Որոնման արդյունքները - Computer simulation

Chaos Bound : Orderly Disorder in Contemporary Literature and Science / ‌ Hayles, N. Katherine, 1943-

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Canals and Communities : Small-Scale Irrigation Systems /

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Histories of Technology, the Environment and Modern Britain /

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Salience in sociolinguistics : a quantitative approach / ‌ Rácz, Péter

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Understanding medical education : evidence, theory, and practice /

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Frontiers in quantum information research decoherence, entanglement, entropy, MPS and DMRG /

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Model-Based Demography Essays on Integrating Data, Technique and Theory / ‌ Burch, Thomas K.

Բովանդակություն: “…Computer Simulation and Statistical Modeling: Rivals or Complements? …”
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Explaining creativity the science of human innovation / ‌ Sawyer, R. Keith (Robert Keith)

Բովանդակություն: “…Conceptions -- Introduction -- Conceptions of creativity -- Individualist approaches -- Defining creativity through assessment -- The creative personality -- The creative process, part 1 -- The creative process, part 2 -- The creative process, part 3 -- Computer simulations of the creative process -- Biology and creativity -- Cognitive neuroscience and creativity -- Sociocultural approaches -- Sociology -- Group creativity -- Organizational creativity -- Culture and creativity -- History and creativity -- Creativity in the domains -- Visual arts -- Writing -- Music -- Theater -- Science -- Everyday creativity -- Education and creativity -- How to be more creative -- Conclusion: the future of creativity.…”
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Transient analysis of power systems : solution techniques, tools and applications / ‌ Martinez-Velasco, Juan A.

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Continuity in linguistic semantics

Բովանդակություն: “…/ Pierre Le Goffic -- The use of computer corpora in the textual demonstrability of gradience in linguistic categories / Geoffrey Leech, Brian Francis & Xunfeng Xu -- A "continuous definition" of polysemous items / Jacqueline Picoche -- The challenges of continuity for a linguistic approach to semantics / Catherine Fuchs -- What kind of models do we need for the simulation of understanding? …”
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Demystifying Climate Models A Users Guide to Earth System Models / ‌ Gettelman, Andrew, Rood, Richard B.

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Modeling power electronics and interfacing energy conversion systems /

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Psychedelic psychiatry : LSD from clinic to campus / ‌ Dyck, Erika

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The Impact of Food Bioactives on Health in vitro and ex vivo models /

Բովանդակություն: “…Introduction -- Gastrointestinal digestion models, general introduction -- Static digestion models general introduction -- InfoGest consensus method -- Approaches to static digestion models -- Dynamic digestion models general introduction -- The TNO gastro-Intestinal Model (TIM) -- Dynamic Gastric Model (DGM) -- Human Gastric Simulator (Riddet model) -- The DIDGI® System -- General introduction to cells, cell lines and cell culture -- Epithelial cell models; General introduction -- Caco-2 cell line -- HT29 cell line -- The IPEC-J2 cell line -- Co-cultivation of Caco-2 and HT-29MT -- Innate and adaptive immune cells; General introduction -- THP-1 and U937 cells -- Peripheral blood mononuclear cells -- PBMC-derived T cells -- Dendritic Cells -- Co-culture Caco-2/ immune cells -- Enteroendocrine Cell Models: General introduction -- STC-1 cells -- NCI-H716 cells -- Murine GLUTag cells -- In vitro intestinal tissue models: General introduction -- Intestinal crypt organoids as experimental models -- Porcine ex vivo intestinal segment model -- Ussing chamber -- In vitro fermentation models: General Introduction -- One compartment fermentation model -- The TNO in vitro model of the colon - TIM-2 -- The Simulator of the Human Intestinal Microbial Ecosystem – SHIME® -- The computer-controlled multicompartmental dynamic model of the gastrointestinal system SIMGI.…”
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Refractories : recent developments in materials, production and use : 12th International Congress, Part 1 /

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Three-dimensional imaging for orthodontics and maxillofacial surgery

Բովանդակություն: “….] -- A new clinical protocol to plan cranio-maxillofacial surgery using computer-aide simulation (CASS) / James J. Xia, Jaime Gateno, John F. …”
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Specific ion effects

Բովանդակություն: “…Foreword -- Preface -- Acknowledgements -- List of contributors -- An attempt of a general overview / Werner Kunz and Roland Neueder -- Phospholipid aggregates as model systems to understand ion-specific effects : experiments and models / Epameinondas Leontidis -- Modelling specific ion effects in engineering science / Christoph Held and Gabriele Sadowski -- Linear and non-linear optical techniques to probe ion profiles at the air-water interface / Hubert Motschmann and Patrick Koelsch -- X-ray studies of ion specific effects / Padmanabhan Viswanath, Luc Girard, Jean Daillant, Luc Belloni, Olivier Spalla and Dmitri Novikov -- Determination of specific ion structure by neutron scattering and computer simulation / George W. Neilson, Philip E. …”
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Statistical monitoring of complex multivariate processes with applications in industrial process control / ‌ Krüger, Uwe, Dr

Բովանդակություն: “…Machine generated contents note: Preface Introduction I Fundamentals of Multivariate Statistical Process Control 1 Motivation for Multivariate Statistical Process Control 1.1 Summary of Statistical Process Control 1.1.1 Roots and Evolution of Statistical Process Control 1.1.2 Principles of Statistical Process Control 1.1.3 Hypothesis Testing, Type I and II errors 1.2 Why Multivariate Statistical Process Control 1.2.1 Statistically Uncorrelated Variables 1.2.2 Perfectly Correlated Variables 1.2.3 Highly Correlated Variables 1.2.4 Type I and II Errors and Dimension Reduction 1.3 Tutorial Session 2 Multivariate Data Modeling Methods 2.1 Principal Component Analysis 2.1.1 Assumptions for Underlying Data Structure 2.1.2 Geometric Analysis of Data Structure 2.1.3 A Simulation Example 2.2 Partial Least Squares 2.2.1 Assumptions for Underlying Data Structure 2.2.2 Deflation Procedure for Estimating Data Models 2.2.3 A Simulation Example 2.3 Maximum Redundancy Partial Least Squares 2.3.1 Assumptions for Underlying Data Structure 2.3.2 Source Signal Estimation 2.3.3 Geometric Analysis of Data Structure 2.3.4 A Simulation Example 2.4 Estimating the Number of Source Signals 2.4.1 Stopping Rules for PCA Models 2.4.2 Stopping Rules for PLS Models 2.5 Tutorial Session 3 Process Monitoring Charts 3.1 Fault Detection 3.1.1 Scatter Diagrams 3.1.2 Nonnegative Quadratic Monitoring Statistics 3.2 Fault Isolation and Identification 3.2.1 Contribution Charts 3.2.2 Residual-Based Tests 3.2.3 Variable Reconstruction 3.3 Geometry of Variable Projections 3.3.1 Linear Dependency of Projection Residuals 3.3.2 Geometric Analysis of Variable Reconstruction 3.4 Tutorial Session II Application Studies 4 Application to a Chemical Reaction Process 4.1 Process Description 4.2 Identification of a Monitoring Model 4.3 Diagnosis of a Fault Condition 5 Application to a Distillation Process 5.1 Process Description 5.2 Identification of a Monitoring Model 5.3 Diagnosis of a Fault Condition III Advances in Multivariate Statistical Process Control 6 Further Modeling Issues 6.1 Accuracy of Estimating PCA Models 6.1.1 Revisiting the Eigendecomposition of Sz0z0 6.1.2 Two Illustrative Examples 6.1.3 Maximum Likelihood PCA for Known Sgg 6.1.4 Maximum Likelihood PCA for Unknown Sgg 6.1.5 A Simulation Example 6.1.6 A Stopping Rule for Maximum Likelihood PCA Models 6.1.7 Properties of Model and Residual Subspace Estimates 6.1.8 Application to a Chemical Reaction Process - Revisited 6.2 Accuracy of Estimating PLS Models 6.2.1 Bias and Variance of Parameter Estimation 6.2.2 Comparing Accuracy of PLS and OLS Regression Models 6.2.3 Impact of Error-in-Variables Structure upon PLS Models 6.2.4 Error-in-Variable Estimate for Known See 6.2.5 Error-in-Variable Estimate for Unknown See 6.2.6 Application to a Distillation Process - Revisited 6.3 Robust Model Estimation 6.3.1 Robust Parameter Estimation 6.3.2 Trimming Approaches 6.4 Small Sample Sets 6.5 Tutorial Session 7 Monitoring Multivariate Time-Varying Processes 7.1 Problem Analysis 7.2 Recursive Principal Component Analysis 7.3 MovingWindow Principal Component Analysis 7.3.1 Adapting the Data Correlation Matrix 7.3.2 Adapting the Eigendecomposition 7.3.3 Computational Analysis of the Adaptation Procedure 7.3.4 Adaptation of Control Limits 7.3.5 Process Monitoring using an Application Delay 7.3.6 MinimumWindow Length 7.4 A Simulation Example 7.4.1 Data Generation 7.4.2 Application of PCA 7.4.3 Utilizing MWPCA based on an Application Delay 7.5 Application to a Fluid Catalytic Cracking Unit 7.5.1 Process Description 7.5.2 Data Generation 7.5.3 Pre-analysis of Simulated Data 7.5.4 Application of PCA 7.5.5 Application of MWPCA 7.6 Application to a Furnace Process 7.6.1 Process Description 7.6.2 Description of Sensor Bias 7.6.3 Application of PCA 7.6.4 Utilizing MWPCA based on an Application Delay 7.7 Adaptive Partial Least Squares 7.7.1 Recursive Adaptation of Sx0x0 and Sx0y0 7.7.2 MovingWindow Adaptation of Sv0v0 and Sv0y0 7.7.3 Adapting The Number of Source Signals 7.7.4 Adaptation of the PLS Model 7.8 Tutorial Session 8 Monitoring Changes in Covariance Structure 8.1 Problem Analysis 8.1.1 First Intuitive Example 8.1.2 Generic Statistical Analysis 8.1.3 Second Intuitive Example 8.2 Preliminary Discussion of Related Techniques 8.3 Definition of Primary and Improved Residuals 8.3.1 Primary Residuals for Eigenvectors 8.3.2 Primary Residuals for Eigenvalues 8.3.3 Comparing both Types of Primary Residuals 8.3.4 Statistical Properties of Primary Residuals 8.3.5 Improved Residuals for Eigenvalues 8.4 Revisiting the Simulation Examples in Section 8.1 8.4.1 First Simulation Example 8.4.2 Second Simulation Example 8.5 Fault Isolation and Identification 8.5.1 Diagnosis of Step-Type Fault Conditions 8.5.2 Diagnosis of General Deterministic Fault Conditions 8.5.3 A Simulation Example 8.6 Application Study to a Gearbox System 8.6.1 Process Description 8.6.2 Fault Description 8.6.3 Identification of a Monitoring Model 8.6.4 Detecting a Fault Condition 8.7 Analysis of Primary and Improved Residuals 8.7.1 Central Limit Theorem 8.7.2 Further Statistical Properties of Primary Residuals 8.7.3 Sensitivity of Statistics based on Improved Residuals 8.8 Tutorial Session IV Description of Modeling Methods 9 Principal Component Analysis 9.1 The Core Algorithm 9.2 Summary of the PCA Algorithm 9.3 Properties of a PCA Model 10 Partial Least Squares 10.1 Preliminaries 10.2 The Core Algorithm 10.3 Summary of the PLS Algorithm10.4 Properties of PLS 10.5 Properties of Maximum Redundancy PLS References Index.…”
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Indiscretions : Avant-Garde Film, Video, and Feminism / ‌ Mellencamp, Patricia

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Globalization policies and issues

Բովանդակություն: “…Kuriakose -- An overview of computational methods in forecasting tourism demand : recommendations and future research / Marcos Álvarez-Díaz and Jaume Rosselló-Nadal -- Shifting locus of influence in the labor union movement : negotiations in international framework agreements / Niklas Egels-Zandén -- Trade policy in the globalizing world : policy modeling and simulations of futures / Akira Onishi.…”
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