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International Conference on Information, Intelligence, Systems and Applications

作者： Georgios Drakopoulos Vasileios Megalooikonomou Multidimensional Data Analysis and Knowledge Management Lab Computer Engineering and Informatics Department University of Patras Patras 26500 Hellas

ISBN: (纸本)9781467393126

Approximating and representing a process, a function, or a system with an adaptive parametric model constitutes a major part of current machine learning research. An important characteristic of these models is parameter sparsity, an indicator of how succintly a model can codify fundamental properties of the approximated function. This paper investigates the sparsity patterns of a multilayer perceptron netwrok trained to mount a man-on-the-middle attack on the DES symmetric cryptosystem. The notions of absolute and effective synaptic weight sparsity are introduced and their importance to network learning procedure is explained. Finally, the results from the training of the actual multilayer perceptron are outlined and discussed. In order to promote reproducible research, the MatLab network implementation has been posted in GitHub.

关键词： Absolute synaptic weight sparsity Effective synaptic weight sparsity Higher order computation Private key cryptography Man-in-the-middle attack

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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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Abstract vs concrete clabjects in Dual Deep Instantiation

Abstract vs concrete clabjects in Dual Deep Instantiation

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Workshop on Multi-Level Modelling, MULTI 2014, Co-located with ACM/IEEE 17th International Conference on Model Driven engineering Languages and Systems, MoDELS 2014

作者： Neumayr, Bernd Schrefl, Michael Department of Business Informatics - Data and Knowledge Engineering Johannes Kepler University Linz Austria

Deep Instantiation allows for a compact representation of models with multiple instantiation levels where clabjects combine object and class facets and allow to characterize the schema of model elements several instantiation levels below. Clabjects with common properties may be generalized to superclabjects. In order to clarify the exact nature of superclabjects, Dual Deep Instantiation, a variation of Deep Instantiation, distinguishes between abstract and concrete clabjects and demands that superclabjects are abstract. An abstract clabject combines the notion of abstract class, i.e., it may not be instantiated by concrete objects, and of abstract object, i.e., is does not represent a single concrete object but properties common to a set of concrete objects. This paper clarifies the distinction between abstract and concrete clabjects and discusses the role of concrete clabjects for mandatory constraints at multiple levels and for coping with dual inheritance introduced with the combination of generalization and deep instantiation. The reflections in this paper are formalized based on a simplified form of dual deep instantiation but should be relevant to deep characterization in general.

关键词： Concretes

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Variability in artifact-centric process modeling: The hetero-homogeneous approach 10th

Variability in artifact-centric process modeling: The hetero...

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10th Asia-Pacific Conference on Conceptual Modelling APCCM 2014

作者： Schütz, Christoph Schrefl, Michael Department of Business Informatics-Data and Knowledge Engineering Johannes Kepler University Linz Austria

ISBN: (纸本)9781921770364

Today's dynamic business environment demands from companies variable and flexible processes. Rather than imposing a single fixed process, process models must account for the variability of real-world business problems. Many companies are hierarchically organized with top-down decision making processes. On the one hand, company policies and legal regulations often require compliance with standard process models prescribed by higher-level management. On the other hand, lower-level employees should be flexible within the prescribed boundaries. In this paper, we propose a hetero-homogeneous approach to modeling process variability. We employ the multilevel business artifact (MBA) in order to represent within a single object the homogeneous schema of an abstraction hierarchy of processes. We employ multilevel concretization for the introduction of heterogeneities into sub-hierarchies which comply with the homogeneous global schema. © 2014, Australian Computer Society, Inc.

关键词： Regulatory compliance

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Design and implementation of a dynamic educational content viewer with big data analytics functionality

International Journal of Multimedia and Ubiquitous Engineeri...

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International Journal of Multimedia and Ubiquitous engineering 2014年第12期9卷 73-84页

作者： Seong-Yeon, Ju Song, Min-Ho Ryu, Ga-Ae Kim, Mihye Yoo, Kwan-Hee Department of Business Data Convergence Chungbuk National University Department of Digital Informatics and Convergence Chungbuk National University Department of Software Engineering Chungbuk National University 410 Seongbongro Heungukgu CheongjuChungbuk Korea Republic of Computer Science Education Catholic University of Daegu 13-13 Hanyangro Hayangeup GyeongsansiGyeongsangbukdo Korea Republic of

The use of smart mobile devices has grown considerably in recent years. A large variety of digital content has entered the market and, in particular, there has been rapid growth in sales of electronic books (e-books). Consequently, demand for more diverse digital content has increased greatly as has the demand, in particular, for smart digital content for educational purposes, including digital textbooks. This demand has been accelerated through the implementation of an educational environment termed ‘Smart Education’ in Korea. Digital content and digital textbooks can be displayed on smart devices using a content viewer application or an e-book reader. However, existing content viewers only support a limited range of features, most of which are platform-dependent. In addition, most content viewers do not support features that deliver analysis of big data. To address these shortcomings, here we propose a dynamic educational content viewer, which can implement big data analytics and supports multiple device platforms and a wide range of content types. © 2014 SERSC

关键词： Big data

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The decision-scope approach to specialization of business rules: Application in business process modeling and data warehousing 9th

The decision-scope approach to specialization of business ru...

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9th Asia - Pacific Conference on Conceptual Modelling, APCCM 2013

作者： Schre, Michael Neumayr, Bernd Stumptner, Markus Department of Business Informatics Data and Knowledge Engineering Johannes Kepler Univ. of Linz Austria Advanced Computing Research Centre Knowledge and Software Eng. Lab University of South Australia Australia

ISBN: (纸本)9781921770289

It is common in organizational contexts and in law to apply a decision-scope approach to decision making. Higher organization levels set a decision scope within which lower organization levels may operate. In case of conflict the regulations and rules of a higher level (e.g. European Union) take precedence over those of a lower level (e.g. a member state). This approach can also be beneficially applied to the specialization of the most important kind of business rules in information systems, action rules. Such rules define under which conditions certain actions may, must not, or need to be taken. Applying the decision scope approach to business process modeling based on BPMN means that business rules should not be buried in decision tasks but be made explicit at the flow level. This requires a rethinking of the current BPMN modeling paradigm in that several aspects in conditional flow so far modeled jointly are separately captured: (a) potential ordering of tasks, (b) conditions under which a task may or may not be invoked, and (c) conditions under which a particular task needs to be invoked. Rather than re-defining BPMN as such, an appropriate extension may be provided on-top of BPMN and mapped to standard BPMN primitives. Applying the decision scope approach to active data warehousing, where analysis rules express actionable knowledge, requires to consider two alternative hierarchies: (1) hierarchies of sets of points at the same granularity and (2) the roll-up hierarchy of points in multi-dimensional space. This paper presents the decision scope approach, outlines how it complements inheritance and specialization approaches typically followed in objectoriented systems, and introduces consistency rules for business rule specialization as well as auto-correction rules, which rectify an inconsistent lower-level business rule such that it becomes consistent with higherlevel business rules. © 2013, Australian Computer Society, Inc.

关键词： data warehouses

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Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016

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Implement Sci 2017年第SUPPL 1期12卷 48-48页

作者： David Chambers Lisa Simpson Gila Neta Ulrica von Thiele Schwarz Antoinette Percy-Laurry Gregory A. Aarons Ross Brownson Amanda Vogel Shannon Wiltsey Stirman Kenneth Sherr Rachel Sturke Wynne E. Norton Allyson Varley Cynthia Vinson Lisa Klesges Suzanne Heurtin-Roberts M. Rashad Massoud Leighann Kimble Arne Beck Claire Neely Jennifer Boggs Carmel Nichols Wen Wan Erin Staab Neda Laiteerapong Nathalie Moise Ravi Shah Susan Essock Margaret Handley Amy Jones Jay Carruthers Karina Davidson Lauren Peccoralo Lloyd Sederer Todd Molfenter Ashley Scudder Sarah Taber-Thomas Kristen Schaffner Amy Herschell Eva Woodward Jeffery Pitcock Mona Ritchie JoAnn Kirchner Julia E. Moore Sobia Khan Shusmita Rashid Jamie Park Melissa Courvoisier Sharon Straus Daniel Blonigen Allison Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal David Smelson Christine Timko Nicole Stadnick Jennifer Regan Miya Barnett Anna Lau Lauren Brookman-Frazee Erick Guerrero Karissa Fenwick Yinfei Kong Gregory Aarons Rebecca Lengnick-Hall Benjamin Henwood Nina Sayer Craig Rosen Robert Orazem Brandy Smith Lindsey Zimmerman David Lounsbury Rachel Kimerling Jodie A. Trafton Steven Lindley Rahul Bhargava Hal Roberts Laura Gibson Gabriel J. Escobar Vincent Liu Benjamin Turk Arona Ragins Patricia Kipnis Ashley Ketterer Gruszkowski Michael W. Kennedy Emily Rentschler Drobek Lior Turgeman Aleksandra Sasha Milicevic Terrence L. Hubert Larissa Myaskovsky Youxu C. Tjader Robert J. Monte Kathryn G. Sapnas Edmond Ramly Diane R Lauver Christie M Bartels Shereef Elnahal Andrea Ippolito Hillary Peabody Carolyn Clancy Randall Cebul Thomas Love Douglas Einstadter Shari Bolen Brook Watts Vera Yakovchenko Angela Park William Lukesh Donald R. Miller David Thornton Mari-Lynn Drainoni Allen L. Gifford Shawna Smith Julia Kyle Mark S Bauer Daniel Eisenberg Celeste Liebrecht Michelle Barbaresso Amy Kilbourne Elyse Park Giselle Perez Jamie Ostroff Sarah Greene Michael Parchman Brian Austin Eric Larson Stefanie Ferreri Chris Shea Megan Smith Kea Turner Jennifer Bacci Kyle Bigham Geoffr Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD 20850 USA AcademyHealth Washington DC 20009 USA Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm 17177 Sweden Department of Psychiatry University of California San Diego San Diego CA 92093 USA George Warren Brown School of Social Work Washington University in St. Louis St. Louis MO 63130 USA Center for Global Health National Cancer Institute Rockville MD 20850 USA Dissemination and Training Division VA National Center for PTSD Palo Alto CA 94305 USA Department of Global Health University of Washington Seattle WA 98105 USA Center for Global Health Studies Fogarty International Center National Institutes of Health Bethesda MD 20912 USA School of Public Health University of Alabama at Birmingham Birmingham AL 35243 USA School of Public Health University of Memphis Memphis TN 38152 USA USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project Bethesda Maryland 20814 USA Institute for Health Research Kaiser Permanente Denver CO 80231 USA ICSI Institute for Clinical Systems Improvement Bloomington MN 55425 USA Medicine University of Chicago Chicago IL 60637 USA Medicine Columbia University Medical Center New York NY 10032 USA Psychiatry Columbia University New York NY 10032 USA General Internal Medicine Epidemiology and Biostatistics University of California San Francisco San Francisco CA 94110 USA New York State Office of Mental Health New York NY 10001 USA Medicine Icahn School of Medicine at Mount Sinai New York NY 10029 USA Center for Health Enhancement System Studies University of Wisconsin Madison WI 53706 USA Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA Psychology University at Buffalo Buffalo NY 14260 USA Department of Psychology West Virginia University Morgantown WV 26506 USA MIRECC VA North Little Rock AR 72114 USA QUERI for Team-Based Behavioral Health Centr

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An hidden markov model-based transcription factor mining method

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Journal of Bionanoscience 2013年第1期7卷 66-71页

作者： Wu, Chunguo Li, Gaoyang Wu, Xiaozhou Han, Xiaosong Wang, Binghong Breis, Jesualdo Tomás Fernández Wang, Fei Liang, Yanchun Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Jilin University Changchun 130012 China Business School University of Shanghai for Science and Technology Shanghai 200093 China Shanghai Key Laboratory of Intelligent Information Processing Shanghai 200433 China Department of Informatics and Systems University of Murcia 30100 Murcia Spain

A text mining algorithm named HMM-TFM (Hidden Markov Model based transcription factor name mining) is presented. The proposed algorithm does not need a dictionary of transcription factor names. A small verb set is defined to filter sentences. Transcription factor names are mined according to the part of speech tagged by hidden Markov model. Experimental results show that the recall and precision of HMM-TFM achieve 74.2% and 77.9%, respectively. Copyright © 2013 American Scientific Publishers.

关键词： data mining

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Using domain ontologies as semantic dimensions in data warehouses

Using domain ontologies as semantic dimensions in data wareh...

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31st International Conference on Conceptual Modeling, ER 2012

作者： Anderlik, Stefan Neumayr, Bernd Schrefl, Michael Department of Business Informatics - Data and Knowledge Engineering Johannes Kepler University Linz Austria

ISBN: (纸本)9783642340017

More and more transaction systems collect records that reference concepts of domain ontologies in so-called semantic attributes. This paper investigates how such semantic attributes together with their referenced domain ontology can be best exploited for data analysis in data warehouses. This gives rise to two challenges: first, exploit the rich knowledge represented in domain ontologies for targeted analysis and, second, aggregate data along the subsumption hierarchy of concepts and ensuring summarizability in the absence of predefined aggregation levels. To meet these challenges, the paper extends OLAP (OnLine Analytical Processing) by integrating concept expressions and proper level definitions over domain ontologies into OLAP operations. A prototype demonstrates the feasibility of the approach. © 2012 Springer-Verlag.

关键词： data warehouses

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Multi-dimensional navigation modeling using BI analysis graphs

Multi-dimensional navigation modeling using BI analysis grap...

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31st International Conference on Conceptual Modeling, ER 2012

作者： Neuböck, Thomas Neumayr, Bernd Rossgatterer, Thomas Anderlik, Stefan Schrefl, Michael Solvistas GmbH Graben 18 Linz 4020 Austria Department of Business Informatics - Data and Knowledge Engineering Johannes Kepler University Linz Altenberger Straße 69 4040 Linz Austria

ISBN: (纸本)9783642339981

To solve analysis tasks in business intelligence, business analysts frequently apply a step-by-step approach. Using their expert knowledge they navigate between different measures, also referred to as business ratios or key performance indicators, at different levels of detail and focus on different aspects or parts of their organization. In this paper we introduce BI Analysis Graphs to document and analyze these navigation steps. We further introduce BI Analysis Graph Templates to model and re-use recurrent navigation patterns. We describe reasoning tasks over BI Analysis Graph Templates and sketch how they are implemented in our proof-of-concept prototype. BI Analysis Graph Templates may serve as formal foundation for interactive dashboards and guided analytics in business intelligence applications. © 2012 Springer-Verlag.

关键词： data warehouses

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