Search Results - (((((((want OR dient) OR semantic) OR win) OR cantor) OR anne) OR shape) OR hints) algorithms.

OIPE 2012

Table of Contents: “…Optimization of EMI filters for electrical drives in aircraftAdaptive level set method for accurate boundary shape in optimization of electromagnetic systems; Amodified immune algorithm with spatial filtering for multiobjective topology optimisation of electromagnetic devices; Use of compensation theorem for the robustness assessment of electromagnetic devices optimal design; Multi-physics optimisation of an energy harvester device for automotive application; Stochastic modeling error reduction using Bayesian approach coupled with an adaptive Kriging-based model.…”
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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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Artificial Intelligence and Machine Learning Fundamentals : Develop Real-World Applications Powered by the Latest AI Advances. by Nagy, Zsolt

Table of Contents: “…Optimizing the Minmax Algorithm with Alpha-Beta PruningDRYing up the Minmax Algorithm -- The NegaMax Algorithm; Using the EasyAI Library; Activity 4: Connect Four; Summary; Regression; Introduction; Linear Regression with One Variable; What Is Regression?…”
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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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Handbook of Computational Geometry. by Sack, J. R.

Table of Contents: “…Arrangements and their applications; Chapter 3. Discrete geometric shapes: Matching, interpolation, and approximation; Chapter 4. …”
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The NURBS Book by Piegl, Les

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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Nonlinear Optimization of Vehicle Safety Structures : Modeling of Structures Subjected to Large Deformations. by Christensen, Jesper

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Code halos : how the digital lives of people, things, and organizations are changing the rules of business by Frank, Malcolm

Table of Contents: “…The "Skinterface" Will Change the Consumer ExperienceIndustrial Amplifiers: Harnessing the Power of the Internet of Things; Smart Appliances Become Amplifiers in the Home; The Application Interface: Window to a Beautiful Experience; The Algorithm: Data Becomes Meaning; Facebook's EdgeRank Algorithm Makes It Personal; Successful Algorithms Power Code Connections and Create Insight; All Data, Great and Small; Netflix Lassos Data to Win in the Market; New Business Models Showcase Code Halo Value; Why Didn't They Tune in the Zune?…”
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Media technologies : essays on communication, materiality, and society

Table of Contents: “…Bowker -- "What Do We Want?" "Materiality!" "When Do We Want It?" "Now!" …”
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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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Applied modelling, numerical simulation, computation and optimization. by De Souza Neto, Eduardo

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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Firewall design and analysis by Liu, Alex X.

Table of Contents: “…Diverse firewall design. 3.1. Construction algorithm. 3.2. Shaping algorithm. 3.3. Comparison algorithm. 3.4. …”
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Stairs 2006 : Proceedings of the Third Starting AI Researchers' Symposium

Table of Contents: “…A Comparison of Two Machine-Learning Techniques to Focus the Diagnosis TaskArgumentation Semantics for Temporal Defeasible Logic; NEWPAR: An Optimized Feature Selection and Weighting Schema for Category Ranking; Challenges and Solutions for Hierarchical Task Network Planning in E-Learning; Invited Talks; Artificial Intelligence and Unmanned Aerial Vehicles; Writing a Good Grant Proposal; Author Index…”
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Future Farming. by Shukla, Praveen Kumar

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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Rough fuzzy image analysis : foundations and methodologies

Table of Contents: “…1. Cantor, fuzzy, near, and rough sets in image analysis / James F. …”
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Digital holography by Picart, Pascal

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Learning Boost C++ libraries : solve practical programming problems using powerful, portable, and expressive libraries from Boost by Mukherjee, Arindam

Table of Contents: “…Shared ownership semanticsboost::shared_ptr and std::shared_ptr; Intrusive smart pointers -- boost::intrusive_ptr; shared_array; Managing non-memory resources using smart pointers; Self-test questions; Summary; References; Chapter 4: Working with Strings; Text processing with Boost String Algorithms library; Using Boost String Algorithms; Find algorithms; Case-conversion and trimming algorithms; The replace and erase algorithms; The split and join algorithms; Splitting text using the Boost Tokenizer library; Tokenizing based on separators…”
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Handbook of Modal Logic. by Blackburn, Patrick

Table of Contents: “…13 Quantified Modal Logic13.1 Syntax and Semantics; 13.2 Constant Domain Tableaus; 13.3 Soundness and Completeness; 13.4 Variations; 14 Conclusion; Bibliography; Chapter 3 Complexity of Modal Logic; 1 Introduction; 1.1 Examples of decision problems in modal logic; 1.2 A simple and a hard problem; 1.3 The model checking problem; 1.4 The consequence problem; 1.5 A tiling logic; 2 Decision algorithms; 2.1 Selection of points; 2.2 Filtration; 2.3 Hintikka set elimination; 2.4 Hintikka set elimination without constraints; 2.5 Forcing exponentially deep paths; 2.6 Tree automata; 2.7 Pseudo-models.…”
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Uniqueness questions in reconstruction of multidimensional objects from tomography-type projection data by Golubyatnikov, V. P. (Vladimir P.)

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