Search Results - (((((((want OR wantii) OR mantis) OR when) OR cantor) OR anne) OR shared) OR hints) algorithms.

Multiple Sclerosis : Clinician's Guide to Diagnosis and Treatment. by Birnbaum, Gary

Table of Contents: “…Long-Term Disease-Modifying Therapies; Issues with Long-Term Immune-Modulating Therapies; Choosing a Disease-Modifying Therapy; Ensuring Treatment Adherence and Compliance; When Do I Initiate Treatment With Disease-Modifying Therapies?…”
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Robust statistics : theory and methods (with R) by Maronna, Ricardo A.

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Microbiological sensors for the drinking water industry

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A Statistical approach to genetic epidemiology : concepts and applications, with an e-Learning Platform. by Ziegler, Andreas, 1966-

Table of Contents: “…; 4.3 HOW SHOULD GENOTYPING ERRORS BE CHECKED IN POPULATION-BASED STUDIES USING THE HARDY-WEINBERG EQUILIBRIUM?; Algorithm 4.1.; Algorithm 4.2.; Algorithm 4.3.; 4.4 HOW CAN GENOTYPING ERRORS BE DETECTED IN HIGH-THROUGHPUT GENOTYPING STUDIES?…”
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Drones and other unmanned weapons systems under international law by Casey-Maslen, Stuart, Homayounnejad, Maziar, Stauffer, Hilary, Weizmann, Nathalie

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The Maudsley Prescribing Guidelines in Psychiatry by Taylor, David, 1963-, Paton, Carol, Kapur, Shitij

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The spirit of the hive : the mechanisms of social evolution by Page, Robert E.

Table of Contents: “…The regulatory architecture of pollen hoarding -- 9.1. Loading algorithms -- 9.2. Heritability of the pollen-hoarding syndrome -- 9.3. …”
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QoS in integrated 3G networks by Lloyd-Evans, Robert

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Applied mechanics and industrial technologies : selected, peer reviewed papers from the 2012 International Conference on Applied Mechanics and Manufacturing Technology (AMMT 2012),...

Table of Contents: “…An Assessment of Wet Compression Process in Gas Turbine Systems with an Analytical ModelingAssessment of Hole Quality and Thrust Force when Drilling CFRP/Al Stack Using Carbide Tools; Multi-Objective Optimization of Filament Wound Composite Pressure Vessels Based on Weight and Matrix Cracking/ Burst Pressure Using Imperialist Competitive Algorithm; In Situ Laser Build-Up Welding of Shipboard Crankshafts; Stress and Deformation Analysis for Caster Segment Based on ANSYS; Instable Crack Propagation Analysis with PDS-FEM; Reducing the Manufacturing Cost by Using Combination Die.…”
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Hierarchical Protection for Smart Grids. by Ma, Jing

Table of Contents: “…2.3.4 Adaptive Overload Identification Method Based on the Complex Phasor Plane2.3.5 Novel Fault Phase Selection Scheme Utilizing Fault Phase Selection Factors; 2.4 Summary; References; Chapter 3 Local Area Protection for Renewable Energy; 3.1 Introduction; 3.2 Fault Transient Characteristics of Renewable Energy Sources; 3.2.1 Mathematical Model and LVRT Characteristics of the DFIG; 3.2.2 DFIG Fault Transient Characteristics When Crowbar Protection Is Not Put into Operation; 3.2.3 DFIG Fault Transient Characteristics When Crowbar Protection Is Put into Operation.…”
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Uncommon sense : investment wisdom since the stock market's dawn by Kemp, Michael E.

Table of Contents: “…-- RELATING BOOK VALUE PER SHARE TO MARKET PRICE -- WHAT IS A LOW P/B RATIO TELLING US? …”
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Comprehensive Ruby Programming. by Hudgens, Jordan

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Multicriteria decision aid and artificial intelligence : links, theory and applications by Doumpos, Michael

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Integration of demand response into the electricity chain : challenges, opportunities and smart grid solutions

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Modern aerodynamic methods for direct and inverse applications by Chin, Wilson C.

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Image processing and jump regression analysis by Qiu, Peihua, 1965-

Table of Contents: “…Cover -- Contents -- Preface -- 1 Introduction -- 1.1 Images and image representation -- 1.2 Regression curves and sugaces with jumps -- 1.3 Edge detection, image restoration, and jump regression analysis -- 1.4 Statistical process control and some other related topics -- 1.5 Organization of the book -- Problems -- 2 Basic Statistical Concepts and Conventional Smoothing Techniques -- 2.1 Introduction -- 2.2 Some basic statistical concepts and terminologies -- 2.2.1 Populations, samples, and distributions -- 2.2.2 Point estimation of population parameters -- 2.2.3 Confidence intervals and hypothesis testing -- 2.2.4 Maximum likelihood estimation and least squares estimation -- 2.3 Nadaraya- Watson and other kernel smoothing techniques -- 2.3.1 Univariate kernel estimators -- 2.3.2 Some statistical properties of kernel estimators -- 2.3.3 Multivariate kernel estimators -- 2.4 Local polynomial kernel smoothing techniques -- 2.4.1 Univariate local polynomial kernel estimators -- 2.4.2 Some statistical properties -- 2.4.3 Multivariate local polynomial kernel estimators -- 2.4.4 Bandwidth selection -- 2.5 Spline smoothing procedures -- 2.5.1 Univariate smoothing spline estimation -- 2.5.2 Selection of the smoothing parameter -- 2.5.3 Multivariate smoothing spline estimation -- 2.5.4 Regression spline estimation -- 2.6 Wavelet transformation methods -- 2.6.1 Function estimation based on Fourier transformation -- 2.6.2 Univariate wavelet transformations -- 2.6.3 Bivariate wavelet transformations -- Problems -- 3 Estimation of Jump Regression Curves -- 3.1 Introduction -- 3.2 Jump detection when the number of jumps is known -- 3.2.1 Difference kernel estimation procedures -- 3.2.2 Jump detection based on local linear kernel smoothing -- 3.2.3 Estimation of jump regression functions based on semiparametric modeling -- 3.2.4 Estimation of jump regression functions by spline smoothing -- 3.2.5 Jump and cusp detection by wavelet transformations -- 3.3 Jump estimation when the number of jumps is unknown -- 3.3.1 Jump detection by comparing three local estimators -- 3.3.2 Estimation of the number of jumps by a sequence of hypothesis tests -- 3.3.3 Jump detection by DAKE -- 3.3.4 Jump detection by local polynomial regression -- 3.4 Jump-preserving curve estimation -- 3.4.1 Jump curve estimation by split linear smoothing -- 3.4.2 Jump-preserving curve fitting based on local piecewise-linear kernel estimation -- 3.4.3 Jump-preserving smoothers based on robust estimation -- 3.5 Some discussions -- Problems -- 4 Estimation of Jump Location Curves of Regression Surfaces -- 4.1 Introduction -- 4.2 Jump detection when the number of jump location curves is known -- 4.2.1 Jump detection by RDKE -- 4.2.2 Minimax edge detection -- 4.2.3 Jump estimation based on a contrast statistic -- 4.2.4 Algorithms for tracking the JLCs -- 4.2.5 Estimation of JLCs by wavelet transformations -- 4.3 Detection of arbitrary jumps by local smoothing -- 4.3.1 Treat JLCs as a pointset in the design space -- 4.3.2 Jump detection by local linear estimation -- 4.3.3 Two modijication procedures -- 4.4 Jump detection in two or more given directions -- 4.4.1 Jump detection in two given directions -- 4.4.2 Measuring the p.…”
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Bayesian Analysis with Python. by Osvaldo Martin

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Combinatorial and Computational Mathematics : Present and Future.

Table of Contents: “…2 LIST OF APPLICABLE MATHEMATICS IN SOCIAL SCIENCE3 SOCIAL WELFARE FUNCTIONS (SWF); 4 PROSPECTS; 5 OPEN PROBLEMS; References; Twelve Views of Matroid Theory; INTRODUCTION; 1 LINEAR DEPENDENCE WITHOUT SCALARS; 2 BASIS EXCHANGE PROPERTIES; 3 GEOMETRIC LATTICES; 4 GRAPH THEORY WITHOUT VERTICES; 5 GRAPH THEORY AND LEAN LINEAR ALGEBRA; 6 VARIETIES OF FINITE MATROIDS; 7 SECRET-SHARING MATROIDS; 8 GREEDY ALGORITHMS, MATROID INTERSECTION, AND MATROID PARTITION; 9 MATRIX MULTIPLICATION AND THE CAUCHY-BINET IDENTITY; 10 BASIS GENERATING FUNCTIONS AND THE MATRIX-TREE THEOREM…”
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Entity information life cycle for big data : master data management and information integration by Talburt, John R., Zhou, Yinle, 1986-

Table of Contents: “…CLUSTER-TO-CLUSTER CLASSIFICATIONSELECTING AN APPROPRIATE ALGORITHM; CONCLUDING REMARKS; Chapter 9 -- Blocking; BLOCKING; BLOCKING BY MATCH KEY; DYNAMIC BLOCKING VERSUS PRERESOLUTION BLOCKING; BLOCKING PRECISION AND RECALL; MATCH KEY BLOCKING FOR BOOLEAN RULES; MATCH KEY BLOCKING FOR SCORING RULES; CONCLUDING REMARKS; Chapter 10 -- CSRUD for Big Data; LARGE-SCALE ER FOR MDM; THE TRANSITIVE CLOSURE PROBLEM; DISTRIBUTED, MULTIPLE-INDEX, RECORD-BASED RESOLUTION; AN ITERATIVE, NONRECURSIVE ALGORITHM FOR TRANSITIVE CLOSURE; ITERATION PHASE: SUCCESSIVE CLOSURE BY REFERENCE IDENTIFIER.…”
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Systemic Risk from Global Financial Derivatives. by Markose, Sheri M.

Table of Contents: “…FDIC FIs as Participants in the Five Financial Derivatives Markets; Tables; 1. Value and Market Share of Financial Derivatives for 202 FIs; B. Market Data Based Systemic Risk Measures and Financial Network Perspective; III. …”
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