Search Results - (((((((ant OR mantis) OR antiii) OR granting) OR cantor) OR anne) OR shape) OR hints) algorithms.

Data and Application Security : Developments and Directions by Thuraisingham, Bhavani M.

Table of Contents: “…Protecting Information when Access is Granted for Collaboration -- Author-?: A Java-Based System For XML Data Protection -- A Fair-Exchange E-Commerce Protocol With Automated Dispute Resolution -- XML Access Control Systems: A Component-Based Approach -- A Configurable Security Architecture Prototype -- Distributed Policies for Data Management -- Making Policies Mobile -- Security Architecture of The Multimedia Mediator -- Simulation And Analysis of Cryptographic Protocols -- Authentic Third-Party Data Publication -- Protecting File Systems Against Corruption Using Checksums -- Web Security and Privacy -- Coordinating Policy for Federated Applications -- Integrating Multilevel Security Policies in Multilevel Federated Database Systems -- Wrappers -- A Mechanism to Support State-Based Authorization in Web Applications -- An Integrated Framework for Database Privacy Protection -- Discovery of Multi-Level Security Policies -- Protecting Deductive Databases from Unauthorized Retrievals -- Confidentiality vs Integrity in Secure Databases -- Extending SQL's Grant Operation to Limit Privileges -- Language Extensions for Programmable Security -- Protecting Privacy from Continuous High-Resolution Satellite Surveillance -- Database Security Integration Using Role-Based Access Control -- User Role-Based Security Model for a Distributed Environment -- WorkFlow Analyzed for Security and Privacy in using Databases -- Identifying Security Holes in OLAP Applications -- Algorithms and Experience in Increasing the Intelligibility and Hygiene of Access Control in Large Organizations -- Database Security 2000 -- Declarative Semantics of Belief Queries in Mls Deductive Databases -- Trust Management in Distributed Databases -- Active Authorization as High-level Control -- Conference Key Agreement Protocol using Oblivious Transfer -- An Integration Model of Role-Based Access Control and Activity-Based Access Control Using Task -- Authorization Model in Object-Oriented Systems -- Panel 2 -- Conference Summary.…”
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Applied mechatronics and android robotics : selected, peer reviewed papers from the International Conference on Applied Mechatronics and Android Robotics (ICAMAR 2013), July 13-14,...

Table of Contents: “…Applied Mechatronics and Android Robotics; Preface, Committees and Sponsors; Table of Contents; Chapter 1: Robot Design, Motion Planning and Robot Control; Design of a Master Manipulator with Dynamical Simplification for Master-Slave Robot; Parameter Self-Adjusting Path Tracking Algorithm of Mobile Robots; Global Path Planning for Mobile Robot Based on Improved Ant Colony Algorithms; A Study of Robot Platform Based on WiFi Remote Control; Fire Detection System Based-On Mobile Robots; Phase Plane Analysis of Battery Series Balancing on Robot…”
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Deep Learning Quick Reference : Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras. by Bernico, Michael

Table of Contents: “…Drawbacks to consider when using a neural network for regressionUsing deep neural networks for regression; How to plan a machine learning problem; Defining our example problem; Loading the dataset; Defining our cost function; Building an MLP in Keras; Input layer shape; Hidden layer shape; Output layer shape; Neural network architecture; Training the Keras model; Measuring the performance of our model; Building a deep neural network in Keras; Measuring the deep neural network performance; Tuning the model hyperparameters; Saving and loading a trained Keras model; Summary.…”
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Comorbidity in migraine

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

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Solutions in lidar profiling of the atmosphere by Kovalev, Vladimir A.

Table of Contents: “…1.6.1 Algorithm and Solution Uncertainty1.6.2 Numerical Simulations and Experimental Data; 1.7 Examination of the Remaining Offset in the Backscatter Signal by~Analyzing the Shape of the Integrated Signal; 1.8 Issues in the Examination of the Lidar Overlap Function; 1.8.1 Influence of Distortions in the Lidar Signal when Determining the~Overlap Function; 1.8.2 Issues of Lidar Signal Inversion within the Incomplete Overlap Area; Chapter 2 Essentials and Issues in Separating the Backscatter and Transmission Terms in The Lidar Equation.…”
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Computational intelligence in aerospace sciences

Table of Contents: “…Guenov, Mrco Nunez, Arturo Molina-Cristóbal, Vis Sripawadkul, varun Datta and Atif Riaz ; Surrogate modeling in the service of multidisciplinary design / Stephen Powell and András Sóbester ; Multidisciplinary design optimization of aerospace transportation systems / Edmondo Minisci and Massimilliano Vasile -- Aerodynamics optimization: Aerodynamic shape design using evolutionary computation : a tutorial with examples and case studies / Domenico Quagliarella ; Multiobjective design optimization using Nash games / Jean-Antoine Désidéri and Régis Duvigneau ; Design rule extraction using multiobjective design exploration / Shigeru Obayashi -- Space trajectory design: Automated interplanetary mission planning / Jacob Englander and Bruce Conway ; On the global optimization of multigravity assist trajectories with evolutionary algorithms / Massimilliano Vasile and Edmondo Minisci, Marco Locatelli ; An incremental algorithm for the optimization of multiple gravity assist trajectories / Massimilliano Vasile, Matteo Ceriotti, Victor M. …”
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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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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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Advances in digital technologies : proceedings of the 6th International Conference on Applications of Digital Information and Web Technologies 2015

Table of Contents: “…Application of Genetic Algorithms to Context-Sensitive Text MiningA Decision Tree Classification Model for Determining the Location for Solar Power Plant; A Framework for Multi-Label Learning Using Label Ranking and Correlation; A Comparative Analysis of Pruning Methods for C4.5 and Fuzzy C4.5; Subject Index; Author Index.…”
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An introduction to computational engineering with Matlab by Yang, Xin-She

Table of Contents: “…Optimization in Engineering -- 12.1 Introduction -- 12.2 Bioinspired Algorithms -- 12.2.1 Genetic Algorithms -- 12.2.2 Neural Networks…”
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Java Deep Learning Projects : Implement 10 Real-World Deep Learning Applications Using Deeplearning4j and Open Source APIs. by Karim, Rezaul

Table of Contents: “…; Artificial Neural Networks; Biological neurons; A brief history of ANNs; How does an ANN learn?; ANNs and the backpropagation algorithm; Forward and backward passes; Weights and biases; Weight optimization; Activation functions.…”
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Optimization advances in electric power systems

Table of Contents: “…Unreliability Costs -- 3.5. Proposed Algorithms -- 3.5.1. ES and TS Algorithms -- 3.5.2. …”
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Integrated and collaborative product development environment : technologies and implementations by Li, W. D.

Table of Contents: “…Intelligent Optimisation of Process Planning; 5.1 Intelligent Optimisation Strategies for CAPP Systems; 5.2 Knowledge Representation of Process Plans; 5.2.1 Process plan representation; 5.2.2 Machining cost criteria for process plans; 5.2.3 Precedence constraints; 5.3 A Hybrid GA/SA-based Optimisation Method; 5.3.1 Overview of the algorithm; 5.3.2 Genetic algorithm -- phase 1; 5.3.3 Simulated annealing algorithm -- phase 2; 5.3.4 Constraint handling algorithm.…”
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Deep Learning with TensorFlow : Explore neural networks and build intelligent systems with Python, 2nd Edition. by Zaccone, Giancarlo

Table of Contents: “…; Artificial neural networks; The biological neurons; The artificial neuron; How does an ANN learn?; ANNs and the backpropagation algorithm; Weight optimization; Stochastic gradient descent; Neural network architectures; Deep Neural Networks (DNNs); Multilayer perceptron; Deep Belief Networks (DBNs).…”
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Artificial intelligence for big data : complete guide to automating big data solutions using artificial intelligence techniques. by Deshpande, Anand

Table of Contents: “…Snowball stemming -- Lancaster stemming -- Lovins stemming -- Dawson stemming -- Lemmatization -- N-grams -- Feature extraction -- One hot encoding -- TF-IDF -- CountVectorizer -- Word2Vec -- CBOW -- Skip-Gram model -- Applying NLP techniques -- Text classification -- Introduction to Naive Bayes' algorithm -- Random Forest -- Naive Bayes' text classification code example -- Implementing sentiment analysis -- Frequently asked questions -- Summary -- Chapter 7: Fuzzy Systems -- Fuzzy logic fundamentals -- Fuzzy sets and membership functions -- Attributes and notations of crisp sets -- Operations on crisp sets -- Properties of crisp sets -- Fuzzification -- Defuzzification -- Defuzzification methods -- Fuzzy inference -- ANFIS network -- Adaptive network -- ANFIS architecture and hybrid learning algorithm -- Fuzzy C-means clustering -- NEFCLASS -- Frequently asked questions -- Summary -- Chapter 8: Genetic Programming -- Genetic algorithms structure -- KEEL framework -- Encog machine learning framework -- Encog development environment setup -- Encog API structure -- Introduction to the Weka framework -- Weka Explorer features -- Preprocess -- Classify -- Attribute search with genetic algorithms in Weka -- Frequently asked questions -- Summary -- Chapter 9: Swarm Intelligence -- Swarm intelligence -- Self-organization -- Stigmergy -- Division of labor -- Advantages of collective intelligent systems -- Design principles for developing SI systems -- The particle swarm optimization model -- PSO implementation considerations -- Ant colony optimization model -- MASON Library -- MASON Layered Architecture -- Opt4J library -- Applications in big data analytics -- Handling dynamical data -- Multi-objective optimization -- Frequently asked questions -- Summary -- Chapter 10: Reinforcement Learning -- Reinforcement learning algorithms concept.…”
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Seismic Data Interpretation using Digital Image Processing by Al-Shuhail, Abdullatif A., Al-Dossary, Saleh A., Mousa, Wail A.

Table of Contents: “…5.5 Two-Dimensional Second-Order Derivative Operator5.5.1 The Coherence Attribute; 5.5.2 The Dip Attribute; 5.6 The Curvature Attribute; 5.7 Curvature of the Surface; 5.7.1 Curve, Velocity, and Curvature; 5.7.2 Surface, Tangent Plane, and Norm; 5.8 Shape Operator, Normal Curvature, and Principal Curvature; 5.8.1 Normal Curvature; 5.8.2 Shape Operator; 5.8.3 The Principal Curvatures; 5.8.4 Calculation of the Principal Curvatures; 5.8.5 Summary of Calculation of Principal Curvature for a Surface; 5.9 The Randomness Attribute; 5.10 Technique for Two-Dimensional Images.…”
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Revolutionary routines : the habits of social transformation by Pedwell, Carolyn

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