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International Joint Conference on Neural Networks (IJCNN)

作者： Alexandre C. Barbosa Thays A. Oliveira Vitor N. Coelho Graduate Program in Sustainable Territorial Development Universitá Degli Studi di Padova Italy and Katholieke Universiteit Leuven Belgium Universitè Paris 1 Pantheon-Sorbonne France Graduate Program in Engineering and Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain Institute of Computer Science Universidade Federal Fluminense Niterói RJ Brazil

The smart city debate will still be the scope of business, policy-making and territorial planning in the following years. Based on that, the paper aims to propose an interdisciplinary conceptualization of smart territories. The goal is to promote the contrary movement of megacities creation and also consolidate the geographical aspect of smartness. The concept was formulated based on the elements of sustainable territorial development, strategic spatial planning and smart governance. In addition, taking hand of a parallel literature review, the study explores the potential of creating complementary cryptocurrencies as a strategy of territorial planning. This term was built based on already existing complementary currency systems in distributed ledger technologies scope. The idea provided presents a great potential for poverty alleviation by bringing together financial and digital inclusion.

关键词： Planning Smart cities Collaboration Decision making Government Cryptography Cultural differences

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The SRG/eROSITA All-Sky Survey: Dark Energy Survey Year 3 Weak Gravitational Lensing by eRASS1 selected Galaxy Clusters

arXiv

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arXiv 2024年

作者： Grandis, S. Ghirardini, V. Bocquet, S. Garrel, C. Mohr, J.J. Liu, A. Kluge, M. Kimmig, L. Reiprich, T.H. Alarcon, A. Amon, A. Artis, E. Bahar, Y.E. Balzer, F. Bechtol, K. Becker, M.R. Bernstein, G. Bulbul, E. Campos, A. Carnero Rosell, A. Carrasco Kind, M. Cawthon, R. Chang, C. Chen, R. Chiu, I. Choi, A. Clerc, N. Comparat, J. Cordero, J. Davis, C. Derose, J. Diehl, H.T. Dodelson, S. Doux, C. Drlica-Wagner, A. Eckert, K. Elvin-Poole, J. Everett, S. Ferte, A. Gatti, M. Giannini, G. Giles, P. Gruen, D. Gruendl, R.A. Harrison, I. Hartley, W.G. Herner, K. Huff, E.M. Kleinebreil, F. Kuropatkin, N. Leget, P.F. Maccrann, N. McCullough, J. Merloni, A. Myles, J. Nandra, K. Navarro-Alsina, A. Okabe, N. Pacaud, F. Pandey, S. Prat, J. Predehl, P. Ramos, M. Raveri, M. Rollins, R.P. Roodman, A. Ross, A.J. Rykoff, E.S. Sanchez, C. Sanders, J. Schrabback, T. Secco, L.F. Seppi, R. Sevilla-Noarbe, I. Sheldon, E. Shin, T. Troxel, M. Tutusaus, I. Varga, T.N. Wu, H. Yanny, B. Yin, B. Zhang, X. Zhang, Y. Alves, O. Bhargava, S. Brooks, D. Burke, D.L. Carretero, J. Costanzi, M. da Costa, L.N. Pereira, M.E.S. De Vicente, J. Desai, S. Doel, P. Ferrero, I. Flaugher, B. Friedel, D. Frieman, J. García-Bellido, J. Gutierrez, G. Hinton, S.R. Hollowood, D.L. Honscheid, K. James, D.J. Jeffrey, N. Lahav, O. Lee, S. Marshall, J.L. Menanteau, F. Ogando, R.L.C. Pieres, A. Plazas Malagón, A.A. Romer, A.K. Sanchez, E. Schubnell, M. Smith, M. Suchyta, E. Swanson, M.E.C. Tarle, G. Weaverdyck, N. Weller, J. Universität Innsbruck Institut für Astro- und Teilchenphysik Technikerstr. 25/8 Innsbruck6020 Austria Max Planck Institute for Extraterrestrial Physics Giessenbachstrasse 1 Garching85748 Germany Faculty of Physics Ludwig-Maximilians-Universität München Scheinerstr. 1 Munich81679 Germany Universität Bonn Auf dem Hügel 71 Bonn53121 Germany Kavli Institute for Cosmology University of Cambridge Mading- ley Road CambridgeCB3 0HA United Kingdom Institute of Astronomy University of Cambridge Madingley Road CambridgeCB3 0HA United Kingdom Physics Department University of Wisconsin-Madison MadisonWI53706 United States Argonne National Laboratory 9700 South Cass Avenue LemontIL60439 United States Department of Physics and Astronomy University of Pennsylvania PhiladelphiaPA19104 United States Department of Physics Carnegie Mellon University PittsburghPA15312 United States Instituto de Astrofisica de Canarias Tenerife La LagunaE-38205 Spain Laboratório Interinstitucional de e-Astronomia - LIneA Rua Gal. José Cristino 77 RJ Rio de Janeiro20921-400 Brazil Universidad de La Laguna Dpto. Astrofísica Tenerife La LagunaE-38206 Spain Center for Astrophysical Surveys National Center for Supercom- puting Applications 1205 West Clark St. UrbanaIL61801 United States Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States Physics Department William Jewell College LibertyMO64068 United States Department of Astronomy and Astrophysics University of Chicago ChicagoIL60637 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Department of Physics Duke University DurhamNC27708 United States Department of Physics National Cheng Kung University Tainan70101 Taiwan NASA Goddard Space Flight Center 8800 Greenbelt Rd Green- belt MD20771 United States IRAP Université de Toulouse CNRS UPS CNES Toulouse France Jodrell Bank Center f

Context. Number counts of galaxy clusters across redshift are a powerful cosmological probe, if a precise and accurate reconstruction of the underlying mass distribution is performed - a challenge called mass calibration. With the advent of wide and deep photometric surveys, weak gravitational lensing by clusters has become the method of choice to perform this measurement. Aims. We measure and validate the weak gravitational lensing (WL) signature in the shape of galaxies observed in the first 3 years of the Dark Energy Survey (DES Y3) caused by galaxy clusters and groups selected in the first all-sky survey performed by SRG (Spectrum Roentgen Gamma)/eROSITA (eRASS1). These data are then used to determine the scaling between X-ray photon count rate of the clusters and their halo mass and redshift. Methods. We empirically determine the degree of cluster member contamination in our background source sample. The individual cluster shear profiles are then analysed with a Bayesian population model that self-consistently accounts for the lens sample selection and contamination, and includes marginalization over a host of instrumental and astrophysical systematics. To quantify the accuracy of the mass extraction of that model, we perform mass measurements on mock cluster catalogs with realistic synthetic shear profiles. This allows us to establish that hydro-dynamical modelling uncertainties at low lens redshifts (z © 2024, CC BY.

关键词： Calibration

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Managing distributed UCONabc policies with authorization assertions and policy templates 20

Managing distributed UCONabc policies with authorization ass...

引用

20th IEEE Symposium on computers and Communication, ISCC 2015

作者： Stihler, Maicon Santin, Altair O. Marcon, Arlindo L. Federal Center for Technological Education-CEFET-MG Department of Computing and Mechanics LeopoldinaMG Brazil Pontifical Catholic University of Parana-PUCPR Graduate Program on Computer Science-PPGIa CuritibaPR Brazil

ISBN: (纸本)9781467371940

Managing UCONabc policies in modern distributed computing systems is a challenge for traditional approaches. The provisioning model has trouble to keep track and to synchronize large numbers of distributed policies, outsourcing model may suffer from network overhead and single point of failure. This paper describes an approach to manage distributed UCONabc policies, derived from the combination of authorization assertions and policy templates. It combines the benefits of provisioning and outsourcing, eliminating their respective drawbacks. Prototyping details and performance evaluation are shown, messages are 42.7% smaller than provisioning and response times are faster than outsourcing. © 2015 IEEE.

关键词： Outsourcing

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Local changes in marching cubes to generate less degenerated triangles 10

Local changes in marching cubes to generate less degenerated...

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10th International Conference on computer Graphics Theory and Applications, GRAPP 2015

作者： Leal, Thiago F. Peixoto, Aruquia B. M. Silva, Cassia I. G. Dreux, Marcelo De A. De Moura, Carlos A. Department of Mathematics Rio de Janeiro Federal Institute IFRJ Paracambi Rio de Janeiro Brazil Mechanical Engineering Doctorate Program Rio de Janeiro State University UERJ Rio de Janeiro Brazil Department of Basic Disciplines CEFET/RJ Nova Iguaçu Rio de Janeiro Brazil Computer Science Doctorate Program Fluminense Federal University UFF Niteroi Rio de Janeiro Brazil Mechanical Engineering Department Rio de Janeiro Pontifical Catholic University PUC-Rio Rio de Janeiro Brazil Mathematics and Statistics Institute Rio de Janeiro State University UERJ Rio de Janeiro Brazil

ISBN: (纸本)9789897580871

The Marching Cubes algorithm is widely used to generate surfaces from implicit functions. It builds a mesh of triangles but many degenerated ones happen to appear among them, which can make the mesh thus built unfit for many applications, like the Finite Element Method. To overcome this undesired behavior our work proposes changes on the triangle generation that are automatically generated by Marching Cubes inside each voxel. We first generate the polygon border inside each voxel that intersects the surface. Each polygon is tested so as to guarantee the need to insert a new vertex inside itself, the triangles being then generated according to each polygon properties in order to guarantee the best ratio between their sides and angles. The resulting triangles inside each voxel exhibit the best possible ratio between their dimensions, thus leading to a better mesh. Copyright © 2015 SCITEPRESS - science and Technology Publications. All rights reserved.

关键词： Finite element method

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

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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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"Minha Saude" a healthcare social network for patients with cardiovascular diseases

"Minha Saude" a healthcare social network for patients with ...

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IEEE International Conference on Serious Games and Applications for Health (SeGAH)

作者： Edhelmira Lima-Medina Orlando Loques Claudio Mesquita Computing Institute - Graduate Program in Computer Science Fluminense Federal University Niterói RJ Brazil School of Medicine Graduate Program in Cardiovascular Science Fluminense Federal University Niterói RJ Brazil

Many patients use the Internet to find information that can improve their health conditions. In this context, Health Social Networks are acquiring greater force in people's lives by offering them opportunities for social networking to expose questions, experiences, besides new treatments and seek to form relationships giving or receiving emotional support. We developed a Healthcare Social Network called "Minha Saude", a virtual environment that facilitates contact between patients with cardiovascular problems with the goal to promote actions related to social inclusion of people involved. Through a called "Care Plan" available in the Social Network, we tried to motivate patients to get more interest in their own care. Daily activities, emotional states, symptoms and situations will be provided by the patient in the system through any device with internet connection. This information will be used to visualize the progress of patient's health and can be used to make medical decisions as needed. Also, we distinguish an important fact related to the Care Plan, which is the inter-relationship between patients with similar characteristics, we found it important to this action that patients can feed back their experiences and this fact can serve as motivation for them to adhere more their treatments. For this, we developed an algorithm following a Content-plus-link approach for friendship recommendation between those patients who share similar interests and thus increase the level of collaboration and communication between them. This recommendation is based on data from clinical profile, health status, interests and possible previously existing connections. The results are promising about to use of the Care Plan module and the recommendations that were accepted by the participants to create friendship.

关键词： Social network services Vectors Diseases Internet Biomedical monitoring Monitoring

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A heuristic fuzzy algorithm bio-inspired by Evolution Strategies for energy forecasting problems

A heuristic fuzzy algorithm bio-inspired by Evolution Strate...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Vitor N. Coelho Frederico G. Guimarães Agnaldo J. R. Reis Igor M. Coelho Bruno N. Coelho Marcone J. F. Souza Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Departament of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Control Engineering and Automation Universidade Federal de Ouro Preto Ouro Preto MG Brazil Institute of Computing Universidade Federal Fluminense Niteri RJ Brazil Department of Computer Science Universidade Federal de Ouro Preto Ouro Preto MG Brazil

Improving the use of energy resources has been a great challenge in the last years. A new complex scenario involving a decentralized bidirectional communication between energy suppliers, distribution system and consumption is nowadays becoming reality. Sometimes cited as the largest and most complex machine ever built, Electric Grids (EG) are been transformed into Smart Grids (SG). Hence, the load forecasting problem has become more difficulty and more autonomous load predictors are needed in this new conjecture. In this paper a novel method, so-called MSES, bio-inspired by Evolution Strategies (ES) combined with Multi-Start (MS) procedure is described. This procedure is mainly based on a self-adaptive algorithm to calibrate the parameters of the fuzzy rules. MSES was implemented in C++ via OptFrame framework. Our main goal is to evaluate the performance of this algorithm in a grid environment. Real data from an electric utility have been used in order to test the proposed methodology. The obtained results are fully described and analyzed.

关键词： Forecasting Vectors Prediction algorithms Predictive models Training Standards Adaptation models

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Qualitocracy: A data quality collaborative framework applied to citizen science

Qualitocracy: A data quality collaborative framework applied...

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2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012

作者： Antelio, Marcio Esteves, Maria Gilda P. Schneider, Daniel Souza, Jano Moreira De PESC/COPPE/UFRJ Graduate School of Engineering Federal University of Rio de Janeiro Brazil CEFET-RJ Graduate School of Engineering Federal Center for Technological Education Celso Suckow Da Fonseca Brazil DEMAT/ICE/UFRRJ School of Computer Science Federal Rural University of Rio de Janeiro Brazil

ISBN: (纸本)9781467317146

Citizen science projects generally use the Web platform to promote scientific research and recruit volunteers to assist them. Through a crowdsourcing platform, a large amount of data is submitted and some factors may lead the scientific community to doubt the seriousness of some projects. This may be due to the unreliability of data collected on a voluntary basis and the absence of criteria for quality control of the submitted data. Our main research goal is to propose a collaborative framework for improving data quality. By associating data quality dimensions to scientists through a voting network, we aim to create a continuous process for data quality validation. © 2012 IEEE.

关键词： Crowdsourcing

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Multiobjective optimization for project portfolio selection 12

Multiobjective optimization for project portfolio selection

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14th International Conference on Genetic and Evolutionary Computation Companion, GECCO'12 Companion

作者： De Barros, Márcio O. Costa, Hélio R. Figueiredo, Fábio V. Da Rocha, Ana Regina C. Post-graduate Information Systems Program - PPGI UNIRIO Av. Pasteur 458 Urca - Rio de Janeiro RJ Brazil COPPE UFRJ System Engineering and Computer Science Department Caixa Postal: 68511 CEP: 21945-970 - Rio de Janeiro Brazil CCA-RJ Brazilian Air Force Ponta do Galeão s/no Ilha do Governador CEP: 21941-510 - Rio de Janeiro Brazil

ISBN: (纸本)9781450311786

This paper proposes a multiobjective heuristic search approach to support a project portfolio selection technique on scenarios with a large number of candidate projects. The original formulation for the technique requires analyzing all combinations of candidate projects, which is unfeasible when more than a few alternatives are available. We have used a multiobjective genetic algorithm to partially explore the search space of project combinations and select the most effective ones. We present an experimental study based on four project selection problems that compares the results found by the genetic algorithm to those yielded by a non-systematic search procedure. Results show evidence that the project selection technique can be used in large-scale scenarios and that GA presents better results than simpler search strategy. Copyright is held by the author/owner(s).

关键词： Multiobjective optimization

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Qualitocracy: A Data Quality Collaborative Framework Applied to Citizen science

Qualitocracy: A Data Quality Collaborative Framework Applied...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Marcio Antelio Maria Gilda P. Esteves Daniel Schneider Jano Moreira de Souza CEFET-RJ Graduate School of Engineering Federal Center for Technological Education Celso Suckow da Fonseca PESC/COPPE/UFRJ Graduate School of Engineering Federal University of Rio de Janeiro DEMAT/ICE/UFRRJ School of Computer Science Federal Rural University of Rio de Janeiro

ISBN: (纸本)9781467317139

关键词： Data quality Crowdsourcing Citizen science Collaborative framework Data Quality Seriousness Continuous production scientific research scientific community science projects Quality Control Frameworks

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