Tabla de Contenidos: “…. -- La Convention anticorruption de 1997, un premier pas dans la bonne direction -- Un problème clé : la sollicitation de pots-de-vin -- Le programme de lutte contre la sollicitation de pots-de-vin mis en place par le BIAC -- Reconnaissance publique du problème -- Intégration à des programmes de suivi -- Procédure de validation des transactions -- Assistance en cas de sollicitation -- Coordination des mesures -- Conclusions -- Chapitre 15. …”

Tabla de Contenidos: “…Front Cover -- Advances in GPU Research and Practice -- Copyright -- Dedication -- Contents -- List of Contributors -- Preface -- Acknowledgments -- Part 1: Programming and tools -- Chapter 1: Formal analysis techniques for reliable GPU programming: current solutions and call to action -- 1 GPUs in Support of Parallel Computing -- Bugs in parallel and GPU code -- 2 A quick introduction to GPUs -- Organization of threads -- Memory spaces -- Barrier synchronization -- Warps and lock-step execution -- Dot product example -- 3 Correctness issues in GPU programming -- Data races -- Lack of forward progress guarantees -- Floating-point accuracy -- 4 The need for effective tools -- 4.1 A Taxonomy of Current Tools -- 4.2 Canonical Schedules and the Two-Thread Reduction -- Race freedom implies determinism -- Detecting races: ``all for one and one for all'' -- Restricting to a canonical schedule -- Reduction to a pair of threads -- 4.3 Symbolic Bug-Finding Case Study: GKLEE -- 4.4 Verification Case Study: GPUVerify -- 5 Call to Action -- GPUs will become more pervasive -- Current tools show promise -- Solving basic correctness issues -- Equivalence checking -- Clarity from vendors and standards bodies -- User validation of tools -- Acknowledgments -- References -- Chapter 2: SnuCL: A unified OpenCL framework for heterogeneous clusters -- 1 Introduction -- 2 OpenCL -- 2.1 Platform Model -- 2.2 Execution Model -- 2.3 Memory Model -- 2.4 Synchronization -- 2.5 Memory Consistency -- 2.6 OpenCL ICD -- 3 Overview of SnuCL framework -- 3.1 Limitations of OpenCL -- 3.2 SnuCL CPU -- 3.3 SnuCL Single -- 3.4 SnuCL Cluster -- 3.4.1 Processing synchronization commands -- 4 Memory management in SnuCL Cluster -- 4.1 Space Allocation to Memory Objects -- 4.2 Minimizing Copying Overhead -- 4.3 Processing Memory Commands -- 4.4 Consistency Management…”

Tabla de Contenidos: “…The use of TEs for validation of measurements -- 3.3.1.2. Systematic errors in PMU measurements -- 3.3.1.3. …”

Tabla de Contenidos: “…Limitations of the Review and Threats to Validity -- 3.4.3.1. Bias -- 3.4.3.2. Domain of study -- 3.5. …”

Tabla de Contenidos: “…Summary -- 6 Making adaptable automations -- 6.1 Event handling -- 6.1.1 Using try/catch blocks for event handling -- 6.1.2 Creating custom event handles -- 6.2 Building data-driven functions -- 6.2.1 Determining your data structure -- 6.2.2 Storing your data -- 6.2.3 Updating your data structure -- 6.2.4 Creating classes -- 6.2.5 Building the function -- 6.3 Controlling scripts with configuration data -- 6.3.1 Organizing your data -- 6.3.2 Using your configuration data -- 6.3.3 Storing your configuration data -- 6.3.4 Do not put cmdlets into your configuration data -- Summary -- 7 Working with SQL -- 7.1 Setting your schema -- 7.1.1 Data types -- 7.2 Connecting to SQL -- 7.2.1 Permissions -- 7.3 Adding data to a table -- 7.3.1 String validation -- 7.3.2 Inserting data to a table -- 7.4 Getting data from a table -- 7.4.1 SQL where clause -- 7.5 Updating records -- 7.5.1 Passing pipeline data -- 7.6 Keeping data in sync -- 7.6.1 Getting server data -- 7.7 Setting a solid foundation -- Summary -- 8 Cloud-based automation -- 8.1 Chapter resources -- 8.2 Setting up Azure Automation -- 8.2.1 Azure Automation -- 8.2.2 Log Analytics -- 8.2.3 Creating Azure resources -- 8.2.4 Authentication from Automation runbooks -- 8.2.5 Resource keys -- 8.3 Creating a hybrid runbook worker -- 8.3.1 PowerShell modules on hybrid runbook workers -- 8.4 Creating a PowerShell runbook -- 8.4.1 Automation assets -- 8.4.2 Runbook Editor -- 8.4.3 Runbook output -- 8.4.4 Interactive Cmdlets -- 8.5 Security considerations -- Summary -- 9 Working outside of PowerShell -- 9.1 Using COM objects and .NET Framework -- 9.1.1 Importing Word objects -- 9.1.2 Creating a Word document -- 9.1.3 Writing to a Word document -- 9.1.4 Adding tables to a Word document -- 9.2 Building tables from a PowerShell object -- 9.2.1 Converting PowerShell objects to tables…”

Tabla de Contenidos: “…Cover -- Series Page -- Title Page -- Copyright Page -- Dedication Page -- Contents -- List of Figures -- List of Tables -- Foreword -- Preface -- Acknowledgments -- Acronyms -- Part I: Artificial Intelligence Applications -- Chapter 1 Artificial Intelligence Overview: Architecture, Applications and Challenges -- 1.1 Introduction -- 1.1.1 History of Artificial Intelligence -- 1.1.2 Components of Artificial Intelligence -- 1.1.3 Levels of Artificial Intelligence -- 1.2 Artificial Intelligence Agents -- 1.3 Artificial Intelligence Algorithms -- 1.4 Applications of Artificial Intelligence -- 1.4.1 Agriculture -- 1.4.2 Healthcare -- 1.4.3 Education -- 1.4.4 Banking -- 1.4.5 Opportunities and Challenges -- 1.5 Conclusion -- References -- Chapter 2 Video Analytics Using Deep Learning Models -- 2.1 Introduction -- 2.1.1 Artificial Intelligence -- 2.1.2 Deep Learning Overview and Evolution -- 2.1.3 Edge Computing -- 2.1.4 Cloud Computing -- 2.2 Video Analytics -- 2.2.1 Video Surveillance -- 2.2.2 Real-Time Video Mining and Video Monitoring -- 2.2.3 Video Analytics Functional Model -- 2.3 Object Detection and Object Tracking -- 2.3.1 Object Detection -- 2.3.2 Object Tracking -- 2.3.3 Role of Deep Learning in Object Tracking -- 2.3.4 Functional Model -- 2.4 Industrial Application -- 2.4.1 Healthcare -- 2.4.2 Smart City -- 2.4.3 Connected Home -- 2.4.4 Security -- 2.4.5 Sports -- 2.5 Conclusion -- References -- Chapter 3 Optimizing Search Engine for Enhancing Computing and Communication in Real-Time Systems -- 3.1 Introduction -- 3.1.1 Existing System -- 3.1.2 Problem Definition -- 3.1.3 Feasibility Study -- 3.1.4 Experimental Work -- 3.2 Literature Review -- 3.3 Requirement Specification -- 3.3.1 Search Engine Optimization -- 3.3.2 Web Analytics -- 3.3.3 Web Architecture Diagram -- 3.4 Testing and Validation -- 3.4.1 SEO Testing…”

Tabla de Contenidos: “…-- 1.11.1 Source -- 1.11.2 Input transducer -- 1.11.3 Encoder of source -- 1.11.4 Encoder of channels -- 1.12 Prediction for the future of digital communications -- 1.12.1 In-app messaging becomes dominant -- 1.12.2 VR adoption: Make or break -- 1.12.3 The need for human contact and validation -- 1.13 What will the future of AI look like? …”

Tabla de Contenidos: “…7.6 Conclusion -- References -- 8 Performance Isolation in Cloud-Based Big Data Architectures -- 8.1 Introduction -- 8.2 Background -- 8.2.1 Cloud Computing -- 8.2.2 Big Data Architecture -- 8.3 Case Study and Problem Statement -- 8.3.1 Case Study -- 8.3.2 Problem Statement -- 8.4 Performance Monitoring in Cloud-Based Systems -- 8.5 Application Framework for Performance Isolation -- 8.6 Evaluation of the Framework -- 8.6.1 Evaluation Results -- 8.7 Discussion -- 8.8 Related Work -- 8.9 Conclusion -- References -- 9 From Legacy to Cloud: Risks and Bene ts in Software Cloud Migration -- 9.1 Introduction -- 9.2 Research Method -- 9.2.1 Pilot Study -- 9.2.2 Search Strategy -- 9.2.2.1 Research question -- 9.2.2.2 Data sources -- 9.2.2.3 Search query -- 9.2.2.4 Search process -- 9.2.2.5 Selection of primary studies -- 9.2.2.6 Included and excluded studies -- 9.2.2.7 Search result management -- 9.2.2.8 Quality assessment of primary studies -- 9.2.3 Data Extraction -- 9.2.4 Data Analysis Method -- 9.3 Results -- 9.3.1 Overview of Primary Studies and Quality Evaluation -- 9.3.2 Bene ts and Risks -- 9.3.3 General Measures -- 9.3.4 Models and Frameworks for Cloud Migration -- 9.4 Discussion -- 9.4.1 Findings and Lessons Learned -- 9.4.2 Threats to Validity -- 9.5 Conclusion -- References -- 10 Big Data: A Practitioners Perspective -- 10.1 Big Data Is a New Paradigm - Differences With Traditional Data Warehouse, Pitfalls and Consideration -- 10.1.1 Differences With Traditional Data Warehouse -- 10.1.2 Pitfalls -- 10.1.2.1 Insuf cient volume of data -- 10.1.2.2 Not having a business challenge -- 10.1.2.3 Ignoring the data quality -- 10.1.2.4 Big data can predict the future -- 10.1.3 Considerations -- 10.2 Product Considerations for Big Data - Use of Open Source Products for Big Data, Pitfalls and Considerations…”

Tabla de Contenidos: “…Intro -- Half Title -- Title Page -- Copyright -- Contents -- Editor Bios -- Contributor Bios -- Acknowledgments -- Introductory Chapter: Asia Finance: The Emergence of Asia Economy and New Development in Finance -- Banking -- Market Developments and Governance Issues -- Sovereign Wealth Funds -- Summary of Individual Chapters in Volume 1 -- Disclaimers -- Part One: Banking -- 1 Risk Rating in Asian Banks -- 1.1 Introduction -- 1.2 PIT Versus Behavior Modeling -- 1.2.1 Transaction Behavior Data -- 1.2.2 Back-Testing -- 1.3 Transaction Behavior Scoring -- 1.3.1 Scoring Process -- 1.3.2 Validation -- 1.4 Simulation and Conclusion -- References -- 2 Private Wealth Management in Asia -- 2.1 Introduction -- 2.2 Global Market Distribution of Private Wealth -- 2.3 Asian Market Distribution of Private Wealth -- 2.4 Asian Private Wealth Management -- 2.5 Asian Centers of Private Wealth Management -- 2.5.1 Hong Kong and Singapore -- 2.5.2 China and India as Emerging Markets -- 2.5.3 Japan's Challenges -- 2.6 Swiss Private Banking Across Asia -- 2.7 Conclusion -- References -- 3 The Banking Networks of Asian Financial Centers -- 3.1 Introduction -- 3.2 The Roots of Asia's Banking Networks -- 3.3 Asia's Leading Financial Centers -- 3.3.1 The View from HSBC -- 3.3.2 The Ranking of Asia's Financial Centers -- 3.4 Asia's Exchanges -- 3.5 China's Financial Centers -- 3.6 Conclusion -- Acknowledgments -- References -- 4 Dynamics of House Prices and Bank Lending in Korea -- 4.1 Introduction -- 4.2 Literature Review -- 4.3 Apartment House Prices and Bank Lending: Stylized Facts in Regional Submarkets of House in Korea -- 4.4 Long-Run Analysis -- 4.5 Short-Run Relationship -- 4.6 Conclusion -- Appendix 1. …”

Tabla de Contenidos: “…Automating forecasting at scale -- 19 Automating time series forecasting with Prophet -- 19.1 Overview of the automated forecasting libraries -- 19.2 Exploring Prophet -- 19.3 Basic forecasting with Prophet -- 19.4 Exploring Prophet's advanced functionality -- 19.4.1 Visualization capabilities -- 19.4.2 Cross-validation and performance metrics -- 19.4.3 Hyperparameter tuning -- 19.5 Implementing a robust forecasting process with Prophet…”

Tabla de Contenidos: “…8.2 Methodology -- 8.3 AI-Based Predictive Modeling -- 8.3.1 Linear Regression -- 8.3.2 Random Forests -- 8.3.3 XGBoost -- 8.3.4 SVM -- 8.4 Performance Indices -- 8.4.1 Root Mean Squared Error (RMSE) -- 8.4.2 Mean Squared Error (MSE) -- 8.4.3 R2 (R-Squared) -- 8.5 Results and Discussion -- 8.5.1 Key Performance Metrics (KPIs) During the Model Training Phase -- 8.5.2 Key Performance Index Metrics (KPIs) During the Model Testing Phase -- 8.5.3 K Cross Fold Validation -- 8.6 Conclusions -- References -- Chapter 9 Performance Comparison of Differential Evolutionary Algorithm-Based Contour Detection to Monocular Depth Estimation for Elevation Classification in 2D Drone-Based Imagery -- 9.1 Introduction -- 9.2 Literature Survey -- 9.3 Research Methodology -- 9.3.1 Dataset and Metrics -- 9.4 Result and Discussion -- 9.5 Conclusion -- References -- Chapter 10 Bioinspired MOPSO-Based Power Allocation for Energy Efficiency and Spectral Efficiency Trade-Off in Downlink NOMA -- 10.1 Introduction -- 10.2 System Model -- 10.3 User Clustering -- 10.4 Optimal Power Allocation for EE-SE Tradeoff -- 10.4.1 Multiobjective Optimization Problem -- 10.4.2 Multiobjective PSO -- 10.4.3 MOPSO Algorithm for EE-SE Trade-Off in Downlink NOMA -- 10.5 Numerical Results -- 10.6 Conclusion -- References -- Chapter 11 Performances of Machine Learning Models and Featurization Techniques on Amazon Fine Food Reviews -- 11.1 Introduction -- 11.1.1 Related Work -- 11.2 Materials and Methods -- 11.2.1 Data Cleaning and Pre-Processing -- 11.2.2 Feature Extraction -- 11.2.3 Classifiers -- 11.3 Results and Experiments -- 11.4 Conclusion -- References -- Chapter 12 Optimization of Cutting Parameters for Turning by Using Genetic Algorithm -- 12.1 Introduction -- 12.2 Genetic Algorithm GA: An Evolutionary Computational Technique -- 12.3 Design of Multiobjective Optimization Problem…”

Tabla de Contenidos: “…Water safety plans -- 4.1 System assessment and design -- 4.1.1 New systems -- 4.1.2 Collecting and evaluating available data -- 4.1.3 Resource and source protection -- 4.1.4 Treatment -- 4.1.5 Piped distribution systems -- 4.1.6 Non-piped, community and household systems -- 4.1.7 Validation -- 4.1.8 Upgrade and improvement -- 4.2 Operational monitoring and maintaining control -- 4.2.1 Determining system control measures -- 4.2.2 Selecting operational monitoring parameters -- 4.2.3 Establishing operational and critical limits -- 4.2.4 Non-piped, community and household systems -- 4.3 Verification -- 4.3.1 Microbial water quality -- 4.3.2 Chemical water quality -- 4.3.3 Source waters -- 4.3.4 Piped distribution systems -- 4.3.5 Community-managed supplies -- 4.3.6 Quality assurance and quality control -- 4.3.7 Water safety plans -- 4.4 Management procedures for piped distribution systems -- 4.4.1 Predictable incidents ("deviations") -- 4.4.2 Unplanned events -- 4.4.3 Emergencies -- 4.4.4 Preparing a monitoring plan -- 4.4.5 Supporting programmes -- 4.5 Management of community and household water supplies -- 4.6 Documentation and communication -- 4.7 Planned review -- 4.7.1 Periodic review -- 4.7.2 Post-incident review -- 5. …”

Tabla de Contenidos: “…Empty Activity Templates -- 24.2 The Android Studio Layout Editor -- 24.3 Design Mode -- 24.4 The Palette -- 24.5 Design Mode and Layout Views -- 24.6 Code Mode -- 24.7 Split Mode -- 24.8 Setting Attributes -- 24.9 Converting Views -- 24.10 Displaying Sample Data -- 24.11 Creating a Custom Device Definition -- 24.12 Changing the Current Device -- 24.13 Layout Validation (Multi Preview) -- 24.14 Summary -- 25. A Guide to the Android ConstraintLayout -- 25.1 How ConstraintLayout Works -- 25.1.1 Constraints -- 25.1.2 Margins -- 25.1.3 Opposing Constraints…”

Tabla de Contenidos: “…Les nouvelles technologies à l'école -- Évaluation, appréciation et validation -- Enseignants, salaires et statut -- Tableau 2.2. …”

Tabla de Contenidos: “…3.4.2 Open Interest and Cumulative Open Interest -- 3.4.3 Validation -- 3.4.4 Case Study with Live Market Data -- 3.5 OI in Option Contracts -- 3.5.1 Decoding Buyer or Seller in Option Chain -- 3.5.2 Put-Call Ratio (PCR) -- 3.5.3 Detection of Anomaly in Stock Price -- 3.6 Conclusion -- References -- Chapter 4 Stock Market Predictions Using Deep Learning: Developments and Future Research Directions -- 4.1 Background and Introduction -- 4.1.1 Machine Learning -- 4.1.2 About Deep Learning -- 4.2 Studies Related to the Current Work, i.e., Literature Review -- 4.3 Objective of Research and Research Methodology -- 4.4 Results and Analysis of the Selected Papers -- 4.5 Overview of Data Used in the Earlier Studies Selected for the Current Research -- 4.6 Data Source -- 4.7 Technical Indicators -- 4.7.1 Other (Advanced Technical Indicators) -- 4.8 Stock Market Prediction: Need and Methods -- 4.9 Process of Stock Market Prediction -- 4.10 Reviewing Methods for Stock Market Predictions -- 4.11 Analysis and Prediction Techniques -- 4.12 Classification Techniques (Also Called Clustering Techniques) -- 4.13 Future Direction -- 4.13.1 Cross-Market Evaluation or Analysis -- 4.13.2 Various Data Inputs -- 4.13.3 Unexplored Frameworks -- 4.13.4 Trading Strategies Based on Algorithm -- 4.14 Conclusion -- References -- Chapter 5 Artificial Intelligence and Quantum Computing Techniques for Stock Market Predictions -- 5.1 Introduction -- 5.2 Literature Survey -- 5.3 Analysis of Popular Deep Learning Techniques for Stock Market Prediction -- 5.3.1 Blind Quantum Computing (BQC) in Stock Market Prediction -- 5.3.2 Quantum Neural Networks (QNNs) for Time Series Forecasting -- 5.3.3 Artificial Intelligence-Based Algorithms -- 5.3.3.1 Deep Learning Models -- 5.3.3.2 Support Vector Machines (SVM) -- 5.3.3.3 Reinforcement Learning (RL) -- 5.3.4 Quantum Computing-Based Algorithms…”

Tabla de Contenidos: “…3.7 Selecting a LDAP-compliant user directory for your deployment -- 3.7.1 Supported directories -- 3.7.2 Multiple LDAP directories -- 3.7.3 Common LDAP scenarios -- 3.8 LDAP requirements for IBM Workplace Collaboration Services -- 3.8.1 Groups and users for Workplace Collaboration Services authentication directory -- 3.8.2 Workplace Collaboration Services account checklist -- 3.9 LDAP directory validation -- 3.9.1 Connection information -- 3.9.2 Verifying IP-level connectivity -- 3.9.3 Verifying the LDAP schema -- 3.10 Configuring IBM Tivoli Directory Server -- 3.10.1 Creating user accounts for IBM Tivoli Directory Server -- 3.10.2 Indexing the IBM Tivoli Directory Server LDAP database -- 3.11 Configuring IBM Lotus Domino Directory -- 3.11.1 Adding dominoUNID to the Domino Directory schema -- 3.11.2 Creating a Domino agent to populate existing documents with dominoUNID -- 3.11.3 Creating required entries in the Domino Directory -- 3.11.4 Configuring e-mail addresses for Domino Directory groups -- 3.11.5 (Optional) Configuring write access to the Domino Directory -- 3.11.6 Creating a full-text index on the Domino Directory -- 3.11.7 (Optional) Configuring directory assistance -- 3.12 Configuring Microsoft Active Directory server -- 3.12.1 Adding required attributes to the Active Directory schema -- 3.12.2 Modifying the Active Directory schema -- 3.12.3 Adding users and groups to Microsoft Active Directory -- 3.12.4 Indexing attributes for Microsoft Active Directory -- Chapter 4. …”

Tabla de Contenidos: “…Customizing the Online Meeting Center -- 11.1 Typical reasons for branding the Meeting Center -- 11.2 Branding the Meeting Center -- 11.2.1 Changing the page header -- 11.2.2 Changing the look -- 11.2.3 Using a Java Server Page (JSP) front-end -- 11.3 Meeting summary e-mail -- 11.3.1 Overview -- 11.3.2 Behind the scenes -- 11.3.3 Implementing the e-mail notification feature -- 11.3.4 Design changes -- 11.3.5 Validating the changes -- 11.4 Summary -- Chapter 12. …”

Tabla de Contenidos: “…Results and Analysis -- 7.5. Threats to Validity -- 7.6. Summary -- 8. Conclusion: Summary, Future Work, and Perspective -- 8.1. …”

Tabla de Contenidos: “…Empty Activity Templates -- 17.2 The Android Studio Layout Editor -- 17.3 Design Mode -- 17.4 The Palette -- 17.5 Design Mode and Layout Views -- 17.6 Code Mode -- 17.7 Split Mode -- 17.8 Setting Attributes -- 17.9 Converting Views -- 17.10 Displaying Sample Data -- 17.11 Creating a Custom Device Definition -- 17.12 Changing the Current Device -- 17.13 Layout Validation (Multi Preview) -- 17.14 Summary -- 18. A Guide to the Android ConstraintLayout -- 18.1 How ConstraintLayout Works -- 18.1.1 Constraints -- 18.1.2 Margins -- 18.1.3 Opposing Constraints -- 18.1.4 Constraint Bias -- 18.1.5 Chains -- 18.1.6 Chain Styles -- 18.2 Baseline Alignment -- 18.3 Working with Guidelines -- 18.4 Configuring Widget Dimensions -- 18.5 Working with Barriers -- 18.6 Ratios -- 18.7 ConstraintLayout Advantages -- 18.8 ConstraintLayout Availability -- 18.9 Summary -- 19. …”

Tabla de Contenidos: “…Assessing and Addressing Model Strengths and Weaknesses -- 2.6.1. Verification, Validation, and Accreditation -- 2.6.2. Addressing Errors of Omission and Commission -- References -- Chapter 3: The Evolution of Global Modeling -- 3.1. …”