Tabla de Contenidos: “…78 3.3 LTE meets Demands of Public Safety Networks 79 3.4 Wide Range of LTE Devices for Public Safety 80 3.5 Standalone versus Shared Deployments 81 3.6 Interworking 83 3.6.1 Device Aspects 83 3.6.2 Network Aspects 83 References 83 4 Proximity Services 85 4.1 Introduction to Proximity Services 85 4.1.1 Proximity Services Overview 85 4.1.2 ProSe Communication 86 4.1.3 ProSe Discovery 88 4.1.4 ProSe for Public Safety 88 4.2 Proximity Services Architectures 90 4.2.1 Non-roaming Architecture 90 4.2.2 Inter-PLMN Architecture 91 4.2.3 Roaming Architecture 91 4.2.4 Description of Functional Entities 93 4.2.5 Interfaces and Protocols 97 4.3 Synchronization 104 4.3.1 LTE Primary and Secondary Synchronization Signals 106 4.3.2 LTE D2D Synchronization 107 4.4 Service Authorization 108 4.5 ProSe Direct Discovery 109 4.5.1 ProSe Direct Discovery Models 110 4.5.2 ProSe Direct Discovery Modes 110 4.5.3 Direct Discovery Procedure for Model A 111 4.5.4 Radio Aspects and Physical Layer Design 112 4.5.5 Radio Resource Allocation for Direct Discovery 112 4.5.6 Inter-frequency ProSe Discovery 113 4.5.7 Announce Procedure (non-roaming) 114 4.5.8 Announce Procedure (roaming) 115 4.5.9 Monitor Procedure (non-roaming) 117 4.5.10 Monitor Procedure (roaming) 118 4.5.11 Match Procedure (non-roaming) 120 4.5.12 Match Procedure (roaming) 121 4.5.13 Direct Discovery Procedure for Model B 123 4.6 ProSe Direct Communication 123 4.6.1 Radio Aspects and Physical Layer Design 124 4.6.2 Radio Resource Allocation for Direct Communication 125 4.6.3 Inter-frequency ProSe Communication 127 4.6.4 IP Address Allocation 128 4.6.5 One-to-Many Communication (Transmission) 128 4.6.6 One-to-Many Communication (Reception) 130 4.6.7 Direct Communication via ProSe Relay 130 4.7 EPC-Level ProSe Discovery 131 4.7.1 EPC-Level ProSe Discovery Procedure 132 4.7.2 User Equipment Registration 133 4.7.3 Application Registration 134 4.8 Other Essential Functions for Proximity Services 135 4.8.1 Provisioning 135 4.8.2 Subscription Data 136 4.8.3 Security 136 4.8.4 Charging 138 4.8.5 ProSe-Related Identifiers 140 4.8.6 Illustration for Match Event 144 4.9 Deployment Scenarios 146 4.9.1 ProSe Direct Discovery 146 4.9.2 ProSe Direct Communication 147 4.10 Public Safety Use Cases 147 4.10.1 Use Cases for ProSe Communication 148 4.10.2 Use Cases for Network to UE Relay 149 4.10.3 Performance Characteristics 149 4.11 Outlook to Enhanced Proximity Services 150 4.12 Terms and Definitions 151 4.12.1 Home PLMN 151 4.12.2 Equivalent Home PLMN 151 4.12.3 Visited PLMN 151 4.12.4 Registered (Serving) PLMN 152 4.12.5 Local PLMN 152 4.12.6 Hybrid Adaptive Repeat and Request 152 4.12.7 Radio Link Control 152 4.12.8 Logical Channel Prioritization 153 4.12.9 System Information 153 4.12.10 OFDM Symbol 154 4.12.11 Dual-Rx UE 154 References 154 5 Group Communication Over LTE 157 5.1 Introduction to Group Communication Services 157 5.2 Group Communication System Enablers for LTE 158 5.3 Principles of Group Communication over LTE 159 5.4 Functional Entities 162 5.4.1 User Equipment 162 5.4.2 GCS AS 162 5.4.3 BM-SC 163 5.4.4 eNB, MME, S-GW, P-GW, PCRF 163 5.5 Interfaces and Protocols 163 5.5.1 MB2 Interface 163 5.5.2 Rx and SGi Interfaces 167 5.6 GCSE Functions 169 5.6.1 Unicast Delivery 169 5.6.2 MBMS Delivery 171 5.6.3 Service Continuity 172 5.6.4 Priority and Preemption 173 5.6.5 MBMS Delivery Status Notification 175 5.7 Establishment of MBMS Delivery 175 5.7.1 Pre-establishment 175 5.7.2 Dynamic Establishment 176 5.8 MBMS Delivery Procedures 179 5.8.1 MBMS Delivery Modification 179 5.8.2 MBMS Delivery Deactivation 181 5.8.3 TMGI Management 182 5.9 Access Control 183 5.10 Mission Critical Push To Talk 185 5.10.1 MCPTT Service Description 186 5.10.2 MCPTT Call Types 187 5.10.3 MCPTT Priorities 187 5.10.4 Shareable MCPTT Devices 188 5.10.5 On and Off Network Mode of Operation 188 5.10.6 Interworking with legacy PTT Systems 189 References 189 6 Summary and Outlook 191 6.1 Role of LTE 191 6.2 Public Safety Features 192 6.3 LTE for Public Safety 193 6.4 Outlook 196 References 196 Appendix A 197 A.1 Call Flows 197 A.1.1 Attach 197 A.1.2 Detach 200 A.1.3 Tracking Area Update 201 A.1.4 Paging 202 A.1.5 Service Request 203 A.1.6 X2-Based Handover 205 A.1.7 S1-Based Handover 206 A.1.8 MBMS Session Start 210 A.1.9 MBMS Session Stop 212 A.1.10 MBMS Session Update 213 A.1.11 UE-requested PDN Connectivity 214 A.1.12 Dedicated Bearer Context Activation 216 A.2 3GPP Reference Points 217 References 221 Index 223 …”

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: “…The Art of Money Getting (P.T. Barnum) -- Contents -- Introduction -- 1. …”

Tabla de Contenidos: “…Front cover -- Contents -- Figures -- Tables -- Examples -- Notices -- Trademarks -- Preface -- The team that wrote this redbook -- Become a published author -- Comments welcome -- Chapter 1. e-Business Intelligence and DB2 UDB ESE -- 1.1 Business issues and challenges -- 1.1.1 Build larger and larger data warehouses -- 1.1.2 Load and populate the data warehouse as fast as possible -- 1.1.3 Perform queries with performances -- 1.1.4 Operate in a 24 hours/7 days mode -- 1.1.5 Manage the data warehouse -- 1.1.6 Upgrade the data warehouse -- 1.1.7 Summary -- 1.2 DB2 UDB V8.1 functions for e-Business Intelligence -- 1.2.1 Performance enhancements -- 1.2.2 Availability enhancements -- 1.2.3 Manageability enhancements -- 1.2.4 UNION ALL views -- 1.3 New functionalities of IBM e-server p690 -- 1.3.1 Hardware overview -- 1.3.2 Logical partitioning for OLTP-aware e-BI -- 1.3.3 Cluster 1600 -- 1.3.4 Enhancements with AIX V5.2 -- 1.3.5 Workload management -- 1.4 Case study and technical environment -- 1.4.1 The case study based on TPC-H -- 1.4.2 Technical environment -- Chapter 2. …”

Tabla de Contenidos: “…Estrategia y competitividad (P4IC3)C -- 1. Estrategia -- 1.1. Historia -- 1.2. …”

Tabla de Contenidos: “…-- 5.4 The Sampling Design Process -- 5.5 Random Versus Non-Random Sampling -- 5.6 Random Sampling Methods -- 5.7 Non-Random Sampling -- 5.8 Sampling and Non-Sampling Errors -- 5.9 Sampling Distribution -- 5.10 Central Limit Theorem -- 5.11 Sample Distribution of Sample Proportion p -- Summary -- Key Terms -- Discussion Questions -- Numerical Problems -- Case Study -- III Sources and Collection of Data -- 6 Secondary Data Sources -- 6.1 Introduction -- 6.2 Meaning of Primary and Secondary Data…”

“…Lo suyo lleva una impronta. Es lo que V. P. sabe y ha experimentado del tema ; y la erudición, lo que han dicho los demás, lo ha digerido, ha pasado por su tamiz, lo ha incorporado, le ha dado su molde. …”

“…Este trabajo posibilita el enlace de las cuestines más clásicas y tradicionales en CTS con las últimas innovaciones, p ara lo cual ha sido preciso un laboriosos plan de investigación internacional con autores correspondientes a las universidades de mayor prestigio e historia en los estudios CTS de diferentes países, como lo avalan ldos paortaciones inéditas hasta ahora y exclusivas para este libro: el prólogo de Carl Mitcham y el epílogo de Wiebe E. …”

“…The combination of these technological advances make it possible to efficiently study the inter-dependency of AQPs, regulation through phosphorylation and reversible phosphorylation, networking with other transporters, structural features, pH gating systems, trafficking and degradation. …”

“…Vallon, des inconditionnels de l’Association nationale rassemblés autour de P. Lefranc ou des partisans de l’ordre qui rejoignent les CDR en mai 1968. …”

“…Exception au XVIe siècle, par là même anticipation du XVIe siècle : c'est faire de l'étude de Valladolid une contribution à la recherche des origines de la décadence espagnole. » Jean-Pierre Amalric, Annales ESC, septembre-octobre 1971, p. 982-1002. Avec « Les Réimpressions » des titres du fonds des Éditions de l'EHESS, publiés des années 1950 aux années 1970 sous l'égide de la VI" Section de l'École Pratique des Hautes Études, sont à nouveau disponibles. …”

“…However, for professional developers, it is important to note that the book will not focus on advanced use cases with features like using public APIs and 3P integrations. No programming knowledge or experience is needed to start creating basic apps. …”

“…Além disso, acrescentei-lhe algumas notas que me foram sugeridas durante a sessão, que teve no início a intervenção dos ex-directores da Imprensa depois da sua refundação em 1998, Doutores Fernando Regateiro, José Faria e Costa e João GouveiaMonteiro, sob o tema “Desafios e perspetivas das editorasuniversitárias na actualidade”, dado que a IUC foi extintaem 1934 pelo governo de Salazar, quando era seu administradoro Doutor Joaquim de Carvalho e em que era publicado,já com data de 1935, o livro Amor Místico, da autoriado meu mestre, que sempre recordo, Doutor Sílvio Lima.</p>Inicio, porém, a publicação destes apontamentos, comofiz na sessão, com uma homenagem póstuma ao reitor queacabou por refundar a IUC e que recebeu neste ano o prémio“Joaquim de Carvalho”: o Doutor Fernando Rebelo, meu colegados bancos da Faculdade, meu adversário vitorioso naseleições para reitor em 1998 e meu amigo, que guardo namemória daqueles que vão partindo. …”

“…You can download the example code files for all Packt books you have purchased from your account at http://www.PacktP..…”

“…Yiqiao Yin is a senior data scientist at an S&P 500 company LabCorp, developing AI-driven solutions for drug diagnostics and development. …”

“…A simple quote from Mr. J. P. Morgan is used often in this text - "Lending is not based primarily on money or property. …”

“…Rob is a registered professional engineer (P.Eng) and has worked in the IT industry for more than 20 years, the last 17 of which have been at Cisco. …”

“…You can start building flows between Kafka and ElasticSearch, an FT,P and MongoDB, and so much more! Your imagination is the limit This course will take you through the Apache NiFi technology. …”

“…Yiqiao Yin is a senior data scientist at an S&P 500 company LabCorp, developing AI-driven solutions for drug diagnostics and development. …”

Tabla de Contenidos: “…. ; Fol. Se ha respetado la p ntuación original. Sign.: 2E4-2N4, 2O7. …”