Tabla de Contenidos: “…Intro -- Cover -- Half Title -- Title Page -- Copyright Page -- Contents -- Contributors -- Chapter 1 A Review on Comparative Study of Image-Denoising in Medical Imaging -- 1.1 Introduction -- 1.1.1 Evaluation of Image-Denoising Techniques -- 1.1.2 Image-Denoising Techniques -- 1.1.3 Applications -- 1.1.4 Comparison -- 1.2 Conclusion -- References -- Chapter 2 Remote-Sensing Image Classification: A Comprehensive Review and Applications -- 2.1 Introduction -- 2.1.1 Need for This Survey -- 2.1.2 Need for Remote-Sensing Image Classification -- 2.1.3 Significance of Remote-Sensing Image Classification -- 2.1.4 Research Gap for Deep Learning-Based Remote-Sensing Image Classification -- 2.2 Deep Learning Architectures for Remote-Sensing Image Classification -- 2.2.1 Convolutional Neural Networks (CNNs) -- 2.2.2 Fully Convolutional Networks (FCNs) -- 2.2.3 U-Net -- 2.2.4 SegNet -- 2.2.5 DeepLab -- 2.2.6 Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) Networks -- 2.2.7 Autoencoders -- 2.2.8 Generative Adversarial Networks (GANs) -- 2.2.9 Capsule Networks (CapsNets) -- 2.2.10 Attention-Based Mechanisms -- 2.2.11 Graph Convolutional Networks (GCNs) -- 2.2.12 Siamese Networks -- 2.2.13 3D Convolutional Neural Networks (3D-CNNs) -- 2.3 Differences in Deep Learning Architectures for Remote-Sensing Image Classification -- 2.3.1 Architecture -- 2.3.2 Input Data -- 2.3.3 Training Strategy -- 2.3.4 Transfer Learning -- 2.3.5 Optimization -- 2.3.6 Interpretability -- 2.4 Remote-Sensing Data Sources and Characteristics -- 2.4.1 Satellites -- 2.4.2 UAVs -- 2.4.3 Multispectral Sensors -- 2.4.4 Hyperspectral Sensors -- 2.4.5 Synthetic Aperture Radar (SAR) -- 2.4.6 Spatial Resolution -- 2.4.7 Spectral Resolution -- 2.4.8 Temporal Resolution -- 2.4.9 Radiometric Resolution -- 2.5 Application of Deep Learning in Remote Sensing…”

Tabla de Contenidos: “…Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Acknowledgments -- 1. …”

Tabla de Contenidos: “…Intro -- Cover Page -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Preface -- About the Authors -- 1 Overview of the Entrepreneur's Journey -- 2 Basics of Market Research -- 2.1 Basic Market Research Concepts -- 2.1.1 Primary and Secondary Market Research -- 2.1.2 Quantitative and Qualitative Data -- 2.1.3 "Miles Wide" versus "Deep Dives" Research -- 2.1.4 Types of Market Research -- 2.2 Preparing Your Market Research Plan -- 2.3 Collecting Data - Primary Research -- 2.3.1 Data Collection Methods -- 2.4 Secondary Research -- 2.4.1 Active Secondary Research -- 2.4.2 Passive Secondary Research -- 2.4.3 Internal Secondary Data -- 2.5 A Few Words on Ethics and Market Research -- 3 Basics of a Product-Market Fit -- 3.1 Getting Your Data -- 3.1.1 Conducting Conversations -- 3.1.2 Collecting Online Reviews -- 3.1.3 Organizing Online Surveys -- 3.2 Evaluating PMF -- 3.3 The Final Word -- 4 Basics of Intellectual Property Strategy -- 4.1 The IP Portfolio -- 4.1.1 Patents -- 4.1.2 Trademarks -- 4.1.3 Copyrights -- 4.1.4 Trade Secrets -- 4.2 Activities That Enhance the Value of Your IP Portfolio -- 4.2.1 Patentability Assessment -- 4.2.2 Freedom to Operate Search -- 4.3 Theranos and the Limits of the IP Portfolio -- 4.4 Final Thoughts -- 5 Developing a Customer-Centric Approach -- 5.1 Introduction to the Healthcare Ecosystem -- 5.1.1 Overview of the Healthcare Ecosystem -- 5.1.2 A Transforming Healthcare Ecosystem -- 5.2 Different Ecosystems, Different Payer Models -- 5.2.1 Single-Payer Healthcare -- 5.2.2 The Social Insurance Model -- 5.2.3 National Health Insurance Model -- 5.2.4 The Out-of-Pocket Model -- 5.2.5 Standing on Its Own: The United States -- 5.3 Correctly Identifying Your Client -- 5.3.1 Building Customer Profiles -- 5.4 Developing a Customer-Centric Approach -- 5.5 Closing Words -- 6 Developing Your Business Model…”

Tabla de Contenidos: “…You can see the shift Seeing supersedes reading A visual language Connect an image with your story Momentary magic: Infographics in business Breakdown of complex information The age of YouTube and business TL;DR: Too Long; Didn't Read CHAPTER TEN Putting Brevity to Work: Grainger and the Al and Betty Story PART THREE Decisiveness Gaining the decisiveness to know when and where to be brief CHAPTER ELEVEN Meeting You Half-Way Defeat the villains of meetings Meeting villain #1: Time Meeting villain #2: Type Meeting villain #3: Tyrants Change the format and tone -- make it a conversation Put brief back into a briefing Long story, short. …”

Tabla de Contenidos: “…Intro -- Title -- Copyright -- The ASTD Trainer's WorkShop Series -- Content -- Preface -- Chapter 1 - Introduction: How to Use This Book Effectively -- Why a Coaching Approach -- Utilizing This Workbook -- Definition of Terms -- Content of the Training -- How the Book Is Organized -- Icons -- What to Do Next -- Chapter 2 - Assessing the Needs of Learners -- Why Use Assessments -- The Right Questions to Ask -- Using the Training Objectives Matrix -- Resource Commitment -- Participant Training Objectives -- Matrix Rating Guide -- Other Assessment Methods -- What to Do Next -- Chapter 3 - Designing and Facilitating Engagement Training -- Design a Learner-Centered Training Program -- Basic Adult Learning Principles -- Factors That Drive Successful Training -- Present the Right Subject Matter -- 10 Tips for Better Presentations and Facilitation -- What to Do Next -- Chapter 4 - Evaluating Effectiveness -- Why Evaluation Is Important -- Benefits of Evaluation -- Classic Training Evaluation Levels -- A Few Four-Level Details -- What to Do Next -- Chapter 5 - Short Program Training-2.5 Hours -- Training Objectives -- Choosing the Content -- Step-by-Step Instructions -- What to Do Next -- Chapter 6 - Half-Day Training -- Presenting Longer Programs -- Training Objectives -- Choosing the Content -- Step-by-Step Instructions -- What to Do Next -- Chapter 7 - 1.5-Day Training -- Presenting Longer Programs -- Training Objectives -- Choosing the Content -- Step-by-Step Instructions -- What to Do Next -- Chapter 8 - 2-Day Training -- Presenting Longer Programs -- Training Objectives -- Choosing the Content -- Step-by-Step Instructions -- What to Do Next -- Chapter 9 - Content Modules -- The Modules -- Using the Modules -- Content Module 9.1-The Importance of Communication -- Content Module 9.2-Coaching Communication Model…”

Tabla de Contenidos: “…Hills and Mark Russell / Carbohydrates for Soccer: A Focus on Skilled Actions and Half-Time Practices / Reprinted from: Nutrients 2018, 10, 22, doi: 10.3390/nu10010022 -- Silvia Zambrana, Lena C. …”

“…Hashing was invented during the design of the IBM 701 machine in the 1950s by Hans Peter Luhn. In the ensuing half century, the hashing concept has found a variety of applications. …”

Tabla de Contenidos: “…Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgment -- 1 Introduction to Cognitive Computing -- 1.1 Introduction: Definition of Cognition, Cognitive Computing -- 1.2 Defining and Understanding Cognitive Computing -- 1.3 Cognitive Computing Evolution and Importance -- 1.4 Difference Between Cognitive Computing and Artificial Intelligence -- 1.5 The Elements of a Cognitive System -- 1.5.1 Infrastructure and Deployment Modalities -- 1.5.2 Data Access, Metadata, and Management Services -- 1.5.3 The Corpus, Taxonomies, and Data Catalogs -- 1.5.4 Data Analytics Services -- 1.5.5 Constant Machine Learning -- 1.5.6 Components of a Cognitive System -- 1.5.7 Building the Corpus -- 1.5.8 Corpus Administration Governing and Protection Factors -- 1.6 Ingesting Data Into Cognitive System -- 1.6.1 Leveraging Interior and Exterior Data Sources -- 1.6.2 Data Access and Feature Extraction -- 1.7 Analytics Services -- 1.8 Machine Learning -- 1.9 Machine Learning Process -- 1.9.1 Data Collection -- 1.9.2 Data Preparation -- 1.9.3 Choosing a Model -- 1.9.4 Training the Model -- 1.9.5 Evaluate the Model -- 1.9.6 Parameter Tuning -- 1.9.7 Make Predictions -- 1.10 Machine Learning Techniques -- 1.10.1 Supervised Learning -- 1.10.2 Unsupervised Learning -- 1.10.3 Reinforcement Learning -- 1.10.4 The Significant Challenges in Machine Learning -- 1.11 Hypothesis Space -- 1.11.1 Hypothesis Generation -- 1.11.2 Hypotheses Score -- 1.12 Developing a Cognitive Computing Application -- 1.13 Building a Health Care Application -- 1.13.1 Healthcare Ecosystem Constituents -- 1.13.2 Beginning With a Cognitive Healthcare Application -- 1.13.3 Characterize the Questions Asked by the Clients -- 1.13.4 Creating a Corpus and Ingesting the Content -- 1.13.5 Training the System…”

Tabla de Contenidos: “…Cover -- Half title -- Title -- Copyright -- Contents -- List of Figures -- List of Tables -- Foreword -- Contributors -- Introduction -- The COEURE Project -- Advances in Economic Research: Foundations forEuropean Policies -- About the Chapters -- The Relevance of Data and Methods -- Acknowledgements -- Notes -- 1 Innovation and Growth: The Schumpeterian Perspective -- 1.1 Introduction -- 1.2 Looking for Growth Paradigms to Think about Growth Policy -- 1.2.1 The Neoclassical Growth Model -- 1.2.2 The AK Model -- 1.2.3 The Product-Variety Model -- 1.2.4 The Schumpeterian Model -- 1.3 Some Main Applications and Extensions of Schumpeterian Growth Theory -- 1.3.1 Growth Meets IO -- 1.3.2 Schumpeterian Growth and Firm Dynamics -- 1.3.3 Growth Meets Development: Appropriate Institutions -- 1.3.4 Growth Meets Development: Firm Dynamics in Developing Countries -- 1.3.5 Growth and Unemployment -- 1.4 Enhancing Productivity Growth in Advanced Countries -- 1.4.1 Pillars of Innovation-Led Growth -- 1.4.2 Competition Policy against Industrial Policy -- 1.4.3 Reforming the State -- 1.4.4 Macroeconomic Policy -- 1.4.5 Innovation, Inequality, and Social Mobility: Making Growth Inclusive -- 1.5 Technological Waves and the Debate on Secular Stagnation -- 1.5.1 The Debate -- 1.5.2 Historical Wave Patterns -- 1.6 Schumpeterian Insights into R&amp -- D Policy -- 1.6.1 R&amp -- D Policies and Firm Selection -- 1.6.2 Basic versus Applied R&amp -- D -- 1.7 The Role of Freedom and Openness in the Innovation Process -- 1.7.1 The ADS Framework and the Role of Academic Freedom -- 1.7.2 Freedom and Openness -- 1.7.3 Evidence on the Limits of IP and the Role of Openness and Freedom -- 1.8 Towards a New Growth Pact in Europe -- 1.8.1 Structural Reforms and the Role of Structural Funds -- 1.8.2 Rethinking Industrial Policy in the EU…”

Tabla de Contenidos: “…Cover -- Half-Title Page -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- 1 Bioinfomatics as a Tool in Drug Designing -- 1.1 Introduction -- 1.2 Steps Involved in Drug Designing -- 1.2.1 Identification of the Target Protein/Enzyme -- 1.2.2 Detection of Molecular Site (Active Site) in the Target Protein -- 1.2.3 Molecular Modeling -- 1.2.4 Virtual Screening -- 1.2.5 Molecular Docking -- 1.2.6 QSAR (Quantitative Structure-Activity Relationship) -- 1.2.7 Pharmacophore Modeling -- 1.2.8 Solubility of Molecule -- 1.2.9 Molecular Dynamic Simulation -- 1.2.10 ADME Prediction -- 1.3 Various Softwares Used in the Steps of Drug Designing -- 1.4 Applications -- 1.5 Conclusion -- References -- 2 New Strategies in Drug Discovery -- 2.1 Introduction -- 2.2 Road Toward Advancement -- 2.3 Methodology -- 2.3.1 Target Identification -- 2.3.2 Docking-Based Virtual Screening -- 2.3.3 Conformation Sampling -- 2.3.4 Scoring Function -- 2.3.5 Molecular Similarity Methods -- 2.3.6 Virtual Library Construction -- 2.3.7 Sequence-Based Drug Design -- 2.4 Role of OMICS Technology -- 2.5 High-Throughput Screening and Its Tools -- 2.6 Chemoinformatic -- 2.6.1 Exploratory Data Analysis -- 2.6.2 Example Discovery -- 2.6.3 Pattern Explanation -- 2.6.4 New Technologies -- 2.7 Concluding Remarks and Future Prospects -- References -- 3 Role of Bioinformatics in Early Drug Discovery: An Overview and Perspective -- 3.1 Introduction -- 3.2 Bioinformatics and Drug Discovery -- 3.2.1 Structure-Based Drug Design (SBDD) -- 3.2.2 Ligand-Based Drug Design (LBDD) -- 3.3 Bioinformatics Tools in Early Drug Discovery -- 3.3.1 Possible Biological Activity Prediction Tools -- 3.3.2 Possible Physicochemical and Drug-Likeness Properties Verification Tools -- 3.3.3 Possible Toxicity and ADME/T Profile Prediction Tools -- 3.4 Future Directions With Bioinformatics Tool…”

Tabla de Contenidos: “…Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Editor -- Contributors -- Chapter 1 Certain Banach-Space Operators Acting on Free Poisson Elements Induced by Orthogonal Projections -- 1.1 Introduction -- 1.2 Preliminaries -- 1.3 Some Banach *-Algebras Induced by Projections -- 1.4 Weighted-Semicircular Elements Induced by Q -- 1.5 Semicircular Elements Induced by Q -- 1.6 The Semicircular Filterization (L[sub(Q)], Ί) -- 1.7 Free Poisson Elements of L[sub(Q)] -- 1.7.1 Free Poisson Elements -- 1.7.2 Certain Free Poisson Elements Induced by S -- 1.7.3 Some Free Poisson Elements Induced by S U X -- 1.8 Free Weighted-Poisson Elements of L[sub(Q)] -- 1.8.1 Free Weighted-Poisson Elements -- 1.8.2 Free Weighted-Poisson Elements Induced by S U X -- 1.8.3 Free Weighted-Poisson Elements Induced by X -- 1.9 Shifts on Z and Integer-Shifts on L[sub(Q)] -- 1.9.1 (±)-Shifts on Z -- 1.9.2 Integer-Shifts on L[sub(Q)] -- 1.9.3 Free Probability on L[sub(Q)] Under the Group-Action of B -- 1.10 Banach-Space Operators on L[sub(Q)] Generated by B -- 1.10.1 Deformed Free Probability of L[sub(Q)] by A -- 1.10.2 Deformed Semicircular Laws on L[sub(Q)] by A -- 1.11 Deformed Free Poisson Distributions on L[sub(Q)] by A -- References -- Chapter 2 Linear Positive Operators Involving Orthogonal Polynomials -- 2.1 Operators Based on Orthogonal Polynomials -- 2.1.1 Notations -- 2.1.2 Definitions -- 2.1.3 Appell Polynomials -- 2.1.4 Boas-Buck-Type Polynomials -- 2.1.5 Charlier Polynomials -- 2.1.6 Approximation by Appell Polynomials -- 2.1.7 Approximation by Operators Including Generalized Appell Polynomials -- 2.1.8 Szász-Type Operators Involving Multiple Appell Polynomials -- 2.1.9 Kantorovich-Type Generalization of K[sub(n)] Operators -- 2.1.10 Kantorovich Variant of Szász Operators Based on Brenke-Type Polynomials…”

Tabla de Contenidos: “…Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Preface -- PART 1 -- 1. …”

Tabla de Contenidos: “…Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Preface -- Part 1 -- 1. …”

Tabla de Contenidos: “…Cover -- Half-Title Page -- Dedication -- Title Page -- Copyright Page -- Contents -- Introduction -- I.1. …”

Tabla de Contenidos: “…Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgments -- Author -- Chapter 1: CMOS Analog and Mixed-Signal Circuit Design: An Overview -- 1.1 Introduction -- 1.2 Notation, Symbol, and Terminology -- 1.3 Technology, Circuit Topology, and Methodology -- 1.4 Analog and Mixed-Signal Integrated Design Concepts -- 1.5 Summary -- Chapter 2: Devices: An Overview -- 2.1 Introduction -- 2.2 The PN Junction -- 2.2.1 Fermi Level -- 2.2.2 Depletion Layer Capacitance -- 2.2.3 Storage Capacitance -- 2.3 Photo Devices -- 2.4 FETs -- 2.4.1 Long Channel Approximation -- 2.4.1.1 MOS Structure -- 2.4.1.2 MOS with External Bias -- 2.4.1.3 MOS Operation -- 2.4.1.4 Current-Voltage Characteristics -- 2.4.2 MOSFET Scaling -- 2.4.2.1 Full Scaling -- 2.4.2.2 Constant-Voltage Scaling -- 2.4.3 Weak Inversion -- 2.4.4 Short-Channel -- 2.4.4.1 Carrier Drift Velocity Models -- 2.4.4.2 VDSAT -- 2.4.4.3 Current-Voltage Equation for Short Channel Transistor -- 2.4.5 MOSFET Capacitor -- 2.4.5.1 Oxide-Related Capacitance -- 2.4.5.2 Junction Capacitance -- 2.4.6 MOSFET Transition Frequency -- 2.4.7 Noise -- 2.4.7.1 Thermal Noise -- 2.4.7.2 Flicker Noise -- 2.5 Process Fitting Ratio -- 2.5.1 150-90 nm Design Transfer -- 2.6 MOSFET Parameter Exercise -- 2.7 SPICE Example -- 2.8 Summary -- References -- Chapter 3: Amplifiers -- 3.1 Introduction -- 3.1.1 CMOS Amplifier -- 3.2 Input Voltage Range -- 3.2.1 Theory -- 3.2.2 Example -- 3.3 Signal Path of CMOS Operational Amplifier -- 3.3.1 Overall Signal Path -- 3.3.2 Load -- 3.3.3 Cascode Current Source -- 3.3.4 Example -- 3.4 CMOS Amplifier Parameters -- 3.4.1 Input Offset -- 3.4.2 Common Mode Input Voltage Range -- 3.4.3 Current Consumption -- 3.4.4 Common Mode Rejection Ratio (CMRR) -- 3.4.5 Power Supply Rejection Ratio -- 3.4.6 Slew Rate and Settling Time -- 3.4.7 DC Gain, fs, and fT…”

Tabla de Contenidos: “…Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Editors -- List of contributors -- Preface -- Part I: AI trends and challenges -- Chapter 1: AI-based computing applications in future communication -- 1.1 Introduction -- 1.2 Artificial Intelligence -- 1.2.1 Why is artificial intelligence important? …”

Tabla de Contenidos: “…Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- About the Editors -- List of Contributors -- Chapter 1 A Review Approach On Deep Learning Algorithms in Computer Vision -- 1.1 Introduction -- 1.2 Deep Learning Algorithms -- 1.2.1 Convolutional Neural Networks -- 1.2.2 Restricted Boltzmann Machines -- 1.2.3 Deep Boltzmann Machines -- 1.2.4 Deep Belief Networks -- 1.2.5 Stacked (de-Noising) Auto-Encoders -- 1.2.5.1 Auto-Encoders -- 1.2.5.2 Denoising Auto Encoders -- 1.3 Comparison of the Deep Learning Algorithms -- 1.4 Challenges in Deep Learning Algorithms -- 1.5 Conclusion and Future Scope -- References -- Chapter 2 Object Extraction From Real Time Color Images Using Edge Based Approach -- 2.1 Introduction -- 2.2 Applications of Object Extraction -- 2.3 Edge Detection Techniques -- 2.3.1 Roberts Edge Detection -- 2.3.2 Sobel Edge Detection -- 2.3.3 Prewitt's Operator -- 2.3.4 Laplacian Edge Detection -- 2.4 Related Work -- 2.5 Proposed Model -- 2.6 Results and Discussion -- 2.7 Conclusion -- References -- Chapter 3 Deep Learning Techniques for Image Captioning -- 3.1 Introduction to Image Captioning -- 3.1.1 How Does Image Recognition Work? …”

Tabla de Contenidos: “…Cover -- Half Title -- Series Information -- Title Page -- Copyright Page -- Table of Contents -- Aim and Scope -- Preface -- About the Editors -- Contributors -- Acknowledgment -- Chapter 1 Digital Manufacturing: Artificial Intelligence in Industry 5.0 -- 1.1 Introduction -- 1.2 Transformative Journey: Industry 1.0 to 5.0 -- 1.3 Artificial Intelligence in Industry 5.0 -- 1.3.1 AI-Powered Digital Manufacturing Processes -- 1.3.2 AI-Powered Smart Automation and Robotics -- 1.3.3 AI-Powered Supply Chain Optimization -- 1.3.4 AI-Powered Product Quality and Inspection -- 1.3.5 Human-Machine Collaboration in Industry 5.0 -- 1.3.6 AI-Powered Digital Twins -- 1.3.6.1 Digital Twins Applications -- 1.4 Success Stories in AI-Powered Manufacturing -- 1.4.1 Case 1: Ford Motors-Predictive Maintenance With AI -- 1.4.2 Case 2: Boeing-AI-Powered Defect Detection in Aircraft Manufacturing -- 1.4.3 Case 3: Adidas-AI-Driven Demand Forecasting and Customization -- 1.4.4 Case 4: Siemens-AI-Powered Optimization of Production Lines -- 1.4.5 Case 5: Schneider Electric-AI-Powered Supply Chain Management -- 1.5 Challenges and Opportunities -- 1.6 Conclusion -- References -- Chapter 2 The Rise of Industry 5.0: How Artificial Intelligence Is Shaping the Future of Manufacturing -- 2.1 Introduction -- 2.1.1 First Industrial Revolution (Eighteenth to Nineteenth Century) -- 2.1.2 Second Industrial Revolution (After Nineteenth to Before Twentieth Century) -- 2.1.3 Third Industrial Revolution (Late Twentieth Century) -- 2.1.4 Fourth Industrial Revolution (Twenty-First Century) -- 2.2 Characteristics of Industry 5.0 -- 2.3 Importance of AI in Industry 5.0 -- 2.3.1 Techniques and Approaches -- 2.3.2 Challenges and Considerations -- 2.4 Importance of AI in Industrial Transformation -- 2.5 Key Drivers for AI Adoption in Industry 5.0 -- 2.6 Applications of AI in Industry 5.0.…”

Tabla de Contenidos: “…Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Editor -- Contributors -- Preface -- Chapter 1: Distributed and Parallel Computing -- 1.1 Introduction -- 1.2 Distributed Computing -- 1.2.1 Cluster Computing -- 1.2.1.1 Architecture -- 1.2.1.2 Data and Message Communication -- 1.2.1.3 Task Management and Administration -- 1.2.1.4 Example Geospatial Big Data Project on Cluster -- 1.2.2 Grid Computing -- 1.2.2.1 Architecture -- 1.2.2.2 Types of Grid Architectures -- 1.2.2.3 Topology -- 1.2.2.4 Perspectives -- 1.2.2.4.1 User -- 1.2.2.4.2 Administrator -- 1.2.2.4.3 Application Developer -- 1.2.2.5 Example Geospatial Big Data Project on Grids -- 1.2.3 Cloud Computing -- 1.2.3.1 Taxonomies -- 1.2.3.2 Cloud Service Models -- 1.2.3.3 Cloud Deployment Models -- 1.2.3.3.1 Cloud APIs -- 1.2.3.3.2 Levels of Cloud APIs -- 1.2.3.3.3 Categories of APIs -- 1.2.3.4 Example Geospatial Big Data Project on Clouds -- 1.3 Parallel Computing -- 1.3.1 Classes of Parallel Computing -- 1.3.2 Shared Memory Multiple Processing -- 1.3.3 Distributed Memory Multiple Processing -- 1.3.4 Hybrid Distributed Shared Memory -- 1.3.5 Example Geospatial Big Data Project on Parallel Computers -- 1.4 Supercomputing -- 1.4.1 Supercomputing Worldwide -- 1.4.2 Trend -- 1.4.3 Future Supercomputer Research -- 1.4.4 Example Geospatial Big Data Project on Supercomputers -- 1.5 XSEDE: A Single Virtual System -- 1.5.1 Resources -- 1.5.2 Services -- 1.5.3 Example Big Geospatial Data Project on XSEDE -- 1.6 Choosing Appropriate Computing Environment -- 1.7 Summary -- References -- Chapter 2: GEOSS Clearinghouse Integrating Geospatial Resources to Support the Global Earth Observation System of Systems -- 2.1 Introduction -- 2.2 Catalog and Clearinghouse Research Review -- 2.2.1 Metadata Repository and Standardized Metadata…”

Tabla de Contenidos: “…Cover -- Half Title -- Title -- Copyright -- Dedication -- Table of Contents -- Preface -- INTRODUCTION -- 1.1 Introduction -- 1.2 A little bit of history -- 1.3 Information -- 1.4 Digital versus analogue -- 1.5 Conversion to digital -- 1.6 Sampling theory -- 1.7 Quantization -- 1.8 Exercises -- COMPRESSION TECHNIQUES -- 2.1 Introduction -- 2.2 Compression methods -- 2.3 Letter probabilities -- 2.4 Coding methods -- 2.5 Statistical encoding -- 2.6 Repetitive sequence suppression -- 2.7 Differential encoding -- 2.8 Transform encoding -- 2.9 Exercises -- 2.10 Letter probablity program -- HUFFMAN/LEMPEL-ZIV COMPRESSION METHODS -- 3.1 Introduction -- 3.2 Huffman coding -- 3.3 Adaptive Huffman coding -- 3.4 Lempel-Ziv coding -- 3.5 Lempel-Ziv-Welsh coding -- 3.6 Variable-length-code LZW compression -- 3.7 Disadvantages with LZ compression -- 3.8 Practical Lempel-Ziv/Huffman coding -- 3.9 Exercises -- IMAGE COMPRESSION (GIF/TIFF/ PCX) -- 4.1 Introduction -- 4.2 Comparison of the different methods -- 4.3 GIF coding -- 4.4 TIFF coding -- 4.5 GIF interlaced images -- 4.6 PCX coding -- 4.7 Exercises -- IMAGE COMPRESSION (JPEG) -- 5.1 Introduction -- 5.2 JPEG coding -- 5.3 JPEG decoding -- 5.4 JPEG file format -- 5.5 JPEG modes -- 5.6 Exercises -- VIDEO SIGNALS -- 6.1 Introduction -- 6.2 Color-difference signals -- 6.3 Quadrature modulation -- 6.4 Baseband video signals -- 6.5 Digitizing TV signals -- 6.6 100 Hz pictures -- 6.7 Compressed TV -- 6.8 HDTV quality -- 6.9 Exercise -- MOTION VIDEO COMPRESSION -- 7.1 Motion video -- 7.2 MPEG-1 overview -- 7.3 MPEG-1 video compression -- 7.4 MPEG-1 compression process -- 7.5 MPEG-1 decoder -- 7.6 MPEG-1 audio compression -- 7.7 MPEG-2 -- 7.8 MPEG-2 system layer -- 7.9 Other MPEG-2 enhancements -- 7.10 MPEG-2 bit rate -- 7.11 Exercises -- SPEECH AND AUDIO SIGNALS -- 8.1 Introduction -- 8.2 PCM parameters…”