Search Results - (((((((kant OR wantsa) OR semantic) OR when) OR cantor) OR anne) OR shape) OR hints) algorithms.

Selected papers from the 11th international symposium on electromagnetics fields in electrical engineering ISEF 2003 by Wiak, S.

Table of Contents: “…Editorial advisory board; Abstracts; Editorial; Application of Haar's wavelets in the method of moments to solve electrostatic problems; A 3D multimodal FDTD algorithm for electromagnetic and acoustic propagation in curved waveguides and bent ducts of varying cross-section; The highly efficient three-phase small induction motors with stator cores made from amorphous iron; Optimal shape design of a high-voltage test arrangement; Cogging torque calculation considering magnetic anisotropy for permanent magnet synchronous motors; Magnetoelastic coupling and Rayleigh damping…”
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Automata and Computability. by Kozen, Dexter, 1951-

Table of Contents: “…Miscellaneous Exercises Turing Machines and Effective ComputabilityHints for Selected Miscellaneous Exercises; Solutions to Selected Miscellaneous Exercises; References; Notation and Abbreviations; Index.…”
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Windows 2000 Graphics API Black Book. by Chandler, Damon

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Biomechanics : optimization, uncertainties and reliability by Kharmanda, Ghias, El Hami, Abdelkhalak

Table of Contents: “…Sizing optimization; 1.4. Shape optimization; 1.5. Topology optimization; 1.6. …”
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Data and Application Security : Developments and Directions by Thuraisingham, Bhavani M.

Table of Contents: “…Protecting Information when Access is Granted for Collaboration -- Author-?…”
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Learning-based local visual representation and indexing by Rongrong, Ji, Yao, Hongxun, Gao, Yue, Duan, Ling-Yu, Dai, Qionghai

Table of Contents: “…3.4.1 Cross-database Case3.4.2 Incremental Transfer; 3.5 Experiments; 3.5.1 Quantitative results; 3.6 Summary; Chapter 4: Supervised Dictionary Learning via Semantic Embedding ; 4.1 Introduction; 4.2 Semantic Labeling Propagation; 4.2.1 Density Diversity Estimation ; 4.3 Supervised Dictionary Learning; 4.3.1 Generative Modeling ; 4.3.2 Supervised Quantization ; 4.4 Experiments; 4.4.1 Database and Evaluations; 4.4.2 Quantitative Results; 4.5 Summary; Chapter 5: Visual Pattern Mining; 5.1 Introduction; 5.2 Discriminative 3D Pattern Mining; 5.2.1 The Proposed Mining Scheme.…”
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Constraint Solving over Multi-valued Logics : Application to Digital Circuits.

Table of Contents: “…-- 3.2 Test Generation -- 3.3 TG Modelling Approaches and Algorithms.…”
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Media Backends : Digital Infrastructures and Sociotechnical Relations. by Parks, Lisa

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New developments in lasers and electro-optics research

Table of Contents: “…Cho -- Shape detection by means of a laser line and approximation neural networks / J. …”
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Digital workflows in architecture : designing design -- designing assembly -- designing industry

Table of Contents: “…DIGITAL CRAFTSMANSHIP: FROM THINKING TO MODELING TO BUILDINGWireframe Algorithms (Editor's Notes); ALGORITHMIC WORKFLOWS IN ASSOCIATIVE MODELING; Workflow Teams (Editor's Notes); WORKFLOW CONSULTANCY; THE SCENT OF THE SYSTEM; indeterminacy (Editor's Notes); DESIGNING INDUSTRY; WHAT DO WE MEAN BY BUILDING DESIGN?…”
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Essential US for trauma : E-FAST

Table of Contents: “…Foreword -- Preface -- 1 Basic physics, instrumentation and knobology -- 2 E-FAST protocol: Introduction and focused questions -- 3 Abdominal views: Anatomy, Techniques, Scanning tips and tricks, abnormal images -- 4Thoracic views: Anatomy, Techniques, Scanning Tips and Tricks, Abnormal Images -- 5Including EFAST in Trauma Algorithm: When? What to do next? -- 6 The role of EFAST in Comprehensive US Trauma Management (ABCDE-US) Facing Clinical Scenarios -- 7 Pre-Hospital US in Trauma: Role and Tips -- 8CEUS-FAST: What is it?…”
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Vision Geometry. by Melter, Robert A.

Table of Contents: “…Star-Shapedness of Digitized Planar ShapesAlgorithms for the Decomposition of Convex Polygons -- Decomposition of Discrete Curves into Piecewise Straight Segments in Linear Time -- Digitization Schemes and the Recognition of Digital Straight Lines, Hyperplanes, and Flats in Arbitrary Dimensions -- Computational Geometry and Computer Vision -- Convexity, Visibility, and Orthogonal Polygons…”
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Big Data, IoT, and Machine Learning : Tools and Applications. by Agrawal, Rashmi

Table of Contents: “…Chapter 3 Reviews Analysis of Apple Store Applications Using Supervised Machine Learning -- 3.1 Introduction -- 3.2 Literature Review -- 3.2.1 Machine Learning Algorithms -- 3.2.2 Feature Extraction Algorithms -- 3.3 Proposed Methodology -- 3.3.1 Data Collection -- 3.3.2 Feature Extraction -- 3.3.3 Data Analysis and Sentiment Analysis -- Text Processing -- 3.3.4 Text Normalisation -- 3.4 Feature Extraction Algorithm -- 3.4.1 CountVectorizer -- 3.4.2 TfidfVectorizer (TF-IDF) -- 3.5 Supervised ML Classification -- 3.6 Experiment Design -- 3.7 Experimental Results and Analysis…”
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Principles of artificial neural networks by Graupe, Daniel

Table of Contents: “…Fundamentals of biological neural networks -- ch. 3. Basic principles of ANNs and their early structures. 3.1. Basic principles of ANN design. 3.2. …”
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Function Estimates. by Marron, J. S.

Table of Contents: “…Contents -- Preface -- Logspline density estimation -- Statistical encounters with B-splines -- Estimation of a transfer function in a nongaussian context -- Evaluating the performance of an inversion algorithm -- Harmonic splines in geomagnetism -- Problems in estimating the anomalous gravity potential of the earth from discrete data -- What regression model should be chosen when the statistician misspecifies the error distribution? …”
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The silicon jungle : a novel of deception, power, and Internet intrigue by Baluja, Shumeet, 1971-

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Knowledge discovery for business information systems

Table of Contents: “…Problem Description -- 3. The FUP Algorithm for the Insertion Only Case -- 4. The FUP Algorithm for the Deletions Only Case -- 5. …”
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Introduction to graph theory by Voloshin, Vitaly I. (Vitaly Ivanovich), 1954-

Table of Contents: “…What Is Mathematical Induction; 7.2. Graph Theory Algorithms and Their Complexity; 7.3. Answers and Hints to Selected Exercises; 7.4. …”
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In silico dreams : how artificial intelligence and biotechnology will create the medicines of the future by Hilbush, Brian

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Advanced Artificial Intelligence.

Table of Contents: “…Applications of temporal and spatial logic; 4.7.4. Randell algorithm; Exercises; Chapter 5 Case-Based Reasoning; 5.1 Overview; 5.2 Basic Notations; 5.3 Process Model; 5.4 Case Representation; 5.4.1 Semantic Memory Unit; 5.4.2 Memory Network; 5.5 Case Indexing; 5.6 Case Retrieval; 5.7 Similarity Relations in CBR; 5.7.1 Semantic similarity; 5.7.2 Structural similarity; 5.7.3 Goal's features; 5.7.4 Individual similarity; 5.7.5 Similarity assessment; 5.8 Case Reuse; 5.9 Case Retainion; 5.10 Instance-Based Learning.…”
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