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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A Systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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Message from the demonstrations chair

Proceedings - Conference on Local Computer Networks, LCN

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Proceedings - Conference on Local computer Networks, LCN 2014年

作者： Akkaya, Kemal Aust, Stefan Hollick, Matthias Itaya, Satoko Kantarci, Burak Pfeiffer, Tom Senel, Fatih Strayer, Tim Andersson, Karl Southern Illinois University United States NEC Communication Systems Ltd. Japan TU Darmstadt Germany Smart Wireless Laboratory NICT Japan University of Ottawa Canada TU Berlin Germany International Antalya University Turkey BBN Technologies United States Pervasive and Mobile Computing Laboratory Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden

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Scaling and correlation of human movements in cyberspace and physical space

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Physical Review E 2014年第5期90卷 050802(R)-050802(R)页

作者： Zhi-Dan Zhao Zi-Gang Huang Liang Huang Huan Liu Ying-Cheng Lai Web Sciences Center University of Electronic Science and Technology of China Chengdu 610054 China School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Institute of Computational Physics and Complex Systems and Key Laboratory for Magnetism and Magnetic Materials of MOE Lanzhou University Lanzhou Gansu 730000 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA

Understanding the dynamics of human movements is key to issues of significant current interest such as behavioral prediction, recommendation, and control of epidemic spreading. We collect and analyze big data sets of human movements in both cyberspace (through browsing of websites) and physical space (through mobile towers) and find a superlinear scaling relation between the mean frequency of visit 〈f〉 and its fluctuation σ:σ∼〈f〉β with β≈1.2. The probability distribution of the visiting frequency is found to be a stretched exponential function. We develop a model incorporating two essential ingredients, preferential return and exploration, and show that these are necessary for generating the scaling relation extracted from real data. A striking finding is that human movements in cyberspace and physical space are strongly correlated, indicating a distinctive behavioral identifying characteristic and implying that the behaviors in one space can be used to predict those in the other.

关键词： Probability distributions

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Social Adaptation of Robots for Modulating Self-Organization in Animal Societies

Social Adaptation of Robots for Modulating Self-Organization...

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IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW

作者： Payam Zahadat Michael Bodi Ziad Salem Frank Bonnet Marcelo Elias De Oliveira Francesco Mondada Karlo Griparic Tomislav Haus Stjepan Bogdan Rob Mills Pedro Mariano Luis Correia Olga Kernbach Serge Kernbach Thomas Schmickl Artificial Life Laboratory of the Department of Zoology Karl-Franzens University Graz Austria Computer Engineering Department Aleppo University Syrian Arab Republic Rbotic Systems Laboratory Swiss Federal Institute of Technology (EPFL) Lausanne Switzerland Ecole Polytechnique Federale de Lausanne Lausanne VD CH Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Zagreb Croatia Universidade de Lisboa Lisboa Lisboa PT Cybertronica Research Research Center of Advanced Robotics and Environmental Science Stuttgart Germany

The goal of the work presented here is to influence the overall behaviour of specific animal societies by integrating computational mechatronic devices (robots) into those societies. To do so, these devices should be accepted by the animals aspart of the society and/or as part of the collectively formed environment. For that, we have developed two sets of robotic hardware for integrating into societies of two different animals: zebra fish and young honeybees. We also developed mechanisms to provide feedback from the behaviours of societies for the controllers of the robotic system. Two different computational methods are then used as the controllers of the robots in simulation and successfully adapted by evolutionary algorithms to influence the simulated animals for desired behaviours. Together, these advances in mechatronic hardware, feedback mechanisms, and controller methodology are laying essential foundations to facilitate experiments on modulating self-organised behaviour in mixed animal -- robot societies.

关键词： Animals Heating Vibrations Robot sensing systems Hardware Biochemistry

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Understanding the implications of virtual machine management on processor microarchitecture design

Understanding the implications of virtual machine management...

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2013 IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2013

作者： Sui, Xiufeng Sun, Tao Li, Tao Zhang, Lixin Advanced Computer Systems Laboratory Institute of Computing Technology CAS Beijing China Computer Science and Technology Department University of Science and Technology of China Hefei China Dept. of Electrical and Computer Engineering University of Florida United States

ISBN: (纸本)9781467357777

Cloud computing has demonstrated tremendous capability in a wide spectrum of online services. Virtualization provides an efficient solution to the utilization of modern multicore processor systems while affording significant flexibility. The growing popularity of virtualized datacenters motivates deeper understanding of the interactions between virtual machine management and the micro-architecture behaviors of the privileged domain. We argue that these behaviors must be factored into the design of processor microarchitecture in virtualized datacenters. In this work, we use performance counters on modern servers to study the micro-architectural execution characteristics of the privileged domain while performing various VM management operations. Our study shows that today's state-of-the-art processor still has room for further optimizations when executing virtualized cloud workloads, particularly in the organization of last level caches and on-chip cache coherence protocol. Specifically, our analysis shows that: shared caches could be partitioned to eliminate interference between the privileged domain and guest domains;the cache coherence protocol could support a high degree of data sharing of the privileged domain;and cache capacity or CPU utilization occupied by the privileged domain could be effectively managed when performing management workflows to achieve high system throughput. © 2013 IEEE.

关键词： Virtualization

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Fast mode decision based on optimal stopping theory for multiview video coding

Fast mode decision based on optimal stopping theory for mult...

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19th International Conference on Advances in Multimedia Modeling, MMM 2013

作者： Wang, Hanli Heng, Yue Zhao, Tiesong Xiao, Bo Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China Department of Electrical and Computer Engineering University of Waterloo Waterloo ON Canada

ISBN: (纸本)9783642357275

Optimal stopping theory is developed to achieve a good trade-off between decision performance and decision efforts such as the consumed decision time. In this paper, the optimal stopping theory is applied to fast mode decision for multiview video coding in order to reduce the tremendous encoding computational complexity, with the benefit of theoretical decision-making expectation and predictable decision performance. The characteristics of encoding modes in multiview video coding are studied to derive an optimal stopping theory-based model to early terminate mode decision and thus a fast mode decision algorithm is designed. Extensive experimental results demonstrate that the proposed algorithm can save a great amount of encoding time for multiview video coding and meanwhile keep the compression performance more or less intact. © Springer-Verlag 2013.

关键词： Decision making

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Dynamic performance model of wind turbine generators

Dynamic performance model of wind turbine generators

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IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： Prajwal K. Gautam Ganesh K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Holcombe Department of Electrical and Computer Engineering Clemson University Clemson SC USA

To characterize the power performance of wind turbine generators (WTGs), the International Electrotechnical Commission provides a power curve for each one based on ten minutes average. This approach causes the problem of systematic errors because of the nonlinear relationship between power and wind speed. In this paper, recurrent neural networks are introduced as an alternative approach to model this nonlinear relationship. Based on actual wind speed input and wind power output, an input-output relationship is established for a permanent magnet synchronous machine based wind power generator. Experimental studies are carried out to the develop power curve that characterize dynamic power performance of the wind turbine generator. These dynamic power performance models of wind turbine generators can be used as operational and planning models in control centers. Some preliminary results on the integration of a neural network wind generator model in a micro-grid simulation is presented.

关键词： Wind turbines Wind speed Wind power generation Generators Neural networks Testing

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CNN based power system transient stability margin and voltage stability index prediction

CNN based power system transient stability margin and voltag...

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IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： Karthikeyan Balasubramaniam Ganesh Kumar Venayagamoorthy Neville Watson Real-Time Power and Intelligent Systems Laboratory Holcombe Department of Electrical & Computer Engineering Clemson University Clemson SC USA Department of Electrical Engineering University of Canterbury Christchurch New Zealand

Operators at electric grid control centers are faced with the task of making important decisions in real-time. With the plethora of data available it becomes important to extract information from the available data, based on which knowledge of system condition can be formed. This knowledge can then be used in decision making. Metrics such as transient stability margin (TSM) and voltage stability load index (VSLI) help in assessing the stability of the system. In this study, cellular neural network (CNN) based stability margin prediction system is developed in a distributed computing framework. The developed system not only extracts information from available data but also predicts the same, one step ahead of time. Moreover, the framework employed uses distributed computing and hence could be used on a large scale power system with a linear increase in computation time instead of an exponential increase. A reduced version of New Zealand's South Island power system is used as the test system to demonstrate the feasibility of CNNs for TSM and VSLI prediction.

关键词： Power system stability Generators Stability criteria Rotors Transient analysis

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Power system controller design using multi-population PBIL

Power system controller design using multi-population PBIL

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IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)

作者： Komla Agbenyo Folly Ganesh Kumar Venayagamoorthy Department of Electrical Engineering University of Cape Town Cape Town South Africa Real-Time Power and Intelligent Systems Laboratory Holcombe Department of Electrical & Computer Engineering Clemson University SC USA

The application of a multi-population based Population-Based Incremental Learning (PBIL) to power system controller design is presented in this paper. PBIL is a combination of evolutionary optimization and competitive learning derived from artificial neural networks. Single population PBIL has recently received increasing attention in various engineering fields due to its effectiveness., easy implementation and robustness. Despite these strengths., PBIL still suffers from issues of loss of diversity in the population. The use of multi-population is seen as one way of increasing the diversity in the population. The approach is applied to power system controller design. Simulations results show that the multi-population PBIL approach performs better than the standard PBIL and is as effective as PBIL where adaptive learning is used.

关键词： Vectors Sociology Statistics Standards Power system stability Optimization Control systems

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Workshop on recommender systems meet big data & semantic technologies - SeRSy 2013 13

Workshop on recommender systems meet big data & semantic tec...

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7th ACM Conference on Recommender Systems, RecSys 2013

作者： De Gemmis, Marco Di Noia, Tommaso Lassila, Ora Lops, Pasquale Lukasiewicz, Thomas Semeraro, Giovanni Dept. of Computer Science Univ. of Bari Aldo Moro Italy Electrical and Electronics Engineering Department Technical University of Bari Italy Nokia Location and Commerce Burlington MA United States Computing Laboratory University of Oxford United Kingdom

ISBN: (纸本)9781450324090

The primary goal of the workshop is to showcase cutting edge research on the intersection of Recommender Systems and Semantic Technologies, by taking the best of the two worlds. This combination may provide the RecSys community with important scenarios where the potential of Semantic Technologies can be effectively exploited into systems performing complex tasks, such as recommendation engines processing Big Data. © 2013 ACM.

关键词： Linked data

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