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: “…ÉVALUATION DE LA VIABILITÉ ÉCONOMIQUE -- 3.1 Résultats de l'analyse -- 3.2 Impact de la réduction de la durée des études grâce à la validation des acquis -- 3.3 Enseignements de nature à renforcer la viabilité économique -- 4. …”

Tabla de Contenidos: “…4.5.2 VERTICAL METAL-OXIDE SEMICONDUCTOR POWER FIELD-EFFECT TRANSISTORS -- 4.5.3 GATE DRIVE IMPEDANCE -- Gate-Source Overvoltage -- Source Lead Inductance -- 4.5.4 SWITCHING SPEED -- 4.5.5 ON-STATE RESISTANCE -- P-Channel Vertical Metal-Oxide Semiconductor -- 4.6 INSULATED GATE BIPOLAR TRANSISTORS -- 4.6.1 INSULATED GATE BIPOLAR TRANSISTOR STRUCTURE -- 4.6.2 ADVANTAGES OVER MOSFETS AND BIPOLARS -- 4.6.3 DISADVANTAGES -- 4.7 WIDE BAND GAP DEVICES -- 5 - Analog Integrated Circuits -- 5.1 THE IDEAL OP-AMP -- 5.1.1 APPLICATIONS CATEGORIES -- 5.2 THE PRACTICAL OP-AMP -- 5.2.1 OFFSET VOLTAGE -- Output Saturation Due to Amplified Offset -- Reducing the Effect of Offset -- Offset Drift -- Circuit Techniques to Remove the Effect of Drift -- 5.2.2 BIAS AND OFFSET CURRENTS -- Bias Current Levels -- Output Offsets Due to Bias and Offset Currents -- 5.2.3 COMMON-MODE EFFECTS -- Common-Mode Rejection Ratio -- Power Supply Rejection Ratio -- 5.2.4 INPUT VOLTAGE RANGE -- Absolute Maximum Input -- 5.2.5 OUTPUT PARAMETERS -- Power Rail Voltage -- Load Impedance -- 5.2.6 AC PARAMETERS -- 5.2.7 SLEW RATE AND LARGE-SIGNAL BANDWIDTH -- Slew Rate -- Large-Signal Bandwidth -- Slewing Distortion -- 5.2.8 SMALL-SIGNAL BANDWIDTH -- 5.2.9 SETTLING TIME -- 5.2.10 THE OSCILLATING AMPLIFIER -- Ground Coupling -- Power Supply Coupling -- Output-Stage Instability -- Stray Capacitance at the Input -- Parasitic Feedback -- 5.2.11 OPEN-LOOP GAIN -- Sagging AOL -- 5.2.12 NOISE -- Definitions -- 5.2.13 CALCULATING THE EFFECT OF NOISE IN A CIRCUIT -- Power Spectral Density of Noise -- Types of Noise -- Thermal Noise -- Amplifier Noise -- Noise Bandwidth -- Modeling and Simulation of Noise -- 5.2.14 SUPPLY CURRENT AND VOLTAGE -- Supply Voltage -- Supply Current -- lS Versus Speed and Dissipation -- 5.2.15 TEMPERATURE RATINGS -- Specification Validity -- Package Reliability…”

Tabla de Contenidos: “…Step 2: Move the Turtle -- Step 3: Move the Bag of Gold -- Step 4: Update the User's Score -- Try It Out 11-5 -- Programming Challenges -- Chapter 12: Building Graphical User Interfaces -- Design a User Interface with the Controls Object -- Step 1: The Design Phase -- Step 2: Program Interactivity -- Try It Out 12-1 -- Make a Colorful Drawing Program -- Try It Out 12-2 -- Explore Circuits with Code -- Step 1: Open the Startup File -- Step 2: Add the Main Code -- Step 3: Toggle the Switch -- Step 4: Respond to Changes -- Step 5: Update the Program's Interface -- Try It Out 12-3 -- Program Your Own Image Viewer -- Try It Out 12-4 -- Programming Challenges -- Chapter 13: Repeating For Loops -- The For Loop -- Try It Out 13-1 -- Magical Moving Text -- Try It Out 13-2 -- Adding 'em Up -- Try It Out 13-3 -- Formatting Your Output -- Try It Out 13-4 -- Drawing All Kinds of Lines -- Try It Out 13-5 -- Changing the Step Size -- Counting Down by Twos -- Making a Fractional Step -- Try It Out 13-6 -- Nested Loops -- Tessellating for Fun -- Try It Out 13-7 -- Multiple Nesting Levels -- Try It Out 13-8 -- Programming Challenges -- Chapter 14: Creating Conditional While Loops -- When to Use While Loops -- Writing a While Loop -- Try It Out 14-1 -- Validating Your Inputs -- Try It Out 14-2 -- Infinite Loops -- Try It Out 14-3 -- Create a Rock-Paper-Scissors Game -- Step 1: Open the Startup File -- Step 2: Add the MouseDown Handler -- Step 3: Switch the Images -- Step 4: Announce the Winner -- Try It Out 14-4 -- Programming Challenges -- Chapter 15: Grouping Data in One-Dimensional Arrays -- Getting Started with Indexed Arrays -- Array Basics -- Initializing Arrays -- Try It Out 15-1 -- Filling Arrays with a For Loop -- Constant Initialization -- Random Initialization -- Formula Initialization -- User Initialization -- Try It Out 15-2 -- Displaying Arrays…”

Tabla de Contenidos: “…Front Cover -- Quantum Inspired Computational Intelligence: Research and Applications -- Copyright -- Dedication -- Contents -- List of Contributors -- About the Editors -- Foreword -- Preface -- Acknowledgments -- Part I : Research -- Chapter 1: Quantum neural computation of entanglement is robust to noise and decoherence -- 1 Introduction and Literature Background -- 2 Dynamic Learning of an Entanglement Indicator -- 3 Learning with Noise -- 4 Decoherence -- 5 Noise Plus Decoherence -- 6 Conclusions -- Acknowledgments -- References -- Chapter 2: Quantum computing and supervised machine learning: Training, model selection, and error estimation -- 1 Introduction -- 2 The Supervised Learning Problem: Training, Model Selection, and Error Estimation -- 3 Classical and Quantum Computing -- 3.1 Classical Computing -- 3.2 Quantum Computing -- 4 Quantum Computing for Training -- 4.1 Bounded Loss Functions -- 4.1.1 Example: The problems behind the convex relaxation -- 4.2 Energy-Efficient Models -- 4.3 Sparse Solutions -- 4.4 Gibbs and Bayes Classifiers -- 5 Quantum Computing for Model Selection and Error Estimation -- 5.1 Out-of-Sample Methods: Hold-Out, Cross Validation, and Bootstrap -- 5.2 Vapnik-Chervonenkis Theory -- 5.3 (Local) Rademacher Complexity Theory -- 5.4 PAC-Bayes Theory -- 5.4.1 Algorithmic stability -- 5.4.2 Compression bound -- 6 Conclusions -- References -- Chapter 3: Field computation: A framework for quantum-inspired computing -- 1 Introduction -- 2 Fields -- 3 Field computation -- 4 Derivatives of Field Transformations -- 5 Examples of Field Computation -- 5.1 Neural Network-Style Computation -- 5.2 Discrete Basis Function Networks -- 5.3 Continua of Basis Functions -- 5.4 Approximations of Spatial Integration and Differentiation -- 5.5 Iterative Field Computation -- 5.6 Field Differential Equations…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Part I: Chemical and Electrochemical Hydrogen Storage -- 1 Metal Hydride Hydrogen Compression Systems - Materials, Applications and Numerical Analysis -- 1.1 Introduction -- 1.2 Adoption of a Hydrogen-Based Economy -- 1.2.1 Climate Change and Pollution -- 1.2.2 Toward a Hydrogen-Based Future -- 1.2.3 Hydrogen Storage -- 1.2.3.1 Compressed Hydrogen Storage -- 1.2.3.2 Hydrogen Storage in Liquid Form -- 1.2.3.3 Solid-State Hydrogen Storage -- 1.3 Hydrogen Compression Technologies -- 1.3.1 Reciprocating Piston Compressor -- 1.3.2 Ionic Liquid Piston Compressor -- 1.3.3 Piston-Metal Diaphragm Compressor -- 1.3.4 Electrochemical Hydrogen Compressor -- 1.4 Metal Hydride Hydrogen Compressors (MHHC) -- 1.4.1 Operation of a Two-Stage MHHC -- 1.4.2 Metal Hydrides -- 1.4.3 Thermodynamic Analysis of the Metal Hydride Formation -- 1.4.3.1 Pressure-Composition-Temperature (P-c-T) Properties -- 1.4.3.2 Slope and Hysteresis -- 1.4.4 Material Challenges for MHHCs -- 1.4.4.1 AB5 Intermetallics -- 1.4.4.2 AB2 Intermetallics -- 1.4.4.3 TiFe-Based AB-Type Intermetallics -- 1.4.4.4 Vanadium-Based BCC Solid Solution Alloys -- 1.5 Numerical Analysis of a Multistage MHHC System -- 1.5.1 Assumptions -- 1.5.2 Physical Model and Geometries -- 1.5.3 Heat Equation -- 1.5.4 Hydrogen Mass Balance -- 1.5.5 Momentum Equation -- 1.5.6 Kinetic Expressions for the Hydrogenation and Dehydrogenation -- 1.5.7 Equilibrium Pressure -- 1.5.8 Coupled Mass and Energy Balance -- 1.5.9 Validation of the Numerical Model -- 1.5.10 Material Selection for a Three-Stage MHHC -- 1.5.11 Temperature Evolution of the Complete Three-Stage Compression Cycle -- 1.5.12 Pressure and Storage Capacity Evolution During the Complete Three-Stage Compression Cycle -- 1.5.13 Importance of the Number of Stages and Proper Selection -- 1.6 Conclusions…”

Tabla de Contenidos: “…#3: Erwarte Variabilität - bewahre Optionen -- #4: Entwickle inkrementell mit schnellen integrierten Lernzyklen -- #5: Lege Meilensteine basierend auf einer objektiven Bewertung laufender Systeme fest -- #6: Visualisiere und begrenze WIP-Limits, reduziere Losgrößen und manage die Länge von Warteschlangen -- #7: Nutze Kadenzen und synchronisiere über Bereichsgrenzen hinweg -- #8: Entwickle die intrinsische Motivation von Wissensarbeitern -- #9: Dezentralisiere Entscheidungsfindung -- 2.9 Leadership -- Führung kommt in den Fokus -- Führungsbild und Rolle der Führung -- 3 Agile Teams in SAFe -- 3.1 Zwei Wurzeln agiler Entwicklung -- 3.2 Vier Vorteile agiler Teams -- Vorhersagbare Entwicklung -- Schnelles Feedback und belastbare Fortschrittsberichte -- Mehr Spaß und Motivation in der Entwicklung -- Beschleunigtes Lernen -- 3.3 Beschleunigtes Lernen ist Team-Lernen -- Team-»Ba« als Voraussetzung -- Darum sind Teams so wichtig -- 3.4 Vier Vorteile agiler Softwaretechniken -- Technische Schulden beherrschen -- Stabilisierung des Prozesses und der Entwicklungsgeschwindigkeit -- Regelmäßige Lieferung in kleinen Inkrementen -- Valide Fortschrittskontrolle -- 3.5 Herausforderungen in skalierten Umgebungen -- Wertströme und Fluss -- Takt -- Content Ownership -- Selbstorganisation und Führung -- Abhängigkeiten und Übergaben zwischen Teams -- Liefern in kurzen Zyklen -- 3.6 Teams bei SAFe -- Cross-funktionale stabile Teams -- Feature-Teams -- Der Agile Release Train als Team von Teams -- Scrum/Kanban und XP als Grundlage -- Codequalität und Architektur -- Alignment - Unterschiede zu einzelnen Teams -- Transparenz -- Planung und Schätzung -- Teams im Kanban-Modus -- 4 Die Programmebene -- 4.1 Einführung -- Skalieren in verschiedenen Dimensionen -- Die Metapher des Agile Release Train -- 4.2 Der Agile Release Train -- 4.2.1 Arbeitsprinzipien…”

Tabla de Contenidos: “…4.2 Data Analytics -- 4.3 Data Visualization -- 4.4 Data Analytics and Data Visualization for Formulation Development -- 4.5 Data Analytics and Data Visualization for Drug Product Development -- 4.6 Data Analytics and Data Visualization for Drug Product Life Cycle Management -- 4.7 Conclusion and Future Prospects -- References -- Chapter 5 Mass Spectrometry, Protein Interaction and Amalgamation of Bioinformatics -- 5.1 Introduction -- 5.2 Mass Spectrometry - Protein Interaction -- 5.2.1 The Prerequisites -- 5.2.2 Finding Affinity Partner (The Bait) -- 5.2.3 Antibody-Based Affinity Tags -- 5.2.4 Small Molecule Ligands -- 5.2.5 Fusion Protein-Based Affinity Tags -- 5.3 MS Analysis -- 5.4 Validating Specific Interactions -- 5.5 Mass Spectrometry - Qualitative and Quantitative Analysis -- 5.6 Challenges Associated with Mass Analysis -- 5.7 Relative vs. …”

Tabla de Contenidos: “…Intro -- Cover -- Contents -- Preface -- List of Contributors -- Part 1: Process Fundamentals -- Chapter 1 : Algal systems for resource recovery from waste and wastewater -- 1.1 Process Fundamentals -- 1.2 Algal-Based Wastewater Treatment -- 1.3 Valorization of Algal Biomass by Integrating with Different Technologies -- 1.4 Algal Biotechnology -- References -- Chapter 2 : Metabolic modelling of microalgae for wastewater treatment -- 2.1 Introduction -- 2.2 Main Metabolic Pathways -- 2.2.1 Photosynthesis -- 2.2.2 Glycolysis and pentose phosphate pathway -- 2.2.3 Tricarboxylic acid cycle -- 2.2.4 Glyoxylate shunt -- 2.2.5 Lipid biosynthesis -- 2.3 Genome-Scale Metabolic Models -- 2.4 Modelling Metabolic Networks -- 2.5 Tools for Steady-State Conditions -- 2.5.1 Elementary flux modes -- 2.5.1.1 Mathematical construction of EFMs -- 2.5.1.2 Minimal generating sets and EFM reduction -- 2.5.2 Flux balance analysis -- 2.6 Metabolic Networks Reduction -- 2.6.1 The DRUM framework -- 2.7 Case Study: Microalgae Cultivation -- 2.7.1 Introduction: volatile fatty acid -- 2.7.2 Determination of the subnetworks and accumulating metabolites -- 2.7.3 Derivation of MR -- 2.7.4 Choice of kinetic model -- 2.7.5 Model calibration and validation -- 2.7.6 Example of application: optimization of waste treatment time -- 2.8 Conclusion -- References -- Chapter 3 : Wastewater treatment using microalgal-bacterial consortia in the photo-activated sludge process -- 3.1 Microalgal-Bacterial Consortia -- 3.1.1 Use of microalgal-bacterial consortia in environmental technologies -- 3.1.2 Interactions within microalgal-bacterial consortia -- 3.1.3 Nutrient removal by microalgal-bacterial consortia -- 3.1.4 Microalgal-bacterial systems and configurations…”

Tabla de Contenidos: “…Seeking Clarification and Validation -- Chapter Highlights -- Evaluate Yourself -- References/Further Readings -- Chapter 2: Interpersonal Relationship -- 1. …”

Tabla de Contenidos: “…10.4 Key Derivation Algorithms -- 11 Interworking Security Between EPS and Other Systems -- 11.1 Interworking with GSM and 3G Networks -- 11.1.1 Routing Area Update Procedure in UTRAN -- 11.1.2 Tracking Area Update Procedure in EPS -- 11.1.3 Handover from EPS to 3G or GSM -- 11.1.4 Handover from 3G or GSM to EPS -- 11.2 Interworking with Non-3GPP Networks -- 11.2.1 Principles of Interworking with Non-3GPP Networks -- 11.2.2 Authentication and Key Agreement for Trusted Access -- 11.2.3 Authentication and Key Agreement for Untrusted Access -- 11.2.4 Security for Mobile IP Signalling -- 11.2.5 Mobility between 3GPP and non-3GPP Access Networks -- 12 Security for Voice over LTE -- 12.1 Methods for Providing Voice over LTE -- 12.1.1 IMS over LTE -- 12.1.2 Circuit Switched Fallback (CSFB) -- 12.1.3 Single Radio Voice Call Continuity (SRVCC) -- 12.2 Security Mechanisms for Voice over LTE -- 12.2.1 Security for IMS over LTE -- 12.2.2 Security for Circuit Switched Fallback -- 12.2.3 Security for Single Radio Voice Call Continuity -- 13 Security for Home Base Station Deployment -- 13.1 Security Architecture, Threats and Requirements -- 13.1.1 Scenario -- 13.1.2 Threats and Risks -- 13.1.3 Requirements -- 13.1.4 Security Architecture -- 13.2 Security Features -- 13.2.1 Authentication -- 13.2.2 Local Security -- 13.2.3 Communications Security -- 13.2.4 Location Verification and Time Synchronization -- 13.3 Security Procedures Internal to the Home Base Station -- 13.3.1 Secure Boot and Device Integrity Check -- 13.3.2 Removal of Hosting Party Module -- 13.3.3 Loss of Backhaul Link -- 13.3.4 Secure Time Base -- 13.3.5 Handling of Internal Transient Data -- 13.4 Security Procedures between Home Base Station and Security Gateway -- 13.4.1 Device Integrity Validation -- 13.4.2 Device Authentication -- 13.4.3 IKEv2 and Certificate Profiling…”

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: “…20.4 Multivariate Results -- 20.4.1 Firm Value -- 20.4.2 Firm Riskiness and Firm Accounting Performance -- 20.5 Conclusion -- References -- Appendix: Estimated MTEs -- Chapter 21 Exercises -- Exercise 1 Portfolio Choice and the Notion of Value at Risk (VaR) -- Calculating VaR -- Incremental VaR -- Reference -- Solution for Exercise 1 -- Conclusion Regarding the Calculations for the VaR -- Incremental VaR -- Exercise 2 Backtesting of VaR Models -- The Importance of Backtesting -- Definitions for the Backtesting -- Validation of the Model over a Longer Period -- Linear Regression Approach -- References -- Exercise 3 Calculation of VaR with Different Distributions and Accuracy of VaR -- Calculating VaR using a Lognormal or Truncated Normal Distribution -- Estimating the Precision of the VaR Calculated -- Solution to Exercise 3 -- Precision Estimation of the Calculated VaR -- References -- Exercise 4 VaR for an Equity Portfolio with Options -- Part A Choosing a Portfolio Application of VaR Calculations with Real Data from a Stock Portfolio -- Part B Application of the Delta and Delta‐Gamma Methods to Calculate VaR -- Risk Exposure of the Portfolio by the Delta Approach -- Risk Exposure of the Portfolio by the Delta‐Gamma Approach -- Solution to Exercise 4 -- Exercise 5 CVaR Conditional Value at Risk -- Mathematical Expressions of CVaR -- Recapitulation of the Three Models: Normal Distribution, Student's t, and Mixture of Two Normal Distributions -- Conclusion -- Reference -- Conclusion -- General References -- Index -- EULA…”

Tabla de Contenidos: “…Set the Current Workbook's Name and File Path in a Cell -- Check Whether a Workbook Is Open -- Check Whether a Sheet in an Open Workbook Exists -- Count the Number of Workbooks in a Directory -- Retrieve USERID -- Retrieve Date and Time of Last Save -- Retrieve Permanent Date and Time -- Validate an E-mail Address -- Sum Cells Based on Interior Color -- Count Unique Values -- Remove Duplicates from a Range -- Find the First Nonzero-Length Cell in a Range -- Substitute Multiple Characters -- Retrieve Numbers from Mixed Text -- Convert Week Number into Date -- Separate Delimited String -- Sort and Concatenate -- Sort Numeric and Alpha Characters -- Search for a String Within Text -- Reverse the Contents of a Cell -- Multiple Max -- Return Hyperlink Address -- Return the Column Letter of a Cell Address -- Static Random -- Using Select Case on a Worksheet -- Next Steps -- 5 Looping and Flow Control -- For...Next Loops -- Using Variables in the For Statement -- Variations on the For...Next Loop -- Exiting a Loop Early After a Condition Is Met -- Nesting One Loop Inside Another Loop -- Do Loops -- Using the While or Until Clause in Do Loops -- While...Wend Loops -- VBA Loop: For Each -- Object Variables -- Flow Control: Using If...Then...Else and Select Case -- Basic Flow Control: If...Then...Else -- Conditions -- If...Then...End If -- Either/Or Decisions: If...Then...Else...End If -- Using If...Else If...End If for Multiple Conditions -- Using Select Case...End Select for Multiple Conditions -- Complex Expressions in Case Statements -- Nesting If Statements -- Next Steps -- 6 R1C1-Style Formulas -- Referring to Cells: A1 Versus R1C1 References -- Switching Excel to Display R1C1-Style References -- The Miracle of Excel Formulas -- Enter a Formula Once and Copy 1,000 Times -- The Secret: It's Not That Amazing -- Explanation of R1C1 Reference Style…”

Tabla de Contenidos: “…-- SQL Developer Snippets -- Searching, Replacing, and Validating Text -- Lab 4.1 Exercises -- Lab 4.1 Exercise Answers -- Lab 4.1 Quiz -- LAB 4.2 Number Functions -- The ABS Function -- The SIGN Function -- ROUND and TRUNC Functions -- The FLOOR and CEIL Functions…”

Tabla de Contenidos: “…4 Handling errors without exceptions -- 4.1 The good and bad aspects of exceptions -- 4.2 Possible alternatives to exceptions -- 4.3 The Option data type -- 4.3.1 Usage patterns for Option -- 4.3.2 Option composition, lifting, and wrapping exception-oriented APIs -- 4.4 The Either data type -- 4.4.1 Accumulating errors -- 4.4.2 Extracting a Validated type -- 4.5 Conclusion -- Summary -- 4.6 Exercise answers -- 5 Strictness and laziness -- 5.1 Strict and nonstrict functions -- 5.2 Lazy lists: An extended example -- 5.2.1 Memoizing lazy lists and avoiding recomputation -- 5.2.2 Helper functions for inspecting lazy lists -- 5.3 Separating program description from evaluation -- 5.4 Infinite lazy lists and corecursion -- 5.5 Conclusion -- Summary -- 5.6 Exercise answers -- 6 Purely functional state -- 6.1 Generating random numbers using side effects -- 6.2 Purely functional random number generation -- 6.3 Making stateful APIs pure -- 6.4 A better API for state actions -- 6.4.1 Combining state actions -- 6.4.2 Nesting state actions -- 6.5 A general state action data type -- 6.6 Purely functional imperative programming -- 6.7 Conclusion -- Summary -- 6.8 Exercise Answers -- Part 2. …”

Tabla de Contenidos: “…3.4 Electronic Design Automation (EDA) -- 3.4.1 System-Level Design -- 3.4.2 Logic Synthesis and Physical Design -- 3.4.3 Test, Diagnosis, and Validation -- 3.5 Verification -- 3.6 Challenges -- 3.7 Conclusion -- References -- Chapter 4 IoT-Based Smart Home Security Alert System for Continuous Supervision -- 4.1 Introduction -- 4.2 Literature Survey -- 4.3 Results and Discussions -- 4.3.1 Raspberry Pi-3 B+Module -- 4.3.2 Pi Camera -- 4.3.3 Relay -- 4.3.4 Power Source -- 4.3.5 Sensors -- 4.3.5.1 IR &amp -- Ultrasonic Sensor -- 4.3.5.2 Gas Sensor -- 4.3.5.3 Fire Sensor -- 4.3.5.4 GSM Module -- 4.3.5.5 Buzzer -- 4.3.5.6 Cloud -- 4.3.5.7 Mobile -- 4.4 Conclusions -- References -- Chapter 5 A Detailed Roadmap from Conventional-MOSFET to Nanowire-MOSFET -- 5.1 Introduction -- 5.2 Scaling Challenges Beyond 100nm Node -- 5.3 Alternate Concepts in MOFSETs -- 5.4 Thin-Body Field-Effect Transistors -- 5.4.1 Single-Gate Ultrathin-Body Field-Effect Transistor -- 5.4.2 Multiple-Gate Ultrathin-Body Field-Effect Transistor -- 5.5 Fin-FET Devices -- 5.6 GAA Nanowire-MOSFETS -- 5.7 Conclusion -- References -- Chapter 6 Gate All Around MOSFETs-A Futuristic Approach -- 6.1 Introduction -- 6.1.1 Semiconductor Technology: History -- 6.2 Importance of Scaling in CMOS Technology -- 6.2.1 Scaling Rules -- 6.2.2 The End of Planar Scaling -- 6.2.3 Enhance Power Efficiency -- 6.2.4 Scaling Challenges -- 6.2.4.1 Poly Silicon Depletion Effect -- 6.2.4.2 Quantum Effect -- 6.2.4.3 Gate Tunneling -- 6.2.5 Horizontal Scaling Challenges -- 6.2.5.1 Threshold Voltage Roll-Off -- 6.2.5.2 Drain Induce Barrier Lowering (DIBL) -- 6.2.5.3 Trap Charge Carrier -- 6.2.5.4 Mobility Degradation -- 6.3 Remedies of Scaling Challenges -- 6.3.1 By Channel Engineering (Horizontal) -- 6.3.1.1 Shallow S/D Junction -- 6.3.1.2 Multi-Material Gate -- 6.3.2 By Gate Engineering (Vertical)…”

Tabla de Contenidos: “…Baracca, G.Cantarella , S. Forti, F. Fussi, VALIDATION OF THE ITALIAN VERSION OF THE SINGING VOICE HANDICAP INDEX -- Session IV: VOICE MONITORING -- A. …”

Tabla de Contenidos: “…Chapter 10 Optimizing Prediction of Liver Disease Using Machine Learning Algorithms -- 10.1 Introduction -- 10.2 Related Works -- 10.3 Proposed Methodology -- 10.4 Result and Discussions -- 10.5 Conclusion -- References -- Chapter 11 Optimized Ensembled Model to Predict Diabetes Using Machine Learning -- 11.1 Introduction -- 11.2 Literature Review -- 11.3 Proposed Methodology -- 11.3.1 Missing Value Imputation (MVI) -- 11.3.2 Feature Selection -- 11.3.3 K-Fold Cross-Validation -- 11.3.4 ML Classifiers -- 11.3.5 Evaluation Metrics -- 11.4 Results and Discussion -- 11.5 Concluding Remarks and Future Scope -- References -- Chapter 12 Wearable Gait Authentication: A Framework for Secure User Identification in Healthcare -- 12.1 Introduction -- 12.2 Literature Survey -- 12.3 Proposed System -- 12.3.1 Walking Detection -- 12.3.2 Experimental Setup -- 12.4 Results and Discussion -- 12.4.1 Dataset Used -- 12.4.2 Results -- 12.4.3 Comparison Used Techniques -- 12.5 Conclusion and Future Scope -- References -- Chapter 13 NLP-Based Speech Analysis Using K-Neighbor Classifier -- 13.1 Introduction -- 13.2 Supervised Machine Learning for NLP and Text Analytics -- 13.2.1 Categorization and Classification -- 13.3 Unsupervised Machine Learning for NLP and Text Analytics -- 13.4 Experiments and Results -- 13.5 Conclusion -- References -- Chapter 14 Fusion of Various Machine Learning Algorithms for Early Heart Attack Prediction -- 14.1 Introduction -- 14.2 Literature Review -- 14.3 Materials and Methods -- 14.3.1 Dataset -- 14.3.2 EDA -- 14.3.3 Machine Learning Model Implemented -- 14.4 Result Analysis -- 14.5 Conclusion -- References -- Chapter 15 Machine Learning-Based Approaches for Improving Healthcare Services and Quality of Life (QoL): Opportunities, Issues and Challenges -- 15.1 Introduction…”

Tabla de Contenidos: “…4.2.2.8 Decision Making -- 4.2.2.9 Consumer Nation Identity (CNI) -- 4.2.2.10 Quality of Service -- 4.3 Conclusion -- 4.4 Further Studies -- References -- Chapter 5 A Method for Ranking Fuzzy Numbers Based on Their Value, Ambiguity, Fuzziness, and Vagueness -- 5.1 Introduction -- 5.2 Preliminaries -- 5.2.1 Definitions and Concepts -- 5.3 The Designed Method -- 5.4 Validate the Reasonableness of the Suggested Ranking Algorithm -- 5.5 Comparative Analysis and Numerical Examples -- 5.6 Application -- 5.7 Conclusions -- References -- Chapter 6 Evacuation of Attributes to Translucent TNSET in Mathematics Using Rough Topology -- 6.1 Introduction -- 6.2 Basic Concepts of Rough Topology -- 6.2.1 Conditional Attribute -- 6.2.2 Decision Attribute -- 6.2.3 Rough Topology -- 6.2.4 Lower Approximation -- 6.2.5 Upper Approximation -- 6.2.6 Boundary Region -- 6.2.7 Basis -- 6.2.8 Information System -- 6.2.9 Core -- 6.3 Algorithm -- 6.4 Information System -- 6.5 Working Procedure -- 6.6 Conclusion -- References -- Chapter 7 Design of Type-2 Fuzzy Controller for Hybrid Multi-Area Power System -- 7.1 Introduction -- 7.2 Plant Model -- 7.3 Controller Design -- 7.3.1 Proportional Integral Derivative (PID) Controller -- 7.3.2 Fractional Order Proportional Integral Derivative (FOPID) Controller -- 7.3.3 Type-2-Fuzzy Logic -- 7.4 Levenberg-Marquardt Algorithm -- 7.5 Optimization of Controller Parameters Using CASO Algorithm -- 7.6 Result and Analysis -- 7.6.1 Without Disturbances -- 7.6.2 With Disturbances -- 7.7 Conclusion -- Appendix -- References -- Chapter 8 Alzheimer's Detection and Classification Using Fine-Tuned Convolutional Neural Network -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 Methodology -- 8.3.1 Dataset -- 8.3.2 Pre-Processing -- 8.4 Implementation and Results -- 8.5 Conclusion -- References…”