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Selecting Informative Genes from Microarray Data by Using a Cyclic GA-Based Method

Selecting Informative Genes from Microarray Data by Using a ...

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International Conference on Intelligent systems, Modelling and Simulation (ISMS)

作者： Mohd Saberi Mohamad Sigeru Omatu Safaai Deris Michifumi Yoshioka Department of Software Engineering Universiti Teknologi Malaysia Skudai Johore Malaysia Department of Computer Science and Intelligent Systems Osaka Prefecture University Sakai Osaka Japan Department of Software Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia

ISBN: (纸本)9781424459841;9780769539737

Microarray data are expected to be of significant help in the development of efficient cancer diagnoses and classification platforms. The main problem that needs to be addressed is the selection of a small subset of genes from the thousands of genes in the data that contributes to a cancer disease. This selection process is difficult due to the availability of a small number of samples compared to the huge number of genes, many irrelevant genes, and noisy genes. Therefore, this paper proposes a cyclic method based on genetic algorithms (GA) to select a near-optimal (small) subset of informative genes that is relevant for cancer classification. The performance of the proposed method was evaluated by three benchmark microarray data sets and obtained encouraging results as compared with other experimented methods and previous related works.

关键词： Cancer Filters Genetic algorithms Support vector machines Support vector machine classification Diseases Gene expression Intelligent systems Computational modeling computer simulation

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A Three-Stage Method to Select Informative Genes from Gene Expression Data in Classifying Cancer Classes

A Three-Stage Method to Select Informative Genes from Gene E...

引用

International Conference on Intelligent systems, Modelling and Simulation (ISMS)

作者： Mohd Saberi Mohamad Sigeru Omatu Safaai Deris Michifumi Yoshioka Department of Software Engineering Universiti Teknologi Malaysia Skudai Johor Malaysia Department of Computer Science and Intelligent Systems Osaka Prefecture University Sakai Osaka Japan

ISBN: (纸本)9781424459841;9780769539737

The process of gene selection for the cancer classification faces with a major problem due to the properties of the data such as the small number of samples compared to the huge number of genes, irrelevant genes, and noisy data. Hence, this paper aims to select a near-optimal (small) subset of informative genes that is most relevant for the cancer classification. To achieve the aim, a three-stage method has been proposed. It has three stages: (1) pre-selecting genes using a filter method; (2) optimizing the gene subset using a multi-objective hybrid method; (3) analyzing the frequency of appearance of each gene. By performing experiments on three public gene expression data sets, classification accuracies and the number of selected genes of the proposed method are better than those of other experimented methods and previous works. A list of informative genes in the final gene subsets is also presented for biological usage.

关键词： Gene expression Cancer Filters Genetic algorithms Support vector machines Support vector machine classification Frequency Intelligent systems Computational modeling computer simulation

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A Particle Swarm Optimization-Based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments

A Particle Swarm Optimization-Based Heuristic for Scheduling...

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Suraj Pandey Linlin Wu Siddeswara Mayura Guru Rajkumar Buyya Cloud Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia CSIRO Tasmanian ICT Centre Hobart Australia

ISBN: (纸本)9781424466955;9780769540184

Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. However, users are charged on a pay-per-use basis. User applications may incur large data retrieval and execution costs when they are scheduled taking into account only the `execution time'. In addition to optimizing execution time, the cost arising from data transfers between resources as well as execution costs must also be taken into account. In this paper, we present a particle swarm optimization (PSO) based heuristic to schedule applications to cloud resources that takes into account both computation cost and data transmission cost. We experiment with a workflow application by varying its computation and communication costs. We compare the cost savings when using PSO and existing `Best Resource Selection' (BRS) algorithm. Our results show that PSO can achieve: (a) as much as 3 times cost savings as compared to BRS, and (b) good distribution of workload onto resources.

关键词： Particle swarm optimization Processor scheduling Cloud computing Application software Cost function Computational efficiency Dynamic scheduling computer science software engineering Application virtualization

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Anaphora Resolution of Malay Text: Issues and Proposed Solution Model

Anaphora Resolution of Malay Text: Issues and Proposed Solut...

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International Conference on Asian language Processing (IALP)

作者： Noorhuzaimi Karimah Mohd Noor Shahrul Azman Noah Mohd Juzaidin Ab. Aziz Mohd Pouzi Hamzah Computer Systems & Software Engineering Universiti Malaysia Pahang Pahang Malaysia Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Computer Science Department FST Universiti Malaysia TerEngganu Terengganu Malaysia

Anaphora resolution (AR) is a process to identify the appropriate antecedent with its anaphor which occur before the anaphor. AR able to improve most of the NLP applications such as question answering, short answer examination system and information extraction. Most of AR systems are deal with English language. Thus, in 1990's the research on AR has been applied for other language, such as Arabic, Chinese, Hindi and Norwegian. There are however limited or no effort in dealing with Malay text. The AR systems for one language cannot be simply adapted to use in other languages. This is due to the fact that different languages have different set of rules relating to syntax and semantic to respective language. This paper proposed a model for resolving anaphora phenomena in Malay text. The model consists of three elements consisting of anaphora resolution process, syntactic knowledge process and semantic-world knowledge process. The elements are defined based on the observable fact occurring in Malay language.

关键词： Semantics Humans Syntactics Animals Computational modeling Computational linguistics Electronic mail

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I-superior approach to study the stability of logistic map

I-superior approach to study the stability of logistic map

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International Conference on Mechanical and Electrical Technology (ICMET)

作者： Mamta Rani Saurabh Goel Faculty of Computer Systems & Software Engineering Universiti Malaysia Pahang Kuantan Pahang Malaysia Research Scholar Department Of Computer Science Galgotias Institute of Management Technology Greater Noida India

Verlhust logistic map f(x) = r x (1 - x) is a widely studied and applicable model in discrete dynamical system. Its behavior has been, extensively, studied in Picard orbit and recently studied in superior orbit. Rani et. al. [22] and [25] has shown that in superior orbit, logistic map is stable for larger values of r than that of Picard orbit. In this paper, we have attempted to make the map stable for further larger values of r via I-superior iterates.

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Reports of the AAAI 2010 conference workshops

Reports of the AAAI 2010 conference workshops

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作者： Aha, David W. Boddy, Mark Bulitko, Vadim D'Avila Garcez, Artur S. Doshi, Prashant Edelkamp, Stefan Geib, Christopher Gmytrasiewicz, Piotr Goldman, Robert P. Halevy, Alon Hitzler, Pascal Isbell, Charles Josyula, Darsana Kaelbling, Leslie Pack Kersting, Kristian Kunda, Maithilee Lamb, Luis C. Marthi, Bhaskara McGreggor, Keith Mihalkova, Lilyana Nastase, Vivi Natarajan, Sriraam Provan, Gregory Raja, Anita Ram, Ashwin Riedl, Mark Russell, Stuart Sabharwal, Ashish Smaus, Jan-Georg Sukthankar, Gita Tuyls, Karl Van Der Meyden, Ron Adaptive Systems Section Naval Research Laboratory Washington DC United States Adventium Labs. Minneapolis MN United States Department of Computer Science University of Alberta Canada City University London United Kingdom University of Georgia United States University of Bremen Germany School of Informatics University of Edinburgh United Kingdom University of Illinois Chicago United States Smart Information Flow Technologies LLC Minneapolis MN United States Structured Data Group Google Research United States Department of Computer Science Wright State University Dayton OH United States School of Interactive Computing Georgia Institute of Technology Atlanta GA United States Department of Computer Science Bowie State University United States Department of Computer Science and Engineering Massachusetts Institute of Technology United States Statistical Relational Mining Group Fraunhofer IAIS Germany Department of Computer Science Federal University of Rio Grande Do sul Brazil Willow Garage Inc. CA United States Computer Science Department University of Maryland College Park United States Heidelberg Institute for Theoretical Studies Heidelberg Germany Department of Computer Science University of Wisconsin Madison United States University College Cork Ireland Cork Complex Systems Lab. Ireland Department of Software and Information Systems University of North Carolina Charlotte United States Department of Computer Science and Engineering University of California Berkeley United States Department of Computer Science Cornell University United States Institute for Computational Sustainability United States University of Freiburg Germany School of Electrical Engineering and Computer Science University of Central Florida United States Maastricht University Netherlands University of New South Wales NICTA Australia

The AAAI-10 workshop program was held on July 11-12, 2010, at the Westin Peachtree Plaza in Atlanta, Georgia. The workshop program included 13 workshops covering a wide range of topics in artificial intelligence. There were several presentations on particular formalisms for combining the levels of planning from the perspectives of classical planning, motion planning, POMDPs, search-based planning, and temporal logic-based constraints. Henry Lieberman from Massachusetts Institute of Technology Media Laboratory presented work developing a platform for knowledge acquisition and usage from expert users, built upon experience with eliciting information from nonexperts in a collaborative manner. The objective of the AAAI Workshop on Goal-Directed Autonomy (GDA) was to encourage discussion and novel contributions on intelligent agents that can self-select their goals. Jeremy Baxter from QinetiQ focused on user interaction, while Nick Hawes described a goal-directed reasoning framework for controlling a mobile robot.

关键词： Motion planning

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CloudAnalyst: A CloudSim-based Visual Modeller for Analysing Cloud Computing Environments and Applications

CloudAnalyst: A CloudSim-based Visual Modeller for Analysing...

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International Conference on Advanced Information Networking and Applications

作者： Bhathiya Wickremasinghe Rodrigo N. Calheiros Rajkumar Buyya The Cloud Computing and Distributed Systems (CLOUDS) Laboratory Department of Computer Science and Software Engineering The University of Melbourne Pontifical Catholic University of Rio Grande do Sul

ISBN: (纸本)9781424466955;9780769540184

Advances in Cloud computing opens up many new possibilities for Internet applications developers. Previously, a main concern of Internet applications developers was deployment and hosting of applications, because it required acquisition of a server with a fixed capacity able to handle the expected application peak demand and the installation and maintenance of the whole software infrastructure of the platform supporting the application. Furthermore, server was underutilized because peak traffic happens only at specific times. With the advent of the Cloud, deployment and hosting became cheaper and easier with the use of pay-peruse flexible elastic infrastructure services offered by Cloud providers. Because several Cloud providers are available, each one offering different pricing models and located in different geographic regions, a new concern of application developers is selecting providers and data center locations for applications. However, there is a lack of tools that enable developers to evaluate requirements of large-scale Cloud applications in terms of geographic distribution of both computing servers and user workloads. To fill this gap in tools for evaluation and modeling of Cloud environments and applications, we propose CloudAnalyst. It was developed to simulate large-scale Cloud applications with the purpose of studying the behavior of such applications under various deployment configurations. CloudAnalyst helps developers with insights in how to distribute applications among Cloud infrastructures and value added services such as optimization of applications performance and providers incoming with the use of Service Brokers.

关键词： Cloud Computing Modeling Simulation

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An improved SOM-based visualization technique for DNA microarray data analysis

An improved SOM-based visualization technique for DNA microa...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jagdish C. Patra Jacob Abraham Pramod K. Meher Goutam Chakraborty School of Computer Engineering Nanyang Technological University Singapore Department of Communication Systems Institute for Infocomm Research Singapore Department of Software and Information Science Iwate Prefectural University Japan

Effective and meaningful visualization techniques are quite important for multidimensional DNA microarray gene expression data analysis. Elucidating the cluster properties of these multidimensional data are often complex. Patterns, hypotheses on the relationships, and ultimately of the function of the gene can be analyzed and visualized by non-linear reduction of the multidimensional data to a lower dimension. In this paper, an improved SOM visualization technique named Improved Side Intensity Modulated (ISIM) Self-Organizing Map (SOM) has been proposed and compared with other SOM based visualization techniques. On different datasets, ISIM-SOM is found to offer better cluster boundary, simplicity and clarity.

关键词： Data visualization Neurons Iris Gene expression Clustering algorithms Training DNA

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Analysis of Integrity Vulnerabilities and a Non-repudiation Protocol for Cloud Data Storage Platforms

Analysis of Integrity Vulnerabilities and a Non-repudiation ...

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International Conference on Parallel Processing Workshops (ICPPW)

作者： Jun Feng Yu Chen Wei-Shinn Ku Pu Liu Department of Electrical & Computer Engineering State University of New York Binghamton Binghamton NY USA Department of Computer Science & Software Engineering Aubum University Auburn AL USA Systems and Technology Group IBM Endicott Endicott NY USA

Data storage technologies have been recognized as one of the major dimensions of information management along with the network infrastructure and applications. The prosperity of cloud computing requires the migration from server-attached storage to network-based distributed storage. Along with variant advantages, distributed storage also poses new challenges in creating a secure and reliable data storage and access facility. The data security in cloud is one of the challenges to be addressed before the novel pay-as-you-go business model can be accepted and applied widely. Concerns are raised from both insecure/unreliable service providers and potential malicious users. In this article, we analyze the integrity vulnerability existing in the current cloud storage platforms and show the problem of repudiation. A novel non-repudiation (NR) protocol specifically designed in the context of cloud computing environment is proposed. We have also discussed the robustness of the NR protocol against typical attacks in the network environments.

关键词： Clouds Cloud computing Protocols Authentication Google

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LM: a miner for scenario-based specifications

LM: a miner for scenario-based specifications

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International Conference on software engineering (ICSE)

作者： Tuan-Anh Doan David Lo Shahar Maoz Siau-Cheng Khoo School of Computing National University of Singapore Singapore School of Information Systems Singapore Management University Singapore Department of Computer Science Software Engineering RWTH-Aachen Germany

We present LM, a tool for mining scenario-based specifications in the form of Live Sequence Charts, a visual language that extends sequence diagrams with modalities. LM comes with a project management component, a wizard-like interface to the mining algorithm, a set of pre- and post-processing extensions, and a visualization module.

关键词： Data mining Semantics Visualization Measurement software engineering Feature extraction software algorithms

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