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FANTOM5 CAGE profiles of human and mouse samples

Scientific Data 2017年第1期4卷 1-10页

作者： Noguchi, Shuhei Arakawa, Takahiro Fukuda, Shiro Furuno, Masaaki Hasegawa, Akira Hori, Fumi Ishikawa-Kato, Sachi Kaida, Kaoru Kaiho, Ai Kanamori-Katayama, Mutsumi Kawashima, Tsugumi Kojima, Miki Kubosaki, Atsutaka Manabe, Ri-Ichiroh Murata, Mitsuyoshi Nagao-Sato, Sayaka Nakazato, Kenichi Ninomiya, Noriko Nishiyori-Sueki, Hiromi Noma, Shohei Saijyo, Eri Saka, Akiko Sakai, Mizuho Simon, Christophe Suzuki, Naoko Tagami, Michihira Watanabe, Shoko Yoshida, Shigehiro Arner, Peter Axton, Richard A. Babina, Magda Kenneth Baillie, J. Barnett, Timothy C. Beckhouse, Anthony G. Blumenthal, Antje Bodega, Beatrice Bonetti, Alessandro Briggs, James Brombacher, Frank Carlisle, Ailsa J. Clevers, Hans C. Davis, Carrie A. Detmar, Michael Dohi, Taeko Edge, B. Albert S. Edinger, Matthias Ehrlund, Anna Ekwall, Karl Endoh, Mitsuhiro Enomoto, Hideki Eslami, Afsaneh Fagiolini, Michela Fairbairn, Lynsey Farach-Carson, Mary C. Faulkner, Geoffrey J. Ferrai, Carmelo Fisher, Malcolm E. Forrester, Lesley M. Fujita, Rie Furusawa, Jun-Ichi Geijtenbeek, Teunis B. Gingeras, Thomas Goldowitz, Daniel Guhl, Sven Guler, Reto Gustincich, Stefano Ha, Thomas J. Hamaguchi, Masahide Hara, Mitsuko Hasegawa, Yuki Herlyn, Meenhard Heutink, Peter Hitchens, Kelly J. Hume, David A. Ikawa, Tomokatsu Ishizu, Yuri Kai, Chieko Kawamoto, Hiroshi Kawamura, Yuki I. Kempfle, Judith S. Kenna, Tony J. Kere, Juha Khachigian, Levon M. Kitamura, Toshio Klein, Sarah Peter Klinken, S. Knox, Alan J. Kojima, Soichi Koseki, Haruhiko Koyasu, Shigeo Lee, Weonju Lennartsson, Andreas MacKay-Sim, Alan Mejhert, Niklas Mizuno, Yosuke Morikawa, Hiromasa Morimoto, Mitsuru Moro, Kazuyo Morris, Kelly J. Motohashi, Hozumi Mummery, Christine L. Nakachi, Yutaka Nakahara, Fumio Nakamura, Toshiyuki Nakamura, Yukio Nozaki, Tadasuke Ogishima, Soichi Ohkura, Naganari Ohno, Hiroshi Ohshima, Mitsuhiro Okada-Hatakeyama, Mariko Okazaki, Yasushi Orlando, Valerio Ovchinnikov, Dmitry A. Passier, Robert Patrikakis, Margaret Pombo, Ana Pradhan-Bhatt, Swati Qin, Xian-Yang Rehli, Michael Rizzu, Patrizia Roy, S Division of Genomic Technologies RIKEN Center for Life Science Technologies Yokohama Kanagawa 230-0045 Japan RIKEN Omics Science Center Yokohama Kanagawa 230-0045 Japan Department of Medicine Karolinska Institutet Stockholm 14186 Sweden Karolinska University Hospital Center for Metabolism and Endocrinology Stockholm 14186 Sweden Scottish Centre for Regenerative Medicine University of Edinburgh 5 Little France Drive Edinburgh EH164UU United Kingdom Department of Dermatology and Allergy Charite University Medicine Berlin Charitéplatz 1 Berlin 10117 Germany Roslin Institute and Royal School of Veterinary Studies University of Edinburgh Edinburgh EH259RG United Kingdom Australian Infectious Diseases Research Centre University of Queensland St Lucia 4072 QLD Australia School of Chemistry and Molecular Biosciences University of Queensland St Lucia 4072 QLD Australia Bio-Rad Laboratories Pty Ltd Hercules 94547 CA United States University of Queensland Diamantina Institute University of Queensland Woolloongabba 4102 QLD Australia IRCCS Fondazione Santa Lucia Via del Fosso di Fiorano 64 Rome 00143 Italy Australian Institute for Bioengineering and Nanotechnology University of Queensland Brisbane St Lucia 4072 QLD Australia Division of Immunology Institute of Infectious Diseases and Molecular Medicine University of Cape Town Anzio Road Observatory 7925 South Africa Immunology of Infectious Diseases Faculty of Health Sciences South African Medical Research Council University of Cape Town Anzio Road 7925 South Africa International Centre for Genetic Engineering and Biotechnology Cape Town Component Anzio Road 7925 South Africa Hubrecht Institute Royal Netherlands Academy of Arts and Sciences Uppsalalaan 8 3584 Netherlands University Medical Centre Utrecht Postbus 85500 Utrecht 3508 Netherlands Genomics Cold Spring Harbor Laboratory Cold Spring Harbor New York 11797 NY United States Institute of Pharmaceutical Sciences ETH Zurich Vladi

In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.

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A Hybrid Methodology for Tackling the Irregular Strip Packing Problem *

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IFAC Proceedings Volumes 2013年第7期46卷 396-401页

作者： Bonfim A. Junior Plácido R. Pinheiro Rommel D. Saraiva Graduate Program in Applied Informatics University of Fortaleza Av. Washington Soares 1321 - J30 60.811-905 Fortaleza - Brazil

This paper presents a hybrid approach for tackling the irregular strip packing problem, which requires a set of polygons to be placed within a rectangular object. The methodology includes a meta-heuristic engine (e.g., a genetic algorithm) that determines the order in which polygons are handled by a placement heuristic. In addition, differently from several approaches presented in the literature, we investigate the application of the no-fit polygon as a placement tool for obtaining local optima. The results are further improved by a shrinking algorithm that works within the meta-heuristic component. To assess the potentials of the proposed methodology, computational experiments performed on a set of difficult benchmark instances of the irregular strip packing problem are discussed here for evaluation purposes.

关键词： Cutting and Packing Nesting and Irregular Shapes Packing Industrial Applications Hybrid Methods Genetic Algorithm

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Dealing the Selection of Project Management through Hybrid Model of Verbal Decision Analysis

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Procedia Computer Science 2013年 17卷 332-339页

作者： Plácido Rogerio Pinheiro Thais Cristina Sampaio Machado Isabelle Tamanini University of Fortaleza (UNIFOR) Graduate Program in Applied Informatics Av. Washington Soares 1321 - Bl J Sl 30 - 60.811-905 Fortaleza Brazil

The decision may be defined as a result of a process of choice, given an identified problem or when the decision maker faces an opportunity of creation, optimization or improvement in an environment. Considering that agile methodologies, in focus Framework SCRUM, are always more popular in Development Software Companies, and noticing that the mentioned companies cannot always apply every characteristics of the framework, this paper presents an hybrid application of methodologies from Verbal Decision Analysis (VDA) framework to select some of the SCRUM approaches to be applied in the company, considering the elicitation of preferences of a decision maker. The work intends to provide an evaluation of Project Management approaches applied in the Software Development and examine them toward to identify which are the most preferable ones, aided by the application of a hybrid model of decision making. The hybrid model aims at classifying alternatives using ORCLASS method, through the developed software, and ranking them using a Verbal Decision Analysis method (ZAPROS III-i). Afterward, Specific Practices (SP) of Capability Maturity Model Integration (CMMi) level 2 were chosen, and approaches to attend the SP's were ranked from the most preferable to the least preferable ones, aiming to help enterprises which are not able to reach a complete CMMi qualification.

关键词： Verbal Decision Analysis ZAPROS III-i ORCLASS Project Management Specific Practices Capability Maturity Model Integration

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Service Agile Development Using XP

Service Agile Development Using XP

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2013 IEEE Seventh International Symposium on Service-Oriented System Engineering

作者： Felipe Carvalho Leonardo Guerreiro Azevedo Petrobras-Petróleo Brasileiro S/A Graduate Program in Informatics (PPGI) Federal University of the State of Rio de Janeiro Rio de Janeiro Brazil Applied Informatics Department (DIA) Graduate Program in Informatics (PPGI) Federal University of the State of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9781467356596

System development using a Service-Oriented Architecture approach encompasses new roles and tasks as opposed to traditional development. It brings new challenges in different aspects, such as: reuse, flexibility, stakeholders' involvement, business understanding. Considering methods for system development, those aspects are handled by agile methods. However, there is no consensus on how to use agile methods in service-oriented system development. Agile methods can be used in different phases of a software development lifecycle, such as: project management, modeling, software construction, software testing. Extreme programming (XP) is one of the methods more closely related to the construction phase. XP is widely adopted in the industry and offers practices that can be applied to several business contexts. The goal of this work is to propose guidelines and best practices towards service development, focused on the construction phase, in an SOA environment using XP. It goes towards the identification of the shared concerns and the gaps between SOA and XP practices and, additionally, presents open issues and main challenges to be considered when incrementally constructing service solutions with continuous feedback and flexibility to rapidly develop services that meet changing business requirements.

关键词： Service-oriented architecture Semiconductor optical amplifiers Contracts Complexity theory programming

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3D segmentation and visualization of lung and its structures using CT images of the thorax

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Journal of Biomedical Science and Engineering 2013年第11期6卷 1099-1108页

作者： Pedro P.Reboucas Filho Paulo Cesar Cortez Victor Hugo C.de Albuquerque Industry Area Federal Institute of Education Science and Technology of CearaMaracanauBrazil Teleinformatic Engineering Department Federal University of CearáFortalezaBrazil Graduate Program in Applied Informatics University of FortalezaFortalezaBrazil

Computing systems have been playing an important role in various medical fields, notably in image diagnosis. Studies in the field of Computational Vision aim at developing techniques and systems capable of detecting various illnesses automatically. What has been highlighted among the existing exams that allow diagnosis aid and the application of computing systems in parallel is Computed Tomography (CT). CT enables the visualization of internal organs, such as the lung and its structures. Computational Vision systems extract information from the CT images by segmenting the regions of interest, and then recognize and identify details in those images. This work focuses on the segmentation phase of CT lung images with singularity-based techniques. Among these methods are the region growing (RG) technique and its 3D RG variations and the thresholding technique with multi-thresholding. The 3D RG method is applied to lung segmentation and from the 3D RG segments of the lung hilum, the multi-thresholding can segment the blood vessels, lung emphysema and the bones. The results of lung segmentation in this work were evaluated by two pulmonologists. The results obtained showed that these methods can integrate aid systems for medical diagnosis in the pulmonology field.

关键词： 3D Region Growing Lungs segmentation COPD Pulmonary Structure Visualization Computed Tomography

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Hierarchical Classification of Bird Species Using Their Audio Recorded Songs

Hierarchical Classification of Bird Species Using Their Audi...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Carlos N. Silla Celso A. A. Kaestner Post-Graduate Program in Informatics (PPGI) Federal University of Technology of Paraná (UTFPR-CP) Cornélio Procópio Brazil Post-Graduate Program in Applied Computer Science (PPGCA) Federal University of Technology of Paraná (UTFPR) Curitiba Brazil

ISBN: (纸本)9781479906505

In this paper we address the task of hierarchical bird species identification from audio recordings. We evaluate three types of approaches to deal with hierarchical classification problems: the flat classification approach, the local-model per parent node classifier approach and the global-model hierarchical-classification approach. For the flat and local-model classification approach we employ the classic Naive Bayes algorithm. For the global-model approach we use the Global Model Naive Bayes (GMNB) algorithm. As in the classical Naive Bayes, the algorithm computes prior probabilities and likelihoods, but these computations take into account the hierarchical classification scenario: it assumes that any example which belongs to a given class will also belong to all its ancestor classes. In the current application, the employed class hierarchy is the standard scientific taxonomy of birds used in Biology. In order to deal with the bird songs we obtain features by computing several acoustic quantities from intervals of the audio signal. We conduct three experiments in order to compare the three different approaches to the hierarchical bird species identification problem. Our experimental results show that the use of the GMNB hierarchical classification algorithm outperforms both the flat and local-model approaches (Using the Hierarchical F-measure metric);hence the use of a global-model approach (such as the GMNB) can be a feasible way to improve the classification performance for problems with a large number of classes.

关键词： Bird species identification Audio classification Hierarchical classification Hierarchical Naive Bayes classifier bird species Hierarchical Bayes Audio recordings audio signals Songs

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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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Towards the applied hybrid model in decision making: Support the early diagnosis of type 2 diabetes

Towards the applied hybrid model in decision making: Support...

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3rd International Conference on Information Computing and Applications, ICICA 2012

作者： Menezes, Andrea Carvalho Pinheiro, Placido Rogerio Pinheiro, Mirian Caliope Dantas Cavalcante, Tarcísio Pequeno Graduate Program in Applied Informatics Av. Washington Soares 1321 - Bl J Sl 30 60.811-905 Fortaleza Brazil

ISBN: (纸本)9783642340611

A hybrid model, combining Bayesian network and a multicriteria method, is presented in order to assist with the decision making process about which questions would be more attractive to the definition of the diagnosis of Diabetes type 2. We have proposed the application of an expert system structured in probability rules and structured representations of knowledge in production rules and probabilities (Artificial Intelligence - AI). The importance of the early diagnosis associated with the appropriate treatment is to decrease the chance of developing the complications of diabetes, reducing the impact on our society. Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. © 2012 Springer-Verlag.

关键词： Expert systems

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World Congress Integrative Medicine & Health 2017: Part one: Berlin, Germany. 3-5 May 2017

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BMC Complement Altern Med 2017年第SUPPL 1期17卷 322-322页

作者： Benno Brinkhaus Torkel Falkenberg Aviad Haramati Stefan N. Willich Josephine P. Briggs Merlin Willcox Klaus Linde Töres Theorell Lisa M. Wong Jeffrey Dusek Darong Wu David Eisenberg Bettina Berger Kathi Kemper Beate Stock-Schröer Hedda Sützl-Klein Rosaria Ferreri Gary Kaplan Harald Matthes Gabriele Rotter Elad Schiff Zahi Arnon Eckhard Hahn Christina M. Luberto David Martin Silke Schwarz Diethard Tauschel Andrew Flower Harsha Gramminger Hedwig H. Gupta S. N. Gupta Annette Kerckhoff Christian S. Kessler Andreas Michalsen Eun S. Kim Eun H. Jang Rana Kim Sae B. Jan Martin Mittwede Wiebke Mohme Eran Ben-Arye Massimo Bonucci Bashar Saad Thomas Breitkreuz Elio Rossi Rejin Kebudi Michel Daher Samaher Razaq Nahla Gafer Omar Nimri Mohamed Hablas Gunver Sophia Kienle Noah Samuels Michael Silbermann Lena Bandelin Anna-Lena Lang Eva Wartner Christoph Holtermann Maxwell Binstock Robert Riebau Edin Mujkanovic Holger Cramer Romy Lauche Andres Michalsen Lesley Ward Dominik Irnich Wolfram Stör Geoffrey Burnstock Hans-Georg Schaible Thomas Ots Jost Langhorst Tobias Sundberg Catherina Amarell Melanie Anheyer Marion Eckert Mercedes Ogal Annette Schönauer Birgit Reisenberger Bernhard Brand Dennis Anheyer Gustav Dobos Matthias Kroez Aldo Ammendola Jun J. Mao Claudia Witt Yufei Yang Miriam Oritz Markus Horneber Petra Voiß Alexandra von Rosenstiel Catharina Amarell Friedemann Schad Marc Schläppi Matthias Kröz Arndt Büssing Gil Bar-Sela David Avshalomov Samuel Attias Sian Cotton Miek Jong Mats Jong Christian Scheffer Friedrich Edelhäuser Abdullah AlBedah Myeong Soo Lee Mohamed Khalil Keiko Ogawa Yoshiharu Motoo Junsuke Arimitsu Masao Ogawa Genki Shimizu Rainer Stange Karin Kraft Kenny Kuchta Kenji Watanabe D Bonin Harald Gruber Sabine Koch Urs Pohlmann Christine Caldwell Barbara Krantz Ria Kortum Lily Martin Lisa S. Wieland Ben Kligler Susan Gould-Fogerite Yuqing Zhang John J. Riva Michael Lumpkin Emily Ratner Liu Ping Pei Jian Gesa-Meyer Hamme Xiaosong Mao Han Chouping Sven Schröder Josef Hummelsberger Michael Wullinger Marc Brodzky Chr Institute for Social Medicine Epidemiology and Health Economics Charité – Universitätsmedizin Berlin Berlin Germany Department of Neurobiology Care Sciences and Society Division of Nursing Research Group Integrative Care Karolinska Institutet Stockholm Sweden I C – The Integrative Care Science Center Järna Sweden Department of Biochemistry Molecular and Cellular Biology Georgetown University Medical Center Washington DC USA Department of Medicine Georgetown University Medical Center Washington DC USA NCCIH NIH Bethesda MD USA Department of Primary Care and Population Sciences University of Southampton Aldermoor Health Centre Coxford Rd Southampton 2016 5ST UK Institute of General Practice Technical University Munich Munich Germany Department of Neuroscience Karolinska Institute Stockholm Sweden Stress Research Institute Stockholm University Stockholm Sweden Arts and Humanities Initiative Harvard Medical School Boston MA 02115 USA Psychosomatic medicine Neuropsychology Allina Health Minneapolis MN USA nd Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou China Department of Nutrition Harvard University T H Chan School of Public Health Boston MA 02115 USA Department of Health University of Witten/Herdecke Witten/Herdecke Germany OSU Blacklick OH USA Carstens-Foundation and FORUM D-45276 Essen Germany ESIHR (European Society for Integrative Health Care) A-1070 Vienna Austria Hospital Centre of Integrated Medicine Hospital of Pitiglian o ASL SudEst Toscana Grosseto Italy The Kaplan Center for Integrative Medicine Georgetown University McLean VA USA Hospital Havelhöhe Berlin Germany Institute for Social Medicine Epidemiology and Health Economics Charité University Hospital Berlin Germany Internal medicine and Complementary medicine service Bnai Zion Medical Center Haifa Israel Complementary-Integrative Surgery Service Bnai Zion Medical Center Haifa Israel The Emek Yezreel Academic College Yezreel Valley Israel Medicine

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A novel application of crossover operator to a hybrid optimization framework: Investigation into cutting problems

A novel application of crossover operator to a hybrid optimi...

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Congress on Evolutionary Computation

作者： Rommel Dias Saraiva Plácido Rogério Pinheiro State University of Ceará Fortaleza Brazil Graduate Program in Applied Informatics University of Fortaleza-UNIFOR Fortaleza Brazil

ISBN: (纸本)9781467315104

The Generate and Solve (GS) is a hybrid optimization framework that combines a metaheuristic engine (genetic algorithm), which works as a generator of reduced instances of the original optimization problem, and an integer programming solver. GS has been recently introduced in the literature and achieved promising results in cutting and packing problem instances. In this paper, we present a novel application of crossover operator, the Uniform Order-Based Crossover, to the GS framework. As a means to assess the potentialities behind the novel application, we provide as instantiation of the framework for dealing specifically with the constrained two-dimensional non-guillotine cutting problem. Computational experiments performed over standard benchmark problems are reported and discussed here, evidencing the effectiveness of the novel operator.

关键词： Genetic algorithms Optimization Biological cells Heuristic algorithms Integer linear programming Search problems Hybrid power systems

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