Tabla de Contenidos: “…Les PME coréennes entrent pour une large part dans les prêts bancaires aux entreprises -- Problèmes associés à l'intervention de l'État dans le financement des PME -- Graphique 1.13. …”

Tabla de Contenidos: “…Soutien au titre de la production par produit, par pays, 2007-09 -- Des paiements au titre de l'utilisation d'intrants sont prévus par un large éventail de mesures -- Graphique 1.8. OCDE : Évolution du soutien au titre de l'utilisation d'intrants, 1986-2009 -- Graphique 1.9. …”

Tabla de Contenidos: “…-- 7.1.2 Traf c and Performance Measures -- 7.1.3 Characterizing Traf c -- 7.1.4 Average Delay in a Single Link System -- 7.1.5 Nonstationarity of Traf c -- 7.2 Applications' View -- 7.2.1 TCP Throughput and Possible Bottlenecks -- 7.2.2 Bandwidth-Delay Product -- 7.2.3 Router Buffer Size -- 7.3 Traf c Engineering: An Architectural Framework -- 7.4 Traf c Engineering: A Four-Node Illustration -- 7.4.1 Network Flow Optimization -- 7.4.2 Shortest Path Routing and Network Flow -- 7.5 IGP Metric (Link Weight) Determination Problem for the Load Balancing Objective: Preliminary Discussion -- 7.6 Determining IGP Link Weights via duality of MCNF Problems -- 7.6.1 Illustration of Duality Through a Three-Node Network for Minimum Cost Routing -- 7.6.2 Minimum Cost Routing, Duality, and Link Weights -- 7.6.3 Illustration of Duality Through a Three-Node Network for the Load Balancing Objective -- 7.6.4 Load Balancing Problem, duality, and Link Weights -- 7.6.5 A Composite Objective Function, duality, and Link Weights -- 7.6.6 Minimization of Average Delay, duality, and Link Weights -- 7.7 Illustration of Link Weight Determination through Duality -- 7.7.1 Case Study: I -- 7.7.2 Case Study: II -- 7.8 Link Weight Determination: Large Networks -- 7.9 IP Traf c Engineering of PoP-to-DataCenter Networks -- 7.10 Summary -- Further Lookup -- Exercises -- 8 Multicast Routing -- 8.1 Multicast IP Addressing -- 8.2 Internet Group Management Protocol (IGMP) -- 8.3 Multicast Listener Discovery Protocol (MLD) -- 8.4 Reverse Path Forwarding (RPF) -- 8.5 Distance Vector Multicast Routing Protocol (DVMRP) -- 8.6 Multicast OSPF -- 8.7 Core Based Trees…”

Tabla de Contenidos: “…Niveau du salaire minimum avant et après la crise, OCDE -- Le débat sur le salaire minimum devrait tenir compte des objectifs plus larges et des interactions avec les autres politiques -- Tableau 1.3. …”

Tabla de Contenidos: “…Effectiveness of various device configurations 8.5 Manifestations of lift in the atmosphere at large 8.5.1 ... The net vertical momentum imparted to the atmosphere 8.5.2 ... …”

Tabla de Contenidos: “…5.3.3 Analytical process -- 5.3.4 Global optimization -- 5.3.5 Medical disease diagnosis -- 5.3.6 Data clustering -- 5.3.7 Shape and size optimization -- 5.3.8 Investment decisions -- 5.3.9 Large graph coloring problems -- 5.4 Discussion and future works -- 5.5 Conclusion -- References -- 6 Arithmetic optimization algorithm: a review and analysis -- 6.1 Introduction -- 6.2 Arithmetic optimization algorithm -- 6.2.1 Initialization -- 6.2.2 Exploration -- 6.2.3 Exploitation -- 6.3 Related Works -- 6.3.1 Engineering application -- 6.3.2 Artificial intelligence -- 6.3.3 Chemistry -- 6.3.4 Machine learning -- 6.3.5 Network -- 6.3.6 Other applications -- 6.4 Discussion -- 6.5 Conclusion and future work -- References -- 7 Aquila optimizer: review, results and applications -- 7.1 Introduction -- 7.2 Procedure -- 7.2.1 Step1: (X1) -- 7.2.2 Step 2: (X2) -- 7.2.3 Step 3: (X3) -- 7.2.4 Step 4: (X4) -- 7.2.5 Aquila Optimizer Pseudocode -- 7.3 Related works -- 7.4 Discussion -- 7.5 Conclusion -- References -- 8 Whale optimization algorithm: analysis and full survey -- 8.1 Introduction -- 8.2 The whale optimization algorithm -- 8.2.1 Inspiration -- 8.2.2 Mathematical model and the optimization algorithm -- 8.2.2.1 Encircling prey -- 8.2.2.2 Bubble-net attacking method -- 8.2.2.3 Exploration phase: searching for a prey -- 8.3 Related work -- 8.3.1 Computer networks -- 8.3.2 Network security -- 8.3.3 Clustering -- 8.3.4 Image processing -- 8.3.5 Feature selection -- 8.3.6 Electrical power and energy systems -- 8.4 Discussion -- 8.5 Conclusion and future work -- References -- 9 Spider monkey optimizations: application review and results -- 9.1 Introduction -- 9.2 Spider monkey optimization algorithm -- 9.2.1 The behavior of spider monkey optimization -- 9.2.2 The spider monkey optimization algorithm -- 9.2.2.1 Preparation of the community…”

Tabla de Contenidos: “…-- 1.1.1 Storage Resource Management, then and now -- 1.2 Storage management issues today -- 1.2.1 Growth -- 1.2.2 Storage costs too much, and money is not used efficiently -- 1.2.3 Unmanaged storage costs too much, and the scope is large -- 1.2.4 Storage management functions defined -- 1.2.5 Architecture for a suite of Storage Management solutions -- 1.2.6 Standards and Storage Resource Management tools -- 1.3 Objectives of Storage Resource Management -- Chapter 2. …”

Tabla de Contenidos: “…9.3.1 Session Setup 212 -- 9.3.2 D2D Transmit Power 214 -- 9.3.3 Multiantenna Techniques 215 -- 9.3.4 Radio Resource Management 220 -- 9.4 Future Directions 225 -- References 228 -- 10 The End-to-end Performance of LTE-Advanced 231 -- 10.1 IMT-Advanced Evaluation: ITU Process, Scenarios and Requirements 231 -- 10.1.1 ITU-R Process for IMT-Advanced 232 -- 10.1.2 Evaluation Scenarios 234 -- 10.1.3 Performance Requirements 235 -- 10.2 Short Introduction to LTE-Advanced Features 238 -- 10.2.1 The WINNER+ Evaluation Group Assessment Approach 238 -- 10.3 Performance of LTE-Advanced 239 -- 10.3.1 3GPP Self-evaluation 239 -- 10.3.2 Simulative Performance Assessment by WINNER+ 241 -- 10.3.3 LTE-Advanced Performance in the Rural Indian Open Area Scenario 243 -- 10.4 Channel Model Implementation and Calibration 243 -- 10.4.1 IMT-Advanced Channel Model 243 -- 10.4.2 Calibration of Large-Scale Parameters 246 -- 10.4.3 Calibration of Small-Scale Parameters 247 -- 10.5 Simulator Calibration 248 -- 10.6 Conclusion and Outlook on the IMT-Advanced Process 249 -- References 250 -- 11 Future Directions 251 -- 11.1 Radio Resource Allocation 252 -- 11.2 Heterogeneous Networks 252 -- 11.3 MIMO and CoMP 253 -- 11.4 Relaying and Network Coding 254 -- 11.5 Device-to-Device Communications 254 -- 11.6 Green and Energy Efficiency 255 -- References 256 -- Appendices 259 -- Appendix A Resource Allocation 261 -- A.1 Dynamic Resource Allocation 261 -- A.1.1 Utility Predictive Scheduler 261 -- A.1.2 Resource Allocation with Relays 261 -- A.2 Multiuser Resource Allocation 263 -- A.2.1 PHY/MAC Layer Model 263 -- A.2.2 APP Layer Model 263 -- A.2.3 Optimization Problem 264 -- A.2.4 Simulation Results 265 -- A.3 Busy Burst Extended to MIMO 266 -- A.4 Efficient MBMS Transmission 267 -- A.4.1 Service Operation 267 -- A.4.2 Frequency Division Multiplexing (FDM) Performance 268 -- Appendix B Spectrum Awareness 269 -- B.1 Spectrum Sensing 269 -- B.2 Geo-Location Databases 270 -- B.3 Beacon Signaling 270 -- Appendix C CoordinatedMultiPoint (CoMP) 271.…”

Tabla de Contenidos: “…. -- 5.6 Exercises -- Part II: All the Fundamentals Applied to Inferring a Binomial Probability -- Chapter 6: Inferring a Binomial Probability via Exact Mathematical Analysis -- 6.1 The Likelihood Function: Bernoulli Distribution -- 6.2 A Description of Credibilities: The Beta Distribution -- 6.2.1 Specifying a beta prior -- 6.3 The Posterior Beta -- 6.3.1 Posterior is compromise of prior and likelihood -- 6.4 Examples -- 6.4.1 Prior knowledge expressed as a beta distribution -- 6.4.2 Prior knowledge that cannot be expressed as a beta distribution -- 6.5 Summary -- 6.6 Appendix: R Code for Figure 6.4 -- 6.7 Exercises -- Chapter 7: Markov Chain Monte Carlo -- 7.1 Approximating a Distribution with a Large Sample -- 7.2 A Simple Case of the Metropolis Algorithm -- 7.2.1 A politician stumbles upon the Metropolis algorithm -- 7.2.2 A random walk -- 7.2.3 General properties of a random walk -- 7.2.4 Why we care -- 7.2.5 Why it works -- 7.3 The Metropolis Algorithm More Generally -- 7.3.1 Metropolis algorithm applied to Bernoulli likelihood and beta prior -- 7.3.2 Summary of Metropolis algorithm -- 7.4 Toward Gibbs Sampling: Estimating Two Coin Biases -- 7.4.1 Prior, likelihood and posterior for two biases -- 7.4.2 The posterior via exact formal analysis -- 7.4.3 The posterior via the Metropolis algorithm -- 7.4.4 Gibbs sampling -- 7.4.5 Is there a difference between biases? …”

Tabla de Contenidos: “…The importance of having sufficiently large intermediate layers -- 3.5.8. Further experiments -- 3.5.9. …”

Tabla de Contenidos: “…8.4.3.1 Example of embedded SoC for multimodal localization -- 8.4.3.2 Smart phones -- 8.4.3.3 Smart glasses -- 8.4.3.4 Autonomous mobile robots -- 8.4.3.5 Unmanned aerial vehicles -- 8.4.3.6 Autonomous driving vehicles -- 8.4.4 Discussion -- 8.5 Application Domains -- 8.5.1 Scene Mapping -- 8.5.1.1 Aircraft inspection -- 8.5.1.2 SenseFly eBee classic -- 8.5.2 Pedestrian Localization -- 8.5.2.1 Indoor localization in large-scale buildings -- 8.5.2.2 Precise localization of mobile devices in unknown environments -- 8.5.3 Automotive Navigation -- 8.5.3.1 Autonomous driving -- 8.5.3.2 Smart factory -- 8.5.4 Mixed Reality -- 8.5.4.1 Virtual cane system for visually impaired individuals -- 8.5.4.2 Engineering, construction and maintenance -- 8.6 Conclusion -- References -- 9 Self-Supervised Learning from Web Data for Multimodal Retrieval -- 9.1 Introduction -- 9.1.1 Annotating Data: A Bottleneck for Training Deep Neural Networks -- 9.1.2 Alternatives to Annotated Data -- 9.1.3 Exploiting Multimodal Web Data -- 9.2 Related Work -- 9.2.1 Contributions -- 9.3 Multimodal Text-Image Embedding -- 9.4 Text Embeddings -- 9.5 Benchmarks -- 9.5.1 InstaCities1M -- 9.5.2 WebVision -- 9.5.3 MIRFlickr -- 9.6 Retrieval on InstaCities1M and WebVision Datasets -- 9.6.1 Experiment Setup -- 9.6.2 Results and Conclusions -- 9.6.3 Error Analysis -- 9.6.3.1 Visual features confusion -- 9.6.3.2 Errors from the dataset statistics -- 9.6.3.3 Words with different meanings or uses -- 9.7 Retrieval in the MIRFlickr Dataset -- 9.7.1 Experiment Setup -- 9.7.2 Results and Conclusions -- 9.8 Comparing the Image and Text Embeddings -- 9.8.1 Experiment Setup -- 9.8.2 Results and Conclusions -- 9.9 Visualizing CNN Activation Maps -- 9.10 Visualizing the Learned Semantic Space with t-SNE -- 9.10.1 Dimensionality Reduction with t-SNE -- 9.10.2 Visualizing Both Image and Text Embeddings…”

Tabla de Contenidos: “…Rotor currents and torque-large slip -- 5.3.7. Generating-Negative slip…”

Tabla de Contenidos: “…Learning from images in the real world: Early detection of lung cancer -- 9 Using PyTorch to fight cancer -- 9.1 Introduction to the use case -- 9.2 Preparing for a large-scale project -- 9.3 What is a CT scan, exactly? …”

Tabla de Contenidos: “…6.6.1 Methodology and configuration -- 6.6.2 Performance -- 6.7 Detailed analysis of flow control -- 6.7.1 The detailed buffer utilization -- 6.7.1.1 Allowable EVCs -- 6.7.1.2 Performance analysis -- 6.7.2 The effect of flow control on fairness -- 6.8 Further discussion -- 6.8.1 Packet length -- 6.8.2 Dynamically allocated multiqueue and hybrid flow controls -- 6.9 Chapter summary -- Appendix: Logical Equivalence of Alg and Alg + WPF -- References -- Chapter 7: Deadlock-free flow control for torus networks-on-chip -- 7.1 Introduction -- 7.2 Limitations of existing designs -- 7.2.1 Dateline -- 7.2.2 Localized bubble scheme -- 7.2.3 Critical bubble scheme -- 7.2.4 Inefficiency with variable-size packets -- 7.3 Flit bubble flow control -- 7.3.1 Theoretical description -- 7.3.2 FBFC-localized -- 7.3.3 FBFC-critical -- 7.3.4 Starvation -- 7.4 Router microarchitecture -- 7.4.1 FBFC routers -- 7.4.2 VCT routers -- 7.5 Methodology -- 7.6 Evaluation on 1D tori (rings) -- 7.6.1 Performance -- 7.6.2 Buffer utilization -- 7.6.3 Latency of short and long packets -- 7.7 Evaluation on 2D tori -- 7.7.1 Performance for a 44 torus -- 7.7.2 Sensitivity to SFP ratios -- 7.7.3 Sensitivity to buffer size -- 7.7.4 Scalability for an 88 torus -- 7.7.5 Effect of starvation -- 7.7.6 Real application performance -- 7.7.7 Large-scale systems and message passing -- 7.8 Overheads: Power and area -- 7.8.1 Methodology -- 7.8.2 Power efficiency -- 7.8.3 Area -- 7.8.4 Comparison with meshes -- 7.9 Discussion and related work -- 7.9.1 Discussion -- 7.9.2 Related work -- 7.10 Chapter summary -- References -- Part IV: Programming paradigms -- Chapter 8: Supporting cache-coherent collective communications -- 8.1 Introduction -- 8.2 Message combination framework -- 8.2.1 MCT format -- 8.2.2 Message combination example -- 8.2.3 Insufficient MCT entries -- 8.3 BAM routing…”

Tabla de Contenidos: “…A Quick Application Monitor Tour: Active and post analysis -- 7.1 Using Application Monitor to monitor a running task -- 7.2 Analyzing an active job -- 7.3 Analyzing historical data -- 7.3.1 Specifying how you want to analyze the historical data -- 7.3.2 Analyzing historical data as one large segment -- 7.3.3 Analyzing historical data as multiple intervals -- 7.3.4 Analyzing a subset of the historical data -- Chapter 8. …”

Tabla de Contenidos: “…3.5.8.3 VARIABLES -- 3.5.8.4 OBJECTIVE -- 3.5.8.5 CONSTRAINTS -- Chapter 4 Structured linear programming models -- 4.1 Multiple plant, product and period models -- 4.2 Stochastic programmes -- 4.3 Decomposing a large model -- 4.3.1 The submodels -- 4.3.2 The restricted master model -- Chapter 5 Applications and special types of mathematical programming model -- 5.1 Typical applications -- 5.1.1 The petroleum industry -- 5.1.2 The chemical industry -- 5.1.3 Manufacturing industry -- 5.1.4 Transport and distribution -- 5.1.5 Finance -- 5.1.6 Agriculture -- 5.1.7 Health -- 5.1.8 Mining -- 5.1.9 Manpower planning -- 5.1.10 Food -- 5.1.11 Energy -- 5.1.12 Pulp and paper -- 5.1.13 Advertising -- 5.1.14 Defence -- 5.1.15 The supply chain -- 5.1.16 Other applications -- 5.2 Economic models -- 5.2.1 The static model -- 5.2.2 The dynamic model -- 5.2.3 Aggregation -- 5.3 Network models -- 5.3.1 The transportation problem -- 5.3.2 The assignment problem -- 5.3.3 The transhipment problem -- 5.3.4 The minimum cost flow problem -- 5.3.5 The shortest path problem -- 5.3.6 Maximum flow through a network -- 5.3.7 Critical path analysis -- 5.4 Converting linear programs to networks -- Chapter 6 Interpreting and using the solution of a linear programming model -- 6.1 Validating a model -- 6.1.1 Infeasible models -- 6.1.2 Unbounded models -- 6.1.3 Solvable models -- 6.2 Economic interpretations -- 6.2.1 The dual model -- 6.2.2 Shadow prices -- 6.2.3 Productive capacity constraints -- 6.2.4 Raw material availabilities -- 6.2.5 Marketing demands and limitations -- 6.2.6 Material balance (continuity) constraints -- 6.2.7 Quality stipulations -- 6.2.8 Reduced costs -- 6.3 Sensitivity analysis and the stability of a model -- 6.3.1 Right-hand side ranges -- 6.3.2 Objective ranges -- 6.3.3 Ranges on interior coefficients -- 6.3.4 Marginal rates of substitution…”

Tabla de Contenidos: “…Troubleshooting the deployment -- 17.1 Configuration issues for multihomed servers -- 17.2 Execution issues -- 17.2.1 System log files -- 17.2.2 Analyze traffic on your network -- 17.2.3 Reprocessing failed events and business documents -- 17.3 Performance Issues -- 17.3.1 Increase the Receiver timeout setting -- 17.3.2 Insufficient virtual memory for DB2 agents -- 17.3.3 Optimizing database query performance -- 17.3.4 Avoiding out-of-memory errors -- 17.3.5 Avoid long processing time on large, encrypted AS documents -- Chapter 18. Implementing HTTPS -- 18.1 Overview of SSL and the SSL handshake -- 18.2 SSL data flow -- 18.3 Firewall changes -- 18.3.1 Validating the firewalls -- 18.4 Configuring the IBM HTTP Server 1.3.x for SSL -- 18.4.1 Create a key store file -- 18.4.2 Generate a self-signed certificate -- 18.4.3 Configure the IBM HTTP Server for SSL -- 18.4.4 Validating the reverse proxy -- 18.5 Using IBM HTTP Server V2.x as a reverse proxy -- 18.6 Establishing trust from the proxy server to the Console -- 18.6.1 Validating the reverse proxy -- 18.7 Enforcing SSL connections to the Community Console -- 18.7.1 Validating the changes -- 18.8 SSL with Load Balancer…”

Tabla de Contenidos: “…5.1.3.3 Type II Censoring -- 5.2 Reliability Data Sources -- 5.3 Nonparametric and Plotting Methods for Reliability Functions -- 5.3.1 Nonparametric Procedures for Reliability Functions -- 5.3.1.1 Nonparametric Component Reliability Estimation Using Small Samples -- 5.3.1.2 Nonparametric Component Reliability Estimation Using Large Samples -- 5.3.2 Probability Distribution Plotting Using Life Data -- 5.3.2.1 Exponential Distribution Probability Plotting -- 5.3.2.2 Weibull Distribution Probability Plotting -- 5.3.2.3 Normal and Lognormal Distribution Probability Plotting -- 5.4 Maximum Likelihood Estimation of Reliability Distribution Parameters -- 5.4.1 Elements of MLE Using Reliability Data -- 5.4.2 Exponential Distribution MLE Point Estimation -- 5.4.2.1 Type I Life Test with Replacement -- 5.4.2.2 Type I Life Test without Replacement -- 5.4.2.3 Type II Life Test with Replacement -- 5.4.2.4 Type II Life Test without Replacement -- 5.4.3 Exponential Distribution Interval Estimation -- 5.4.4 Normal Distribution -- 5.4.5 Lognormal Distribution -- 5.4.6 Weibull Distribution -- 5.4.7 Binomial Distribution -- 5.5 Classical Nonparametric Distribution Estimation -- 5.5.1 Confidence Intervals for cdf and Reliability Function for Complete and Censored Data -- 5.5.2 Confidence Intervals of Reliability Function for Censored Data -- 5.6 Bayesian Estimation Procedures -- 5.6.1 Estimation of the Parameter of Exponential Distribution -- 5.6.1.1 Selecting Hyperparameters for the Gamma Prior Distribution -- 5.6.1.2 Uniform Prior Distribution -- 5.6.1.3 Jeffrey's Prior Distribution -- 5.6.2 Bayesian Estimation of the Parameter of Binomial Distribution -- 5.6.2.1 Standard Uniform Prior Distribution -- 5.6.2.2 Beta Prior Distribution -- 5.6.2.3 Jeffrey's Prior Distribution -- 5.6.2.4 Lognormal Prior Distribution -- 5.6.3 Bayesian Estimation of Other Distributions…”

Tabla de Contenidos: “…322 -- 11.2 Campagne pour la souveraineté sur les semences331 -- 11.2.1 La souveraineté sur les semences dans l'arène de la conservation de la biodiversité . 332 -- 11.2.2 La campagne pour la souveraineté des semences dans le cadre plus large de la lutte pour la souveraineté alimentaire : les arènes de la sécurité alimentaire et de la propriété intellectuelle341 -- 11.2.3 Vers un droit humain sur les semences?…”

Tabla de Contenidos: “…12.1.3.1 ISIS and Cyber-Based Attacks -- 12.1.3.2 Monitoring ISIS -- 12.1.3.3 Israeli Bombing of Hamas Cyber Operators -- 12.1.4 Tactical Cyber Effects' Wrap-up -- 12.A Cost of Example Tactical Cyber Attacks (Iran) -- Bibliography -- Chapter 13 Cyber Crime Effects -- 13.1 Criminal Cyber Effects -- 13.1.1 Records Theft -- 13.1.1.1 Cost of a Data Breach -- 13.1.1.2 Business Records Attacks (2006-2019) -- 13.1.1.3 2017 Large Exfiltration Attack Example (Equifax (2017) - 143 Million Records) -- 13.1.2 Cyber Crime Examples -- 13.1.2.1 Conficker (2011) -- 13.1.2.2 Silk Road (2013) -- 13.1.2.3 Bangladesh Bank (2016) -- 13.1.2.4 Hydra (2015-2022) -- 13.1.2.5 Ransomware (&gt -- 2017) -- 13.1.3 Cyber Criminal Organizations - Gangs and Nation-States -- 13.1.3.1 Cyber Gangs -- 13.1.3.2 CONTI Ransomware Group -- 13.1.3.3 Nation-State Use of Cyber Crime -- 13.1.4 Cyber Crime Effects' Wrap-up -- Bibliography -- Section II Cyber Effects Conclusions -- II.1 Cyber Effects Overview -- II.2 Cyber Effects' Wrap-up -- Bibliography -- Section III Cyberspace Environment and Tools Introduction -- Bibliography -- Chapter 14 Criminal Cyber Operations and Tools -- 14.1 Criminal Cyber Operations and Tools -- 14.1.1 Shadow Brokers' Tools -- 14.1.1.1 Criminals Continue to Misuse Cobalt Strike -- 14.1.2 Malware Loaders -- 14.1.2.1 EMOTET -- 14.1.2.2 HIVE Ransomware Group use of Cobalt Strike Example -- 14.1.3 Botnets -- 14.1.3.1 Mirai Botnet -- 14.1.4 Criminal Cyber Tools' Wrap-up -- Bibliography -- Chapter 15 Russian Cyber Operations and Tools -- 15.1 Russian Cyber Operations and Tools -- 15.1.1 Example Operations' Attack Paths -- 15.1.1.1 U.S. …”