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International Conference on Asian Language Processing (IALP)

作者： Suhaila Saee Lay-Ki Soon Tek-Yong Lim Bali Ranaivo-Malançon Jovianna Juk Enya Kong Tang Faculty of Computing and Informatics Multimedia University Cyberjaya Selangor Malaysia Faculty of Computer Science and IT Universiti Malaysia Sarawak Kota Samarahan Sarawak Malaysia Linton University College School of Computer Science and Information Technology Mantin Negeri Sembilan Malaysia

Computational morphological resources are the crucial component needed in providing morphological information to create morphological analyser. To acquire the morphological resources in a manual way, two main components are required. The components, which are preprocessing and morphology induction, have led to two issues: i) time consuming and ii) ambiguity in managing the resources from under-resourced languages perspective. We proposed an automatic acquisition of morphological resources tool, which is an extension from the manual way, to overcome the mentioned issues. In this work, three main modules in the proposed automatic tool are: i) tokenization - to tokenise a raw text and generate a wordlist, ii) conversion - to convert a softcopy of morphological resources into required formats and iii) integration of segmentation tools - to integrate two established segmentation tools, namely, Linguistica and Morfessor, in obtaining morphological information from the generated wordlist. Two testing methods have been conducted are component and integration testing. Result shows the proposed tool has been devised and the effectiveness has been demonstrated which allows the linguist to obtain their wordlist and segmented data easily. We believe the proposed tool will assist other researchers to construct computational morphological resources in automated way for under-resourced languages.

关键词： Testing Morphology Manuals Educational institutions Computer science Conferences

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Motion planning and control of ladder climbing on DRC-Hubo for DARPA Robotics Challenge

Motion planning and control of ladder climbing on DRC-Hubo f...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yajia Zhang Jingru Luo Kris Hauser H. Andy Park Manas Paldhe C. S. George Lee Robert Ellenberg Brittany Killen Paul Oh Jun Ho Oh Jungho Lee Inhyeok Kim School of Informatics & Computing Indiana University Bloomington USA School of Electrical & Computer Engineering Purdue University USA Purdue University System West Lafayette IN US Mechanical Engineering & Mechanics Drexel University USA Korea Advanced Institute of Science and Technology South Korea Rainbow Co. South Korea

This video presents our preliminary work towards addressing the ladder climbing event in DARPA Robotics Challenge (DRC) using DRC-Hubo robot. A ladder-climbing motion planner is developed which generates a collision-free, stable quasi-static trajectory for execution. Compliance control is enabled on arm joints to compensate for the calibration error, modeling error and control error. We have demonstrated that DRC-Hubo can robustly climb a variety of ladders in simulation and successfully climb a ship ladder on the hardware.

关键词： Collision avoidance Marine vehicles Humanoid robots Joints Robustness Hardware

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Caching of Content-Centric Networking under bursty content requests

Caching of Content-Centric Networking under bursty content r...

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IEEE Conference on Wireless Communications and Networking

作者： Haozhe Wang Geyong Min Jia Hu Hao Yin Wang Miao School of Computing Informatics and Media University of Bradford UK College of Engineering Mathematics and Physical Sciences University of Exeter UK Department of Computer Science Liverpool Hope University UK Research Institute of Information Technology Tsinghua University P. R. China

ISBN: (纸本)9781479930845

The rapid development in wireless technologies and multimedia services has given rise to new requirements for the Internet, such as supporting billions of mobile devices and transmitting huge amount of multimedia content in real time. Content-Centric Networking (CCN), a future Internet architecture for efficient content dissemination, has been attracting ever-increasing attention from both academia and industry. In this paper, a new analytical model is developed as a cost-effective tool to investigate the performance of caching in CCN under bursty content requests. The accuracy of the model is validated through comparing the analytical results with those obtained from the extensive simulation experiments. As an example of its applications, the analytical model is used to investigate the effects of the cache size, content size, and bursty content requests on the cache hit ratio in CCN.

关键词： Analytical models Mobile communication Internet Wireless networks Educational institutions Mobile computing Accuracy

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Full-text based context-rich heterogeneous network mining approach for citation recommendation 14

Full-text based context-rich heterogeneous network mining ap...

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IEEE/ACM Joint Conference on Digital Libraries(JCDL)

作者： Xiaozhong Liu Yingying Yu Chun Guo Yizhou Sun Liangcai Gao School of Informatics and Computing Indiana University Bloomington Bloomington IN USA College of Transportation Management Dalian Maritime University Dalian China College of Computer and Information Science Northeastern University Boston MA USA Institute of Computer Science and Technology Peking University Beijing China

ISBN: (纸本)9781479955695

Citation relationship between scientific publications has been successfully used for scholarly bibliometrics, information retrieval and data mining tasks, and citation-based recommendation algorithms are well documented. While previous studies investigated citation relations from various viewpoints, most of them share the same assumption that, if paper 1 cites paper 2 (or author 1 cites author 2 ), they are connected, regardless of citation importance, sentiment, reason, topic, or motivation. However, this assumption is oversimplified. In this study, we employ an innovative “context-rich heterogeneous network” approach, which paves a new way for citation recommendation task. In the network, we characterize (1) the importance of citation relationships between citing and cited papers, and (2) the topical citation motivation. Unlike earlier studies, the citation information, in this paper, is characterized by citation textual contexts extracted from the full-text citing paper. We also propose algorithm to cope with the situation when large portion of full-text missing information exists in the bibliographic repository. Evaluation results show that, context-rich heterogeneous network can significantly enhance the citation recommendation performance.

关键词： Context Educational institutions Data mining Citation analysis Inference algorithms Focusing Abstracts

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Accuracy vs. robustness: Bi-criteria optimized ensemble of metamodels 14

Accuracy vs. robustness: Bi-criteria optimized ensemble of m...

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Simulation Winter Conference

作者： Can Cui Teresa Wu Mengqi Hu Jeffery D. Weir Xianghua Chu School of Computing Informatics Decision Systems Engineering Arizona State University Tempe AZ USA Department of Industrial and Systems Engineering Mississippi State University Starkville MS USA Department of Operational Sciences Air Force Institute of Technology Ohio USA Shenzhen Graduate School Xili University Town Guangdong CHINA

Simulation has been widely used in modeling engineering systems. A metamodel is a surrogate model used to approximate a computationally expensive simulation model. Extensive research has investigated the performance of different metamodeling techniques in terms of accuracy and/or robustness and concluded no model outperforms others across diverse problem structures. Motivated by this finding, this research proposes a bi-criteria (accuracy and robustness) optimized ensemble framework to optimally identify the contributions from each metamodel (Kriging, Support Vector Regression and Radial Basis Function), where uncertainties are modeled for evaluating robustness. Twenty-eight functions from the literature are tested. It is observed for most problems, a Pareto Frontier is obtained, while for some problems only a single point is obtained. Seven geometrical and statistical metrics are introduced to explore the relationships between the function properties and the ensemble models. It is concluded that the bi-criteria optimized ensembles render not only accurate but also robust metamodels.

关键词： Computational modeling Accuracy Robustness Uncertainty Predictive models Optimization

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ZZ→ℓ+ℓ−ℓ′+ℓ′− cross-section measurements and search for anomalous triple gauge couplings in 13 TeV pp collisions with the ATLAS detector

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Physical Review D 2018年第3期97卷 032005-032005页

作者： M. Aaboud G. Aad B. Abbott O. Abdinov B. Abeloos S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu R. Abreu Y. Abulaiti B. S. Acharya S. Adachi L. Adamczyk J. Adelman M. Adersberger T. Adye A. A. Affolder Y. Afik T. Agatonovic-Jovin C. Agheorghiesei J. A. Aguilar-Saavedra S. P. Ahlen F. Ahmadov G. Aielli S. Akatsuka H. Akerstedt T. P. A. Åkesson E. Akilli A. V. Akimov G. L. Alberghi J. Albert P. Albicocco M. J. Alconada Verzini S. C. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa G. Alexander T. Alexopoulos M. Alhroob B. Ali M. Aliev G. Alimonti J. Alison S. P. Alkire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. A. Alshehri M. I. Alstaty B. Alvarez Gonzalez D. Álvarez Piqueras M. G. Alviggi B. T. Amadio Y. Amaral Coutinho C. Amelung D. Amidei S. P. Amor Dos Santos S. Amoroso G. Amundsen C. Anastopoulos L. S. Ancu N. Andari T. Andeen C. F. Anders J. K. Anders K. J. Anderson A. Andreazza V. Andrei S. Angelidakis I. Angelozzi A. Angerami A. V. Anisenkov N. Anjos A. Annovi C. Antel M. Antonelli A. Antonov D. J. Antrim F. Anulli M. Aoki L. Aperio Bella G. Arabidze Y. Arai J. P. Araque V. Araujo Ferraz A. T. H. Arce R. E. Ardell F. A. Arduh J-F. Arguin S. Argyropoulos M. Arik A. J. Armbruster L. J. Armitage O. Arnaez H. Arnold M. Arratia O. Arslan A. Artamonov G. Artoni S. Artz S. Asai N. Asbah A. Ashkenazi L. Asquith K. Assamagan R. Astalos M. Atkinson N. B. Atlay K. Augsten G. Avolio B. Axen M. K. Ayoub G. Azuelos A. E. Baas M. J. Baca H. Bachacou K. Bachas M. Backes P. Bagnaia M. Bahmani H. Bahrasemani J. T. Baines M. Bajic O. K. Baker E. M. Baldin P. Balek F. Balli W. K. Balunas E. Banas A. Bandyopadhyay Sw. Banerjee A. A. E. Bannoura L. Barak E. L. Barberio D. Barberis M. Barbero T. Barillari M-S Barisits J. T. Barkeloo T. Barklow N. Barlow S. L. Barnes B. M. Barnett R. M. Barnett Z. Barnovska-Blenessy A. Baroncelli G. Barone A. J. Barr L. Barranco Navarro F. Barreiro J. Barreiro Guimarães da Costa R. Bartoldus A. E. Barton P. Bartos A. Basalaev A. B Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Ontario Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene Oregon USA Department of Physics Stockholm University Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb Illinois USA Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas - LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos Universidad de Granada Granada Portugal Department of Physics Boston University Boston Massachusetts USA Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Italy Dipartimento di Fisica Un

Measurements of ZZ production in the ℓ+ℓ−ℓ′+ℓ′− channel in proton–proton collisions at 13 TeV center-of-mass energy at the Large Hadron Collider are presented. The data correspond to 36.1 fb−1 of collisions collected by the ATLAS experiment in 2015 and 2016. Here ℓ and ℓ′ stand for electrons or muons. Integrated and differential ZZ→ℓ+ℓ−ℓ′+ℓ′− cross sections with Z→ℓ+ℓ− candidate masses in the range of 66 GeV to 116 GeV are measured in a fiducial phase space corresponding to the detector acceptance and corrected for detector effects. The differential cross sections are presented in bins of twenty observables, including several that describe the jet activity. The integrated cross section is also extrapolated to a total phase space and to all standard model decays of Z bosons with mass between 66 GeV and 116 GeV, resulting in a value of 17.3±0.9[±0.6(stat)±0.5(syst)±0.6(lumi)] pb. The measurements are found to be in good agreement with the standard model. A search for neutral triple gauge couplings is performed using the transverse momentum distribution of the leading Z boson candidate. No evidence for such couplings is found and exclusion limits are set on their parameters.

关键词： Electroweak interaction W & Z bosons Particle data analysis

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A fast approach to unknown tag identification in large scale RFID systems

A fast approach to unknown tag identification in large scale...

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2013 IEEE 2013 22nd International Conference on Computer Communication and Networks, ICCCN 2013

作者： Liu, Xiulong Li, Keqiu Shen, Yanming Min, Geyong Xiao, Bin Qu, Wenyu Li, Hongjuan School of Computer Science and Technology Dalian University of Technology China School of Computing Informatics and Media University of Bradford United Kingdom Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong School of Information Science and Technology Dalian Maritime University China

ISBN: (纸本)9781467357746

Radio Frequency Identification (RFID) technology has been widely applied in many scenarios such as inventory control, supply chain management due to its superior properties including fast identification and relatively long interrogating range over barcode systems. It is critical to efficiently identify the unknown tags because these tags can appear when new tagged objects are moved in or wrongly placed. The state-of-the-art Basic Unknown tag Identification Protocol-with Collision-Fresh slot paring (BUIP-CF) protocol can first deactivate all the known tags and then collect all the unknown tags. However, BUIP-CF protocol investigates an ALOHA-like technique and causes too many tag responses, which results in low efficiency. This paper proposes a Fast Unknown tag Identification (FUI) protocol which investigates an indicator vector to label the unknown tags with a given accuracy and removes the time-consuming tag responses in the deactivation phase. FUI also adopts the classical Enhanced Dynamic Framed Slotted ALOHA (EDFSA) protocol to collect the labeled unknown tags. We then investigate the optimal parameter settings to maximize the performance of the proposed FUI protocol. Extensive simulation experiments are conducted to evaluate the performance of the proposed FUI protocol and the experimental results show that it considerably outperforms the state-of-the-art protocol. © 2013 IEEE.

关键词： Inventory control

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Exploiting mapreduce and data compression for data-intensive applications 13

Exploiting mapreduce and data compression for data-intensive...

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Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2013

作者： Ruan, Guangchen Zhang, Hui Plale, Beth Data to Insight Center School of Informatics and Computing Indiana University United States Pervasive Technology Institute Indiana University United States

ISBN: (纸本)9781450321709

HPC platform shows good success for predominantly computeintensive jobs, however, data intensive jobs still struggle on HPC platform as large amounts of concurrent data movement from I/O nodes to compute nodes can easily saturate the network links. MapReduce, the "moving computation to data" paradigm for many pleasingly parallel applications, assumes that data are resident on local disks and computation is scheduled where the data are located. However, on an HPC machine data must be staged from a broader file system (such as Luster), to HDFS where it can be accessed;this staging can represent a substantial delay in processing. In this paper we look at data compression's effect on reducing bandwidth needs of getting data to the application, as well as its impact on the overall performance of data-intensive applications. Our study examines two types of applications, a 3D-time series caries lesion assessment focusing on large scale medical image dataset, and a HTRC word counting task concerning large scale text analysis running on XSEDE resources. Our extensive experimental results demonstrate significant performance improvement in terms of storage space, data stage-in time, and job execution time. © 2013 by the Association for computing Machinery, Inc.

关键词： MapReduce

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Workflows in a Dashboard: A New Generation of Usability

Workflows in a Dashboard: A New Generation of Usability

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Workshop on Workflows in Support of Large-Scale Science (WORKS)

作者： Sandra Gesing Malcolm Atkinson Rosa Filgueira Ian Taylor Andrew Jones Vlado Stankovski Chee Sun Liew Alessandro Spinuso Gabor Terstyanszky Peter Kacsuk University of Notre Dame Center for Research Computing Notre Dame IN US University of Edinburgh Informatics Forum Edinburgh UK Cardiff University School of Computer Science & Informatics UK University of Ljubljana Ljubljana Slovenia Faculty of Computer Science & Information Technology University of Malaya Kuala Lumpur Malaysia KNMI - Royal Netherlands Meteorological Institute The Netherlands University of Westminster London UK MTA SZTAKI Budapest Hungary

In the last 20 years quite a few mature workflow engines and workflow editors have been developed to support communities in managing workflows. While there is a trend followed by the providers of workflow engines to ease the creation of workflows tailored to their specific workflow system, the management tools still often necessitate much understanding of the workflow concepts and languages. This paper describes the approach targeting various workflow systems and building a single user interface for editing and monitoring workflows under consideration of aspects such as optimization and provenance of data. The design allots agile Web frameworks and novel technologies to build a workflow dashboard offered in a web browser and connecting seamlessly to available workflow systems and external resources like Cloud infrastructures. The user interface eliminates the need to become acquainted with diverse layouts. Thus, the usability is immensely increased for various aspects of managing workflows.

关键词： Engines Communities User interfaces Usability Monitoring Portals Interoperability

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11th German Conference on Chemoinformatics (GCC 2015) Abstracts

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JOURNAL OF CHEMinformatics 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

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