratio 105 5.4.3 Root Mean Square Error 107 5.4.3.1 Qab/f 108 5.5 Conclusion 108 References 109 6 Deepfake Detection Using LSTM-Based Neural Network 111 Tejaswini Yesugade, Shrikant Kokate, Sarjana Patil, Ritik Varma and Sejal Pawar 6.1 Introduction 111 6.2 Related Work 112 6.2.1 Deepfake Generation 112 6.2.2 LSTM and CNN 112 6.3 Existing System 113 6.3.1 AI-Generated Fake Face Videos by Detecting Eye Blinking 113 6.3.2 Detection Using Inconsistence in Head Pose 113 6.3.3 Exploiting Visual Artifacts 113 6.4 Proposed System 114 6.4.1 Dataset 114 6.4.2 Preprocessing 114 6.4.3 Model 115 6.5 Results 117 6.6 Limitations 119 6.7 Application 119 6.8 Conclusion 119 References 119 7 Classification of Fetal Brain Abnormalities with MRI Images: A Survey 121 Kavita Shinde and Anuradha Thakare 7.1 Introduction 121 7.2 Related Work 123 7.3 Evaluation of Related Research 129 7.4 General Framework for Fetal Brain Abnormality Classification 129 7.4.1 Image Acquisition 130 7.4.2 Image Pre-Processing 130 7.4.2.1 Image Thresholding 130 7.4.2.2 Morphological Operations 131 7.4.2.3 Hole Filling and Mask Generation 131 7.4.2.4 MRI Segmentation for Fetal Brain Extraction 132 7.4.3 Feature Extraction 132 7.4.3.1 Gray-Level Co-Occurrence Matrix 133 7.4.3.2 Discrete Wavelet Transformation 133 7.4.3.3 Gabor Filters 134 7.4.3.4 Discrete Statistical Descriptive Features 134 7.4.4 Feature Reduction 134 7.4.4.1 Principal Component Analysis 135 7.4.4.2 Linear Discriminant Analysis 136 7.4.4.3 Non-Linear Dimensionality Reduction Techniques 137 7.4.5 Classification by Using Machine Learning Classifiers 137 7.4.5.1 Support Vector Machine 138 7.4.5.2 K-Nearest Neighbors 138 7.4.5.3 Random Forest 139 7.4.5.4 Linear Discriminant Analysis 139 7.4.5.5 Naïve Bayes 139 7.4.5.6 Decision Tree (DT) 140 7.4.5.7 Convolutional Neural Network 140 7.5 Performance Metrics for Research in Fetal Brain Analysis 141 7.6 Challenges 142 7.7 Conclusion and Future Works 142 References 143 8 Analysis of COVID-19 Data Using Machine Learning Algorithm 147 Chinnaiah Kotadi, Mithun Chakravarthi K., Srihari Chintha and Kapil Gupta 8.1 Introduction 147 8.2 Pre-Processing 148 8.3 Selecting Features 149 8.4 Analysis of COVID-19–Confirmed Cases in India 152 8.4.1 Analysis to Highest COVID-19–Confirmed Case States in India 153 8.4.2 Analysis to Highest COVID-19 Death Rate States in India 153 8.4.3 Analysis to Highest COVID-19 Cured Case States in India 154 8.4.4 Analysis of Daily COVID-19 Cases in Maharashtra State 155 8.5 Linear Regression Used for Predicting Daily Wise COVID- 19 Cases in Maharashtra 156 8.6 Conclusion 157 References 157 9 Intelligent Recommendation System to Evaluate Teaching Faculty Performance Using Adaptive Collaborative Filtering 159 Manish Sharma and Rutuja Deshmukh 9.1 Introduction 160 9.2 Related Work 162 9.3 Recommender Systems and Collaborative Filtering 164 9.4 Proposed Methodology 165 9.5 Experiment Analysis 167 9.6 Conclusion 168 References 168 10 Virtual Moratorium System 171 Manisha Bhende, Muzasarali Badger, Pranish Kumbhar, Vedanti Bhatkar and Payal Chavan 10.1 Introduction 172 10.1.1 Objectives 172 10.2 Literature Survey 172 10.2.1 Virtual Assistant—BLU 172 10.2.2 HDFC Ask EVA 173 10.3 Methodologies of Problem Solving 173 10.4 Modules 174 10.4.1 Chatbot 174 10.4.2 Android Application 175 10.4.3 Web Application 175 10.5 Detailed Flow of Proposed Work 176 10.5.1 System Architecture 176 10.5.2 DFD Level 1 177 10.6 Architecture Design 178 10.6.1 Main Server 178 10.6.2 Chatbot 178 10.6.3 Database Architecture 180 10.6.4 Web Scraper 180 10.7 Algorithms Used 181 10.7.1 AES-256 Algorithm 181 10.7.2 Rasa NLU 181 10.8 Results 182 10.9 Discussions 183 10.9.1 Applications 183 10.9.2 Future Work 183 10.9.3 Conclusion 183 References 183 11 Efficient Land Cover Classification for Urban Planning 185 Vandana Tulshidas Chavan and Sanjeev J. Wagh 11.1 Introduction 185 11.2 Literature Survey 189 11.3 Proposed Methodology 191 11.4 Conclusion 192 References 192 12 Data-Driven Approches for Fake News Detection on Social Media Platforms: Review 195 Pradnya Patil and Sanjeev J. Wagh 12.1 Introduction 196 12.2 Literature Survey 196 12.3 Problem Statement and Objectives 201 12.3.1 Problem Statement 201 12.3.2 Objectives 201 12.4 Proposed Methodology 202 12.4.1 Pre-Processing 202 12.4.2 Feature Extraction 203 12.4.3 Classification 203 12.5 Conclusion 204 References 204 13 Distance Measurement for Object Detection for Automotive Applications Using 3D Density-Based Clustering 207 Anupama Patil, Manisha Bhende, Suvarna Patil and P. P. Shevatekar 13.1 Introduction 208 13.2 Related Work 210 13.3 Distance Measurement Using Stereo Vision 213 13.3.1 Calibration of the Camera 215 13.3.2 Stereo Image Rectification 215 13.3.3 Disparity Estimation and Stereo Matching 216 13.3.4 Measurement of Distance 217 13.4 Object Segmentation in Depth Map 218 13.4.1 Formation of Depth Map 218 13.4.2 Density-Based in 3D Object Grouping Clustering 218 13.4.3 Layered Images Object Segmentation 219 13.4.3.1 Image Layer Formation 221 13.4.3.2 Determination of Object Boundaries 222 13.5 Conclusion 223 References 224 14 Real-Time Depth Estimation Using BLOB Detection/ Contour Detection 227 Arokia Priya Charles, Anupama V. Patil and Sunil Dambhare 14.1 Introduction 227 14.2 Estimation of Depth Using Blob Detection 229 14.2.1 Grayscale Conversion 230 14.2.2 Thresholding 231 14.2.3 Image Subtraction in Case of Input with Background 232 14.2.3.1 Preliminaries 233 14.2.3.2 Computing Time 234 14.3 Blob 234 14.3.1 BLOB Extraction 234 14.3.2 Blob Classification 235 14.3.2.1 Image Moments 236 14.3.2.2 Centroid Using Image Moments 238 14.3.2.3 Central Moments 238 14.4 Challenges 241 14.5 Experimental Results 241 14.6 Conclusion 251 References 255 Index 257

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Book SynopsisTable of ContentsPreface xv 1 Overview of Digital Twin 1 Manisha Vohra 1.1 A Simplistic Introduction to Digital Twin 1 1.2 Basic Definition and Explanation of What is Digital Twin 5 1.3 The History of Digital Twin 7 1.4 Working 9 1.5 Features 11 1.5.1 Replication of Each and Every Aspect of the Original Device or Product 11 1.5.2 Helps in Product Lifecycle Management 11 1.5.3 Digital Twin can Prevent Downtime 11 1.6 Advantages of Digital Twin 11 1.6.1 Digital Twin is Helpful in Preventing Issues or Errors in the Actual Object, Product or Process 11 1.6.2 Helps in Well Utilization of Resources 12 1.6.3 Keeping Vigilance of the Actual Object, Product or Process Through Digital Twin is Possible 12 1.6.4 Helps in Efficient Handling and Managing of Objects, Device, Equipment, etc. 12 1.6.5 Reduction in Overall Cost of Manufacturing of Objects, Products, etc. 13 1.7 Applications 13 1.8 A Simple Example of Digital Twin Application 13 1.9 Digital Twin Technology and the Metaverse 14 1.10 Challenges 15 1.10.1 Careful Handling of Different Factors Involved in Digital Twin 15 1.10.2 Expertise Required 15 1.10.3 Data Security and Privacy 15 1.11 Conclusion 16 References 16 2 Introduction, History, and Concept of Digital Twin 19 N. Rajamurugu and M. K. Karthik 2.1 Introduction 19 2.2 History of Digital Twin 21 2.3 Concept of Digital Twin 23 2.3.1 DTP 23 2.3.2 DTI 24 2.3.3 DTE 24 2.3.4 Conceptualization 25 2.3.5 Comparison 25 2.3.6 Collaboration 25 2.4 Working Principle 26 2.5 Characteristics of Digital Twin 27 2.5.1 Homogenization 27 2.5.2 Digital Trail 27 2.5.3 Connectivity 27 2.6 Advantages 28 2.6.1 Companies Can Benefit From Digital Twin by Tracking Performance-Related Data 28 2.6.2 Different Sector’s Progress Can Be Accelerated 28 2.6.3 Digital Twins Can Be Used for Various Application 28 2.6.4 Digital Twin Can Help Decide Future Course of Work 28 2.6.5 Manufacturing Work Can Be Monitored 29 2.7 Limitations 29 2.7.1 Data Transmission Could Have Delays and Distortions 29 2.7.2 Digital Twin Implementation Will Need Required Skills and Sound Knowledge About It 29 2.8 Example of Digital Twin Application 29 2.8.1 Digital Twin Application in General Electric (GE) Renewable Energy 29 2.9 Conclusion 30 References 30 3 An Insight to Digital Twin 33 Anant Kumar Patel, Ashish Patel and Kanchan Mona Patel 3.1 Introduction 33 3.2 Understanding Digital Twin 35 3.3 Digital Twin History 36 3.4 Essential Aspects From Working Perspectives of Digital Twin 37 3.5 How Does a Digital Twin Work? 37 3.6 Insights to Digital Twin Technology Concept 38 3.6.1 Parts Twins 38 3.6.2 Product Twins 39 3.6.3 System Twins 39 3.6.4 Process Twins 39 3.7 Types of Digital Twin 39 3.7.1 Digital Twin Prototype (DTP) 40 3.7.2 Digital Twin Instance (DTI) 40 3.7.3 Digital Twin Environment (DTE) 40 3.8 Traits of Digital Twin 40 3.8.1 Look Same as the Original Object 40 3.8.2 Consists Different Details of the Original Object 41 3.8.3 Behaves Same as the Original Object 41 3.8.4 Can Predict and Inform in Advance About Problems That Could Occur 41 3.9 Value of Digital Twin 41 3.10 Advantages of Digital Twin 42 3.11 Real-World Examples of Use of Digital Twin 43 3.12 Conclusion 44 References 45 4 Digital Twin Solution Architecture 47 Suhas D. Joshi 4.1 Introduction 47 4.2 Previous Work 48 4.2.1 How This Work Differs 49 4.3 Use Cases 50 4.4 Architecture Considerations 51 4.5 Understanding the Physical Object 52 4.5.1 Modeling Considerations 55 4.6 Digital Twin and IoT 56 4.7 Digital Twin Solution Architecture 57 4.7.1 Conceptual Digital Twin Solution Architecture 57 4.7.2 Infrastructure Platform and IoT Services 57 4.7.3 Digital Twin Data and Process Model 57 4.7.4 Digital Twin Services 60 4.7.5 Digital Twin Applications 61 4.7.6 Sample Basic Data Flow through Digital Twin 61 4.7.7 Sample Data Flow for Exception Handling 63 4.7.8 Sample Data Flow through Digital Twin Applications 63 4.7.9 Development Considerations 65 4.8 Database Considerations 66 4.9 Messaging 67 4.10 Interfaces 69 4.11 User Experience 70 4.12 Cyber Security 70 4.13 Use Case Coverage 71 4.14 Future Direction and Trends 73 4.15 Conclusion 74 References 74 5 Role of Digital Twin Technology in Medical Sector—Toward Ensuring Safe Healthcare 77 S.N. Kumar, A. Lenin Fred, L.R. Jonisha Miriam, Christina Jane I., H. Ajay Kumar, Parasuraman Padmanabhan and Balazs Gulyas 5.1 Introduction to Digital Twin 78 5.2 Generic Applications of Digital Twin 79 5.3 Digital Twin Applications in Medical Field 83 5.3.1 Biosignal and Physiological Parameters Analysis for Body Area Network 84 5.3.2 Medicinal Drug Delivery 85 5.3.3 Surgical Preplanning 86 5.3.4 COVID 19 Screening and Diagnosis 87 5.4 Ongoing and Future Applications of Digital Twin in Healthcare Sector 89 5.5 Conclusion 89 Acknowledgments 90 References 90 6 Digital Twin as a Revamping Tool for Construction Industry 97 Greeshma A. S. and Philbin M. Philip 6.1 Introduction 97 6.2 Introduction to Digital Twin 99 6.3 Overview of Digital Twin in Construction 100 6.4 The Perks of Digital Twin 101 6.5 The Evolution of Digital Twin 102 6.6 Application of Digital Twin Technology in Construction Industry 103 6.7 Digital Twins Application for Construction Working Personnel Safety 106 6.8 Digital Twin Applications in Smart City Construction 107 6.9 Discussion 107 6.10 Conclusion 108 References 109 7 Digital Twin Applications and Challenges in Healthcare 111 Pavithra S., Pavithra D., Vanithamani R. and Judith Justin 7.1 Introduction 111 7.2 Digital Twin 112 7.3 Applications of Digital Twin 114 7.3.1 Smart Cities 114 7.3.2 Manufacturing Sector 115 7.3.3 Healthcare 115 7.3.4 Aviation 115 7.3.5 The Disney Park 115 7.4 Challenges with Digital Twin 115 7.5 Digital Twin in Healthcare 116 7.5.1 Digital Twin for Hospital Workflow Management 116 7.5.2 Digital Twin for a Healthcare Facility 117 7.5.3 Digital Twin for Different Medical Product Manufacturing 118 7.5.4 Cardiovascular Digital Twin 118 7.5.5 Digital Twin Utilization for Supporting Personalized Treatment 119 7.5.6 Digital Twin for Multiple Sclerosis (MS) 119 7.6 Digital Twin Challenges in Healthcare 119 7.6.1 Need of Training and Knowledge 120 7.6.2 Cost Factor 120 7.6.3 Trust Factor 120 7.7 Conclusion 121 References 122 8 Monitoring Structural Health Using Digital Twin 125 Samaya Pillai, Venkatesh Iyengar and Pankaj Pathak 8.1 Introduction 126 8.1.1 Digital Twin—The Approach and Uses 126 8.2 Structural Health Monitoring Systems (SHMS) 128 8.2.1 Criticality and Need for SHMS Approach 128 8.2.2 Passive and Active SHMS 129 8.3 Sensor Technology, Digital Twin (DT) and Structural Health Monitoring Systems (SHMS) 130 8.4 Conclusion 135 References 136 9 Role and Advantages of Digital Twin in Oil and Gas Industry 141 Prakash J. 9.1 Introduction 141 9.2 Digital Twin 142 9.3 Evolution of Digital Twin Technology 144 9.4 Various Digital Twins that Can Be Built 145 9.4.1 Parts Twins 145 9.4.2 Product Twins or Asset Twins 146 9.4.3 System Twins or Unit Twins 146 9.4.4 Process Twins 146 9.5 Advantage of Digital Twin 146 9.5.1 Paced Prototypin 147 9.5.2 Prediction 147 9.5.3 Enhanced Maintenance 147 9.5.4 Monitoring 147 9.5.5 Safety 147 9.5.6 Reduced Waste 147 9.6 Applications of Digital Twin 148 9.6.1 Aerospace 148 9.6.2 Power-Generation Equipment 148 9.6.3 Structures and Their Systems 148 9.6.4 Manufacturing Operations 149 9.6.5 Healthcare Services 149 9.6.6 Automotive Industry 149 9.6.7 Urban Planning and Construction 149 9.6.8 Smart Cities 149 9.6.9 Industrial Applications 149 9.7 Characteristics of Digital Twin 150 9.7.1 High-Fidelity 150 9.7.2 Lively 150 9.7.3 Multidisciplinary 150 9.7.4 Homogenization 150 9.7.5 Digital Footprint 151 9.8 Digital Twin in Oil and Gas Industry 151 9.9 Role of Digital Twin in the Various Areas of Oil and Gas Industry 152 9.9.1 Planning of Drilling Process 153 9.9.2 Performance Monitoring of Oil Field 153 9.9.3 Data Analytics and Simulation for Oil Field Production 153 9.9.4 Improving Field Personnel and Workforce Safety 153 9.9.5 Predictive Maintenance 153 9.10 The Advantages of Digital Twin in the Oil and Gas Industry 154 9.10.1 Production Efficacy 154 9.10.2 Preemptive Maintenance 154 9.10.3 Scenario Development 154 9.10.4 Different Processes Monitoring 155 9.10.5 Compliance Criteria 155 9.10.6 Cost Savings 155 9.10.7 Workplace Safety 155 9.11 Conclusion 155 References 156 10 Digital Twin in Smart Cities: Application and Benefits 159 Manisha Vohra 10.1 Introduction 159 10.2 Introduction of Digital Twin in Smart Cities 162 10.3 Applications of Digital Twin in Smart Cities 164 10.3.1 Traffic Management 164 10.3.2 Construction 165 10.3.3 Structural Health Monitoring 166 10.3.4 Healthcare 167 10.3.5 Digital Twin for Drainage System 168 10.3.6 Digital Twin for Power Grid 169 10.4 Conclusion 169 References 170 11 Digital Twin in Pharmaceutical Industry 173 Anant Kumar Patel, Ashish Patel and Kanchan Mona Patel 11.1 Introduction 173 11.2 What is Digital Twin? 175 11.2.1 Digital Twin Prototype (DTP) 176 11.2.2 Digital Twin Instance 176 11.2.3 Parts Twins 177 11.2.4 Product Twins 177 11.2.5 System Twins 177 11.2.6 Process Twins 178 11.3 Digital Twin in the Pharmaceutical Industry 178 11.4 Digital Twin Applications in Pharmaceutical Industry 180 11.4.1 Digital Twin of the Pharmaceutical Manufacturing Process 180 11.4.2 Digital Twin for Pharmaceutical Supply Chains 180 11.5 Examples of Use of Digital Twin in Pharmaceutical Industry 181 11.5.1 Digital Twin Simulator for Supporting Scientific Exchange of Views With Expert Physicians 181 11.5.2 Digital Twin for Medical Products 182 11.5.3 Digital Twin for Pharmaceutical Companies 182 11.6 Advantages of Digital Twin in the Pharmaceutical Industry 182 11.6.1 Wastage Can Be Reduced 182 11.6.2 Cost Savings 183 11.6.3 Faster Time to Market 183 11.6.4 Smooth Management 183 11.6.5 Remote Monitoring 184 11.7 Digital Twin in the Pharmaceutical Industry as a Game-Changer 184 11.8 Conclusion 184 References 185 12 Different Applications and Importance of Digital Twin 189 R. Suganya, Seyed M. Buhari and S. Rajaram 12.1 Introduction 189 12.2 History of Digital Twin 191 12.3 Applications of Digital Twin 192 12.3.1 Agriculture 193 12.3.2 Education 193 12.3.3 Healthcare 194 12.3.4 Manufacturing and Industry 195 12.3.5 Automotive Industry 197 12.3.6 Security 198 12.3.7 Smart Cities 199 12.3.8 Weather Forecasting and Meteorology 199 12.4 Importance of Digital Twin 199 12.5 Challenges 200 12.6 Conclusion 200 References 201 13 Digital Twin in Development of Products 205 Pedro Pablo Chambi Condori 13.1 Introduction 206 13.2 Digital Twin 207 13.2.1 Digital Twin Types 210 13.3 Different Aspects of an Organization and Digital Twin in Development of Products in Organizations 210 13.4 Implications of Digital Twin in Development of Products in Organizations 214 13.5 Advantages 214 13.5.1 Digital Twin Helps in Decision Making 214 13.5.2 Avoiding Downtine 215 13.5.3 Maximizing Efficiency 215 13.5.4 Cost Savings 215 13.5.5 Optimum Use of Resources 215 13.6 Conclusion 215 References 216 14 Possibilities with Digital Twin 219 Vismay Shah and Anilkumar Suthar 14.1 Introduction 219 14.2 What is Digital Twin Technology? 220 14.3 Possibilities With Digital Twin in Aviation Sector 224 14.3.1 Aviation Engineering in Combination With Digital Twin 224 14.3.2 Concept of Digital Twin for Aviation Components 225 14.3.3 How Important is Digital Twin in the Aviation Industry? 225 14.4 Possibilities With Digital Twin in Automotive Industry 226 14.4.1 Digital Twin in Automotive Industry 226 14.5 How Can Digital Twin Help in Improving Supply Chain Management? 228 14.6 Discussion 229 14.7 Conclusion 229 References 229 15 Digital Twin: Pros and Cons 233 Prakash J. 15.1 Introduction 233 15.2 Introduction to Digital Twin 234 15.3 Pros of Digital Twin 238 15.3.1 Digital Twin Can Forecast the Problem in Advance Before Its Arrival 238 15.3.2 Digital Twin Can Be Used in Monitoring Work 239 15.3.3 Reduction in Waste 240 15.3.4 Helps Avoid Hazardous Situations at Work 240 15.3.5 Increases Speed of Work Completion 240 15.4 Cons of Digital Twin 240 15.4.1 Deep Knowledge Will Be Needed for Creating and Handling the Digital Twin 241 15.4.2 Issues with Sensors Issue Can Affect the Digital Twin 241 15.4.3 Security 241 15.5 Application Wise Pros of Digital Twin 241 15.5.1 Oil and Gas Sector 242 15.5.2 Industrial Sector 242 15.5.3 Automotive Sector 242 15.5.4 Construction Sector 242 15.6 Conclusion 243 References 243 Index 247

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Book SynopsisProvides students with clear and up-to-date coverage of the various areas associated with representations of diversity within the mass media Diversity in U.S. Mass Media is designed to help undergraduate and graduate students deepen the conversations around diversity, equity, and inclusion in the media industries. Identifying consistencies and differences in representations of social identity groups in the United States, this comprehensive textbook critically examines a wide range of issues surrounding media portrayals of race, ethnicity, gender, sexual orientation, disability, age, class, and religion. Throughout the text, students are encouraged to contextualize various issues, place one social group within the framework of others, and consider how diverse communities inform and intersect with each other. Now in its third edition, Diversity in U.S. Mass Media addresses ongoing problematic portrayals, highlights recent progress, presents new research studies and observations, and offers innovative approaches for promoting positive change across the media landscape. Two entirely new chapters explore the ways identity-based social movements, Artificial Intelligence (AI), gaming, social media, and social activism construct, challenge, and defend representations of different groups. Updated references and new examples of social group depictions in streaming services and digital media are accompanied by expanded discussion of intersectionality, social activism, creating inclusive learning and working environments, media depictions of mixed-race individuals and couples, and more. Offering fresh insights into the contemporary issues surrounding depictions of social groups in films, television, and the press, Diversity in U.S. Mass Media: Examines the historical evolution and current media depictions of American Indians, African Americans, Latino/Hispanic Americans, Arab Americans, and Asian AmericansHelps prepare students in Journalism and Mass Communication programs to work in diverse teamsCovers the theoretical foundations of research in mass media representations, including social comparison theory and feminist theoryContains a wealth of real-world examples illustrating the concepts and perspectives discussed in each chapterIncludes access to an instructor's website with a test bank, viewing list, exercises, sample syllabi, and other useful pedagogical tools Diversity in U.S. Mass Media, Third Edition, remains an ideal textbook for upper-level undergraduate and graduate courses in Media Communication, Film and Television Studies, Journalism, American Studies, Entertainment and Media Research, and Diversity, Equity, and Inclusion (DEI).

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Book Synopsis

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