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5th International Conference on Computational Science - ICCS 2005

作者： Kolli, Vijaya Smitha Liu, Hui Pan, Michelle Hong Pan, Yi Department of Computer Science Georgia State University Atlanta GA 30303 United States Public Health Informatics Fellow Program Career Development Division Centers for Disease Control and Prevention 1600 Clifton Rd Atlanta GA 30333 United States

ISBN: (纸本)9783540260431

As the need for comparing genomes of different species has grown dramatically with the fast progress of the Human Genome Project, the evolution at the level of whole genomes has attracted more and more attention from both biologists and computer scientists. They are especially interested in the scenarios in which the genome evolves through insertions, deletions, and movements of genes along its chromosomes. Marron et al proposed a polynomial-time approximation algorithm to compute (near) minimum edit distances under inversions, deletions, and unrestricted insertions. Our work is based on their algorithm, which carries out lots of comparisons and sorting to calculate the edit distance. These comparisons and sorting are extremely time-consuming, and they result in decrease of computational efficiency. We believe the time of the algorithm can be improved through parallelization. We parallelize their algorithm via OpenMP using Intel C++ compiler for Linux 7.1, and compare three levels of parallelism: coarse grain, fine grain and combination of both. The experiments are conducted for a varying number of threads and different lengths of the gene sequences. The experimental results show that either coarse grain parallelism or fine grain parallelism alone does not improve the performance of the algorithm very much. However, the use of combination of both fine grain and coarse grain parallelism improves the performance of the algorithm drastically. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Genes

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E-NOSE response classification of sewage odors by neural networks and fuzzy clustering

E-NOSE response classification of sewage odors by neural net...

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First International Conference on Natural Computation, ICNC 2005

作者： Önkal-Engin, Güleda Demir, Ibrahim Engin, Seref N. Gebze Institute of Technology Department of Environmental Engineering Gebze 41400 Kocaeli Turkey Environmental Informatics and Control Program Warnel School of Forest Resources University of Georgia Athens GA 30602 United States Department of Electrical Engineering Yildiz Technical University 34800 Besiktas Istanbul Turkey

Each stage of the sewage treatment process emits odor causing compounds and these compounds may vary from one location in a sewage treatment works to another. In order to determine the boundaries of legal standards, reliable and efficient odor measurement methods need to be defined. An electronic NOSE equipped with 12 different polypyrrole sensors is used for the purpose of characterizing sewage odors. Samples collected at different locations of a WWTP were classified using a fuzzy clustering technique and a neural network trained with a back-propagation algorithm. © Sringer-Verlag Berlin Heidelberg 2005.

关键词： Sewage treatment

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Developing shared context within group stories

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11th International Workshop on Groupware: Design, Implementation, and Use, CRIWG 2005

作者： Santoro, Flávia Maria Brézillon, Patrick Post-Graduate Program in Informatics NCE and IM Universidade Federal do Rio de Janeiro PO Box 2324 CEP 20001-970 Rio de Janeiro Brazil School of Applied Informatics Universidade Federal do Estado do Rio de Janeiro Av. Pasteur 458 Rio de Janeiro Brazil LIP 6 Université Pierre et Marie Curie - Paris VI 8 rue de Capitain Scott Paris France

ISBN: (纸本)3540291105

Eliciting and re-using knowledge within an organization requires a very structured communication process among its employees in order to avoid misunderstanding and confusion. The transfer of knowledge among actors can only be successful if a common interpretative focus and its context are set up. So far, information about the real context that surrounded team's past activities can help their members to better understand situations at hand. In this paper, we argue that a combination of group storytelling technique and a groupware tool can help the elicitation and use of the context shared by a group. Moreover, our main goal is to discuss how groupware can help to structure and formalize the contextual information behind the scenes of a story told by a group, making it easier to understand, interpret and reuse the knowledge intrinsic to it. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Knowledge engineering

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Real time spatial cluster detection using interpoint distances among precise patient locations

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BMC Medical informatics and Decision Making 2005年第1期5卷 1-12页

作者： Olson, Karen L. Bonetti, Marco Pagano, Marcello Mandl, Kenneth D. Children's Hospital Informatics Program Children's Hospital Boston Boston MA United States Department of Pediatrics Harvard Medical School Boston MA United States Department of Biostatistics Harvard School of Public Health Boston MA United States Istituto di Metodi Quantitativi Università Bocconi Milano Italy

Background: Public health departments in the United States are beginning to gain timely access to health data, often as soon as one day after a visit to a health care facility. Consequently, new approaches to outbreak surveillance are being developed. When cases cluster geographically, an analysis of their spatial distribution can facilitate outbreak detection. Our method focuses on detecting perturbations in the distribution of pair-wise distances among all patients in a geographical region. Barring outbreaks, this distribution can be quite stable over time. We sought to exemplify the method by measuring its cluster detection performance, and to determine factors affecting sensitivity to spatial clustering among patients presenting to hospital emergency departments with respiratory syndromes. Methods: The approach was to (1) define a baseline spatial distribution of home addresses for a population of patients visiting an emergency department with respiratory syndromes using historical data;(2) develop a controlled feature set simulation by inserting simulated outbreak data with varied parameters into authentic background noise, thereby creating semisynthetic data;(3) compare the observed with the expected spatial distribution;(4) establish the relative value of different alarm strategies so as to maximize sensitivity for the detection of clustering;and (5) measure factors which have an impact on sensitivity. Results: Overall sensitivity to detect spatial clustering was 62%. This contrasts with an overall alarm rate of less than 5% for the same number of extra visits when the extra visits were not characterized by geographic clustering. Clusters that produced the least number of alarms were those that were small in size (10 extra visits in a week, where visits per week ranged from 120 to 472), diffusely distributed over an area with a 3 km radius, and located close to the hospital (5 km) in a region most densely populated with patients to this hospital. Near perfect

关键词： False Alarm Rate Spatial Cluster Home Address Additional Visit Outbreak Detection

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A comparative evaluation of competitive learning algorithms for edge detection enhancement

A comparative evaluation of competitive learning algorithms ...

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13th European Signal Processing Conference, EUSIPCO 2005

作者： Sirin, Tuba Saglam, Mehmet Izzet Erer, Isin Gokmen, Muhittin Ersoy, Okan Informatics Institute Advanced Technologies in Engineering Computer Science and Engineering Maslak Istanbul 34469 Turkey Informatics Institute Advanced Technologies in Engineering Satellite Communication and Remote Sensing Program Maslak Istanbul 34469 Turkey Faculty of Electrical and Electronic Engineering Electronics and Communication Department Maslak Istanbul 34469 Turkey Faculty of Electrical and Electronic Engineering Computer Engineering Department Istanbul Technical University Maslak Istanbul 34469 Turkey Purdue University School of Electrical and Computer Engineering West Lafayette IN United States

ISBN: (纸本)1604238216

Most edge detection algorithms include three main stages: smoothing, differentiation, and labeling. In this paper, we evaluate the performance of algorithms in which competitive learning is applied first to enhance edges, followed by an edge detector to locate the edges. In this way, more detailed and relatively more unbroken edges can be found as compared to the results when an edge detector is applied alone. The algorithms compared are K-Means, SOM and SOGR for clustering, and Canny and GED for edge detection. Perceptionally, best results were obtained with the GED-SOGR algorithm. The SOGR is also considerably simpler and faster than the SOM algorithm.

关键词： Edge detection

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Edge detection in multispectral remote sensing images

Edge detection in multispectral remote sensing images

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RAST 2005 - 2nd International Conference on Recent Advances in Space Technologies

作者： Sirin, Tuba Saglam, Mehmet Izzet Erer, Isin Gökmen, Muhittin Ersoy, Okan Istanbul Technical University Informatics Institute Advanced Technologies in Engineering Maslak/Istanbul Turkey Istanbul Technical University Informatics Institute Satellite Communication and Remote Sensing Program Maslak/Istanbul Turkey Istanbul Technical University Faculty of Electrical and Electronic Engineering Electronics and Communication Department Maslak/Istanbul Turkey Istanbul Technical University Faculty of Electrical and Electronic Engineering Computer Engineering Department Maslak/Istanbul Turkey Purdue University School of Electrical and Computer Engineering West Lafayette IN United States

ISBN: (纸本)0780389778

In this paper, we discuss edge detection by first using a clustering algorithm followed by a known edge detection filter such as Canny or Generalized Edge Detector (GED). We developed a new clustering method called Self-Organizing Global Ranking (SOGR). Comparative results with multispectral satellite images including SOGR, SOM and K-Means clustering methods are discussed. The results show that the two-stage algorithms are better than single stage edge detector algorithms. © 2005 IEEE.

关键词： Edge detection

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Handling missing attribute values in preterm birth data sets

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10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005

作者： Grzymala-Busse, Jerzy W. Goodwin, Linda K. Grzymala-Busse, Witold J. Zheng, Xinqun Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS 66045 United States Institute of Computer Science Polish Academy of Sciences 01-237 Warsaw Poland Nursing Informatics Program Duke University Durham NC 27710 United States Filterlogix Lawrence KS 66049 United States

ISBN: (纸本)3540286608

The objective of our research was to find the best approach to handle missing attribute values in data sets describing preterm birth provided by the Duke University. Five strategies were used for filling in missing attribute values, based on most common values and closest fit for symbolic attributes, averages for numerical attributes, and a special approach to induce only certain rules from specified information using the MLEM2 approach. The final conclusion is that the best strategy was to use the global most common method for symbolic attributes and the global average method for numerical attributes. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Data handling

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Calculating genomic distances in parallel using OpenMP 1

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International Workshop on Bioinformatics Research and Applications, IWBRA 2005

作者： Kolli, Vijaya Smitha Liu, Hui He, Jieyue Pan, Michelle Hong Pan, Yi Department of Computer Science Georgia State University Atlanta GA 30303 United States Department of Computer Science Southeast University Nanjing Jiangsu China Public Health Informatics Fellow Program Career Development Division Centers for Disease Control and Prevention 1600 Clifton Rd. Atlanta GA 30333 United States

ISBN: (数字)9783540316619

ISBN: (纸本)3540294015

By finding the corresponding shortest edit distance between two signed gene permutations, we can know the smallest number of insertions, deletions, and inversions required to change on string of genes into another, where insertion, deletion and inversion are the process of genome evolutions. However, it is NP-hard problem to compute the edit distance between two genomes. Marron et al proposed a polynomial-time approximation algorithm to compute (near) minimum edit distances under inversions, deletions, and unrestricted insertions. Our work is based on Marron's et al algorithm, which carries out lots of comparisons and sorting to calculate the edit distance. These comparisons and sorting are extremely time-consuming, and they result in the decrease of the efficiency. We believe the efficiency of the algorithm can be improved by parallelizing. We parallelize their algorithm via OpenMP on Intel C++ compiler for Linux 7.1, and compare three levels of parallelism: coarse grain, fine grain and combination of both. The experiments are conducted for a varying number of threads and length of the gene sequences. The experimental results have shown that either coarse grain parallelism or fine grain parallelism alone does not improve the performance of the algorithm very much, however, the combination of both fine grain and coarse grain parallelism have improve the performance to a great extent. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Genes

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A comparative evaluation of competitive learning algorithms for edge detection enhancement

A comparative evaluation of competitive learning algorithms ...

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European Signal Processing Conference (EUSIPCO)

作者： Tuba Sirin Mehmet Izzet Saglam Isin Erer Muhittin Gokmen Okan Ersoy Informatics Institute Computer Science and Engineering Informatics Institute Satellite Communication and Remote Sensing Program Faculty of Electrical and Electronic Engineering Electronics and Communication Department Faculty of Electrical and Electronic Engineering Istanbul Technical University Maslak Istanbul TURKEY Purdue University School of Electrical and Computer Engineering West Lafayette Indiana USA

关键词： Image edge detection Image segmentation Vectors Abstracts Filtering algorithms Erbium Training

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Bioinformatic analysis of the metal-binding protein families and heavy metal resistance amongst cyanobacteria

Bioinformatic analysis of the metal-binding protein families...

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International Conference on Intelligent Sensing and Information Processing (ICISIP)

作者： T.-C. Chu L.H. Lee S. Srinivasan Biomedical Information Program Department of Health Informatics University of Medicine and Dentistry of New Jersey Newark NJ USA Department of Biology and Molecular Biology Montclair State University Upper Montclair NJ USA

Cyanobacteria are often used as an indicator of the presence and level of pollutants in the environment. They have been especially recognized for their ability to identify contamination of heavy metals. Class II metallothioneins (MTs), usually found in cyanobacteria, are low molecular weight metal-binding proteins and may be required for heavy metal tolerance. It would be important to examine the phylogenetic pattern as well as prokaryotic evolution of metal-binding protein families among cyanobacteria. All the available protein sequences of cyanobacteria metallothioneins from GenBank, PDB and Pfam have been aligned and the phylogenetic tree was constructed by utilizing four multiple sequence alignment software ClustalW, T-Coffee, POA and GCG-PileUp. Eight cyanobacteria included in this study were Synechococcus sp. PCC 7942, Synechococcus sp. WH 8102, Thermosynechococcus vulcanus, Thermosynechococcus elongates BP-1, Nostoc sp. PCC 7120, Gloeobacter violaceus PCC 7421, Oscillatoria brevis, and Magnetospirillum magnetotacticum. 22 reported heavy metal resistant sequences from these 8 species of cyanobacteria were aligned. A phyletic pattern search tool provided by Cluster of Orthologous Groups (COGs) database, a collection of COGs from 63 sequenced prokaryotes and 3 unicellular eukaryotic genomes was also used to select a desired pattern of presence-absence of species. Cn3D 4.1 program was used for structural alignment. The results indicated that the tree was composed by five clusters. Most Synechococcus and Thermosynechococcus were clustered into 2 clades while others had relatively far genetic distance with Synechococcus but closely linked to each other. Structure alignment of metallothionein among cyanobacteria indicated that a major portion of their structure are not identical but with similar properties such as polarity. The results clearly showed several conserved C-X-C motifs near N-and C-terminus of Class II metallothioneins.

关键词： Bioinformatics Proteins Immune system Sequences Phylogeny Amino acids Pollution Evolution (biology) Databases Genomics

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