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Correction to: Gyral-sulcal contrast in intrinsic functional brain networks across task performances

Brain imaging and behavior 2021年第4期15卷 2235页

作者： Lin Zhao Tuo Zhang Lei Guo Tianming Liu Xi Jiang School of Automation Northwestern Polytechnical University Xi'an China. Cortical Architecture Imaging and Discovery Lab Department of Computer Science and Bioimaging Research Center The University of Georgia Athens GA USA. School of Automation Northwestern Polytechnical University Xi'an China. tuozhang@***. School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China. xijiang@***.

A Correction to this paper has been published: https://***/10.1007/s11682-020-00426-z

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Exploring vestibulo-ocular adaptation in a closed-loop neuro-robotic experiment using STDP. A simulation study

arXiv

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arXiv 2020年

作者： Naveros, Francisco Garrido, Jesús A. Arleo, Angelo Ros, Eduardo Luque, Niceto R. Department of Computer Architecture and Technology University of Granada Granada18014 Spain Institut de la Vision Institut National de la Santé et de la Recherche Médicale U968 and Centre National de la Recherche Scientifique ParisUMR_7210 France UMR_S 968 Sorbonne Universités Université Pierre et Marie Curie Paris 06 Paris France

Studying and understanding the computational primitives of our neural system requires for a diverse and complementary set of techniques. In this work, we use the Neuro-robotic Platform (NRP) to evaluate the vestibulo ocular cerebellar adaptation (Vestibulo-ocular reflex, VOR) mediated by two STDP mechanisms located at the cerebellar molecular layer and the vestibular nuclei respectively. This simulation study adopts an experimental setup (rotatory VOR) widely used by neuroscientists to better understand the contribution of certain specific cerebellar properties (i.e. distributed STDP, neural properties, coding cerebellar topology, etc.) to r-VOR adaptation. The work proposes and describes an embodiment solution for which we endow a simulated humanoid robot (iCub) with a spiking cerebellar model by means of the NRP, and we face the humanoid to an r-VOR task. The results validate the adaptive capabilities of the spiking cerebellar model (with STDP) in a perception-action closed-loop (r-VOR) causing the simulated iCub robot to mimic a human behavior. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain

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Communication lower bound in convolution accelerators

arXiv

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arXiv 2019年

作者： Chen, Xiaoming Han, Yinhe Wang, Yu Center for Intelligent Computing Systems State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Department of Electronic Engineering Tsinghua University Beijing China

In current convolutional neural network (CNN) accelerators, communication (i.e., memory access) dominates the energy consumption. This work provides comprehensive analysis and methodologies to minimize the communication for CNN accelerators. For the off-chip communication, we derive the theoretical lower bound for any convolutional layer and propose a dataflow to reach the lower bound. This fundamental problem has never been solved by prior studies. The on-chip communication is minimized based on an elaborate workload and storage mapping *** in addition design a communication-optimal CNN accelerator architecture. Evaluations based on the 65nm technology demonstrate that the proposed architecture nearly reaches the theoretical minimum communication in a threelevel memory hierarchy and it is computation dominant. The gap between the energy efficiency of our accelerator and the theoretical best value is only 37-87%. Copyright © 2019, The Authors. All rights reserved.

关键词： Acceleration

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Comparing the Design Neurocognition of Mechanical Engineers and Architects: A Study of the Effect of Designer’s Domain

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Proceedings of the Design Society: International Conference on Engineering Design 2019年第1期1卷 1853-1862页

作者： Sonia Liliana da Silva Vieira John S. Gero Jessica Delmoral Valentin Gattol Carlos Fernandes António A. Fernandes INEGI Institute of Science and Innovation in Mechanical and Industrial Engineering Porto Portugal Department of Computer Science and School of Architecture University of North Carolina at Charlotte United States AIT Austrian Institute of Technology Vienna Austria FMUP Faculty of Medicine of the University of Porto Portugal FEUP Faculty of Engineering University of Porto Portugal

New tools from neuroscience allow design researchers to explore design neurocognition. By taking the advantage of EEG's temporal resolution we give up spatial resolution to focus on the performance of time-related design tasks. This paper presents results from an experiment using EEG to measure brain activation to study mechanical engineers and architects to compare their design neurocognition. In this study, we adopted and extended the tasks described in a previous fMRI study of design neurocognition reported in the literature. The block experiment consists of a sequence of 3 tasks: problem solving, basic design and open design using a physical interface. The block is preceded by a familiarizing pre-task using the physical interface and then extended to a fourth task using free-hand sketching. Brainwaves were collected from both mechanical engineers and architects. Results comparing 36 mechanical engineers and architects while designing were produced. These results indicate design cognition differences between the two domains in task-related power between the problem-solving task and the design tasks, in temporal resolution and transformed power.

关键词： Design cognition Research methodologies and methods Human behaviour in design Design domains Design neuroscience

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Improving seismic performance of welded joints in CFST Truss towers: Effects of concrete fill and ring stiffener configurations

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Structures 2025年 77卷

作者： Cao, Yan Zandi, Y. Mohammed, Khidhair Jasim Sadighi Agdas, A. Ali, H. Elhosiny Khadimallah, Mohamed Amine Sadaghdes, Z. Asllzadhe, Hamid School of Computer Science and Engineering Xi'an Technological University Xi'an710021 China School of Mechatronic Engineering Xi'an Technological University Xi'an710021 China Department of Civil Engineering Tabriz Branch Islamic Azad University Tabriz Iran Air Conditioning and Refrigeration Techniques Engineering Department College of Engineering and Technologies Al-Mustaqbal University Babylon Hilla51001 Iraq Ghateh Gostar Novin Company Tabriz51579 Iran Department of Physics Faculty of Science King Khalid University P.O. Box 9004 Abha61413 Saudi Arabia Department of Civil Engineering College of Engineering in Al-Kharj Prince Sattam Bin Abdulaziz University Al-Kharj11942 Saudi Arabia College of Civil Engineering and Architecture Zhejiang University Hangzhou310058 China Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Engineering & Technology Duy Tan University Da Nang Viet Nam Department of Biomaterials Saveetha Dental College and Hospital Saveetha Institute of Medical and Technical Sciences Chennai600077 India

This study presents a novel approach to enhance the longevity and seismic resilience of ‎ Concrete-Filled Steel Tubular (CFST) frame towers commonly used in ‎onshore wind turbines. Fatigue-related failures at welded joints pose significant challenges to the durability of these towers. This research investigates the impact of optimized ring stiffener ‎configurations and concrete infill on reducing stress concentrations and improving ‎fatigue resistance under simulated seismic loading. The study utilizes with samples including CFST-gusset plate joints and non-concrete-filled joints, with different configurations of concrete infill and ring stiffeners. ‎These samples were evaluated under static loading to assess the influence of stiffener width, thickness, and spacing on Stress Concentration Factors (SCFs). Subsequently, cyclic loading tests were conducted to observe crack initiation and progression. The results show that ‎optimized configurations of both concrete fill and ring stiffeners significantly reduce ‎SCFs, improve stress distribution, and delay crack initiation, enhancing the seismic ‎fatigue performance of CFST joints. Moreover, the study integrates Artificial Intelligence ‎‎(AI) techniques, specifically Support Vector Machines (SVM), to predict the fatigue ‎behavior of these joints under different loading conditions. The SVM model was trained on experimental data and demonstrated high predictive accuracy in forecasting the fatigue life of CFST joints, achieving an R² value of 0.95, an RMSE of 0.11, and an MAE of 0.08. These results validate the AI model's ‎ability to optimize design parameters and predict fatigue life, contributing to more ‎efficient and reliable CFST joint design. This integration of AI enhances design ‎optimization by providing precise predictions based on complex variables like stiffener ‎geometry and concrete filling. Overall, the findings suggest that incorporating ‎optimized stiffener configurations, concrete infill, and AI-based desi

关键词： Stress concentration

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Measurement of the τ lepton polarization in Z boson decays in proton-proton collisions at (Formula presented.)

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Journal of High Energy Physics 2024年第1期2024卷 101页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Escalante Del Valle, A. Hussain, P.S. Jeitler, M. Krammer, N. Liko, D. Mikulec, I. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Van Mechelen, P. Bols, E.S. D’Hondt, J. Dansana, S. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Makarenko, I. Müller, D. Sahasransu, A.R. Tavernier, S. Tytgat, M. Van Putte, S. Vannerom, D. Clerbaux, B. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Khalilzadeh, A. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. De Coen, M. Dobur, D. Hong, Y. Knolle, J. Lambrecht, L. Mestdach, G. Rendón, C. Samalan, A. Skovpen, K. Van Den Bossche, N. Wezenbeek, L. Benecke, A. Bruno, G. Caputo, C. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Mondal, K. Tran, T.T. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. Menezes De Oliveira, T. Moraes, A. Rebello Teles, P. Soeiro, M. Aldá Júnior, W.L. Alves Gallo Pereira, M. Barroso Ferreira Filho, M. Brandao Malbouisson, H. Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. Fonseca De Souza, S. Martins, J. Mora Herrera, C. Mota Amarilo, K. Mundim, L. Nogima, H. Santoro, A. Silva Do Amaral, S.M. Sznajder, A. Thiel, M. Vilela Pereira, A. Bernardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. Gregores, E.M. Mercadante, P.G. Novaes, S.F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Guo, Q. Javaid, T. Mittal, M. Yuan, L. Bauer, G. Hu, Z. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Monti, F. Sharma, R. Song, J.N. Tao, J. Wang, C. Wang, J. Wang, Z. Zhang, H. Agapitos, A. Ban, Y. Lev Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) — Fudan University Shanghai China Zhejiang University Zhejiang Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics

The polarization of τ leptons is measured using leptonic and hadronic τ lepton decays in Z → τ+ τ− events in proton-proton collisions at (Formula presented.) recorded by CMS at the CERN LHC with an integrated lum... 详细信息

The polarization of τ leptons is measured using leptonic and hadronic τ lepton decays in Z → τ⁺ τ⁻ events in proton-proton collisions at (Formula presented.) recorded by CMS at the CERN LHC with an integrated luminosity of 36.3 fb⁻¹. The measured τ⁻ lepton polarization at the Z boson mass pole is P_τ(Z) = −0.144 ± 0.006 (stat) ± 0.014 (syst) = −0.144 ± 0.015, in good agreement with the measurement of the τ lepton asymmetry parameter of A_τ = 0.1439 ± 0.0043 = − P_τ(Z) at LEP. The τ lepton polarization depends on the ratio of the vector to axial-vector couplings of the τ leptons in the neutral current expression, and thus on the effective weak mixing angle sin² θWeff , independently of the Z boson production mechanism. The obtained value sin² θWeff = 0.2319 ± 0.0008(stat) ± 0.0018(syst) = 0.2319 ± 0.0019 is in good agreement with measurements at e⁺ e⁻ colliders. [Figure not available: see fulltext.]. © 2024, The Author(s).

关键词： Hadron-Hadron Scattering Tau Physics

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Eager to Learn vs. Quick to Complain? How a socially adaptive robot architecture performs with different robot personalities

Eager to Learn vs. Quick to Complain? How a socially adaptiv...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ana Tanevska Francesco Rea Giulio Sandini Lola Cañamero Alessandra Sciutti Department of Robotics Brain and Cognitive Science Italian Institute of Technology (IIT) Genova Italy Embodied Emotion Cognition and (Inter-)Action (EECAiA) Lab School of Computer Science University of Hertfordshire Hatfield United Kingdom Cognitive Architecture for Collaborative Technologies Unit Italian Institute of Technology (IIT) Genova Italy

A social robot that is aware of our needs and continuously adapts its behaviour to them has the potential of creating a complex, personalized, human-like interaction of the kind we are used to have with our peers in our everyday lives. We are interested in exploring how would an adaptive architecture function and personalize to different users when given different initial values of its variables, i.e. when implementing the same adaptive framework with different robot personalities. Would an architecture that learns very quickly outperform a slower but steadier learning profile? To further explore this, we propose a cognitive architecture for the humanoid robot iCub supporting adaptability and we attempt to validate its functionality and test different robot profiles.

关键词： Robots computer architecture Face Testing Skin Torso Visualization

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Measurement of the double-differential inclusive jet cross section in proton-proton collisions at s = 5.02 TeV

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Journal of High Energy Physics 2025年第1期2025卷 1-49页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Escalante Del Valle, A. Hussain, P.S. Jeitler, M. Krammer, N. Lechner, L. Liko, D. Mikulec, I. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Kello, T. Van Mechelen, P. Bols, E.S. D’Hondt, J. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Makarenko, I. Morton, A. Müller, D. Sahasransu, A.R. Tavernier, S. Van Putte, S. Vannerom, D. Clerbaux, B. Dansana, S. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. De Coen, M. Dobur, D. Knolle, J. Lambrecht, L. Mestdach, G. Rendón, C. Samalan, A. Skovpen, K. Tytgat, M. Van Den Bossche, N. Vermassen, B. Wezenbeek, L. Benecke, A. Bruno, G. Bury, F. Caputo, C. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Mondal, K. Tran, T.T. Vischia, P. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. Moraes, A. Rebello Teles, P. Aldá Júnior, W.L. Alves Gallo Pereira, M. Barroso Ferreira Filho, M. Brandao Malbouisson, H. Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. Dos Santos Sousa, V. Fonseca De Souza, S. Martins, J. Mora Herrera, C. Mota Amarilo, K. Mundim, L. Nogima, H. Santoro, A. Silva Do Amaral, S.M. Sznajder, A. Thiel, M. Vilela Pereira, A. Bernardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. Gregores, E.M. Mercadante, P.G. Novaes, S.F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Guo, Q. Javaid, T. Mittal, M. Yuan, L. Bauer, G. Hu, Z. Lezki, S. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Monti, F. Sharma, R. Song, J.N. Tao, J. Wang, J. Zhang, H. Aga Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) — Fudan University Shanghai China Zhejiang University Zhejiang Hangzhou China Universidad de Los Andes Bogota Venezuela Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics

The inclusive jet cross section is measured as a function of jet transverse momentum pT and rapidity y. The measurement is performed using proton-proton collision data at s = 5.02 TeV, recorded by the CMS experiment a... 详细信息

The inclusive jet cross section is measured as a function of jet transverse momentum p_T and rapidity y. The measurement is performed using proton-proton collision data at s = 5.02 TeV, recorded by the CMS experiment at the LHC, corresponding to an integrated luminosity of 27.4 pb⁻¹. The jets are reconstructed with the anti-k_T algorithm using a distance parameter of R = 0.4, within the rapidity interval |y| < 2, and across the kinematic range 0.06 < p_T< 1 TeV. The jet cross section is unfolded from detector to particle level using the determined jet response and resolution. The results are compared to predictions of perturbative quantum chromodynamics, calculated at both next-to-leading order and next-to-next-to-leading order. The predictions are corrected for nonperturbative effects, and presented for a variety of parton distribution functions and choices of the renormalization/factorization scales and the strong coupling α_S. © The Author(s) 2025.

关键词： Hadron-Hadron Scattering Jet Physics QCD

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Exploring the Mechanism of Residential Attractiveness in Compact Urban Areas – a Case Study of Hong Kong

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IOP Conference Series: Materials Science and Engineering 2020年第1期829卷

作者： Yunxi Bai Jusheng Song Shanshan Wu S M Lo Gang Bai School of Architecture Harbin Institute of Technology HIT Campus of University Town of Shenzhen Shenzhen Guangdong China Department of Architecture Tongji University Siping Road Shanghai China Department of Architecture and Civil Engineering City University of Hong Kong Tat Chee Avenue Kowloon Hong Kong College of Computer and Control Engineering Nankai University Weijin Road Tianjin China

Compact cities adopt high density, mixed land use and transit-oriented development (TOD). For sustainable development, compact development reduces the use of automobile and lessens the overdevelopment of land resources. For solving urban sprawl and housing shortage, more and more metropolises have adopted compact development. Academics, planners and policy makers mainly focused on evaluating the impacts of neighborhood attributes on housing prices and residential movements. Few have examined the relationships between residents' demand and residential attractiveness in compact cities. Therefore, this study develops Residential Attractiveness Evaluation (RAE) Model to evaluate the attractive degree of urban areas based on residents' demand in compact cities. Hong Kong is chosen as the study area which is a typical compact city. The results show that districts near the CBD and both sides of Victoria Harbor have highest residential attractiveness than other areas. Community planners and policy makers should consider residential attractiveness based on residents' demand in efforts to promote sustainable development. Residential attractiveness is the foundation of residential land use planning and policies. Planners in compact cities should adopt various planning strategies according to different residential attractiveness. Moreover, residential attractiveness is the benchmark of evaluating residents' satisfaction of new residential planning and policies.

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Early Prediction of the Winner in StarCraft Matches

Early Prediction of the Winner in StarCraft Matches

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9th International Joint Conference on Computational Intelligence, IJCCI 2017

作者： Alvarez-Caballero, Antonio Merelo, J.J. Sanchez, Pablo Garcıa Fernandez-Ares, A. Department of Computer Architecture and Computer Technology University of Granada Spain Department of Computer Science University of Cadiz Spain

ISBN: (纸本)9789897582745

A fast and precise prediction of the outcome of a game is essential for the design of bots that play the game;it can be used either offline as a fast way to design bot strategies or online for conserving resources and conceding defeat or speed up victory, as well as evaluating the consequences of actions. The objective of this paper is predicting the winner of a StarCraft match as soon as possible. This study is done with supervised learning, because a lot of suitable data is available. The main problem of this approach is the big amount of generated data, so it has to be selected and organised properly and be treated with proper tools. A set of six learning algorithms is used, from simpler ones to more complex algorithms. Spark and MLlib are used due to their capabilities to deal with big amounts of data. With the learned models, time of matches are restricted, trying to get a time bound for predicting results. With this approach we get that it is not necessary to play a whole match to predict its winner with high accuracy: with 10 minutes we can predict the outcome with 90% of accuracy. © 2017 by SCITEPRESS–Science and technology Publications, Lda. All rights reserved.

关键词： Forecasting

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