Tabla de Contenidos: “…Chapter 4 Machine Learning Integration in Agriculture Domain: Concepts and Applications -- 4.1 Introduction -- 4.2 Fog Computing in Agriculture -- 4.2.1 Smart Farming -- 4.3 Methodology -- 4.3.1 Data Source -- 4.3.2 Data Analysis and Pre-Processing -- 4.3.3 Feature Extraction -- 4.3.4 Model Selection -- 4.3.5 Hyper-Parameter Tuning -- 4.3.6 Train-Test Split -- 4.4 Results and Discussion -- 4.4.1 Modeling Algorithms -- 4.5 Conclusion -- 4.6 Future Scope -- References -- Chapter 5 Role of Intelligent IoT Applications in Fog Computing -- 5.1 Introduction -- 5.1.1 PaaS/SaaS Platforms Have Various Benefits That are Crucial to the Success of Many Small IoT Startup Businesses -- 5.2 Cloud Service Model's Drawbacks -- 5.3 Fog Computation -- 5.3.1 Standardization -- 5.3.2 Growing Use Cases for Fog Computing -- 5.3.3 IoT Applications with Intelligence -- 5.3.4 Graphics Processing Units -- 5.4 Recompenses of FoG -- 5.5 Limitation of Fog Computing -- 5.6 Fog Computing with IoT -- 5.6.1 Benefits of Fog Computing with IoT -- 5.6.2 Challenges of Fog Computing with IoT -- 5.7 Edge AI Embedded -- 5.7.1 Key Software Characteristics in Fog Computing -- 5.7.2 Fog Cluster Management -- 5.7.3 Technology for Computing in the Fog -- 5.7.4 Concentrating Intelligence -- 5.7.5 Device-Driven Intelligence -- 5.8 Network Intelligence Objectives -- 5.9 Farming with Fog Computation (Case Study) -- 5.10 Conclusion -- References -- Chapter 6 SaaS-Based Data Visualization Platform-A Study in COVID-19 Perspective -- 6.1 Introduction -- 6.1.1 Motivation and the Problem of Interest -- 6.2 Summary of Objectives -- 6.3 What is a Pandemic? …”

Tabla de Contenidos: “…MIMO Detection 209 -- 8.1 Introduction 209 -- 8.2 Linear Detection 210 -- 8.2.1 Zero Forcing (ZF) 210 -- 8.2.2 Minimum Mean Squared Error (MMSE) 211 -- 8.3 MIMO Detection with Channel Preprocessing 212 -- 8.3.1 Sorting 212 -- 8.3.2 QR Decomposition 213 -- 8.3.3 MMSE-SQRD 215 -- 8.3.4 Ordered Successive Interference Cancelation (OSIC) 216 -- 8.3.5 Lattice Reduction (LR) 218 -- 8.4 Sphere Decoder 220 -- 8.4.1 Depth-First Tree Search 221 -- 8.4.2 Breadth-First Tree Search 223 -- 8.4.3 Best-First Tree Search 224 -- 8.4.4 Complexity Measurement 227 -- 8.4.5 Design Space Exploration of Sphere Decoder 227 -- 8.5 Soft-Output Sphere Decoder 230 -- 8.5.1 Repeated Tree Search 231 -- 8.5.2 Single Tree Search 232 -- 8.5.3 LLR Clipping 232 -- 8.6 Iterative MIMO Detection 234 -- 8.6.1 List Sphere Decoder 234 -- 8.6.2 Soft-Input Soft-Output Sphere Decoder 235.…”

Tabla de Contenidos: “…Choosing a measure of success -- 4.5.3. Deciding on an evaluation protocol -- 4.5.4. …”

Tabla de Contenidos: “…1.26 True RMS-Responding Voltmeter -- 1.27 Balanced Bridge Voltmeter (VTVM) -- 1.27.1 Advantages -- 1.27.2 Disadvantages -- 1.28 Transistor Voltmeter (TVM) -- 1.29 Electronic Multimeter -- 1.29.1 Resistance Ranges -- 1.30 AC Current Measurement -- 1.30.1 Differential Voltmeter -- 1.31 Differential Amplifier -- 1.32 Alternating Current Instruments (AC Meters) -- 1.32.1 D'Arsonval Meter Movement for AC Circuit -- 1.32.2 Modified Circuit for AC Measurements -- 1.32.3 D'Arsonval Meter Movement Circuit (FWR) -- 1.33 Electrodynamometer Movement -- 1.33.1 Transfer Instruments -- 1.33.2 Iron Vane-Meter Movement -- 1.34 Thermocouple Meter -- 1.34.1 Constant Voltage Source -- 1.34.2 Constant Current Source -- 1.34.3 Volt Box -- 1.34.4 Factors to be Considered in the Selection of an Analog Voltmeter -- 1.35 Digital Voltmeters -- 1.35.1 General Specifications -- 1.36 Ramp-Type DVM -- 1.37 Staircase Ramp-Type DVM -- 1.38 Dual Slope Integrating-Type DVM -- 1.39 Successive-Approximation Conversion (SAC) -- 1.39.1 Block Schematic -- 1.40 Continuous Balance-Type DVM -- 1.41 Automatic Polarity Indication for DVM -- 1.42 Autoranging for DVM -- 1.42.1 Typical Case -- 1.43 3 3 4 Digit Display -- 1.44 Picoammeter -- 1.44.1 Applications -- 1.45 Low-Current Ammeter Applications -- 1.45.1 Wafer-Level Photodiode Testing -- 1.45.2 Monitoring and Control of Focused Ion Beam Currents -- 1.46 High-Resistance Measurements -- 1.47 Summary -- Points to Remember -- Objective-type Questions -- Review Questions -- Unsolved Problems -- Chapter 2: Waveform Generators -- 2.1 Introduction -- 2.2 Considerations in Choosing an Oscillator or Signal Generator -- 2.3 Sine Wave Generator -- 2.4 Oscillator Circuit -- 2.5 Attenuator -- 2.6 Frequency-Synthesised Signal Generator -- 2.7 Sweep-Frequency Generator -- 2.8 Pulse and Square Wave Generator -- 2.9 Function Generator…”

Tabla de Contenidos: “…Administration tools -- 11.1 Administrative tools for the developer -- 11.2 Starting the tools -- 11.2.1 Starting Interchange Server Express -- 11.2.2 Starting System Manager -- 11.2.3 Starting the Flow manager -- 11.2.4 Setting up to run the Web-based tools -- 11.2.5 Starting ICSMonitor -- 11.2.6 Starting Failed Event Manager -- 11.3 Logging and tracing -- 11.3.1 Configuring logging and tracing -- 11.3.2 Generating sample tracing -- 11.3.3 Viewing the tracing information -- 11.3.4 Using the Log Viewer to look at trace -- 11.4 Debugging collaborations -- 11.4.1 Debugging a success flow -- 11.4.2 Debugging a failure flow -- 11.4.3 Finished debugging -- 11.5 Managing failed events -- 11.5.1 Using Flow manager -- 11.5.2 Using the Failed Event Manager -- 11.5.3 Failed event actions -- 11.6 Using statistics for system interrogation -- 11.6.1 Connector statistics -- 11.6.2 Collaboration statistics -- 11.7 Starting and stopping components -- 11.7.1 Controlling components from System Manager -- 11.7.2 Controlling components from ICSMonitor -- Part 3 Developing an integration sample -- Chapter 12. …”

Tabla de Contenidos: “…Enterprise Identity Mapping -- 6.1 EIM overview -- 6.1.1 The problem of managing multiple user registries -- 6.1.2 Current approaches -- 6.1.3 The EIM approach -- 6.2 Benefits of single signon -- 6.2.1 Benefits for users -- 6.2.2 Benefits for administrators -- 6.2.3 Benefits for application developers -- 6.3 EIM components -- 6.3.1 EIM domain controller -- 6.3.2 EIM domain -- 6.3.3 EIM identifiers -- 6.3.4 EIM registry definitions -- 6.3.5 EIM associations -- 6.3.6 EIM lookup operations -- 6.3.7 EIM authorities -- 6.3.8 Setting Up EIM Authorities -- 6.4 APIs available to work with the EIM environment -- 6.5 Three steps to success -- 6.5.1 Collection -- 6.5.2 Collation -- 6.5.3 Population…”

Tabla de Contenidos: “…10.4.1 mmWave Analog Beamforming -- 10.4.2 Hybrid Beamforming in mmWave -- 10.4.3 Multi-Beamforming -- 10.5 Simulation Results -- 10.6 Deployment and Practical Issues for Smart City -- 10.6.1 Application of Pairing Greater than Three Users -- 10.6.2 Successive Interference Cancelation (SIC) -- 10.6.3 User Mobility -- 10.6.4 Channel State Information -- 10.6.5 Multiple-Cell NOMA -- 10.7 Conclusion -- References -- Chapter 11 Traditional and Modern Techniques for Visible Light Positioning Systems -- 11.1 Introduction: An Overview of Visible Light Positioning Techniques -- 11.2 Localization Process and Operational Framework -- 11.3 Traditional Methods for Positioning -- 11.3.1 Angle of Arrival (AoA) -- 11.3.2 Time of Arrival (ToA) -- 11.3.3 Time Difference of Arrival (TDoA) -- 11.3.4 Received Signal Strength (RSS) -- 11.4 Positioning Algorithms - An Overview -- 11.4.1 Mathematical Method: -- 11.4.2 Sensor-Assisted Method -- 11.4.3 Optimization Method -- 11.5 Review of Machine Learning and Artificial Intelligence -- 11.5.1 Supervised Learning -- 11.5.2 Unsupervised Learning -- 11.5.3 Semi-Supervised Learning -- 11.5.4 Reinforcement Learning -- 11.5.5 Deep Learning -- 11.5.5.1 Dense Neural Networking (DNN) -- 11.5.5.2 Convolutional Neural Networking (CNN) -- 11.5.5.3 Recurrent Neural Networking (RNN) -- 11.5.6 Auto-Encoders -- 11.5.7 Extreme Learning Machine -- 11.6 Machine Learning and Artificial Intelligence-Based Positioning Algorithms -- 11.6.1 Indoor Localization with Supervised Learning Approaches -- 11.6.2 Indoor Localization with the Deep Learning Approaches -- 11.6.3 Indoor Localization with Unsupervised Learning Approaches -- 11.7 Comparison of Machine Learning-Based Positioning Algorithms -- 11.8 Conclusion and Future Work -- References -- Index…”

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