Tabla de Contenidos: “…Chapter 5 Genetically Optimized Computer-Aided Diagnosis for Detection and Classification of COVID-19 -- 5.1 Introduction -- 5.2 Related Works -- 5.3 Problem Definition -- 5.4 Proposed Methodology -- 5.4.1 Data Acquisition -- 5.4.2 Preprocessing -- 5.4.3 Segmentation Using Optimized Region Growing -- 5.4.4 Feature Extraction and Feature Selection -- 5.4.5 Two Stage Classification Using Genetically Optimized ANN Classification -- 5.4.5.1 Stage 1 Classification -- 5.4.5.2 Stage 2 Classification -- 5.5 Performance Analysis of the Proposed Methodology -- 5.5.1 Parameter Settings and Experimental Setup -- 5.5.2 Segmentation Performance of Proposed Methodology -- 5.5.3 Classification Performance of the Proposed Approach -- 5.6 Conclusion -- References -- Chapter 6 Micro-Expression Recognition Using 3D-CNN Layering -- 6.1 Introduction -- 6.2 Literature Review -- 6.2.1 Hand-Designed (Manual) Techniques -- 6.2.2 Learning-Based (Dynamic) Techniques -- 6.3 Micro-Expressions Datasets -- 6.3.1 Non-Spontaneous Dataset -- 6.3.1.1 Polikovsky Dataset -- 6.3.1.2 USF-HD -- 6.3.1.3 York DDT -- 6.3.2 Spontaneous Datasets -- 6.3.2.1 CASME -- 6.3.2.2 SMIC -- 6.3.2.3 CASME II -- 6.3.2.4 SAMM Dataset -- 6.3.2.5 CAS(ME)2 -- 6.4 Proposed CNN Models -- 6.4.1 Primary CNN -- 6.4.2 Secondary CNN -- 6.5 Experimental Results and Discussions -- 6.5.1 Experimental Results -- 6.5.2 Accuracy Standard Deviation Analysis -- 6.5.3 Effect of 3D Kernel -- 6.5.4 Impact of Facial Features -- 6.6 Conclusion -- References -- Chapter 7 Applications of AI, IoT, IoMT, and Biosensing Devices in Curbing COVID-19 -- 7.1 Introduction -- 7.1.1 Clinical Properties -- 7.1.2 Mode of Transmission -- 7.2 Related Work -- 7.2.1 History of Similar Pandemics -- 7.2.2 Viruses of the Respiratory Tract -- 7.3 COVID-19 Diagnosis -- 7.4 Treatment -- 7.5 Prevention…”

Tabla de Contenidos: “…Les services échangeables et l'extraction de ressources contribuent au rattrapage -- Graphique 1.13. …”

Tabla de Contenidos: “…Implementation -- 4.5.1. Feature Extraction -- 4.5.2. Dimensionality Reduction -- 4.5.3. …”

Tabla de Contenidos: “…17.3 Effects and Negative Consequences of Harmonics 535 -- 17.4 International Standards for Harmonics 536 -- 17.5 Types of Harmonics 537 -- 17.5.1 Harmonic Current Sources 537 -- 17.5.2 Harmonic Voltage Sources 537 -- 17.6 Passive Filters 539 -- 17.7 Power Definitions 540 -- 17.8 Active Power Filters 543 -- 17.9 APF Switching Frequency Choice Methodology 547 -- 17.10 Harmonic Current Extraction Techniques (HCET) 548 -- 17.11 Shunt Active Power Filter 555 -- 17.12 Series Active Power Filter 564 -- 17.13 Unified Power Quality Conditioner 565 -- Acknowledgment 569 -- References 569 -- 18A Hardware-in-the-Loop Systems with Power Electronics: A Powerful Simulation Tool 573 -- 18A.1 Background 573 -- 18A.2 Increasing the Performance of the Power Stage 575 -- 18A.3 Machine Model of an Asynchronous Machine 581 -- 18A.4 Results and Conclusions 583 -- References 589 -- 18B Real-Time Simulation of Modular Multilevel Converters (MMCs) 591 -- 18B.1 Introduction 591 -- 18B.2 Choice of Modeling for MMC and Its Limitations 597 -- 18B.3 Hardware Technology for Real-Time Simulation 598 -- 18B.4 Implementation for Real-Time Simulator Using Different Approach 601 -- 18B.5 Conclusion 606 -- References 606 -- 19 Model Predictive Speed Control of Electrical Machines 608 -- 19.1 Introduction 608 -- 19.2 Review of Classical Speed Control Schemes for Electrical Machines 609 -- 19.3 Predictive Current Control 613 -- 19.4 Predictive Torque Control 617 -- 19.5 Predictive Torque Control Using a Direct Matrix Converter 619 -- 19.6 Predictive Speed Control 622 -- 19.7 Conclusions 626 -- Acknowledgment 627 -- References 627 -- 20 The Electrical Drive Systems with the Current Source Converter 630 -- 20.1 Introduction 630 -- 20.2 The Drive System Structure 631 -- 20.3 The PWM in CSCs 633 -- 20.4 The Generalized Control of a CSR 636 -- 20.5 The Mathematical Model of an Asynchronous and a Permanent Magnet Synchronous Motor 639 -- 20.6 The Current and Voltage Control of an Induction Machine 641 -- 20.7 The Current and Voltage Control of Permanent Magnet Synchronous Motor 651.…”

Tabla de Contenidos: “…3.5.3 The barbershop problem: introducing fairness -- 3.5.4 Readers-writers -- 3.5.4.1 A solution favoring the readers -- 3.5.4.2 Giving priority to the writers -- 3.5.4.3 A fair solution -- 3.6 Monitors -- 3.6.1 Design approach 1: critical section inside the monitor -- 3.6.2 Design approach 2: monitor controls entry to critical section -- 3.7 Applying monitors in classical problems -- 3.7.1 Producers-consumers revisited -- 3.7.1.1 Producers-consumers: buffer manipulation within the monitor -- 3.7.1.2 Producers-consumers: buffer insertion/extraction exterior to the monitor -- 3.7.2 Readers-writers -- 3.7.2.1 A solution favoring the readers -- 3.7.2.2 Giving priority to the writers -- 3.7.2.3 A fair solution -- 3.8 Dynamic vs. static thread management -- 3.8.1 Qt's thread pool -- 3.8.2 Creating and managing a pool of threads -- 3.9 Debugging multithreaded applications -- 3.10 Higher-level constructs: multithreaded programming without threads -- 3.10.1 Concurrent map -- 3.10.2 Map-reduce -- 3.10.3 Concurrent filter -- 3.10.4 Filter-reduce -- 3.10.5 A case study: multithreaded sorting -- 3.10.6 A case study: multithreaded image matching -- Exercises -- Chapter 4: Shared-memory programming: OpenMP -- 4.1 Introduction -- 4.2 Your First OpenMP Program -- 4.3 Variable Scope -- 4.3.1 OpenMP Integration V.0: Manual Partitioning -- 4.3.2 OpenMP Integration V.1: Manual Partitioning Without a Race Condition -- 4.3.3 OpenMP Integration V.2: Implicit Partitioning with Locking -- 4.3.4 OpenMP Integration V.3: Implicit Partitioning with Reduction -- 4.3.5 Final Words on Variable Scope -- 4.4 Loop-Level Parallelism -- 4.4.1 Data Dependencies -- 4.4.1.1 Flow Dependencies -- 4.4.1.2 Antidependencies -- 4.4.1.3 Output Dependencies -- 4.4.2 Nested Loops -- 4.4.3 Scheduling -- 4.5 Task Parallelism -- 4.5.1 The sections Directive -- 4.5.1.1 Producers-Consumers in OpenMP…”

Tabla de Contenidos: “…Chapter 9 Generation-Z Student Video-Based Learning Pedagogy Preference and Teaching Challenges -- 9.1 Introduction -- 9.1.1 Purpose of the Chapter -- 9.2 Generation Z Behavioral Feature -- 9.3 Video-Based Learning Motives (VBLM) -- 9.4 Video-Based Learning Platform -- 9.5 Teachers Role Transformation -- 9.6 Conclusion -- 9.7 Limitation and Further Research Scope -- References -- Chapter 10 Quantitative Monitoring and Analysis of Rare Symptoms of COVID-19 Infection: Application of a Text and Citation Management Software as a Tool -- 10.1 Introduction: The COVID Pandemic -- 10.2 Materials and Methods -- 10.2.1 REVMAN Software -- 10.2.2 Data Input Pane -- 10.2.3 Systematic Application of REVMAN on COVID 19 Rare Symptoms -- 10.2.4 Database Scrutiny -- 10.2.5 Combining BOOLEAN and MeSH Terms for Optimizing the Application Software -- 10.2.6 Secondary Data on Rare Symptoms of COVID-19 -- 10.2.7 Data Extraction -- 10.2.8 Systematic Analysis -- 10.2.9 Statistical Analysis -- 10.3 Results and Discussion -- 10.4 Conclusion -- References -- Chapter 11 Role and Impact of ICT on Rapidly Advancing New Age Teaching Pedagogy in Higher Educational Institutions in Oman -- 11.1 Introduction -- 11.1.1 Evolution of ICT in the Field of Higher Education in Oman -- 11.1.2 ICT Tools Used for Teaching -- 11.2 ICT Methodologies Adopted for Teaching -- 11.3 Gaps Between Deliverables and Delivered -- 11.3.1 Types of Gaps -- 11.3.2 Product/Market Gap -- 11.3.3 Performance Gap -- 11.3.4 Manpower Gap -- 11.4 Causes of the Technological Gaps -- 11.5 Ways to Fill in the Gaps -- 11.5.1 SWOT Analysis -- 11.5.2 Fishbone - Cause and Effect Analysis of ICT in Education -- 11.5.2.1 Language Barriers -- 11.5.2.2 Ease of Access -- 11.5.2.3 Privacy -- 11.5.2.4 Technology -- 11.5.3 McKinsey 7S Model -- 11.6 ICT Training -- 11.7 Importance of ICT Training in the Field of Education…”

Tabla de Contenidos: “…References -- 8 Cybersecurity using artificial intelligence -- 8.1 Introduction -- 8.1.1 Background -- 8.2 Problems with strategy -- 8.2.1 Technical challenges -- 8.2.2 Some nontechnical challenges -- 8.2.3 Some nontechnical challenges -- 8.2.4 Needs to make a good trade-off -- 8.3 Assessment -- 8.4 Conclusions -- References -- Further reading -- 9 Transformers in wildfire detection -- 9.1 Introduction -- 9.1.1 Related works -- 9.1.1.1 Transformers applications -- 9.1.1.1.1 Self-attention for object detection -- 9.1.1.1.2 Self-attention for visual representations -- 9.1.1.1.3 Pretraining and self-training -- 9.1.1.2 Machine learning classification -- 9.2 Methodology -- 9.2.1 Study design -- 9.2.2 The model -- 9.2.3 Feature extraction -- 9.2.4 Feature selection -- 9.2.5 Data acquisition -- 9.2.5.1 Encoder-decoder -- 9.2.6 Method -- 9.2.7 Detection transformer architecture -- 9.3 Results -- 9.4 Conclusion -- References -- 10 Distributed mobile cloud computing services and the internet of things -- 10.1 Introduction -- 10.1.1 Motivation -- 10.1.2 Objectives -- 10.1.3 Scope and organization -- 10.2 Amount of previously published work -- 10.2.1 Internet of Things research -- 10.2.2 Distributed mobile cloud computing research -- 10.2.3 Overall assessment -- 10.3 Internet of things and distributed mobile cloud computing services -- 10.3.1 Experimental setup -- 10.3.1.1 Hardware components -- 10.3.1.2 Software components -- 10.3.1.3 Network infrastructure -- 10.4 Distributed mobile cloud computing and the internet of things -- 10.4.1 Literature review -- 10.4.2 Experimental design -- 10.4.3 Implementation -- 10.4.4 Data collection and analysis -- 10.4.5 Discussion -- 10.5 Results and discussion follow -- 10.5.1 Performance evaluation metrics -- 10.5.1.1 Latency -- 10.5.1.2 Energy consumption -- 10.5.1.3 Computational speed -- 10.5.1.4 Data transfer rate…”

Tabla de Contenidos: “…4.5.3.3 Per Cent variation in capacitance -- 4.5.3.4 Per Cent variation in coupling capacitance -- 4.5.4 Compact Conductance Model of a Three-Dimensional Via -- 4.5.4.1 Compact models of through silicon via conductance -- 4.6 Electrical Characterization Through Numerical Simulation -- 4.6.1 Ansys Quick Three-Dimensional Electromagnetic Field Solver -- 4.6.2 Numerical Analysis of Through Silicon Via Impedance -- 4.7 Case Study-Through Silicon Via Characterization of the MITLL TSV process -- 4.7.1 MIT Lincoln Laboratory Three-Dimensional Process -- 4.7.2 RLC Extraction of a Single Three-Dimensional Via -- 4.7.3 RLC Coupling Between Two Three-Dimensional Vias -- 4.7.4 Effects of Three-Dimensional Via Placement on Shielding -- 4.7.5 Effect of the Return Path on Three-Dimensional Via Inductance -- 4.8 Summary -- 5 Substrate Noise Coupling in Heterogeneous Three-Dimensional ICs -- 5.1 Heterogeneous Substrate Coupling -- 5.1.1 Common Circuits and Compatible Substrate Types -- 5.1.2 Resistive Properties of Different Substrate Materials -- 5.1.3 Noise Model Reduction for Different Substrate Materials -- 5.2 Frequency Response -- 5.2.1 Isolation Efficiency of Noise Coupled System -- 5.2.2 Transfer Function of Noise Coupled System -- 5.3 Techniques to Improve Noise Isolation -- 5.3.1 Ground Network Inductance -- 5.3.2 Distance Between Aggressor and Victim -- 5.4 Summary -- 6 Three-Dimensional ICs with Inductive Links -- 6.1 Wireless On-Chip Communication Interfaces -- 6.1.1 Inductive Links -- 6.2 On-Chip Inductors for Intertier Links -- 6.2.1 Intertier Coupling Efficiency -- 6.2.2 Geometry and Electrical Characteristics of Inductor -- 6.2.3 Design Flow for Inductive Link Coils -- 6.3 Transmitter and Receiver Circuits -- 6.3.1 Design of Synchronous Inductive Link Transceivers -- 6.3.2 Asynchronous Data Transmission and Recovery -- 6.3.3 Burst Data Transmission…”

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: “…Optimally weighted majority voting -- 3.3. Feature extraction -- 3.4. Layer modification -- 4. Experimental setup -- 4.1. …”

Tabla de Contenidos: “…10.3 Pre-defined Streams -- 10.4 Buffering -- 10.5 Stream Classes -- 10.6 Formatted and Unformatted Data -- 10.7 Input/Output using Extraction (&gt -- &gt -- ) and Insertion (&lt -- &lt -- ) Operators -- 10.7.1 Input and Output Streams -- 10.8 Writing Simple C++ Programs with/without Comments -- 10.9 Typecasting with cout Statement -- 10.10 Formatted Console I/O Operations -- Summary -- Exercises -- Chapter 11: Control Structures -- 11.1 Introduction -- 11.2 Decision-making Statements -- 11.3 The if-else Statement -- 11.4 The Nested if-else Statement -- 11.5 The goto Statement -- 11.6 The break Statement -- 11.7 The continue Statement -- 11.8 The switch case Statement -- 11.9 The Nested switch case Statement -- 11.10 Loops in C/C++ -- 11.11 The for Loop -- 11.12 Nested for Loops -- 11.13 The while Loop -- 11.14 The do-while Loop -- Summary -- Exercises -- Chapter 12: Functions in C++ -- 12.1 Introduction -- 12.2 The main () Function in C and C++ -- 12.3 Structure of a Function -- 12.3.1 Function Prototypes -- 12.3.2 Function Definition -- 12.3.3 Function Call -- 12.3.4 Actual and Formal Arguments -- 12.3.5 The return Statement -- 12.4 Passing Arguments -- 12.4.1 Pass by Value -- 12.4.2 Pass by Address -- 12.4.3 Passing by Reference -- 12.5 Return by Reference -- 12.6 Returning More Values by Reference -- 12.7 Default Arguments -- 12.8 The const Argument -- 12.9 Inputting Default Arguments -- 12.10 Inline Functions -- 12.11 Function Overloading -- 12.12 Library Functions -- 12.13 Recursion -- 12.14 Storage Class -- Summary -- Exercises -- Chapter 13: Arrays -- 13.1 Introduction -- 13.2 Array Declaration and Initialization -- 13.3 Characteristics of Arrays -- 13.4 Initialization of Arrays using Functions -- 13.5 Arrays of Classes -- 13.6 Passing Array Elements as Arguments to a Function -- 13.6.1 Call by Value -- 13.6.2 Call by Reference…”

Tabla de Contenidos: “…7.4 Efficiently building the bookings grid with useMemo -- 7.4.1 Generating a grid of sessions and dates -- 7.4.2 Generating a lookup for bookings -- 7.4.3 Providing a getBookings data-loading function -- 7.4.4 Creating the BookingsGrid component and calling useMemo -- 7.4.5 Coping with racing responses when fetching data in useEffect -- Summary -- 8 Managing state with the Context API -- 8.1 Needing state from higher up the component tree -- 8.1.1 Displaying a call-to-action message when the page first loads -- 8.1.2 Displaying booking information when a visitor selects a booking -- 8.1.3 Displaying an edit button for a user's bookings: The problem -- 8.1.4 Displaying an edit button for a user's bookings: The solution -- 8.2 Working with custom providers and multiple contexts -- 8.2.1 Setting an object as the context provider's value -- 8.2.2 Moving the state to a custom provider -- 8.2.3 Working with multiple contexts -- 8.2.4 Specifying a default value for a context -- Summary -- 9 Creating your own hooks -- 9.1 Extracting functionality into custom hooks -- 9.1.1 Recognizing functionality that could be shared -- 9.1.2 Defining custom hooks outside your components -- 9.1.3 Calling custom hooks from custom hooks -- 9.2 Following the Rules of Hooks -- 9.2.1 Call hooks only at the top level -- 9.2.2 Call hooks only from React functions -- 9.2.3 Using an ESLint plugin for the rules of hooks -- 9.3 Extracting further examples of custom hooks -- 9.3.1 Accessing window dimensions with a useWindowSize hook -- 9.3.2 Getting and setting values with a useLocalStorage hook -- 9.4 Consuming a context value with a custom hook -- 9.5 Encapsulating data fetching with a custom hook -- 9.5.1 Creating the useFetch hook -- 9.5.2 Using the data, status, and error values the useFetch hook returns -- 9.5.3 Creating a more specialized data-fetching hook: useBookings…”

Tabla de Contenidos: “…Front Cover -- Magnetic Fusion Energy -- Related titles -- Magnetic Fusion Energy -- Copyright -- Contents -- List of contributors -- Woodhead Publishing Series in Energy -- One - Magnetic fusion issues -- 1 - Introduction: the journey to magnetic fusion energy -- 2 - Plasma performance, burn and sustainment -- 2.1 Introduction -- 2.2 Key fusion plasma physics areas related to performance, burn and sustainment -- 2.3 Requirements for a fusion reactor -- 2.4 The present status of physics research and future prospects -- 2.4.1 Transport -- 2.4.2 Stability -- 2.4.3 α-Heating -- 2.4.4 Tokamak operational scenarios -- 2.5 Summary and outlook -- References -- 3 - Plasma exhaust -- 3.1 Introduction -- 3.2 Plasma exhaust -- 3.2.1 Particle exhaust -- 3.2.2 Power exhaust -- 3.2.3 Momentum exhaust -- 3.3 Transients and 3D effects on plasma exhaust -- 3.3.1 Edge localized modes -- 3.3.2 Disruptions and 3D asymmetries -- 3.4 PMI and materials options -- 3.4.1 PMI at the wall, and cross-field transport -- 3.4.2 Considerations for plasma facing materials -- 3.4.2.1 Solids -- 3.4.2.2 Liquids -- 3.5 Recent challenges -- 3.5.1 Energy confinement with a metal wall -- 3.5.2 Contraction of the divertor heat exhaust channel with poloidal field -- 3.6 Outlook and summary -- References -- 4 - Power extraction and tritium self-sufficiency -- 4.1 Introduction -- 4.2 Power extraction -- 4.2.1 Heating of plasma facing components -- 4.2.2 Primary heat transfer system -- 4.2.3 Balance of plant -- 4.3 Tritium production -- References -- Two - Experiments: scientific foundations for ITER -- 5 - ASDEX Upgrade -- 5.1 Introduction -- 5.2 The ASDEX Upgrade device -- 5.3 Plasma wall interaction -- 5.3.1 Tungsten plasma-facing components for ASDEX Upgrade -- 5.3.2 Retention of gases with tungsten PFCs -- 5.3.3 Tungsten sources and transport -- 5.4 Pedestal and H-mode physics…”

Tabla de Contenidos: “…Multiple Anti-Virus Scanning -- 3.1 Scanning the Suspect Binary with VirusTotal -- 3.2 Querying Hash Values Using VirusTotal Public API -- 4. Extracting Strings -- 4.1 String Extraction Using Tools -- 4.2 Decoding Obfuscated Strings Using FLOSS -- 5. …”

Tabla de Contenidos: “…. -- 6.1 Introduction -- 6.2 Related works -- 6.3 Proposed model -- 6.3.1 Tokenization -- 6.3.2 Stop words removal -- 6.3.3 Normalization -- 6.3.4 Feature extraction -- 6.3.4.1 CountVectorizer -- 6.3.4.2 Term frequency and inverse document frequency -- 6.3.4.3 Word2vec -- 6.3.4.4 Improved adaptive synthetic sampling (ADASYN) -- 6.4 Results and discussion -- 6.5 Conclusion -- References -- 7 Emotion detection from text data using machine learning for human behavior analysis -- 7.1 Introduction -- 7.1.1 Human behavior analysis -- 7.1.1.1 Theories of emotion -- 7.1.1.1.1 Social cognitive theory -- 7.1.1.2 Theories of personality -- 7.1.1.2.1 Social identity theory -- 7.1.1.2.2 Self-determination theory -- 7.1.2 Models of emotion -- 7.1.3 Affective computing for emotion detection -- 7.1.4 Natural language processing for emotion detection -- 7.1.4.1 Applications -- 7.1.4.2 Challenges -- 7.2 Available tools and resources -- 7.2.1 Tools for emotion detection -- 7.2.2 Datasets -- 7.2.3 Feature extraction tools -- 7.3 Methods and materials -- 7.3.1 Rule-based approaches -- 7.3.1.1 Lexicon-based approach -- 7.3.1.2 Keyword-based approach -- 7.3.1.3 Regular expressions -- 7.3.2 Statistical learning -- 7.3.2.1 Machine learning-based approaches -- 7.3.2.2 Deep learning methods -- 7.3.2.3 Contextual adaptation -- 7.3.2.4 Personalized bots -- 7.3.3 Explainable AI for emotion detection -- 7.4 Outlook -- 7.4.1 Ethical considerations -- 7.4.2 Limitations of NLP in emotion detection -- 7.5 Conclusion -- References -- 8 Optimization of effectual sentiment analysis in film reviews using machine learning techniques -- 8.1 Introduction -- 8.2 Literature Survey -- 8.3 Proposed System -- 8.3.1 Hybrid algorithm Design -- 8.3.2 Solution Representation…”

Tabla de Contenidos: “…4.5.3.1 Single Cylinder Model -- 4.5.3.2 Human Body With the Arms Outstretched -- 4.5.3.3 Human Exposure to High Frequency (HF) Radiation -- References -- 5 Realistic Models for Static and Low Frequency (LF) Dosimetry -- 5.1 Parameters for Quantifying LF Exposures -- 5.2 Human Head Exposed to Electrostatic Field -- 5.2.1 Finite Element Solution -- 5.2.2 Boundary Element Solution -- 5.2.3 Computational Examples -- 5.3 Whole Body Exposed to LF Fields -- 5.3.1 Quasi-Static Formulation -- 5.3.2 Multi-Domain Model of the Human Body -- 5.3.3 Realistic Model of the Human Body - No Arms -- 5.3.4 Realistic Model of the Human Body - Arms Included -- 5.3.5 Pregnant Woman/Fetus Exposed to ELF Electric Field -- References -- 6 Realistic Models for Human Exposure to High Frequency (HF) Radiation -- 6.1 Internal Electromagnetic Field Dosimetry Methods -- 6.1.1 Surface Integral Equation Formulation -- 6.1.1.1 Numerical Solution Using Method of Moments -- 6.1.2 Tensor Volume Integral Equation -- 6.1.2.1 Numerical Solution Using Method of Moments -- 6.1.3 Hybrid Finite Element/Boundary Element Approach -- 6.1.4 The Human Eye Exposure -- 6.1.4.1 Model of the Human Eye -- 6.1.4.2 Human Eye Exposed to Plane Wave -- 6.1.4.3 Compound Versus Extracted Eye Models -- 6.1.5 The Brain Exposure -- 6.1.5.1 Model of the Human Brain -- 6.1.5.2 Human Brain Exposed to Plane Wave -- 6.1.5.3 Child Brain Exposed to Plane Wave -- 6.1.6 The Human Head Exposure -- 6.1.6.1 Brain Dosimetry Comparison -- 6.1.7 The Whole Body Exposure -- 6.2 Thermal Dosimetry Procedures -- 6.2.1 Bioheat Transfer Equation -- 6.2.1.1 Heat Conduction Equation -- 6.2.1.2 Heat Conduction Equation -- 6.2.1.3 Convective Heat Transfer -- 6.2.1.4 Pennes' Equation -- 6.2.2 Finite Element Solution -- 6.2.3 Boundary Element Solution -- 6.2.4 Computational Examples…”

Tabla de Contenidos: “…6 Attacking vulnerable database services -- 6.1 Compromising Microsoft SQL Server -- 6.1.1 MSSQL stored procedures -- 6.1.2 Enumerating MSSQL servers with Metasploit -- 6.1.3 Enabling xp_cmdshell -- 6.1.4 Running OS commands with xp_cmdshell -- 6.2 Stealing Windows account password hashes -- 6.2.1 Copying registry hives with reg.exe -- 6.2.2 Downloading registry hive copies -- 6.3 Extracting password hashes with creddump -- 6.3.1 Understanding pwdump's output -- Summary -- 7 Attacking unpatched services -- 7.1 Understanding software exploits -- 7.2 Understanding the typical exploit life cycle -- 7.3 Compromising MS17-010 with Metasploit -- 7.3.1 Verifying that the patch is missing -- 7.3.2 Using the ms17_010_psexec exploit module -- 7.4 The Meterpreter shell payload -- 7.4.1 Useful Meterpreter commands -- 7.5 Cautions about the public exploit database -- 7.5.1 Generating custom shellcode -- Summary -- Phase 3. …”

Tabla de Contenidos: “…12.3.1.5 Spying -- 12.3.2 Active Attacks -- 12.3.2.1 Denial of Service -- 12.3.2.2 Distributed Denial of Service (DDOS) -- 12.3.2.3 Message Modification -- 12.3.2.4 Masquerade -- 12.3.2.5 Trojans -- 12.3.2.6 Replay Attacks -- 12.3.3 Programming Weapons for the Attackers -- 12.3.3.1 Dormant Phase -- 12.3.3.2 Propagation Phase -- 12.3.3.3 Triggering Phase -- 12.3.3.4 Execution Phase -- 12.4 Recent Cyber Attacks -- 12.5 Drawbacks of Traditional Cryptography -- 12.5.1 Cost and Time Delay -- 12.5.2 Disclosure of Mathematical Computation -- 12.5.3 Unsalted Hashing -- 12.5.4 Attacks -- 12.6 Need of Quantum Cryptography -- 12.6.1 Quantum Mechanics -- 12.7 Evolution of Quantum Cryptography -- 12.8 Conclusion and Future Work -- References -- Chapter 13 Identification of Bacterial Diseases in Plants Using Re-Trained Transfer Learning in Quantum Computing Environment -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Proposed Methodology -- 13.3.1 SVM Classifier -- 13.3.2 Random Forest to Classify the Rice Leaf -- 13.3.2.1 Image Pre-Processing -- 13.3.2.2 Feature Extraction -- 13.3.2.3 Classification -- 13.4 Experiment Results -- Conclusion -- References -- Chapter 14 Quantum Cryptography -- 14.1 Fundamentals of Cryptography -- 14.2 Principle of Quantum Cryptography -- 14.2.1 Quantum vs. …”

Tabla de Contenidos: “…Agriculture -- 5.6. Industries extractives -- 5.7. Raffineries -- B. Marchés publics -- Notes -- Annexe 1. …”

Tabla de Contenidos: “…Configuring columns -- Merging nodes -- Applying shapes to enhance legibility -- Configuring the PivotDiagram options -- Laying the nodes out -- Overlaying linked data -- Summary -- Chapter 6: Creating Custom Master Shapes -- Modifying the ribbon -- Preparing shapes for data linking -- Making graphics respond to data value changes -- Using elapsed days to size and position shapes -- Sharing custom Templates, Stencils, and Masters -- Including in a custom template -- Delivering Templates and Stencils with SharePoint -- Creating installation packages -- Summary -- Chapter 7: Creating Custom Data Graphics -- Understanding the structure of graphic item Masters -- Knowing which Data Graphic is applied -- Reviewing a Text Callout graphic item Master -- Reviewing an Icon Set graphic item Master -- Reviewing a Data Bar graphic item Master -- Reviewing a Color by Value graphic item -- Modifying graphic items -- Modifying a Text Callout graphic item -- Changing the symbol height -- Using Text Callouts to display symbols -- Modifying an Icon Set -- Modifying a Data Bar -- Summary -- Chapter 8: Validating and Extracting Information -- Introducing validation rules -- Getting information from data diagrams -- Using Shape Reports -- Reading Shape Data -- Reading User-defined Cells -- Reading connections -- Listing connected shapes -- Listing glued shapes -- Listing routes or pathways through a diagram -- Reading containment -- Summary -- Chapter 9: Automating Structured Diagrams -- Structuring diagrams overview -- Enabling diagram services -- Setting undo scopes -- Selecting a Master shape to drop -- Dropping and linking shapes to data -- Connecting shapes from data -- Adding data-linked shapes to containers -- Adding data-linked shapes to lists -- Adding Callouts to shapes -- Summary -- Chapter 10: Sharing Data Diagrams -- Thinking about sharing…”