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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Adaptive density-based spatial clustering of applications with noise (DBSCAN) according to data

Adaptive density-based spatial clustering of applications wi...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Wei-Tung Wang Yi-Leh Wu Cheng-Yuan Tang Maw-Kae Hor Dept. of. Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan ROC Dept. of Information Management Huafan University Taipei Taiwan ROC School of Informatics Kainan University Taoyuan Taiwan ROC

ISBN: (纸本)9781467372220

Clustering is a task that aims to grouping data objects into several groups. DBSCAN is a density-based clustering method. However, it requires two parameters and these two parameters are hard to decide. Also, DBSCAN has difficulties in finding clusters when the density changes in the dataset. In this paper, we modify the original DBSCAN to make it able to determine the appropriate eps values according to data distribution and to cluster when the density varies among dataset. The main idea is to run DBSCAN with different eps and Minpts values. We also modified the calculation of the Minpts so that DBSCAN can have better clustering results. We did several experiments to evaluate the performance. The results suggest that our proposed DBSCAN can automatically decide the appropriate eps and Minpts values and can detect clusters with different density-levels.

关键词： Clustering DBSCAN Data mining Cluster Analysis data mining two parameter Dataset data distribution

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Erratum to: Search for diboson resonances in hadronic final states in 139 fb−1 of pp collisions at = 13 TeV with the ATLAS detector

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Journal of High Energy Physics 2020年第6期2020卷 1-19页

作者： Aad, G. Abbott, B. Abbott, D. C. Abdinov, O. Abed Abud, A. Abeling, K. Abhayasinghe, D. K. Abidi, S. H. AbouZeid, O. S. Abraham, N. L. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B. S. Achkar, B. Adachi, S. Adam, L. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Adelman, J. Adersberger, M. Adiguzel, A. Adorni, S. Adye, T. Affolder, A. A. Afik, Y. Agapopoulou, C. Agaras, M. N. Aggarwal, A. Agheorghiesei, C. Aguilar-Saavedra, J. A. Ahmadov, F. Ahmed, W. S. Ai, X. Aielli, G. Akatsuka, S. Åkesson, T. P. A. Akilli, E. Akimov, A. V. Al Khoury, K. Alberghi, G. L. Albert, J. Alconada Verzini, M. J. Alderweireldt, S. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexandre, D. Alexopoulos, T. Alfonsi, A. 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. Alvarez Estevez, M. Álvarez Piqueras, D. Alviggi, M. G. Amaral Coutinho, Y. Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amoroso, S. Amrouche, C. S. An, F. Anastopoulos, C. Andari, N. Andeen, T. Anders, C. F. Anders, J. K. Andreazza, A. Andrei, V. Anelli, C. R. Angelidakis, S. 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. Arcangeletti, C. Arce, A. T. H. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arling, J.-H. Armbruster, A. J. Armitage, L. J. Armstrong, A. Arnaez, O. Arnold, H. 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. Atmani, H. Augsten, K. Avolio, G. Avramidou, R. Ayoub, M. K. Azoulay, A. M. Azuelos, G. Baca, M. J. Bachacou, H. Bachas, K. Backes, M. Backman, F. Bagnaia, P. Bahmani, M. Bahrasemani, H. Bailey, A. J. Bailey, V. R. 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. CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman United States of America Department of Physics University of Massachusetts Amherst United States of America Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan INFN Sezione di Pavia Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark 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 High Energy Physics Division Argonne National Laboratory Argonne United States of America INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom International Center for Elementary Particle Physics and Department of Physics University of Tokyo Tokyo Japan Institut für Physik Universität Mainz Mainz Germany LAL Université Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb United States of America Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Istanbul University Dept. of Physics Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cr

A mistake was identified for the paper [1] in the treatment of the radion [2] cross-sections, which resulted in multiple changes.

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A PubMed Meta search engine based on biomedical entity mining 25

A PubMed Meta search engine based on biomedical entity minin...

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25th International Workshop on Database and Expert Systems Applications, DEXA 2014

作者： Kanavos, Andreas Theodoridis, Evangelos Tsakalidis, Athanasios Computer Engineering and Informatics Department University of Patras Greece Informatics Engineering Dept. Technological Educational Institute of Central Greece Computer Technology Institute and Press Greece

ISBN: (纸本)9781479957224

Biomedical knowledge stored in the web is increasing significantly as most of the biomedical research papers are published online. Biomedical entity extraction is a crucial procedure for efficient text analysis and retrieval. PubMed is a very popular indexing engine, concerning life sciences and biomedical research. Being a free database, it accesses primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics. In this work, we propose a metasearch engine over PubMed, which classifies PubMed results according to their specific topic and the extracted Biomedical entities. This method helps researchers to browse and search in the retrieved results. In order to provide more accurate clustering results, we utilize the biomedical ontology, named MeSH as well as RxNorm which is a tool for supporting semantic interoperation between drug terminologies and pharmacy knowledge base systems. Finally, we embed the proposed methodology in an online system. © 2014 IEEE.

关键词： Semantics

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Do Learners to Create an Artifact with Good Quality Make a Number of Trials and Errors during the Editing Process?

Do Learners to Create an Artifact with Good Quality Make a N...

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International Conference on Applied Computing and Information technology/International Conference on Computational Science and Intelligence (ACIT-CSI)

作者： Takafumi Tanaka Atsuo Hazeyama Hiroaki Hashiura Seiichi Komiya Graduate School of Education Tokyo Gakugei University Tokyo Japan Dept. of Information Science Tokyo Gakugei University Tokyo Japan Dept. of Computer and Information Engineering Nippon Institute of Technology Saitama Japan GRACE Center Nat. Inst. of Inf. Tokyo Japan

Courses to train modeling competence are held in higher educational inst.tutions. These courses focus on the final artifacts submitted by learners for analysis and/or evaluation and do not clarify the intermediate creation process. This study focuses on quality of the final class diagram submitted by learners and trials and errors during the creation process. We tried to verify a hypothesis that learners to create an artifact with good quality make a number of trials and errors during the editing process. We collected the fine-grained data regarding the editing history of class diagrams created by learners by our tool called KIfU. We verified the hypothesis by analyzing the collected data. First, we defined two metrics ("Number of editing" and "Number of movement" of symbols in the artifact) calculated from the data that show the learners' trials and errors. Second, we divided learners into two groups, group that created artifacts with good quality and that with not good quality. Finally, we compared the metrics between the groups. The results show that there are statistically significantly differences of values of both metrics between the groups. We conclude the hypothesis we set is correct from the result.

关键词： Unified modeling language Measurement Software Databases Process modeling History Browsers

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Embedded systems security challenges

Embedded systems security challenges

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4th International Conference on Pervasive and Embedded Computing and Communication Systems, PECCS 2014

作者： Fysarakis, Konstantinos Hatzivasilis, George Rantos, Konstantinos Papanikolaou, Alexandros Manifavas, Charalampos Dept. of Electronic and Computer Engineering Technical University of Crete Chania Greece Dept. of Computer and Informatics Engineering Eastern Macedonia and Thrace Institute of Technology Kavala Greece Dept. of Informatics Engineering Technological Educational Institute of Crete Heraklion Crete Greece

ISBN: (纸本)9789897580000

In a world of pervasive computing, embedded systems can be found in a wide range of products and are employed in various heterogeneous domains. The abovementioned devices often need to access, store, manipulate and/or communicate sensitive or even critical information, making the security of their resources and services an important concern in their design process. These issues are further exacerbated by the resource-constrained nature of the devices, in conjunction with the ever-present need for smaller size and lower production costs. This paper aims to provide an overview of the challenges in designing secure embedded systems, covering both node hardware and software issues, as well as relevant network protocols and cryptographic algorithms. Moreover, recent advances in the field are identified, highlighting opportunities for future research.

关键词： Embedded systems

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DSAPE - Dynamic Security Awareness Program Evaluation

DSAPE - Dynamic Security Awareness Program Evaluation

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2nd International Conference on Human Aspects of Information Security, Privacy, and Trust, HAS 2014 - Held as Part of 16th International Conference on Human-computer Interaction, HCI International 2014

作者： Manifavas, Charalampos Fysarakis, Konstantinos Rantos, Konstantinos Hatzivasilis, George Dept. of Informatics Engineering Technological Educational Institute of Crete Heraklion Crete Greece Dept. of Electronic and Computer Engineering Technical University of Crete Chania Crete Greece Dept. of Computer and Informatics Engineering Eastern Macedonia and Thrace Institute of Technology Kavala Greece

ISBN: (纸本)9783319076195

This paper addresses the importance of continuously evaluating an organization's awareness program and provides guidelines that will help organizations assess their efforts, extending the authors' work in [1]. The proposed methodology evaluates an awareness program considering the most common and essential methods used for delivering awareness material. Key awareness-related processes and accompanying quantitative metrics are identified, along with a methodology for dynamically evaluating the metrics and the overall awareness program as a whole. A software tool is developed, to facilitate the deployment and maintenance of the assessment methods and to formalize their aggregation and evaluation. An organization's security awareness posture is modelled as a dynamic system and the awareness level is calculated and monitored through time via Event Calculus. Furthermore, the tool can be deployed in a multi-agent form, to enable its use by organizations operating through remote offices and distributed locations. © 2014 Springer International Publishing.

关键词： Calculations

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Example-Specific Density Based Matching Kernels for Scene Classification Using Support Vector Machines

Example-Specific Density Based Matching Kernels for Scene Cl...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Abhijeet Sachdev Veena Thenkanidiyoor A.D. Dileep C. Chandra Sekhar School of Computing and Electrical Engineering Indian Institute of Technology Mandi Kamand Himachal Pradesh India Dept. of Comput. Sci. & Eng. Nat. Inst. of Technol. Goa Ponda India Department of Computer Science and Engineering Indian Institute of Technology Madras Chennai Tamilnadu India

In this paper, we propose the example-specific density based matching kernel (ESDMK) for classification of scene images represented as sets of local feature vectors. The proposed kernel is computed between the pair of examples, represented as sets of local feature vectors, by matching the estimates of example-specific densities computed at every local feature vector in those two examples. In this work, the number of local feature vectors of an example among the K nearest neighbors of a local feature vector is considered as an estimate of the example-specific density. The minimum of the two example-specific densities, one for each example, at a local feature vector is considered as the matching score. The ESDMK is then computed as the sum of the matching score computed at every local feature vector in a pair of examples. We also propose the spatial ESDMK (SESDMK) to include spatial information present in the scene images while matching the pair of scene images. Each of the scene images is divided spatially into a fixed number of regions. Then the SESDMK is computed as a combination of region specific ESDMKs that match the corresponding regions. We study the performance of the support vector machine (SVM) based classifiers using the proposed ESDMKs for scene classification and compare with that of the SVM-based classifiers using the state-of-the-art kernels for sets of local feature vectors.

关键词： Kernel Support vector machines Visualization Histograms Feature extraction Semantics Maximum likelihood estimation

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Minimal strongly unsatisfiable subsets of reactive system specifications 14

Minimal strongly unsatisfiable subsets of reactive system sp...

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29th ACM/IEEE International Conference on Automated Software engineering, ASE 2014

作者： Hagihara, Shigeki Egawa, Naoki Shimakawa, Masaya Yonezaki, Naoki Dept. of Computer Science Tokyo Inst. of Technology Japan R and D Division Sony Computer Entertainment Inc. Japan

ISBN: (纸本)9781450330138

Verifying realizability in the specification phase is expected to reduce the development costs of safety-critical reactive systems. If a specification is not realizable, we must correct the specification. However, it is not always obvious what part of a specification should be modified. In this paper, we propose a method for obtaining the location of flaws. Rather than realizability, we use strong satisfiability, due to the fact that many practical unrealizable specifications are also strongly unsatisfiable. Using strong satisfiability, the process of analyzing realizability becomes less complex. We define minimal strongly unsatisfiable subsets (MSUSs) to locate flaws, and construct a procedure to compute them. We also show correctness properties of our method, and clarify the time complexity of our method. Furthermore, we implement the procedure, and confirm that MSUSs are computable for specifications of reactive systems at non-trivial scales. © 2014 ACM.

关键词： Specifications

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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