Tabla de Contenidos: “…4.2.2 ARTs sind multifunktional -- 4.2.3 Rollen -- 4.2.4 Release Trains aufsetzen -- Wertströme identifizieren und Trains etablieren -- Programminkrement: PI-Planung und Arbeitsweise festlegen -- 4.2.5 Arbeiten im Programminkrement -- PI-Planung -- Reporting -- Scrum of Scrums -- Inspect &amp -- Adapt -- 4.3 Das Programminkrement -- 4.3.1 Das PI als Super-Sprint -- 4.4 Entwickeln im Takt - liefern nach Bedarf -- 4.4.1 Entwickeln im Takt -- Man kann nicht auf Kosten der Qualität Zeit sparen -- Der Entwicklungsfluss in SAFe -- Die Lieferpipeline -- Synchronisation -- 4.4.2 Liefern nach Bedarf -- Releases und potenziell auslieferbare Software -- Häufigkeit von Releases -- Features tragen Kundennutzen -- Laufende Software: potenziell auslieferbares Inkrement -- Von potenziell auslieferbar bis zum Release -- Systemvalidierung -- Fertigstellen des Release -- 4.5 Artefakte des Release Train -- 4.5.1 Die Programmvision -- Inhalt -- Quellen der Vision -- Repräsentation der Vision -- 4.5.2 Die Roadmap -- 4.5.3 Das ART-Backlog -- Quellen und Inhalt -- Priorisierung -- Schätzen im ART-Backlog -- 4.5.4 Programm-Epics -- 4.5.5 Features -- Features und Nutzen -- Akzeptanzkriterien für Features -- Die »Top Ten«-Features in der PI-Planung -- 4.5.6 Enablers oder Architektur-Features -- 4.6 Planen für den Agile Release Train -- 4.6.1 Das ART-Backlog vorbereiten -- 4.6.2 Features aufsplitten -- 4.6.3 Features zwischen Teams aufteilen -- 4.6.4 Schätzen von Features -- 4.6.5 Kapazitäten allokieren -- 4.6.6 Die optimale Länge des Backlogs -- 4.7 Meetings -- 4.7.1 PI-Planung - Start des Programminkrements -- Vorbereitung des Meetings -- Das Meeting -- Tag 1 -- Tag 2 -- Ergebnisse -- PI-Planung und Sprint-Planung der Teams -- 4.7.2 Die zweiwöchentliche Systemdemo -- 4.7.3 Die ART-Demo -- 4.7.4 Das Inspect &amp -- Adapt-Meeting -- Demo der Lösung -- Quantitative Messungen…”

Tabla de Contenidos: “…4.1.1 Properties: Key/value pairs for configuration -- 4.1.2 Profiles: Feature flags and configuration groups -- 4.2 Externalized configuration: One build, multiple configurations -- 4.2.1 Configuring an application through command-line arguments -- 4.2.2 Configuring an application through JVM system properties -- 4.2.3 Configuring an application through environment variables -- 4.3 Centralized configuration management with Spring Cloud Config Server -- 4.3.1 Using Git to store your configuration data -- 4.3.2 Setting up a configuration server -- 4.3.3 Making the configuration server resilient -- 4.3.4 Understanding the configuration server REST API -- 4.4 Using a configuration server with Spring Cloud Config Client -- 4.4.1 Setting up a configuration client -- 4.4.2 Making the configuration client resilient -- 4.4.3 Refreshing configuration at runtime -- Summary -- 5 Persisting and managing data in the cloud -- 5.1 Databases for cloud native systems -- 5.1.1 Data services in the cloud -- 5.1.2 Running PostgreSQL as a container -- 5.2 Data persistence with Spring Data JDBC -- 5.2.1 Connecting to a database with JDBC -- 5.2.2 Defining persistent entities with Spring Data -- 5.2.3 Enabling and configuring JDBC auditing -- 5.2.4 Data repositories with Spring Data -- 5.3 Testing data persistence with Spring and Testcontainers -- 5.3.1 Configuring Testcontainers for PostgreSQL -- 5.3.2 Testing data persistence with @DataJdbcTest and Testcontainers -- 5.3.3 Integration tests with @SpringBootTest and Testcontainers -- 5.4 Managing databases in production with Flyway -- 5.4.1 Understanding Flyway: Version control for your database -- 5.4.2 Initializing a database schema with Flyway -- 5.4.3 Evolving a database with Flyway -- Summary -- 6 Containerizing Spring Boot -- 6.1 Working with container images on Docker -- 6.1.1 Understanding container images…”

Tabla de Contenidos: “…3.4.8 Noise -- 3.4.9 Distortion -- 3.5 Common Mode Feedback -- 3.6 Compensation in Amplifier -- 3.6.1 Loop Response -- 3.6.2 Pulse Response -- 3.7 Wideband Amplifier Technique -- 3.7.1 Source and Load -- 3.7.2 Stages and Feedback -- 3.8 Noises in Amplifiers -- 3.8.1 Noise in Circuits -- 3.8.2 Noise in Single-Stage Amplifiers -- 3.8.3 Noise in Differential Pairs -- 3.8.4 Noise in Amplifier with Resistors in the Feedback -- 3.8.5 Noise Bandwidth -- 3.9 Current Density Design Approach -- 3.10 Layout Examples -- 3.11 Summary -- References -- Chapter 4: Low Power Amplifier -- 4.1 Introduction -- 4.2 Low Voltage CMOS Amplifier -- 4.2.1 Body or Bulk Control -- 4.2.2 Circuit Technique -- 4.3 Subthreshold -- 4.4 Current Reuse CMOS Amplifier -- 4.5 Other Techniques -- 4.5.1 Common-Gate with Gain-Boosting Wideband Differential LNA -- 4.6 Spice Example -- 4.7 Summary -- References -- Chapter 5: Voltage Regulator, References and Biasing -- 5.1 Introduction -- 5.2 Current Sources -- 5.3 Self-Biased -- 5.4 CTAT and PTAT -- 5.5 Bandgap Voltage Reference -- 5.5.1 Bandgap Reference -- 5.6 Diode-Less Voltage Reference -- 5.7 Cascode Current Source -- 5.8 Regulated Power Supply -- 5.9 Design Example -- 5.10 Spice Example -- 5.11 Layout Example -- 5.12 Summary -- Problems -- References -- Chapter 6: Introduction of Advanced Analog Circuit -- 6.1 Introduction -- 6.2 MOSFET as a Switch -- 6.3 Basic Switched Capacitor -- 6.3.1 Switching Capacitor Sensitive to Parasitic Capacitances -- 6.4 Active Integrator -- 6.4.1 Non-inverting Switching Capacitor Non-sensitive to Parasitic Capacitances -- 6.4.2 Inverting Active Integrator without a Delay -- 6.4.3 Inverting the Switching Capacitor with a Delay, Non-sensitive to Parasitic Capacitances -- 6.4.4 SC Behavior in Discrete Points of Time -- 6.4.5 Non-inverting Active Integrator with a Delay -- 6.5 Sample-and-Hold Amplifier…”

Tabla de Contenidos: “…-- 4.2 Architectural constraints of REST applications -- 4.2.1 Separation of concerns: The client-server architecture principle -- 4.2.2 Make it scalable: The statelessness principle -- 4.2.3 Optimize for performance: The cacheability principle -- 4.2.4 Make it simple for the client: The layered system principle -- 4.2.5 Extendable interfaces: The code-on-demand principle -- 4.2.6 Keep it consistent: The uniform interface principle -- 4.3 Hypermedia as the engine of application state -- 4.4 Analyzing the maturity of an API with the Richardson maturity model -- 4.4.1 Level 0: Web APIs à la RPC -- 4.4.2 Level 1: Introducing the concept of resource -- 4.4.3 Level 2: Using HTTP methods and status codes -- 4.4.4 Level 3: API discoverability -- 4.5 Structured resource URLs with HTTP methods -- 4.6 Using HTTP status codes to create expressive HTTP responses -- 4.6.1 What are HTTP status codes? …”

Tabla de Contenidos: “…2.3.2 Automating the building of our application -- Summary -- 3 Volumes -- 3.1 Using volumes with containers -- 3.1.1 Named volumes -- 3.1.2 Volume mount options -- 3.1.3 podman run - -mount command option -- Summary -- 4 Pods -- 4.1 Running pods -- 4.2 Creating a pod -- 4.3 Adding a container to a pod -- 4.4 Starting a pod -- 4.5 Stopping a pod -- 4.6 Listing pods -- 4.7 Removing pods -- Summary -- Part 2. …”

Tabla de Contenidos: “…3.3.4 Accessing metadata at runtime -- Summary -- 4 Working with Spring Data JPA -- 4.1 Introducing Spring Data JPA -- 4.2 Starting a new Spring Data JPA project -- 4.3 First steps for configuring a Spring Data JPA project -- 4.4 Defining query methods with Spring Data JPA -- 4.5 Limiting query results, sorting, and paging -- 4.6 Streaming results -- 4.7 The @Query annotation -- 4.8 Projections -- 4.9 Modifying queries -- 4.10 Query by Example -- Summary -- Part 2. …”

Tabla de Contenidos: “…4 Quantum Hilbert spaces and their creation -- 4.1 Explicit Hilbert spaces underlying quantum technology -- 4.2 Complexification -- 4.3 Dual space used in quantum -- 4.4 Double dual Hilbert space -- 4.5 Outer product -- 4.6 Multilinear forms, wedge, and interior products -- 4.7 Many-sorted algebra for tensor vector spaces -- 4.8 The determinant -- 4.9 Tensor algebra -- 4.10 Many-sorted algebra for tensor product of Hilbert spaces -- 4.11 Hilbert space of rays -- 4.12 Projective space -- References -- 5 Quantum and machine learning applications involving matrices -- 5.1 Matrix operations -- 5.2 Qubits and their matrix representations -- 5.3 Complex representation for the Bloch sphere -- 5.4 Interior, exterior, and Lie derivatives -- 5.5 Spectra for matrices and Frobenius covariant matrices -- 5.6 Principal component analysis -- 5.7 Kernel principal component analysis -- 5.8 Singular value decomposition -- References -- 6 Quantum annealing and adiabatic quantum computing -- 6.1 Schrödinger's characterization of quantum -- 6.2 Quantum basics of annealing and adiabatic quantum computing -- 6.3 Delta function potential well and tunneling -- 6.4 Quantum memory and the no-cloning theorem -- 6.5 Basic structure of atoms and ions -- 6.6 Overview of qubit fabrication -- 6.7 Trapped ions -- 6.8 Super-conductance and the Josephson junction -- 6.9 Quantum dots -- 6.10 D-wave adiabatic quantum computers and computing -- 6.11 Adiabatic theorem -- Reference -- Further reading -- 7 Operators on Hilbert space -- 7.1 Linear operators, a MSA view -- 7.2 Closed operators in Hilbert spaces -- 7.3 Bounded operators -- 7.4 Pure tensors versus pure state operators -- 7.5 Trace class operators -- 7.6 Hilbert-Schmidt operators -- 7.7 Compact operators -- References -- 8 Spaces and algebras for quantum operators…”

Tabla de Contenidos: “…L'Union européenne perd des parts de marché au profit de l'Océanie -- Graphique 44. Hausse de la consommation de fromage, en particulier dans les pays non membres -- Encadré 7. …”

Tabla de Contenidos: “…4.3.2 Factorization-Based Techniques -- 4.3.3 Probabilistic-Based Techniques -- 4.3.4 Geometric-Based Biclustering -- 4.3.5 Biclustering for Coherent Evolution -- 4.4 Evolutionary Algorithms Based Biclustering -- 4.5 Conclusion -- References -- 5 Inference of Vohradský's Models of Genetic Networks using a Real-coded Genetic Algorithm -- 5.1 Introduction -- 5.2 Model -- 5.3 Inference Based on Back-Propagation Through Time -- 5.4 Inference by Solving Simultaneous Equations -- 5.4.1 Problem Definition -- 5.4.2 Efficient Technique for Solving Simultaneous Equations -- 5.5 REX/JGG -- 5.5.1 JGG -- 5.5.2 REX -- 5.6 Inference of an Artificial Network -- 5.6.1 Experimental Setup -- 5.6.2 Results -- 5.7 Inference of an Actual Genetic Network -- 5.7.1 Experimental Setup -- 5.7.2 Results -- 5.8 Conclusion -- Acknowledgements -- References -- 6 GPU-powered Evolutionary Design of Mass-Action-Based Models of Gene Regulation -- 6.1 Introduction -- 6.2 Evolutionary Computation for the Inference of Biochemical Models -- 6.3 Methods -- 6.3.1 Mass-Action-Based Modeling of Gene Regulation -- 6.3.2 Cartesian Genetic Programming -- 6.3.3 Particle Swarm Optimization -- 6.3.4 General-Purpose GPU Computing -- 6.4 Design Methodology of Gene Regulation Models by Means of CGP and PSO -- 6.5 Results -- 6.5.1 ED of Synthetic Circuits with Two Genes -- 6.5.2 ED of Synthetic Circuits with Three Genes -- 6.5.3 Computational Results -- 6.6 Discussion -- 6.7 Conclusions and Future Perspectives -- References -- 7 Modeling Dynamic Gene Expression in Streptomyces Coelicolor: Comparing Single and Multi-Objective Setups -- 7.1 Introduction -- 7.1.1 Modeling Gene Expression -- 7.1.2 Reverse Engineering Biological Networks from Expression Data -- 7.1.3 The Life Cycle of Streptomyces coelicolor -- 7.1.4 The PhoP Sub-Network -- 7.1.5 Computational Approach…”

Tabla de Contenidos: “…4.1 Introduction: The Tukey's School of Statistics -- 4.2 Essential Summaries of EDA -- 4.3 Graphical Techniques in EDA -- 4.3.1 Boxplot -- 4.3.2 Histogram -- 4.3.3 Histogram Extensions and the Rootogram -- 4.3.4 Pareto Chart -- 4.3.5 Stem-and-Leaf Plot -- 4.3.6 Run Chart -- 4.3.7 Scatter Plot -- 4.4 Quantitative Techniques in EDA -- 4.4.1 Trimean -- 4.4.2 Letter Values -- 4.5 Exploratory Regression Models -- 4.5.1 Resistant Line -- 4.5.2 Median Polish -- 4.6 Further Reading -- 4.7 Complements, Problems, and Programs -- Part II Probability and Inference -- Chapter 5 Probability Theory -- 5.1 Introduction -- 5.2 Sample Space, Set Algebra, and Elementary Probability -- 5.3 Counting Methods -- 5.3.1 Sampling: The Diverse Ways -- 5.3.2 The Binomial Coefficients and the Pascals Triangle -- 5.3.3 Some Problems Based on Combinatorics -- 5.4 Probability: A Definition -- 5.4.1 The Prerequisites -- 5.4.2 The Kolmogorov Definition -- 5.5 Conditional Probability and Independence -- 5.6 Bayes Formula -- 5.7 Random Variables, Expectations, and Moments -- 5.7.1 The Definition -- 5.7.2 Expectation of Random Variables -- 5.8 Distribution Function, Characteristic Function, and Moment Generation Function -- 5.9 Inequalities -- 5.9.1 The Markov Inequality -- 5.9.2 The Jensen's Inequality -- 5.9.3 The Chebyshev Inequality -- 5.10 Convergence of Random Variables -- 5.10.1 Convergence in Distributions -- 5.10.2 Convergence in Probability -- 5.10.3 Convergence in rth Mean -- 5.10.4 Almost Sure Convergence -- 5.11 The Law of Large Numbers -- 5.11.1 The Weak Law of Large Numbers -- 5.12 The Central Limit Theorem -- 5.12.1 The de Moivre-Laplace Central Limit Theorem -- 5.12.2 CLT for iid Case -- 5.12.3 The Lindeberg-Feller CLT -- 5.12.4 The Liapounov CLT -- 5.13 Further Reading -- 5.13.1 Intuitive, Elementary, and First Course Source…”

Tabla de Contenidos: “…3.2 Security Issues in e-Business -- 3.2.1 Vulnerabilities -- 3.2.2 Security Attacks -- 3.2.3 Malware as a Threat -- 3.3 Common Vulnerabilities in e-Business -- 3.3.1 Phishing -- 3.3.2 Cross-Site Scripting (XSS) -- 3.4 Threats in e-Business -- 3.4.1 Ransomware -- 3.4.2 Spyware -- 3.4.3 Worms -- 3.4.4 Trojan Horse -- 3.5 Prevention Mechanism -- 3.6 Conclusion -- References -- 4 e-Commerce Security: Threats, Issues, andMethods -- 4.1 Introduction -- 4.2 Literature Review -- 4.3 e-Commerce -- 4.3.1 Characteristics of e-Commerce Technology -- 4.3.2 Architectural Framework of e-Commerce -- 4.3.2.1 Two-Tier Architecture -- 4.3.2.2 Three-Tier Architecture -- 4.3.3 Advantages and Disadvantages of e-Commerce -- 4.4 Security Overview in e-Commerce -- 4.4.1 Purpose of Security in e-Commerce -- 4.4.2 Security Element at Different Levels of e-Commerce System -- 4.4.2.1 Hardware -- 4.4.2.2 Software -- 4.4.2.3 Environment -- 4.5 Security Issues in e-Commerce -- 4.5.1 Client Level -- 4.5.2 Front-End Servers and Software Application Level -- 4.5.3 Network and Server Level -- 4.6 Security Threats in e-Commerce -- 4.7 Security Approaches in e-Commerce -- 4.8 Comparative Analysis of Various Security Threats in e-Commerce -- 4.9 e-Commerce Security Life-Cycle Model -- 4.10 Conclusion -- References -- 5 Cyberwar is Coming -- 5.1 Introduction -- 5.2 Ransomware Attacks -- 5.2.1 Petya -- 5.2.2 WannaCry -- 5.2.3 Locky -- 5.3 Are Nations Ready? …”

Tabla de Contenidos: “…3.5 Limitations -- 3.6 Future Improvements -- References -- Further Reading -- Chapter 4 AI-Based Surveillance Systems for Effective Attendance Management: Challenges and Opportunities -- 4.1 Introduction -- 4.2 Artificial Intelligence (AI) and Smart Surveillance -- 4.3 Artificial Intelligence (AI) and Attendance Management -- 4.4 Technologies in Automatic Attendance Management Image Processing -- 4.5 Deep Learning and Various Neural Network Techniques for Attendance Management -- 4.5.1 Applications of Convolutional Neural Networks (CNN) for Attendance Management -- 4.5.1.1 Mathematical Model of CNN -- 4.5.2 Applications of Recursive Neural Network (RNN) for Attendance Management -- 4.5.2.1 Mathematical Model of RNN -- 4.5.3 Applications of Generative Adversarial Network (GAN) for Attendance Management -- 4.5.3.1 Mathematical Model of Generalized Neural Network -- 4.6 Role of AI Technologies in Attendance Management -- 4.7 Challenges -- 4.8 Opportunities -- 4.9 Discussion &amp -- Conclusion -- References -- Chapter 5 Enhancing Surveillance Systems through Mathematical Models and Artificial Intelligence: An Image Processing Approach -- 5.1 Introduction -- 5.1.1 Surveillance -- 5.1.1.1 Crime Prevention and Detection -- 5.1.1.2 Public Safety -- 5.1.1.3 Terrorism Prevention -- 5.1.1.4 Traffic Management -- 5.1.1.5 Workplace Monitoring -- 5.1.1.6 Evidence Collection -- 5.1.1.7 Emergency Response -- 5.1.1.8 National Security -- 5.1.1.9 Public Health Monitoring -- 5.1.1.10 Accountability and Transparency -- 5.1.2 Image Processing -- 5.1.2.1 Image Enhancement -- 5.1.2.2 Image Restoration -- 5.1.2.3 Image Compression -- 5.1.2.4 Image Segmentation -- 5.1.2.5 Object Detection and Recognition -- 5.1.2.6 Image Analysis and Measurement -- 5.1.2.7 Image Registration -- 5.1.2.8 Image Classification and Machine Learning -- 5.1.2.9 Image Synthesis and Manipulation…”

Tabla de Contenidos: “…3.9.2 Domains of real-world applications -- 3.9.3 Financial applications -- 3.9.4 Medical and data science -- 3.9.5 Internet of Things -- 3.10 Conclusion -- References -- Part II: Machine intelligence in network technologies -- Chapter 4: Deformation prediction and monitoring using real-time WSN and machine learning algorithms: A review -- 4.1 Introduction -- 4.2 Causes of landslides -- 4.2.1 Climate changes -- 4.2.2 Earthquake -- 4.2.3 Deforestation -- 4.3 Early warning system -- 4.3.1 Risk Knowledge -- 4.3.2 Monitoring and warning services -- 4.3.3 Dissemination and communication -- 4.3.4 Response capability -- 4.3.5 Classification of early warning system -- 4.4 Landslide monitoring techniques -- 4.4.1 Multi-antenna GPS deformation monitoring systems -- 4.4.2 Monitoring landslide deformation using InSAR Technique -- 4.4.3 Electro-Mechanical System (MEMS) tilt sensor -- 4.4.4 Low-cost vibration sensor network -- 4.4.5 Extensometer -- 4.4.6 Rain gauge -- 4.5 Landside prediction modeling and forecasting using machine learning and statistical analysis -- 4.6 Conclusion -- Acknowledgments -- References -- Chapter 5: Unmanned aerial vehicle: Integration in healthcare sector for transforming interplay among smart cities -- 5.1 Introduction -- 5.1.1 Objectives of the chapter -- 5.1.2 Significance of study -- 5.2 UAVs in healthcare: Applications and benefits -- 5.2.1 Specific applications of UAVs in healthcare sector -- 5.2.1.1 Transportation -- 5.2.1.2 Livestock monitoring -- 5.2.1.3 Disaster relief -- 5.2.1.4 Public health surveillance and medical research -- 5.2.2 Benefits of UAVs in healthcare sector -- 5.3 Communication protocols for UAVs in healthcare -- 5.3.1 Diverse communication protocols suitable for UAVs in healthcare settings -- 5.3.2 Addressing challenges and requirements of real-time data transmission -- 5.4 Deployment strategies and logistics…”

Tabla de Contenidos: “…4.2 Object Detection -- 4.3 Two-Stage Object Detectors -- 4.3.1 R-CNN -- 4.3.2 SPPNet -- 4.3.3 Fast RCNN -- 4.3.4 Faster RCNN -- 4.3.5 R-FCN -- 4.3.6 FPN -- 4.3.7 Mask RCNN -- 4.3.8 G-RCNN -- 4.4 One-Stage Object Detectors -- 4.4.1 YOLO -- 4.4.2 CenterNet -- 4.4.3 SSD -- 4.4.4 RetinaNet -- 4.4.5 EfficientDet -- 4.4.6 YOLOR -- 4.5 Discussion On Model Performance -- 4.5.1 Future Trends -- 4.6 Conclusion -- References -- Chapter 5 Deep Learning Algorithms for Computer Vision: A Deep Insight Into Principles and Applications -- 5.1 Introduction -- 5.2 Preliminary Concepts of Deep Learning -- 5.2.1 Artificial Neural Network -- 5.2.2 Convolution Neural Network (CNNs) -- 5.3 Recurrent Neural Network (RNNs) -- 5.4 Overview of Applied Deep Learning in Computer Vision -- 5.6 Industrial Applications of Computer Vision -- 5.7 Future Scope in Computer Vision -- 5.8 Conclusion -- References -- Chapter 6 Handwritten Equation Solver Using Convolutional Neural Network -- 6.1 Introduction -- 6.2 State-Of-The-Art -- 6.3 Convolutional Neural Network -- 6.3.1 Convolution Layer -- 6.3.2 Pooling Layer -- 6.3.3 Fully Connected Layer -- 6.3.4 Activation Function -- 6.4 Handwritten Equation Recognition -- 6.4.1 Dataset Preparation -- 6.4.2 Proposed Methodology -- 6.4.2.1 Dataset Acquisition -- 6.4.2.2 Preprocessing -- 6.4.2.3 Recognition Through CNN Model -- 6.4.2.4 Processing Inside CNN Model -- 6.4.3 Solution Approach -- 6.5 Results and Discussion -- 6.6 Conclusion and Future Scope -- References -- Chapter 7 Agriware: Crop Suggester System By Estimating the Soil Nutrient Indicators -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Proposed Methodology -- 7.4 Experimental Results and Discussion -- 7.5 Conclusion and Future Work -- References -- Chapter 8 A Machine Learning Based Expeditious Covid-19 Prediction Model Through Clinical Blood Investigations -- 8.1 Introduction…”

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…”

Tabla de Contenidos: “…General planning -- 4.1 Migration methods -- 4.1.1 In-place database migration -- 4.1.2 Without-in place database migration -- 4.2 Hardware considerations -- 4.3 Software considerations -- 4.4 Human resource roles -- 4.5 Time considerations -- 4.5.1 Duration -- 4.5.2 Schedule -- 4.5.3 Status -- 4.5.4 Other time considerations -- 4.6 Fault planning -- 4.7 Stage checklists -- Part 2 Migration steps -- Chapter 5. …”

Tabla de Contenidos: “…3.3.2 Composition and Mechanical Behavior of Spongy Bone -- 3.4 Teeth -- 3.4.1 Tooth Anatomy and Evolution -- 3.4.2 Plaque, Organic Acids, Alter pH and Demineralize Tooth Surfaces -- 3.4.3 Dentin Exposure Through the Gum-line: Periodontal Disease -- 3.4.4 Tooth Statics and Dynamics: The Origins of Orthodontia -- 3.4.5 Endodonics: Resolving the Dying Internal Structure of a Tooth -- 3.4.6 Sealants as a Preventive Procedure to Fight Tooth Decay -- 3.4.7 Oral Surgery, Bone Implants, and Fracture Fixation -- 3.5 Conclusions -- 3.6 Problems -- References -- 4 Connective and Soft Tissues -- 4.1 Introduction -- 4.2 Protein Structure and Composition in the Circulatory System -- 4.3 Protein Structure of Valvular Tissue and Leaflets -- 4.3.1 Valve and Leaflet Defects -- 4.3.2 Aneurysms and Fistulae -- 4.3.3 Aortic Dissection -- 4.4 Dermal Tissues, Including Hair and Nerves -- 4.4.1 The Skin -- 4.4.2 The Subcutaneous or Adipose Tissues -- 4.4.3 The Dermis -- 4.4.4 The Stratum Corneum and Epidermis -- 4.4.5 Skin Care as a Business -- 4.5 Hair -- 4.5.1 Hair Morphology -- 4.5.2 Features and Attributes of Hair -- 4.5.3 Hair as a Business -- 4.6 Nails -- 4.7 Muscle Tissues -- 4.8 Looking Ahead -- 4.9 Conclusions -- 4.10 Problems -- References -- 5 Property Assessments of Tissues -- 5.1 Introduction -- 5.2 Mechanical Properties -- 5.2.1 Uniaxial Extension and Compression -- 5.3 How Much Does the Humerus Bone Length Shrink Upon Loading With the Bar? …”

Tabla de Contenidos: “…4.3 The Abuse of Information and Knowledge -- 4.3.1 Projected Use of Machines to Block Human Abuse -- 4.3.2 Abuse of Machines Against Humans -- 4.4 Indulgence of Societies in Negative Social Settings -- 4.5 Deception and Cowardice in Humans -- 4.6 Negative Social Change: Deterioration and Decay -- 4.7 Social Decay of Nations and Cultures -- Conclusions -- References -- 5 Role of Devices, Computers and Networks -- 5.1 Introduction -- 5.2 Devices, Machines, Humans, and Social Realities -- 5.2.1 Beneficial and Constructive Role -- 5.2.2 Detrimental and Exploitive Role -- 5.3 Reality and Oscillation of Social Norms -- 5.3.1 Social Energy and Ensuing Shifts -- 5.3.2 Change in the Four (K, C, W, and E) Spaces -- 5.3.3 Noise in the Social Setting -- 5.4 Typical Global Shifts in Societies and Nations -- 5.5 Oscillation of Social Norms -- 5.5.1 Social Lais Sez-Faire -- 5.5.2 Social Supervision -- Conclusions -- References -- II. …”

Tabla de Contenidos: “…-- 4.2 Definitions for Leadership -- 4.3 Theories of Leadership -- 4.4 Leadership Categories -- 4.5 Leadership and Goal Setting -- 4.6 Characteristics of Quality Leaders -- 4.7 Warren Bennis Principles of Great Teams -- 4.8 The Seven Habits of Highly Effective Leaders -- 4.9 The Ten Commandments of cGMPs (Current Good Manufacturing Practices) -- 4.10 Fifty Insights for CEOs -- 4.11 Fifteen Thoughts of Chanakya -- 4.12 Wilkie's Leadership Qualities -- 4.13 Leadership Responsibilities -- 4.14 Moral Leadership -- 4.15 Contributors for Moral Leadership -- 4.16 Role of Top Management in Quality Management -- 4.17 Leadership and Knowledge of Psychology -- 4.18 Case Studies on Leadership Qualities -- 4.19 Some Quotations on Leadership -- 4.20 Conclusion -- Further Reading -- Chapter 5: Scientific Management -- 5.1 TQM and Scientific Management -- 5.2 The Industrial Revolution -- 5.3 Evolution of Management Thinking -- 5.4 Phases of Growth of Management Thinking -- 5.5 Early Pioneers in Management Thinking- Pre-19th Century -- 5.6 Concepts of Scientific Management -- 5.7 Specific Aims of Scientific Management -- 5.8 Advantages of Scientific Management -- 5.9 Misconceptions of Scientific Management -- 5.10 Resistance to Scientific Management -- 5.11 Conclusion -- Further Reading -- Chapter 6: System Approach to Management Theory -- 6.1 Development of System Approach -- 6.2 What is a System? …”

Tabla de Contenidos: “…4.3 Other Data Structures -- 4.3.1 Arrays and Ranges -- 4.3.2 Blocks -- 4.3.3 Hashes and Symbols -- 4.3.4 CSS Revisited -- 4.4 Ruby Classes -- 4.4.1 Constructors -- 4.4.2 Class Inheritance -- 4.4.3 Modifying Built-In Classes -- 4.4.4 A Controller Class -- 4.4.5 A User Class -- 4.5 Exercises -- Chapter 5 Filling in the Layout -- 5.1 Adding Some Structure -- 5.1.1 Site Navigation -- 5.1.2 Custom CSS -- 5.1.3 Partials -- 5.2 Layout Links -- 5.2.1 Integration Tests -- 5.2.2 Rails Routes -- 5.2.3 Named Routes -- 5.3 User Signup: A First Step -- 5.3.1 Users Controller -- 5.3.2 Signup URL -- 5.4 Conclusion -- 5.5 Exercises -- Chapter 6 Modeling and Viewing Users, Part I -- 6.1 User Model -- 6.1.1 Database Migrations -- 6.1.2 The Model File -- 6.1.3 Creating User Objects -- 6.1.4 Finding User Objects -- 6.1.5 Updating User Objects -- 6.2 User Validations -- 6.2.1 Validating Presence -- 6.2.2 Length Validation -- 6.2.3 Format Validation -- 6.2.4 Uniqueness Validation -- 6.3 Viewing Users -- 6.3.1 Debug and Rails Environments -- 6.3.2 User Model, View, Controller -- 6.3.3 A Users Resource -- 6.4 Conclusion -- 6.5 Exercises -- Chapter 7 Modeling and Viewing Users, Part II -- 7.1 Insecure Passwords -- 7.1.1 Password Validations -- 7.1.2 A Password Migration -- 7.1.3 An Active Record Callback -- 7.2 Secure Passwords -- 7.2.1 A Secure Password Test -- 7.2.2 Some Secure Password Theory -- 7.2.3 Implementing has_password? …”