Imaging systems and technology Books

Book SynopsisThis book describes the latest development in optical fiber devices, and their applications to sensor technology. Optical fiber sensors, an important application of the optical fiber, have experienced fast development, and attracted wide attentions in basic science as well as in practical applications.Trade Review“The book provides a well-organized and in-depth treatment of optical fiber sensors for students and can also serve as a convenient reference for engineers and scientists working in the field.” (IEEE Electrical Insulation Magazine, 1 March 2014) Table of ContentsPreface xi 1 Introduction 1 1.1 Historical Review and Perspective 1 1.2 Classifications of Optical Fiber Sensors 3 1.3 Overview of the Chapters 6 References 8 2 Fundamentals of Optical Fibers 10 2.1 Introduction to Optical Fibers 10 2.1.1 Basic Structure and Fabrication of Optical Fiber 10 2.1.2 Basic Characteristics 12 2.1.3 Classifications of Optical Fibers 17 2.2 Electromagnetic Theory of Step-Index Optical Fibers 18 2.2.1 Maxwell Equations in Cylindrical Coordinates 19 2.2.2 Boundary Conditions and Eigenvalue Equations 23 2.2.3 Weakly Guiding Approximation, Hybrid Modes, and Linear Polarized Modes 26 2.2.4 Field Distribution and Polarization Characteristics 29 2.2.5 Multimode Fiber and Cladding Modes 35 2.2.6 Propagation of Optical Pulses in Optical Fibers 39 2.3 Basic Theory of the Gradient-Index Optical Fiber 42 2.3.1 Ray Equation in Inhomogeneous Media 42 2.3.2 Ray Optics of GRIN Fiber 46 2.3.3 Wave Optics of GRIN Fiber 51 2.3.4 Basic Characteristics of Gradient Index Lens 56 2.4 Special Optical Fibers 57 2.4.1 Rare-Earth-Doped Fibers and Double-Cladding Fibers 57 2.4.2 Polarization Maintaining Fibers 60 2.4.3 Photonic Crystal Fiber and Microstructure Fiber 64 Problems 69 References 71 3 Fiber Sensitivities and Fiber Devices 76 3.1 Fiber Sensitivities to Physical Conditions 76 3.1.1 Sensitivity to Axial Strain 77 3.1.2 Sensitivity to Lateral Pressure 78 3.1.3 Bending-Induced Birefringence 83 3.1.4 Torsion-Induced Polarization Mode Cross-Coupling 87 3.1.5 Bending Loss 91 3.1.6 Vibration and Mechanical Waves in Fiber 95 3.1.7 Sensitivity to Temperature 96 3.2 Fiber Couplers 97 3.2.1 Structures and Fabrications of 2×2 Couplers 98 3.2.2 Basic Characteristics and Theoretical Analyses of the Coupler 99 3.2.3 N×N and 1×N Fiber Star Couplers 110 3.2.4 Coupling in Axial Direction and Tapered Fiber 114 3.3 Fiber Loop Devices Incorporated with Couplers 118 3.3.1 Fiber Sagnac Loops 118 3.3.2 Fiber Rings 126 3.3.3 Fiber Mach–Zehnder Interferometers and Michelson Interferometers 131 3.3.4 Fiber Loops Incorporated with 3×3 Couplers 135 3.4 Polarization Characteristics of Fibers 142 3.4.1 Polarization State Evolution in Fibers 142 3.4.2 Basic Characteristics of Polarization Mode Dispersion 154 3.4.3 Spun Fiber and Circular Birefringence Fiber 157 3.4.4 Faraday Rotation and Optical Activity 159 3.5 Fiber Polarization Devices 162 3.5.1 Fiber Polarizers 162 3.5.2 Fiber Polarization Controller 165 3.5.3 Fiber Depolarizer and Polarization Scrambler 166 3.5.4 Fiber Optical Isolator and Circulator 170 Problems 172 References 174 4 Fiber Gratings and Related Devices 183 4.1 Introduction to Fiber Gratings 183 4.1.1 Basic Structure and Principle 183 4.1.2 Photosensitivity of Optical Fiber 186 4.1.3 Fabrication and Classifications of Fiber Gratings 190 4.2 Theory of Fiber Grating 194 4.2.1 Theory of Uniform FBG 194 4.2.2 Theory of Long-Period Fiber Grating 202 4.2.3 Basic Theory of Nonuniform Fiber Gratings 208 4.2.4 Inverse Engineering Design 214 4.2.5 Apodization of Fiber Grating 219 4.3 Special Fiber Grating Devices 222 4.3.1 Multisection FBGs 222 4.3.2 Chirped Fiber Bragg Grating 233 4.3.3 Tilted Fiber Bragg Gratings 236 4.3.4 Polarization Maintaining Fiber Gratings 243 4.3.5 In-Fiber Interferometers and Acoustic Optic Tunable Filter 246 4.4 Fiber Grating Sensitivities and Fiber Grating Sensors 249 4.4.1 Sensitivities of Fiber Gratings 250 4.4.2 Tunability of Fiber Gratings 252 4.4.3 Packaging of Fiber Grating Devices 255 4.4.4 Fiber Grating Sensor Systems and Their Applications 259 Problems 263 References 266 5 Distributed Optical Fiber Sensors 278 5.1 Optical Scattering in Fiber 278 5.1.1 Elastic Optical Scattering 279 5.1.2 Inelastic Optical Scattering 281 5.1.3 Stimulated Raman Scattering and Stimulated Brillouin Scattering 285 5.2 Distributed Sensors Based on Rayleigh Scattering 286 5.2.1 Optical Time Domain Reflectometer 286 5.2.2 Polarization OTDR 292 5.2.3 Coherent OTDR and Phase Sensitive OTDR 294 5.2.4 Optical Frequency Domain Reflectometry 298 5.3 Distributed Sensors Based on Raman Scattering 300 5.3.1 Raman Scattering in Fiber 301 5.3.2 Distributed Anti-Stokes Raman Thermometry 304 5.3.3 Frequency Domain DART 307 5.4 Distributed Sensors Based on Brillouin Scattering 308 5.4.1 Brillouin Scattering in Fiber 308 5.4.2 Brillouin Optical Time Domain Reflectrometer 312 5.4.3 Brillouin Optical Time Domain Analyzer 316 5.5 Distributed Sensors Based on Fiber Interferometers 322 5.5.1 Configuration and Characteristics of Interferometric Fiber Sensors 323 5.5.2 Low Coherence Technology in a Distributed Sensor System 327 5.5.3 Sensors Based on Speckle Effect and Mode Coupling in Multimode Fiber 331 Problems 335 References 337 6 Fiber Sensors With Special Applications 351 6.1 Fiber Optic Gyroscope 351 6.1.1 Interferometric FOG 352 6.1.2 Brillouin Laser Gyro and Resonance Fiber Optic Gyroscope 362 6.2 Fiber Optic Hydrophone 364 6.2.1 Basic Structures 365 6.2.2 Sensor Arrays and Multiplexing 370 6.2.3 Low Noise Laser Source 372 6.3 Fiber Faraday Sensor 373 6.3.1 Faraday Effect in Fiber 374 6.3.2 Electric Current Sensor Based on Faraday Rotation 376 6.4 Fiber Sensors Based on Surface Plasmon Effect 379 6.4.1 Surface Plasmon Effect 379 6.4.2 Sensors Based on SPW 383 Problems 386 References 387 7 Extrinsic Fiber Fabry–Perot Interferometer Sensor 395 7.1 Basic Principles and Structures of Extrinsic Fiber F-P Sensors 395 7.1.1 Structures of EFFP Devices 396 7.1.2 Basic Characteristics of a Fabry–Perot Interferometer 398 7.2 Theory of a Gaussian Beam Fabry–Perot Interferometer 401 7.2.1 Basic Model and Theoretical Analysis 401 7.2.2 Approximation as a Fizeau Interferometer 404 7.3 Basic Characteristics and Performances of EFFPI Sensors 406 7.3.1 Sensitivity of an EFFPI Sensor 406 7.3.2 Linear Range and Dynamic Range of Measurement 408 7.3.3 Interrogation and Stability 410 7.3.4 Frequency Response 413 7.4 Applications of the EFFPI Sensor and Related Techniques 417 7.4.1 Localization of the Sound Source 417 7.4.2 Applications in an Atomic Force Microscope 418 7.4.3 More Application Examples 419 Problems 421 References 422 Appendices 427 Appendix 1 Mathematical Formulas 427 A1.1 Bessel Equations and Bessel Functions 427 A1.2 Runge–Kutta Method 432 A1.3 The First-Order Linear Differential Equation 433 A1.4 Riccati Equation 433 A1.5 Airy Equation and Airy Functions 434 Appendix 2 Fundamentals of Elasticity 435 A2.1 Strain, Stress, and Hooke’s Law 435 A2.2 Conversions Between Coordinates 438 A2.3 Plane Deformation 440 A2.4 Equilibrium of Plates and Rods 443 A2.5 Photoelastic Effect 446 Appendix 3 Fundamentals of Polarization Optics 446 A3.1 Polarized Light and Jones Vector 446 A3.2 Stokes Vector and Poincar´e Sphere 447 A3.3 Optics of Anisotropic Media 449 A3.4 Jones Matrix and Mueller Matrix 450 A3.5 Measurement of Jones Vector and Stokes Vector 453 Appendix 4 Specifications of Related Materials and Devices 454 A4.1 Fiber Connectors 456 Index 459

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Book SynopsisThe third book in the trilogy that explores the popular missional movement From Reggie McNeal, the bestselling author of The Present Future and Missional Renaissance, comes the third book in the series that helps to define and illuminate the popular missional movement. This newest book in the trilogy examines a natural outgrowth of the move toward a missional orientation: the deconstruction of congregations into very small Christian communities. For all those thousands of churches and leaders who have followed Reggie McNeal''s bold lead, this book details the rise of a new life form in churches. Discusses how to move a church from an internal to an external ministry focus Reggie McNeal is a recognized leader in the missional movement Outlines an alternative to the program church model that is focused on the projects and passions of the congregants This book draws on McNeal''s twenty years of leadership roles in localTable of ContentsAbout the Jossey-Bass Leadership Network Series xi Foreword by Hugh Halter xiii Acknowledgments xvii Introduction xix 1 ‘‘Let There Be . . . Missional Communities’’ 1 2 The Missional Church Conversation 15 3 Missional Communities—European Style 39 4 Soma Communities: Missional Communities as Organizing Architecture 65 5 Campus Renewal UT: Missional Communities as Campus Evangelism Strategy 85 6 Future Travelers: Missional Communities as Megachurch Strategy 103 7 Mission Houston: Missional Communities for Spiritual Formation and Community Transformation 125 8 Looking Ahead 145 About the Author 155 Index 157

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Book SynopsisIn order to truly understand data signals transmitted by satellite, one must understand scintillation theory in addition to well established theories of EM wave propagation and scattering. Scintillation is a nuisance in satellite EM communications, but it has stimulated numerous theoretical developments with science applications.Table of Contents1. Introduction. 1.1 Electromagnetic Propagation Theory. 1.2 Anticipating Scintillation Theory. 2. The Forward Propagation Equation. 2.1 Weakly Inhomogeneous Media. 2.2 Numerical Simulations. 3. The Statistical Theory of Scintillation. 3.1 Background. 3.2 Calculation of Field Moments. 3.3 Second-Order Moments. 3.4 Fourth-Order Moments. 3.5 Intensity Statistics. 3.6 Numerical Simulations. 3.7 Statistical Theory Limitations. 4. Beacon Satellite Scintillation. 4.1 Geometric Considerations. 4.2 Phase Structure Revisited. 4.3 Complex Field Coherence Revisited. 4.4 Satellite Orbit & Earth Magnetic Field Calculation. 4.5 Examples. 4.6 Theory and Simulations. 5. System Applications of Scintillation. 5.1 An Introduction to Waveforms. 5.2 Scintillation Channel Model. 5.3 System Performance Analysis. 5.4 Scintillation Data Processing. 5.5 Scintillation Data Interpretation. 5.6 Beacon Satellite Research. 6. Scattering and Boundaries. 6.1 Embedded Compact Scattering Objects. 6.2 Boundary Surfaces. Appendix A. A.1 Far-Field Approximation. A.2 Backscatter. A.3 Anisotropy Transformations. A.4 Wavefront Curvature Correction. A.5 Two-Dimensional Boundary Integrals. References. Index.

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Book SynopsisFourier Methods in Imaging first introduces the basic mathematical concepts of linear algebra for vectors and functions, a knowledge of which is necessary for understanding the subsequent discussions.Trade Review"Overall, this is an excellent text, appropriate for the graduate student approaching this material for the first time, and for the seasoned professional looking for an up-to-date reference." (Journal of Electronic Imaging, 1 April 2011) "This comprehensive textbook represents a practical review of Fourier techniques in imaging methods. It will be very useful for graduate students (in engineering, science, computer science, and applied mathematics) as well as engineers interested in linear imaging systems." (Zentralblatt Math, 2010)Table of ContentsSeries Editor’s Preface. Preface. 1 Introduction. 1.1 Signals, Operators, and Imaging Systems. 1.2 The Three Imaging Tasks. 1.3 Examples of Optical Imaging. 1.4 ImagingTasks inMedical Imaging. 2 Operators and Functions. 2.1 Classes of Imaging Operators. 2.2 Continuous and Discrete Functions. Problems. 3 Vectors with Real-Valued Components. 3.1 Scalar Products. 3.2 Matrices. 3.3 Vector Spaces. Problems. 4 Complex Numbers and Functions. 4.1 Arithmetic of Complex Numbers. 4.2 Graphical Representation of Complex Numbers. 4.3 Complex Functions. 4.4 Generalized Spatial Frequency – Negative Frequencies. 4.5 Argand Diagrams of Complex-Valued Functions. Problems. 5 Complex-Valued Matrices and Systems. 5.1 Vectors with Complex-Valued Components. 5.2 Matrix Analogues of Shift-Invariant Systems. 5.3 Matrix Formulation of ImagingTasks. 5.4 Continuous Analogues of Vector Operations. Problems. 6 1-D Special Functions. 6.1 Definitions of 1-D Special Functions. 6.2 1-D Dirac Delta Function. 6.3 1-D Complex-Valued Special Functions. 6.4 1-D Stochastic Functions–Noise. 6.5 Appendix A: Area of SINC[x] and SINC2[x]. 6.6 Appendix B: Series Solutions for Bessel Functions J0[x] and J1[x]. Problems. 7 2-D Special Functions. 7.1 2-D Separable Functions. 7.2 Definitions of 2-D Special Functions. 7.3 2-D Dirac Delta Function and its Relatives. 7.4 2-D Functions with Circular Symmetry. 7.5 Complex-Valued 2-D Functions. 7.6 Special Functions of Three (orMore) Variables. Problems. 8 Linear Operators. 8.1 Linear Operators. 8.2 Shift-Invariant.Operators. 8.3 Linear Shift-Invariant (LSI) Operators. 8.4 Calculating Convolutions. 8.5 Properties of Convolutions. 8.6 Autocorrelation. 8.7 Crosscorrelation. 8.8 2-DLSIOperations. 8.9 Crosscorrelations of 2-D Functions. 8.10 Autocorrelations of 2-D.Functions. Problems. 9 Fourier Transforms of 1-D Functions. 9.1 Transforms of Continuous-Domain Functions. 9.2 Linear Combinations of Reference Functions. 9.3 Complex-Valued Reference Functions. 9.4 Transforms of Complex-Valued Functions. 9.5 Fourier Analysis of Dirac Delta Functions. 9.6 Inverse Fourier Transform. 9.7 Fourier Transforms of 1-D Special Functions. 9.8 Theorems of the Fourier Transform. 9.9 Appendix: Spectrum of Gaussian via Path Integral. Problems. 10 Multidimensional Fourier Transforms. 10.1 2-D Fourier Transforms. 10.2 Spectra of Separable 2-D Functions. 10.3 Theorems of 2-D Fourier Transforms. Problems. 11 Spectra of Circular Functions. 11.1 The Hankel Transform. 11.2 Inverse Hankel Transform. 11.3 Theorems of Hankel Transforms. 11.4 Hankel Transforms of Special Functions. 11.5 Appendix: Derivations of Equations (11.12) and (11.14). Problems. 12 The Radon Transform. 12.1 Line-Integral Projections onto Radial Axes. 12.2 Radon Transforms of Special Functions. 12.3 Theorems of the Radon Transform. 12.4 Inverse Radon Transform. 12.5 Central-Slice Transform. 12.6 Three Transforms of Four Functions. 12.7 Fourier and Radon Transforms of Images. Problems. 13 Approximations to Fourier Transforms. 13.1 Moment Theorem. 13.2 1-D Spectra via Method of Stationary Phase. 13.3 Central-Limit Theorem. 13.4 Width Metrics and Uncertainty Relations. Problems. 14 Discrete Systems, Sampling, and Quantization. 14.1 Ideal Sampling. 14.2 Ideal Sampling of Special Functions. 14.3 Interpolation of Sampled Functions. 14.4 Whittaker–Shannon Sampling Theorem. 14.5 Aliasingand Interpolation. 14.6 “Prefiltering” to Prevent Aliasing. 14.7 Realistic Sampling. 14.8 Realistic Interpolation. 14.9 Quantization. 14.10 Discrete Convolution. Problems. 15 Discrete Fourier Transforms. 15.1 Inverse of the Infinite-Support DFT. 15.2 DFT over Finite Interval. 15.3 Fourier Series Derived from Fourier Transform. 15.4 Efficient Evaluation of the Finite DFT. 15.5 Practical Considerations for DFT and FFT. 15.6 FFTs of 2-D Arrays. 15.7 Discrete Cosine Transform. Problems. 16 Magnitude Filtering. 16.1 Classes of Filters. 16.2 Eigenfunctions of Convolution. 16.3 Power Transmission of Filters. 16.4 Lowpass Filters. 16.5 Highpass Filters. 16.6 Bandpass Filters. 16.7 Fourier Transform as a Bandpass Filter. 16.8 Bandboost and Bandstop Filters. 16.9 Wavelet Transform. Problems. 17 Allpass (Phase) Filters. 17.1 Power-Series Expansion for Allpass Filters. 17.2 Constant-Phase Allpass Filter. 17.3 Linear-Phase Allpass Filter. 17.4 Quadratic-Phase Filter. 17.5 Allpass Filters with Higher-Order Phase. 17.6 Allpass Random-Phase Filter. 17.7 Relative Importance of Magnitude and Phase. 17.8 Imaging of Phase Objects. 17.9 Chirp Fourier Transform. Problems. 18 Magnitude–Phase Filters. 18.1 Transfer Functions of Three Operations. 18.2 Fourier Transform of Ramp Function. 18.3 Causal Filters. 18.4 Damped Harmonic Oscillator. 18.5 Mixed Filters with Linear or Random Phase. 18.6 Mixed Filter with Quadratic Phase. Problems. 19 Applications of Linear Filters. 19.1 Linear Filters for the Imaging Tasks. 19.2 Deconvolution– “Inverse Filtering”. 19.3 Optimum Estimators for Signals in Noise. 19.4 Detection of Known Signals – Matched Filter. 19.5 Analogies of Inverse and Matched Filters. 19.6 Approximations to Reciprocal Filters. 19.7 Inverse Filtering of Shift-Variant Blur. Problems. 20 Filtering in Discrete Systems. 20.1 Translation, Leakage, and Interpolation. 20.2 Averaging Operators– Lowpass Filters. 20.3 Differencing Operators – Highpass Filters. 20.4 Discrete Sharpening Operators. 20.5 2-DGradient. 20.6 Pattern Matching. 20.7 Approximate Discrete Reciprocal Filters. Problems. 21 Optical Imaging in Monochromatic Light. 21.1 Imaging Systems Based on Ray Optics Model. 21.2 Mathematical Model of Light Propagation. 21.3 Fraunhofer Diffraction. 21.4 Imaging System based on Fraunhofer Diffraction. 21.5 Transmissive Optical Elements. 21.6 Monochromatic Optical Systems. 21.7 Shift-Variant Imaging Systems. Problems. 22 Incoherent Optical Imaging Systems. 22.1 Coherence. 22.2 Polychromatic Source – Temporal Coherence. 22.3 Imaging in Incoherent Light. 22.4 System Function in Incoherent Light. Problems. 23 Holography. 23.1 Fraunhofer Holography. 23.2 Holography in Fresnel Diffraction Region. 23.3 Computer-Generated Holography. 23.4 Matched Filtering with Cell-Type CGH. 23.5 Synthetic-Aperture Radar (SAR). Problems. References. Index.

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Book SynopsisLearn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems development, making it easier to master such tasks as classification, clustering, and feature selection. Rough-Fuzzy Pattern Recognition examines the important underlying theory as well as algorithms and applications, helping readers see the connections between theory and practice. The first chapter provides an introduction to pattern recognition and data mining, including the Table of ContentsForeword xiii Preface xv About the Authors xix 1 Introduction to Pattern Recognition and Data Mining 1 1.1 Introduction 1 1.2 Pattern Recognition 3 1.2.1 Data Acquisition 4 1.2.2 Feature Selection 4 1.2.3 Classification and Clustering 5 1.3 Data Mining 6 1.3.1 Tasks, Tools, and Applications 7 1.3.2 Pattern Recognition Perspective 8 1.4 Relevance of Soft Computing 9 1.5 Scope and Organization of the Book 10 References 14 2 Rough-Fuzzy Hybridization and Granular Computing 21 2.1 Introduction 21 2.2 Fuzzy Sets 22 2.3 Rough Sets 23 2.4 Emergence of Rough-Fuzzy Computing 26 2.4.1 Granular Computing 26 2.4.2 Computational Theory of Perception and f -Granulation 26 2.4.3 Rough-Fuzzy Computing 28 2.5 Generalized Rough Sets 29 2.6 Entropy Measures 30 2.7 Conclusion and Discussion 36 References 37 3 Rough-Fuzzy Clustering: Generalized c-Means Algorithm 47 3.1 Introduction 47 3.2 Existing c-Means Algorithms 49 3.2.1 Hard c-Means 49 3.2.2 Fuzzy c-Means 50 3.2.3 Possibilistic c-Means 51 3.2.4 Rough c-Means 52 3.3 Rough-Fuzzy-Possibilistic c-Means 53 3.3.1 Objective Function 54 3.3.2 Cluster Prototypes 55 3.3.3 Fundamental Properties 56 3.3.4 Convergence Condition 57 3.3.5 Details of the Algorithm 59 3.3.6 Selection of Parameters 60 3.4 Generalization of Existing c-Means Algorithms 61 3.4.1 RFCM: Rough-Fuzzy c-Means 61 3.4.2 RPCM: Rough-Possibilistic c-Means 62 3.4.3 RCM: Rough c-Means 63 3.4.4 FPCM: Fuzzy-Possibilistic c-Means 64 3.4.5 FCM: Fuzzy c-Means 64 3.4.6 PCM: Possibilistic c-Means 64 3.4.7 HCM: Hard c-Means 65 3.5 Quantitative Indices for Rough-Fuzzy Clustering 65 3.5.1 Average Accuracy, α Index 65 3.5.2 Average Roughness, ϱ Index 67 3.5.3 Accuracy of Approximation, α⋆ Index 67 3.5.4 Quality of Approximation, γ Index 68 3.6 Performance Analysis 68 3.6.1 Quantitative Indices 68 3.6.2 Synthetic Data Set: X32 69 3.6.3 Benchmark Data Sets 70 3.7 Conclusion and Discussion 80 References 81 4 Rough-Fuzzy Granulation and Pattern Classification 85 4.1 Introduction 85 4.2 Pattern Classification Model 87 4.2.1 Class-Dependent Fuzzy Granulation 88 4.2.2 Rough-Set-Based Feature Selection 90 4.3 Quantitative Measures 95 4.3.1 Dispersion Measure 95 4.3.2 Classification Accuracy, Precision, and Recall 96 4.3.3 κ Coefficient 96 4.3.4 β Index 97 4.4 Description of Data Sets 97 4.4.1 Completely Labeled Data Sets 98 4.4.2 Partially Labeled Data Sets 99 4.5 Experimental Results 100 4.5.1 Statistical Significance Test 102 4.5.2 Class Prediction Methods 103 4.5.3 Performance on Completely Labeled Data 103 4.5.4 Performance on Partially Labeled Data 110 4.6 Conclusion and Discussion 112 References 114 5 Fuzzy-Rough Feature Selection using f -Information Measures 117 5.1 Introduction 117 5.2 Fuzzy-Rough Sets 120 5.3 Information Measure on Fuzzy Approximation Spaces 121 5.3.1 Fuzzy Equivalence Partition Matrix and Entropy 121 5.3.2 Mutual Information 123 5.4 f -Information and Fuzzy Approximation Spaces 125 5.4.1 V -Information 125 5.4.2 Iα-Information 126 5.4.3 Mα-Information 127 5.4.4 χα-Information 127 5.4.5 Hellinger Integral 128 5.4.6 Renyi Distance 128 5.5 f -Information for Feature Selection 129 5.5.1 Feature Selection Using f -Information 129 5.5.2 Computational Complexity 130 5.5.3 Fuzzy Equivalence Classes 131 5.6 Quantitative Measures 133 5.6.1 Fuzzy-Rough-Set-Based Quantitative Indices 133 5.6.2 Existing Feature Evaluation Indices 133 5.7 Experimental Results 135 5.7.1 Description of Data Sets 136 5.7.2 Illustrative Example 137 5.7.3 Effectiveness of the FEPM-Based Method 138 5.7.4 Optimum Value of Weight Parameter β 141 5.7.5 Optimum Value of Multiplicative Parameter η 141 5.7.6 Performance of Different f -Information Measures 145 5.7.7 Comparative Performance of Different Algorithms 152 5.8 Conclusion and Discussion 156 References 156 6 Rough Fuzzy c-Medoids and Amino Acid Sequence Analysis 161 6.1 Introduction 161 6.2 Bio-Basis Function and String Selection Methods 164 6.2.1 Bio-Basis Function 164 6.2.2 Selection of Bio-Basis Strings Using Mutual Information 166 6.2.3 Selection of Bio-Basis Strings Using Fisher Ratio 167 6.3 Fuzzy-Possibilistic c-Medoids Algorithm 168 6.3.1 Hard c-Medoids 168 6.3.2 Fuzzy c-Medoids 169 6.3.3 Possibilistic c-Medoids 170 6.3.4 Fuzzy-Possibilistic c-Medoids 171 6.4 Rough-Fuzzy c-Medoids Algorithm 172 6.4.1 Rough c-Medoids 172 6.4.2 Rough-Fuzzy c-Medoids 174 6.5 Relational Clustering for Bio-Basis String Selection 176 6.6 Quantitative Measures 178 6.6.1 Using Homology Alignment Score 178 6.6.2 Using Mutual Information 179 6.7 Experimental Results 181 6.7.1 Description of Data Sets 181 6.7.2 Illustrative Example 183 6.7.3 Performance Analysis 184 6.8 Conclusion and Discussion 196 References 196 7 Clustering Functionally Similar Genes from Microarray Data 201 7.1 Introduction 201 7.2 Clustering Gene Expression Data 203 7.2.1 k-Means Algorithm 203 7.2.2 Self-Organizing Map 203 7.2.3 Hierarchical Clustering 204 7.2.4 Graph-Theoretical Approach 204 7.2.5 Model-Based Clustering 205 7.2.6 Density-Based Hierarchical Approach 206 7.2.7 Fuzzy Clustering 206 7.2.8 Rough-Fuzzy Clustering 206 7.3 Quantitative and Qualitative Analysis 207 7.3.1 Silhouette Index 207 7.3.2 Eisen and Cluster Profile Plots 207 7.3.3 Z Score 208 7.3.4 Gene-Ontology-Based Analysis 208 7.4 Description of Data Sets 209 7.4.1 Fifteen Yeast Data 209 7.4.2 Yeast Sporulation 211 7.4.3 Auble Data 211 7.4.4 Cho et al. Data 211 7.4.5 Reduced Cell Cycle Data 211 7.5 Experimental Results 212 7.5.1 Performance Analysis of Rough-Fuzzy c-Means 212 7.5.2 Comparative Analysis of Different c-Means 212 7.5.3 Biological Significance Analysis 215 7.5.4 Comparative Analysis of Different Algorithms 215 7.5.5 Performance Analysis of Rough-Fuzzy-Possibilistic c-Means 217 7.6 Conclusion and Discussion 217 References 220 8 Selection of Discriminative Genes from Microarray Data 225 8.1 Introduction 225 8.2 Evaluation Criteria for Gene Selection 227 8.2.1 Statistical Tests 228 8.2.2 Euclidean Distance 228 8.2.3 Pearson’s Correlation 229 8.2.4 Mutual Information 229 8.2.5 f -Information Measures 230 8.3 Approximation of Density Function 230 8.3.1 Discretization 231 8.3.2 Parzen Window Density Estimator 231 8.3.3 Fuzzy Equivalence Partition Matrix 233 8.4 Gene Selection using Information Measures 234 8.5 Experimental Results 235 8.5.1 Support Vector Machine 235 8.5.2 Gene Expression Data Sets 236 8.5.3 Performance Analysis of the FEPM 236 8.5.4 Comparative Performance Analysis 250 8.6 Conclusion and Discussion 250 References 252 9 Segmentation of Brain Magnetic Resonance Images 257 9.1 Introduction 257 9.2 Pixel Classification of Brain MR Images 259 9.2.1 Performance on Real Brain MR Images 260 9.2.2 Performance on Simulated Brain MR Images 263 9.3 Segmentation of Brain MR Images 264 9.3.1 Feature Extraction 265 9.3.2 Selection of Initial Prototypes 274 9.4 Experimental Results 277 9.4.1 Illustrative Example 277 9.4.2 Importance of Homogeneity and Edge Value 278 9.4.3 Importance of Discriminant Analysis-Based Initialization 279 9.4.4 Comparative Performance Analysis 280 9.5 Conclusion and Discussion 283 References 283 Index 287

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Book SynopsisNMR in Pharmaceutical Sciencesis intended to be a comprehensive source of information for the many individuals that utilize MR in studies of relevance to the pharmaceutical sector. The book is intended to educate and inform those who develop and apply MR approaches within the wider pharmaceutical environment, emphasizing the toolbox that is available to spectroscopists and radiologists. This book is structured on the key processes in drug discovery, development and manufacture, but underpinned by an understanding of fundamental NMR principles and the unique contribution that NMR (including MRI) can provide. After an introductory chapter, which constitutes an overview, the content is organised into five sections. The first section is on the basics of NMR theory and relevant experimental methods. The rest follow a sequence based on the chronology of drug discovery and development, firstly ''Idea to Lead'' then ''Lead to Drug Candidate'', followed by ''Clinical DevelopmenTable of ContentsContributors xi Series Preface xvii Preface xix Part A: Introduction 1 1 Drug Discovery and Development: The Role of NMRJeremy R. Everett 3 Part B: NMR Theory & Experimental Methods 21 2 Modern NMR Pulse Sequences in Pharmaceutical R&DJohn A. Parkinson 23 3 Experimental NMR Methods for Pharmaceutical Research and DevelopmentAnthony C. Dona 41 4 19F NMR Spectroscopy: Applications in Pharmaceutical StudiesJohn C. Lindon and Ian D. Wilson 53 5 Quantitative NMR Spectroscopy in Pharmaceutical R&DUlrike Holzgrabe 63 6 High-throughput NMR in Pharmaceutical R&DJohn C. Hollerton 79 7 Multivariate Data Analysis Methods for NMR-based Metabolic Phenotyping in Pharmaceutical and Clinical ResearchKirill A. Veselkov, James S. McKenzie, and Jeremy K. Nicholson 89 Part C: Idea to Lead 103 8 The Role of NMR in Target Identification and Validation for Pharmaceutical R&DKrishna Saxena and Harald Schwalbe 105 9 High-resolution MAS NMR of Tissues and CellsLeo L. Cheng 117 10 NMR Studies of Inborn Errors of MetabolismSarantos Kostidis and Emmanuel Mikros 131 11 NMR-based Structure Confirmation of Hits and Leads in Pharmaceutical R&DPhilip J. Sidebottom 147 12 Fragment-based Drug Design Using NMR MethodsLeonor Puchades-Carrasco and Antonio Pineda-Lucena 155 13 Hit Discovery from Natural Products in Pharmaceutical R&DOlivia Corcoran 173 Part D: Lead to Drug Candidate 183 14 NMR-based Structure Determination of Drug Leads and CandidatesTorren M. Peakman 185 15 Mixture Analysis in Pharmaceutical R&D Using Hyphenated NMR TechniquesIan D. Wilson and John C. Lindon 197 16 Conformation and Stereochemical Analysis of Drug MoleculesGary J. Sharman 207 17 NMR Methods for the Assignment of Absolute Stereochemistry of Bioactive CompoundsJose M. Seco and Ricardo Riguera 221 18 Applications of Preclinical MRI/MRS in the Evaluation of Drug Efficacy and SafetyThomas M. Bocan, Lauren Keith, and David M. Thomasson 255 19 Practical Applications of NMR Spectroscopy in Preclinical Drug Metabolism StudiesRaman Sharma and Gregory S. Walker 267 20 Preclinical Drug Efficacy and Safety Using NMR SpectroscopyMuireann Coen and Ian D. Wilson 281 21 Characterization of Pharmaceutical Compounds by Solid-state NMRFrederick G. Vogt 297 22 Structure-based Drug Design Using NMRMark Jeeves, Lee Quill, and Michael Overduin 317 23 Pharmaceutical Technology Studied by MRIDavid G. Reid and Stephen J. Byard 331 Part E: Clinical Development 345 24 NMR-based Metabolic Phenotyping for Disease Diagnosis and StratificationBeatriz Jiménez 347 25 NMR-based Pharmacometabonomics: A New Approach to Personalized MedicineJeremy R. Everett 359 26 Clinical MRI Studies of Drug Efficacy and SafetyDavid G. Reid, Paul D. Hockings, and Nadeem Saeed 373 27 The Role of NMR in the Protection of Intellectual Property in Pharmaceutical R&DFrederick G. Vogt 385 Part F: Drug Manufacture 395 28 Analysis of Counterfeit Medicines and Adulterated Dietary Supplements by NMRMyriam Malet-Martino and Robert Martino 397 29 Pharmaceutical Industry: Regulatory Control and Impact on NMR SpectroscopyAndrea Ruggiero and Sarah K. Branch 413 30 NMR Spectroscopy in the European and US PharmacopeiasHelen Corns and Sarah K. Branch 425 31 NMR in Pharmaceutical ManufacturingEdwin Kellenbach and Paulo Dani 441 Index 453

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Book SynopsisThis fifth edition of the most accessible introduction to MRI principles and applications from renowned teachers in the field provides an understandable yet comprehensive update. Accessible introductory guide from renowned teachers in the field Provides a concise yet thorough introduction for MRI focusing on fundamental physics, pulse sequences, and clinical applications without presenting advanced math Takes a practical approach, including up-to-date protocols, and supports technical concepts with thorough explanations and illustrations Highlights sections that are directly relevant to radiology board exams Presents new information on the latest scan techniques and applications including 3 Tesla whole body scanners, safety issues, and the nephrotoxic effects of gadolinium-based contrast media Table of ContentsPreface, ix ABR study guide topics, xi 1 Production of net magnetization 1 1.1 Magnetic fields 1 1.2 Nuclear spin 2 1.3 Nuclear magnetic moments 4 1.4 Larmor precession 4 1.5 Net magnetization 6 1.6 Susceptibility and magnetic materials 8 2 Concepts of magnetic resonance 10 2.1 Radiofrequency excitation 10 2.2 Radiofrequency signal detection 12 2.3 Chemical shift 14 3 Relaxation 17 3.1 T1 relaxation and saturation 17 3.2 T2 relaxation, T2* relaxation, and spin echoes 21 4 Principles of magnetic resonance imaging – 1 26 4.1 Gradient fields 26 4.2 Slice selection 28 4.3 Readout or frequency encoding 30 4.4 Phase encoding 33 4.5 Sequence looping 35 5 Principles of magnetic resonance imaging – 2 39 5.1 Frequency selective excitation 39 5.2 Composite pulses 44 5.3 Raw data and image data matrices 46 5.4 Signal-to-noise ratio and tradeoffs 47 5.5 Raw data and k-space 48 5.6 Reduced k-space techniques 51 5.7 Reordered k-space filling techniques 54 5.8 Other k-space filling techniques 56 5.9 Phased-array coils 58 5.10 Parallel acquisition methods 60 6 Pulse sequences 65 6.1 Spin echo sequences 67 6.2 Gradient echo sequences 70 6.3 Echo planar imaging sequences 75 6.4 Magnetization-prepared sequences 77 7 Measurement parameters and image contrast 86 7.1 Intrinsic parameters 87 7.2 Extrinsic parameters 89 7.3 Parameter tradeoffs 91 8 Signal suppression techniques 94 8.1 Spatial presaturation 94 8.2 Magnetization transfer suppression 96 8.3 Frequency-selective saturation 99 8.4 Nonsaturation methods 101 9 Artifacts 103 9.1 Motion artifacts 103 9.2 Sequence/Protocol-related artifacts 105 9.3 External artifacts 119 10 Motion artifact reduction techniques 126 10.1 Acquisition parameter modification 126 10.2 Triggering/Gating 127 10.3 Flow compensation 132 10.4 Radial-based motion compensation 134 11 Magnetic resonance angiography 135 11.1 Time-of-flight MRA 137 11.2 Phase contrast MRA 141 11.3 Maximum intensity projection 144 12 Advanced imaging applications 147 12.1 Diffusion 147 12.2 Perfusion 153 12.3 Functional brain imaging 156 12.4 Ultra-high field imaging 158 12.5 Noble gas imaging 159 13 Magnetic resonance spectroscopy 162 13.1 Additional concepts 162 13.2 Localization techniques 167 13.3 Spectral analysis and postprocessing 169 13.4 Ultra-high field spectroscopy 173 14 Instrumentation 177 14.1 Computer systems 177 14.2 Magnet system 180 14.3 Gradient system 182 14.4 Radiofrequency system 184 14.5 Data acquisition system 186 14.6 Summary of system components 187 15 Contrast agents 189 15.1 Intravenous agents 190 15.2 Oral agents 195 16 Safety 196 16.1 Base magnetic field 197 16.2 Cryogens 197 16.3 Gradients 198 16.4 RF power deposition 198 16.5 Contrast media 199 17 Clinical applications 200 17.1 General principles of clinical MR imaging 200 17.2 Examination design considerations 202 17.3 Protocol considerations for anatomical regions 203 17.4 Recommendations for specific sequences and clinical situations 218 References and suggested readings 222 Index 225

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Book SynopsisMRI PHYSICS MRI PHYSICSTECH TO TECH EXPLANATIONSTechnologists must have a solid understanding of the physics behind Magnetic Resonance Imaging (MRI), including safety, the hows and whys of the quantum physics of the MR phenomenon, and how to competently operate MRI scanners. Generating the highest quality images of the human body involves thorough knowledge of scanner hardware, pulse sequences, image contrast, geometric parameters, and tissue suppression techniques.MRI Physics: Tech to Tech Explanations is designed to help student MRI technologists and radiotherapists preparing for Advanced MRI certification examinations to better understand difficult concepts and topics in a quick and easy manner.Written by a highly experienced technologist, this useful guide provides clear and reader-friendly coverage of what every MR Technologist needs to know. Topics include safety considerations associated with the magnetic field and RF, pulse sequences, Table of ContentsAbout the Author xv Preface xvii Acknowledgements xix Introduction 1 1 Hardware: Magnet Types and Coils 15 Magnets 15 Coils 17 2 The Basics 23 Why the Hydrogen Molecule? 24 The Net Magnetization Vector 26 MRI is a Sequence of Events 27 Free Induction Decay (FID) 32 Relaxation 33 Proton Density 38 Image Contrast 38 The IQ Triangle: Contrast, SNR, Resolution 39 B0 and B1 43 Free and Bound Protons 44 3 Image Weighting 47 Where Does Image Weighting Come From? 48 Time of Repetition (TR) 50 Time of Echo (TE) 52 TE and TR 54 Why Different TR Ranges for Different Field Strengths? 54 How Does TR Control T1? 55 What Does TR Affect? 56 Interpreting the T1 Relaxation Curve 57 Time of Repetition: Effects of the TR 57 TE: The T1 and T2 of it 58 Interpreting the T2 Relaxation Curve 60 Effects of TE on Image Contrast 62 What Do the Lines on the Curves Really Mean Anyway? 62 One Last Weighting Triangle 65 T1 and T2 Contrast Review 66 4 Introduction to the Basic Pulse Sequences 69 What is a Pulse Sequence? 69 Spin Echo (SE) 70 Gradient Echo/Gradient Recalled Echo (GRE) 73 Line Diagram Anatomy 74 The Ernst Angle 77 5 Multi Echo Spin Echo Sequence 81 Introduction to k-Space 82 k-Space: Phase Encoding 85 With FSE, Watch the Speed Limit! 86 k-Space, ETL, and Image Contrast 87 Filling k-Space 89 Pros and Cons of FSE 89 Another Way to View T2* and 180°s 91 Where Do Relaxation and Decay Curves Come From? 92 A T2* Curve Compared to the T2 Curve 93 Metal Artifact Reduction (MARS) 94 Driven Equilibrium: A “Forced T1” 95 3D FSE: CUBE/SPACE/VISTA 97 Single Shot FSE/HASTE 98 6 Tissue Suppression 105 Tissue Saturation versus Suppression 107 Inversion Recovery – Part One: STIR 108 Inversion Recovery: STIR with Vectors 109 Inversion Recovery Part Two: T2 FLAIR 113 IR Sequences: T1 and T2 FLAIR 116 IR Weightings: STIR, T1 and T2 FLAIR 117 Inversion Recovery – Part Two 119 The Rupture View 120 Tissue Saturation: Chemical Shift 121 Chemical Saturation at Low Fields 123 Tissue Saturation: SPAIR and SPIR 124 The Dixon Technique 126 Water Excitation 126 Saturation Pulses or Bands 129 Subtractions 131 Magnetization Transfer 135 IR Prepped Sequences 137 How is an RF Pulse Selective or Non-Selective? 140 Water Excitation Sequences 142 7 The Gradient Echo Sequence 145 GRE Sequence Structure 147 Phase Dispersion and Gradient Reversal 148 Analog to Digital Converter (ADC) 149 GRE Sequence Image Weighting 149 Two Different Kinds of T2 Relaxation 152 The GRE Weighting Triangle 153 GRE and SE Differences 156 Different Gradient Echo Types 157 In and Out of Phase TEs 161 In Phase/Out of Phase at 1.5 T 163 8 Gradient Echo Magnetic Resonance Angiography 167 Time of Flight MRA 168 TOF Angiography: Two Golden Rules 171 Types of MRA Sequences 171 TOF Concept in MRA versus MRV 172 2D versus 3D 172 2D TOF MRAs 175 3D TOF MRAs 176 In-Plane Saturation 178 In-Plane Saturation Avoidance 179 Magnetization Transfer (MT) 181 Options for Better MRAs 183 Phase Contrast MRA 185 9 k-Space 191 What Is Fourier Transform? 192 k-Space Filling 192 10 Echo Planar Sequences 203 Diffusion Weighted Imaging 205 Diffusion Tensor Imaging or White Matter Tractography 215 Susceptibility Weighted Imaging 216 Brain Perfusion 218 Arterial Spin Labeling 222 Spectroscopy 225 11 Geometric Parameters: Trade-offs and Effects on Image Quality 231 Field of View (FOV) Is Your Film Size 232 Nex, ACQ, NSA, and SNR 235 Scan Matrix 237 Frequency Matrix 237 Echo Train Length 238 Echo Spacing 239 Echo Train Balancing 240 Slice Thickness and Slice Gap 242 Fractional Echo 243 Bandwidth 244 Rectangular (Rec.) FOV 249 No Phase Wrap/Phase Oversampling/Fold-Over Suppression 251 Concatenations or Acquisitions 254 Sequential Order Acquisition 255 12 Image Artifacts 257 Motion 258 Flow Artifact/Phase Mis-registration 262 RF Artifacts 265 Wrap/Aliasing/Fold-over Artifact 265 Gibbs Artifact (Ringing/Truncation) 268 Chemical Shift Artifact 271 Cross-talk 276 Cross-excitation 278 Gradient Warp or Distortion 281 Metal Artifacts 281 Corduroy Artifact 283 Annifact 284 Moiré Fringe Artifact or Zebra Artifact 285 Magnetic Susceptibility Artifact 286 Dielectric Effect or Standing Wave 288 Magic Angle Artifact 290 13 Gradients 295 Physical Gradients 296 Logical Gradients 302 14 MRI Math 313 The Larmor Equation: W0 = γB0 314 Acquisitions or Nex or NSA 314 Scan Time Equations 315 Pixel Size and Voxel Volume 317 How to Convert Hz per Pixel to MHz 318 In and Out of Phase TEs 319 Dixon Method or Technique 320 SNR and the 3D Sequence 321 15 Parallel Imaging 325 Parallel Imaging: What Is It? 325 When and Where to Use the Speed 326 Parallel Imaging: How Does It Work? 327 Parallel Imaging: Pros and Cons 330 16 IV Gadolinium 335 Why We Use Gad 336 How Does Gad Shorten the T1 of Tissues? 337 The Blood–Brain Barrier 341 Post Contrast T2 FLAIR Imaging 342 Imaging Gadolinium 345 Eovist® 347 Glossary 351 Suggested Reading 388 Index 389

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Book SynopsisPodcasting is a powerful tool of communication and creative expression that doesn''t need to be intimidating. This book brings together the creative and technical aspects of audio engineering to help podcasters communicate their ideas effectively and creatively. The Podcaster''s Audio Handbook focuses on simple techniques that immediately elevate the audio quality of your podcast. The book provides an overview of podcast recording and editing techniques, so that podcasters can avoid common pitfalls. Readers will also gain access to audio downloads to enhance the learning process. With this book, you can improve the technical aspects of recording and editing your podcasts. Anyone can learn audio techniques and I encourage anyone to share their stories through podcasting. Unleash your creativity and connect with your audience!  What You Will Learn  Choose the correct file formats and settings  Set up a portable recorder  MaTable of ContentsThe Podcaster's Audio HandbookPreface (old chapter 1)Chapter 1: File Formats and Settings (old chapter 2)Chapter 2: Gear (old chapter 3)Chapter 3: Getting a Good Take (old chapter 7)Chapter 4: Recording InsideChapter 5: Recording OutsideChapter 6: Recording RemotelyChapter 7: Editing (old chapter 8)

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Book SynopsisThis handbook introduces speckle techniques to nonspecialists to help them understand the basic principles of speckle interferometry. The book mainly focuses on the use of speckle patterns with direct phase-measuring methods that produce an instantaneous phase. The major electronic speckle pattern interferometry (ESPI) techniques are presented using simplified mathematical notation that includes rigid-body and standard-body displacements to estimate object pose changes with six degrees of freedom. Additionally, the adoption of temporal phase unwrapping instead of spatial phase unwrapping is promoted. This handbook also includes a summary of recent industrial applications, with an update on current research in the ESPI field.Table of Contents Fundamentals of Interference Speckle Interference and Displacement Electronic Speckle Pattern Interferometers Illumination and Displacement Detection Transient Displacement Analysis Phase Detection

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Book SynopsisThe speckle phenomenon is ubiquitous, occurring in all regions of the electromagnetic spectrum, as well as in both ultrasound and synthetic-aperture-radar imaging. Speckle occurs whenever radiation is reflected from a surface that is rough on the scale of a wavelength, or is passed through a diffusing surface that introduces random path-length delays on the scale of a wavelength. This book is devoted to simulation of speckle phenomena using the software package Mathematica®. Various techniques for simulating speckle are discussed. Simulation topics include first-order amplitude and intensity statistics, speckle phenomena in both imaging and free-space propagation, speckle at low light levels, polarization speckle, phase vortices in speckle, and speckle metrology methods.Table of Contents First-Order Statistics of Speckle Amplitude First-Order Statistics of Speckle Intensity Simulation of Speckle in Optical Imaging Simulation of Speckle in Free-Space Propagation Speckle at Low Light Levels Speckle Phase Vortices Polarization Speckle Speckle Simulation for Metrology

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Book SynopsisThis book is in part an introduction to ladar (or lidar), providing the technical building blocks for understanding the technology, but also provides in-depth coverage of aspects of coherent detection. It covers the mathematical background of traditional direct-detection architecture, including a detailed description of photon-counting detection, which is usually achieved with Geiger-mode APD technology. The book also dives into details of coherent detection architecture, explaining various imaging techniques such as synthetic aperture lidar and vibration sensing lidar. This book can serve as a reference for readers who want to become more acquainted with lidar technology and can also be used as a textbook on the subject.Table of Contents Ladar: A New Light on Imaging Laser Transmitters Receiver Detector The Ladar Range Equation Detection Statistics, Probability of Detection and False Alarm, and Statistical Improvement Techniques Image Resolution and Optical Considerations Ladar Waveforms Receiver, Signal Processing, and Data Extraction Coherent Detection Ladar Waveform Considerations in Coherent Ladar Coherent Detection with a Geiger-Mode Receiver Lidar Applications: Present and Future

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Book SynopsisThe speckle phenomenon is ubiquitous, occurring in all regions of the electromagnetic spectrum, as well as in both ultrasound and synthetic-aperture-radar imaging. Speckle occurs whenever radiation is reflected from a surface that is rough on the scale of a wavelength or is passed through a diffusing surface that introduces random path-length delays on the scale of a wavelength. This book is devoted to simulation of speckle phenomena using the software package Python. Various techniques for simulating speckle are discussed. Simulation topics include first-order amplitude and intensity statistics, speckle phenomena in both imaging and free-space propagation, speckle at low light levels, polarization speckle, phase vortices in speckle, and speckle metrology methods.Table of Contents Introduction First-Order Statistics of Speckle Amplitude First-Order Statistics of Speckle Intensity Simulation of Speckle in Optical Imaging Simulation of Speckle in Free-Space Propagation Speckle at Low Light Levels Speckle Phase Vortices Polarization Speckle Speckle Simulation for Metrology

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Book SynopsisIn the field of image processing, many applications require real-time execution, particularly those in the domains of medicine, robotics and transmission, to name but a few. Recent technological developments have allowed for the integration of more complex algorithms with large data volume into embedded systems, in turn producing a series of new sophisticated electronic architectures at affordable prices. This book performs an in-depth survey on this topic. It is primarily written for those who are familiar with the basics of image processing and want to implement the target processing design using different electronic platforms for computing acceleration. The authors present techniques and approaches, step by step, through illustrative examples. This book is also suitable for electronics/embedded systems engineers who want to consider image processing applications as sufficient imaging algorithm details are given to facilitate their understanding.Table of Contents1. Introduction of Real-time Image Processing. 2. Hardware Architectures for
Real-time Processing. 3. Rapid Prototyping of Parallel Reconfigurable Instruction Set Processor for Efficient Real-Time Image Processing. 4. Exploration of High-Level Synthesis Technique. 5. CDMS4HLS: A Novel Source- To-Source
Compilation Strategy for HLS-Based FPGA Design. 6. Embedded Implementation of VHR Satellite Image Segmentation. 7. Real-time Image Processing with Very High-level Synthesis.

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Book SynopsisThe imaging of moving organs such as the heart, in particular, is a real challenge because of its movement. This book presents current and emerging methods developed for the acquisition of images of moving organs in the five main medical imaging modalities: conventional X-rays, computed tomography (CT), magnetic resonance imaging (MRI), nuclear imaging and ultrasound. The availability of dynamic image sequences allows for the qualitative and quantitative assessment of an organ’s dynamics, which is often linked to pathologies.Table of ContentsPREFACE xiii ACKNOWLEDGMENTS xv INTRODUCTION xvii PART 1. METHODOLOGICAL BASES 1 CHAPTER 1. EXTRACTION AND SEGMENTATION OF STRUCTURES IN IMAGE SEQUENCES 3Olivier BERNARD, Patrick CLARYSSE, Thomas DIETENBECK, Denis FRIBOULET, Stéphanie JEHAN-BESSON and Jérome POUSIN 1.1. Problematics 3 1.2. Overview of segmentation methods 3 1.3. Summary of the different classes of deformable models 6 1.3.1. Non-energy approaches 7 1.3.2. Energy-based approaches 8 1.4. Deformable templates 11 1.4.1. Elastic deformable template principle 12 1.4.2. Dynamic elastic deformable template 14 1.4.3. Elastic deformable template and modal analysis 15 1.4.4. The elastic deformable template in practice 15 1.5. Variational active contours 17 1.5.1. Active contour representations 17 1.5.2. Energy functional 21 1.5.3. Obtaining the evolution equation 26 1.5.4. Level set digital implementation 34 1.6. Integration of a priori constraints in the formalism of variational contours 35 1.6.1. Shape a priori 36 1.6.2. Motion a priori 38 1.7. Implementation examples in cardiac imaging 44 1.7.1. Echographic imaging: choice of the data fitting term 44 1.7.2. Example of 3D echocardiography image segmentation 46 1.7.3. Example of 2D echocardiography image segmentation 48 1.8. Conclusion 50 1.9. Bibliography 52 CHAPTER 2. MOTION ESTIMATION AND ANALYSIS 65Patrick CLARYSSE and Jérome POUSIN 2.1. Problematics 65 2.2. Problem formulation 66 2.3. Transport methods 67 2.3.1. Optical flow 68 2.3.2. Motion estimation seen as an optimal transport problem 70 2.4. Probabilistic approaches 74 2.5. Image registration 76 2.5.1. Transformation 77 2.5.2. Similarity function 78 2.5.3. Optimization 78 2.5.4. Practical considerations 79 2.6. Local methods 79 2.6.1. Block or primitive-matching 79 2.6.2. Least-square estimation 81 2.7. Hybrid methods 81 2.7.1. Power spectrum-based methods 82 2.7.2. Spatiotemporal description 82 2.8. Phase-based methods 84 2.8.1. Fleet and Jepson’s method 85 2.8.2. Analytic and monogenic signal 86 2.8.3. Harmonic phase methods 88 2.9. Registration and motion estimation in a sequence of images 89 2.9.1. Lagrangian description 89 2.9.2. Eulerian description 91 2.9.3. Strategies for the estimation in sequence 91 2.10. Evaluation of motion estimation methods 92 2.11. Conclusion 95 2.12. Bibliography 95 CHAPTER 3. POST-PROCESSING AND ANALYSIS OF DYNAMIC MAGNETIC RESONANCE IMAGES FOR MYOCARDIAL PERFUSION QUANTIFICATION 103Bruno NEYRAN and Magalie VIALLON 3.1. Introduction 103 3.2. Dynamic measurement of perfusion with contrast agents: reminder about the MRI sequences and the different contrast agents used 107 3.2.1. Brief reminder about cardiac perfusion MRI sequences 107 3.2.2. MRI signal conversion/tracer concentration 107 3.2.3. Different clinical-candidate contrast agents 108 3.3. Motion correction and contour segmentation of the myocardium: important preprocessing prior to quantitative analysis 109 3.3.1. Dynamic image registration 109 3.3.2. Automatic contour extraction 109 3.4. Semi-quantitative perfusion analysis: calculation of relative parameters depending on the injection of the contrast medium 110 3.4.1. Semi-quantitative perfusion parameters 110 3.4.2. Heuristic modeling using a varied gamma function 112 3.4.3. Heuristic modeling with a bi-exponential function 114 3.4.4. Heuristic modeling with the Moate model 115 3.5. Absolute parameters independent of the contrast agent injection (taking account of the arterial input): pharmacokinetic modeling 117 3.5.1. General studies: tracer kinetics theory 118 3.5.2. Identification of the residual function 127 3.5.3. Identification of the discrete residual function 129 3.6. Conclusion 133 3.7. Bibliography 135 CHAPTER 4. TENSOR DECOMPOSITION OF A DYNAMIC SEQUENCE OF IMAGES INTO SIMPLE ELEMENTS 141Frédérique FROUIN and Claire PELLOT-BARAKAT 4.1. Problematics 141 4.2. Panorama of methods for the quantitative analysis of dynamic image sequences 143 4.2.1. Regions of interest method 143 4.2.2. Parametric imaging methods 144 4.2.3. Movement analysis methods 145 4.2.4. Tensor decomposition of a sequence of images into simple elements 145 4.3. Tensor decomposition methods of an image sequence into simple elements 146 4.3.1. Notations and decomposition principle 146 4.3.2. Orthogonal decomposition of an image sequence 147 4.3.3. Decomposition into simple elements 148 4.4. Specifications for radiotracer or contrast medium monitoring 149 4.4.1. Proposed approach objectives and associated constraints definition 149 4.4.2. Components estimation principle 149 4.4.3. Example of tensor decomposition into simple elements in myocardial perfusion studies 152 4.4.4. Limitations of the proposed approach 153 4.4.5. Clinical applications of the tensor decomposition into simple elements for cardiac imaging 155 4.5. Specifications for the study of cardiac motion 156 4.5.1. Proposed approach objectives and associated constraint definition 156 4.5.2. Tensor decomposition method solution 157 4.5.3. Tensor decomposition model extensions 160 4.5.4. Clinical applications and perspectives 164 4.6. Conclusion 165 4.7. Bibliography 166 PART 2. APPLICATION EXAMPLES 169 CHAPTER 5. EVALUATION OF CARDIAC STRUCTURE SEGMENTATION IN CINE MAGNETIC RESONANCE IMAGING 171Alain LALANDE, Mireille GARREAU and Frédérique FROUIN 5.1. Context: significance of the automatic segmentation of the cardiac structures 171 5.1.1. Cine MRI in short-axis orientation 171 5.1.2. Left ventricle and right ventricle 172 5.2. Evaluation necessity 175 5.2.1. The place of evaluation 175 5.2.2. Analytic and empirical methods 176 5.3. Empirical evaluation methods 177 5.4. Visual evaluation methods 179 5.5. Supervised methods 180 5.5.1. The definition of a reference 180 5.5.2. Creation of an expert database 183 5.5.3. Evaluation criterion: edge-based approaches 184 5.5.4. Evaluation criteria: region-based approaches 188 5.5.5. Supervised methods for the estimation of a clinical parameter 192 5.5.6. ROC curves 193 5.5.7. Comparison of the supervised methods 194 5.5.8. Limitations of the supervised methods 195 5.6. Non-supervised evaluation methods 198 5.6.1. Unsupervised methods relying on region- or edge-based descriptors 198 5.6.2. Methods using a clinical parameter 202 5.6.3. Estimation methods of a reference segmentation 204 5.6.4. Difficulties in unsupervised methods 205 5.7. Conclusion 205 5.8. IMPEIC and MEDIEVAL working groups 207 5.9. Bibliography 209 CHAPTER 6. PHASE-BASED HEART MOTION ESTIMATION IN MULTIMODALITY CARDIAC IMAGING 217Martino ALESSANDRINI, Adrian BASARAB, Olivier BERNARD and Philippe DELACHARTRE 6.1. Phase images 218 6.1.1. Multidimensional analytic signals 218 6.1.2. Monogenic signal 219 6.2. Optical flow motion estimation on the phase of the two single-orthant analytic signals and using a deformable mesh: application to cardiac MRI sequences 221 6.2.1. Optical flow method applied to spatial phase images 223 6.2.2. Parametric modeling of local motion 226 6.2.3. Trajectory estimation 228 6.2.4. Results 230 6.2.5. Conclusion 235 6.3. Motion estimation by optical flow from the monogenic phase using a local affine model and multiscale analysis – application to ultrasonic cardiac sequences 236 6.3.1. Affine model 237 6.3.2. Multiscale choice of the window size 238 6.3.3. Iterative refinement of the displacement 238 6.4. Bibliography 244 CHAPTER 7. CARDIAC MOTION ANALYSIS IN TAGGED MRI 247Patrick CLARYSSE and Pierre CROISILLE 7.1. Motion quantification by the SinMod method 248 7.2. Processing pipeline and features of the software inTag 250 7.2.1. Data and input parameters 251 7.2.2. Motion field estimation 251 7.2.3. LV contour extraction 252 7.2.4. LV motion and deformation analysis 252 7.3. Perspectives 254 7.4. Bibliography 254 CHAPTER 8. LEFT VENTRICLE MOTION ESTIMATION IN COMPUTED TOMOGRAPHY IMAGING 257Antoine SIMON, Mireille GARREAU, Régis DELAUNAY, Dominique BOULMIER, Erwan DONAL and Christophe LECLERCQ 8.1. Introduction 257 8.1.1. Clinical problem and objectives 257 8.1.2. Technological choice: cardiac CT imaging 258 8.1.3. State of the art and method positioning 259 8.2. Surface matching method 262 8.2.1. Surface segmentation and reconstruction stage 262 8.2.2. Surface–surface matching 263 8.3. Surface–surface approach evaluation 267 8.3.1. Simulated data 267 8.3.2. Real data 270 8.4. Surface–surface approach conclusion 278 8.5. Surface and volume matching method: surface–volume approach 278 8.6. Surface–volume approach evaluation 280 8.6.1. Simulated data 280 8.6.2. Real data 283 8.7. Conclusion 285 8.8. Acknowledgments 287 8.9. Bibliography 287 PART 3 . TOWARD PATIENT-SPECIFIC CARDIOLOGY 293 CHAPTER 9. PERSONALIZATION OF ELECTROMECHANICAL MODELS OF THE CARDIAC VENTRICULAR FUNCTION BY HETEROGENEOUS CLINICAL DATA ASSIMILATION 295Stephanie MARCHESSEAU, Maxime SERMESANT, Florence BILLET, Hervé DELINGETTE and Nicholas AYACHE 9.1. Introduction 295 9.2. Anatomy and electrophysiology personalization from clinical data 298 9.2.1. Personalization of the heart and the tissue structure anatomy 298 9.2.2. Cardiac electrophysiology personalization 300 9.3. Heart mechanics modeling 302 9.3.1. Modeling of the Bestel–Clément–Sorine electromechanical coupling 302 9.3.2. Blood flow modeling 304 9.3.3. Other boundary conditions 305 9.3.4. Discussion about this model 306 9.4. Image data processing: cardiac kinematics personalization 306 9.4.1. Metrics for the comparison between observed and simulated motion 307 9.4.2. Data time interpolation 307 9.4.3. Deformable models approach 308 9.4.4. Data displacement case 310 9.4.5. Velocity data case 311 9.4.6. Results with cine-MRI data 311 9.4.7. Results from dynamic CT data 312 9.5. Calibration of the mechanical parameters from global data 313 9.5.1. Available data description 314 9.5.2. Unscented transform calibration 315 9.5.3. Calibration results with healthy volunteers 317 9.5.4. Calibration results with pathological cases 317 9.6. Mechanical personalization by variational data assimilation 318 9.6.1. Variational approach on a simplified model 320 9.6.2. Application to synthetic cases 321 9.6.3. Application to clinical cases 322 9.6.4. Sequential approach on full model 322 9.7. Conclusion 323 9.8. Bibliography 324 CONCLUSION 331 APPENDIX 1 335 APPENDIX 2 339 LIST OF AUTHORS 343 INDEX 347

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Book SynopsisImage processing and image analysis are typically important fields in information science and technology. By “image processing”, we generally understand all kinds of operation performed on images (or sequences of images) in order to increase their quality, restore their original content, emphasize some particular aspect of the information or optimize their transmission, or to perform radiometric and/or spatial analysis. By “image analysis” we understand, however, all kinds of operation performed on images (or sequences of images) in order to extract qualitative or quantitative data, perform measurements and apply statistical analysis. Whereas there are nowadays many books dealing with image processing, only a small number deal with image analysis. The methods and techniques involved in these fields of course have a wide range of applications in our daily world: industrial vision, material imaging, medical imaging, biological imaging, multimedia applications, satellite imaging, quality control, traffic control, and so onTable of ContentsPart 1. An Overview of Image Processing and Analysis (IPA) 1. Gray-Tone Images. 2. Gray-Tone Image Processing and Analysis. 3. Binary Images. 4. Binary Image Processing and Analysis. 5. Key Concepts and Notions for IPA. 6. Mathematical Imaging Frameworks. Part 2. Basic Mathematical Reminders for Gray-Tone and Binary Image Processing and Analysis 7. Basic Reminders in Set Theory. 8. Basic Reminders in Topology and Functional Analysis. Part 3. The Main Mathematical Notions for the Spatial and Tonal Domains 9. The Spatial Domain. 10. The Tonal Domain. Part 4. Ten Main Functional Frameworks for Gray Tone Images 11. The Algebraic and Order Functional Framework. 12. The Morphological Functional Framework. 13. The Integral Functional Framework. 14. The Convolutional Functional Framework. 15. The Differential Functional Framework. 16. The Generalized Functional Framework. 17. The Frequential Functional Framework. 18. The Multiscale Functional Framework. 19. The Variational Functional Framework. 20. The Probabilistic Functional Framework.

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Book SynopsisThis textbook provides comprehensive coverage for courses in the basics of design and implementation of digital filters. The book assumes only basic knowledge in digital signal processing and covers state-of-the-art methods for digital filter design and provides a simple route for the readers to design their own filters. The advanced mathematics that is required for the filter design is minimized by providing an extensive MATLAB toolbox with over 300 files. The book presents over 200 design examples with MATLAB code and over 300 problems to be solved by the reader. The students can design and modify the code for their use. The book and the design examples cover almost all known design methods of frequency-selective digital filters as well as some of the authors’ own, unique techniques. Table of ContentsIntroduction.- Signals and Transforms.- Discrete-Time and Digital Filters.- Filter Algorithms.- Finite Wordlength Effects.- Synthesis of Fir Filters.- Realization of Fir Filters.- Synthesis of Analog Filters.- Analog Filters with Lumped and Distributed Elements.- Synthesis of IIR Filters.- Wave Digital Filters.- Ladder Wave Digital Filters.- Symmetric Wave Digital Filters.- Frequency-Response Masking Filters.- Sampling Rate Converters.- Multirate Filters.- Implementation of Digital Filters.- References.- Index.

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Book SynopsisThis comprehensive reference provides easy access to relevant information on all aspects of Computer Vision. An A-Z format of over 240 entries offers a diverse range of topics for those seeking entry into any aspect within the broad field of Computer Vision. Over 200 Authors from both industry and academia contributed to this volume.Each entry includes synonyms, a definition and discussion of the topic, and a robust bibliography. Extensive cross-references to other entries support efficient, user-friendly searches for immediate access to relevant information. Entries were peer-reviewed by a distinguished international advisory board, both scientifically and geographically diverse, ensuring balanced coverage. Over 3700 bibliographic references for further reading enable deeper exploration into any of the topics covered.The content of Computer Vision: A Reference Guide is expository and tutorial, making the book a practical resource for students who are considering entering the field, as well as professionals in other fields who need to access this vital information but may not have the time to work their way through an entire text on their topic of interest.Table of ContentsOver 240 entries organized A to Z.

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Book SynopsisIn der hochbitratigen optischen Nachrichtentechnik ist es wichtig, parasitäre induktive und kapazitive Einflüsse auf die Funktion von Laser- und Fotodioden zu kompensieren. Wegen des nichtlinearen Charakters der u-i-Relationen der Induktivitäten, Kapazitäten und Widerstände ist es möglich, Kompensationsverfahren gegen parasitäre Effekte zu entwickeln oder die Nichtlinearitäten gezielt zur Signalübertragung einzusetzen. Reiner Thiele beweist, dass bei Applikation der vorgestellten Kompensationsverfahren kapazitive und induktive Influenzen auf die Grundfunktion der optoelektronischen Bauelemente vermeidbar sind, das Klemmenverhalten durch die u-i-Kennlinien von Laser- oder Fotodioden komplett erfasst wird und ungünstige Einflüsse der Systemumgebung auf die optoelektronischen Schaltungen vermieden werden. Außerdem stellt er Definitionen für optoelektronische Grundstromkreise sowie ihre Berechnung für die Applikation gleichartiger Laser- oder Fotodioden als Sende- bzw. Empfangsbauelemente der optischen Nachrichtentechnik vor.Der Autor: Prof. Dr.-Ing. Reiner Thiele lehrte an der Hochschule Zittau/Görlitz und unterrichtet derzeit an der Staatlichen Studienakademie Bautzen.Table of ContentsParameter von Dioden.- Kompensation elektromagnetischer Beeinflussungen.- Optoelektronische Grundstromkreise.

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Book SynopsisThis book presents the peer-reviewed proceedings of the Sixth International Conference on Intelligent Computing and Applications (ICICA 2020), held at Government College of Engineering, Keonjhar, Odisha, India, during December 22–24, 2020. The book includes the latest research on advanced computational methodologies such as neural networks, fuzzy systems, evolutionary algorithms, hybrid intelligent systems, uncertain reasoning techniques, and other machine learning methods and their applications to decision-making and problem-solving in mobile and wireless communication networks.Table of ContentsClosed Loop Vision Based Ball Balancer.- A Novel Network Learning For Image Compressive Sensing.- COVID – 19 Severıty Predıctıons: An Analysis Usıng Correlatıon Measures.- A Novel Methodology for Comparative Analysis of Power Quality Improvement for a 3 Phase DC/AC Embedded DC/DC Converter.- Performance of Photovoltaic based ZETA Converter Water Pumping Application.- Performance Analysis of Radial Distribution System by Optimal Deployment of DG and DSTATCOM Considering Network Reconfiguration using a SAR Algorithm.

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Book SynopsisThis book is a collection of selected high-quality research papers presented at the International Conference on Computing in Engineering and Technology (ICCET 2021), organized by Dr. Babasaheb Ambedkar Technological University, Lonere, India, during January 30–31, 2021. Focusing on frontier topics and next-generation technologies, it presents original and innovative research from academics, scientists, students and engineers alike. The theme of the conference is Applied Information Processing System.Table of ContentsChapter 1. CNN parameter adjustment for brain tumor classification.- Chapter 2. Advance Fuzzy Radial Basis Function Neural Network.- Chapter 3. Unbounded Fuzzy Radial Basis Function Neural Network Classifier.- Chapter 4. A study on the adaptability of Deep Learning-based Polar coded NOMA in Ultra-Reliable Low-Latency Communication Scenario.- Chapter 5. Heart Rate Variability based Mental Stress Detection using Deep Learning Approach.- Chapter 6. Product Based Market Analysis using Deep Learning.- Chapter 7. Driver drowsiness detection using Deep-Learning Chapter 8. Emotion detection from social media-based using machine learning techniques: A Survey.- Chapter 9. Deep age estimation using sclera images in multiple environment.- Chapter 10. Data Handling Approach for Machine Learning in Wireless Communication: A Survey.- Chapter 11. Breast cancer detection in mammograms using deep learning.- Chapter 12. Deep learning based Parameterized Framework to investigate the influence of Pedagogical Innovations in Engineering Courses.- Chapter 13. Modern Transfer Learning based preliminary diagnosis of COVID-19 using forced cough recordings with Mel-frequency cepstral coefficients.- Chapter 14. Biomedical Text Summarization: A Graph Based Ranking Approach.- Chapter 15. EEG based Diagnosis of Alzheimer's Disease Using Kolmogorov Complexity.

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Book SynopsisThis book provides insights into the Third International Conference on Intelligent Systems and Signal Processing (eISSP 2020) held By Electronics & Communication Engineering Department of G H Patel College of Engineering & Technology, Gujarat, India, during 28–30 December 2020. The book comprises contributions by the research scholars and academicians covering the topics in signal processing and communication engineering, applied electronics and emerging technologies, Internet of Things (IoT), robotics, machine learning, deep learning and artificial intelligence. The main emphasis of the book is on dissemination of information, experience and research results on the current topics of interest through in-depth discussions and contribution of researchers from all over world. The book is useful for research community, academicians, industrialists and postgraduate students across the globe.Table of ContentsChapter 1: Design and Analysis of Modified Split Ring Resonator Structured Multiband Antenna for WCDMA and WiMAX Applications.- Chapter 2: A Wearable Finger Exoskeleton For Motor Rehabilitation Using Mobile Application.- Chapter 3: Game theoretical approach for cluster-based routing protocol in Wireless Sensor Networks.- Chapter 4: Advance Digital Signal Processing for Interference Mitigation in Very High Throughput Satellite.- Chapter 5: Low-Power Endoscopic Image Compression Algorithms Using Modified Golomb Codes.- Chapter 6: Image Steganography Using Ridgelet Transform and SVD.- Chapter 7: HWCMA and HW-LS-CMA blind learning method for intelligent antenna system.- Chapter 8: Performance evaluation of prediction algorithm based tracking methods in a recovery of a lost target using Wireless Sensor Network.- Chapter 9: An Efficient Convolutional Neural Network for Acute Pain Recognition using HRV Features.- Chapter 10: Design and development of LSTM–RNN model for the prediction of RR intervals in ECG signals.- Chapter 11: FHSS Signals Classification by Linear Discriminant in a Multi-Signal Environment.- Chapter 12: Non-invasive Thyroid detection using thermal Imaging technique.- Chapter 13: Non Orthogonal Multiple Access Techniques for Next Generation Wireless Networks: A Review.- Chapter 14: Triple band circular patch antenna using complimentary split ring resonators.- Chapter 15: Features Analysis of Electroencephalography (EEG) for Mindfulness Meditation Effect on Cancer Patient toward Stress Level.

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Book SynopsisThe book is a collection of academician Yanzhong Zhang’s research papers published in English. It represents the development of aerospace systems engineering and information technology in China over the past 4 decades. Regarded as the crucial reference materials of related disciplines, it falls into three categories, namely, information technique, aeronautical engineering strategy issue of development, as well as PhD thesis.Table of ContentsInformation Technique.- Aeronautical Engineering.- Strategy Issue of Development.- Ph.D. Thesis.

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Book SynopsisThis book gathers selected high-quality research papers presented at the 2nd International Conference on Advanced Computing Applications (ICACA 2021), held virtually during 27––28 March 2021. The book is divided into four sections. These are communication and computing, signal processing and multimedia, computational intelligence and data analytics and decision computing. The topics covered are advanced communication technologies, IoT-based systems and applications, network security and reliability, virtualization technologies, compressed sensors and multimedia applications, signal image and video processing, machine learning, pattern recognitions, intelligent computing, big data analytics, analytics in bio-computing, AI-driven 6G mobile wireless networks and autonomous driving.Table of ContentsInternet of Things-based Animal Health Monitoring and Management.- Cryptanalysis of an Authentication and Key Management Scheme in Context of Generic Hierarchical IoT Network.- Personalized Smart Recommendation System for Industrial Internet of Things.- IoT Based Anti-Poaching Technology to Save Wildlife.- GeoLens: Geospatial Location Exploration Using Mobile Crowdsensing in Tourism 4.0: A case study of Kunjanagar, Falakata, West Bengal.- IoT Cloud System for Streetlights Monitoring based on Solar Energy using ESP32.- Smart Vehicle Management System using Internet of Vehicles (IoV).- IoT Based Real Time HRV Performance Analysis.- Implementation of Acoustic Source Localization on Edge-IoT Platform.- Internet of Things Platform for Advantageous Renewable Energy Generation.

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Book SynopsisThis book presents the proceedings of the International Science and Technology Conference “FarEastCon 2021,” which took place on October 5–8, 2021, in Vladivostok, Russian Federation. The book discusses modern achievements and promising research in the sphere of intelligent technologies in solving real, applied problems in various fields of industry and economic policies of different countries. Featuring selected papers from the conference, this book is of interest to experts in various fields whose work involves developing innovative solutions and increasing the efficiency of economic activities.Table of ContentsOperator of Connection Between the Langmuir Equation and Oparin’s Kinematic Equation for Pendulum-Type Waves. Part I.- Operator of Connection Between the Langmuir Equation and Oparin’s Kinematic Equation for Pendulum-Type Waves. Part II.- Operator of Connection Between the Langmuir Equation and Oparin’s Kinematic Equation for Pendulum-Type Waves. Part III.- On Algorithms of Digital Simulators in Education.- Problems and Risks of the It Outsourcing Market in Russia.- Investment Prospects for Renewable Energy Projects in the Republic of Buryatia.- Software Development Technology for Predictive Analysis of the Functioning of Credit Institutions.- Method for Assessing Organization System Quality.- Analysis of the Management of Sector “Security” as Part of the Strategic Management of Bulgaria.- Circular Economy (CE) Innovation and Internationalization of Small and Medium Enterprises (SMEs): Geographical Overview and Sectorial Patterns.- Methodology for Evaluating the Effectiveness of Implementing Investments in Lean Enterprise Production.- Perfection of the Process of Interaction of Various Types of Transport in the Far Eastern Transport Hubs.

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Book SynopsisTo meet the increasing demand of electrical power, the use of renewable energy-based smart grid is attracting significant attention in recent years throughout the world. The high penetration of renewable power in the smart grids is growing its importance due to its non-finishing, reusable, reliable, sustainable, lower cost, and available characteristics. The renewable energy-based smart grid technology may mitigate the increasing energy demands effectively and efficiently without hampering the environment. But the uncertain nature of renewable sources largely affects the operation of the smart grid by un-stabling the voltage and frequency that may introduces power quality and reliability problems, which requires special control techniques. This book investigates the challenges in controlling renewable energy-based smart grids and proposes different control techniques to control the voltage and frequency effectively to improve the power quality and reliability of the power grids. This book is a valuable resource for readers interested in practical solutions in smart grids and renewable energy systems.Table of ContentsChapter 1: A Robust Controller for Multi-level Distributed Generation Based Island-ed Microgrid.- Chapter 2: Multi-source Microgrid Fre-quency Stability Control Using Learning-Based Technology.- Chapter 3: Hybrid Renewable Energy Sys-tems for Future Power Grids.- Chapter 4: Operation of Renewable Ener-gy and Energy Storage-based Hybrid Re-mote-area Power Sup-ply (RAPS) Systems: Challenges and State-of-the-arts.- Chapter 5: A Symbolic Aggregate Approx-imation-based Data Mining Tool for the Detection and Classification of Power Grid Voltage Events.- Chapter 6: Identifying Hosting Capacity of Renewable DG units in Smart Grids Con-sidering Protection Systems.- Chapter 7: Management of Distributed Generation for Smart Buildings.- Chapter 8: Smart Inverters and Controls for Grid-Connected Renewable Energy Sources.- Chapter 9: Transformerless Three-Phase Solar Photovoltaic Converters.- Chapter 10: Sensorless Control Technolo-gies for Stand-alone and Grid-connected Operation of Brush-less Doubly-Fed In-duction Generators in Smart Grid.- Chapter 11: Control and Observation of Induction Motors Based on Full-Order Terminal Sliding Mode Technique.

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Book SynopsisThis volume consists of selected peer reviewed papers from the 10th International Conference on Mechatronics and Control Engineering (ICMCE 2021) discussing latest advances in mechanical engineering and dynamic analysis, sensor technology and application, mechanical design and system modelling, control system and engineering, robot design and control engineering, development and performance analysis of functional materials. Additional themes include methodologies, algorithms, applications and knowledge discovery in mechatronics and control engineering. This volume will prove a valuable resource for those in academia and industry.Table of ContentsMechanical engineering and dynamic analysis.- Sensor Technology and Application.- Mechanical Design and System Modelling.- Control System and Engineering.- Robot design and control Engineering.- Development and performance analysis of functional materials.

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Book SynopsisThis book presents and analyzes methods to perform image co-segmentation. In this book, the authors describe efficient solutions to this problem ensuring robustness and accuracy, and provide theoretical analysis for the same. Six different methods for image co-segmentation are presented. These methods use concepts from statistical mode detection, subgraph matching, latent class graph, region growing, graph CNN, conditional encoder–decoder network, meta-learning, conditional variational encoder–decoder, and attention mechanisms. The authors have included several block diagrams and illustrative examples for the ease of readers. This book is a highly useful resource to researchers and academicians not only in the specific area of image co-segmentation but also in related areas of image processing, graph neural networks, statistical learning, and few-shot learning.Table of ContentsIntroduction.- Survey of Image Co-segmentation.- Mathematical Background.- Co-segmentation using a Classification Framework.- Use of Maximum Common Subgraph Matching.- Maximally Occurring Common Subgraph Matching.- Co-segmentation using Graph Convolutional Neural Network.- Use of a Conditional Siamese Convolutional Network.- Few-shot Learning for Co-segmentation.- Conclusions.

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Book SynopsisPanoramic imaging is a progressive application and research area. This technology has applications in digital photography, robotics, film productions for panoramic screens, architecture, environmental studies, remote sensing and GIS technology. Applications demand different levels of accuracy for 3D documentation or visualizations. This book describes two modern technologies for capturing high-accuracy panoramic images and range data, namely the use of sensor-line cameras and laser range-finders. It provides mathematically accurate descriptions of the geometry of these sensing technologies and the necessary information required to apply them to 3D scene visualization or 3D representation. The book is divided into three parts: Part One contains a full introduction to panoramic cameras and laser range-finders, including a discussion of calibration to aid preparation of equipment ready for use. Part Two explains the concept of stereo panoramic imaging,Table of ContentsPreface. Series Preface. Website and Exercises. List of Symbols. 1. Introduction. 1.1 Panoramas 1.2 Panoramic Paintings 1.3 Panoramic or Wide-Angle Photographs 1.4 Digital Panoramas 1.5 Striving for Accuracy 1.6 Exercises 1.7 Further Reading 2. Cameras and Sensors. 2.1 Camera Models 2.2 Optics 2.3 Sensor Models 2.4 Examples and Challenges 2.5 Exercises 2.6 Further Reading 3. Spatial Alignments. 3.1 Mathematical Fundamentals 3.2 Central Projection:World into Image Plane 3.3 Classification of Panoramas 3.4 Coordinate Systems for Panoramas 3.5 General Projection Formula for Cylindrical Panorama 3.6 Rotating Cameras 3.7 Mappings between Different Image Surfaces 3.8 Laser Range-Finder 3.9 Exercises 3.10 Further Reading 4. Epipolar Geometry. 4.1 General Epipolar Curve Equation 4.2 Constrained Poses of Cameras 4.3 Exercises 4.4 Further Reading 5. Sensor Calibration. 5.1 Basics 5.2 Preprocesses for a Rotating Sensor-Line Camera 5.3 A Least-Square Error Optimization Calibration Procedure 5.4 Geometric Dependencies of R and w 5.5 Error Components in LRF Data 5.6 Exercises 5.7 Further Reading 6. Spatial Sampling. 6.1 Stereo Panoramas 6.2 Sampling Structure 6.3 Spatial Resolution 6.4 Distances between Spatial Samples 6.5 Exercises 6.6 Further Reading 7. Image Quality Control. 7.1 Two Requirements 7.2 Terminology 7.3 Parameter Optimization 7.4 Error Analysis 7.5 Exercises 7.6 Further Reading 8. Sensor Analysis and Design. 8.1 Introduction 8.2 Scene Composition Analysis 8.3 Stereoacuity Analysis 8.4 Specification of Camera Parameters 8.5 Exercises 8.6 Further Reading 9. 3D Meshing and Visualization. 9.1 3D Graphics 9.2 Surface Modeling 9.3 More Techniques for Dealing with Digital Surfaces 9.4 Exercises 9.5 Further Reading 10. Data Fusion. 10.1 Determination of Camera Image Coordinates 10.2 Texture Mapping 10.3 High Resolution Orthophotos 10.4 Fusion of Panoramic Images and Airborne Data 10.5 Exercises 10.6 Further Reading References. Index.

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Book SynopsisMultivariate imagery is now a very common tool in numerous applications, ranging from satellite remote sensing and astrophysics to biomedical imagery, monitoring of the environment or industrial inspection. Multivariate must be understood in th emost general way: color and multispectral imaging, but also multimodal, multisource or multitemporal imagery. In all the cases, the multivariate image corresponds to a set of standard grey level images. The availability of the additional diversity, be it spectral temporal and s.o., provides an invaluable source of information, enabling to consider a wide range of new applications. However, in order to address these applications, theoretical developments are required in terms of signal and image processing, or, more generally speaking, information processing. As a matter of fact, most of the standard algorithms designed for grey level images do not generalize easily to multidimensional spaces and some specific derivations are required. This book aims at presenting the most recent advances in signal and image processing for the analysis of multivariate data. It should be helpful for electrical engineers, PhD students and researcher working in the field of signal processing, but also for any engineer dealing with some specific application where multidimensional data are processed.Trade Review"A most welcome addition to the publishers' series on Digital Signal and Image Processing, this handsome book of fourteen chapters has perforce to be highly selective in its choice of subject matter. It is a welcome addition to the studies on the subject of multivariate image processing. All chapters measure up to this reviewer's expectations. This book aims at presenting the most recent advances in signal and image processing for the analysis of multivariate data. It should be helpful for electrical engineers, students at higher levels, and researchers working in the field of signal processing, and extremely ideal for any engineer dealing with a specific application where multidimensional data are processed." (Current Engineering Practice, 26 October 2010)Table of Contents1. Introduction to Multivariate Image Processing from the Basics to New Challenges. 2. Registration. 3. Fusion of SAR and Optical Data. 4. Fusion of Satellite Images at Different Resolutions. 5. Multitemporal Processing and Change Detection. 6. Bayesian Approach to Linear Spectral Mixture Analysis. 7. Detection and Tracking of Emission Rays in Radioastronomy. 8. Wavelet Transform for the Denoising of Multivariate Images. 9. Bayesian Approach for Polarization-encoded Image Analysis. 10. Unsupervised Classification for Multivariate Images. 11. Noise Estimation.

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Book SynopsisWireless optical communication refers to communication based on the unguided propagation of optical waves. The past 30 years have seen significant improvements in this technique – a wireless communication solution for the current millennium – that offers an alternative to radio systems; a technique that could gain attractiveness due to recent concerns regarding the potential effects of radiofrequency waves on human health. The aim of this book is to look at the free space optics that are already used for the exchange of current information; its many benefits, such as incorporating channel properties, propagation models, link budgets, data processing including coding, modulation, standards and concerns around health and safety (IEC 60825 or FCC - Class 1 for example), etc. will become indispensable over the next decade in addressing computer architectures for short-, medium- and long-range telecommunications as we move from gigabytes to terabytes per second. Wireless Optical Communications is an excellent tool for any engineer wanting to learn about wireless optical communications or involved in the implementation of real complete systems. Students will find a wide range of information and useful concepts such as those relating to propagation, optics and photometry, as well the necessary information on safety. Contents 1. Light. 2. History of Optical Telecommunications. 3. The Contemporary and the Everyday Life of Wireless Optical Communication. 4. Propagation Model. 5. Propagation in the Atmosphere. 6. Indoor Optic Link Budget. 7. Immunity, Safety, Energy and Legislation. 8. Optics and Optronics. 9. Data Processing. 10. Data Transmission. 11. Installation and System Engineering. 12. Conclusion.Table of ContentsForeword.xi Pierre-Noël FAVENNEC Acronyms xiii Introduction.xix Chapter 1. Light 1 Chapter 2. History of Optical Telecommunications 7 2.1. Some definitions 7 2.2. The prehistory of telecommunications 8 2.3. The optical aerial telegraph 11 2.4. The code 14 2.5. The optical telegraph 18 2.6. Alexander Graham Bell’s photophone 20 Chapter 3. The Contemporary and the Everyday Life of Wireless Optical Communication 25 3.1. Basic principles 25 3.2. Wireless optical communication 53 Chapter 4. Propagation Model 63 4.1. Introduction.63 4.2. Baseband equivalent model 63 4.3. Diffuse propagation link budget in a confined environment 73 Chapter 5. Propagation in the Atmosphere 85 5.1. Introduction.85 5.2. The atmosphere 86 5.3. The propagation of light in the atmosphere 87 5.4. Models.93 5.5. Experimental set-up 103 5.6. Experimental results.104 5.7. Fog, haze, and mist 107 5.8. The runway visual range (RVR) 108 5.9. Calculating process of an FSO link availability 114 5.10. Conclusion 116 Chapter 6. Indoor Optic Link Budget.119 6.1. Emission and reception parameters 119 6.2. Link budget for line of sight communication 128 6.3. Link budget for communication with retroreflectors.132 6.4. Examples of optical budget and signal-to-noise ratio (SNR) 135 Chapter 7. Immunity, Safety, Energy and Legislation 141 7.1. Immunity 141 7.2. The confidentiality of communication 149 7.3. Energy 153 7.4. Legislation 154 Chapter 8. Optics and Optronics 157 8.1. Overview 157 8.2. Optronics: transmitters and receivers.157 8.3. Optics 170 Chapter 9. Data Processing 177 9.1. Introduction.177 9.2. Modulation 178 9.3. The coding 184 Chapter 10. Data Transmission 197 10.1. Introduction 197 10.2. Point-to-point link 201 10.3. Point-to-multipoint data link 206 10.4. Summary 212 Chapter 11. Installation and System Engineering 213 11.1. Free-space optic system engineering and installation 213 11.2. Wireless optical system installation engineering in limited space 225 Chapter 12. Conclusion.237 APPENDICES 241 Appendix 1. Geometrical Optics, Photometry and Energy Elements 243 Appendix 2. The Decibel Unit (dB) 257 Bibliography 261 List of Figures 273 List of Tables 277 List of Equations 279 Index 283

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Book SynopsisThis book presents a substantial description of the principles and applications of digital holography.The first part of the book deals with mathematical basics and the linear filtering theory necessary to approach the topic. The next part describes the fundamentals of diffraction theory and exhaustively details the numerical computation of diffracted fields using FFT algorithms. A thorough presentation of the principles of holography and digital holography, including digital color holography, is proposed in the third part.A special section is devoted to the algorithms and methods for the numerical reconstruction of holograms. There is also a chapter devoted to digital holographic interferometry with applications in holographic microscopy, quantitative phase contrast imaging, multidimensional deformation investigations, surface shape measurements, fluid mechanics, refractive index investigations, synthetic aperture imaging and information encrypting.Keys so as to understand the differences between digital holography and speckle interferometry and examples of software for hologram reconstructions are also treated in brief. Contents 1. Mathematical Prerequisites.2. The Scalar Theory of Diffraction.3. Calculating Diffraction by Fast Fourier Transform.4. Fundamentals of Holography.5. Digital Off-Axis Fresnel Holography.6. Reconstructing Wavefronts Propagated through an Optical System.7. Digital Holographic Interferometry and Its Applications.Appendix. Examples of Digital Hologram Reconstruction ProgramsTable of ContentsIntroduction xv Chapter 1. Mathematical Prerequisites 1 Chapter 2. The Scalar Theory of Diffraction 27 Chapter 3. Calculating Diffraction by Fast Fourier Transform 77 Chapter 4. Fundamentals of Holography 115 Chapter 5. Digital Off-Axis Fresnel Holography 165 Chapter 6. Reconstructing Wavefronts Propagated through an Optical System 237 Chapter 7. Digital Holographic Interferometry and Its Applications 271 Appendix. Examples of Digital Hologram Reconstruction Programs 319 Bibliography 339 Index 355

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Book SynopsisThe authors describe a technique that can visualize the atomic structure of molecules, it is necessary, in terms of the image processing, to consider the reconstruction of sparse images. Many works have leveraged the assumption of sparsity in order to achieve an improved performance that would not otherwise be possible. For nano MRI, the assumption of sparsity is given by default since, at the atomic scale, molecules aresparse structures. This work reviews the latest results on molecular imaging for nano MRI. Sparse image reconstruction methods can be categorized as either non-Bayesian or Bayesian. A comparison of the performance and complexity of several such algorithms is given.Table of ContentsIntroduction ix Chapter 1. Nano MRI 1 Chapter 2. Sparse Image Reconstruction 7 Chapter 3. Iterative Thresholding Methods 15 Chapter 4. Hyperparameter Selection Using the SURE Criterion 43 Chapter 5. Monte Carlo Approach: Gibbs Sampling 53 Chapter 6. Simulation Study 65 Bibliography 73 Index 77

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Book SynopsisThis book describes the different principles and equipment used in medical imaging. The importance of medical imaging for diagnostics is rapidly increasing. A good working knowledge of all the different possible physical principles involved in medical imaging is now imperative. This book covers many of these principles including matter photon interactions, the principles of detectors, detectors and information processing for radiology, X-ray tomography, positron tomography, single photon tomography and optical tomography.Table of ContentsForeword ix Guy FRIJA Chapter 1. Ultrasound Medical Imaging 1 Didier VRAY, Elisabeth BRUSSEAU, Valérie DETTI, François VARRAY, Adrian BASARAB, Olivier BEUF, Olivier BASSET, Christian CACHARD, Hervé LIEBGOTT, Philippe DELACHARTRE 1.1. Introduction 1 1.2. Physical principles of echography 3 1.2.1. Ultrasound waves 3 1.2.2. Wavefronts 4 1.2.3. Stress/Strain relation 5 1.2.4. Propagation equation 6 1.2.5. Acoustic impedance 7 1.2.6. Acoustic intensity 7 1.2.7. Mechanical Index 9 1.2.8. Generation, emission 9 1.2.9. Resolution 10 1.2.10. Propagation of a plane wave in a finite isotropic medium 11 1.2.11. Propagation of a plane wave in a non-homogeneous medium 13 1.2.12. Speckle 15 1.2.13. Nonlinear waves 16 1.2.14. Contrast agents 17 1.3. Medical ultrasound systems 18 1.3.1. Principle 18 1.3.2. The different stages in image formation 19 1.3.3. Ultrasound imaging probe 21 1.3.4. Modes of imaging, B-mode and M-mode, and harmonic imaging modes 24 1.3.5. Doppler imaging 27 1.4. The US image 34 1.4.1. Properties of speckle, echostructure and statistical laws 34 1.4.2. Segmentation of US images 38 1.4.3. Simulation of US images 41 1.5. Recent advances in ultrasound imaging 44 1.5.1. Generation/emission of ultrasounds 44 1.5.2. Signal- and image processing 49 1.5.3. Multimodal imaging 60 1.6. A bright future for ultrasound imaging 65 1.7. Bibliography 65 Chapter 2. Magnetic Resonance Imaging 73 Dominique SAPPEY-MARINIER and André BRIGUET 2.1. Introduction 73 2.2. Fundamental elements for MRI 76 2.2.1. Introduction 76 2.2.2. Vectorial description of nuclear magnetic resonance (NMR) 78 2.2.3. RF pulses and their effect on magnetizations 88 2.2.4. Elementary pulse sequences using the refocusing technique 97 2.2.5. Spatial discrimination of signals using gradients: fundamental principle of MRI 106 2.2.6. Multi-parameter aspect of MRI 110 2.3. Instrumentation 115 2.3.1. Introduction 115 2.3.2. Recording the signal 117 2.3.3. Magnetic systems 129 2.3.4. A typical MRI installation in a clinical environment 136 2.3.5. Operation and safety 139 2.4. Image properties 144 2.4.1. Introduction 144 2.4.2. Field of view 144 2.4.3. Spatial resolution 148 2.4.4. Contrast and signal 155 2.4.5. Contrast elements in MRI practice 162 2.5. Imaging sequences and modes of reconstruction 168 2.5.1. Introduction 168 2.5.2. Overall view of acquisition sequences 168 2.5.3. Modes of reconstruction 195 2.6. Application of MRI: uses and evolution in the biomedical field 208 2.6.1. Introduction 208 2.6.2. Spectroscopy and imaging: technical and clinical complementarity 210 2.6.3. Diffusion MRI: a morphological and functional approach 217 2.6.4. Functional MRI (fMRI) of cerebral activation 236 2.6.5. Bi-modal approach to MRI: the example of MR/PET 239 2.7. Bibliography 244 List of Authors 263 Index 265

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