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International Conference on Computing, engineering and Information, ICC

作者： Jaratdech Chatchaval Veera Boonjing Pisit Chanvarasuth Software Systems Engineering Laboratory Mathematics and Computer Science Department Faculty of Science King Mongkut''s Institute of Technology Ladkrabang Thailand School of Management Technology Sirindhorn International Institute of Technology Thammasat University Pathum Thani Thailand

In this paper, we propose to improve the SvS algorithm by skipping elements of the smaller set for reducing a search boundary. The boundary of skipped element is determined by boundaries of elements prior to and next to it. We perform experiments on uniformly distributed random datasets to compare our algorithm with the standard SvS. We use regression analysis to get an equation for determining an appropriate skipping number. Our results show that the skipping SvS algorithm using the equation obtained can reduce approximately 41% on the number of comparisons of the standard SvS algorithm.

关键词： Equations software algorithms software systems systems engineering and theory Laboratories Mathematics computer science Conference management Technology management engineering management

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Meeting Report: BioSharing at ISMB 2010

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Standards in genomic sciences 2010年第3期3卷 254-8页

作者： Dawn Field Susanna Sansone Edward F Delong Peter Sterk Iddo Friedberg Pascale Gaudet Susanna Lewis Renzo Kottmann Lynette Hirschman George Garrity Guy Cochrane John Wooley Folker Meyer Sarah Hunter Owen White Brian Bramlett Susan Gregurick Hilmar Lapp Sandra Orchard Philippe Rocca-Serra Alan Ruttenberg Nigam Shah Chris Taylor Anne Thessen Centre for Ecology & Hydrology Wallingford UK Oxford e-Research Centre University of Oxford Oxford UK Department of Biological Engineering Massachusetts Institue of Technology Cambridge USA Department of Microbiology Miami University Oxford USA Department of Computer Science and Software Engineering Miami University Oxford USA Swiss Institute of Bioinformatics Geneva 4 Switzerland Lawrence Berkeley National Laboratory Berkeley USA Microbial Genomics Group Max Planck Institute for Marine Microbiology & Jacobs University Bremen Bremen Germany Information Technology Center The MITRE Corporation Bedford USA Department of Microbiology and Molecular Genetics Michigan State University East Lansing USA European Molecular Biology Laboratory (EMBL) Outstation European Bioinformatics Institute (EBI) Cambridge UK University of California San Diego La Jolla USA Argonne National Laboratory Argonne USA Institute for Genome Sciences University of Maryland School of Medicine Baltimore USA Lux Bio Group Portland USA Biological Systems Science Division Department of Energy Washington DC USA National Evolutionary Synthesis Center (NESCent) Durham USA Science Commons c/o Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory Cambridge USA Stanford Center for Biomedical Informatics Research Stanford USA Marine Biological Laboratory USA

This report summarizes the proceedings of the one day BioSharing meeting held at the intelligent systems for Molecular Biology (ISMB) 2010 conference in Boston, MA, USA This inaugural BioSharing event was hosted by the Genomic Standards Consortium as part of its M3 & BioSharing special interest group (SIG) workshop. The BioSharing event included invited talks from a range of community leaders and a panel discussion at the end of the day. The panel session led to the formal agreement among community leaders to join together to promote cross-community knowledge exchange and collaborations. A key focus of the newly formed Biosharing community will be linking up resources to promote real-world data sharing (virtuous cycle of data) and supporting compliance with data policies through the creation of a one-stop-portal of information. Further information about the newly established BioSharing effort can be found at http://***.

关键词： Community Leader Funding Agency Special Interest Group Panel Discussion Standardization Effort

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Comparing Commercial Tools and State-of-the-Art Methods for Generating Text Summaries

Comparing Commercial Tools and State-of-the-Art Methods for ...

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Mexican International Conference on Artificial Intelligence, MICAI

作者： René Arnulfo García-Hernández Yulia Ledeneva Griselda Matías Mendoza Ángel Hernández Dominguez Jorge Chavez Alexander Gelbukh José Luis Tapia Fabela Software Engineering Department Autonomous University of the State of Mexico Santiago Tianguistenco Mexico Computer Science Department Juarez Autonomous University of Tabasco Mexico Computational Systems Engineering Iguala Institute of Technology Iguala Guerrero Mexico Natural Language Laboratory National Polytechnic Institute CIC Mexico

Nowadays, there are commercial tools that allow automatic generation of text summaries. However, it is not known the quality of the generated summaries and the method that it is used for the generation of the summaries using these commercial tools. This paper provides a study about the commercial tools such as Copernic Summarizer, Microsoft Office Word Summarizer 2003 and Microsoft Office Word Summarizer 2007, with the objective to detect which of them gives the summaries more similar to those made by a human. Furthermore, the comparison between commercial tools and state-of-the-art methods is realized. The experiments were carried out using DUC-2002 standard collection which contains 567 news in English.

关键词： Humans Natural languages Data mining Artificial intelligence software engineering systems engineering and theory Laboratories computer science Operating systems software systems

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Programmable and Scalable Per-Flow Traffic Management Scheme Using a Control Server

Programmable and Scalable Per-Flow Traffic Management Scheme...

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IEEE International Conference on Communications (ICC)

作者： Y. Shinohara H. Shimonishi H. Tode K. Murakami Department of Information Networking Graduate School of Information Science and Technology Osaka University Suita Osaka Japan System Platforms Research Laboratory NEC Corporation Limited Kawasaki Kanagawa Japan Department of Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University Sakai Osaka Japan

We propose a programmable and scalable traffic management scheme. Programmable traffic management at high-speed routers is difficult because programmability and high-speed packet processing have involved a serious tradeoff. To attain both, the new scheme combines control programs at a control server and simple packet handling functions, such as sampling packet headers and discarding packets, at routers. Therefore, by installing appropriate control programs into the server, a variety of active queue management schemes, per-flow bandwidth management schemes, DoS mitigation schemes, and so on, are achieved. One of the main contributions of this paper is its proposal of a statistical scheme for handling flows. As only a fraction of complete flow information stored at the control server is loaded into the router's flow table and it is replaced cyclically, the proposed scheme scales more than the router's flow table capacity. Our simulation results indicate that the scheme provides efficient traffic management, per-flow WFQ emulation in our example, even with very small flow tables compared to the number of concurrently active flows. Furthermore, we discuss implementation issues with the proposed scheme and reveal that the processing cost at the server and router is sufficiently small for use with 10 Gbps links.

关键词： Traffic control Quality of service Communication system traffic control Electronic mail Costs Probability computer network management Technology management engineering management Network servers

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LogisticLDA: Regularizing latent dirichlet allocation by logistic regression

PACLIC 23 - Proceedings of the 23rd Pacific Asia Conference ...

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PACLIC 23 - Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation 2009年 1卷 160-169页

作者： Guo, Jia-Cheng Lu, Bao-Liang Li, Zhiwei Zhang, Lei Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai 200040 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai 200040 China Microsoft Research Asia 49 Zhichun Road Haidian District Beijing 100080 China

ISBN: (纸本)9789624423198

We present in this paper a supervised topic model for multi-class classification problems. To incorporate supervisory information, we jointly model documents and their labels in a graphical model called LogisticLDA, which mathematically integrates a generative model and a discriminative model in a principled way. By maximizing the posterior of document labels using logistic normal distributions, the model effectively incorporates the supervisory information to maximize inter-class distance in the topic space, while documents still enjoy the interchangeability characteristic for ease of inference. Experimental results on three benchmark datasets demonstrate that the model outperforms state-of-the-art supervised topic models. Compared with support vector machine, the model also achieves comparable performance, but meanwhile it discovers a topic space, which is valuable for dimension reduction, topic mining and document retrieval. © 2009 by Jia-Cheng Guo, Bao-Liang Lu, Zhiwei Li, and Lei Zhang.

关键词： Normal distribution

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Extracting keyphrases from Chinese news articles using Text Rank and query log knowledge

PACLIC 23 - Proceedings of the 23rd Pacific Asia Conference ...

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PACLIC 23 - Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation 2009年 2卷 733-740页

作者： Liang, Weiming Huang, Chang-Ning Li, Mu Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai 200240 China Microsoft Research Asia 49 Zhichun Road Haidian District Beijing 100080 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai 200240 China

ISBN: (纸本)9789624423198

Keyphrases extracted from articles are beneficial in helping people boost browsing speed, but unfortunately keyphrases are rarely available for news articles due to the high expense of labor and time for manual annotation. This paper proposes a practical approach to extracting keyphrases for Chinese news articles using the Text Rank and query log knowledge. Previous work is word based, while our approach uses phrase as its basic element. We generate phrases by employing several statistical criteria with the huge amount of queries as a training corpus. We use Text Rank, a graph-based learning algorithm, for extracting keyphrases from Chinese news articles. In addition, two instructive features, lengths and positions of phrases, are incorporated into the Text Rank model. Experimental results demonstrate that our methods improve the performance significantly. © 2009 by Weiming Liang, Chang-Ning Huang, Mu Li, and Bao-Liang Lu.

关键词： Graphic methods

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An approach using hybrid methods to select informative genes from microarray data for cancer classification

An approach using hybrid methods to select informative genes...

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2nd Asia International Conference on Modelling and Simulation, AMS 2008

作者： Mohamad, Mohd Saberi Omatu, Sigeru Yoshioka, Michifumi Deris, Safaai Department of Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University Sakai Osaka 599-8531 Japan Department of Software Engineering Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 Skudai Johore Malaysia

ISBN: (纸本)9780769531366

Recent advances in microarray technology allow scientists to measure expression levels of thousands of genes simultaneously in human tissue samples. This technology has been increasingly used in cancer research because of its potential for classification of the tissue samples based only on gene expression levels. A major problem in these microarray data is that the number of genes greatly exceeds the number of tissue samples. Moreover, these data have a noisy nature. It has been shown from literature review that selecting a small subset of informative genes can lead to an improved classification accuracy. Thus, this paper aims to select a small subset of informative genes that is most relevant for the cancer classification. To achieve this aim, an approach using two hybrid methods has been proposed. This approach is assessed on two well-known microarray data. The experimental results have shown that the gene subsets are very small in size and yield better classification accuracy as compared with other previous works as well as four methods experimented in this work. In addition, a list of informative genes in the best subsets is also presented for biological usage © 2008 IEEE.

关键词： Gene expression

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Verifying and analyzing adaptive logic through UML state models

Verifying and analyzing adaptive logic through UML state mod...

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1st International Conference on software Testing, Verification and Validation, ICST 2008

作者： Ramirez, Andres J. Cheng, Betty H. C. Software Engineering and Network Systems Laboratory Department of Computer Science and Engineering Michigan State University East Lansing MI 48824 United States

ISBN: (纸本)076953127X

It is becoming increasingly important to be able to adapt an application's behavior at run time in response to changing requirements and environmental conditions. Adaptive programs are typically difficult to specify, design, and verify. A variety of conditions may trigger an adaptation, each of which may involve different types of adaptation mechanisms. In many cases, adaptive systems are concurrent, thus further exacerbating the complexity. Furthermore, it is important that adaptations do not put the system into an inconsistent state during or after adaptation. This paper presents an iterative approach to modeling and analyzing UML behavioral design models of adaptive systems, where the UML state diagrams are automatically translated into Promela code for analysis with the Spin model checker. The adaptive models are analyzed for adherence to both system invariants and properties that should hold during adaptation. We demonstrate this approach on applications for the mobile computing domain where we verify the design models against formally-specified properties. © 2008 IEEE.

关键词： Adaptive systems

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Embedded neural network for fire classification using an array of gas sensors

Embedded neural network for fire classification using an arr...

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作者： Bashyal, Shishir Venayagamoorthy, Ganesh Kumar Paudel, Bandana Real-Time and Intelligent Systems Laboratory Department of Electrical and Computer Engineering Missouri University of Science and Technology United States Real-Time Power and Intelligent Systems Laboratory Department of Electrical Engineering Missouri University of Science and Technology United States Smart Engineering Systems Laboratory Systems Engineering Department Missouri University of Science and Technology United States

ISBN: (纸本)9781424419630

Fire is one of the most common hazards in US households. In 2006 alone, 2705 people were killed due to fire in building structures. 74% of the deaths result from fires in homes with no smoke alarms or no working smoke alarms while surveys report that 96% of all homes have at least one smoke alarm. This study discusses the development of a fire sensing system that is not only capable of detecting fire in its early stage but also of classifying the fire based on the smell of the smoke in the environment. By using an array of sensors along with a neural network for sensor pattern recognition, an impressive result is obtained. Instead of confining the ANN to a PC based application, this work extends the implementation of the neural network fire classifier in a general purpose microcontroller. The result is a low cost intelligent embedded fire classifier that can be used in real life situations for fire hazards minimization, for example this intelligent fire classifier can be used for the development of a smart extinguisher that detects the fire, classifies it and then uses appropriate extinguishing material required for extinguishing the particular class of fire. ©2008 IEEE.

关键词： Fires

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A multi-objective strategy in genetic algorithm for gene selection of gene expression data

A multi-objective strategy in genetic algorithm for gene sel...

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作者： Mohamad, M.S. Omatu, S. Deris, S. Misman, M.F. Department of Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University Sakai Osaka 599-8531 Japan Department of Software Engineering Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 Skudai Johore Malaysia

ISBN: (纸本)9784990288020

Microarray device offers the ability to measure the expression levels of thousands of genes simultaneously. It is used to collect information from tissue and cell samples regarding gene expression differences that could be useful for cancer classification. However, the urgent issues in the use of gene expression data are the availability of huge number of genes relative to the small number of available samples, and many of the genes are not relevant to the classification. It has been shown that selecting a small subset of genes can lead to an improved accuracy of the classification. Hence, this paper proposes a solution to the problem of gene selection by using a multi-objective strategy in genetic algorithm. This approach is experimented on two benchmark gene expression data sets and it presented the experimental results. It obtains encouraging result on those data sets as compared with an approach that uses single-objective strategy in genetic algorithm. ©ISAROB 2008.

关键词： Genetic algorithms

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