Search Results - (((((((ant OR wante) OR mantis) OR when) OR cantor) OR anne) OR shape) OR hints) algorithms.

Industrial engineering and applied research : selected, peer reviewed papers from the 2014 3rd International Conference on Industrial Design and Mechanics Power (3rd ICIDMP 2014),...

Table of Contents: “…3-D Model Reconstruction and Mold Flow Simulation for an Existing Shaped PartAnalysis of Surge Shaft Excavation Process Based on 3-Dimensional Finite Difference Method; Singular Configurations Analysis of a Redundantly Actuated Parallel Manipulator; Two-Machine Flowshop Problem with Release Dates, Rejection and Non-Availability Interval on the First Machine; Internal Flow Field Analysis of Air-Suction Roller-Type Precision Metering Device; The UG Parametric Design of Vertical Horizontal Circular Vibration Drier Chassis…”
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Non-line-of-sight radar by Watson, Brian C., Guerci, J. R.

Table of Contents: “…5.2 Diffraction -- 5.2.1 KED -- 5.2.2 UTD -- 5.3 SEKE -- 5.4 Radar Simulations Using Elliptical C -- 5.5 Commercial Software -- References -- 6 Computing Hardware Acceleration Strategi -- 6.1 GPU Computational Model -- 6.2 GPU Programming -- 6.3 FPGA -- 6.4 Ray-Tracing Line-of-Sight Algorithms -- 6.4.1 Shapes and Ray Intersections -- 6.4.2 Intersection Acceleration Algorith -- 6.5 GPU Ray-Tracing Example -- 6.6 FPGA Ray Tracing -- References -- About the Authors -- Index.…”
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Artificial Intelligence Research and Development : Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence

Table of Contents: “…Agell -- A similarity calculus for comparing qualitative shape descriptions / Z. Falomir [and others].…”
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Dynamics among nations : the evolution of legitimacy and development in modern states by Root, Hilton L.

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FX barrier options : a comprehensive guide for industry quants by Dadachanji, Zareer

Table of Contents: “…Stupid; 4.10 Five things we want from a model; 4.11 Stochastic volatility (SV) models; 4.11.1 SABR model; 4.11.2 Heston model; 4.12 Mixed local/stochastic volatility (lsv) models; 4.12.1 Term structure of volatility of volatility; 4.13 Other models and methods; 4.13.1 Uncertain Volatility (UV) models; 4.13.2 Jump-diffusion models; 4.13.3 Vanna-volga methods; 5 Smile Risk Management; 5.1 Black-Scholes with term structure; 5.2 Local volatility model; 5.3 Spot risk under smile models; 5.4 Theta risk under smile models; 5.5 Mixed local/stochastic volatility models; 5.6 Static hedging; 5.7 Managing risk across businesses; 6 Numerical Methods; 6.1 Finite-difference (FD) methods; 6.1.1 Grid geometry; 6.1.2 Finite-difference schemes; 6.2 Monte Carlo (MC) methods; 6.2.1 Monte Carlo schedules; 6.2.2 Monte Carlo algorithms; 6.2.3 Variance reduction; 6.2.4 The Brownian Bridge; 6.2.5 Early…”
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Electromagnetic nondestructive evaluation (XII)

Table of Contents: “…Elastic Properties of Thermally Aged Fe-Cu Model Alloys Measured by EMAR Method -- Nondestructive Evaluation of Ferromagnetic Structural Materials Using FG Sensor -- Inverse Problem and Imaging -- Standoff Detection and Imaging of Suspicious and Concealed Objects with Electromagnetic Waves in the Centimetre and Millimetre Range -- Pulsed Terahertz Imaging for Nondestructive Evaluation -- On the Imaging of Two-Dimensional Thin Inclusions by a MUSIC-Type Algorithm from Boundary Measurements -- Chance-Constrained Programming: A Tool for Solving Linear Eddy Current Inverse Problem -- A Multiple Frequency Strategy for Reconstruction of Stress Corrosion Crack from ECT Signals -- Estimation Theory Metrics in Electromagnetic NDE -- Three Dimensional Shape Recovery of Fatigue Crack Using Eddy Current Testing Signals -- Application of Electromagnetic Nondestructive Techniques -- Development of Strong Magnetizer and Robust Sensor Mount System to Increase Performance in Detecting Defects on Pipeline -- Electromagnetic Evaluation of Honeycomb Composite Materials -- An Electromagnetic Method for Evaluation of Fatigue and for Detection of Damage at Bjork-Shiley Convexo-Concave Prosthetic Heart Valves -- Electromagnetic Evaluation of Soil Condition -- Investigation of Cu-Pc Thin Films on ITO Substrate by Using a Near-Field Microwave Microprobe -- Noncontact Characterization of Electric Carriers Density at Heterojunction Interfaces -- Electromagnetic Field Interaction with Aqueous Glucose Solution in Dielectric Resonator -- Quantitative Evaluation of Corrosion Shape on Back Surface of SUS Samples by EMAT -- Inspection of 3D Flaws Using EMAT -- Nondestructive Evaluation of Beryllium to Copper Joining for ITER by Using an Electromagnetic Acoustic Transducer (EMAT) -- Subject Index -- Author Index.…”
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Mastering D3.js. by Castillo, Pablo Navarro

Table of Contents: “…Updating the datasetFixing the enter and exit transitions; Using the barcode chart; Creating a layout algorithm; The radial layout; Computing the angles; Using the layout; Summary; Chapter 3: Creating Visualizations without SVG; SVG support in the browser market; Visualizations without SVG; Loading and sorting the data; The force layout method; Setting the color and size; Creating a legend; Polyfilling; Feature detection; The canvg example; Using canvas and D3; Creating figures with canvas; Creating shapes; Integrating canvas and D3; Summary; Chapter 4: Creating a Color Picker with D3.…”
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Great Myths of Personality. by Donnellan, M. Brent

Table of Contents: “…Cover -- Title Page -- Copyright Page -- Contents -- Introduction -- Research methods 101 -- Organization of chapters -- Foundational material -- Biological aspects of personality -- Personality assessment -- Personality development -- Well-being/happiness -- Applications of personality -- Basic vocabulary -- References -- Chapter 1 Situational Factors Overwhelm Personality When Predicting Behavior -- Defining personality -- Personality and assessment -- Responding to personality and assessment -- References…”
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Theory and application of special functions : proceedings of an advanced seminar sponsored by the Mathematics Research Center, the University of Wisconsin-Madison, March 31-April 2...

Table of Contents: “…Nonlinear recurrence algorithms for elliptic integrals and elliptic functions; 4. …”
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Beginning software engineering by Stephens, Rod, 1961-

Table of Contents: “…WhatWhen; Where; Why; How; Study Users; Refining Requirements; Copy Existing Systems; Clairvoyance; Brainstorm; Recording Requirements; UML; User Stories; Use Cases; Prototypes; Requirements Specification; Validation and Verification; Changing Requirements; Summary; CHAPTER 5: HIGH-LEVEL DESIGN; The Big Picture; What to Specify; Security; Hardware; User Interface; Internal Interfaces; External Interfaces; Architecture; Monolithic; Client/Server; Component-Based; Service-Oriented; Data-Centric; Event-Driven; Rule-Based; Distributed; Mix and Match; Reports; Other Outputs; Database; Audit Trails.…”
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Securing SQL server : protecting Your database from attackers by Cherry, Denny

Table of Contents: “…; Personally Identifiable Information; When should security objectives been identified?; How to identify security objectives?…”
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Intelligent computational systems : a multi-disciplinary perspective

Table of Contents: “…3.2.1. Genetic Algorithm (GA) -- 3.2.2. Particle Swarm Optimization Algorithm (PSO) -- 3.3. …”
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Mathematics of evolution and phylogeny

Table of Contents: “…List of Contributors -- 1 The minimum evolution distance-based approach of phylogenetic inference -- 1.1 Introduction -- 1.2 Tree metrics -- 1.2.1 Notation and basics -- 1.2.2 Three-point and four-point conditions -- 1.2.3 Linear decomposition into split metrics -- 1.2.4 Topological matrices -- 1.2.5 Unweighted and balanced averages -- 1.2.6 Alternate balanced basis for tree metrics -- 1.2.7 Tree metric inference in phylogenetics -- 1.3 Edge and tree length estimation -- 1.3.1 The LS approach -- 1.3.2 Edge length formulae -- 1.3.3 Tree length formulae -- 1.3.4 The positivity constraint -- 1.3.5 The balanced scheme of Pauplin -- 1.3.6 Semple and Steel combinatorial interpretation -- 1.3.7 BME: a WLS interpretation -- 1.4 The agglomerative approach -- 1.4.1 UPGMA and WPGMA -- 1.4.2 NJ as a balanced minimum evolution algorithm -- 1.4.3 Other agglomerative algorithms -- 1.5 Iterative topology searching and tree building -- 1.5.1 Topology transformations.; 1.5.2 A fast algorithm for NNIs with OLS -- 1.5.3 A fast algorithm for NNIs with BME -- 1.5.4 Iterative tree building with OLS -- 1.5.5 From OLS to BME -- 1.6 Statistical consistency -- 1.6.1 Positive results -- 1.6.2 Negative results -- 1.6.3 Atteson's safety radius analysis -- 1.7 Discussion -- Acknowledgements -- 2 Likelihood calculation in molecular phylogenetics -- 2.1 Introduction -- 2.2 Markov models of sequence evolution -- 2.2.1 Independence of sites -- 2.2.2 Setting up the basic model -- 2.2.3 Stationary distribution -- 2.2.4 Time reversibility -- 2.2.5 Rate of mutation -- 2.2.6 Probability of sequence evolution on a tree -- 2.3 Likelihood calculation: the basic algorithm -- 2.4 Likelihood calculation: improved models -- 2.4.1 Choosing the rate matrix -- 2.4.2 Among site rate variation -- 2.4.3 Site-specific rate variation -- 2.4.4 Correlated evolution between sites -- 2.5 Optimizing parameters -- 2.5.1 Optimizing continuous parameters -- 2.5.2 Searching for the optimal tree.; 2.5.3 Alternative search strategies -- 2.6 Consistency of the likelihood approach -- 2.6.1 Statistical consistency -- 2.6.2 Identifiability of the phylogenetic models -- 2.6.3 Coping with errors in the model -- 2.7 Likelihood ratio tests -- 2.7.1 When to use the asymptotic x2 distribution -- 2.7.2 Testing a subset of real parameters -- 2.7.3 Testing parameters with boundary conditions -- 2.7.4 Testing trees -- 2.8 Concluding remarks -- Acknowledgements -- 3 Bayesian inference in molecular phylogenetics -- 3.1 The likelihood function and maximum likelihood estimates -- 3.2 The Bayesian paradigm -- 3.3 Prior -- 3.4 Markov chain Monte Carlo -- 3.4.1 Metropolis-Hastings algorithm -- 3.4.2 Single-component Metropolis-Hastings algorithm -- 3.4.3 Gibbs sampler -- 3.4.4 Metropolis-coupled MCMC -- 3.5 Simple moves and their proposal ratios -- 3.5.1 Sliding window using uniform proposal -- 3.5.2 Sliding window using normally distributed proposal.; 3.5.3 Sliding window using normal proposal in multidimensions -- 3.5.4 Proportional shrinking and expanding -- 3.6 Monitoring Markov chains and processing output -- 3.6.1 Diagnosing and validating MCMC algorithms -- 3.6.2 Gelman and Rubin's potential scale reduction statistic -- 3.6.3 Processing output -- 3.7 Applications to molecular phylogenetics -- 3.7.1 Estimation of phylogenies -- 3.7.2 Estimation of species divergence times -- 3.8 Conclusions and perspectives -- Acknowledgements -- 4 Statistical approach to tests involving phylogenies -- 4.1 The statistical approach to phylogenetic inference -- 4.2 Hypotheses testing -- 4.2.1 Null and alternative hypotheses -- 4.2.2 Test statistics -- 4.2.3 Significance and power -- 4.2.4 Bayesian hypothesis testing -- 4.2.5 Questions posed as function of the tree parameter -- 4.2.6 Topology of treespace -- 4.2.7 The data -- 4.2.8 Statistical paradigms -- 4.2.9 Distributions on treespace -- 4.3 Different types of tests involving phylogenies.; 4.3.1 Testing t1 versus t2 -- 4.3.2 Conditional tests -- 4.3.3 Modern Bayesian hypothesis testing -- 4.3.4 Bootstrap tests -- 4.4 Non-parametric multivariate hypothesis testing -- 4.4.1 Multivariate con.dence regions -- 4.5 Conclusions: there are many open problems -- Acknowledgements -- 5 Mixture models in phylogenetic inference -- 5.1 Introduction: models of gene-sequence evolution -- 5.2 Mixture models -- 5.3 Defining mixture models -- 5.3.1 Partitioning and mixture models -- 5.3.2 Discrete-gamma model as a mixture model -- 5.3.3 Combining rate and pattern-heterogeneity -- 5.4 Digression: Bayesian phylogenetic inference -- 5.4.1 Bayesian inference of trees via MCMC -- 5.5 A mixture model combining rate and pattern-heterogeneity -- 5.5.1 Selected simulation results -- 5.6 Application of the mixture model to inferring the phylogeny of the mammals -- 5.6.1 Model testing -- 5.7 Results -- 5.7.1 How many rate matrices to include in the mixture model?…”
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Ultra-wideband signals and systems in communication engineering by Ghavami, M.

Table of Contents: “…Ultra Wideband Signals and Systems in Communication Engineering; Contents; Preface; Acknowledgments; List of Figures; List of Tables; Introduction; I.1 Ultra wideband overview; I.2 A note on terminology; I.3 Historical development of UWB; I.4 Key benefits of UWB; I.5 UWB and Shannon's theory; I.6 Challenges for ultra wideband; I.7 Summary; 1 Basic properties of UWB signals and systems; 1.1 Introduction; 1.2 Power spectral density; 1.3 Pulse shape; 1.4 Pulse trains; 1.5 Spectral masks; 1.6 Multipath; 1.7 Penetration characteristics; 1.8 Spatial and spectral capacities…”
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Frontiers of manufacturing science and measuring technology IV : selected, peer reviewed papers from the 2014 4th International Conference on Frontiers of Manufacturing Science and...

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Chemical engineering and material properties III : selected, peer reviewed papers from the 2014 4th International Symposium on Chemical Engineering and Material Properties (ISCEMP...

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Biological computation by Lamm, Ehud

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Minor Surgery at a Glance. by Mohan, Helen

Table of Contents: “…Part 3 Core surgical knowledge -- 17 Skin incisions -- Scalpels -- Holding the scalpel to make an incision -- Basic principles for incision -- Minor surgical incisions -- Techniques for a good scar -- Electrodissection to incise -- 18 Principles of wound closure -- Plan the skin incision -- Choosing the suture size -- Choosing the suture material -- Suture placement -- Technique for simple interrupted sutures -- When should I use a different suturing technique? …”
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The SMART CYBER ECOSYSTEM FOR SUSTAINABLE DEVELOPMENT.

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A primer on experiments with mixtures by Cornell, John A., 1941-

Table of Contents: “…QuestionsAppendix 2A: Least-Squares Estimation Formula for the Polynomial Coefficients and Their Variances: Matrix Notation; Appendix 2B: Cubic and Quartic Polynomials and Formulas for the Estimates of the Coefficients; Appendix 2C: The Partitioning of the Sources in the Analysis of Variance Table When Fitting the Scheffé Mixture Models; 3. Multiple Constraints on the Component Proportions; 3.1 Lower-Bound Restrictions on Some or All of the Component Proportions; 3.2 Introducing L-Pseudocomponents; 3.3 A Numerical Example of Fitting An L-Pseudocomponent Model.…”
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