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Incorporating biological inspired optimization into modeling of district heating networks

Energy Education Science and technology Part A: Energy Science and Research 2014年第2期32卷 1347-1354页

作者： Shang, Leiming Zhao, Xiaomin Qu, Hongchun Huaibei Normal University School of Computer Science and Technology Huaibei Anhui China China University of Mining and Technology School of Resource and Earth Science XuzhouJiangsu China Huaibei Normal University School of Physics and Electronic Information Huaibei Anhui China Chongqing University of Posts and Telecommunications Key laboratory of industrial IoT and networked control of the Ministry of Education Division of theoretical research for complex systems Chongqing China

In this paper, we proposed a biologically inspired model to solve the optimization problem of building district heating networks. The optimization strategy of the model was inspired from physiological observations of the food foraging procedure of the true slime mold Physarum polycephalum (plasmodium) which was found and proved to be able to find optimal path in complex networks such as mazes and road maps. We developed a simulation model to mimic the food foraging procedure of the plasmodium to help to generate heating distribution networks. Simulation results were compared to a well-tuned ant colony algorithm and a genetic algorithm which were used to build the same heating network. The results indicated that although there was not large-scale efficiency savings had been made, the biologically inspired simulation model is capable of finding optimal heating distribution network which is of equal or better optimality than the compared ant colony algorithm and genetic algorithm and, to achieve network robustness, stability and reliability. © Sila Science.

关键词： Complex networks

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Study of the material of the ATLAS inner detector for Run 2 of the LHC

arXiv

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arXiv 2017年

作者： Aaboud, M. Aad, G. Abbott, B. Abdallah, J. Abdinov, O. Abeloos, B. Abidi, S.H. AbouZeid, O.S. Abraham, N.L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B.S. Adachi, S. Adamczyk, L. Adelman, J. Adersberger, M. Adye, T. Affolder, A.A. Agatonovic-Jovin, T. Agheorghiesei, C. Aguilar-Saavedra, J.A. Ahlen, S.P. Ahmadov, F. Aielli, G. Akatsuka, S. Akerstedt, H. Åkesson, T.P.A. Akilli, E. Akimov, A.V. Alberghi, G.L. Albert, J. Albicocco, P. Alconada Verzini, M.J. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S.P. Allbrooke, B.M.M. Allen, B.W. Allport, P.P. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A.A. Alstaty, M. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M.G. Amadio, B.T. Amelung, C. Amidei, D. Amor Dos Santos, S.P. Amorim, A. Amoroso, S. Amundsen, G. Anastopoulos, C. Ancu, L.S. Andari, N. Andeen, T. Anders, C.F. Anders, J.K. Anderson, K.J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Angerami, A. Anisenkov, A.V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Antrim, D.J. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J.P. Araujo Ferraz, V. Arce, A.T.H. Ardell, R.E. Arduh, F.A. Arguin, J.-F. Argyropoulos, S. Arik, M. Armbruster, A.J. Armitage, L.J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N.B. Augsten, K. Avolio, G. Axen, B. Ayoub, M.K. Azuelos, G. Baas, A.E. Baca, M.J. Bachacou, H. Bachas, K. Backes, M. Backhaus, M. Bagnaia, P. Bahrasemani, H. Baines, J.T. Bajic, M. Baker, O.K. Baldin, E.M. Balek, P. Balli, F. Balunas, W.K. Banas, E. Banerjee, Sw. Bannoura, A.A.E. Barak, L. Barberio, E.L. Barbero, M. Barillari, T. Barisits, M.-S. Barkeloo, J.T. Barklow, T. Barlow, N. Barnes, S.L. Barnett, B.M. Barnett, R.M. Barnovska-Blenessy, Z. Baroncelli, A. Barone, G. Barr, A.J. Department of Physics University of Adelaide Adelaide Australia Physics Department SUNY Albany AlbanyNY United States Department of Physics University of Alberta EdmontonAB Canada Department of Physics Ankara University Ankara Turkey LAPP CNRS/IN2P3 Université Savoie Mont Blanc Annecy-le-Vieux France High Energy Physics Division Argonne National Laboratory ArgonneIL United States Department of Physics University of Arizona TucsonAZ United States Department of Physics University of Texas at Arlington ArlingtonTX United States Physics Department National and Kapodistrian University of Athens Athens Greece Physics Department National Technical University of Athens Zografou Greece Department of Physics The University of Texas at Austin AustinTX United States Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Barcelona Institute of Science and Technology Barcelona Spain Institute of Physics University of Belgrade Belgrade Serbia Department for Physics and Technology University of Bergen Bergen Norway Physics Division Lawrence Berkeley National Laboratory University of California BerkeleyCA United States Department of Physics Humboldt University Berlin Germany Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern Bern Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom Department of Physics Bogazici University Istanbul Turkey Centro de Investigaciones Universidad Antonio Narino Bogota Colombia INFN Sezione di Bologna Dipartimento di Fisica e Astronomia Università di Bologna Bologna Italy Physikalisches Institut University of Bonn Bonn Germany Department of Physics Boston University BostonMA United States Department of Physics Brandeis University WalthamMA United States Juiz de Fora Physics Department Brookhaven National Laboratory UptonNY United States Transilvania University of Brasov BrasovHoria Hulubei National I

The ATLAS inner detector comprises three different sub-detectors: the pixel detector, the silicon strip tracker, and the transition-radiation drift-tube tracker. The Insertable B-Layer, a new innermost pixel layer, was installed during the shutdown period in 2014, together with modifications to the layout of the cables and support structures of the existing pixel detector. The material in the inner detector is studied with several methods, using a low-luminosity √s = 13 TeV pp collision sample corresponding to around 2.0 nb−1 collected in 2015 with the ATLAS experiment at the LHC. In this paper, the material within the innermost barrel region is studied using reconstructed hadronic interaction and photon conversion vertices. For the forward rapidity region, the material is probed by a measurement of the efficiency with which single tracks reconstructed from pixel detector hits alone can be extended with hits on the track in the strip layers. The results of these studies have been taken into account in an improved description of the material in the ATLAS inner detector simulation, resulting in a reduction in the uncertainties associated with the charged-particle reconstruction efficiency determined from simulation. Copyright © 2017, The Authors. All rights reserved.

关键词： Readout systems

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Application and Study on Sentiment-oriented Analysis on Social Semantic Network

Application and Study on Sentiment-oriented Analysis on Soci...

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2013 International Conference on Advanced computer Science and Electronics information(ICACSEI 2013)

作者： Dan Zhang Dongsheng Wang Haiping Huang College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications Department of Computer and Information Science Korea University Seoul College of Computer & Information Science Nanjing University of Posts and Telecommunications Jiangsu Computer Information Processing Technology Key Laboratory Suzhou University

With the increasing growth of users and exponential propagation of messages, Social Network Services such as Twitter, Facebook can be used to analyze social trend, people's interests and personal-favor. Recently, the Social Network Analysis based on Semantic Web technology tends to be a hot study. In this paper, we propose a sentiment-oriented method that takes advantage of emotion ontology to reason out Twitter users' basic emotions and retrieve YAGO ontology to explain associative topics. We implement a prototype system that visualizes the analysis result, which is human- readable as well as machine-understandable.

关键词： Semantic Web technology, Twitter Mining, Social Network Analysis, emotion analysis, Social Semantic Network

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Weld seam detection and feature extraction based on laser vision

Weld seam detection and feature extraction based on laser vi...

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Chinese Control Conference (CCC)

作者： Xiuping Wang Ruilin Bai Ziteng Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Information and Control Experiment Teaching Center Jiangnan University Wuxi Jiangsu CN Wuxi Professional College of Science and Technology Wuxi China

This paper presents an algorithm for real time weld seam detection and feature extraction of butt weld, which is based on laser vision sensor installed on the end hand of welding robot. The algorithm preprocesses the weld seam images captured by laser vision sensor as first step and then detects laser stripe edges thus obtains the center of laser stripe. Then a two-step method is used to extract the initial value of center point of weld seam. Finally the weld region is separated from the laser stripe center line using iterative search method, then two edge points and accurate center point of weld region together with the width of weld seam can be calculated. Experiments have shown that the algorithm proposed in this paper has good stability and accuracy, and it can meet the real-time requirements.

关键词： Welding Feature extraction Robot sensing systems Surface emitting lasers Image edge detection

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Detecting genuine communities from large-scale social networks: A pattern-based method

Detecting genuine communities from large-scale social networ...

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作者： Wu, Zhiang Cao, Jie Wu, Junjie Wang, Youquan Liu, Chunyang Jiangsu Provincial Key Laboratory of E-Business Nanjing University of Finance and Economics Nanjing210003 China College of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Department of Information Systems School of Economics and Management Beihang 100191 China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing China

Community detection is a long-standing yet very difficult task in social network analysis. It becomes more challenging as many online social networking sites are evolving into super-large scales. Numerous methods have been proposed for community detection from massive networks, but how to reconcile the partitioning efficiency and the community quality remains an open problem. In this paper, we attempt to address this challenge by introducing a COSine-pattern-based COMmunity extraction framework: COSCOM. The COSCOM adopts an extracting view of community detection. It first extracts the so-called asymptotically equivalent structures (AESs) from networks, from which the nodes are further partitioned into crisp communities using any of the existing methods. Specifically, we prove that an AES is a very tight group of nodes, and is actually a cosine pattern defined by the extended cosine similarity. A novel cosine-pattern mining algorithm based on the ordered anti-monotone of cosine similarity is thus proposed for the efficient extraction of AESs. Experiments on various real-world social networks demonstrate the advantage of the extracting view of community detection. In particular, COSCOM shows merits in detecting genuine communities by either internal or external validity. © The British computer Society 2013. All rights reserved.

关键词： Extraction

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Search for heavy resonances decaying to a Z boson and a photon in pp collisions at s=13 TeV with the ATLAS detector

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2017年 764卷 11-30页

作者： Aaboud, M. Aad, G. Abbott, B. Abdallah, J. Abdinov, O. Abeloos, B. Aben, R. AbouZeid, O.S. Abraham, N.L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B.S. Adachi, S. Adamczyk, L. Adams, D.L. Adelman, J. Adomeit, S. Adye, T. Affolder, A.A. Agatonovic-Jovin, T. Agricola, J. Aguilar-Saavedra, J.A. Ahlen, S.P. Ahmadov, F. Aielli, G. Akerstedt, H. Åkesson, T.P.A. Akimov, A.V. Alberghi, G.L. Albert, J. Albrand, S. Alconada Verzini, M.J. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S.P. Allbrooke, B.M.M. Allen, B.W. Allport, P.P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A.A. Alstaty, M. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M.G. Amadio, B.T. Amako, K. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S.P. Amorim, A. Amoroso, S. Amundsen, G. Anastopoulos, C. Ancu, L.S. Andari, N. Andeen, T. Anders, C.F. Anders, G. Anders, J.K. Anderson, K.J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Anger, P. Angerami, A. Anghinolfi, F. Anisenkov, A.V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J.P. Arce, A.T.H. Arduh, F.A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A.J. Armitage, L.J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Åsman, B. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N.B. Augsten, K. Avolio, G. Axen, B. Ayoub, M.K. Azuelos, G. Baak, M.A. Baas, A.E. Baca, M.J. Bachacou, H. Bachas, K. Backes, M. Backhaus, M. Bagiacchi, P. Bagnaia, P. Bai, Y. Baines, J.T. Baker, O.K. Baldin, E.M. Balek, P. Balestri, T. Balli, F. Balunas, W.K. Banas, E. Banerjee, Sw. Bannoura, A.A.E. Barak, L. Barberio, E.L. Barberis, D. Barbero, M. Barillari, T. Barisits, M-S Barklow, T. Barlow, N. Barnes, S.L. Barnett, B.M. Barnett, R.M. Barnovska-Blenessy, Z. Baroncelli, A. Barone, G. Barr, A.J. Barranco Navarro, L. Barreiro, F. Barreiro Gui Department of Physics University of Adelaide Adelaide Australia Physics Department SUNY Albany Albany NY United States Department of Physics University of Alberta Edmonton AB Canada Department of Physics Ankara University Ankara Turkey Istanbul Aydin University Istanbul Turkey Division of Physics TOBB University of Economics and Technology Ankara Turkey LAPP CNRS/IN2P3 Université Savoie Mont Blanc Annecy-le-Vieux France High Energy Physics Division Argonne National Laboratory Argonne IL United States Department of Physics University of Arizona Tucson AZ United States Department of Physics The University of Texas at Arlington Arlington TX United States Physics Department University of Athens Athens Greece Physics Department National Technical University of Athens Zografou Greece Department of Physics The University of Texas at Austin Austin TX United States Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Institut de Física d'Altes Energies (IFAE) The Barcelona Institute of Science and Technology Barcelona Spain Institute of Physics University of Belgrade Belgrade Serbia Department for Physics and Technology University of Bergen Bergen Norway Physics Division Lawrence Berkeley National Laboratory University of California Berkeley CA United States Department of Physics Humboldt University Berlin Germany Albert Einstein Center for Fundamental Physics Laboratory for High Energy Physics University of Bern Bern Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom Department of Physics Bogazici University Istanbul Turkey Department of Physics Engineering Gaziantep University Gaziantep Turkey Istanbul Bilgi University Faculty of Engineering and Natural Sciences Istanbul Turkey Bahcesehir University Faculty of Engineering and Natural Sciences Istanbul Turkey Centro de Investigaciones Universidad Antonio Narino Bogota Colombia INFN Sezione di Bologna Italy Dipartimento di Fis

This Letter presents a search for new resonances with mass larger than 250 GeV, decaying to a Z boson and a photon. The dataset consists of an integrated luminosity of 3.2 fb−1 of pp collisions collected at s=13 TeV w... 详细信息

This Letter presents a search for new resonances with mass larger than 250 GeV, decaying to a Z boson and a photon. The dataset consists of an integrated luminosity of 3.2 fb⁻¹ of pp collisions collected at s=13 TeV with the ATLAS detector at the Large Hadron Collider. The Z bosons are identified through their decays either to charged, light, lepton pairs (e⁺e⁻, μ⁺μ⁻) or to hadrons. The data are found to be consistent with the expected background in the whole mass range investigated and upper limits are set on the production cross section times decay branching ratio to Zγ of a narrow scalar boson with mass between 250 GeV and 2.75 TeV. © 2016 The Author(s)

关键词： Z bosons CROSS sections (Nuclear physics) PHOTON-photon interactions LARGE Hadron Collider (France & Switzerland) DILEPTON production NUCLEAR counters

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Efficient Auction Mechanism with Group Price for Resource Allocation in Clouds

Efficient Auction Mechanism with Group Price for Resource Al...

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International Conference on Advanced Cloud and Big Data (CBD)

作者： Yiyi Ma Bin Li Yonglong Zhang Junwu Zhu Yangzhou University Yangzhou Jiangsu CN State Key Laboratory for Novel Software Technology Nanjing University Nanjing China School of Information Engineering Yangzhou University Yangzhou China School of computer science and technology Nanjing University of Aeronautics and Astronautics Nanjing China

With the rapid grows of cloud-based internet application, a need for efficient resource allocation, load balance and cost management increases. In this paper, we propose a group-auction based mechanism for the cloud instance market to efficiently allocate resources. In the market system, resource providers offer resources in the form of virtual machine. Users submit their bids. The proposed system assists to decide how providers allocate their resources to users efficiently. Group auction is also used to reduce cost and improve sales volume for the participants. To find how to allocate resources, the utility optimization problem is formulated as a Distributed Constraint Optimization Problem (DCOP), and we apply a distributed message passing algorithm, max-sum algorithm using the group auction formation game to find the nearly optimal solution with quadratic time complexity. In comparison study, we deploy the system on two scenarios. In terms of resource efficiency and acceptance rate, we compare our algorithm with greedy algorithm and random algorithm. Experiment results show that our system performs very well in probable setting.

关键词： Resource management Algorithm design and analysis Cost accounting Optimization Cloud computing Virtual machining Message passing

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Coverage Enhancement Strategy Based on Novel Perception and Co-evolution for Multimedia Sensor Networks

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电子学报(英文版) 2013年第1期22卷 135-140页

作者： XIAO Fu WANG Jing SUN Lijuan WANG Ruchuan GUO Jian College of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing 210003 China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing 210003 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou 215006 China

Coverage enhancement is one of the hot research topics in wireless multimedia sensor net- works. A novel Coverage-enhancing algorithm based on three-dimensional Directional perception and co-evolution (DPCCA) is proposed in multimedia sensor networks on the basis of the model whose pitch angle and deviation angle can be adjusted. Based on the proposed elliptical cone sensing model, we can derive the coverage area of the node and calculate the optimal pitch angle according the information of monitoring area and the nodes, and then the deviation angle is optimized based on co-evolution al- gorithm, which eliminate the overlapped and blind sensing area effectively. A set of simulations demonstrate the ef- fectiveness of our algorithm in coverage ratio.

关键词：无线多媒体传感器网络网络覆盖协同进化感知增强算法网络工程测量模型

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A fuzzy grey cognitive maps-based decision support system for maintaining water quality

A fuzzy grey cognitive maps-based decision support system fo...

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第25届中国控制与决策会议

作者： Bingyi Kang Yong Deng Jiangsu Key Laboratory of Resources and Environmental Information Engineering China University of Mining and Technology School of Computer and Information Science Southwest University

ISBN: (纸本)9781467355339

Maintaining water quality is of great importance for consumer's health. How to evaluate and predict the aging water quality is an open issue. In this paper, a framework based on fuzzy grey cognitive maps (FGCMs) is proposed to quantify overall potential for water quality failures. A new method of aggregating different experts based on interval number is presented in the process of constructing FGCM. At last, a case study is utilized to illustrate the efficiency of the proposed method.

关键词： Water Quality Management, Fuzzy Grey Cognitive Maps, Interval number

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Search for Dark Matter Produced in Association with a Higgs Boson Decaying to bb¯ Using 36 fb−1 of pp Collisions at s=13 TeV with the ATLAS Detector

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Physical Review Letters 2017年第18期119卷 181804-181804页

作者： M. Aaboud G. Aad B. Abbott O. Abdinov B. Abeloos S. H. Abidi O. S. AbouZeid N. L. Abraham H. Abramowicz H. Abreu R. Abreu Y. Abulaiti B. S. Acharya S. Adachi L. Adamczyk J. Adelman M. Adersberger T. Adye A. A. Affolder T. Agatonovic-Jovin C. Agheorghiesei J. A. Aguilar-Saavedra S. P. Ahlen F. Ahmadov G. Aielli S. Akatsuka H. Akerstedt T. P. A. Åkesson E. Akilli A. V. Akimov G. L. Alberghi J. Albert P. Albicocco M. J. Alconada Verzini S. C. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa G. Alexander T. Alexopoulos M. Alhroob B. Ali M. Aliev G. Alimonti J. Alison S. P. Alkire B. M. M. Allbrooke B. W. Allen P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. A. Alshehri M. I. Alstaty B. Alvarez Gonzalez D. Álvarez Piqueras M. G. Alviggi B. T. Amadio Y. Amaral Coutinho C. Amelung D. Amidei S. P. Amor Dos Santos A. Amorim S. Amoroso G. Amundsen C. Anastopoulos L. S. Ancu N. Andari T. Andeen C. F. Anders J. K. Anders K. J. Anderson A. Andreazza V. Andrei S. Angelidakis I. Angelozzi A. Angerami A. V. Anisenkov N. Anjos A. Annovi C. Antel M. Antonelli A. Antonov D. J. Antrim F. Anulli M. Aoki L. Aperio Bella G. Arabidze Y. Arai J. P. Araque V. Araujo Ferraz A. T. H. Arce R. E. Ardell F. A. Arduh J-F. Arguin S. Argyropoulos M. Arik A. J. Armbruster L. J. Armitage O. Arnaez H. Arnold M. Arratia O. Arslan A. Artamonov G. Artoni S. Artz S. Asai N. Asbah A. Ashkenazi L. Asquith K. Assamagan R. Astalos M. Atkinson N. B. Atlay K. Augsten G. Avolio B. Axen M. K. Ayoub G. Azuelos A. E. Baas M. J. Baca H. Bachacou K. Bachas M. Backes M. Backhaus P. Bagnaia M. Bahmani H. Bahrasemani J. T. Baines M. Bajic O. K. Baker E. M. Baldin P. Balek F. Balli W. K. Balunas E. Banas A. Bandyopadhyay Sw. Banerjee A. A. E. Bannoura L. Barak E. L. Barberio D. Barberis M. Barbero T. Barillari M-S Barisits J. T. Barkeloo T. Barklow N. Barlow S. L. Barnes B. M. Barnett R. M. Barnett Z. Barnovska-Blenessy A. Baroncelli G. Barone A. J. Barr L. Barranco Navarro F. Barreiro J. Barreiro Guimarães da Costa R. Bartoldus A. E. Barton P. Bartos A. Faculté des Sciences Université Mohamed Premier and LPTPM Oujda Morocco CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Department of Physics University of Toronto Toronto Ontario Canada Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene Oregon USA Department of Physics Stockholm University Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy International Center for Elementary Particle Physics and Department of Physics The University of Tokyo Tokyo Japan AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb Illinois USA Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Laboratório de Instrumentação e Física Experimental de Partículas - LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Portugal Department of Physics Boston University Boston Massachusetts USA Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Italy Dipartimen

Several extensions of the standard model predict associated production of dark-matter particles with a Higgs boson. Such processes are searched for in final states with missing transverse momentum and a Higgs boson decaying to a bb¯ pair with the ATLAS detector using 36.1 fb−1 of pp collisions at a center-of-mass energy of 13 TeV at the LHC. The observed data are in agreement with the standard model predictions and limits are placed on the associated production of dark-matter particles and a Higgs boson.

关键词： Extensions of Higgs sector Particle dark matter Weakly interacting massive particles

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