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Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Scientific data 2021年第1期8卷 72页

作者： Gilberto Pastorello Carlo Trotta Eleonora Canfora Housen Chu Danielle Christianson You-Wei Cheah Cristina Poindexter Jiquan Chen Abdelrahman Elbashandy Marty Humphrey Peter Isaac Diego Polidori Markus Reichstein Alessio Ribeca Catharine van Ingen Nicolas Vuichard Leiming Zhang Brian Amiro Christof Ammann M Altaf Arain Jonas Ardö Timothy Arkebauer Stefan K Arndt Nicola Arriga Marc Aubinet Mika Aurela Dennis Baldocchi Alan Barr Eric Beamesderfer Luca Belelli Marchesini Onil Bergeron Jason Beringer Christian Bernhofer Daniel Berveiller Dave Billesbach Thomas Andrew Black Peter D Blanken Gil Bohrer Julia Boike Paul V Bolstad Damien Bonal Jean-Marc Bonnefond David R Bowling Rosvel Bracho Jason Brodeur Christian Brümmer Nina Buchmann Benoit Burban Sean P Burns Pauline Buysse Peter Cale Mauro Cavagna Pierre Cellier Shiping Chen Isaac Chini Torben R Christensen James Cleverly Alessio Collalti Claudia Consalvo Bruce D Cook David Cook Carole Coursolle Edoardo Cremonese Peter S Curtis Ettore D'Andrea Humberto da Rocha Xiaoqin Dai Kenneth J Davis Bruno De Cinti Agnes de Grandcourt Anne De Ligne Raimundo C De Oliveira Nicolas Delpierre Ankur R Desai Carlos Marcelo Di Bella Paul di Tommasi Han Dolman Francisco Domingo Gang Dong Sabina Dore Pierpaolo Duce Eric Dufrêne Allison Dunn Jiří Dušek Derek Eamus Uwe Eichelmann Hatim Abdalla M ElKhidir Werner Eugster Cacilia M Ewenz Brent Ewers Daniela Famulari Silvano Fares Iris Feigenwinter Andrew Feitz Rasmus Fensholt Gianluca Filippa Marc Fischer John Frank Marta Galvagno Mana Gharun Damiano Gianelle Bert Gielen Beniamino Gioli Anatoly Gitelson Ignacio Goded Mathias Goeckede Allen H Goldstein Christopher M Gough Michael L Goulden Alexander Graf Anne Griebel Carsten Gruening Thomas Grünwald Albin Hammerle Shijie Han Xingguo Han Birger Ulf Hansen Chad Hanson Juha Hatakka Yongtao He Markus Hehn Bernard Heinesch Nina Hinko-Najera Lukas Hörtnagl Lindsay Hutley Andreas Ibrom Hiroki Ikawa Marcin Jackowicz-Korczynski Dalibor Janouš Wilma Jans Rachhpal Jassal Shicheng Jiang Tomomichi Kato Myr Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. gzpastorello@lbl.gov. DIBAF University of Tuscia Viterbo 01100 Italy. Euro-Mediterranean Centre on Climate Change Foundation (CMCC) Lecce 73100 Italy. Climate & Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Department of Civil Engineering California State University Sacramento CA 95819 USA. Department of Geography Environment and Spatial Sciences Michigan State University East Lansing MI 48823 USA. Department of Computer Science University of Virginia Charlottesville VA 22904 USA. TERN Ecosystem Processes Menzies Creek VIC3159 Australia. Max Planck Institute for Biogeochemistry Jena 07701 Germany. Laboratoire des Sciences du Climat et de l'Environnement (LSCE) CEA CNRS UVSQ UPSACLAY Gif sur Yvette 91190 France. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China. Department of Soil Science University of Manitoba Winnipeg MB R3T2N2 Canada. Department of Agroecology and Environment Agroscope Research Institute Zürich 8046 Switzerland. School of Geography and Earth Sciences McMaster University L8S4K1 Hamilton ON Canada. Department of Physical Geography and Ecosystem Science Lund University Lund 22362 Sweden. Department of Agronomy and Horticulture University of Nebraska-Lincoln Lincoln NE 68583 USA. School of Ecosystem and Forest Sciences The University of Melbourne Richmond VIC3121 Australia. Department of Biology Research Group PLECO University of Antwerp Antwerp 2610 Belgium. Joint Research Centre European Commission Ispra 21027 Italy. TERRA Teaching and Research Center University of Liege Gembloux B-5030 Belgium. Finnish Meteorological Institute Helsinki 00560 Finland. ES

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An image mining based approach to detect pressure ulcer stage

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Pattern Recognition and Image Analysis 2014年第2期24卷 292-296页

作者： Guadagnin, R. Neves, R.de S. Santana, L.A. Guilhem, D.B. MS Program on Information Technology and Knowledge Management SGAN 916 Modulo B Catholic University of Brasilia 70790-160 Brasilia DF Brazil 72.300-175 Samambaia DF Brazil Bachelor Degree on Physiotherapy Catholic University of Brasilia Campus I QS 07 Lote 01 EPCT 71966-700 Aguas Claras Taguatinga DF Brazil

Treatment of pressure ulcers (PU) is essentially image dependent, because its surface provides relevant visual information for medical procedures. There is an increasing interest to adapt information technology advances for a more effective medical image processing. Artificial Intelligence concerned techniques, say Image Mining, can be very helpful to manage large amount of PU images in order to increase productivity of health professionals and patients life quality. This paper proposes an Image Mining based system for automatic interpretation of tissue and color to support the treatment of patients with PU. © 2014 Pleiades Publishing, Ltd.

关键词： Patient treatment

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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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An approach to provide visual information to support skin wounds therapy

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Pattern Recognition and Image Analysis 2014年第1期24卷 81-85页

作者： Guadagnin, R. Santana, L.A. Brasil', L.M. Neves, R.S. MS Program in Information Technology and Knowledge Management Catholic University of Brasília Campus II SGAN 916 Norte 70. 790-160 Brasília DF Brazil BS Course in Physiotherapy Catholic University of Brasília Campus I QS 07 Lote 01 EPCT 71. 966-700 Águas Claras Taguatinga DF Brazil Faculdade Gama Setor Central University of Brasilia 72405-610 Gama DF Brazil 300-573 Samambaia DF Brazil

Availability of visual information means an effective way to improve specialized work in quite different areas. They enable reality modeling, a faster context analysis, a more successful search for problem solutions, an objective oriented decision making, as well as important elements for instructional processes. Avisual model is a simulation form that stimulate insights, say, creative answers to yet open questions and derivation of yet not imagined possible facts concerning a studied reality. Visual features of human body are highly relevant as basic information for a variety of decisions on activities in health domain. Through mechanisms of user-friendly interface one can promptly access and eventually perform adjustments. One can achieve better life quality and greater efficiency in health service from state as well. This paper describes an approach towards a visualization process of skin lesions, including features recognition for therapeutic processes and relevant decisions, with experimental validation. © 2014 Pleiades Publishing, Ltd.

关键词： Visualization

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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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Convolution gradient method based on fitness-driven design considering global information

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ICIC Express Letters 2014年第3期8卷 651-659页

作者： Domoto, Eri Okuhara, Koji Koide, Noriaki Ueno, Nobuyuki Department of Media Business Hiroshima University of Economics 5-37-1 Gion Asaminami-Ku Hiroshima 731-0192 Japan Department of Information and Physical Sciences Graduate School of Information Science and Technology Osaka University 1-5 Yamadaoka Suita Osaka 565-0871 Japan Graduate School of Comprehensive Scientific Research Program in Management and Information Systems Prefectural University of Hiroshima 1-1-71 Ujina-Higashi Minami-ku Hiroshima City Hiroshima 734-8558 Japan

In many industries, a usual business model has a problem to realize mass customization, because it is difficult to satisfy the diversified customer needs. Total supply chain optimization is formulated as a stochastic programming problem, and then it is difficult to obtain a better solution for it. In this paper, we have proposed a new hybrid dynamical system of convolution gradient dynamics and swarm intelligence for finding a better optimal solution. Dynamics of convolution gradient has been derived in neural network framework. Swarm intelligence is the optimization technique based on the action of groups, such as birds, fish, and a colony of ants. From a theoretical point of view, we show how to combine them. The proposed hybrid algorithm can realize the interpolation search which is the mechanism of the dynamics of local search and global search. In numerical examples, we show that the proposed model can behave better dynamics for test functions and application of total supply chain optimization. © 2014 ICIC International.

关键词： Convolution

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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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Ontologies for support preventive maintenance processes of critical IT assets 22

Ontologies for support preventive maintenance processes of c...

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22nd International Conference on Production Research, ICPR 2013

作者： Czelusniak, D.J. De Abreu, A.F. Souza, J.A. Dergint, D.E.A. Federal University of Santa Catarina Engineering Production Post Graduate Program Technological Center P.O. Box 476 Trindade Florianópolis SCCEP 88010-970 Brazil Federal University of Santa Catarina Knowledge Management Engineering Post Graduate Program Technological Center P.O.Box 476 Trindade Florianópolis SC.CEP 88010-970 Brazil Federal Technological University of Paraná Technology Post Graduate Program 3165 Sete de Setembro Avenue Rebouças Curitiba PR.CEP 80230-901 Brazil

The goal of this paper is to show a study to evaluate the possibility of using ontologies to support maintenance procedures in IT equipment in a small power company. The aim is to improve the degree of reliability in detection of potential failures and defects in maintenance processes of information technology critical assets, trying to obtain less downtime of services that they provide. The methodological procedures used in this study were literature review, to present the modeling concepts of knowledge focused on ontologies creation and state of the art in building of field procedures describing the steps from initial drafting of ontology finishing with their tests. The results demonstrate that it is viable to utilize this technique, where the network equipment that keeps critical services require high level of availability on meeting the needs of the corporation.

关键词： Ontology

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Pressure ulcers attributes image mining to support therapeutic process: A research proposal

Pressure ulcers attributes image mining to support therapeut...

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4th International Workshop on Image Mining. Theory and Applications, IMTA 2013, In Conjunction with VISIGRAPP 2013

作者： De Souza Neves, Rinaldo Guadagnin, Renato Gulhem, Dirce B. Santana, Levy Aniceto University of Brasília Faculty of Health Sciences Asa Norte Campus Universitário 70910-900 Brasília DF Brazil Catholic University of Brasília MS Program on Information Technology and Knowledge Management SGAN 916 Módulo B 70790-160 Brasília DF Brazil Catholic University of Brasília Campus I QS 07 Lote 01 EPCT 71966-700 Águas Claras Taguatinga DF Brazil

ISBN: (纸本)9789898565501

The high number of clients suffering from pressure ulcers (PU) overloads hospital services, which are not equipped with the necessary human and technological resources. One needs to increase the productivity of this work, since health professionals, especially nurses use subjective and inaccurate assessments for PU diagnosis. This paper proposes a system for automatic interpretation of tissue and color to support the treatment of patients with PU.

关键词： Diagnosis

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A scoring model to detect abusive billing patterns in health insurance claims

A scoring model to detect abusive billing patterns in health...

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第二届(2013)老年人口与健康产业国际会议

作者： Hyunjung Shin Hayoung Park Junwoo Lee Won Chul Jhee Department of Industrial and Information Systems Engineering Ajou UniversitySan 5 Woncheon-dongYeo Technology Management Economicsand Policy Graduate ProgramSeoul National University599 Gwanak-ro Department of Industrial and Information Engineering Hongik University72-1 Sangsu-dongMapo-gu Seou

We propose a scoring model that detects outpatient clinics with abusive utilization patterns based on profiling information extracted from electronic insurance *** model consists of (1) scoring to quantify the degree of abusiveness and (2) segmentation to categorize the problematic providers with similar utilization *** performed the modeling for 3705 Korean internal medicine *** applied data from practitioner claims submitted to the National Health Insurance Corporation for outpatient care during the 3rd quarter of 2007 and used 4th quarter data to validate the *** considered the Health Insurance Review and Assessment Services decisions on interventions to be accurate for model *** compared the conditional probability distributions of the composite degree of anomaly (CDA) score formulated for intervention and non-intervention *** assess the validity of the model,we examined confusion matrices by intervention history and group as defined by the CDA *** CDA aggregated 38 indicators of abusiveness for individual clinics,which were grouped based on the CDAs,and we used the decision tree to further segment them into homogeneous clusters based on their utilization *** validation indicated that the proposed model was largely consistent with the manual detection techniques currently used to identify potential *** proposed model,which can be used to automate abuse detection,is flexible and easy to *** may present an opportunity to fight escalating healthcare costs in the era of increasing availability of electronic healthcare information.

关键词： Health insurance claims Medical abuse detection Fraud detection Degrees of anomaly Data mining

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