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International Joint Conference on Neural Networks (IJCNN)

作者： Daniel M. M. da Costa Sarajane M. Peres Clodoaldo A. M. Lima Pollyana Mustaro Information Systems Program University of São Paulo São Paulo SP Brazil Graduate Program in Electrical Engineering and Computing Mackenzie Presbyterian University São Paulo SP Brazil

ISBN: (纸本)9781479919611

In recent years, human identification based on face recognition has attracted the attention of the scientific community and the general public due to its wide range of applications. A face recognition system involves three important phases: face detection, feature extraction and classification (identification and/or verification). The robustness of face recognition could be improved by treating the variations in these stages. One of the main issues in design of face recognition system is how to extract discriminative facial features. A precise extraction of a representative feature set will improve the performance of a face recognition system. Various techniques have been used to represent images efficiently, of which the most well-known and widely applied are Wavelet, Contourlet, Shearlet and Curvelet Transform. Their ability to capture localized time-frequency information of image motivates their use for feature extraction. In this paper, we conduct a systematic empirical study on these transforms as feature extractors from face images. To further reduce the feature dimensionality, we adopt Principal Component Analysis and Linear Discriminant Analysis to select the most discriminative feature sets. The performance levels delivered by each transform are contrasted in terms of the accuracy measure computed over the outputs generated by the Support Vector Machine classifier (SVM). Experimental results conducted on a publicly available database are reported whereby we observe that the Curvelet Transform followed by the Wavelet Transform significantly outperform the others according to accuracy measure calculated over the SVM classifier.

关键词： Face recognition Support vector machines Wavelet transforms

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Financial forensic analysis 13

Financial forensic analysis

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13th International Conference WWW/Internet 2014, ICWI 2014

作者： Da Silva, Márcio Alexandre Pereira Da Silva, Paulo Caetano Master Program in Systems and Computing Salvador University Salvador - Bahia Brazil

ISBN: (纸本)9789898533241

The Information Technology has led many countries to adopt technologies based on internationally accepted standards for the disclosure of their financial statements. The XBRL technology is adopted to represent financial data (instances) and its semantics (which are based on XML Schema and XLink) to facilitate the exchange of data and increase the transparency of financial information available on the Internet. However, the occurrences of financial crime in large corporations require that computational solutions are designed to detect fraud. With such goal, this paper proposes a support tool for forensic financial analysis, based on OLAP query languages for the digital detection of fraud in financial reports represented in XBRL. Operators were incorporated at the Mondrian server, an OLAP tool, which supports queries in XML documents connected by XLink and XML Schema (the basis of XBRL) and also relational databases. The forensic operators are presented, extending those defined in LMDQL (Link-based and Multidimensional Query Language), and its use is demonstrated on a relational repository of multidimensional data (based on the XBRL specification). Since XBRL expresses the semantics of the financial data, whose relationships among accounting elements (described in XBRL Schema) are commonly defined in one or more linkbases, this repository contains tables that store the data referring to these relationships. To review the forensic operators a case study was realized using XBRL documents and linkbases provided by U.S. SEC, to which an ETL processing was applied for the data loading, making it possible to analyze the occurrence of fraud in large volumes of data presented.

关键词： Query languages

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Assesment of methodologies for the construction of the ontology for Brazilian academic records 13

Assesment of methodologies for the construction of the ontol...

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13th International Conference WWW/Internet 2014, ICWI 2014

作者： De Oliveira, Márcio Melo Da Silva, Paulo Caetano Master Program in Systems and Computing Salvador University Salvador - Bahia Brazil

ISBN: (纸本)9789898533241

There is no centralized system to undertake the management of academic records of federal educational institutions in Brazil, each one developed its solution within an environment in which there are several semantic vaguenesses. This context produces difficulties to the Ministry of Education to generate indicators that assist the management of Brazilian education. Thus, there is a need to develop a solution that semantically harmonizes the information generated by these educational institutions. To help solve this problem we propose the development of an ontology that performs the semantic mapping of the field of academic records of the Brazilian educational model. This ontology can serve as the semantic basis for the adjustment and development of data collection software's from the Ministry of Education of Brazil, as well as the academic management systems of each federal institution of education. However, before it is necessary to select or develop appropriate ontology development methodology for the domain of academic records of federal teaching institutions. This paper surveys the literature to identify the methodologies for creating ontologies and evaluates them in order to indicate the most appropriate for use in the construction of this ontology.

关键词： Ontology

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Author Correction: Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase

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Scientific reports 2020年第1期10卷 3531页

作者： Matthew Ezewudo Amanda Borens Álvaro Chiner-Oms Paolo Miotto Leonid Chindelevitch Angela M Starks Debra Hanna Richard Liwski Matteo Zignol Christopher Gilpin Stefan Niemann Thomas Andreas Kohl Robin M Warren Derrick Crook Sebastien Gagneux Sven Hoffner Camilla Rodrigues Iñaki Comas David M Engelthaler David Alland Leen Rigouts Christoph Lange Keertan Dheda Rumina Hasan Ruth McNerney Daniela M Cirillo Marco Schito Timothy C Rodwell James Posey Critical Path Institute 1730 E River Rd. Tucson AZ 85718 USA. Joint unit Infection and Public Health FISABIO-CSISP/University of Valencia Institute of integrative Systems Biology Valencia Spain. Emerging Bacterial Pathogens Unit IRCCS San Raffaele Scientific Institute via Olgettina 58 20132 Milano Italy. School of Computing Science Simon Fraser University 8888 University Ave Burnaby BC V5A 1S6 Canada. Division of Tuberculosis Elimination National Center for HIV/AIDS Viral Hepatitis STD and TB Prevention Centers for Disease Control and Prevention 1600 Clifton Road MS F08 Atlanta GA 30329 USA. Global Tuberculosis Program World Health Organization Geneva Switzerland. German Center for Infection Research Partner Site Borstel Borstel Germany. Molecular and Experimental Mycobacteriology Priority area Infections Research Center Borstel Borstel Germany. DST/NRF Centre of Excellence for Biomedical Tuberculosis Research/SAMRC Centre for Tuberculosis Research Division of Molecular Biology and Human Genetics Faculty of Medicine and Health Sciences Stellenbosch University Stellenbosch South Africa. Nuffield Department of Medicine John Radcliffe Hospital University of Oxford Oxford OX3 9DU United Kingdom. Swiss Tropical and Public Health Institute Basel Switzerland. Department of Public Health Sciences Karolinska institute Stockholm Sweden. Hinduja Hospital Veer Savarkar Marg Mahim Mumbai India. Tuberculosis Genomics Unit Biomedicine Institute of Valencia (IBV-CSIC) Street Jaime Roig 11. P.O. 4010 Valencia Spain. Translational Genomics Research Institute 3051 W. Shamrell Blvd. Ste 106 Flagstaff AZ 86005 USA. Center for Emerging Pathogens Rutgers-New Jersey Medical School 185 South Orange Avenue Newark NJ 07103 USA. Department of Biomedical Sciences Institute of Tropical Medicine Antwerp Belgium. Division of Clinical Infectious Diseases and German Center for Infection Research Tuberculosis Unit Research Center Borstel Borstel Germany. Lung Infection

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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A Simple Framework of Conservative Algorithms for the Coupled Nonlinear Schrdinger Equations with Multiply Components

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Communications in Theoretical Physics 2014年第6期61卷 703-709页

作者：钱旭宋松和李伟斌 Department of Mathematics and Systems Science National University of Defense Technology Program in Applied and Computational Mathematics Princeton University State Key Laboratory of High Performance Computing National University of Defense Technology

Considering the coupled nonlinear Schr¨odinger system with multiply components, we provide a novel framework for constructing energy-preserving algorithms. In detail, based on the high order compact finite difference method, Fourier pseudospectral method and wavelet collocation method for spatial discretizations, a series of high accurate conservative algorithms are presented. The proposed algorithms can preserve the corresponding discrete charge and energy conservation laws exactly, which would guarantee their numerical stabilities during long time ***, several analogous multi-symplectic algorithms are constructed as comparison. Numerical experiments for the unstable plane waves will show the advantages of the proposed algorithms over long time and verify the theoretical analysis.

关键词： conservative algorithm coupled nonlinear SchrSdinger equation multiply components unstablewave

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Proceedings of the 16th Annual UT-KBRIN Bioinformatics Summit 2016: proceedings

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BMC Proceedings 2017年第9期11卷 1-6页

作者： L. Leon Dent Sammed N. Mandape Siddharth Pratap Jianan Dong Jamaine Davis Jennifer A. Gaddy Kofi Amoah Steve Damo Dana R. Marshall Jacob Jones Toni Brandt Gilberto Diaz Qingguo Wang Todd Gary Ashwini Yenamandra Marina Z. Ghattas Marwa Elrakaiby Ramy K. Aziz Hamdallah H. Zedan Moamen Elmassry Marwa ElRakaiby Mariam Lotfy Jarrad Marcel Rania A. Khattab Maha M. Abdelfattah Jack A. Gilbert Pouya Dini Shavahn C. Loux Kirsten E. Scoggin Alejandro Esteller-Vico Edward L. Squires Mats H. T. Troedsson Barry A. Ball Peter Daels Kalpani De Silva Ernest Bailey Joel C. Stephens Theodore S. Kalbfleisch Christine E. Dolin Lauren G. Poole Gavin E. Arteel Michael L. Merchant Daniel W. Wilkey Michelle T. Barati Eric C. Rouchka Richard M. Higashi Teresa W-M Fan Hunter Moseley Andrew N Lane Department of Surgery Meharry Medical College Nashville TN 37208 USA Bioinformatics Core Meharry Medical College Nashville TN 37208 USA Department of Biochemistry and Cancer Biology Meharry Medical College Nashville TN 37208 USA Department of Medicine Vanderbilt University Medical Center Nashville TN 37232 USA Department of Life and Physical Sciences Fisk University Nashville TN 37208 USA Department of Pathology Anatomy and Cell Biology Meharry Medical College Nashville TN 37208 USA College of Computing and Technology Lipscomb University 1 University Park Drive Nashville TN 37204 USA Vanderbilt University Medical Center Nashville TN 37232 USA Office of Research Middle Tennessee State University 1301 East Main St Murfreesboro TN 37132 USA Department of Microbiology and Immunology Faculty of Pharmacy Cairo University Cairo Egypt Department of Biological Sciences Texas Tech University Lubbock TX 79409 USA Clinical Operations Department Ray-Clinical Research Organization Giza Egypt Genomic and Systems Biology Bioscience Division Argonne National Laboratory Argonne IL 60439 USA Research Institute of Ophthalmology Giza Egypt Department of Surgery University of Chicago Chicago IL 60637 USA Microbial Ecology Group Argonne National Laboratory Argonne IL 60439 USA Department of Veterinary Science University of Kentucky Lexington KY 40536 USA Department of Reproduction Faculty of Veterinary Medicine University of Gent Merelbeke Belgium Interdisciplinary Studies Program: Specialization in Bioinformatics University of Louisville Louisville KY 40292 USA Department of Veterinary Science University of Kentucky Lexington KY 40506 USA Genomics GPS Guilford CT 06437 USA Department of Biochemistry and Molecular Genetics School of Medicine University of Louisville Louisville KY 40292 USA Department of Pharmacology & Toxicology University of Louisville Louisville KY 40202 USA Department of Medicine University of Louisville

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LifeTime and improving European healthcare through cell-based interceptive medicine (vol 587, pg 377, 2020)

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NATURE 2021年第7852期592卷 E8-E8页

作者： Rajewsky, Nikolaus Almouzni, Genevieve Gorski, Stanislaw A. Aerts, Stein Amit, Ido Bertero, Michela G. Bock, Christoph Bredenoord, Annelien L. Cavalli, Giacomo Chiocca, Susanna Clevers, Hans De Strooper, Bart Eggert, Angelika Ellenberg, Jan Fernandez, Xose M. Figlerowicz, Marek Gasser, Susan M. Hubner, Norbert Kjems, Jorgen Knoblich, Jurgen A. Krabbe, Grietje Lichter, Peter Linnarsson, Sten Marine, Jean-Christophe Marioni, John C. Marti-Renom, Marc A. Netea, Mihai G. Nickel, Dorthe Nollmann, Marcelo Novak, Halina R. Parkinson, Helen Piccolo, Stefano Pinheiro, Ines Pombo, Ana Popp, Christian Reik, Wolf Roman-Roman, Sergio Rosenstiel, Philip Schultze, Joachim L. Stegle, Oliver Tanay, Amos Testa, Giuseppe Thanos, Dimitris Theis, Fabian J. Torres-Padilla, Maria-Elena Valencia, Alfonso Vallot, Celine van Oudenaarden, Alexander Vidal, Marie Voet, Thierry Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine in the Helmholtz Association Berlin Germany Charité-Universitätsmedizin Berlin Germany Berlin Institute of Health (BIH) Berlin Germany German Center for Cardiovascular Research (DZHK) Partner Site Berlin Berlin Germany Institute for Biology Humboldt University of Berlin Berlin Germany Cardiovascular and Metabolic Sciences Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Berlin Germany Department of Pediatric Oncology/Hematology Charité-Universitätsmedizin Berlin Berlin Germany Institut Curie CNRS PSL Research University Sorbonne Université Nuclear Dynamics Unit Equipe Labellisée Ligue contre le cancer Paris France VIB Center for Brain and Disease Research Leuven Belgium Department of Human Genetics KU Leuven Leuven Belgium Department of Neurosciences KU Leuven Leuven Belgium UK Dementia Research Institute at UCL University College London London UK Wellcome Sanger Institute Wellcome Genome Campus Cambridge UK Department of Immunology Weizmann Institute of Science Rehovot Israel Centre for Genomic Regulation (CRG) Barcelona Institute of Science and Technology Barcelona Spain CNAG-CRG Centre for Genomic Regulation Barcelona Institute of Science and Technology Barcelona Spain Universitat Pompeu Fabra Barcelona Spain ICREA Barcelona Spain CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna Austria Department of Laboratory Medicine Medical University of Vienna Vienna Austria Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases Vienna Austria Department of Medical Humanities Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht The Netherlands Institute of Human Genetics UMR 9002 CNRS and University of Montpellier Montpellier France Department of Experimental Oncology IEO European Institute of Oncology IRCCS Milan Italy Department of Oncology and Hemato

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Creation and analysis of biochemical constraint-based models: The COBRA Toolbox v3.0

arXiv

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arXiv 2017年

作者： Heirendt, Laurent Arreckx, Sylvain Pfau, Thomas Mendoza, Sebastián N. Richelle, Anne Heinken, Almut Haraldsdóttir, Hulda S. Wachowiak, Jacek Keating, Sarah M. Vlasov, Vanja Magnusdóttir, Stefania Ng, Chiam Yu Preciat, German Žagare, Alise Chan, Siu H.J. Aurich, Maike K. Clancy, Catherine M. Modamio, Jennifer Sauls, John T. Noronha, Alberto Bordbar, Aarash Cousins, Benjamin El Assal, Diana C. Valcarcel, Luis V. Apaolaza, Iñigo Ghaderi, Susan Ahookhosh, Masoud Guebila, Marouen Ben Kostromins, Andrejs Sompairac, Nicolas Le, Hoai M. Ma, Ding Sun, Yuekai Wang, Lin Yurkovich, James T. Oliveira, Miguel A.P. Vuong, Phan T. El Assal, Lemmer P. Kuperstein, Inna Zinovyev, Andrei Scott Hinton, H. Bryant, William A. Aragón Artacho, Francisco J. Planes, Francisco J. Stalidzans, Egils Maass, Alejandro Vempala, Santosh Hucka, Michael Saunders, Michael A. Maranas, Costas D. Lewis, Nathan E. Sauter, Thomas Palsson, Bernhard Ø. Thiele, Ines Fleming, Ronan M.T. Luxembourg Centre for Systems Biomedicine University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg Life Sciences Research Unit University of Luxembourg 6 avenue du Swing BelvauxL-4367 Luxembourg University of Chile Blanco Encalada 2085 Santiago Chile Department of Pediatrics University of California San Diego School of Medicine San DiegoCA92093 United States Hinxton CambridgeCB10 1SD United Kingdom Department of Chemical Engineering Pennsylvania State University University University ParkPA16802 United States Department of Physics University of California San Diego 9500 Gilman Dr. San DiegoCA92093 United States Bioinformatics and Systems Biology Program University of California San Diego San DiegoCA United States Sinopia Biosciences San DiegoCA United States School of Computer Science Algorithms and Randomness Center Georgia Institute of Technology AtlantaGA United States Biomedical Engineering and Sciences Department TECNUN University of Navarra Paseo de Manuel Lardizabal 13 San Sebastian20018 Spain Institute of Microbiology and Biotechnology University of Latvia Jelgavas iela 1 RigaLV-1004 Latvia Department of Management Science and Engineering Stanford University StanfordCA94305-4026 United States Bioengineering Department University of California San Diego San DiegoCA United States Utah State University Research Foundation 1695 North Research Park Way North LoganUT84341 United States Centre for Integrative Systems Biology and Bioinformatics Department of Life Sciences Imperial College London London United Kingdom Department of Mathematics University of Alicante Spain California Institute of Technology Computing and Mathematical Sciences MC 305-16 1200 E. California Blvd. PasadenaCA91125 United States Mathomics Center for Mathematical Modeling University of Chile Beauchef 851 Santiago Chile Novo Nordisk Foundation Center for Biosustainability University of California San Diego San DiegoCA92093 Uni

COnstraint-Based Reconstruction and Analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive software suite of interoperable COBRA methods. It has found widespread applications in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. Version 3.0 includes new methods for quality controlled reconstruction, modelling, topological analysis, strain and experimental design, network visualisation as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimisation solvers for multi-scale, multi-cellular and reaction kinetic modelling, respectively. This protocol can be adapted for the generation and analysis of a constraint-based model in a wide variety of molecular systems biology scenarios. This protocol is an update to the COBRA Toolbox 1.0 and 2.0. The COBRA Toolbox 3.0 provides an unparalleled depth of constraint-based reconstruction and analysis methods. Copyright © 2017, The Authors. All rights reserved.

关键词： Data integration

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The Role of Certainty and Time Delay in Students' Cheating Decisions during Online Testing 37

The Role of Certainty and Time Delay in Students' Cheating D...

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37th Annual Meeting of the Cognitive Science Society: Mind, Technology, and Society, CogSci 2015

作者： Chuang, Chia-Yuan Craig, Scotty D. Femiani, John Arizona State University Simulation Modeling and Applied Cognitive Science Program 7171 E Sonoran Arroyo Mall MesaAZ85212 United States Arizona State University Human Systems Engineering 7171 E Sonoran Arroyo Mall MesaAZ85212 United States Arizona State University School of Computing Informatics and Decision System Engineering Peralta Hall 7171 E Sonoran Arroyo Mall Rm 230U MesaAZ85212 United States

ISBN: (纸本)9780991196722

In an attempt to assist proctors to prevent test takers from academic dishonesty in remotely administrated exams, this study investigated the ability of test takers' behaviors during online assessments to predict their cheating decisions. Specifically, this experimental study focused on the role of students' time delay and certainty rating during lab based online testing sessions. The analysis of hierarchical logistic regression indicated that not only time delay but also certainty rating had significantly statistical relation to test takers' cheating decisions. The importance of the two proposed factors during online assessments was discussed and the prospects of the improvements of online proctoring systems were addressed. © Cognitive Science Society, CogSci *** rights reserved.

关键词： Time delay

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Learning multiple description logics concepts 23

Learning multiple description logics concepts

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23rd International Conference on Inductive Logic programming, ILP 2013

作者： Melo, Raphael Revoredo, Kate Paes, Aline Postgraduate Information Systems Program UNIRIO Rio de Janeiro Brazil Department of Computer Science Institute of Computing UFF Rio de Janeiro Brazil

Description logics based languages have became the standard representation scheme for ontologies. They formalize the domain knowledge using interrelated concepts, contained in terminologies. The manual definition of terminologies is an expensive and error prone task, therefore automatic learning methods are a necessity. In this paper we lay the foundations of a multiple concept learning method that uses virtual concepts to aid the learning process, yielding more compact and readable terminologies. In this paper, we define virtual concepts and how they can be implemented in the current concept learning methods. We show through experiments how the method stacks up against other multiple concept learning methods.

关键词： Terminology

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