Search Results - (((((((ant OR canton) OR mantis) OR went) OR cantor) OR anne) OR share) OR hints) algorithms.

  1. 281

    Concise encyclopaedia of bioinformatics and computational biology 2e

    Published 2014
    Table of Contents: “….; Akaike Information Criterion; Pedro Larranaga and Concha Bielza; Algorithm; Matthew He; Alignment (Domain Alignment, Repeats Alignment); Jaap Heringa; Alignment Score; Laszlo Patthy; Allele-Sharing Methods (Non-parametric Linkage Analysis).…”
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  2. 282

    CUDA Application Design and Development. by Farber, Rob

    Published 2011
    Table of Contents: “…The Nsight Timeline Analysis -- The NVTX Tracing Library -- Scaling Behavior of the CUDA API -- Tuning and Analysis Utilities (TAU) -- Summary -- 4 The CUDA Execution Model -- GPU Architecture Overview -- Thread Scheduling: Orchestrating Performance and Parallelism via the Execution Configuration -- Relevant computeprof Values for a Warp -- Warp Divergence -- Guidelines for Warp Divergence -- Relevant computeprof Values for Warp Divergence -- Warp Scheduling and TLP -- Relevant computeprof Values for Occupancy -- ILP: Higher Performance at Lower Occupancy -- ILP Hides Arithmetic Latency -- ILP Hides Data Latency -- ILP in the Future -- Relevant computeprof Values for Instruction Rates -- Little's Law -- CUDA Tools to Identify Limiting Factors -- The nvcc Compiler -- Launch Bounds -- The Disassembler -- PTX Kernels -- GPU Emulators -- Summary -- 5 CUDA Memory -- The CUDA Memory Hierarchy -- GPU Memory -- L2 Cache -- Relevant computeprof Values for the L2 Cache -- L1 Cache -- Relevant computeprof Values for the L1 Cache -- CUDA Memory Types -- Registers -- Local memory -- Relevant computeprof Values for Local Memory Cache -- Shared Memory -- Relevant computeprof Values for Shared Memory -- Constant Memory -- Texture Memory -- Relevant computeprof Values for Texture Memory -- Global Memory -- Common Coalescing Use Cases -- Allocation of Global Memory -- Limiting Factors in the Design of Global Memory -- Relevant computeprof Values for Global Memory -- Summary -- 6 Efficiently Using GPU Memory -- Reduction -- The Reduction Template -- A Test Program for functionReduce.h -- Results -- Utilizing Irregular Data Structures -- Sparse Matrices and the CUSP Library -- Graph Algorithms -- SoA, AoS, and Other Structures -- Tiles and Stencils -- Summary -- 7 Techniques to Increase Parallelism -- CUDA Contexts Extend Parallelism -- Streams and Contexts.…”
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    Large Scale Network-Centric Distributed Systems

    Published 2014
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  6. 286

    Machine Learning in Chemical Safety and Health : Fundamentals with Applications. by Wang, Qingsheng

    Published 2022
    Table of Contents: “…Chapter 3 Flammability Characteristics Prediction Using QSPR Modeling -- 3.1 Introduction -- 3.1.1 Flammability Characteristics -- 3.1.2 QSPR Application -- 3.1.2.1 Concept of QSPR -- 3.1.2.2 Trends and Characteristics of QSPR -- 3.2 Flowchart for Flammability Characteristics Prediction -- 3.2.1 Dataset Preparation -- 3.2.2 Structure Input and Molecular Simulation -- 3.2.3 Calculation of Molecular Descriptors -- 3.2.4 Preliminary Screening of Molecular Descriptors -- 3.2.5 Descriptor Selection and Modeling -- 3.2.6 Model Validation -- 3.2.6.1 Model Fitting Ability Evaluation -- 3.2.6.2 Model Stability Analysis -- 3.2.6.3 Model Predictivity Evaluation -- 3.2.7 Model Mechanism Explanation -- 3.2.8 Summary of QSPR Process -- 3.3 QSPR Review for Flammability Characteristics -- 3.3.1 Flammability Limits -- 3.3.1.1 LFLT and LFL -- 3.3.1.2 UFLT and UFL -- 3.3.2 Flash Point -- 3.3.3 Auto-ignition Temperature -- 3.3.4 Heat of Combustion -- 3.3.5 Minimum Ignition Energy -- 3.3.6 Gas-liquid Critical Temperature -- 3.3.7 Other Properties -- 3.4 Limitations -- 3.5 Conclusions and Future Prospects -- References -- Chapter 4 Consequence Prediction Using Quantitative Property-Consequence Relationship Models -- 4.1 Introduction -- 4.2 Conventional Consequence Prediction Methods -- 4.2.1 Empirical Method -- 4.2.2 Computational Fluid Dynamics (CFD) Method -- 4.2.3 Integral Method -- 4.3 Machine Learning and Deep Learning-Based Consequence Prediction Models -- 4.4 Quantitative Property-Consequence Relationship Models -- 4.4.1 Consequence Database -- 4.4.2 Property Descriptors -- 4.4.3 Machine Learning and Deep Learning Algorithms -- 4.5 Challenges and Future Directions -- References -- Chapter 5 Machine Learning in Process Safety and Asset Integrity Management -- 5.1 Opportunities and Threats -- 5.2 State-of-the-Art Reviews -- 5.2.1 Artificial Neural Networks (ANNs).…”
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  7. 287

    Frontiers In The Study Of Chaotic Dynamical Systems With Open Problems.

    Published 2011
    Table of Contents: “…Preface; Contents; Chapter 1 Problems with Lorenz's Modeling and the Algorithm of Chaos Doctrine; 1.1. Introduction; 1.2. …”
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  8. 288

    Computational models of argument : Proceedings of COMMA 2012

    Published 2012
    Table of Contents: “…Simari -- Automated Deployment of Argumentation Protocols / Michael Rovatsos -- On Preferred Extension Enumeration in Abstract Argumentation / Katie Atkinson -- Towards Experimental Algorithms for Abstract Argumentation / Katie Atkinson.…”
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    Banking and finance issues in emerging markets.

    Published 2018
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    Stochastic filtering with applications in finance by Bhar, Ramaprasad

    Published 2010
    Table of Contents: “…Economic convergence in a filtering framework. 3.3. Ex-ante equity risk premium. 3.4. Concluding remarks -- 4. …”
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  15. 295

    Design optimization of fluid machinery : applying computational fluid dynamics and numerical optimization by Kim, Kwang-Yong, 1956-, Samad, Abdus, Benini, Ernesto

    Published 2019
    Table of Contents: “…2.2.5.3 Periodic/Cyclic Boundary Conditions2.2.5.4 Symmetry Boundary Conditions; 2.2.6 Moving Reference Frame (MRF); 2.2.7 Verification and Validation; 2.2.8 Commercial CFD Software; 2.2.9 Open Source Codes; 2.2.9.1 OpenFOAM; References; Chapter 3 Optimization Methodology; 3.1 Introduction; 3.1.1 Engineering Optimization Definition; 3.1.2 Design Space; 3.1.3 Design Variables and Objectives; 3.1.4 Optimization Procedure; 3.1.5 Search Algorithm; 3.2 Multi-Objective Optimization (MOO); 3.2.1 Weighted Sum Approach; 3.2.2 Pareto-Optimal Front…”
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  16. 296

    Digital information ecosystems : smart press by Augey, Dominique

    Published 2019
    Table of Contents: “…The problem of revenue sharing between media and social networks; 6.2. The social network eco-system; 6.2.1. …”
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    Credit securitizations and derivatives : challenges for the global markets

    Published 2013
    Table of Contents: “…Market Credit Risk Pricing -- Regulation -- Developments in Structured Finance Markets -- Impairments of Asset-Backed Securities and Outstanding Ratings -- Issuance of Asset-backed Securities and Outstanding Volume -- Global CDO Issuance and Outstanding Volume -- PART II CREDIT PORTFOLIO RISK MEASUREMENT -- Mortgage Credit Risk -- Five C's of Credit and Mortgage Credit Risk -- Determinants of Mortgage Default, Loss Given Default and Exposure at Default -- Determinants of Mortgage Default -- Determinants of Mortgage LGD -- Determinants of Mortgage EAD -- Modeling Methods for Default, LGD and EAD -- Model Risk Management -- Credit Portfolio Correlations and Uncertainty -- Introduction -- Gaussian and Semi-Gaussian Single Risk Factor Model -- Individual and Simultaneous Confidence Bounds and Intervals -- Confidence Intervals for Asset Correlations -- Confidence Intervals for Default and Survival Time Correlations -- Confidence Intervals for Default Correlations -- Confidence Intervals for Survival Time Correlations -- Credit Portfolio Correlations with Dynamic Leverage Ratios -- The Hui et al. (2007) Model -- The Method of Images for Constant Coefficients -- The Method of Images for Time-Varying Coefficients -- Modelling Default Correlations in a Two-Firm Model -- Default Correlations -- A Two-Firm Model with Dynamic Leverage Ratios -- Method of Images for Constant Coefficients -- Method of Images for Time-Varying Coefficients -- Alternative Methodologies for General Values -- Numerical Results -- Accuracy -- The Impact of Correlation between Two Firms -- The Impact of Different Credit Quality Paired Firms -- The Impact of Volatilities -- The Impact of Drift Levels -- The Impact of Initial Value of Leverage Ratio Levels -- Impact of Correlation between Firms and Interest Rates -- The Price of Credit-Linked Notes -- A Hierarchical Model of Tail-Dependent Asset Returns -- The Variance Compound Gamma Model -- Multivariate Process for Logarithmic Asset Returns -- Dependence Structure -- Sampling -- Copula Properties -- An Application Example -- Portfolio Setup -- Test Portfolios -- Parameter Setup -- Simulation Results -- Importance Sampling Algorithm -- Conclusions -- Appendix A: The VCG Probability Distribution Function Appendix B: HAC Representation for the VCG Framework -- Monte Carlo Methods for Portfolio Credit Risk -- Modeling Credit Portfolio Losses -- Risk Measures -- Modeling Dependency -- Estimating Risk Measures via Monte Carlo -- Crude Monte Carlo Estimators -- Importance Sampling -- Specific Models -- The Bernoulli Mixture Model -- Factor Models -- Copula Models -- Intensity Models -- An Example Point Process Model -- Appendix A: A Primer on Rare-event Simulation -- Efficiency -- Importance Sampling -- The Choice of g -- Adaptive Importance Sampling -- Importance Sampling for Stochastic Processes -- Credit Portfolio Risk and Diversification -- Introduction -- Model Setup -- Independent Asset Values -- Correlated Asset Values -- Large Portfolio Limit -- Correlated Diffusion -- Correlated GARCH Process -- Applications of the Structural Recovery Rate -- Conclusions -- PART III CREDIT PORTFOLIO RISK SECURITIZATION AND TRANCHING -- Differences in Tranching Methods: Some Results and Implications -- Defining a Tranche -- The Mathematics of Tranching -- PD-based Tranching -- EL-based Tranching -- The EL of a Tranche Necessarily Increases When Either the Attachment Point or the Detachment Point is Decreased -- Upper Bound on Tranche Expected LGD (LGDt) Assumption Given EL-based Tranches -- Skipping of Some Tranches in the EL-based Approach -- Global Structured Finance Rating -- Asset-Backed Securities -- The ABS Structure for the Experiment -- Cash Flow Modeling -- Modeling and Simulating Defaults -- Expected Loss Rating -- Global Sensitivity Analysis -- Elementary Effects -- Variance-based Method -- Global Sensitivity Analysis Results -- Uncertainty Analysis -- Sensitivity Analysis -- Global Rating -- PART IV CREDIT DERIVATIVES -- Analytic Dynamic Factor Copula Model -- Pricing Equations -- One-factor Copula Model -- Multi-period Factor Copula Models -- Calibration -- Dynamic Modeling of Credit Derivatives -- General Model Choice -- Modeling Option Prices -- Modeling Credit Risk -- Portfolio Credit Derivatives -- Modeling Asset Dynamics -- The Market Model -- The Asset-value Model -- Empirical Analysis -- Elementary Data -- Implied Dividends -- Market Dynamics -- Asset Value Model -- Tranche Pricing -- Out-of-time Application -- Pricing and Calibration in Market Models -- Basic notions -- The model -- Modeling Assumptions -- Absence of Arbitrage -- An affine specification -- Pricing -- Calibration -- Calibration Procedure -- Calibration Results -- Appendix A: Computations -- Counterparty Credit Risk and Clearing of Derivatives -- From the Perspective of an Industrial Corporate with a Focus on Commodity Markets -- Credit exposures in commodity business -- Settlement Exposure -- Performance Exposure -- Example of Fixed Price Deal with Performance Exposure -- Example of a Floating Price Deal with Performance Exposure -- General Remarks on Credit Exposure Concepts -- Ex Ante exposure-reducing techniques -- Payment Terms -- Material Adverse Change Clauses -- Master Agreements -- Netting -- Margining -- Close Out Exposure and Threshold -- Ex Ante risk-reducing techniques -- Credit Enhancements in General -- Parent Company Guarantees -- Letters of Credit -- Credit Insurance -- Clearing via a Central Counterparty -- Ex Post risk-reducing techniques -- Factoring -- Novation -- Risk-reducing Trades -- Hedging with CDS -- Hedging with Contingent-CDS -- Hedging with Puts on Equity -- Ex Post work out considerations -- Practical credit risk management and pricing Peculiarities of commodity markets -- Peculiarities of commodity related credit portfolios -- Credit Risk Capital for a commodity related portfolio measured with an extension of CreditMetrics -- CreditRisk+ study: applied to a commodity related credit portfolio -- CDS Industrial Sector Indices, Credit and Liquidity Risk -- The Data -- Methodology and Results -- Preliminary Analysis -- Common Factor Analysis -- Stability of Relations -- Risk Transfer and Pricing of Illiquid Assets with Loan CDS -- Shipping Market -- Loan Credit Default Swaps -- LCDS Pricing -- Modeling LCDS Under the Intensity-based Model -- Valuation Framework for LCDS -- The Structural Approach -- Credit Risk in Shipping Loans -- Valuation of LCDS on Shipping Loans -- Simulation Model -- Numerical Results -- Appendix A: Monte Carlo Parameterization PART V REGULATION -- Regulatory Capital Requirements for Securitizations -- Regulatory Approaches for Securitizations -- Ratings Based Approach (RBA) -- Supervisory Formula Approach (SFA) -- Standardized Approach (SA) -- Post-crisis Revisions to the Basel Framework -- Regulating OTC Derivatives -- The Wall Street Transparency and Accountability Part of the Dodd-Frank Act of 2010 -- Which Derivatives Will Be Affected? …”
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  19. 299

    Advanced security solutions for multimedia

    Published 2021
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  20. 300

    Security, Privacy and Reliability in Computer Communications and Networks. by Sha, Kewei

    Published 2016
    Table of Contents: “…Front Cover -- Half Title Page -- RIVER PUBLISHERS SERIES IN INNOVATION AND CHANGE IN EDUCATION -- CROSS-CULTURAL PERSPECTIVE -- Title Page -- Security, Privacy and Reliability in Computer Communications and Networks -- Copyright Page -- Contents -- Preface -- Acknowledgments -- List of Contributors -- List of Figures -- List of Tables -- List of Algorithms -- List of Abbreviations -- PART I -- Privacy -- Chapter 1 -- Distributed Beamforming Relay Selection to Increase Base Station Anonymity in Wireless Ad Hoc Networks -- Abstract -- 1.1 Introduction -- 1.2 Anonymity Definition, Metrics, and Contemporary Measures -- 1.2.1 Anonymity Definition and Assessment -- 1.2.2 Antitraffic Analysis Measures -- 1.3 System Assumptions and Attack Model -- 1.3.1 Network Model -- 1.3.2 Adversary Model -- 1.3.3 Evidence Theory and Belief Metric -- 1.4 Distributed Beamforming to Increase the BS Anonymity -- 1.4.1 Overview of the DiBAN Protocol -- 1.4.2 DiBAN Illustrative Example -- 1.4.3 DiBAN Energy Analysis -- 1.5 Distributed Beamforming Relay Selection Approach -- 1.6 Validation Experiments -- 1.6.1 Simulation Environment -- 1.6.2 Simulation Results -- 1.7 Conclusions and FutureWork -- Appendix I: Numerical Evidence Theory Belief Calculation Example -- References -- Chapter 2 -- A Privacy-Preserving and Efficient Information Sharing Scheme for VANET Secure Communication -- Abstract -- 2.1 Introduction -- 2.2 Related Works -- 2.3 System Model and Preliminaries -- 2.3.1 Network Model -- 2.3.2 Attack Model -- 2.3.3 Security Requirements -- 2.4 The Proposed PETS Scheme -- 2.4.1 Scheme Overview -- 2.4.2 System Initiation -- 2.4.3 Vehicle-RSU Key Agreement -- 2.4.4 Traffic Information Collection and Aggregation -- 2.4.5 Traffic Jam Message Propagation -- 2.5 Security Analysis -- 2.6 Performance Evaluation -- 2.6.1 Traffic Information Sending/Collection Overhead.…”
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