Advances in Computational Algorithms and Data Analysis

by Sio-Iong Ao, Burghard B. Rieger, Su-Shing Chen

Overview

Advances in Computational Algorithms and Data Analysis offers state of the art tremendous advances in computational algorithms and data analysis. The selected articles are representative in these subjects sitting on the top-end-high technologies. The volume serves as an excellent reference work for researchers and graduate students working on computational algorithms and data analysis.

Product Details

ISBN-13:	9789048180271
Publisher:	Springer Netherlands
Publication date:	11/10/2010
Series:	Lecture Notes in Electrical Engineering , #14
Edition description:	Softcover reprint of hardcover 1st ed. 2009
Pages:	588
Product dimensions:	6.10(w) x 9.25(h) x 0.05(d)

Table of Contents

Scaling Exponent for the Healthy and Diseased Heartbeat.- CLUSTAG & WCLUSTAG: Hierarchical Clustering Algorithms for Efficient Tag-SNP Selection.- The Effects of Gene Recruitment on the Evolvability and Robustness of Pattern-Forming Gene Networks.- Comprehensive Genetic Database of Expressed Sequence Tags for Coccolithophorids.- Hybrid Intelligent Regressions with Neural Network and Fuzzy Clustering.- Design of DroDeASys (Drowsy Detection and Alarming System).- The Calculation of Axisymmetric Duct Geometries for Incompressible Rotational Flow with Blockage Effects and Body Forces.- Fault Tolerant Cache Schemes.- Reversible Binary Coded Decimal Adders using Toffoli Gates.- Sparse Matrix Computational Techniques in Concept Decomposition Matrix Approximation.- Transferable E-cheques: An Application of Forward-Secure Serial Multi-signatures.- A Hidden Markov Model based Speech Recognition Approach to Automated Cryptanalysis of Two Time Pads.- A Reconfigurable and Modular Open Architecture Controller: The New Frontiers.- An Adaptive Machine Vision System for Parts Assembly Inspection.- Tactile Sensing-based Control System for Dexterous Robot Manipulation.- A Novel Kinematic Model for Rough Terrain Robots.- Behavior Emergence in Autonomous Robot Control by Means of Evolutionary Neural Networks.- Swarm Economics.- Machines Imitating Humans.- Reinforced ART (ReART) for Online Neural Control.- The Bump Hunting by the Decision Tree with the Genetic Algorithm.- Machine Learning Approaches for the Inversion of the Radiative Transfer Equation.- Enhancing the Performance of Entropy Algorithm using Minimum Tree in Decision Tree Classifier.- Numerical Analysis of Large Diameter Butterfly Valve.- Axial Crushing of Thin-Walled Columns with Octagonal Section: Modeling and Design.- A FastState Estimation Method for DC Motors.- Flatness based GPI Control for Flexible Robots.- Estimation of Mass-Spring-Dumper Systems.- MIMO PID Controller Synthesis with Closed-Loop Pole Assignment.- Robust Design of Motor PWM Control using Modeling and Simulation.- Modeling, Control and Simulation of a Novel Mobile Robotic System.- All Circuits Enumeration in Macro-Econometric Models.- Noise and Vibration Modeling for Anti-Lock Brake Systems.- Investigation of Single Phase Approximation and Mixture Model on Flow Behaviour and Heat Transfer of a Ferrofluid using CFD Simulation.- Two Level Parallel Grammatical Evolution.- Genetic Algorithms for Scenario Generation in Shastic Programming.- New Approach of Recurrent Neural Network Weight Initialization.- GAHC: Hybrid Genetic Algorithm.- Forecasting Inflation with the Influence of Globalization using Artificial Neural Network-based Thin and Thick Models.- Pan-Tilt Motion Estimation Using Superposition-Type Spherical Compound-Like Eye.

Editorial Reviews

From the reviews:

"Computational science is concerned with designing computing models and techniques, and using computers to analyze and solve scientific and engineering problems. … The book presents the collected papers of a conference organized by the International Association of Engineers … . As with many conference-paper collections, the book seems to be geared toward scientists already armed with a general understanding of the topic. … a researchers in a specific field will have no difficulty following a particular paper or subset of papers." (Stefan Robila, ACM Computing Reviews, February, 2009)

From the Publisher