Tabla de Contenidos: “…Loading and preprocessing the text dataset -- Instantiating and training the model -- Building a bidirectional LSTM -- Loading and preprocessing the text dataset -- Instantiating and training the LSTM model -- Discussing GRUs and attention-based models -- GRUs and PyTorch -- Attention-based models -- Summary -- References -- Chapter 5: Advanced Hybrid Models -- Building a transformer model for language modeling -- Reviewing language modeling -- Understanding the transformer model architecture -- Defining a transformer model in PyTorch -- Loading and processing the dataset -- Training the transformer model -- Developing a RandWireNN model from scratch -- Understanding RandWireNNs -- Developing RandWireNNs using PyTorch -- Defining a training routine and loading data -- Defining the randomly wired graph -- Defining RandWireNN model modules -- Transforming a random graph into a neural network -- Training the RandWireNN model -- Evaluating and visualizing the RandWireNN model -- Summary -- References -- Chapter 6: Graph Neural Networks -- Introduction to GNNs -- Understanding the intuition behind GNNs -- Using regular NNs on graph data - a thought experiment -- Understanding the power of GNNs with computational graphs -- Types of graph learning tasks -- Understanding node-level tasks -- Understanding edge-level tasks -- Understanding graph-level tasks -- Reviewing prominent GNN models -- Understanding graph convolutions with GCNs -- Using attention in graphs with GAT -- Performing graph sampling with GraphSAGE -- Building a GCN model using PyTorch Geometric -- Loading and exploring the citation networks dataset -- Building a simple NN-based node classifier -- Building a GCN model for node classification -- Training a GAT model with PyTorch Geometric -- Summary -- Reference list -- Chapter 7: Music and Text Generation with PyTorch…”

Tabla de Contenidos: “…Front Cover -- Half Title Page -- RIVER PUBLISHERS SERIES IN COMMUNICATIONS -- Title Page - Cognitive Hyperconnected Digital Transformation Internet of Things Intelligence Evolution -- Copyright Page -- Dedication -- Contents -- Preface -- Editors Biography -- List of Figures -- List of Tables -- Chapter 1 - IoT Driving Digital Transformation - Impact on Economy and Society -- 1.1 IoT as a Major Enabler for Digitizing Industry -- 1.2 Main Elements of the IoT Implementation Plan and Its First Pillar -- 1.3 The Second and the Third Pillar - Projects, Partnerships and Standardisation -- 1.4 Conclusion -- Reference -- Chapter 2 - Next Generation IoT Platforms -- 2.1 Introduction -- 2.2 DEI Implementation - Working Groups -- 2.3 IoT Platforms - State of Play -- 2.4 Needs and Priorities for the Next Generation IoT Platforms -- 2.5 Conclusion -- References -- Chapter 3 - Internet of Things Cognitive Transformation Technology Research Trends and Applications -- 3.1 Internet of Things Evolving Vision -- 3.1.1 IoT Common Definition -- 3.1.2 IoT Cognitive Transformation -- 3.2 IoT Strategic Research and Innovation Directions -- 3.2.1 IoT Research Directions and Challenges -- 3.3 IoT Smart Environments and Applications -- 3.3.1 IoT Use Cases and Applications -- 3.3.2 Wearables -- 3.3.3 Smart Health, Wellness and Ageing Well -- 3.3.4 Smart Buildings and Architecture -- 3.3.5 Smart Energy -- 3.3.6 Smart Mobility and Transport -- 3.4 IoT and Related Future Internet Technologies -- 3.4.1 Edge Computing -- 3.4.2 Networks and Communication -- 3.5 IoT Distributed Security - Blockchain Technology -- 3.5.1 Verification and Validation in Blockchain -- 3.5.2 IoT Blockchain Application in Healthcare -- 3.6 IoT Platforms -- References -- Chapter 4 - Internet of Robotic Things - Converging Sensing/Actuating, Hyperconnectivity, Artificial Intelligence and IoT Platforms…”

Tabla de Contenidos: “…-- 1.3 The Continuous Strategic High Productivity Improvement -- 1.3.1 Estrangement Results between Company Health and Just Synchronous Operations -- 1.3.2 Changing from Synchronous Operations to Synchronous Profitable Operations -- 1.3.3 Synchronous Profitable Operations Should be Continuously Enhanced -- 1.3.4 The Crucial Role of Strategic Productivity Improvement -- 1.4 The Potential for Profitability Increases Based on Productivity -- 1.5 Targeting the Strategic High Productivity Improvement -- 1.6 The New Approach to Strategic Systematic Improvements -- 1.7 The Strategic Kaizen for Synchronous Profitable Operations -- 1.7.1 The Concept -- 1.7.2 The Basic Image -- 1.7.3 The Seven Basic Processes -- 1.7.4 Five Problems Targeted to Be Solved -- 1.8 Conclusion -- References -- Chapter 2 Current Condition, Basic Policy, and Strategy -- 2.1 Studying the Impact of Current Strategies on Operations and Lowering Costs -- 2.2 Deep Understanding of the Company's Key External Factors -- 2.3 Internal Strategic Capabilities -- 2.4 Current Business Performance Against Expectations -- 2.4.1 Operational and Financial Performance -- 2.4.2 Current Level of Synchronous Profitable Operations -- 2.5 The Basic Policy Framework for Strategic Kaizen -- 2.5.1 At the Cutting Edge: Identifying Strategic Drivers -- 2.5.2 Two Productivity Improvement Scenarios -- 2.5.3 The Strategic Intent of Each Strategic Drivers -- 2.6 Winning Key Strategies…”

Tabla de Contenidos: “…16.1.3.1 Explicit Token Creation -- 16.1.3.2 Implicit Token Creation: Forking a New Path -- 16.1.3.3 Multiple Forks -- 16.1.3.4 Forking vs Spawning -- 16.1.4 Consuming Tokens -- 16.1.4.1 Multiple Forks -- 16.1.4.2 Flow Final -- 16.1.5 Joining at an Action -- 16.2 Timers and Timing Events -- 16.3 Object Flows/Edges -- 16.4 Advanced Topics -- 16.4.1 Weights -- 16.4.2 Stream -- 16.4.3 Send/Receive Messages/Events -- 16.4.4 Local Pre/Postconditions -- 16.5 Activity Diagrams -- 16.5.1 Activities -- 16.5.2 Invoking an Activity -- 16.5.3 Calling an Operation -- 17 Questions for Chapter 16 -- Answers for Chapter 16 -- 18 Behavior: State Machine Diagrams -- 18.1 What is a State and State Machine -- 18.1.1 States and Modes -- 18.1.2 Differences Between States -- 18.1.3 Qualitatively Different States -- 18.1.4 Naming States -- 18.1.5 Overlapping States -- 18.1.6 Finding States -- 18.2 Transitions -- 18.2.1 Events -- 18.2.2 Simple State Machine -- 18.2.3 Guard Conditions -- 18.2.4 Transition Effect -- 18.2.5 Transition Syntax -- 18.2.6 Ongoing Behavior -- 18.2.6.1 Implicit Behavior -- 18.2.6.2 Do Behavior -- 18.2.7 State Setup and Teardown -- 18.2.8 Exit/Entry Action Equivalents -- 18.2.9 Completion -- 18.2.10 Internal Transitions -- 18.3 State Machine Processing -- 18.3.1 Run-to-Completion -- 18.3.2 States and Pseudostates -- 18.3.3 Types of Transitions -- 18.3.4 State Diagrams and Machines -- 18.3.5 Hierarchy of States -- 18.3.6 States Contours -- 18.4 State vs Activity Semantics -- 19 Questions for Chapter 18 -- Answers for Chapter 18 -- Index -- Back Cover…”

Tabla de Contenidos: “…Load Balancer setup -- C.1 Linux installation -- C.1.1 Install preparations -- C.1.2 Linux installation using RDM -- C.1.3 Final setup -- C.2 WebSphere Application Server Edge components installation -- C.2.1 Verification -- Appendix D. …”

Tabla de Contenidos: “…Machine generated contents note: Preface List of Abbreviations 1 Introduction 1.1 Forward Problem 1.2 Inverse Problem 1.3 Issues in Inverse Problem Solving 1.4 Linear, Nonlinear and Linearized Problems 2 Signal and System as Vectors 2.1 Vector Space 2.1.1 Vector Space and Subspace 2.1.2 Basis, Norm and Inner Product 2.1.3 Hilbert Space 2.2 Vector Calculus 2.2.1 Gradient 2.2.2 Divergence 2.2.3 Curl 2.2.4 Curve 2.2.5 Curvature 2.3 Taylor's Expansion 2.4 Linear System of Equations 2.4.1 Linear System and Transform 2.4.2 Vector Space of Matrix 2.4.3 Least Square Solution 2.4.4 Singular Value Decomposition (SVD) 2.4.5 Pseudo-inverse 2.5 Fourier Transform 2.5.1 Series Expansion 2.5.2 Fourier Transform 2.5.3 Discrete Fourier Transform (DFT) 2.5.4 Fast Fourier Transform (FFT) 2.5.5 Two-dimensional Fourier Transform References 3 Basics for Forward Problem 3.1 Understanding PDE using Images as Examples 3.2 Heat Equation 3.2.1 Formulation of Heat Equation 3.2.2 One-dimensional Heat Equation 3.2.3 Two-dimensional Heat Equation and Isotropic Diffusion 3.2.4 Boundary Conditions 3.3 Wave Equation 3.4 Laplace and Poisson Equations 3.4.1 Boundary Value Problem 3.4.2 Laplace Equation in a Circle 3.4.3 Laplace Equation in Three-dimensional Domain 3.4.4 Representation Formula for Poisson Equation References 4 Analysis for Inverse Problem 4.1 Examples of Inverse Problems in Medical Imaging 4.1.1 Electrical Property Imaging 4.1.2 Mechanical Property Imaging 4.1.3 Image Restoration 4.2 Basic Analysis 4.2.1 Sobolev Space 4.2.2 Some Important Estimates 4.2.3 Helmholtz Decomposition 4.3 Variational Problems 4.3.1 Lax-Milgram Theorem 4.3.2 Ritz Approach 4.3.3 Euler-Lagrange Equations 4.3.4 Regularity Theory and Asymptotic Analysis 4.4 Tikhonov Regularization and Spectral Analysis 4.4.1 Overview of Tikhonov Regularization 4.4.2 Bounded Linear Operators in Banach Space 4.4.3 Regularization in Hilbert Space or Banach Space 4.5 Basics of Real Analysis 4.5.1 Riemann Integrable 4.5.2 Measure Space 4.5.3 Lebesgue Measurable Function 4.5.4 Pointwise, Uniform, Norm Convergence and Convergence in Measure 4.5.5 Differentiation Theory References 5 Numerical Methods 5.1 Iterative Method for Nonlinear Problem 5.2 Numerical Computation of One-dimensional Heat equation 5.2.1 Explicit Scheme 5.2.2 Implicit Scheme 5.2.3 Crank-Nicolson Method 5.3 Numerical Solution of Linear System of Equations 5.3.1 Direct Method using LU Factorization 5.3.2 Iterative Method using Matrix Splitting 5.3.3 Iterative Method using Steepest Descent Minimization 5.3.4 Conjugate Gradient (CG) Method 5.4 Finite Difference Method (FDM) 5.4.1 Poisson Equation 5.4.2 Elliptic Equation 5.5 Finite Element Method (FEM) 5.5.1 One-dimensional Model 5.5.2 Two-dimensional Model 5.5.3 Numerical Examples References 6 CT, MRI and Image Processing Problems 6.1 X-ray CT 6.1.1 Inverse Problem 6.1.2 Basic Principle and Nonlinear Effects 6.1.3 Inverse Radon Transform 6.1.4 Artifacts in CT 6.2 MRI 6.2.1 Basic Principle 6.2.2 K-space Data 6.2.3 Image Reconstruction 6.3 Image Restoration 6.3.1 Role of p in (6.35) 6.3.2 Total Variation Restoration 6.3.3 Anisotropic Edge-preserving Diffusion 6.3.4 Sparse Sensing 6.4 Segmentation 6.4.1 Active Contour Method 6.4.2 Level Set Method 6.4.3 Motion Tracking for Echocardiography References 7 Electrical Impedance Tomography 7.1 Introduction 7.2 Measurement Method and Data 7.2.1 Conductivity and Resistance 7.2.2 Permittivity and Capacitance 7.2.3 Phasor and Impedance 7.2.4 Admittivity and Trans-impedance 7.2.5 Electrode Contact Impedance 7.2.6 EIT System 7.2.7 Data Collection Protocol and Data Set 7.2.8 Linearity between Current and Voltage 7.3 Representation of Physical Phenomena 7.3.1 Derivation of Elliptic PDE 7.3.2 Elliptic PDE for Four-electrode Method 7.3.3 Elliptic PDE for Two-electrode Method 7.3.4 Min-max Property of Complex Potential 7.4 Forward Problem and Model 7.4.1 Continuous Neumann-to-Dirichlet Data 7.4.2 Discrete Neumann-to-Dirichlet Data 7.4.3 Nonlinearity between Admittivity and Voltage 7.5 Uniqueness Theory and Direct Reconstruction Method 7.5.1 Calderon's Approach 7.5.2 Uniqueness and Three-dimensional Reconstruction: Infinite Measurements 7.5.3 Nachmann's D-bar Method in Two Dimension 7.6 Backprojection Algorithm 7.7 Sensitivity and Sensitivity Matrix 7.7.1 Perturbation and Sensitivity 7.7.2 Sensitivity Matrix 7.7.3 Linearization 7.7.4 Quality of Sensitivity Matrix 7.8 Inverse Problem of EIT 7.8.1 Inverse Problem of RC Circuit 7.8.2 Formulation of EIT Inverse Problem 7.8.3 Ill-posedness of EIT Inverse Problem 7.9 Static Imaging 7.9.1 Iterative Data Fitting Method 7.9.2 Static Imaging using 4-channel EIT System 7.9.3 Regularization 7.9.4 Technical Difficulty of Static Imaging 7.10 Time-difference Imaging 7.10.1 Data Sets for Time-difference Imaging 7.10.2 Equivalent Homogeneous Admittivity 7.10.3 Linear Time-difference Algorithm using Sensitivity Matrix 7.10.4 Interpretation of Time-difference Image 7.11 Frequency-difference Imaging 7.11.1 Data Sets for Frequency-difference Imaging 7.11.2 Simple Difference Ft,ω2− Ft,ω1 7.11.3 Weighted Difference Ft,ω2− [alpha] Ft,ω1 7.11.4 Linear Frequency-difference Algorithm using Sensitivity Matrix 7.11.5 Interpretation of Frequency-difference Image References 8 Anomaly Estimation and Layer Potential Techniques 8.1 Harmonic Analysis and Potential Theory 8.1.1 Layer Potentials and Boundary Value Problems for Laplace Equation 8.1.2 Regularity for Solution of Elliptic Equation along Boundary of Inhomogeneity 8.2 Anomaly Estimation using EIT 8.2.1 Size Estimation Method 8.2.2 Location Search Method 8.3 Anomaly Estimation using Planar Probe 8.3.1 Mathematical Formulation 8.3.2 Representation Formula References 9 Magnetic Resonance Electrical Impedance Tomography 9.1 Data Collection using MRI 9.1.1 Measurement of Bz 9.1.2 Noise in Measured Bz Data 9.1.3 Measurement of B = (Bx,By,Bz) 9.2 Forward Problem and Model Construction 9.2.1 Relation between J , Bz and σ 9.2.2 Three Key Observations 9.2.3 Data Bz Traces σ∇u © e z-directional Change of σ 9.2.4 Mathematical Analysis toward MREIT Model 9.3 Inverse Problem Formulation using B or J 9.4 Inverse Problem Formulation using Bz 9.4.1 Model with Two Linearly Independent Currents 9.4.2 Uniqueness 9.4.3 Defected Bz Data in a Local Region 9.5 Image Reconstruction Algorithm 9.5.1 J-substitution Algorithm 9.5.2 Harmonic Bz Algorithm 9.5.3 Gradient Bz Decomposition and Variational Bz Algorithm 9.5.4 Local Harmonic Bz Algorithm 9.5.5 Sensitivity Matrix Based Algorithm 9.5.6 Anisotropic Conductivity Reconstruction Algorithm 9.5.7 Other Algorithms 9.6 Validation and Interpretation 9.6.1 Image Reconstruction Procedure using Harmonic Bz Algorithm 9.6.2 Conductivity Phantom Imaging 9.6.3 Animal Imaging 9.6.4 Human Imaging 9.7 Applications References 10 Magnetic Resonance Elastography 10.1 Representation of Physical Phenomena 10.1.1 Overview of Hooke's Law 10.1.2 Strain Tensor in Lagrangian Coordinates 10.2 Forward Problem and Model 10.3 Inverse Problem in MRE 10.4 Reconstruction Algorithms 10.4.1 Reconstruction of [mu] with the Assumption of Local Homogeneity 10.4.2 Reconstruction of [mu] without the Assumption of Local Homogeneity 10.4.3 Anisotropic Elastic Moduli Reconstruction 10.5 Technical Issues in MRE References…”

Tabla de Contenidos: “…Note pecked notches for hafting on opposing long edges. -- Figure 2.31: A suggested reconstruction of the sequence of ramparts A-D based on Trench 1. -- Figure 2.32: A reconstruction of the fort: multi-vallate with two entrances and in a dramatic location overlooking lower Strathearn (artist Chris Mitchell). -- 3. …”

“…Graphs represent a system of edges connected at one or more branching points (vertices). …”

Tabla de Contenidos: “…3.5 FUNDAMENTOS PARA EL EXAMEN -- 4 AAA -- 4.1 INTRODUCCIÓN A AAA -- 4.1.1 Modos de acceso AAA -- 4.1.2 Autenticación AAA -- 4.1.3 Autorización AAA -- 4.1.4 Auditoría AAA -- 4.2 CONFIGURACIÓN LOCAL DE AAA -- 4.2.1 Configuración de AAA con CLI -- 4.2.2 Configuración de AAA con CCP -- 4.3 AUTENTICACIÓN AAA BASADA EN SERVIDOR -- 4.3.1 Protocolos de autenticación AAA -- 4.3.2 Cisco Secure ACS -- 4.3.3 Instalación de ACS -- 4.3.4 Configuración de ACS -- 4.4 CONFIGURACIÓN DE AUTENTICACIÓN BASADA EN SERVIDOR -- 4.4.1 Configuración de RADIUS y TACACS+ con CLI -- 4.5 CONFIGURACIÓN DE TACACS+ CON CCP -- 4.6 RESOLUCIÓN DE FALLOS EN AAA -- 4.7 CONFIGURACIÓN DE AUTORIZACIÓN BASADA EN SERVIDOR -- 4.7.1 Configuración de autorización con CCP -- 4.8 REGISTRO DE AUDITORÍA AAA BASADA EN SERVIDOR -- 4.8.1 Configuración del registro de auditoría -- 4.9 FUNDAMENTOS PARA EL EXAMEN -- 5 SEGURIDAD DE CAPA 2 -- 5.1 SEGURIDAD DE LAN -- 5.1.1 Seguridad en los dispositivos finales -- 5.1.2 Dispositivos Cisco de seguridad para terminales -- 5.2 SEGURIDAD EN CAPA 2 -- 5.2.1 Ataques comunes de capa 2 -- 5.3 SEGURIDAD DE PUERTOS DE CAPA 2 -- 5.3.1 Configuración de seguridad de puertos -- 5.3.2 Verificación de la seguridad de puertos -- 5.4 CONTROL DE TORMENTAS -- 5.4.1 Configuración de control de tormentas -- 5.5 PROTECCIÓN DE LAS TOPOLOGÍAS STP -- 5.5.1 Configuración de BPDU Guard -- 5.5.2 Configuración de BPDU Filter -- 5.5.3 Configuración de Root Guard -- 5.6 SEGURIDAD EN VLAN -- 5.6.1 Seguridad del enlace troncal -- 5.6.2 Configuración de un enlace troncal seguro -- 5.6.3 VLAN Access Lists -- 5.6.4 Private VLAN -- 5.6.5 Private VLAN Edge -- 5.6.6 Switched Port Analyzer -- 5.7 FUNDAMENTOS PARA EL EXAMEN -- 6 LISTAS DE CONTROL DE ACCESO -- 6.1 INTRODUCCIÓN A ACL -- 6.1.1 Funcionamiento de las ACL -- 6.1.2 Mitigación de ataques con ACL -- 6.1.3 Tipos de lista de acceso…”

Tabla de Contenidos: “…Schliebs Optimization of material logistics by using leading edge electronic Information and Communication Technologies (ICT) in underground coalmine M.T. …”

Tabla de Contenidos: “…5.1.2.10 Remote Sensing and Image Analysis -- 5.2 History of Surveillance Systems -- 5.3 Literature Review -- 5.4 Mathematical Models for Surveillance Systems -- 5.4.1 Overview of Mathematical Modeling in Surveillance -- 5.4.2 Role of Probability and Statistics in Surveillance -- 5.4.2.1 Anomaly Detection -- 5.4.2.2 Predictive Analytics -- 5.4.2.3 Risk Assessment -- 5.4.2.4 Decision Support -- 5.4.2.5 Data Fusion and Integration -- 5.4.3 Modeling Human Behavior in Surveillance Scenario -- 5.4.3.1 Behavioral Patterns -- 5.4.3.2 Machine Learning -- 5.4.3.3 Social Dynamics -- 5.4.3.4 Continuous Learning and Adaptation -- 5.4.3.5 Cognitive Modeling -- 5.4.4 Mathematical Modeling for Tracking and Motion Analysis -- 5.4.4.1 Object Tracking -- 5.4.4.2 Motion Prediction -- 5.4.4.3 Motion Analysis -- 5.4.4.4 Motion Representation -- 5.4.4.5 Trajectory Analysis -- 5.4.4.6 Data Fusion -- 5.4.4.7 Continuous Learning and Adaptation -- 5.5 Artificial Intelligence in Surveillance Systems -- 5.5.1 Object Recognition and Detection -- 5.5.2 Behavior Analysis -- 5.5.3 Facial Recognition -- 5.5.4 Video Analytics -- 5.5.5 Real-Time Alert Generation -- 5.5.6 Predictive Analytics -- 5.5.7 Data Management and Analytics -- 5.6 Use of Mathematical Models for Pre-Processing Image Data -- 5.6.1 Filtering and Smoothing -- 5.6.2 Image Enhancement -- 5.6.3 Edge Detection -- 5.6.4 Image Restoration -- 5.6.5 Feature Extraction -- 5.6.6 Dimensionality Reduction -- 5.7 Future Directions and Challenges -- 5.7.1 Deep Learning and Neural Networks -- 5.7.2 Real-Time Processing -- 5.7.3 Multi-Modal Data Fusion -- 5.7.4 Privacy-Preserving Techniques -- 5.7.5 Human-Centric Surveillance -- 5.7.6 Robustness to Adversarial Attacks -- 5.7.7 Interoperability and Scalability -- 5.7.8 Ethical and Legal Considerations -- 5.8 Conclusion -- 5.8.1 Summary of the Chapter…”

Tabla de Contenidos: “…8.1.3 Service-level tests: Testing a microservice from outside its process -- 8.1.4 Unit-level tests: Testing endpoints from within the process -- 8.2 Testing libraries: Microsoft.AspNetCore.TestHost and xUnit -- 8.2.1 Meet Microsoft.AspNetCore.TestHost -- 8.2.2 Meet xUnit -- 8.2.3 xUnit and Microsoft.AspNetCore.TestHost working together -- 8.3 Writing unit tests using Microsoft.AspNetCore.TestHost -- 8.3.1 Setting up a unit-test project -- 8.3.2 Using the TestServer and HttpClient to unit-test endpoints -- 8.3.3 Injecting mocks into endpoints -- 8.4 Writing service-level tests -- 8.4.1 Creating a service-level test project -- 8.4.2 Creating mocked endpoints -- 8.4.3 Executing the test scenario against the microservice under test -- Summary -- Part 3 Handling cross-cutting concerns: Building a reusable microservice platform -- 9 Cross-cutting concerns: Monitoring and logging -- 9.1 Monitoring needs in microservices -- 9.2 Logging needs in microservices -- 9.2.1 Tracing requests across microservices -- 9.2.2 Structured logging with Serilog -- 9.3 Implementing the monitoring endpoints -- 9.3.1 Implementing the /health/live monitoring endpoint -- 9.3.2 Implementing the /health/startup monitoring endpoint -- 9.4 Implementing structured logging -- 9.4.1 Adding a trace ID to all log messages -- 9.4.2 Trace ID is included in outgoing HTTP requests -- 9.4.3 Logging unhandled exceptions -- 9.5 Implementing monitoring and logging in Kubernetes -- 9.5.1 Configure monitoring in Kubernetes -- Summary -- 10 Securing microservice-to-microservice communication -- 10.1 Microservice security concerns -- 10.1.1 Authenticating users at the edge -- 10.1.2 Authorizing users in microservices -- 10.1.3 How much should microservices trust each other? …”

Tabla de Contenidos: “…Spatial Filters -- 4.1 Introduction -- 4.2 Filtering -- 4.2.1 Mean Filter -- 4.2.2 Median Filter -- 4.2.3 Max Filter -- 4.2.4 Min Filter -- 4.3 Edge Detection using Derivatives -- 4.3.1 First Derivative Filters -- 4.3.1.1 Sobel Filter -- 4.3.1.2 Prewitt Filter -- 4.3.1.3 Canny Filter…”

Tabla de Contenidos: “…Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- List of Acronyms -- Preface -- Author -- Chapter 1 Introduction to Flight Vehicles -- 1.1 Introduction -- 1.2 Components of an Aeroplane -- 1.2.1 Fuselage -- 1.2.2 Wings -- 1.2.3 Tail Surfaces or Empennage -- 1.2.4 Landing Gear -- 1.3 Basic Principles of Flight -- 1.3.1 Forces Acting on an Aeroplane -- 1.3.2 Drag and Its Reduction -- 1.3.3 Aerodynamically Conforming Shapes: Streamlining -- 1.3.4 Stability and Balance -- 1.4 Flying Control Surfaces: Elevator, Ailerons and Rudder -- 1.4.1 Flaps, High-Lift and Flow Control Devices -- 1.4.2 Introducing Boundary Layers -- 1.4.3 Spoilers -- 1.5 Pilot's Controls: The Throttle, the Control Column and Yoke, the Rudder Pedals and the Toe Brakes -- 1.6 Modes of Flight -- 1.6.1 Static and In-Flight Stability Margins -- 1.7 Power Plant -- 1.7.1 Propeller-Driven Aircraft -- 1.7.2 Jet Propulsion -- 1.8 Avionics, Instrumentation and Systems -- 1.8.1 Autonomous Navigation -- 1.9 Geometry of Aerofoils and Wings -- 1.9.1 Aerofoil Geometry -- 1.9.2 Chord Line -- 1.9.3 Camber -- 1.9.4 Leading and Trailing Edges -- 1.9.5 Specifying Aerofoils -- 1.9.6 Equations Defining Mean Camber Line -- 1.9.7 Aerofoil Thickness Distributions -- 1.9.8 Wing Geometry -- Chapter Highlights -- Exercises -- Answers to Selected Exercises -- References -- Chapter 2 Basic Principles Governing Aerodynamic Flows -- 2.1 Introduction -- 2.2 Continuity Principle -- 2.2.1 Streamlines and Stream Tubes -- 2.3 Bernoulli's Principle -- 2.4 Laminar Flows and Boundary Layers -- 2.5 Turbulent Flows -- 2.6 Aerodynamics of Aerofoils and Wings -- 2.6.1 Flow Around an Aerofoil -- 2.6.2 Mach Number and Subsonic and Supersonic Flows -- 2.7 Properties of Air in the Atmosphere…”