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5th International Joint Conference on Computational Intelligence, IJCCI 2013

作者： Góes, Anderson Roges Teixeira Steiner, Maria Teresinha Arns Neto, Pedro José Steiner Graduate Programs in Numerical Methods in Engineering Federal University of Paraná Centro Politécnico CP: 19081 CEP: 81531-990 Curitiba PR Brazil Graduate Program in Industrial and Systems Engineering Pontifical Catholic University of Paraná Rua Imaculada Conceição 1155 Prado Velho CEP: 80.215-901 Curitiba PR Brazil Numerical Methods in Engineering and Industrial Engineering Federal University of Paraná Centro Politécnico CP: 1908 CEP: 81531-990 Curitiba PR Brazil Graduate Programs in Business Administration Federal University of Paraná Av. Pref. Lothario Meissner 632 CEP: 80210-170 Curitiba PR Brazil

ISBN: (纸本)9789898565778

In this paper we propose a methodology to classify Power Quality for feeders, based on sags and by the use of KDD technique, establishing a quality level printed in labels. To support the methodology, it was applied to feeders on a substation located in Curitiba, Paraná, Brazil, based on attributes such as sag length, duration and frequency (number of occurrences on a given period of time). In the search for feeders quality classification, on the Data Mining stage, the main stage on KDD process, three different techniques were used in a comparatively way for pattern recognition: Artificial Neural Networks, Support Vector Machines an Genetic Algorithms. Those techniques presented acceptable results in classification feeders with no possible classification using a simplified method based on maximum number of sags. Thus, by printing the label with information and Quality level, utilities companies can get better organized for mitigation procedures, by establishing clear targets.

关键词： Pattern recognition

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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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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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Erratum: Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

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Nature communications 2017年第1期8卷 1414页

作者： M Carola Zillikens Serkalem Demissie Yi-Hsiang Hsu Laura M Yerges-Armstrong Wen-Chi Chou Lisette Stolk Gregory Livshits Linda Broer Toby Johnson Daniel L Koller Zoltán Kutalik Jian'an Luan Ida Malkin Janina S Ried Albert V Smith Gudmar Thorleifsson Liesbeth Vandenput Jing Hua Zhao Weihua Zhang Ali Aghdassi Kristina Åkesson Najaf Amin Leslie J Baier Inês Barroso David A Bennett Lars Bertram Rainer Biffar Murielle Bochud Michael Boehnke Ingrid B Borecki Aron S Buchman Liisa Byberg Harry Campbell Natalia Campos Obanda Jane A Cauley Peggy M Cawthon Henna Cederberg Zhao Chen Nam H Cho Hyung Jin Choi Melina Claussnitzer Francis Collins Steven R Cummings Philip L De Jager Ilja Demuth Rosalie A M Dhonukshe-Rutten Luda Diatchenko Gudny Eiriksdottir Anke W Enneman Mike Erdos Johan G Eriksson Joel Eriksson Karol Estrada Daniel S Evans Mary F Feitosa Mao Fu Melissa Garcia Christian Gieger Thomas Girke Nicole L Glazer Harald Grallert Jagvir Grewal Bok-Ghee Han Robert L Hanson Caroline Hayward Albert Hofman Eric P Hoffman Georg Homuth Wen-Chi Hsueh Monica J Hubal Alan Hubbard Kim M Huffman Lise B Husted Thomas Illig Erik Ingelsson Till Ittermann John-Olov Jansson Joanne M Jordan Antti Jula Magnus Karlsson Kay-Tee Khaw Tuomas O Kilpeläinen Norman Klopp Jacqueline S L Kloth Heikki A Koistinen William E Kraus Stephen Kritchevsky Teemu Kuulasmaa Johanna Kuusisto Markku Laakso Jari Lahti Thomas Lang Bente L Langdahl Lenore J Launer Jong-Young Lee Markus M Lerch Joshua R Lewis Lars Lind Cecilia Lindgren Yongmei Liu Tian Liu Youfang Liu Östen Ljunggren Mattias Lorentzon Robert N Luben William Maixner Fiona E McGuigan Carolina Medina-Gomez Thomas Meitinger Håkan Melhus Dan Mellström Simon Melov Karl Michaëlsson Braxton D Mitchell Andrew P Morris Leif Mosekilde Anne Newman Carrie M Nielson Jeffrey R O'Connell Ben A Oostra Eric S Orwoll Aarno Palotie Stephen C J Parker Munro Peacock Markus Perola Annette Peters Ozren Polasek Richard L Prince Katri Räikkönen Stuart H Ralston Samuli Ripatti John A Robbins Jerome I Rotter Igor Rudan Veikko Department of Internal Medicine Erasmus MC Rotterdam 3000 The Netherlands. Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA) Leiden 2593 The Netherlands. Department of Biostatistics Boston University School of Public Health Boston MA 02118 USA. Hebrew SeniorLife Institute for Aging Research Roslindale MA 02131 USA. Harvard Medical School Boston MA 02115 USA. Molecular and Integrative Physiological Sciences Program Harvard School of Public Health Boston MA 02115 USA. Program in Personalized and Genomic Medicine and Department of Medicine Division of Endocrinology Diabetes and Nutrition University of Maryland School of Medicine Baltimore MD 21201 USA. Broad Institute Cambridge MA 02142 USA. Sackler Faculty of Medicine Department of Anatomy and Anthropology Tel Aviv University Tel Aviv 6997801 Israel. Department of Twin Research and Genetic Epidemiology King's College London St Thomas' Campus London WC2R 2LS UK. Department of Epidemiology Erasmus MC Rotterdam 3000 The Netherlands. Department of Medical Genetics University of Lausanne Lausanne 1011 Switzerland. Swiss Institute of Bioinformatics Lausanne 1015 Switzerland. Centre Hospitalier Universitaire (CHUV) University Institute for Social and Preventive Medicine Lausanne 1010 Switzerland. Department of Medical and Molecular Genetics Indiana University School of Medicine Indianapolis IN 46202 USA. MRC Epidemiology Unit University of Cambridge School of Clinical Medicine Cambridge Biomedical Campus Cambridge CB2 OQQ UK. Institute of Epidemiology II Helmholtz Zentrum München - German Research Center for Environmental Health Neuherberg 85764 Germany. Icelandic Heart Association Kopavogur 201 Iceland. Faculty of Medicine University of Iceland Reykjavik 101 Iceland. deCODE Genetics Reykjavik 101 Iceland. Department of Internal Medicine Institute of Medicine Sahlgrenska Academy University of Gothenburg Gothenburg SE-405 30 Sweden. Dep

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Corrigendum to “A decision support method, based on bounded rationality concepts, to reveal feature saliency in clustering problems” [Decision Support Systems (54) (1) (2012) 292–303]

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Decision Support Systems 2013年第2期54卷 1205-1205页

作者： Barak Aviad Gelbard Roy Information System Program Graduate School of Business Administration Bar-Ilan University Ramat-Gan 52900 Israel

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Knowledge,attitudes and practices towards avian influenza A(H5N1) among Cambodian women:A cross-sectional study

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Asian Pacific Journal of Tropical Medicine 2012年第9期5卷 727-734页

作者： Mav Khun Chantha Heng Md.Harun-Or-Rashid Hideki Kasuya Junichi Sakamoto Young Leaders' Program in Healthcare Administration Nagoya University Graduate School of MedicineNagoyaJapan Communicable Disease Control Rapid Response TeamKampot Provincial Health DepartmentKampot ProvinceCambodia Department of Surgery Ⅱ Nagoya University Graduate School of MedicineNagoyaJapan

Objective:To measure highly pathogenic avian influenza(HPAI)-related knowledge,attitudes, and practices(KAPs) among Cambodian ***:This cross-sectional study selected 246 married women aged between 18-55 years who had backyard poultry and lived at least one year in the areas of the survey through multi-stage cluster *** average score of correct answers was generated to evaluate respondents’ knowledge(Good/Poor).attitudes(Positive/ Negative),and practices(Good/Bad).Results:We reported that about half of the respondents had good knowledge and good practices and four-fifth of them had positive attitudes towards *** ratios(ORs) and 95%confidence intervals(CIs) were estimated through a logistic regression model to explore contributing factors that raise their KAP *** of the sources were significant in increasing knowledge of the respondent,like television(OR=l.6.95%CI=1.0- 2.7),radio(OR=2.5.95%CI=l.3-4.9).leaflets/booklets(OR=2.1,95%CI=1.2-3.9),school students (OR=18.4.95%CI=2.4-142.9).village health volunteers(OR=4.5.95%CI=2.2-10.9) *** such as television(OR=3.7.95%CI=2.1-6.4).leaflets/booklets(OR=2.6,95%CI7=1.4-5.1).and public health staff(OR=2.2,95%CI=1.2-4.1) had similar influence on ***,we found similar effect on raising the attitudes of the responded,it was not ***: We report a satisfactory level of positive attitudes,and moderate level of knowledge and practices related to HPAI among Cambodian *** KAPs through television,radio and other medias may be more efficient than using usual information,education and communication materials to prevent HPAI.

关键词： Highly pathogenic avian influenza Knowledge Attitudes Practices Kampot Cambodia

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Planning and production indicators facing seasonal agricultura machinery market

Planning and production indicators facing seasonal agricultu...

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2012 IEEE 6th International Conference on Management of Innovation and Technology, ICMIT 2012

作者： Frey, E.E. Braz, P.H. Camargo, M.E. Cruz, M.R. Galelli, A. Russo, S.L. Silva, G.F. Post-Graduate Program in Administration University of Caxias Do Sul Caxias do Sul Brazil Federal University of Sergipe Aracaju Brazil

ISBN: (纸本)9781467301107

This article aims to compare the profile of the domestic market demand for agricultural machinery, and production indicators and planning of the mechanical industry. The data on sales, this market over the past eleven years, which showed the seasonal pattern characterized by a decline in demand from November and a recovery that begins in late February. The search about quantitative indicators of planning and operational efficiency, productivity of the 2009-2010 were related to market behavior. It can be concluded that manufacturing is efficient, since the actual production has correlation with production planned and that during the retraction of market resources are underutilized reflecting the low productivity that underscores the lack of company strategy for the period of falling demand. © 2012 IEEE.

关键词： Productivity

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Innovation as a strategy for the apple productive chain in Brazil

Innovation as a strategy for the apple productive chain in B...

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2012 IEEE 6th International Conference on Management of Innovation and Technology, ICMIT 2012

作者： Cruz, M.R. Camargo, M.E. Tissot, P.B. Severo, E.A. Milan, G.S. Russo, S.L. Silva, G.F. Post-Graduate Program in Administration University of Caxias Do Sul Caxias do Sul Brazil Federal University of Sergipe Aracaju Brazil

ISBN: (纸本)9781467301107

The challenges of companies nowadays pass through the necessity to meet the diversity of events of everyday life. In this context, this study aims to propose alternatives to the apple productive chain in Brazil, focused in the innovation management. The aims is propose some actions to maintain the competitiveness of this segment, so the proposals are focused on strategies to make the chain innovative, especially in the commercialization process and also strategies directed to the consumer market. As result, the actions raised in the study can contribute to a direction that will bring more competition to the productive chain of Brazilian apples, both domestically and externally, as well as offer its members a greater profitability and return on investment. © 2012 IEEE.

关键词： Profitability

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WAO International Scientific Conference (WISC 2016) Abstracts

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WORLD ALLERGY ORGANIZATION JOURNAL 2017年第SUPPL 1期10卷 25-25页

作者： [Anonymous] Xin Hua Hospital Shanghai Jiao Tong University School of Medicine Pediatric Respirology Shanghai China Cincinnati Childrens Hospital Medical Center Division of Allergy and Immunology Cincinnati OH USA Cincinnati Childrens Hospital Medical Center Division of Asthma Research Cincinnati OH USA Cincinnati Childrens Hospital Medical Center Division of Human Genetics Cincinnati OH USA Universidad La Salle Facultad Mexicana de Medicina Mexico City Mexico Hospital Infantil de Mexico Federico Gomez Pediatric Allergy & Clinical Immunology Mexico City Mexico Beijing TongRen Hospital Department of Otolaryngology Head and Neck Surgery Beijing China Beijing Institute of Otolaryngology Beijing Key Laboratory of Nasal Diseases Beijing China Beijing TongRen Hospital Department of Allergy Beijing China Ghent University Hospital Upper Airways Research Laboratory Ghent Belgium University of Manitoba Section of Allergy and Immunology Department of Paediatrics and Child Health Winnipeg Canada India Department of Pharmacology Pune Poona College of Pharmacy Bharati Vidyapeeth Deemed University Department of Pharmacology Erandwane Paud Road Pune 411038 Maharashtra India Brigham and Women Pulmonary Critical Care Boston MA USA Harvard University Harvard Clinical Research Institute Boston MA USA Harvard TH Chan School of Public Health Environmental Health Boston MA USA Brigham and Women’s Hospital Pulmonary Critical Care Boston MA USA National Jewish Health Pulmonary Critical Care Denver CO USA American Academy of Family Physicians Family Medicine Denver CO USA University of Minnesota Family and Community Health Minneapolis Minnesota MN USA Soonchynhyang University Respiratory-Allergy Bucheon South Korea Utah University Biology Salt Lake City UT USA Sydney University Mathematics Sydney Australia Kaohsiung Veterans General Hospital Pediatrics Kaohsiung Taiwan Kaohsiung Veterans General Hospital Cardiac Surgery Kaohsiung Taiwan Kaohsiung Veterans General Hospital Patho

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The effect of menu labeling with calories and exercise equivalents on food selection and consumption

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BMC obesity 2014年第1期1卷 21页

作者： Charles Platkin Ming-Chin Yeh Kimberly Hirsch Ellen Weiss Wiewel Chang-Yun Lin Ho-Jui Tung Victoria H Castellanos City University of New York School of Public Health Hunter College Nutrition and Food Science Program Hunter College Silberman Bldg 2180 Third Avenue New York NY 10035 USA. CUNY School of Public Health Graduate Center New York USA. Department of Applied Mathematics and Institute of Statistics National Chung Hsing University Taichung City Taiwan. Department of Healthcare Administration Asia University Taichung City Taiwan. The University of Scranton Scranton PA USA.

BACKGROUND:Better techniques are needed to help consumers make lower calorie food choices. This pilot study examined the effect of menu labeling with caloric information and exercise equivalents (EE) on food selection. Participants, 62 females, ages 18-34, recruited for this study, ordered a fast food meal with menus that contained the names of the food (Lunch 1 (L1), control meal). One week later (Lunch 2 (L2), experiment meal), participants ordered a meal from one of three menus with the same items as the previous week: no calorie information, calorie information only, or calorie information and EE. RESULTS:There were no absolute differences between groups in calories ordered from L1 to L2. However, it is noteworthy that calorie only and calorie plus exercise equivalents ordered about 16% (206 kcal) and 14% (162 kcal) fewer calories from Lunch 1 to Lunch 2, respectively; whereas, the no information group ordered only 2% (25 kcal) fewer. CONCLUSIONS:Menu labeling alone may be insufficient to reduce calories; however, further research is needed in finding the most effective ways of presenting the menu labels for general public.

关键词： Exercise equivalents Fast food Menu labeling Nutrition labeling Obesity Point-of-purchase

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