Search Results - (((((((want OR when) OR semantic) OR arts) OR cantor) OR anne) OR maarten) OR santis) algorithms.

3D Shape Analysis : Fundamentals, Theory and Applications. by Tabia, Hedi

Table of Contents: “…7.2 Problem Formulation7.3 Mathematical Tools; 7.4 Isometric Correspondence and Registration; 7.5 Nonisometric (Elastic) Correspondence and Registration; 7.6 Summary and Further Reading; 8 Semantic Correspondences; 8.1 Introduction; 8.2 Mathematical Formulation; 8.3 Graph Representation; 8.4 Energy Functions for Semantic Labeling; 8.5 Semantic Labeling; 8.6 Examples; 8.7 Summary and Further Reading; Part IV: Applications; 9 Examples of 3D Semantic Applications; 9.1 Introduction; 9.2 Semantics: Shape or Status; 9.3 Semantics: Class or Identity; 9.4 Semantics: Behavior; 9.5 Semantics: Position…”
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Papers from the first European Workshop on Technological & Security Issues in Digital Rights Management (EuDiRights '06)

Table of Contents: “…Cover; CONTENTS; EDITORIAL ADVISORY BOARD; The digital information war; Complementing DRM with digital watermarking: mark, search, retrieve; A class of non-linear asymptotic fingerprinting codes with 1-error; Verification algorithms for governed use of multimedia content; Toward semantics-aware management of intellectual property rights; DRM, law and technology: an American perspective; Clustering search results. …”
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Creating wicked students : designing courses for a complex world by Hanstedt, Paul, 1965-

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What Every Teacher Should Know About Effective Teaching Strategies. by Tileston, Donna E. Walker

Table of Contents: “…-- Why the Way We Teach is Important -- The Linguistic Modality -- The Nonlinguistic Modality -- The Affective Modality -- Semantic Memory -- Episodic Memory -- Procedural Memory -- Automatic Memory -- Emotional Memory -- Chapter 2 -- Choosing Effective Teaching Strategies for Beginning Activities -- Great Beginnings -- The Self-System…”
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Numerical linear algebra with applications : using MATLAB by Ford, William H.

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

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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Cybernetic Intelligence

Table of Contents: “…Editorial advisory board; Preface; Editorial; Second-order cybernetics and enactive perception; Semantic category theory cognition and conceptual reference; Bipolar logic and probabilistic interpretation; Cooperative clans; Future reasoning machines: mind and body; Machine vision methods for autonomous micro-robotic systems; Optimisation enhancement using self-organising fuzzy control; Intelligent agents and distributed models for cooperative task support; Landscape classification and problem specific reasoning for genetic algorithms; Business cybernetics: a provocative suggestion.…”
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Modeling and optimization of air traffic by Delahaye, Daniel

Table of Contents: “…pt. 1: Optimization and artificial evolution -- Optimization: State of the art -- Genetic algorithms and improvements -- A new concept for genetic algorithms based on order statistics -- pt. 2: Applications to air traffic control -- Air traffic control -- Contributions to airspace sectorization -- Contribution to traffic assignment -- Airspace congestion metrics -- Conclusion and future perspectives.…”
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Metaheuristic applications in structures and infrastructures

Table of Contents: “…Metaheuristic Algorithms in Modeling and Optimization -- A Review on Traditional and Modern Structural Optimization: Problems and Techniques -- Particle Swarm Optimization in Civil Infrastructure Systems: State-of-the-Art Review -- Evolution Strategies-Based Metaheuristics in Structural Design Optimization -- Multidisciplinary Design and Optimization Methods -- Cost Optimization of Column Layout Design of Reinforced Concrete Buildings -- Layout Design of Beam-Slab Floors by a Genetic Algorithm -- Optimum Design of Skeletal Structures via Big Bang-Big Crunch Algorithm -- Truss Weight Minimization Using Hybrid Harmony Search and Big Bang-Big Crunch Algorithms -- Graph Theory in Evolutionary Truss Design Optimization -- Element Exchange Method for Stochastic Topology Optimization -- Evolutionary Path-Dependent Damper Optimization for Variable Building Stiffness Distributions -- Application of Genetic Algorithms in Ground Motion Selection for Seismic Analysis -- Optimization of Tuned Mass Damper with Harmony Search -- Identification of Passive Devices for Vibration Control by Evolutionary Algorithms -- Structural Optimization for Frequency Constraints -- Optimum Performance-Based Seismic Design of Frames Using Metaheuristic Optimization Algorithms -- Expression Programming Techniques for Formulation of Structural Engineering Systems -- An Evolutionary Divide-and-Conquer Strategy for Structural Identification -- Swarm Intelligence for Large-Scale Optimization in Construction Management -- Network-Level Infrastructure Management Based on Metaheuristics -- Large-Scale Maintenance Optimization Problems for Civil Infrastructure Systems -- Metaheuristic Applications in Bridge Infrastructure Maintenance Scheduling Considering Stochastic Aspects of Deterioration.…”
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Machine Learning for Mobile : Practical Guide to Building Intelligent Mobile Applications Powered by Machine Learning. by Gopalakrishnan, Revathi

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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Language engineering for lesser-studied languages

Table of Contents: “…Derzhanski -- Computational morphology for lesser-studied languages / Kemal Olfazer -- Practical syntastic processing of flexible word order languages with dynamic syntax / David Tugwell -- Computation field semantics : acquiring an ontological-semantic lexicon for a new language / Sergei Nirenburg and Marjorie McShane -- Applying machine translation for low- and middle-density languages / Stella Markantonatou [and others] -- Language resources for semitic languages : challenges and solutions / Shuly Wintner -- Low-density language strategies for Persian and Armenian / Karine Megerdoomian.…”
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Theory of information : fundamentality, diversity and unification by Burgin, M. S. (Mark Semenovich)

Table of Contents: “…Algorithmic information theory based on recursive algorithms : recursive approach. 5.3. …”
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Can markets compute equilibria? by Monroe, Hunter K.

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Agent-based computing

Table of Contents: “…Analysis of Algorithm -- 2.1.1. Chain-Like Agent Structure -- 2.1.2. …”
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A companion to rhetoric and rhetorical criticism

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Python unlocked : become more fluent in Python--learn strategies and techniques for smart and high-performance Python programming by Tigeraniya, Arun

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Sharing economy and big data analytics by Sedkaoui, Soraya, Khelfaoui, Mounia

Table of Contents: “…Not Without Big Data Algorithms. Linear Regression -- Classification Algorithms -- Cluster Analysis -- Conclusion -- References -- Index -- Other titles from iSTE in Information Systems, Web and Pervasive Computing.…”
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Urodynamics : a quick pocket guide by Vignoli, Giancarlo

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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Mount Sinai expert guides. Hepatology

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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Building Machine Learning Systems with Python. by Richert, Willi

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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