Tabla de Contenidos: “…Background -- 2. Methods -- 2.1. Minimizing inter-host transmissions -- 2.2. Description of TreeFix-TP -- 2.3. …”

Tabla de Contenidos: “…Intro -- Preface -- Organisation -- Table of Contents -- Communication in Automation -- TSN basierte automatisch etablierte Redundanz für deterministische Kommunikation -- 1 Einleitung -- 2 Mechanismen für Quality of Service (QoS) -- 3 Industrielle Anforderungen an Echtzeitkommunikation -- 3.1 Latenz -- 3.2 Verfügbarkeit -- 4 Stream Reservation -- 5 Redundante Stream Reservierung -- 5.1 End-to-End Frame Replication and Elimination for Reliability (E2E FRER) -- 5.2 Network Frame Replication and Elimination for Reliability (Network-FRER) -- 6 Fazit -- Literatur -- Arduino based Framework for Rapid Application Development of a Generic IO-Link interface -- 1 Introduction -- 2 Framework overview -- 3 Firmware -- 4 GUI -- 5 Hardware interface -- 6 Proof of concept -- 6.1 IO-Link distance sensor -- 7 Conclusions -- References -- On the suitability of 6TiSCH for industrial wireless communication -- 1 Introduction -- 2 Overview of 6TiSCH-stack -- 2.1 Time Slotted Channel Hopping -- 2.2 Routing protocol RPL -- 2.3 6TiSCH-WG standardization activities -- 3 Challenges -- Challenge 1: Convergence on industrial concerns -- Challenge 2: Avoidance of specification implementation mismatches -- Challenge 3: Design of the management architecture scheme -- Challenge 4: Concurrence of other wireless technologies -- 4 Analysis and Improvements of the 6TiSCH minimal configuration -- 4.1 6TiSCH network formation procedure -- 4.2 Shortcomings of 6TiSCH-MC -- 4.3 Improvements of 6TiSCH-MC -- 4.4 Diagonal: Our improvement proposal for 6TiSCH-MC -- 5 Conclusions -- References -- Ein dezentraler Regelalgorithmus für ein automatisches Koexistenzmanagement -- 1 Einführung -- 2 Der Betrachtungsraum als Regelkreis -- 3 Modellierung der Regelstrecke zur Koexistenz -- 4 Modellierung eines dezentralen Regleralgorithmusses -- 5 Validierung des Modells für die dezentrale Regelung…”

Tabla de Contenidos: “…2.6-2.10 From the Bottom Up: The Structures of the Brain -- 2.6 The Hindbrain -- 2.7 Structures Under the Cortex: The Limbic System -- 2.8 The Cortex -- 2.9 The Association Areas of the Cortex -- Classic Studies in Psychology: Through the Looking Glass-Spatial Neglect -- 2.10 The Cerebral Hemispheres -- 2.11-2.12 The Nervous System: the Rest of the Story -- 2.11 The Central Nervous System: The "Central Processing Unit" -- 2.12 The Peripheral Nervous System: Nerves on the Edge -- 2.13-2.14 the Endocrine Glands -- 2.13 the Pituitary: Master of the Hormonal Universe -- 2.14 Other Endocrine Glands -- APA Goal 2: Scientific Inquiry and Critical Thinking: Phineas Gage and Neuroplasticity -- Applying Psychology to Everyday Life: Minimizing the Impact of Adult Attention-Deficit/Hyperactivity Disorder -- Chapter Summary -- Test Yourself -- 3 Sensation and Perception -- 3.1-3.3 The Abcs of Sensation -- 3.1 Transduction -- 3.2 Sensory Thresholds -- 3.3 Habituation and Sensory Adaptation -- 3.4-3.6 The Science of Seeing -- 3.4 Light and the Eye -- 3.5 The Visual Pathway -- 3.6 Perception of Color -- 3.7-3.9 The Hearing Sense: Can You Hear Me Now? …”

Tabla de Contenidos: “…Optimizing Job Scheduling Console performance -- 7.1 Factors affecting the Job Scheduling Console performance -- 7.2 Applying the latest fixes -- 7.3 Resource requirements -- 7.4 Setting the refresh rate -- 7.5 Setting the buffer size -- 7.6 Minimize the JSC windows to force the garbage collector to work -- 7.7 Number of open editors -- 7.8 Number of open windows -- 7.9 Applying filters and propagating to JSC users -- 7.10 Java tuning -- 7.11 Startup script -- Chapter 8. …”

Tabla de Contenidos: “…MCOD installation and merge using SAP tools -- 3.1 Introduction -- 3.1.1 SAP Basis Releases 4.6C and 4.6D -- 3.1.2 SAP Basis Releases 6.10 and later -- 3.2 Installing a new component -- 3.2.1 SAP Basis Releases 4.6C and 4.6D -- 3.2.2 SAP Basis Releases 6.10 and later -- 3.3 Merging components into an MCOD landscape -- 3.3.1 SAP Basis Releases 4.6C and 4.6D -- 3.3.2 SAP Basis Release 6.10 and later -- 3.4 Steps after installation or merge -- 3.5 Minimizing migration down time -- 3.5.1 Incremental migration -- 3.5.2 Merging without moving the data -- Chapter 4. …”

Tabla de Contenidos: “…9.5 Radio Resource Management 124 -- 9.6 Coverage and Capacity 125 -- 9.6.1 Coverage Gain 126 -- 9.6.2 User Throughput Gains 128 -- 9.6.3 Cost Analysis 129 -- 9.7 Relay Enhancements 130 -- 9.8 Summary 132 -- References 132 -- 10 Self-Organizing Networks (SON) 135 /Cinzia Sartori and Harri Holma -- 10.1 Introduction 135 -- 10.2 SON Roadmap in 3GPP Releases 135 -- 10.3 Self-Optimization 137 -- 10.3.1 Mobility Robustness Optimization 137 -- 10.3.2 Mobility Load Balancing 142 -- 10.3.3 Minimization of Drive Tests 142 -- 10.3.4 MDT Management and Reporting 144 -- 10.3.5 Energy Savings 145 -- 10.3.6 eNodeB Overlay 146 -- 10.3.7 Capacity-Limited Network 147 -- 10.3.8 Capacity and Coverage Optimization 148 -- 10.4 Self-Healing 150 -- 10.4.1 Cell Outage Compensation 150 -- 10.5 SON Features in 3GPP Release 11 151 -- 10.6 Summary 151 -- References 152 -- 11 Performance Evaluation 153 /Harri Holma and Klaus Pedersen -- 11.1 Introduction 153 -- 11.2 LTE-Advanced Targets 154 -- 11.2.1 ITU Evaluation Environments 155 -- 11.3 LTE-Advanced Performance Evaluation 156 -- 11.3.1 Peak Data Rates 156 -- 11.3.2 UE Categories 157 -- 11.3.3 ITU Efficiency Evaluation 158 -- 11.3.4 3GPP Efficiency Evaluation 160 -- 11.4 Network Capacity and Coverage 163 -- 11.5 Summary 165 -- References 165 -- 12 Release 11 and Outlook Towards Release 12 166 /Timo Lunttila, Rapeepat Ratasuk, Jun Tan, Amitava Ghosh and Antti Toskala -- 12.1 Introduction 166 -- 12.2 Release 11 LTE-Advanced Content 166 -- 12.3 Advanced LTE UE Receiver 168 -- 12.3.1 Overview of MMSE-MRC and MMSE-IRC Methods 169 -- 12.3.2 Performance of UE Receiver using IRC and its Comparison -- to MRC Receiver for Various DL Transmit Modes 170 -- 12.4 Machine Type Communications 172 -- 12.5 Carrier Aggregation Enhancements 177 -- 12.6 Enhanced Downlink Control Channel 179 -- 12.7 Release 12 LTE-Advanced Outlook 181 -- 12.8 Conclusions 183 -- References 183 -- 13 Coordinated Multipoint Transmission and Reception 184 /Harri Holma, Kari Hooli, Pasi Kinnunen, Troels Kolding, PatrickMarsch and Xiaoyi Wang…”

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…”