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2006

Algorithms

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Articles 1 - 13 of 13

Full-Text Articles in Physical Sciences and Mathematics

Improving Database Quality Through Eliminating Duplicate Records, Mingzhen Wei, Andrew H. Sung, Martha E. Cather Nov 2006

Improving Database Quality Through Eliminating Duplicate Records, Mingzhen Wei, Andrew H. Sung, Martha E. Cather

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Redundant or duplicate data are the most troublesome problem in database management and applications. Approximate field matching is the key solution to resolve the problem by identifying semantically equivalent string values in syntactically different representations. This paper considers token-based solutions and proposes a general field matching framework to generalize the field matching problem in different domains. By introducing a concept of String Matching Points (SMP) in string comparison, string matching accuracy and efficiency are improved, compared with other commonly-applied field matching algorithms. The paper discusses the development of field matching algorithms from the developed general framework. The framework and corresponding …


Extraction Of Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai Jul 2006

Extraction Of Coherent Relevant Passages Using Hidden Markov Models, Jing Jiang, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

In information retrieval, retrieving relevant passages, as opposed to whole documents, not only directly benefits the end user by filtering out the irrelevant information within a long relevant document, but also improves retrieval accuracy in general. A critical problem in passage retrieval is to extract coherent relevant passages accurately from a document, which we refer to as passage extraction. While much work has been done on passage retrieval, the passage extraction problem has not been seriously studied. Most existing work tends to rely on presegmenting documents into fixed-length passages which are unlikely optimal because the length of a relevant passage …


Bounded Search For De Novo Identification Of Degenerate Cis-Regulatory Elements, Jonathan M. Carlson, Arijit Chakravarty, Radhika S. Khetani, Robert H. Gross May 2006

Bounded Search For De Novo Identification Of Degenerate Cis-Regulatory Elements, Jonathan M. Carlson, Arijit Chakravarty, Radhika S. Khetani, Robert H. Gross

Dartmouth Scholarship

The identification of statistically overrepresented sequences in the upstream regions of coregulated genes should theoretically permit the identification of potential cis-regulatory elements. However, in practice many cis-regulatory elements are highly degenerate, precluding the use of an exhaustive word-counting strategy for their identification. While numerous methods exist for inferring base distributions using a position weight matrix, recent studies suggest that the independence assumptions inherent in the model, as well as the inability to reach a global optimum, limit this approach.


Identification Of Gene Expression Patterns Using Planned Linear Contrasts, Hao Li, Constance L. Wood, Yushu Liu, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg May 2006

Identification Of Gene Expression Patterns Using Planned Linear Contrasts, Hao Li, Constance L. Wood, Yushu Liu, Thomas V. Getchell, Marilyn L. Getchell, Arnold J. Stromberg

Statistics Faculty Publications

BACKGROUND: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With the same timing of the initial change, genes which share similar patterns of expression for any number of sampling intervals from the beginning should be considered co-expressed at certain level(s) in the gene networks. In addition, multiple testing problems are complicated in experiments with multi-level treatments when thousands of genes are involved.

RESULTS: To address these issues, we first performed an ANOVA F test to identify significantly regulated genes. The Benjamini and …


Engineering A Suburban Ad-Hoc Network, Mike Tyson, Ronald D. Pose, Carlo Kopp, Mohammad Rokonuzzaman, Muhammad Mahmudul Islam Apr 2006

Engineering A Suburban Ad-Hoc Network, Mike Tyson, Ronald D. Pose, Carlo Kopp, Mohammad Rokonuzzaman, Muhammad Mahmudul Islam

Australian Information Warfare and Security Conference

Networks are growing in popularity, as wireless communication hardware, both fixed and mobile, becomes more common and affordable. The Monash Suburban Ad-Hoc Network (SAHN) project has devised a system that provides a highly secure and survivable ad-hoc network, capable of delivering broadband speeds to co-operating users within a fixed environment, such as a residential neighbourhood, or a campus. The SAHN can be used by residents within a community to exchange information, to share access to the Internet, providing last-mile access, or for local telephony and video conferencing. SAHN nodes are designed to be self-configuring and selfmanaging, relying on no experienced …


Crosscutting Score: An Indicator Metric For Aspect Orientation, Subhajit Datta Mar 2006

Crosscutting Score: An Indicator Metric For Aspect Orientation, Subhajit Datta

Research Collection School Of Computing and Information Systems

Aspect Oriented Programming (AOP) provides powerful techniques for modeling and implementing enterprise software systems. To leverage its full potential, AOP needs to be perceived in the context of existing methodologies such as Object Oriented Programming (OOP). This paper addresses an important question for AOP practitioners - how to decide whether a component is best modeled as a class or an aspect? Towards that end, we present an indicator metric, the Crosscutting Score and a method for its calculation and interpretation. We will illustrate our approach through a sample calculation.


Gpnn: Power Studies And Applications Of A Neural Network Method For Detecting Gene-Gene Interactions In Studies Of Human Disease, Alison A. Motsinger, Stephen L. Lee, George Mellick, Marylyn D. Ritchie Jan 2006

Gpnn: Power Studies And Applications Of A Neural Network Method For Detecting Gene-Gene Interactions In Studies Of Human Disease, Alison A. Motsinger, Stephen L. Lee, George Mellick, Marylyn D. Ritchie

Dartmouth Scholarship

The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease.


Performance Evaluation Of Vertical Handoff Decision Algorithms In Heterogeneous Wireless Networks, Min Liu, Zhong-Cheng Li, Xiao-Bing Guo, Eryk Dutkiewicz, De-Kui Zhang Jan 2006

Performance Evaluation Of Vertical Handoff Decision Algorithms In Heterogeneous Wireless Networks, Min Liu, Zhong-Cheng Li, Xiao-Bing Guo, Eryk Dutkiewicz, De-Kui Zhang

Faculty of Informatics - Papers (Archive)

In recent years, many research works have focused on vertical handoff (VHO) decision algorithms. However, evaluation scenarios in different papers are often quite different and there is no consensus on how to evaluate performance of VHO algorithms. In this paper, we address this important issue by proposing an approach for systematic and thorough performance evaluation of VHO algorithms. Firstly we define the evaluation criteria for VHO with two metrics: matching ratio and average ping-pong number. Subsequently we analyze the general movement characteristics of mobile hosts and identify a set of novel performance evaluation models for VHO algorithms. Equipped with these …


An Improved Ant Colony Algorithm With Diversified Solutions Based On The Immune Strategy, Ling Qin, Yi Pan, Ling Chen, Yixin Chen Jan 2006

An Improved Ant Colony Algorithm With Diversified Solutions Based On The Immune Strategy, Ling Qin, Yi Pan, Ling Chen, Yixin Chen

Computer Science Faculty Publications

Background: Ant colony algorithm has emerged recently as a new meta- heuristic method, which is inspired from the behaviours of real ants for solving NP-hard problems. However, the classical ant colony algorithm also has its defects of stagnation and premature. This paper aims at remedying these problems.

Results: In this paper, we propose an adaptive ant colony algorithm that simulates the behaviour of biological immune system. The solutions of the problem are much more diversified than traditional ant colony algorithms.

Conclusion: The proposed method for improving the performance of traditional ant colony algorithm takes into account the polarization of the …


A Novel Approach To Phylogenetic Tree Construction Using Stochastic Optimization And Clustering, Ling Qin, Yixin Chen, Yi Pan, Ling Chen Jan 2006

A Novel Approach To Phylogenetic Tree Construction Using Stochastic Optimization And Clustering, Ling Qin, Yixin Chen, Yi Pan, Ling Chen

Computer Science Faculty Publications

Background: The problem of inferring the evolutionary history and constructing the phylogenetic tree with high performance has become one of the major problems in computational biology.

Results: A new phylogenetic tree construction method from a given set of objects (proteins, species, etc.) is presented. As an extension of ant colony optimization, this method proposes an adaptive phylogenetic clustering algorithm based on a digraph to find a tree structure that defines the ancestral relationships among the given objects.

Conclusion: Our phylogenetic tree construction method is tested to compare its results with that of the genetic algorithm (GA). Experimental results show that …


Fitness Evaluation For Structural Optimisation Genetic Algorithms Using Neural Networks, Koren Ward, Timothy J. Mccarthy Jan 2006

Fitness Evaluation For Structural Optimisation Genetic Algorithms Using Neural Networks, Koren Ward, Timothy J. Mccarthy

Faculty of Informatics - Papers (Archive)

This paper relates to the optimisation of structural design using Genetic Algorithms (GAs) and presents an improved method for determining the fitness of genetic codes that represent possible design solutions by using a neural network to generalize fitness. Two problems that often impede design optimization using genetic algorithms are expensive fitness evaluation and high epistasis. In this paper we show that by using a neural network as a fitness approximator, optimal solutions to certain design problems can be achieved in significantly less generations and with considerably less fitness evaluations.


Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.) Jan 2006

Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …


The Convergence Of V-Cycle Multigrid Algorithms For Axisymmetric Laplace And Maxwell Equations, Jay Gopalakrishnan, Joseph E. Pasciak Jan 2006

The Convergence Of V-Cycle Multigrid Algorithms For Axisymmetric Laplace And Maxwell Equations, Jay Gopalakrishnan, Joseph E. Pasciak

Mathematics and Statistics Faculty Publications and Presentations

We investigate some simple finite element discretizations for the axisymmetric Laplace equation and the azimuthal component of the axisymmetric Maxwell equations as well as multigrid algorithms for these discretizations. Our analysis is targeted at simple model problems and our main result is that the standard V-cycle with point smoothing converges at a rate independent of the number of unknowns. This is contrary to suggestions in the existing literature that line relaxations and semicoarsening are needed in multigrid algorithms to overcome difficulties caused by the singularities in the axisymmetric Maxwell problems. Our multigrid analysis proceeds by applying the well known regularity …