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

Slantwise moves : games, literature, and social invention in nineteenth-century America by Guerra, Douglas

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Continuing Kepler's Quest : Assessing Air Force Space Command's Astrodynamics Standards

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Technologies for Engineering Manufacturing Systems Control in Closed Loop. by Preuße, Sebastian

Table of Contents: “…Intro; 1 Introduction; 2 Basic Principles; 2.1 Technologies for studying Behavior; 2.2 Plants; 2.3 Controllers; 2.3.1 IEC 61131-3; 2.3.2 IEC 61499-1; 2.4 System Models; 2.4.1 Syntax; 2.4.2 Semantics; 2.5 Basics of Specifications; 2.5.1 Computation Tree Logic; 2.5.2 Extended Computation Tree Logic; 2.5.3 Timed Computation Tree Logic; 2.5.4 Symbolic Timing Diagrams; 2.6 Closed-Loop Composition; 2.7 Model Checking; 2.7.1 General Remarks; 2.7.2 Model Checking Algorithm; 2.8 Summary; 3 Formal Modeling of Plant, Controller, and the Closed Loop; 3.1 Demonstration Example; 3.2 Formal Plant Modeling.…”
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Computational number theory : proceedings of the Colloquium on Computational Number Theory held at Kossuth Lajos University, Debrecen (Hungary), September 4-9, 1989

Table of Contents: “…On the solution of the diophantine equation Gn = P(x) with sieve algorithmOn Thue equations associated with certain quartic number fields; KANT -- a tool for computations in algebraic number fields; SIMATH -- a computer algebra system…”
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Visible Business : Uncover the Blindspots and Engage the World's Female Economy. by Brideson, RJ

Table of Contents: “…Blind Spots; Contents; Foreword; About the Author; Acknowledgements; To my community; To my village; Preface; Introduction; Chapter 1 From history to herstory; The birth of business marketing; Things have changed -- or have they?; Women want more; The wo-man algorithm; Become conscious of the bias; From reject to results; Chapter 2 Are you blind?…”
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Twelfth Scandinavian Conference on Artificial Intelligence : SCAI 2013

Table of Contents: “…Trap Escape for Local Search by Backtracking and Conflict ReverseIncorporating Prior Knowledge when Learning Mixtures of Truncated Basis Functions from Data; Expansion of the Variational Garrote to a Multiple Measurement Vectors Model; Classification of Movement Patterns in Skiing; Combining Constraint Types from Public Data in Aerial Image Segmentation; Formalizing Theatrical Performances Using Multi-Agent Organizations; A Hierarchical Model for Continuous Gesture Recognition Using Kinect; Expressive Planning Through Constraints…”
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Information Theory Meets Power Laws : Stochastic Processes and Language Models. by Dębowski, Łukasz Jerzy, $$d 1975- $$e author

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Parts-feeding systems for assembly : organisation, logistics and automation

Table of Contents: “…A model for kitting operations planningRobust optimization approach to production system with failure in rework and breakdown under uncertainty: evolutionary methods; Re-layout of an assembly area: a case study at Bosch Rexroth Oil Control; A simple mechanical measurement system for the posture evaluation of wing components using the PSO and ICP algorithms; Implementation framework for a fully flexible assembly system (F-FAS); A genetic algorithm for supermarket location problem; New Kanban model for tow-train feeding system design.…”
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3D face modeling, analysis and recognition by Daoudi, Mohamed, Ph. D., Srivastava, Anuj, Veltkamp, Remco C., 1963-

Table of Contents: “…3.5.4 Extension to Facial Surfaces Shape Analysis3.6 The Dense Scalar Field (DSF); 3.7 Statistical Shape Analysis; 3.7.1 Statistics on Manifolds: Karcher Mean; 3.7.2 Learning Statistical Models in Shape Space; 3.8 Applications of Statistical Shape Analysis; 3.8.1 3D Face Restoration; 3.8.2 Hierarchical Organization of Facial Shapes; 3.9 The Iso-geodesic Stripes; 3.9.1 Extraction of Facial Stripes; 3.9.2 Computing Relationships between Facial Stripes; 3.9.3 Face Representation and Matching Using Iso-geodesic Stripes; Exercises; Glossary; References.…”
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Wavelet theory approach to pattern recognition

Table of Contents: “…Comparison with other wavelets. 7.4. Algorithm and experiments -- ch. 8. Skeletonization of ribbon-like shapes with new wavelet function. 8.1. …”
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Discovering knowledge in data : an introduction to data mining by Larose, Daniel T.

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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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International e-Conference of Computer Science 2006

Table of Contents: “…A Computational Algorithm to Obtain the Law of the Solvable Lie Algebra of n x n Upper-Triangular MatricesWeb Data Extraction using Semantic Generators -- Integrity-Enhanced Improvements for ISO 9001 registeredOrganizations -- A Ghost Bit Based Finite Field Arithmetic for FPGAs -- A Scalable Finite Field Multiplier with Interleaving Reduction -- Intelligent Tutoring Systems and Convex Geometries -- Towards Operational Content Infrastructure -- A Computational Fusion of Wavelets and Neural Networks in a Classifier for Biomedical Applications…”
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STAIRS 2010 : Proceedings of the Fifth Starting AI Researchers' Symposium. by Ågotnes, Thomas

Table of Contents: “…; Generative Structure Learning for Markov Logic Networks; Learning Fuzzy Models of User Interests in a Semantic Information Retrieval System; Ontology-Based Document and Query Representation May Improve the Effectiveness of Information Retrieval.…”
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Literature and encyclopedism in Enlightenment Britain : the pursuit of complete knowledge by Rudy, Seth, 1978-

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Optimization of Observation and Control Processes. by Malyshev, V. V.

Table of Contents: “…Optimization of Informational Noise When Observing a Dynamic Object""; ""4.6. Example of Observing a Maneuvering Object""; ""Chapter 5. …”
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The Finite Element Method : a Practical Course. by Liu, G. R.

Table of Contents: “…3.4.3.3 On other means of construct shape functions3.4.4 Properties of the shape functions; 3.4.5 Formulation of finite element equations in local coordinate system; 3.4.6 Coordinate transformation; 3.4.7 Assembly of global FE equation; 3.4.8 Imposition of displacement constraints; 3.4.9 Solving the global FE equation; 3.5 Static analysis; 3.6 Analysis of free vibration (eigenvalue analysis); 3.7 Transient response; 3.7.1 Central difference algorithm; 3.7.2 Newmark's method (Newmark, 1959); 3.8 Remarks; 3.8.1 Summary of shape function properties.…”
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Machine learning for the web by Isoni, Andrea

Table of Contents: “…Multinomial Naive BayesGaussian Naive Bayes; Decision trees; Support vector machine; Kernel trick; A comparison of methods; Regression problem; Classification problem; Hidden Markov model; A Python example; Summary; Web Mining Techniques; Web structure mining; Web crawlers (or spiders); Indexer; Ranking -- PageRank algorithm; Web content mining; Parsing; Natural language processing; Information retrieval models; TF-IDF; Latent Semantic Analysis (LSA); Doc2Vec (word2vec); Word2vec -- continuous bag of words and skip-gram architectures; Mathematical description of the CBOW model.…”
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Data mining techniques : for marketing, sales, and customer relationship management by Berry, Michael J. A.

Table of Contents: “…-- The virtuous cycle of data mining -- Data mining methodology and best practices -- Data mining applications in marketing and customer relationship management -- The lure of statistics : data mining using familiar tools -- Decision trees -- Artificial neural networks -- Nearest neighbor approaches : memory-based reasoning and collaborative filtering -- Market basket analysis and association rules -- Link analysis -- Automatic cluster detection -- Knowing when to worry : hazard functions and survival analysis in marketing -- Genetic algorithms -- Data mining throughout the customer life cycle -- Data warehousing, OLAP, and data mining -- Building the data mining environment -- Preparing data for mining -- Putting data mining to work.…”
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Explorations in Computing : an Introduction to Computer Science. by Conery, John S.

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