Electronics and communications engineering Books

Book SynopsisThis book discusses modern-day Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) and future trends of transistor devices. This bookprovides an overview of Field Effect Transistors (FETs)by discussing the basic principles ofFETs andexploring the latest technological developments in the field.It covers and connects a wide spectrum of topics related to semiconductor device physics, physics of transistors, and advanced transistor concepts. This book containssix chapters. Chapter 1 discusses electronic materials and charge. Chapter 2 examines junctions, discusses contacts under thermal-equilibrium, metal-semiconductor contacts, and metal-insulator-semiconductor systems. Chapter 3 covers traditional planar Metal Oxide Semiconductor Field Effect Transistors (MOSFETs). Chapter 4 describes scaling-driving technological variationsandnovel dimensions of MOSFETs. Chapter 5 analyzes Heterojunction Field Effect Transistors (FETs) and also discusses the challenges and rewaTable of ContentsIntroduction xi 1 Electronic Materials and Charge Transport 1 1.1 Wave/Particle Electrons in Solids 1 1.1.1 Quantum Description of Electrons 3 1.1.2 Band Diagram and Effective-Mass Formalism 6 1.1.3 Density of States Function 7 1.1.4 Conduction and Valence Bands 8 1.1.5 Band Diagram and Free Charge Carriers 10 1.1.6 Supplementary Notes on Band Diagram 11 1.1.7 Bond Model 14 1.2 Electrons, Holes, and Doping in Semiconductors 14 1.2.1 Electrons and Holes 14 1.2.2 Doping 18 1.2.3 Calculation of Ionization Energies in Semiconductors 24 1.3 Thermal-Equilibrium Statistics 25 1.3.1 Fermi–Dirac Statistics 25 1.3.2 Maxwell–Boltzmann Statistics 27 1.3.3 Calculating Electron and Hole Concentration in Nondegenerate Semiconductors 29 1.3.4 Mass Action Law 31 1.3.5 Calculation of Electron and Hole Concentration in a Degenerate Semiconductor 33 1.3.6 Quasi-Fermi Levels 35 1.3.7 Statistics of Dopant Activation Process 35 1.4 Charge-Carrier Transport in Semiconductors 37 1.4.1 Current-Continuity Equation 39 1.4.2 Drift–Diffusion Formalism 40 1.4.3 Characterization of Low Electric-Field Transport Parameters 53 1.4.4 High Electric-Field Drift Transport 54 1.4.5 Thermionic and Field Emission 61 1.5 Breakdown in Semiconductors 66 1.6 Crystallinity and Semiconductor Materials 69 1.6.1 Bravais Lattices 71 1.6.2 Strain and Techniques of Epitaxy 78 1.7 Quantum Transport Phenomena and Scattering Mechanisms in Semiconductors 89 1.7.1 Quantum Phenomena in Carrier Transport: A Snapshot 90 1.7.2 Drude’s Model: A Close-UP 91 1.7.3 Major Scattering Processes 95 Further Reading 109 Solid-State Theory 109 Physics of Semiconductor Devices 109 Semiconductor Materials and Heterostructures 109 Problems 110 Appendix 1.A Derivation of Fermi–Dirac Statistics 111 Further Reading 114 Appendix 1.B Derivation of Einstein Relationship in Degenerate Semiconductors 114 Further Reading 115 Appendix 1.C Strain Tensor 116 2 Junctions 119 2.1 Contacts Under Thermal Equilibrium 119 2.2 Metal–Semiconductor Contacts 121 2.2.1 Band Diagram of an MS Junction 122 2.2.2 SDA 127 2.3 P–N Junctions 149 2.3.1 Thermal-Equilibrium Band Diagram of P–N Junctions 149 2.3.2 Calculation of Potential across P–N Junctions and SDA 151 2.4 Metal–Insulator–Semiconductor System 188 2.4.1 Thermal-Equilibrium Band Diagram of MOS System 189 2.4.2 Biased MOS System 192 2.4.3 Threshold-Voltage Adjustment and Calculations 200 2.4.4 C–V Characteristic of MOS Systems 208 2.5 Current Conduction in the Presence of Band Discontinuities in Junctions 216 2.5.1 Thermionic Emission 216 2.5.2 Field Emission and Thermionic-Field Emission 224 Further Reading 227 Physics of Semiconductor Devices 227 Problems 228 Appendix 2.A Limitations of SDA and the Meaning of Debye Length 229 3 Traditional Planar MOSFETs: Operation, Modeling, and Technology Scaling 231 3.1 Battle of Transistors: MOSFET Versus BJT 232 3.2 Principles of Operation of MOSFETs and Device Modeling: First-Order Principles 236 3.2.1 Modeling of the Operation of Long-Channel MOSFET 238 3.2.2 Modeling of the Operation of Short-Channel MOSFET 250 3.3 Quantum Confinement and Electrostatics of MOSFET 282 3.4 Subthreshold Operation of Short-Channel MOSFET 285 3.5 Limits of Scaling: A Recap 290 Reference 291 Further Reading 291 Physics of Semiconductor Devices 292 Microfabrication Technology and Material Characterization 292 Problems 292 4 From Scaling-Driven Technological Variations to Novel Dimensions in MISFETs 295 4.1 FinFET, UTBSOI, and Other Multiple-Gate FETs 296 4.1.1 Quantitative Assessment of the Advantages of SOI and Multiple-Gate MOSFETs 301 4.1.2 Multiple-Gate MOSFETs: A Complementary Perspective on the Implementation and Physics of Operation 306 4.1.3 Strain Engineering: From Bulk to Multiple-Gate MOSFETs 313 4.1.4 Limitations of the Introduction of III–V Channels to Multiple-Gate and Other Modern CMOS Technologies 320 4.2 Velocity-Modulation Transistor 321 4.2.1 VMT: Basic Principles of Operation 322 4.2.2 Real-Space Transfer: Speed and Functionality 325 4.3 Resonant-Gate and Resonant-Channel Transistors 333 4.3.1 Resonant-Gate Transistor: Principles of Operation 336 4.3.2 Resonant-Channel Transistor: Principles of Operation 343 4.4 Carbon Nanotube FET and FETs Realized on Other Nanotube and Nanowires 346 4.4.1 CNFETs versus MOSFETs: Differences in Principles of Operation and Realization 348 4.4.2 Other Nanotube and Nanowire Transistors 363 4.5 spinFET 365 4.5.1 spinFET: Principles of Operation 365 4.5.2 spinFET: Challenges in Realization 368 References 372 Further Reading 372 Problems 373 5 Heterojunction FETs 375 5.1 Challenges and Rewards of Heteroepitaxy 377 5.1.1 Lattice Matching and the Substrate Challenge 379 5.1.2 Properties of a Few Famous Nonpolar Heterostructures: A Brief Visit 380 5.2 Quantum Phenomena in Semiconductor Heterostructures 385 5.2.1 Electron Behavior in a Triangular Quantum Well 389 5.2.2 Subbands and Two-Dimensional Electron Gas 391 5.2.3 Semiconductor Heterojunctions and Self-Consistent Evaluation 392 5.2.4 Modulation Doping 394 5.3 HFET: Brief Exposé of Design Intricacies 400 5.3.1 Deep Donors and Modulation Doping 407 5.3.2 Threshold-Voltage Calculation in HFET 409 5.3.3 HFET: A Brief Visit to Microfabrication Challenges 414 5.3.4 Hot Electron Applications Among HFETs 416 5.4 Polar III-Nitride HFET 417 5.4.1 Polarization Among III-Nitride Heterostructures 418 5.4.2 Subband Energy Levels and 2DEG Characteristics of Polar AlGaN/GaN Heterojunctions 422 References 427 Further Reading 427 Physics of Heterostructures and High-Speed Transistors 427 Material Properties and Processing of Semiconductor Materials and Heterostructures 427 Problems 428 6 FETs at Molecular Scales 429 6.1 FET: A Change of Paradigm 430 6.2 Resistance Redefined 431 6.3 Evaluation of Current–Voltage Characteristics of a Single Energy-Level Channel FET 440 6.4 From Current Conduction in Single Energy-Level Channels to Definition of Conductance in Macroscale Conductors 444 Further Reading 448 Index 449

Read more less

Book SynopsisA comprehensive reference of the latest developments in MV drive technology in the area of power converter topologies This new edition reflects the recent technological advancements in the MV drive industry, such as advanced multilevel converters and drive configurations. It includes three new chapters, Control of Synchronous Motor Drives, Transformerless MV Drives, and Matrix Converter Fed Drives. In addition, there are extensively revised chapters on Multilevel Voltage Source Inverters and Voltage Source Inverter-Fed Drives. This book includes a systematic analysis on a variety of high-power multilevel converters, illustrates important concepts with simulations and experiments, introduces various megawatt drives produced by world leading drive manufacturers, and addresses practical problems and their mitigations methods. This new edition: Provides an in-depth discussion and analysis of various control schemes for the MV synchronous motor drives Table of ContentsAbout the Authors xv Preface and Acknowledgments xvii List of Abbreviations xix Part One Introduction 1 1. Introduction 3 1.1 Overview of High-Power Drives 3 1.2 Technical Requirements and Challenges 5 1.3 Converter Configurations 8 1.4 Industrial MV Drives 11 1.5 Summary 14 References 15 Appendix 16 2. High-Power Semiconductor Devices 17 2.1 Introduction 17 2.2 High-Power Switching Devices 18 2.3 Operation of Series Connected Devices 29 2.4 Summary 32 References 33 Part Two Multipulse Diode and SCR Rectifiers 35 3. Multipulse Diode Rectifiers 37 3.1 Introduction 37 3.2 Six-Pulse Diode Rectifier 38 3.3 Series-Type Multipulse Diode Rectifiers 47 3.4 Separate-Type Multipulse Diode Rectifiers 57 3.5 Summary 62 References 63 4. Multipulse SCR Rectifiers 65 4.1 Introduction 65 4.2 Six-Pulse SCR Rectifier 65 4.3 12-Pulse SCR Rectifier 74 4.4 18- and 24-Pulse SCR Rectifiers 79 4.5 Summary 80 References 81 5. Phase-Shifting Transformers 83 5.1 Introduction 83 5.2 Y/Z Phase-Shifting Transformers 83 5.3 Δ/Z Transformers 86 5.4 Harmonic Current Cancellation 89 5.5 Summary 92 Part Three Multilevel Voltage Source Converters 93 6. Two-Level Voltage Source Inverter 95 6.1 Introduction 95 6.2 Sinusoidal PWM 95 6.3 Space Vector Modulation 101 6.4 Summary 116 References 117 7. Cascaded H-Bridge Multilevel Inverters 119 7.1 Introduction 119 7.2 H-Bridge Inverter 120 7.3 Multilevel Inverter Topologies 124 7.4 Carrier-Based PWM Schemes 128 7.5 Staircase Modulation 138 7.6 Summary 140 References 140 8. Diode-Clamped Multilevel Inverters 143 8.1 Introduction 143 8.2 Three-Level Inverter 143 8.3 Space Vector Modulation 148 8.4 Neutral-Point Voltage Control 165 8.5 Carrier-Based PWM Scheme and Neutral-Point Voltage Control 167 8.6 Other Space Vector Modulation Algorithms 169 8.7 High-Level Diode-Clamped Inverters 170 8.8 NPC/H-Bridge Inverter 174 8.9 Summary 180 References 180 Appendix 182 9. Other Multilevel Voltage Source Inverters 185 9.1 Introduction 185 9.2 Multilevel Flying-Capacitor Inverter 185 9.3 Active Neutral-Point Clamped Inverter 188 9.4 Neutral-Point Piloted Inverter 197 9.5 Nested Neutral-Point Clamped Inverter 200 9.6 Modular Multilevel Converter 209 9.7 Summary 222 References 222 Part Four PWM Current Source Converters 225 10. PWM Current Source Inverters 227 10.1 Introduction 227 10.2 PWM Current Source Inverter 228 10.3 Space Vector Modulation 237 10.4 Parallel Current Source Inverters 247 10.5 Load-Commutated Inverter (LCI) 253 10.6 Summary 254 References 255 Appendix 256 11. PWM Current Source Rectifiers 257 11.1 Introduction 257 11.2 Single-Bridge Current Source Rectifier 257 11.3 Dual-Bridge Current Source Rectifier 265 11.4 Power Factor Control 269 11.5 Active Damping Control 275 11.6 Summary 283 References 284 Appendix 285 Part Five High-Power AC Drives 287 12. Voltage Source Inverter Fed Drives 289 12.1 Introduction 289 12.2 Two-Level VSI-Based MV Drives 289 12.3 Neutral Point Clamped (NPC) Inverter Fed Drives 293 12.4 Multilevel Cascaded H-Bridge (CHB) Inverter Fed Drives 298 12.5 NPC/H-Bridge Inverter Fed Drives 302 12.6 ANPC Inverter Fed Drive 303 12.7 MMC Inverter Fed Drive 305 12.8 10 KV-Class Drives with Multilevel Converters 306 12.9 Summary 307 References 307 13. Current Source Inverter Fed Drives 309 13.1 Introduction 309 13.2 CSI Drives with PWM Rectifiers 309 13.3 Transformerless CSI Drive for Standard AC Motors 315 13.4 CSI Drive with Multipulse SCR Rectifier 316 13.5 LCI Drives for Synchronous Motors 318 13.6 Summary 320 References 320 14. Control of Induction Motor Drives 321 14.1 Introduction 321 14.2 Reference Frame Transformation 322 14.3 Induction Motor Dynamic Models 325 14.4 Principle of Field Oriented Control (FOC) 332 14.5 Direct Field Oriented Control 335 14.6 Indirect Field Oriented Control 339 14.7 FOC for CSI Fed Drives 341 14.8 Direct Torque Control 344 14.9 Summary 351 References 351 15. Control of Synchronous Motor Drives 353 15.1 Introduction 353 15.2 Modeling of Synchronous Motor 353 15.3 VSC FED SM Drive with Zero d-Axis Current (ZDC) Control 360 15.4 VSC FED SM Drive with MTPA Control 367 15.5 VSC FED SM Drive with DTC Scheme 372 15.6 Control of CSC FED SM Drives 381 15.7 Summary 390 References 390 Appendix 391 Part Six Special Topics on MV Drives 393 16. Matrix Converter Fed MV Drives 395 16.1 Introduction 395 16.2 Classic Matrix Converter (MC) 396 16.3 Three-Module Matrix Converter 401 16.4 Multi-Module Cascaded Matrix Converter (CMC) 408 16.5 Multi-Module CMC Fed MV Drive 413 16.6 Summary 415 References 415 17. Transformerless MV Drives 417 17.1 Introduction 417 17.2 Common-Mode Voltage Issues and Conventional Solution 418 17.3 CM Voltage Reduction in Multilevel VSC 422 17.4 Transformerless Drives with Multilevel VSC 434 17.5 Transformerless CSI Fed Drives 440 17.6 Summary 444 References 445 Index 447

Read more less

Book SynopsisA thorough and complete examination of LTE networks, their operating principles and key insights to performance optimization.Table of ContentsAbout the Author xvi Preface xvii Part 1 LTE Basics and Optimization Overview 1 1 LTE Basement 3 1.1 LTE Principle 3 1.1.1 LTE Architecture 6 1.1.2 LTE Network Interfaces 7 1.2 LTE Services 11 1.2.1 Circuit]Switched Fallback 12 1.2.2 Voice over LTE 13 1.2.3 IMS Centralized Services 16 1.2.4 Over the Top Solutions 16 1.2.5 SMS Alternatives over LTE 17 1.2.6 Converged Communication 19 1.3 LTE Key Technology Overview 19 1.3.1 Orthogonal Frequency Division Multiplexing 20 1.3.2 MIMO 21 1.3.3 Radio Resource Management 22 2 LTE Optimization Principle and Method 24 2.1 LTE Wireless Optimization Overview 24 2.1.1 Why LTE Wireless Optimization 24 2.1.2 Characters of LTE Optimization 24 2.1.3 LTE Joint Optimization with 2G/3G 25 2.1.4 Optimization Target 25 2.2 LTE Optimization Procedure 26 2.2.1 Optimization Procedure Overview 26 2.2.2 Collection of Mass Nerwork Measurement Data 28 2.2.3 Measurement Report Data Analysis 30 2.2.4 Signaling Data Analysis 31 2.2.5 UE Positioning 32 2.2.5.1 Timing Advance 33 2.2.5.2 Location Accuracy Evaluation 35 2.2.5.3 Location Support 36 2.2.5.4 3D Geolocation 37 2.2.6 Key Performance Indicators Optimization 42 2.2.7 Technology Evolution of Optimization 43 2.3 LTE Optimization Key Point 44 2.3.1 RF Optimization 44 2.3.1.1 RSRP/RSSI/SINR/CINR 44 2.3.1.2 External Interference 48 2.3.2 CQI versus RSRP and SINR 51 2.3.2.1 CQI Adjustment 51 2.3.2.2 SINR Versus Load 54 2.3.2.3 SINR Versus MCS 56 2.3.3 Channel Power Configuration 58 2.3.3.1 RE Power 58 2.3.3.2 CRS Power Boosting 64 2.3.3.3 Power Allocation Optimization 66 2.3.4 Link Adaption 67 2.3.5 Adaptive Modulation and Coding 69 2.3.6 Scheduler 70 2.3.6.1 Downlink Scheduler 72 2.3.6.2 Uplink Scheduler 74 2.3.7 Radio Frame 75 2.3.8 System Information and Timers 76 2.3.8.1 System Information 76 2.3.8.2 Timers 81 2.3.9 Random Access 83 2.3.10 Radio Admission Control 85 2.3.11 Paging Control 86 2.3.11.1 Paging 86 2.3.11.2 Paging Capacity 92 2.3.11.3 Paging Message Size 95 2.3.11.4 Smart Paging 95 2.3.11.5 Priority Paging 96 2.3.12 MIMO and Beamforming 97 2.3.12.1 Basic Multi]Antenna Techniques 100 2.3.12.2 2D]Beamforming 101 2.3.12.3 2D MIMO and Parameters 104 2.3.12.4 Massive]MIMO 105 2.3.13 Power Control 107 2.3.13.1 PUSCH/PUCCH Power Control 107 2.3.13.2 PRACH Power Control 109 2.3.14 Antenna Adjustment 111 2.3.14.1 Antenna Position 112 2.3.14.2 Remote Electrical Tilt 113 2.3.14.3 Antenna Azimuths and Tilts Optimization 117 2.3.14.4 VSWR Troubleshooting 118 2.3.15 Main Key Performance Indicators 120 Part 2 Main Principles of LTE Optimization 123 3 Coverage Optimization 125 3.1 Traffic Channel Coverage 125 3.1.1 Parameters of Coverage 126 3.1.2 Weak Coverage 128 3.1.2.1 DL Coverage Hole 128 3.1.2.2 UL Weak Coverage 128 3.1.2.3 UL and DL Imbalance 129 3.1.3 Overlapping Coverage 129 3.1.4 Overshooting 130 3.1.5 Tx1/Tx2 RSRP Imbalance 132 3.1.6 Extended Coverage 132 3.1.7 Cell Border Adjustment 135 3.1.8 Vertical Coverage 137 3.1.9 Parameters Impacting Coverage 138 3.2 Control Channel Coverage 138 4 Capacity Optimization 140 4.1 RS SINR 140 4.2 PDCCH Capacity 141 4.3 PUCCH Capacity 144 4.3.1 Factors Affecting PUCCH Capacity 145 4.3.2 PUCCH Dimensioning Example 151 4.4 Number of Scheduled UEs 152 4.5 Spectral Efficiency 153 4.6 DL Data Rate Optimization 154 4.6.1 Limitation Factor 156 4.6.2 Model of DL Data Throughput 157 4.6.3 UDP/TCP Protocol 158 4.6.4 MIMO 161 4.6.4.1 DL MIMO 161 4.6.4.2 4Tx/4Rx Performance 163 4.6.4.3 Transmission Mode Switch 163 4.6.4.4 UL MU]MIMO 164 4.6.5 DL PRB Allocation and Utilization Mechanism 165 4.6.6 DL BLER 167 4.6.7 Impact of UE Velocity 169 4.6.8 Single User Throughput Optimization 170 4.6.8.1 Radio Analysis – Assignable Bits 171 4.6.8.2 Radio Analysis – CFI and Scheduling 171 4.6.8.3 Radio Analysis – HARQ 171 4.6.9 Avarage Cell Throughput Optimization 172 4.6.10 Cell Edge Throughput Optimization 172 4.6.11 Some Issues of DL Throughput 173 4.6.11.1 Antenna Diversity not Balanced 173 4.6.11.2 DL Grant is not Enough 173 4.6.11.3 Unstable Rate 175 4.7 UL Data Rate Optimization 175 4.7.1 Model of UL Data Throughput 176 4.7.2 UL SINR and PUSCH Data Rate 176 4.7.3 PRB Stretching and Throughput 179 4.7.4 Single User Throughput Optimization 180 4.7.4.1 Radio Analysis – Available PRBs 181 4.7.4.2 Radio Analysis—Link Adaptation 181 4.7.4.3 Radio Analysis – PDCCH 182 4.7.5 Cell Avarage and Cell]edge Throughput Optimization 182 4.7.6 Some Issues of UL Throughput 183 4.8 Parameters Impacting Throughput 185 5 Internal Interference Optimization 188 5.1 Interference Concept 188 5.2 DL Interference 190 5.2.1 DL Interference Ratio 191 5.2.2 Balance Between SINR and RSRP 192 5.3 UL Interference 192 5.3.1 UL Interference Detection 194 5.3.2 Generation of UL Interference 196 5.3.2.1 Cell Loading Versus Inter]Cell Interference 196 5.3.2.2 Unreasonable UL Network Structure 197 5.3.2.3 Cross slot interference 199 5.3.3 PUSCH Tx Power Analysis 200 5.3.4 UL Effect of P0 and α 202 5.3.5 PRACH Power Control 204 5.3.6 SRS Power Control 206 5.3.7 Interference Rejection Combinin 209 5.4 Inter]Cell Interference Coordination 210 5.5 UL IoT Control 210 5.5.1 UL Interference Issues and Possible Solutions 210 5.5.2 UL IoT Control Mechanism 210 5.5.3 PUSCH UL_SINR Target Calculation 212 5.5.4 UL Interference Criteria 213 6 Drop Call Optimization 216 6.1 Drop Call Mechanism 216 6.1.1 Radio Link Failure Detection by UE 217 6.1.2 RadioLink Failure Detection by eNB 220 6.1.2.1 Link Monitors in eNB 220 6.1.2.2 Time Alignment Mechanism 221 6.1.2.3 Maximum RLC Retransmissions Exceeded 224 6.1.3 RadioLink Failure Optimization and Recovery 225 6.2 Reasons of Call Drop and Optimization 227 6.2.1 Reasons of E]RAB Drop 227 6.2.2 S1 Release 230 6.2.3 Retainability Optimization 233 6.3 RRC Connection Reestablishment 233 6.4 RRC Connection Supervision 239 7 Latency Optimization 244 7.1 User Plane Latency 244 7.2 Control Plane Latency 247 7.3 Random Access Latency Optimization 247 7.4 Attach Latency Optimization 248 7.5 Paging Latency Optimization 250 7.6 Parameters Impacting Latency 250 8 Mobility Optimization 254 8.1 Mobility Management 255 8.1.1 RRC Connection Management 256 8.1.2 Measurement and Handover Events 256 8.1.3 Handover Procedure 260 8.1.3.1 X2 Handover 261 8.1.3.2 S1 Handover 267 8.1.3.3 Key point of X2/S1 Handover 267 8.2 Mobility Parameter 269 8.2.1 Attach and Dettach 272 8.2.2 UE Measurement Criterion in Idle Mode and Cell Selection 273 8.2.3 Cell Priority 276 8.3 Intra]LTE Cell Reselection 276 8.3.1 Cell Reselection Procedure 278 8.3.2 Inter]Frequency Cell Reselection 279 8.3.3 Cell Reselection Parameters 282 8.3.4 Inter]Frequency Reselection Optimization 283 8.4 Intra]LTE Handover Optimization 285 8.4.1 A3 and A5 Handover 285 8.4.2 Data Forwarding 290 8.4.3 Intra]Frequency Handover Optimization 291 8.4.4 Inter]Frequency Handover Optimization 292 8.4.5 Timers for Handover Failures 296 8.5 Neighbor Cell Optimization 297 8.5.1 Intra]LTE Neighbor Cell Optimization 297 8.5.1.1 Neighbor Relations Table 297 8.5.1.2 ANR 298 8.5.2 Suitable Neighbors for Load Balancing 299 8.6 Measurement Gap 299 8.6.1 Measurement Gap Pattern 299 8.6.2 Measurement Gap Versus Period of CQI Report and DRX 304 8.6.3 Impact of Throughput on Measurement Gap 304 8.7 Indoor and Outdoor Mobility 305 8.8 Inter]RAT Mobility 306 8.8.1 Inter]RAT Mobility Architecture and Key Technology 307 8.8.2 LTE to G/U Strategy 309 8.8.3 Reselection Optimization 314 8.8.3.1 LTE to UTRAN 315 8.8.3.2 UTRAN to LTE 319 8.8.4 Redirection Optimization 320 8.8.4.1 LTE to UTRAN 320 8.8.4.2 UTRAN to LTE 322 8.8.5 PS Handover Optimization 322 8.8.5.1 LTE to UTRAN 322 8.8.5.2 UTRAN to LTE 324 8.8.6 Reselection and Redirection Latency 325 8.8.7 Optimization Case Study 326 8.9 Handover Interruption Time Optimization 326 8.9.1 Control Plane and User Plane Latency 329 8.9.2 Inter]RAT Mobility Latency 332 8.10 Handover Failure and Improvement 332 8.11 Mobility Robustness Optimization 335 8.12 Carrier Aggregation Mobility Optimization 341 8.13 FDD]TDD Inter]mode Mobility Optimization 345 8.14 Load Balance 346 8.14.1 Inter]Frequency Load Balance 346 8.14.2 Inter]RAT Load Balance 348 8.14.3 Load Based Idle Mode Mobility 349 8.15 High]Speed Mobile Optimization 351 8.15.1 High]Speed Mobile Feature 353 8.15.2 Speed]Dependent Cell Reselection 354 8.15.3 PRACH Issues 356 8.15.4 Solution for Air to Ground 358 9 Traffic Model of Smartphone and Optimization 360 9.1 Traffic Model of Smartphone 360 9.1.1 QoS Mechanism 362 9.1.2 Rate Shaping and Traffic Management 366 9.1.3 Traffic Model 371 9.2 Smartphone]Based Optimization 372 9.3 High]Traffic Scenario Optimization 372 9.3.1 Resource Configuration 374 9.3.2 Capacity Monitoring 375 9.3.3 Special Features and Parameters for High Traffic 377 9.3.4 UL Noise Rise 379 9.3.5 Offload Solution and Parameter Settings 379 Part III Voice Optimization of LTE 383 10 Circuit Switched Fallback Optimization 385 10.1 Voice Evolution 385 10.2 CSFB Network Architecture and Configuration 386 10.2.1 CSFB Architecture 386 10.2.2 Combined Register 387 10.2.3 CSFB Call Procedure 392 10.2.3.1 Fallback Options 392 10.2.3.2 RRC Release with Redirection 393 10.2.3.3 CSFB Call Procedure 395 10.2.4 Mismatch Between TA and LA 397 10.3 CSFB Performance Optimization 402 10.3.1 CSFB Optimization 402 10.3.1.1 Main Issues of CSFB 402 10.3.1.2 CSFB Optimization Method 403 10.3.2 CSFB Main KPI 407 10.3.3 Fallback RAT Frequency Configuration Optimization 409 10.3.4 Call Setup Time Latency Optimization 411 10.3.4.1 ESR to Redirection Optimization 416 10.3.4.2 Twice Paging 416 10.3.5 Data Interruption Time 418 10.3.6 Return to LTE After Call Complete 419 10.4 Short Message Over CSFB 422 10.5 Case Study of CSFB Optimization 423 10.5.1 Combined TA/LA Updating Issue 423 10.5.2 MTRF Issue 425 10.5.3 Track Area Update Reject After CSFB 425 10.5.3.1 No EPS Bearer Context Issue 428 10.5.3.2 Implicitly Detach Issue 428 10.5.3.3 MS Identity Issue 428 10.5.4 Pseudo Base Station 428 11 VoLTE Optimization 434 11.1 VoLTE Architecture and Protocol Stack 435 11.1.1 VoLTE Architecture 435 11.1.2 VoLTE Protocol Stack 435 11.1.3 VoLTE Technical Summary 438 11.1.4 VoLTE Capability in UE 439 11.2 VoIP/Video QoS and Features 442 11.2.1 VoIP/Video QoS 442 11.2.2 Voice Codec 444 11.2.3 Video Codec 446 11.2.4 Radio Bearer for VoLTE 449 11.2.5 RLC UM 454 11.2.6 Call Procedure 457 11.2.6.1 LTE Attach and IMS Register 458 11.2.6.2 E2E IMS Flow 458 11.2.6.3 Video Phone Session Handling 462 11.2.7 Multiple Bearers Setup and Release 466 11.2.8 VoLTE Call On]Hold/Call Waiting 467 11.2.9 Differentiated Paging Priority 468 11.2.10 Robust Header Compression 470 11.2.10.1 RoHC Feature 470 11.2.10.2 Gain by RoHC 470 11.2.11 Inter]eNB Uplink CoMP for VoLTE 475 11.3 Semi] Persistent Scheduling and Other Scheduling Methods 477 11.3.1 SPS Scheduling 477 11.3.2 SPS Link Adaptation 478 11.3.3 Delay Based Scheduling 481 11.3.4 Pre]scheduling 482 11.4 PRB and MCS Selection Mechanism 484 11.4.1 Optimized Segmentation 484 11.4.2 PRB and MCS Selection 485 11.5 VoLTE Capacity 486 11.5.1 Control Channel for VoLTE 487 11.5.2 Performance of Mixed VoIP and Data 488 11.6 VoLTE Coverage 491 11.6.1 VoIP Payload and RoHC 492 11.6.2 RLC Segmentation 492 11.6.3 TTI Bundling 498 11.6.4 TTI Bundling Optimization 502 11.6.5 Coverage Gain with RLC Segmentation and TTI Bundling 507 11.6.6 MCS/TBS/PRB Selection 509 11.6.7 Link Budget 510 11.7 VoLTE Delay 513 11.7.1 Call Setup Delay 516 11.7.1.1 Call Setup Time 516 11.7.1.2 Reasons for Long Call Setup Time 516 11.7.2 Conversation Start Delay 519 11.7.3 RTP Delay 521 11.7.4 Handover Delay and Optimization 525 11.8 Intra]LTE Handover and eSRVCC 527 11.8.1 Intra]Frequency Handover 527 11.8.2 Inter]Frequency Handover 528 11.8.3 Single Radio Voice Call Continuity Procedure 529 11.8.4 SRVCC Parameters Optimization 539 11.8.4.1 Handover Parameters 539 11.8.4.2 SRVCC–Related Timer 539 11.8.5 aSRVCC and bSRVCC 543 11.8.6 SRVCC Failure 543 11.8.7 Reducing SRVCC Voice Gap and eSRVCC 545 11.8.7.1 Voice Interruption Time during SRVCC 545 11.8.7.2 eSRVCC 549 11.8.8 Fast Return to LTE 552 11.8.9 Roaming Behavior According to Network Capabilities 555 11.9 Network Quality and Subjective Speech Quality 555 11.9.1 Bearer Latency 558 11.9.2 MoS 561 11.9.2.1 Voice Quality 561 11.9.2.2 Video Quality 570 11.9.3 Jitter 571 11.9.4 Packet Loss 572 11.9.5 One Way Audio 575 11.9.6 PDCP Discard Timer Operation 576 11.10 Optimization 577 11.10.1 Distribution of Main Indicators of Field Test 580 11.10.2 Compression Ratio and GBR Throughput 584 11.10.3 RB Utilization 584 11.10.4 BLER Issue 587 11.10.5 Quality Due to Handover 589 11.10.6 eSRVCC Handover Issues 589 11.10.7 Packet Loss 592 11.10.7.1 Packet Loss due to Poor RF 592 11.10.7.2 Packet Loss due to Massive users 592 11.10.7.3 Packet Loss Due to Insufficient UL grant 592 11.10.7.4 Packet Loss due to Handover 601 11.10.7.5 Packet Loss Due to Network Issue 601 11.10.8 Call Setup Issues 601 11.10.8.1 Missed Pages 602 11.10.8.2 IMS Issues 604 11.10.8.3 Dedicated Bearer Setup Issues 609 11.10.8.4 CSFB Call Issues 612 11.10.8.5 aSRVCC Failure 612 11.10.8.6 RF Issues 612 11.10.8.7 Frequent TFT Updates 617 11.10.8.8 Encryption Issue 618 11.10.9 Call Drop 619 11.10.9.1 Call Drop 619 11.10.9.2 Radio Link Failure 622 11.10.9.3 RTP]RTCP Timeout 624 11.10.9.4 RLC/PDCP SN Length Mismatch 626 11.10.9.5 IMS Session Drop 626 11.10.9.6 eNB/MME Initiated Drop 632 11.10.10 Packet Aggregation Level 632 11.10.11 VoIP Padding 633 11.10.12 VoIP Ralated Parameters 635 11.10.13 Video]Related Optimization 635 11.10.13.1 Video Bit Rate and Frame Rate 637 11.10.13.2 Video MoS and Audio/Video Sync 637 11.10.14 IMS Ralated Timer 637 11.11 UE Battery Consumption Optimization for VoLTE 638 11.11.1 Connected Mode DRX Parameter 643 11.11.2 DRX Optimization 644 11.11.2.1 State Estimation 644 11.11.2.2 DRX Optimization and Parameters 644 11.11.2.3 KPI Impacts with DRX 648 11.11.3 Scheduling Request Periodicity and Disabling of Aperiodic CQI 652 11.12 Comparation with VoLTE and OTT 654 11.12.1 OTT VoIP User Experience 654 11.12.2 OTT VoIP Codec 657 11.12.3 Signaling Load of OTT VoIP 658 Part IV Advanced Optimization of LTE 663 12 PRACH Optimization 665 12.1 Overview 665 12.2 PRACH Configuration Index 669 12.3 RACH Root Sequence 673 12.4 PRACH Cyclic Shift 674 12.4.1 PRACH Cyclic Shift Optimization 674 12.4.2 Rrestricted Set 679 12.5 Prach Frequency Offset 682 12.6 Preamble Collision Probability 683 12.7 Preamble Power 684 12.8 Random Access Issues 687 12.9 RACH Message Optimization 689 12.10 Accessibility Optimization 692 12.10.1 Reasons for Poor Accessibility 692 12.10.2 Accessibility 693 12.10.3 Accessibility Analysis Tree 695 12.10.4 Call and Data Session Setup Optimization 697 12.10.5 RACH Estimation for Different Traffic Profile 698 13 Physical Cell ID Optimization 702 13.1 Overview 702 13.2 PCI Optimization Methodology 703 13.2.1 PCI Group Optimization 705 13.2.2 PCI Code Reuse Distance 705 13.2.3 Mod3/30 Discrepancy Analysis 708 13.2.4 Collision and Confusion 708 13.3 PCI Optimization 709 14 Tracking Areas Optimization 711 14.1 TA Optimization 712 14.1.1 TA Update Procedure 713 14.1.2 TA Optimization and TAU Failure 715 14.2 TA List Optimization 716 14.3 TAU Reject Analysis and Optimization 719 15 Uplink Signal Optimization 721 15.1 Uplink Reference Signal Optimization 721 15.1.1 Coding Scheme of UL RS 722 15.1.2 Correlation of UL Sequence Group 723 15.1.2.1 UL Sequence Group Hopping 725 15.1.2.2 UL Sequence Hopping 726 15.1.2.3 UL Cyclic Shift Hopping 726 15.1.3 UL Sequence Group Optimization 727 15.2 Uplink Sounding Signal Optimization 729 15.2.1 SRS Characters 730 15.2.2 Wideband SRS Coverage 736 15.2.3 Dynamic SRS Adjustment Scheme 736 15.2.4 SRS Selection Dimension and Confliction 737 15.2.5 SRS Conflict and Optimization 739 16 HetNet Optimization 741 16.1 UE Geolocation and Identification of Traffic Hot Spots 741 16.2 Wave Propagation Characteristics for HetNet 745 16.3 New Features in HetNet 746 16.4 Combined Cell Optimization 747 16.5 Cell Range Expansion Offset 748 16.6 HetNet Cell Reselection and Handover Optimization 751 17 QoE Evaluation and Optimization Strategy 752 17.1 QoE Modeling 753 17.2 Data Collecting and Processing 756 17.3 QoE]Based Traffic Evaluation 757 17.3.1 Online Video QoE 757 17.3.1.1 Video Quality Monitoring Methods 761 17.3.1.2 RATE Adaptive Video Codecs 763 17.3.1.3 Streaming KPI and QoE 764 17.3.1.4 Video Optimization 766 17.3.2 Voice QoE 769 17.3.3 Data Service QoE 770 17.3.3.1 Web browsing 770 17.3.3.2 Online Gaming 774 17.4 QoE Based Optimization 776 18 Signaling]Based Optimization 780 18.1 S1] AP Signaling 780 18.1.1 NAS signaling 782 18.1.2 Inactivity Supervision 783 18.1.3 UE signaling Management 785 18.2 Signaling radio bearers 786 18.3 Signaling Storm 788 18.4 Signaling Troubleshooting Method 788 18.4.1 Attach Failure 788 18.4.2 Service Request Failure 796 18.4.3 S1/X2]Based Handover 796 18.4.4 eSRVCC Failure 798 18.4.5 CSFB Failure 800 Appendix 802 Glossary of Acronyms 820 References 823 Index 825

Read more less

Book SynopsisAn extensive introduction to the engineering and manufacture of current and next-generation flat panel displays This book provides a broad overview of the manufacturing of flat panel displays, with a particular emphasis on the display systems at the forefront of the current mobile device revolution. It is structured to cover a broad spectrum of topics within the unifying theme of display systems manufacturing. An important theme of this book is treating displays as systems, which expands the scope beyond the technologies and manufacturing of traditional display panels (LCD and OLED) to also include key components for mobile device applications, such as flexible OLED, thin LCD backlights, as well as the manufacturing of display module assemblies. Flat Panel Display Manufacturing fills an important gap in the current book literature describing the state of the art in display manufacturing for today's displays, and looks to create a reference the development of next generation displaysTrade Review"If there is only one book on flat panel displays that is going to be on your bookshelf, then I would highly recommend this one. It will be a text that you refer to time and again for clear and concise explanations of how LCD and OLED displays are constructed and the processes used to make them into commercially successful products. As you use it, you will find yourself drawn in by the clear and colorful illustrations and will find it hard to not read more than you first intended." Aris Silzars Ph.D., Member of the Board of Advisors, NanoLumens, Inc. and Past President of SID, USATable of ContentsList of Contributors xxi Series Editor’s Foreword xxv Preface xxvii 1 Introduction 1Fang‐Chen Luo, Jun Souk, Shinji Morozumi, and Ion Bita 1.1 Introduction 1 1.2 Historic Review of TFT‐LCD Manufacturing Technology Progress 1 1.2.1 Early Stage TFT and TFT‐Based Displays 2 1.2.2 The 1990s: Initiation of TFT‐LCD Manufacturing and Incubation of TFT‐LCD Products 2 1.2.3 Late 1990s: Booming of LCD Desktop Monitor and Wide Viewing Angle Technologies 4 1.2.4 The 2000s: A Golden Time for LCD‐TV Manufacturing Technology Advances 4 1.3 Analyzing the Success Factors in LCD Manufacturing 5 1.3.1 Scaling the LCD Substrate Size 7 1.3.2 Major Milestones in TFT‐LCD Manufacturing Technology 9 1.3.2.1 First Revolution: AKT Cluster PECVD Tool in 1993 9 1.3.2.2 Second Revolution: Wide Viewing Angle Technology in 1997 9 1.3.2.3 Third Revolution: LC Drop Filling Technology in 2003 10 1.3.3 Major Stepping Stones Leading to the Success of Active Matrix Displays 10 References 11 2 TFT Array Process Architecture and Manufacturing Process Flow 13Chiwoo Kim 2.1 Introduction 13 2.2 Material Properties and TFT Characteristics of a‐Si, LTPS, and Metal Oxide TFTs 15 2.2.1 a‐Si TFT 15 2.2.2 LTPS TFT 16 2.2.2.1 Excimer Laser Annealing (ELA) 17 2.2.3 Amorphous Oxide Semiconductor TFTs 22 2.3 a‐Si TFT Array Process Architecture and Process Flow 22 2.3.1 Four‐Mask Count Process Architecture for TFT‐LCDs 24 2.4 Poly‐Si TFT Architecture and Fabrication 27 2.5 Oxide Semiconductor TFT Architecture and Fabrication 30 2.6 TFT LCD Applications 32 2.7 Development of SLS‐Based System on Glass Display [1, 11, 14, 15] 33 References 35 3 Color Filter Architecture, Materials, and Process Flow 39Young Seok Choi, Musun Kwak, and Youn Sung Na 3.1 Introduction 39 3.2 Structure and Role of the Color Filter 39 3.2.1 Red, Green, and Blue (RGB) Layer 40 3.2.1.1 Color Coordinate and Color Gamut 41 3.2.2 Black Matrix 44 3.2.3 Overcoat and Transparent Electrode 45 3.2.4 Column Spacer 46 3.3 Color Filter Manufacturing Process Flow 46 3.3.1 Unit Process 46 3.3.1.1 Formation of Black Matrix 46 3.3.1.2 Formation of RGB Layer 48 3.3.1.3 Overcoat (OC) 51 3.3.1.4 Formation of ITO Electrodes 53 3.3.1.5 Column Spacer (Pattern Spacer) 53 3.3.2 Process Flow for Different LC Mode 54 3.3.2.1 Color Filter for the TN Mode 54 3.3.2.2 Color Filter for the IPS Mode 54 3.3.2.3 Color Filter for the VA Mode 55 3.4 New Color Filter Design 55 3.4.1 White Color (Four Primary Colors) Technology 55 3.4.2 Color Filter on TFT 56 References 57 4 Liquid Crystal Cell Process 59Heung‐Shik Park and Ki‐Chul Shin 4.1 Introduction 59 4.2 Liquid Crystal Cell Process 59 4.2.1 Alignment Layer Treatment 61 4.2.2 Process of Applying PI Layers 62 4.2.3 Rubbing Process 63 4.2.4 Photo‐Alignment Process 64 4.2.5 LC Filling Process 65 4.2.5.1 Vacuum Filling Method 66 4.2.5.2 End Seal Process 66 4.2.5.3 One Drop Filling (ODF) Method 67 4.2.6 Vacuum Assembly Process 68 4.2.7 Polarizer Attachment Process 69 4.3 Conclusions 70 Acknowledgments 70 References 70 5 TFT‐LCD Module and Package Process 73Chun Chang Hung 5.1 Introduction 73 5.2 Driver IC Bonding: TAB and COG 73 5.3 Introduction to Large‐Panel JI Process 74 5.3.1 COF Bonding 75 5.3.1.1 Edge Clean 75 5.3.1.2 ACF Attachment 76 5.3.1.3 COF Pre‐Bonding 77 5.3.1.4 COF Main Bonding 78 5.3.1.5 Lead Check 78 5.3.1.6 Silicone Dispensing 78 5.3.2 PCB Bonding 79 5.3.3 PCB Test 79 5.3.4 Press Heads: Long Bar or Short Bar 79 5.4 Introduction to Small‐Panel JI Process 79 5.4.1 Beveling 80 5.4.2 Panel Cleaning 80 5.4.3 Polarizer Attachment 80 5.4.4 Chip on Glass (COG) Bonding 81 5.4.5 FPC on Glass (FOG) Bonding 81 5.4.6 Optical Microscope (OM) Inspection 81 5.4.7 UV Glue Dispense 82 5.4.8 Post Bonding Inspection (PBI) 82 5.4.9 Protection Glue Dispensing 82 5.5 LCD Module Assembly 83 5.6 Aging 84 5.7 Module in Backlight or Backlight in Module 85 References 86 6 LCD Backlights 87Insun Hwang and Jae‐Hyeon Ko 6.1 Introduction 87 6.2 LED Sources 90 6.2.1 GaN Epi‐Wafer on Sapphire 92 6.2.2 LED Chip 93 6.2.3 Light Extraction 94 6.2.4 LED Package 96 6.2.5 SMT on FPCB 97 6.3 Light Guide Plate 98 6.3.1 Optical Principles of LGP 98 6.3.2 Optical Pattern Design 99 6.3.3 Manufacturing of LGP 101 6.3.3.1 Injection Molding 101 6.3.3.2 Screen Printing 102 6.3.3.3 Other Methods 103 6.4 Optical Films 104 6.4.1 Diffuser 106 6.4.2 Prism Film 107 6.4.3 Reflector 108 6.4.4 Other Films 108 6.5 Direct‐Type BLU 111 6.6 Summary 111 References 112 7 TFT Backplane and Issues for OLED 115Chiwoo Kim 7.1 Introduction 115 7.2 LTPS TFT Backplane for OLED Films 116 7.2.1 Advanced Excimer Laser Annealing (AELA) for Large‐Sized AMOLED Displays 117 7.2.2 Line‐Scan Sequential Lateral Solidification Process for AMOLED Application 120 7.3 Oxide Semiconductor TFT for OLED 122 7.3.1 Oxide TFT–Based OLED for Large‐Sized TVs 123 7.4 Best Backplane Solution for AMOLED 125 References 127 8A OLED Manufacturing Process for Mobile Application 129Jang Hyuk Kwon and Raju Lampande 8A.1 Introduction 129 8A.2 Current Status of AMOLED for Mobile Display 130 8A.2.1 Top Emission Technology 130 8A.3 Fine Metal Mask Technology (Shadow Mask Technology) 133 8A.4 Encapsulation Techniques for OLEDs 135 8A.4.1 Frit Sealing 135 8A.4.2 Thin‐Film Encapsulation 136 8A.5 Flexible OLED technology 137 8A.6 AMOLED Manufacturing Process 137 8A.7 Summary 140 References 140 8B OLED Manufacturing Process for TV Application 143Chang Wook Han and Yoon Heung Tak 8B.1 Introduction 143 8B.2 Fine Metal Mask (FMM) 144 8B.3 Manufacturing Process for White OLED and Color Filter Methods 147 8B.3.1 One‐Stacked White OLED Device 149 8B.3.2 Two‐Stacked White OLED Device 152 8B.3.3 Three‐Stacked White‐OLED Device 155 References 157 9 OLED Encapsulation Technology 159Young‐Hoon Shin 9.1 Introduction 159 9.2 Principles of OLED Encapsulation 159 9.2.1 Effect of H2O 160 9.3 Classification of Encapsulation Technologies 162 9.3.1 Edge Seal 163 9.3.2 Frit Seal 164 9.3.3 Dam and Fill 166 9.3.4 Face Seal 167 9.3.5 Thin‐Film Encapsulation (TFE) 168 9.4 Summary 170 References 170 10 Flexible OLED Manufacturing 173Woojae Lee and Jun Souk 10.1 Introduction 173 10.2 Critical Technologies in Flexible OLED Display 174 10.2.1 High‐Temperature PI Film 175 10.2.2 Encapsulation Layer 176 10.2.2.1 Thin‐Film Encapsulation (TFE) Method 176 10.2.2.2 Hyrid Encapsulation Method 177 10.2.2.3 Other Encapsulation Methods 178 10.2.2.4 Measurement of Barrier Performance 179 10.2.3 Laser Lift‐Off 180 10.2.4 Touch Sensor on F‐OLED 181 10.3 Process Flow of F‐OLED 181 10.3.1 PI Film Coating and Curing 181 10.3.2 LTPS TFT Backplane Process 183 10.3.3 OLED Deposition Process 183 10.3.4 Thin‐Film Encapsulation 185 10.3.5 Laser Lift‐Off 185 10.3.6 Lamination of Backing Plastic Film and Cut to Cell Size 185 10.3.7 Touch Sensor Attach 186 10.3.8 Circular Polarizer Attach 186 10.3.9 Module Assembly (Bonding Drive IC) 186 10.4 Foldable OLED 186 10.5 Summary 188 References 189 11A Metal Lines and ITO PVD 193Hyun Eok Shin, Chang Oh Jeong, and Junho Song 11A.1 Introduction 193 11A.1.1 Basic Requirements of Metallization for Display 193 11A.1.2 Thin‐Film Deposition by Sputtering 195 11A.2 Metal Line Evolution in Past Years of TFT‐LCD 198 11A.2.1 Gate Line Metals 199 11A.2.1.1 Al and Al Alloy Electrode 199 11A.2.1.2 Cu Electrode 201 11A.2.2 Data line (Source/Drain) Metals 202 11A.2.2.1 Data Al Metal 202 11A.2.2.2 Data Cu Metal 203 11A.2.2.3 Data Chromium (Cr) Metal 203 11A.2.2.4 Molybdenum (Mo) Metal 203 11A.2.2.5 Titanium (Ti) Metal 204 11A.3 Metallization for OLED Display 205 11A.3.1 Gate Line Metals 205 11A.3.2 Source/Drain Metals 205 11A.3.3 Pixel Anode 206 11A.4 Transparent Electrode 207 References 208 11B Thin‐Film PVD: Materials, Processes, and Equipment 209Tetsuhiro Ohno 11B.1 Introduction 209 11B.2 Sputtering Method 210 11B.3 Evolution of Sputtering Equipment for FPD Devices 212 11B.3.1 Cluster Tool for Gen 2 Size 212 11B.3.2 Cluster Tool for Gen 4.5 to Gen 7 Size 213 11B.3.3 Vertical Cluster Tool for Gen 8 Size 213 11B.4 Evolution of Sputtering Cathode 215 11B.4.1 Cathode Structure Evolution 215 11B.4.2 Dynamic Multi Cathode for LTPS 217 11B.4.3 Cathode Selection Strategy 217 11B.5 Transparent Oxide Semiconductor (TOS) Thin‐Film Deposition Technology 218 11B.5.1 Deposition Equipment for TOS‐TFT 218 11B.5.2 New Cathode Structure for TOS‐TFT 219 11B.6 Metallization Materials and Deposition Technology 221 References 223 11C Thin‐Film PVD (Rotary Target) 225 Marcus Bender 11C. 1 Introduction 225 11C.2 Source Technology 227 11C.2.1 Planar Cathodes 227 11C.2.2 Rotary Cathodes 229 11C.2.3 Rotary Cathode Array 230 11C.3 Materials, Processes, and Characterization 232 11C.3.1 Introduction 232 11C.3.2 Backplane Metallization 232 11C.3.3 Layers for Metal‐Oxide TFTs 234 11C.3.4 Transparent Electrodes 236 11C.3.5 Adding Touch Functionality and Improving End‐User Experience 238 References 239 12A Thin‐Film PECVD (AKT) 241Tae Kyung Won, Soo Young Choi, and John M. White 12A.1 Introduction 241 12A.2 Process Chamber Technology 243 12A.2.1 Electrode Design 243 12A.2.1.1 Hollow Cathode Effect and Hollow Cathode Gradient 243 12A.2.1.2 Gas Flow Control 245 12A.2.1.3 Susceptor 245 12A.2.2 Chamber Cleaning 246 12A.3 Thin‐Film Material, Process, and Characterization 248 12A.3.1 Amorphous Si (a‐Si) TFT 248 12A.3.1.1 Silicon Nitride (SiN) 248 12A.3.1.2 Amorphous Silicon (a‐Si) 253 12A.3.1.3 Phosphorus‐Doped Amorphous Silicon (n+ a‐Si) 257 12A.3.2 Low‐Temperature Poly Silicon (LTPS) TFT 258 12A.3.2.1 Silicon Oxide (SiO) 259 12A.3.2.2 a‐Si Precursor Film (Dehydrogenation) 260 12A.3.3 Metal‐Oxide (MO) TFT 263 12A.3.3.1 Silicon Oxide (SiO) 265 12A.3.4 Thin‐Film Encapsulation (TFE) 269 12A.3.4.1 Barrier Layer (Silicon Nitride) 269 12A.3.4.2 Buffer Layer 271 References 271 12B Thin‐Film PECVD (Ulvac) 273Masashi Kikuchi 12B.1 Introduction 273 12B.2 Plasma of PECVD 273 12B.3 Plasma Modes and Reactor Configuration 273 12B.3.1 CCP‐Type Reactor 274 12B.3.2 Microwave‐Type Reactor 274 12B.3.3 ICP‐Type Reactor 275 12B.4 PECVD Process for Display 276 12B.4.1 a‐Si Film for a‐Si TFT 276 12B.4.2 a‐Si Film for LTPS 277 12B.4.3 SiNx Film 278 12B.4.4 TEOS SiO2 Film 279 12B.5 PECVD System Overview 279 12B.6 Remote Plasma Cleaning 279 12B.6.1 Gas Flow Style of Remote Plasma Cleaning 281 12B.6.2 Cleaning and Corrosion 281 12B.7 Passivation Layer for OLED 282 12B.7.1 Passivation by Single/Double/Multi‐Layer 282 12B.8 PECVD Deposition for IGZO TFT 283 12B.8.1 Gate Insulator for IGZO TFT 283 12B.8.2 Passivation Film for IGZO TFT 284 12B.9 Particle Generation 284 References 286 13 Photolithography 287Yasunori Nishimura, Kozo Yano, Masataka Itoh, and Masahiro Ito 13.1 Introduction 287 13.2 Photolithography Process Overview 288 13.2.1 Cleaning 289 13.2.2 Preparation 289 13.2.3 Photoresist Coating 289 13.2.4 Exposure 289 13.2.5 Development 289 13.2.6 Etching 289 13.2.7 Resist Removal 289 13.3 Photoresist Coating 290 13.3.1 Evolution of Photoresist Coating 290 13.3.2 Slit Coating 290 13.3.2.1 Principles of Slit Coating 290 13.3.2.2 Slit‐Coating System 291 13.4 Exposure 292 13.4.1 Photoresist and Exposure 292 13.4.1.1 Photoresist 292 13.4.1.2 Color Resist 292 13.4.1.3 UV Light Source for Exposure 292 13.4.2 General Aspects of Exposure Systems 292 13.4.3 Stepper 293 13.4.4 Projection Scanning Exposure System 294 13.4.5 Mirror Projection Scan System (Canon) 296 13.4.6 Multi‐Lens Projection System (Nikon) 296 13.4.6.1 Multi‐Lens Optics 296 13.4.6.2 Multi‐Lens Projection System 296 13.4.7 Proximity Exposure 297 13.5 Photoresist Development 300 13.6 Inline Photolithography Processing Equipment 301 13.7 Photoresist Stripping 302 13.8 Photolithography for Color Filters 303 13.8.1 Color Filter Structures 303 13.8.1.1 TN 304 13.8.1.2 VA 304 13.8.1.3 IPS 304 13.8.2 Materials for Color Filters 305 13.8.2.1 Black Matrix Materials 305 13.8.2.2 RGB Color Materials 305 13.8.2.3 PS (Photo Spacer) Materials 306 13.8.3 Photolithography Process for Color Filters 307 13.8.3.1 Color Resist Coating 307 13.8.3.2 Exposure 307 13.8.3.3 Development 308 13.8.4 Higher‐Performance Color Filters 309 13.8.4.1 Mobile Applications 309 13.8.4.2 TV Applications 309 References 310 14A Wet Etching Processes and Equipment 311Kazuo Jodai 14A.1 Introduction 311 14A.2 Overview of TFT Process 312 14A.3 Applications and Equipment of Wet Etching 313 14A.3.1 Applications 313 14A.3.2 Equipment (Outline) 313 14A.3.3 Substrate Transferring System 315 14A.3.4 Dip Etching System 316 14A.3.5 Cascade Rinse System 316 14A.4 Problems Due to Increased Mother Glass Size and Solutions 317 14A.4.1 Etchant Concentration Management 317 14A.4.2 Quick Rinse 317 14A.4.3 Other Issues 318 14A.5 Conclusion 318 References 318 14B Dry Etching Processes and Equipment 319Ippei Horikoshi 14B.1 Introduction 319 14B.2 Principle of Dry Etching 319 14B.2.1 Plasma 320 14B.2.2 Ions 321 14B.2.3 Radicals 321 14B.3 Architecture for Dry Etching Equipment 322 14B.4 Dry Etching Modes 323 14B.4.1 Conventional Etching Mode and Each Characteristic 324 14B.4.2 Current Etching Mode and Each Characteristic 325 14B.5 TFT Process 325 14B.5.1 a‐Si Process 325 14B.5.2 LTPS Process 326 14B.5.3 Oxide Process 327 References 328 15 TFT Array: Inspection, Testing, and Repair 329Shulik Leshem, Noam Cohen, Savier Pham, Mike Lim, and Amir Peled 15.1 Defect Theory 329 15.1.1 Typical Production Defects 329 15.1.1.1 Pattern Defects 329 15.1.1.2 Foreign Particles 331 15.1.2 Understanding the Nature of Defects 332 15.1.2.1 Critical and Non‐Critical Defects 332 15.1.2.2 Electrical and Non‐Electrical Defects 333 15.1.3 Effect of Defects on Final FPD Devices and Yields 333 15.2 AOI (Automated Optical Inspection) 334 15.2.1 The Need 334 15.2.2 AOI Tasks, Functions, and Sequences 335 15.2.2.1 Image Acquisition 335 15.2.2.2 Defect Detection 336 15.2.2.3 Defect Classification 336 15.2.2.4 Review Image Grabbing 337 15.2.2.5 Defect Reporting and Judgment 337 15.2.3 AOI Optical Concept 337 15.2.3.1 Image Quality Criteria 338 15.2.3.2 Scan Cameras 339 15.2.3.2.1 Camera Type 339 15.2.3.2.2 Resolution Changer 339 15.2.3.2.3 Backside Inspection 339 15.2.3.3 Scan Illumination 339 15.2.3.3.1 Types of Illumination 339 15.2.3.4 Video Grabbing for Defect Review and Metrology 340 15.2.3.4.1 Review/Metrology Cameras 340 15.2.3.4.2 On‐the‐Fly Video Grabbing 340 15.2.3.4.3 Alternative to Video Images 340 15.2.4 AOI Defect Detection Principles 341 15.2.4.1 Gray Level Concept 342 15.2.4.2 Comparison of Gray Level Values Between Neighboring Cells 342 15.2.4.3 Detection Sensitivity 342 15.2.4.4 Detection Selectivity 344 15.2.5 AOI Special Features 344 15.2.5.1 Detection of Special Defect Types 344 15.2.5.2 Inspection of In‐Cell Touch Panels 345 15.2.5.3 Peripheral Area Inspection 346 15.2.5.4 Mura Defects 346 15.2.5.5 Cell Process Inspection 347 15.2.5.6 Defect Classification 347 15.2.5.7 Metrology: CD/O Measurement 349 15.2.5.8 Automatic Judgment 350 15.2.6 Offline Versus Inline AOI 350 15.2.7 AOI Usage, Application and Trends 351 15.3 Electrical Testing 352 15.3.1 The Need 352 15.3.2 Array Tester Tasks, Functions, and Sequences 353 15.3.2.1 Panel Signal Driving 353 15.3.2.1.1 Shorting Bar Probing Method 354 15.3.2.1.2 Full Contact Probing Method 354 15.3.2.2 Contact or Non‐Contact Sensing 354 15.3.2.2.1 Contact Sensing 355 15.3.2.2.2 Non‐Contact Sensing Methods 355 15.3.2.3 Panel Image Processing and Defect Detection 355 15.3.2.4 Post‐Defect Detection Processes 355 15.3.3 Array Tester System Design Concept 356 15.3.3.1 Signal Driving Probing 357 15.3.3.2 Ultra‐High‐Resolution Testing 357 15.3.3.3 System TACT 358 15.3.3.4 “High‐Channel” Testing 358 15.3.3.5 Advanced Process Technology Testing (AMOLED, FLEX OLED) 358 15.3.4 Array Tester Special Features 359 15.3.4.1 GOA, ASG, and IGD Testing 359 15.3.4.2 Electro Mura Monitoring 359 15.3.4.3 Free‐Form Panel Testing 361 15.3.5 Array Tester Usage, Application, and Trends 361 15.3.5.1 Source Drain Layer Testing for LTPS LCD/OLED 362 15.3.5.2 New Probing Concept 363 15.3.5.3 In‐Cell Touch Panel Testing 363 15.4 Defect Repair 363 15.4.1 The Need 363 15.4.2 Repair System in the Production Process 364 15.4.2.1 In‐Process Repair 364 15.4.2.2 Final Repair 364 15.4.3 Repair Sequence 364 15.4.4 Short‐Circuit Repair Method 365 15.4.4.1 Laser Ablation Concept 365 15.4.4.1.1 Thermal Ablation 366 15.4.4.1.2 Cold Ablation 366 15.4.4.1.3 Photochemical Ablation 366 15.4.4.2 Laser Light Wavelengths and their Typical Applications 366 15.4.4.2.1 Laser Matter Interaction 366 15.4.4.2.2 Using DUV Laser Light (266 nm) for Short‐Circuit Defect Repair 367 15.4.4.2.3 Using Infrared Laser Light (1,064 nm) for Short‐Circuit Defect Repair 367 15.4.4.3.4 Using Green Laser Light (532 nm) for Short‐Circuit Defect Repair 367 15.4.4.3 Typical Applications of the Short‐Circuit Repair Method 367 15.4.4.3.1 Cutting 367 15.4.4.3.2 Welding 368 15.4.5 Open‐Circuit Repair Method 369 15.4.5.1 LCVD (Laser Chemical Vapor Deposition) 369 15.4.5.2 Metal Ink Deposition Repair 370 15.4.5.2.1 Dispensing 370 15.4.5.2.2 Metal Inkjet Deposition 370 15.4.5.2.3 LIFT (Laser‐Induced Forward Transfer) Deposition 371 15.4.5.3 Main Applications of the Deposition Repair (Open‐Circuit Repair) 372 15.4.6 Photoresist (PR) Repair 372 15.4.6.1 Main Applications of the Photoresist Repair 373 15.4.6.2 Photoresist Repair Technology 373 15.4.6.2.1 Using DMD for Patterning 373 15.4.6.2.2 Using FSM for Patterning 373 15.4.7 Special Features of the Repair System 375 15.4.7.1 Line Defect Locator (LDL) 375 15.4.7.2 Parallel Repair Mode for Maximum System Throughput 375 15.4.8 Repair Technology Trends 376 15.4.8.1 Cold Ablation 376 15.4.8.2 Full Automatic Repair Solution 377 15.4.9 Summary 377 16 LCM Inspection and Repair 379Chun Chang Hung 379 16.1 Introduction 379 16.2 Functional Defects Inspection 379 16.3 Cosmetic Defects Inspection 381 16.4 Key Factors for Proper Inspection 383 16.4.1 Variation Between Inspectors 383 16.4.2 Testing Environments 385 16.4.3 Inspection Distance, Viewing Angle, and Sequence of Test Patterns 385 16.4.4 Characteristics of Product and Components 387 16.5 Automatic Optical Inspection (AOI) 388 16.6 LCM Defect Repair 388 References 391 17 Productivity and Quality Control Overview 393Kozo Yano, Yasunori Nishimura, and Masataka Itoh 17.1 Introduction 393 17.2 Productivity Improvement 394 17.2.1 Challenges for Productivity Improvement 394 17.2.2 Enlargement of Glass Substrate 395 17.2.2.1 Productivity Improvement and Cost Reduction by Glass Size Enlargement 397 17.3 Yield Management 399 17.3.1 Yield Analysis 399 17.3.1.1 Inspection and Yield 399 17.3.1.2 Failure Mode Analysis 401 17.3.2 Yield Improvement Activity 404 17.3.2.1 Process Yield Improvement 404 17.3.2.2 Systematic Failure Minimization 404 17.3.2.3 Random Failure Minimization by Clean Process 404 17.3.2.4 Yield Improvement by Repairing 406 17.4 Quality Control System 406 17.4.1 Materials (IQC) 407 17.4.2 Facility Control 408 17.4.3 Process Quality Control 408 17.4.3.1 TFT Array Process 409 17.4.3.2 Color Filter Process 410 17.4.3.3 LCD Cell Process 412 17.4.3.4 Modulization Process 412 17.4.4 Organization and Key Issues for Quality Control 413 References 417 18 Plant Architectures and Supporting Systems 419Kozo Yano and Michihiro Yamakawa 18.1 Introduction 419 18.2 General Issues in Plant Architecture 420 18.2.1 Plant Overview 420 18.2.2 Plant Design Procedure and Baseline 422 18.3 Clean Room Design 423 18.3.1 Clean Room Evolution 423 18.3.2 Floor Structure for Clean Room 424 18.3.3 Clean Room Ceiling Height 424 18.3.4 Air Flow and Circulation Design 427 18.3.5 Cleanliness Control 428 18.3.6 Air Flow Control Against Particle 428 18.3.7 Chemical Contamination Countermeasures 431 18.3.8 Energy Saving in FFU 433 18.4 Supporting Systems with Environmental Consideration 433 18.4.1 Incidental Facilities 433 18.4.2 Water and Its Recycle 434 18.4.3 Chemicals 436 18.4.4 Gases 436 18.4.5 Electricity 437 18.5 Production Control System 437 References 440 19 Green Manufacturing 441YiLin Wei, Mona Yang, and Matt Chien 19.1 Introduction 441 19.2 Fabrication Plant (Fab) Design 441 19.2.1 Fab Features 441 19.2.2 Green Building Design 442 19.3 Product Material Uses 443 19.3.1 Material Types and Uses 443 19.3.2 Hazardous Substance Management 444 19.3.3 Material Hazard and Green Trend 446 19.3.4 Conflict Minerals Control 446 19.4 Manufacturing Features and Green Management 447 19.4.1 The Manufacturing Processes 447 19.4.2 Greenhouse Gas Inventory 448 19.4.3 Energy Saving in Manufacturing 449 19.4.4 Reduction of Greenhouse Gas from Manufacturing 449 19.4.5 Air Pollution and Control 451 19.4.6 Water Management and Emissions Control 452 19.4.7 Waste Recycling and Reuse 453 19.5 Future Challenges 453 References 454 Index 457

Read more less

Book SynopsisOver the past forty years, media education research has emerged as a historical, epistemological and practical field of study. Shifts in the fieldalong with radical transformations in media technologies, aesthetic forms, ownership models, and audience participation practiceshave driven the application of new concepts and theories across a range of both school and non-school settings. The Handbook on Media Education Research is a unique exploration of the complex set of practices, theories, and tools of media research. Featuring contributions from a diverse range of internationally recognized experts and practitioners, this timely volume discusses recent developments in the field in the context of related scholarship, public policy, formal and non-formal teaching and learning, and DIY and community practice. Offering a truly global perspective, the Handbook focuses on empirical work from Media and Information Literacy (MIL) practitioners from around the world. The book's five parts explTable of ContentsForeword xiUlla Carlsson About the Editors xix Notes on Contributors xxi Introduction: Media Education Research in a Rapidly Changing Media Environment 1Stuart R. Poyntz, Divina Frau-Meigs, Michael Hoechsmann, Sirkku Kotilainen, and Manisha Pathak-Shelat Part I Global Youth Cultures 17Stuart R. Poyntz 1 Micro-Celebrity Communities, and Media Education: Understanding Fan Practices on YouTube and Wattpad 19Michael Dezuanni 2 Memes Production as Parodic Activism: Inclusion and Exclusion in Young People’s Digital Participation in Latin America 33Rosalía Winocur and Inés Dussel 3 Youth, ICTs, and “Violent Extremism”: A Media Education Perspective 47Sanjay Asthana 4 Unaccompanied Refugee Children and Media Literacy: Doing Media Education Research on the Margins 61Annamária Neag 5 The Change in Young Australians’ Television Viewing Behavior and What It Means for the Future of Local Content 75Marc C-Scott 6 “We Don’t Do That Here” and “Isme Tera Ghata, Mera Kuch Nahi Jata”: Young People’s Meme Cultures in India 85Devina Sarwatay 7 Toward Hybridized and Glocalized Youth Identities in Africa: Revisiting Old Concerns and Reimagining New Possibilities for Media Education 97Chikezie E. Uzuegbunam 8 Social Media Influences on Youth with Disabilities in the Global South 105Tafadzwa Rugoho Part II Pedagogies and Practices 113Manisha Pathak‐Shelat 9 Toward Transmedia Learning: Practices, Approaches, and Tools 115Maria-Jose Masanet, Gabriella Taddeo, and Simona Tirocchi 10 Youth Media Education in the Age of Algorithm-Driven Social Media 131Sirkku Kotilainen, Jussi Okkonen, Jaakko Vuorio, and Karoliina Leisti 11 Integrating Nonviolent Communication in Pedagogies of Media Literacy Education 141Vedabhyas Kundu 12 Different Countries, Similar Issues: Media Binds or Blinds? 155Melda N. Yildiz 13 Teaching Gender and Sexuality in a Critical Media Literacy Framework: Curriculum, Pedagogical Interventions, and Autoethnographic Reflections 167Ruchi Jaggi 14 Competencies About the News for Elementary School Children 175Ioli Campos 15 Looking for Digital (Alter) Natives: Why Teachers’ Beliefs About Children Matter in Media Education 183Pekka Mertala and Saara Salomaa 16 Understanding Media Regulation in the Public Interest 189Robert Beveridge 17 “Doing Journalism Isn’t Lying” – Literacies and Fake News in an Experience with Children in the Invisibility Triad 195Lumárya Souza de Sousa and Thaiane Oliveira 18 Teaching Media Literacy Through Scientific Controversies 201José Azevedo 19 Teaching Interactive Narratives: Developing User Engagement Through Theory-Empowered Practice 207Willemien Sanders Part III Histories 215Michael Hoechsmann 20 Media Education History: The Early Years 217Keval J. Kumar 21 Media Education 3.0? How Big Data, Algorithms, and AI Redefine Media Education 229Grzegorz Ptaszek 22 Media Education in Latin America: The Paradigm of Educommunication 241Cláudia Lago, Claudemir E. Viana, Maria Cristina Palma Mungioli, and Marciel Consani 23 A Brief History of Media Education in Chile 253Pablo Andrada and Cristian Cabalin 24 Nordic Perspectives on the History and Future of Media Education 259Reijo Kupiainen and Daniel Schofield 25 Media Education in Israel – Mainstreaming the Avant-Garde 267Arielle Friedman, Ornat Turin, and Orly Melamed 26 Media Education in the Czech Republic: Vision and Disconnection 275Lucie Römer 27 Media Education in India: Policy and Praxis in Old and New Communication Media 281C.S.H.N. Murthy Part IV Institutions and Policy Developments 289Divina Frau‐Meigs 28 Defining Media Education Policies: Building Blocks, Scope, and Characteristics 291Normand Landry and Christiane Caneva 29 The Development of Media Literacy in Chinese Societies: From Grassroots Efforts to Institutional Support 309Alice Y.L. Lee 30 Digital Privacy Policy Literacy: A Framework for Canadian Youth 327Leslie Regan Shade and Sharly Chan 31 Searching for Common Ground: Multiliteracy and Curricular Consistency in the Finnish Education System 339Lauri Palsa 32 Taking Media Literacy Education in Armenia to the Next Level: From Civil Society Movement to Post-Revolution Government Efforts 347Lusine Grigoryan 33 Media Education Challenges in a Digital Society: The Case of Chile 355Rayén Condeza Dall’Orso, Myrna Gálvez Johnson, Nadia Herrada Hidalgo, and Francisco J. Fernandez Medina 34 Landscape and Terrain of Digital Literacy Policy and Practice: Canada in the Twenty-First Century 363Helen DeWaard and Michael Hoechsmann 35 Media Education Policy Developments in Times of “Fake News”: The Case of the Czech Republic 373Markéta Supa, Lucie Štástna, and Jan Jirak Part V Critical Citizenship and Futures 381Sirkku Kotilainen 36 Expanding Ethics to the Environment with Ecomedia Literacy 383Antonio Lopez 37 Engaging the World: Social Media Literacy for Transcultural Citizenship 399Manisha Pathak-Shelat and Kiran Vinod Bhatia 38 Data and Privacy Literacy: The Role of the School in Educating Children in a Datafied Society 413Sonia Livingstone, Mariya Stoilova, and Rishita Nandagiri 39 Media Education and Dynamic Research: Known Unknowns and Rich Intersections 427Julian McDougall and Isabella Rega 40 Radical Media Education Practices from Social Movement Media: Lessons from Teaching and Learning in Lebanon 441Gretchen King 41 Activating Student Voice and Choice Globally: Reframing Negative Narratives in Ghana 449Ed Madison 42 Advocacy as Media Education: The Educational Activities of Digital Rights Advocates 459Efrat Daskal 43 Cyberbullying, Media Education, and Agents of Socialization in Montenegro 467Ida Cortoni and Jelena Perović Index 475

Read more less

Book SynopsisA practical review of state-of-the-art non-contiguous multicarrier technologies that are revolutionizing how data is transmitted, received, and processed This book addresses the advantages and the limitations of modern multicarrier technologies and how to meet the challenges they pose using non-contiguous multicarrier technologies and novel algorithms that enhance spectral efficiency, interference robustness, and reception performance. It explores techniques using non-contiguous subcarriers which allow for flexible spectrum aggregation while achieving high spectral efficiency and flexible transmission and reception at lower OSI layers. These include non-contiguous orthogonal frequency division multiplexing (NC-OFDM), its enhanced version, non-contiguous filter-bank-based multicarrier (NC-FBMC), and generalized multicarrier. Following an overview of current multicarrier technologies for radio communication, the authors examine particular properties of these technTable of ContentsPreface ix List of Abbreviations xiii 1 Introduction 1 1.1 5G Radio Communications 2 1.2 Challenges for Future Radio Communications 6 1.3 Initiatives for the Future Radio Interface Definition 8 2 Multicarrier Technologies in Radio Communication Systems 11 2.1 The Principles of OFDM 15 2.2 Nonlinear Distortions in Multicarrier Systems 18 2.2.1 Power Amplifier Models 22 2.3 PAPR Reduction Methods 25 2.4 Link Adaptation in Multicarrier Systems 31 2.5 Reception Techniques and CFO Sensitivity 35 2.5.1 Synchronization 35 2.5.2 Channel Estimation and Equalization 40 3 Noncontiguous OFDM for Future Radio Communications 45 3.1 Enhanced NC-OFDM with Cancellation Carriers 54 3.1.1 Reception Quality Improvement for Cancellation Carrier Method 57 3.1.2 Reduced-Complexity Reduced-Power Combination of CCs and Windowing 63 3.1.3 Rate and Power Issues with the CC Method 64 3.2 Reduction of Subcarrier Spectrum Sidelobes by Flexible Quasi-Systematic Precoding 69 3.2.1 Precoder Design 70 3.2.2 Reception Quality Improvement for NC-OFDM with Quasi-Systematic Precoding 72 3.3 Optimized Cancellation Carriers Selection 77 3.3.1 Computational Complexity 80 3.3.2 Heuristic Approach to OCCS 80 3.4 Reduction of Nonlinear Effects in NC-OFDM 85 3.4.1 Sequential PAPR and OOB Power Reduction 88 3.4.2 Joint Non-linear Effects Reduction with Extra Carriers 91 3.5 NC-OFDM Receiver Design 101 3.5.1 NC-OFDM Receiver Synchronization 103 3.5.2 In-Band-Interference Robust Synchronization Algorithm for an NC-OFDMSystem 106 3.5.3 Performance Evaluation 119 3.5.4 Computational Complexity 126 3.6 Summary: Potentials and Challenges of NC-OFDM 127 4 Generalized Multicarrier Techniques for 5G Radio 131 4.1 The Principles of GMC 132 4.1.1 Frame Theory and Gabor Transform 135 4.1.2 Short-Time Fourier Transform and Gabor Transform 140 4.1.3 Calculation of the Dual Pulse 141 4.1.4 GMC Transceiver Design Using Polyphase Filters 143 4.2 Peak-to-Average Power Ratio Reduction in GMC Transmitters 145 4.2.1 Optimization of the Synthesis Pulse Shape for Minimization of Nonlinear Distortions 145 4.2.2 Active Constellation Extension for GMC Signals 150 4.3 Link Adaptation in GMC Systems 159 4.3.1 Two-DimensionalWater-Filling 159 4.3.2 AdaptiveModulation in GMC Transmitters 165 4.3.3 Application of the Modified Hughes–Hartogs Algorithm in GMC Systems 167 4.3.4 Remarks on Link Adaptation in the GMC Transmission 170 4.4 GMC Receiver Issues 173 4.4.1 Received Signal Analysis 174 4.4.2 Successive Interference Cancellation (SIC) 177 4.4.3 Parallel Interference Cancellation (PIC) 179 4.4.4 Hybrid Interference Cancellation (HIC) 181 4.5 Summary 190 5 Filter-Bank-Based Multicarrier Technologies 193 5.1 The Principles of FBMC Transmission 194 5.2 FBMC Transceiver Design 196 5.3 Pulse Design 199 5.3.1 Nyquist Filters and Ambiguity Function 199 5.3.2 IOTA Function 200 5.3.3 PHYDYAS Pulse 203 5.3.4 Other Pulse-Shape Proposals for FBMC 205 5.4 Practical FBMC System Design Issues 207 5.4.1 Self-Interference Problem in the FBMC Systems 207 5.4.2 Computational Complexity 209 5.4.3 Limitations of FBMC in Burst Transmission Schemes 211 5.4.4 MIMO technique for FBMC Transmission 211 5.5 Filter-bank-Based Multicarrier Systems Revisited 213 5.6 Summary 218 6 Multicarrier Technologies for Flexible Spectrum Usage 219 6.1 Cognitive Radio 219 6.2 Spectrum Sharing and Licensing Schemes 223 6.2.1 Exclusive Use of Spectrum 225 6.2.2 License Exempt Rules 225 6.2.3 Licensed Shared Access and Authorized Shared Access 226 6.2.4 Citizen Broadband Radio Service and Spectrum Access System 226 6.2.5 Pluralistic Licensing 227 6.2.6 Licensed Assisted Access 227 6.2.7 Co-Primary Shared Access 228 6.3 Dynamic Spectrum Access Based on Multicarrier Technologies 228 6.3.1 DSA Based on Spectrum Pricing 229 6.3.2 DSA Based on Coopetition 231 6.4 Dynamic Spectrum Aggregation 231 6.4.1 Complexity and Aggregation Dynamics 236 6.4.2 Transmitter Issues 237 6.4.3 Receiver Issues 239 6.4.4 Throughput Maximization 241 6.5 Summary 245 7 Conclusions and Future Outlook 247 References 251 Index 283

Read more less

Book SynopsisA hands-on guide to image registration theory and methods with examples of a wide range of real-world applications Theory and Applications of Image Registration offers comprehensive coverage of feature-based image registration methods.Table of ContentsContributors xv Acknowledgments xvii About the Companion Website xix 1 Introduction 1 1.1 Organization of the Book 3 1.2 Further Reading 5 References 5 2 Image Orientation Detection 9 2.1 Introduction 9 2.2 Geometric Gradient and Geometric Smoothing 13 2.2.1 Calculating Geometric Gradients 15 2.3 Comparison of Geometric Gradients and Intensity Gradients 18 2.4 Finding the Rotational Difference between Two Images 21 2.5 Performance Evaluation 23 2.5.1 Reliability 23 2.5.2 Accuracy 31 2.5.3 Computational Complexity 32 2.6 Registering Images with a Known Rotational Difference 34 2.7 Discussion 36 2.8 Further Reading 37 References 40 3 Feature Point Detection 43 3.1 Introduction 43 3.2 Variant Features 44 3.2.1 Central Moments 44 3.2.2 Uniqueness 48 3.3 Invariant Features 50 3.3.1 Rotation-Invariant Features 50 3.3.1.1 Laplacian of Gaussian (LoG) Detector 51 3.3.1.2 Entropy 53 3.3.1.3 InvariantMoments 55 3.3.2 SIFT: A Scale-and Rotation-Invariant Point Detector 58 3.3.3 Radiometric-Invariant Features 60 3.3.3.1 Harris Corner Detector 60 3.3.3.2 Hessian Corner Detector 63 3.4 Performance Evaluation 64 3.5 Further Reading 68 References 68 4 FeatureLineDetection 75 4.1 Hough Transform Using Polar Equation of Lines 79 4.2 Hough Transform Using Slope and y-Intercept Equation of Lines 82 4.3 Line Detection Using Parametric Equation of Lines 86 4.4 Line Detection by Clustering 89 4.5 Line Detection by Contour Tracing 92 4.6 Line Detection by Curve Fitting 95 4.7 Line Detection by Region Subdivision 101 4.8 Comparison of the Line Detection Algorithms 106 4.8.1 Sensitivity to Noise 106 4.8.2 Positional and Directional Errors 106 4.8.3 Length Accuracy 109 4.8.4 Speed 109 4.8.5 Quality of Detected Lines 109 4.9 Revisiting Image Dominant Orientation Detection 117 4.10 Further Reading 121 References 125 5 Finding Homologous Points 133 5.1 Introduction 133 5.2 Point Pattern Matching 134 5.2.1 Parameter Estimation by Clustering 137 5.2.2 Parameter Estimation by RANSAC 141 5.3 Point Descriptors 146 5.3.1 Histogram-Based Descriptors 147 5.3.2 SIFT Descriptor 148 5.3.3 GLOH Descriptor 151 5.3.4 Composite Descriptors 152 5.3.4.1 Hu InvariantMoments 152 5.3.4.2 Complex Moments 152 5.3.4.3 Cornerness Measures 153 5.3.4.4 Power Spectrum Features 154 5.3.4.5 Differential Features 155 5.3.4.6 Spatial Domain Features 155 5.4 SimilarityMeasures 160 5.4.1 Correlation Coefficient 160 5.4.2 Minimum Ratio 161 5.4.3 Spearman’s ;; 161 5.4.4 Ordinal Measure 162 5.4.5 Correlation Ratio 162 5.4.6 Shannon Mutual Information 164 5.4.7 Tsallis Mutual Information 165 5.4.8 F-Information 166 5.5 Distance Measures 167 5.5.1 Sum of Absolute Differences 167 5.5.2 Median of Absolute Differences 167 5.5.3 Square Euclidean Distance 168 5.5.4 Intensity-Ratio Variance 168 5.5.5 Rank Distance 169 5.5.6 Shannon Joint Entropy 169 5.5.7 Exclusive F-Information 170 5.6 TemplateMatching 170 5.6.1 Coarse-to-Fine Matching 171 5.6.2 MultistageMatching 172 5.6.3 Rotationally InvariantMatching 173 5.6.4 Gaussian-Weighted TemplateMatching 174 5.6.5 Template Matching in Different Modality Rotated Images 175 5.7 Robust Parameter Estimation 178 5.7.1 Ordinary Least-Squares Estimator 180 5.7.2 Weighted Least-Squares Estimator 182 5.7.3 Least Median of Squares Estimator 184 5.7.4 Least Trimmed Squares Estimator 184 5.7.5 Rank Estimator 185 5.8 Finding Optimal Transformation Parameters 193 5.9 Performance Evaluation 193 5.10 Further Reading 197 References 200 6 Finding Homologous Lines 215 6.1 Introduction 215 6.2 Determining Transformation Parameters from Line Parameters 215 6.3 Finding Homologous Lines by Clustering 221 6.3.1 Finding the Rotation Parameter 222 6.3.2 Finding the Translation Parameters 223 6.4 Finding Homologous Lines by RANSAC 229 6.5 Line Grouping Using Local Image Information 232 6.6 Line Grouping Using Vanishing Points 235 6.6.1 Methods Searching the Image Space 235 6.6.2 Methods Searching the Polar Space 236 6.6.3 Methods Searching the Gaussian Sphere 236 6.6.4 A Method Searching Both Image and Gaussian Sphere 237 6.6.5 Measuring the Accuracy of Detected Vanishing Points 244 6.6.6 Discussion 247 6.7 Robust Parameter Estimation Using Homologous Lines 253 6.8 Revisiting Image Dominant Orientation Detection 255 6.9 Further Reading 256 References 257 7 Nonrigid Image Registration 261 7.1 Introduction 261 7.2 Finding Homologous Points 262 7.2.1 Coarse-to-Fine Matching 262 7.2.2 Correspondence by Template Matching 269 7.3 Outlier Removal 274 7.4 Elastic Transformation Models 278 7.4.1 Surface Spline (SS) Interpolation 280 7.4.2 Piecewise Linear (PWL) Interpolation 282 7.4.3 Moving Least Squares (MLS) Approximation 283 7.4.4 Weighted Linear (WL) Approximation 285 7.4.5 Performance Evaluation 287 7.4.6 Choosing the Right Transformation Model 291 7.5 Further Reading 292 References 293 8 Volume Image Registration 299 8.1 Introduction 299 8.2 Feature Point Detection 301 8.2.1 Central Moments 301 8.2.2 Entropy 302 8.2.3 LoG Operator 302 8.2.4 First-Derivative Intensities 303 8.2.5 Second-Derivative Intensities 304 8.2.6 Speed-Up Considerations in Feature Point Detection 305 8.2.7 Evaluation of Feature Point Detectors 305 8.3 Finding Homologous Points 307 8.3.1 Finding Initial Homologous Points Using Image Descriptors 310 8.3.2 Finding Initial Homologous Points by Template Matching 313 8.3.3 Finding Final Homologous Points from Coarse to Fine 315 8.3.4 Finding the Final Homologous Points by Outlier Removal 320 8.4 Transformation Models for Volume Image Registration 321 8.4.1 Volume Spline 323 8.4.2 Weighted Rigid Transformation 325 8.4.3 Computing the Overall Transformation 327 8.5 Performance Evaluation 330 8.5.1 Accuracy 330 8.5.2 Reliability 333 8.5.3 Speed 333 8.6 Further Reading 335 References 337 9 Validation Methods 343 9.1 Introduction 343 9.2 Validation Using Simulation Data 344 9.3 Validation Using a Gold Standard 345 9.4 Validation by an Expert Observer 347 9.5 Validation Using a Consistency Measure 348 9.6 Validation Using a Similarity/DistanceMeasure 350 9.7 Further Reading 351 References 352 10 Video Image Registration 357 EdgardoMolina,Wai Lun Khoo, Hao Tang, and Zhigang Zhu 10.1 Introduction 357 10.2 Motion Modeling 358 10.2.1 The Motion Field of Rigid Objects 358 10.2.2 Motion Models 360 10.2.2.1 Pure Rotation and a 3-D Scene 361 10.2.2.2 General Motion and a Planar Scene 362 10.2.2.3 TranslationalMotion and a 3-D Scene 363 10.3 Image Alignment 365 10.3.1 Feature-Based Methods 367 10.3.2 Mechanical-Based Methods 369 10.4 Image Composition 370 10.4.1 Compositing Surface 370 10.4.2 ImageWarping 371 10.4.3 Pixel Selection and Blending 373 10.5 Application Examples 374 10.5.1 Pushbroom Stereo Mosaics Under TranslationalMotion 374 10.5.1.1 Parallel-Perspective Geometry and Panoramas 374 10.5.1.2 Stereo and Multiview Panoramas 376 10.5.1.3 Results 378 10.5.2 Stereo Mosaics when Moving a Camera on a Circular Path 378 10.5.2.1 Circular Geometry 379 10.5.2.2 Stereo Geometry 379 10.5.2.3 Geometry and ResultsWhen Using PRISM 381 10.5.3 Multimodal Panoramic Registration of Video Images 382 10.5.3.1 Concentric Geometry 383 10.5.3.2 Multimodal Alignment 385 10.5.3.3 Results 387 10.5.4 Video Mosaics Under GeneralMotion 387 10.5.4.1 Direct Layering Approach 389 10.5.4.2 Multiple Runs and Results 392 10.6 Further Reading 393 References 395 11 Multitemporal Image Registration 397 11.1 Introduction 397 11.2 Finding Transformation Parameters from Line Parameters 398 11.3 Finding an Initial Set of Homologous Lines 399 11.4 Maximizing the Number of Homologous Lines 403 11.5 Examples of Multitemporal Image Registration 406 11.6 Further Reading 413 References 415 12 Open Problems and Research Topics 419 12.1 Finding Rotational Difference between Multimodality Images 419 12.2 Designing a Robust Image Descriptor 420 12.3 Finding Homologous Lines for Nonrigid Registration 421 12.4 Nonrigid Registration Using Homologous Lines 423 12.5 Transformation Models with Nonsymmetric Basis Functions 423 12.6 Finding Homologous Points along Homologous Contours 426 12.7 4-D Image Registration 429 References 430 Glossary 433 Acronyms 437 Symbols 439 A Image Registration Software 441 A.1 Chapter 2: Image Orientation Detection 441 A.1.1 Introduction 441 A.1.2 Operations 442 A.2 Chapter 3: Feature Point Detection 444 A.2.1 Introduction 444 A.2.2 Operations 445 A.3 Chapter 4: Feature Line Detection 448 A.3.1 Introduction 448 A.3.2 Operations 449 A.4 Chapter 5: Finding Homologous Points 452 A.4.1 Introduction 452 A.4.2 Operations 452 A.5 Chapter 6: Finding Homologous Lines 459 A.5.1 Introduction 459 A.5.2 Operations 460 A.6 Chapter 7: Nonrigid Image Registration 469 A.6.1 Introduction 469 A.6.2 Operations 469 A.7 Chapter 8: Volume Image Registration 479 A.7.1 Introduction 479 A.7.2 I/O File Formats 479 A.7.3 Operations 480 References 487 Index 489

Read more less

Book SynopsisExplore foundational and advanced topics in nanoscience with this intuitive introduction In the newly revised Second Edition of Introduction to Nanoscience and Nanotechnology, renowned researcher Dr. Chris Binns delivers an accessible and broad-based treatment of nanoscience and nanotechnology. Beginning with the fundamental physicochemical properties of nanoparticles and nanostructures, the book moves on to discuss how these properties can be exploited to produce high-performance materials and devices. Following chapters explore naturally occurring nanoparticles and artificially engineered carbon nanoparticles, their mechanical properties, and their applications in nanotechnological science. Both design ideologies for manufacturing nanostructuresbottom-up and top-downare examined, as is the idea that the two methodologies can be combined to allow for the imaging, probing, and manipulation of nanostructures. A survey of the current state of nanoteTable of ContentsPreface to Second Edition ix Acknowledgments x Introduction to Second Edition 1 1 Size Matters 13 1.1 The Fundamental Importance of Size 13 1.2 The Magnetic Behavior of Nanoparticles 16 1.3 The Mechanical Properties of Nanostructured Materials 26 1.4 The Chemical Properties of Nanoparticles 27 1.5 Nanoparticles Interacting with Bacteria and Viruses 29 Problems 31 References 32 2 Nanoparticles and the Environment 35 2.1 Nanoparticles in the Atmosphere 35 2.2 Atmospheric Nanoparticles and Health 39 2.2.1 Entry Via the Lungs 39 2.2.2 Entry Via the Intestines 42 2.2.3 Nanoparticles and the Skin 43 2.2.4 Air Quality Specifications 44 2.3 Nanoparticles and Clouds 44 2.4 Marine Aerosol 48 2.5 Effect of Cosmic Rays on Atmospheric Aerosol 50 2.6 Nanoparticles in Space 51 2.7 Environmental Applications of Nanoparticles 52 2.7.1 Water Remediation Using Magnetic Nanoparticles 52 2.7.2 Conversion of Waste Plastics to High-Grade Materials (Upcycling) 55 Problems 57 References 59 3 Carbon Nanostructures: Bucky Balls and Nanotubes 61 3.1 Why Carbon? 61 3.2 Discovery of the First Fullerene – C60 62 3.3 Structural Symmetry of the Closed Fullerenes 64 3.4 Smaller Fullerenes and “Shrink-Wrapping” Atoms 68 3.5 Larger Fullerenes 70 3.6 Electronic Properties of Individual Fullerenes 72 3.7 Materials Produced by Assembling Fullerenes (Fullerites and Fullerides) 76 3.8 Discovery of Carbon Nanotubes 81 3.9 Structure of Single-Wall Carbon Nanotubes (SWNTs) 82 3.10 Electronic Properties of SWNTs 84 3.11 Electronic Transport in Carbon Nanotubes 86 3.12 Field Emission from Carbon Nanotubes 87 3.13 Mechanical Properties of Nanotubes 88 3.14 Thermal Conductivity of Nanotubes 92 3.15 Carbon Nanohorns 93 3.16 Carbon Nanobuds and Pea Pods 94 Problems 95 References 96 4 Graphene 99 4.1 Background 99 4.1.1 Low-Dimensional Materials 99 4.1.2 Discovery of Graphene 101 4.2 Electrical Properties of Graphene 101 4.2.1 Electrical Conduction in Normal Metals 101 4.2.2 Electrical Conduction in Semiconductors 104 4.2.3 Electrical Conduction in Graphene 107 4.3 Graphene as a Testbed for Relativistic Quantum Effects 112 4.4 Thermal Conductivity of Graphene 112 4.5 Mechanical Strength of Graphene 116 4.6 Superconductivity in Graphene Bilayers 117 4.7 Current Technological Applications of Graphene 120 4.7.1 Graphene Batteries 120 4.7.2 Graphene Nanoelectromechanical Systems (NEMS) Accelerometers 124 4.7.3 Graphene Membranes for Water Desalination 125 4.8 Summary 126 Problems 126 References 128 5 The Nanotechnology Toolkit 131 5.1 Making Nanostructures Using Bottom–Up Methods 131 5.1.1 Making Nanoparticles Using Supersaturated Vapor 131 5.1.2 Sources Producing Nanoparticle Beams in Vacuum 133 5.1.3 Synthesis of Alloy, Core–Shell, and Janus Nanoparticles 137 5.1.4 Mass Selection of Charged Nanoparticle Beams in Vacuum 141 5.1.5 Aerodynamic Lensing and Mass Selection of Neutral Nanoparticles 147 5.1.6 Plasma, Spark and Flame Metal Aerosol Sources 147 5.1.7 Size Selection of Nanoparticles in Aerosols 150 5.1.8 Chemical Synthesis of Nanoparticles in Liquid Suspensions 153 5.1.9 Biological Synthesis of Magnetic Nanoparticles 156 5.1.10 Gas-Phase Synthesis of Hydrosols 157 5.1.11 Size Determination of Nanoparticles in Liquids 157 5.1.12 Synthesis of Graphene 160 5.1.13 Synthesis of Fullerenes 162 5.1.14 Synthesis of Carbon Nanotubes 163 5.1.15 Controlling the Growth of SWNTs 165 5.2 Making Nanostructures Using Top–Down Methods 167 5.2.1 Electron-Beam Lithography 168 5.2.2 Manufacturing Nanostructures Using Focused Ion Beams 171 5.3 Combining Bottom–up and Top–Down Nanostructures 176 5.4 Imaging, Probing, and Manipulating Nanostructures 180 5.4.1 Scanning Tunneling Microscope 180 5.4.2 Manipulating Atoms and Molecules with STM 185 5.4.3 Scanning Tunneling Spectroscopy (STS) 189 5.4.4 Atomic Force Microscopy 192 5.4.5 AFM Imaging of Biological Samples in Liquids 195 5.4.6 Dip-Pen Nanolithography 198 5.4.7 Electron Microscopy 200 Problems 204 References 206 6 Single-Nanoparticles Devices 211 6.1 Data Storage on Magnetic Nanoparticles 211 6.2 Quantum Dots 218 6.3 Quantum Dot Solar Cells 222 6.4 Nanoparticles as Transistors 226 6.5 Carbon Nano-Electronics 232 6.5.1 Fullerene SET 232 6.5.2 Porphyrin Molecule SET 234 6.5.3 Carbon Nanotube SET 236 6.5.4 Limitations of SETs in Applications and Moving to Multiple Transistor Devices 236 6.6 Carbon Nanotube Light Emitters and Detectors 239 Problems 240 References 240 7 Hydrosols, Nanobubbles, and Nanoscale Interfaces 243 7.1 Reynolds Number 243 7.2 Brownian Motion 245 7.3 Stability of Hydrosols 250 7.4 Nanobubbles 257 7.4.1 Fundamental Considerations 257 7.4.2 Synthesis of Bulk Nanobubbles 260 7.4.3 Properties of Bulk Nanobubbles 262 7.4.4 Surface Nanobubbles 265 7.4.5 Applications of Nanobubbles 267 7.5 Nanofluidics 271 Problems 277 References 278 8 Magic Beacons and Magic Bullets: The Medical Applications of Functional Nanoparticles 281 8.1 Nanoparticles Interacting with Living Organisms 282 8.1.1 Targeted Nanovectors for Therapy and Diagnosis 282 8.1.2 Uptake of Nanomaterials by the Body 284 8.1.3 Types of Core Nanoparticle in Nanovectors 286 8.1.4 Targeting to Tumors by Enhanced Permeability and Retention (EPR) 288 8.1.5 Some Elementary Cell Biology 289 8.1.5.1 The Outer Cell Membrane (Plasma Membrane) 290 8.1.5.2 Membrane Proteins 291 8.1.5.3 Internal Cell Structure 292 8.1.5.4 Cytoskeleton 292 8.1.6 “Trojan horse” Targeting Using Stem Cells and Macrophages 294 8.1.7 Molecular Targeting 296 8.1.8 Magnetic Targeting 302 8.2 Treatment of Tumors by Hyperthermia 304 8.2.1 Biological Response to Heating 304 8.2.2 Magnetic Nanoparticle Hyperthermia (MNH) 307 8.2.2.1 Current State of the art in Clinical Trials 307 8.2.2.2 Limitations on the Applied RF Magnetic Field 309 8.2.2.3 Heating Mechanisms of Magnetic Nanoparticles in an AMF 311 8.2.2.4 New Nanoparticles for MNH 316 8.2.3 Optical Hyperthermia Using Near-Infrared Radiation 318 8.2.4 Hyperthermia with Carbon Nanotubes 326 8.3 Medical Diagnosis and “Theranostics” using Nanomaterials 327 8.3.1 Magnetic Resonance Imaging (MRI) and Contrast Enhancement Using Magnetic Nanoparticles 328 8.3.2 Magnetic Particle Imaging (MPI) 331 8.3.3 Imaging Using Au Nanoparticles 337 8.3.4 Imaging Using QDs 339 8.4 Antibacterial and Antiviral Applications of Nanoparticles 343 8.4.1 Nanoparticle Delivery Systems for Covid 19 Vaccines 343 8.4.2 Antibacterial Action of Ag Nanoparticles 343 8.4.3 Antiviral Action of Nanoparticles 346 Problems 347 References 348 9 Radical Nanotechnology 355 9.1 Locomotion for Nanobots and Nanofactories 356 9.1.1 Movement Within the Nanofactory using Kinesin 356 9.1.2 Moving Small Cargo in the Nanofactory: DNA Walkers 364 9.1.3 Propulsion for Swimmers 369 9.2 Onboard Processing for Nanomachines 374 9.3 Medical Micro/Nanobots 374 9.4 Molecular Assembly 376 Problems 379 References 379 10 Prodding the Cosmic Fabric 381 10.1 Zero-Point Energy of Space 381 10.2 The Casimir Force 385 10.3 The Casimir Force in Micro-and Nanomachines 389 10.4 Controlling the Casimir Force Using Phase-Change Materials 394 10.5 Repulsive Casimir Forces 395 Problems 397 References 398 Glossary 401 Index 403

Read more less

Book SynopsisA guide to the latest developments in grid dynamics and control and highlights the role of transmission and distribution grids Dynamics and Control of Electric Transmission and Microgrids offers a concise and comprehensive review of the most recent developments and research in grid dynamics and control. In addition, the authors present a new style of presentation that highlights the role of transmission and distribution grids that ensure the reliability and quality of electric power supply. The authors noted experts in the field offer an introduction to the topic and explore the basic characteristics and operations of the grid. The text also reviews a wealth of vital topics such as FACTS and HVDC Converter controllers, the stability and security issues of the bulk power system, loads which can be viewed as negative generation, the power limits and energy availability when distributed storage is used and much more. This important resource: Puts the focus on the role of transmissionTrade ReviewThis textbook is one of the first on Power System Dynamics, Control and Stability to integrate in a straightforward and illustrative way the recently introduced modern power system components, such as Renewable Energy Sources (RES), converter interfaced generating sources, FACTS, energy storage devices, and wide area measurement systems (WAMS), in the same, common and well defined framework with the more conventional component, such as Synchronous Generators. - C. Vournas, NTUA, Athens, GreeceTable of ContentsPreface xiii Acknowledgements xv 1 Introduction 1 1.1 Present Status of Grid Operation 1 1.1.1 General 1 1.1.2 HVDC Transmission 4 1.1.3 Reliability of Electricity Supply 4 1.2 Overview of System Dynamics and Control 4 1.2.1 Power System Stability 4 1.2.2 Mathematical Preliminaries 6 Stability of Equilibrium Point 6 Steady-State Behavior 8 1.2.3 Power System Security 8 1.3 Monitoring and Enhancing System Security 10 1.4 Emergency Control and System Protection 11 1.5 Recent Developments 12 1.5.1 Power System Protection 12 1.5.2 Development of Smart Grids 13 1.5.3 Microgrids 14 1.5.4 Role of System Dynamics and Control 14 1.6 Outline of Chapters 14 References 17 2 Grid Characteristics and Operation 19 2.1 Description of Electric Grids 19 2.2 Detailed Modeling of Three-Phase AC Lines 21 2.3 Circuit Models of Symmetric Networks 22 2.4 Network Equations in DQo and 𝛼𝛽o Components 23 2.4.1 Transformation to Park (dqo) Components 24 2.4.2 Steady-State Equations 25 2.4.3 D-Q Transformation using 𝛼-𝛽 Variables 26 2.5 Frequency and Power Control 28 2.5.1 Tie-Line Bias Frequency Control 31 2.6 Dynamic Characteristics of AC Grids 33 2.6.1 Grid Response to Frequency Modulation 33 2.6.2 Grid Response to Injection of Reactive Current 35 2.7 Control of Power Flow in AC Grids 38 2.7.1 Power Transfer Capability of a Line 38 2.7.2 Power Flow in a Line connected to an AC Transmission Grid 41 2.8 Analysis of Electromagnetic Transients 42 2.8.1 Modeling of Lumped Parameter Components 42 2.8.2 Modeling of a Single-Phase Line 43 2.8.3 Approximation of Series Resistance of Line 44 2.8.4 Modeling of Lossless Multiphase Line 45 2.8.5 Modeling of Multiphase Networks with Lumped Parameters 46 2.9 Transmission Expansion Planning 47 2.10 Reliability in Distribution Systems 48 2.11 Reliable Power Flows in a Transmission Network 48 2.12 Reliability Analysis of Transmission Networks 50 2.A Analysis of a Distributed Parameter Single-Phase Line in Steady State 51 2.A.1 Expressions for a Lossless Line 53 2.A.2 Performance of a Symmetrical Line 54 2.B Computation of Electrical Torque 55 References 57 3 Modeling and Simulation of Synchronous Generator Dynamics 59 3.1 Introduction 59 3.2 Detailed Model of a Synchronous Machine 59 3.2.1 Flux Linkage Equations 60 3.2.2 Voltage equations 61 3.3 Park’s Transformation 62 3.4 Per-Unit Quantities 69 3.5 Equivalent Circuits of a Synchronous Machine 72 3.6 Synchronous Machine Models for Stability Analysis 76 3.6.1 Application of Model (2.1) 80 3.6.2 Application of Model (1.1) 80 3.6.3 Modeling of Saturation 82 3.7 An Exact Circuit Model of a Synchronous Machine for Electromagnetic Transient Analysis 82 3.7.1 Derivation of the Circuit Model 83 3.7.2 Transformation of the Circuit Model 87 3.7.3 Modeling of a Synchronous Generator in the Simulation of Electromagnetic Transients 91 3.7.4 Treatment of Dynamic Saliency 92 3.8 Excitation and Prime Mover Controllers 93 3.8.1 Excitation Systems 93 3.8.2 Modeling of Prime-Mover Control Systems 98 3.9 Transient Instability due to Loss of Synchronism 101 3.10 Extended Equal Area Criterion 103 3.11 Dynamics of a Synchronous Generator 104 Network Equations 104 Calculation of Initial Conditions 106 System Simulation 108 3.A Derivation of Electrical Torque 110 References 112 4 Modeling and Simulation of Wind Power Generators 115 4.1 Introduction 115 4.2 Power Extraction byWind Turbines 116 4.2.1 Wind Speed Characteristics 117 4.2.2 Control of Power Extraction 118 4.3 Generator and Power Electronic Configurations 120 4.3.1 Wind Farm Configurations 122 4.4 Modeling of the Rotating System 122 4.5 Induction Generator Model 124 4.5.1 Rotor Speed Instability 127 4.5.2 Modeling Issues 130 4.5.3 Frequency Conversion Using Voltage Source Converters 132 4.6 Control of Type IIIWTG System 133 4.6.1 Rotor-Side Converter Control 133 4.6.2 Grid-Side Converter Control 136 4.6.3 Overall Control Scheme for a Type III WTG system 137 4.6.4 Simplified Modeling of the Controllers for Slow Transient Studies 141 4.7 Control of Type IVWTG System 142 References 143 5 Modeling and Analysis of FACTS and HVDC Controllers 145 5.1 Introduction 145 5.2 FACTS Controllers 146 5.2.1 Description 146 5.2.2 A General Equivalent Circuit for FACTS Controllers 147 5.2.3 Benefits of the Application of FACTS Controllers 148 5.2.4 Application of FACTS Controllers in Distribution Systems 150 5.3 Reactive Power Control 150 Control Characteristics 153 5.4 Thyristor-Controlled Series Capacitor 153 5.4.1 Basic Concepts of Controlled Series Compensation 155 5.4.2 Operation of a TCSC 157 5.4.3 Analysis of a TCSC 158 5.4.4 Computation of the TCSC Reactance (XTCSC) 159 5.4.5 Control of the TCSC 161 5.5 Static Synchronous Compensator 166 5.5.1 General 166 5.5.2 Two-Level (Graetz Bridge) Voltage Source Converter 168 5.5.3 Pulse0020Width Modulation 169 5.5.4 Analysis of a Voltage Source Converter 171 5.5.5 Control of VSC 175 5.6 HVDC Power Transmission 177 5.6.1 Application of DC Transmission 178 5.6.2 Description of HVDC Transmission Systems 178 5.6.3 Analysis of a Line Commutated Converter 180 5.6.4 Introduction of VSC-HVDC Transmission 186 5.A Case Study of a VSC-HVDC Link 190 References 193 6 Damping of Power Swings 195 6.1 Introduction 195 6.2 Origin of Power Swings 196 6.3 SMIB Model with Field Flux Dynamics and AVR 199 6.3.1 Small-Signal Model and Eigenvalue Analysis 201 6.4 Damping and Synchronizing Torque Analysis 205 6.5 Analysis of Multi-Machine Systems 210 6.5.1 Electro-Mechanical Modes in a Multi-Machine System 210 6.5.2 Analysis with Detailed Models 216 6.6 Principles of Damping Controller Design 225 6.6.1 Actuator Location and Choice of Feedback Signals 229 6.6.2 Components of a PSDC 230 6.6.3 PSDCs based on Generator Excitation Systems: Power System Stabilizers 231 6.6.4 Adverse Torsional Interactions with the Speed/Slip Signal 237 6.6.5 Damping of Swings using Grid-Connected Power Electronic Systems 237 6.7 Concluding Remarks 241 6.A Eigenvalues of the Stiffness matrix K of Section 6.5.1 242 6.B Three-Machine Data 244 References 244 7 Analysis and Control of Loss of Synchronism 247 7.1 Introduction 247 7.2 Effect of LoS 247 7.3 Understanding the LoS Phenomenon 249 7.4 Criteria for Assessment of Stability 251 7.5 Power System Modeling and Simulation for Analysis of LoS 252 7.5.1 Effect of System Model 254 7.5.2 Effect of Changing Operating Conditions 255 7.6 Loss of Synchronism in Multi-Machine Systems 256 7.6.1 Effect of Disturbance Location on Mode of Separation: 258 7.6.2 Effect of the Load Model 258 7.6.3 Effect of Series Compensation in a Critical Line 260 7.6.4 Effect of a Change in the Pre-fault Generation Schedule 261 7.6.5 Voltage Phase Angular Differences across Critical Lines/Apparent Impedance seen by Relays 261 7.7 Measures to Avoid LoS 263 7.7.1 System Planning and Design 263 7.7.2 Preventive Control During Actual Operation 264 7.7.3 Emergency Control 264 7.8 Assessment and Control of LoS Using Energy Functions 265 7.8.1 Energy Function Method Applied to an SMIB System 266 7.8.2 Energy Function Method Applied to Multi-Machine Systems/Detailed Models 270 7.8.3 Evaluation of Critical Energy in a Multi-Machine System 274 7.9 Generation Rescheduling Using Energy Margin Sensitivities 274 7.9.1 Case Study: Generation Rescheduling 276 7.A Simulation Methods for Transient Stability Studies 276 7.A.1 Simultaneous Implicit Method 277 7.A.2 Partitioned Explicit Method 277 7.B Ten-Machine System Data 279 References 281 8 Analysis of Voltage Stability and Control 283 8.1 Introduction 283 8.2 Definitions of Voltage Stability 284 8.3 Comparison of Angle and Voltage Stability 286 8.3.1 Analysis of the SMLB System 287 8.4 Mathematical Preliminaries 290 8.5 Factors Affecting Instability and Collapse 292 8.5.1 Induction Motor Loads 292 8.5.2 HVDC Converter 293 8.5.3 Overexcitation Limiters 294 8.5.4 OLTC Transformers 295 8.5.5 A Nonlinear Dynamic Load Model 296 8.6 Dynamics of Load Restoration 296 8.7 Analysis of Voltage Stability and Collapse 298 8.7.1 Simulation 298 8.7.2 Small Signal (Linear) Analysis 298 8.8 Integrated Analysis of Voltage and Angle Stability 301 8.9 Analysis of Small Signal Voltage Instability Decoupled from Angle Instability 303 8.9.1 Decoupling of Angle and Voltage Variables 304 8.9.2 Incremental RCFN 305 8.9.3 Nonlinear Reactive Loads 306 8.9.4 Generator Model 306 Discussion 307 8.10 Control of Voltage Instability 308 References 308 9 Wide-AreaMeasurements and Applications 311 9.1 Introduction 311 9.2 Technology and Standards 311 9.2.1 Synchrophasor Definition 313 9.2.2 Reporting Rates 314 9.2.3 Latency and Data Loss 315 9.3 Modeling ofWAMS in Angular Stability Programs 315 9.4 Online Monitoring of Power Swing Damping 316 9.4.1 Modal Estimation based on Ringdown Analysis 317 9.4.2 Modal Estimation based on Probing Signals 319 9.4.3 Modal Estimation based on Ambient Data Analysis 323 9.5 WAMS Applications in Power Swing Damping Controllers 327 9.6 WAMS Applications in Emergency Control 330 9.7 Generator Parameter Estimation 335 9.8 Electro-MechanicalWave Propagation and Other Observations in Large Grids 335 References 338 10 Analysis of Subsynchronous Resonance 341 10.1 Introduction 341 10.2 Analysis of Electrical Network Dynamics 342 10.2.1 Equations in DQo Variables 344 10.2.2 Interfacing a DQ Network Model with a Generator Model 346 10.3 Torsional Dynamics of a Generator-Turbine System 353 10.3.1 Damping of Torsional Oscillations 359 10.3.2 Sensitivity of the Torsional Modes to the External Electrical System 360 10.4 Generator-Turbine and Network Interactions: Subsynchronous Resonance 362 10.4.1 Torsional Modes in Multi-Generator Systems 368 10.4.2 Adverse Interactions with Turbine-Generator Controllers 371 10.4.3 Detection of SSR/Torsional Monitoring 373 10.4.4 Countermeasures for Subsynchronous Resonance and Subsynchronous Torsional Interactions 374 10.4.5 Case Study: TCSC-Based SSDC 377 10.5 Time-InvariantModels of Grid-Connected Power Electronic Systems 378 10.5.1 Discrete-Time DynamicModels using the PoincaréMapping Technique 380 10.5.2 Dynamic Phasor-Based Modeling 380 10.5.3 Numerical Derivation of PES Models: A Frequency Scanning Approach 383 10.A Transfer Function Representation of the Network 385 References 386 11 Solar Power Generation and Energy Storage 391 11.1 Introduction 391 11.2 Solar Thermal Power Generation 392 11.3 Solar PV Power Generation 392 11.3.1 Solar Module I-V Characteristics 393 11.3.2 Solar PV Connections and Power Extraction Strategies 393 11.3.3 Power Electronic Converters for Solar PV Applications 395 11.3.4 Maximum Power Point Tracking Algorithms 397 11.3.5 Control of Grid-Connected Solar PV Plants 398 11.3.6 Low-Voltage Ride Through and Voltage Support Capability 400 11.4 Energy Storage 403 11.4.1 Attributes of Energy Storage Devices 404 11.4.2 Energy Storage Technologies 404 11.4.3 Mapping to Applications 406 11.4.4 Battery Modeling 410 References 412 12 Microgrids: Operation and Control 415 12.1 Introduction 415 12.2 Microgrid Concept 416 12.2.1 Definition of a Microgrid 416 12.2.2 Control System 417 12.3 Microgrid Architecture 419 12.4 Distribution Automation and Control 420 12.5 Operation and Control of Microgrids 421 12.5.1 DER Units 421 12.5.2 Microgrid Loads 423 12.5.3 DER Controls 423 12.5.4 Control Strategies under Grid-Connected Operation 425 12.5.5 Control Strategy for an Islanded Microgrid 427 12.6 Energy Management System 428 12.6.1 Microgrid Supervisory Control 429 12.6.2 Decentralized Microgrid Control based on a Multi-Agent System 430 12.6.3 IndustrialMicrogrid Controllers 431 12.7 Adaptive Network Protection in Microgrids 432 12.7.1 Protection Issues 433 12.7.2 Adaptive Protection 434 12.8 Dynamic Modeling of Distributed Energy Resources 435 12.8.1 Photovoltaic Array with MPP Tracker 435 12.8.2 Fuel Cells 437 12.8.3 Natural Gas Generator Set 438 12.8.4 Fixed-SpeedWind Turbine Driving SCIG 439 12.9 Some Operating Problems in Microgirds 442 12.10 Integration of DG and DS in a Microgrid 444 12.11 DC Microgrids 444 12.12 Future Trends and Conclusions 445 12.A A Three-Phase Model of an Induction Machine 448 References 452 A Equal Area Criterion 455 An Interesting Network Analogy 456 References 458 B Grid Synchronization and Current Regulation 459 Choice of Reference Frames 459 References 462 C Fryze–Buchbolz–Depenbrock Method for Load Compensation 463 C.1 Introduction 463 C.2 Description of FBDTheory 463 C.3 Power Theory in Multiconductor Circuits 466 Virtual Star Point 466 Collective Quantities 467 C.4 Examples 469 C.5 Load Characterization over a Period 470 C.6 Compensation of Non-Active Currents 471 Discussion 472 References 472 D Symmetrical Components and Per-Unit Representation 473 D.1 Symmetrical Component Representation of Three-Phase Systems 473 D.2 Per-Unit Representation 476 References 478 Index 479

Read more less

Book SynopsisA comprehensive collection of influential articles from one of IEEE Computer magazine's most popular columns This book is a compendium of extended and revised publications that have appeared in the Software Technologies column of IEEE Computer magazine, which covers key topics in software engineering such as software development, software correctness and related techniques, cloud computing, self-managing software and self-aware systems. Emerging properties of software technology are also discussed in this book, which will help refine the developing framework for creating the next generation of software technologies and help readers predict future developments and challenges in the field. Software Technology provides guidance on the challenges of developing software today and points readers to where the best advances are being made. Filled with one insightful article after another, the book serves to inform the conversation about the next wavTable of ContentsForeword xv Preface xix Acknowledgments xxiii List of Contributors xxv Part I The Software Landscape 1 1 Software Crisis 2.0 3Brian Fitzgerald 1.1 Software Crisis 1.0 3 1.2 Software Crisis 2.0 5 1.2.1 Hardware Advances 6 1.2.2 “Big Data” 8 1.2.3 Digital Natives Lifelogging and the Quantified Self 9 1.2.4 Software-Defined∗ 10 1.3 Software Crisis 2.0: The Bottleneck 10 1.3.1 Significant Increase in Volume of Software Required 11 1.3.2 New Skill Sets Required for Software Developers 12 1.4 Conclusion 13 References 14 2 Simplicity as a Driver for Agile Innovation 17Tiziana Margaria and Bernhard Steffen 2.1 Motivation and Background 17 2.2 Important Factors 20 2.3 The Future 22 2.4 Less Is More: The 80/20 Principle 27 2.5 Simplicity: A Never Ending Challenge 28 2.6 IT Specifics 29 2.7 Conclusions 29 Acknowledgments 30 References 30 3 Intercomponent Dependency Issues in Software Ecosystems 35Maëlick Claes, Alexandre Decan, and Tom Mens 3.1 Introduction 35 3.2 Problem Overview 36 3.2.1 Terminology 36 3.2.2 Identifying and Retrieving Dependency Information 38 3.2.3 Satisfying Dependencies and Conflicts 39 3.2.4 Component Upgrade 40 3.2.5 Inter-Project Cloning 41 3.3 First Case Study: Debian 42 3.3.1 Overview of Debian 42 3.3.2 Aggregate Analysis of Strong Conflicts 44 3.3.3 Package-Level Analysis of Strong Conflicts 45 3.4 Second Case Study: The R Ecosystem 46 3.4.1 Overview of R 46 3.4.2 R Package Repositories 47 3.4.3 Interrepository Dependencies 50 3.4.4 Intrarepository Dependencies 52 3.5 Conclusion 53 Acknowledgments 54 References 54 4 Triangulating Research Dissemination Methods: A Three-Pronged Approach to Closing the Research–Practice Divide 58Sarah Beecham, Ita Richardson, Ian Sommerville, Padraig O’Leary, Sean Baker, and John Noll 4.1 Introduction 58 4.2 Meeting the Needs of Industry 60 4.2.1 Commercialization Feasibility Study 61 4.2.2 Typical GSE Issues Were Reported 62 4.3 The Theory–Practice Divide 63 4.3.1 Making Research Accessible 64 4.3.2 Where Do Practitioners Really Go for Support? 65 4.4 Solutions: Rethinking Our Dissemination Methods 66 4.4.1 Workshops, Outreach, and Seminars 66 4.4.2 Case Studies 69 4.4.3 Action Research 70 4.4.4 Practitioner Ph.D.’s 71 4.4.5 Industry Fellowships 73 4.4.6 Commercializing Research 74 4.5 Obstacles to Research Relevance 76 4.5.1 The (IR) Relevance of Academic Software Engineering Research 76 4.5.2 Barriers to Research Commercialization 77 4.5.3 Academic Barriers to Commercialization 78 4.5.4 Business Barriers to Commercialization 79 4.5.5 Organizational Barriers to Commercialization 80 4.5.6 Funding Barriers to Commercialization 81 4.6 Conclusion 84 4.6.1 Research and Practice Working Together to Innovate 85 4.6.2 Final Thoughts 86 Acknowledgments 86 References 86 Part II Autonomous Software Systems 91 5 Apoptotic Computing: Programmed Death by Default for Software Technologies 93Roy Sterritt and Mike Hinchey 5.1 Biological Apoptosis 93 5.2 Autonomic Agents 94 5.3 Apoptosis within Autonomic Agents 96 5.4 NASA SWARM Concept Missions 98 5.5 The Evolving State-of-the-Art Apoptotic Computing 100 5.5.1 Strong versus Weak Apoptotic Computing 100 5.5.2 Other Research 101 5.6 “This Message Will Self-Destruct”: Commercial Applications 102 5.7 Conclusion 102 Acknowledgments 103 References 103 6 Requirements Engineering for Adaptive and Self-Adaptive Systems 107Emil Vassev and Mike Hinchey 6.1 Introduction 107 6.2 Understanding ARE 108 6.3 System Goals and Goals Models 109 6.4 Self-∗ Objectives and Autonomy-Assistive Requirements 111 6.4.1 Constraints and Self-∗ Objectives 113 6.4.2 Mission Analysis and Self-∗ Objectives 114 6.5 Recording and Formalizing Autonomy Requirements 116 6.5.1 ARE Requirements Chunk 117 6.6 Conclusion 118 Acknowledgments 119 References 119 7 Toward Artificial Intelligence through Knowledge Representation for Awareness 121Emil Vassev and Mike Hinchey 7.1 Introduction 121 7.2 Knowledge Representation 122 7.2.1 Rules 122 7.2.2 Frames 122 7.2.3 Semantic Networks and Concept Maps 122 7.2.4 Ontologies 123 7.2.5 Logic 123 7.2.6 Completeness and Consistency 124 7.2.7 Reasoning 125 7.2.8 Technologies 125 7.3 KnowLang 126 7.3.1 Modeling Knowledge with KnowLang 127 7.3.2 Knowledge Representation for Self-Adaptive Behavior 129 7.3.3 Case Study 129 7.4 Awareness 131 7.4.1 Classes of Awareness 132 7.4.2 Structuring Awareness 133 7.4.3 Implementing Awareness 134 7.5 Challenges and Conclusion 136 References 136 Part III Software Development and Evolution 139 8 Continuous Model-Driven Engineering 141Tiziana Margaria, Anna-Lena Lamprecht, and Bernhard Steffen 8.1 Introduction 141 8.2 Continuous Model-Driven Engineering 143 8.3 CMDE in Practice 147 8.4 Conclusion 150 Acknowledgment 150 References 151 9 Rethinking Functional Requirements: A Novel Approach Categorizing System and Software Requirements 155Manfred Broy 9.1 Introduction 155 9.2 Discussion: Classifying Requirements – Why and How 158 9.2.1 On Classifying Requirements as Being Functional 158 9.2.2 “Nonfunctional” Requirements and Their Characterization 159 9.2.3 Limitations of Classification Due to Heterogeneity and Lacking Precision 160 9.2.4 Approach: System Model-Based Categorization of Requirements 162 9.3 The System Model 164 9.3.1 The Basics: System Modeling Ontology 164 9.3.2 System Views and Levels of Abstractions 171 9.3.3 Structuring Systems into Views 172 9.4 Categorizing System Properties 172 9.4.1 System Behavior: Behavioral Properties 173 9.4.2 Variations in Modeling System Behavior 175 9.4.3 System Context: Properties of the Context 176 9.4.4 Nonbehavioral System Properties: System Representation 177 9.5 Categorizing Requirements 178 9.5.1 A Rough Categorization of Requirements 179 9.5.2 A Novel Taxonomy of Requirements? 183 9.6 Summary 186 Acknowledgments 187 References 187 10 The Power of Ten—Rules for Developing Safety Critical Code 188Gerard J. Holzmann 10.1 Introduction 188 10.2 Context 189 10.3 The Choice of Rules 190 10.4 Ten Rules for Safety Critical Code 192 10.5 Synopsis 200 References 201 11 Seven Principles of Software Testing 202Bertrand Meyer 11.1 Introduction 202 11.2 Defining Testing 202 11.3 Tests and Specifications 203 11.4 Regression Testing 204 11.5 Oracles 204 11.6 Manual and Automatic Test Cases 205 11.7 Testing Strategies 205 11.8 Assessment Criteria 206 11.9 Conclusion 207 References 207 12 Analyzing the Evolution of Database Usage in Data-Intensive Software Systems 208Loup Meurice, Mathieu Goeminne, Tom Mens, Csaba Nagy, Alexandre Decan, and Anthony Cleve 12.1 Introduction 208 12.2 State of the Art 210 12.2.1 Our Own Research 211 12.3 Analyzing the Usage of ORM Technologies in Database-Driven Java Systems 212 12.4 Coarse-Grained Analysis of Database Technology Usage 215 12.4.5 Discussion 222 12.5 Fine-Grained Analysis of Database Technology Usage 222 12.5.1 Analysis Background 222 12.5.2 Conceptual Schema 224 12.5.3 Metrics 226 12.5.4 Discussion 235 12.6 Conclusion 236 12.7 Future Work 237 Acknowledgments 238 References 238 Part IV Software Product Lines and Variability 41 13 Dynamic Software Product Lines 243Svein Hallsteinsen, Mike Hinchey, Sooyong Park, and Klaus Schmid 13.1 Introduction 243 13.2 Product Line Engineering 243 13.3 Software Product Lines 244 13.4 Dynamic SPLs 245 References 246 14 Cutting-Edge Topics on Dynamic Software Variability 247Rafael Capilla, Jan Bosch, and Mike Hinchey 14.1 Introduction 247 14.2 The Postdeployment Era 248 14.3 Runtime Variability Challenges Revisited 249 14.4 What Industry Needs from Variability at Any Time? 253 14.5 Approaches and Techniques for Dynamic Variability Adoption 255 14.6 Summary 266 14.7 Conclusions 267 References 268 Part V Formal Methods 271 15 The Quest for Formal Methods in Software Product Line Engineering 273Reiner Hähnle and Ina Schaefer 15.1 Introduction 273 15.2 SPLE: Benefits and Limitations 274 15.3 Applying Formal Methods to SPLE 275 15.4 The Abstract Behavioral Specification Language 277 15.5 Model-Centric SPL Development with ABS 279 15.6 Remaining Challenges 280 15.6.4 Maintenance 280 15.7 Conclusion 281 References 281 16 Formality, Agility, Security, and Evolution in Software Engineering 282Jonathan P. Bowen, Mike Hinchey, Helge Janicke, Martin Ward, and Hussein Zedan 16.1 Introduction 282 16.2 Formality 283 16.3 Agility 283 16.4 Security 284 16.5 Evolution 285 16.6 Conclusion 289 Acknowledgments 290 References 290 Part VI Cloud Computing 293 17 Cloud Computing: An Exploration of Factors Impacting Adoption 295Lorraine Morgan and Kieran Conboy 17.1 Introduction 295 17.2 Theoretical Background 296 17.3 Research Method 298 17.4 Findings and Analysis 303 17.4.2 Organizational Factors Impacting Adoption 306 17.4.3 Environmental Factors Impacting Adoption 308 17.5 Discussion and Conclusion 310 17.5.1 Limitations and Future Research 311 References 311 18 A Model-Centric Approach to the Design of Resource-Aware Cloud Applications 315Reiner Hähnle and Einar Broch Johnsen 18.1 Capitalizing on the Cloud 315 18.2 Challenges 316 18.2.1 Empowering the Designer 316 18.2.2 Deployment Aspects at Design Time 316 18.3 Controlling Deployment in the Design Phase 318 18.4 ABS: Modeling Support for Designing Resource-Aware Applications 319 18.5 Resource Modeling with ABS 320 18.6 Opportunities 324 18.6.1 Fine-Grained Provisioning 324 18.6.2 Tighter Provisioning 324 18.6.3 Application-Specific Resource Control 324 18.6.4 Application-Controlled Elasticity 324 18.7 Summary 325 Acknowledgments 325 References 325 Index 327

Read more less

Book SynopsisExplores how we judge engineering education in order to effectively redesign courses and programs that will prepare new engineers for various professional and academic careers Shows how present approaches to assessment were shaped and what the future holds Analyzes the validity of teaching and judging engineering education Shows the integral role that assessment plays in curriculum design and implementation Examines the sociotechnical system's impact on engineering curricula Table of ContentsPreface xiii Acknowledgments xv 1 Prologue 1 1.1 General Introduction: The Functions of Assessment 1 1.2 Health Warning: Ambiguities in the Use of the Term “Assessment” 6 1.3 The Assessment of Persons for the Professions 8 1.4 The Engineering Profession 10 1.5 The Development of Higher and Engineering Education as Areas of Academic Study in the 1960s 12 1.6 Assumptions About Examinations: Reliability 12 1.7 Myths Surrounding Examinations 14 1.8 The Introduction of Coursework Assessment 17 1.9 Rethinking Validity 19 1.10 Wastage (Dropout): The Predictive Value of School Examinations for Satisfactory Performance in Higher Education 20 1.11 Factors Influencing Performance in College Courses 22 1.12 Assessment: Results and Accountability 25 1.13 Assessing the Learner 26 Notes 27 References 27 2 Assessment and the Preparation of Engineers for Work 35 2.1 Engineers at Work 36 2.2 An Alternative Approach to the Education and Training of Engineers for Industry 37 2.3 Toward an Alternative Curriculum for Engineering 42 2.4 Creativity in Engineering and Design 43 2.5 Furneaux’s Study of a University’s Examinations in First-Year Mechanical Engineering: The Argument for “Objectives” 48 2.6 Discussion 51 Notes 53 References 54 3 The Development of a Multiple-Objective (Strategy) Examination and Multidimensional Assessment and Evaluation 61 3.1 The Development of an Advanced Level Examination in Engineering Science (For 17/18-Year-Old High School Students): The Assessment of Achievement and Competency 62 3.2 Skills Involved in Writing Design Proposals and Practical Laboratory Work 72 3.3 A Balanced System of Assessment 74 3.4 Pictures of the Curriculum Process 75 3.5 Multidimensional Assessment and Evaluation: A Case Study 79 3.6 Discussion 83 Notes 84 References 85 4 Categorizing the Work Done by Engineers: Implications for Assessment and Training 89 4.1 Introduction 90 4.2 A Study of Engineers at Work in a Firm in the Aircraft Industry 91 4.3 The Application of The Taxonomy of Educational Objectives to the Task Analysis of Managers in a Steel Plant 96 4.4 The Significance of Interpersonal Competence 96 4.5 A Comparative Study of British and German Production Engineers (Managers) 101 4.6 Engineering Knowledge 103 4.7 Discussion 105 Notes 105 References 107 5 Competency-Based Qualifications in the United Kingdom and United States and Other Developments 111 5.1 The Development of Competency-Based Vocational Qualifications in the United Kingdom 112 5.2 Outcomes Approaches in High Schools in the United Kingdom 115 5.3 Standards in Schools in the United States 116 5.4 Education for Capability: Capability vs. Competence 117 5.5 Ability (Assessment)-Led Curricula: The Alverno College Model 119 5.6 The Enterprise in Higher Education Initiative in the United Kingdom and the SCANS Report in the United States 122 5.7 The College Outcome Measures Program 125 5.8 Discussion 127 Notes 130 References 130 6 The Impact of Accreditation 133 6.1 ABET, European Higher Education Area (Bologna Process), and the Regulation of the Curriculum 134 6.2 Taxonomies 135 6.3 Outcomes-Based Engineering Education 142 6.4 Mastery Learning and Personalized Systems of Instruction 147 6.5 Discussion 152 References 152 7 Student Variability: The Individual the Organization, and Evaluation 157 7.1 Introduction 158 7.2 Learning and Teaching Styles 161 7.3 Study Habits/Strategies 163 7.4 Intellectual Development 165 7.5 Critical Thinking 168 7.6 The Assessment of Development 172 7.7 The Reflective Practitioner 174 7.8 Adaptive Expertise 180 7.9 Discussion 181 Notes 182 References 183 8 Emotional Intelligence, Peer and Self-Assessment, Journals and Portfolios, and Learning-How-to-Learn 189 8.1 Introduction 190 8.2 Emotional Intelligence 191 8.3 Self- and Peer Assessment 193 8.4 Learning Journals and Portfolios 206 8.5 Learning-How-to-Learn 209 8.6 Discussion 210 Note 211 References 211 9 Experiential Learning, Interdisciplinarity, Projects, and Teamwork 217 9.1 Introduction 218 9.2 Project Work as a Vehicle for Integrated Learning and Interdisciplinarity 219 9.3 Learning to Collaborate 220 9.4 Constructive Controversy 224 9.5 Communication Teamwork ,and Collegial Impediments to the Development of Good Engineering Practice 225 9.6 The Demand for Skill in Innovation: Can It Be Taught? 227 9.7 Creativity Teamwork and Reflective Practice (See Also Section 2.4) 228 9.8 Can Teamwork Be Taught? 229 9.9 Discussion 235 References 236 10 Competencies 241 10.1 Introduction 242 10.2 The Iowa Studies (ISU) 244 10.3 The Outcomes Approach in Australia Europe, and Elsewhere 246 10.4 The CDIO Initiative 247 10.5 A Standards-Based Approach to the Curriculum 248 10.6 Recent European Studies 252 10.7 Impact of Subjects (Courses) on Person-Centered Interventions 255 10.8 The Potential for Comparative Studies: Choosing Competencies 256 10.9 Expressive Outcomes 258 10.10 Discussion 259 References 260 11 “Outside” Competency 265 11.1 Introduction 266 11.2 Accidental Competencies 267 11.3 Understanding Competence at Work 269 11.4 Contextual Competence 270 11.5 A Post-Technician Cooperative Apprenticeship 272 11.6 Theories of Competence Development in Adult Life 275 11.7 Discussion 278 Notes 279 References 280 12 Assessment, Moral Purpose and Social Responsibility 283 12.1 Introduction 283 12.2 Moral Purpose and the Power of Grading 284 12.3 From Reliability to Validity: Toward a Philosophy of Engineering Education 284 12.4 Screening the Aims of Engineering Education 285 12.5 The Role of Educational Institutions in the Preparation for Industry (the Development of Professional Skills) 287 12.6 The Role of Industry in Professional Development 289 12.7 Assessment and the Curriculum 290 12.8 Changing Patterns in the Workforce the Structure of Higher Education 291 12.9 Lifelong Education and Credentialing 293 12.10 Conclusion 295 Notes 297 References 298 A A Quick Guide to the Changing Terminology in the Area of “Assessment” 301 A.1 Objectives and Outcomes 301 A.2 Assessment and Evaluation 307 References 308 B Extracts from the Syllabus and Notes for the Guidance of Schools for GCE Engineering Science (Advanced) 1972 Joint Matriculation Board Manchester 311 B. 1 Extract 1 (pp. 2–6) 311 B. 2 Extract 2 (p. 9) 317 B. 3 Extract 3 (pp. 13–16) 318 Author Index 325 Subject Index 339

Read more less

Book SynopsisA systematic guide to the theory, applications, and design of thermal management for LED packaging In Thermal Management for Opto-electronics Packaging and Applications, a team of distinguished engineers and researchers deliver an authoritative discussion of the fundamental theory and practical design required for LED product development. Readers will get a solid grounding in thermal management strategies and find up-to-date coverage of heat transfer fundamentals, thermal modeling, and thermal simulation and design. The authors explain cooling technologies and testing techniques that will help the reader evaluate device performance and accelerate the design and manufacturing cycle. In this all-inclusive guide to LED package thermal management, the book provides the latest advances in thermal engineering design and opto-electronic devices and systems. The book also includes: A thorough introduction to thermal conduction and solutions, including discussi

Read more less

Book SynopsisA comprehensive resource that provides the basic concepts of electric power systems, microeconomics, and optimization techniques Electricity Markets: Theories and Applications offers students and practitioners a clear understanding of the fundamental concepts of the economic theories, particularly microeconomic theories, as well as information on some advanced optimization methods of electricity markets. The authorsnoted experts in the fieldcover the basic drivers for the transformation of the electricity industry in both the United States and around the world and discuss the fundamentals of power system operation, electricity market design and structures, and electricity market operations. The text also explores advanced topics of power system operations and electricity market design and structure including zonal versus nodal pricing, market performance and market power issues, transmission pricing, and the emerging problems electricity markets face in sTable of ContentsAbout the Authors ix Preface xi 1 Introduction 1 2 Electric Power System 29 3 Microeconomic Theories 57 4 Power System Unit Commitment 97 5 Power System Economic Dispatch 119 6 Optimal Power Flow 147 7 Design, Structure, and Operation of an Electricity Market 173 8 Pricing, Modeling, and Simulation of an Electricity Market 211 9 Evaluation of an Electricity Market 239 10 Transmission Planning Under Electricity Market Regime 255 11 Electricity Market under a Future Grid 293 Index 315

Read more less

Book SynopsisPresents the foundational systemic thinking needed to conceive systems that address complex socio-technical problems This book emphasizes the underlying systems analysis components and associated thought processes.Table of ContentsPreface ix Original Preface from Jack Gibson xiii Acknowledgments xv About the Companion Website xvii Part One: Primer 1. Introduction 3 1.1 What is a System? 4 1.2 Terminology Confusion 6 1.3 Systems Analysis Equals Operations Research Plus Policy Analysis 10 1.4 Attributes of Large-Scale Systems 11 1.5 Transportation Systems: An Example of a Large-Scale System 13 1.6 Systems Integration 16 1.7 What Makes a “Systems Analysis” Different? 17 1.8 Distant Roots of Systems Analysis 19 1.9 Immediate Precursors to Systems Analysis 20 1.10 Development of Systems Analysis as a Distinct Discipline: The Influence of RAND 23 References 26 2. Six Major Phases of Systems Analysis 28 2.1 The Systems Analysis Method: Six Major Phases 28 2.1.1 Determine Goals 28 2.1.2 Establish Criteria for Ranking Alternative Candidates 30 2.1.3 Develop Alternative Solutions 31 2.1.4 Rank Alternatives 32 2.1.5 Iterate 34 2.1.6 Action 35 2.2 The Goal-Centered or Top-Down Approach 35 2.3 The Index of Performance Concept 41 2.4 Developing Alternative Scenarios 45 2.5 Ranking Alternatives 47 2.6 Iteration and the “Error-Embracing” Approach 47 2.7 The Action Phase: The Life Cycle of a System 51 References 53 3. Goal Development 55 3.1 Seven Steps in Goal Development 55 3.2 On Generalizing the Question 59 3.3 The Descriptive Scenario 61 3.4 The Normative Scenario 63 3.5 The Axiological Component 63 3.6 Developing an Objectives Tree 67 3.7 Validate 73 3.8 Iterate 74 References 75 4. The Index of Performance 76 4.1 Introduction 76 4.2 Desirable Characteristics for an Index of Performance 78 4.3 Economic Criteria 81 4.4 Four Common Criteria of Economic Efficiency 83 4.5 Is There a Problem with Multiple Criteria? 86 4.6 What is Wrong with the B–C Ratio? 90 4.7 Can IRR be Fixed? 92 4.8 Expected Monetary Value 94 4.9 Nonmonetary Performance Indices 96 References 99 5. Develop and Evaluate Alternative Candidate Solutions 101 5.1 Introduction 101 5.2 The Classical Approach to Creativity 101 5.3 Concepts in Creativity 103 5.4 Brainstorming 104 5.5 Brainwriting 107 5.6 Dynamic Confrontation 109 5.7 Zwicky’s Morphological Box 110 5.8 The Options Field/Options Profile Approach 112 5.9 Computer Creativity 115 5.10 Trade Study Methods 116 5.11 Trade Study Example 120 References 127 6. The 10 Golden Rules of Systems Analysis 130 6.1 Introduction 130 6.2 Rule 1: There Always is a Client 131 6.3 Rule 2: Your Client Does Not Understand His Own Problem 132 6.4 Rule 3: The Original Problem Statement is too Specific: You Must Generalize the Problem to Give it Contextual Integrity 133 6.5 Rule 4: The Client Does Not Understand the Concept of the Index of Performance 135 6.6 Rule 5: You are the Analyst, Not the Decision Maker 137 6.7 Rule 6: Meet the Time Deadline and the Cost Budget 139 6.8 Rule 7: Take a Goal-Centered Approach to the Problem, not a Technology-Centered or Chronological Approach 140 6.9 Rule 8: Non-users Must Be Considered in the Analysis and in the Final Recommendations 141 6.10 Rule 9: The Universal Computer Model is a Fantasy 143 6.11 Rule 10: The Role of Decision Maker in Public Systems is Often a Confused One 143 References 145 Part Two: Casebook Cases in Systems Engineering 149 Introduction 149 The Case Study Method 151 What is a “Case”? 152 Implementing the Case Study Method 152 Chat Rooms and Polls 152 In-Class Group Activities 153 Case Study Assignments 153 Peer Review 154 The Case Studies 154 Using Case Studies to Build Teamwork and Communications Skills 154 Building the Systems Team 155 Tips on Managing the Team 156 How to Make an Effective Oral Presentation 157 How to Write a Report 162 Aligning Case Studies with the Ten Golden Rules of Systems Analysis 164 To Winnebago or to not Winnebago? 164 How can this Case be Used to Teach and Reinforce Systems Analysis? 169 A Word about the Cases 170 Validation of Learning: Evidence-Based Learning 170 Sample Evaluation Instrument: Exam with Solutions 171 Sample Evaluation Instrument: Exam without Solutions 176 Case 1: Great Buys 183 Case 2: Surf’s Up? 188 Case 3: Extended Engineering Education 189 Case 4: Systems Engineering Majors Proliferating 192 Case 5: Motor Carrier Safety and Compliance 193 Case 6: Is Getting There Half the Fun? 202 Case 7: Is Getting There Half the Fun? (Revisited) 206 Case 8: Which Camper Should We Choose? 210 Case 9: Seat Belt Issue 217 Case 10: Baseball Free Agent Draft—20xx 219 Case 11: For the Birds? 221 Case 12: Wal-Mart Crisis 222 Case 13: Ocean Cleanup 224 Case 14: BRAC 226 Case 15: Opportunity? 227 Case 16: Risky Business 228 Case 17: Corporate Headquarters 230 Case 18: The Ad Forecaster 231 Case 19: For the Birds (Revisited) 232 Case 20: Best MBA? 234 Case 21: Health Insurance? What Health Insurance? 235 Case 22: Social Media in Emergency Management 237 Case 23: Which Bridges to Repair? 241 Case 24: Going-to-the-Sun Road Rehabilitation Project 245 Case 25: HEV versus HOV? 256 Case 26: “Show Me the Money!” 259 Case 27: The Collections Subsidiary 261 Case 28: MNB One Credit Card Portfolio 266 Case 29: Select Collections 273 Case 30: To Distance or Not to Distance? Is That the Question? 278 Index 279

Read more less

Book SynopsisApplies basic field behavior in circuit design anddemonstrates how it relates togrounding and shielding requirements and techniques in circuit design This book connects the fundamentals of electromagnetic theory to the problems of interference in all types of electronic design. The text covers power distribution in facilities, mixing of analog and digital circuitry, circuit board layout at high clock rates, and meeting radiation and susceptibility standards. The author examines the grounding and shielding requirements and techniques in circuit design and applies basic physics to circuit behavior. The sixth edition of this book has been updated with new material added throughout the chapters where appropriate. The presentation of the book has also been rearranged in order to reflect the current trends in the field. Grounding and Shielding: Circuits and Interference, Sixth Edition: Includes new material on vias and field control, capacitTable of ContentsPreface to the Sixth Edition xi A Historical Perspective into Grounding and Shielding xv 1. Voltage and Capacitors 1 1.1. Introduction 1 1.2. Charges and Electrons 4 1.3. The Electric Force Field 6 1.4. Field Representations 6 1.5. The Definition of Voltage 9 1.6. Equipotential Surfaces 10 1.7. The Force Field or E Field Between Two Conducting Plates 11 1.8. Electric Field Patterns 12 1.9. The Energy Stored in An Electric Field 16 1.10. Dielectrics 17 1.11. The D Field 18 1.12. Capacitance 19 1.13. Mutual Capacitance 21 1.14. Displacement Current 22 1.15. Energy Stored in a Capacitor 23 1.16. Forces in the Electric Field 24 1.17. Capacitors 25 1.18. Dielectric Absorption 25 1.19. Resistance of Plane Conductors 26 2. Magnetics 27 2.1. Magnetic Fields 27 2.2. Ampere’s Law 29 2.3. The Solenoid 30 2.4. Faraday’s Law and the Induction Field 30 2.5. The Definition of Inductance 32 2.6. The Energy Stored in an Inductance 32 2.7. Magnetic Field Energy in Space 34 2.8. Electron Drift 36 2.9. The Magnetic Circuit 36 2.10. A Magnetic Circuit with a Gap 38 2.11. Small Inductors 39 2.12. Self- and Mutual Inductance 40 2.13. Transformer Action 40 2.14. Hysteresis and Permeability 45 2.15. Eddy Currents 46 3. Digital Electronics 48 3.1. Introduction 49 3.2. The Transport of Electrical Energy 49 3.3. Transmission Lines–Introduction 50 3.4. Transmission Line Operations 52 3.5. Transmission Line Field Patterns 54 3.6. A Terminated Transmission Line 54 3.7. The Unterminated Transmission Line 56 3.8. A Short Circuit Termination 58 3.9. The Real World 59 3.10. SineWaves Versus Step Voltages 60 3.11. A Bit of History 61 3.12. Ideal Conditions 61 3.13. Reflection and Transmission Coefficients 62 3.14. Taking Energy from an Ideal Energy Source 63 3.15. A Capacitor as a Transmission Line 63 3.16. Decoupling Capacitors and Natural Frequencies 65 3.17. Printed Circuit Boards 66 3.18. Two-Layer Logic Boards 67 3.19. Vias 68 3.20. The Termination of Transmission Lines 70 3.21. Energy in the Ground/Power Plane Capacitance 72 3.22. Poynting’s Vector 73 3.23. Skin Effect 74 3.24. Measurement Problems: Ground Bounce 75 3.25. Balanced Transmission 76 3.26. Ribbon Cable and Connectors 77 3.27. Interfacing Analog and Digital Circuits 78 4. Analog Circuits 80 4.1. Introduction 80 4.2. Instrumentation 81 4.3. History 83 4.4. The Basic Shield Enclosure 83 4.5. The Enclosure and Utility Power 86 4.6. The Two-Ground Problem 88 4.7. Instrumentation and the Two-Ground Problem 89 4.8. Strain-Gauge Instrumentation 92 4.9. The Floating Strain Gauge 93 4.10. The Thermocouple 95 4.11. The Basic Low-Gain Differential Amplifier (Forward Referencing Amplifer) 96 4.12. Shielding in Power Transformers 98 4.13. Calibration and Interference 99 4.14. The Guard Shield Above 100 kHz 100 4.15. Signal Flow Paths in Analog Circuits 101 4.16. Parallel Active Components 101 4.17. Feedback Stability–Introduction 102 4.18. Feedback Theory 103 4.19. Output Loads and Circuit Stability 105 4.20. Feedback Around a Power Stage 105 4.21. Constant Current Loops 106 4.22. Filters and Aliasing Errors 107 4.23. Isolation and DC-To-DC Converters 108 4.24. Charge Converter Basics 110 4.25. DC Power Supplies 113 4.26. Guard Rings 113 4.27. Thermocouple Effects 114 4.28. Some Thoughts on Instrumentation 114 5. Utility Power and Facility Grounding 115 5.1. Introduction 115 5.2. History 116 5.3. Semantics 116 5.4. Utility Power 117 5.5. The Earth as a Conductor 119 5.6. The Neutral Connection to Earth 120 5.7. Ground Potential Differences 122 5.8. Field Coupling to Power Conductors 124 5.9. Neutral Conductors 125 5.10. k Factor in Transformers 126 5.11. Power Factor Correction 127 5.12. Ungrounded Power 127 5.13. A Request for Power 128 5.14. Earth Power Currents 129 5.15. Line Filters 129 5.16. Isolated Grounds 130 5.17. Facility Grounds–Some More History 132 5.18. Ground Planes in Facilities 134 5.19. Other Ground Planes 137 5.20. Ground at Remote Sites 137 5.21. Extending Ground Planes 137 5.22. Lightning 138 5.23. Lightning and Facilities 139 5.24. Lightning Protection for Boats and Ships 141 5.25. Grounding of Boats and Ships at Dock 143 5.26. Aircraft Grounding (Fueling) 144 5.27. Ground Fault Interruption (GFI) 144 5.28. Isolation Transformers 145 5.29. Grounding and the Pacific Intertie 147 5.30. SolarWind 148 6. Radiation 149 6.1. Handling Radiation and Susceptibility 149 6.2. Radiation 150 6.3. SineWaves and Transmission Lines 151 6.4. Approximations for Pulses and SquareWaves 152 6.5. Radiation from Components 156 6.6. The Dipole Antenna 157 6.7. Wave Impedance 158 6.8. Field Strength and Antenna Gain 159 6.9. Radiation from Loops 160 6.10. E-Field Coupling to a Loop 162 6.11. Radiation from Printed Circuit Boards 163 6.12. The Sniffer and the Antenna 164 6.13. Microwave Ovens 165 7. Shielding from Radiation 166 7.1. Cables with Shields 166 7.2. Low-Noise Cables 168 7.3. Transfer Impedance 169 7.4. Waveguides 172 7.5. Electromagnetic Fields over a Ground Plane 173 7.6. Fields and Conductors 174 7.7. Conductive Enclosures–Introduction 175 7.8. Coupling Through EnclosureWalls by an Induction Field 176 7.9. Reflection and Absorption of Field Energy at a Conducting Surface 177 7.10. Independent Apertures 178 7.11. Dependent Apertures 179 7.12. Honeycombs 180 7.13. Summing Field Penetrations 181 7.14. Power Line Filters 182 7.15. Backshell Connectors 184 7.16. H-Field Coupling 186 7.17. Gaskets 186 7.18. Finger Stock 187 7.19. Glass Apertures 188 7.20. Guarding Large Transistors 188 7.21. Mounting Components on Surfaces 188 7.22. Zappers 190 7.23. Shielded and Screen Rooms 190 AppendixA. The Decibel 192 Further Reading 194 Index 195

Read more less

Book SynopsisThe book examines how Fog will change the information technology industry in the next decade. Fog distributes the services of computation, communication, control and storage closer to the edge, access and users. As a computing and networking architecture, Fog enables key applications in wireless 5G, the Internet of Things, and big data.Table of ContentsContributors xi Introduction 1Bharath Balasubramanian, Mung Chiang, and Flavio Bonomi I.1 Summary of Chapters 5 I.2 Acknowledgments 7 References 8 I Communication and Management of Fog 11 1 ParaDrop: An Edge Computing Platform in Home Gateways 13Suman Banerjee, Peng Liu, Ashish Patro, and Dale Willis 1.1 Introduction 13 1.1.1 Enabling Multitenant Wireless Gateways and Applications through ParaDrop 14 1.1.2 ParaDrop Capabilities 15 1.2 Implementing Services for the ParaDrop Platform 17 1.3 Develop Services for ParaDrop 19 1.3.1 A Security Camera Service Using ParaDrop 19 1.3.2 An Environmental Sensor Service Using ParaDrop 22 References 23 2 Mind Your Own Bandwidth 24Carlee Joe-Wong, Sangtae Ha, Zhenming Liu, Felix Ming Fai Wong, and Mung Chiang 2.1 Introduction 24 2.1.1 Leveraging the Fog 25 2.1.2 A Home Solution to a Home Problem 25 2.2 Related Work 28 2.3 Credit Distribution and Optimal Spending 28 2.3.1 Credit Distribution 29 2.3.2 Optimal Credit Spending 31 2.4 An Online Bandwidth Allocation Algorithm 32 2.4.1 Estimating Other Gateways’ Spending 32 2.4.2 Online Spending Decisions and App Prioritization 34 2.5 Design and Implementation 35 2.5.1 Traffic and Device Classification 37 2.5.2 Rate Limiting Engine 37 2.5.3 Traffic Prioritization Engine 38 2.6 Experimental Results 39 2.6.1 Rate Limiting 39 2.6.2 Traffic Prioritization 41 2.7 Gateway Sharing Results 41 2.8 Concluding Remarks 45 Acknowledgments 46 Appendix 2.A 46 2.A.1 Proof of Lemma 2.1 46 2.A.2 Proof of Lemma 2.2 46 2.A.3 Proof of Proposition 2.1 47 2.A.4 Proof of Proposition 2.2 48 2.A.5 Proof of Proposition 2.3 49 2.A.6 Proof of Proposition 2.4 49 References 50 3 Socially-Aware Cooperative D2D and D4D Communications toward Fog Networking 52Xu Chen, Junshan Zhang, and Satyajayant Misra 3.1 Introduction 52 3.1.1 From Social Trust and Social Reciprocity to D2D Cooperation 54 3.1.2 Smart Grid: An IoT Case for Socially-Aware Cooperative D2D and D4D Communications 55 3.1.3 Summary of Main Results 57 3.2 Related Work 58 3.3 System Model 59 3.3.1 Physical (Communication) Graph Model 60 3.3.2 Social Graph Model 61 3.4 Socially-Aware Cooperative D2D and D4D Communications toward Fog Networking 62 3.4.1 Social Trust-Based Relay Selection 63 3.4.2 Social Reciprocity-Based Relay Selection 63 3.4.3 Social Trust and Social Reciprocity-Based Relay Selection 68 3.5 Network Assisted Relay Selection Mechanism 69 3.5.1 Reciprocal Relay Selection Cycle Finding 69 3.5.2 NARS Mechanism 70 3.5.3 Properties of NARS Mechanism 73 3.6 Simulations 75 3.6.1 Erdos–Renyi Social Graph 76 3.6.2 Real Trace Based Social Graph 78 3.7 Conclusion 82 Acknowledgments 82 References 83 4 You Deserve Better Properties (From Your Smart Devices) 86Steven Y. Ko 4.1 Why We Need to Provide Better Properties 86 4.2 Where We Need to Provide Better Properties 87 4.3 What Properties We Need to Provide and How 88 4.3.1 Transparency 88 4.3.2 Predictable Performance 93 4.3.3 Openness 99 4.4 Conclusions 102 Acknowledgment 102 References 103 II Storage and Computation in Fog 107 5 Distributed Caching for Enhancing Communications Efficiency 109A. Salman Avestimehr and Andreas F. Molisch 5.1 Introduction 109 5.2 Femtocaching 111 5.2.1 System Model 111 5.2.2 Adaptive Streaming from Helper Stations 114 5.3 User-Caching 115 5.3.1 Cluster-Based Caching and D2D Communications 115 5.3.2 IT LinQ-Based Caching and Communications 118 5.3.3 Coded Multicast 126 5.4 Conclusions and Outlook 130 References 131 6 Wireless Video Fog: Collaborative Live Streaming with Error Recovery 133Bo Zhang, Zhi Liu, and S.-H. Gary Chan 6.1 Introduction 133 6.2 Related Work 136 6.3 System Operation and Network Model 138 6.4 Problem Formulation and Complexity 140 6.4.1 NC Packet Selection Optimization 140 6.4.2 Broadcaster Selection Optimization 143 6.4.3 Complexity Analysis 144 6.5 VBCR: A Distributed Heuristic for Live Video with Cooperative Recovery 144 6.5.1 Initial Information Exchange 145 6.5.2 Cooperative Recovery 145 6.5.3 Updated Information Exchange 147 6.5.4 Video Packet Forwarding 147 6.6 Illustrative Simulation Results 150 6.7 Concluding Remarks 156 References 156 7 Elastic Mobile Device Clouds: Leveraging Mobile Devices to Provide Cloud Computing Services at the Edge 159Karim Habak, Cong Shi, Ellen W. Zegura, Khaled A. Harras, and Mostafa Ammar 7.1 Introduction 159 7.2 Design Space with Examples 161 7.2.1 Mont-Blanc 162 7.2.2 Computing while Charging 163 7.2.3 FemtoCloud 164 7.2.4 Serendipity 166 7.3 FemtoCloud Performance Evaluation 168 7.3.1 Experimental Setup 168 7.3.2 FemtoCloud Simulation Results 169 7.3.3 FemtoCloud Prototype Evaluation 173 7.4 Serendipity Performance Evaluation 175 7.4.1 Experimental Setup 175 7.4.2 Serendipity’s Performance Benefits 176 7.4.3 Impact of Network Environment 179 7.4.4 The Impact of the Job Properties 182 7.5 Challenges 186 References 186 III Applications of Fog 189 8 The Role of Fog Computing in the Future of the Automobile 191Flavio Bonomi, Stefan Poledna, and Wilfried Steiner 8.1 Introduction 191 8.2 Current Automobile Electronic Architectures 193 8.3 Future Challenges of Automotive E/E Architectures and Solution Strategies 195 8.4 Future Automobiles as Fog Nodes on Wheels 200 8.5 Deterministic FOG Nodes on Wheels Through Real-Time Computing and Time-Triggered Technologies 203 8.5.1 Deterministic Fog Node Addressing the Scalability Challenge through Virtualization 203 8.5.2 Deterministic Fog Node Addressing the Connectivity and Security Challenges 204 8.5.3 Emerging Use Case of Deterministic Fog Nodes in Automotive Applications—Vehicle-Wide Virtualization 206 8.6 Conclusion 209 References 209 9 Geographic Addressing for Field Networks 211Robert J. Hall 9.1 Introduction 211 9.1.1 Field Networking 211 9.1.2 Challenges of Field Networking 212 9.2 Geographic Addressing 214 9.3 SAGP: Wireless GA in the Field 215 9.3.1 SAGP Processing 216 9.3.2 SAGP Retransmission Heuristics 217 9.3.3 Example of SAGP Packet Propagation 218 9.3.4 Followcast: Efficient SAGP Streaming 219 9.3.5 Meeting the Challenges 220 9.4 Georouting: Extending GA to the Cloud 221 9.5 SGAF: A Multi-Tiered Architecture for Large-Scale GA 222 9.5.1 Bridging Between Tiers 223 9.5.2 Hybrid Security Architecture 225 9.6 The AT&T Labs Geocast System 225 9.7 Two GA Applications 226 9.7.1 PSCommander 226 9.7.2 Geocast Games 230 9.8 Conclusions 232 References 232 10 Distributed Online Learning and Stream Processing for a Smarter Planet 234Deepak S. Turaga and Mihaela van der Schaar 10.1 Introduction: Smarter Planet 234 10.2 Illustrative Problem: Transportation 237 10.3 Stream Processing Characteristics 238 10.4 Distributed Stream Processing Systems 239 10.4.1 State of the Art 239 10.4.2 Stream Processing Systems 240 10.5 Distributed Online Learning Frameworks 244 10.5.1 State of the Art 244 10.5.2 Systematic Framework for Online Distributed Ensemble Learning 247 10.5.3 Online Learning of the Aggregation Weights 250 10.5.4 Collision Detection Application 254 10.6 What Lies Ahead 257 Acknowledgment 258 References 258 11 Securing the Internet of Things: Need for a New Paradigm and Fog Computing 261Tao Zhang, Yi Zheng, Raymond Zheng, and Helder Antunes 11.1 Introduction 261 11.2 New IoT Security Challenges That Necessitate Fundamental Changes to the Existing Security Paradigm 263 11.2.1 Many Things Will Have Long Life Spans but Constrained and Difficult-to-Upgrade Resources 264 11.2.2 Putting All IoT Devices Inside Firewalled Castles Will Become Infeasible or Impractical 264 11.2.3 Mission-Critical Systems Will Demand Minimal-Impact Incident Responses 265 11.2.4 The Need to Know the Security Status of a Vast Number of Devices 266 11.3 A New Security Paradigm for the Internet of Things 268 11.3.1 Help the Less Capable with Fog Computing 269 11.3.2 Scale Security Monitoring to Large Number of Devices with Crowd Attestation 272 11.3.3 Dynamic Risk–Benefit-Proportional Protection with Adaptive Immune Security 277 11.4 Summary 281 Acknowledgment 281 References 281 Index 285

Read more less

Book SynopsisThis new edition specifically addresses the most recent and relevant developments in the design and manufacture of OLED displays Provides knowledge of OLED fundamentals and related technologies for applications such as displays and solid state lighting along with processing and manufacturing technologies Serves as a reference for people engaged in OLED research, manufacturing, applications and marketing Includes coverage of white + color filter technology, which has become industry standard technology for large televisions Table of ContentsAbout the Author xi Preface xiii Series Editor’s Foreword to the Second Edition xv 1 Introduction 1 References 5 2 OLED Devices 7 2.1 OLED Definition 7 2.1.1 History of OLED Research and Development 7 2.1.2 Luminescent Effects in Nature 8 2.1.3 Difference Between OLED, LED, and Inorganic ELs 11 2.1.3.1 Inorganic EL 11 2.1.3.2 LED 11 2.2 Basic Device Structure 12 2.3 Basic Light Emission Mechanism 14 2.3.1 Potential Energy of Molecules 14 2.3.2 Highest Occupied and Lowest Unoccupied Molecular Orbitals (HOMO and LUMO) 15 2.3.3 Configuration of Two Electrons 17 2.3.4 Spin Function 20 2.3.5 Singlet and Triplet Excitons 20 2.3.6 Charge Injection from Electrodes 24 2.3.6.1 Charge Injection by Schottky Thermionic Emission 25 2.3.6.2 Tunneling Injection 28 2.3.6.3 Vacuum-Level Shift 28 2.3.7 Charge Transfer and Recombination 29 2.3.7.1 Charge Transfer Behavior 29 2.3.7.2 Space-Charge-Limited Current 29 2.3.7.3 Poole–Frenkel conduction 32 2.3.7.4 Recombination and Generation of Excitons 33 2.4 Emission Efficiency 36 2.4.1 Internal/External Quantum Efficiency 36 2.4.2 Energy Conversion and Quenching 37 2.4.2.1 Internal Conversion 37 2.4.2.2 Intersystem Crossing 37 2.4.2.3 Doping 38 2.4.2.4 Quenching 40 2.4.3 Outcoupling Efficiency of OLED Display 42 2.4.3.1 Light Output Distribution 42 2.4.3.2 Snell’s Law and Critical Angle 43 2.4.3.3 Loss Due to Light Extraction 44 2.4.3.4 Performance Enhancement by Molecular Alignment 45 2.5 Lifetime and Image Burning 46 2.5.1 Lifetime Definitions 46 2.5.2 Degradation Analysis and Design Optimization 47 2.5.3 Degradation Measurement and Mechanisms 50 2.5.3.1 Acceleration Factor and Temperature Contribution 50 2.5.3.2 Degradation Mechanism Variation 50 2.6 Technologies to Enhance the Device Performance 51 2.6.1 Thermally Activated Delayed Fluorescence 51 2.6.2 Other Types of Excited States 53 2.6.2.1 Excimer and Exciplex 53 2.6.2.2 Charge-Transfer Complex 53 2.6.3 Charge Generation Layer 54 References 56 3 OLED Manufacturing Process 61 3.1 Material Preparation 61 3.1.1 Basic Material Properties 61 3.1.1.1 Hole Injection Material 61 3.1.1.2 Hole Transportation Material 62 3.1.1.3 Emission Layer Material 62 3.1.1.4 Electron Transportation Material and Charge Blocking Material 63 3.1.2 Purification Process 67 3.2 Evaporation Process 68 3.2.1 Principle 68 3.2.2 Evaporation Sources 72 3.2.2.1 Resistive Heating Method 72 3.2.2.2 Electron Beam Evaporation 75 3.2.2.3 Monitoring Thickness Using a Quartz Oscillator 76 3.3 Encapsulation 79 3.3.1 Dark Spot and Edge Growth Defects 79 3.3.2 Light Emission from the Bottom and Top of the OLED Device 80 3.3.3 Bottom Emission and perimeter sealing 81 3.3.4 Top Emission 82 3.3.5 Encapsulation Technologies and Measurement 83 3.3.5.1 Thin-Film Encapsulation 84 3.3.5.2 Face Sealing Encapsulation 87 3.3.5.3 Frit Encapsulation 88 3.3.5.4 WVTR Measurement 88 3.4 Problem Analysis 91 3.4.1 Ionization Potential Measurement 91 3.4.2 Electron Affinity Measurement 92 3.4.3 HPLC Analysis 93 3.4.4 Cyclic Voltammetry 94 References 96 4 OLED Display Module 99 4.1 Comparison Between OLED and LCD Modules 99 4.2 Basic Display Design and Related Characteristics 101 4.2.1 Luminous Intensity, Luminance, and Illuminance 101 4.2.1.1 Luminous Intensity 101 4.2.1.2 Luminance 102 4.2.1.3 Illuminance 103 4.2.1.4 Metrics Summary 104 4.2.1.5 Helmholtz–Kohlrausch Effect 106 4.2.2 OLED Current Efficiencies and Power Efficacies 106 4.2.3 Color Reproduction 109 4.2.4 Uniform Color Space 115 4.2.5 White Point Determination 116 4.2.6 Color Boost 119 4.2.7 Viewing Condition 120 4.3 Passive-Matrix OLED Display 121 4.3.1 Structure 121 4.3.2 Pixel Driving 122 4.4 Active-Matrix OLED Display 125 4.4.1 OLED Module Components 125 4.4.2 Two-Transistor One-Capacitor (2T1C) Driving Circuit 127 4.4.3 Ambient Performance 136 4.4.3.1 Living Room Contrast Ratio 136 4.4.3.2 Chroma Reduction Due to Ambient Light 137 4.4.4 Subpixel Rendering 138 References 139 5 OLED Color Patterning Technologies 143 5.1 Color-Patterning Technologies 143 5.1.1 Shadow Mask Patterning 143 5.1.1.1 Shadow Mask Process 143 5.1.1.2 Blue Common Layer 146 5.1.1.3 Polychromatic Pixel 147 5.1.2 White+Color Filter Patterning 148 5.1.3 Color Conversion Medium (CCM) Patterning 149 5.1.4 Laser-Induced Thermal Imaging (LITI) Method 149 5.1.5 Radiation-Induced Sublimation Transfer (RIST) Method 151 5.1.6 Dual-Plate OLED Display (DOD) Method 152 5.1.7 Other Methods 153 5.2 Solution-Processed Materials and Technologies 153 5.3 Next-Generation OLED Manufacturing Tools 158 5.3.1 Vapor Injection Source Technology (VIST) Deposition 158 5.3.2 Hot-Wall Method 163 5.3.3 Organic Vapor-Phase Deposition (OVPD) Method 164 References 165 6 TFT and Driving for Active-Matrix Display 167 6.1 TFT Structure 167 6.2 TFT Process 169 6.2.1 Low-Temperature Polysilicon Process Overview 169 6.2.2 Thin-Film Formation 172 6.2.3 Patterning Technique 173 6.2.4 Excimer Laser Crystallization 177 6.3 MOSFET Basics 180 6.4 LTPS-TFT-Driven OLED Display Design 183 6.4.1 OFF Current 183 6.4.2 Driver TFT Size Restriction 184 6.4.3 Restriction Due to Voltage Drop 185 6.4.4 LTPS-TFT Pixel Compensation Circuit 190 6.4.4.1 Voltage Programming 190 6.4.4.2 Current Programming 192 6.4.4.3 External Compensation Method 193 6.4.4.4 Digital Driving 194 6.4.5 Circuit Integration by LTPS-TFT 197 6.5 TFT Technologies for OLED Displays 200 6.5.1 Selective Annealing Method 200 6.5.1.1 Sequential Lateral Solidification (SLS) Method 200 6.5.1.2 Selective Annealing by Microlens Array 200 6.5.2 Microcrystalline and Superamorphous Silicon 202 6.5.3 Solid-Phase Crystallization 205 6.5.3.1 MIC and MILC Methods 205 6.5.3.2 AMFC Method 205 6.5.4 Oxide Semiconductors 207 References 210 7 OLED Television Applications 215 7.1 Performance Target 215 7.2 Scalability Concept 217 7.2.1 Relationship between Defect Density and Production Yield 217 7.2.1.1 Purpose of Yield Simulation 217 7.2.1.2 Defective Pixel Number Estimation Using the Poisson Equation 217 7.2.2 Scalable Technology 217 7.2.2.1 Scalability 218 7.3 Murdoch’s Algorithm to Achieve Low Power and Wide Color Gamut 219 7.3.1 A Method for Achieving Both Low Power and Wide Color Gamut 219 7.3.2 RGBW Driving Algorithm 221 7.4 An Approach to Achieve 100% NTSC Color Gamut With Low Power Consumption Using White + Color Filter 224 7.4.1 Consideration of Performance Difference between W-RGB and W-RGBW Method 224 7.4.1.1 Issues of White+Color Filter Method for Large Displays 224 7.4.1.2 Analysis of W-RGBW Approach to Circumvent Its Trade-off Situation 224 7.4.1.3 Design of a Prototype to Demonstrate That Low Power Consumption Can Be Achieved with Large Color Gamut 229 7.4.1.4 Product-Level Performance Demonstration by the Combination of Scalable Technologies 230 References 233 8 New OLED Applications 235 8.1 Flexible Display/Wearable Displays 235 8.1.1 Flexible Display Applications 235 8.1.2 Flexible Display Substrates 235 8.1.3 Laser Liftoff Process 236 8.1.4 Barrier Technology for Flexible Displays 240 8.1.5 Organic TFTs for Flexible Displays 241 8.1.5.1 Organic Semiconductor Materials 242 8.1.5.2 Organic TFT Device Structure and Processing 243 8.1.5.3 Organic TFT Characteristics 245 8.2 Transparent Displays 245 8.3 Tiled Display 247 8.3.1 Passive-Matrix Tiling 247 8.3.2 Active-Matrix Tiling 248 References 252 9 OLED Lighting 255 9.1 Performance Improvement of OLED Lighting 255 9.2 Color Rendering Index 257 9.3 OLED Lighting Requirement 259 9.3.1 Correlated Color Temperature (CCT) 260 9.3.2 Other Requirements 262 9.4 Light Extraction Enhancement of OLED Lighting 262 9.4.1 Various Light Absorption Mechanisms 262 9.4.2 Microlens Array Structure 266 9.4.3 Diffusion Structure 266 9.4.4 Diffraction Structure 268 9.4.5 Reduction of Plasmon Absorption 268 9.4.5.1 Plasmonic Loss Mechanism 268 9.5 Color Tunable OLED Lighting 269 9.6 OLED Lighting Design 272 9.6.1 Resistance Reduction 272 9.6.2 Current Reduction 272 9.7 Roll-to-Roll OLED Lighting Manufacturing 273 References 275 Appendix 277 Index 281

Read more less

Book SynopsisAn all-in-one guide to high-voltage, multi-terminal converters, this book brings together the state of the art and cutting-edge techniques in the various stages of designing and constructing a high-voltage converter. The book includes 9 chapters, and can be classified into three aspects. First, all existing high-voltage converters are introduced, including the conventional two-level converter, and the multi-level converters, such as the modular multi-level converter (MMC). Second, different kinds of multi-terminal high-voltage converters are presented in detail, including the topology, operation principle, control scheme and simulation verification. Third, some common issues of the proposed multi-terminal high-voltage converters are discussed, and different industrial applications of the proposed multi-terminal high-voltage converters are provided. Systematically proposes, for the first time, the design methodology for high-voltage converters in use of MTDC grids; also Table of ContentsAbout the Authors xi Preface xiii Acknowledgments xv 1 Overview of High-voltage Converters 1 1.1 Introduction 1 1.2 Classification of High-voltage High-Power Converters 5 1.2.1 Two-Level Converters 5 1.2.2 Multilevel Converters 7 1.3 Topologies of Multilevel Converters 8 1.3.1 Neutral-Point Clamped Converter 8 1.3.2 Flying Capacitor Converter 10 1.3.3 Cascaded H-bridge Converter 11 1.3.4 Modular Multilevel Converter 13 1.3.5 Active Neutral-Point Clamped Converter 16 1.3.6 Hybrid Multilevel Converters 19 1.4 Modulation Methods of Multilevel Converter 22 1.4.1 Space-Vector Modulation 24 1.4.2 Multicarrier Pulse-Width Modulation 24 1.4.3 Selective Harmonic Elimination Modulation 25 1.4.4 Nearest-Level Control Method 26 1.4.5 Hybrid Modulation 27 1.5 Architecture of Multi-terminal High-voltage Converter 27 1.6 Arrangement of this Book 31 References 32 2 Multiple-Bridge-Module High-voltage Converters 35 2.1 Introduction 35 2.2 Configuration of Bridge Module 35 2.2.1 Half-Bridge Module 36 2.2.2 Full-Bridge Module 37 2.3 Single-Phase Half-Bridge-Module High-voltage Converter 39 2.3.1 Basic Structure and Operating Principle 39 2.3.2 Control Scheme 41 2.3.3 Output Voltage Verification 43 2.3.4 Simplified Single-Phase Half-Bridge Module 43 2.4 Three-Phase Half-Bridge-Module High-voltage Converter 45 2.4.1 Basic Structure and Operating Principle 45 2.4.2 Control Scheme 47 2.4.3 Output Voltage Verification 49 2.5 Three-Phase Four-Leg Half-Bridge-Module High-voltage Converter 51 2.6 Full-Bridge-Module High-voltage Converter 51 2.7 Advantages of Multiple-Bridge-Module Converter 53 2.8 Summary 54 References 54 3 Single-InputMultiple-Output High-voltage DC–AC Converters 55 3.1 Introduction 55 3.2 Single-Input Dual-Output Half-Bridge Single-Phase DC–AC Converter 55 3.2.1 Basic Structure and Operating Principle 55 3.2.2 Control Scheme 57 3.2.3 Output Voltage Verification 59 3.3 Single-Input Dual-Output Full-Bridge Single-Phase DC–AC Converter 60 3.3.1 Basic Structure and Operating Principle 60 3.3.2 Control Scheme 62 3.3.3 Output Voltage Verification 62 3.4 Single-Input Dual-Output Three-Phase DC–AC Converter 64 3.4.1 Basic Structure and Operating Principle 64 3.4.2 Control Scheme 64 3.4.3 Output Voltage Verification 66 3.5 Single-InputMultiple-Output Half-Bridge Single-Phase DC–AC Converter 67 3.5.1 Basic Structure and Operating Principle 67 3.5.2 Control Scheme 69 3.5.3 Output Voltage Verification 70 3.6 Single-InputMultiple-Output Full-Bridge Single-Phase DC–AC Converter 72 3.6.1 Basic Structure and Operating Principle 72 3.6.2 Control Scheme 72 3.6.3 Output Voltage Verification 75 3.7 Single-InputMultiple-Output Three-Phase DC–AC Converter 75 3.7.1 Basic Structure and Operating Principle 75 3.7.2 Control Scheme 77 3.7.3 Output Voltage Verification 77 3.8 Summary 79 References 79 4 Multiple-Input Single-Output High-voltage AC–DC Converters 81 4.1 Introduction 81 4.2 Single-PhaseThree-Arm Dual-Input Single-Output AC–DC Converter 81 4.2.1 Basic Structure and Operating Principle 81 4.2.2 Control Scheme 83 4.2.3 Performance Verification 84 4.3 Single-Phase Six-Arm Dual-Input Single-Output AC–DC Converter 84 4.3.1 Basic Structure and Operating Principle 84 4.3.2 Control Scheme 88 4.3.3 Performance Verification 89 4.4 Three-Phase Nine-Arm Dual-Input Single-Output AC–DC Converter 93 4.4.1 Basic Structure and Operating Principle 93 4.4.2 Control Scheme 93 4.4.3 Performance Verification 95 4.5 Single-Phase M-Arm Multiple-Input Single-Output AC–DC Converter 95 4.5.1 Basic Structure and Operating Principle 95 4.5.2 Control Scheme 98 4.5.3 Performance Verification 100 4.6 Single-Phase 2M-Arm Multiple-Input Single-Output AC–DC Converter 100 4.6.1 Basic Structure and Operating Principle 100 4.6.2 Control Scheme 104 4.6.3 Performance Verification 105 4.7 Three-Phase 3M-Arm Multiple-Input Single-Output AC–DC Converter 106 4.7.1 Basic Structure and Operating Principle 106 4.7.2 Control Scheme 106 4.7.3 Performance Verification 110 4.8 Summary 110 References 112 5 Multiple-InputMultiple-Output High-voltage AC–AC Converters 113 5.1 Introduction 113 5.2 Single-Phase Single-Input Single-Output AC–AC Converter 113 5.2.1 Basic Structure and Operating Principle 113 5.2.2 Control Scheme 114 5.2.3 Output Voltage Verification 117 5.3 Three-Phase Single-Input Single-Output AC–AC Converter 117 5.3.1 Basic Structure and Operating Principle 117 5.3.2 Control Scheme 118 5.3.3 Output Voltage Verification 120 5.4 Single-Phase Multiple-terminal AC–AC Converter 122 5.4.1 Basic Structure and Operating Principle 122 5.4.2 Control Scheme 124 5.4.3 Output Voltage Verification 125 5.5 Three-Phase Multiple-terminal AC–AC Converter 125 5.5.1 Basic Structure and Operating Principle 125 5.5.2 Control Scheme 126 5.5.3 Output Voltage Verification 129 5.6 Summary 133 References 133 6 Multiple-terminal High-voltage DC–DC Converters 135 6.1 Introduction 135 6.2 Single-Input Dual-Output DC–DC Converter 135 6.2.1 Basic Structure and Operating Principle 135 6.2.2 Control Scheme 136 6.2.3 Simulation Verification 138 6.3 Single-InputMultiple-Output DC–DC Converter 138 6.3.1 Basic Structure and Operating Principle 138 6.3.2 Control Scheme 141 6.3.3 Simulation Verification 143 6.4 Multiple-InputMultiple-Output DC–DC Converter 143 6.5 Summary 146 References 146 7 Multiple-terminal High-voltage Hybrid Converters 147 7.1 Introduction 147 7.2 Six-Arm Hybrid Converter with Single-Phase AC Input 147 7.2.1 Basic Structure and Operating Principle 147 7.2.2 Control Scheme 149 7.2.3 Simulation Verification 151 7.3 Nine-Arm Hybrid Converter with Three-Phase AC Input 151 7.3.1 Basic Structure and Operating Principle 151 7.3.2 Control Scheme 152 7.3.3 Simulation Verification 153 7.4 Multiple-Arm Hybrid Converter 153 7.4.1 Basic Structure and Operating Principle 153 7.4.2 Control Scheme 158 7.5 Summary 159 References 159 8 Short-Circuit Protection for High-voltage Converters 161 8.1 Introduction 161 8.2 Modular DC Circuit Breaker 162 8.3 Sub-Modules with DC Fault-Handling Capability 165 8.3.1 Full-Bridge Sub-Module 165 8.3.2 Clamp-Double Sub-Module 166 8.3.3 Unipolar-Voltage Sub-Module 167 8.3.4 Cross-Connected Sub-Module 168 8.3.5 Series-Connected Double Sub-Module 170 8.4 Configuration of the Hybrid Multi-terminal High-voltage Converter 171 8.5 Summary 174 References 175 9 Common Techniques and Applications of Multi-terminal High-voltage Converters 177 9.1 Introduction 177 9.2 Capacitor Voltage Control Scheme for Multi-terminal High-voltage Converters 177 9.2.1 Single-Input Dual-Output DC–AC Converter 177 9.2.2 Single-Phase Multiple-Input Single-Output AC–DC Converter 182 9.3 Applications of Multi-terminal High-voltage Converter 192 9.3.1 Multiple Wind Turbines and DC Bus 192 9.3.2 Multiple Wind Turbines and AC Bus 196 9.3.3 Multiple AC Motors and DC Bus 196 9.3.4 Multiple AC Motors and AC Bus 196 9.4 Summary 200 References 200 Index201

Read more less

Book SynopsisA timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, showcasing recent advances and industrially relevant applications Explores the synergy between the important topics of iterative learning control (ILC) and multi-agent systems (MAS) Concisely summarizes recent advances and significant applications in ILC methods for power grids, sensor networks and control processes Covers basic theory, rigorous mathematics as well as engineering practice Table of ContentsPreface ix 1 Introduction 1 1.1 Introduction to Iterative Learning Control 1 1.1.1 Contraction-Mapping Approach 3 1.1.2 Composite Energy Function Approach 4 1.2 Introduction to MAS Coordination 5 1.3 Motivation and Overview 7 1.4 Common Notations in This Book 9 2 Optimal Iterative Learning Control for Multi-agent Consensus Tracking 11 2.1 Introduction 11 2.2 Preliminaries and Problem Description 12 2.2.1 Preliminaries 12 2.2.2 Problem Description 13 2.3 Main Results 15 2.3.1 Controller Design for Homogeneous Agents 15 2.3.2 Controller Design for Heterogeneous Agents 20 2.4 Optimal Learning Gain Design 21 2.5 Illustrative Example 23 2.6 Conclusion 26 3 Iterative Learning Control for Multi-agent Coordination Under Iteration-Varying Graph 27 3.1 Introduction 27 3.2 Problem Description 28 3.3 Main Results 29 3.3.1 Fixed Strongly Connected Graph 29 3.3.2 Iteration-Varying Strongly Connected Graph 32 3.3.3 Uniformly Strongly Connected Graph 37 3.4 Illustrative Example 38 3.5 Conclusion 40 4 Iterative Learning Control for Multi-agent Coordination with Initial State Error 41 4.1 Introduction 41 4.2 Problem Description 42 4.3 Main Results 43 4.3.1 Distributed D-type Updating Rule 43 4.3.2 Distributed PD-type Updating Rule 48 4.4 Illustrative Examples 49 4.5 Conclusion 50 5 Multi-agent Consensus Tracking with Input Sharing by Iterative Learning Control 53 5.1 Introduction 53 5.2 Problem Formulation 54 5.3 Controller Design and Convergence Analysis 54 5.3.1 Controller Design Without Leader’s Input Sharing 55 5.3.2 Optimal Design Without Leader’s Input Sharing 58 5.3.3 Controller Design with Leader’s Input Sharing 59 5.4 Extension to Iteration-Varying Graph 60 5.4.1 Iteration-Varying Graph with Spanning Trees 60 5.4.2 Iteration-Varying Strongly Connected Graph 60 5.4.3 Uniformly Strongly Connected Graph 62 5.5 Illustrative Examples 63 5.5.1 Example 1: Iteration-Invariant Communication Graph 63 5.5.2 Example 2: Iteration-Varying Communication Graph 64 5.5.3 Example 3: Uniformly Strongly Connected Graph 66 5.6 Conclusion 68 6 A HOIM-Based Iterative Learning Control Scheme for Multi-agent Formation 69 6.1 Introduction 69 6.2 Kinematic Model Formulation 70 6.3 HOIM-Based ILC for Multi-agent Formation 71 6.3.1 Control Law for Agent 1 72 6.3.2 Control Law for Agent 2 74 6.3.3 Control Law for Agent 3 75 6.3.4 Switching Between Two Structures 78 6.4 Illustrative Example 78 6.5 Conclusion 80 7 P-type Iterative Learning for Non-parameterized Systems with Uncertain Local Lipschitz Terms 81 7.1 Introduction 81 7.2 Motivation and Problem Description 82 7.2.1 Motivation 82 7.2.2 Problem Description 83 7.3 Convergence Properties with Lyapunov Stability Conditions 84 7.3.1 Preliminary Results 84 7.3.2 Lyapunov Stable Systems 86 7.3.3 Systems with Stable Local Lipschitz Terms but Unstable Global Lipschitz Factors 90 7.4 Convergence Properties in the Presence of Bounding Conditions 92 7.4.1 Systems with Bounded Drift Term 92 7.4.2 Systems with Bounded Control Input 94 7.5 Application of P-type Rule in MAS with Local Lipschitz Uncertainties 97 7.6 Conclusion 99 8 Synchronization for Nonlinear Multi-agent Systems by Adaptive Iterative Learning Control 101 8.1 Introduction 101 8.2 Preliminaries and Problem Description 102 8.2.1 Preliminaries 102 8.2.2 Problem Description for First-Order Systems 102 8.3 Controller Design for First-Order Multi-agent Systems 105 8.3.1 Main Results 105 8.3.2 Extension to Alignment Condition 107 8.4 Extension to High-Order Systems 108 8.5 Illustrative Example 113 8.5.1 First-Order Agents 114 8.5.2 High-Order Agents 115 8.6 Conclusion 118 9 Distributed Adaptive Iterative Learning Control for Nonlinear Multi-agent Systems with State Constraints 123 9.1 Introduction 123 9.2 Problem Formulation 124 9.3 Main Results 127 9.3.1 Original Algorithms 127 9.3.2 Projection Based Algorithms 135 9.3.3 Smooth Function Based Algorithms 138 9.3.4 Alternative Smooth Function Based Algorithms 141 9.3.5 Practical Dead-Zone Based Algorithms 156 9.4 Illustrative Example 163 9.5 Conclusion 171 10 Synchronization for Networked Lagrangian Systems under Directed Graphs 173 10.1 Introduction 173 10.2 Problem Description 174 10.3 Controller Design and Performance Analysis 175 10.4 Extension to Alignment Condition 181 10.5 Illustrative Example 182 10.6 Conclusion 186 11 Generalized Iterative Learning for Economic Dispatch Problem in a Smart Grid 187 11.1 Introduction 187 11.2 Preliminaries 188 11.2.1 In-Neighbor and Out-Neighbor 188 11.2.2 Discrete-Time Consensus Algorithm 189 11.2.3 Analytic Solution to EDP with Loss Calculation 190 11.3 Main Results 191 11.3.1 Upper Level: Estimating the Power Loss 192 11.3.2 Lower Level: Solving Economic Dispatch Distributively 192 11.3.3 Generalization to the Constrained Case 195 11.4 Learning Gain Design 196 11.5 Application Examples 198 11.5.1 Case Study 1: Convergence Test 199 11.5.2 Case Study 2: Robustness of Command Node Connections 200 11.5.3 Case Study 3: Plug and Play Test 201 11.5.4 Case Study 4: Time-Varying Demand 203 11.5.5 Case Study 5: Application in Large Networks 205 11.5.6 Case Study 6: Relation Between Convergence Speed and Learning Gain 205 11.6 Conclusion 206 12 Summary and Future Research Directions 207 12.1 Summary 207 12.2 Future Research Directions 208 12.2.1 Open Issues in MAS Control 208 12.2.2 Applications 212 Appendix A Graph Theory Revisit 221 Appendix B Detailed Proofs 223 B.1 HOIM Constraints Derivation 223 B.2 Proof of Proposition 2.1 224 B.3 Proof of Lemma 2.1 225 B.4 Proof of Theorem 8.1 227 B.5 Proof of Corollary 8.1 228 Bibliography 231 Index 000

Read more less

Book SynopsisLeverage the power of OpenStack to develop scalable applications with no vendor lock-in OpenStack Cloud Application Development is a fast-paced, professional book for OpenStack developers, delivering comprehensive guidance without wasting time on development fundamentals.Table of ContentsINTRODUCTION xi PART I: OPENSTACK OVERVIEW CHAPTER 1: INTRODUCING OPENSTACK 3 What Is Cloud Computing? 3 Why Should I Care? 6 Understanding the Architecture 13 Summary 18 CHAPTER 2: UNDERSTANDING THE OPENSTACK ECOSYSTEM: CORE PROJECTS 19 Identity 20 Compute 24 Storage 28 Imaging 34 Dashboard 37 Networking 38 Bringing It All Together 45 Summary 48 CHAPTER 3: UNDERSTANDING THE OPENSTACK ECOSYSTEM: ADDITIONAL PROJECTS 49 OpenStack Heat 50 OpenStack Database as a Service: Trove 54 Designate: DNS as a Service 62 Magnum 67 Murano: Application as a Service 70 Ceilometer: Telemetry as a Service 75 Summary 76 PART II: DEVELOPING AND DEPLOYING APPLICATIONS WITH OPENSTACK CHAPTER 4: APPLICATION DEVELOPMENT 79 Converting a Legacy App to an OpenStack App 79 Building Apps from Scratch 83 OpenStack App Description and Deployment Strategies 87 Summary 92 CHAPTER 5: IMPROVING ON THE APPLICATION 93 Failure Scenarios 94 Hostname and IP Addressing 99 Scaling 103 Improving Our Application 111 Summary 119 CHAPTER 6: DEPLOYING THE APPLICATION 121 Bare Metal, Virtual Machines, and Containers 122 Orchestration and Configuration Management 127 Monitoring and Metering 136 Elasticity 137 Updating and Patching 147 Summary 149 Book Wrap Up 149 INDEX 151

Read more less

Book SynopsisExamines the important topic of fuel cell science by way of combining membrane design, chemical degradation mechanisms, and stabilization strategies This book describes the mechanism of membrane degradation and stabilization, as well as the search for stable membranes that can be used in alkaline fuel cells. Arranged in ten chapters, the book presents detailed studies that can help readers understand the attack and degradation mechanisms of polymer membranes and mitigation strategies. Coverage starts from fundamentals and moves to different fuel cell membrane types and methods to profile and analyze them. The Chemistry of Membranes Used in Fuel Cells: Degradation and Stabilization features chapters on: Fuel Cell Fundamentals: The Evolution of Fuel Cells and their Components; Degradation Mechanism of Perfluorinated Membranes; Ranking the Stability of Perfluorinated Membranes Used in Fuel Cells to Attack by Hydroxyl Radicals; Stabilization Mechanism of PerfTable of Contents Preface xiii About the Editor xvii List of Contributors xix 1 The Evolution of Fuel Cells and Their Components 1Thomas A. Zawodzinski, Zhijiang Tang, and Nelly Cantillo 1.1 Overview: A Personal Perspective of Recent Developments 1 1.2 Basics of Fuel Cell Operation 3 1.3 Types of Fuel Cells 5 1.3.1 Phosphoric Acid Fuel Cell 5 1.3.2 Molten Carbonate Fuel Cell and Solid Oxide Fuel Cell 5 1.3.3 Proton Exchange Membranes Fuel Cell 6 1.3.4 Alkaline Fuel Cell 6 1.3.5 Solid Acid Fuel Cell 8 1.4 Low Temperature Fuel Cells: Components 8 1.4.1 Membranes in PEM Systems 9 1.4.2 Electrocatalysts in PEM Systems 11 1.4.2.1 Catalyst Layer Structure in PEM Systems 13 1.5 Summary 16 Acknowledgments 16 References 16 2 Degradation Mechanism of Perfluorinated Membranes 19Marek Danilczuk, Shulamith Schlick, and Frank D. Coms 2.1 Introduction 19 2.2 Fluoride Release Rate 22 2.3 Nuclear Magnetic Resonance 26 2.4 Fourier Transform Infrared Spectroscopy 30 2.5 Electron Spin Resonance 37 2.5.1 Direct ESR Radical Detection in Perfluorinated Membranes 37 2.5.2 Spin Trapping ESR 40 2.5.3 In Situ ESR Fuel Cell 41 2.5.4 Chemical Reactions and Crossover Processes in a Fuel Cell 43 2.5.5 Effect of Membrane Thickness 46 2.6 Conclusions 49 Acknowledgments 51 References 51 3 Ranking the Stability of Perfluorinated Membranes to Attack by Hydroxyl Radicals 55Marek Danilczuk and Shulamith Schlick 3.1 Introduction 55 3.2 The Chemical Stability of Perfluorinated Ionomers 57 3.3 Electron Spin Resonance Studies of PFSAs Exposed to Hydroxyl Radicals 61 3.3.1 Spin©\Trapping ESR 61 3.3.2 Competitive Kinetics: Perfluorinated Ionomers as Competitors for HO• Radicals 62 3.3.3 Ce(III) as Competitor 68 3.4 Conclusions 70 Acknowledgments 72 References 72 4 Stabilization of Perfluorinated Membranes Using Ce3+ and Mn2+ Redox Scavengers: Mechanisms and Applications 75Frank D. Coms, Shulamith Schlick, and Marek Danilczuk 4.1 Introduction 75 4.2 Oxidant Chemistry 76 4.3 Degradation Mechanisms of PFSA 79 4.4 Mitigation of Chemical Degradation by Redox Quenchers 81 4.4.1 Mitigation Mechanisms of Ce3+ and Mn2+ 82 4.4.1.1 Cerium Mitigation and Chain Scission Processes 89 4.4.2 ESR Spin Trapping Studies 89 4.4.3 Oxidative Stress and Ce3+ Mitigation 91 4.4.3.1 MEA Design 96 4.4.4 Cerium Distribution and Migration 97 4.4.5 CeO2 Mitigation 100 4.4.6 Synergistic Mitigation Strategies 101 4.5 Conclusions 103 Acknowledgments 104 References 104 5 Hydrocarbon Proton Exchange Membranes 107Lorenz Gubler and Willem H. Koppenol 5.1 Introduction 107 5.2 Radical Intermediates in Fuel Cells 108 5.3 Hydrocarbon Membranes 114 5.4 Chemical Stabilization by Antioxidants 119 5.4.1 Regenerative Radical Scavenging in PFSA Membranes 119 5.4.2 Hydrocarbon Membranes Doped with Organic Antioxidants 121 5.4.3 Polymer©\Bound Antioxidants 122 5.5 The Challenge of Regeneration 125 5.5.1 Learnings from Mother Nature 125 5.5.2 Approaches for the Fuel Cell 126 5.6 Concluding Remarks 133 References 134 6 Stabilization of Perfluorinated Membranes Using Nanoparticle Additives 139Guanxiong Wang, Javier Parrondo, and Vijay Ramani 6.1 Nanoparticle Additives as a Stabilizer for Perfluorinated Membranes 139 6.2 CeO2 and Modified CeO2 Nanoparticles as FRSs 141 6.3 Platinum©\Supported Ceria as FRS 152 6.4 Manganese Oxide and Manganese Oxide Composite as FRSs 154 6.5 Metal Nanoparticles as FRSs 160 6.6 Experimental Techniques for the Detection of Free Radicals and Measurement of the Membrane Degradation Rates 163 6.6.1 Fluoride Emission Rate 163 6.6.2 Fluorescence Spectroscopy as a Tool for the Detection and Quantification of Free Radical Degradation in PEMs 163 6.7 Conclusions 164 Acknowledgments 165 References 166 7 Degradation Mechanisms in Aquivion® Perfluorinated Membranes and Stabilization Strategies 171Vincenzo Arcella, Luca Merlo, and Alessandro Ghielmi 7.1 Introduction 171 7.2 Properties of SSC Ionomers 173 7.3 Properties of Aquivion® Ionomers 173 7.4 The Need for High Stability of PFSA Membranes 177 7.5 PFSA Membrane Degradation in Fuel Cell 177 7.6 Generation of Radical Species in the Fuel Cell Environment 178 7.7 Degradation Studies on Aquivion® Membranes 181 7.8 Stabilization Procedures on Aquivion® Membranes 185 7.9 Conclusions 190 References 190 8 Anion Exchange Membranes: Stability and Synthetic Approach 195Dongwon Shin, Chulsung Bae, and Yu Seung Kim 8.1 Introduction 195 8.2 Chemical Degradation Mechanisms 196 8.2.1 Degradation of Cationic Groups 196 8.2.1.1 Alkyl Ammoniums 196 8.2.1.2 N©\Based Cyclic Cations 199 8.2.1.3 Other Cationic Groups 202 8.2.2 Degradation of Polymer Backbones 204 8.2.2.1 Polyolefins 205 8.2.2.2 Polyaromatics 205 8.2.2.3 Polyacrylates 207 8.2.2.4 Polybenzimidazoles 208 8.2.2.5 Perfluorinated Polymers 208 8.3 Synthetic Approaches 210 8.3.1 Polyolefins 210 8.3.1.1 Polyethylene and Polypropylene 211 8.3.1.2 Polystyrene 212 8.3.1.3 Others 215 8.3.2 Polyaromatics 217 8.3.2.1 Cationic©\Group©\Tethered Poly(arylene)s 217 8.3.2.2 Poly(arylene)©\Containing Cationic Polymer Backbones 219 8.3.2.3 Multication©\Tethered Poly(arylene)s 219 8.3.3 Other Polymers 221 8.3.3.1 Polybenzimidazoles 221 8.3.3.2 Polynorbornenes 223 8.3.3.3 Perfluorinated Polymers 224 8.4 Conclusions 225 Acknowledgments 225 References 226 9 Profiling of Membrane Degradation Processes in a Fuel Cell by 2D Spectral–Spatial FTIR 229Shulamith Schlick and Marek Danilczuk 9.1 Introduction 229 9.2 Optical Images of Nafion® Cross Sections 231 9.3 Line Scan Maps of the Membranes 232 9.4 FTIR Spectra of Nafion® MEAs 232 9.5 Abstraction of a Fluorine Atom on a Carbon in the Nafion® Main Chain by H• 235 9.6 Conclusions 237 Acknowledgments 237 References 238 10 Quantum Mechanical Calculations of the Degradation in Perfluorinated Membranes Used in Fuel Cells 241Ted H. Yu, Boris V. Merinov, and William A. Goddard III 10.1 Introduction 241 10.2 Computational Methods 244 10.3 Results and Discussion 244 10.3.1 Generation of Radicals 244 10.3.1.1 Hydroxyl Radicals 244 10.3.1.2 Hydrogen Radicals, H• 247 10.3.1.3 Hydroperoxyl Radicals, HOO• 249 10.3.2 Concentrated HO• Conditions versus Fuel Cell Conditions 249 10.3.3 Degradation under Concentrated HO• Conditions 249 10.3.3.1 R©¤CF2H Polymer Main Chain Defect Initiation 249 10.3.3.2 R©¤CF¨TCF2 Polymer Main Chain Defect Initiation 250 10.3.3.3 R©¤COOH Polymer Main Chain Defect Initiation 250 10.3.3.4 Propagating Polymer Main Chain Degradation 250 10.3.3.5 Side©\Chain Degradation 252 10.3.4 Degradation under Fuel Cell Conditions with Fuel Crossover 256 10.3.4.1 Polymer Main Chain End©\Group Initiation 256 10.3.4.2 Propagating Polymer Main Chain Degradation 256 10.3.4.3 Side©\Chain Degradation 257 10.3.5 Degradation under Fuel Cell Conditions without Crossover 259 10.3.5.1 Degradation at the Cathode without H2 Crossover 259 10.3.5.2 Degradation at the Anode without O2 Crossover 261 10.4 Summary 265 10.4.1 Concentrated HO• Conditions 265 10.4.2 Fuel Cell Conditions 265 10.4.2.1 Fuel Cell Conditions without Crossover at Cathode 266 10.4.2.2 Fuel Cell Conditions without Crossover at Anode 266 Acknowledgments 267 References 267 Index 271

Read more less

Book SynopsisOffers a theoretical and practical guide to the communication and navigation of autonomous mobile robots and multi-robot systems This book covers the methods and algorithms for the navigation, motion planning, and control of mobile robots acting individually and in groups. It addresses methods of positioning in global and local coordinates systems, off-line and on-line path-planning, sensing and sensors fusion, algorithms of obstacle avoidance, swarming techniques and cooperative behavior. The book includes ready-to-use algorithms, numerical examples and simulations, which can be directly implemented in both simple and advanced mobile robots, and is accompanied by a website hosting codes, videos, and PowerPoint slides Autonomous Mobile Robots and Multi-Robot Systems: Motion-Planning, Communication and Swarming consists of four main parts. The first looks at the models and algorithms of navigation and motion planning in global coordinates systems with compTable of ContentsList of Contributors xi Preface xiii Acknowledgments xv About the Companion Website xvii Introduction 1Eugene Kagan, Nir Shvalb, and Irad Ben-Gal I.1 Early History of Robots 1 I.2 Autonomous Robots 2 I.3 Robot Arm Manipulators 6 I.4 Mobile Robots 8 I.5 Multi-Robot Systems and Swarms 12 I.6 Goal and Structure of the Book 16 References 17 1 Motion-Planning Schemes in Global Coordinates 21Oded Medina and Nir Shvalb 1.1 Motivation 21 1.2 Notations 21 1.2.1 The Configuration Space 22 1.2.2 The Workspace 23 1.2.3 The Weight Function 23 1.3 Motion-Planning Schemes: Known Configuration Spaces 25 1.3.1 Potential-Field Algorithms 25 1.3.2 Grid-Based Algorithms 27 1.3.3 Sampling-Based Algorithms 29 1.4 Motion-Planning Schemes: Partially Known Configuration Spaces 30 1.4.1 BUG0 (Reads Bug-Zero) 31 1.4.2 BUG1 32 1.4.3 BUG2 32 1.5 Summary 33 References 33 2 Basic Perception 35Simon Lineykin 2.1 Basic Scheme of Sensors 35 2.2 Obstacle Sensor (Bumper) 36 2.3 The Odometry Sensor 48 2.4 Distance Sensors 52 2.4.1 The ToF Range Finders 52 2.4.2 The Phase Shift Range Finder 56 2.4.3 Triangulation Range Finder 59 2.4.4 Ultrasonic Rangefinder 60 2.5 Summary 63 References 63 3 Motion in the Global Coordinates 65Nir Shvalb and Shlomi Hacohen 3.1 Models of Mobile Robots 65 3.1.1 Wheeled Mobile Robots 65 3.1.2 Aerial Mobile Robots 67 3.2 Kinematic and Control of Hilare-Type Mobile Robots 69 3.2.1 Forward Kinematics of Hilare-Type Mobile Robots 69 3.2.2 Velocity Control of Hilare-Type Mobile Robots 71 3.2.3 Trajectory Tracking 72 3.3 Kinematic and Control of Quadrotor Mobile Robots 74 3.3.1 Dynamics of Quadrotor-Type Mobile Robots 74 3.3.2 Forces and Torques Generated by the Propellers 75 3.3.3 Relative End Global Coordinates 76 3.3.4 The Quadrotor Dynamic Model 78 3.3.5 A Simplified Dynamic Model 79 3.3.6 Trajectory Tracking Control of Quadrotors 80 3.3.7 Simulations 84 References 85 4 Motion in Potential Field and Navigation Function 87Nir Shvalb and Shlomi Hacohen 4.1 Problem Statement 87 4.2 Gradient Descent Method of Optimization 89 4.2.1 Gradient Descent Without Constraints 89 4.2.2 Gradient Descent with Constraints 92 4.3 Minkowski Sum 94 4.4 Potential Field 95 4.5 Navigation Function 99 4.5.1 Navigation Function in Static Deterministic Environment 99 4.5.2 Navigation Function in Static Uncertain Environment 102 4.5.3 Navigation Function and Potential Fields in Dynamic Environment 104 4.5.3.1 Estimation 105 4.5.3.2 Prediction 105 4.5.3.3 Optimization 106 4.6 Summary 106 References 107 5 GNSS and Robot Localization 109Roi Yozevitch and Boaz Ben-Moshe 5.1 Introduction to Satellite Navigation 109 5.1.1 Trilateration 109 5.2 Position Calculation 111 5.2.1 Multipath Signals 111 5.2.2 GNSS Accuracy Analysis 112 5.2.3 DoP 112 5.3 Coordinate Systems 113 5.3.1 Latitude, Longitude, and Altitude 113 5.3.2 UTM Projection 113 5.3.3 Local Cartesian Coordinates 114 5.4 Velocity Calculation 115 5.4.1 Calculation Outlines 115 5.4.2 Implantation Remarks 116 5.5 Urban Navigation 116 5.5.1 Urban Canyon Navigation 117 5.5.2 Map Matching 117 5.5.3 Dead Reckoning – Inertial Sensors 118 5.6 Incorporating GNSS Data with INS 118 5.6.1 Modified Particle Filter 118 5.6.2 Estimating Velocity by Combining GNSS and INS 119 5.7 GNSS Protocols 120 5.8 Other Types of GPS 121 5.8.1 A-GPS 121 5.8.2 DGPS Systems 122 5.8.3 RTK Navigation 122 5.9 GNSS Threats 123 5.9.1 GNSS Jamming 123 5.9.2 GNSS Spoofing 123 References 123 6 Motion in Local Coordinates 125Shraga Shoval 6.1 Global Motion Planning and Navigation 125 6.2 Motion Planning with Uncertainties 128 6.2.1 Uncertainties in Vehicle Performance 128 6.2.1.1 Internal Dynamic Uncertainties 128 6.2.1.2 External Dynamic Uncertainties 129 6.2.2 Sensors Uncertainties 129 6.2.3 Motion-Planning Adaptation to Uncertainties 130 6.3 Online Motion Planning 131 6.3.1 Motion Planning with Differential Constraints 132 6.3.2 Reactive Motion Planning 134 6.4 Global Positioning with Local Maps 135 6.5 UAV Motion Planning in 3D Space 137 6.6 Summary 139 References 140 7 Motion in an Unknown Environment 143Eugene Kagan 7.1 Probabilistic Map-Based Localization 143 7.1.1 Beliefs Distribution and Markov Localization 145 7.1.2 Motion Prediction and Kalman Localization 150 7.2 Mapping the Unknown Environment and Decision-Making 154 7.2.1 Mapping and Localization 155 7.2.2 Decision-Making under Uncertainties 161 7.3 Examples of Probabilistic Motion Planning 169 7.3.1 Motion Planning in Belief Space 169 7.3.2 Mapping of the Environment 176 7.4 Summary 178 References 179 8 Energy Limitations and Energetic Efficiency of Mobile Robots 183Michael Ben Chaim 8.1 Introduction 183 8.2 The Problem of Energy Limitations in Mobile Robots 183 8.3 Review of Selected Literature on Power Management and Energy Control in Mobile Robots 185 8.4 Energetic Model of Mobile Robot 186 8.5 Mobile Robots Propulsion 188 8.5.1 Wheeled Mobile Robots Propulsion 189 8.5.2 Propulsion of Mobile Robots with Caterpillar Drive 190 8.6 Energetic Model of Mechanical Energies Sources 192 8.6.1 Internal Combustion Engines 193 8.6.2 Lithium Electric Batteries 194 8.7 Summary 195 References 195 9 Multi-Robot Systems and Swarming 199Eugene Kagan, Nir Shvalb, Shlomi Hacohen, and Alexander Novoselsky 9.1 Multi-Agent Systems and Swarm Robotics 199 9.1.1 Principles of Multi-Agent Systems 200 9.1.2 Basic Flocking and Methods of Aggregation and Collision Avoidance 208 9.2 Control of the Agents and Positioning of Swarms 218 9.2.1 Agent-Based Models 219 9.2.2 Probabilistic Models of Swarm Dynamics 234 9.3 Summary 236 References 238 10 Collective Motion with Shared Environment Map 243Eugene Kagan and Irad Ben-Gal 10.1 Collective Motion with Shared Information 243 10.1.1 Motion in Common Potential Field 244 10.1.2 Motion in the Terrain with Sharing Information About Local Environment 250 10.2 Swarm Dynamics in a Heterogeneous Environment 253 10.2.1 Basic Flocking in Heterogeneous Environment and External Potential Field 253 10.2.2 Swarm Search with Common Probability Map 259 10.3 Examples of Swarm Dynamics with Shared Environment Map 261 10.3.1 Probabilistic Search with Multiple Searchers 261 10.3.2 Obstacle and Collision Avoidance Using Attraction/Repulsion Potentials 264 10.4 Summary 270 References 270 11 Collective Motion with Direct and Indirect Communication 273Eugene Kagan and Irad Ben-Gal 11.1 Communication Between Mobile Robots in Groups 273 11.2 Simple Communication Protocols and Examples of Collective Behavior 277 11.2.1 Examples of Communication Protocols for the Group of Mobile Robots 278 11.2.1.1 Simple Protocol for Emulating One-to-One Communication in the Lego NXT Robots 278 11.2.1.2 Flocking and Preserving Collective Motion of the Robot’s Group 284 11.2.2 Implementation of the Protocols and Examples of Collective Behavior of Mobile Robots 287 11.2.2.1 One-to-One Communication and Centralized Control in the Lego NXT Robots 287 11.2.2.2 Collective Motion of Lego NXT Robots Preserving the Group Activity 291 11.3 Examples of Indirect and Combined Communication 293 11.3.1 Models of Ant Motion and Simulations of Pheromone Robotic System 293 11.3.2 Biosignaling and Destructive Search by the Group of Mobile Agents 297 11.4 Summary 300 References 301 12 Brownian Motion and Swarm Dynamics 305Eugene Khmelnitsky 12.1 Langevin and Fokker-Plank Formalism 305 12.2 Examples 307 12.3 Summary 316 References 316 13 Conclusions 317Nir Shvalb, Eugene Kagan, and Irad Ben-Gal Index 319

Read more less

Book SynopsisPresents an overview on the different aspects of the energy value chain and discusses the issues that future energy is facing This book covers energy and the energy policy choices which face society. The book presents easy-to-grasp information and analysis, and includes statistical data for energy production, consumption and simple formulas. Among the aspects considered are: science, technology, economics and the impact on health and the environment. In this new edition two new chapters have been added: The first new chapter deals with unconventional fossil fuels, a resource which has become very important from the economical point of view, especially in the United States. The second new chapter presents the applications of nanotechnology in the energy domain. Provides a global vision of available and potential energy sources Discusses advantages and drawbacks to help prepare current and future generations to use energy differently IncludTable of ContentsPreface to the Second Edition xiii Preface to the First Edition xv 1. We Need Energy 1 1.1. Generalities 1 1.1.1. Primary and Secondary Energy 1 1.1.2. Energy Units 3 1.1.3. Power 5 1.1.4. Energy and First Law of Thermodynamics 5 1.1.5. Entropy and Second Law of Thermodynamics 6 1.1.6. Exergy 7 1.1.7. Going Back to the Past 7 1.1.8. Humans and Energy 8 1.2. Always More! 9 1.2.1. Why do we Need More Energy? 10 1.2.2. Energy Sources we Use 13 1.2.3. Security of Supply 18 1.2.4. Environmental Concerns 24 2. Oil and Natural Gas 26 2.1. Genesis of Oil and Natural Gas 27 2.2. Recovering Oil and Gas 30 2.3. Peak Oil 32 2.4. Reserves 34 2.4.1. Crude Oil Reserves 35 2.4.2. Natural Gas Reserves 36 2.5. Properties of Hydrocarbons 38 2.6. Oil Fields 40 2.7. Prices 41 2.8. Consumption 44 2.9. Electricity Generation 46 2.10. Impact on Environment 49 2.11. Conclusion 52 3. Unconventional Oil and Gas Resources 53 3.1. Hydrocarbon Formation 53 3.2. Offshore Hydrocarbons 55 3.3. Unconventional Hydrocarbons 58 3.4. Unconventional Oils 59 3.4.1. Unconventional Oils Contained in Reservoirs 59 3.4.2. Unconventional Oils Contained in Source Rock 60 3.5. Unconventional Gases 61 3.5.1. Unconventional Gases Contained in Reservoirs 61 3.5.2. Unconventional Gases Contained in Source Rocks 62 3.6. Methane Hydrates 69 3.7. Conclusion 70 4. Coal: Fossil Fuel of the Future 71 4.1. Genesis of Coal 72 4.2. Rank of Coals 73 4.3. Classification of Coals 73 4.4. Peat 76 4.5. Use of Coal 78 4.6. Coal Reserves 78 4.7. Production and Consumption 82 4.8. Electricity Production 86 4.9. Coal Combustion for Power Generation 87 4.9.1. Advanced Pulverized Coal Combustion 88 4.9.2. Fluidized‐Bed Combustion at Atmospheric Pressure 88 4.9.3. Pressurized Fluidized‐Bed Combustion 88 4.10. Combined Heat and Power Generation 88 4.11. Integrated Gasification Combined–Cycle Power Plants 89 4.12. Coal‐to‐Liquid Technologies 90 4.13. Direct Coal Liquefaction 90 4.14. Indirect Coal Liquefaction 91 4.15. Direct or Indirect CTL Technology? 92 4.16. Carbon Capture and Sequestration 93 4.16.1. Capture 93 4.16.2. Transport 97 4.16.3. Sequestration 97 4.16.4. Cost 100 4.17. Coal Pit Accidents 100 4.18. Environmental Impacts 101 4.19. Conclusion 102 5. Fossil Fuels and Greenhouse Effect 103 5.1. Greenhouse Effect 104 5.2. Greenhouse Gases 107 5.3. Weather and Climate 111 5.4. Natural Change of Climate 112 5.5. Anthropogenic Emissions 112 5.6. Water and Aerosols 115 5.7. Global Warming Potentials 116 5.8. Increase of Average Temperature 117 5.9. Model Predictions 118 5.10. Energy and Greenhouse Gas Emissions 119 5.11. Consequences 126 5.12. Other Impacts on Ocean 126 5.13. Factor 4 128 5.14. Kyoto Protocol 129 5.15. Conclusion 131 6. Energy from Water 133 6.1. Hydropower 133 6.1.1. Hydropower: Important Source of Electricity 134 6.1.2. Dams and Diversions 137 6.1.3. Head and Flow 139 6.1.4. Turbines 140 6.1.5. Small‐Scale Hydropower 142 6.1.6. Environmental Concerns 144 6.1.7. Costs 144 6.2. Energy from the Ocean 145 6.2.1. Offshore Wind Energy 147 6.2.2. Wave Energy 147 6.2.3. Tidal Energy 151 6.2.4. Marine Current Energy 153 6.2.5. Ocean Thermal Energy Conversion 154 6.2.6. Osmotic Energy 155 7. Biomass 157 7.1. Producing Biomass 159 7.2. An Old Energy Resource 161 7.3. Electricity Production 162 7.4. Technologies 164 7.4.1. Direct Combustion Technologies 164 7.4.2. Cofiring Technologies 165 7.4.3. Biomass Gasification 165 7.4.4. Anaerobic Digestion 166 7.4.5. Pyrolysis 166 7.5. Heat Production 167 7.6. Biomass for Cooking 168 7.7. Environmental Impact 169 7.8. Market Share 170 7.9. Biofuels 172 7.9.1. First‐Generation Biofuels 174 7.9.2. Second‐Generation Biofuels 181 7.9.3. Third‐Generation Biofuels 182 7.10. From Well to Wheels 182 7.11. Conclusion 183 8. Solar Energy 184 8.1. Solar Energy: A Huge Potential 185 8.2. Thermal Solar Energy 186 8.2.1. Producing Hot Water for Domestic Purposes 186 8.2.2. Heating, Cooling, and Ventilation Using Solar Energy 189 8.2.3. The Solar Cooker 190 8.3. Concentrated Solar Power Plants 191 8.3.1. Parabolic Troughs 191 8.3.2. Power Towers 193 8.3.3. Parabolic Dish Collectors 194 8.4. Solar Chimneys or Towers 194 8.5. Photovoltaic Systems 196 8.5.1. Market Dominated by Silicon 197 8.5.2. Other Photovoltaic Technologies 198 8.5.3. Applications 199 8.6. Electricity Storage 204 8.7. Economy and Environment 205 8.8. Conclusion 205 9. Geothermal Energy 207 9.1. Available in Many Places 210 9.2. Different Uses 212 9.3. Technologies 212 9.4. Geothermal Energy in the World 216 9.5. Conclusion 219 10. Wind Energy 220 10.1. Already A Long History 220 10.2. From Theory to Practice 222 10.3. Development of Wind Power 224 10.4. Offshore Wind Turbines 232 10.5. Conclusion 233 11. Nuclear Energy 234 11.1. Basics of Nuclear Energy 234 11.1.1. Atoms and Nuclei 235 11.1.2. Radioactivity 236 11.1.3. Energy and Mass 238 11.1.4. Fission 240 11.1.5. Fissile and Fertile 241 11.1.6. Chain Reaction 242 11.1.7. Critical Mass 244 11.1.8. Nuclear Reactors 245 11.1.9. Natural Nuclear Reactors: Oklo 246 11.1.10. Conclusion 247 11.2. Uses of Nuclear Energy 247 11.2.1. Different Technologies 248 11.2.2. Selection Process 251 11.2.3. Why Nuclear Energy? 253 11.2.4. Uranium Resources 254 11.2.5. Fuel Cycles 257 11.2.6. Safety 260 11.2.7. Nuclear Waste 263 11.2.8. Conclusion 265 11.3. Thermonuclear Fusion 266 11.3.1. Nuclei: Concentrated Sources of Energy 266 11.3.2. The Sun 267 11.3.3. Fusion of Light Nuclei 268 11.3.4. Difficulties 268 11.3.5. A Bit of History 269 11.3.6. Thermonuclear Fusion in Tokamaks 269 11.3.7. ITER: New Step Toward Mastering Fusion 270 11.3.8. About Fuel Reserves 271 11.3.9. Longer Term Possibilities 271 11.3.10. Safety and Waste Issues 272 11.3.11. Conclusion 272 Appendix 273 12. Electricity: Smart Use of Energy 274 12.1. Rapid Development 275 12.2. Energy Sources for Electricity Production 279 12.3. No Unique Solution 281 12.4. From Mechanical Energy to Consumer 286 12.5. Impact on Environment 288 12.6. Cost 289 12.7. Conclusion 290 13. Weak Point of Energy Supply Chain 292 13.1. Electricity Storage 294 13.1.1. Characteristics of Electricity Storage 296 13.1.2. Large‐Quantity Storage Technologies 297 13.1.3. Electrochemical Batteries 303 13.1.4. Supercapacitors 315 13.1.5. Flywheels 317 13.2. Thermal Energy Storage 318 13.2.1. Basic Heat Storage 320 13.2.2. Sensible Heat Storage 320 13.2.3. Phase Change Materials 320 13.2.4. Thermochemical and Thermophysical Energy Storage 322 13.2.5. Applications of Thermal Energy Storage 323 13.2.6. Underground Energy Storage 324 13.2.7. Conclusion 326 14. Transportation 327 14.1. Short History of Transportation 327 14.2. Energy and Transportation 329 14.3. Road Transportation 331 14.4. Ship Transportation 336 14.5. Air Transport 337 14.6. Car Dynamics 339 14.7. Fuels for Road Transportation 340 14.8. Co2 Emissions 343 14.9. Hybrid Vehicles 354 14.10. Electric Vehicles 356 14.11. Conclusion 358 15. Housing 359 15.1. Importance of Housing 359 15.2. Toward More Efficient Housing 363 15.3. Different Regions, Different Solutions 367 15.4. Bioclimatic Architecture 369 15.5. Insulation 370 15.6. Glazing 374 15.7. Lighting 376 15.8. Ventilation 379 15.9. Water 380 15.10. Energy Use in a Household 382 15.11. Heat Pumps 384 15.12. Impact on Environment 387 15.13. Conclusion 390 16. Smart Energy Consumption 391 16.1. Housing 392 16.2. Improving the Way we Consume Energy 393 16.3. Cogeneration 394 16.4. Standby Consumption 396 16.5. Lighting 401 16.6. Transportation 402 16.6.1. Technology 404 16.6.2. Individuals 405 16.7. Conclusion 407 17. Hydrogen 409 17.1. From Production To Distribution 409 17.1.1. Properties 409 17.1.2. Production 411 17.1.3. Storage 420 17.1.4. Hydrogen Transport and Distribution 425 17.1.5. Conclusion 428 17.2. Hydrogen: Energetic Applications 428 17.2.1. Fundamentals of Fuel Cells 428 17.2.2. Different Types of Fuel Cells 431 17.2.3. Transportation 439 17.2.4. Direct Use of Hydrogen 446 17.2.5. Direct Combined Heat and Power 447 17.2.6. Hydrogen and Portable Devices 448 17.2.7. Hydrogen Safety 449 17.2.8. Conclusion 450 18. Nanotechnology and Energy 452 18.1. What is New at the Nanoscale? 452 18.1.1. Surface Effects Prevail 453 18.1.2. Quantum Effects 453 18.2. Nanotechnology and Energy Production 456 18.2.1. Fossil Fuels 457 18.2.2. Syngas 458 18.3. New Energy Technologies 459 18.3.1. Solar Energy 460 18.3.2. Wind Energy 462 18.3.3. Hydrogen 462 18.3.4. Fuel Cells 462 18.3.5. Batteries 463 18.3.6. Thermoelectricity 464 18.3.7. Electrical Distribution 464 18.4. Nanotechnology and Housing 464 18.4.1. Construction Engineering 464 18.4.2. Insulation 465 18.4.3. Lighting 466 18.4.4. Heating, Ventilating, and Air‐Conditioning 468 18.4.5. Surface Materials 468 18.5. Nanotechnology and Transportation 468 18.5.1. Bodywork 469 18.5.2. Interior of the Car 470 18.5.3. Tires 470 18.5.4. Powertrain 471 18.5.5. Electronics 471 18.5.6. Outlook in the Automotive Sector 471 18.6. Conclusion 472 19. Conclusion 474 Exercises 480 Solutions 490 Bibliography 500 Index 505

Read more less

Book SynopsisIntroduction to SYSTEM SCIENCE with MATLAB Explores the mathematical basis for developing and evaluating continuous and discrete systems In this revised Second Edition of Introduction to System Science with MATLAB, the authors Gary Sandquist and Zakary Wilde provide a comprehensive exploration of essential concepts, mathematical framework, analytical resources, and productive skills required to address any rational system confidently and adequately for quantitative evaluation. This Second Edition is supplemented with new updates to the mathematical and technical materials from the first edition. A new chapter to assist readers to generalize and execute algorithms for systems development and analysis, as well as an expansion of the chapter covering specific system science applications, is included. The book provides the mathematical basis for developing and evaluating single and multiple input/output systems that are contiTable of ContentsPreface xi 1 Introduction 1 1.1 System Science 1 1.1.1 Definition of System Science 2 1.2 Principle of Causality 3 1.2.1 Definition 3 1.2.2 Common Examples 4 1.2.3 Relationship to System Science 6 1.3 Overview of System Science 7 1.3.1 Historical Background 7 1.3.2 Major System Science Achievements in the Twentieth Century 9 1.3.3 Measurable Systems and Quantitative Modeling 9 1.3.4 Application of Computers to System Science 13 1.3.5 Utilization of Computer Software in System Science 14 1.3.6 General Applications of System Science 16 1.4 Outline and Utilization of Text 17 1.4.1 Outline of Text 17 1.4.2 Study Schedules by Discipline for this Text 18 1.5 Summary 18 Bibliography 20 Problems 21 2 Fundamental System Concepts 25 2.1 Definitions of System Concepts and Terms 25 2.1.1 Concept and Definition of a System 25 2.1.2 System Causes 26 2.1.3 System Effects 26 2.1.4 Measurability of System Causes and Effects 26 2.1.5 Isolation of a System from Its External Environment 27 2.1.6 Intrinsic and Extrinsic System Feedback 28 2.2 Discussion of System Concepts 28 2.2.1 Concept of a System 28 2.2.2 Isolation of a System from the Environment 29 2.2.3 Identifying and Distinguishing Between Causes and Effects 31 2.3 Classification of Systems by Type 32 2.3.1 Irrational and Immeasurable Systems 33 2.3.2 Continuous and Discrete Systems 35 2.3.3 Deterministic and Stochastic Systems 36 2.3.4 Feedback Systems 37 2.3.5 Controllable Systems 40 2.4 System Analysis and Evaluation Using a Computer 41 2.4.1 Computer Applications to System Analysis 41 2.4.2 Symbolic Computer Applications to System Analysis 41 2.5 Summary 44 Bibliography 45 Problems 46 3 Basic System Equations 49 3.1 Functional Dependence of System Causes and Effects 49 3.1.1 Proportionality Relationship Between Cause and Effect 50 3.1.2 The System Kernel 51 3.2 Classification of System Equations 54 3.2.1 Single-Input, Single-Output Systems 55 3.2.2 Single-Input, Multiple-Output Systems 57 3.2.3 Multiple-Input, Single-Output Systems 61 3.2.4 Multiple-Input, Multiple-Output Systems 63 3.3 Summary 66 Bibliography 67 Problems 67 4 Single-Input Systems 75 4.1 Definition and Significance of a Single-Input System 75 4.2 Single-Input, Single-Output Systems 76 4.2.1 Discrete Systems 77 4.2.2 Continuous Systems 79 4.2.3 Constant System Kernels 81 4.2.4 Linear System Kernels 81 4.2.5 Exact System Kernels 84 4.2.6 Separable System Kernels 87 4.2.7 Homogeneous System Kernels 88 4.2.8 Bernoulli-Type System Kernels 90 4.2.9 Ricatti-Type System Kernels 91 4.2.10 Other Special System Kernel Types 93 4.3 Single-Input, Multiple-Output Systems 97 4.3.1 Discrete System Kernels 98 4.3.2 Continuous System Kernels 100 4.3.3 Constant System Kernels 103 4.3.4 Linear System Kernels with Constant Coefficients 104 4.3.5 Linear System Kernels with Variable Coefficients 107 4.3.6 Exact System Kernels 111 4.3.7 Separable System Kernels 112 4.3.8 Homogeneous System Kernels 114 4.3.9 Autonomous System Kernels 116 4.3.10 System Kernels Associated with Classical Second-Order Ordinary Differential Equations (ODEs) 118 4.3.11 Equivalence of Single-Input System Equations with Ordinary Differential and Difference Equations of Any Order 124 4.4 Treatment of Single-Input Systems Using MATLAB Symbolic Toolbox 128 4.5 Summary 131 Bibliography 131 Problems 132 5 Multiple-Input Systems 141 5.1 Definition and Mathematical Significance 141 5.2 Multiple-Input, Single-Output Systems 142 5.2.1 Discrete Systems 143 5.2.2 Continuous Systems 146 5.2.3 Constant System Kernels 147 5.2.4 Exact System Kernels 148 5.2.5 Linear System Kernels 151 5.2.6 Separable System Kernels 153 5.2.7 Homogeneous System Kernels 154 5.2.8 Inversion of the System Kernel 155 5.2.9 Equivalence of Multiple-Input, Single-Output System Equations and First-Order Partial Differential Equations 157 5.3 Multiple-Input, Multiple-Output Systems 161 5.3.1 Discrete Systems 162 5.3.2 Continuous System Kernels 164 5.3.3 Constant System Kernels 166 5.3.4 Exact System Kernels 166 5.3.5 Linear System Kernels 167 5.3.6 Separable System Kernels 171 5.3.7 Equivalence of Multiple-Input, Multiple-Output Systems and Partial Differential Equations 172 5.3.8 Reduction of Multiple-Input, Multiple-Output Systems Equations 173 5.3.9 Integral Equation Form of the System Equation 175 5.3.10 Elimination of Individual Output Solutions to Reduce the System Equation 176 5.4 Summary 177 Bibliography 178 Problems 178 6 System Modeling 183 6.1 Graphical Representation of Systems 183 6.1.1 Block Diagramming 184 6.1.2 Signal-Flow Graphs 189 6.1.3 Organization Diagrams 194 6.2 Modeling System Inputs, Outputs, and Kernels 199 6.2.1 Single-Input, Single-Output System 204 6.2.2 Physical Systems 206 6.2.3 Nonphysical Systems 209 6.2.4 Experimental Modeling 212 6.2.5 Stochastic Modeling 223 6.2.6 Heuristic Modeling 226 6.3 Paradigm for System Modeling, Analysis, and Evaluation 228 6.4 Summary 229 Bibliography 229 Problems 230 7 Analysis Methods for Systems with Linear Kernels 245 7.1 Background and Justification 245 7.2 Linearization Methods 247 7.2.1 Taylor Series Expansion 248 7.2.2 Perturbation Methods 251 7.2.3 Variable Coefficient Elimination 252 7.3 Single-Input Linear Systems 254 7.3.1 Single-Input, Single-Output Systems 254 7.3.2 Single-Input, Multiple-Output Linear Systems 258 7.4 Multiple-Input Linear Systems 265 7.4.1 Multiple-Input, Single-Output 266 7.4.2 Multiple-Input, Multiple-Output Continuous System Equations 270 7.5 Summary 272 Bibliography 273 Problems 274 8 Generalized System Analysis Methods 279 8.1 Simplification and Reduction of System Kernels 279 8.1.1 Conversion of Variable System Kernels to Constant Kernels 280 8.1.2 Reduction of System Kernels 282 8.2 System Normalization and Parameter Reduction 288 8.2.1 System Variable Normalization 288 8.2.2 Parameter Reduction and Minimization 292 8.2.3 Sensitivity Analysis of System Parameters 297 8.3 Systems with Feedback 300 8.3.1 System Kernel Feedback Gain 301 8.3.2 Effect of Feedback on Linear Kernels 304 8.3.3 Single-Input, Single-Output Systems with Feedback 306 8.3.4 Inversion of System Kernels with Feedback 308 8.4 Computer-Aided Analysis of Systems 310 8.5 Summary 313 Bibliography 313 Problems 314 9 System Science Applications 321 9.1 Classification of System Science by Topics 321 9.2 System Science Applications to Space, Time, Matter, and Energy in Physical Science 328 9.2.1 First Law of Thermodynamics 328 9.2.2 Particle Diffusion Model 331 9.2.3 Relativistic Mechanics Model 333 9.2.4 System Problems for Matter, Energy, Space, and Time 339 9.3 Earth Science Applications of System Science 352 9.3.1 Atmospheric Model 353 9.3.2 Geothermal Model 355 9.3.3 Terrestrial Water Balance Model 357 9.3.4 Topical System Applications in the Earth Sciences 360 9.4 Life Systems Applications of System Science 366 9.4.1 Continuous and Discrete Growth Models 366 9.4.2 The Mammalian Lung Model 367 9.4.3 Topical System Problems in Life Science 369 9.5 Applications of System Science to Human Life 381 9.5.1 Hemodynamic Circulatory System 381 9.5.2 Model for Medical Diagnosis Using Radioactive Nuclides 386 9.5.3 Quantitative Model for Stress 388 9.5.4 Topical System Problems Associated with Human Life 390 9.6 Applications of System Science to Human Society 401 9.6.1 World Cultural and Economic Regions 401 9.6.2 Solow Model for Economic Growth 403 9.6.3 Model for Cost of Crime to Society 406 9.6.4 Energy Consumption and GNP 413 9.6.5 Topical System Problems in Human Society 414 9.7 Applications of System Science to the Arts 423 9.7.1 Quantitative Assessment of Language 424 9.7.2 Art Awareness Model 427 9.7.3 Topical System Problems in the Arts 427 9.8 Applications of System Science to Technology 430 9.8.1 Nuclear Reactor Stability with Xenon-135 Dependence 431 9.8.2 Fluid Flow with Friction 441 9.8.3 Models for Forecasting Electrical Power Demand 443 9.8.4 Topical System Problems in Technology 445 9.9 Applications of System Science to Religion 450 9.9.1 Quality of Life and Belief in God Model 450 9.9.2 Models for the Great Religions 455 9.9.3 Topical System Problems in Religion 456 9.10 Applications of System Science to History 462 9.10.1 Expansion Model for Aggressive Societies 462 9.10.2 Historical Growth in Weapons Trade 465 9.10.3 Additional Modeling Problems 466 General System Science Bibliography 468 10 System Modeling Paradigms 475 10.1 Background 475 10.2 Modeling Paradigm 476 10.3 Essential System Modeling Paradigm Steps 477 10.3.1 Step-1 Explore and Document 477 10.3.2 Step-2 Define and Contain 481 10.3.3 Step-3 Select and Develop 481 10.3.4 Step-4 Construct and Quantify 482 10.3.5 Step-5 Analyze and Evaluate 482 10.3.6 Step-6 Assess and Re-Evaluate 482 10.3.7 Step-7 Finalize and Confirm 483 10.3.8 Step-8 Resolve and Accept 483 10.3.9 Step-9 Publish and Disseminate 483 10.4 Example of Analysis Process after System Identification using MATLAB 483 10.5 Final Words 486 Index 489

Read more less

Book SynopsisIdentifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability assessment methods, supported by the underpinning mathematics. DeveloTable of ContentsList of Contributors xv Foreword xix Preface xxi 1 Introduction: The Role of Wide Area Monitoring Systems in Dynamic Vulnerability Assessment 1 Jaime C. Cepeda and José Luis Rueda-Torres 1.1 Introduction 1 1.2 Power System Vulnerability 2 1.2.1 Vulnerability Assessment 2 1.2.2 Timescale of Power System Actions and Operations 4 1.3 Power System Vulnerability Symptoms 5 1.3.1 Rotor Angle Stability 6 1.3.2 Short-Term Voltage Stability 7 1.3.3 Short-Term Frequency Stability 7 1.3.4 Post-Contingency Overloads 7 1.4 Synchronized Phasor Measurement Technology 8 1.4.1 Phasor Representation of Sinusoids 8 1.4.2 Synchronized Phasors 9 1.4.3 Phasor Measurement Units (PMUs) 9 1.4.4 Discrete Fourier Transform and Phasor Calculation 10 1.4.5 Wide Area Monitoring Systems 10 1.4.6 WAMPAC Communication Time Delay 12 1.5 The Fundamental Role of WAMS in Dynamic Vulnerability Assessment 13 1.6 Concluding Remarks 16 2 Steady-state Security 21 Evelyn Heylen, Steven De Boeck, Marten Ovaere, Hakan Ergun, and Dirk Van Hertem 2.1 Power System Reliability Management: A Combination of Reliability Assessment and Reliability Control 22 2.1.1 Reliability Assessment 23 2.1.2 Reliability Control 24 2.2 Reliability Under Various Timeframes 31 2.3 Reliability Criteria 33 2.4 Reliability and Its Cost as a Function of Uncertainty 34 2.4.1 Reliability Costs 34 2.4.2 Interruption Costs 35 2.4.3 Minimizing the Sum of Reliability and Interruption Costs 36 3 Probabilistic Indicators for the Assessment of Reliability and Security of Future Power Systems 41 Bart W. Tuinema, Nikoleta Kandalepa, and José Luis Rueda-Torres 3.1 Introduction 41 3.2 Time Horizons in the Planning and Operation of Power Systems 42 3.2.1 Time Horizons 42 3.2.2 Overlapping and Interaction 42 3.2.3 Remedial Actions 42 3.3 Reliability Indicators 45 3.3.1 Security-of-Supply Related Indicators 45 3.3.2 Additional Indicators 47 3.4 Reliability Analysis 49 3.4.1 Input Information 49 3.4.2 Pre-calculations 50 3.4.3 Reliability Analysis 50 3.4.4 Output: Reliability Indicators 53 3.5 Application Example: EHV Underground Cables 53 3.5.1 Input Parameters 54 3.5.2 Results of Analysis 56 4 An Enhanced WAMS-based Power System Oscillation Analysis Approach 63 Qing Liu, Hassan Bevrani, and Yasunori Mitani 4.1 Introduction 63 4.2 HHT Method 65 4.2.1 EMD 65 4.2.2 Hilbert Transform 65 4.2.3 Hilbert Spectrum and Hilbert Marginal Spectrum 66 4.2.4 HHT Issues 67 4.3 The Enhanced HHT Method 71 4.3.1 Data Pre-treatment Processing 71 4.3.2 Inhibiting the Boundary End Effect 75 4.3.3 Parameter Identification 80 4.4 Enhanced HHT Method Evaluation 81 4.4.1 Case I 81 4.4.2 Case II 84 4.4.3 Case III 85 4.5 Application to RealWide Area Measurements 88 5 Pattern Recognition-Based Approach for Dynamic Vulnerability Status Prediction 95 Jaime C. Cepeda, José Luis Rueda-Torres, Delia G. Colomé, and István Erlich 5.1 Introduction 95 5.2 Post-contingency Dynamic Vulnerability Regions 96 5.3 Recognition of Post-contingency DVRs 97 5.3.1 N-1 Contingency Monte Carlo Simulation 98 5.3.2 Post-contingency Pattern Recognition Method 100 5.3.3 Definition of Data-TimeWindows 103 5.3.4 Identification of Post-contingency DVRs—Case Study 104 5.4 Real-Time Vulnerability Status Prediction 109 5.4.1 Support Vector Classifier (SVC) Training 112 5.4.2 SVC Real-Time Implementation 113 5.5 Concluding Remarks 115 6 Performance Indicator-Based Real-Time Vulnerability Assessment 119 Jaime C. Cepeda, José Luis Rueda-Torres, Delia G. Colomé, and István Erlich 6.1 Introduction 119 6.2 Overview of the Proposed Vulnerability Assessment Methodology 120 6.3 Real-Time Area Coherency Identification 122 6.3.1 Associated PMU Coherent Areas 122 6.4 TVFS Vulnerability Performance Indicators 125 6.4.1 Transient Stability Index (TSI) 125 6.4.2 Voltage Deviation Index (VDI) 128 6.4.3 Frequency Deviation Index (FDI) 131 6.4.4 Assessment of TVFS Security Level for the Illustrative Examples 131 6.4.5 Complete TVFS Real-Time Vulnerability Assessment 133 6.5 Slower Phenomena Vulnerability Performance Indicators 137 6.5.1 Oscillatory Index (OSI) 137 6.5.2 Overload Index (OVI) 141 6.6 Concluding Remarks 145 7 Challenges Ahead Risk-Based AC Optimal Power Flow Under Uncertainty for Smart Sustainable Power Systems 149 Florin Capitanescu 7.1 Chapter Overview 149 7.2 Conventional (Deterministic) AC Optimal Power Flow (OPF) 150 7.2.1 Introduction 150 7.2.2 Abstract Mathematical Formulation of the OPF Problem 150 7.2.3 OPF Solution via Interior-Point Method 151 7.2.4 Illustrative Example 154 7.3 Risk-Based OPF 158 7.3.1 Motivation and Principle 158 7.3.2 Risk-Based OPF Problem Formulation 159 7.3.3 Illustrative Example 160 7.4 OPF Under Uncertainty 162 7.4.1 Motivation and Potential Approaches 162 7.4.2 Robust Optimization Framework 162 7.4.3 Methodology for Solving the R-OPF Problem 163 7.4.4 Illustrative Example 164 7.5 Advanced Issues and Outlook 169 7.5.1 Conventional OPF 169 7.5.2 Beyond the Scope of Conventional OPF: Risk, Uncertainty, Smarter Sustainable Grid 172 8 Modeling Preventive and Corrective Actions Using Linear Formulation 177 Tom Van Acker and Dirk Van Hertem 8.1 Introduction 177 8.2 Security Constrained OPF 178 8.3 Available Control Actions in AC Power Systems 178 8.3.1 Generator Redispatch 179 8.3.2 Load Shedding and Demand Side Management 179 8.3.3 Phase Shifting Transformer 179 8.3.4 Switching Actions 180 8.3.5 Reactive Power Management 180 8.3.6 Special Protection Schemes 180 8.4 Linear Implementation of Control Actions in a SCOPF Environment 180 8.4.1 Generator Redispatch 181 8.4.2 Load Shedding and Demand Side Management 182 8.4.3 Phase Shifting Transformer 183 8.4.4 Switching 184 8.5 Case Study of Preventive and Corrective Actions 185 8.5.1 Case Study 1: Generator Redispatch and Load Shedding (CS1) 186 8.5.2 Case Study 2: Generator Redispatch, Load Shedding and PST (CS2) 187 8.5.3 Case Study 3: Generator Redispatch, Load Shedding and Switching (CS3) 190 9 Model-based Predictive Control for Damping Electromechanical Oscillations in Power Systems 193 DaWang 9.1 Introduction 193 9.2 MPC BasicTheory & Damping Controller Models 194 9.2.1 What is MPC? 194 9.2.2 Damping Controller Models 196 9.3 MPC for Damping Oscillations 198 9.3.1 Outline of Idea 198 9.3.2 Mathematical Formulation 199 9.3.3 Proposed Control Schemes 200 9.4 Test System & Simulation Setting 204 9.5 Performance Analysis of MPC Schemes 204 9.5.1 Centralized MPC 204 9.5.2 Distributed MPC 209 9.5.3 Hierarchical MPC 209 9.6 Conclusions and Discussions 213 10 Voltage Stability Enhancement by Computational Intelligence Methods 217 Worawat Nakawiro 10.1 Introduction 217 10.2 Theoretical Background 218 10.2.1 Voltage Stability Assessment 218 10.2.2 Sensitivity Analysis 219 10.2.3 Optimal Power Flow 220 10.2.4 Artificial Neural Network 220 10.2.5 Ant Colony Optimisation 221 10.3 Test Power System 223 10.4 Example 1: Preventive Measure 224 10.4.1 Problem Statement 224 10.4.2 Simulation Results 225 10.5 Example 2: Corrective Measure 226 10.5.1 Problem Statement 226 10.5.2 Simulation Results 227 11 Knowledge-Based Primary and Optimization-Based Secondary Control of Multi-terminal HVDCGrids 233 Adedotun J. Agbemuko, Mario Ndreko, Marjan Popov, José Luis Rueda-Torres, and Mart A.M.M van der Meijden 11.1 Introduction 234 11.2 Conventional Control Schemes in HV-MTDC Grids 234 11.3 Principles of Fuzzy-Based Control 236 11.4 Implementation of the Knowledge-Based Power-Voltage Droop Control Strategy 236 11.4.1 Control Scheme for Primary and Secondary Power-Voltage Control 237 11.4.2 Input/Output Variables 238 11.4.3 Knowledge Base and Inference Engine 241 11.4.4 Defuzzification and Output 241 11.5 Optimization-Based Secondary Control Strategy 242 11.5.1 Fitness Function 242 11.5.2 Constraints 244 11.6 Simulation Results 245 11.6.1 Set Point Change 245 11.6.2 Constantly Changing Reference Set Points 246 11.6.3 Sudden Disconnection ofWind Farm for Undefined Period 246 11.6.4 Permanent Outage of VSC 3 247 12 Model Based Voltage/Reactive Control in Sustainable Distribution Systems 251 Hoan Van Pham and Sultan Nasiruddin Ahmed 12.1 Introduction 251 12.2 BackgroundTheory 252 12.2.1 Voltage Control 252 12.2.2 Model Predictive Control 253 12.2.3 Model Analysis 255 12.2.4 Implementation 257 12.3 MPC Based Voltage/Reactive Controller – an Example 258 12.3.1 Control Scheme 258 12.3.2 Overall Objective Function of the MPC Based Controller 259 12.3.3 Implementation of the MPC Based Controller 261 12.4 Test Results 262 12.4.1 Test System and Measurement Deployment 262 12.4.2 Parameter Setup and Algorithm Selection for the Controller 263 12.4.3 Results and Discussion 263 12.5 Conclusions 266 13 Multi-Agent based Approach for Intelligent Control of Reactive Power Injection in Transmission Systems 269 Hoan Van Pham and Sultan Nasiruddin Ahmed 13.1 Introduction 269 13.2 System Model and Problem Formulation 270 13.3 Multi-Agent Based Approach 275 13.3.1 Augmented Lagrange Formulation 275 13.3.2 Implementation Algorithm 275 13.4 Case Studies and Simulation Results 277 13.4.1 Case Studies 277 13.4.2 Simulation Results 277 14 Operation of Distribution SystemsWithin Secure Limits Using Real-Time Model Predictive Control 283 Hamid Soleimani Bidgoli, Gustavo Valverde, Petros Aristidou, Mevludin Glavic, and Thierry Van Cutsem 14.1 Introduction 283 14.2 Basic MPC Principles 285 14.3 Control Problem Formulation 285 14.4 Voltage CorrectionWith Minimum Control Effort 288 14.4.1 Inclusion of LTC Actions as Known Disturbances 289 14.4.2 Problem Formulation 290 14.5 Correction of Voltages and Congestion Management with Minimum Deviation from References 291 14.5.4 Problem Formulation 295 14.6 Test System 296 14.7 Simulation Results: Voltage Correction with Minimal Control Effort 298 14.8 Simulation Results: Voltage and/or Congestion Corrections with Minimum Deviation from Reference 302 15 Enhancement of Transmission System Voltage Stability through Local Control of Distribution Networks 311 Gustavo Valverde, Petros Aristidou, and Thierry Van Cutsem 15.1 Introduction 311 15.2 Long-Term Voltage Stability 313 15.2.1 Countermeasures 314 15.3 Impact of Volt-VAR Control on Long-Term Voltage Stability 316 15.3.1 Countermeasures 318 15.4 Test System Description 319 15.4.1 Test System 319 15.4.2 VVC Algorithm 321 15.4.3 Emergency Detection 322 15.5 Case Studies and Simulation Results 323 15.5.1 Results in Stable Scenarios 323 15.5.2 Results in Unstable Scenarios 326 15.5.3 Results with Emergency Support From Distribution 328 16 Electric Power Network Splitting Considering Frequency Dynamics and Transmission Overloading Constraints 337 Nelson Granda and Delia G. Colomé 16.1 Introduction 337 16.1.1 Stage One: Vulnerability Assessment 337 16.1.2 Stage Two: Islanding Process 338 16.2 Network Splitting Mechanism 340 16.2.1 Graph Modeling, Update, and Reduction 341 16.2.2 Graph Partitioning Procedure 342 16.2.3 Load Shedding/Generation Tripping Schemes 343 16.2.4 Tie-Lines Determination 344 16.3 Power Imbalance Constraint Limits 344 16.3.1 Reduced Frequency ResponseModel 345 16.3.2 Power Imbalance Constraint Limits Determination 347 16.4 Overload Assessment and Control 348 16.5 Test Results 349 16.5.1 Power System Collapse 349 16.5.2 Application of Proposed Methodology 351 16.5.3 Performance of Proposed ACIS 354 16.6 Conclusions and Recommendations 356 17 High-Speed Transmission Line Protection Based on Empirical Orthogonal Functions 361 Rommel P. Aguilar and Fabián E. Pérez-Yauli 17.1 Introduction 361 17.2 Empirical Orthogonal Functions 363 17.2.1 Formulation 363 17.3 Applications of EOFs for Transmission Line Protection 365 17.3.1 Fault Direction 366 17.3.2 Fault Classification 367 17.3.3 Fault Location 369 17.4 Study Case 369 17.4.1 Transmission Line Model and Simulation 369 17.4.2 The Power System and Transmission Line 370 17.4.3 Training Data 370 17.4.4 Training Data Matrix 370 17.4.5 Signal Conditioning 373 17.4.6 Energy Patterns 373 17.4.7 EOF Analysis 376 17.4.8 Evaluation of the Protection Scheme 379 17.4.9 Fault Classification 380 17.4.10 Fault Location 382 17.5 Conclusions 383 Study Cases:WECC 9-bus, ATPDrawModels and Parameters 384 18 Implementation of a Real Phasor Based Vulnerability Assessment and Control Scheme: The Ecuadorian WAMPAC System 389 Pablo X. Verdugo, Jaime C. Cepeda, Aharon B. De La Torre, and Diego E. Echeverría 18.1 Introduction 389 18.2 PMU Location in the Ecuadorian SNI 390 18.3 Steady-State Angle Stability 391 18.4 Steady-State Voltage Stability 395 18.5 Oscillatory Stability 398 18.5.1 Power System Stabilizer Tuning 402 18.6 Ecuadorian Special Protection Scheme (SPS) 407 18.6.1 SPS Operation Analysis 409 18.7 Concluding Remarks 410 Index 413

Read more less

Book SynopsisPresents a comprehensive overview and analysis of the recent developments in signal processing for Chipless Radio Frequency Identification Systems This book presents the recent research results on Radio Frequency Identification (RFID) and provides smart signal processing methods for detection, signal integrity, multiple-access and localization, tracking, and collision avoidance in Chipless RFID systems. The book is divided into two sections: The first section discusses techniques for detection and denoising in Chipless RFID systems. These techniques include signal space representation, detection of frequency signatures using UWB impulse radio interrogation, time domain analysis, singularity expansion method for data extraction, and noise reduction and filtering techniques. The second section covers collision and error correction protocols, multi-tag identification through time-frequency analysis, FMCW radar based collision detection and multi-access for Chipless RFID tags as we as locaTable of ContentsPREFACE xi 1 INTRODUCTION 1 1.1 Chipless RFID 1 1.2 Chipless RFID Tag Reader 7 1.3 Conclusion 12 References 13 2 Signal Space Representation of Chipless RFID Signatures 15 2.1 Wireless Communication Systems and Chipless RFID Systems 15 2.1.1 The Conventional Digital Wireless Communication System 15 2.1.2 Chipped RFID System 16 2.1.3 Chipless RFID System 17 2.2 The Geometric Representation of Signals in a Signal Space 18 2.2.1 Representing Transmit Signals Using Orthonormal Basis Functions 18 2.2.2 Receiving Signals and Decoding Information 20 2.3 Novel Model for the Representation of Chipless RFID Signatures 22 2.3.1 Signal Space Representation of Frequency Signatures 24 2.3.2 Application of New Model 27 2.4 Performance Analysis 32 2.5 Experimental Results Using the Complete Tag 34 2.6 Conclusion 36 References 38 3 Time-Domain Analysis of Frequency Signature-Based Chipless RFID 39 3.1 Limitations of Current Continuous-Wave Swept Frequency Interrogation and Reading Methods for Chipless RFID 39 3.2 UWB-IR Interrogation of Time-Domain Reflectometry-Based Chipless RFID 43 3.3 Time-Domain Analysis of Frequency Signature-Based Chipless RFID 47 3.4 Analysis of Backscatter from a Multiresonator Loaded Chipless Tag 47 3.4.1 System Description and Mathematical Model for Backscatter Analysis 49 3.4.2 Chipless RFID Tag Design 53 3.5 Simulation Results 55 3.6 Processing Results 56 3.7 Analysis of Backscatter from a Multipatch-Based Chipless Tag 59 3.7.1 System Model and Expressions for Backscatter 59 3.7.2 The Design and Operation of the Multipatch-Based Chipless RFID 61 3.8 Electromagnetic Simulation of System 62 3.8.1 Four-Patch Backscattering Chipless Tag 62 3.8.2 Investigation into Reading Distance and Orientation of Tag 66 3.8.3 Measurement Results 67 3.9 Conclusion 68 References 70 4 Singularity Expansion Method for Data Extraction for Chipless RFID 71 4.1 Introduction 71 4.2 The SEM 72 4.2.1 The Complex Frequency Domain 74 4.2.2 Extraction of Poles and Residues 77 4.2.3 Matrix Pencil Algorithm 77 4.2.4 Case Study 81 4.3 Application of SEM for Chipless RFID 84 4.4 Conclusion 89 References 91 5 Denoising and Filtering Techniques for Chipless RFID 93 5.1 Introduction 93 5.2 Matrix Pencil Algorithm]Based Filtering 95 5.3 Noise Suppression Through Signal Space Representation 99 5.4 SSI 103 5.5 Wavelet-Based Filtering of Noise 107 5.6 Conclusion 108 References 109 6 Collision and Error Correction Protoco ls in Chipless RFID 111 6.1 Introduction 111 6.2 RFID System and Collision 113 6.2.1 Reader–Reader Collision 114 6.2.2 Reader–Tag Collision 114 6.2.3 Tag–Tag Collision 115 6.3 Applications that Involve Multiple Tags 115 6.4 Anticollision Algorithm in Chipped RFID Tags 118 6.4.1 SDMA 119 6.4.2 FDMA 122 6.4.3 CDMA 123 6.4.4 Time Division Multiple Access: TDMA 125 6.5 Anticollision Algorithm for Chipless RFID 128 6.5.1 Linear Block Coding 129 6.5.2 Correlative Signal Processing-Based Approach 131 6.5.3 Walsh-Domain Matched Filtering 131 6.5.4 Spatial Focusing (SDMA) 132 6.5.5 Other Anticollision/Multi-Access Methods 134 6.6 Collision Detection and Multiple Access for Chipless RFID System 135 6.7 Introducing Block Coding in Chipless RFID 138 6.7.1 Coding 139 6.7.2 Block Coding for Collision Detection 141 6.7.3 Block Coding for Improving Data Integrity 144 6.7.4 Advantages and Challenges of Block Coding 146 6.8 Conclusion 148 References 148 7 Multi-Tag Identification Through Time–Frequency Analysis 153 7.1 Introduction 153 7.2 t–f Analysis and Chipless RFID Systems 154 7.3 FrFT: Background Theory 157 7.3.1 Linear Frequency Modulated Signal 157 7.3.2 FrFT 161 7.4 System Description 167 7.4.1 ADS Simulation Environment 170 7.4.2 Postprocessing in MATLAB 171 7.5 Results and Discussion 174 7.6 Conclusion 180 References 180 8 FMCW RADAR-Based Multi-Tag Identification 183 8.1 Introduction 183 8.2 Background Theory 186 8.2.1 Overview of FMCW RADAR 186 8.2.2 FMCW RADAR Technique for Chipless RFID Systems: Multi-Tag Identification 189 8.3 System Description 196 8.3.1 ADS Simulation Environment 196 8.3.2 Postprocessing in MATLAB 199 8.4 Results and Discussion 201 8.4.1 Collision Detection and Range Extraction 202 8.4.2 Tag Identification 206 8.5 Conclusion 212 References 213 9 Chipless Tag Localization 215 9.1 Introduction 215 9.2 Significance of Localization 216 9.3 Tag localization: Chipless Versus Conventional RFID 217 9.4 Conventional RFID Tag Localization Techniques 218 9.4.1 RTOF Estimation 218 9.4.2 RSS-Based Localization 220 9.4.3 Phase Evaluation Method 220 9.5 Chipless RFID Tag Localization 221 9.6 Benefits of Chipless Tag Localization 222 9.7 Proposed Localization for Chipless RFID Tags 223 9.7.1 Backscattered Signal from Chipless Tag 223 9.7.2 Maximum Detection Range 225 9.7.3 Localization of Tag 228 9.7.4 Ranging of Tag 230 9.7.5 Positioning of Tag 231 9.8 Results and Discussion 233 9.8.1 Simulation Environment 233 9.8.2 Experimental Setup 234 9.8.3 Results and Discussion 236 9.8.4 Unknown Tag Localization 240 9.9 Conclusion 241 References 242 10 State-of-the-Art Chipless RFID Reader 247 10.1 Introduction 247 10.2 Challenges in Mass Deployment 249 10.3 Smart RFID Reader 252 10.3.1 Physical Layer (Front End) 253 10.3.2 IT Layer (Back End) 255 10.4 Various Smart Readers 261 10.5 Conclusion 263 References 264 Index 265

Read more less

Book SynopsisExamines new cooperative control methodologies tailored to real-world applications in various domains such as in communication systems, physics systems, and multi-robotic systems Provides the fundamental mechanism for solving collective behaviors in naturally-occurring systems as well as cooperative behaviors in man-made systems Discusses cooperative control methodologies using real-world applications, including semi-conductor laser arrays, mobile sensor networks, and multi-robotic systems Includes results from the research group at the Stevens Institute of Technology to show how advanced control technologies can impact challenging issues, such as high energy systems and oil spill monitoring Table of ContentsPreface xii About the Companion Website xiv 1 Introduction 1 1.1 Motivation and Challenges 1 1.1.1 From Collective Behaviors to Cooperative Control 1 1.1.2 Challenges 2 1.2 Background and Related Work 4 1.2.1 Networked Communication Systems 4 1.2.2 Cooperating Autonomous Mobile Robots 5 1.2.3 Nanoscale Systems and Laser Synchronization 7 1.3 Overview of the Book 9 References 12 2 Distributed Consensus and Consensus Filters 19 2.1 Introduction and Literature Review 19 2.2 Preliminaries on Graph Theory 22 2.3 Distributed Consensus 26 2.3.1 The Continuous-Time Consensus Protocol 26 2.3.2 The Discrete-Time Consensus Protocol 28 2.4 Distributed Consensus Filter 29 2.4.1 PI Average Consensus Filter: Continuous-Time 30 2.4.2 PI Average Consensus Filter: Discrete-Time 30 References 31 Part I Distributed Consensus for Networked Communication Systems 37 3 Average Consensus for Quantized Communication 39 3.1 Introduction 39 3.2 Problem Formulation 41 3.2.1 Average Consensus Protocol with Quantization 41 3.2.2 Problem Statement 42 3.3 Weighting Matrix Design for Average Consensus with Quantization 42 3.3.1 State Transformation 43 3.3.2 Design for Fixed and Directed Graphs 44 3.3.3 Design for Switching and Directed Graphs 52 3.4 Simulations and Performance Evaluation 54 3.4.1 Fixed and Directed Graphs 54 3.4.2 Switching and Directed Graphs 55 3.4.3 Fixed and Directed Graphs 56 3.4.4 Performance Comparison 57 3.5 Conclusion 61 Notes 61 References 62 4 Weighted Average Consensus for Cooperative Spectrum Sensing 64 4.1 Introduction 64 4.2 Problem Statement 67 4.3 Cooperative Spectrum Sensing Using Weighted Average Consensus 71 4.3.1 Weighted Average Consensus Algorithm 71 4.3.2 Fusion Convergence Performance in Terms of Detection Probability 72 4.3.3 Optimal Weight Design under AWGN Measurement Channels 73 4.3.4 Heuristic Weight Design under Rayleigh Fading Channels 75 4.4 Convergence Analysis 76 4.4.1 Fixed Communication Channels 76 4.4.2 Dynamic Communication Channels 79 4.4.3 Convergence Rate with Random Link Failures 83 4.5 Simulations and Performance Evaluation 87 4.5.1 SU Network Setup 87 4.5.2 Convergence of Weighted Average Consensus 88 4.5.3 Metrics and Methodologies 90 4.5.4 Performance Evaluation 91 4.6 Conclusion 97 Notes 97 References 97 5 Distributed Consensus Filter for Radio Environment Mapping 101 5.1 Introduction 101 5.2 Problem Formulation 103 5.2.1 System Configuration and Distributed Sensor Placement 103 5.2.2 The Model and Problem Statement 105 5.3 Distributed REM Tracking 106 5.3.1 System Matrix Estimation 107 5.3.2 Kalman–EM Filter 108 5.3.3 PI Consensus Filter for Distributed Estimation and Tracking 109 5.4 Communication and Computation Complexity 110 5.4.1 Communication Complexity 112 5.4.2 Computation Complexity 112 5.5 Simulations and Performance Evaluation 113 5.5.1 Dynamic Radio Transmitter 113 5.5.2 Stationary Radio Transmitter 116 5.5.3 Comparison with Existing Centralized Methods 116 5.6 Conclusion 118 Notes 119 References 119 Part II Distributed Cooperative Control for Multirobotic Systems 123 6 Distributed Source Seeking by Cooperative Robots 125 6.1 Introduction 125 6.2 Problem Formulation 126 6.3 Source Seeking with All-to-All Communications 127 6.3.1 Cooperative Estimation of Gradients 127 6.3.2 Control Law Design 128 6.4 Distributed Source Seeking with Limited Communications 133 6.5 Simulations 135 6.6 Experimental Validation 138 6.6.1 The Robot 138 6.6.2 The Experiment Setup 140 6.6.3 Experimental Results 141 6.7 Conclusion 144 Notes 144 References 144 7 Distributed Plume Front Tracking by Cooperative Robots 146 7.1 Introduction 146 7.2 Problem Statement 148 7.3 Plume Front Estimation and Tracking by Single Robot 150 7.3.1 State Equation of the Plume Front Dynamics 151 7.3.2 Measurement Equation and Observer Design 152 7.3.3 Estimation-Based Tracking Control 153 7.3.4 Convergence Analysis 155 7.4 Multirobot Cooperative Tracking of Plume Front 156 7.4.1 Boundary Robots 157 7.4.2 Follower Robots 157 7.4.3 Convergence Analysis 158 7.5 Simulations 160 7.5.1 Simulation Environment 160 7.5.2 Single-Robot Plume Front Tracking 161 7.5.3 Multirobot Cooperative Plume Front Tracking 161 7.6 Conclusion 164 Notes 165 References 165 Part III Distributed Cooperative Control for Multiagent Physics Systems 167 8 Friction Control of Nano-particle Array 169 8.1 Introduction 169 8.2 The Frenkel–Kontorova Model 170 8.3 Open-Loop Stability Analysis 172 8.3.1 Linear Particle Interactions 172 8.3.2 Nonlinear Particle Interactions 176 8.4 Control Problem Formulation 177 8.5 Tracking Control Design 178 8.5.1 Tracking Control of the Average System 178 8.5.2 Stability of Single Particles in the Closed-Loop System 181 8.6 Simulation Results 186 8.7 Conclusion 191 Notes 194 References 195 9 Synchronizing Coupled Semiconductor Lasers 197 9.1 Introduction 197 9.2 The Model of Coupled Semiconductor Lasers 198 9.3 Stability Properties of Decoupled Semiconductor Laser 200 9.4 Synchronization of Coupled Semiconductor Lasers 203 9.5 Simulation Examples 207 9.6 Conclusion 209 Notes 209 References 210 Appendix A Notation and Symbols 212 Appendix B Kronecker Product and Properties 213 Appendix C Quantization Schemes 214 Appendix D Finite L2 Gain 215 Appendix E Radio Signal Propagation Model 216 Index 218

Read more less

Book SynopsisProvides the foundations and principles needed for addressing the various challenges of developing smart cities Smart cities are emerging as a priority for research and development across the world. They open up significant opportunities in several areas, such as economic growth, health, wellness, energy efficiency, and transportation, to promote the sustainable development of cities. This book provides the basics of smart cities, and it examines the possible future trends of this technology. Smart Cities: Foundations, Principles, and Applications provides a systems science perspective in presenting the foundations and principles that span multiple disciplines for the development of smart cities. Divided into three partsfoundations, principles, and applicationsSmart Cities addresses the various challenges and opportunities of creating smart cities and all that they have to offer. It also covers smart city theory modeling and simulation, and examineTable of ContentsEditors Biographies xxiii List of Contributors xxvii Foreword xxxiii Preface xxxv Acknowledgments xxxvii 1 Cyber–Physical Systems in Smart Cities – Mastering Technological, Economic, and Social Challenges 1Martina Fromhold-Eisebith2 Big Data Analytics Processes and Platforms Facilitating Smart Cities 23Pethuru Raj and Sathish A. P. Kumar 3 Multi-Scale Computing for a Sustainable Built Environment 53Massimiliano Manfren 4 Autonomous Radios and Open Spectrum in Smart Cities 99Corey D. Cooke and Adam L. Anderson 5 Mobile Crowd-Sensing for Smart Cities 125Chandreyee Chowdhury and Sarbani Roy 6 Wide-Area Monitoring and Control of Smart Energy Cyber-Physical Systems (CPS) 155Nilanjan R. Chaudhuri 7 Smart Technologies and Vehicle-to-X (V2X) Infrastructures for Smart Mobility Cities 181Bernard Fong, Lixin Situ, and Alvis C.M. Fong 8 Smart Ecology of Cities: Integrating Development Impacts on Ecosystem Services for Land Parcels 209Marc Morrison, Ravi S. Srinivasan, and Cynnamon Dobbs 9 Data-Driven Modeling, Control, and Tools for Smart Cities 243Madhur Behl and Rahul Mangharam 10 Bringing Named Data Networks into Smart Cities 275Syed Hassan Ahmed, Safdar Hussain Bouk, Dongkyun Kim, and Mahasweta Sarkar 11 Human Context Sensing in Smart Cities 311Juhi Ranjan, Erin Griffiths, and Kamin Whitehouse 12 Smart Cities and the Symbiotic Relationship between Smart Governance and Citizen Engagement 343Tori Okner and Russell Preston 13 Smart Economic Development 373Madhavi Venkatesan 14 Managing the Cyber Security Life-Cycle of Smart Cities 391Mridul S. Barik, Anirban Sengupta, and Chandan Mazumdar 15 Mobility as a Service 409Christopher Expósito-Izquierdo, AiramExpósito-Márquez, and Julio Brito-Santana 16 Clustering and Fuzzy Reasoning as Data Mining Methods for the Development of Retrofit Strategies for Building Stocks 437Philipp Geyer and Arno Schlueter 17 A Framework to Achieve Large Scale Energy Savings for Building Stocks through Targeted Occupancy Interventions 473Aslihan Karatas, Allisandra Stoiko, and Carol C. Menassa 18 Sustainability in Smart Cities: Balancing Social, Economic, Environmental, and Institutional Aspects of Urban Life 503Ali Komeily and Ravi Srinivasan 19 Toward Resilience of the Electric Grid 535JiankangWang 20 Smart Energy and Grid: Novel Approaches for the Efficient Generation, Storage, and Usage of Energy in the Smart Home and the SmartGrid Linkup 575Julian Praß, JohannesWeber, Sebastian Staub, Johannes Bürner, Ralf Böhm, Thomas Braun, Moritz Hein, MarkusMichl,Michael Beck, and Jörg Franke 21 Building Cyber-Physical Systems – A Smart Building Use Case 605Jupiter Bakakeu, Franziska Schäfer, Jochen Bauer, MarkusMichl, and Jörg Franke 22 Climate Resilience and the Design of Smart Buildings 641Saranya Gunasingh, NoraWang, Doug Ahl, and Scott Schuetter 23 Smart Audio Sensing-Based HVAC Monitoring 669Shahriar Nirjon, Ravi Srinivasan, and Tamim Sookoor 24 Smart Lighting 697Jie Lian 25 Large Scale Air-Quality Monitoring in Smart and Sustainable Cities 725Xiaofan Jiang 26 The Smart City Production System 755Gary Graham, Jag Srai, Patrick Hennelly, and RoyMeriton 27 Smart Health Monitoring Using Smart Systems 773Carl Chalmers 28 Significance of Automated Driving in Japan 793Sadayuki Tsugawa 29 Environmental-Assisted Vehicular Data in Smart Cities 819Wei Chang, Huanyang Zheng, JieWu, Chiu C. Tan, and Haibin Ling Index 845

Read more less

Book SynopsisIntroduces advanced high-capacity data encoding and throughput improvement techniques for fully printable multi-bit Chipless RFID tags and reader systems The book proposes new approaches to chipless RFID tag encoding and tag detection that supersede their predecessors in signal processing, tag design, and reader architectures. The text is divided into two main sections: the first section introduces the fundamentals of electromagnetic (EM) imaging at mm-wave band to enhance the content capacity of Chipless RFID systems. The EM Imaging through Synthetic Aperture Radar (SAR) technique is used for data extraction. The second section presents a few smart tag detection techniques for existing chipless RFID systems. A Multiple-Input and Multiple-Output (MIMO) based tag detection technique improves the spectral efficiency and increases data bit capacity. The book concludes with a discussion of how the MIMO approach can be combined with the image based technique to introduce a Table of ContentsPreface xiAcknowledgment xvPART I EM IMAGE-BASED CHIPLESS RFID SYSTEM 11 Introduction 31.1 Barcodes as Identification Technology 41.2 RFID Systems 61.3 Barcodes Versus RFID 71.4 Chipless RFID Tag for Low-Cost Item Tagging 71.5 Chipless RFID Systems 101.6 Spatial-Based Chipless RFID System 161.7 Book Outline 17References 202 EM Imaging 252.1 EM-Imaging Fundamentals 252.2 Range Resolution 272.3 Cross-Range or Azimuth Resolution 292.4 Synthetic Aperture Radar (SAR) Necessity 312.5 EM Imaging for Content Coding 342.6 Conclusions 35References 363 Tiny Polarizers Secret of the New Technique 373.1 Introduction 373.2 Sweetness of Diffraction 393.3 Strip-Line Polarizer 433.4 Meander-Line Polarizer 453.5 Multiple Polarizers 473.6 Polarizer Fabrication 503.7 Conclusions 52References 534 Attributes of EM Polarizers 554.1 Introduction 554.2 Suggested Structures as Effective EM Polarizers 564.3 Cross-Polar Working Basis 594.4 Effect of Highly Reflective Items 644.5 Secure Identification 684.6 Bending Effect on Tag Performance 714.7 Conclusion 74References 765 System Technical Aspects 775.1 Introduction 775.2 The mm-Band of 60 GHz 775.3 Reader Antenna 815.4 Conclusions 106References 1076 SAR-Based Signal Processing 1116.1 Introduction 1116.2 SAR Modes of Operation 1126.3 SAR Block Diagram 1136.4 SAR-Based Signal Processing 1136.5 Tag Imaging Results 1166.6 System Downsides 1256.7 Conclusions 128References 1297 Fast Imaging Through MIMO-SAR 1317.1 Introduction 1317.2 Conventional Phased Array Antenna 1327.3 MIMO-SAR Systems 1337.4 Optimization 1437.5 MIMO-SAR Results 1557.6 Conclusion 158References 159PART II ADVANCED TAG DETECTION TECHNIQUES FOR CHIPLESS RFID SYSTEMS 1618 Introduction 1638.1 RFID Systems 1638.2 Review of Chipless RFID Tag Detection Techniques 1678.3 Maximum Likelihood Detection Techniques 1688.4 Conclusions 170References 1709 Chipless RFID Tag Design 1779.1 Introduction 1779.2 SISO Tag Design 1779.3 MIMO Tag Design 1799.4 Conclusions 188References 18810 ML Detection Techniques for SISO Chipless RFID Tags 18910.1 Introduction 18910.2 System Models–Time Domain 19010.3 System Models–Frequency Domain 20010.4 Simulations 20510.5 Experimental Setup 20710.6 Results 20810.7 Conclusion 230References 23011 Computationally Feasible Tag Detection Techniques 23311.1 Introduction 23311.2 Bit-By-Bit Detection Method 23411.3 Trellis-Tree-Based Viterbi Decoding 23711.4 Simulation Setup 24211.5 Results 24411.6 Conclusions 246References 24612 Signal Processing for MIMO-Based Chipless RFID Systems 24712.1 Introduction 24712.2 MIMO Decomposing Techniques 24912.3 Tag Detection in MIMO 25112.4 Experimental Setup 25312.5 Simulations 25412.6 Results 25812.7 Conclusion 268Reference 26813 Conclusion for Part II 26913.1 Summary of The Proposed Techniques in Part II 26913.2 Limitations of The Proposed System 27113.3 Potential Applications 27213.4 Future Work and Open Issues 273Reference 274Index 275

Read more less

Book SynopsisApplies lean manufacturing principles across the cloud service delivery chain to enable application and infrastructure service providers to sustainably achieve the shortest lead time, best quality, and value Applies lean thinking across the cloud service delivery chain to recognize and minimize wasteLeverages lessons learned from electric power industry operations to operations of cloud infrastructureApplies insights from just-in-time inventory management to operation of cloud based applicationsExplains how traditional, Information Technology Infrastructure Library (ITIL) and Enhanced Telecom Operation Map (eTOM) capacity management evolves to lean computing for the cloud Table of ContentsIntroduction xi Acknowledgments xv Abbreviations xvii 1. Basics 1 1.1 Cloud Computing Fundamentals 1 1.2 Roles in Cloud Computing 6 1.3 Applications 9 1.3.1 Application Service Quality 11 1.4 Demand, Supply, Capacity, and Fungibility 13 1.5 Demand Variability 16 1.6 Chapter Review 18 2. Rethinking Capacity Management 19 2.1 Capacity Management 19 2.2 Demand Management 21 2.3 Performance Management 21 2.4 Canonical Capacity Management 23 2.4.1 Traditional Capacity Management 24 2.4.2 ITIL Capacity Management 27 2.4.3 eTOM Capacity Management 28 2.4.4 Discussion 30 2.5 Three Cloud Capacity Management Problems 30 2.5.1 Physical Resource Capacity Management 31 2.5.2 Virtual Resource Capacity Management 32 2.5.3 Application Capacity Management 33 2.6 Cloud Capacity Management as a Value Chain 36 2.7 Chapter Review 39 3. Lean Thinking on Cloud Capacity Management 41 3.1 Lean Thinking Overview 41 3.2 Goal 42 3.3 Seeing Waste (Nonvalue-Adding Activities) 43 3.3.1 Reserve Capacity 45 3.3.2 Excess Application Capacity 46 3.3.3 Excess Online Infrastructure Capacity 46 3.3.4 Excess Physical Infrastructure Capacity 46 3.3.5 Inadequate Capacity 47 3.3.6 Infrastructure Overhead 48 3.3.7 Capacity Management Overhead 48 3.3.8 Resource Overhead 49 3.3.9 Power Management Overhead 50 3.3.10 Workload Migration 50 3.3.11 Complexity Overhead 51 3.3.12 Resource Allocation Failure 51 3.3.13 Leaking and Lost Resources 53 3.3.14 Waste Heat 53 3.3.15 Carbon Footprint 54 3.4 Key Principles 54 3.4.1 Move toward Flow 55 3.4.2 Pull versus Push 55 3.4.3 Level the Workload 55 3.4.4 Stop and Fix Problems 55 3.4.5 Master Practices 56 3.4.6 Visual Management 57 3.4.7 Use Well-Tested Technology 57 3.4.8 Take a Long-Term Perspective 58 3.4.9 Grow, Learn, and Teach Others 58 3.4.10 Develop Exceptional People 58 3.4.11 Partners Help Each Other Improve 58 3.4.12 Go See 59 3.4.13 Implement Rapidly 59 3.4.14 Become a Learning Organization 59 3.5 Pillar: Respect 59 3.6 Pillar: Continuous Improvement 61 3.7 Foundation 62 3.8 Cadence 62 3.9 Lean Capacity Management Philosophy 63 3.10 Chapter Review 64 4. Lean Cloud Capacity Management Strategy 67 4.1 Lean Application Service Provider Strategy 68 4.1.1 User Workload Placement 71 4.1.2 Application Performance Management 73 4.2 Lean Infrastructure Service Provider Strategies 73 4.2.1 Physical Resource Capacity Management 76 4.3 Full Stream Optimization 77 4.4 Chapter Review 79 5. Electric Power Generation as Cloud Infrastructure Analog 81 5.1 Power Generation as a Cloud Infrastructure Analog 81 5.2 Business Context 83 5.3 Business Structure 86 5.4 Technical Similarities 88 5.5 Impedance and Fungibility 91 5.6 Capacity Ratings 94 5.7 Bottled Capacity 95 5.8 Location of Production Considerations 95 5.9 Demand Management 97 5.10 Demand and Reserves 98 5.11 Service Curtailment 99 5.12 Balance and Grid Operations 100 5.13 Chapter Review 103 6. Application Capacity Management as an Inventory Management Problem 105 6.1 The Application Capacity Management Service Delivery Chain 105 6.2 Traditional Application Service Production Chain 107 6.3 Elasticity and Demand-Driven Capacity Management 108 6.4 Application Service as Retail Analog 110 6.4.1 Locational Consideration 112 6.4.2 Inventory and Capacity 112 6.4.3 Service Level 113 6.4.4 Inventory Carrying Costs 114 6.4.5 Inventory Decision, Planning, and Ordering 115 6.4.6 Agility 118 6.4.7 Changing Consumption Patterns 118 6.5 Chapter Review 118 7. Lean Demand Management 119 7.1 Infrastructure Demand Management Techniques 120 7.1.1 Resource Scheduling 121 7.1.2 Resource Curtailment 121 7.1.3 Mandatory Demand Shaping 122 7.1.4 Voluntary Demand Shaping 123 7.1.5 Scheduling Maintenance Actions 123 7.1.6 Resource Pricing 123 7.2 Application Demand Management Techniques 124 7.2.1 Queues and Buffers 124 7.2.2 Load Balancers 124 7.2.3 Overload Controls 125 7.2.4 Explicit Demand Management Actions 125 7.2.5 Scheduling Maintenance Actions 125 7.2.6 User Pricing Strategies 126 7.3 Full Stream Analysis Methodology 126 7.3.1 Analyze Applications' Natural Demand Patterns 127 7.3.2 Analyze Applications' Tolerances 128 7.3.3 Create Attractive Infrastructure Pricing Models 129 7.3.4 Deploy Optimal Infrastructure Demand Management Models 130 7.4 Chapter Review 131 8. Lean Reserves 133 8.1 What Is Reserve Capacity? 133 8.2 Uses of Reserve Capacity 135 8.2.1 Random Demand Peaks 135 8.2.2 Component or Resource Failure 136 8.2.3 Infrastructure Element Failure 136 8.2.4 Infrastructure Resource Curtailment or Demand Management Action 137 8.2.5 Demand Exceeding Forecast 137 8.2.6 Lead Time Demand 137 8.2.7 Catastrophic Failures and Force Majeure Events 139 8.3 Reserve Capacity as a Feature 139 8.4 Types of Reserve Capacity 140 8.4.1 Automatic Infrastructure Power Management Controls 140 8.4.2 Utilize Application Reserve Capacity 141 8.4.3 Place/Migrate Demand into Underutilized Capacity 141 8.4.4 Grow Online Capacity 141 8.4.5 Service Curtailment/Degradation 141 8.4.6 Mandatory Demand Shaping 141 8.4.7 Voluntary Demand Shaping 142 8.4.8 Emergency Reserves 142 8.5 Limits of Reserve Capacity 144 8.6 Ideal Reserve 144 8.6.1 Normal (Co-located) Reserve 144 8.6.2 Emergency (Geographically Distributed) Reserve 146 8.7 Chapter Review 147 9. Lean Infrastructure Commitment 149 9.1 Unit Commitment and Infrastructure Commitment 150 9.2 Framing the Unit Commitment Problem 151 9.3 Framing the Infrastructure Commitment Problem 153 9.4 Understanding Element Startup Time 155 9.5 Understanding Element Shutdown Time 157 9.6 Pulling It All Together 160 9.7 Chapter Review 166 10. Lean Cloud Capacity Management Performance Indicators 167 10.1 Perfect Capacity Metrics 168 10.2 Capacity Management Metrics 172 10.3 Infrastructure Commitment Metrics 173 10.4 Waste Metrics 174 10.4.1 Reserve Capacity Waste Metrics 174 10.4.2 Excess Application Capacity Metrics 175 10.4.3 Excess Online Infrastructure Capacity Metrics 175 10.4.4 Excess Physical Infrastructure Capacity Metrics 175 10.4.5 Inadequate Capacity Metrics 175 10.4.6 Infrastructure Overhead Waste Metrics 176 10.4.7 Capacity Management Overhead Waste Metrics 176 10.4.8 Resource Overhead Waste Metrics 176 10.4.9 Power Management Overhead Waste Metrics 177 10.4.10 Workload Migration Metrics 177 10.4.11 Complexity Overhead Metrics 178 10.4.12 Resource Allocation Failure Metrics 178 10.4.13 Leaking and Lost Resources 179 10.4.14 Waste Heat Metrics 179 10.4.15 Carbon Footprint Metrics 180 10.5 Key Principle Indicators 180 10.6 Cost of Poor Quality 181 10.7 Metrics and Service Boundaries 182 10.8 Measurements and Maturity 183 10.9 Chapter Review 185 11. Summary 187 11.1 Cloud Computing as a Service Delivery Chain 187 11.2 Lean Cloud Computing 190 11.3 Reimagining Cloud Capacity 192 11.4 Lean Demand Management 195 11.5 Lean Reserves 197 11.6 Lean Infrastructure Service Provider Considerations 198 11.7 Lean Application Service Provider Considerations 198 11.8 Lean Infrastructure Commitment 199 11.9 Visualizing Perfect Capacity 201 11.10 Lean Cloud Computing Metrics 203 11.11 Concluding Remarks 204 References 207 About the Author 211 Index 213

Read more less

Book SynopsisPresentsinformationto create a trade-off analysis framework for use in government and commercial acquisition environments This book presents a decision management process based on decision theory and cost analysis best practices aligned with the ISO/IEC 15288, the Systems Engineering Handbook, and the Systems Engineering Body of Knowledge. It provides a sound trade-off analysis framework to generate the tradespace and evaluate value and risk to support system decision-making throughout the life cycle. Trade-off analysis and risk analysis techniques are examined. The authors present an integrated value trade-off and risk analysis framework based on decision theory. These trade-off analysis concepts are illustrated in the different life cycle stages using multiple examples from defense and commercial domains. Provides techniques to identify and structure stakeholder objectives and creative, doable alternatives Presents the advantages and disadvantagTable of ContentsList of Contributors xix About the Authors xxi Foreword xxxi Preface xxxiii Acknowledgments xli About the Companion Website xlv 1 Introduction to Trade-off Analysis 1Gregory S. Parnell, Matthew Cilli, Azad M. Madni and Garry Roedler 1.1 Introduction 2 1.2 Trade-off Analyses Throughout the Life Cycle 3 1.3 Trade-off Analysis to Identify System Value 3 1.4 Trade-off Analysis to Identify System Uncertainties and Risks 6 1.5 Trade-off Analyses can Integrate Value and Risk Analysis 6 1.6 Trade-off Analysis in the Systems Engineering Decision Management Process 8 1.7 Trade-off Analysis Mistakes of Omission and Commission 9 1.7.1 Mistakes of Omission 12 1.7.2 Mistakes of Commission 15 1.7.3 Impacts of the Trade-Off Analysis Mistakes 18 1.8 Overview of the Book 20 1.8.1 Illustrative Examples and Techniques Used in the Book 24 1.9 Key Terms 24 1.10 Exercises 25 References 26 2 A Conceptual Framework and Mathematical Foundation for Trade-Off Analysis 29Gregory S. Parnell, Azad M. Madni and Robert F. Bordley 2.1 Introduction 29 2.2 Trade-Off Analysis Terms 30 2.3 Influence Diagram of the Tradespace 31 2.3.1 Stakeholder Needs System Functions and Requirements 33 2.3.2 Objectives 33 2.3.3 System Alternatives 34 2.3.4 Uncertainty 36 2.3.5 Preferences and Evaluation of Alternatives 37 2.3.6 Resource Analysis 44 2.3.7 An Integrated Trade-Off Analyses 44 2.4 Tradespace Exploration 46 2.5 Summary 46 2.6 Key Words 47 2.7 Exercises 48 References 48 3 Quantifying Uncertainty 51Robert F. Bordley 3.1 Sources of Uncertainty in Systems Engineering 51 3.2 The Rules of Probability and Human Intuition 52 3.3 Probability Distributions 56 3.3.1 Calculating Probabilities from Experiments 56 3.3.2 Calculating Complex Probabilities from Simpler Probabilities 58 3.3.3 Calculating Probabilities Using Parametric Distributions 59 3.3.4 Applications of Parametric Probability Distributions 62 3.4 Estimating Probabilities 66 3.4.1 Using Historical Data 66 3.4.2 Using Human Judgment 68 3.4.3 Biases in Judgment 70 3.5 Modeling Using Probability 72 3.5.1 Bayes Nets 72 3.5.2 Monte Carlo Simulation 75 3.5.3 Monte Carlo Simulation with Dependent Uncertainties 76 3.5.4 Monte Carlo Simulation with Partial Information on Output Values 77 3.5.5 Variations on Monte Carlo Simulation 78 3.5.6 Sensitivity Analysis 78 3.6 Summary 81 3.7 Key Terms 81 3.8 Exercises 83 References 86 4 Analyzing Resources 91Edward A. Pohl, Simon R. Goerger and Kirk Michealson 4.1 Introduction 91 4.2 Resources 92 4.2.1 People 92 4.2.2 Facilities 95 4.2.3 Costs 95 4.2.4 Resource Space 99 4.3 Cost Analysis 99 4.3.1 Cost Estimation 102 4.3.2 Cost Estimation Techniques 108 4.3.3 Learning Curves 120 4.3.4 Net Present Value 125 4.3.5 Monte Carlo Simulation 130 4.3.6 Sensitivity Analysis 134 4.4 Affordability Analysis 135 4.4.1 Background 136 4.4.2 The Basics of Affordability Analysis Are Not Difficult 137 4.4.3 DoD Comparison of Cost Analysis and Affordability Analysis 138 4.4.4 Affordability Analysis Definitions 139 4.4.5 “Big A” Affordability Analysis Process Guide 141 4.5 Key Terms 147 4.6 Excercises 149 References 152 5 Understanding Decision Management 155Matthew Cilli and Gregory S. Parnell 5.1 Introduction 155 5.2 Decision Process Context 156 5.3 Decision Process Activities 157 5.3.1 Frame Decision 159 5.3.2 Develop Objectives and Measures 163 5.3.3 Generate Creative Alternatives 171 5.3.4 Assess Alternatives via Deterministic Analysis 180 5.3.5 Synthesize Results 183 5.3.6 Develop Multidimensional Value Model 187 5.3.7 Identify Uncertainty and Conduct Probabilistic Analysis 190 5.3.8 Assess Impact of Uncertainty 192 5.3.9 Improve Alternatives 196 5.3.10 Communicating Trade-Offs 197 5.3.11 Present Recommendation and Implementation Plan 197 5.4 Summary 199 5.5 Key Terms 199 5.6 Exercises 200 References 201 6 Identifying Opportunities 203Donna H. Rhodes and Simon R. Goerger 6.1 Introduction 203 6.2 Knowledge 205 6.2.1 Domain Knowledge 205 6.2.2 Technical Knowledge 205 6.2.3 Business Knowledge 205 6.2.4 Expert Knowledge 206 6.2.5 Stakeholder Knowledge 206 6.3 Decision Traps 207 6.4 Techniques 210 6.4.1 Interviews 210 6.4.2 Focus Groups 213 6.4.3 Surveys 215 6.5 Tools 219 6.5.1 Concept Map 219 6.5.2 System Boundary 220 6.5.3 Decision Hierarchy 220 6.5.4 Issues List 221 6.5.5 Vision Statement 221 6.5.6 Influence Diagram 222 6.5.7 Selecting Appropriate Tools and Techniques 223 6.6 Illustrative Examples 223 6.6.1 Commercial 223 6.6.2 Defense 226 6.7 Key Terms 228 6.8 Exercises 230 References 230 7 Identifying Objectives and Value Measures 233Gregory S. Parnell and William D. Miller 7.1 Introduction 233 7.2 Value-Focused Thinking 234 7.2.1 Four Major VFT Ideas 235 7.2.2 Benefits of VFT 235 7.3 Shareholder and Stakeholder Value 236 7.3.1 Private Company Example 237 7.3.2 Government Agency Example 237 7.4 Challenges in Identifying Objectives 238 7.5 Identifying the Decision Objectives 239 7.5.1 Questions to Help Identify Decision Objectives 239 7.5.2 How to Get Answers to the Questions 240 7.6 The Financial or Cost Objective 241 7.6.1 Financial Objectives for Private Companies 241 7.6.2 Cost Objective for Public Organizations 242 7.7 Developing Value Measures 243 7.8 Structuring Multiple Objectives 243 7.8.1 Value Hierarchies 244 7.8.2 Techniques for Developing Value Hierarchies 245 7.8.3 Value Hierarchy Best Practices 247 7.8.4 Cautions about Cost and Risk Objectives 248 7.9 Illustrative Examples 248 7.9.1 Military Illustrative Example 248 7.9.2 Homeland Security Illustrative Example 250 7.10 Summary 250 7.11 Key Terms 252 7.12 Exercises 253 References 255 8 Developing and Evaluating Alternatives 257C. Robert Kenley, Clifford Whitcomb and Gregory S. Parnell 8.1 Introduction 257 8.2 Overview of Decision-making Creativity and Teams 258 8.2.1 Approaches to Decision-Making 258 8.2.2 Cognitive Methods for Creating Alternatives 260 8.2.3 Key Concepts for Building and Operating Teams 260 8.3 Alternative Development Techniques 263 8.3.1 Structured Creativity Methods 263 8.3.2 Morphological Box 266 8.3.3 Pugh Method for Alternative Generation 270 8.3.4 TRIZ for Alternative Development 271 8.4 Assessment of Alternative Development Techniques 275 8.5 Alternative Evaluation Techniques 276 8.5.1 Decision-Theory-Based Approaches 276 8.5.2 Pugh Method for Alternative Evaluation 276 8.5.3 Axiomatic Approach to Design (AAD) 277 8.5.4 TRIZ for Alternative Evaluation 280 8.5.5 Design of Experiments (DOE) 280 8.5.6 Taguchi Approach 282 8.5.7 Quality Function Deployment (QFD) 283 8.5.8 Analytic Hierarchy Process AHP 287 8.6 Assessment of Alternative Evaluation Techniques 290 8.7 Key Terms 290 8.8 Exercises 290 References 293 9 An Integrated Model for Trade-Off Analysis 297Alexander D. MacCalman, Gregory S. Parnell and Sam Savage 9.1 Introduction 297 9.2 Conceptual Design Example 298 9.3 Integrated Approach Influence Diagram 300 9.3.1 Decision Nodes 300 9.3.2 Uncertainty Nodes 303 9.3.3 Constant Node 310 9.3.4 Value Nodes 314 9.4 Other Types of Trade-Off Analysis 322 9.5 Simulation Tools 322 9.5.1 Monte Carlo Simulation Proprietary Add-Ins 324 9.5.2 The Discipline of Probability Management 324 9.5.3 SIPmathTM Tool in Native Excel 324 9.5.4 Model Building Steps 325 9.6 Summary 329 9.7 Key Terms 330 9.8 Exercises 331 References 335 10 Exploring Concept Trade-Offs 337Azad M. Madni and Adam M. Ross 10.1 Introduction 337 10.1.1 Key Concepts Concept Trade-Offs and Concept Exploration 341 10.2 Defining the Concept Space and System Concept of Operations 345 10.3 Exploring the Concept Space 346 10.3.1 Storytelling-Enabled Tradespace Exploration 346 10.3.2 Decisions and Outcomes 347 10.3.3 Contingent Decision-Making 347 10.4 Trade-off Analysis Frameworks 348 10.5 Tradespace and System Design Life Cycle 349 10.6 From Point Trade-offs to Tradespace Exploration 351 10.7 Value-based Multiattribute Tradespace Analysis 351 10.7.1 Tradespace Exploration and Sensitivity Analysis 353 10.7.2 Tradespace Exploration and Uncertainty 354 10.7.3 Tradespace Exploration with Spiral Development 356 10.7.4 Tradespace Exploration in Relation to Optimization and Decision Theory 356 10.8 Illustrative Example 359 10.8.1 Step 1: Determine Key Decision-Makers 359 10.8.2 Step 2: Scope and Bound the Mission 360 10.8.3 Step 3: Elicit Attributes and Utilities (Preference Capture) 360 10.8.4 Step 4: Define Design Vector Elements (Concept Generation) 362 10.8.5 Step 5: Develop Model(s) (Evaluation) 362 10.8.6 Step 6: Generate the Tradespace (Computation) 364 10.8.7 Step 7: Explore the Tradespace (Analysis and Synthesis) 365 10.9 Conclusions 369 10.10 Key Terms 371 10.11 Exercises 372 References 372 11 Architecture Evaluation Framework 377James N. Martin 11.1 Introduction 377 11.1.1 Architecture in the Decision Space 378 11.1.2 Architecture Evaluation 379 11.1.3 Architecture Views and Viewpoints 380 11.1.4 Stakeholders 382 11.1.5 Stakeholder Concerns 382 11.1.6 Architecture versus Design 383 11.1.7 On the Uses of Architecture 384 11.1.8 Standardizing on an Architecture Evaluation Strategy 384 11.2 Key Considerations in Evaluating Architectures 385 11.2.1 Plan-Driven Evaluation Effort 386 11.2.2 Objectives-Driven Evaluation 387 11.2.3 Assessment versus Analysis 387 11.3 Architecture Evaluation Elements 389 11.3.1 Architecture Evaluation Approach 389 11.3.2 Architecture Evaluation Objectives 390 11.3.3 Evaluation Approach Examples 391 11.3.4 Value Assessment Methods 391 11.3.5 Value Assessment Criteria 393 11.3.6 Architecture Analysis Methods 394 11.4 Steps in an Architecture Evaluation Process 396 11.5 Example Evaluation Taxonomy 398 11.5.1 Business Impact Factors 398 11.5.2 Mission Impact Factors 398 11.5.3 Architecture Attributes 399 11.6 Summary 400 11.7 Key Terms 400 11.8 Exercises 402 References 402 12 Exploring the Design Space 405Clifford Whitcomb and Paul Beery 12.1 Introduction 405 12.2 Example 1: Liftboat 406 12.2.1 Liftboat Fractional Factorial Design of Experiments 406 12.2.2 Liftboat Design Trade-Off Space 409 12.2.3 Liftboat Uncertainty Analysis 411 12.2.4 Liftboat Example Summary 411 12.3 Example 2: Cruise Ship Design 411 12.3.1 Cruise Ship Taguchi Design of Experiments 411 12.3.2 Cruise Ship Design Trade-Off Space 412 12.3.3 Cruise Ship Example Summary 416 12.4 Example 3: NATO Naval Surface Combatant Ship 417 12.4.1 NATO Surface Combatant Ship Stakeholder Need 418 12.4.2 NATO Surface Combatant Ship Box–Behnken Design of Experiments 420 12.4.3 NATO Surface Combatant Ship Cost-Effectiveness Trade-Off 421 12.4.4 NATO Surface Combatant Ship Design Tradespace 421 12.4.5 NATO Surface Combatant Ship Design Trade-Off 422 12.4.6 NATO Surface Combatant Ship Trade-Off Summary 430 12.5 Key Terms 431 12.6 Exercises 433 References 435 13 Sustainment Related Models and Trade Studies 437John E. MacCarthy and Andres Vargas 13.1 Introduction 437 13.2 Availability Modeling and Trade Studies 439 13.2.1 FMDS Background 439 13.2.2 FMDS Availability Trade Studies 449 13.2.3 Section Synopsis 453 13.3 Sustainment Life Cycle Cost Modeling and Trade Studies14 454 13.3.1 The Total System Life Cycle Model 454 13.3.2 The O&S Cost Model 456 13.3.3 Life Cycle Cost Trade Study 459 13.4 Optimization in Availability Trade Studies 464 13.4.1 Setting Up the Optimization Problem 464 13.4.2 Instantiating the Optimization Model 465 13.4.3 Discussion of the Optimization Model Results 468 13.4.4 Deterministic Sensitivity Analysis 469 13.5 Monte Carlo Modeling 471 13.5.1 Input Probability Distributions for the Monte Carlo Model 471 13.5.2 Monte Carlo Simulation Results 472 13.5.3 Stochastic Sensitivity Analysis 473 13.6 Chapter Summary 475 13.7 Key Terms 476 13.8 Exercises 478 References 482 14 Performing Programmatic Trade-Off Analyses 483Gina Guillaume-Joseph and John E. MacCarthy 14.1 Introduction 483 14.2 System Acceptance Decisions and Trade Studies 485 14.2.1 Acceptance Decision Framework 486 14.2.2 Calculating the Confidence That a System Is “Good” 491 14.2.3 Acceptance Test Design and Trade Studies 493 14.2.4 A “Delay Fix and Test” Cost Model 499 14.2.5 The Integrated Decision Model 504 14.2.6 Conclusions 511 14.3 Product Cancelation Decision Trade Study 512 14.3.1 Introduction 512 14.3.2 Significance 513 14.3.3 Defining Failure 514 14.3.4 Developing the Predictive Model 519 14.3.5 Research Results 522 14.3.6 Model Implementation In Industry 528 14.3.7 Predictive Model Deployment in Industry 530 14.3.8 When the Decision Has Been Made to Cancel the System 536 14.3.9 Conclusion 537 14.4 Product Retirement Decision Trade Study 538 14.4.1 Introduction 538 14.4.2 Legacy HR Systems 539 14.4.3 The US NAVY Retirement and Decommission Program for Nuclear-Powered Vessels 544 14.4.4 Decision Analysis for Decommissioning Offshore Oil and Gas Platforms in California 551 14.4.5 System Retirement and Decommissioning Strategy 559 14.4.6 Conclusion 561 14.5 Key Terms 562 14.6 Exercises 564 References 566 15 Summary and Future Trends 571Gregory S. Parnell and Simon R. Goerger 15.1 Introduction 571 15.2 Major Trade-Off Analysis Themes 572 15.2.1 Use Standard Systems Engineering Terminology 572 15.2.2 Avoid the Mistakes of Omission and Commission 572 15.2.3 Use a Decision Management Framework 572 15.2.4 Use Decision Analysis as the Mathematical Foundation 573 15.2.5 Explicitly Define the Decision Opportunity 573 15.2.6 Identify and Structure Decision Objectives and Measures 574 15.2.7 Identify Creative Doable Alternatives 574 15.2.8 Use the Most Appropriate Modeling and Simulation Technique for the Life Cycle Stage 575 15.2.9 Include Resource Analysis in the Trade-Off Analysis 575 15.2.10 Explicitly Consider Uncertainty 575 15.2.11 Identify the Cost Value Schedule and Risk Drivers 575 15.2.12 Provide an Integrated Framework for Cost Value and Risk Analyses 576 15.3 Future of Trade-Off Analysis 576 15.3.1 Education and Training of Systems Engineers 577 15.3.2 Systems Engineering Methodologies and Tools 577 15.3.3 Emergent Tradespace Factors 580 15.4 Summary 581 References 581 Index 583

Read more less

Book SynopsisThis book presents and discusses strategies for the design and implementation of common-mode suppressed balanced microwave filters, including, narrowband, wideband, and ultra-wideband filters This book examines differential-mode, or balanced, microwave filters by discussing several implementations of practical realizations of these passive components. Topics covered include selective mode suppression, designs based on distributed and semi-lumped approaches, multilayer technologies, defect ground structures, coupled resonators, metamaterials, interference techniques, and substrate integrated waveguides, among others. Divided into five parts, Balanced Microwave Filters begins with an introduction that presents the fundamentals of balanced lines, circuits, and networks. Part 2 covers balanced transmission lines with common-mode noise suppression, including several types of common-mode filters and the application of such filters to enhance common-mode suppression in balanced bandpass filteTable of ContentsLIST OF CONTRIBUTORS xix PREFACE xxiii PART 1 INTRODUCTION 1 1 INTRODUCTION TO BALANCED TRANSMISSION LINES, CIRCUITS, AND NETWORKS 3Ferran Martín, Jordi Naqui, Francisco Medina, Lei Zhu, and Jiasheng Hong 1.1 Introduction 3 1.2 Balanced Versus Single-Ended Transmission Lines and Circuits 4 1.3 Common-Mode Noise 5 1.4 Fundamentals of Differential Transmission Lines 6 1.4.1 Topology 6 1.4.2 Propagating Modes 8 1.4.2.1 Even and Odd Mode 8 1.4.2.2 Common and Differential Mode 11 1.5 Scattering Parameters 13 1.5.1 Single-Ended S-Parameters 13 1.5.2 Mixed-Mode S-Parameters 16 1.6 Summary 19 References 19 PART 2 BALANCED TRANSMISSION LINES WITH COMMON-MODE NOISE SUPPRESSION 21 2 STRATEGIES FOR COMMON-MODE SUPPRESSION IN BALANCED LINES 23Ferran Martín, Paris Vélez, Armando Fernández-Prieto, Jordi Naqui, Francisco Medina, and Jiasheng Hong 2.1 Introduction 23 2.2 Selective Mode Suppression in Differential Transmission Lines 25 2.3 Common-Mode Suppression Filters Based on Patterned Ground Planes 27 2.3.1 Common-Mode Filter Based on Dumbbell-Shaped Patterned Ground Plane 27 2.3.2 Common-Mode Filter Based on Complementary Split Ring Resonators (CSRRs) 30 2.3.3 Common-Mode Filter Based on Defected Ground Plane Artificial Line 40 2.3.4 Common-Mode Filter Based on C-Shaped Patterned Ground Structures 44 2.4 Common-Mode Suppression Filters Based on Electromagnetic Bandgaps (EBGs) 49 2.4.1 Common-Mode Filter Based on Nonuniform Coupled Lines 50 2.4.2 Common-Mode Filter Based on Uniplanar Compact Photonic Bandgap (UC-PBG) Structure 55 2.5 Other Approaches for Common-Mode Suppression 55 2.6 Comparison of Common-Mode Filters 60 2.7 Summary 61 Appendix 2.A: Dispersion Relation for Common-Mode Rejection Filters with Coupled CSRRs or DS-CSRRs 61 Appendix 2.B: Dispersion Relation for Common-Mode Rejection Filters with Coupled Patches Grounded through Inductive Strips 64 References 65 3 COUPLED-RESONATOR BALANCED BANDPASS FILTERS WITH COMMON-MODE SUPPRESSION DIFFERENTIAL LINES 73Armando Fernández-Prieto, Jordi Naqui, Jesús Martel, Ferran Martín, and Francisco Medina 3.1 Introduction 73 3.2 Balanced Coupled-Resonator Filters 74 3.2.1 Single-Band Balanced Bandpass Filter Based on Folded Stepped-Impedance Resonators 75 3.2.2 Balanced Filter Loaded with Common-Mode Rejection Sections 79 3.2.3 Balanced Dual-Band Bandpass Filter Loaded with Common-Mode Rejection Sections 82 3.3 Summary 88 References 88 PART 3 WIDEBAND AND ULTRA-WIDEBAND (UWB) BALANCED BAND PASS FILTERS WITH INTRINSIC COMMON-MODE SUPPRESSION 91 4 WIDEBAND AND UWB BALANCED BANDPASS FILTERS BASED ON BRANCH-LINE TOPOLOGY 93Teck Beng Lim and Lei Zhu 4.1 Introduction 93 4.2 Branch-Line Balanced Wideband Bandpass Filter 97 4.3 Balanced Bandpass Filter for UWB Application 105 4.4 Balanced Wideband Bandpass Filter with Good Common-Mode Suppression 111 4.5 Highly Selective Balanced Wideband Bandpass Filters 116 4.6 Summary 131 References 131 5 WIDEBAND AND UWB COMMON-MODE SUPPRESSED DIFFERENTIAL-MODE FILTERS BASED ON COUPLED LINE SECTIONS 135Qing-Xin Chu, Shi-Xuan Zhang, and Fu-Chang Chen 5.1 Balanced UWB Filter by Combining UWB BPF with UWB BSF 135 5.2 Balanced Wideband Bandpass Filter Using Coupled Line Stubs 142 5.3 Balanced Wideband Filter Using Internal Cross-Coupling 148 5.4 Balanced Wideband Filter Using Stub-Loaded Ring Resonator 155 5.5 Balanced Wideband Filter Using Modified Coupled Feed Lines and Coupled Line Stubs 161 5.6 Summary 173 References 174 6 WIDEBAND DIFFERENTIAL CIRCUITS USING T-SHAPED STRUCTURES AND RING RESONATORS 177Wenquan Che and Wenjie Feng 6.1 Introduction 177 6.2 Wideband Differential Bandpass Filters Using T-Shaped Resonators 179 6.2.1 Mixed-Mode S-Parameters for Four-Port Balanced Circuits 179 6.2.2 T-Shaped Structures with Open/Shorted Stubs 184 6.2.2.1 T-Shaped Structure with Shorted Stubs 184 6.2.2.2 T-Shaped Structure with Open Stubs 185 6.2.3 Wideband Bandpass Filters without Cross Coupling 187 6.2.3.1 Differential-Mode Excitation 189 6.2.3.2 Common-Mode Excitation 191 6.2.4 Wideband Bandpass Filter with Cross Coupling 193 6.3 Wideband Differential Bandpass Filters Using Half-/Full-Wavelength Ring Resonators 201 6.3.1 Differential Filter Using Half-Wavelength Ring Resonators 201 6.3.2 Differential Filter Using Full-Wavelength Ring Resonators 206 6.3.3 Differential Filter Using Open/Shorted Coupled Lines 215 6.3.4 Comparisons of Several Wideband Balanced Filters Based on Different Techniques 220 6.4 Wideband Differential Networks Using Marchand Balun 223 6.4.1 S-Parameter for Six-Port Differential Network 223 6.4.2 Wideband In-Phase Differential Network 227 6.4.3 Wideband Out-of-Phase Differential Network 236 6.5 Summary 244 References 245 7 UWB AND NOTCHED-BAND UWB DIFFERENTIAL FILTERS USING MULTILAYER AND DEFECTED GROUND STRUCTURES (DGSS) 249Jian-Xin Chen, Li-Heng Zhou, and Quan Xue 7.1 Conventional Multilayer Microstrip-to-Slotline Transition (MST) 250 7.2 Differential MST 251 7.2.1 Differential MST with a Two-Layer Structure 251 7.2.2 Differential MST with Three-Layer Structure 252 7.3 UWB Differential Filters Based on the MST 253 7.3.1 Differential Wideband Filters Based on the Conventional MST 253 7.3.2 Differential Wideband Filters Based on the Differential MST 255 7.4 Differential Wideband Filters Based on the Strip-Loaded Slotline Resonator 262 7.4.1 Differential Wideband Filters Using Triple-Mode Slotline Resonator 265 7.4.2 Differential Wideband Filters Using Quadruple-Mode Slotline Resonator 267 7.5 UWB Differential Notched-Band Filter 270 7.5.1 UWB Differential Notched-Band Filter Based on the Traditional MST 270 7.5.2 UWB Differential Notched-Band Filter Based on the Differential MST 272 7.6 Differential UWB Filters with Enhanced Stopband Suppression 277 7.7 Summary 280 References 281 8 APPLICATION OF SIGNAL INTERFERENCE TECHNIQUE TO THE IMPLEMENTATION OF WIDEBAND DIFFERENTIAL FILTERS 283Wei Qin and Quan Xue 8.1 Basic Concept of the Signal Interference Technique 283 8.1.1 Fundamental Theory 284 8.1.2 One Filter Example Based on Ring Resonator 287 8.1.3 Simplified Circuit Model 288 8.2 Signal Interference Technique for Wideband Differential Filters 290 8.2.1 Circuit Model of Wideband Differential Bandpass Filter 290 8.2.2 S-Matrix for Differential Bandpass Filters 292 8.3 Several Designs of Wideband Differential Bandpass Filters 293 8.3.1 Differential Bandpass Filter Based on Wideband Marchand Baluns 293 8.3.2 Differential Bandpass Filter Based on π-Type UWB 180 Phase Shifters 299 8.3.3 Differential Bandpass Filter Based on DSPSL UWB 180 Phase Inverter 302 8.3.3.1 Differential-Mode Analysis 305 8.3.3.2 Common-Mode Analysis 305 8.3.3.3 Filter Design and Measurement 308 8.4 Summary 308 References 309 9 WIDEBAND BALANCED FILTERS BASED ON MULTI-SECTION MIRRORED STEPPED IMPEDANCE RESONATORS (SIRs) 311 Ferran Martín, Jordi Selga, Paris Vélez, Marc Sans, Jordi Bonache, Ana Rodríguez, Vicente E. Boria, Armando Fernández-Prieto, and Francisco Medina 9.1 Introduction 311 9.2 The Multi-Section Mirrored Stepped Impedance Resonator (SIR) 312 9.3 Wideband Balanced Bandpass Filters Based on 7-Section Mirrored SIRs Coupled Through Admittance Inverters 317 9.3.1 Finding the Optimum Filter Schematic 319 9.3.2 Layout Synthesis 325 9.3.2.1 Resonator Synthesis 325 9.3.2.2 Determination of the Line Width 327 9.3.2.3 Optimization of the Line Length (Filter Cell Synthesis) 327 9.3.3 A Seventh-Order Filter Example 330 9.3.4 Comparison with Other Approaches 334 9.4 Compact Ultra-Wideband (UWB) Balanced Bandpass Filters Based on 5-Section Mirrored SIRs and Patch Capacitors 336 9.4.1 Topology and Circuit Model of the Series Resonators 337 9.4.2 Filter Design 341 9.4.3 Comparison with Other Approaches 345 9.5 Summary 346 Appendix 9.A: General Formulation of Aggressive Space Mapping (ASM) 347 References 349 10 METAMATERIAL-INSPIRED BALANCED FILTERS 353Ferran Martín, Paris Vélez, Ali Karami-Horestani, Francisco Medina, and Christophe Fumeaux 10.1 Introduction 353 10.2 Balanced Bandpass Filters Based on Open Split Ring ResonatorS (OSRRS) and Open Complementary Split Ring Resonators (OCSRRS) 354 10.2.1 Topology of the OSRR and OCSRR 354 10.2.2 Filter Design and Illustrative Example 356 10.3 Balanced Filters Based on S-Shaped Complementary Split Ring Resonators (S-CSRRs) 363 10.3.1 Principle for Balanced Bandpass Filter Design and Modeling 365 10.3.2 Illustrative Example 367 10.4 Summary 369 References 369 11 WIDEBAND BALANCED FILTERS ON SLOTLINE RESONATOR WITH INTRINSIC COMMON-MODE REJECTION 373Xin Guo, Lei Zhu, and Wen Wu 11.1 Introduction 373 11.2 Wideband Balanced Bandpass Filter on Slotline MMR 375 11.2.1 Working Mechanism 375 11.2.2 Synthesis Method 378 11.2.3 Geometry and Layout 382 11.2.4 Fabrication and Experimental Verification 388 11.3 Wideband Balanced BPF on Strip-Loaded Slotline Resonator 392 11.3.1 Strip-Loaded Slotline Resonator 392 11.3.2 Wideband Balanced Bandpass Filters 396 11.3.2.1 Wideband Balanced BPF on Strip-Loaded Triple-Mode Slotline Resonator 397 11.3.2.2 Wideband Balanced BPF on Strip-Loaded Quadruple-Mode Slotline Resonator 403 11.4 Wideband Balanced Bandpass Filter on Hybrid MMR 408 11.4.1 Hybrid MMR 408 11.4.2 Wideband Balanced Bandpass Filters 416 11.5 Summary 420 References 420 PART 4 NARROWBAND AND DUAL-BAND BALANCED BANDPASS FILTERS WITH INTRINSIC COMMON-MODE SUPPRESSION 423 12 NARROWBAND COUPLED-RESONATOR BALANCED BANDPASS FILTERS AND DIPLEXERS 425Armando Fernández-Prieto, Francisco Medina, and Jesús Martel 12.1 Introduction 425 12.2 Coupled-Resonator Balanced Filters with Intrinsic Common-Mode Rejection 426 12.2.1 Loop and SIR Resonator Filters with Mixed Coupling 427 12.2.1.1 Quasi-elliptic Response BPF: First Example 428 12.2.1.2 Quasi-elliptic Response BPF: Second Example 434 12.2.2 Magnetically Coupled Open-Loop and FSIR Balanced Filters 439 12.2.2.1 Filters with Magnetic Coupling: First Example 439 12.2.2.2 Filters with Magnetic Coupling: Second Example 447 12.2.3 Interdigital Line Resonators Filters 449 12.2.3.1 ILR Filter Design Example 450 12.2.4 Dual-Mode and Dual-Behavior Resonators for Balanced Filter Design 451 12.2.4.1 Dual-Mode Square Patch Resonator Filters 453 12.2.4.2 Filters Based on Dual-Behavior Resonators 458 12.2.5 LTCC-Based Multilayer Balanced Filter 464 12.2.6 Balanced Bandpass Filters Based on Dielectric Resonators 466 12.3 Loaded Resonators for Common-Mode Suppression Improvement 469 12.3.1 Capacitively, Inductively, and Resistively Center-Loaded Resonators 470 12.3.1.1 Open-Loop UIR-Loaded Filter 470 12.3.1.2 Folded SIR Loaded Filter 476 12.3.2 Filters with Defected Ground Structures (DGS) 484 12.3.2.1 Control of the Transmission Zeros 488 12.3.3 Multilayer Loaded Resonators 490 12.3.3.1 Design Example 492 12.4 Coupled Line Balanced Bandpass Filter 493 12.4.1 Type-II Design Example 495 12.5 Balanced Diplexers 499 12.5.1 Unbalanced-to-Balanced Diplexer Based on Uniform Impedance Stub-Loaded Coupled Resonators 500 12.5.1.1 Resonator Geometry 500 12.5.1.2 Unbalanced-to-Balanced Diplexer Design 502 12.5.2 Example Two: Balanced-to-Balanced Diplexer Based on UIRs and Short-Ended Parallel-Coupled Lines 505 12.6 Summary 508 References 510 13 DUAL-BAND BALANCED FILTERS BASED ON LOADED AND COUPLED RESONATORS 515Jin Shi and Quan Xue 13.1 Dual-Band Balanced Filter with Loaded Uniform Impedance Resonators 516 13.1.1 Center-Loaded Uniform Impedance Resonator 516 13.1.2 Dual-Band Balanced Filter Using the Uniform Impedance Resonator with Center-Loaded Lumped Elements 520 13.1.3 Dual-Band Balanced Filter Using Stub-Loaded Uniform Impedance Resonators 526 13.2 Dual-Band Balanced Filter with Loaded Stepped-Impedance Resonators 528 13.2.1 Center-Loaded Stepped-Impedance Resonator 528 13.2.2 Dual-Band Balanced Filter Using Stepped-Impedance Resonators with Center-Loaded Lumped Elements 531 13.2.3 Dual-Band Balanced Filter Using Stub-Loaded Stepped-Impedance Resonators 535 13.3 Dual-Band Balanced Filter Based on Coupled Resonators 538 13.3.1 Dual-Band Balanced Filter with Coupled Stepped-Impedance Resonators 538 13.3.2 Dual-Band Balanced Filter with Coupled Stub-Loaded Short-Ended Resonators 542 13.4 Summary 546 References 547 14 DUAL-BAND BALANCED FILTERS IMPLEMENTED IN SUBSTRATE INTEGRATED WAVEGUIDE (SIW) TECHNOLOGY 549Wen Wu, Jianpeng Wang, and Chunxia Zhou 14.1 Substrate Integrated Waveguide (SIW) Cavity 550 14.2 Closely Proximate Dual-Band Balanced Filter Design 551 14.3 Dual-Band Balanced Filter Design Utilizing High-Order Modes in SIW Cavities 555 14.4 Summary 563 References 563 PART 5 OTHER BALANCED CIRCUITS 565 15 BALANCED POWER DIVIDERS/COMBINERS 567Lin-Sheng Wu, Bin Xia, and Jun-Fa Mao 15.1 Introduction 567 15.2 Balanced-to-Balanced Wilkinson Power Divider with Microstrip Line 569 15.2.1 Mixed-Mode Analysis 569 15.2.1.1 Mixed-Mode Scattering Matrix of a Balanced-to-Balanced Power Divider 569 15.2.1.2 Constraint Rules of Balanced-to-Balanced Power Divider 571 15.2.1.3 Odd- and Even-Mode Scattering Matrices of Balanced-to-Balanced Power Divider 572 15.2.2 A Transmission-Line Balanced-to-Balanced Power Divider 572 15.2.2.1 Even-Mode Circuit Model 572 15.2.2.2 Odd-Mode Circuit Model 573 15.2.2.3 Scattering Matrix of the Balanced-to-Balanced Power Divider 575 15.2.3 Theoretical Result 575 15.2.4 Simulated and Measured Results 576 15.3 Balanced-to-Balanced Gysel Power Divider with Half-Mode Substrate Integrated Waveguide (SIW) 580 15.3.1 Conversion from Single-Ended Circuit to Balanced Form 580 15.3.2 Half-Mode SIW Ring Structure 581 15.3.3 Results and Discussion 583 15.4 Balanced-to-Balanced Gysel Power Divider with Arbitrary Power Division 585 15.4.1 Analysis and Design 585 15.4.2 Results and Discussion 587 15.5 Balanced-to-Balanced Gysel Power Divider with Bandpass Filtering Response 590 15.5.1 Coupled-Resonator Circuit Model 590 15.5.2 Realization in Transmission Lines 591 15.5.2.1 Internal Coupling Coefficient 592 15.5.2.2 External Q Factor 594 15.5.3 Results and Discussion 595 15.6 Filtering Balanced-to-Balanced Power Divider with Unequal Power Division 598 15.7 Dual-Band Balanced-to-Balanced Power Divider 599 15.7.1 Analysis and Design 599 15.7.2 Results and Discussion 601 15.8 Summary 603 References 603 16 DIFFERENTIAL-MODE EQUALIZERS WITH COMMON-MODE FILTERING 607Tzong-Lin Wu and Chiu-Chih Chou 16.1 Introduction 607 16.2 Design Considerations 610 16.2.1 Equalizer Design 610 16.2.2 Common-Mode Filter Design 612 16.3 First Design 613 16.3.1 Proposed Topology 613 16.3.2 Odd-Mode Analysis 616 16.3.2.1 Equalizer Optimization in Time Domain 617 16.3.3 Even-Mode Analysis 623 16.3.4 Measurement Validation 628 16.4 Second Design 633 16.4.1 Proposed Circuit and Analysis 633 16.4.2 Realization and Measurement 637 16.4.2.1 Realization 637 16.4.2.2 Common-Mode Noise Suppression 638 16.4.2.3 Differential-Mode Equalization 640 16.5 Summary 641 References 641 INDEX 645

Read more less

Book SynopsisPresents a new, effective methodology in software size measurement Software size measurement is an extremely important and highly specialized aspect of the software life cycle.Table of ContentsPreface xi Acknowledgments xv About the Author xvii List of Acronyms xix About the Companion Websites xxv Part One FSSM: Introduction 1 Introduction to Functional Software Size Measurement 3 1.1 Introduction 3 1.2 Functional Size Measurement and Effort Estimation 3 1.3 Important Considerations for the Software Size Measurement and Effort Estimation 4 1.4 Introduction to the Functional Software Size Measurement Methodology with Effort Estimation and Performance Indication (FSSM) 10 1.5 Chapter Summary 12 Exercises 13 2 Synopsis of the Functional Software Size Measurement Methodology with Effort Estimation and Performance Indication (FSSM) 15 2.1 Salient Characteristics of the FSSM 15 2.2 Distinguishing Unique Key Features of the FSSM 20 2.3 Synoptic Description of the FSSM 22 2.4 Lists and Brief Descriptions of the FSSM Constituents 36 2.5 Source of Information for the FSSM Constituents 46 2.6 Examples 47 2.7 Chapter Summary 49 Exercises 49 Part Two FSSM: Software View 3 Software’s Measurable Components in the FSSM 53 3.1 Software’s Measurable Component (SMC) Description 53 3.2 Software’s Measurable Components (SMCs) Characteristics 56 3.3 Software’s Measurable Components (SMCs) Presence and Size 56 3.4 Examples 57 3.5 Chapter Summary 57 Exercises 58 4 Software Component’s Measurable Features in the FSSM 59 4.1 Software Component’s Measurable Feature (SCMF) Description 59 4.2 Usage of the Software Component’s Measurable Features (SCMFs) 71 4.3 Software Component’s Measurable Features (SCMFs) Presence and Quantity 72 4.4 Examples 72 4.5 Chapter Summary 74 Exercises 75 Part Three FSSM: Measurements 5 Software Component’s Feature Points in the FSSM 79 5.1 Software Component’s Feature Point (SCFP) Description 79 5.2 Usage of the Software Component’s Feature Points (SCFPs) 92 5.3 Software Component’s Feature Points (SCFPs) Presence and Quantity 92 5.4 Examples 93 5.5 Chapter Summary 95 Exercises 96 6 Software Component’s Feature Point Counts in the FSSM 97 6.1 Software Component’s Feature Point Count (SCFPC) Description 97 6.2 Counting Guidelines Flowchart for the Software Component’s Measurable Features (SCMFs) of the Software’s Measurable Component ‘Functionality Execution’ (CFE) 105 6.3 Some Specific Guidelines for the Software Component’s Feature Point (SCFP) Counting 105 6.4 Software Component’s Feature Point Counts (SCFPCs) Formation 110 6.5 Usage of the Software Component’s Feature Point Counts (SCFPCs) 110 6.6 Software Component’s Feature Point Counts (SCFPCs) Value 112 6.7 Examples 112 6.8 Chapter Summary 113 Exercises 114 7 Software Component’s Measurements through Software Component’s Feature Measurements in the FSSM 116 7.1 Software Component’s Measurement (SCM) and Software Component’s Feature Measurement (SCFM) Description 116 7.2 Software Component’s Measurement (SCM) and Software Component’s Feature Measurement (SCFM) Formulae 123 7.3 Examples 130 7.4 Chapter Summary 131 Exercises 133 Part Four FSSM: Estimations and Indications 8 Software Size Determination and Effort Estimations in the FSSM 137 8.1 Software Analysis – Size Determination and Effort Estimation, Static Structure, and Dynamic Characteristics in the FSSM 137 8.2 Software Size and Effort Estimation (SSEE) Description 138 8.3 Software Size and Effort Estimation (SSEE) Formulae 143 8.4 Chapter Summary 150 Exercises 152 9 Software Performance Quality Indicators for Static Structure and Dynamic Characteristics in the FSSM 153 9.1 Software Performance Quality Indicator (SPQI) Description 153 9.2 Software Performance Quality Indicator (SPQI) Construction Information Source 164 9.3 Software Performance Quality Indicator (SPQI) Formulae 165 9.4 Examples 183 9.5 Chapter Summary 183 Exercises 187 Part Five FSSM: Summary Charts 10 Summary Charts of the FSSM 191 10.1 Summary Charts of the FSSM Constituents 191 10.2 Chapter Summary 206 Part Six FSSM: Strengths 11 Software Diagnostics Based on the Software Component’s Feature Measurements and Software Performance Quality Indicators in the FSSM 209 11.1 Basic Diagnostics About the Functional Requirements Specifications (FRS) and Software, Based on the Software Component’s Feature Measurements (SCFMs) 209 11.2 Advanced Diagnostics About the System Architecture, Functional Requirements Specifications (FRS), and Software, Based on the Software Performance Quality Indicators (SPQIs) 214 11.3 Chapter Summary 216 12 Convertibility and ISO/IEC Standards Compliance of the FSSM 217 12.1 Convertibility of the FSSM to Other Functional Size Measurement (FSM) Methodology COSMIC 217 12.2 ISO/IEC Standards Compliance of the FSSM 218 12.3 Chapter Summary 225 13 Significant Strengths of the FSSM 226 13.1 Coverage Capabilities of the FSSM in Comparison with Some Existing Software Size Measurement Methodologies 226 13.2 Advantages of the FSSM Over the Currently Available Methodologies 231 13.3 Examples 239 13.4 Chapter Summary 241 Part Seven FSSM: Usage – Example 14 Example for Using the FSSM 247 14.1 Mini-FSSM Application Software Development (ASD) Introduction 247 14.2 Functional Requirements Specifications (FRS) of the Example – ‘Mini-FSSM Application Software Development’ 248 14.3 Software Component’s Feature Point (SCFP) Counting Explanation for the Example Mini-FSSM ASD 260 14.4 Software Component’s Feature Point (SCFP) Counting and Software Component’s Feature Point Count (SCFPC) Formation Table for the Example Mini-FSSM ASD 289 14.5 FSSM Results Tables for the Software Example Mini-FSSM Application Software Development 289 14.6 Graphical Representation of the Final Output Results for the Example Mini-FSSM 305 14.7 Chapter Summary 306 Part Eight Concluding Information 15 Effort Estimate for the Usage of the FSSM 313 15.1 Software Component’s Feature Point (SCFP) Counting, Analysis, and Report Preparation Effort Estimate for the Usage of the FSSM 313 15.2 Chapter Summary 315 16 Known Limitations, Improvement Scope, and Conclusion 316 16.1 Known Limitations of the FSSM 316 16.2 Improvement Possibilities in the FSSM 316 16.3 Conclusion 317 16.4 Chapter Summary 318 Part Nine Glossary 17 Glossary 321 17.1 Terms and Their Significance 321 Part Ten List of Figures and Answers to Exercises 18 List of Figures 393 19 Answers to Exercises 395 19.1 Chapter 1 Exercises 395 19.2 Chapter 2 Exercises 395 19.3 Chapter 3 Exercises 395 19.4 Chapter 4 Exercises 396 19.5 Chapter 5 Exercises 396 19.6 Chapter 6 Exercises 396 19.7 Chapter 7 Exercises 396 19.8 Chapter 8 Exercises 396 19.9 Chapter 9 Exercises 396 References 397 Index 399

Read more less

Book SynopsisADVANCES IN ENERGY STORAGE An accessible reference describing the newest advancements in energy storage technologies Advances in Energy Storage: Latest Developments from R&D to the Market is a comprehensive exploration of a wide range of energy storage technologies that use the fundamental energy conversion method. The distinguished contributors discuss the foundational principles, common materials, construction, device operation, and system level performance of the technology, as well as real-world applications. The book also includes examinations of the industry standards that apply to energy storage technologies and the commercial status of various kinds of energy storage. The book has been written by accomplished leaders in the field and address electrochemical, chemical, thermal, mechanical, and superconducting magnetic energy storage. They offer insightful treatments of relevant policy instruments and posit likely future advancements that will suppTable of ContentsList of Contributors xxi 1 Energy Storage Solutions for Future Energy Systems 1Andreas Hauer 1.1 The Role of Energy Storage 1 1.2 The Definition of Energy Storage 1 1.3 Technologies for Energy Storage 5 1.4 Applications for Energy Storage 11 Part I Electrochemical, Electrical, and Super Magnetic Energy Storages 15 2 An Introduction to Electrochemistry in Modern Power Sources 17Frank C. Walsh, Andrew Cruden, and Peter J. Hall 2.1 Introduction 17 2.2 Electrode Reactions 17 2.3 Electrochemical Cells 18 2.4 The Case for Electrochemical Power Sources 19 2.5 The Thermodynamics of Electrochemical Cells 20 2.6 The Actual Cell Voltage: Thermodynamic, Electrode Kinetic, and Ohmic Losses 20 2.7 Faraday’s Laws and Charge Capacity 22 2.8 The Performance of Cells: Charge Capacity and Specific Energy Capability 23 2.9 Types of Electrochemical Device for Energy Conversion 23 3 Standalone Batteries for Power Backup and Energy Storage 31Declan Bryans, Martin R Jiminez, Jennifer M Maxwell, Jon M Mitxelena, David Kerr, and Léonard E A Berlouis 3.1 Introduction 31 3.2 Standalone Battery Technologies 31 3.3 Comparisons 54 3.4 Conclusions 54 4 Environmental Aspects and Recycling of Battery Materials 61Guangjin Zhao 4.1 Introduction 61 4.2 Classical Batteries 63 4.3 Summary 64 4.4 Future Perspectives 64 4.5 Future Developments 68 5 Supercapacitors for Short-term, High Power Energy Storage 71Lingbin Kong, Maocheng Liu, Jianyun Cao, Rutao Wang, Weibin Zhang, Kun Yan, Xiaohong Li, and Frank C. Walsh 5.1 Introduction 71 5.2 Electrode Materials 73 5.3 Supercapacitor Devices 80 5.4 Conclusions 88 5.5 Outlook 89 6 Overview of Superconducting Magnetic Energy Storage Technology 99Jing Shi, Xiao Zhou, Yang Liu, Li Ren, Yuejin Tang, and Shijie Chen 6.1 Introduction 99 6.2 The Principle of SMES 99 6.3 Development Status of SMES 102 6.4 Development Trend of SMES 104 6.5 Research Topics for Developing SMES 107 6.6 Conclusions 109 7 Key Technologies of Superconducting Magnets for SMES 113Ying Xu, Li Ren, Jing Shi, and Yuejin Tang 7.1 Introduction 113 7.2 The Development of SMES Magnets 116 7.3 Considerations in the Design of SMES Magnets 119 7.4 Current Leads of SMES Magnets 124 7.5 Quench Protection for SMES Magnets 128 7.6 Summary 132 8 Testing Technologies for Developing SMES 135Jing Shi, Yuxiang Liao, Lihui Zhang, Ying Xu, Li Ren, Jingdong Li, and Yuejin Tang 8.1 Introduction 135 8.2 HTS Tape Property Test Method 135 8.3 Magnet Coils Experimental Methods 138 8.4 SMES Test 140 8.5 Conclusions 147 9 Superconducting Wires and Tapes for SMES 149Yuejin Tang, Ying Xu, Sinian Yan, Feng Feng, and Guo Yan 9.1 Introduction 149 9.2 A Brief Explanation of Superconductivity 150 9.3 Wires Made from LTc Superconductors 157 9.4 Wires or Tapes Made from HTc Superconductors 158 9.5 Discussion 162 10 Cryogenic Technology 165Li Ren, Ying Xu, and Yuejin Tang 10.1 Introduction 165 10.2 Cryogens 166 10.3 Cryo-cooler 170 10.4 Cryogenic System 173 10.5 Vacuum Technology 176 10.6 An Evaluation Method for Conduction-cooled SMES Cryogenic Cooling Systems 178 10.7 Case Study 181 11 Control Strategies for Different Application Modes of SMES 187Jiakun Fang, Wei Yao, Jinyu Wen, and Shijie Cheng 11.1 Overview of the Control Strategies for SMES Applications 187 11.2 Robust Control for SMES in Coordination with Wind Generators 188 11.3 Anti-windup Compensation for SMES-Based Power System Damping Controller 196 11.4 Monitoring and Control Unit of SMES 204 11.5 Conclusion 208 Part II Mechanical Energy Storage and Pumped Hydro Energy Storage 211 12 Overview of Pumped Hydro Resource 213Pål-Tore Storli 12.1 Pumped Hydro Storage Basic Concepts 213 12.2 Historic Perspective 226 12.3 Worldwide Installed Base 231 12.4 The Future for PHS 231 13 Pumped Storage Machines – Motor Generators 239Stefanie Kemmer and Thomas Hildinger 13.1 Synchronous Machine Fixed Speed 240 13.2 Doubly fed Induction Machine Adjustable Speed (DFIM) 247 13.3 Synchronous Machine Adjustable Speed (FFIM) 252 14 Pumped Storage Machines – Ternary Units 257Manfred Sallaberger and Thomas Gaal 14.1 Ternary Units 257 15 Hydro-Mechanical Equipment 273Claudia Pollak-Reibenwein 15.1 Steel-lined Pressure Conduits 273 15.2 Typical Control and Shut-Off Devices for Pumped Storage Plants 284 16 Pumped Storage Machines - Hydraulic Short-circuit Operation 289Thomas Gaal and Manfred Sallaberger 16.1 Hydraulic Short-circuit Operation 289 Part III Mechanical Energy Storage, Compressed Air Energy Storage, and Flywheels 303 17 Compressed Air Energy Storage: Are the Market and Technical Knowledge Ready? 305Pierre Bérest, Benoît Brouard, Louis Londe, and Arnaud Réveillère 17.1 Introduction 305 17.2 Historical Developments 307 17.3 Challenges Raised by Air Storage in Salt Caverns 308 17.4 (Selected) Recent Projects 314 17.5 Business Case 316 17.6 Conclusion 320 18 The Geology, Historical Background, and Developments in CAES 323David J. Evans 18.1 Introduction 323 18.2 Operational Modes – Diabatic, Adiabatic, Isothermal (Heat), Isochoric, and Isobaric (Pressure) Operations 333 18.3 Brief Review of the Historical Origins of CAES – How It All Began and Where It Is Now 334 18.4 Overview of Underground (Geological) Storage Options 341 18.5 Summary 376 19 Compressed Air Energy Storage in Aquifer and Depleted Gas Storage Reservoirs 391Michael J. King and George Moridis 19.1 Introduction 391 19.2 History of CAES Development 391 19.3 Power Train Requirements 393 19.4 How Does a CAES Energy Storage System Work? Matching the Storage System to CAES Power Train Requirements 394 19.5 Advantages and Disadvantages of CAES in Aquifer Structures and Depleted Gas Reservoirs 401 19.6 CAES Storage System Design Tools, Development, and Operation 403 19.7 Summary 405 20 Open Accumulator Isothermal Compressed Air Energy Storage (OA-ICAES) System 409Perry Y. Li, Eric Loth, Chao (Chris) Qin, Terrence W. Simon, and James D. Van de Ven 20.1 Introduction 409 20.2 Open Accumulator Isothermal Compressed Air Energy Storage (OA-ICAES) System Architecture 412 20.3 Liquid Piston Isothermal Compressor/Expander 413 20.4 Using Water Droplet Spray to Enhance Heat Transfer 425 20.5 Systems and Control 429 20.6 Discussion 432 20.7 Conclusions 434 Part IV Chemical Energy Storage 439 21 Hydrogen (or Syngas) Generation – Solar Thermal 441Jonathan Scheffe, Dylan McCord, and Diego Gordon 21.2 Solar Thermochemical Processes 447 22 Power-to-Liquids – Conversion of CO2 and Renewable H2 to Methanol 489Robin J. White 22.1 Introduction 489 22.2 Methanol Synthesis 494 22.3 Catalysts for Methanol Synthesis 496 22.4 Transitioning to Sustainable Methanol Production 500 22.5 Elaboration of a Methanol Economy 505 22.6 Conclusion and Summary 512 23 Hydrogenation Energy Recovery – Small Molecule Liquid Organic Hydrogen Carriers and Catalytic Dehydrogenation 521Jong-Hoo Choi, Dominic van der Waals, Thomas Zell, Robert Langer, and Martin H.G. Prechtl 23.1 Introduction 521 23.2 Methanol (CH3OH) 525 23.3 Formaldehyde/Methanediol (CH2O/CH2OHOH) 535 23.4 Formic Acid (HCO2H) 537 23.5 Other Alcohols, Diols, and Amino Alcohols 544 23.6 Summary and Outlook 550 24 Hydrogen Energy Recovery – H2-Based Fuel Cells 559Nada Zamel and Ulf Groos 24.1 Introduction 559 24.2 Polymer Electrolyte Membrane Fuel Cells 561 24.3 Topics of Research 569 24.4 Characterization Techniques 577 24.5 Conclusions 582 Part V Thermal Energy Storage 589 25 Thermal Energy Storage – An Introduction 591Andreas Hauer and Eberhard Laevemann 25.1 Introduction 591 25.2 Characteristic Parameters of Thermal Energy Storage 592 25.3 The Physical Storage Principle – Sensible, Latent, and Thermochemical 596 25.4 Design of a Thermal Energy Storage and Integration into an Energy System 600 25.5 Thermal Energy Storage Classification 602 25.6 Conclusions 604 26 New Phase Change Materials for Latent Heat Storage 607Elena Palomo del Barrio and Fouzia Achchaq 26.1 Introduction 607 26.2 Fundamentals, Materials, Groups, and Properties 608 26.3 Currently Used and Emerging Phase Change Materials 614 26.4 Approaches to Improve PCMs’ Properties 621 26.5 Commercial Status 627 26.6 Future Development Directions 627 27 Sorption Material Developments for TES Applications 631Alenka Ristić 27.1 Introduction 631 27.2 Sorption Materials 635 27.3 Future Developments 647 28 Vacuum Super Insulated Thermal Storage Systems for Buildings and Industrial Applications 655Thomas Beikircher and Matthias Rottmann 28.1 Introduction 655 28.2 VSI with Expanded Perlite for Highly Efficient and Economical Thermal Storages 658 28.3 Storage Media for Medium and High Temperatures 669 28.4 VSI and VSI Storages in Industrial Applications 671 28.5 Conclusions 672 29 Heat Transfer Enhancement for Latent Heat Storage Components 675Jaume Gasia, Laia Miró, Alvaro de Gracia, and Luisa F. Cabeza 29.1 Introduction 675 29.2 Heat Transfer Enhancement Techniques 676 29.3 Technology Development and Commercial Status 690 30 Reactor Design for Thermochemical Energy Storage Systems 695Wim Van Helden 30.1 Requirements for TCM Reactors 695 30.2 Charging and Discharging Processes in TCM Reactors 695 30.3 Types of Reactors and Examples of Design Solutions 699 30.4 Conclusions and Outlook 702 31 Phase Change Materials in Buildings – State of the Art 705Thomas Haussmann, Tabea Obergfell, and Stefan Gschwander 31.1 Introduction 705 31.2 Materials 707 31.3 Example of Building Integration of PCM 710 31.4 Planning Boundary Conditions 722 31.5 Long Term Experience 725 32 Industrial Applications of Thermal Energy Storage Systems 729Viktoria Martin and Ningwei Justin Chiu 32.1 Why Thermal Energy Storage in Industry? 729 32.2 Integration of TES in Industrial Scale Applications 734 32.3 Mobile TES in Innovative Energy Distribution 742 32.4 Concluding Remarks 744 33 Economy of Thermal Energy Storage Systems in Different Applications 749Christoph Rathgeber, Eberhard Lävemann, and Andreas Hauer 33.1 Introduction 749 33.2 Methods to Evaluate Thermal Energy Storage Economics 749 33.3 Comparison of Acceptable and Realized Storage Capacity Costs in Different TES Applications 752 33.4 Discussion on the Major Influencing Factors on the Economics of Thermal Energy Storage 757 33.5 Conclusions 758 Part VI Energy Storage Concepts, Regulations, and Markets 761 34 Energy Storage Can Stop Global Warming 763Halime Ö. Paksoy 34.1 Introduction 763 34.2 Energy Storage Technologies 765 34.3 Energy Storage Systems 766 34.4 The Potentials of Energy Storage 767 34.5 Policy Frameworks 771 34.6 Cross-cutting Aspects 772 34.7 Conclusions 773 35 Energy Storage Participation in Electricity Markets 775Tom Brijs, Andreas Belderbos, Kris Kessels, Daan Six, Ronnie Belmans, and Frederik Geth 35.1 Introduction 775 35.2 Classification of Energy Storage Options 777 35.3 Techno-economic Energy Storage Characteristics 782 35.4 Energy Storage Applications 784 35.5 Interaction Market Opportunities and Technical Characteristics –Illustrative Case Studies 788 35.6 Conclusions 792 36 Public Perceptions and Acceptance of Energy Storage Technologies 795Per Alex Soerensen 36.1 Introduction 795 36.2 Why Resistance? 795 36.3 Who Will Resist? 796 36.4 Cases 796 36.5 Drivers for Positive Public Perceptions and Acceptance 798 36.6 Is There a Manual for Citizen Involvement? 800 36.7 Perception of Acceptance of Energy Storage Technologies 801 37 Business Case for Energy Storage in Japan 805Masaya Okumaya 37.1 Energy Consumption in Japan 805 37.2 Electricity Situation 806 37.3 Climate Condition and Cooling/heating Load 807 37.4 Situation of Thermal Energy Storage (TES) Spread 808 37.5 Variation of TES 809 37.6 Water Storage 810 37.7 Ice Storage 811 38 Energy Storage in the Electricity Market: Business Models and Regulatory Framework in Germany 817Helena Teschner 38.1 Introduction 818 38.2 Business Models in Germany 819 38.3 Legal and Regulatory Framework – Opportunities and Barriers 829 38.4 Conclusion and Outlook 835 39 Integration of Renewable Energy by Distributed Energy Storages 839Christian Doetsch and Anna Grevé 39.1 Introduction 839 39.2 Usage of Variable Renewable Energies and Induced Problems 839 39.3 Energy Balancing Technologies and Options 843 39.4 Applications for Electric Energy Storages (Adapted from [4]) 845 39.5 Business Cases for Electric Energy Storages 847 39.6 Distributed Storage Concepts 848 39.7 Summary 849 40 Thermal Storages and Power to Heat 851Per Alex Soerensen 40.1 Introduction 851 40.2 Why Power to Heat? 851 40.3 Technologies for Power to Heat 853 40.4 Examples of Power to Heat Concepts 865 40.5 The Future. Smart Energy Systems 868 Index 871

Read more less

Book SynopsisA concise, in-depth introduction to active disturbance rejection control theory for nonlinear systems, with numerical simulations and clearly worked out equations Provides the fundamental, theoretical foundation for applications of active disturbance rejection control Features numerical simulations and clearly worked out equations Highlights the advantages of active disturbance rejection control, including small overshooting, fast convergence, and energy savings Table of ContentsPreface ix 1 Introduction 1 1.1 Problem Statement 1 1.2 Overview of Engineering Applications 6 1.3 Preliminaries 9 1.3.1 Canonical Form of ADRC 9 1.3.2 Stability for Nonlinear Systems 18 1.3.3 Stability of Linear Systems 24 1.3.4 Finite-Time Stability of Continuous System 27 1.3.5 Stability of Discontinuous Systems 32 1.3.6 Proof of Theorem 1.3.11 34 1.4 Remarks and Bibliographical Notes 50 2 The Tracking Differentiator (TD) 53 2.1 Linear Tracking Differentiator 55 2.2 Nonlinear Tracking Differentiator 59 2.2.1 Second-Order Nonlinear Tracking Differentiator 60 2.2.2 High-Order Nonlinear Tracking Differentiator 64 2.3 Finite-Time Stable System-Based Tracking Differentiator 69 2.3.1 Convergence of Finite-Time Stable System-Based TD 70 2.3.2 A Second-Order Finite-Time Stable Tracking Differentiator 75 2.4 Illustrative Examples and Applications 77 2.4.1 Comparison of Three Differentiators 77 2.4.2 Applications to Frequency Online Estimation 81 2.4.3 Application to the Boundary Stabilization of Wave Equation 85 2.5 Summary and Open Problems 88 2.6 Remarks and Bibliographical Notes 89 3 Extended State Observer 93 3.1 Linear Extended State Observer for SISO Systems 94 3.2 Nonlinear Extended State Observer for SISO Systems 100 3.2.1 Nonlinear ESO for SISO Systems 101 3.2.2 Some Special ESO 109 3.3 The ESO for SISO Systems with Time-Varying Gain 119 3.4 The ESO for MIMO Systems with Uncertainty 133 3.4.1 ESO for Systems with Total Disturbance 133 3.4.2 ESO for Systems with External Disturbance Only 141 3.4.3 Examples and Numerical Simulations 144 3.5 Summary and Open Problems 150 3.6 Remarks and Bibliographical Notes 153 4 The Active Disturbance Rejection Control 155 4.1 Linear ADRC for SISO Systems 157 4.1.1 Global Convergence of Linear ADRC for SISO Systems 157 4.1.2 Global Convergence for Systems with External Disturbance Only 167 4.1.3 Semi-Global Convergence of LADRC 176 4.1.4 Numerical Simulations 183 4.2 Nonlinear ADRC for SISO Systems 187 4.2.1 Global ADRC for SISO Systems with Total Disturbance 187 4.2.2 Global ADRC for SISO System with External Disturbance Only 195 4.2.3 Semi-global ADRC for SISO System with Vast Uncertainty 203 4.2.4 Examples and Numerical Simulations 204 4.3 ADRC with Time-Varying Tuning Parameter 206 4.4 Nonlinear ADRC for MIMO Systems with Vast Uncertainty 228 4.4.1 Semi-Global ADRC for MIMO Systems with Uncertainty 231 4.4.2 Global ADRC for MIMO Systems with Uncertainty 238 4.4.3 Global ADRC for MIMO Systems with External Disturbance Only 245 4.4.4 Numerical Simulations 250 4.5 IMP Versus ADRC 252 4.6 HGC and SMC Versus ADRC 263 4.7 Applications to PMSMs 267 4.8 Application to Wave Equation with Uncertainty 270 4.8.1 Control Design 271 4.8.2 Proof of Theorem 4.8.1 279 4.9 Summary and Open Problems 287 4.10 Remarks and Bibliographical Notes 289 5 ADRC for Lower Triangular Nonlinear Systems 291 5.1 ESO for Lower Triangular Systems 291 5.1.1 Constant High-Gain ESO 292 5.1.2 Time-Varying Gain ESO 301 5.1.3 Numerical Simulation 306 5.2 Stabilization of Lower Triangular Systems by ADRC 312 5.2.1 ADRC with Constant Gain ESO 313 5.2.2 ADRC with Time-Varying Gain ESO 327 5.3 Numerical Simulations 331 5.4 Summary and Open Problems 336 5.5 Remarks and Bibliographical Notes 338 References 341 Index 349

Read more less

Book SynopsisPHOTOVOLTAIC MANUFACTURING This book covers the state-of-the-art and the fundamentals of silicon wafer solar cells manufacturing, written by world-class researchers and experts in the field. High quality and economic photovoltaic manufacturing is central to realizing reliable photovoltaic power supplies at reasonable cost. While photovoltaic silicon wafer manufacturing is at a mature, industrial and mass production stage, knowing and applying the fundamentals in solar manufacturing is essential to anyone working in this field. This is the first book on photovoltaic wet processing for silicon wafers, both mono- and multi-crystalline. The comprehensive book provides information for process, equipment, and device engineers and researchers in the solar manufacturing field. The authors of the chapters are world-class researchers and experts in their field of endeavor. The fundamentals of wet processing chemistry are introduced, covering etching, texturing, cleaning an

Read more less

Book SynopsisA synergy of techniques on hybrid intelligence for real-life image analysis Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding.Table of ContentsEditor Biographies xvii List of Contributors xxi Foreword xxvii Preface xxxi About the Companion website xxxv 1 Multilevel Image Segmentation UsingModified Genetic Algorithm (MfGA)-based Fuzzy C-Means 1Sourav De, Sunanda Das, Siddhartha Bhattacharyya, and Paramartha Dutta 1.1 Introduction 1 1.2 Fuzzy C-Means Algorithm 5 1.3 Modified Genetic Algorithms 6 1.4 Quality Evaluation Metrics for Image Segmentation 8 1.4.1 Correlation Coefficient 8 1.4.2 Empirical Measure Q(I) 8 1.5 MfGA-Based FCM Algorithm 9 1.6 Experimental Results and Discussion 11 1.7 Conclusion 22 References 22 2 Character Recognition Using Entropy-Based Fuzzy C-Means Clustering 25B. Kondalarao, S. Sahoo, and D.K. Pratihar 2.1 Introduction 25 2.2 Tools and Techniques Used 27 2.2.1 Fuzzy Clustering Algorithms 27 2.2.1.1 Fuzzy C-means Algorithm 28 2.2.1.2 Entropy-based Fuzzy Clustering 29 2.2.1.3 Entropy-based Fuzzy C-Means Algorithm 29 2.2.2 Sammon’s Nonlinear Mapping 30 2.3 Methodology 31 2.3.1 Data Collection 31 2.3.2 Preprocessing 31 2.3.3 Feature Extraction 32 2.3.4 Classification and Recognition 34 2.4 Results and Discussion 34 2.5 Conclusion and Future Scope ofWork 38 References 39 Appendix 41 3 A Two-Stage Approach to Handwritten Indic Script Identification 47Pawan Kumar Singh, Supratim Das, Ram Sarkar, andMita Nasipuri 3.1 Introduction 47 3.2 Review of RelatedWork 48 3.3 Properties of Scripts Used in the PresentWork 51 3.4 ProposedWork 52 3.4.1 DiscreteWavelet Transform 53 3.4.1.1 HaarWavelet Transform 55 3.4.2 Radon Transform (RT) 57 3.5 Experimental Results and Discussion 63 3.5.1 Evaluation of the Present Technique 65 3.5.1.1 Statistical Significance Tests 66 3.5.2 Statistical Performance Analysis of SVM Classifier 68 3.5.3 Comparison with Other RelatedWorks 71 3.5.4 Error Analysis 73 3.6 Conclusion 74 Acknowledgments 75 References 75 4 Feature Extraction and Segmentation Techniques in a Static Hand Gesture Recognition System 79Subhamoy Chatterjee, Piyush Bhandari, and Mahesh Kumar Kolekar 4.1 Introduction 79 4.2 Segmentation Techniques 81 4.2.1 Otsu Method for Gesture Segmentation 81 4.2.2 Color Space–Based Models for Hand Gesture Segmentation 82 4.2.2.1 RGB Color Space–Based Segmentation 82 4.2.2.2 HSI Color Space–Based Segmentation 83 4.2.2.3 YCbCr Color Space–Based Segmentation 83 4.2.2.4 YIQ Color Space–Based Segmentation 83 4.2.3 Robust Skin Color Region Detection Using K-Means Clustering and Mahalanobish Distance 84 4.2.3.1 Rotation Normalization 85 4.2.3.2 Illumination Normalization 85 4.2.3.3 Morphological Filtering 85 4.3 Feature Extraction Techniques 86 4.3.1 Theory of Moment Features 86 4.3.2 Contour-Based Features 88 4.4 State of the Art of Static Hand Gesture Recognition Techniques 89 4.4.1 Zoning Methods 90 4.4.2 F-Ratio-BasedWeighted Feature Extraction 90 4.4.3 Feature Fusion Techniques 91 4.5 Results and Discussion 92 4.5.1 Segmentation Result 93 4.5.2 Feature Extraction Result 94 4.6 Conclusion 97 4.6.1 FutureWork 99 Acknowledgment 99 References 99 5 SVM Combination for an Enhanced Prediction ofWriters’ Soft Biometrics 103Nesrine Bouadjenek, Hassiba Nemmour, and Youcef Chibani 5.1 Introduction 103 5.2 Soft Biometrics and Handwriting Over Time 104 5.3 Soft Biometrics Prediction System 106 5.3.1 Feature Extraction 107 5.3.1.1 Local Binary Patterns 107 5.3.1.2 Histogram of Oriented Gradients 108 5.3.1.3 Gradient Local Binary Patterns 108 5.3.2 Classification 109 5.3.3 Fuzzy Integrals–Based Combination Classifier 111 5.3.3.1 g�� Fuzzy Measure 111 5.3.3.2 Sugeno’s Fuzzy Integral 113 5.3.3.3 Fuzzy Min-Max 113 5.4 Experimental Evaluation 113 5.4.1 Data Sets 113 5.4.1.1 IAM Data Set 113 5.4.1.2 KHATT Data Set 114 5.4.2 Experimental Setting 114 5.4.3 Gender Prediction Results 117 5.4.4 Handedness Prediction Results 117 5.4.5 Age Prediction Results 118 5.5 Discussion and Performance Comparison 118 5.6 Conclusion 120 References 121 6 Brain-Inspired Machine Intelligence for Image Analysis: Convolutional Neural Networks 127Siddharth Srivastava and Brejesh Lall 6.1 Introduction 127 6.2 Convolutional Neural Networks 129 6.2.1 Building Blocks 130 6.2.1.1 Perceptron 134 6.2.2 Learning 135 6.2.2.1 Gradient Descent 136 6.2.2.2 Back-Propagation 136 6.2.3 Convolution 139 6.2.4 Convolutional Neural Networks:The Architecture 141 6.2.4.1 Convolution Layer 142 6.2.4.2 Pooling Layer 145 6.2.4.3 Dense or Fully Connected Layer 146 6.2.5 Considerations in Implementation of CNNs 146 6.2.6 CNN in Action 147 6.2.7 Tools for Convolutional Neural Networks 148 6.2.8 CNN Coding Examples 148 6.2.8.1 MatConvNet 148 6.2.8.2 Visualizing a CNN 149 6.2.8.3 Image Category Classification Using Deep Learning 153 6.3 Toward Understanding the Brain, CNNs, and Images 157 6.3.1 Applications 157 6.3.2 Case Studies 158 6.4 Conclusion 159 References 159 7 Human Behavioral Analysis Using Evolutionary Algorithms and Deep Learning 165Earnest Paul Ijjina and Chalavadi Krishna Mohan 7.1 Introduction 165 7.2 Human Action Recognition Using Evolutionary Algorithms and Deep Learning 167 7.2.1 Evolutionary Algorithms for Search Optimization 168 7.2.2 Action Bank Representation for Action Recognition 168 7.2.3 Deep Convolutional Neural Network for Human Action Recognition 169 7.2.4 CNN Classifier Optimized Using Evolutionary Algorithms 170 7.3 Experimental Study 170 7.3.1 Evaluation on the UCF50 Data Set 170 7.3.2 Evaluation on the KTH Video Data Set 172 7.3.3 Analysis and Discussion 176 7.3.4 Experimental Setup and Parameter Optimization 177 7.3.5 Computational Complexity 182 7.4 Conclusions and FutureWork 183 References 183 8 Feature-Based Robust Description andMonocular Detection: An Application to Vehicle Tracking 187Ramazan Yíldíz and Tankut Acarman 8.1 Introduction 187 8.2 Extraction of Local Features by SIFT and SURF 188 8.3 Global Features: Real-Time Detection and Vehicle Tracking 190 8.4 Vehicle Detection and Validation 194 8.4.1 X-Analysis 194 8.4.2 Horizontal Prominent Line Frequency Analysis 195 8.4.3 Detection History 196 8.5 Experimental Study 197 8.5.1 Local Features Assessment 197 8.5.2 Global Features Assessment 197 8.5.3 Local versus Global Features Assessment 201 8.6 Conclusions 201 References 202 9 A GIS Anchored Technique for Social Utility Hotspot Detection 205Anirban Chakraborty, J.K.Mandal, Arnab Patra, and JayatraMajumdar 9.1 Introduction 205 9.2 The Technique 207 9.3 Case Study 209 9.4 Implementation and Results 221 9.5 Analysis and Comparisons 224 9.6 Conclusions 229 Acknowledgments 229 References 230 10 Hyperspectral Data Processing: Spectral Unmixing, Classification, and Target Identification 233Vaibhav Lodhi, Debashish Chakravarty, and PabitraMitra 10.1 Introduction 233 10.2 Background and Hyperspectral Imaging System 234 10.3 Overview of Hyperspectral Image Processing 236 10.3.1 Image Acquisition 237 10.3.2 Calibration 237 10.3.3 Spatial and Spectral preprocessing 238 10.3.4 Dimension Reduction 239 10.3.4.1 Transformation-Based Approaches 239 10.3.4.2 Selection-Based Approaches 239 10.3.5 postprocessing 240 10.4 Spectral Unmixing 240 10.4.1 Unmixing Processing Chain 240 10.4.2 Mixing Model 241 10.4.2.1 Linear Mixing Model (LMM) 242 10.4.2.2 Nonlinear Mixing Model 242 10.4.3 Geometrical-Based Approaches to Linear Spectral Unmixing 243 10.4.3.1 Pure Pixel-Based Techniques 243 10.4.3.2 Minimum Volume-Based Techniques 244 10.4.4 Statistics-Based Approaches 244 10.4.5 Sparse Regression-Based Approach 245 10.4.5.1 Moore–Penrose Pseudoinverse (MPP) 245 10.4.5.2 Orthogonal Matching Pursuit (OMP) 246 10.4.5.3 Iterative Spectral Mixture Analysis (ISMA) 246 10.4.6 Hybrid Techniques 246 10.5 Classification 247 10.5.1 Feature Mining 247 10.5.1.1 Feature Selection (FS) 248 10.5.1.2 Feature Extraction 248 10.5.2 Supervised Classification 248 10.5.2.1 Minimum Distance Classifier 249 10.5.2.2 Maximum Likelihood Classifier (MLC) 250 10.5.2.3 Support Vector Machines (SVMs) 250 10.5.3 Hybrid Techniques 250 10.6 Target Detection 251 10.6.1 Anomaly Detection 251 10.6.1.1 RX Anomaly Detection 252 10.6.1.2 Subspace-Based Anomaly Detection 253 10.6.2 Signature-Based Target Detection 253 10.6.2.1 Euclidean distance 254 10.6.2.2 Spectral Angle Mapper (SAM) 254 10.6.2.3 Spectral Matched Vilter (SMF) 254 10.6.2.4 Matched Subspace Detector (MSD) 255 10.6.3 Hybrid Techniques 255 10.7 Conclusions 256 References 256 11 A Hybrid Approach for Band Selection of Hyperspectral Images 263Aditi Roy Chowdhury, Joydev Hazra, and Paramartha Dutta 11.1 Introduction 263 11.2 Relevant Concept Revisit 266 11.2.1 Feature Extraction 266 11.2.2 Feature Selection Using 2D PCA 266 11.2.3 Immune Clonal System 267 11.2.4 Fuzzy KNN 268 11.3 Proposed Algorithm 271 11.4 Experiment and Result 271 11.4.1 Description of the Data Set 272 11.4.2 Experimental Details 274 11.4.3 Analysis of Results 275 11.5 Conclusion 278 References 279 12 Uncertainty-Based Clustering Algorithms for Medical Image Analysis 283Deepthi P. Hudedagaddi and B.K. Tripathy 12.1 Introduction 283 12.2 Uncertainty-Based Clustering Algorithms 283 12.2.1 Fuzzy C-Means 284 12.2.2 Rough Fuzzy C-Means 285 12.2.3 Intuitionistic Fuzzy C-Means 285 12.2.4 Rough Intuitionistic Fuzzy C-Means 286 12.3 Image Processing 286 12.4 Medical Image Analysis with Uncertainty-Based Clustering Algorithms 287 12.4.1 FCM with Spatial Information for Image Segmentation 287 12.4.2 Fast and Robust FCM Incorporating Local Information for Image Segmentation 290 12.4.3 Image Segmentation Using Spatial IFCM 291 12.4.3.1 Applications of Spatial FCM and Spatial IFCM on Leukemia Images 292 12.5 Conclusions 293 References 293 13 An Optimized Breast Cancer Diagnosis SystemUsing a Cuckoo Search Algorithm and Support Vector Machine Classifier 297Manoharan Prabukumar, Loganathan Agilandeeswari, and Arun Kumar Sangaiah 13.1 Introduction 297 13.2 Technical Background 301 13.2.1 Morphological Segmentation 301 13.2.2 Cuckoo Search Optimization Algorithm 302 13.2.3 Support Vector Machines 303 13.3 Proposed Breast Cancer Diagnosis System 303 13.3.1 Preprocessing of Breast Cancer Image 303 13.3.2 Feature Extraction 304 13.3.2.1 Geometric Features 304 13.3.2.2 Texture Features 305 13.3.2.3 Statistical Features 306 13.3.3 Features Selection 306 13.3.4 Features Classification 307 13.4 Results and Discussions 307 13.5 Conclusion 310 13.6 FutureWork 310 References 310 14 Analysis of Hand Vein Images Using Hybrid Techniques 315R. Sudhakar, S. Bharathi, and V. Gurunathan 14.1 Introduction 315 14.2 Analysis of Vein Images in the Spatial Domain 318 14.2.1 Preprocessing 318 14.2.2 Feature Extraction 319 14.2.3 Feature-Level Fusion 320 14.2.4 Score Level Fusion 320 14.2.5 Results and Discussion 322 14.2.5.1 Evaluation Metrics 323 14.3 Analysis of Vein Images in the Frequency Domain 326 14.3.1 Preprocessing 326 14.3.2 Feature Extraction 326 14.3.3 Feature-Level Fusion 330 14.3.4 Support Vector Machine Classifier 331 14.3.5 Results and Discussion 331 14.4 Comparative Analysis of Spatial and Frequency Domain Systems 332 14.5 Conclusion 335 References 335 15 Identification of Abnormal Masses in Digital Mammogram Using Statistical Decision Making 339Indra Kanta Maitra and Samir Kumar Bandyopadhyay 15.1 Introduction 339 15.1.1 Breast Cancer 339 15.1.2 Computer-Aided Detection/Diagnosis (CAD) 340 15.1.3 Segmentation 340 15.2 PreviousWorks 341 15.3 Proposed Method 343 15.3.1 Preparation 343 15.3.2 Preprocessing 345 15.3.2.1 Image Enhancement and Edge Detection 346 15.3.2.2 Isolation and Suppression of Pectoral Muscle 348 15.3.2.3 Breast Contour Detection 351 15.3.2.4 Anatomical Segmentation 353 15.3.3 Identification of Abnormal Region(s) 354 15.3.3.1 Coloring of Regions 354 15.3.3.2 Statistical Decision Making 355 15.4 Experimental Result 358 15.4.1 Case Study with Normal Mammogram 358 15.4.2 Case Study with Abnormalities Embedded in Fatty Tissues 358 15.4.3 Case Study with Abnormalities Embedded in Fatty-Fibro-Glandular Tissues 359 15.4.4 Case Study with Abnormalities Embedded in Dense-Fibro-Glandular Tissues 359 15.5 Result Evaluation 360 15.5.1 Statistical Analysis 361 15.5.2 ROC Analysis 361 15.5.3 Accuracy Estimation 365 15.6 Comparative Analysis 366 15.7 Conclusion 366 Acknowledgments 366 References 367 16 Automatic Detection of Coronary Artery Stenosis Using Bayesian Classification and Gaussian Filters Based on Differential Evolution 369Ivan Cruz-Aceves, Fernando Cervantes-Sanchez, and Arturo Hernandez-Aguirre 16.1 Introduction 369 16.2 Background 370 16.2.1 Gaussian Matched Filters 371 16.2.2 Differential Evolution 371 16.2.2.1 Example: Global Optimization of the Ackley Function 373 16.2.3 Bayesian Classification 375 16.2.3.1 Example: Classification Problem 375 16.3 Proposed Method 377 16.3.1 Optimal Parameter Selection of GMF Using Differential Evolution 377 16.3.2 Thresholding of the Gaussian Filter Response 378 16.3.3 Stenosis Detection Using Second-Order Derivatives 378 16.3.4 Stenosis Detection Using Bayesian Classification 379 16.4 Computational Experiments 381 16.4.1 Results of Vessel Detection 382 16.4.2 Results of Vessel Segmentation 382 16.4.3 Evaluation of Detection of Coronary Artery Stenosis 384 16.5 Concluding Remarks 386 Acknowledgment 388 References 388 17 Evaluating the Efficacy of Multi-resolution Texture Features for Prediction of Breast Density UsingMammographic Images 391Kriti, Harleen Kaur, and Jitendra Virmani 17.1 Introduction 391 17.1.1 Comparison of Related Methods with the Proposed Method 397 17.2 Materials and Methods 398 17.2.1 Description of Database 398 17.2.2 ROI Extraction Protocol 398 17.2.3 Workflow for CAD System Design 398 17.2.3.1 Feature Extraction 400 17.2.3.2 Classification 407 17.3 Results 410 17.3.1 Results Based on Classification Performance of the Classifiers (Classification Accuracy and Sensitivity) for Each Class 411 17.3.1.1 Experiment I: To Determine the Performance of Different FDVs Using SVM Classifier 411 17.3.1.2 Experiment II: To Determine the Performance of Different FDVs Using SSVM Classifier 412 17.3.2 Results Based on Computational Efficiency of Classifiers for Predicting 161 Instances of Testing Dataset 412 17.4 Conclusion and Future Scope 413 References 415 Index 423

Read more less

Book SynopsisA guide to all practical aspects of building, implementing, managing, and maintaining MPC applications in industrial plants Multivariable Predictive Control: Applications in Industry provides engineers with a thorough understanding of all practical aspects of multivariate predictive control (MPC) applications, as well as expert guidance on how to derive maximum benefit from those systems. Short on theory and long on step-by-step information, it covers everything plant process engineers and control engineers need to know about building, deploying, and managing MPC applications in their companies. MPC has more than proven itself to be one the most important tools for optimising plant operations on an ongoing basis. Companies, worldwide, across a range of industries are successfully using MPC systems to optimise materials and utility consumption, reduce waste, minimise pollution, and maximise production. Unfortunately, due in part to the lack of practical reTable of ContentsFigure List xix Table List xxi Preface xxiii 1 Introduction of Model Predictive Control 1 1.1 Purpose of Process Control in Chemical Process Industries (CPI) 1 1.2 Shortcomings of Simple Regulatory PID Control 2 1.3 What Is Multivariable Model Predictive Control? 3 1.4 Why Is a Multivariable Model Predictive Optimizing Controller Necessary? 4 1.5 Relevance of Multivariable Predictive Control (MPC) in Chemical Process Industry in Today’s Business Environment 6 1.6 Position of MPC in Control Hierarchy 6 1.6.1 Regulatory PID Control Layer 6 1.6.2 Advance Regulatory Control (ARC) Layer 8 1.6.3 Multivariable Model‐Based Control 8 1.6.4 Economic Optimization Layer 8 1.6.4.1 First Layer of Optimization 8 1.6.4.2 Second Layer of Optimization 9 1.6.4.3 Third Layer of Optimization 9 1.7 Advantage of Implementing MPC 10 1.8 How Does MPC Extract Benefit? 13 1.8.1 MPC Inherent Stabilization Effect 13 1.8.2 Process Interactions 14 1.8.3 Multiple Constraints 15 1.8.4 Intangible Benefits of MPC 17 1.9 Application of MPC in Oil Refinery, Petrochemical, Fertilizer, and Chemical Plants, and Related Benefits 17 2 Theoretical Base of MPC 23 2.1 Why MPC? 23 2.2 Variables Used in MPC 25 2.2.1 Manipulated Variables (MVs) 25 2.2.2 Controlled Variables (CVs) 25 2.2.3 Disturbance Variables (DVs) 25 2.3 Features of MPC 26 2.3.1 MPC Is a Multivariable Controller 26 2.3.2 MPC Is a Model Predictive Controller 26 2.3.3 MPC Is a Constrained Controller 26 2.3.4 MPC Is an Optimizing Controller 27 2.3.5 MPC Is a Rigorous Controller 27 2.4 Brief Introduction to Model Predictive Control Techniques 27 2.4.1 Simplified Dynamic Control Strategy of MPC 28 2.4.2 Step 1: Read Process Input and Output 29 2.4.3 Step 2: Prediction of CVs 30 2.4.3.1 Building Dynamic Process Model 30 2.4.3.2 How MPC Predicts the Future 32 2.4.4 Step 3: Model Reconciliation 33 2.4.5 Step 4: Determine the Size of the Control Process 34 2.4.6 Step 5: Removal of Ill‐Conditioned Problems 34 2.4.7 Step 6: Optimum Steady‐State Targets 35 2.4.8 Step 7: Develop Detailed Plan of MV Movement 36 3 Historical Development of Different MPC Technology 43 3.1 History of MPC Technology 43 3.1.1 Pre‐Era 43 3.1.1.1 Developer 43 3.1.1.2 Motivation 44 3.1.1.3 Limitations 44 3.1.2 First Generation of MPC (1970–1980) 44 3.1.2.1 Characteristics of First‐Generation MPC Technology 44 3.1.2.2 IDCOM Algorithm and Its Features 45 3.1.2.3 DMC Algorithm and Its Features 46 3.1.3 Second‐Generation MPC (1980–1985) 46 3.1.4 Third‐Generation MPC (1985–1990) 47 3.1.4.1 Distinguishing Features of Third‐Generation MPC Algorithm 48 3.1.4.2 Distinguishing Features of the IDCOM‐M Algorithm 49 3.1.4.3 Evolution of SMOC 50 3.1.4.4 Distinctive Features of SMOC 50 3.1.5 Fourth‐Generation MPC (1990–2000) 50 3.1.5.1 Distinctive Features of Fourth‐Generation MPC 51 3.1.6 Fifth‐Generation MPC (2000–2015) 51 3.2 Points to Consider While Selecting an MPC 52 4 MPC Implementation Steps 55 4.1 Implementing a MPC Controller 55 4.1.1 Step 1: Preliminary Cost–Benefit Analysis 55 4.1.2 Step 2: Assessment of Base Control Loops 55 4.1.3 Step 3: Functional Design of Controller 56 4.1.4 Step 4: Conduct the Preliminary Plant Test (Pre‐Stepping) 57 4.1.5 Step 5: Conduct the Plant Step Test 57 4.1.6 Step 6: Identify a Process Model 57 4.1.7 Step 7: Generate Online Soft Sensors or Virtual Sensors 58 4.1.8 Step 8: Perform Offline Controller Simulation/Tuning 58 4.1.9 Step 9: Commission the Online Controller 58 4.1.10 Step 10: Online MPC Controller Tuning 59 4.1.11 Step 11: Hold Formal Operator Training 59 4.1.12 Step 12: Performance Monitoring of MPC Controller 59 4.1.13 Step 13: Maintain the MPC Controller 60 4.2 Summary of Steps Involved in MPC Projects with Vendor 60 5 Cost–Benefit Analysis of MPC before Implementation 63 5.1 Purpose of Cost–Benefit Analysis of MPC before Implementation 63 5.2 Overview of Cost–Benefit Analysis Procedure 64 5.3 Detailed Benefit Estimation Procedures 65 5.3.1 Initial Screening for Suitability of Process to Implement MPC 65 5.3.2 Process Analysis and Economics Analysis 66 5.3.3 Understand the Constraints 67 5.3.4 Identify Qualitatively Potential Area of Opportunities 67 5.3.4.1 Example 1: Air Separation Plant 68 5.3.4.2 Example 2: Distillation Columns 69 5.3.5 Collect All Relevant Plant and Economic Data (Trends, Records) 69 5.3.6 Calculate the Standard Deviation and Define the Limit 69 5.3.7 Estimate the Stabilizing Effect of MPC and Shift in the Average 70 5.3.7.1 Benefit Estimation: When the Constraint Is Known 71 5.3.7.2 Benefit Estimation: When the Constraint Is Not Well Known or Changing 72 5.3.8 Estimate Change in Key Performance Parameters Such as Yield, Throughput, and Energy Consumption 72 5.3.8.1 Example: Ethylene Oxide Reactor 72 5.3.9 Identify How This Effect Translates to Plant Profit Margin 73 5.3.10 Estimate the Economic Value of the Effect 73 5.4 Case Studies 73 5.4.1 Case Study 1 73 5.4.1.1 Benefit Estimation Procedure 73 5.4.2 Case Study 2 74 5.4.2.1 Benefit Estimation Procedure 74 6 Assessment of Regulatory Base Control Layer in Plants 77 6.1 Failure Mode of Control Loops and Their Remedies 77 6.2 Control Valve Problems 77 6.2.1 Improper Valve Sizing 78 6.2.1.1 How to Detect a Particular Control Valve Sizing Problem 78 6.2.2 Valve Stiction 79 6.2.2.1 What Is Control Valve Stiction? 79 6.2.2.2 How to Detect Control Valve Stiction Online 80 6.2.2.3 Combating Stiction 80 6.2.2.4 Techniques for Combating Stiction Online 80 6.2.3 Valve Hysteresis and Backlash 81 6.3 Sensor Problems 82 6.3.1 Noisy 82 6.3.2 Flatlining 82 6.3.3 Scale/Range 82 6.3.4 Calibration 82 6.3.5 Overfiltered 83 6.4 Controller Problems 83 6.4.1 Poor Tuning and Lack of Maintenance 83 6.4.2 Poor or Missing Feedforward Compensation 83 6.4.3 Inappropriate Control Structure 84 6.5 Process‐Related Problems 84 6.5.1 Problems of Variable Gain 84 6.5.2 Oscillations 84 6.5.2.1 Variable Valve Gain 85 6.5.2.2 Variable Process Gain 85 6.6 Human Factor 85 6.7 Control Performance Assessment/Monitoring 86 6.7.1 Available Software for Control Performance Monitoring 86 6.7.2 Basic Assessment Procedure 87 6.8 Commonly Used Control System Performance KPIs 87 6.8.1 Traditional Indices 88 6.8.1.1 Peak Overshoot Ratio (POR) 88 6.8.1.2 Decay Rate 88 6.8.1.3 Peak Time and Rise Time 88 6.8.1.4 Settling Time 88 6.8.1.5 Integral of Error Indexes 88 6.8.2 Simple Statistical Indices 88 6.8.2.1 Mean of Control Error (%) 89 6.8.2.2 Standard Deviation of Control Error (%) 89 6.8.2.3 Standard Variation of Control Error (%) 89 6.8.2.4 Standard Deviation of Controller Output (%) 89 6.8.2.5 Skewness of Control Error 89 6.8.2.6 Kurtosis of Control Error 89 6.8.2.7 Ratio of Standard of Control Error and Controller Output 89 6.8.2.8 Maximum Bicoherence 90 6.8.3 Business/Operational Metrics 90 6.8.3.1 Loop Health 90 6.8.3.2 Service Factor 90 6.8.3.3 Key Performance Indicators 90 6.8.3.4 Operational Performance Efficiency Factor 90 6.8.3.5 Overall Loop Performance Index 90 6.8.3.6 Controller Output Changes in Manual 90 6.8.3.7 Mode Changes 90 6.8.3.8 Totalized Valve Reversals and Valve Travel 90 6.8.3.9 Process Model Parameters 90 6.8.4 Advanced Indices 90 6.8.4.1 Harris Index 91 6.8.4.2 Nonlinearity Index 91 6.8.4.3 Oscillation‐Detection Indices 91 6.8.4.4 Disturbance Detection Indices 92 6.8.4.5 Autocorrelation Indices 92 6.9 Tuning for PID Controllers 92 6.9.1 Complications with Tuning PID Controllers 93 6.9.2 Loop Retuning 93 6.9.3 Classical Controller Tuning Algorithms 94 6.9.3.1 Controller Tuning Methods 94 6.9.3.2 Ziegler‐Nichols Tuning Method 94 6.9.3.3 Dahlin (Lambda) Tuning Method 94 6.9.4 Manual Controller Tuning Methods in Absence of Any Software 95 6.9.4.1 Pre‐Tuning 95 6.9.4.2 Bring in Baseline Parameters 97 6.9.4.3 Some Like It Simple 97 6.9.4.4 Tuning Cascade Control 98 7 Functional Design of MPC Controllers 101 7.1 What Is Functional Design? 101 7.2 Steps in Functional Design 102 7.2.1 Step 1: Define Process Control Objectives 102 7.2.1.1 Economic Objectives 102 7.2.1.2 Operating Objectives 103 7.2.1.3 Control Objectives 104 7.2.2 Step 2: Identify Process Constraints 104 7.2.2.1 Process Limitations 104 7.2.2.2 Safety Limitations 104 7.2.2.3 Process Instrument Limitations 105 7.2.2.4 Raw Material and Utility Supply Limitation 105 7.2.2.5 Product Limitations 105 7.2.3 Step 3: Define Controller Scope 105 7.2.4 Step 4: Select the Variables 106 7.2.4.1 Economics of the Unit 106 7.2.4.2 Constraints of the Unit 107 7.2.4.3 Control of the Unit 107 7.2.4.4 Manipulated Variables (MVs) 107 7.2.4.5 Controlled Variables (CVs) 107 7.2.4.6 Disturbance Variables (DVs) 108 7.2.4.7 Practical Guidelines for Variable Selections 108 7.2.5 Step 5: Rectify Regulatory Control Issues 109 7.2.5.1 Practical Guidelines for Changing Regulatory Controller Strategy 109 7.2.6 Step 6: Explore the Scope of Inclusions of Inferential Calculations 110 7.2.7 Step 7: Evaluate Potential Optimization Opportunity 110 7.2.7.1 Practical Guidelines for Finding out Optimization Opportunities 111 7.2.8 Step 8: Define LP or QP Objective Function 111 7.2.8.1 CDU Example 112 8 Preliminary Process Test and Step Test 113 8.1 Pre‐Stepping, or Preliminary Process Test 113 8.1.1 What Is Pre‐Stepping? 113 8.1.2 Objective of Pre‐Stepping 113 8.1.3 Prerequisites of Pre‐Stepping 113 8.1.4 Pre‐Stepping 114 8.2 Step Testing 115 8.2.1 What Is a Step Test? 115 8.2.2 What Is the Purpose of a Step Test? 115 8.2.3 Details of Step Testing 116 8.2.3.1 Administrative Aspects 116 8.2.3.2 Technical Aspects 116 8.2.4 Different Step‐Testing Method 117 8.2.4.1 Manual Step Testing 117 8.2.4.2 PRBS (Pseudo Random Binary Sequence) 117 8.2.4.3 General Guidelines of PRBS Test 117 8.2.5 Difference between Normal Step Testing and PRBS Testing 118 8.2.6 Which One to Choose? 118 8.2.7 Dos and Don’ts of Step Testing 118 8.3 Development of Step‐Testing Methodology over the Years 120 9 Model Building and System Identification 123 9.1 Introduction to Model Building 123 9.2 Key Issues in Model Identifications 124 9.2.1 Identification Test 124 9.2.2 Model Structure and Parameter Estimation 125 9.2.3 Order Selection 126 9.2.4 Model Validation 127 9.3 The Basic Steps of System Identification 127 9.3.1 Step 0: Experimental Design and Execution 128 9.3.2 Step 1: Plan the Case that Needs to Be Modeled 130 9.3.2.1 Action 1 130 9.3.2.2 Action 2 130 9.3.3 Step 2: Identify Good Slices of Data 130 9.3.3.1 Looking at the Data 131 9.3.4 Step 3: Pre‐Processing of Data 131 9.3.5 Step 4: Identification of Model Curve 132 9.3.5.1 Hybrid Approach to System Identification 132 9.3.5.2 Direct Modeling Approach of System Identification 133 9.3.5.3 Subspace Identification 134 9.3.5.4 Detailed Steps of Implementations 135 9.3.6 Step 5: Select Final Model 136 9.4 Model Structures 137 9.4.1 FIR Models 138 9.4.1.1 FIR Structures 138 9.4.2 Prediction Error Models (PEM Models) 139 9.4.2.1 PEM Structures 139 9.4.3 Model for Order and Variance Reduction 140 9.4.3.1 ARX Parametric Models (Discrete Time) 140 9.4.3.2 Output Error Models (Discrete Time) 140 9.4.3.3 Laplace Domain Parametric Models 141 9.4.3.4 Final Model Form 141 9.4.4 State‐Space Models 141 9.4.5 How to Know Which Structure and Method to Use 142 9.5 Common Features of Commercial Identification Packages 142 10 Soft Sensors 145 10.1 What Is a Soft Sensor? 145 10.2 Why Soft Sensors Are Necessary 145 10.2.1 Process Monitoring and Process Fault Detection 146 10.2.2 Sensor Fault Detection and Reconstruction 146 10.2.3 Use of Soft Sensors in MPC Application 146 10.3 Types of Soft Sensors 147 10.3.1 First Principle‐Based Soft Sensors 147 10.3.1.1 Advantages 147 10.3.1.2 Disadvantages 147 10.3.2 Data‐Driven Soft Sensors 148 10.3.2.1 Advantages 148 10.3.2.2 Disadvantages 148 10.3.3 Gray Model‐Based Soft Sensors 148 10.3.3.1 Advantages 149 10.3.4 Hybrid Model‐Based Soft Sensors 149 10.3.4.1 Advantages 149 10.4 Soft Sensors Development Methodology 149 10.4.1 Data Collection and Data Inspection 149 10.4.2 Data Preprocessing and Data Conditioning 150 10.4.2.1 Outlier Detection and Replacement 151 10.4.2.2 Univariate Approach to Detect Outliers 151 10.4.2.3 Multivariate Approach to Detect Outliers (Lin 2007) 151 10.4.2.4 Handling of Missing Data 152 10.4.3 Selection of Relevant Input Output Variables 153 10.4.4 Data Alignment 153 10.4.5 Model Selection, Training, and Validation (Kadlec 2009; Lin 2007) 153 10.4.6 Analyze Process Dynamics 154 10.4.7 Deployment and Maintenance 155 10.5 Data‐Driven Methods for Soft Sensing 156 10.5.1 Principle Component Analysis 156 10.5.1.1 The Basics of PCA 156 10.5.1.2 Why Do We Need to Rotate the Data? 156 10.5.1.3 How Do We Generate Principal Components? 156 10.5.1.4 Steps to Calculating Principal Components 157 10.5.2 Partial Least Squares 157 10.5.3 Artificial Neural Networks 158 10.5.3.1 Network Architecture 159 10.5.3.2 Back Propagation Algorithm (BPA) 159 10.5.4 Neuro‐Fuzzy Systems 160 10.5.5 Support Vector Machines 161 10.5.5.1 Support Vector Regression–Based Modeling 161 10.6 Open Issues and Future Steps of Soft Sensor Development 162 10.6.1 Large Effort Required for Preprocessing of Industrial Data 162 10.6.2 Which Modeling Method to Choose? 163 10.6.3 Agreement of the Developed Model with Physics of the Process 163 10.6.4 Performance Deterioration of Developed Soft Sensor Model 163 11 Offline Simulation 167 11.1 What Is Offline Simulation? 167 11.2 Purpose of Offline Simulation 167 11.3 Main Task of Offline Simulation 168 11.4 Understanding Different Tuning Parameters of Offline Simulations 168 11.4.1 Tuning Parameters for CVs 169 11.4.1.1 Methods for Handling of Infeasibility 170 11.4.1.2 Priority Ranking of CVs 170 11.4.1.3 cv Give‐Up 170 11.4.1.4 cv Error Weight 170 11.4.2 Tuning Parameters for MVs 171 11.4.2.1 mv Maximum Movement Limits or Rate‐of‐Change Limits 171 11.4.2.2 Movement Weights 171 11.4.3 Tuning Parameters for Optimizer 172 11.4.3.1 Economic Optimization 172 11.4.3.2 General Form of Objective Function 173 11.4.3.3 Weighting Coefficients 173 11.4.3.4 Setting Linear Objective Coefficients 173 11.4.3.5 Optimization Horizon and Optimization Speed Factor 174 11.4.3.6 Optimization Speed Factor 174 11.4.3.7 mv Optimization Priority 174 11.4.4 Soft Limits 175 11.4.4.1 How Soft Limits Work 175 11.4.4.2 cv Soft Limits 175 11.4.4.3 mv Soft Limits 176 11.5 Different Steps to Build and Activate Simulator in an Offline PC 176 11.6 Example of Tests Carried out in Simulator 177 11.6.1 Control and Optimization Objectives 177 11.6.1.1 Test 1 178 11.6.1.2 Test 2 179 11.6.1.3 Test 3 179 11.6.1.4 Test 4 180 11.6.1.5 Test 5 180 11.6.1.6 Test 6 180 11.6.1.7 Others Tests 181 11.7 Guidelines for Choosing Tuning Parameters 181 11.7.1 Guidelines for Choosing Initial Values 181 11.7.2 How to Select Maximum Move Size and MV Movement Weights During Simulation Study 182 12 Online Deployment of MPC Application in Real Plants 183 12.1 What Is Online Deployment (Controller Commissioning)? 183 12.2 Steps for Controller Commissioning 183 12.2.1 Set up the Controller Configuration and Final Review of the Model 183 12.2.2 Build the Controller 184 12.2.3 Load Operator Station on PC Near the Panel Operator 184 12.2.4 Take MPC Controller in Line with Prediction Mode 186 12.2.5 Put the MPC Controller in Close Loop with One CV at a Time 187 12.2.6 Observe MPC Controller Performance 187 12.2.7 Put Optimizer in Line and Observe Optimizer Performance 189 12.2.8 Evaluate Overall Controller Performance 189 12.2.9 Perform Online Tuning and Troubleshooting 190 12.2.10 Train Operators and Engineers on Online Platform 190 12.2.11 Document MPC Features 190 12.2.12 Maintain the MPC Controller 191 13 Online Controller Tuning 193 13.1 What Is Online MPC Controller Tuning? 193 13.2 Basics of Online Tuning 193 13.2.1 Key Checkout Regarding Controller Performance 193 13.2.2 Steps to Troubleshoot the Problem 194 13.3 Guidelines to Choose Different Tuning Parameters 195 14 Why Do Some MPC Applications Fail? 199 14.1 What Went Wrong? 199 14.2 Failure to Build Efficient MPC Application 201 14.2.1 Historical Perspective 201 14.2.2 Capability of MPC Software to Capture Benefits 202 14.2.3 Expertise of Implementation Team 202 14.2.3.1 MPC Vendor Limitations 203 14.2.3.2 Client Limitations 204 14.2.4 Reliability of APC Project Methodology 204 14.3 Contributing Failure Factors of Postimplementation MPC Application 205 14.3.1 Technical Failure Factors 206 14.3.1.1 Lack of Performance Monitoring of MPC Application 206 14.3.1.2 Unresolved Basic Control Problems 206 14.3.1.3 Poor Tuning and Degraded Model Quality 207 14.3.1.4 Problems Related to Controller Design 207 14.3.1.5 Significant Process Modifications and Enhancement 207 14.3.2 Nontechnical Failure Factors 208 14.3.2.1 Lack of Properly Trained Personnel 208 14.3.2.2 Lack of Standards and Guidelines to MPC Support Personnel 208 14.3.2.3 Lack of Organizational Collaboration and Alignment 208 14.3.2.4 Poor Management of Control System 209 14.4 Strategies to Avoid MPC Failures 210 14.4.1 Technical Solutions 211 14.4.1.1 Development of Online Performance Monitoring of APC Applications 211 14.4.1.2 Improvement of Base Control Layer 212 14.4.1.3 Tuning Basic Controls 212 14.4.1.4 Control Performance Monitoring Software 213 14.4.2 Management Solutions 214 14.4.2.1 Training of MPC Console Operators 214 14.4.2.2 Training of MPC Control Engineers 215 14.4.2.3 Development of Corporate MPC Standards and Guidelines 216 14.4.2.4 Central Engineering Support Organization for MPC 217 14.4.3 Outsourcing Solutions 219 15 MPC Performance Monitoring 221 15.1 Why Performance Assessment of MPC Application Is Necessary 221 15.2 Types of Performance Assessment 222 15.2.1 Control Performance 222 15.2.2 Optimization Performance 222 15.2.3 Economic Performance 222 15.2.4 Intangible Performance 222 15.3 Benefit Measurement after MPC Implementation 222 15.4 Parameters to Be Monitored for MPC Performance Evaluation 223 15.4.1 Service Factors 224 15.4.2 KPI for Financial Criteria 224 15.4.3 KPI for Standard Deviation of Key Process Variable 225 15.4.3.1 Safety Parameters 225 15.4.3.2 Quality Giveaway Parameters 225 15.4.3.3 Economic Parameters 225 15.4.4 KPI for Constraint Activity 226 15.4.5 KPI for Constraint Violation 226 15.4.6 KPI for Inferential Model Monitoring 226 15.4.7 Model Quality 226 15.4.8 Limit Change Frequencies for CV/MVs 227 15.4.9 Active MV Limit 227 15.4.10 Long‐Term Performance Monitoring of MPC 227 15.5 KPIs to Troubleshoot Poor Performance of Multivariable Controls 228 15.5.1 Supporting KPIs for Low Service Factor 228 15.5.2 KPIs to Troubleshoot Cycling 229 15.5.3 KPIs for Oscillation Detection 230 15.5.4 KPIs for Regulatory Control Issues 230 15.5.5 KPIs for Measuring Operator Actions 231 15.5.6 KPIs for Measuring Process Changes and Disturbances 231 15.6 Exploitation of Constraints Handling and Maximization of MPC Benefit 231 16 Commercial MPC Vendors and Applications 235 16.1 Basic Modules and Components of Commercial MPC Software 235 16.1.1 Basic MPC Package 235 16.1.2 Data Collection Module 236 16.1.3 MPC Online Controller 236 16.1.4 Operator/ Engineer Station 237 16.1.5 System Identification Module 237 16.1.5.1 Different Modeling Options 239 16.1.5.2 Reporting and Documentation Function 239 16.1.5.3 Data Analysis and Pre‐Processing 239 16.1.6 PC‐Based Offline Simulation Package 240 16.1.7 Control Performance Monitoring and Diagnostics Software 240 16.1.7.1 Control Performance Monitoring 240 16.1.7.2 Basic Features of Performance Monitoring and Diagnostics Software 240 16.1.7.3 Performance and Benefits Metrics 241 16.1.7.4 Offline Module 241 16.1.7.5 Online Package 241 16.1.7.6 Online Reports 241 16.1.8 Soft Sensor Module (Also Called Quality Estimator Module) 242 16.1.8.1 Soft Sensor Offline Package 242 16.1.8.2 Soft Sensor Online Package 243 16.1.8.3 Soft Sensor Module Simulation Tool 243 16.2 Major Commercial MPC Software 243 16.3 AspenTech and DMCplus 244 16.3.1 Brief History of Development 244 16.3.1.1 Enhancement of DMC Technology to QDMC Technology in 1983, Regarded as Second‐Generation of MPC Technology (1980–1985) 244 16.3.1.2 Introduction of AspenTech and Evolvement of Third‐Generation MPC Technology (1985–1990) 245 16.3.1.3 Appearance of DMCplus Product with Fourth‐Generation MPC Technology (1990–2000) 245 16.3.1.4 Improvement of DMCplus Technology for Quicker Implementation in Shop Floor, Regarded as Fifth‐Generation MPC (2000–2015) 245 16.3.2 DMCplus Product Package 246 16.3.2.1 Aspen DMCplus Desktop 246 16.3.2.2 Aspen DMCplus Online 246 16.3.2.3 DMCplus Models and Identification Package 247 16.3.2.4 Aspen IQ (Soft Sensor Software) 247 16.3.2.5 Aspen Watch: AspenTech MPC Monitoring and Diagnostic Software 247 16.3.3 Distinctive Features of DMCplus Software Package 248 16.3.3.1 Automating Best Practices in Process Unit Step Testing 248 16.3.3.2 Adaptive Modeling 248 16.3.3.3 New Innovation 249 16.3.3.4 Background Step Testing 250 16.4 RMPCT by Honeywell 251 16.4.1 Brief History of Development 251 16.4.2 Honeywell MPC Product Package and Its Special Features 251 16.4.3 Key Features and Functions of RMPCT 251 16.4.3.1 Special Feature to Handle Model Error 251 16.4.3.2 Coping with Model Error 252 16.4.3.3 Funnels 252 16.4.3.4 Range Control Algorithm 252 16.4.4 Product Value Optimization Capabilities 252 16.4.5 “One‐Knob” Tuning 253 16.5 SMOC–Shell Global Solution 253 16.5.1 Evolution of Advance Process Control in Shell 253 16.5.1.1 1975–1998: The Beginnings 253 16.5.1.2 1998–2008: Shell Global Solution and Partnering with Yokogawa Era 254 16.5.1.3 2008 Onward: Shell Returns to Its Own Application 254 16.5.2 Shell MPC Product Package and Its Special Features 255 16.5.2.1 Key Characteristics of SMOC 255 16.5.2.2 Applications 255 16.5.3 SMOC Integrated Software Modules 255 16.5.3.1 AIDA Pro Offline Modeling Package 256 16.5.3.2 md Pro 256 16.5.3.3 RQE Pro 256 16.5.3.4 SMOC Pro 257 16.5.4 SMOC Claim of Superior Distinctive Features 259 16.5.4.1 Integrated Dynamic Modeling Tools and Automatic Step Tests 259 16.5.4.2 State‐of‐the‐Art Online Commissioning Tools 259 16.5.4.3 Online Tuning 259 16.5.4.4 Advance Regulatory Controls 260 16.5.4.5 Features of New Product 260 16.6 Conclusion 261 Index 263

Read more less

Book SynopsisThis textbook is an introduction to microwave engineering. The scope of this book extends from topics for a first course in electrical engineering, in which impedances are analyzed using complex numbers, through the introduction of transmission lines that are analyzed using the Smith Chart, and on to graduate level subjects, such as equivalent circuits for obstacles in hollow waveguides, analyzed using Green's Functions. This book is a virtual encyclopedia of circuit design methods. Despite the complexity, topics are presented in a conversational manner for ease of comprehension. The book is not only an excellent text at the undergraduate and graduate levels, but is as well a detailed reference for the practicing engineer. Consider how well informed an engineer will be who has become familiar with these topics as treated in High Frequency Techniques: (in order of presentation) Brief history of wireless (radio) and the Morse codeU.S. Radio Frequency AllocatTable of ContentsPreface xv Acknowledgments xvii 1 Introduction 1 1.1 Beginning of Wireless 1 1.2 Current Radio Spectrum 4 1.3 Conventions Used in This Text 8 Sections 8 Equations 8 Figures 8 Exercises 8 Symbols 8 Prefixes 10 Fonts 10 1.4 Vectors and Coordinates 11 1.5 General Constants and Useful Conversions 14 2 Review of AC Analysis and Network Simulation 16 2.1 Basic Circuit Elements 16 The Resistor 16 Ohm’s Law 18 The Inductor 19 The Capacitor 20 2.2 Kirchhoff’s Laws 22 2.3 Alternating Current (AC) Analysis 23 Ohm’s Law in Complex Form 26 2.4 Voltage and Current Phasors 26 2.5 Impedance 28 Estimating Reactance 28 Addition of Series Impedances 29 2.6 Admittance 30 Admittance Definition 30 Addition of Parallel Admittances 30 The Product over the Sum 32 2.7 LLFPB Networks 33 2.8 Decibels, dBW, and dBm 33 Logarithms (Logs) 33 Multiplying by Adding Logs 34 Dividing by Subtracting Logs 34 Zero Powers 34 Bel Scale 34 Decibel Scale 35 Decibels—Relative Measures 35 Absolute Power Levels—dBm and dBW 37 Decibel Power Scales 38 2.9 Power Transfer 38 Calculating Power Transfer 38 Maximum Power Transfer 39 2.10 Specifying Loss 40 Insertion Loss 40 Transducer Loss 41 Loss Due to a Series Impedance 42 Loss Due to a Shunt Admittance 43 Loss in Terms of Scattering Parameters 44 2.11 Real RLC Models 44 Resistor with Parasitics 44 Inductor with Parasitics 44 Capacitor with Parasitics 44 2.12 Designing LC Elements 46 Lumped Coils 46 High μ Inductor Cores—the Hysteresis Curve 47 Estimating Wire Inductance 48 Parallel Plate Capacitors 49 2.13 Skin Effect 51 2.14 Network Simulation 53 3 LC Resonance and Matching Networks 59 3.1 LC Resonance 59 3.2 Series Circuit Quality Factors 60 Q of Inductors and Capacitors 60 QE, External Q 61 QL, Loaded Q 62 3.3 Parallel Circuit Quality Factors 62 3.4 Coupled Resonators 63 Direct Coupled Resonators 63 Lightly Coupled Resonators 63 3.5 Q Matching 67 Low to High Resistance 67 Broadbanding the Q Matching Method 70 High to Low Resistance 71 4 Distributed Circuits 78 4.1 Transmission Lines 78 4.2 Wavelength in a Dielectric 81 4.3 Pulses on Transmission Lines 82 4.4 Incident and Reflected Waves 83 4.5 Reflection Coefficient 85 4.6 Return Loss 86 4.7 Mismatch Loss 86 4.8 Mismatch Error 87 4.9 The Telegrapher Equations 91 4.10 Transmission Line Wave Equations 92 4.11 Wave Propagation 94 4.12 Phase and Group Velocities 97 4.13 Reflection Coefficient and Impedance 100 4.14 Impedance Transformation Equation 101 4.15 Impedance Matching with One Transmission Line 108 4.16 Fano’s (and Bode’s) Limit 109 Type A Mismatched Loads 109 Type B Mismatched Loads 112 Impedance Transformation Not Included 113 5 The Smith Chart 119 5.1 Basis of the Smith Chart 119 5.2 Drawing the Smith Chart 124 5.3 Admittance on the Smith Chart 130 5.4 Tuning a Mismatched Load 132 5.5 Slotted-Line Impedance Measurement 135 5.6 VSWR = r 139 5.7 Negative Resistance Smith Chart 140 5.8 Navigating the Smith Chart 140 5.9 Smith Chart Software 145 5.10 Estimating Bandwidth on the Smith Chart 147 5.11 Approximate Tuning May Be Better 148 5.12 Frequency Contours on the Smith Chart 150 5.13 Using the Smith Chart without Transmission Lines 150 5.14 Constant Q Circles 151 5.15 Transmission Line Lumped Circuit Equivalent 153 6 Matrix Analysis 161 6.1 Matrix Algebra 161 6.2 Z and Y Matrices 164 6.3 Reciprocity 166 6.4 The ABCD Matrix 167 6.5 The Scattering Matrix 172 6.6 The Transmission Matrix 177 7 Electromagnetic Fields and Waves 183 7.1 Vector Force Fields 183 7.2 E and H Fields 185 7.3 Electric Field E 185 7.4 Magnetic Flux Density 187 7.5 Vector Cross Product 188 7.6 Electrostatics and Gauss’s Law 193 7.7 Vector Dot Product and Divergence 194 7.8 Static Potential Function and the Gradient 196 7.9 Divergence of the B Field 200 7.10 Ampere’s Law 201 7.11 Vector Curl 202 7.12 Faraday’s Law of Induction 208 7.13 Maxwell’s Equations 209 Maxwell’s Four Equations 209 Auxiliary Relations and Definitions 210 Visualizing Maxwell’s Equations 211 7.14 Primary Vector Operations 214 7.15 The Laplacian 215 7.16 Vector and Scalar Identities 218 7.17 Free Charge within a Conductor 219 7.18 Skin Effect 221 7.19 Conductor Internal Impedance 224 7.20 The Wave Equation 227 7.21 The Helmholtz Equations 229 7.22 Plane Propagating Waves 230 7.23 Poynting’s Theorem 233 7.24 Wave Polarization 236 7.25 EH Fields on Transmission Lines 240 7.26 Waveguides 246 General Waveguide Solution 246 Waveguide Types 250 Rectangular Waveguide Fields 251 Applying Boundary Conditions 252 Propagation Constants and Waveguide Modes 253 Characteristic Wave Impedance for Waveguides 256 Phase and Group Velocities 257 TE and TM Mode Summary for Rectangular Waveguide 257 7.27 Fourier Series and Green’s Functions 261 Fourier Series 261 Green’s Functions 263 7.28 Higher Order Modes in Circuits 269 7.29 Vector Potential 271 7.30 Retarded Potentials 274 7.31 Potential Functions in the Sinusoidal Case 275 7.32 Antennas 275 Short Straight Wire Antenna 275 Radiation Resistance 279 Radiation Pattern 280 Half-Wavelength Dipole 280 Antenna Gain 283 Antenna Effective Area 284 Monopole Antenna 285 Aperture Antennas 286 Phased Arrays 288 7.33 Path Loss 290 7.34 Electromagnetic (EM) Simulation 294 8 Directional Couplers 307 8.1 Wavelength Comparable Dimensions 307 8.2 The Backward Wave Coupler 307 8.3 Even- and Odd-Mode Analysis 309 8.4 Reflectively Terminated 3-dB Coupler 320 8.5 Coupler Specifications 323 8.6 Measurements Using Directional Couplers 325 8.7 Network Analyzer Impedance Measurements 326 8.8 Two-Port Scattering Measurements 327 8.9 Branch Line Coupler 327 8.10 Hybrid Ring Coupler 330 8.11 Wilkinson Power Divider 330 9 Filter Design 335 9.1 Voltage Transfer Function 335 9.2 Low-Pass Prototype 336 9.3 Butterworth or Maximally Flat Filter 337 9.4 Denormalizing the Prototype Response 339 9.5 High-Pass Filters 343 9.6 Bandpass Filters 345 9.7 Bandstop Filters 349 9.8 Chebyshev Filters 351 9.9 Phase and Group Delay 356 9.10 Filter Q 361 9.11 Diplexer Filters 364 9.12 Top-Coupled Bandpass Filters 367 9.13 Elliptic Filters 369 9.14 Distributed Filters 370 9.15 The Richards Transformation 374 9.16 Kuroda’s Identities 379 9.17 Mumford’s Maximally Flat Stub Filters 381 9.18 Filter Design with the Optimizer 384 9.19 Statistical Design and Yield Analysis 386 Using Standard Part Values 386 The Normal Distribution 387 Other Distributions 391 10 Transistor Amplifier Design 399 10.1 Unilateral Design 399 Evaluating S Parameters 399 Transistor Biasing 400 Evaluating RF Performance 403 10.2 Amplifier Stability 405 10.3 K Factor 409 10.4 Transducer Gain 413 10.5 Unilateral Gain Design 416 10.6 Unilateral Gain Circles 422 Input Gain Circles 422 Output Gain Circles 424 10.7 Simultaneous Conjugate Match Design 428 10.8 Various Gain Definitions 431 10.9 Operating Gain Design 433 10.10 Available Gain Design 437 10.11 Noise in Systems 442 Thermal Noise Limit 442 Other Noise Sources 444 Noise Figure of a Two-Port Network 445 Noise Factor of a Cascade 447 Noise Temperature 448 10.12 Low-Noise Amplifiers 450 10.13 Amplifier Nonlinearity 455 Gain Saturation 455 Intermodulation Distortion 456 10.14 Broadbanding with Feedback 460 10.15 Cascading Amplifier Stages 466 10.16 Amplifier Design Summary 468 Appendices A. Symbols and Units 474 B. Complex Mathematics 478 C. Diameter and Resistance of Annealed Copper Wire by Gauge Size 483 D. Properties of Some Materials 485 E. Standard Rectangular Waveguides 486 Frequently Used Relations 487 Index 491

Read more less

Book SynopsisThe definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems.Table of ContentsAbout the Authors xi Preface xiii About the Companion Website xvii Part 1 Big Data, Clouds and Internet of Things 1 1. Big Data Science and Machine Intelligence 3 1.1 Enabling Technologies for Big Data Computing 3 1.2 Social-Media, Mobile Networks and Cloud Computing 16 1.3 Big Data Acquisition and Analytics Evolution 24 1.4 Machine Intelligence and Big Data Applications 32 1.5 Conclusions 42 Homework Problems 42 References 43 2. Smart Clouds, Virtualization and Mashup Services 45 2.1 Cloud Computing Models and Services 45 2.2 Creation of Virtual Machines and Docker Containers 57 2.3 Cloud Architectures and Resources Management 65 2.4 Case Studies of IaaS, PaaS and SaaS Clouds 77 2.5 Mobile Clouds and Inter-Cloud Mashup Services 88 2.6 Conclusions 98 Homework Problems 98 References 103 3. IoT Sensing, Mobile and Cognitive Systems 105 3.1 Sensing Technologies for Internet of Things 105 3.2 IoT Interactions with GPS, Clouds and Smart Machines 111 3.3 Radio Frequency Identification (RFID) 119 3.4 Sensors, Wireless Sensor Networks and GPS Systems 124 3.5 Cognitive Computing Technologies and Prototype Systems 139 3.6 Conclusions 149 Homework Problems 150 References 152 Part 2 Machine Learning and Deep Learning Algorithms 155 4. Supervised Machine Learning Algorithms 157 4.1 Taxonomy of Machine Learning Algorithms 157 4.2 Regression Methods for Machine Learning 164 4.3 Supervised Classification Methods 171 4.4 Bayesian Network and Ensemble Methods 187 4.5 Conclusions 200 Homework Problems 200 References 203 5. Unsupervised Machine Learning Algorithms 205 5.1 Introduction and Association Analysis 205 5.2 Clustering Methods without Labels 213 5.3 Dimensionality Reduction and Other Algorithms 225 5.4 How to Choose Machine Learning Algorithms? 233 5.5 Conclusions 243 Homework Problems 243 References 247 6. Deep Learning with Artificial Neural Networks 249 6.1 Introduction 249 6.2 Artificial Neural Networks (ANN) 256 6.3 Stacked Auto Encoder and Deep Belief Network 264 6.4 Convolutional Neural Networks (CNN) and Extensions 277 6.5 Conclusions 287 Homework Problems 288 References 291 Part 3 Big Data Analytics for Health-Care and Cognitive Learning 293 7. Machine Learning for Big Data in Healthcare Applications 295 7.1 Healthcare Problems and Machine Learning Tools 295 7.2 IoT-based Healthcare Systems and Applications 299 7.3 Big Data Analytics for Healthcare Applications 310 7.4 Emotion-Control Healthcare Applications 322 7.5 Conclusions 335 Homework Problems 336 References 339 8. Deep Reinforcement Learning and Social Media Analytics 343 8.1 Deep Learning Systems and Social Media Industry 343 8.2 Text and Image Recognition using ANN and CNN 348 8.3 DeepMind with Deep Reinforcement Learning 362 8.4 Data Analytics for Social-Media Applications 375 8.5 Conclusions 390 Homework Problems 391 References 393 Index 395

Read more less

Book SynopsisComprehensive Handbook Demystifies 5G for Technical and Business Professionals in Mobile Telecommunication Fields Much is being said regarding the possibilities and capabilities of the emerging 5G technology, as the evolution towards 5G promises to transform entire industries and many aspects of our society. 5G for the Connected World offers a comprehensive technical overview that telecommunication professionals need to understand and take advantage of these developments. The book offers a wide-ranging coverage of the technical aspects of 5G (with special consideration of the 3GPP Release 15 content), how it enables new services and how it differs from LTE. This includes information on potential use cases, aspects of radio and core networks, spectrum considerations and the services primarily driving 5G development and deployment. The text also looks at 5G in relation to the Internet of Things, machine to machine communication and technical enablers such as LTE-M, NB-IoT and EC-GSM. Table of ContentsAbout the Editors xvii List of Contributors xix Foreword by Tommi Uitto xxi Foreword by Karri Kuoppamaki xxiii Preface xxv Acknowledgements xxvii Introduction xxix Terminology xxxi 1 Drivers and Motivation for 5G 1Betsy Covell and Rainer Liebhart 1.1 Drivers for 5G 1 1.2 ITU-R and IMT 2020 Vision 3 1.3 NGMN (Next Generation Mobile Networks) 5 1.4 5GPPP (5G Public-Private Partnership) 8 1.5 Requirements for Support of Known and New Services 9 1.6 5G Use Cases 19 1.7 Business Models 26 1.8 Deployment Strategies 28 1.9 3GPP Role and Timelines 30 References 34 2 Wireless Spectrum for 5G 35Juho Pirskanen, Karri Ranta-aho, Rauno Ruismäki and Mikko Uusitalo 2.1 Current Spectrum for Mobile Communication 35 2.2 Spectrum Considerations for 5G 35 2.3 Identified New Spectrum 37 2.4 Spectrum Regulations 38 2.5 Characteristics of Spectrum Available for 5G 43 2.6 NR Bands Defined by 3GPP 46 References 48 3 Radio Access Technology 51Sami Hakola, Toni Levanen, Juho Pirskanen, Karri Ranta-aho, Samuli Turtinen, Keeth Jayasinghe and Fred Vook 3.1 Evolution Toward 5G 51 3.2 Basic Building Blocks 56 3.3 Downlink Physical Layer 83 3.4 Uplink Physical Layer 92 3.5 Radio Protocols 96 3.6 Mobile Broadband 117 References 124 4 Next Generation Network Architecture 127Devaki Chandramouli, Subramanya Chandrashekar, AndreasMaeder, Tuomas Niemela, Thomas Theimer and Laurent Thiebaut 4.1 Drivers and Motivation for a New Architecture 127 4.2 Architecture Requirements and Principles 130 4.3 5G System Architecture 139 4.4 NG RAN Architecture 149 4.5 Non-Standalone and Standalone Deployment Options 158 4.6 Identifiers 161 4.7 Network Slicing 163 4.8 Multi-Access Edge Computing 171 4.9 Data Storage Architecture 173 4.10 Network Capability Exposure 180 4.11 Interworking and Migration 182 4.12 Non-3GPP Access 189 4.13 Fixed Mobile Convergence 193 4.14 Network Function Service Framework 196 4.15 IMS Services 203 4.16 Emergency Services 205 4.17 Location Services 207 4.18 Short Message Service 208 4.19 Public Warning System 210 4.20 Protocol Stacks 212 4.21 Charging 218 4.22 Summary and Outlook of 5G System Features 219 4.23 Terminology and Definitions 221 References 222 5 Access Control and Mobility Management 225Devaki Chandramouli, Subramanya Chandrashekar, JarmoMakinen,Mikko Säily and Sung HwanWon 5.1 General Principles 225 5.2 Mobility States and Functionalities 228 5.3 Initial Access and Registration 234 5.4 Connected Mode Mobility 238 5.5 Idle Mode mobility and UE Reachability 261 5.6 RRC Inactive State mobility and UE Reachability 265 5.7 Beam Level Mobility 268 5.8 Support for High Speed Mobility 270 5.9 Support for Ultralow Latency and Reliable Mobility 273 5.10 UE Mobility Restrictions and Special Modes 276 5.11 Inter-System (5GS-EPS) Mobility 277 5.12 Outlook 280 References 281 6 Sessions, User Plane, and QoS Management 283Devaki Chandramouli, Thomas Theimer and Laurent Thiebaut 6.1 Introduction 283 6.2 Basic Principles of PDU Sessions 283 6.3 Ultra-reliable Low Latency Communication 293 6.4 QoS Management in 5GS 295 6.5 User Plane Transport 301 6.6 Policy Control and Application Impact on Traffic Routing 302 6.7 Session Management 306 6.8 SMF Programming UPF Capabilities 309 References 310 7 Security 311Peter Schneider 7.1 Drivers, Requirements and High-Level Security Vision 311 7.2 Overall 5G Security Architecture 316 7.3 3GPP Specific Security Mechanisms 319 7.4 SDN Security 327 7.5 NFV Security 330 7.6 Network Slicing Security 332 7.7 Private Network Infrastructure 335 References 335 8 Critical Machine Type Communication 337Zexian Li and Rainer Liebhart 8.1 Introduction 337 8.2 Key Performance Indicators 340 8.3 Solutions 341 References 374 9 Massive Machine Type Communication and the Internet of Things 377Devaki Chandramouli, Betsy Covell, Volker Held, Hannu Hietalahti, Jürgen Hofmann and Rapeepat Ratasuk 9.1 Massive M2M Versus IoT 377 9.2 Requirements and Challenges 379 9.3 Technology Evolution 382 9.4 EPS Architecture Evolution 384 9.5 Cellular Internet of Things 391 9.6 GERAN 405 9.7 LTE-M 418 9.8 NB-IoT 422 9.9 5G for M2M 428 9.10 Comparison of EPS and 5GS 431 9.11 Future Enhancements 433 9.12 Other Technologies 438 References 438 10 Summary and Outlook 441Rainer Liebhart and Devaki Chandramouli 10.1 Summary 441 10.2 Outlook 442 Appendix of 3GPP Reference Points 447 Index 451

Read more less

Book SynopsisThe definitive guide to developing robust content delivery networks This book examines the real-world engineering challenges of developing robust content delivery networks (CDNs) and provides the tools required to overcome those challenges and to ensure high-quality content delivery that fully satisfies operators' and consumers'' commercial objectives. It is informed by the author's two decades of experience building and delivering large, mission-critical live video, webcasts, and radio streaming, online and over private IP networks. Following an overview of the field, the book cuts to the chase with in-depth discussionslaced with good-natured humorof a wide range of design considerations for different network topologies. It begins with a description of the author''s own requirement filtration processes. From there it moves on to initial sketches, through considerations of stakeholder roles and responsibilities, to the complex challenges of managing change in esTable of ContentsFrontispiece xiii Topics Include xiii About the Book xiv Synposis xiv Unique Perspective xv Market Need xvi Audience xvii 1 Welcome 1 1.1 A Few Words of Introduction 1 1.2 The “Why” of this Book 2 1.3 Relevant Milestones of the Personal Voyage 3 2 Context and Orientation 9 2.1 History of Streaming 10 2.1.1 Foundations – What does “Streaming” Really Mean? 12 2.1.2 Streaming 13 2.1.3 Related Network Models 16 2.1.4 Physical Network Considerations 16 2.1.5 Internet Layer Considerations 17 2.1.6 Transport Layer Considerations 17 2.1.7 Applications – Transport Protocols 18 2.1.8 Protocol Evolution 19 2.1.9 Format Evolution 25 2.2 Industry Evolution 25 2.2.1 “Stack Creep” 26 2.2.2 Real World – Blue Chips and Video Delivery Networks 26 2.3 Consumer Adoption 29 2.3.1 The Audience 29 2.3.2 Traditional Ratings Companies and Audience Measurement 32 2.3.3 Streaming Media and Measurement 34 2.3.4 Predictions of Others 37 2.3.5 The Pending Collapse of the Value of Broadcasting to Advertisers 41 2.3.6 “Device Effect” and Formats 41 2.3.7 Video Formats (in Particular, Multicast and UDP) and Network Architecture 43 2.3.8 Discovery, Curation, and Social Media 45 2.4 Encode > Serve > Play 54 2.4.1 The Basic Building Blocks 54 2.4.2 The Acacia Patent 55 2.4.3 Akamai vs. Limelight 57 2.4.4 Standards, Standards, Standards, … 58 2.4.5 D]Book Connected TV Standards from the Digital Television Group 60 2.4.6 The CoDec Concerns 61 2.5 What is a CDN: A Simple Model 63 2.5.1 Setting the Scene for CDNs 63 2.5.2 CDNs as Money Savers 66 2.5.3 Request Routing 67 2.5.4 CDN Brokerage 69 2.5.5 SaaS Models within the CDN Ecosystems 70 2.6 Cloud Inside – New Generation 75 2.7 The Three Generations of CDN 76 2.8 Software Definition 82 2.8.1 Multicore CPU and Functional Programming 86 2.8.2 Functional Programming and Containers 86 2.9 “Service Velocity” and the Operator 87 3 Workflows 89 3.1 Live Event Focus 92 3.1.1 Approaches to Webcasting 93 3.1.2 Think Before You Start – Your Client Probably Hasn’t! 94 3.1.3 Budgets 95 3.1.4 Objectives – Quality vs. Reliability 97 3.1.5 Production Principles 98 3.2 Backhaul/Contribution and Acquisition 102 3.2.1 Broadcast 104 3.2.2 Wire 104 3.2.3 Wireless 107 3.2.4 Satellite 108 3.2.5 3g/4G CellMux 109 3.2.6 Reliable UDP and HTTP/UDP Solutions 111 3.2.7 Throughput vs. Goodput 112 3.3 Cloud Saas 113 3.3.1 In Workflow “Treatment” (Transcode/Transmux, etc.) 114 3.3.2 DVR Workflows 117 3.3.3 Catch]up Workflows 119 3.3.4 VOD Workflows 121 4 Publishing 125 4.1 Publishers, OVPs, CDNs, and MCNs 126 4.2 Small Objects, Large Objects, or Continuous Streams 129 4.2.1 Compression 132 4.2.2 The “Quality Question” … 134 4.2.3 Latency 136 4.2.4 Application, Site, Web, and Games Acceleration 137 4.3 Desktop and Device Delivery Applications 138 4.3.1 Standalone Media Players and Applications 138 4.3.2 Video Tags in HTML5 141 4.3.3 WebRTC – Beyond HTML5 142 4.4 Request Routing (The Dark Art of the CDN) 142 4.5 Logging Analytics and the Devil in the Detail 143 5 Service Velocity 145 6 Charging for IP]Delivered Content 151 6.1 Lessons from the Music Industry 151 6.2 Success Cases 153 6.2.1 YouTube 154 6.2.2 Netflix 155 6.2.3 On the Horizon 156 6.3 Failure Cases 158 6.3.1 Scour.net 158 6.3.2 mp3.com 159 6.3.3 Napster 160 6.3.4 Broadcast.com 160 6.3.5 The “Yacht Projects” 162 6.4 General Commentary on Commercial Models 163 6.4.1 Cable TV 164 6.4.2 IPTV 165 6.4.3 OTT Pureplay + Operator CDN 166 6.4.4 Fog Distribution 167 6.4.5 Variation from Live Linear to VOD, and Everything in Between 168 6.4.6 DRM 169 6.4.7 Watermarking 171 7 Competition and the Regulatory Environment 175 7.1 ISOC, ITU, and WSIS 176 7.2 Policy – Net Neutrality 179 7.3 Value Chain Alignment with QoS and SLA Propositions 181 7.4 Layer] 2 Workaround? 181 8 Cultural Change 183 8.1 Traditional Broadcasters 183 8.2 The Millenial Subscriber 185 8.3 ISP and Content Providers 186 8.4 Telco and Telecoms 188 8.5 Content Providers 188 9 Preparing for Change in Your Design 191 9.1 Preface and Philosophy 191 9.2 Models, Diagrams, and Schematics 193 9.3 How to do a Good Diagram? 193 9.4 Scenario Planning 194 9.5 Risk, Responsibility, and Reassurance 196 9.6 Optimization and Upsell 196 9.7 Value Creation/Agility 197 9.8 Expectation Management 197 10 Multicast – the Sleeping Giant 199 10.1 Multicast Recap 199 10.1.1 Basics 199 10.1.2 Routing Protocols 200 10.1.3 Flood, Prune, Storms, and a Bad Taste 201 10.1.4 Commercial Outcome 201 10.2 What Happens Now? 202 10.3 To Singularity and Beyond 204 11 Deep]Dives (Case Studies) 207 11.1 Hitting the TV Screen – IPTV/Hybrid TV and OTT 207 11.1.1 The Taxonomy of OTT Video 210 11.1.2 Arqiva Connect and Freeview Plus 214 11.2 Creating Nasdaq’s Cloud]Based Virtual Workflow 217 11.2.1 The Genesis of a Virtual Workflow 218 11.2.2 The Technology Behind the Workflow 219 11.2.3 Why Amazon EC2? 220 11.2.4 What Sort of Scaling Issues did You Face? 222 11.2.5 How about SLA? 222 11.2.6 What about Signal Acquisition? 222 11.2.7 What about OS Choices and Stacks? 223 11.2.8 How Is the System Controlled? 223 11.2.9 How Does it Report? 224 12 Wrap Up 225 Index 229

Read more less

Book SynopsisA comprehensive guide that addresses the theory and practice of spatial audio This book provides readers with the principles and best practices in spatial audio signal processing. It describes how sound fields and their perceptual attributes are captured and analyzed within the time-frequency domain, how essential representation parameters are coded, and how such signals are efficiently reproduced for practical applications. The book is split into four parts starting with an overview of the fundamentals. It then goes on to explain the reproduction of spatial sound before offering an examination of signal-dependent spatial filtering. The book finishes with coverage of both current and future applications and the direction that spatial audio research is heading in. Parametric Time-frequency Domain Spatial Audio focuses on applications in entertainment audio, including music, home cinema, and gamingcovering the capturing and reproduction of spatial sound as Table of ContentsContents List of Contributors xiii Preface xv About the Companion Website xix Part I Analysis and Synthesis of Spatial Sound 1 Time–Frequency Processing: Methods and Tools 3Juha Vilkamo and Tom Ba¨ckstro¨m 1.1 Introduction 3 1.2 Time–Frequency Processing 4 1.2.1 Basic Structure 4 1.2.2 Uniform Filter Banks 5 1.2.3 Prototype Filters and Modulation 6 1.2.4 A Robust Complex-Modulated Filter Bank, and Comparison with STFT 8 1.2.5 Overlap-Add and Windowing 12 1.2.6 Example Implementation of a Robust Filter Bank in Matlab 13 1.2.7 Cascaded Filters 15 1.3 Processing of Spatial Audio 16 1.3.1 Stochastic Estimates 17 1.3.2 Decorrelation 18 1.3.3 Optimal and Generalized Solution for Spatial Sound Processing Using Covariance Matrices 19 References 23 2 Spatial Decomposition by Spherical Array Processing 25David Lou Alon and Boaz Rafaely 2.1 Introduction 25 2.2 Sound Field Measurement by a Spherical Array 26 2.3 Array Processing and Plane-Wave Decomposition 26 2.4 Sensitivity to Noise and Standard Regularization Methods 29 2.5 Optimal Noise-Robust Design 32 2.5.1 PWD Estimation Error Measure 32 2.5.2 PWD Error Minimization 34 2.5.3 R-PWD Simulation Study 35 2.6 Spatial Aliasing and High Frequency Performance Limit 37 2.7 High Frequency Bandwidth Extension by Aliasing Cancellation 39 2.7.1 Spatial Aliasing Error 39 2.7.2 AC-PWD Simulation Study 40 2.8 High Performance Broadband PWD Example 42 2.8.1 Broadband Measurement Model 42 2.8.2 Minimizing Broadband PWD Error 42 2.8.3 BB-PWD Simulation Study 44 2.9 Summary 45 2.10 Acknowledgment 46 References 46 3 Sound Field Analysis Using Sparse Recovery 49Craig T. Jin, Nicolas Epain, and Tahereh Noohi 3.1 Introduction 49 3.2 The Plane-Wave Decomposition Problem 50 3.2.1 Sparse Plane-Wave Decomposition 51 3.2.2 The Iteratively Reweighted Least-Squares Algorithm 51 3.3 Bayesian Approach to Plane-Wave Decomposition 53 3.4 Calculating the IRLS Noise-Power Regularization Parameter 55 3.4.1 Estimation of the Relative Noise Power 56 3.5 Numerical Simulations 58 3.6 Experiment: Echoic Sound Scene Analysis 59 3.7 Conclusions 65 Appendix 65 References 66 Part II Reproduction of Spatial Sound 69 Overview of Time–Frequency Domain Parametric Spatial Audio Techniques 71Archontis Politis, Symeon Delikaris-Manias, and Ville Pulkki 4.1 Introduction 71 4.2 Parametric Processing Overview 73 4.2.1 Analysis Principles 74 4.2.2 Synthesis Principles 75 4.2.3 Spatial Audio Coding and Up-Mixing 76 4.2.4 Spatial Sound Recording and Reproduction 78 4.2.5 Auralization of Measured Room Acoustics and Spatial Rendering of Room Impulse Responses 81 References 82 5 First-Order Directional Audio Coding (DirAC) 89Ville Pulkki, Archontis Politis, Mikko-Ville Laitinen, Juha Vilkamo, and Jukka Ahonen 5.1 Representing Spatial Sound with First-Order B-Format Signals 89 5.2 Some Notes on the Evolution of the Technique 92 5.3 DirAC with Ideal B-Format Signals 94 5.4 Analysis of Directional Parameters with Real Microphone Setups 97 5.4.1 DOA Analysis with Open 2D Microphone Arrays 97 5.4.2 DOA Analysis with 2D Arrays with a Rigid Baffle 99 5.4.3 DOA Analysis in Underdetermined Cases 101 5.4.4 DOA Analysis: Further Methods 102 5.4.5 Effect of Spatial Aliasing and Microphone Noise on the Analysis of Diffuseness 103 5.5 First-Order DirAC with Monophonic Audio Transmission 105 5.6 First-Order DirAC with Multichannel Audio Transmission 106 5.6.1 Stream-Based Virtual Microphone Rendering 106 5.6.2 Evaluation of Virtual Microphone DirAC 109 5.6.3 Discussion of Virtual Microphone DirAC 111 5.6.4 Optimized DirAC Synthesis 111 5.6.5 DirAC-Based Reproduction of Spaced-Array Recordings 114 5.7 DirAC Synthesis for Headphones and for Hearing Aids 117 5.7.1 Reproduction of B-Format Signals 117 5.7.2 DirAC in Hearing Aids 118 5.8 Optimizing the Time–Frequency Resolution of DirAC for Critical Signals 119 5.9 Example Implementation 120 5.9.1 Executing DirAC and Plotting Parameter History 122 5.9.2 DirAC Initialization 125 5.9.3 DirAC Runtime 131 5.9.4 Simplistic Binaural Synthesis of Loudspeaker Listening 136 5.10 Summary 137 References 138 6 Higher-Order Directional Audio Coding 141Archontis Politis and Ville Pulkki 6.1 Introduction 141 6.2 Sound Field Model 144 6.3 Energetic Analysis and Estimation of Parameters 145 6.3.1 Analysis of Intensity and Diffuseness in the Spherical Harmonic Domain 146 6.3.2 Higher-Order Energetic Analysis 147 6.3.3 Sector Profiles 149 6.4 Synthesis of Target Setup Signals 151 6.4.1 Loudspeaker Rendering 152 6.4.2 Binaural Rendering 155 6.5 Subjective Evaluation 157 6.6 Conclusions 157 References 158 7 Multi-Channel Sound Acquisition Using a Multi-Wave Sound Field Model 161Oliver Thiergart and Emanue¨l Habets 7.1 Introduction 161 7.2 Parametric Sound Acquisition and Processing 163 7.2.1 Problem Formulation 163 7.2.2 Principal Estimation of the Target Signal 166 7.3 Multi-Wave Sound Field and Signal Model 167 7.3.1 Direct Sound Model 168 7.3.2 Diffuse Sound Model 169 7.3.3 Noise Model 169 7.4 Direct and Diffuse Signal Estimation 170 7.4.1 Estimation of the Direct Signal Ys(k, n) 170 7.4.2 Estimation of the Diffuse Signal Yd(k, n) 176 7.5 Parameter Estimation 179 7.5.1 Estimation of the Number of Sources 179 7.5.2 Direction of Arrival Estimation 181 7.5.3 Microphone Input PSD Matrix 181 7.5.4 Noise PSD Estimation 182 7.5.5 Diffuse Sound PSD Estimation 182 7.5.6 Signal PSD Estimation in Multi-Wave Scenarios 185 7.6 Application to Spatial Sound Reproduction 186 7.6.1 State of the Art 186 7.6.2 Spatial Sound Reproduction Based on Informed Spatial Filtering 187 7.7 Summary 194 References 195 8 Adaptive Mixing of Excessively Directive and Robust Beamformers for Reproduction of Spatial Sound 201Symeon Delikaris-Manias and Juha Vilkamo 8.1 Introduction 201 8.2 Notation and Signal Model 202 8.3 Overview of the Method 203 8.4 Loudspeaker-Based Spatial Sound Reproduction 204 8.4.1 Estimation of the Target Covariance Matrix Cy 204 8.4.2 Estimation of the Synthesis Beamforming Signals Ws 206 8.4.4 Processing the Synthesis Signals (Wsx) to Obtain the Target Covariance Matrix Cy 206 Spatial Energy Distribution 207 8.4.5 Listening Tests 208 8.5 Binaural-Based Spatial Sound Reproduction 209 8.5.1 Estimation of the Analysis and Synthesis Beamforming Weight Matrices 210 8.5.2 Diffuse-Field Equalization of HRTFs 210 8.5.3 Adaptive Mixing and Decorrelation 211 8.5.4 Subjective Evaluation 211 8.6 Conclusions 212 References 212 9 Source Separation and Reconstruction of Spatial Audio Using Spectrogram Factorization 215Joonas Nikunen and Tuomas Virtanen 9.1 Introduction 215 9.2 Spectrogram Factorization 217 9.2.1 Mixtures of Sounds 217 9.2.2 Magnitude Spectrogram Models 218 9.2.3 Complex-Valued Spectrogram Models 221 9.2.4 Source Separation by Time–Frequency Filtering 225 9.3 Array Signal Processing and Spectrogram Factorization 226 9.3.1 Spaced Microphone Arrays 226 9.3.2 Model for Spatial Covariance Based on Direction of Arrival 227 9.3.3 Complex-Valued NMF with the Spatial Covariance Model 229 9.4 Applications of Spectrogram Factorization in Spatial Audio 231 9.4.1 Parameterization of Surround Sound: Upmixing by Time–Frequency Filtering 231 9.4.2 Source Separation Using a Compact Microphone Array 233 9.4.3 Reconstruction of Binaural Sound Through Source Separation 238 9.5 Discussion 243 9.6 Matlab Example 243 References 247 Part III Signal-Dependent Spatial Filtering 251 10 Time–Frequency Domain Spatial Audio Enhancement 253Symeon Delikaris-Manias and Pasi Pertila 10.1 Introduction 253 10.2 Signal-Independent Enhancement 254 10.3 Signal-Dependent Enhancement 255 10.3.1 Adaptive Beamformers 255 10.3.2 Post-Filters 257 10.3.3 Post-Filter Types 257 10.3.4 Estimating Post-Filters with Machine Learning 259 10.3.5 Post-Filter Design Based on Spatial Parameters 259 References 261 11 Cross-Spectrum-Based Post-Filter Utilizing Noisy and Robust Beamformers 265Symeon Delikaris-Manias and Ville Pulkki 11.1 Introduction 265 11.2 Notation and Signal Model 267 11.2.1 Virtual Microphone Design Utilizing Pressure Microphones 268 11.3 Estimation of the Cross-Spectrum-Based Post-Filter 269 11.3.1 Post-Filter Estimation Utilizing Two Static Beamformers 270 11.3.2 Post-Filter Estimation Utilizing a Static and an Adaptive Beamformer 272 11.3.3 Smoothing Techniques 277 11.4 Implementation Examples 279 11.4.1 Ideal Conditions 279 11.4.2 Prototype Microphone Arrays 281 11.5 Conclusions and Further Remarks 283 11.6 Source Code 284 References 287 12 Microphone-Array-Based Speech Enhancement Using Neural NetworksPasi Pertila 291 12.1 Introduction 291 12.2 Time–Frequency Masks for Speech Enhancement Using Supervised Learning 293 12.2.1 Beamforming with Post-Filtering 293 12.2.2 Overview of Mask Prediction 294 12.2.3 Features for Mask Learning 295 12.2.4 Target Mask Design 297 12.3 Artificial Neural Networks 298 12.3.1 Learning the Weights 299 12.3.2 Generalization 301 12.3.3 Deep Neural Networks 305 12.4 Mask Learning: A Simulated Example 305 12.4.1 Feature Extraction 306 12.4.2 Target Mask Design 306 12.4.3 Neural Network Training 307 12.4.4 Results 308 12.5 Mask Learning: A Real-World Example 310 12.5.1 Brief Description of the Third CHiME Challenge Data 310 12.5.2 Data Processing and Beamforming 312 12.5.3 Description of Network Structure, Features, and Targets 312 12.5.4 Mask Prediction Results and Discussion 314 12.5.5 Speech Enhancement Results 316 12.6 Conclusions 318 12.7 Source Code 318 12.7.1 Matlab Code for Neural-Network-Based Sawtooth Denoising Example 318 12.7.2 Matlab Code for Phase Feature Extraction 321 References 324 Part IV Applications 327 13 Upmixing and Beamforming in Professional Audio 329Christof Faller 13.1 Introduction 329 13.2 Stereo-to-Multichannel Upmix Processor 329 13.2.1 Product Description 329 13.2.2 Considerations for Professional Audio and Broadcast 331 13.2.3 Signal Processing 332 13.3 Digitally Enhanced Shotgun Microphone 336 13.3.1 Product Description 336 13.3.2 Concept 336 13.3.3 Signal Processing 336 13.3.4 Evaluations and Measurements 339 13.4 Surround Microphone System Based on Two Microphone Elements 341 13.4.1 Product Description 341 13.4.2 Concept 344 13.5 Summary 345 References 345 14 Spatial Sound Scene Synthesis and Manipulation for Virtual Reality and Audio Effects 347Ville Pulkki, Archontis Politis, Tapani Pihlajama¨ki, and Mikko-Ville Laitinen 14.1 Introduction 347 14.2 Parametric Sound Scene Synthesis for Virtual Reality 348 14.2.1 Overall Structure 348 14.2.2 Synthesis of Virtual Sources 350 14.2.3 Synthesis of Room Reverberation 352 14.2.4 Augmentation of Virtual Reality with Real Spatial Recordings 352 14.2.5 Higher-Order Processing 353 14.2.6 Loudspeaker-Signal Bus 354 14.3 Spatial Manipulation of Sound Scenes 355 14.3.1 Parametric Directional Transformations 356 14.3.2 Sweet-Spot Translation and Zooming 356 14.3.3 Spatial Filtering 356 14.3.4 Spatial Modulation 357 14.3.5 Diffuse Field Level Control 358 14.3.6 Ambience Extraction 359 14.3.7 Spatialization of Monophonic Signals 360 14.4 Summary 360 References 361 15 Parametric Spatial Audio Techniques in Teleconferencing and Remote Presence 363Anastasios Alexandridis, Despoina Pavlidi, Nikolaos Stefanakis, and Athanasios Mouchtaris 15.1 Introduction and Motivation 363 15.2 Background 365 15.3 Immersive Audio Communication System (ImmACS) 366 15.3.1 Encoder 366 15.3.2 Decoder 373 15.4 Capture and Reproduction of Crowded Acoustic Environments 376 15.4.1 Sound Source Positioning Based on VBAP 376 15.4.2 Non-Parametric Approach 377 15.4.3 Parametric Approach 379 15.4.4 Example Application 382 15.5 Conclusions 384 References 384 Index 387

Read more less

Book SynopsisA novel approach to decision engineering, with a verified framework for modeling human reasoning Soft Computing Evaluation Logic provides an in-depth examination of evaluation decision problems and presents comprehensive guidance toward the use of the Logic Scoring of Preference (LSP) method in modeling complex decision criteria. Fully aligned with current developments in computational intelligence, the discussion covers the design and use of LSP criteria for evaluation and comparison in diverse areas, such as search engines, medical conditions, real estate, space management, habitat mitigation projects in ecology, and land use and residential development suitability maps, with versatile transfer to other similar decision-modeling contexts. Human decision making is rife with fuzziness, imprecision, uncertainty, and half-truthsyet humans make evaluation decisions every day. In this book, such decision processes are observed, analyzed, and modeled. The resuTable of ContentsPreface xvii About the Companion Website xxiii Previous Publications xxiv Acknowledgments xxv List of Symbols and Abbreviations xxvii Part One EVALUATION DECISION PROBLEMS 1 1.1 Intuitive Evaluation as a Logic Decision Process 5 1.1.1 Main Observable Steps of the Intuitive Evaluation Process 6 1.1.2 Subjective and Objective Components in Evaluation 18 1.2 Quantitative Evaluation—An Introductory Example 21 1.2.1 Stakeholders and Their Goals 21 1.2.2 Attributes 22 1.2.3 Attribute Criteria 23 1.2.4 Simple Direct Ranking 27 1.2.5 Aggregation of Attribute Suitability Degrees 29 1.2.6 Using Cost and Suitability to Compute the Overall Value 32 1.3 Drawbacks of Simple Additive and Multiplicative Scoring and Utility Models 35 1.3.1 Simple Additive Scoring: The Irresistible Attractiveness of Simplicity 36 1.3.2 Simple Multiplicative Scoring 45 1.3.3 Logic Unsuitability of Scoring and Utility Theory Models in Professional Evaluation 47 1.4 Introduction to Professional Quantitative Evaluation 51 1.4.1 Five Fundamental Types of Professional Evaluation Problems 51 1.4.2 A Survey of Typical Professional Evaluation Problems 54 1.4.3 Components of Methodology for Professional Quantitative Evaluation 58 Part Two GRADED LOGIC AND AGGREGATION 63 2.1 Graded Logic as a Generalization of Classical Boolean Logic 69 2.1.1 Aggregators and Their Classification 70 2.1.1.1 Means 71 2.1.1.2 General Aggregation Functions 71 2.1.1.3 Logic Aggregators 73 2.1.1.4 Triangular Norms and Conorms 73 2.1.2 How Do Human Beings Aggregate Subjective Categories? 75 2.1.3 Definition and Classification of Logic Aggregators 85 2.1.4 Logic Bisection, Trisection, and Quadrisection of the Unit Hypercube 92 2.1.5 Propositions, Value Statements, Graded Logic, and Fuzzy Logic 95 2.1.6 Classical Bivalent Boolean Logic 100 2.1.7 Six Generalizations of Bivalent Boolean Logic 108 2.1.7.1 Expansion of Function Domain 109 2.1.7.2 Expansion of Logic Domain 111 2.1.7.3 Expansion of Annihilator Adjustability 112 2.1.7.4 Expansion of Semantic Domain 115 2.1.7.5 Expansion of Compensative Logic Functions 117 2.1.7.6 Expansion of the Range of Andness/Orness from Drastic Conjunction to Drastic Disjunction 118 2.1.8 GL Conjecture: Ten Necessary and Sufficient GL Functions 123 2.1.9 Basic Idempotent GL Aggregators 127 2.1.10 A Summary of Differences between Graded Logic and Bivalent Boolean Logic 134 2.1.11 Relationships between Graded Logic, Perceptual Computing, and Fuzzy Logic 136 2.1.12 A Brief History of Graded Logic 142 2.2 Observable Properties of Human Evaluation Logic 147 2.2.1 Perceptual Computer and Its Basic Properties 152 2.2.2 Simultaneity and Substitutability in Evaluation Models 177 2.2.3 Basic Semantic Aspects of Evaluation Logic Reasoning 190 2.2.4 Multipolarity: Grouping and Aggregation of Semantically Heterogeneous Inputs 212 2.2.5 Grouping and Aggregation of Semantically Homogeneous Inputs 218 2.2.6 Imprecision, Incompleteness, Logic Inconsistency, and Errors 222 2.3 Andness and Orness 237 2.3.1 A General Definition of Andness/Orness 237 2.3.2 Local Andness and Orness in the Simplest Case of Two Variables 239 2.3.3 Variability of Local Andness 242 2.3.4 Mean Local Andness and Orness in the Case of Two Variables 248 2.3.5 Local and Mean Local Andness and Orness in the Case of n Variables 251 2.3.6 Global Andness and Orness 253 2.3.7 Mean Global Andness/Orness Theorems and Their Applications 272 2.3.8 Geometric Interpretations of Andness and Orness 275 2.4 Graded Conjunction/Disjunction and Logic Modeling of Simultaneity and Substitutability 283 2.4.1 Definitions and Basic Mathematical Properties of Logic Aggregators 284 2.4.2 Classification of Conjunctive and Disjunctive Logic Aggregators 295 2.4.3 Properties of Means Used in Logic Aggregation 298 2.4.4 Algebraic Properties of Aggregators Based on Weighted Power Means 304 2.4.5 Logic Aggregators Based on Weighted Means with Adjustable Andness/Orness 313 2.4.6 Selection and Use of the Threshold Andness Aggregator 318 2.4.7 Andness-Directed Interpolative GCD Aggregators 327 2.4.8 Uniform and Nonuniform Interpolative GCD Aggregators 334 2.4.8.1 The Uniform Interpolative GCD Aggregator (UGCD) 334 2.4.8.2 An Extremely Soft Interpolative Aggregator 338 2.4.8.3 An Extremely Hard Interpolative Aggregator 338 2.4.9 Extending GCD to Include Hyperconjunction and Hyperdisjunction 342 2.4.10 From Drastic Conjunction to Drastic Disjunction: A General GCD Aggregator 347 2.4.11 Gamma Aggregators versus Extended GCD Aggregators 348 2.4.11.1 Multiplicative and Additive Gamma Aggregators 351 2.4.11.2 Comparison of Gamma Aggregators and GCD 355 2.4.12 Four Main Families of GCD Aggregators and Sixteen Conditions They Must Satisfy 361 2.5 The Percept of Importance and the Use of Weights 367 2.5.1 Multiplicative, Implicative, and Exponential Weights as Importance Quantifiers 369 2.5.1.1 Multiplicative Weights 370 2.5.1.2 Implicative Weights and the Weighted Conjunction/Disjunction 374 2.5.1.3 Exponential Weights 390 2.5.2 Impact of Weights on Aggregation Results 393 2.5.3 Semantic Components in Logic Aggregation Models 398 2.5.4 Seven Techniques for Weight Adjustment 402 2.5.4.1 Importance Decomposition Method 402 2.5.4.2 Direct Weight Assessment 405 2.5.4.3 Weights Based on Ranking 405 2.5.4.4 Weights Based on Menu 407 2.5.4.5 Collective Weight Determination 409 2.5.4.6 Weights Obtained from Pairwise Comparisons 411 2.5.4.7 Weights Based on Preferential Neuron Training 414 2.5.5 Multivariate Weighted Aggregation Based on Binary Aggregation Trees 417 2.6 Partial Absorption: A Fundamental Asymmetric Aggregator 429 2.6.1 Conjunctive Partial Absorption 430 2.6.2 Disjunctive Partial Absorption 436 2.6.3 Visualizing the Partial Absorption Function, Penalty, and Reward 439 2.6.4 Mathematical Models of Penalty and Reward 442 2.6.5 Selecting Parameters of Partial Absorption 449 2.7 Logic Functions That Use Negation 453 2.7.1 Negation and De Morgan’s Duality 453 2.7.2 De Morgan’s Laws for Weighted Aggregators and Dualized Weighted Aggregators 455 2.7.3 De Morgan’s Duals of Compound Functions 458 2.7.4 Nonidempotent Logic Functions 460 2.8 Penalty-Controlled Missingness-Tolerant Aggregation 463 2.8.1 Missing Data in Evaluation Problems 463 2.8.2 Penalty-Controlled Numerical Coding of Missing Data 465 2.8.3 A Penalty-Controlled Missingness-Tolerant Aggregation Algorithm 467 2.8.4 The Impact of Penalty on Missingness-Tolerant Aggregation 472 2.9 Rating Scales and Verbalization 475 2.9.1 Design of Rating Scales 476 2.9.1.1 Strict Monotonicity of Linguistic Labeling 477 2.9.1.2 Linearity of Rating Scales 483 2.9.1.3 Balance of Rating Scales 486 2.9.1.4 Cardinality of Rating Scales 488 2.9.1.5 Hybrid Rating Scales 489 2.9.2 Stepwise Refinement of Rating Scales for Andness and Orness 491 2.9.3 Scaling and Verbalizing Degrees of Importance 496 2.9.4 Scaling and Verbalizing Degrees of Suitability/Preference 497 Part Three LSP METHOD 499 3.1 An Overview of the LSP Method 501 3.1.1 Characterization of Stakeholder and Organization of an Evaluation Project 503 3.1.2 Development of the Suitability Attribute Tree 506 3.1.3 Elementary Attribute Criteria 514 3.1.4 Logic Aggregation of Suitability 519 3.1.4.1 Logic Aggregation Using Graded Conjunction/ Disjunction 523 3.1.4.2 Logic Aggregation Using Partial Absorption 526 3.1.5 Cost/Suitability Analysis and Comparison of Evaluated Objects Using Their Overall Value 536 3.1.6 Summary of Properties of the LSP Method 540 3.2 LSP Decision Engineering Framework for Professional Evaluation Projects 543 3.2.1 Participants in a Professional Evaluation Process Based on LSP DEF 544 3.2.2 Relationships between Evaluators and Domain Experts 546 3.2.3 The Structure of LSP DEF and the Corresponding Professional Evaluation Process 547 3.2.4 Predictive Nature of Evaluation Models 551 3.2.5 Interpretation of Evaluation Results 552 3.2.6 Complexity, Completeness, and Accuracy of Evaluation Models 553 3.2.7 Combining Opinions of n Experts 555 3.2.7.1 The Maximum Likelihood Estimate 555 3.2.7.2 The Expert Competence Estimate 557 3.3 Elementary Attribute Criteria 561 3.3.1 Notation of Elementary Criteria 561 3.3.2 Verbalization of Elementary Criteria 565 3.3.3 Continuous Nonlinear Elementary Criteria 566 3.3.4 Classification of Twelve Characteristic Types of Elementary Criteria 569 3.4 Aggregation Techniques and Tools 579 3.4.1 Selecting GCD Aggregators for an LSP Project 579 3.4.2 Selecting GCD Aggregators by Training Preferential Neurons 581 3.4.3 Analytic Techniques for Selecting Partial Absorption Aggregators 589 3.4.3.1 AH Version of the Conjunctive Partial Absorption Aggregator 589 3.4.3.2 AH Version of the Disjunctive Partial Absorption Aggregator 594 3.4.4 Boundary Penalty/Reward Tables for Selecting Partial Absorption Aggregators 595 3.4.5 Selecting Partial Absorption Aggregators by Training Preferential Neurons 597 3.4.6 Nonstationary LSP Criteria 602 3.4.7 Graphic Notation of Aggregation Structures 606 3.5 Canonical Aggregation Structures 611 3.5.1 Conjunctive CAS with Increasing Andness 611 3.5.2 Disjunctive CAS with Increasing Orness 614 3.5.3 Aggregated Mandatory/Optional and Sufficient/Optional CAS 616 3.5.4 Design of a Simple LSP Evaluator Tool 617 3.5.5 Distributed Mandatory/Optional and Sufficient/Optional CAS 619 3.5.6 Nested Mandatory/Desired/Optional and Sufficient/Desired/Optional CAS 621 3.5.7 Decreasing Andness and Decreasing Orness CAS 622 3.6 Cost/Suitability Analysis as a Graded Logic Problem 623 3.6.1 Cost Analysis 623 3.6.2 Cost/Suitability Analysis Based on Linear Equi-Value Model 626 3.6.3 Using Cost/Suitability Analysis in Competitive Bidding 627 3.6.4 Conjunctive Suitability-Affordability Method 630 3.7 Sensitivity Analysis and Tradeoff Analysis 635 3.7.1 Sensitivity Analysis 635 3.7.1.1 Sensitivity with Respect to Input Suitability Scores 637 3.7.1.2 Sensitivity Properties of Basic Aggregators 641 3.7.1.3 Sensitivity with Respect to Input Attributes 643 3.7.2 Tradeoff Analysis 644 3.7.2.1 Compensatory Properties of LSP Criteria and Graded Logic Aggregators 647 3.7.2.2 The Concept of Compensation Ratio 651 3.8 Reliability Analysis 655 3.8.1 Sources of Errors in LSP Criteria and Their Empirical Analysis 655 3.8.2 The Problem of Confidence in Evaluation Results 660 3.8.3 Case Study of Reliability Analysis for a Computer Evaluation Project 664 3.9 System Optimization 671 3.9.1 Three Fundamental Constrained Optimization Problems 671 3.9.2 The Cloud Diagram and the Set of Optimum Configurations 673 3.9.3 A Case Study of Computer Configuration Optimization 675 3.10 LSP Software Technology 683 Part Four APPLICATIONS 689 4.1 Job Selection 693 4.1.1 Job Selection Attribute Tree 694 4.1.2 Elementary Attribute Criteria for Job Selection 697 4.1.3 Logic Aggregation of Suitability for the Job Selection Criterion 701 4.1.4 A Job Selection Example 705 4.2 Home Selection 711 4.2.1 Home Selection Using ORE Websites and LSPhome 711 4.2.2 Home Attribute Tree and Elementary Criteria 716 4.2.3 Home Suitability Aggregation Structure as a Shade Diagram 717 4.2.4 Using Missingness-Tolerant LSP Criteria 725 4.2.5 The Optimum Home Pricing Problem 728 4.2.6 A Personalized Home Selection Criterion 731 4.3 Evaluation of Medical Conditions 737 4.3.1 Evaluation of Disease Severity and Patient Disability 738 4.3.2 Limitations of Medical Rating Scales 740 4.3.3 LSP Models for Computing OSD, ODD, and PDD 743 4.3.4 Evaluation of PDD for Peripheral Neuropathy 745 4.3.5 The Risky Therapy Decision Problem 752 4.3.6 A Case Study of Anti-MAG Neuropathy 755 4.3.7 LSPmed—An Internet Tool for Medical Evaluation 758 4.3.7.1 LSPmed User Types and Their Functions 758 4.3.7.2 The Use of LSPmed 760 4.3.7.3 Serving a Patient 762 4.4 LSP Criteria in Ecology: Selecting Multi-Species Habitat Mitigation Projects 769 4.4.1 Multi-Species Compensatory Mitigation Projects 769 4.4.2 A Generic LSP Attribute Tree for Evaluation of Habitat Mitigation Projects 771 4.4.3 Attribute Criteria and the Logic Aggregation Structure 772 4.4.4 Sensitivity Analysis 777 4.4.5 Logic Refining of the Aggregation Structure 779 4.4.6 Cost/Suitability Analysis 781 4.4.7 MSHCP Software Support 783 4.5 Space Management Decision Problems 785 4.5.1 A Decision Model for School Location 785 4.5.1.1 Statement of the Problem 785 4.5.1.2 School Locations Attribute Tree 786 4.5.1.3 Elementary Criteria 786 4.5.1.4 Aggregation of Suitability Degrees 792 4.5.1.5 Cost Analysis 794 4.5.1.6 Competitive Locations 795 4.5.1.7 Cost/Suitability Analysis 796 4.5.2 Suitability of Locations for Residential Development 798 4.6 LSP Suitability Maps 803 4.6.1 The Concept of Map Logic and LSP Suitability Maps 803 4.6.2 Suitability Maps Based on Points of Interest 806 4.6.3 The Problem of Optimum Location of City Objects 810 4.6.4 Suitability Analysis of Urban Locations Using the LSPmap Tool 816 4.6.5 GIS-LSP Suitability Maps Based on TerrSet/Idrisi 821 4.6.6 GIS-LSP Suitability Maps Based on ArcGIS 823 4.7 Evaluation and Comparison of Search Engines 833 4.7.1 Search Engine User and Workload Models 834 4.7.2 SEben—A Search Engine Benchmarking Tool 837 4.7.3 LSP Criterion for Evaluation of Search Engines 838 4.7.4 Search Engine Evaluation Results 843 References 847 Index 871

Read more less

Book SynopsisThe first edition of Satellite Communications Systems Engineering (Wiley 2008) was written for those concerned with the design and performance of satellite communications systems employed in fixed point to point, broadcasting, mobile, radio navigation, data relay, computer communications, and related satellite based applications. This welcome Second Edition continues the basic premise and enhances the publication with the latest updated information and new technologies developed since the publication of the first edition. The book is based on graduate level satellite communications course material and has served as the primary text for electrical engineering Masters and Doctoral level courses in satellite communications and related areas. Introductory to advanced engineering level students in electrical, communications and wireless network courses, and electrical engineers, communications engineers, systems engineers, and wireless network engineers looking for a refresher wilTable of ContentsList of Acronyms xiii Preface to Second Edition xix 1 Introduction to Satellite Communications 1 1.1 Early History of Satellite Communications 3 1.1.1 SCORE 3 1.1.2 ECHO 3 1.1.3 COURIER 4 1.1.4 WESTFORD 4 1.1.5 TELSTAR 4 1.1.6 RELAY 4 1.1.7 SYNCOM 5 1.1.8 EARLYBIRD 5 1.1.9 APPLICATIONS TECHNOLOGY SATELLITE-1, ATS-1 5 1.1.10 ATS-3 5 1.1.11 ATS-5 6 1.1.12 ANIK A 6 1.1.13 ATS-6 6 1.1.14 CTS 8 1.2 Some Basic Communications Satellite System Definitions 9 1.2.1 Satellite Communications Segments 9 1.2.2 Satellite Link Parameters 10 1.2.3 Satellite Orbits 11 1.2.4 Frequency Band Designations 13 1.3 Overview of Book Structure and Topics 13 References 15 2 Satellite Orbits 17 2.1 Kepler’s Laws 18 2.2 Orbital Parameters 19 2.3 Orbits in Common Use 22 2.3.1 Geostationary Orbit 23 2.3.2 Low Earth Orbit 25 2.3.3 Medium Earth Orbit 26 2.3.4 Highly Elliptical Orbit 26 2.3.5 Polar Orbit 27 2.4 Geometry of GSO Links 27 2.4.1 Range to Satellite 29 2.4.2 Elevation Angle to Satellite 29 2.4.3 Azimuth Angle to Satellite 30 2.4.4 Sample Calculation 31 References 33 Problems 33 3 Satellite Subsystems 35 3.1 Satellite Bus 36 3.1.1 Physical Structure 37 3.1.2 Power Subsystem 38 3.1.3 Attitude Control 39 3.1.4 Orbital Control 39 3.1.5 Thermal Control 41 3.1.6 Electronic Propulsion Satellites 42 3.1.7 Tracking, Telemetry, Command, and Monitoring 43 3.2 Satellite Payload 45 3.2.1 Transponder 45 3.2.2 Antennas 47 References 48 4 The RF Link 49 4.1 Transmission Fundamentals 49 4.1.1 Effective Isotropic Radiated Power 51 4.1.2 Power Flux Density 51 4.1.3 Antenna Gain 52 4.1.4 Free-Space Path Loss 55 4.1.5 Basic Link Equation for Received Power 56 4.2 System Noise 59 4.2.1 Noise Figure 61 4.2.2 Noise Temperature 63 4.2.3 System Noise Temperature 66 4.2.4 Figure of Merit 69 4.3 Link Performance Parameters 70 4.3.1 Carrier-to-Noise Ratio 70 4.3.2 Carrier-to-Noise Density 72 4.3.3 Energy-per-Bit to Noise Density 72 Reference 73 Problems 73 5 Link System Performance 75 5.1 Link Considerations 75 5.1.1 Fixed Antenna Size Link 76 5.1.2 Fixed Antenna Gain Link 77 5.1.3 Fixed Antenna Gain, Fixed Antenna Size Link 77 5.2 Uplink 79 5.2.1 Multiple Carrier Operation 81 5.3 Downlink 81 5.4 Percent of Time Performance Specifications 82 References 84 Problems 85 6 Transmission Impairments 87 6.1 Radiowave Frequency and Space Communications 87 6.2 Radiowave Propagation Mechanisms 89 6.2.1 Absorption 90 6.2.2 Scattering 90 6.2.3 Refraction 90 6.2.4 Diffraction 90 6.2.5 Multipath 90 6.2.6 Scintillation 90 6.2.7 Fading 90 6.2.8 Frequency Dispersion 90 6.3 Propagation Below About 3 GHz 92 6.3.1 Ionospheric Scintillation 95 6.3.2 Polarization Rotation 97 6.3.3 Group Delay 98 6.3.4 Dispersion 99 6.4 Propagation Above About 3 GHz 100 6.4.1 Rain Attenuation 101 6.4.2 Gaseous Attenuation 105 6.4.3 Cloud and Fog Attenuation 107 6.4.4 Depolarization 108 6.4.5 Tropospheric Scintillation 114 6.5 Radio Noise 117 6.5.1 Specification of Radio Noise 119 6.5.2 Noise From Atmospheric Gases 121 6.5.3 Sky Noise Due To Rain 124 6.5.4 Sky Noise Due to Clouds 125 6.5.5 Noise From Extra-Terrestrial Sources 126 References 134 Problems 135 7 Propagation Effects Modeling and Prediction 138 7.1 Atmospheric Gases 138 7.1.1 Leibe Complex Refractivity Model 139 7.1.2 ITU-R Gaseous Attenuation Models 140 7.2 Clouds and Fog 152 7.2.1 ITU-R Cloud Attenuation Model 153 7.2.2 Slobin Cloud Model 155 7.3 Rain Attenuation 162 7.3.1 ITU-R Rain Attenuation Model 162 7.3.2 Crane Rain Attenuation Models 176 7.4 Depolarization 187 7.4.1 Rain Depolarization Modeling 188 7.4.2 Ice Depolarization Modeling 190 7.5 Tropospheric Scintillation 194 7.5.1 Karasawa Scintillation Model 194 7.5.2 ITU-R Scintillation Model 197 7.5.3 van de Camp Cloud Scintillation Model 199 References 201 Problems 203 8 Rain Fade Mitigation 205 8.1 Power Restoral Techniques 205 8.1.1 Beam Diversity 206 8.1.2 Power Control 207 8.1.3 Site Diversity 211 8.1.4 Orbit Diversity 227 8.2 Signal Modification Restoral Techniques 229 8.2.1 Frequency Diversity 230 8.2.2 Bandwidth Reduction 231 8.2.3 Time-Delayed Transmission Diversity 231 8.2.4 Adaptive Coding and Modulation 231 8.3 Summary 232 References 232 Problems 233 9 The Composite Link 235 9.1 Frequency Translation (FT) Satellite 236 9.1.1 Uplink 236 9.1.2 Downlink 238 9.1.3 Composite Carrier-to-Noise Ratio 238 9.1.4 Performance Implications 243 9.1.5 Path Losses and Link Performance 244 9.2 On-Board Processing (OBP) Satellite 248 9.2.1 OBP Uplink and Downlink 250 9.2.2 Composite OBP Performance 250 9.3 Comparison of FT and OBP Performance 252 9.4 Intermodulation Noise 255 9.5 Link Design Summary 257 References 258 Problems 258 10 Satellite Communications Signal Processing 261 10.1 Analog Systems 261 10.1.1 Analog Baseband Formatting 262 10.1.2 Analog Source Combining 264 10.1.3 Analog Modulation 264 10.2 Digital Baseband Formatting 270 10.2.1 PCM Bandwidth Requirements 273 10.2.2 Nearly Instantaneous Companding (NIC) 273 10.2.3 Adaptive Delta Modulation (ADM) or Continuously Variable Slope Delta Modulation (CVSD) 273 10.2.4 Adaptive Differential PCM (ADPCM) 274 10.3 Digital Source Combining 274 10.4 Digital Carrier Modulation 275 10.4.1 Binary Phase Shift Keying 278 10.4.2 Quadrature Phase Shift Keying 280 10.4.3 Higher Order Phase Modulation 283 10.5 Summary 283 Reference 284 Problems 284 11 Satellite Multiple Access 286 11.1 Frequency Division Multiple Access 289 11.1.1 PCM/TDM/PSK/FDMA 290 11.1.2 PCM/SCPC/PSK/FDMA 292 11.2 Time Division Multiple Access 293 11.2.1 PCM/TDM/PSK/TDMA 294 11.2.2 TDMA Frame Efficiency 295 11.2.3 TDMA Capacity 296 11.2.4 Satellite Switched TDMA 299 11.3 Code Division Multiple Access 303 11.3.1 Direct Sequence Spread Spectrum 306 11.3.2 Frequency Hopping Spread Spectrum 309 11.3.3 CDMA Processing Gain 310 11.3.4 CDMA Capacity 312 References 314 Problems 314 12 The Mobile Satellite Channel 316 12.1 Mobile Channel Propagation 316 12.1.1 Reflection 317 12.1.2 Diffraction 318 12.1.3 Scattering 318 12.2 Narrowband Channel 321 12.2.1 Path Loss Factor 323 12.2.2 Shadow Fading 327 12.2.3 Multipath Fading 333 12.2.4 Blockage 340 12.2.5 Mixed Propagation Conditions 346 12.3 Wideband Channel 348 12.4 Multi-Satellite Mobile Links 351 12.4.1 Uncorrelated Fading 351 12.4.2 Correlated Fading 353 References 355 13 Spectrum Management in Satellite Communications 357 13.1 Spectrum Management Functions and Activities 357 13.1.1 International Spectrum Management 358 13.1.2 World Radiocommunication Conference (WRC) 361 13.1.3 Frequency Allocation Process 361 13.1.4 Spectrum Management in the United States 365 13.2 Methods of Radio Spectrum Sharing 368 13.2.1 Frequency Separation 369 13.2.2 Spatial Separation 371 13.2.3 Time Separation 372 13.2.4 Signal Separation 372 13.3 Spectrum Efficiency Metrics 372 13.3.1 Spectrum Utilization Factor (U) 373 13.3.2 Spectrum Utilization Efficiency (SUE) 373 References 374 Problems 374 14 Interference Mitigation in Satellite Communications 376 14.1 Interference Designations 376 14.2 Modes of Interference for Satellite Services Networks 377 14.2.1 Interference Between Space and Terrestrial Services Systems 377 14.2.2 Interference Between Space Services Networks 378 14.2.3 Interference Between Space Services Networks with Reverse Band Allocations 379 14.3 Interference Propagation Mechanisms 379 14.3.1 Line-of-Sight Interference 381 14.3.2 Diffraction 382 14.3.3 Tropospheric Scatter 383 14.3.4 Surface Ducting and Layer Reflection 383 14.3.5 Hydrometeor (Rain) Scatter 384 14.4 Interference and the RF Link 386 14.4.1 Single Interferer (pfd) 387 14.4.2 Multiple Interferers (epfd) 387 14.5 Coordination for Interference Mitigation 388 14.5.1 Radio-Climate Zones 390 14.5.2 Distance Limits 391 14.5.3 Coordination Distance for Mode (1) Propagation 392 14.5.4 Coordination Distance for Mode (2) Propagation 393 14.5.5 ITU-R Coordination Procedures for Satellite and Terrestrial Services 394 References 395 Problems 396 15 High Throughput Satellites 398 15.1 Evolution of Satellite Broadband 399 15.2 Multiple Beam Antennas and Frequency Reuse 401 15.2.1 Multiple Beam Antenna Array Design 402 15.2.2 Adjacent Beam SIR 406 15.3 HTS Ground Systems Infrastructure 412 15.3.1 Network Architectures 412 15.3.2 Frequency Band Options 413 15.4 Satellite HTS and 5G 416 15.4.1 Cellular Mobile Technology Development 416 15.4.2 Satellite 5G Technologies 418 References 422 Appendix Error Functions and Bit Error Rate 423 A.1 Error Functions 423 A.2 Approximation for BER 425 Index 427

Read more less

Book SynopsisI was pleased to review Dan''s new book - pleased because he addresses an old topic in a new way. He is making no assumptions for trainers who are not fully experienced andseasoned. Hetakes them step-by-step through practical and realistic methods to set up training graduatesto actually be on-the-job performers. Enjoy,learn and be inspired. Jim Kirkpatrick, PhD Senior Consultant, Kirkpatrick Partners, USA Daniel Bixby's approach to Product Training for technical experts is practical, relevant and exactly what anyone who is required to train others on technical content really needs. He writes with candor and with a sense of ease, making the reader feel as though he is right there with you helping to develop your training competency. A must read for anyone on your team required to provide technical training to others! Jennifer Alfaro Chief Human Resources Officer, USA An expert guide to developinTable of ContentsForeword xix Preface xxi Acknowledgments xxiii How to Use This Book xxv About the Companion Website xxix Introduction xxxi Part I The Foundation of Hands-On Learning 1 1 Hands-On Learning in the Classroom: Articulate Your Approach 3 Product Training as You Know It 3 What Makes Training Effective? 4 Your Goal: Proficiency 6 Articulating Your Training Approach 6 Three Things to Document 7 Adult Learning Principles: The Foundation of Hands-On Learning 8 The Strategy of Hands-On Learning 10 The Structure of Hands-On Learning 10 The Delivery of Hands-On Learning 10 Conclusion 11 Making It Practical 11 Notes 12 2 Experiencing Learning: Emphasize Skill over Information 13 How Does One Develop a Skill? 13 Remember How You Became an Expert 14 Build on Your Students’ Experiences 14 Create Experiences in the Classroom 15 Let Them Learn from Negative Experiences 16 Allow Students to Make Mistakes 17 Capitalize on Informal Learning 17 Allow Students to Share Their Experiences 18 Give Lecture and Observation Their Rightful Place 19 Provide a Structure for Your Hands-On Training 19 Phase One: Exhibit the Product 19 Phase Two: Execute a Function 20 Phase Three: Explore Independently 20 Apply All Three Phases 21 Conclusion 21 Making It Practical 21 Note 22 3 You Know It, Can You Teach It? Overcoming Your Own Intelligence 23 Address Your Biggest Challenge: Yourself 23 The Four Stages of Competency Applied to Instructors 24 Unconsciously Unskilled 25 Consciously Unskilled 25 Consciously Skilled 25 Unconsciously Skilled 25 Why Experts Find It Difficult to Teach 26 Experts Rarely Remember How They Perfected Their Skill 26 Experts Have Trouble Distinguishing Between the Simple and the Difficult 26 Experts Don’t Differentiate Between the Essential and the Nonessential 27 How Experts Can Teach It 27 Ask the Instructor (Yourself) the Right Questions 28 Conclusion 29 Making It Practical 29 Note 30 4 Ready or Not? Why Some Students Are More Ready to Learn Than Others 31 The Four Principles of Learner-Readiness 31 They Must Recognize the Need for Learning 32 What if Their Reason for Learning Is Wrong? 32 They Must Take Responsibility for Their Learning 32 Questions Demonstrate Learning 33 The Instructor’s Responsibility 33 They Must Relate It to Their Experience 34 They Must Be Ready to Apply It 35 Conclusion 35 Making It Practical 36 Part II The Strategy of Hands-On Learning 37 5 It is Never Just Product Training: Why You Should Offer the Training 39 Product Solution Training Versus Talent Development 39 Employee Product Training 40 Customer Product Training 41 Business Plan 41 Training as a Cost of Doing Business 41 Training as a Profit Center 42 Training that Sells Products 44 Conclusion 44 Making It Practical 45 Note 46 6 From Good to Great: Defining the Focus of Effective Product Training 47 Aim at the Right Target: Doing Versus Knowing 47 Change the Approach: Facilitator Versus Lecturer 48 Call It the Right Thing: Training Versus Presentation 49 Make It Sustainable: Standardized Versus Customized 51 Measure the Right Things: Performance Versus Reactions 51 Value the Right Things: Results Versus Head Count 52 Use the Right Delivery Methods: Effectiveness Versus Availability 52 Continue the Conversation: Process Versus Event 54 Keep Improving: Progress Versus Contentment 55 Conclusion 55 Making It Practical 55 7 What Is Expected Must Be Inspected: Assessing and Evaluating Hands-On Learning 57 Assessing the Individual 58 Assessing Their Knowledge 58 Quizzes 58 Exams 59 About Creating Exam Questions 59 About Administrating the Exam 60 Assessing Their Skills 60 Creative Assessments 61 Combining the Grades 61 Evaluating the Class 62 Evaluating Perceptions 64 A Note about Measuring Instructor’s Facilitation Skills 65 Conclusion 65 Making It Practical 65 Notes 66 Part III The Structure of Hands-On Learning 67 8 Dethroning King Content: A Paradigm Shift 69 When Content Is King 70 What if Content Is All They Need? 70 How to Tell if Content Is King 71 Giving Content Its Rightful Place 71 Introducing the 4 × 8 Proficiency Design Model 72 Is Training the Solution? 73 Training Will Not Improve Your Product or Solution 74 Training Is Not a Marketing Gimmick 74 How Can You Know if Training Is the Solution? 75 Conclusion 75 Making It Practical 76 Note 77 9 Designing for Proficiency: Determining the Curriculum 79 The 4 × 8 Proficiency Design Model 80 Level 1 80 Business Goal 80 Intended Audience 81 Level 2 82 Objectives 82 Exercise 83 Level 3 84 Outline 84 Constructive Activities 87 Determine Delivery Method 88 Delivery Method 88 Duration 89 Maximum Number of Students 89 Other Logistics 89 Level 4 89 Provide an Assessment to Validate the Learning 89 Create the Content 89 Why Is Content After Assessment? 90 Conclusion 90 Making It Practical 91 10 Pixels or Paper? How to Build the Content and Deliverables 93 Ask the Questions Again 93 Create a Student Guide 94 Create Your Visual Aids 95 Creating Presentation Slides 96 Use the Software Correctly 96 Don’t Rely on a Presentation 96 Don’t Let the Presentation Tie You Down 97 Know Your Material 97 Creating Handouts 98 Statement of Indemnification 98 Create an Instructor’s Guide 99 Running a Pilot Class 99 When an Instructor Teaches This Class for the First Time 99 When This Class Is Being Taught for the First Time 100 Handpick the Audience 100 Plan on Extra Time 100 Be Aware of Too Many Auditors 100 Debrief with Everyone 101 Debrief with Your Core Team 101 Conclusion 101 Making It Practical 101 Part IV The Facilitation of Hands-On Learning 103 11 Speak Up: Effective Verbal Engagement 105 Decorative Speaking 106 Controlled Energy 106 Controlled Breathing 106 Controlled Pitch 107 Controlled Tempo 108 Controlled Volume 108 Controlled Articulation 109 Declarative Speaking 109 Controlled Jargon 109 Verbal Crutches 110 If Your Use of Verbal Crutches Is a Communication Issue 110 If Your Use of Verbal Crutches Is a Habit 111 Poor Grammar 111 Conclusion 111 Making It Practical 112 Notes 113 12 Shut Up: Effective Listening and Engagement 115 What You Are Listening for 115 What They Already Know (or Think They Know) 116 What They Want to Learn 116 What They Have Learned 117 The Foundation for Engaging Learning 117 Students Learn Better When They’re Awake 117 Learners Require Time to Absorb the Learning 117 Set the Expectation for Engagement 118 Practical Engagement in the Classroom 118 Engaging as a Conversation 118 Engaging with Questions and Answers 120 Why Instructors Ask Questions 120 When and How to Ask Questions 121 Answering Student Questions 122 Engaging Group Learning Activities 123 Engaging Labs and Exercises 124 Icebreakers, Games, and Other Interactive Options 124 When Should They Be Done? 125 Games and Gamification 125 Interactive Technology 126 Conclusion 126 Making It Practical 126 13 Stand Up: Effective Nonverbal Engagement 129 Observed Communication: What They See You Saying 129 Posture 130 Facial Expressions 131 Eye Contact 131 Gestures 132 Physical Presence 132 Physical Appearance 133 Perceived Communication: What They Feel You Are Saying 134 Be Genuine and Humble 134 Be Likeable and Pleasant 134 Be Available and Prepared 134 Be Positive and Have Fun 134 Be Confident and in Control 135 Environmental Influences 136 Room Layout 136 Furniture, Lighting, and Technology 136 Know Your Environment 136 Hosting a Training Event 137 Make Your Students Feel Welcome 137 Conclusion 138 Making It Practical 139 Note 140 14 The Smartest Engineer: And Other Difficult Students 141 Set the Expectations at the Beginning 141 Take Responsibility for Your Learning 141 Be Prepared for Difficult Responses 142 The Stubborn Mule 142 The Pessimist 143 The Helper 143 The Talker 144 The Extreme Introvert 144 The Sleeper 144 The Expert 145 Conclusion 145 Making It Practical 146 15 Virtual Facilitation: Tips for Effective Webinars 147 What Doesn’t Change 147 The Philosophical Approach 147 The Structure 148 The Definition 148 Facilitating Virtually 148 Regarding the Presentation 149 Regarding the Tool 149 About the Event 149 Conclusion 150 Making It Practical 150 16 Technical Presentations: Effectively Design and Deliver Technical Information 151 When to Use Presentations 151 When the Objective Is to Deliver Information 152 When Time Is Limited 152 When the Audience Is Large 153 To Motivate and Encourage Change 154 How to Design Effective Technical Presentations 154 Determine the Delivery Method (Optional) 156 Informational Objectives 156 Motivational Objectives 156 Delivering Your Presentation 159 Ask Questions 159 Practice, Practice, Practice 159 Relax and Have Fun! 160 Conclusion 160 Making It Practical 160 17 Culture and Proficiency: Training for Proficiency in a Global Environment 161 What Doesn’t Change 162 The Philosophy of Hands-on Learning 162 The Strategy of Hands-on Learning 162 The Structural Design of Hands-on Learning 163 What Does Change 163 The Delivery of Hands-on Learning 163 The Facilitation of Hands-on Learning 164 Other Tips for the Traveling Trainer 165 Conclusion 165 Making It Practical 166 Part V The Operation of Hands-On Learning 167 18 Certifying Proficiency: The Fundamentals of a Product Proficiency Certification Program 169 What Is Product Proficiency Certification? 169 When Do You Need a Certification Program? 170 When Is a Certificate Program Sufficient? 170 Why You Should Consider a Certification Program 171 If the Product Is Complex 171 If Your Product Is Unique 172 Products That Are New to the Market 172 When the Go-to-Market Strategy Is Indirect or Complex 172 If It Involves More Than One Party to Integrate 173 If There Are Standards That Must Be Met 174 If There Are Industry or Company Standards That Must Be Met 174 When Quality Standards Must Be Verified 174 If the Product or Technology Changes Regularly 175 If Misuse Could Cause a Safety Issue 175 The Requirements of Product Proficiency Certification 175 Proof of Authenticity 176 Board of Decision-Makers 176 Curriculum and Program Acceptance 176 Proof of Conformity 176 Education or Experience 177 Exam and/or Proficiency Assessment 177 Code of Conduct 177 Recertification or Maintenance 177 Instructor Certification Process 178 Proof of Impartiality 179 Selection and Opportunity 179 Administration and Traceability 179 Exceptions and Deviations 179 Documenting the Certification Program 180 Certification Program Document 180 Process Documents 180 Conclusion 182 Making It Practical 182 Notes 182 19 Managing the Details: The Effective Administration of Hands-On Learning 183 Measurability 183 Sustainability 184 Revision Control 185 Simple Revision Tracking 185 Global Enterprise Classification 186 Propose, Approve, Implement 191 Train the Trainer 191 Prerequisites and Follow-Up 192 Prerequisites 192 Follow-Up 192 Traceable 193 Tracking People and Programs 193 Tracking Business Results 195 Tracking Compliance 196 Tracking Revenue Generation 196 Tracking Cost Savings 196 Improve Services 196 Conclusion 197 Making It Practical 197 Notes 197 20 Developing New Product Talent: Effective Mentoring of New and Junior Employees 199 Why Mentoring Matters 199 Why It Matters to the Mentor 200 Employers Value Mentoring Experts 200 Successful Experts Are Teaching Experts 201 Why It Matters to Your Company 201 Mentored Employees Have Real Input Sooner 201 More Meaningful Experience Sooner 202 Mentoring for Proficiency 202 Multiple Mentors 202 Real-Time Mentoring 203 Partnership Mentoring 203 The Foundation of a Mentoring Program 203 Develop a Structure for Success 203 Get Appropriate Endorsement and Approvals 204 Set Realistic Goals 204 Create Individual Objectives 204 Define the Qualifications of a Good Mentor 205 Aptitude 205 Attitude 205 Conclusion 206 Making It Practical 206 21 Now, Go Do It: To Be an Effective Trainer, You Must Train 207 Define Your Approach 207 DO Articulate How You Will Make Learning Effective 207 DO Emphasize Proficiency over Knowledge 207 DO Become Consciously Skilled on Your Products 208 DO Identify Students That Are Ready to Learn 208 Develop with a Strategy 208 DO Demonstrate the Value of Training 208 DO Improve Your Training from Good to Great 208 DO Inspect and Evaluate Your Training 208 Design with a Structure 208 DO Dethrone King Content 208 DO Use the 4 × 8 Proficiency Design Model 209 DO Build Engaging Content and Deliverables 209 Deliver with a Purpose 209 DO Speak Up 209 DO Shut Up and Listen to Your Students 209 DO Stand Up and Be Confident 209 DO Prepare for Difficult Students and Circumstances 209 DO Deliver Effective Virtual Training 209 DO Deliver Effective Technical Presentations 210 DO Allow for Flexibility When Training in Other Cultures 210 Don’t Forget the Details 210 DO Define Certification Properly 210 DO Manage the Details Properly 210 DO Mentor New Employees 210 Conclusion 210 Making It Practical 211 Part VI For the Boss: Executive Overviews 213 22 The Foundation of Hands-On Learning: An Executive Summary 215 An Overview 215 How You Can Help 216 Conclusion 217 23 The Strategy of Hands-On Learning: An Executive Summary 219 Overview 219 How You Can Help 220 Conclusion 221 24 The Structure of Hands-On Learning: An Executive Summary 223 Overview 223 How You Can Help 224 Conclusion 225 25 The Facilitation of Hands-On Learning: An Executive Summary 227 Overview 227 How You Can Help 228 Conclusion 229 26 The Operation of Hands-On Learning: An Executive Summary 231 Overview 231 How You Can Help 232 Conclusion 233 Index 235

Read more less

Book SynopsisThis comprehensive text examines existing and emerging electrical drive technologies. The authors clearly define the most basic electrical drive concepts and go on to explain the most important details while maintaining a solid connection to the theory and design of the associated electrical machines. Also including links to a number of industrial applications, the authors take their investigation of electrical drives beyond theory to examine a number of practical aspects of electrical drive control and application. Key features: * Provides a comprehensive summary of all aspects of controlled-speed electrical drive technology including control and operation. * Handling of electrical drives is solidly linked to the theory and design of the associated electrical machines. Added insight into problems and functions are illustrated with clearly understandable figures. * Offers an understanding of the main phenomena associated with electrical mTable of ContentsPreface vii Abbreviations and Symbols ix 1 Introduction to Electrical Machine Drives Control 1 2 Aspects Common to All Controlled Electrical Machine Drive Types 17 3 The Fundamentals of Electric Machines 36 4 The Fundamentals of Space-Vector Theory 66 5 Torque and Force Production and Power 91 6 Basic Control Principles for Electric Machines 107 7 DC and AC Power Electronic Topologies – Modulation for the Control of Rotating-Field Motors 147 8 Synchronous Electrical Machine Drives 191 9 Permanent Magnet Synchronous Machine Drives 296 10 Synchronous Reluctance Machine Drives 346 11 Asynchronous Electrical Machine Drives 373 12 Switched Reluctance Machine Drives 449 13 Other Considerations: The Motor Cable, Voltage Stresses, and Bearing Currents 469 Index 499

Read more less