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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Arinze Akutekwe Huseyin Seker Bio-Health Informatics Research Group Department of Computer Science and Digital Technologies Faculty of Engineering and Environment University of Northumbria at Newcastle Newcastle upon Tyne NE1 8ST UK

ISBN: (纸本)9781424492695

Comprehensive understanding of gene regulatory networks (GRNs) is a major challenge in systems biology. Most methods for modeling and inferring the dynamics of GRNs, such as those based on state space models, vector autoregressive models and G1DBN algorithm, assume linear dependencies among genes. However, this strong assumption does not make for true representation of time-course relationships across the genes, which are inherently nonlinear. Nonlinear modeling methods such as the S-systems and causal structure identification (CSI) have been proposed, but are known to be statistically inefficient and analytically intractable in high dimensions. To overcome these limitations, we propose an optimized ensemble approach based on support vector regression (SVR) and dynamic Bayesian networks (DBNs). The method called SVR-DBN, uses nonlinear kernels of the SVR to infer the temporal relationships among genes within the DBN framework. The two-stage ensemble is further improved by SVR parameter optimization using Particle Swarm Optimization. Results on eight insilico-generated datasets, and two real world datasets of Drosophila Melanogaster and Escherichia Coli, show that our method outperformed the G1DBN algorithm by a total average accuracy of 12% We further applied our method to model the time-course relationships of ovarian carcinoma. From our results, four hub genes were discovered. Stratified analysis further showed that the expression levels Prostrate differentiation factor and BTG family member 2 genes, were significantly increased by the cisplatin and oxaliplatin platinum drugs;while expression levels of Polo-like kinase and Cyclin B1 genes, were both decreased by the platinum drugs. These hub genes might be potential biomarkers for ovarian carcinoma.

关键词： CSI DBN BTG Bayesian networks Gene Regulatory Networks Ovarian epithelial cancer systems biology Genes beta-Thromboglobulin Support Vector Network nonlinearity Drosophila melanogaster ELAVL2 gene HUB

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Presentation of the Church of Zelemér in the Virtual Collaboration Arena (VirCA)

Presentation of the Church of Zelemér in the Virtual Collab...

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International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Attila Gilányi Marianna Bálint Róbert Hajdu Sándor Tarsoly Imre Erdős Faculty of Informatics University of Debrecen Debrecen Hungary Hajdúsági Museum Hajdúböszörmény Hungary Institute for Computer Science and Control Hungarian Academy of Sciences Budapest Hungary Faculty of Engineering University of Debrecen Debrecen Hungary

We present a three-dimensional visualization of the medieval Church of Zelemer developed in the Virtual Collaboration Arena (VirCA).

关键词： Libraries Visualization Buildings Conferences Collaboration Electronic mail Three-dimensional displays

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SupraBiology 2014： Promoting UK-China collaboration on Systems Biology and High Performance Computing

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Frontiers of Electrical and Electronic engineering in China 2015年第1期10卷 46-53页

作者： Ettore Murabito Riccardo Colombo Chengkun Wu Malkhey Verma Samrina Rehman Jacky Snoep Shao-Liang Peng Naiyang Guan Xiangke Liao Hans V. Westerhoff Manchester Institute of Biotechnology School of Computer Science Faculty of Engineering and Physical Sciences Manchester Centre for Integrative Systems Biology The University of Manchester Manchester M139PL United Kingdom. Department of Informatics Systems and Communication University of Milan-Bicocca Milan 20126 Italy. SYSBIO - Centre of Systems Biology Milan 20126 Italy. Manchester Institute of Biotechnology School of Chemical Engineering and Analytical Sciences Manchester Centre forIntegrative Systems Biology The University of Manchester Manchester M139PL United Kingdom. School of Computer Science National University of Defence Technology Changsha 410073China

In the second half of 2014 the Manchester Institute of Biotechnology, based in Manchester （UK）, hosted the first SupraBiology congress, an event attended by representa- tives of different academic institutions and industry based in both the UK and China. The congress was aimed to serve as a platform to discuss and promote potential collaborations between the UK and China on the subject of Systems Biology and High Performance Computing. The event, sponsored by the ＂BBSRC China Partnering Awards＂ and ISBE, was organised as a sequence of talks addressing the different aspects of Systems Biology that can benefit from High Performance Computing. A general discussion session followed where the scientific, techni- cal, and logistic aspects of the prospected UK-China collaborations were examined.

关键词： 2014 UK-China High Performance Computing

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Search for Higgs boson pair production in the WW(∗)WW(∗) decay channel using ATLAS data recorded at √s = 13 TeV

arXiv

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arXiv 2018年

作者： Aaboud, M. Aad, G. Abbott, B. Abdinov, O. Abeloos, B. Abhayasinghe, D.K. Abidi, S.H. AbouZeid, O.S. Abraham, N.L. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B.S. Adachi, S. Adam, L. Adamczyk, L. Adelman, J. Adersberger, M. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agheorghiesei, C. Aguilar-Saavedra, J.A. Ahmadov, F. Aielli, G. Akatsuka, S. Åkesson, T.P.A. Akilli, E. Akimov, A.V. Alberghi, G.L. Albert, J. Albicocco, P. Alconada Verzini, M.J. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alhroob, M. Ali, B. Alimonti, G. Alison, J. Alkire, S.P. Allaire, C. Allbrooke, B.M.M. Allen, B.W. Allport, P.P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A.A. Alstaty, M.I. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M.G. Amadio, B.T. Amaral Coutinho, Y. Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Amor Dos Santos, S.P. Amoroso, S. Amrouche, C.S. Anastopoulos, C. Ancu, L.S. Andari, N. Andeen, T. Anders, C.F. Anders, J.K. Anderson, K.J. Andreazza, A. Andrei, V. Anelli, C.R. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antonelli, M. Antrim, D.J.A. Anulli, F. Aoki, M. Aparisi Pozo, J.A. Aperio Bella, L. Arabidze, G. Araque, J.P. Araujo Ferraz, V. Araujo Pereira, R. Arce, A.T.H. Ardell, R.E. Arduh, F.A. Arguin, J-F. Argyropoulos, S. Armbruster, A.J. Armitage, L.J. Armstrong, A. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Asimakopoulou, E.M. Asquith, L. Assamagan, K. Astalos, R. Atkin, R.J. Atkinson, M. Atlay, N.B. Augsten, K. Avolio, G. Avramidou, R. Ayoub, M.K. Azuelos, G. Baas, A.E. Baca, M.J. Bachacou, H. Bachas, K. Backes, M. Bagnaia, P. Bahmani, M. Bahrasemani, H. Bailey, A.J. Baines, J.T. Bajic, M. Bakalis, C. Baker, O.K. Bakker, P.J. Bakshi Gupta, D. Balaji, S. Baldin, E.M. Balek, P. Balli, F. Balunas, W.K. Balz, J. Banas, E. Bandyopadhyay, A. Banerjee, S. Bannoura, A.A.E. Barak, L. Barbe, W.M. Barberio, E.L. Department of Physics University of Adelaide Adelaide Australia Physics Department SUNY Albany AlbanyNY United States Department of Physics University of Alberta EdmontonAB Canada Department of Physics Ankara University Ankara Turkey LAPP Université Grenoble Alpes Université Savoie Mont Blanc CNRS/IN2P3 Annecy France High Energy Physics Division Argonne National Laboratory ArgonneIL United States Department of Physics University of Arizona TucsonAZ United States Department of Physics University of Texas at Arlington ArlingtonTX United States Physics Department National and Kapodistrian University of Athens Athens Greece Physics Department National Technical University of Athens Zografou Greece Department of Physics University of Texas at Austin AustinTX United States Bahcesehir University Faculty of Engineering and Natural Sciences Istanbul Turkey Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Barcelona Institute of Science and Technology Barcelona Spain Institute of High Energy Physics Chinese Academy of Sciences Beijing China Institute of Physics University of Belgrade Belgrade Serbia Department for Physics and Technology University of Bergen Bergen Norway Physics Division Lawrence Berkeley National Laboratory University of California BerkeleyCA United States Institut für Physik Humboldt Universität zu Berlin Berlin Germany Albert Einstein Center for Fundamental Physics Laboratory for High Energy Physics University of Bern Bern Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom Centro de Investigaciónes Universidad Antonio Nariño Bogota Colombia Dipartimento di Fisica e Astronomia Università di Bologna Bologna Italy Physikalisches Institut Universität Bonn Bonn Germany Department of Physics Boston University BostonMA United States Department of Physics Brandeis University WalthamMA United States Transilvania University of Brasov Brasov Romania Faculty of

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Study of the hard double-parton scattering contribution to inclusive four-lepton production in pp collisions at √s = 8 TeV with the ATLAS detector

arXiv

引用

arXiv 2018年

作者： Aaboud, M. Aad, G. Abbott, B. Abdinov, O. Abeloos, B. Abhayasinghe, D.K. Abidi, S.H. AbouZeid, O.S. Abraham, N.L. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B.S. Adachi, S. Adam, L. Adamczyk, L. Adelman, J. Adersberger, M. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agheorghiesei, C. Aguilar-Saavedra, J.A. Ahmadov, F. Aielli, G. Akatsuka, S. Åkesson, T.P.A. Akilli, E. Akimov, A.V. Alberghi, G.L. Albert, J. Albicocco, P. Alconada Verzini, M.J. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alhroob, M. Ali, B. Alimonti, G. Alison, J. Alkire, S.P. Allaire, C. Allbrooke, B.M.M. Allen, B.W. Allport, P.P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A.A. Alstaty, M.I. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M.G. Amadio, B.T. Amaral Coutinho, Y. Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Amor Dos Santos, S.P. Amoroso, S. Amrouche, C.S. Anastopoulos, C. Ancu, L.S. Andari, N. Andeen, T. Anders, C.F. Anders, J.K. Anderson, K.J. Andreazza, A. Andrei, V. Anelli, C.R. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antonelli, M. Antrim, D.J.A. Anulli, F. Aoki, M. Aparisi Pozo, J. Aperio Bella, L. Arabidze, G. Araque, J.P. Araujo Ferraz, V. Araujo Pereira, R. Arce, A.T.H. Ardell, R.E. Arduh, F.A. Arguin, J-F. Argyropoulos, S. Armbruster, A.J. Armitage, L.J. Armstrong, A. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Asimakopoulou, E.M. Asquith, L. Assamagan, K. Astalos, R. Atkin, R.J. Atkinson, M. Atlay, N.B. Augsten, K. Avolio, G. Avramidou, R. Ayoub, M.K. Azuelos, G. Baas, A.E. Baca, M.J. Bachacou, H. Bachas, K. Backes, M. Bagnaia, P. Bahmani, M. Bahrasemani, H. Bailey, A.J. Baines, J.T. Bajic, M. Bakalis, C. Baker, O.K. Bakker, P.J. Bakshi Gupta, D. Balaji, S. Baldin, E.M. Balek, P. Balli, F. Balunas, W.K. Balz, J. Banas, E. Bandyopadhyay, A. Banerjee, S. Bannoura, A.A.E. Barak, L. Barbe, W.M. Barberio, E.L. Barberis, D. Department of Physics University of Adelaide Adelaide Australia Physics Department SUNY Albany AlbanyNY United States Department of Physics University of Alberta EdmontonAB Canada Department of Physics Ankara University Ankara Turkey LAPP Université Grenoble Alpes Université Savoie Mont Blanc CNRS/IN2P3 Annecy France High Energy Physics Division Argonne National Laboratory ArgonneIL United States Department of Physics University of Arizona TucsonAZ United States Department of Physics University of Texas at Arlington ArlingtonTX United States Physics Department National and Kapodistrian University of Athens Athens Greece Physics Department National Technical University of Athens Zografou Greece Department of Physics University of Texas at Austin AustinTX United States Bahcesehir University Faculty of Engineering and Natural Sciences Istanbul Turkey Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Barcelona Institute of Science and Technology Barcelona Spain Institute of High Energy Physics Chinese Academy of Sciences Beijing China Institute of Physics University of Belgrade Belgrade Serbia Department for Physics and Technology University of Bergen Bergen Norway Physics Division Lawrence Berkeley National Laboratory University of California BerkeleyCA United States Institut für Physik Humboldt Universität zu Berlin Berlin Germany Albert Einstein Center for Fundamental Physics Laboratory for High Energy Physics University of Bern Bern Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom Centro de Investigaciónes Universidad Antonio Nariño Bogota Colombia Dipartimento di Fisica e Astronomia Università di Bologna Bologna Italy Physikalisches Institut Universität Bonn Bonn Germany Department of Physics Boston University BostonMA United States Department of Physics Brandeis University WalthamMA United States Transilvania University of Brasov Brasov Romania Faculty of

The inclusive production of four isolated charged leptons in pp collisions is analysed for the presence of hard double-parton scattering, using 20.2 fb−1 of data recorded in the ATLAS detector at the LHC at centre-of-mass energy √s = 8 TeV. In the four-lepton invariant-mass range of 80 4` DPS = 0.042, which results in an estimated lower limit on the effective cross section at 95% confidence level of 1.0 mb. Copyright © 2018, The Authors. All rights reserved.

关键词： Elementary particles

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A pictorial mobile-based communication application for non-verbal people with autism

A pictorial mobile-based communication application for non-v...

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2014 International Conference on Interactive Collaborative Learning, ICL 2014

作者： El-Seoud, M. Samir Abou Karkar, Abdel Ghani Al Ja'Am, Jihad M. Karam, Omar H. Faculty of Informatics and Computer Science British University in Egypt - BUE Egypt Dept. of Computer Science and Engineering Qatar University Doha Qatar

ISBN: (纸本)9781479944378

Non-verbal people with autism are usually unable to communicate normally using natural languages. They can, however, learn to communicate through specific symbols and images. Special education instructors have adopted this method of communication to teach non-verbal people with autism. They introduce the symbols and images to them through different methodologies. This learning process appeared to be effective but it is very long. The process is carried out manually and requires a lots of times, dedication, and resources. The instructors should find the materials in different formats and circumstances. They should repeat the lessons several times and normally in a face-to-face framework. We propose in this paper a mobile-based application that allows non-verbal people with autism to learn and communicate with their surroundings using a smart device. They can then be taught to use specific symbols and images through the smart mobile phones. They can form simple words and sentences to express their feelings and needs. The application is flexible and allows the addition of new contents very easily. To assess the progress of the users, different exercises and puzzles are proposed. These allow the users to improve their skills and to continue learning outside the classrooms. © 2014 IEEE.

关键词： Teaching

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Time series modelling with Fuzzy Cognitive Maps: Study on an alternative concept's representation method 7

Time series modelling with Fuzzy Cognitive Maps: Study on an...

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7th International Conference on Agents and Artificial Intelligence, ICAART 2015

作者： Homenda, Wladyslaw Jastrzebska, Agnieszka Pedrycz, Witold Faculty of Mathematics and Information Science Warsaw University of Technology ul. Koszykowa 75 Warsaw00-662 Poland Faculty of Economics and Informatics in Vilnius University of Bialystok Kalvariju G. 135 VilniusLT-08221 Lithuania System Research Institute Polish Academy of Sciences ul. Newelska 6 Warsaw01-447 Poland Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2G7 Canada

ISBN: (纸本)9789897580741

In the article we have discussed an approach to time series modelling based on Fuzzy Cognitive Maps (FCMs). We have introduced FCM design method that is based on replicated ordered time series data points. We named this representation method history h, where h is number of consecutive data points we gather. Custom procedure for concepts/nodes extraction follows the same convention. The objective of the study reported in this paper was to investigate how increasing h influences modelling accuracy. We have shown on a selection of 12 time series that the higher the h, the smaller the error. Increasing h improves model's quality without increasing FCM's size. The method is stable - gains are comparable for FCMs of different sizes.

关键词： Fuzzy Cognitive Maps

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Rejecting foreign elements in pattern recognition problem: Reinforced training of rejection level 7

Rejecting foreign elements in pattern recognition problem: R...

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7th International Conference on Agents and Artificial Intelligence, ICAART 2015

ISBN: (纸本)9789897580741

Standard assumption of pattern recognition problem is that processed elements belong to recognized classes. However, in practice, we are often faced with elements presented to recognizers, which do not belong to such classes. For instance, paper-to-computer recognition technologies (e.g. character or music recognition technologies, both printed and handwritten) must cope with garbage elements produced at segmentation level. In this paper we distinguish between elements of desired classes and other ones. We call them native and foreign elements, respectively. The assumption that we have only native elements results in incorrect inclusion of foreign ones into desired classes. Since foreign elements are usually not known at the stage of recognizer construction, standard classification methods fail to eliminate them. In this paper we study construction of recognizers based on support vector machines and aimed on coping with foreign elements. Several tests are performed on real-world data.

关键词： Support vector machines

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Resource Usage Prediction Algorithms for Optimal Selection of Multimedia Content Delivery Methods

Resource Usage Prediction Algorithms for Optimal Selection o...

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IEEE International Conference on Communications

作者： Yiannos Kryftis Constandinos X. Mavromoustakis Joel J. P. C. Rodrigues George Mastorakis Evangelos Pallis Ciprian Dobre Jordi Mongay Batalla Georgios Kormentzas Department of Computer Science University of Nicosia Department of Informatics Instituto de Telecomunicacoes University of Beira Interior Portugal and University ITMO Department of Informatics Engineering Technological Educational Institute of Crete Faculty of Autonomic Control and Computers University Politehnica of Bucharest National Institute of Telecommunications Department of Information and Communication Systems Engineering University of the Aegean

ISBN: (纸本)9781467364300

This paper proposes two algorithms adopted in a prototype network architecture, for optimal selection of multimedia content delivery methods, as well as balanced delivery load, by exploiting a novel resource prediction engine. The proposed architecture exploits both algorithms for the prediction of future multimedia services demands, by providing the ability to keep optimal the distribution of the streaming data, among Content Delivery Networks, cloud-based providers and Home Media Gateways. In addition, the prediction of the upcoming fluctuations of the network, provides the ability to the proposed network architecture, achieving optimized Quality of Service (QoS) and Quality of Experience (QoE) for the end users. Both algorithms were evaluated to establish their efficiency, towards effectively predicting future network traffic demands. The experimental results validated their performance and indicated fields for further research and experimentation.

关键词： Resource Prediction Engine Resource Usage Prediction Algorithms Content Delivery Networks Multimedia Services Systems

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Optimization Process of Glycerol Esterification Using Real Time Adaptive Control

Optimization Process of Glycerol Esterification Using Real T...

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International Conference on Advanced computer science and Information Systems

作者： Iwan Aang Soenandi Ani Suryani Taufik Djatna Irzaman Post Graduate Program of Agro-industrial Technology Bogor Agricultural University Dramaga Indonesia Lecturer Faculty of Engineering and Computer Science Krida Wacana Christian University Post Graduate Program of Agro-industrial Technology Bogor Agricultural University. Dramaga Indonesia Post Graduate Program of Agro-industrial Technology and Graduate Program of Computer Science Bogor Agricultural University. Dramaga Indonesia Department of Physics Faculty Mathematics and Natural Sciences Bogor Agricultural University. Dramaga Indonesia

ISBN: (纸本)9781509003648

The synthesis reaction used in esterification needs high energy consumption and a precise processing time to get the best yield of target. In this study, a model was formulated to optimize glycerol esterification process by minimizing the time needed for the process and maximizing the yield of Mono-glycerides. This optimization has gained importance for boosting the esterification industry and improving the production efficiency. Optimization through adaptive monitoring and control has provided significant advances in the process efficiency, a lower energy consumption and a better product quality. This paper presents the optimization with a computational algorithm in real time and adaptive control (RTAC), as compared to the conventional (traditional) methods to monitor and control of glycerol esterification processes. The identification of esterification status based on temperature and time are evaluated to strengthen the optimization. An adaptive method as feature selection to select wavelength IR sensors at specified intervals was carried out with Relief algorithm and Adaptive Pillar K-means clustering method to set the parameter control was proposed in this paper. Many combinations were evaluated from real time condition process, to achieve the best optimization results. The experimental results demonstrate that real time adaptive control can be achieved by using three clusters, which are heating up, stabilizing and finishing. In RTAC, each cluster has its own parameter to set the control point by the servo motor that was attached to magnetic stirrer-heater. By using optimization parameter for each cluster, esterification process time can be shortened by 15-20 minutes with a higher yield (7% or more), lower range stirrer rotation (300rpm-450 rpm) and a lower final temperature of 200℃ - 210℃.

关键词： Optimization Real Time Adaptive Control Glycerol Esterification

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