Tabla de Contenidos: “…Niveau et structure des dépenses de R-D dans la zone de l'OCDE -- Tableau 13. Coefficient d'inventivité -- Facteurs affectant le climat entreprenarial -- Obstacles supposés à la création et la croissance d'entreprises -- Graphique 16. …”

Tabla de Contenidos: “…Zones d'emploi -- Éducation et formation : comble r le déficit de compé tences -- Réformer le système d'impôts et de transferts pour rendre le New Deal plus attractif -- Encadré 12. …”

Tabla de Contenidos: “…Aides à l'industrie -- Tableau 11. Dépenses de R-D et sources de financement -- La restructuration du secteur agricole devrait être accélérée -- Graphique 11. …”

Tabla de Contenidos: “…Pas de perte d'efficacité lorsque la demande est parfaitement inélastique par r... -- Graphique III.6. Inefficacité économique causée par des externalités positives (avec importations)…”

Tabla de Contenidos: “…4.26.7 Variance of Normal Distribution -- 4.26.8 Mode of Normal Distribution -- 4.26.9 Median of the Normal Distribution -- 4.26.10 Moment Generating Function of Normal Distribution With Respect to Origin -- 4.26.11 Mean Deviation of Normal Distribution -- 4.26.11.1 Solved Examples -- 4.26.12 Fitting a Normal Distribution -- 4.26.13 Linear Combination of Independent Normal Variables -- 4.26.14 Fitting a Normal Distribution -- 4.26.15 Normal Approximation to Binomial Distribution -- 4.27 Characteristic Function -- 4.28 Gamma Distribution -- 4.28.1 Mean and Variance of Gamma Distribution -- 4.28.2 Gamma Distribution of Second Kind -- 4.29 Beta Distribution of First Kind -- 4.29.1 Beta Distribution of Second Kind -- 4.30 Weibull Distribution -- 5 Curve Fitting -- 5.1 Introduction -- 5.2 The Method of Least Squares -- 5.3 The Least-Squares Line -- 5.4 Fitting a Parabola by the Method of Least Squares -- 5.5 Fitting the exponential curve of the form y=a ebx -- 6 Correlation and Regression -- 6.1 Introduction -- 6.2 Correlation -- 6.2.1 Types of Correlation -- 6.3 Coefficient of Correlation -- 6.3.1 Properties of Coefficient of Correlation -- 6.4 Methods of Finding Coefficient of Correlation -- 6.5 Scatter Diagram -- 6.6 Direct Method -- 6.7 Spearman's Rank Correlation Coefficient -- 6.7.1 Rank Correlation Coefficient When the Ranks Are Tied -- 6.8 Calculation of r (Correlation Coefficient) (Karl Pearson's Formula) -- 6.9 Regression -- 6.10 Regression Equation -- 6.11 Curve of Regression -- 6.12 Types of Regression -- 6.13 Regression Equations (Linear Fit) -- 6.13.1 Linear Regression Equation of y on x -- 6.13.2 Regression Equation of x and y -- 6.14 Angle between Two Lines of Regression -- 6.15 Coefficient of Determination -- 6.16 Coefficient Nondetermination -- 6.17 Coefficient of Alienation -- 6.17.1 Solved Examples -- 6.18 Multilinear Regression…”

Tabla de Contenidos: “…3.4.1.1 - Problem definition -- 3.4.1.2 - Numerical method -- 3.4.2 - Effects of active parameters -- 3.5 - Nanofluid flow and heat transfer between parallel plates considering Brownian motion using DTM -- 3.5.1 - Problem definition -- 3.5.2 - Semianalytical method -- 3.5.2.1 - Basic idea of DTM -- 3.5.2.2 - Application of DTM -- 3.5.3 - Effects of active parameters -- 3.6 - Effect of Lorentz forces on forced convection nanofluid flow over a stretched surface -- 3.6.1 - Problem definition and mathematical model -- 3.6.1.1 - Problem definition -- 3.6.1.2 - Numerical method -- 3.6.2 - Effects of active parameters -- 3.7 - Forced convective heat transfer of magnetic nanofluid in a double-sided, lid-driven cavity with a wavy wall -- 3.7.1 - Problem definition -- 3.7.2 - Effects of active parameters -- References -- Chapter 4 - Nanofluid Flow and Heat Transfer in the Presence of Thermal Radiation -- 4.1 - MHD free convection of Al2O3-water nanofluid considering thermal radiation -- 4.1.1 - Problem definition -- 4.1.2 - Effects of active parameters -- 4.2 - Unsteady nanofluid flow and heat transfer in the presence of magnetic field considering thermal radiation -- 4.2.1 - Problem definition -- 4.2.2 - Effects of active parameters -- 4.3 - Effect of thermal radiation on magnetohydrodynamic nanofluid flow and heat transfer by means of two-phase model -- 4.3.1 - Problem definition -- 4.3.2 - Effects of active parameters -- 4.4 - Ferrofluid flow and heat transfer in a semiannulus enclosure in the presence of magnetic source considering thermal r... -- 4.4.1 - Problem definition -- 4.4.2 - Effects of active parameters -- 4.5 - Nanofluid flow and heat transfer over a stretching porous cylinder considering thermal radiation -- 4.5.1 - Problem definition and mathematical model -- 4.5.1.1 - Problem definition -- 4.5.1.2 - Numerical method…”

Tabla de Contenidos: “…The TM Package: Text Mining in R -- A.3.10. SpaCY -- A.3.11. Mallet -- A.3.12. …”

Tabla de Contenidos: “…Les dépenses fiscales dans le système d'impôt sur les sociétés -- Graphique 3.3. La R-D bénéficie d'un traitement fiscal relativement généreux en Corée -- Favoriser la croissance économique -- Graphique 3.4. …”

Tabla de Contenidos: “…Capital humain et recherche-développement (R-D)/innovation -- Graphique 1.12. Améliorer le niveau de compétences de la population adulte constitue un enjeu de l'action publique dans la plupart des pays -- Graphique 1.13. …”

Tabla de Contenidos: “…-- 8.2 A Few Practical Concerns -- 8.3 Binary versus Multiclass -- 8.4 Example Script -- 8.5 Specific Classifiers -- 8.6 Evaluating Classifiers -- 8.7 Selecting Classification Cutoffs -- 8.8 Further Reading -- 8.9 Glossary -- Chapter 9 Technical Communication and Documentation -- 9.1 Several Guiding Principles -- 9.2 Slide Decks -- 9.3 Written Reports -- 9.4 Speaking: What Has Worked for Me -- 9.5 Code Documentation -- 9.6 Further Reading -- 9.7 Glossary -- Part II Stuff You Still Need to Know -- Chapter 10 Unsupervised Learning: Clustering and Dimensionality Reduction -- 10.1 The Curse of Dimensionality -- 10.2 Example: Eigenfaces for Dimensionality Reduction -- 10.3 Principal Component Analysis and Factor Analysis -- 10.4 Skree Plots and Understanding Dimensionality -- 10.5 Factor Analysis -- 10.6 Limitations of PCA -- 10.7 Clustering -- 10.8 Further Reading -- 10.9 Glossary -- Chapter 11 Regression -- 11.1 Example: Predicting Diabetes Progression -- 11.2 Least Squares -- 11.3 Fitting Nonlinear Curves -- 11.4 Goodness of Fit: R2 and Correlation -- 11.5 Correlation of Residuals -- 11.6 Linear Regression -- 11.7 LASSO Regression and Feature Selection -- 11.8 Further Reading -- 11.9 Glossary -- Chapter 12 Data Encodings and File Formats -- 12.1 Typical File Format Categories -- 12.2 CSV Files -- 12.3 JSON Files -- 12.4 XML Files…”

Tabla de Contenidos: “…Architectural scenarios and considerations -- 2.1 Architectural scenarios -- 2.1.1 Scenario 1: Single iSeries server -- 2.1.2 Scenario 2: Remote database server -- 2.1.3 Scenario 3: LEI 6 integration with Domino R5 applications -- 2.1.4 Scenario 4: Decentralized Advanced RealTime access -- 2.1.5 Scenario 5: Advanced RealTime in a hub and spoke environment -- 2.1.6 Scenario 6: Accessing multiple relational databases from iSeries -- 2.2 Security considerations -- 2.2.1 Generic user ID and password in connection document -- 2.2.2 Integrated credentials -- 2.2.3 Fields and public key encryption -- 2.3 Performance considerations -- 2.3.1 LEI considerations -- 2.3.2 Performance spectrum scenarios -- 2.3.3 DB2 UDB considerations -- 2.3.4 Connection pooling verses persistent connections…”

Tabla de Contenidos: “…8.5.2 Exploiting domain rules -- 8.6 Validating configuration -- 8.6.1 Causes for configuration-related security flaws -- 8.6.2 Automated tests as your safety net -- 8.6.3 Knowing your defaults and verifying them -- Summary -- 9 Handling failures securely -- 9.1 Using exceptions to deal with failure -- 9.1.1 Throwing exceptions -- 9.1.2 Handling exceptions -- 9.1.3 Dealing with exception payload -- 9.2 Handling failures without exceptions -- 9.2.1 Failures aren't exceptional -- 9.2.2 Designing for failures -- 9.3 Designing for availability -- 9.3.1 Resilience -- 9.3.2 Responsiveness -- 9.3.3 Circuit breakers and timeouts -- Always specify a timeout -- 9.3.4 Bulkheads -- 9.4 Handling bad data -- Cross-site scripting and second-order attacks -- 9.4.1 Don't repair data before validation -- 9.4.2 Never echo input verbatim -- Summary -- 10 Benefits of cloud thinking -- 10.1 The twelve-factor app and cloud-native concepts -- 10.2 Storing configuration in the environment -- 10.2.1 Don't put environment configuration in code -- 10.2.2 Never store secrets in resource files -- 10.2.3 Placing configuration in the environment -- 10.3 Separate processes -- 10.3.1 Deploying and running are separate things -- 10.3.2 Processing instances don't hold state -- 10.3.3 Security benefits -- 10.4 Avoid logging to file -- 10.4.1 Confidentiality -- 10.4.2 Integrity -- 10.4.3 Availability -- 10.4.4 Logging as a service -- 10.5 Admin processes -- 10.5.1 The security risk of overlooked admin tasks -- 10.5.2 Admin tasks as first-class citizens -- Admin of log files -- 10.6 Service discovery and load balancing -- 10.6.1 Centralized load balancing -- 10.6.2 Client-side load balancing -- 10.6.3 Embracing change -- 10.7 The three R's of enterprise security -- 10.7.1 Increase change to reduce risk -- 10.7.2 Rotate -- 10.7.3 Repave -- 10.7.4 Repair -- Summary…”

Tabla de Contenidos: “…Sectoral Demand (GDS) Calculations -- Military Sector -- Health Sector -- Education Sector -- Core Infrastructure Sector -- Other Infrastructure Sector -- Research and Development (R&D) -- Other Public Spending -- Exogenous Override -- 6.2.4.3. …”

Tabla de Contenidos: “…BD 80 - anomalous. Figure 12r. BD 96/97 with anomalous scene. -- Figure 13a. …”

Tabla de Contenidos: “…Stevenson / Effects of Beetroot Juice on Recovery of Muscle Function and Performance between Bouts of Repeated Sprint Exercise, Reprinted from: Nutrients 2016, 8(8), 506; doi: 10.3390/nu8080506 -- R. Andrew Shanely, David C. Nieman, Penelope Perkins-Veazie, Dru A. …”

Tabla de Contenidos: “…6.4.2.2 Gradient Tree Boosting -- 6.4.2.3 XGBoost -- 6.4.3 Stacking -- 6.5 Results -- 6.5.1 Bagging Meta Estimator -- 6.5.2 Random Forest -- 6.5.3 AdaBoost -- 6.5.4 Gradient Tree Boosting -- 6.5.5 XGBoost -- 6.5.6 Stacking -- 6.5.7 Comparison with Single Classifiers -- 6.6 Conclusion -- Acknowledgement -- References -- Chapter 7 Feature Engineering and Selection Approach Over Malicious Image -- 7.1 Introduction -- 7.2 Feature Engineering Techniques -- 7.2.1 Methodologies in Feature Engineering -- 7.2.2 Strides in Feature Engineering -- 7.2.3 Feature Extraction -- 7.2.4 Feature Selection -- 7.2.5 Feature Engineering in Image Processing -- 7.2.6 Importance of Feature Engineering in Image Processing -- 7.3 Malicious Feature Engineering -- 7.4 Image Processing Technique -- 7.4.1 Steps Involved in Image Processing Technique -- 7.4.2 Image Processing Task -- 7.4.2.1 Image Enhancement -- 7.4.2.2 Image Restoration -- 7.4.2.3 Coloring Image Processing -- 7.4.2.4 Wavelets Processing and Multiple Solutions -- 7.4.2.5 Image Compression -- 7.4.2.6 Character Recognition -- 7.4.2.7 Characteristics of Image Processing -- 7.5 Image Processing Techniques for Analysis on Malicious Images -- 7.6 Conclusion -- References -- Blog -- Chapter 8 Cubic-Regression and Likelihood Based Boosting GAM to Model Drug Sensitivity for Glioblastoma -- 8.1 Introduction -- 8.1.1 Glioblastoma -- 8.2 Literature Survey -- 8.3 Materials and Methods -- 8.3.1 Methodology -- 8.3.1.1 Generalized Additive Models (GAMs) -- 8.3.1.2 Model-Based Boosting - Boosted GAM -- 8.3.2 Datasets Description -- 8.4 Evaluations, Results and Discussions -- 8.4.1 Akaike Information Criterion (AIC) -- 8.4.2 Adjusted R-Squared -- 8.4.3 Discussion -- Conclusion -- References -- Chapter 9 Unobtrusive Engagement Detection through Semantic Pose Estimation and Lightweight ResNet for an Online Class Environment…”

Tabla de Contenidos: “…Soutien financier à l'investissement privé dans la R-D -- Partie II. Études thématiques -- Chapitre 4. …”

“…In addition, data examples, with all relevant R code, are available on a companion website. Provides a balanced presentation of theory and practice, exploring both categorical and integer-valued series Covers common models for time series of counts as well as for categorical time series, and works out their most important stochastic properties Addresses statistical approaches for analyzing discrete-valued time series and illustrates their implementation with numerous data examples Covers classical approaches such as ARMA models, Box-Jenkins program and how to generate functions Includes dataset examples with all necessary R code provided on a companion website An Introduction to Discrete-Valued Time Series is a valuable working resource for researchers and practitioners in a broad range of fields, including statistics, data science, machine learning, and engineering. …”

“…This new edition is expanded to include: Detailed information about the latest motherboards and chipsets from AMD, Intel, SiS, and VIA Extensive coverage of the Pentium 4 and the latest AMD processors, including the Athlon XP/MP Full details about new hard drive standards, including the latest SCSI standards, ATA/133, Serial ATA, and the new 48-bit "Big Drive" ATA interface Extended coverage of DVD drives, including DVD-RAM, DVD-R/RW, and DVD+R/RW Details about Flat Panel Displays, including how to choose one (and why you might not want to) New chapters on serial communications, parallel communications, and USB communications (including USB 2.0) Enhanced troubleshooting coverage PC Hardware in a Nutshell, 2nd Edition provides independent, useful and practical information in a no-nonsense manner with specific recommendations on components. …”

“…This comprehensive book contains information on "harmonious solutions" in multiobjective problem-solving (analyzing < X, F> models), construction and analysis of < X , R > models, results aimed at generating robust solutions in analyzing multicriteria problems under uncertainty, and more. …”