Electronics and communications engineering Books
John Wiley & Sons Inc INCOSE Needs and Requirements Manual
Book SynopsisComplete and comprehensive manual for eliciting, defining, and managing needs and requirements, integration, verification, and validation across the lifecycle The INCOSE Needs and Requirements Manual presents product development and systems engineering practices, activities, and artifacts from the perspective of needs, requirements, verification, and validation across the system lifecycle. Composed of 16 chapters, this book provides practical guidance to help organizations understand the importance of lifecycle concepts, needs, requirements, verification, and validation activities, enabling them to successfully and effectively implement these activities during product development, systems engineering, and project management. The parent handbook published by Wiley, INCOSE Systems Engineering Handbook, divides the system lifecycle into a series of processes, with each process described in terms of a series of activities. This Manual provides more detail needed by practitioners to success
£65.25
Wiley-Blackwell Sensor Fusion Approaches for Positioning Navigati
Book Synopsis
£99.00
John Wiley & Sons Inc Modern Ferrites Volume 2
Book SynopsisMODERN FERRITES, Volume 2 A robust exploration of the basic principles of ferrimagnetic and their applications In Modern Ferrites: Volume 2, renowned researcher and educator, Vincent G. Harris delivers a comprehensive overview of ferrimagnetic phenomena and discussions of select applications of modern ferrite materials in emerging technologies and applications. Volume 2 explores fundamental properties of ferrite systems, including their structure, chemistry, and magnetism, as well as practical applications, such as permanent magnets; inductors, inverters, and filters; and their use in emerging applications as metamaterials, multiferroics, and biomedical technologies. In addition to the properties of ferrites, the included resources explore the processing, structure, and property relationships in ferrites as nanoparticles, thin and thick films, compacts, and crystals. The authors discuss how these relationships are key to realizing practical device applicat
£103.50
John Wiley & Sons Inc Metaverse Communication and Computing Networks
Book SynopsisMetaverse Communication and Computing Networks Understand the future of the Internet with this wide-ranging analysis Metaverse is the term for applications that allow users to assume digital avatars to interact with other humans and software functions in a three-dimensional virtual space. These applications and the spaces they create constitute an exciting and challenging new frontier in digital communication. Surmounting the technological and conceptual barriers to creating the Metaverse will require researchers and engineers familiar with its underlying theories and a wide range of technologies and techniques. Metaverse Communication and Computing Networks provides a comprehensive treatment of Metaverse theory and the technologies that can be brought to bear on this new pursuit. It begins by describing the Metaverse's underlying architecture and infrastructure, physical and digital, before addressing how existing technologies are being adapted to its us
£95.40
John Wiley & Sons Inc Teach Yourself VISUALLY Photoshop Elements 2023
Book SynopsisA fast and easy way for visual learners to get a grip on Photoshop Elements Are you a visual learner? Do you prefer a single, crystal-clear screenshot showing you how to do something to a long-winded explanation telling you how to do it? If so, then this book is for you. Open up Teach Yourself VISUALLY Photoshop Elements and you'll find vibrant, step-by-step screenshots showing you how to master over 100 Photoshop Elements tasks. Each task-based spread covers one technique at a time, ensuring you get up and running fast. You'll learn how to: Organize, import, save, and print your photosEnhance the lighting and color of pictures that need a little sprucing upApply cool effects that make your photos more lively and interestingThe book breaks big topics down into bite-sized modules with succinct explanations, walking you through every step you need to take. The full-color screenshots demonstrate each task, and helpful sidebars offer practical, hands-on tips and tricks you'll use every timTable of ContentsChapter 1 Getting Started Introducing Photoshop Elements 2023 4 Understanding Digital Images 6 Start Photoshop Elements 8 Explore the Editor Workspace 9 Tour the Organizer Workspace 10 Switch Between the Organizer and the Editor 11 Introducing the Photoshop Elements Tools 12 Switch Editing Modes 14 Work with Tools 16 Work with Panels 18 Set Program Preferences 20 View Rulers and Guides 22 Chapter 2 Importing and Opening Digital Images Get Photos for Your Projects 26 Import Photos from a Digital Camera or Card Reader 28 Import Photos from a Scanner 30 Open a Photo 32 Create a Blank Image 34 Save an Image 36 Print Photos 38 Create a Photo Panorama 40 Duplicate a Photo 42 Close a Photo 43 Chapter 3 Applying Basic Image Edits Manage Open Images 46 Using Layouts 48 Using the Zoom Tool 50 Pan the Image 52 Change the Canvas Size 54 Resize an Image by Resampling 56 Crop an Image 58 Straighten an Image 60 Rotate an Image 61 Work in Quick Mode 62 Apply an Effect in Quick Mode 64 Add a Frame in Quick Mode 65 Apply Automatic Enhancements 66 Add a Texture 68 Undo Edits 70 Revert an Image 71 Chapter 4 Using Layers Introducing Layers 74 Create and Add Content to a Layer 76 Hide a Layer 78 Move a Layer 79 Duplicate a Layer 80 Delete a Layer 81 Reorder Layers 82 Change the Opacity of a Layer 84 Link Layers 85 Merge Layers 86 Rename a Layer 87 Create a Fill Layer 88 Blend Layers 90 Chapter 5 Making Selections Select an Area with the Marquee 94 Select an Area with the Lasso 96 Select an Area with the Magic Wand 100 Select an Area with the Quick Selection Tool 102 Select an Area with the Selection Brush 104 Save and Load a Selection 106 Invert a Selection 108 Deselect a Selection 109 Chapter 6 Manipulating Selections Add to or Subtract from a Selection 112 Move a Selection 114 Apply the Content-Aware Move Tool 116 Copy and Paste a Selection 118 Delete a Selection 119 Rotate a Selection 120 Scale a Selection 121 Skew or Distort a Selection 122 Refine the Edge of a Selection 124 Use Feathering to Create a Soft Border 126 Chapter 7 Enhancing Lighting, Color, and Sharpness Adjust Levels 130 Adjust Shadows and Highlights 132 Change Brightness and Contrast 134 Use the Dodge and Burn Tools 136 Sharpen an Image 138 Use the Blur and Sharpen Tools 140 Adjust Skin Color 142 Adjust Color with the Sponge Tool 144 Replace a Color 146 Convert a Color Photo to Black and White 148 Add Color to a Black and White Photo 150 Adjust Colors by Using Color Curves 152 Apply the Auto Smart Tone Tool 154 Chapter 8 Applying Quick and Guided Edits Quickly Fix a Photo 158 Remove Red Eye 160 Remove a Color Cast 162 Restore an Old Photo 164 Improve a Portrait 166 Apply a Lomo Camera Effect 168 Add Motion with Zoom Burst 170 Create a Perfect Pet Pic 172 Create Soft Focus with the Orton Effect 174 Apply a Reflection 176 Make a Meme 178 Create a Vintage Look 180 Chapter 9 Painting and Drawing on Photos Retouch with the Clone Stamp Tool 184 Remove a Spot 186 Set the Foreground and Background Colors 188 Add Color with the Brush Tool 190 Change Brush Styles 192 Use a Brush to Replace a Color 194 Adjust Colors with the Smart Brush 196 Draw a Simple Shape 198 Add an Arrow 200 Apply the Eraser 202 Apply a Gradient 204 Add Content from the Graphics Panel 206 Add Text 208 Modify Text 210 Create Warped Text 212 Draw Text Around a Shape 214 Add a Layer Mask 216 Edit a Layer Mask 218 Chapter 10 Applying Filters and Styles Equalize an Image 222 Create a Negative 223 Blur an Image 224 Distort an Image 226 Turn an Image into Art 228 Turn an Image into a Sketch 230 Create a Print Halftone 232 Add a Drop Shadow to a Layer 234 Apply Other Styles 236 Enhance with an Effect 237 Chapter 11 Organizing Your Photos Introducing the Organizer 240 Open the Organizer 242 Change the View 243 Create a Catalog 244 View Photos in Media View 246 View Photos in Full Screen 248 View File Information 250 Work with Albums 252 Find Photos 254 View Versions of a File 256 Remove a Photo from the Organizer 257 Apply an Instant Fix 258 Perform Other Organization Tasks 260 Index 262
£21.24
John Wiley & Sons Inc The Economics of Microgrids
Book SynopsisTHE ECONOMICS OF MICROGRIDS An incisive and practical exploration of the engineering economics of microgrids In The Economics of Microgrids, a pair of distinguished researchers delivers an expert discussion of the microeconomic perspectives on microgrids in the context of low-carbon, sustainable energy delivery. In the book, readers will explore an engineering economics framework on the investment decisions and capital expenditure analyses required for an assessment of microgrid projects. The authors also examine economic concepts and models for minimizing microgrid operation costs, including the cost of local generation resources and energy purchases from main grids to supply local loads. The book presents economic models for the expansion of microgrids under load and market price uncertainties, as well as discussions of the economics of resilience in microgrids for optimal operation during outages and power disturbances. Readers will also find: A thorough introduction to the engineer
£85.46
John Wiley & Sons Inc Microgrids for Commercial Systems
Book SynopsisMICROGRIDS for COMMERCIAL SYSTEMS This distinct volume provides detailed information on the concepts and applications of the emerging field of microgrids for commercial applications, offering solutions in the design, installation, and operation of this new, cutting-edge technology. The microgrid is defined as Distributed Energy Resources (DER) and interconnected loads with clearly defined electrical boundaries that act as a single controllable entity concerning the grid as per IEEE standard 2030.7-2017. It provides an uninterrupted power supply to end-user loads with high reliability. Commercial systems like IT/ITES, shopping complexes, malls, the banking sector, hospitals, etc., need an uninterrupted input power supply with high reliability. Microgrids are more suitable for commercial systems to service their clients with no service discontinuity. The microgrid enables both connection and disconnection from the grid. That is, the microgrid can operate both in grid-connected and islan
£153.00
John Wiley & Sons Inc Advanced Ultra LowPower Semiconductor Devices
Book SynopsisADVANCED ULTRA LOW-POWER SEMICONDUCTOR DEVICES Written and edited by a team of experts in the field, this important new volume broadly covers the design and applications of metal oxide semiconductor field effect transistors. This outstanding new volume offers a comprehensive overview of cutting-edge semiconductor components tailored for ultra-low power applications. These components, pivotal to the foundation of electronic devices, play a central role in shaping the landscape of electronics. With a focus on emerging low-power electronic devices and their application across domains like wireless communication, biosensing, and circuits, this book presents an invaluable resource for understanding this dynamic field. Bringing together experts and researchers from various facets of the VLSI domain, the book addresses the challenges posed by advanced low-power devices. This collaborative effort aims to propel engineering innovations and refine the practical implementation ofTable of ContentsPreface xi 1 Subthreshold Transistors: Concept and Technology 1Ball Mukund Mani Tripathi 1.1 Introduction 2 1.2 Major Sources of Leakage and Possible Methods of Prevention 2 1.3 Possibilities and Challenges 12 1.4 Conclusions 21 2 Introduction to Conventional MOSFET and Advanced Transistor TFET 29M. Saravanan, K. Ramkumar, Eswaran Parthasarathy, J. Ajayan and S. Sreejith 2.1 Introduction 30 2.2 Device Structure 30 2.3 TFET Principle of Operation 31 2.4 Material Characterization 33 2.5 Characteristics of TFET 35 2.6 Comparison of OFF-State Characteristics 37 2.7 Phonon Scattering's Impact 39 2.8 ON-State Performance Comparison 40 2.9 Performance Analysis Based on Intrinsic Delay 40 2.10 Bandgap's Effect on Device Performance 41 2.11 MOSFET and TFET Scaling Behaviour 43 2.12 Surface Potential of an N-TFET and N-MOSFET 45 2.13 Professional Advantages of TFET over MOSFET 46 2.14 Conclusion 46 3 Operation Principle and Fabrication of TFET 51Mekonnen Getnet Yirak and Rishu Chaujar 3.1 Introduction 52 3.2 Planar MOSFET's Limitations 54 3.3 Demand for Low Power Operation 55 3.4 TFET: Operation Principle of TFET 56 3.5 TFET: Recent Design Issues in TFET 63 3.6 TFET: Modeling and Application 65 3.7 TFET: Fabrication Perspective 68 3.8 TFET: Applications and Future of Low-Power Electronics 70 3.9 Expected Challenges in Replacing MOSFET with TFET 70 3.10 Conclusion 71 4 Mathematical Modeling of TFET and Its Future Applications: Ultra Low-Power SRAM Circuit and III-IV TFET 77Nayana G H and P. Vimala 4.1 Introduction 78 4.2 Modeling Approaches 78 4.3 Structure 81 4.4 Applications of Tunnel Field-Effect Transistor 83 4.5 Road Ahead for Tunnel Field Effect Transistors 87 5 Analysis of Channel Doping Variation on Transfer Characteristics to High Frequency Performance of F-TFET 91Prabhat Singh and Dharmendra Singh Yadav 5.1 Introduction 92 5.2 Simulated Device Structure and Parameters 93 5.3 DC Characteristics 93 5.4 Analysis of Analog/RF FOMs 98 5.5 Conclusion 101 6 Comparative Study of Gate Engineered TFETs and Optimization of Ferroelectric Heterogate TFET Structure 105Susmitha Kothapalli, Zohmingliana and Brinda Bhowmick 6.1 Introduction 106 6.2 Study of Different TFET Structures 106 6.3 Proposed Structure 109 6.4 Results and Discussion 110 6.5 Conclusion 127 6.6 Future Scope 128 7 State of the Art Tunnel FETs for Low Power Memory Applications 131Arun A. V., Sreelekshmi P. S. and Jobymol Jacob 7.1 Static Random Access Memory 131 7.2 Performance Parameters of SRAM Cell 134 7.3 TFET-Based SRAM Cell Design 135 7.4 Conclusion 159 8 Epitaxial Layer-Based Si/SiGe Hetero-Junction Line Tunnel FETs: A Physical Insight 165Abhishek Acharya, Sourabh Panwar, Shobhit Srivastava and Shashidhara M. 8.1 Fundamental Limitation of CMOS: Tunnel FETs 165 8.2 Working Principle of Tunnel FET 168 8.3 Point and Line TFETs: Tunneling Direction 169 8.4 Perspective of Line TFETs 170 8.5 Analytical Models of Line TFETs 176 8.6 Line TFETs for Analog & Digital Circuits Design 178 8.7 Other Steep Slope Devices 179 8.8 Conclusion 181 9 Investigation of Thermal Performance on Conventional and Junctionless Nanosheet Field Effect Transistors 187Sresta Valasa, Shubham Tayal and Laxman Raju Thoutam 9.1 Introduction 188 9.2 Device Simulation Details 190 9.3 Results and Discussion 192 9.4 Conclusion 201 10 Introduction to Newly Adopted NCFET and Ferroelectrics for Low-Power Application 207Shelja Kaushal 10.1 Introduction 208 10.2 NCFET and Its Design Constraints 209 10.3 NCFET for Low-Power Applications 216 10.4 Summary 226 11 Application of Ferroelectrics: Monolithic-3D Inference Engine with IGZO Based Ferroelectric Thin Film Transistor Synapses 235Sourav De, Maximilian Lederer, Yannick Raffel, David Lehninger, Sunanda Thunder, Michael P.M. Jank, Tarek Ali and Thomas Kämpfe 11.1 Introduction 236 11.2 Ferroelectricity in Hafnium Oxide 241x Contents 11.3 IGZO Based Ferroelectric Thin Film Transistor 245 11.4 Applications in Neural Networks 249 11.5 Conclusion 250 12 Radiation Effects and Their Impact on SRAM Design: A Comprehensive Survey with Contemporary Challenges 261Y. Alekhya, Umakanta Nanda and Chandan Kumar Pandey 12.1 Introduction 261 12.2 Literature Survey 263 12.3 Impact of Radiation Effects on Sram Cells 266 12.4 Results and Discussion 267 12.5 Conclusion 274 13 Final Summary and Future of Advanced Ultra Low Power Metal Oxide Semiconductor Field Effect Transistors 279Young Suh Song, Shiromani Balmukund Rahi, Shahnaz Kossar, Abhishek Kumar Upadhyay, Shubham Tayal, Chandan Kumar Pandey and Biswajit Jena 13.1 Introduction 280 13.2 Challenges in Future Ultra-Low Power Semiconductors 282 13.3 Conclusion 286 References 288 Index 293
£140.40
John Wiley & Sons Inc Drone Technology
Book SynopsisDRONE TECHNOLOGY This book provides a holistic and valuable insight into the revolutionary world of unmanned aerial vehicles (UAV). The book elucidates the revolutionary and riveting research in the ultramodern domain of drone technologies, drone-enabled IoT applications, and artificial intelligence-based smart surveillance. The book explains the most recent developments in the field, challenges, and future scope of drone technologies. Beyond that, it discusses the importance of a wide range of design applications, drone/UAV development, and drone-enabled smart healthcare systems for smart cities. It describes pioneering work on mitigating cyber security threats by employing intelligent machine learning models in the designing of IoT-aided drones. The book also has a fascinating chapter on application intrusion detection by drones using recurrent neural networks. Other chapters address interdisciplinary fields like artificial intelligence, deep learning, the role of drones in healthTable of ContentsPreface xvii 1 Drone Technologies: State-of-the-Art, Challenges, and Future Scope 1 Arun Agarwal, Chandan Mohanta and Saurabh Narendra Mehta 1.1 Introduction 2 1.2 Forces Acting on a Drone 3 1.3 Principal Axes 3 1.4 Broad Classification of Drones 3 1.4.1 Fixed-Wing Drones 3 1.4.1.1 Advantages 4 1.4.1.2 Disadvantages 5 1.4.2 Lighter-Than-Air Systems 5 1.4.2.1 Advantages 5 1.4.2.2 Disadvantages 6 1.4.3 Multi-Rotor Configuration 6 1.4.3.1 Advantages 6 1.4.3.2 Disadvantages 7 1.5 Military Necessity of Drones 7 1.5.1 Features of Sixth-Generation Fighter Planes 7 1.5.1.1 Introduction 7 1.5.1.2 Cyber Warfare and Cyber Security 9 1.5.1.3 Artificial Intelligence 9 1.5.1.4 Drones and Drone Swarms 10 1.5.1.5 Directed Energy Weapons 10 1.5.2 Pseudo Satellite of HAL 11 1.5.3 Surface to Air Missile vs. Modern Fighter Aircraft 13 1.5.4 Drones as Weapons of Mass Destruction 14 1.6 Conclusion and Future Scope 16 References 17 2 Introduction to Drone Flights—An Eye Witness for Flying Devices to the New Destinations 21 S. Venkata Achuta Rao, P. Srilatha, G.V.R.K. Acharyulu and G. Suryanarayana 2.1 Introduction 22 2.1.1 Brief History 23 2.1.2 The Indomitable Significance of Drone Technology 23 2.1.3 Trends 24 2.2 How Drones Work and Their Anatomy 25 2.2.1 Anatomy of a Drone 25 2.2.1.1 Propellers 25 2.2.1.2 Brushless Motors 26 2.2.1.3 Landing Gear 26 2.2.1.4 Electronic Speed Controllers [ESC] 26 2.2.1.5 Flight Controller 26 2.2.1.6 Receiver 27 2.2.1.7 Transmitter 27 2.2.1.8 GPS Module 27 2.2.1.9 Battery 27 2.2.1.10 Camera 28 2.2.2 Types of Drones 28 2.2.2.1 Sub-System of UAVs 29 2.2.2.2 Other Specific Types of Drones 29 2.2.3 Components of Drones 32 2.2.3.1 Hardware 32 2.2.3.2 Software 33 2.2.3.3 Other Specific Components 33 2.3 Salient Features and Important Codes with Public Awareness with Respect to Safety and Necessary Precautionary Points 36 2.3.1 Safety and Legal Note 36 2.3.2 Public Perception 36 2.3.3 Crew 36 2.3.4 Know Before You Fly 36 2.3.5 Simulation Training 37 2.3.6 Mapping Configuration 37 2.3.7 Mapping BFS Camera and Mapping Camera Mount 37 2.3.8 Equipment to Remove 38 2.3.9 Flight Planning 38 2.3.10 Post Processing Data 39 2.4 Top 10 Stunning Applications of Drone Technology 39 2.4.1 Aerial Photography 40 2.4.2 Shipping and Delivery 40 2.4.3 Geographic Mapping 40 2.4.4 Disaster Management 40 2.4.5 Precision Agriculture 40 2.4.6 Search and Rescue 41 2.4.7 Weather Forecast 41 2.4.8 Wildlife Monitoring 41 2.4.9 Law Enforcement 41 2.4.10 Entertainment 42 2.5 Drones in Enterprises: What Value Do They Add? Work Place Safety and Industry Benchmarks 42 2.5.1 Total Workplace Safety with Drones 43 2.5.2 Future of Drones with Idea Forge’s Industry Benchmarks 43 2.6 Advantages and Disadvantages of Drones 44 2.6.1 Significant Advantages 45 2.6.2 Disadvantages of Drones 45 2.6.3 Significant Disadvantages 46 2.6.4 Best Uses for Drones and Its Applications 46 2.7 Drone Technology as Career and Offered Jobs in the Current Industry 47 2.8 Societal Impact—Commercial Drones 47 2.9 Drones Research Challenges and Solutions 48 2.10 Conclusion 49 References 50 3 Drone/UAV Design Development is Important in a Wide Range of Applications: A Critical Review 53 M. V. Kamal, P. Dileep, G. Sharada, V. Suneetha and M. Gayatri 3.1 Introduction 54 3.2 Classification of Various Categories of Air Drones 55 3.2.1 VTOL and HTOL UAVs 57 3.2.2 Tilt-Body, Tilt-Rotor, and Tilt-Wingducted Fan UAVs 57 3.2.3 Heli-Wing and Helicopter UAVs 58 3.3 Drones Acting on Various Industries 58 3.3.1 Military Drones 58 3.3.2 Medical Drones 58 3.3.3 Agricultural Drones 62 3.4 Conclusions and Future Scope 62 References 63 4 A Comprehensive Study on Design and Control of Unmanned Aerial Vehicles 69 P. Venkateshwar Reddy, P. Srinivasa Rao, M. Hrishikesh and C. Satya Kumar 4.1 Introduction 70 4.2 Classification of Drones 72 4.3 Flight Performance Analysis 75 4.4 Dynamics and Design Objectives of Drones 79 4.4.1 Drone Dynamics 79 4.4.2 Design Objectives and Scaling Laws 80 4.4.3 Energy Utilization 81 4.4.4 Agility and Speed 81 4.4.5 Survivability and Robustness 83 4.4.6 Low-Level Control and Stabilization 83 4.5 Design Methods and Challenges 86 4.5.1 Proposed Solutions for Design Challenges 87 4.6 Guidance, Navigation, and Control of Drones 88 4.7 Conclusion 92 References 93 5 Some Studies of the Latest Artificial Intelligence Applications of Drones are Explored in Detail with Application Phenomena 99 G. Vaitheeswaran, B. Sundaravadivazhagan and Karthikeyan 5.1 Introduction 100 5.2 Evolution of the Drone 101 5.2.1 Military Drones 102 5.2.2 Commercial Drones 103 5.3 Drone Features 104 5.4 AI Meets Drones 105 5.5 Use Cases 109 5.5.1 Army 109 5.5.2 Weather Forecast 111 5.5.3 Industry 112 5.5.4 Agriculture 113 5.5.5 Logistics 113 5.6 Conclusion 115 References 115 6 Drone Technologies: Aviation Strategies, Challenges, and Applications 117 Devshri Satyarthi, K.V. Arya and Manish Dixit 6.1 Introduction 118 6.1.1 Categorization of Unmanned Aerial Vehicle (UAV) 119 6.1.1.1 Classification Based on Size 119 6.1.1.2 Classification Based on Range, Endurance, and Altitude 121 6.1.1.3 Classification Based on Weight 121 6.1.1.4 Classification Based on Engine Type 122 6.1.1.5 Classification Based on Configuration 122 6.1.1.6 Classification Based on Mechanical Design and Analysis 123 6.1.2 Specification of Drones 123 6.2 Drone Technology 124 6.2.1 Drone Monitoring Equipment 125 6.2.2 Drone Countermeasure Equipment 127 6.2.3 Collision Avoidance and Obstacle Detection Technology 129 6.2.4 Flight Controllers, Gyroscope Stabilization, and IMU 129 6.2.5 Drone Propulsion Technology 130 6.2.6 Real-Time Telemetry Flight Parameters 130 6.2.7 No Fly Zone Drone Technology 130 6.2.8 LED Flight Indicators 130 6.2.9 Drones with High Performance Camera 131 6.2.10 Remote Control System and Receiver of UAV 131 6.2.11 Range Extender UAV Technology 131 6.2.12 Video Editing Software 131 6.2.13 Operating Systems in Drone 131 6.2.14 Drone Security and Hacking 131 6.2.15 Modern Top Technology (Drones with Camera) 132 6.2.16 Intelligent Flight Systems 133 6.2.17 Drones For Tracking 133 6.3 India 2021: The Drone Policy and Rules 133 6.3.1 India Policy Guideline for Drones 133 6.3.2 Drone Rules 2021 136 6.4 Unmanned Aerial Vehicle (UAV) or Drone Application 137 6.4.1 Precision Agriculture 137 6.4.1.1 Related Work 138 6.4.1.2 Uses of UAV in Precision Agriculture 139 6.4.1.3 Challenges 140 6.4.1.4 Research Trends 140 6.4.1.5 Future Insights 141 6.4.2 Surveillance Applications of UAVs 141 6.4.2.1 Literature Review 141 6.4.2.2 State-of-the-Art Research 142 6.4.2.3 Product Introduction 142 6.4.2.4 Research Trends and Future Insights 142 6.4.3 Search and Rescue (SAR) 142 6.4.3.1 How SAR Operations Utilize UAVs 143 6.4.3.2 Challenges 143 6.4.3.3 Research Trends 143 6.4.3.4 Future Insights 143 6.4.4 Construction and Infrastructure Inspection 144 6.4.4.1 Literature Review 144 6.4.4.2 Deployment of Drone for Construction and Infrastructure Inspection Applications 144 6.4.4.3 Challenges 144 6.4.4.4 Research Trends 144 6.4.4.5 Future Insights 145 6.4.5 Delivery of Goods 145 6.4.5.1 UAVs-Based Goods Delivery System 145 6.4.5.2 Challenges 145 6.4.5.3 Research Trends 146 6.4.5.4 Future Insights 146 6.5 Conclusion 147 References 147 7 AI Applications of Drones 153 LNC Prakash K., Santosh Kumar Ravva, M.V. Rathnamma and G. Suryanarayana 7.1 Introduction 154 7.2 Review of Literature 159 7.3 AI in Drone Navigation 165 7.4 Companies that Use the AI Drone to Solve Big Problems 166 7.5 Drone Applications Using AI 169 7.6 Issues in the Integration of AI with Drones 176 7.7 Conclusion 177 References 179 8 Applications of Drones—A Review 183 Swathi Gowroju and Santhosh Ramchander N. 8.1 Introduction 184 8.2 Drone Hardware 188 8.3 Components of UAV 189 8.4 Literature Survey 190 8.4.1 Applications of Drones in Aerial Systems 190 8.4.2 Applications of Drones in Oil and Gas Industries 194 8.4.3 Applications of Drones in Military 195 8.4.4 Applications of Drones in Mines 195 8.4.4.1 Underground Mine Geotechnical Characterization 196 8.4.4.2 Underground Mine Rock Size Distribution Analysis 196 8.4.4.3 Underground Coal Mine Gas Detection 196 8.5 Analysis and Discussion 196 Conclusion 203 References 204 9 Drone Enables IoT Applications for Smart Cities 207 R. Santosh Kumar, LNC Prakash K. and G. Suryanarayana 9.1 Introduction to Smart Cities 208 9.2 Components and Characteristics of Smart Cities 209 9.2.1 Smart Healthcare 210 9.2.2 Smart Transportation 210 9.2.3 Smart Pollution Monitoring System 211 9.2.4 Smart Infrastructure and Building 212 9.2.5 Smart Building 212 9.3 The Role of IoT in Smart Cities 213 9.3.1 Road Traffic 213 9.3.2 Smart Parking 214 9.3.3 Public Transport 214 9.3.4 Utilities 215 9.3.4.1 Billing and Smart Meters 215 9.3.4.2 Disclosing Consumption Habits 215 9.3.4.3 Remote Surveillance 215 9.3.5 Waste Management 215 9.3.6 Environment 216 9.3.7 Public Safety 216 9.3.8 Security and Privacy for Smart Cities 216 9.4 General Approach to Implement IoT Solutions in Smart City Design 217 9.5 Challenges in IoT Solutions to Use in Smart City Design 219 9.6 Introduction to Unmanned Aerial Vehicles 221 9.7 Opportunities and Challenges of UAV’s in Smart Cities 222 9.8 Drone-Enabled IoT 224 9.8.1 Drone-Enabled IoT for Disaster Management 224 9.8.2 Drone-Enabled IoT for Public Safety 225 9.8.3 Drone-Enabled IoT for Data Collection 226 9.8.4 Drones and IoT for Improving Life Quality 227 9.8.5 Drone-Enabled IoT for Energy Efficiency 227 9.8.6 Privacy and Security Issues in Drone-Enabled IoT 228 9.9 Conclusion and Future Scope 229 References 229 10 AI-Based Smart Surveillance for Drowning and Theft Detection in Beaches Using Drones 243 V. Sakthivel, Suriya E., Jae Woo Lee and P. Prakash 10.1 Introduction 244 10.2 Literature Survey 244 10.3 Proposed Model 245 10.3.1 Drown Detection by Deep Learning Methods 245 10.3.2 People Alert System Using BLE Beacons 250 10.3.3 Abnormal Event Monitoring for Theft Detection 251 10.4 Deep Learning Model Safeties 252 10.5 Performance Evaluation 254 10.6 Conclusion 254 10.7 Conclusion and Future Work 255 Acknowledgements 256 References 256 11 Algorithms to Mitigate Cyber Security Threats by Employing Intelligent Machine Learning Models in the Design of IoT-Aided Drones 257 Devee Siva Prasad, Pyla Jyothi, G. Suryanarayana and Sachi Nandan Mohanty 11.1 Introduction 258 11.2 Research Methodology 260 11.3 Motivation 260 11.4 Machine Learning for Drone Security 262 11.5 Use of AI in Cyber Security 266 11.6 Use of AI in System to Achieve Robustness, Resilience and Response 267 11.7 NIC Algorithms in Cyber Security 271 11.8 Example Systems for AI and ML Applications for Cyber Security Diagnose 272 11.9 Introduction of New Threats 274 11.10 Areas were Malicious Use of Deepfakes is Trending 276 11.11 Model-Aided Deep Reinforcement Learning for Sample- Efficient UAV Trajectory Design in IoT Networks 276 11.12 Model-Aided Deep Q-Learning 278 11.13 Algorithm Model-Aided Deep Q-Learning Trajectory Design 280 11.13.1 Numerical Results 281 11.14 Machine Learning for Drone Security 282 11.15 Surveillance 283 11.16 Technologies Driving Drones’ Success 284 11.17 Related Work 286 11.18 Drones for Public Safety 289 11.19 Securing Drones 292 11.19.1 Machine and Deep Learning Models 293 11.20 Future Work 294 11.21 Contributions 295 Conclusion 295 References 296 12 IoT-Enabled Unmanned Aerial Vehicle: An Emerging Trend in Precision Farming 301 Gayatri Phade, A. T. Kishore, S. Omkar and M. Suresh Kumar 12.1 Introduction to IoT Enabled UAV 302 12.2 Drones in Precision Farming 306 12.2.1 Types of Agriculture Drones for Precision Agriculture 308 12.2.2 Drone Architecture for Precision Farming 310 12.2.3 IoT-Enabled Drone in Precision Farming 311 12.2.4 Safety and Security in IoT-Enabled Drones in Precision Farming 316 12.2.5 IoT Architecture in Drone 316 12.3 Challenges and Future Scope in IoT-Enabled Drone 319 12.4 Results and Discussion 320 Acknowledgement 322 References 322 13 Unmanned Aerial Vehicle for Land Mine Detection and Illegal Migration Surveillance Support in Military Applications 325 C. Anil Kumar Reddy and B.Venkatesh 13.1 Introduction to Military Drones 326 13.1.1 Unmanned Aerial Vehicle (UAV) 326 13.1.2 UAV Types 329 13.1.2.1 Multi-Rotor Drones 330 13.1.3 Problem Statement 330 13.1.4 Objective 330 13.1.5 Previous Work 331 13.2 Literature Review 331 13.2.1 Need of Drones for Indian Borders 334 13.2.2 UAV Technical Specifications 336 13.3 Methodology of UAV’s in Military Applications 336 13.3.1 Proposed System 336 13.3.2 Methodology 337 13.3.2.1 UAV Work Principle 337 13.3.2.2 UAV Controls and Installation 338 13.3.2.3 Drone Material and Frame 342 13.3.2.4 Program Used/Software Used (e.g., Aurdino) and Data Collection 342 13.3.2.5 Illegal Migration Surveillance with Camera 343 13.3.2.6 Data Collection from Mine Detector and Camera 344 13.3.2.7 Testing Conditions Applied for this Drone 344 13.4 Software Implementation 344 13.4.1 Arduino IDE 345 13.4.2 UAV Program/Coding 345 Appendix A 345 13.5 Conclusion 348 References 348 14 Importance of Drone Technology in Agriculture 351 Karuppiah Natarajan, Karthikeyan R. and Rajalingam S. 14.1 Introduction 352 14.2 Components of a Drone 352 14.3 Study of Natural Resources 355 14.3.1 Study of Natural and Manmade Pastures 357 14.3.2 Monitor Water Resources, Floods, and Droughts 357 14.3.3 Study of Weather Patterns 357 14.3.4 Monitoring of Soil Erosion 358 14.3.5 Cloud Seeding 359 14.4 Soil Fertility Management 359 14.4.1 Management of Soils and Their Fertility 360 14.4.2 Variable-Rate Technology for Soil Fertility Management 361 14.5 Irrigation and Water Management 362 14.5.1 Crop Water Stress Index 363 14.5.2 Drones to Monitor Water Resources 363 14.5.3 Drones to Design an Irrigation System 364 14.6 Crop Disease Identification 365 14.6.1 Monitoring and Identification Using Different Drone Platforms and Peripherals 365 14.6.2 Disease Symptoms 366 14.6.2.1 Sheath Blight 366 14.6.2.2 Narrow Brown Leaf Spot 367 14.7 Pest Control Management 368 14.7.1 Drones Offer a Sustainable Pest Control Solution 368 14.8 Agricultural Drones to Improve Crop Yield Management Efficiency 369 14.9 Issues and Challenges 370 14.9.1 Power Source and Flight Time 370 14.9.2 High Capital Cost 371 14.9.3 The Capacity of the Tank to Carry Fertilizer and Water for Spraying 372 14.9.4 Lack of Technical Skills to Operate, Repair, and Service 372 14.9.5 Job Loss of Existing Farm Workers 372 14.10 Conclusion 372 References 373 15 Network Intrusion Detection of Drones Using Recurrent Neural Networks 375 Yadala Sucharitha, Pundru Chandra Shaker Reddy and G. Suryanarayana 15.1 Introduction 376 15.2 Related Works 378 15.3 Drone Intrusion Detection Methodology 380 15.3.1 Drone RNN 381 15.3.2 Data Collector 382 15.3.3 Centralized-RNN 383 15.3.4 Decision-Maker 383 15.4 Results and Discussion 384 15.4.1 Model Assessment 384 15.4.2 Performance Analysis 384 15.4.3 LSTM_RNN Performance over UNSW-NB 15 Dataset 385 15.5 Conclusion 388 References 388 16 Drone-Enabled Smart Healthcare System for Smart Cities 393 Subasish Mohapatra, Amlan Sahoo, Subhadarshini Mohanty and Sachi Nandan Mohanty 16.1 Introduction 394 16.2 Related Works 397 16.3 Applications of Drones 399 16.4 Suggested Framework 411 16.5 Challenges 415 16.6 Conclusion 418 Future Scopes 419 References 420 17 Drone Delivery 425 V. Sakthivel, Sourav Patel, Jae Woo Lee and P. Prakash 17.1 Introduction 426 17.2 History of Drones 427 17.3 Drone Delivery in Healthcare 432 17.4 Drone Delivery of Food 432 17.5 Drone Delivery in Postal Service 433 17.6 Delivery of Goods 433 Acknowledgements 439 References 439 Index 441
£153.00
John Wiley & Sons Inc Practical Control System Design
Book SynopsisPractical Control System Design This book delivers real world experience covering full-scale industrial control design, for students and professional control engineers Inspired by the authors' industrial experience in control, Practical Control System Design: Real World Designs Implemented on Emulated Industrial Systems captures that experience, along with the necessary background theory, to enable readers to acquire the tools and skills necessary to tackle real world control engineering design problems. The book draws upon many industrial projects conducted by the authors and associates; these projects are used as case studies throughout the book, organized in the form of Virtual Laboratories so that readers can explore the studies at their own pace and to their own level of interest. The real-world designs include electromechanical servo systems, fluid storage, continuous steel casting, rolling mill center line gauge control, rocket dynamics and control, crTable of ContentsPreface xix About the Authors xxi Acknowledgements xxiii About the Companion Website xxiv Part I Modelling and Analysis of Linear Systems 1 1 Introduction to Control System Design 3 1.1 Introduction 3 1.2 A Brief History of Control 4 1.3 Digital Control 5 1.4 Our Selection 5 1.5 Thinking Outside the Box 6 1.6 How the Book Is Organised 6 1.7 Testing the Reader’s Understanding 6 1.8 Revision Questions 7 Further Reading 7 2 Control as an Inverse Problem 9 2.1 Introduction 9 2.2 The Elements 9 2.3 Using Eigenvalue Analysis 10 2.4 The Effect of Process and Disturbance Errors 11 2.5 Feedback Control 11 2.6 The Effect of Measurement Noise 12 2.7 Sensitivity Functions 14 2.8 Reducing the Impact of Disturbances and Model Error 14 2.9 Impact of Measurement Noise 14 2.10 Other Useful Sensitivity Functions 14 2.11 Stability (A First Look) 15 2.12 Sum of Sensitivity and Complementary Sensitivity 15 2.13 Revision Questions 16 Further Reading 16 3 Introduction to Modelling 17 3.1 Introduction 17 3.2 Physical Modelling 17 3.2.1 Radio Telescope Positioning 17 3.2.2 Band-Pass Filter 19 3.2.3 Inverted Pendulum 19 3.2.4 Flow of Liquid out of a Tank 20 3.3 State-Space Model Representation 21 3.3.1 Systems Without Zeros 22 3.3.2 Systems Which Depend on Derivatives of the Input 23 3.3.3 Example: State-Space Representation 24 3.4 Linearisation and Approximation 25 3.4.1 Linearisation of Inverted Pendulum Model 26 3.5 Revision Questions 27 Further Reading 28 4 Continuous-Time Signals and Systems 29 4.1 Introduction 29 4.2 Linear Continuous-Time Models 29 4.3 Laplace Transforms 30 4.4 Application of Laplace Transforms to Linear Differential Equations 31 4.4.1 Example: Angle of Radio Telescope 32 4.4.2 Example: Modelling the Angular Velocity of Radio Telescope 33 4.5 A Heuristic Introduction to Laplace Transforms 33 4.6 Transfer Functions 34 4.6.1 High-Order Differential Equation Models 34 4.6.2 Example: Transfer Function for Radio Telescope 35 4.6.3 Transfer Functions for Continuous-Time State-Space Models 35 4.6.4 Example: Inverted Pendulum 36 4.6.5 Poles, Zeros and Other Properties of Transfer Functions 36 4.6.6 Time Delays 36 4.6.7 Heuristic Development of Transfer Function of Delay 37 4.6.8 Example: Heating System 37 4.7 Stability of Transfer Functions 38 4.7.1 Example: Poles of the Radio Telescope Model 38 4.8 Impulse Response of Continuous-Time Linear Systems 38 4.8.1 Impulse Response 38 4.8.2 Convolution and Transfer Functions 39 4.9 Step Response 39 4.10 Steady-State Response and Integral Action 40 4.11 Terms Used to Describe Step Responses 40 4.12 Frequency Response 41 4.12.1 Nyquist Diagrams 43 4.12.2 Bode Diagrams 43 4.12.3 Example: Simple Transfer Function 44 4.13 Revision Questions 45 Further Reading 46 5 Laboratory 1: Modelling of an Electromechanical Servomechanism 47 5.1 Introduction 47 5.2 The Physical Apparatus 47 5.3 Estimation of Motor Parameters 49 5.3.1 Motivation for Building a Model 50 5.3.2 Experiment: Why Build a Model? 50 5.3.3 Step Response Testing 50 5.3.4 Experiment: Measuring the Open-Loop Gain and Time Constant 51 5.3.5 Frequency Response 51 5.3.6 Experiment: Measuring Frequency Response 52 5.3.7 Experiment: Alternative Measurement of Frequency Response 52 5.4 Revision Questions 53 Further Reading 53 Part II Control System Design Techniques for Linear Single-input Single-output Systems 55 6 Analysis of Linear Feedback Systems 57 6.1 Introduction 57 6.2 Feedback Structures 57 6.3 Nominal Sensitivity Functions 59 6.4 Analysing Stability Using the Characteristic Polynomial 60 6.4.1 Example: Pole-Zero Cancellation 61 6.5 Stability and Polynomial Analysis 61 6.5.1 Stability via Evaluation of the Roots 61 6.6 Root Locus (RL) 61 6.7 Nominal Stability Using Frequency Response 63 6.8 Relative Stability: Stability Margins and Sensitivity Peaks 67 6.9 From Polar Plots to Bode Diagrams 68 6.10 Robustness 69 6.10.1 Achieved Sensitivities 69 6.10.2 Robust Stability 69 6.11 Revision Questions 71 Further Reading 72 7 Design of Control Laws for Single-Input Single-Output Linear Systems 73 7.1 Introduction 73 7.2 Closed-Loop Pole Assignment 73 7.2.1 Example: Steam Receiver 74 7.3 Using Root Locus 75 7.3.1 Example: Double Integrator 75 7.3.2 Example: Unstable Process 76 7.4 All Stabilising Control Laws 77 7.5 Design Using the Youla–Kucera Parameterisation 79 7.5.1 Example: Simple First-Order Model 80 7.6 Integral Action 80 7.7 Anti-Windup 81 7.8 PID Design 82 7.8.1 Structure 82 7.8.2 Using the Youla–Kucera Parameterisation for PID Design 84 7.9 Empirical Tuning 84 7.10 Ziegler–Nichols (Z–N) Oscillation Method 84 7.10.1 Example: Third-Order Plant 85 7.11 Two Degrees of Freedom Design 86 7.12 Disturbance Feedforward 86 7.13 Revision Questions 87 Further Reading 88 8 Laboratory 2: Position Control of Electromechanical Servomechanism 89 8.1 Introduction 89 8.2 Proportional Feedback 89 8.2.1 Experiment: Testing a Proportion only Control Law 91 8.3 Using Proportional Plus Derivative Feedback 91 8.3.1 Experiment: Testing a PD Control Law 92 8.4 Tachometer Feedback 92 8.5 PID Design 92 8.5.1 Output Disturbances 92 8.5.2 Input Disturbance 93 8.5.3 A Simple Design Procedure 94 8.5.4 Experiment: Testing a PID Control Law 94 8.6 Revision Questions 95 Further Reading 95 9 Laboratory 3: Continuous Casting Machine: Linear Considerations 97 9.1 Introduction 97 9.2 The Physical Equipment 97 9.3 Modelling of Continuous Casting Machine 99 9.4 Proportional Control 102 9.5 Response to Set-Point Changes 103 9.6 Experiments 103 9.6.1 Experiment: Model Parameter Estimation 103 9.6.2 Low Gain Feedback 104 9.6.3 High Gain Feedback 104 9.7 Effect of Measurement Noise 104 9.7.1 Experiment: Measuring the Impact of Measurement Noise 105 9.8 Pure Integral Control 105 9.8.1 Experiment: Testing Pure Integral Control 106 9.9 PI Control 106 9.9.1 Experiment: Testing PI Control 107 9.9.2 Experiment: Testing the Response to Varying Casting Speed 108 9.10 Feedforward Control 108 9.10.1 Experiment: Testing Feedforward Control 109 9.10.2 Experiment: Testing Sensitivity to the Feedforward Gain 110 9.11 Revision Questions 110 Further Reading 110 10 Laboratory 4: Modelling and Control of Fluid Level in Tanks 113 10.1 Introduction 113 10.2 The Controllers 113 10.3 Physical Modelling 113 10.3.1 Experiment: Estimating Plant Gain and Time Constant 117 10.4 Closed-Loop Level Control for a Single Tank 117 10.4.1 Proportional Only Control 117 10.4.2 Experiment: Testing Proportional Control 117 10.4.3 Integral Only Control 118 10.4.4 Experiment: Testing Integral Control 118 10.4.5 Proportional Plus Integral Control 119 10.4.6 Experiment: Testing PI Control 119 10.4.7 Experiment: Alternative PI Controller 119 10.5 Closed-Loop Level Control of Interconnected Tanks 119 10.6 Revision Questions 120 Further Reading 121 11 Laboratory 5: Wind Power (Mechanical Components) 123 11.1 Introduction 123 11.2 Yaw Control 123 11.2.1 Experiment: Estimating the Yaw Time Constant 127 11.2.2 Design of Yaw Controller 127 11.2.3 Experiment: Testing the Yaw Controller 128 11.3 Rotational Velocity Control 129 11.3.1 Experiment: Testing the Rotational Velocity Control Law 133 11.4 Pitch Control 133 11.5 Experiment: Testing the Pitch Controller 134 11.6 Revision Questions 135 Further Reading 135 Part III More Complex Linear Single-Input Single-Output Systems 137 12 Time Delay Systems 139 12.1 Introduction 139 12.2 Transfer Function Analysis 139 12.3 Classical PID Design Revisited 140 12.4 Padé Approximation 140 12.5 Using the Youla–Kucera Parameterisation 140 12.6 Smith Predictor 141 12.7 Modern Interpretation of Smith Predictor 142 12.8 Sensitivity Trade-Offs 142 12.9 Theoretical Analysis of Effect of Delay Errors on Smith Predictor 143 12.10 Revision Questions 144 Further Reading 145 13 Laboratory 6: Rolling Mill (Transport Delay) 147 13.1 Introduction 147 13.2 The Physical System 147 13.3 Modelling 149 13.3.1 Description of the Process 149 13.3.2 Sensors and Actuators 149 13.3.3 Disturbances 149 13.3.4 Aims of the Control System 149 13.4 Building a Model 150 13.4.1 The Mill Frame 150 13.4.2 Strip Deformation 150 13.4.3 Composite Model 151 13.4.4 Open-Loop Steady-State Performance 152 13.5 Basic Control System Design 152 13.6 Linear Control Ignoring the Time Delay 153 13.6.1 Experiment: Testing a PI Controller 154 13.7 Linear Control Based on Rational Approximation to the Time Delay 155 13.7.1 Experiment: Testing PID Design 156 13.8 Control System Design Based on Smith Predictor 156 13.8.1 Experiment: Testing Smith Predictor 157 13.9 Use of a Soft Sensor 158 13.9.1 The BISRA Gauge 158 13.9.2 Experiment: Testing the BISRA Gauge 159 13.10 Robustness of BISRA Gauge 159 13.10.1 Experiment: Testing Sensitivity to Mill Modulus 159 13.10.2 Experiment: Alternative Solution to Achieve Steady-State Tracking 159 13.11 Revision Questions 159 Further Reading 160 14 Control System Design for Open-Loop Unstable Systems 161 14.1 Introduction 161 14.2 Some Simple Examples of Open-Loop Unstable Systems 161 14.3 All Stabilising Control Laws for Systems Having Undesirable Open-Loop Poles 163 14.4 Revision Questions 164 Further Reading 165 15 Laboratory 7: Control of a Rocket 167 15.1 Introduction 167 15.2 Dynamics of a Rocket in 2D Flight 167 15.2.1 Coordinate Systems 167 15.2.2 Forces 169 15.2.3 Translational Dynamics 170 15.2.4 Rotational Dynamics 170 15.2.5 Composite Model 171 15.3 Equilibrium 171 15.4 Linearised Model 171 15.5 Open-Loop Flight 172 15.6 Controller Design for the Rocket 172 15.6.1 Simplified Design of PID 172 15.6.2 Frequency Domain Design 173 15.7 Experiment: Testing the Control Law 174 15.7.1 Testing the Design Mode in Section 15.6.1 174 15.7.2 Testing the Design Made in Section 15.6.2 175 15.8 Revision Questions 175 Further Reading 175 16 Bode Sensitivity Trade-Offs 177 16.1 Introduction 177 16.2 System Properties 177 16.3 Bode Integral Constraints 178 16.3.1 Open-Loop Stable Systems 178 16.4 Examples of Bode Sensitivity Trade-Offs 178 16.4.1 Open-Loop Unstable Systems 180 16.5 Bode Complementary Sensitivity Integrals 180 16.5.1 Minimum Phase Plants 180 16.5.2 Non-minimum Phase Plants 180 16.6 Bode Sensitivity for Time-Delay Systems 180 16.7 Revision Questions 181 Further Reading 181 Part IV Sampled Data Control Systems 183 17 Principles of Sampled-Data Control System Design 185 17.1 Introduction 185 17.2 A/D Conversion 185 17.3 Sampled Output Noise 185 17.4 D/A Conversion 186 17.5 Sampled-Data Models 187 17.6 Shift Operator Models 187 17.7 Divided Difference Models 187 17.8 Euler Approximate Model 188 17.9 Euler Approximate Model in Delta Domain 188 17.10 Delta Analysis 189 17.11 Historical Notes 189 17.12 An Example of Shift and Delta Models 189 17.13 Sampled-Data Stability 190 17.14 Bode Sensitivity Integrals (Sampled Data Case) 190 17.14.1 Z-Domain 192 17.14.2 Delta Domain 192 17.15 Sampling Zeros 193 17.16 Revision Questions 193 Further Reading 194 18 Laboratory 8: Audio Signal Processing and Optimal Noise Shaping Quantisers 197 18.1 Introduction 197 18.2 The Physical Apparatus 197 18.3 Psychoacoustic Issues 198 18.3.1 Experiment: Testing Your Hearing Sensitivity 199 18.4 Nearest Neighbour Quantisation 200 18.4.1 Experiment: Testing the Nearest Neighbour Quantiser 200 18.5 Optimal Noise Shaping Quantiser 201 18.5.1 Feedback Quantiser 201 18.5.2 Experiment: Test the Feedback Quantiser 202 18.6 Utilising Your Own Hearing Sensitivity 202 18.6.1 Experiment: Test the Feedback Quantiser Using Your Hearing Sensitivity 204 18.7 Audio Quantisation from a Bode Sensitivity Integral Perspective 204 18.7.1 Experiment: Spectrum of Errors 205 18.7.2 Experiment: Testing Bode Sensitivity Integral 205 18.8 Audio Quantisation for More Complex Cases 205 18.8.1 Experiment: More Complex Case 206 18.9 Revision Questions 206 Further Reading 207 Part V Simple Multivariable Control Problems 209 19 Tools Used for Simple Multivariable Control Problems 211 19.1 Introduction 211 19.2 Cascade Control 211 19.2.1 Example of Cascade Control 212 19.3 Imposed SISO Architectures 214 19.4 Relative Gain Array 215 19.5 An Industrial Example 215 19.5.1 The Relative Gain Array 215 19.5.2 A Simple MV Transformation 216 19.6 Revision Questions 216 Further Reading 216 20 Laboratory 9: Wind Power (Electrical Components) 217 20.1 Introduction 217 20.2 Generator Choices 217 20.3 Physical Parameters for the Laboratory Wind Turbine 217 20.4 The Generator and Grid Side Architectures 219 20.5 Background Theory 219 20.5.1 Alpha, Beta Coordinates 220 20.5.2 dq Frame 220 20.5.3 The Inverse Transformation 221 20.5.4 First-Order Dynamics in dq Frame 221 20.6 Generator Side Model 222 20.7 Generator Side Control Law 223 20.7.1 Regulation of I Sd 224 20.7.2 Regulation of I Sq 224 20.7.3 Alignment of dq Frame 224 20.7.4 Conversion of V Sd , V Sq Back to Time Domain 225 20.8 The Link Capacitor Model 225 20.8.1 Current into the Capacitor 225 20.8.2 Dynamics of the Capacitor 225 20.9 Regulation of the Capacitor Voltage 226 20.10 Model for the Grid Side Transformer 226 20.11 The Grid Side Control Law 226 20.11.1 Regulation of I Cq 227 20.11.2 Regulation of I cd 227 20.12 Complete Electrical System Control Law 227 20.13 Testing the Electrical Control Laws 229 20.13.1 Generator Side 229 20.13.2 Grid Side 229 20.14 Experiments on the Complete System 229 20.14.1 Experiment: Testing the Impact of Wind Direction 230 20.14.2 Experiment: Testing the Impact of Wind Speed 231 20.15 Revision Questions 231 Further Reading 233 21 Laboratory 10: Cross-Directional Control in Paper Machines: PID Control 235 21.1 Introduction 235 21.2 Web-Forming Process 235 21.3 Basis Weight Control in a Paper Machine 237 21.4 Process Model 237 21.4.1 Experiment: Measuring the Cross-Directional Profile 241 21.4.2 Experiment: Measuring the Machine Direction Dynamics 241 21.5 Simple SISO Design Ignoring Coupling 241 21.5.1 Experiment: Testing Simple PID Controllers 242 21.6 Simple SISO Design Accounting for Coupling 242 21.6.1 Experiment: Testing a Decoupled PID Structure 243 21.7 Summary 243 21.8 Revision Questions 244 Further Reading 244 Part VI Multivariable Control Systems (More General Methods) 247 22 State Variable Feedback 249 22.1 Introduction 249 22.2 Sampled-Data Control 249 22.2.1 Pole Assignment 249 22.2.2 Linear Quadratic Regulator (LQR) 249 22.3 Dynamic Programming 250 22.4 Infinite Horizon Linear Quadratic Optimal Problem 251 22.5 Delta-Domain Result 251 22.6 Continuous-Time Linear Quadratic Regulator 252 22.6.1 Pole Assignment 252 22.6.2 Continuous-Time Linear Quadratic Regulator 252 22.7 Regulation to a Fixed Set-Point 253 22.8 Frequency Domain Insights into the Linear Quadratic Regulator 254 22.9 Output Feedback 255 22.9.1 A State Estimator (or Observer) 255 22.9.2 Certainty Equivalence 255 22.10 Separation 256 22.11 Achieving Integral Action 256 22.11.1 The Problem 256 22.11.2 The Remedy 256 22.11.3 Properties 257 22.12 All Stabilising Control Laws Revisited 258 22.12.1 Stable Open-Loop Plants 259 22.12.2 Adding Stable Uncontrollable Disturbance States 259 22.12.3 Adding Non-stabilisable Disturbance States 260 22.13 Model Predictive Control 260 22.14 Revision Questions 260 Further Reading 261 23 The Kalman Filter 263 23.1 Introduction 263 23.2 Periodic Disturbances 263 23.2.1 Continuous-Time Model 263 23.2.2 Sampled-Data Process Noise 264 23.2.3 Sampled-Data Measurement Noise 265 23.2.4 The Full Sampled-Data Model 265 23.3 The Best Observer Gain 266 23.4 Steady-State Optimal Estimator 267 23.5 Treating Non-White Noise 268 23.6 Dealing with Constant Disturbances 268 23.7 Periodic Disturbances 268 23.8 Accounting for Delays 269 23.9 Multiple Output Measurements 269 23.10 Continuous-Time Kalman Filter 270 23.11 Linking Continuous Kalman Filter and Discrete Kalman Filter 270 23.12 The Linear Quadratic Regulator Revisited 271 23.13 Quantifying the Performance 271 23.14 Revision Questions 272 Further Reading 274 24 Laboratory 11: Rolling Mill Revisited (Periodic Disturbances) 275 24.1 Introduction 275 24.2 Disturbances 275 24.3 Effects of Roll Eccentricity 276 24.3.1 Experiment: Measuring the Impact of Roll Eccentricity 277 24.4 Tight Feedback Control 277 24.4.1 Experiment: Testing the Impact of Eccentricity on the BISRA Gauge 278 24.4.2 Analysis of the Effect of Control Law Bandwidth 278 24.5 Eccentricity Compensation 278 24.5.1 A Simple Eccentricity Predictor 278 24.6 Optimal Observer Design 279 24.6.1 Experiment: Testing the Eccentricity Estimator 280 24.7 Eccentricity Compensation Using the Kalman Filtering 281 24.7.1 Experiment: Testing the Kalman Filter for Eccentricity Estimation 281 24.8 Conclusion 282 24.9 Revision Questions 282 Further Reading 283 Part VII Introduction to the Modelling and Control of Nonlinear Systems 285 25 Modelling and Analysis of Simple Nonlinear Systems 287 25.1 Introduction 287 25.2 Errors Arising from Large Actuator Movement 287 25.3 Nonlinear Correction by Gain Change 288 25.4 Nonlinear Correction by Cascade Control 288 25.5 Saturation 289 25.5.1 Achieving Integral Action via Feedback 289 25.5.2 Introducing Anti-Windup in Control Laws Implemented via the Youla–Kucera Parameterisation 290 25.5.3 Anti-Windup When an Observer is Used 290 25.6 Extension to Rate Limitations 291 25.7 Minimal Actuator Movement 291 25.8 Describing Function Analysis 291 25.9 Predicting the Period and Amplitude of Oscillations 293 25.10 Revision Questions 293 Further Reading 294 26 Laboratory 12: Continuous Casting Machine (Nonlinear Considerations) 297 26.1 Introduction 297 26.2 The Slide Gate Valve 297 26.3 Investigation of Effect of Nonlinear Valve Geometry 298 26.3.1 Experiment: Testing Impact of the Nonlinear Geometry of the Valve 299 26.3.2 Other Nonlinear Phenomena 300 26.4 An Explanation for the Observed Oscillations 300 26.5 A Redesign to Account for Slip-Stick Friction 302 26.5.1 Experiment: Testing the Impact of Slip-Stick Friction 302 26.6 Revision Questions 303 Further Reading 303 27 Laboratory 13: Cross-Directional Control (Robustness and Impact of Actuator Saturation) 305 27.1 Introduction 305 27.2 Effect of Actuator Saturation Without Anti-Windup Protection 305 27.2.1 Experiment: Impact of Actuator Saturation 305 27.2.2 Experiment: Impact of Actuator Saturation with Decoupled PID Design 306 27.3 PI Decoupled Design with Simple Anti-Windup Protection 306 27.3.1 Experiment: Testing the Simple Anti-Windup Scheme 307 27.4 Conditioning Problems 308 27.4.1 Experiment: Testing Actuator Profile 310 27.5 PI Decoupled Design with Anti-Windup Protection Limited to Low Spatial Frequencies 310 27.5.1 Experiment: Limiting Spatial Frequencies Used in the Controller 310 27.6 PI Decoupled Design with Adaptive Spatial Frequency Selection 311 27.6.1 Experiment: Testing Adaptive Spatial Frequency Selection 312 27.7 Conclusions 312 27.8 Revision Questions 312 Further Reading 312 Part VIII Modelling and Control of More Complex Nonlinear Systems 315 28 Modelling of a Rocket in Three-Dimensional Flight 317 28.1 Introduction 317 28.2 Preliminaries 317 28.2.1 Coordinate Systems 317 28.2.2 Euler Angles in Three Dimensions 318 28.2.3 Time Derivative of Rotation Matrices 320 28.2.4 Angular Velocities 321 28.2.5 Angular Acceleration 321 28.2.6 Cross-Products 323 28.3 Translational Dynamics 323 28.3.1 Forces 323 28.3.2 Model for Translational Dynamics 324 28.4 Rotational Dynamics 324 28.4.1 Torque 324 28.4.2 Model for Rotational Dynamics 325 28.5 Stable or Unstable Rocket 325 28.6 Revision Questions 326 Further Reading 326 29 Modelling of a Steam-Generating Boiler 327 29.1 Introduction 327 29.2 Physical Principles 328 29.2.1 Internal Energy and Enthalpy 328 29.2.2 Ideal Gases 328 29.2.3 Steam 328 29.3 Physical Principles Used in Boiler Modelling 329 29.4 Mass Balances 329 29.5 Constant Volume of Drum, Risers and Downcomers 331 29.5.1 Consequence of Constant Volume of the Drum 332 29.5.2 Consequence of Constant Volume of the Risers 332 29.6 Energy Balances 333 29.6.1 Consequence of Drum Energy Balance 334 29.6.2 Consequences of Energy Balance in the Risers 335 29.7 A Model for Boiler Pressure 335 29.8 A Model for Drum Water Level 336 29.9 Spatial Discretisation and Homogeneous Mixing in the Risers 337 29.9.1 Spatial Discretisation 338 29.9.2 Homogeneous Mixing in a Section of the Risers 339 29.10 Water Flow in the Downcomers 340 29.11 Superheaters 341 29.12 Steam Receiver 341 29.12.1 Mass Balance 342 29.12.2 Energy Balance 342 29.12.3 Constant Volume of the Steam Receiver 342 29.12.4 Summary of the Model for the Steam Receiver 343 29.13 Other Model Components 343 29.13.1 Mass Flow out of Drum 343 29.13.2 Feedwater Mass Flow 344 29.13.3 Total Heat 344 29.13.4 Disturbances 344 29.13.5 A Preliminary Simulation 344 29.14 Revision Questions 344 Further Reading 346 30 Laboratory 14: Control of a Steam Boiler 347 30.1 Introduction 347 30.2 Extracting an Approximate Linear Model 347 30.2.1 Introduction 347 30.2.2 Sine Wave Testing in Closed-Loop (Scalar Case) 348 30.2.3 Application to the Boiler Model 349 30.2.4 The Steam Receiver 350 30.3 The Control Architecture 351 30.4 Regulating Steam Flow from the Boiler 351 30.5 Boiler Pressure Controller 351 30.6 Drum Water Level Controller 352 30.6.1 Experiment: Implementing Drum Water Level Control Law 352 30.7 Steam Receiver Controller 353 30.7.1 Experiment: Testing Steam Receiver Control Law 353 30.8 Experiments 353 30.8.1 Set Up 353 30.8.2 Small Load Change 354 30.8.3 Faster Outer Loop 354 30.8.4 Slower Outer Loop 354 30.8.5 Large Decrease in Load 355 30.8.6 Constraints 355 30.8.7 Large Load Change with ‘Fast’ Outer Loop 355 30.8.8 Large Increase in Load 355 30.9 Summary 355 30.10 Revision Questions 355 Further Reading 356 Index 357
£94.50
Wiley-Blackwell Wireless Identification and Sensing Systems for
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£91.80
John Wiley & Sons Inc Dielectric Resonator Antennas
Book SynopsisDielectric Resonator Antennas A detailed guide to dielectric-based techniques for antenna array design and construction Dielectric designs, which transmit electricity without conducting it, have in recent decades been increasingly incorporated into antenna arrays. The resulting Dielectric Resonator Antennas (DRAs) provide significant benefits over metal antennas, avoiding conduction loss and increasing efficiency. Dielectric elements can also be incorporated into metal antennas to improve performance. Dielectric Resonator Antennas provides an introduction to dielectric-based techniques for manufacturing antenna arrays. It supplies guidelines for identifying dielectric antenna designs (as opposed to metal ones), describes recent developments in dielectric antenna technology, and points toward potential areas of future growth and development. Readers will also find: Cutting-edge DRA applications in microwave and millimeter-wave communications
£99.00
John Wiley & Sons Inc Foundations of Antenna Radiation Theory
Book SynopsisFoundations of Antenna Radiation Theory Understand the theory and function of wireless antennas with this comprehensive guide As wireless technology continues to develop, understanding of antenna properties and performance will only become more critical. Since antennas can be understood as junctions of waveguides, eigenmode analysisthe foundation of waveguide theory, concerned with the unexcited states of systems and their natural resonant characteristicspromises to be a crucial frontier in the study of antenna theory. Foundations of Antenna Radiation Theory incorporates the modal analysis, generic antenna properties and design methods discovered or developed in the last few decades, not being reflected in most antenna books, into a comprehensive introduction to the theory of antennas. This book puts readers into conversation with the latest research and situates students and researchers at the cutting edge of an important field of wireless technology.
£102.60
John Wiley & Sons Inc PhysicalLayer Security for 6G
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John Wiley & Sons Inc Accelerators for Convolutional Neural Networks
Book SynopsisAccelerators for Convolutional Neural Networks Comprehensive and thorough resource exploring different types of convolutional neural networks and complementary accelerators Accelerators for Convolutional Neural Networks provides basic deep learning knowledge and instructive content to build up convolutional neural network (CNN) accelerators for the Internet of things (IoT) and edge computing practitioners, elucidating compressive coding for CNNs, presenting a two-step lossless input feature maps compression method, discussing arithmetic coding -based lossless weights compression method and the design of an associated decoding method, describing contemporary sparse CNNs that consider sparsity in both weights and activation maps, and discussing hardware/software co-design and co-scheduling techniques that can lead to better optimization and utilization of the available hardware resources for CNN acceleration. The first part of the book provides an overview of CNNs along with the composit
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John Wiley & Sons Inc Principles of Soft Computing Using Python
Book SynopsisPrinciples of Soft Computing Using Python Programming An accessible guide to the revolutionary techniques of soft computing Soft computing is a computing approach designed to replicate the human mind's unique capacity to integrate uncertainty and imprecision into its reasoning. It is uniquely suited to computing operations where rigid analytical models will fail to account for the variety and ambiguity of possible solutions. As machine learning and artificial intelligence become more and more prominent in the computing landscape, the potential for soft computing techniques to revolutionize computing has never been greater. Principles of Soft Computing Using Python Programming provides readers with the knowledge required to apply soft computing models and techniques to real computational problems. Beginning with a foundational discussion of soft or fuzzy computing and its differences from hard computing, it describes different models for soft computing and
£85.46
John Wiley & Sons Inc A Users Guide to Vacuum Technology
Book SynopsisA USERS GUIDE TO VACUUM TECHNOLOGY Choose and understand the vacuum technology that fits your project's needs with this indispensable guide Vacuum technology is used to provide process environments for other kinds of engineering technology, making it an unsung cornerstone of hundreds of projects incorporating analysis, research and development, manufacturing, and more. Since it is very often a secondary technology, users primarily interested in processes incorporating it will frequently only encounter vacuum technology when purchasing or troubleshooting. There is an urgent need for a guide to vacuum technology made with these users in mind. For decades, A User's Guide to Vacuum Technology has met this need, with a user-focused introduction to vacuum technology as it is incorporated into semiconductor, optics, solar sell, and other engineering processes. With an emphasis on otherwise neglected subjects and on accessibility to the secondary user of vacuum teTable of ContentsPreface xvii Symbols xix Part I Its Basis 1 1 Vacuum Technology 3 1.1 Units of Measurement 8 References 9 2 Gas Properties 11 2.1 Kinetic Picture of a Gas 11 2.1.1 Velocity Distribution 12 2.1.2 Energy Distribution 13 2.1.3 Mean Free Path 14 2.1.4 Particle Flux 15 2.1.5 Monolayer Formation Time 15 2.1.6 Pressure 16 2.2 Gas Laws 16 2.2.1 Boyle’s Law 17 2.2.2 Amontons’ Law 17 2.2.3 Charles’ Law 18 2.2.4 Dalton’s Law 18 2.2.5 Avogadro’s Law 18 2.2.6 Graham’s Law 19 2.3 Elementary Gas Transport Phenomena 19 2.3.1 Viscosity 19 2.3.2 Thermal Conductivity 22 2.3.3 Diffusion 23 2.3.4 Thermal Transpiration 24 References 25 3 Gas Flow 27 3.1 Flow Regimes 27 3.2 Flow Concepts 29 3.3 Continuum Flow 31 3.3.1 Orifice 32 3.3.2 Long Round Tube 34 3.3.3 Short Round Tube 36 3.4 Molecular Flow 37 3.4.1 Orifice 38 3.4.2 Long Round Tube 39 3.4.3 Short Round Tube 39 3.4.4 Irregular Structures 41 3.4.4.1 Analytical Solutions 42 3.4.4.2 Statistical Solutions 43 3.4.5 Components in Parallel and Series 43 3.5 Models Spanning Molecular and Viscous Flow 53 References 55 4 Gas Release from Solids 59 4.1 Vaporization 59 4.2 Diffusion 60 4.2.1 Reduction of Outdiffusion by Vacuum Baking 62 4.3 Thermal Desorption 63 4.3.1 Zero Order 63 4.3.2 First Order 64 4.3.3 Second Order 65 4.3.4 Desorption from Real Surfaces 67 4.3.5 Outgassing Measurements 67 4.3.6 Outgassing Models 69 4.3.7 Reduction by Baking 69 4.4 Stimulated Desorption 71 4.4.1 Electron-Stimulated Desorption 71 4.4.2 Ion-Stimulated Desorption 71 4.4.3 Stimulated Chemical Reactions 72 4.4.4 Photo Desorption 72 4.5 Permeation 73 4.5.1 Atomic and Molecular Permeation 73 4.5.2 Dissociative Permeation 74 4.5.3 Permeation and Outgassing Units 75 4.6 Pressure Limitations During Pumping 76 References 78 Part II Measurement 81 5 Pressure Gauges 83 5.1 Direct Reading Gauges 83 5.1.1 Diaphragm and Bourdon Gauges 84 5.1.2 Capacitance Manometer 85 5.2 Indirect Reading Gauges 88 5.2.1 Thermal Conductivity Gauges 88 5.2.1.1 Pirani Gauge 90 5.2.1.2 Thermocouple Gauge 91 5.2.1.3 Stability and Calibration 92 5.2.2 Spinning Rotor Gauge 93 5.2.3 Ionization Gauges 95 5.2.3.1 Hot Cathode Gauges 95 5.2.3.2 Hot Cathode Gauge Errors 100 5.2.3.3 Cold Cathode Gauge 103 5.2.3.4 Gauge Calibration 105 References 105 6 Flow Meters 109 6.1 Molar Flow, Mass Flow, and Throughput 109 6.2 Rotameters and Chokes 111 6.3 Differential Pressure Devices 112 6.4 Thermal Mass Flow Technique 114 6.4.1 Mass Flow Meter 114 6.4.2 Mass Flow Controller 117 6.4.3 Mass Flow Meter Calibration 119 References 119 7 Pumping Speed 121 7.1 Definition 121 7.2 Mechanical Pump Speed Measurements 122 7.3 High Vacuum Pump Speed Measurements 123 7.3.1 Methods 123 7.3.2 Gas and Pump Dependence 124 7.3.3 Approximate Speed Measurements 125 7.3.4 Errors 125 References 127 8 Residual Gas Analyzers 129 8.1 Instrument Description 129 8.1.1 Ion Sources 131 8.1.1.1 Open Ion Sources 131 8.1.1.2 Closed Ion Sources 133 8.1.2 Mass Filters 134 8.1.2.1 Magnetic Sector 134 8.1.2.2 RF Quadrupole 135 8.1.2.3 Resolving Power 138 8.1.3 Detectors 138 8.1.3.1 Discrete Dynode Electron Multiplier 139 8.1.3.2 Continuous Dynode Electron Multiplier 140 8.2 Installation and Operation 142 8.2.1 Operation at High Vacuum 142 8.2.1.1 Sensor Mounting 142 8.2.1.2 Stability 143 8.2.2 Operation at Medium and Low Vacuum 145 8.2.2.1 Differentially Pumped Analysis 145 8.2.2.2 Miniature Quadrupoles 148 8.3 Calibration 148 8.4 Choosing an Instrument 149 References 150 9 Interpretation of RGA Data 153 9.1 Cracking Patterns 153 9.1.1 Dissociative Ionization 153 9.1.2 Isotopes 154 9.1.3 Multiple Ionization 154 9.1.4 Combined Effects 154 9.1.5 Ion–Molecule Reactions 157 9.2 Qualitative Analysis 158 9.3 Quantitative Analysis 163 9.3.1 Isolated Spectra 164 9.3.2 Overlapping Spectra 165 References 169 Part III Production 171 10 Mechanical Pumps 173 10.1 Rotary Vane 173 10.2 Lobe 177 10.3 Claw 180 10.4 Multistage Lobe 182 10.5 Scroll 184 10.6 Screw 185 10.7 Diaphragm 185 10.8 Reciprocating Piston 187 10.9 Mechanical Pump Operation 189 References 189 11 Turbomolecular Pumps 191 11.1 Pumping Mechanism 191 11.2 Speed–Compression Relations 192 11.2.1 Maximum Compression 193 11.2.2 Maximum Speed 195 11.2.3 General Relation 197 11.3 Ultimate Pressure 198 11.4 Turbomolecular Pump Designs 199 11.5 Turbo-Drag Pumps 201 References 203 12 Diffusion Pumps 205 12.1 Pumping Mechanism 205 12.2 Speed–Throughput Characteristics 207 12.3 Boiler Heating Effects 211 12.4 Backstreaming, Baffles, and Traps 212 References 215 13 Getter and Ion Pumps 217 13.1 Getter Pumps 217 13.1.1 Titanium Sublimation 218 13.1.2 Non-evaporable Getters 223 13.2 Ion Pumps 224 References 229 14 Cryogenic Pumps 233 14.1 Pumping Mechanisms 234 14.2 Speed, Pressure, and Saturation 237 14.3 Cooling Methods 241 14.4 Cryopump Characteristics 245 14.4.1 Sorption Pumps 246 14.4.2 Gas Refrigerator Pumps 249 14.4.3 Liquid Cryogen Pumps 253 References 253 Part IV Materials 257 15 Materials in Vacuum 259 15.1 Metals 260 15.1.1 Vaporization 260 15.1.2 Permeability 260 15.1.3 Outgassing 261 15.1.3.1 Dissolved Gas 262 15.1.3.2 Surface and Near-Surface Gas 264 15.1.4 Structural Metals 269 15.2 Glasses and Ceramics 272 15.3 Polymers 277 References 281 16 Joints Seals and Valves 285 16.1 Permanent Joints 285 16.1.1 Welding 286 16.1.2 Soldering and Brazing 290 16.1.3 Joining Glasses and Ceramics 291 16.2 Demountable Joints 293 16.2.1 Elastomer Seals 294 16.2.2 Metal Gaskets 300 16.3 Valves and Motion Feedthroughs 302 16.3.1 Small Valves 302 16.3.2 Large Valves 304 16.3.3 Special-Purpose Valves 307 16.3.4 Motion Feedthroughs 308 References 313 17 Pump Fluids and Lubricants 315 17.1 Pump Fluids 315 17.1.1 Fluid Properties 315 17.1.1.1 Vapor Pressure 316 17.1.1.2 Other Characteristics 319 17.1.2 Fluid Types 319 17.1.2.1 Mineral Oils 320 17.1.2.2 Esters 321 17.1.2.3 Silicones 321 17.1.2.4 Ethers 322 17.1.2.5 Fluorochemicals 322 17.1.3 Selecting Fluids 323 17.1.3.1 Rotary, Vane, and Lobe Pump Fluids 323 17.1.3.2 Turbo Pump Fluids 325 17.1.3.3 Diffusion Pump Fluids 325 17.1.4 Reclamation 328 17.2 Lubricants 328 17.2.1 Lubricant Properties 329 17.2.1.1 Absolute Viscosity 330 17.2.1.2 Kinematic Viscosity 331 17.2.1.3 Viscosity Index 332 17.2.2 Selecting Lubricants 333 17.2.2.1 Liquid 333 17.2.2.2 Grease 334 17.2.2.3 Solid Film 336 References 338 Part V Systems 341 18 Rough Vacuum Pumping 343 18.1 Exhaust Rate 344 18.1.1 Pump Size 344 18.1.2 Aerosol Formation 346 18.2 Crossover 350 18.2.1 Minimum Crossover Pressure 351 18.2.2 Maximum Crossover Pressure 354 18.2.2.1 Diffusion 354 18.2.2.2 Turbo 357 18.2.2.3 Cryo 357 18.2.2.4 Sputter-Ion 360 References 362 19 High Vacuum Systems 365 19.1 Diffusion-Pumped Systems 365 19.1.1 Operating Modes 368 19.1.2 Operating Issues 369 19.2 Turbo-Pumped Systems 371 19.2.1 Operating Modes 374 19.2.2 Operating Issues 375 19.3 Sputter-Ion-Pumped Systems 376 19.3.1 Operating Modes 377 19.3.2 Operating Issues 379 19.4 Cryo-Pumped Systems 379 19.4.1 Operating Modes 380 19.4.2 Regeneration 380 19.4.3 Operating Issues 382 19.5 High Vacuum Chambers 383 19.5.1 Managing Water Vapor 384 References 386 20 Ultraclean Vacuum Systems 387 20.1 Ultraclean Pumps 389 20.1.1 Dry Roughing Pumps 390 20.1.2 Turbopumps 390 20.1.3 Cryopumps 390 20.1.4 Sputter-Ion, TSP, and NEG Pumps 391 20.2 Ultraclean Chamber Materials and Components 392 20.3 Ultraclean System Pumping and Pressure Measurement 394 References 398 21 Controlling Contamination in Vacuum Systems 401 21.1 Defining Contamination in a Vacuum Environment 401 21.1.1 Establishing Control of Vacuum Contamination 401 21.1.2 Types of Vacuum Contamination 402 21.1.2.1 Particle Contamination 403 21.1.2.2 Gas Contamination 409 21.1.2.3 Film Contamination 410 21.2 Pump Contamination 411 21.2.1 Low/Rough and Medium Vacuum Pump Contamination 411 21.2.1.1 Fluid-Sealed Mechanical Pumps 412 21.2.1.2 Dry Mechanical Pumps 413 21.2.2 High and UHV Vacuum Pump Contamination 415 21.2.2.1 Diffusion Pumps 416 21.2.2.2 Turbo- and Turbo-Drag Pumps 417 21.2.2.3 Cryopumps 418 21.2.2.4 Sputter-Ion and Titanium-Sublimination Pumps 419 21.3 Evacuation Contamination 420 21.3.1 Particle Sources 420 21.3.2 Remediation Methods 421 21.4 Venting Contamination 422 21.5 Internal Components, Mechanisms, and Bearings 423 21.6 Machining Contamination 426 21.6.1 Cutting, Milling, and Turning 426 21.6.2 Grinding and Polishing 427 21.6.3 Welding 428 21.7 Process-Related Sources 429 21.7.1 Deposition Sources 429 21.7.2 Leak Detection 430 21.8 Lubrication Contamination 432 21.8.1 Liquid Lubricants 432 21.8.2 Solid Lubricants 433 21.8.3 Lamellar, Polymer, and Suspension Lubricants 434 21.9 Vacuum System and Component Cleaning 434 21.9.1 Designing a Cleaning Process 435 21.10 Review of Clean Room Environments for Vacuum Systems 436 21.10.1 The Cleanroom Environment 438 21.10.2 Using Vacuum Systems in a Cleanroom Environment 438 References 442 22 High Flow Systems 445 22.1 Mechanically Pumped Systems 447 22.2 Throttled High Vacuum Systems 449 22.2.1 Chamber Designs 449 22.2.2 Turbo Pumped 451 22.2.3 Cryo Pumped 455 References 459 23 Multichambered Systems 461 23.1 Flexible Substrates 462 23.2 Rigid Substrates 465 23.2.1 Inline Systems 465 23.2.2 Cluster Systems 469 23.3 Analytical Instruments 472 References 472 24 Leak Detection 475 24.1 Mass Spectrometer Leak Detectors 476 24.1.1 Forward Flow 476 24.1.2 Counter flow 477 24.2 Performance 478 24.2.1 Sensitivity 478 24.2.2 Response Time 480 24.2.3 Testing Pressurized Chambers 481 24.2.4 Calibration 482 24.3 Leak Hunting Techniques 483 24.4 Leak Detecting with Hydrogen Tracer Gas 486 References 487 Part VI Appendices 489 Appendix A Units and Constants 491 Appendix B Gas Properties 495 Appendix C Material Properties 509 Appendix D Isotopes 519 Appendix E Cracking Patterns 525 Appendix F Pump Fluid Properties 535 Index 543
£99.00
Wiley-Blackwell Evolutionary LargeScale MultiObjective
Book SynopsisTackle the most challenging problems in science and engineering with these cutting-edge algorithms Multi-objective optimization problems (MOPs) are those in which more than one objective needs to be optimized simultaneously. As a ubiquitous component of research and engineering projects, these problems are notoriously challenging. In recent years, evolutionary algorithms (EAs) have shown significant promise in their ability to solve MOPs, but challenges remain at the level of large-scale multi-objective optimization problems (LSMOPs), where the number of variables increases and the optimized solution is correspondingly harder to reach. Evolutionary Large-Scale Multi-Objective Optimization and Applications constitutes a systematic overview of EAs and their capacity to tackle LSMOPs. It offers an introduction to both the problem class and the algorithms before delving into some of the cutting-edge algorithms which have been specifically adapted to solving LSMOPs. D
£85.46
John Wiley & Sons Inc Next Generation Multiple Access
Book SynopsisHighly comprehensive resource investigating how next-generation multiple access (NGMA) relates to unrestricted global connection, business requirements, and sustainable wireless networks Next Generation Multiple Access is a comprehensive, state-of-the-art, and approachable guide to the fundamentals and applications of next-generation multiple access (NGMA) schemes, guiding the future development of industries, government requirements, and military utilization of multiple access systems for wireless communication systems and providing various application scenarios to fit practical case studies. The scope and depth of this book are balanced for both beginners to advanced users. Additional references are provided for readers who wish to learn more details about certain subjects. Applications of NGMA outside of communications, including data and computing assisted by machine learning, protocol designs, and others, are also covered. Written by four leading experts in the field, Next G
£99.00
John Wiley & Sons Inc Quantum Dot Display Science and Technology
Book Synopsis
£99.00
John Wiley & Sons Inc Converting Power into Chemicals and Fuels
Book SynopsisCONVERTING POWER INTO CHEMICALS AND FUELS Understand the pivotal role that the petrochemical industry will play in the energy transition by integrating renewable or low-carbon alternatives Power into Chemicals and Fuels stresses the versatility of hydrogen as an enabler of the renewable energy system, an energy vector that can be transported and stored, and a fuel for the transportation sector, heating of buildings and providing heat and feedstock to industry. It can reduce both carbon and local emissions, increase energy security and strengthen the economy, as well as support the deployment of renewable power generation such as wind, solar, nuclear and hydro. With a focus on power-to-X technologies, this book discusses the production of basic petrochemicals in such a way as to minimize the carbon footprint and develop procedures that save energy or use energy from renewable sources. Various different power-to-X system configurations are introduced withTable of ContentsAbout the Book xvii Preface xix Acknowledgments xxiii General Literature xxv Nomenclature xxxi Abbreviations and Acronyms xxxiii 1 Power-to-Chemical Technology 1 1.1 Introduction 2 1.2 Power-to-Chemical Engineering 4 1.2.1 Carbon Dioxide Thermodynamics 4 1.2.2 Carbon Dioxide Aromatization Thermodynamics 12 1.2.3 Reaction Mechanism of Carbon Dioxide Methanation 14 1.2.4 Water Electrolysis Thermodynamics 18 1.2.5 Methane Pyrolysis Reaction Thermodynamic Consideration 20 1.2.5.1 The Carbon-Hydrogen System 20 1.2.6 Reaction Kinetics and Mechanism 27 1.2.7 Thermal Mechanism of Methane Pyrolysis into a Sustainable Hydrogen 28 1.2.8 Catalytic Mechanism Splitting of Methane into a Sustainable Hydrogen 30 1.2.9 Conversion of Methane over Metal Catalysts into a Sustainable Hydrogen 35 1.2.9.1 Nickel Catalysts 35 1.2.9.2 Iron Catalysts 37 1.2.9.3 Regeneration of Metal Catalysts 39 1.2.10 Conversion of Methane over Carbon Catalysts into Clean Hydrogen 40 1.2.10.1 Activity of Carbon Catalysts 40 1.2.10.2 Stability and Deactivation of Carbon Catalysts 42 1.2.10.3 Regeneration of Carbon Catalysts 43 1.2.10.4 Co-Feeding to Extend the Lifetime of Carbon Catalysts 44 1.2.11 Reactors 44 1.2.11.1 Conversion, Selectivity and Yields 44 1.2.11.2 Modelling Approach of the Structured Catalytic Reactors 45 1.2.11.3 Reactor Concept for Catalytic Carbon Dioxide Methanation 46 1.2.11.4 Monolithic Reactors 48 1.2.11.5 Mass Transfer in the Honeycomb and Slurry Bubble Column Reactor 49 1.2.11.6 Heat Transfer in Honeycomb and Slurry Bubble Column Reactors 50 1.2.11.7 Process Design 51 1.2.11.8 Comparison and Outlook 52 1.3 Potential Steps Towards Sustainable Hydrocarbon Technology: Vision and Trends 53 1.3.1 Technology Readiness Levels 54 1.3.2 A Vision for the Oil Refinery of 2030 59 1.3.3 The Transition from Fuels to Chemicals 60 1.3.3.1 Crude Oil to Chemicals Investments 66 1.3.3.2 Available Crude-to-Chemicals Routes 67 1.3.4 Business Trends: Petrochemicals 2025 67 1.3.4.1 Asia-Pacific 69 1.3.4.2 Middle East 70 1.3.4.3 United States 70 1.4 Digital Transformation 71 1.4.1 Benefits of Digital Transformation 71 1.4.2 A New Workforce and Workplace 72 1.4.3 Technology Investment 73 1.4.4 The Greening of the Downstream Industry 74 1.4.4.1 Sustainable Alkylation Technology 75 1.4.4.2 Ecofriendly Catalyst 75 1.5 RAM Modelling 76 1.5.1 RAM1 Site Model 77 1.5.2 RAM2 Plant Models 77 1.5.3 RAM3 Models 78 1.5.4 RAM Modelling Benefit 78 1.6 Conclusions 78 Further Reading 80 2 The Green Shift in Power-to-Chemical Technology and Power-to-Chemical Engineering: A Framework for a Sustainable Future 85 2.1 Introduction 86 2.2 Eco-Friendly Catalyst 87 2.2.1 Development of Catalysts Supported on Carbons for Carbon Dioxide Hydrogenation 88 2.2.2 Properties of Carbon Supports 89 2.3 Hydrogen 91 2.3.1 Different Colours and Costs of Hydrogen 92 2.3.1.1 Blue Hydrogen 92 2.3.1.2 Green Hydrogen 92 2.3.1.3 Grey Hydrogen 93 2.3.1.4 Pink Hydrogen 93 2.3.1.5 Yellow Hydrogen 93 2.3.1.6 Multi-Coloured Hydrogen 93 2.3.1.7 Hydrogen Cost 93 2.4 Alternative Feedstocks 95 2.4.1 Carbon Dioxide-Derived Chemicals 95 2.5 Alternative Power-to-X-Technology 97 2.5.1 Power-to-X-Technology to Produce Electrochemicals and Electrofuels 97 2.6 Partial Oxidation of Methane 99 2.7 Biorefining 99 2.8 Sustainable Production to Advance the Circular Economy 100 2.8.1 Introduction 100 2.8.2 Circular Economy 101 2.8.2.1 Sustainability 101 2.8.2.2 Scope 101 2.8.2.3 Background of the Circular Economy 102 2.8.2.3.1 Emergence of the Idea 102 2.8.2.3.2 Moving Away from the Linear Model 103 2.8.2.3.3 Towards the Circular Economy 103 2.8.3 Circular Business Models 103 2.8.4 Industries Adopting a Circular Economy 104 2.8.4.1 Minimizing Dependence on Fossil Fuels 104 2.8.4.2 Minimizing the Impact of Chemical Synthesis and Manufacturing 105 2.8.4.3 Future Research Needs in Developing a Circular Economy 106 2.9 New Chemical Technologies 106 2.9.1 Renewable Power 107 Further Reading 108 3 Storage Renewable Power-to-Chemicals 113 3.1 Introduction 113 3.2 Terminology 118 3.3 Energy Storage Systems 119 3.4 World Primary Energy Consumption 126 3.4.1 2019 Briefly 126 3.4.2 Energy in 2020 128 3.4.2.1 Not Just Green but Greening 128 3.4.2.2 For Energy, 2020 Was a Year Like No Other 129 3.4.2.3 Glasgow Climate Pact 129 3.4.2.4 Energy in 2020: What Happened and How Surprising Was It 131 3.4.2.5 How Should We Think About These Reductions 131 3.4.2.6 What Can We Learn from the COVID-induced Stress Test 133 3.4.2.7 Progress Since Paris – How Is the World Doing 134 3.5 Carbon Dioxide Emissions 135 3.5.1 Carbon Footprint 136 3.5.1.1 Climate-driven Warming 137 3.5.2 Carbon Emissions in 2020 138 3.6 Clean Fuels ‒ the Advancement to Zero Sulfur 139 3.7 Renewables in 2019 140 3.8 Hydroelectricity and Nuclear Energy 141 3.9 Conclusion 141 Further Reading 142 4 Carbon Capture, Utilization and Storage Technologies 145 4.1 Industrial Sources of Carbon Dioxide 145 4.2 Carbon Capture, Utilization and Storage Technologies 147 4.3 Carbon Dioxide Capture 147 4.4 Developing and Deploying CCUS Technology in the Oil and Gas Industry 155 4.5 Sustainable Steel/Chemicals Production: Capturing the Carbon in the Material Value Chain 158 4.5.1 Valorisation of Steel Mill Gases 158 4.5.2 Summary and Outlook 161 Further Reading 162 5 Integrated Refinery Petrochemical Complexes Including Power-to-X Technologies 165 5.1 Introduction 165 5.2 Synergies Between Refining and Petrochemical Assets 167 5.2.1 Reaching Maximum Added Value – Integrated Refining Schemes 168 5.2.1.1 Fluid Catalytic Cracking Alternates 168 5.2.1.2 Hydrocracking Alternates 170 5.2.2 Comparisons and Sensitivities to Product/Utility Pricing 172 5.2.3 Options for Further Increasing the Petrochemical Value Chain 174 5.3 Carbon Dioxide Emissions 175 5.3.1 Effect of a Carbon Dioxide Tax 176 5.3.2 Crude Oil Effects 179 5.4 Summary 180 5.5 Power- to-X Technology 181 5.6 The Role of Nuclear Power 185 5.6.1 Small Nuclear Power Reactors 187 5.6.2 Conclusion 187 Further Reading 188 6 Power-to-Hydrogen Technology 191 6.1 Introduction 192 6.2 Traditional and Developing Technologies for Hydrogen Production 193 6.3 Dry Reforming of Methane 195 6.4 Tri-reforming of Methane 197 6.5 Greenfield Technology Option → Low Carbon Emission Routes 198 6.5.1 Water Electrolysis 201 6.5.1.1 Alkaline Electrolysis 202 6.5.1.2 Polymer Electrolyte Membrane Electrolysis 203 6.5.1.3 Solid Oxide Electrolysis 204 6.5.2 Methane Pyrolysis 207 6.5.2.1 Process Concepts for Industrial Application 208 6.5.2.2 Perspectives of the Carbon Coproduct 211 6.5.3 Thermochemical Processes 213 6.5.4 Photocatalytic Processes 213 6.5.5 Biomass Electro-Reforming 214 6.5.6 Microorganisms 215 6.5.7 Hydrogen from Other Industrial Processes 215 6.5.8 Hydrogen Production Cost 215 6.5.9 Electrolysers 215 6.5.10 Carbon Footprint 216 6.6 Advances in Chemical Carriers for Hydrogen 216 6.6.1 Demand Drivers 217 6.6.2 Options for Hydrogen Deployment 218 6.6.3 Advances in Hydrogen Storage/Transport Technology 218 6.6.4 Global Supply Chain 220 6.6.5 Power-to-Gas Demo 220 6.6.5.1 Hydrogen Fuelling Stations 221 6.6.5.2 Pathway to Commercialization 221 6.6.5.3 Transportation Studies in North America 221 6.6.6 Future Applications 222 6.7 Ammonia Fuel Cells 223 6.7.1 Proton-Conducting Fuel Cells 223 6.7.2 Polymer Electrolyte Membrane Fuel Cells 224 6.7.3 Proton-conducting Solid Oxide Fuel Cells 224 6.7.4 Alkaline Fuel Cells 225 6.7.5 Direct Ammonia Solid Oxide Fuel Cell 226 6.7.6 Equilibrium Potential and Efficiency of the Ammonia-Fed SOFC 227 6.8 Conclusions 228 Further Reading 228 7 Power-to-Fuels 233 7.1 Introduction 234 7.2 Selection of Fuel Candidates 240 7.2.1 Fuel Production Processes 241 7.3 Power-to-Methane Technology 242 7.3.1 Carbon Dioxide Electrochemical Reduction 242 7.3.2 Carbon Dioxide Hydrogenation 244 7.4 Power-to-Methanol 248 7.5 Power-to-Dimethyl Ether 249 7.6 Chemical Conversion Efficiency 250 7.6.1 Exergy 250 7.6.2 Exergy Efficiency 251 7.6.3 Economic and Environmental Evaluation 251 7.6.4 Fuel Assessment 252 7.6.5 Performance of Fuel Production Processes 253 7.6.6 Process Chain Evaluation 254 7.6.7 Fuel Cost 255 7.7 Well-to-Wheel Greenhouse Gas Emissions 257 7.7.1 Environmental Impact 258 7.7.2 Infrastructure 258 7.7.3 Efficiency 259 7.7.4 Energy/Power Density 259 7.7.5 Pollutant Emissions 260 7.8 Gasoline Electrofuels 260 7.9 Diesel Electrofuels 261 7.10 Electrofuels and/or Electrochemicals 263 7.10.1 Physico-Chemical Properties 264 7.10.1.1 Density 264 7.10.1.2 Tribological Properties 264 7.10.1.3 Combustion Characteristics 265 7.10.1.4 Combustion and Emissions 267 7.10.2 Diesel Engine Efficiency 269 7.10.3 Potential of Diesel Electrofuels 269 7.11 Maturity, TRL, Production and Electrolysis Costs 271 7.11.1 Summary 273 7.12 Power-to-Liquid Technology 274 7.12.1 Power-to-Jet Fuel 275 7.12.2 Power-to-Diesel 276 7.13 Conclusion and Outlook 276 Further Reading 278 8 Power-to-Light Alkenes 283 8.1 Oxidative Dehydrogenation 283 8.1.1 Carbon Dioxide as a Soft Oxidant for Catalytic Dehydrogenation 283 8.1.2 Carbon Dioxide: Oxidative Coupling of Methane 285 8.1.3 From Carbon Dioxide to Lower Olefins 289 8.1.4 Low-Carbon Production of Ethylene and Propylene 291 8.1.4.1 Energy Demand per Unit of Ethylene/Propylene Production via Methanol 292 8.1.4.2 Carbon Dioxide Reduction per Unit of Ethylene/Propylene Production 292 8.1.4.3 Economics of Low-Carbon Ethylene and Propylene Production 293 8.2 Life Cycle Assessment 293 8.2.1 Small-Scale Production of Ethylene 293 8.3 Polymerization Reaction 294 8.3.1 Carbon Dioxide-Based Polymers 294 8.3.1.1 Perspective and Practical Applications 298 Further Reading 299 9 Power-to-BTX Aromatics 301 9.1 Low-Carbon Production of Aromatics 301 9.1.1 Methanol to Aromatics Process 303 9.1.1.1 ZSM-5 Catalyst 304 9.1.1.2 Process Variables 305 9.1.1.3 Kinetic Modelling 306 9.1.1.4 Aromatics via Hydrogen-Based Methanol (TRL7) 307 9.1.1.5 Energy Demand per Unit of Low-Carbon BTX Production 308 9.1.1.6 Carbon Dioxide Reduction 308 9.1.1.7 Economics of Low-Carbon BTX Production 308 9.2 Production of p-Xylene from 2,5-Dimethylfuran and Ethylene 308 9.3 Carbon Dioxide Dehydrogenation of Ethylbenzene to Styrene 309 Further Reading 310 10 Power-to-C 1 Chemicals 313 10.1 Introduction 314 10.2 Carbon Dioxide Utilization into Chemical Technology 317 10.3 Mechanism of Conversion of Carbon Dioxide 318 10.4 Hydrogenation of Carbon Dioxide 319 10.4.1 Heterogeneous Hydrogenation 319 10.4.2 Homogeneous Hydrogenation 323 10.5 Electrochemical Conversion of Carbon Dioxide into Valuable Chemicals 324 10.5.1 Technologies Available for Carbon Dioxide Reduction 325 10.6 Electrochemical Technologies 326 10.6.1 Roles of Ionic Liquids on Electrochemical Carbon Dioxide Reduction Promotion 328 10.6.2 Ionic Liquids as Absorbent for Carbon Dioxide Capture 328 10.6.3 Classification of the Electrode Material 328 10.6.4 High Hydrogen Evolution Overvoltage Metal 329 10.6.5 Low Hydrogen Evolution Overvoltage Metals 329 10.6.6 Copper Electrodes 329 10.6.7 Other Electrodes for Carbon Dioxide Reduction 330 10.7 Power-to-Methanol Technology 331 10.7.1 Carbon Dioxide Electrochemical Reduction 332 10.7.2 Direct Carbon Dioxide Hydrogenation into Methanol 334 10.7.3 Low-Carbon Methanol Production 336 10.7.4 Energy Demand 337 10.8 Power-to-Formic Acid Technology 337 10.8.1 Carbon Dioxide Electrochemical Reduction 338 10.8.2 Carbon Dioxide Hydrogenation 339 10.9 Power-to-Formaldehyde Technology 341 10.9.1 Carbon Dioxide Electrochemical Reduction 342 10.9.2 Carbon Dioxide Hydrogenation 342 10.10 Selective Hydrogenation of Carbon Dioxide to Light Olefins 343 10.10.1 Introduction 343 10.10.2 Carbon Dioxide via FTS to Lower Olefins 345 10.10.3 Methane via FTS to Lower Olefins 347 10.10.4 Carbon Dioxide via FTS to Liquid iso-C 5 -C 13 -Alkanes 349 10.10.4.1 Power-to-Liquids 352 10.10.4.2 Energy Demand per Unit of Synthetic Fuel Production 352 10.10.4.3 Carbon Dioxide Reduction per Unit of Synthetic Fuel Production 353 10.10.4.4 Economics 353 10.10.4.5 Comparison of the Hydrogen-Based Low-Carbon Synthesis Routes 353 10.11 Electrochemical Reduction of Carbon Dioxide to Oxalic Acid 354 10.11.1 Process Design and Modelling 355 10.11.2 Carbon Dioxide Absorption in Propylene Carbonate 356 Further Reading 356 11 Power-to-Green Chemicals 363 11.1 Introduction 364 11.2 Biomethanol Production 365 11.2.1 Biomethanol Production Process 365 11.2.2 Energy and Feedstock Demand per Unit of Biomethanol Production 366 11.2.3 Carbon Dioxide Reduction per Unit of Biomethanol Production 367 11.2.4 Economics of Biomethanol Production 367 11.3 Bioethanol Production 367 11.3.1 Bioethanol Production Process 368 11.3.2 Energy and Feedstock Demand per Unit of Bioethanol Production 369 11.3.3 Carbon Dioxide Reduction per Unit of Bioethanol Production 370 11.3.4 Carbon Dioxide Reduction for (Partially) Replacing Gasoline with Bioethanol 370 11.3.5 Economics of Bioethanol Production 370 11.4 Bioethylene Production 371 11.4.1 Bioethylene Production Process 371 11.4.2 Energy and Feedstock Demand per Unit of Bioethylene Production 371 11.4.3 Carbon Dioxide Reduction per Unit of Bioethylene Production 371 11.4.4 Economics of Bioethylene Production 372 11.5 Biopropylene Production 372 11.5.1 Biopropylene Production Processes 372 11.5.2 Energy and Feedstock Demand per Unit of Biopropylene Production 372 11.5.3 Carbon Dioxide Reduction per Unit of Biopropylene Production 373 11.6 BTX Production from Biomass 373 11.6.1 BTX Production Process 373 11.6.2 Energy and Feedstock Demand per Unit of BTX Production from Biomass 374 11.6.3 Carbon Dioxide Emissions per Unit of BTX Production from Biomass 374 11.7 Comparison of the Biomass-Based Synthesis Routes 374 11.8 Biofuels 376 11.8.1 Biodiesel Production 377 11.8.2 Purification of Glycerol 379 11.8.3 Conversion of Glycerol into Valuable Products 380 11.8.3.1 Solketal Synthesis Process 382 11.8.3.2 Reaction Mechanism 383 11.8.3.3 Kinetics of Reaction 384 11.8.3.4 Catalyst Design 385 11.8.3.5 Batch Process 387 11.8.3.6 Continuous Process 388 11.8.4 Current Issues and Challenges 389 11.8.5 Future Recommendation 391 11.8.6 Conclusion 391 11.9 Higher Alcohols and Ether Biofuels 392 11.9.1 Fuel Production Routes and Sustainability 393 11.9.2 Lignin 394 11.9.3 Fuel Properties 394 11.9.4 Concluding Remarks 396 11.10 Biofuels in the World: Biogasoline and Biodiesel 396 Further Reading 399 12 Industrial Small Reactors 405 12.1 Introduction 405 12.2 Thermochemical Water Splitting 406 12.3 Small Modular Reactors 407 12.4 Nuclear Process Heat for Industry 410 12.4.1 High-temperature Reactors for Process Heat 410 12.4.2 Recovery of Oil from Tar Sands 413 12.4.3 Oil Refining 414 12.4.4 Coal and Its Liquefaction 414 12.4.5 Biomass-Based Ethanol Production 415 12.4.6 District Heating 416 12.5 Microchannel Reduction Cell 416 12.6 Conversion of Carbon Dioxide to Graphene 417 12.7 The Ammonia Synthesis Reactor-Development of Small-scale Plants 419 Further Reading 421 13 Recycling of Waste Plastics → Plastics Circularity 423 13.1 Introduction 424 13.2 Mechanism Aspects of Waste Plastic Pyrolysis 426 13.2.1 Polyethylene and Polypropylene 428 13.2.2 Polyethylene Terephthalate 429 13.2.3 Polyvinyl Chloride 430 13.2.4 Polystyrene 431 13.2.5 Poly (Methyl Methacrylate) 432 13.3 Kinetics 433 13.4 Catalysts 434 13.4.1 Zeolites 434 13.4.2 Fluid Catalytic Cracking Catalysts 434 13.5 Parameters Affecting Pyrolysis 436 13.5.1 Type of Plastic Feed 436 13.5.2 Temperature and Residence Time 437 13.5.3 Pressure 438 13.6 Type of Reactors 438 13.6.1 Rotary Kiln Reactor 438 13.6.2 Screw Feed (Auger) Reactor 439 13.6.3 Fluid Catalytic Cracking Reactor 440 13.6.4 Stirred-Tank Reactor 440 13.6.5 Plasma Pyrolysis Reactor 441 13.6.6 Batch Reactor 442 13.6.7 Fixed Bed Reactor 442 13.6.8 Fluidized Bed Reactor 443 13.6.9 Conical Spouted Bed Reactor 443 13.6.10 Microwave Reactor 444 13.6.11 Pyrolysis in Supercritical Water 445 13.7 Applications of Pyrolysis Products 446 13.7.1 Pyrolysis Gases → Hydrogen and Methane 446 13.7.2 Pyrolysis Oil → Aromatics and Diesel Fuels 446 13.7.3 Pyrolysis Char → Nanotubes 449 Further Reading 450 Index 455
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John Wiley & Sons Inc Nanodevices for Integrated Circuit Design
Book SynopsisNANODEVICES FOR INTEGRATED CIRCUIT DESIGN Nanodevices are an integral part of many of the technologies that we use every day. It is a constantly changing and evolving area, with new materials, processes, and applications coming online almost daily. Increasing demand for smart and intelligent devices in human life with better sensing, communication and signal processing is increasingly pushing researchers and designers towards future design challenges based upon internet-of-things (IoT) applications. Several types of research have been done at the level of solid-state devices, circuits, and materials to optimize system performance with low power consumption. For suitable IoT-based systems, there are some key areas, such as the design of energy storage devices, energy harvesters, novel low power high-speed devices, and circuits. Uses of new materials for different purposes, such as semiconductors, metals, and insulators in different parts of devices, circuits, and energy sources, also plTable of ContentsList of Contributors xiii Preface xvii Acknowledgements xix 1 Growth of Nano-Wire Field Effect Transistor in 21st Century 1Kunal Sinha 1.1 Introduction 2 1.2 Initial Works on Nanowire Field-Effect-Transistors (NW-FET) 3 1.2(A) Theoretical and Simulation Studies on Nanowire FET (NW-FET) 4 1.2(B) Fabrication of Nanowire Field-Effect-Transistor (NW-FET) 10 1.3 Application of Nanowire Field-Effect-Transistors (NW-FET) 15 1.4 Conclusion 17 2 Impact of Silicon Nanowire-Based Transistor in IC Design Perspective 23G. Boopathi Raja 2.1 Introduction 24 2.2 Nanoscale Devices 25 2.3 Nanowire Heterostructures and Silicon Nanowires 29 2.4 Performance Analysis of Si Nanowire with SOI FET 38 2.5 Conclusion 40 3 Kink Effect in Field Effect Transistors: Different Models and Techniques 43Abdelaali Fargi, Sami Ghedira and Adel Kalboussi 3.1 Introduction 44 3.2 Techniques of Kink Effect 45 3.3 Different Models of Kink Effect 48 3.4 Kink Effect in MOS Capacitors 48 3.5 Conclusion 58 4 Next Generation Molybdenum Disulfide FET: Its Properties, Evaluation, and Its Applications 61Vydha Pradeep Kumar and Deepak Kumar Panda 4.1 Introduction of Two-Dimensional Materials 62 4.2 Evaluation of 2D-Materials 64 4.3 Overview of MoS2 66 4.4 Properties of MoS2 68 4.5 Fabrication of MoS2 71 4.6 Applications of MoS2 72 4.7 Comparison of Other 2D Materials with MoS2 75 4.8 Conclusion 80 5 Impact of Working Temperature on the ION /IOFF Ratio of a Hetero Step-Shaped Gate TFET With Improved Ambipolar Conduction 83Bijoy Goswami, Savio Jay Sengupta, Ankur Jyoti Sarmah and Nalin Behari Dev Choudhury 5.1 Introduction 84 5.2 Device Structure 84 5.3 Results and Discussion 86 5.4 Conclusion 89 6 Analysis of RF with DC and@Linearity Parameter and Study of Noise Characteristics of Gate-All-Around Junctionless FET (GAA-JLFET) and Its Applications 93Pratikhya Raut, Umakanta Nanda and Deepak Kumar Panda 6.1 Introduction 94 6.2 Structure of GAA-JLFET 97 6.3 Results and Discussion 98 6.4 Applications 112 6.5 Conclusion 112 7 E-Mode-Operated Advanced III-V Heterostructure Quantum Well Devices for Analog/RF and High-Power Switching Applications 117A. Mohanbabu, N. Vinodhkumar, S. Maheswari, S. Baskaran, V. Janakiraman, M. Saravanan and P. Murugapandiyan 7.1 Silicon Era and Scaling Limit 118 7.2 III-V GaN-Based Compound Semiconductors 119 7.3 Band-Gap Engineering 119 7.4 Quantum Well 120 7.5 Polarization in GaN Devices and their Specific Properties 121 7.6 Strain and Lattice Mismatch in III-N Semiconductors 123 7.7 High Electron Mobility Transistors (HEMTs) 123 7.8 Two-Dimensional Electron Gas (2DEG) 124 7.9 AlGaN/GaN Heterostructure HEMT 125 7.10 Enhancement Mode GaN DH-HEMTs Device With Boron-Doped Gate Cap Layer 129 7.11 High-K Gate Dielectric III-Nitride GaN MIS-HEMT Devices 132 7.12 Conclusion 137 8 Design of FinFET as Biosensor 143Suman Lata Tripathi and Balwinder Raj 8.1 Introduction 143 8.2 Existing FET Based Biosensors 145 8.3 Performance Parameters of Biosensors 149 8.4 FinFET Designed as Biosensor Using Visual TCAD 149 8.5 Biosensors in Disease Detection 152 8.6 Conclusion 153 8.7 Acknowledgement 154 9 Biodegradable and Flexible Electronics: Types and Applications 157Vrinda Gupta, Sachin Himalyan and Archit Sundriyal 9.1 Introduction 158 9.2 Biodegradable and Flexible Electronics 160 9.3 Types of Materials Used for Biodegradable and Flexible Electronics 164 9.4 Applications of Biodegradable and Flexible Electronic Devices 171 9.5 Conclusion 176 10 Novel Parameters Extraction Method of High-Speed PIN Diode for Power Integrated Circuit 181Sami Ghedira and Abdelaali Fargi 10.1 Introduction 182 10.2 Review of the Technology and Physics of Power PIN Diodes 183 10.3 State of the Art of PIN Diode Parameters Extraction 186 10.4 Proposed Method 188 10.5 Validation 205 10.6 Conclusion 207 11 Edge AI -- A Promising Technology 211Remya R., Nalesh S. and Kala S. 11.1 Introduction 211 11.2 Deep Neural Networks 213 11.3 Model Compression Techniques for Deep Learning 216 11.4 Computing Infrastructures 221 11.5 Conclusion 223 12 Tunable Frequency Oscillator 227Abhishek Kumar 12.1 Introduction 227 12.2 Experimental Methods and Materials 230 12.3 Results and Discussion 235 12.4 Conclusion 240 13 Introduction to Nanomagnetic Materials for Electronic Devices: Fundamental, Synthesis, Classification and Applications 243Shivani Malhotra, Mansi Chitkara, Lipika Gupta and Monika Parmar 13.1 Introduction -- An Explanation of the Process and Approach 244 13.2 Nanomaterials 244 13.3 Synthesis and Characterization of Nano Materials 248 13.4 Characterization Technique for Structural Analysis 251 13.5 Magnetic Materials 252 13.6 Classification of Magnetic Materials 253 13.7 Magnetic Properties 256 13.8 Ferrites 258 13.9 Applications of Magnetic Materials 265 13.10 Conclusion 268 References 268 About the Editors 273 Index 275
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Composed of nine chapters, the book covers digitaTable of ContentsList of Contributors xxv Preface xxix Acknowledgment xxxi Acronyms xxxiii About the Companion Website xlv Part I Transforming Engineering Through Digital and Model-Based Methods 1Mark Blackburn 1 Fundamentals of Digital Engineering 3Mark R. Blackburn and Timothy D. West 2 Mission and Systems Engineering Methods 25Benjamin Kruse, Brian Chell, Timothy D. West, and Mark R. Blackburn 3 Transforming Systems Engineering Through Integrating Modeling and Simulation and the Digital Thread 47Daniel Dunbar, Tom Hagedorn, Timothy D. West, Brian Chell, John Dzielski, and Mark R. Blackburn 4 Digital Engineering Visualization Technologies and Techniques 69Brian Chell, Tom Hagedorn, Roger Jones, and Mark R. Blackburn 5 Interactive Model-Centric Systems Engineering 91Donna H. Rhodes and Adam M. 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John Wiley & Sons Inc Systems Science for Engineers and Scholars
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Systems Science for Engineers and Scholars readers will discover: Ten systems science principles that open engineers' and scholars' horizons to practical insights related to their areas of interest A methodology for designing holistic systems that exhibit resilient behavior to overcome systems' context uncertainties The most critical current dilemma of humankindthe global environment and energy crises, as well as a systemic, no-nonsense action plan to deal with these issues Independent articles describing how engineers and scholars can utilize systems science creatively in (1) engineering and systemicTable of ContentsPREFACE 10 ACKNOWLEDGMENTS 12 PART 1 - FACETS OF SYSTEMS SCIENCE AND ENGINEERING 14 CHAPTER 1: INTRODUCTION TO SYSTEMS SCIENCE 15 1.1 FOREWORD 15 1.2 CRITICAL HUMANITY CHALLENGE 19 1.3 SYSTEMS SCIENCE IN BRIEF 21 1.4 EARLY SYSTEMS PIONEERS 28 1.5 RECOMMENDED BOOKS ON SYSTEMS SCIENCE 30 1.6 CRITICISM OF SYSTEMS SCIENCE 31 1.7 BIBLIOGRAPHY 34 CHAPTER 2: PRINCIPLES OF SYSTEMS SCIENCE (PART I) 36 2.1 INTRODUCTION 36 2.2 UNIVERSAL CONTEXT 36 2.3 SYSTEMS BOUNDARY 41 2.4 SYSTEMS HIERARCHY 45 2.5 SYSTEMS INTERACTIONS 49 2.6 SYSTEMS CHANGE 54 2.7 BIBLIOGRAPHY 63 CHAPTER 3: PRINCIPLES OF SYSTEMS SCIENCE (PART II) 65 3.1 INTRODUCTION 65 3.2 SYSTEMS INPUT/OUTPUT 65 3.3 SYSTEMS COMPLEXITY 70 3.4 SYSTEMS CONTROL 83 3.5 SYSTEMS EVOLUTION 86 3.6 SYSTEMS EMERGENCE 95 3.7 BIBLIOGRAPHY 99 CHAPTER 4: SYSTEMS THINKING 101 4.1 INTRODUCTION 101 4.2 HISTORY OF SYSTEMS THINKING 101 4.3 FUNDAMENTAL CONCEPTS OF SYSTEMS THINKING 102 4.4 THE ICEBERG MODEL OF SYSTEMS THINKING 104 4.5 EXPLORING SYSTEMS THINKING AS A SYSTEM 105 4.6 BARRIERS TO SYSTEMS THINKING 107 4.7 BIBLIOGRAPHY 109 CHAPTER 5: SYSTEMS ENGINEERING 110 5.1 INTRODUCTION 110 5.2 PHILOSOPHY OF ENGINEERING 110 5.3 BASIC SYSTEMS ENGINEERING CONCEPTS 119 5.4 SYSTEMS ENGINEERING DEFICIENCIES 124 5.5 BIBLIOGRAPHY 135 CHAPTER 6: COMPARATIVE ANALYSIS – TWO DOMAINS 136 6.1 INTRODUCTION 136 6.2 A CASE FOR COMPARISON 136 6.3 STRUCTURE AND FUNCTION OF A COMPUTER HARD DRIVE (CHD) 137 6.4 FUNCTIONAL CORRELATIONS BETWEEN CHD AND THE DHD 139 6.5 CONCLUSIONS 144 6.6 ACKNOWLEDGMENT 145 6.7 BIBLIOGRAPHY 145 PART 2 - HOLISTIC SYSTEMS DESIGN 146 CHAPTER 7: HOLISTIC SYSTEMS CONTEXT 147 7.1 INTRODUCTION 147 7.2 RETHINKING THE CONTEXT OF THE SYSTEM 147 7.3 COMPONENTS OF SYSTEMS' CONTEXT 148 7.4 BIBLIOGRAPHY 152 CHAPTER 8: EXAMPLE - UAV SYSTEM OF INTEREST (SOI) 154 8.1 INTRODUCTION 154 8.2 EXAMPLE - UAV SYSTEM 154 8.3 BIBLIOGRAPHY 163 CHAPTER 9: EXAMPLE - UAV CONTEXT (PART I) 164 9.1 INTRODUCTION 164 9.2 UAV CONTEXT - NATURAL SYSTEMS 164 9.3 UAV CONTEXT - SOCIAL SYSTEMS 167 9.4 UAV CONTEXT - RESEARCHAPTER SYSTEMS 168 9.5 UAV CONTEXT - FORMATION SYSTEMS 173 9.6 UAV CONTEXT - SUSTAINMENT SYSTEMS 176 9.7 UAV CONTEXT - BUSINESS SYSTEMS 178 9.8 UAV CONTEXT - COMMERCIAL SYSTEMS 180 9.9 BIBLIOGRAPHY 186 CHAPTER 10: EXAMPLE - UAV CONTEXT (PART II) 188 10.1 INTRODUCTION 188 10.2 UAV CONTEXT - FINANCIAL SYSTEMS 188 10.3 UAV CONTEXT - POLITICAL SYSTEMS 191 10.4 UAV CONTEXT - LEGAL SYSTEMS 194 10.5 UAV CONTEXT - CULTURAL SYSTEMS 196 10.6 UAV CONTEXT - BIOSPHERE SYSTEMS 202 10.7 BIBLIOGRAPHY 203 PART 3 - GLOBAL ENVIRONMENT AND ENERGY - CRISIS AND ACTION PLAN 205 CHAPTER 11: GLOBAL ENVIRONMENT CRISES 206 11.1 INTRODUCTION 206 11.2 CLIMATE CHANGE 208 11.3 BIODIVERSITY LOSS 216 11.4 BIBLIOGRAPHY 227 CHAPTER 12: SYSTEMIC ENVIRONMENT ACTION PLAN 229 12.1 INTRODUCTION 229 12.2 SUSTAINING THE EARTH'S ENVIRONMENT 229 12.3 SUSTAINING HUMAN SOCIETY 238 12.4 BIBLIOGRAPHY 247 CHAPTER 13: GLOBAL ENERGY CRISIS 248 13.1 INTRODUCTION 248 13.2 CURRENT GLOBAL ENERGY STATUS 248 13.3 ENERGY RETURN ON INVESTMENT (EROI) 250 13.4 RENEWABLE ENERGY 253 13.5 FOSSIL FUELS ENERGY 258 13.6 CONVENTIONAL FISSION REACTION ENERGY 259 13.7 BIBLIOGRAPHY 261 CHAPTER 14: SYSTEMIC ENERGY ACTION PLAN 262 14.1 THE GLOBAL ENERGY DILEMMA 262 14.2 RENEWABLE ENERGY – ACTION PLAN 262 14.3 FOSSIL FUELS ENERGY – ACTION PLAN 263 14.4 CARS AND TRUCKS ACTION PLAN 264 14.5 FISSION REACTION ENERGY – ACTION PLAN 264 14.6 SMALL MODULAR REACTORS (SMRS) ACTION PLAN 265 14.7 FUSION NUCLEAR ENERGY ACTION PLAN 269 14.8 BIBLIOGRAPHY 273 PART 4 - MORE SYSTEMS SCIENCE FOR ENGINEERS AND SCHOLARS 274 CHAPTER 15: ENGINEERING AND SYSTEMIC PSYCHOLOGY 275 15.1 INTRODUCTION 275 15.2 SCHEMA THEORY 275 15.3 COGNITIVE BIASES 276 15.4 SYSTEMS FAILURES 279 15.5 COGNITIVE DEBIASING 285 15.6 BIBLIOGRAPHY 288 CHAPTER 16: DELIVERING VALUE AND RESOLVING CONFLICTS 289 16.1 INTRODUCTION 289 16.2 DELIVERING SYSTEMS VALUE 289 16.3 CONFLICT ANALYSIS AND RESOLUTION 294 16.4 BIBLIOGRAPHY 299 CHAPTER 17: MULTI-OBJECTIVE MULTI-AGENT DECISION MAKING 300 17.1 INTRODUCTION 300 17.2 UTILITY-BASED REWARDS 300 17.3 REPRESENTATION OF THE DECISION PROCESS 301 17.4 KEY TYPES OF DECISION PROCESSES 302 17.5 EXAMPLE-1 - WOLVES AND SHEEP PREDATION 305 17.6 EXAMPLE-2 - COOPERATIVE TARGET OBSERVATION 308 17.7 EXAMPLE-3 - SEAPORT LOGISTICS 310 17.8 BIBLIOGRAPHY 313 CHAPTER 18: SYSTEMS ENGINEERING USING CATEGORY THEORY 315 18.1 INTRODUCTION 315 18.2 THE PROBLEM OF MULTIDISCIPLINARY, COLLABORATIVE DESIGN 315 18.3 BRIEF BACKGROUND ON CATEGORY THEORY AND SYSTEMS ENGINEERING 316 18.4 EXAMPLE - DESIGNING AN ELECTRIC VEHICLE 317 18.5 CATEGORY THEORY (CT) AS A SYSTEM SPECIFICATION LANGUAGE 322 18.6 CATEGORICAL MULTIDISCIPLINARY COLLABORATIVE DESIGN (C-MCD) 329 18.7 THE C-MCD CATEGORIES 331 18.8 THE CATEGORICAL DESIGN PROCESS 339 18.9 CONCLUSION 340 18.10 ACKNOWLEDGMENT 340 18.11 BIBLIOGRAPHY 340 CHAPTER 19: HOLISTIC RISK MANAGEMENT USING SOSF METHODOLOGY 342 19.1 INTRODUCTION 342 19.2 LIMITATIONS OF CURRENT RISK MANAGEMENT PRACTICES 342 19.3 FEATURES OF SYSTEMS OF SYSTEMS FAILURES (SOSF) 343 19.4 EXAMPLE-1 - HOLISTIC RISK MANAGEMENT AND FAILURE CLASSES 347 19.5 EXAMPLE-2 – SYNTHETIC SOSF RISK MANAGEMENT 354 19.6 CONCLUSION 358 19.7 ACKNOWLEDGMENT 358 19.8 BIBLIOGRAPHY 358 CHAPTER 20: SYSTEMIC ACCIDENTS AND MISHAPS ANALYSES 360 20.1 INTRODUCTION TO ACCIDENT CAUSATION MODELS 360 20.2 BASIC ACCIDENTS AND MISHAPS CONCEPTS 360 20.3 CLASSIFICATION OF INCIDENT CAUSATION MODELS 361 20.4 SYSTEMS THEORETIC ACCIDENT MODEL AND PROCESS (STAMP) 362 20.5 CAUSAL ANALYSIS SYSTEM THEORY (CAST) 365 20.6 CAST PROCEDURE 366 20.7 CAST EXAMPLE - CH-53 HELICOPTERS MID-AIR COLLISION 367 20.8 BIBLIOGRAPHY 374 APPENDIX-A: DISTINGUISHED SYSTEMS SCIENCE RESEARCHERS 376 APPENDIX-B: DISTINGUISHED SYSTEMS THINKING RESEARCHERS 378 APPENDIX-C: PERMISSIONS TO USE THIRD-PARTY COPYRIGHT MATERIAL 380 APPENDIX-D: LIST OF ACRONYMS 392 INDEX 398
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Book SynopsisMachine Learning Theory and Applications Enables readers to understand mathematical concepts behind data engineering and machine learning algorithms and apply them using open-source Python libraries Machine Learning Theory and Applications delves into the realm of machine learning and deep learning, exploring their practical applications by comprehending mathematical concepts and implementing them in real-world scenarios using Python and renowned open-source libraries. This comprehensive guide covers a wide range of topics, including data preparation, feature engineering techniques, commonly utilized machine learning algorithms like support vector machines and neural networks, as well as generative AI and foundation models. To facilitate the creation of machine learning pipelines, a dedicated open-source framework named hephAIstos has been developed exclusively for this book. 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Categorical Data 77 2.3 Time-Related Features Engineering 77 2.3.1 Date-Related Features 79 2.3.2 Lag Variables 79 2.3.3 Rolling Window Feature 82 2.3.4 Expending Window Feature 84 2.3.5 Understanding Time Series Data in Context 85 2.4 Handling Missing Values in Machine Learning 88 2.4.1 Row or Column Removal 89 2.4.2 Statistical Imputation: Mean, Median, and Mode 90 2.4.3 Linear Interpolation 91 2.4.4 Multivariate Imputation by Chained Equation Imputation 92 2.4.5 KNN Imputation 93 2.5 Feature Extraction and Selection 97 2.5.1 Feature Extraction 97 2.5.1.1 Principal Component Analysis 98 2.5.1.2 Independent Component Analysis 102 2.5.1.3 Linear Discriminant Analysis 110 2.5.1.4 Locally Linear Embedding 115 2.5.1.5 The t-Distributed Stochastic Neighbor Embedding Technique 123 2.5.1.6 More Manifold Learning Techniques 125 2.5.1.7 Feature Extraction with HephAIstos 130 2.5.2 Feature Selection 131 2.5.2.1 Filter Methods 132 2.5.2.2 Wrapper Methods 146 2.5.2.3 Embedded Methods 154 2.5.2.4 Feature Importance Using Graphics Processing Units (GPUs) 167 2.5.2.5 Feature Selection Using HephAIstos 168 Further Reading 170 3 Machine Learning Algorithms 175 3.1 Linear Regression 176 3.1.1 The Math 176 3.1.2 Gradient Descent to Optimize the Cost Function 177 3.1.3 Implementation of Linear Regression 182 3.1.3.1 Univariate Linear Regression 182 3.1.3.2 Multiple Linear Regression: Predicting Water Temperature 185 3.2 Logistic Regression 202 3.2.1 Binary Logistic Regression 202 3.2.1.1 Cost Function 203 3.2.1.2 Gradient Descent 204 3.2.2 Multinomial Logistic Regression 204 3.2.3 Multinomial Logistic Regression Applied to Fashion MNIST 204 3.2.3.1 Logistic Regression with scikit-learn 205 3.2.3.2 Logistic Regression with Keras on TensorFlow 208 3.2.4 Binary Logistic Regression with Keras on TensorFlow 210 3.3 Support Vector Machine 211 3.3.1 Linearly Separable Data 212 3.3.2 Not Fully Linearly Separable Data 214 3.3.3 Nonlinear SVMs 216 3.3.4 SVMs for Regression 217 3.3.5 Application of SVMs 219 3.3.5.1 SVM Using scikit-learn for Classification 220 3.3.5.2 SVM Using scikit-learn for Regression 222 3.4 Artificial Neural Networks 223 3.4.1 Multilayer Perceptron 224 3.4.2 Estimation of the Parameters 225 3.4.2.1 Loss Functions 225 3.4.2.2 Backpropagation: Binary Classification 226 3.4.2.3 Backpropagation: Multi-class Classification 227 3.4.3 Convolutional Neural Networks 230 3.4.4 Recurrent Neural Network 232 3.4.5 Application of MLP Neural Networks 233 3.4.6 Application of RNNs: LST Memory 242 3.4.7 Building a CNN 246 3.5 Many More Algorithms to Explore 249 3.6 Unsupervised Machine Learning Algorithms 251 3.6.1 Clustering 251 3.6.1.1 K-means 253 3.6.1.2 Mini-batch K-means 255 3.6.1.3 Mean Shift 257 3.6.1.4 Affinity Propagation 259 3.6.1.5 Density-based Spatial Clustering of Applications with Noise 262 3.7 Machine Learning Algorithms with HephAIstos 264 References 270 Further Reading 270 4 Natural Language Processing 273 4.1 Classifying Messages as Spam or Ham 274 4.2 Sentiment Analysis 281 4.3 Bidirectional Encoder Representations from Transformers 286 4.4 BERT’s Functionality 287 4.5 Installing and Training BERT for Binary Text Classification Using TensorFlow 288 4.6 Utilizing BERT for Text Summarization 294 4.7 Utilizing BERT for Question Answering 296 Further Reading 297 5 Machine Learning Algorithms in Quantum Computing 299 5.1 Quantum Machine Learning 303 5.2 Quantum Kernel Machine Learning 306 5.3 Quantum Kernel Training 328 5.4 Pegasos QSVC: Binary Classification 333 5.5 Quantum Neural Networks 337 5.5.1 Binary Classification with EstimatorQNN 338 5.5.2 Classification with a SamplerQNN 343 5.5.3 Classification with Variational Quantum Classifier 348 5.5.4 Regression 351 5.6 Quantum Generative Adversarial Network 352 5.7 Quantum Algorithms with HephAIstos 368 References 372 Further Reading 373 6 Machine Learning in Production 375 6.1 Why Use Docker Containers for Machine Learning? 375 6.1.1 First Things First: The Microservices 375 6.1.2 Containerization 376 6.1.3 Docker and Machine Learning: Resolving the “It Works in My Machine” Problem 376 6.1.4 Quick Install and First Use of Docker 377 6.1.4.1 Install Docker 377 6.1.4.2 Using Docker from the Command Line 378 6.1.5 Dockerfile 380 6.1.6 Build and Run a Docker Container for Your Machine Learning Model 381 6.2 Machine Learning Prediction in Real Time Using Docker and Python REST APIs with Flask 389 6.2.1 Flask-RESTful APIs 390 6.2.2 Machine Learning Models 392 6.2.3 Docker Image for the Online Inference 393 6.2.4 Running Docker Online Inference 394 6.3 From DevOps to MLOPS: Integrate Machine Learning Models Using Jenkins and Docker 396 6.3.1 Jenkins Installation 397 6.3.2 Scenario Implementation 399 6.4 Machine Learning with Docker and Kubernetes: Install a Cluster from Scratch 405 6.4.1 Kubernetes Vocabulary 405 6.4.2 Kubernetes Quick Install 406 6.4.3 Install a Kubernetes Cluster 407 6.4.4 Kubernetes: Initialization and Internal Network 410 6.5 Machine Learning with Docker and Kubernetes: Training Models 415 6.5.1 Kubernetes Jobs: Model Training and Batch Inference 415 6.5.2 Create and Prepare the Virtual Machines 415 6.5.3 Kubeadm Installation 415 6.5.4 Create a Kubernetes Cluster 416 6.5.5 Containerize our Python Application that Trains Models 418 6.5.6 Create Configuration Files for Kubernetes 422 6.5.7 Commands to Delete the Cluster 424 6.6 Machine Learning with Docker and Kubernetes: Batch Inference 424 6.6.1 Create Configuration Files for Kubernetes 427 6.7 Machine Learning Prediction in Real Time Using Docker, Python Rest APIs with Flask, and Kubernetes: Online Inference 428 6.7.1 Flask-RESTful APIs 428 6.7.2 Machine Learning Models 431 6.7.3 Docker Image for Online Inference 432 6.7.4 Running Docker Online Inference 433 6.7.5 Create and Prepare the Virtual Machines 434 6.7.6 Kubeadm Installation 434 6.7.7 Create a Kubernetes Cluster 435 6.7.8 Deploying the Containerized Machine Learning Model to Kubernetes 437 6.8 A Machine Learning 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To Build a Production-Ready ML/DL Environment 454 6.10 Deploying a Machine Learning Model as an API on the Red Hat OpenShift Container Platform: From Source Code in a GitHub Repository with Flask, Scikit-Learn, and Docker 454 6.10.1 Create an OpenShift Cluster Instance 455 6.10.1.1 Deploying an Application from Source Code in a GitHub Repository 457 Further Reading 463 Conclusion: The Future of Computing for Data Science? 465 Index 477
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