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An Approach Using Parallel Architecture to Storage DICOM Images in Distributed File System

Journal of Physics: Conference Series 2012年第1期341卷

作者： Tiago S Soares Thiago C Prado M A R Dantas Douglas D J de Macedo Michael A Bauer Informatics and Statistic Department Federal University of Santa Catarina Florianpolis Brazil Post-Graduate Program of Knowledge Engineering and Management Federal University of Santa Catarina Florianpolis Brazil Department of Computer Science University of Western Ontario UWO London Canada

Telemedicine is a very important area in medical field that is expanding daily motivated by many researchers interested in improving medical applications. In Brazil was started in 2005, in the State of Santa Catarina has a developed server called the CyclopsDCMServer, which the purpose to embrace the HDF for the manipulation of medical images (DICOM) using a distributed file system. Since then, many researches were initiated in order to seek better performance. Our approach for this server represents an additional parallel implementation in I/O operations since HDF version 5 has an essential feature for our work which supports parallel I/O, based upon the MPI paradigm. Early experiments using four parallel nodes, provide good performance when compare to the serial HDF implemented in the CyclopsDCMServer.

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A Radial Basis Function Spike Model for Indirect Learning via Integrate-and-Fire Sampling and Reconstruction Techniques

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Advances in Artificial Neural Systems 2012年第1期2012卷

作者： X. Zhang G. Foderaro C. Henriquez A. M. J. VanDongen S. Ferrari Laboratory for Intelligent Systems and Control (LISC) Department of Mechanical Engineering and Materials Science Duke University Durham NC 27708 USAduke.edu Department of Biomedical Engineering and Department of Computer Science Duke University Durham NC 27708 USAduke.edu Program in Neuroscience & Behavioral Disorders Duke-NUS Graduate Medical School Singapore Singapore

This paper presents a deterministic and adaptive spike model derived from radial basis functions and a leaky integrate-and-fire sampler developed for training spiking neural networks without direct weight manipulation. Several algorithms have been proposed for training spiking neural networks through biologically-plausible learning mechanisms, such as spike-timing-dependent synaptic plasticity and Hebbian plasticity. These algorithms typically rely on the ability to update the synaptic strengths, or weights, directly, through a weight update rule in which the weight increment can be decided and implemented based on the training equations. However, in several potential applications of adaptive spiking neural networks, including neuroprosthetic devices and CMOS/memristor nanoscale neuromorphic chips, the weights cannot be manipulated directly and, instead, tend to change over time by virtue of the pre- and postsynaptic neural activity. This paper presents an indirect learning method that induces changes in the synaptic weights by modulating spike-timing-dependent plasticity by means of controlled input spike trains. In place of the weights, the algorithm manipulates the input spike trains used to stimulate the input neurons by determining a sequence of spike timings that minimize a desired objective function and, indirectly, induce the desired synaptic plasticity in the network.

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Simultaneous identification for synergistic transcription factors and their transcription factor binding sites

Simultaneous identification for synergistic transcription fa...

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5th International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011

作者： Tsai, Zing Tsung-Yeh Huang, Grace Tzu-Wei Tsai, Huai-Kuang Institute of Information Science Academia Sinica Taipei 115 Taiwan Bioinformatics Program Taiwan International Graduate Program Taiwan Institute of Biomedical Informatics National Yang-Ming University Taiwan Joint CMU-Pitt PhD Program in Computational Biology University of Pittsburgh Carnegie Mellon University Pittsburgh PA United States Research Center for Information Technology Innovation Taipei 115 Taiwan Computer Science and Engineering National Taiwan Ocean University Keelung 202 Taiwan

ISBN: (纸本)9780769543734

Identifying transcription factor binding sites (TFBSs) is crucial for understanding the mechanism of transcriptional regulation. It is known that transcription factors (TFs) often cooperate to regulate genes. While traditional approaches can be used to discover binding motifs of a group of co-regulated genes, they often fail to accurately assign motifs to the corresponding TFs. Here, we consider two TFs together to infer their TFBSs and their synergistic relationship simultaneously. The basic idea is that if two TFs interact, their TFBSs, if distinct, would be conserved across species and coincided in the promoter regions of the genes they co-regulated. Applying our method to Saccharomyces cerevisiae chromatin immunoprecipitation data, we predicted 110 TF pairs with statistically significant motif assignments. A majority of these TF pairs have literature support to be synergistic, and the designated motifs to TFs match well with their known consensus. We further examined the synergism of predicted TF pairs in seven experimental conditions using ANOVA, and identified significant interactions. © 2011 IEEE.

关键词： Yeast

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Handling failures of static sensor nodes in wireless sensor network by use of mobile sensors

Handling failures of static sensor nodes in wireless sensor ...

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25th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2011

作者： Pignaton De Freitas, Edison Heimfarth, Tales Netto, Ivayr Farah Pereira, Carlos Eduardo Ferreira, Armando Morado Wagner, Flávio Rech Larsson, Tony IDE Halmstad University Halmstad Sweden Institute of Informatics Federal University of Rio Grande Do Sul Porto Alegre Brazil Computer Science Department Federal University of Lavras Lavras Brazil Electrical Engineering Department Federal University of Rio Grande Do Sul Porto Alegre Brazil Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (纸本)9780769543383

Node failures in Wireless Sensor Networks composed by static sensor nodes are common due to the nature of the sensor devices and the usually harsh environments in which they are deployed. Node failures can diminish the performance of the network as a whole, thus affecting its functionality in delivering the desired services. For instance, significant regions can become uncovered due to failure of several nearby nodes. This paper reports a study about the use of mobile sensor nodes acting in cooperation with static ones in order to fill gaps created by faulty static nodes. The proposed fault handling mechanism presents alternative policies with pros and cons, depending on the user priorities imposed to the system and the occurrence of failures. A discussion about this topic is presented based on results obtained by simulation of the proposed mechanisms. © 2011 IEEE.

关键词： Sensor nodes

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A new method for fuzzy forecasting based on two-factors high-order fuzzy-trend logical relationship groups and particle swarm optimization techniques

A new method for fuzzy forecasting based on two-factors high...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Shyi-Ming Chen Gandhi Maruli Tua Manalu Shu-Chuan Shih Tian-Wei Sheu Hsiang-Chuan Liu Graduate Institute of Educational Measurement and Statistics National Taichung University of Education Taichung Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Biomedical Informatics Asia University Taichung Taiwan

This paper presents a new method for fuzzy forecasting based on two-factors high-order fuzzy-trend logical relationship groups and particle swarm optimization techniques. We fuzzify the historical training data of the main factor and the secondary factor, respectively, to form two-factors high-order fuzzy logical relationships. Then, we group the two-factors high-order fuzzy logical relationships into two-factors high-order fuzzy-trend logical relationship groups. Finally, we obtain the optimal weighting vectors for each fuzzy-trend logical relationship group by using particle swarm optimization techniques to perform the forecasting. The experimental results show that the proposed method gets higher average forecasting accuracy rates than the existing methods.

关键词： Vectors Forecasting Fuzzy sets Particle swarm optimization Time series analysis Testing Training

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A new method for fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights

A new method for fuzzy risk analysis based on ranking genera...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Shyi-Ming Chen Abdul Munif Guey-Shya Chen Bor-Chen Kuo Hsiang-Chuan Liu Graduate Institute of Educational Measurement and Statistics National Taichung University of Education Taichung Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Biomedical Informatics Asia University Taichung Taiwan

This paper presents a new method for fuzzy risk analysis based on ranking generalized fuzzy numbers with different left heights and right heights. First, we present a method for ranking generalized fuzzy numbers with different left heights and right heights. It can overcome the drawbacks of the existing fuzzy ranking methods. Based on the proposed fuzzy ranking method of generalized fuzzy numbers with different left heights and right heights, we propose a new method for fuzzy risk analysis. The proposed fuzzy risk analysis method provides us with a useful way to deal with fuzzy risk analysis problems.

关键词： Risk analysis Economic indicators Educational institutions biomedical measurements biomedical informatics Asia Shape

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Agile parallel bioinformatics workflow management using Pwrake

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BMC Research Notes 2011年第1期4卷 1-8页

作者： Mishima, Hiroyuki Sasaki, Kensaku Tanaka, Masahiro Tatebe, Osamu Yoshiura, Koh-Ichiro Department of Human Genetics Nagasaki University Graduate School of Biomedical Sciences Nagasaki Nagasaki 1-12-4 Sakamoto Japan Nagasaki University Global Center of Excellence Program Nagasaki Nagasaki 1-12-4 Sakamoto Japan Center for Computational Sciences University of Tsukuba Tsukuba Ibaraki 1-1-1 Tennodai Japan Core Research for Evolutional Science and Technology Japan Science and Technology Agency Kawaguchi Saitama 4-1-8 Honcho Japan Departmentent of Computer Science Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki 1-1-1 Tennodai Japan

Background: In bioinformatics projects, scientific workflow systems are widely used to manage computational procedures. Full-featured workflow systems have been proposed to fulfil the demand for workflow management. However, such systems tend to be over-weighted for actual bioinformatics practices. We realize that quick deployment of cutting-edge software implementing advanced algorithms and data formats, and continuous adaptation to changes in computational resources and the environment are often prioritized in scientific workflow management. These features have a greater affinity with the agile software development method through iterative development phases after trial and error. Here, we show the application of a scientific workflow system Pwrake to bioinformatics workflows. Pwrake is a parallel workflow extension of Ruby's standard build tool Rake, the flexibility of which has been demonstrated in the astronomy domain. Therefore, we hypothesize that Pwrake also has advantages in actual bioinformatics workflows. Findings. We implemented the Pwrake workflows to process next generation sequencing data using the Genomic Analysis Toolkit (GATK) and Dindel. GATK and Dindel workflows are typical examples of sequential and parallel workflows, respectively. We found that in practice, actual scientific workflow development iterates over two phases, the workflow definition phase and the parameter adjustment phase. We introduced separate workflow definitions to help focus on each of the two developmental phases, as well as helper methods to simplify the descriptions. This approach increased iterative development efficiency. Moreover, we implemented combined workflows to demonstrate modularity of the GATK and Dindel workflows. Conclusions: Pwrake enables agile management of scientific workflows in the bioinformatics domain. The internal domain specific language design built on Ruby gives the flexibility of rakefiles for writing scientific workflows. Furthermore, readability

关键词： Ruby Iterative Development Agile Software Development Host Language Bioinformatics Domain

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Handling Failures of Static Sensor Nodes in Wireless Sensor Network by Use of Mobile Sensors

Handling Failures of Static Sensor Nodes in Wireless Sensor ...

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International Conference on Advanced Information Networking and Applications Workshops (AINAW)

作者： Edison Pignaton de Freitas Tales Heimfarth Ivayr Farah Netto Carlos Eduardo Pereira Armando Morado Ferreira Flavio Rech Wagner Tony Larsson IDE Halmstad University Halmstad Sweden Institute of Informatics Federal University of Rio Grande do Sul Porto Alegre Brazil Computer Science Department Federal University of Lavras Lavras Brazil Electrical Engineering Department Federal University of Rio Grande do Sul Porto Alegre Brazil Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

关键词： Wireless sensor networks Mobile communication Surveillance Redundancy Sensors Proposals

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Lung cancer diseases diagnostic asistance using Gray color analysis

Lung cancer diseases diagnostic asistance using Gray color a...

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International Conference on Computational Intelligence, Modelling and Simulation

作者： Paulus Gaol, Ford Lumban Graduate Program in Informatics Engineering Department of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9780769542621

Errors in diagnosing the disease is a critical risk that must be faced by any person giving treatment to the hospital. Medical treatment can not always be done with perfect accuracy. Lung cancer is one of the most deadly disease that prone to misdiagnose. In general, some practitioners tend to read cancer in x-ray rontgen image as tumor this could be fatal. To generate a diagnose, a general practitioner use three kind of examination i.e : patient History, Radiologic examination, phisical examination. In this paper, Gray color for image indexing and retrieval are investigated. The features are derived based on the statistical distribution of Harralick feature from image sample. By utilizing the proposed invariant features, the similarity measure between query and database images provides reliable retrieval results. © 2010 IEEE.

关键词： Diseases

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A fuzzy inference system to determine the number of clones in the clonal selection algorithm

A fuzzy inference system to determine the number of clones i...

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2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010

作者： Carraro, Luiz Antonio De Castro, Leandro Nunes De Ré, Angelita Maria Computer and Informatics Faculty Graduate Program in Electrical Engineering Mackenzie University São Paulo Brazil Computer Science Department State University of West-Center Parana Guarapuava Brazil

ISBN: (纸本)9781424473762

Artificial Immune Systems (AISs) are composed of techniques inspired by immunology. The clonal selection principle ensures the organism adaptation to fight invading antigens by an immune response activated by the binding of antigens and antibodies. As an immune response can be elicited even when the binding between an antigen and an antibody is not perfect, an approximate binding might suffice, and a Fuzzy Logic mechanism might be the most appropriate mechanism to control such process. This paper presents a novel hybrid model based on concepts of Immune and Fuzzy Systems with applications to pattern recognition problems. The preliminary results obtained here suggest the proposed model is a promising pattern recognition tool. © 2010 IEEE.

关键词： Fuzzy systems

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