Tabla de Contenidos: “…Cover -- Contents -- Foreword -- Acknowledgements -- 1 Overview of the Book -- 2 Background -- 2.1 Evolution of Cellular Systems -- 2.1.1 Third-generation Network Architecture -- 2.1.2 Important Elements of the 3G Architecture -- 2.1.3 Functions and Protocols in the 3GPP System -- 2.1.4 The EPS System -- 2.2 Basic Security Concepts -- 2.2.1 Information Security -- 2.2.2 Design Principles -- 2.2.3 Communication Security Features -- 2.3 Basic Cryptographic Concepts -- 2.3.1 Cryptographic Functions -- 2.3.2 Securing Systems with Cryptographic Methods -- 2.3.3 Symmetric Encryption Methods -- 2.3.4 Hash Functions -- 2.3.5 Public-key Cryptography and PKI -- 2.3.6 Cryptanalysis -- 2.4 Introduction to LTE Standardization -- 2.4.1 Working Procedures in 3GPP -- 2.5 Notes on Terminology and Specification Language -- 2.5.1 Terminology -- 2.5.2 Specification Language -- 3 GSM Security -- 3.1 Principles of GSM Security -- 3.2 The Role of the SIM -- 3.3 Mechanisms of GSM Security -- 3.3.1 Subscriber Authentication in GSM -- 3.3.2 GSM Encryption -- 3.3.3 GPRS Encryption -- 3.3.4 Subscriber Identity Confidentiality -- 3.4 GSM Cryptographic Algorithms -- 4 Third-generation Security (UMTS) -- 4.1 Principles of Third-generation Security -- 4.1.1 Elements of GSM Security Carried Over to 3G -- 4.1.2 Weaknesses in GSM Security -- 4.1.3 Higher Level Objectives -- 4.2 Third-generation Security Mechanisms -- 4.2.1 Authentication and Key Agreement -- 4.2.2 Ciphering Mechanism -- 4.2.3 Integrity Protection Mechanism -- 4.2.4 Identity Confidentiality Mechanism -- 4.3 Third-generation Cryptographic Algorithms -- 4.3.1 KASUMI -- 4.3.2 UEA1 and UIA1 -- 4.3.3 SNOW3G, UEA2 and UIA2 -- 4.3.4 MILENAGE -- 4.3.5 Hash Functions -- 4.4 Interworking between GSM and 3G security -- 4.4.1 Interworking Scenarios -- 4.4.2 Cases with SIM -- 4.4.3 Cases with USIM…”

Tabla de Contenidos: “…Appendix F Extension: Effort Monitoring and Worker Termination -- References -- References for Appendices -- 4 Heterogeneous Agents in the Macroeconomy: Reduced-Heterogeneity Representations -- 1 Introduction -- 2 The Economic Problem and Notations -- 2.1 The Model -- 2.2 Equilibrium De nition and Intuition to Reduce the State Space -- 3 No-Trade Equilibria -- 3.1 No-Trade Equilibria with Transitory Shocks -- 3.1.1 Assumptions -- 3.2 Preserving Time-Varying Precautionary Saving in the Linear Model -- 3.3 No-Trade Equilibrium with Permanent Shocks -- 4 Small-Heterogeneity Models -- 4.1 Models Based on Assumptions About Labor Supply -- 4.1.1 Assumptions -- 4.1.2 Equilibrium Structure -- 4.1.3 The System -- 4.1.4 Algorithm: Finding the Value of L -- 4.1.5 Simulations -- 4.1.6 References and Limits -- 4.2 Models Based on Linearity in the Period Utility Function -- 4.2.1 Assumptions -- 4.2.2 Equilibrium Structure -- 4.2.3 Using Reduced Heterogeneity to Model Wealth Inequality over the Business Cycle -- 4.2.4 Other References and Remarks -- 4.3 Models Based on a "Family" Assumption -- 4.3.1 Assumptions -- 4.3.2 Equilibrium Structure -- 4.3.3 Algorithm and Simulations -- 4.3.4 Example of Quantitative Work -- 4.4 Assessment of Small-Heterogeneity Models -- 5 Truncated-History Models -- 5.1 Assumptions -- 5.2 Equilibrium Structure -- 5.3 Equations of the Model -- 5.4 Algorithm for the Steady State -- 5.5 Dynamics -- 5.6 Choosing the Preference Shifters ξeN -- 5.7 Numerical Example -- 6 Optimal Policies -- 7 Comparison with Other Approach Using Perturbation Methods -- 8 Heterogeneous Expectations -- 9 Concluding Remarks -- References -- Part 2 Finance -- 5 Heterogeneous Agent Models in Finance -- 1 Introduction -- 2 HAMs of Single Asset Market in Discrete-Time -- 2.1 Market Mood and Adaptive Behavior -- 2.2 Volatility Clustering: Calibration and Mechanisms…”

Tabla de Contenidos: “…DISEÑO PÁGINA -- 4.1 TEMAS -- 4.1.1 TEMAS -- 4.1.2 COLORES -- 4.1.3 FUENTES -- 4.1.4 EFECTOS -- 4.2 CONFIGURAR PÁGINA -- 4.2.1 MÁRGENES -- 4.2.2 ORIENTACIÓN -- 4.2.3 TAMAÑO -- 4.2.4 ÁREA DE IMPRESIÓN -- 4.2.5 SALTOS -- 4.2.6 FONDOS -- 4.2.7 IMPRIMIR TÍTULOS -- 4.2.8 CUADRO DE DIÁLOGO CONFIGURAR PÁGINA (...) -- 4.3 AJUSTAR ÁREA DE IMPRESIÓN -- 4.3.1 ANCHO -- 4.3.2 ALTO -- 4.3.3 ESCALA -- 4.4 OPCIONES DE LA HOJA -- 4.4.1 LÍNEAS DIVISIÓN…”

Tabla de Contenidos: “…3.3 Machine learning for classification -- 3.3.1 Logistic regression -- 3.3.2 Training logistic regression -- 3.3.3 Model interpretation -- 3.3.4 Using the model -- 3.4 Next steps -- 3.4.1 Exercises -- 3.4.2 Other projects -- Summary -- Answers to exercises -- 4 Evaluation metrics for classification -- 4.1 Evaluation metrics -- 4.1.1 Classification accuracy -- 4.1.2 Dummy baseline -- 4.2 Confusion table -- 4.2.1 Introduction to the confusion table -- 4.2.2 Calculating the confusion table with NumPy -- 4.2.3 Precision and recall -- 4.3 ROC curve and AUC score -- 4.3.1 True positive rate and false positive rate -- 4.3.2 Evaluating a model at multiple thresholds -- 4.3.3 Random baseline model -- 4.3.4 The ideal model -- 4.3.5 ROC Curve -- 4.3.6 Area under the ROC curve (AUC) -- 4.4 Parameter tuning -- 4.4.1 K-fold cross-validation -- 4.4.2 Finding best parameters -- 4.5 Next steps -- 4.5.1 Exercises -- 4.5.2 Other projects -- Summary -- Answers to exercises -- 5 Deploying machine learning models -- 5.1 Churn-prediction model -- 5.1.1 Using the model -- 5.1.2 Using Pickle to save and load the model -- 5.2 Model serving -- 5.2.1 Web services -- 5.2.2 Flask -- 5.2.3 Serving churn model with Flask -- 5.3 Managing dependencies -- 5.3.1 Pipenv -- 5.3.2 Docker -- 5.4 Deployment -- 5.4.1 AWS Elastic Beanstalk -- 5.5 Next steps -- 5.5.1 Exercises -- 5.5.2 Other projects -- Summary -- 6 Decision trees and ensemble learning -- 6.1 Credit risk scoring project -- 6.1.1 Credit scoring dataset -- 6.1.2 Data cleaning -- 6.1.3 Dataset preparation -- 6.2 Decision trees -- 6.2.1 Decision tree classifier -- 6.2.2Decision tree learning algorithm -- 6.2.3 Parameter tuning for decision tree -- 6.3 Random forest -- 6.3.1 Training a random forest -- 6.3.2 Parameter tuning for random forest -- 6.4 Gradient boosting -- 6.4.1 XGBoost: Extreme gradient boosting…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright Page -- Dedication Page -- Contents -- Preface -- Acknowledgement -- Chapter 1 Band Reduction of HSI Segmentation Using FCM -- 1.1 Introduction -- 1.2 Existing Method -- 1.2.1 K-Means Clustering Method -- 1.2.2 Fuzzy C-Means -- 1.2.3 Davies Bouldin Index -- 1.2.4 Data Set Description of HSI -- 1.3 Proposed Method -- 1.3.1 Hyperspectral Image Segmentation Using Enhanced Estimation of Centroid -- 1.3.2 Band Reduction Using K-Means Algorithm -- 1.3.3 Band Reduction Using Fuzzy C-Means -- 1.4 Experimental Results -- 1.4.1 DB Index Graph -- 1.4.2 K-Means-Based PSC (EEOC) -- 1.4.3 Fuzzy C-Means-Based PSC (EEOC) -- 1.5 Analysis of Results -- 1.6 Conclusions -- References -- Chapter 2 A Fuzzy Approach to Face Mask Detection -- 2.1 Introduction -- 2.2 Existing Work -- 2.3 The Proposed Framework -- 2.4 Set-Up and Libraries Used -- 2.5 Implementation -- 2.6 Results and Analysis -- 2.7 Conclusion and Future Work -- References -- Chapter 3 Application of Fuzzy Logic to the Healthcare Industry -- 3.1 Introduction -- 3.2 Background -- 3.3 Fuzzy Logic -- 3.4 Fuzzy Logic in Healthcare -- 3.5 Conclusions -- References -- Chapter 4 A Bibliometric Approach and Systematic Exploration of Global Research Activity on Fuzzy Logic in Scopus Database -- 4.1 Introduction -- 4.2 Data Extraction and Interpretation -- 4.3 Results and Discussion -- 4.3.1 Per Year Publication and Citation Count -- 4.3.2 Prominent Affiliations Contributing Toward Fuzzy Logic -- 4.3.3 Top Journals Emerging in Fuzzy Logic in Major Subject Areas -- 4.3.4 Major Contributing Countries Toward Fuzzy Research Articles -- 4.3.5 Prominent Authors Contribution Toward the Fuzzy Logic Analysis -- 4.3.6 Coauthorship of Authors -- 4.3.7 Cocitation Analysis of Cited Authors -- 4.3.8 Cooccurrence of Author Keywords…”

Tabla de Contenidos:

Tabla de Contenidos: “…6.3.1.3 Ultrashort pulse lasers -- 6.3.2 Wavelength based division -- 6.3.2.1 Mid infrared lasers (mid IR) -- 6.3.2.2 Infrared lasers (IR lasers) -- 6.3.2.3 Ultraviolet lasers (UV lasers) -- 6.4 Material removal mechanisms -- 6.4.1 Thermal ablation -- 6.4.2 Cold ablation/photochemical ablation/photo ablation -- 6.5 Laser microprocessing of materials -- 6.5.1 Direct laser micromachining in open surroundings -- 6.5.1.1 Metals and alloys -- 6.5.1.2 Semiconductors, composites, and specially developed materials -- 6.5.1.3 Glass and polymers -- 6.5.2 Direct laser micromachining in different surrounding conditions -- 6.6 Challenges and future of laser processing -- References -- 7 Underwater pulsed laser beam cutting with a case study -- 7.1 Introduction -- 7.2 Laser as a machine tool -- 7.3 Laser material interaction -- 7.4 Laser beam cutting -- 7.4.1 Process characteristics -- 7.4.2 Cut quality characteristics -- 7.4.3 Principles of laser beam cutting -- 7.4.3.1 Different types of laser beam cutting -- 7.4.3.1.1 Laser sublimation cutting -- 7.4.3.1.2 Controlled fracture technique -- 7.4.3.1.3 Laser fusion cutting -- 7.4.3.1.4 Reactive fusion cutting -- 7.4.3.1.5 Laser cutting at different assisted medium -- 7.4.3.1.6 Laser beam microcutting -- 7.4.4 Application of laser beam machining -- 7.5 Underwater laser beam machining -- 7.5.1 Advantages of laser beam cutting at submerged condition -- 7.5.2 Material removal mechanism of nanosecond pulsed laser beam cutting at submerged condition -- 7.5.3 Development of different types of liquid-assisted laser beam machining -- 7.5.3.1 Laser beam cutting in submerged condition -- 7.5.3.2 Underwater assist gas jet/waterjet assisted laser beam cutting -- 7.5.3.3 Molten salt-jet-guided/chemical laser beam -- 7.5.3.4 Water jet following the laser beam…”

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: “…2.4.1 International Standards Not Set in Stone -- 2.4.2 From SNA 1968 to SNA 1993 -- 2.4.3 From SNA 1993 to SNA 2008 -- 2.4.4 The SNA and Source Statistics for Enterprises -- 2.5 Conclusions and Implications for Business Statistics -- References -- Chapter 3 GDP and the SNA: Future Challenges -- 3.1 Introduction -- 3.2 An Agenda for the Future -- 3.3 The Tangled Web of Globalization -- 3.4 The Digital Revolution -- 3.5 Moving Beyond GDP: GDP Impeached -- 3.6 Including a Measure of Well‐being -- 3.7 Putting a Value on the Environment -- 3.8 Challenges Replacing GDP -- 3.9 Conclusions and Implications for Business Statistics -- References -- Chapter 4 Bridging the Gap Between Business and Macroeconomic Statistics: Methodological Considerations and Practical Solutions -- 4.1 Introduction -- 4.2 Global Production and Statistics -- 4.2.1 Concepts of Nationality and Economic Ownership -- 4.2.2 Case Finland: Global Production in Economic Statistics -- 4.2.2.1 Identification of Enterprises Involved in Global Production -- 4.2.2.2 Case on Automotive Industry -- 4.2.2.3 Foreign Trade of Goods Based on Economic Ownership -- 4.2.2.4 Challenges Related to Global Production Recordings -- 4.3 Co‐operation Between National Statistical Offices and National Central Bank Statistics Functions Tackling Globalization Problems -- 4.3.1 Foreign Direct Investment Network as an Example of Co‐operation -- 4.3.2 Early‐Warning System (EWS) -- 4.3.3 A Roadmap for Solving the Globalization‐Related Issues in Monetary, Financial, and Balance of Payments - Statistics -- 4.4 Bridging the Gap Between Business and Economic Statistics Through Global Data Sharing -- 4.4.1 Product Innovation - One‐Off or Regular Data Sharing for Better Quality -- 4.4.2 Service Innovation - Improving Respondent Service for MNEs -- 4.4.3 Process Innovation to Statistical Production by Data Sharing…”

Tabla de Contenidos: “…3.3.3 Graceful terminations -- 3.3.4 Folder watcher -- 3.3.5 Action scripts -- 3.4 Running watchers -- 3.4.1 Testing watcher execution -- 3.4.2 Scheduling watchers -- Summary -- 4 Handling sensitive data -- 4.1 Principles of automation security -- 4.1.1 Do not store sensitive information in scripts -- 4.1.2 Principle of least privilege -- 4.1.3 Consider the context -- 4.1.4 Create role-based service accounts -- 4.1.5 Use logging and alerting -- 4.1.6 Do not rely on security through obscurity -- 4.1.7 Secure your scripts -- 4.2 Credentials and secure strings in PowerShell -- 4.2.1 Secure strings -- 4.2.2 Credential objects -- 4.3 Storing credentials and secure strings in PowerShell -- 4.3.1 The SecretManagement module -- 4.3.2 Set up the SecretStore vault -- 4.3.3 Set up a KeePass vault -- 4.3.4 Choosing the right vault -- 4.3.5 Adding secrets to a vault -- 4.4 Using credentials and secure strings in your automations -- 4.4.1 SecretManagement module -- 4.4.2 Using Jenkins credentials -- 4.5 Know your risks -- Summary -- 5 PowerShell remote execution -- 5.1 PowerShell remoting -- 5.1.1 Remote context -- 5.1.2 Remote protocols -- 5.1.3 Persistent sessions -- 5.2 Script considerations for remote execution -- 5.2.1 Remote execution scripts -- 5.2.2 Remote execution control scripts -- 5.3 PowerShell remoting over WSMan -- 5.3.1 Enable WSMan PowerShell remoting -- 5.3.2 Permissions for WSMan PowerShell remoting -- 5.3.3 Execute commands with WSMan PowerShell remoting -- 5.3.4 Connect to the desired version of PowerShell -- 5.4 PowerShell remoting over SSH -- 5.4.1 Enable SSH PowerShell remoting -- 5.4.2 Authenticating with PowerShell and SSH -- 5.4.3 SSH environment considerations -- 5.4.4 Execute commands with SSH PowerShell remoting -- 5.5 Hypervisor-based remoting -- 5.6 Agent-based remoting -- 5.7 Setting yourself up for success with PowerShell remoting…”

Tabla de Contenidos: “…References -- Chapter 3 Safe and Reliable Smart City Design Based on Blockchain Technology -- 3.1 Introduction -- 3.1.1 Blockchain Technology -- 3.1.2 Use of Blockchain in Smart City -- 3.1.3 Objective of Work -- 3.2 Related Work -- 3.2.1 Problem Statement -- 3.3 Blockchain Technology for Smart Cities -- 3.3.1 Application of the System -- 3.3.2 Blockchain Technology's Many Advantages in the Modern Smart City -- 3.4 Methods -- 3.4.1 Blockchain-Based Smart City Infrastructure -- 3.5 Conclusion -- References -- Chapter 4 Blockchain and Digital Twin for Enhancing Personal Security in Modern Cities -- 4.1 Introduction -- 4.2 Digital Twin -- 4.2.1 Digital Twins in Manufacturing Industry -- 4.2.2 Integration with Emerging Technologies -- 4.2.3 Real-World Reflection Through Sensors -- 4.2.4 Land Management and Global Concerns -- 4.2.5 Increasing Importance of Information Technologies -- 4.2.6 Advancements in IoT and Connectivity -- 4.2.7 Role of Artificial Intelligence (AI) in Digital Twins -- 4.2.8 Cloud Computing Empowering Digital Twins -- 4.2.9 Impact of 5G Technology -- 4.2.10 Smart Cities and the Growing Application Field -- 4.2.11 Big Data's Role in Informed Decision Making -- 4.3 Digital Twin and Metaverse -- 4.3.1 Virtual Prototyping and Design Optimization -- 4.3.2 Healthcare Integration for Personalized Medicine -- 4.3.3 The Intersection of Digital Twins and the Metaverse -- 4.3.4 Immersive Collaborative Environments -- 4.3.5 Enhanced Virtual Experiences Through Data Fusion -- 4.3.6 Challenges and Future Developments -- 4.3.7 Data Privacy and Security Concerns -- 4.3.8 Standardization and Interoperability -- 4.4 Blockchain Technology -- 4.4.1 Overview of Blockchain Technology -- 4.4.2 Data Checking and Analysis -- 4.4.3 Immutable History -- 4.4.4 Potential Problem Solving -- 4.4.5 Rapid Adoption by Major Companies…”

Tabla de Contenidos: “…6.4 Challenges for Wireless On-Chip Communication -- 6.4.1 Performance and Area Analysis -- 6.4.2 Crosstalk Between Inductive Links -- 6.4.3 Crosstalk Noise on Adjacent On-Chip Components -- 6.4.3.1 Crosstalk effects due to an inductive link -- 6.4.3.2 Case study -- 6.4.3.3 Crosstalk noise effects caused by inductive link arrays -- 6.4.3.4 Noise sensitivity of power network topologies -- 6.5 Intertier Power Transfer -- 6.6 Summary -- 7 Interconnect Prediction Models -- 7.1 Interconnect Prediction Models for Two-Dimensional Circuits -- 7.2 Interconnect Prediction Models for Three-Dimensional ICs -- 7.3 Projections for Three-Dimensional ICs -- 7.4 Summary -- 8 Cost Considerations for Three-Dimensional Integration -- 8.1 Through Silicon Via Processing Options -- 8.1.1 TSV Flows and Geometries -- 8.1.2 Cost Comparison of Through Silicon Via Processing Steps -- 8.1.2.1 Through silicon via lithography -- 8.1.2.2 Through silicon via silicon etch -- 8.1.2.3 Through silicon via liner processing -- 8.1.2.4 Through silicon via liner opening for through silicon via last flow -- 8.1.2.5 Through silicon via barrier and Cu seed processing -- 8.1.2.6 Through silicon via Cu plating and effect on chemical mechanical planarization -- 8.1.2.7 Through silicon via chemical mechanical planarization processing -- 8.1.2.8 Backside processing -- 8.1.3 Comparison of Through Silicon Via Processing Cost -- 8.1.3.1 Processing of the 5×50 through silicon via geometry -- 8.1.3.2 Processing of the 10×100 through silicon via geometry -- 8.1.3.3 Scaling through silicon via geometries -- 8.2 Interposer-Based Systems Integration -- 8.2.1 Cost of Interposer Manufacturing Features -- 8.2.1.1 Cost of through silicon via processing -- 8.2.1.2 Cost of die-to-die interconnect processing -- 8.2.1.3 Cost of processing metal planes and metal-insulator-metal capacitors…”

Tabla de Contenidos: “…-- 4.2.6 Types of Neural Networks -- 4.2.6.1 Artificial Neural Network (ANN) -- 4.2.6.2 Recurrent Neural Network (RNN) -- 4.2.6.3 Convolutional Neural Network (CNN) -- 4.2.7 Learning Techniques in Neural Network -- 4.2.8 Applications of Neural Network -- 4.2.9 Advantages of Neural Networks -- 4.2.10 Disadvantages of Neural Network -- 4.2.11 Limitations of Neural Networks -- 4.3 Back-Propagation -- 4.3.1 Working of Back-Propagation -- 4.3.2 Types of Back-Propagation -- 4.3.2.1 Static Back-Propagation -- 4.3.2.2 Recurrent Back-Propagation -- 4.3.2.3 Advantages of Back-Propagation -- 4.3.2.4 Disadvantages of Back-Propagation -- 4.4 Activation Function (AF) -- 4.4.1 Sigmoid Active Function -- 4.4.1.1 Advantages -- 4.4.1.2 Disadvantages -- 4.4.2 RELU Activation Function -- 4.4.2.1 Advantages -- 4.4.2.2 Disadvantages -- 4.4.3 TANH Active Function -- 4.4.3.1 Advantages -- 4.4.3.2 Disadvantages -- 4.4.4 Linear Function -- 4.4.5 Advantages -- 4.4.6 Disadvantages…”

Tabla de Contenidos: “…4.2 Current State of Science -- 4.2.1 Theoretical Framework -- 4.2.2 Smoke Measurements -- 4.2.3 Smoke Plume Modeling -- 4.2.4 Interactive Processes -- 4.2.5 Smoke Decision Support Systems -- 4.3 Gaps in Understanding Plume Dynamics -- 4.3.1 Measurements -- 4.3.2 Plume Rise -- 4.3.3 Dispersion and Transport Modeling -- 4.3.4 Nighttime Smoke -- 4.3.5 Physics-Based Fire Models -- 4.3.6 Smoke Management for Prescribed Fires -- 4.4 Vision for Improving Plume Dynamics Science -- 4.4.1 New Research on Observational and Computational Capabilities -- 4.4.2 New Approaches and Tools -- 4.4.3 New Projects -- 4.4.4 Recent Policies and Integration with Smoke Impacts Research -- 4.5 Emerging Issues and Challenges -- 4.5.1 Coupled Modeling Systems -- 4.5.2 Improving Modeling Tools with Field Campaign Data -- 4.5.3 Real-Time Smoke Transport Modeling and Prediction -- 4.5.4 Smoke from Duff Burning Under Drought Conditions -- 4.5.5 Smoke Plume Dynamics and Climate Change -- 4.5.6 Smoke Dynamics in the Earth System -- 4.6 Conclusions -- 4.7 Key Findings -- References -- 5 Emissions -- 5.1 Introduction -- 5.2 Current State of the Science -- 5.2.1 Fuel Properties, Combustion Processes, and Emissions -- 5.2.2 Smoke Composition and Emission Factors -- 5.2.3 Emission Calculations -- 5.3 Existing Data, Tools, Models, and Other Technology -- 5.3.1 Emission Factors -- 5.3.2 Emission Inventories -- 5.3.3 Emission Models for Land Management -- 5.4 Gaps in Data, Understanding, and Tools/Technology -- 5.4.1 Emission Factors for Wildfires -- 5.4.2 Connecting Laboratory Studies with Field Observations -- 5.4.3 Variability of EFs with Combustion Conditions -- 5.4.4 Validation of Emission Inventories -- 5.4.5 Forecasting Wildfire Emissions -- 5.4.6 Measuring and Modeling PM2.5 -- 5.4.7 Emissions of Hazardous Air Pollutants -- 5.4.8 Emissions from Structure Fires -- 5.5 Conclusions…”

Tabla de Contenidos: “…3.3.1 Attacks On Computer-Vision-Based Applications -- 3.3.2 Attacks On Natural Language Processing Applications -- 3.3.3 Attacks On Data Poisoning Applications -- 3.4 Specific Attacks In The Real World -- 3.4.1 Attacks On Natural Language Processing -- 3.4.2 Attacks Using Data Poisoning -- 3.5 Discussions and Open Issues -- 3.6 Conclusions -- References -- 4 Attack Models for Collaborative Deep Learning -- 4.1 Introduction -- 4.2 Background -- 4.2.1 Deep Learning (DL) -- Convolution Neural Network -- 4.2.2 Collaborative Deep Learning (CDL) -- Architecture -- Collaborative Deep Learning Workflow -- 4.2.3 Deep Learning Security and Collaborative Deep Learning Security -- 4.3 Auror: An Automated Defense -- 4.3.1 Problem Setting -- 4.3.2 Threat Model -- Targeted Poisoning Attacks -- 4.3.3 AUROR Defense -- 4.3.4 Evaluation -- 4.4 A New CDL Attack: Gan Attack -- 4.4.1 Generative Adversarial Network (GAN) -- 4.4.2 GAN Attack -- Main Protocol -- 4.4.3 Experiment Setups -- Dataset -- System Architecture -- Hyperparameter Setup -- 4.4.4 Evaluation -- 4.5 Defend Against Gan Attack In IoT -- 4.5.1 Threat Model -- 4.5.2 Defense System -- 4.5.3 Main Protocols -- 4.5.4 Evaluation -- 4.6 Conclusions -- Acknowledgment -- References -- 5 Attacks On Deep Reinforcement Learning Systems: A Tutorial -- 5.1 Introduction -- 5.2 Characterizing Attacks on DRL Systems -- 5.3 Adversarial Attacks -- 5.4 Policy Induction Attacks -- 5.5 Conclusions and Future Directions -- References -- 6 Trust and Security of Deep Reinforcement Learning -- 6.1 Introduction -- 6.2 Deep Reinforcement Learning Overview -- 6.2.1 Markov Decision Process -- 6.2.2 Value-Based Methods -- V-value Function -- Q-value Function -- Advantage Function -- Bellman Equation -- 6.2.3 Policy-Based Methods -- 6.2.4 Actor-Critic Methods -- 6.2.5 Deep Reinforcement Learning -- 6.3 The Most Recent Reviews…”

Tabla de Contenidos: “…LOS GASTOS DEDUCIBLES -- 4.3.6. REDUCCIONES…”

Tabla de Contenidos: “…-- 4.2.5 Packet Scheduling -- 4.3 The Internet Protocol (IP): IPv4, Addressing, IPv6, and More -- 4.3.1 IPv4 Datagram Format -- 4.3.2 IPv4 Addressing -- 4.3.3 Network Address Translation (NAT) -- 4.3.4 IPv6 -- 4.4 Generalized Forwarding and SDN -- 4.4.1 Match -- 4.4.2 Action -- 4.4.3 OpenFlow Examples of Match-plus-action in Action -- 4.5 Middleboxes -- 4.6 Summary -- Homework Problems and Questions -- Wireshark Lab: IP -- Interview: Vinton G. …”

Tabla de Contenidos: “…-- 4.2.2 COBIT in a SIAM ecosystem -- 4.3 Lean -- 4.3.1 What is Lean? -- 4.3.2 Lean in a SIAM ecosystem -- 4.4 DevOps -- 4.4.1 What is DevOps? …”

Tabla de Contenidos: “…-- 3.4.2 Creating the enemy prefab -- 3.4.3 Instantiating from an invisible SceneController -- 3.5 Shooting by instantiating objects -- 3.5.1 Creating the projectile prefab -- 3.5.2 Shooting the projectile and colliding with a target -- 3.5.3 Damaging the player -- Summary -- 4 Developing graphics for your game -- 4.1 Understanding art assets -- 4.2 Building basic 3D scenery: Whiteboxing -- 4.2.1 Whiteboxing explained -- 4.2.2 Drawing a floor plan for the level -- 4.2.3 Laying out primitives according to the plan -- 4.3 Texturing the scene with 2D images -- 4.3.1 Choosing a file format -- 4.3.2 Importing an image file -- 4.3.3 Applying the image -- 4.4 Generating sky visuals by using texture images -- 4.4.1 What is a skybox? …”

Tabla de Contenidos: “…Experimental design for the development, transfer, scaling-up, and optimisation of treatment technologies: case studies of dewatering and drying -- 4.1 INTRODUCTION -- 4.2 EXPERIMENTATION IN FAECAL SLUDGE MANAGEMENT -- 4.2.1 Scales of experiments -- 4.2.2 Designing an experiment -- 4.3 TRANSFERRING TECHNOLOGY: CONDITIONING TO IMPROVE DEWATERING -- 4.3.1 Introduction to faecal sludge dewatering with conditioners -- 4.3.2 Types and mechanisms of conditioners -- 4.3.3 Key parameters for selection of conditioners and optimal dose -- 4.3.4 Laboratory- and pilot-scale testing…”