Search Results - (((((((want OR wiant) OR santis) OR when) OR cantor) OR anne) OR shape) OR hints) algorithms.

  1. 141
  2. 142

    Data Analytics in Bioinformatics : A Machine Learning Perspective. by Satpathy, Rabinarayan

    Published 2021
    Table of Contents: “…3.4.1 Comparative Analysis of ANN With Broadly Used Traditional ML Algorithms -- 3.5 Critical Analysis -- 3.6 Conclusion -- References -- Part 2: MACHINE LEARNING AND GENOMIC TECHNOLOGY, FEATURE SELECTION AND DIMENSIONALITY REDUCTION -- 4 Dimensionality Reduction Techniques: Principles, Benefits, and Limitations -- 4.1 Introduction -- 4.2 The Benefits and Limitations of Dimension Reduction Methods -- 4.3 Components of Dimension Reduction -- 4.3.1 Feature Selection -- 4.3.2 Feature Reduction -- 4.4 Methods of Dimensionality Reduction -- 4.4.1 Principal Component Analysis (PCA)…”
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  3. 143

    Handbook of Computational Geometry. by Sack, J. R.

    Published 1999
    Table of Contents: “…Arrangements and their applications; Chapter 3. Discrete geometric shapes: Matching, interpolation, and approximation; Chapter 4. …”
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  4. 144

    The NURBS Book by Piegl, Les

    Published 1997
    Table of Contents: “…One Curve and Surface Basics -- 1.1 Implicit and Parametric Forms -- 1.2 Power Basis Form of a Curve -- 1.3 Bézier Curves -- 1.4 Rational Bézier Curves -- 1.5 Tensor Product Surfaces -- Exercises -- Two B-Spline Basis Functions -- 2.1 Introduction -- 2.2 Definition and Properties of B-spline Basis Functions -- 2.3 Derivatives of B-spline Basis Functions -- 2.4 Further Properties of the Basis Functions -- 2.5 Computational Algorithms -- Exercises -- Three B-spline Curves and Surfaces -- 3.1 Introduction -- 3.2 The Definition and Properties of B-spline Curves -- 3.3 The Derivatives of a B-spline Curve -- 3.4 Definition and Properties of B-spline Surfaces -- 3.5 Derivatives of a B-spline Surface -- Exercises -- Four Rational B-spline Curves and Surfaces -- 4.1 Introduction -- 4.2 Definition and Properties of NURBS Curves -- 4.3 Derivatives of a NURBS Curve -- 4.4 Definition and Properties of NURBS Surfaces -- 4.5 Derivatives of a NURBS Surface -- Exercises -- Five Fundamental Geometric Algorithms -- 5.1 Introduction -- 5.2 Knot Insertion -- 5.3 Knot Refinement -- 5.4 Knot Removal -- 5.5 Degree Elevation -- 5.6 Degree Reduction -- Exercises -- Six Advanced Geometric Algorithms -- 6.1 Point Inversion and Projection for Curves and Surfaces -- 6.2 Surface Tangent Vector Inversion -- 6.3 Transformations and Projections of Curves and Surfaces -- 6.4 Reparameterization of NURBS Curves and Surfaces -- 6.5 Curve and Surface Reversal -- 6.6 Conversion Between B-spline and Piecewise Power Basis Forms -- Exercises -- Seven Conics and Circles -- 7.1 Introduction -- 7.2 Various Forms for Representing Conics -- 7.3 The Quadratic Rational Bézier Arc -- 7.4 Infinite Control Points -- 7.5 Construction of Circles -- 7.6 Construction of Conies -- 7.7 Conic Type Classification and Form Conversion -- 7.8 Higher Order Circles -- Exercises -- Eight Construction of Common Surfaces -- 8.1 Introduction -- 8.2 Bilinear Surfaces -- 8.3 The General Cylinder -- 8.4 The Ruled Surface -- 8.5 The Surface of Revolution -- 8.6 Nonuniform Scaling of Surfaces -- 8.7 A Three-sided Spherical Surface -- Nine Curve and Surface Fitting -- 9.1 Introduction -- 9.2 Global Interpolation -- 9.3 Local Interpolation -- 9.4 Global Approximation -- 9.5 Local Approximation -- Exercises -- Ten Advanced Surface Construction Techniques -- 10.1 Introduction -- 10.2 Swung Surfaces -- 10.3 Skinned Surfaces -- 10.4 Swept Surfaces -- 10.5 Interpolation of a Bidirectional Curve Network -- 10.6 Coons Surfaces -- Eleven Shape Modification Tools -- 11.1 Introduction -- 11.2 Control Point Repositioning -- 11.3 Weight Modification -- 11.4 Shape Operators -- 11.5 Constraint-based Curve and Surface Shaping -- Twelve Standards and Data Exchange -- 12.1 Introduction -- 12.2 Knot Vectors -- 12.3 Nurbs Within the Standards -- 12.4 Data Exchange to and from a NURBS System -- Thirteen B-spline Programming Concepts -- 13.1 Introduction -- 13.2 Data Types and Portability -- 13.3 Data Structures -- 13.4 Memory Allocation -- 13.5 Error Control -- 13.6 Utility Routines -- 13.7 Arithmetic Routines -- 13.8 Example Programs -- 13.9 Additional Structures -- 13.10 System Structure -- References.…”
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  5. 145
  6. 146

    Machine Learning for Mobile : Practical Guide to Building Intelligent Mobile Applications Powered by Machine Learning. by Gopalakrishnan, Revathi

    Published 2018
    Table of Contents: “…Chapter 2: Supervised and Unsupervised Learning AlgorithmsIntroduction to supervised learning algorithms; Deep dive into supervised learning algorithms; Naive Bayes; Decision trees; Linear regression; Logistic regression; Support vector machines; Random forest; Introduction to unsupervised learning algorithms; Deep dive into unsupervised learning algorithms; Clustering algorithms; Clustering methods; Hierarchical agglomerative clustering methods; K-means clustering; Association rule learning algorithm; Summary; References; Chapter 3: Random Forest on iOS; Introduction to algorithms…”
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  7. 147

    Can markets compute equilibria? by Monroe, Hunter K.

    Published 2009
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  8. 148

    Agent-based computing

    Published 2010
    Table of Contents: “…Analysis of Algorithm -- 2.1.1. Chain-Like Agent Structure -- 2.1.2. …”
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  12. 152

    Urodynamics : a quick pocket guide by Vignoli, Giancarlo

    Published 2016
    Table of Contents: “…The framework of basic science -- Key symptoms analysis and diagnostic algorithms -- Physical examination and laboratory evaluation -- Urodynamic testing: when and which -- Voiding diary and Pad testing -- Non-invasive urodynamics -- Conventional urodynamics-conventional urodynamics in pediatric age -- Electromyogtrahy -- Urethral profilometry -- Videourodynamics -- Ambulatory urodynamics -- Urodynamics of upper urinary tract.…”
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  13. 153

    Mount Sinai expert guides. Hepatology

    Published 2014
    Table of Contents: “…Cover; Title page; Copyright page; Contents; List of Contributors; Series Foreword; Preface; Abbreviation List; About the Companion Website; PART 1: Hepatology; CHAPTER 1: Approach to the Patient with Abnormal Liver Tests; Section 1: Background; Definition of disease; Disease classification; Etiology; Pathology/pathogenesis; Section 2: Prevention; Section 3: Diagnosis; Typical presentation; Clinical diagnosis; Laboratory diagnosis; Diagnostic algorithm; Potential pitfalls/common errors made regarding diagnosis of disease; Section 4: Treatment; When to hospitalize…”
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  14. 154

    Building Machine Learning Systems with Python. by Richert, Willi

    Published 2013
    Table of Contents: “…Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Getting Started with Python Machine Learning; Machine learning and Python -- the dream team; What the book will teach you (and what it will not); What to do when you are stuck; Getting started; Introduction to NumPy, SciPy, and Matplotlib; Installing Python; Chewing data efficiently with NumPy and intelligently with SciPy; Learning NumPy; Indexing; Handling non-existing values; Comparing runtime behaviors; Learning SciPy; Our first (tiny) machine learning application.…”
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  15. 155

    Applied modelling, numerical simulation, computation and optimization. by De Souza Neto, Eduardo

    Published 2017
    Table of Contents: “…Modeling and control of an unbalanced magnetic rotor-bearing system asa bearingless motorNumerical simulation of the influence of particle shape on the mechanical properties of rockfill materials; Heat dissipation analysis of continuously-moving plate undergoing thermal processing using Laplace Adomian decomposition method; A shortcut algorithm for solving long-term conjugate heat transfer problems based on quasi-steady flow; Identification of plastic anisotropy using spherical indentation on different anisotropic yield criterions.…”
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  16. 156

    Firewall design and analysis by Liu, Alex X.

    Published 2011
    Table of Contents: “…Diverse firewall design. 3.1. Construction algorithm. 3.2. Shaping algorithm. 3.3. Comparison algorithm. 3.4. …”
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  17. 157

    Future Farming. by Shukla, Praveen Kumar

    Published 2023
    Table of Contents: “…PROPOSED METHODOLOGY -- Pre-processing -- Leaf Image from Plants -- Segmentation Model Using Improved Canny Algorithm -- Steps of Improved Canny Algorithm -- Leaf Image Feature Selection Using Hybrid Black Widow Optimization Algorithm with Mayfly Optimization Algorithm (BWO-MA) -- Pseudo-Code of the Hybrid (BWO-MA) Algorithm -- Output: Objective Function's -RMSE -- Leaf Image Classification Using (BWO-MA) with ANN -- Hyper-Parameter Tuning With (BWO-MA) -- RESULT AND DISCUSSION -- Dataset Description -- Evaluation & Results -- CONCLUSION -- REFERENCES…”
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  18. 158

    Rough fuzzy image analysis : foundations and methodologies

    Published 2010
    Table of Contents: “…1. Cantor, fuzzy, near, and rough sets in image analysis / James F. …”
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  19. 159

    Digital holography by Picart, Pascal

    Published 2012
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  20. 160

    Uniqueness questions in reconstruction of multidimensional objects from tomography-type projection data by Golubyatnikov, V. P. (Vladimir P.)

    Published 2000
    Table of Contents: “…Stability estimates for recovering the shapes of convex bodies from the shapes of their projections -- Chapter 3. …”
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