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IEEE International Conference on Agents (ICA)

作者： Tomohiro Nishida Takanori Ito Takayuki Ito Nagoya Institute of Technology Center for Collective Intelligence Nagoya Japan Department of Architecture and Design Nagoya Institute of Technology Nagoya Japan Department of Computer Science Nagoya Institute of Technology Nagoya Japan

We have developed the consensus building support system called COLLAGREE on the Web with facilitator support function. If discussions are conduct by free participation on the Web, celebrity may participate. Therefore, in this work, we conduct large scale social experiments using support systems where celebrities participate. The purpose of this work is to verify the effectiveness and problems of consensus building support system in discussion where celebrities participate. IN the large-scale social experiments, we clarified that new threads by celebrities' increases the number of reply and approval number by about 3 times compared to other participants. Also, we clarified that opinion by celebrities did not little affect voting results. Furthermore, we clarified that participants were not influenced by celebrity opinions, but were influenced by other participants.

关键词： Buildings Urban areas Convergence History Conferences Indium tin oxide Collective intelligence

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Developing Automated Bifurcation Angle Measurement Algorithm for Retinal Image Analysis

Developing Automated Bifurcation Angle Measurement Algorithm...

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2018 International Conference on Computational Approach in Smart Systems Design and Applications, ICASSDA 2018

作者： Kipli, Kuryati Hamid, Isredza Rahmi A. Kipli, Kumalasari Ismail, Nur Afifah Zamhari, Nurdiani Mat, Dayang Azra Awang Suhaili, Shamsiah Sapawi, Rohana Faculty of Engineering Universiti Malaysia Sarawak Kota Samarahan Sarawak Malaysia Department of Information Security Faculty of Computer Sciences Information Technology Universiti Tun Hussein Onn Malaysia Johor Malaysia Faculty of Architecture Planning and Surveying Universiti Teknologi MARA Sarawak Malaysia

ISBN: (纸本)9781538683699

Retina and its vascular network have unique branching characteristics morphology. The abnormalities in the vascular pattern of the retina, such as vessel shape, branching pattern, width, tortuosity, or the appearance of retinal itself, may be associated with the occurrence of retinopathy or cardiovascular diseases. This paper is focus on the development of an algorithm to measure bifurcation angle of the retinal for image analysis. From survey, there is still lack of automation for bifurcation angle measurement. Thus this initial work investigates and proposes the key steps for bifurcation measurement process. The key steps of the proposed method include segmentation of the region of interest (ROI), tracing the vessels that are needed for angle determination and lastly determine the bifurcation angle by using the dot product of the traced boundaries. The results are compared with the manual measurement of the bifurcation angle using quantitative and qualitative measurement. The experimental results show promising result of the proposed method in automating the measurement of bifurcation angle of retinal. Recommendation for room of improvement is also discussed in the paper. © 2018 IEEE.

关键词： Image analysis

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First measurement of the top quark pair production cross section in proton-proton collisions at s = 13.6 TeV

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Journal of High Energy Physics 2023年第8期2023卷 204页

作者： 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. Morton, A. Müller, D. Sahasransu, A.R. Tavernier, S. Van Doninck, W. Van Putte, S. Vannerom, D. Clerbaux, B. Dansana, S. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Makarenko, I. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. 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. David, P. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Lidrych, J. 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. Rodozov, 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. Milosevic, V. Monti, F. Sharma, R. Tao, J. Wang, J. Zhang, H. Zhao, J 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 first measurement of the top quark pair (tt¯) production cross section in proton-proton collisions at s = 13.6 TeV is presented. Data recorded with the CMS detector at the CERN LHC in Summer 2022, corresponding to an integrated luminosity of 1.21 fb⁻¹, are analyzed. Events are selected with one or two charged leptons (electrons or muons) and additional jets. A maximum likelihood fit is performed in event categories defined by the number and flavors of the leptons, the number of jets, and the number of jets identified as originating from b quarks. An inclusive tt¯ production cross section of 881 ± 23 (stat + syst) ± 20 (lumi) pb is measured, in agreement with the standard model prediction of 924₋₄₀⁺³² pb. © The Author(s) 2023.

关键词： Hadron-Hadron Scattering Top Physics

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Measurement of the cross section of top quark-antiquark pair production in association with a W boson in proton-proton collisions at s = 13 TeV

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Journal of High Energy Physics 2023年第7期2023卷 219页

作者： 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. Paulitsch, P. Pitters, F.M. Schieck, J. Schöfbeck, R. Schwarz, D. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Kello, T. Rejeb Sfar, H. Van Mechelen, P. Bols, E.S. D’Hondt, J. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Moortgat, S. Morton, A. Müller, D. Sahasransu, A.R. Tavernier, S. Van Doninck, W. Vannerom, D. Clerbaux, B. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Makarenko, I. Malara, A. Paredes, S. Pétré, L. Postiau, N. Starling, E. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. Dobur, D. Knolle, J. Lambrecht, L. Mestdach, G. Niedziela, M. Rendón, C. Roskas, C. Samalan, A. Skovpen, K. Tytgat, M. Van Den Bossche, N. Vermassen, B. Wezenbeek, L. Benecke, A. Bruno, G. Bury, F. Caputo, C. David, P. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Mondal, K. Prisciandaro, J. Taliercio, A. 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. Torres Da Silva De Araujo, F. Vilela Pereira, A. Bernardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. Gregores, E.M. Mercadante, P.G. Novaes, S.F. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Rodozov, M. Shopova, M. Sultanov, G. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Thakur, S. Cheng, T. Javaid, T. Mittal, M. Yuan, L. Ahmad, M. Bauer, G. Hu, Z. Lezki, S. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Kou, 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 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 University of Helsinki Helsinki Finland Helsinki Institut

The production of a top quark-antiquark pair in association with a W boson (tt¯W) is measured in proton-proton collisions at a center-of-mass energy of 13 TeV. The analyzed data was recorded by the CMS experiment at the CERN LHC and corresponds to an integrated luminosity of 138 fb⁻¹. Events with two or three leptons (electrons and muons) and additional jets are selected. In events with two leptons, a multiclass neural network is used to distinguish between the signal and background processes. Events with three leptons are categorized based on the number of jets and of jets originating from b quark hadronization, and the lepton charges. The inclusive tt¯W production cross section in the full phase space is measured to be 868 ± 40(stat) ± 51(syst) fb. The tt¯W⁺ and tt¯W⁻ cross sections are also measured as 553 ± 30(stat) ± 30(syst) and 343 ± 26(stat) ± 25(syst) fb, respectively, and the corresponding ratio of the two cross sections is found to be 1.61±0.15stat_−0.05^+0.07syst. The measured cross sections are larger than but consistent with the standard model predictions within two standard deviations, and represent the most precise measurement of these cross sections to date. © The Author(s) 2023.

关键词： Hadron-Hadron Scattering Top Physics

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Search for CP violation in t t ¯ H and tH production in multilepton channels in proton-proton collisions at √s = 13 TeV

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Journal of High Energy Physics 2023年第7期2023卷 92页

作者： 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. Paulitsch, P. Pitters, F.M. Schieck, J. Schöfbeck, R. Schwarz, D. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Kello, T. Rejeb Sfar, H. Van Mechelen, P. Bols, E.S. D’Hondt, J. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Moortgat, S. Morton, A. Müller, D. Sahasransu, A.R. Tavernier, S. Van Doninck, W. Vannerom, D. Clerbaux, B. De Lentdecker, G. Favart, L. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Makarenko, I. Malara, A. Paredes, S. Pétré, L. Postiau, N. Starling, E. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. Dobur, D. Knolle, J. Lambrecht, L. Mestdach, G. Niedziela, M. Rendón, C. Roskas, C. Samalan, A. Skovpen, K. Tytgat, M. Van Den Bossche, N. Vermassen, B. Wezenbeek, L. Benecke, A. Bruno, G. Bury, F. Caputo, C. David, P. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Mondal, K. Prisciandaro, J. Taliercio, A. 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. Torres Da Silva De Araujo, F. Vilela Pereira, A. Bernardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. Gregores, E.M. Mercadante, P.G. Novaes, S.F. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Rodozov, M. Shopova, M. Sultanov, G. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Cheng, T. Javaid, T. Mittal, M. Yuan, L. Ahmad, M. 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. Milose 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 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 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 University of Helsinki Helsinki Finland Helsinki Institute of Physics Helsinki Finland Lappeenranta-Lahti University of Technology Lappeen

The charge-parity (CP) structure of the Yukawa interaction between the Higgs (H) boson and the top quark is measured in a data sample enriched in the t t ¯ H and tH associated production, using 138 fb⁻¹ of data collected in proton-proton collisions at s = 13 TeV by the CMS experiment at the CERN LHC. The study targets events where the H boson decays via H → WW or H → ττ and the top quarks decay via t → Wb: the W bosons decay either leptonically or hadronically, and final states characterized by the presence of at least two leptons are studied. Machine learning techniques are applied to these final states to enhance the separation of CP -even from CP -odd scenarios. Two-dimensional confidence regions are set on κ _t and κ~ _t, which are respectively defined as the CP -even and CP -odd top-Higgs Yukawa coupling modifiers. No significant fractional CP -odd contributions, parameterized by the quantity | fCPHtt | are observed;the parameter is determined to be | fCPHtt | = 0.59 with an interval of (0.24, 0.81) at 68% confidence level. The results are combined with previous results covering the H → ZZ and H → γγ decay modes, yielding two- and one-dimensional confidence regions on κ _t and κ~ _t, while | fCPHtt | is determined to be | fCPHtt | = 0.28 with an interval of | fCPHtt | < 0.55 at 68% confidence level, in agreement with the standard model CP -even prediction of | fCPHtt | = 0. [Figure not available: see fulltext.]. © 2023, The Author(s).

关键词： CP Violation Hadron-Hadron Scattering Higgs Physics

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Measurements of inclusive and differential cross sections for the Higgs boson production and decay to four-leptons in proton-proton collisions at s = 13 TeV

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Journal of High Energy Physics 2023年第8期2023卷 40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. 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. 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, C. Zhang, H. Agapitos, A. Ba 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

Measurements of the inclusive and differential fiducial cross sections for the Higgs boson production in the H → ZZ → 4ℓ (ℓ = e, μ) decay channel are presented. The results are obtained from the analysis of proton-proton collision data recorded by the CMS experiment at the CERN LHC at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb⁻¹. The measured inclusive fiducial cross section is 2.73 ± 0.26 fb, in agreement with the standard model expectation of 2.86 ± 0.1 fb. Differential cross sections are measured as a function of several kinematic observables sensitive to the Higgs boson production and decay to four leptons. A set of double-differential measurements is also performed, yielding a comprehensive characterization of the four leptons final state. Constraints on the Higgs boson trilinear coupling and on the bottom and charm quark coupling modifiers are derived from its transverse momentum distribution. All results are consistent with theoretical predictions from the standard model. © The Author(s) 2023.

关键词： Hadron-Hadron Scattering Higgs Physics

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Multi-view multi-instance multi-label learning based on collaborative matrix factorization

arXiv

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arXiv 2019年

作者： Xing, Yuying Yu, Guoxian Domeniconi, Carlotta Wang, Jun Zhang, Zili Guo, Maozu College of Computer and Information Science Southwest University Chongqing China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan China Department of Computer Science George Mason University FairfaxVA United States School of Information Technology Deakin University GeelongVIC Australia School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China

Multi-view Multi-instance Multi-label Learning(M3L) deals with complex objects encompassing diverse instances, represented with different feature views, and annotated with multiple labels. Existing M3L solutions only partially explore the inter or intra relations between objects (or bags), instances, and labels, which can convey important contextual information for M3L. As such, they may have a compromised performance. In this paper, we propose a collaborative matrix factorization based solution called M3Lcmf. M3Lcmf first uses a heterogeneous network composed of nodes of bags, instances, and labels, to encode different types of relations via multiple relational data matrices. To preserve the intrinsic structure of the data matrices, M3Lcmf collaboratively factorizes them into low-rank matrices, explores the latent relationships between bags, instances, and labels, and selectively merges the data matrices. An aggregation scheme is further introduced to aggregate the instance-level labels into bag-level and to guide the factorization. An empirical study on benchmark datasets show that M3Lcmf outperforms other related competitive solutions both in the instance-level and bag-level prediction. Copyright © 2019, The Authors. All rights reserved.

关键词： Matrix factorization

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DLPlib： A Library for Deep Learning Processor

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Journal of computer Science & technology 2017年第2期32卷 286-296页

作者： Hui-Ying Lan Lin-Yang Wu Xiao Zhang Jin-Hua Tao Xun-Yu Chen Bing-Rui Wang Yu-Qing Wang Qi Guo Yun-Ji Chen State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Microprocessor Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Department of Computer Science University of Science and Technology of China Hefei 230026 China

Recently, deep learning processors have become one of the most promising solutions of accelerating deep learning algorithms. Currently, the only method of programming the deep learning processors is through writing assembly instructions by bare hands, which costs a lot of programming efforts and causes very low efficiency. One solution is to integrate the deep learning processors as a new back-end into one prevalent high-level deep learning framework （e.g., TPU （tensor processing unit） is integrated into Tensorflow directly）. However, this will obstruct other frameworks to profit from the programming interface, The alternative approach is to design a framework-independent low-level library for deep learning processors （e.g., the deep learning library for GPU, cuDNN）. In this fashion, the library could be conveniently invoked in high-level programming frameworks and provides more generality. In order to allow more deep learning frameworks to gain benefits from this environment, we envision it as a low-level library which could be easily embedded into current high-level frameworks and provide high performance. Three major issues of designing such a library are discussed. The first one is the design of data structures. Data structures should be as few as possible while being able to support all possible operations. This will allow us to optimize the data structures easier without compromising the generality. The second one is the selection of operations, which should provide a rather wide range of operations to support various types of networks with high efficiency. The third is the design of the API, which should provide a flexible and user-friendly programming model and should be easy to be embedded into existing deep learning frameworks. Considering all the above issues, we propose DLPIib, a tensor-filter based library designed specific for deep learning processors. It contains two major data structures, tensor and filter, and a set of operators including basic neur

关键词： deep learning processor API library DLPlib

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Landscape of big medical data: A pragmatic survey on prioritized tasks

arXiv

引用

arXiv 2019年

作者： Zhang, Zhifei Gao, Wanling Zhang, Fan Huang, Yunyou Dai, Shaopeng Fan, Fanda Zhan, Jianfeng Du, Mengjia Yin, Silin Xiong, Longxin Du, Juan Cheng, Yumei Zhou, Xiexuan Ren, Rui Wang, Lei Ye, Hainan Department of Physiology and Pathophysiology Capital Medical University State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Nanchang First Hospital Neonatal Center Beijing Children's Hospital Affiliated to Capital Medical University Beijing Obstetrics and Gynecology Hospital Affiliated to Capital Medical University Beijing Academy of Frontier Sciences and Technology

Big medical data poses great challenges to life scientists, clinicians, computer scientists, and engineers. In this paper, a group of life scientists, clinicians, computer scientists and engineers sit together to discuss several fundamental issues. First, what are the unique characteristics of big medical data different from those of the other domains? Second, what are the prioritized tasks in clinician research and practices utilizing big medical data? And do we have enough publicly available data sets for performing those tasks? Third, do the state-of-the-practice and state-of-the-art algorithms perform good jobs? Fourth, are there any benchmarks for measuring algorithms and systems for big medical data? Fifth, what are the performance gaps of state-of-the-practice and state-of-the-art systems handling big medical data currently or in future? Finally but not least, are we, life scientists, clinicians, computer scientists and engineers, ready for working together? We believe answering the above issues will help define and shape the landscape of big medical data. Copyright © 2019, The Authors. All rights reserved.

关键词： computer aided diagnosis

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Multidimensional fuzzy sets for texture modelling adapted to user profiles

Multidimensional fuzzy sets for texture modelling adapted to...

引用

2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017

作者： Martínez-Jiménez, Pedro Manuel Chamorro-Martínez, Jesús Soto-Hidalgo, José Manuel Rodríguez-Pérez, Javier Department of Computer Science and Artificial Intelligence University of Granada Spain Department of Computer Architecture Electronics and Electronic Technology University of Cordoba Spain

ISBN: (纸本)9781509060344

The analysis of the perceptual properties of texture plays a fundamental role in tasks where some interaction with subjects is needed. In order to face the imprecision related to these properties, several fuzzy approaches can be found in the literature, but they do not properly take into account the subjectivity of users. In this paper, a generic technique is proposed in order to adapt any multidimensional fuzzy set to the different perceptions of texture properties that a particular user can have. This way, we combine the improvement in the texture characterization given by the use of several computational measures as reference set with the adaptation to the subjectivity of the human perception. In the proposed adaptation method, the membership functions are automatically transformed on the basic of the information given by the user. © 2017 IEEE.

关键词： Fuzzy sets

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