Tabla de Contenidos: “…9.9 Lehmann-SchefféTheorem -- 9.10 Bayes Estimation -- 9.11 Mean-Square-Error Estimation -- 9.12 Mean-Absolute-Error Estimation -- 9.13 Orthogonality Condition -- 9.14 Properties of Estimators -- 9.14.1 Unbiased -- 9.14.2 Consistent -- 9.14.3 Efficient -- 9.15 Maximum A Posteriori Estimation -- 9.16 Maximum Likelihood Estimation -- 9.17 Likelihood Ratio Test -- 9.18 Expectation-Maximization Algorithm -- 9.19 Method of Moments -- 9.20 Least-Squares Estimation -- 9.21 Properties of LS Estimators -- 9.21.1 Minimum ξWLS -- 9.21.2 Uniqueness -- 9.21.3 Orthogonality -- 9.21.4 Unbiased -- 9.21.5 Covariance Matrix -- 9.21.6 Efficient: Achieves CRLB -- 9.21.7 BLU Estimator -- 9.22 Best Linear Unbiased Estimation -- 9.23 Properties of BLU Estimators -- Problems -- Further Reading -- A Note on Part III of the Book -- APPENDICES Introduction to Appendices -- A Summaries of Univariate Parametric Distributions -- A.1 Notation -- A.2 Further Reading -- A.3 Continuous Random Variables -- A.3.1 Beta (Arcsine for α = β = 1/2, Power Function for β = 1) -- A.3.2 Cauchy -- A.3.3 Chi -- A.3.4 Chi-Square -- A.3.5 Exponential (Shifted by c) -- A.3.6 Extreme Value (Type I: Gumbel) -- A.3.7 F-Distribution -- A.3.8 Gamma (Erlang for r ∈ N with Γ (r ) = (r - 1)!) …”

Tabla de Contenidos: “…-- Preface xxi / /Acknowledgments xxv / /Summary of Notations xxvii / /About the Cover xxix / /About the Companion Website xxxi / /1 Mathematical Background and Analysis Techniques 1 / /1.1 Introduction 1 / /1.2 The Fourier Transform and Fourier Series 5 / /1.3 Pulse Distortion with Ideal Filter Models 16 / /1.4 Correlation Processing 19 / /1.5 Random Variables and Probability 20 / /1.6 Random Processes 41 / /1.7 The Matched Filter 44 / /1.8 The Likelihood and Log-Likelihood Ratios 46 / /1.9 Parameter Estimation 47 / /1.10 Modem Configurations and Automatic Repeat Request 55 / /1.11 Windows 57 / /1.12 Matrices Vectors and Related Operations 66 / /1.13 Often Used Mathematical Procedures 70 / /1.14 Often Used Mathematical Relationships 71 / /2 Digital Signal Processing and Modem Design Considerations 81 / /2.1 Introduction 81 / /2.2 Discrete Amplitude Sampling 81 / /2.3 Discrete-Time Sampling 87 / /2.4 Signal Reconstruction Following Discrete-Time Sampling 91 / /2.5 Baseband Sampling 92 / /2.6 Bandpass Sampling 92 / /2.7 Corrections for Nonideal Modulators and Demodulators 99 / /2.8 Multirate Signal Processing and Interpolation 106 / /Appendix 2A Amplitude Quantization Function Subprogram 121 / /Appendix 2B Hilbert Transform Parameters 122 / /Appendix 2C Derivation of Parabolic Interpolation Error 126 / /3 Digital Communications 133 / /3.1 Introduction 133 / /3.2 Digital Data Modulation and Optimum Demodulation Criteria 135 / /3.3 Information and Channel Capacity 139 / /3.4 Bit-Error Probability Bound on Memoryless Channel 148 / /3.5 Probability Integral and the Error Function 150 / /4 Phase Shift Keying (PSK) Modulation Demodulation and Performance 153 / /4.1 Introduction 153 / /4.2 Constant Envelope Phase-Modulated Waveforms 154 / /4.3 Non-Constant Envelope Phase-Modulated Waveforms 175 / /4.4 Phase-Modulated Waveform Spectrums and Performance 178 / /5 Frequency Shift Keying (FSK) Modulation Demodulation and Performance 207 / /5.1 Introduction 207 / /5.2 Coherent Detection of BFSK - Known Frequency and Phase 207 / /5.3 Noncoherent Detection of BFSK - Known Frequency and Unknown Phase 210 / /5.4 Case Studies: Coherent and Noncoherent BFSK Performance Simulation 211 / /5.5 Noncoherent Detection of BFSK - Unknown Frequency and Phase 214 / /5.6 BFSK Spectral Density with Arbitrary Modulation Index 219 / /6 Amplitude Shift Keying Modulation Demodulation and Performance 227 / /6.1 Introduction 227 / /6.2 Amplitude Shift Keying (ASK) 227 / /6.3 Quadrature Amplitude Modulation (QAM) 234 / /6.4 Alternate QAM Waveform Constellations 236 / /6.5 Case Study: 16-ary QAM Performance Evaluation 236 / /6.6 Partial Response Modulation 237 / /7 M-ary Coded Modulation 251 / /7.1 Introduction 251 / /7.2 Coherent Detection of Orthogonal Coded Waveforms 252 / /7.3 Noncoherent Detection of M-ary Orthogonal Waveforms 253 / /7.4 Coherent Detection of M-ary Biorthogonal Waveforms 256 / /8 Coding for Improved Communications 261 / /8.1 Introduction 261 / /8.2 Pulse Code Modulation 261 / /8.3 Gray Coding 268 / /8.4 Differential Coding 269 / /8.5 Pseudo-Random Noise Sequences 270 / /8.6 Binary Cyclic Codes 273 / /8.7 Cyclic Redundancy Check Codes 274 / /8.8 Data Randomizing Codes 276 / /8.9 Data Interleaving 277 / /8.10 Wagner Coding and Decoding 279 / /8.11 Convolutional Codes 283 / /8.12 Turbo and Turbo-Like Codes 299 / /8.13 LDPC Code and TPC 313 / /8.14 Bose-Chaudhuri-Hocquenghem Codes 315 / /Appendix 8A 328 / /Appendix 8B 329 / /9 Forward Error Correction Coding Without Bandwidth Expansion 339 / /9.1 Introduction 339 / /9.2 Multi-h M-ary CPM 340 / /9.3 Case Study: 2-h 4-ary 1REC CPM 350 / /9.4 Multiphase Shift Keying Trellis-Coded Modulation 362 / /9.5 Case Study: Four-State 8PSK-TCM Performance Over Satellite Repeater 367 / /10 Carrier Acquisition and Tracking 375 / /10.1 Introduction 375 / /10.2 Bandpass Limiter 377 / /10.3 Baseband Phaselock Loop Implementation 378 / /10.4 Phase-Error Generation 378 / /10.5 First-Order Phaselock Loop 380 / /10.6 Second-Order Phaselock Loop 380 / /10.7 Third-Order Phaselock Loop 390 / /10.8 Optimum Phase Tracking Algorithms 396 / /10.9 Squaring Loss Evaluation 406 / /10.10 Case Study: BPSK and QPSK Phaselock Loop Performance 408 / /10.11 Case Study: BPSK Phase Tracking Performance of a Disadvantaged Transmit Terminal 410 / /11 Waveform Acquisition 413 / /11.1 Introduction 413 / /11.2 CW Preamble Segment Signal Processing 416 / /11.3 Symbol Synchronization Preamble Segment 432 / /11.4 Start-of-Message (SOM) Preamble segment 452 / /11.5 Signal-to-Noise Ratio Estimation 452 / /12 Adaptive Systems 463 / /12.1 Introduction 463 / /12.2 Optimum Filtering - Wiener's Solution 464 / /12.3 Finite Impulse Response-Adaptive Filter Estimation 465 / /12.4 Intersymbol Interference and Multipath Equalization 469 / /12.5 Interference and Noise Cancellation 472 / /12.6 Recursive Least Square (RLS) Equalizer 473 / /12.7 Case Study: LMS Linear Feedforward Equalization 474 / /12.8 Case Study: Narrowband Interference Cancellation 474 / /12.9 Case Study: Recursive Least Squares Processing 480 / /13 Spread-Spectrum Communications 485 / /13.1 Introduction 485 / /13.2 Spread-Spectrum Waveforms and Spectrums 487 / /13.3 Jammer and Interceptor Encounters 499 / /13.4 Communication Interceptors 502 / /13.5 Bit-Error Performance of DSSS Waveforms with Jamming 504 / /13.6 Performance of MFSK with Partial-Band Noise Jamming 512 / /13.7 Performance of DCMPSK with Partial-Band Noise Jamming 514 / /13.8 FHSS Waveforms with Multitone Jamming 515 / /13.9 Approximate Performance with Jammer Threats 521 / /13.10 Case Study: Terrestrial Jammer Encounter and Link-Standoff Ratio 522 / /14 Modem Testing Modeling and Simulation 531 / /14.1 Introduction 531 / /14.2 Statistical Sampling 532 / /14.3 Computer Generation of Random Variables 539 / /14.4 Baseband Waveform Description 545 / /14.5 Sampled Waveform Characterization 547 / /14.6 Case Study: BPSK Monte Carlo Simulation 548 / /14.7 System Performance Evaluation Using Quadrature Integration 550 / /14.8 Case Study: BPSK Bit-Error Evaluation with PLL Tracking 551 / /14.9 Case Study: QPSK Bit-Error Evaluation with PLL Tracking 553 / /15 Communication Range Equation and Link Analysis 557 / /15.1 Introduction 557 / /15.2 Receiver and System Noise Figures and Temperatures 560 / /15.3 Antenna Gain and Patterns 568 / /15.4 Rain Loss 571 / /15.5 Electric Field Wave Polarization 573 / /15.6 Phase-Noise Loss 578 / /15.7 Scintillation Loss 583 / /15.8 Multipath Loss 583 / /15.9 Interface Mismatch Loss 584 / /15.10 Miscellaneous System Losses 585 / /15.11 Nonlinear Power Amplifier Analysis and Simulation 585 / /15.12 Computer Modeling of TWTA and SSPA Nonlinearities 588 / /15.13 Establishing Signal Levels for Simulation Modeling 590 / /15.14 Case Study: Performance Simulation of SRRC-QPSK with SSPA Nonlinearity 592 / /15.15 Link Budget Analysis 596 / /16 Satellite Orbits 603 / /16.1 Introduction 603 / /16.2 Satellite Orbits 606 / /16.3 Earth Stations 607 / /16.4 Path Loss Doppler and Doppler-rate 609 / /16.5 Satellite Viewing 609 / /16.6 Satellite Orbit Selection 610 / /16.7 Satellite Orbit Position Estimation From Parameter Measurements 611 / /16.8 Case Study: Example Satellite Encounters 612 / /17 Communications Through Bandlimited Time-Invariant Linear Channels 617 / /17.1 Introduction 617 / /17.2 Inphase and Quadrature Channel Response 618 / /17.3 Inphase and Quadrature Channel Response to Arbitrary Signal 619 / /17.4 Pulse Modulated Carrier Signal Characteristics 621 / /17.5 Channel Response to a Pulsed Modulated Waveform 622 / /17.6 Example Performance Simulations 623 / /17.7 Example of Channel Amplitude and Phase Responses 624 / /17.8 Example Channel Amplitude Phase and Delay Functions 627 / /18 Communications in Fading Environments 633 / /18.1 Introduction 633 / /18.2 Ricean Fading Channels 634 / /18.3 Ricean Cumulative Distribution 635 / /18.4 Application of Ricean Channel Model 635 / /18.5 Performance of Several Binary Modulation…”

Tabla de Contenidos:

Tabla de Contenidos: “…3.3.2 Dimensionality Reduction -- 3.4 Importance of Dimensionality Reduction in Machine Learning -- 3.4.1 Methods of Dimensionality Reduction -- 3.4.1.1 Principal Component Analysis (PCA) -- 3.4.1.2 Linear Discriminant Analysis (LDA) -- 3.4.1.3 Generalized Discriminant Analysis (GDA) -- 3.5 Distance Measures -- 3.6 Clustering -- 3.6.1 Algorithms in Clustering -- 3.6.2 Applications of Clustering -- 3.6.3 Iterative Distance-Based Clustering -- 3.7 Hierarchical Model -- 3.8 Density-Based Clustering -- 3.8.1 DBSCAN -- 3.8.2 OPTICS -- 3.9 Role of Machine Learning in Factories of the Future -- 3.10 Identification of the Probable Customers -- 3.11 Conclusion -- References -- Chapter 4 Understanding Neural Networks -- 4.1 Introduction -- 4.2 Components of Neural Networks -- 4.2.1 Neurons -- 4.2.2 Synapses and Weights -- 4.2.3 Bias -- 4.2.4 Architecture of Neural Networks -- 4.2.5 How Do Neural Networks Work? …”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright -- Contents -- Preface -- About the Author -- About the Companion Website -- Chapter 1 Foundations of Convective Heat Transfer -- 1.1 Fundamental Concepts -- 1.2 Coordinate Systems -- 1.3 The Continuum and Thermodynamic Equilibrium Concepts -- 1.4 Velocity and Acceleration -- 1.5 Description of a Fluid Motion: Eulerian and Lagrangian Coordinates and Substantial Derivative -- 1.5.1 Lagrangian Approach -- 1.5.2 Eulerian Approach -- 1.6 Substantial Derivative -- 1.7 Conduction Heat Transfer -- 1.8 Fluid Flow and Heat Transfer -- 1.9 External Flow -- 1.9.1 Velocity Boundary Layer and Newton's Viscosity Relation -- 1.9.2 Thermal Boundary Layer -- 1.10 Internal Flow -- 1.10.1 Mean Velocity -- 1.10.2 Mean Temperature -- 1.11 Thermal Radiation Heat Transfer -- 1.12 The Reynolds Transport Theorem: Time Rate of Change of an Extensive Property of a System Expressed in Terms of a Fixed Finite Control Volume -- Problems -- References -- Chapter 2 Fundamental Equations of Laminar Convective Heat Transfer -- 2.1 Introduction -- 2.2 Integral Formulation -- 2.2.1 Conservation of Mass in Integral Form -- 2.2.2 Conservation of Linear Momentum in Integral Form -- 2.2.3 Conservation of Energy in Integral Form -- 2.3 Differential Formulation of Conservation Equations -- 2.3.1 Conservation of Mass in Differential Form -- 2.3.1.1 Cylindrical Coordinates -- 2.3.1.2 Spherical Coordinates -- 2.3.2 Conservation of Linear Momentum in Differential Form -- 2.3.2.1 Equation of Motion for a Newtonian Fluid with Constant Dynamic Viscosity μ and Density ρ -- 2.3.2.2 Cartesian Coordinates (x, y, z) -- 2.3.2.3 Cylindrical Coordinates (r, θ, z) -- 2.3.2.4 Spherical Coordinates (r, θ, φ) -- 2.3.3 Conservation of Energy in Differential Form -- 2.3.3.1 Mechanical Energy Equation -- 2.3.3.2 Thermal Energy Equation…”

Tabla de Contenidos: “…An Overview of the Android Architecture -- 9.1 The Android Software Stack -- 9.2 The Linux Kernel -- 9.3 Android Runtime - ART -- 9.4 Android Libraries -- 9.4.1 C/C++ Libraries -- 9.5 Application Framework -- 9.6 Applications -- 9.7 Summary -- 10. …”

Tabla de Contenidos:

Tabla de Contenidos: “…Using CM as a repository for LWWCM -- 6.1 Configuring LWWCM to use CM as a data repository -- 6.1.1 Prerequisites -- 6.1.2 Modifying the WebSphere Application Server JVM setting -- 6.1.3 Modifying LWWCM's aptrixjpe.properties file -- 6.1.4 Deleting existing indexes from the LWWCM server -- 6.1.5 Starting LWWCM and running the initial setup -- 6.1.6 Troubleshooting -- 6.2 Accessing a remote Library Server database -- 6.3 LWWCM server routing information to access CM -- 6.3.1 The aptrixjpe.properties file -- 6.3.2 Files cmbicmsrvs.ini and cmbds.ini -- 6.3.3 Testing the ICM and FED connectors -- 6.4 How LWWCM objects are stored in CM…”

Tabla de Contenidos: “…Create a Custom Query with where clauses -- What this exercise is about -- What you should be able to do -- Required materials -- Exercise instructions -- Create a query library -- Create a query -- LAB 6. Create and install software packages for Windows -- What this exercise is about -- What you should be able to do -- Required materials -- Exercise instructions -- Install the Software Package Editor -- Create a simple package -- Test the software package -- Import the software package -- Install the software package -- Verify the distribution was successful -- Install software package in transactional mode and commit installation -- Undo an installation -- Repair a damaged distribution -- Add links, registry keys, and text file objects -- LAB 7. …”

Tabla de Contenidos: “…-- 6.3 A Brief History and Background -- 6.4 Overview -- 6.5 JSP Lifecycle -- 6.5.1 JSP Service Methods -- 6.6 Elements in a JSP Page -- 6.6.1 Declarations -- 6.6.2 Directives -- 6.6.3 Scriptlets -- 6.6.4 Expressions -- 6.6.5 Transfer Control -- 6.7 Implicit JSP Objects -- 6.8 JSP Object Scopes -- 6.9 FavConnect Example Modified -- 6.10 JSP Tags -- 6.10.1 Declarations -- 6.10.2 Directives -- 6.11 JSP Exceptions -- 6.11.1 Expressions -- 6.11.2 Scriptlet -- 6.11.3 Actions -- 6.12 Expression Language (EL) -- 6.13 JSP Standard Tag Library -- 6.14 A JSP Example -- 6.15 Custom Tag Library…”

Tabla de Contenidos: “…-- 1.10.1 Latest generation -- 1.10.2 Multiplatform and open source -- 1.10.3 Rapid development -- 1.10.4 Well supported -- 1.10.5 Access to NuGet libraries -- 1.10.6 Fully featured O/RM -- 1.10.7 Stable library -- 1.10.8 Always high-performance -- 1.11 When should you not use EF Core? …”

Tabla de Contenidos: “…5.3.1 Altering a component's dimensions with flex -- 5.3.2 Specifying the direction of the flex with flexDirection -- 5.3.3 Defining how space is used around a component with justifyContent -- 5.3.4 Aligning children in a container with alignItems -- 5.3.5 Overriding the parent container's alignment with alignSelf -- 5.3.6 Preventing clipped items with flexWrap -- Summary -- Chapter 6: Navigation -- 6.1 React Native navigation vs. web navigation -- 6.2 Building a navigation-based app -- 6.3 Persisting data -- 6.4 Using DrawerNavigator to create drawer-based navigation -- Summary -- Chapter 7: Animations -- 7.1 Introducing the Animated API -- 7.2 Animating a form input to expand on focus -- 7.3 Creating a custom loading animation using interpolation -- 7.4 Creating multiple parallel animations -- 7.5 Creating an animated sequence -- 7.6 Using Animated.stagger to stagger animation start times -- 7.7 Other useful tips for using the Animated library -- 7.7.1 Resetting an animated value -- 7.7.2 Invoking a callback -- 7.7.3 Offloading animations to the native thread -- 7.7.4 Creating a custom animatable component using createAnimatedComponent -- Summary -- Chapter 8: Using the Redux data architecture library -- 8.1 What is Redux? …”

Tabla de Contenidos: “…An Overview of the Android Architecture -- 9.1 The Android Software Stack -- 9.2 The Linux Kernel -- 9.3 Android Runtime - ART -- 9.4 Android Libraries -- 9.4.1 C/C++ Libraries -- 9.5 Application Framework -- 9.6 Applications -- 9.7 Summary -- 10. …”

Tabla de Contenidos: “…3.1 Models as tools for deeper insight -- 3.1.1 Models are simplifications -- 3.1.2 Models are strict -- 3.1.3 Models capture deep understanding -- 3.1.4 Making a model means choosing one -- 3.1.5 The model forms the ubiquitous language -- 3.2 Building blocks for your model -- 3.2.1 Entities -- 3.2.2 Value objects -- 3.2.3 Aggregates -- 3.3 Bounded contexts -- 3.3.1 Semantics of the ubiquitous language -- 3.3.2 The relationship between language, model, and bounded context -- 3.3.3 Identifying the bounded context -- 3.4 Interactions between contexts -- 3.4.1 Sharing a model in two contexts -- 3.4.2 Drawing a context map -- Summary -- 4 Code constructs promoting security -- 4.1 Immutability -- 4.1.1 An ordinary webshop -- 4.2 Failing fast using contracts -- 4.2.1 Checking preconditions for method arguments -- 4.2.2 Upholding invariants in constructors -- 4.2.3 Failing for bad state -- 4.3 Validation -- 4.3.1 Checking the origin of data -- 4.3.2 Checking the size of data -- 4.3.3 Checking lexical content of data -- 4.3.4 Checking the data syntax -- 4.3.5 Checking the data semantics -- Summary -- 5 Domain primitives -- 5.1 Domain primitives and invariants -- 5.1.1 Domain primitives as the smallest building blocks -- 5.1.2 Context boundaries define meaning -- 5.1.3 Building your domain primitive library -- 5.1.4 Hardening APIs with your domain primitive library -- 5.1.5 Avoid exposing your domain publicly -- 5.2 Read-once objects -- 5.2.1 Detecting unintentional use -- 5.2.2 Avoiding leaks caused by evolving code -- 5.3 Standing on the shoulders of domain primitives -- 5.3.1 The risk with overcluttered entity methods -- 5.3.2 Decluttering entities -- 5.3.3 When to use domain primitives in entities -- 5.4 Taint analysis -- Summary -- 6 Ensuring integrity of state -- 6.1 Managing state using entities -- 6.2 Consistent on creation…”

Tabla de Contenidos: “…Working with Bookmarks -- Downloading and Viewing Files -- Saving Web Pages -- Customizing Safari's Toolbar -- Quitting Safari -- 8 Keeping Your Address Book and Schedule -- Using the Address Book -- Using iCal -- 9 Emailing and Chatting Online -- Using Mac Mail -- Using iChat -- 10 Using TextEdit -- Working with Documents -- Navigating and Editing Text -- Setting Margins and Tabs -- Formatting Text -- Formatting Paragraphs -- Exploring Other Formatting Features -- Printing -- 11 Managing and Editing Your Photos -- Setting Up iPhoto -- Importing Photos and Movies -- Viewing Photos -- Viewing, Changing, and Adding Photo Information -- Viewing and Changing Information for Events -- Sorting Photos -- Exploring Methods to Organize Photos -- Searching for Photos -- Editing Photos -- Sharing Photos with Others -- 12 Using Widgets and Other Applications -- Using Widgets -- Using Preview -- Consulting the Dictionary -- Posting Stickies -- Using the Calculator -- 13 Keeping Your Mac Safe, Updated, and Backed Up -- Safely Surfing the Web -- Working with the Keychain -- Maintaining Your Mac Software -- Backing Up with Time Machine -- Part III: Having Fun and Getting Creative -- 14 Watching Movies, Listening to Music, and Playing Games -- Watching Movies and Videos -- Listening to Music with iTunes -- Listening to Music in Front Row -- Acquiring and Playing Podcasts -- Playing Games -- 15 Being Creative with Photos -- Making Self-Portraits in Photo Booth -- Creating and Exporting Slideshows -- Designing and Publishing a Photo Book -- Creating Other Keepsakes -- Using Comic Life -- 16 Making Your Own Movies -- Getting Started -- Adding Video to the Events Library -- Playing Clips in the Event Library -- Creating and Playing a New Movie Project -- Trimming and Splitting Clips -- Adding Transitions between Clips -- Adding Titles -- Sharing and Exporting Movies…”

Tabla de Contenidos: “…Functions of One Random Variable -- 6.2.1. Linear Functions -- 6.2.2. Power Functions -- 6.3. …”

Tabla de Contenidos: “…Mathematical Concepts in Kinematics -- 2.1 Introduction -- 2.2 Complex Numbers and Operations -- 2.2.1 Complex Number Forms -- 2.2.2 Complex Number Addition -- 2.2.3 Complex Number Multiplication and Differentiation -- 2.3 Vector and Point Representation -- 2.4 Linear Simultaneous Equations, Matrices, and Matrix Operations -- 2.4.1 Linear Simultaneous Equation Systems and Matrices -- 2.4.2 Matrix Transpose, Addition, Subtraction, and Multiplication -- 2.4.3 The Identity Matrix and Matrix Inversion -- 2.5 Intermediate and Total Spatial Motion -- 2.6 General Transformation Matrix -- 2.7 Summary -- References -- Additional Reading -- Problems -- 3. …”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright Page -- Contents -- Dedication -- Preface -- Author Biography -- Chapter 1 Concepts and Foundations Automation and Emerging Technologies -- 1.1 Introduction -- 1.2 Structure and Framework of Automation and Key Performance Indexes (KPIs) -- 1.3 Advanced Image Processing Techniques -- 1.4 Fuzzy and Its Recent Advances -- 1.5 Automatic Detection and Its Applications in Infrastructure -- 1.6 Feature Extraction and Fragmentation Methods -- 1.7 Feature Prioritization and Selection Methods -- 1.8 Classification Methods and Its Applications in Infrastructure Management -- 1.9 Models of Performance Measures and Quantification in Automation -- 1.10 Nature-Inspired Optimization Algorithms (NIOAS) -- 1.11 Summary and Conclusion -- 1.12 Questions and Exercise -- Chapter 2 The Structure and Framework of Automation and Key Performance Indices (KPIs) -- 2.1 Introduction -- 2.2 Macro Plan and Architecture of Automation -- 2.2.1 Infrastructure Automation -- 2.2.2 Importance of Infrastructure Automation Evaluation -- 2.3 A General Framework and Design of Automation -- 2.4 Infrastructure Condition Index and Its Relationship with Cracking -- 2.4.1 Road Condition Index -- 2.4.2 Bridge Condition Index -- 2.4.3 Tunnel Condition Index -- 2.5 Automation, Emerging Technologies, and Futures Studies -- 2.6 Summary and Conclusion -- 2.7 Questions -- Further Reading -- Chapter 3 Advanced Images Processing Techniques -- Introduction -- 3.1 Preprocessing (PPS) -- 3.1.1 Edge Preservation Index (EPI) -- 3.1.2 Edge-Strength Similarity-Based Image Quality Metric (ESSIM) -- 3.1.3 QILV Index -- 3.1.4 Structural Content Index (SCI) -- 3.1.5 Signal-To-Noise Ratio Index (PSNR) -- 3.1.6 Computational time index (CTI) -- 3.2 Preprocessing Using Single-Level Methods -- 3.2.1 Single-Level Methods -- 3.2.2 Linear Location Filter (LLF) -- 3.2.3 Median Filter…”

Tabla de Contenidos: “…Problems -- 4. Dynamic linear models -- 4.1. General Linear Model Structures -- 4.2. …”

Tabla de Contenidos: “…9.3 Artificial Intelligence: Transport System and Healthcare -- 9.4 Artificial Intelligence Algorithms -- 9.5 AI Workflow -- 9.6 AI for ITS and e-Healthcare Tasks -- 9.7 Intelligent Transportation, Healthcare, and IoT -- 9.8 AI Techniques Used in ITS and e-Healthcare -- 9.9 Challenges of AI and ML in ITS and e-Healthcare -- 9.10 Conclusions -- References -- Chapter 10 Classification of Dementia Using Statistical First-Order and Second-Order Features -- 10.1 Introduction -- 10.2 Materials and Methods -- 10.2.1 Dataset -- 10.2.2 Image Pre-Processing -- 10.3 Proposed Framework -- 10.3.1 Discrete Wavelet Transform -- 10.3.1.1 Statistical Features -- 10.3.2 Classification -- 10.3.2.1 K-Nearest Neighbor -- 10.3.2.2 Linear Discriminant Analysis -- 10.3.2.3 Support Vector Machine -- 10.3.3 Performance Measure -- 10.4 Experimental Results and Discussion -- 10.5 Conclusion -- References -- Chapter 11 Pulmonary Embolism Detection Using Machine and Deep Learning Techniques -- 11.1 Introduction -- 11.2 The State-of-the-Art of PE Detection Models -- 11.3 Literature Survey -- 11.4 Publications Analysis -- 11.5 Conclusion -- References -- Chapter 12 Computer Vision Techniques for Smart Healthcare Infrastructure -- 12.1 Introduction -- 12.2 Literature Survey -- 12.2.1 Computer Vision -- 12.2.1.1 Computer Vision Techniques for Safety and Driver Assistance -- 12.2.1.2 Types of Optical Character Recognition Systems -- 12.2.1.3 Phases of Optical Character Recognition -- 12.2.1.4 Threshold Segmentation -- 12.2.1.5 Edge Detection Operator -- 12.2.1.6 Use Cases of OCR -- 12.2.1.7 List of Research Papers -- 12.2.2 How is IoT Changing the Face of Information Science? …”