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Comments on recent proposed Cui Et Al.’s KASE and Lu Et Al.’s dIBEKS schemes

Journal of Information Hiding and Multimedia Signal Processing 2018年第1期9卷 162-169页

作者： Wu, Tsu-Yang Meng, Chao Wang, King-Hang Chen, Chien-Ming Pan, Jeng-Shyang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No3 Xueyuan Road University Town Fuzhou350118 China National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology No3 Xueyuan Road University Town Fuzhou350118 China School of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School HIT Campus of University Town of Shenzhen Shenzhen518055 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

Searchable encryption is a cryptographic primitive used to search an encrypted data in cloud storage. Recently, Cui et al. and Lu et al. proposed two variants of secure searchable encryption schemes, respectively. However, based on our best knowledge we demonstrate that the both schemes are insecure against different types of off-line keyword guessing attacks in this paper. Finally, we make discussions about searchable encryption schemes whether resisting off-line keyword guessing attacks. © 2018, Ubiquitous International. All rights reserved.

关键词： Cloud storage

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Research on energy recycle percentage of servo motor 2

Research on energy recycle percentage of servo motor

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2nd International Conference on Precision Machinery and Manufacturing technology, ICPMMT 2017

作者： Tseng, Yen-Ming Chen, Li-Shan Pan, Jeng-Shyang Huang, Jing Key Laboratory of Big Data Mining and Application School of Information Science and Engineering Fujian University of Technology Fuzhou City Fujian350118 China School of Management Fujian University of Technology Minhou Fuzhou City Fujian350118 China School of Information Science and Engineering Fujian University of Technology Fuzhou City Fujian350118 China

The energy recycle circuit fed back the energy to batteries is one of the important means to extend the travel distance of action vehicle for an electric vehicle or hybrid vehicle by driven batteries. In order to achieve energy recycle must be use, such as the motor characteristics, the principle of motor controller and design of circuit to reach the energy recycle of motor in action vehicles. Focus on the 24 V 8A 150W servo motor and its shaft coupling with a condition by magnetic brake to simulate as the analog load and adjust the brake to 0.2 Newton-meter. According to the characteristics of the motor, the principle of the motor controller and the design and energy recovery of the circuit system for discussion, that include drive control circuit of motor and based on the former to design the circuit of energy recycle circuit of motor and to feed back the energy to the driving batteries. According to the characteristics of the motor, the principle of the motor controller and the design and energy recovery of the circuit system for discussion, that include drive control circuit of motor and based on the former to design the circuit of energy recycle circuit of motor and to feed back the energy to the driving batteries. By mean of the architecture of energy recycle circuit to test the power recovery which divide into without load and without energy collector, without load and with energy collector, with load and without energy collector and with load and energy collector four cases under these conditions to investigate the power recovery analysis. For the statistics of energy, the average energy recovery power percentage by without load and without energy collector is 9.7%, the average energy recovery power percentage by without load and with energy collector is 20.5%, the average energy recovery power percentage by with load and without energy collector is 1.82%, and the average energy recovery power percentage by with load and with energy collector is 3.1%. © 2017

关键词： Electric network analysis

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Inland port location planning based on user equilibrium 17

Inland port location planning based on user equilibrium

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17th COTA International Conference of Transportation Professionals: Transportation Reform and Change - Equity, Inclusiveness, Sharing, and Innovation, CICTP 2017

作者： Wei, Jingyi Tian, Daxin Rong, Hui Guo, Peng Wang, Wenyang Gong, Jinfeng Wang, Yunpeng Liu, He Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang Univ. Beijing100191 China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang Univ. Beijing100191 China Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies Nanjing210096 China Automotive Engineering Research Institute China Automotive Technology and Research Center Tianjin300300 China Quartermaster Equipment Institute of the General Logistics Dept. Of CPLA Beijing100010 China

ISBN: (数字)9780784480915

ISBN: (纸本)9780784480915

With stable development of container transportation in shipping industry, the transit shipment from road to railway of inland ports plays a significant role in multimodal transport. This paper presents the method of inland port location planning based on user equilibrium. In the study, the virtual connection simulating the process of transfer in inland ports is conducted to measure the fitness of inland port location through the cargo volume on virtual connection. At last, the methodology was applied into practical experiment with the results showing that the method can locate the suit inland port location. © ASCE.

关键词： Location

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Accurate spectral super-resolution from single RGB image using multi-scale CNN

arXiv

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arXiv 2018年

作者： Yan, Yiqi Zhang, Lei Li, Jun Zhang, Yanning Wei, Wei School of Electronics and Information Northwestern Polytechnical University Xi'an China School of Computer Science Northwestern Polytechnical University Xi'an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology China Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation School of Geography and Planning Sun Yat-Sen University Guangzhou China

Different from traditional hyperspectral super-resolution ap-proaches that focus on improving the spatial resolution, spectral super-resolution aims at producing a high-resolution hyperspectral image from the RGB observation with super-resolution in spectral domain. However, it is challenging to accurately reconstruct a high-dimensional continuous spectrum from three discrete intensity values at each pixel, since too much information is lost during the procedure where the latent hyper-spectral image is downsampled (e.g., with ×10 scaling factor) in spectral domain to produce an RGB observation. To address this problem, we present a multi-scale deep convolutional neural network (CNN) to ex-plicitly map the input RGB image into a hyperspectral image. Through symmetrically downsampling and upsampling the intermediate feature maps in a cascading paradigm, the local and non-local image informa-tion can be jointly encoded for spectral representation, ultimately im-proving the spectral reconstruction accuracy. Extensive experiments on a large hyperspectral dataset demonstrate the effectiveness of the pro-posed method. Copyright © 2018, The Authors. All rights reserved.

关键词： Optical resolving power

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2021 Chinese consensus on the diagnosis and management of primary immune thrombocytopenia in pregnancy

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Chinese Medical Journal 2022年第8期135卷 887-889页

作者： Zhang Xiaohui Chen Fangping Chen Xiequn Cheng Yunfeng Fang Meiyun Feng Jianming Fu Haixia Gao Hong Han Yue He Aili Hou Ming Hu Yu Huang Ruibin Huang Wenrong Jing Zhicheng Kong Peiyan Liang Aibin Liang Meiying Liu Daihong Liu Junling Liu Lin Liu Xiaowei Ma Liangming Mei Heng Ni Heyu Niu Ting Peng Jun Qiao Jianlin Ren Jinhai Song Yongping Tang Liang V Tong Tong Wang Shaoyuan Wang Xin Wang Zhao Wei Hui Wu Depei Wu Guangsheng Xu Caigang Xu Xue Xu Yajing Yang Linhua Yang Renchi Yang Tonghua Yin Chenghong Yu Li Zhang Guangsen Zhang Lei Zhang Liansheng Zhang Xi Zhao Weili Zhao Yongqiang Zhou Daobin Zhou Hu Zhou Zeping Zhu Tienan Wang Jianliu Huang Xiaojun Department of Hematology Peking University People’s HospitalPeking University Institute of HematologyBeijing 100044China Department of Hematology Xiangya Third HospitalCentral South UniversityChangshaHunan 410013China Department of Hematology Xi Jing Hospital Affiliated to the Fourth Military Medical UniversityXi’anShaanxi 710032China Department of Hematology Qingpu Branch of Zhongshan HospitalFudan UniversityShanghai 528404China Department of Hematology Affiliated Zhongshan Hospital of Dalian UniversityDalianLiaoning 116001China Department of Hematology and Rheumatology Qinghai Provincial People’s HospitalXiningQinghai 810007China Department of Internal Medicine Beijing Obstetrics and Gynecology HospitalCapital Medical UniversityBeijing Maternal and Child Health Care HospitalBeijing 100026China Department of Hematology Jiangsu Institute of HematologyNational Clinical Research Center for Hematologic DiseasesThe First Affiliated Hospital of Soochow UniversitySuzhouJiangsu 215006China Department of Hematology The Second Affiliated HospitalMedical School of Xi’an Jiaotong UniversityXi’anShaanxi 710004China Department of Hematology Qilu HospitalCheeloo College of MedicineShandong UniversityJinanShandong 250063China Department of Hematology Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei 430022China Department of Hematology The First Affiliated Hospital of Nanchang UniversityNanchangJiangxi 330006China Department of Hematology Chinese PLA General HospitalMedical School of Chinese PLABeijing 100039China Department of Cardiology Peking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100005China Department of Hematology Medical Center of HematologyXinqiao HospitalThe Third Military Medical UniversityChongqing 400037China Department of Hematology Tongji Hospital of Tongji UniversityShanghai 200092China Department of Obstetrics and Gynecology Peking University People

Immune thrombocytopenia(ITP)is an acquired disease characterized by isolated thrombocytopenia,which is one of the most common causes of thrombocytopenia during *** with ITP who have severe thrombocytopenia are at an increased risk for life-threatening obstetric ***,we established this consensus statement on the diagnosis and management of ITP during pregnancy(detailed information is available in the Supplementary File,http://***7CM9/A978).

关键词： diagnosis pregnancy ITP

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Robust frequent directions with application in online learning

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The Journal of Machine Learning Research 2019年第1期20卷

作者： Luo Luo Cheng Chen Zhihua Zhang Wu-Jun Li Tong Zhang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China National Engineering Lab for Big Data Analysis and Applications School of Mathematical Sciences Peking University Beijing China National Key Laboratory for Novel Software Technology Collaborative Innovation Center of Novel Software Technology and Industrialization Department of Computer Science and Technology Nanjing University Nanjing China Computer Science & Mathematics Hong Kong University of Science and Technology Hong Kong

The frequent directions (FD) technique is a deterministic approach for online sketching that has many applications in machine learning. The conventional FD is a heuristic procedure that often outputs rank deficient matrices. To overcome the rank deficiency problem, we propose a new sketching strategy called robust frequent directions (RFD) by introducing a regularization term. RFD can be derived from an optimization problem. It updates the sketch matrix and the regularization term adaptively and jointly. RFD reduces the approximation error of FD without increasing the computational cost. We also apply RFD to online learning and propose an effective hyperparameter-free online Newton algorithm. We derive a regret bound for our online Newton algorithm based on RFD, which guarantees the robustness of the algorithm. The experimental studies demonstrate that the proposed method outperforms state-of-the-art second order online learning algorithms.

关键词： frequent directions matrix approximation online Newton algorithm online convex optimization sketching

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Observation of the B0→D¯*0K+π− and Bs0→D¯*0K−π+ decays

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Physical Review D 2022年第7期105卷 072005-072005页

作者： R. Aaij A. S. W. Abdelmotteleb C. Abellán Beteta F. Abudinén T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. Agapopoulou C. A. Aidala S. Aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato J. L. Amey Y. Amhis L. An L. Anderlini M. Andersson A. Andreianov M. Andreotti F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista de Souza Leite M. Barbetti R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay A. Beck M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella A. Bertolin C. Betancourt F. Betti Ia. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker N. V. Biesuz S. Bifani P. Billoir A. Biolchini M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura L. Buonincontri A. T. Burke C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes P. Campana A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti L. Carus K. Carvalho Akiba A. Casais Vidal R. Caspary G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli D. Cervenkov A. J. Chadwick M. G. Chapman M. Charles Ph. Charpentier C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Cid V Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Department of Physics University of Warwick Coventry United Kingdom Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France University of Michigan Ann Arbor USA (associated with Syracuse University Syracuse New York USA) INFN Sezione di Milano Milano Italy University of Cincinnati Cincinnati Ohio USA Fakultät Physik Technische Universität Dortmund Dortmund Germany European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom ICCUB Universitat de Barcelona Barcelona Spain Department of Physics and Astronomy University of Manchester Manchester United Kingdom Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Cavendish Laboratory University of Cambridge Cambridge United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France INFN Sezione di Firenze Firenze Italy INFN Sezione di Ferrara Ferrara Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France Institute of Physics Ecole Polyt

The first observations of B0→D¯*(2007)0K+π− and Bs0→D¯*(2007)0K−π+ decays are presented, and their branching fractions relative to that of the B0→D¯*(2007)0π+π− decay are reported. These modes can potentially be used to investigate the spectroscopy of charm and charm-strange resonances and to determine the angle γ of the Cabibbo-Kobayashi-Maskawa unitarity triangle. It is also important to understand them as a source of potential background in determinations of γ from B+→DK+ and B0→DK+π− decays. The analysis is based on a sample corresponding to an integrated luminosity of 5.4 fb−1 of proton-proton collision data at 13 TeV center-of-mass energy recorded with the LHCb detector. The D¯*(2007)0 mesons are fully reconstructed in the D¯0π0 and D¯0γ channels with the D¯0→K+π− decay. A novel weighting method is used to subtract background while simultaneously applying an event-by-event efficiency correction to account for resonant structures in the decays.

关键词： Branching fraction Hadronic decays CP violation

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Measurement of the charm mixing parameter yCP−yCPKπ using two-body D0 meson decays

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Physical Review D 2022年第9期105卷 092013-092013页

作者： R. Aaij A. S. W. Abdelmotteleb C. Abellán Beteta F. Abudinén T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. Agapopoulou C. A. Aidala S. Aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato J. L. Amey Y. Amhis L. An L. Anderlini M. Andersson A. Andreianov M. Andreotti D. Ao F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista de Souza Leite M. Barbetti R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay A. Beck M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella A. Bertolin C. Betancourt F. Betti Ia. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker N. V. Biesuz S. Bifani P. Billoir A. Biolchini M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura L. Buonincontri A. T. Burke C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes P. Campana A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti L. Carus K. Carvalho Akiba A. Casais Vidal R. Caspary G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli D. Cervenkov A. J. Chadwick M. G. Chapman M. Charles Ph. Charpentier C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Department of Physics University of Warwick Coventry United Kingdom Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France University of Michigan Ann Arbor USA (associated with Syracuse University Syracuse New York USA) INFN Sezione di Milano Milano Italy University of Cincinnati Cincinnati Ohio USA Fakultät Physik Technische Universität Dortmund Dortmund Germany European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom ICCUB Universitat de Barcelona Barcelona Spain Department of Physics and Astronomy University of Manchester Manchester United Kingdom Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Cavendish Laboratory University of Cambridge Cambridge United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France INFN Sezione di Firenze Firenze Italy INFN Sezione di Ferrara Ferrara Italy University of Chinese Academy of Sciences Beijing China Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de

A measurement of the ratios of the effective decay widths of D0→π−π+ and D0→K−K+ decays over that of D0→K−π+ decays is performed with the LHCb experiment using proton–proton collisions at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6 fb−1. These observables give access to the charm mixing parameters yCPππ−yCPKπ and yCPKK−yCPKπ, and are measured as yCPππ−yCPKπ=(6.57±0.53±0.16)×10−3, yCPKK−yCPKπ=(7.08±0.30±0.14)×10−3, where the first uncertainties are statistical and the second systematic. The combination of the two measurements is yCP−yCPKπ=(6.96±0.26±0.13)×10−3, which is four times more precise than the previous world average.

关键词： Hadronic decays Particle decays Particle mixing & oscillations Quark mixing Charmed mesons CP symmetry

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Measurement of the Bs0→μ+μ− decay properties and search for the B0→μ+μ− and Bs0→μ+μ−γ decays

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Physical Review D 2022年第1期105卷 012010-012010页

作者： R. Aaij C. Abellán Beteta T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. A. Aidala S. Aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato Y. Amhis L. An L. Anderlini A. Andreianov M. Andreotti F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista Leite R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella A. Bertolin C. Betancourt F. Betti Ia. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker S. Bifani P. Billoir M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice L. Calero Diaz S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes A. Camboni P. Campana A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti L. Carus K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli A. J. Chadwick M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier J. L. Cobbledick V. Coco J. A. B. Coelho J. Cogan E Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France University of Michigan Ann Arbor USA (associated with Syracuse University Syracuse New York USA) INFN Sezione di Milano Milano Italy University of Cincinnati Cincinnati Ohio USA Fakultät Physik Technische Universität Dortmund Dortmund Germany European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom ICCUB Universitat de Barcelona Barcelona Spain Department of Physics and Astronomy University of Manchester Manchester United Kingdom Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Cavendish Laboratory University of Cambridge Cambridge United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France INFN Sezione di Firenze Firenze Italy INFN Sezione di Ferrara Ferrara Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Department of Physics University of Warwick Coventry United Kingdom Centro Brasileiro de Pesquisa

An improved measurement of the decay Bs0→μ+μ− and searches for the decays B0→μ+μ− and Bs0→μ+μ−γ are performed at the LHCb experiment using data collected in proton-proton collisions at s=7, 8 and 13 TeV, corresponding to integrated luminosities of 1, 2 and 6 fb−1, respectively. The Bs0→μ+μ− branching fraction and effective lifetime are measured to be B(Bs0→μ+μ−)=(3.09−0.43−0.11+0.46+0.15)×10−9 and τ(Bs0→μ+μ−)=(2.07±0.29±0.03) ps, respectively, where the uncertainties include both statistical and systematic contributions. No significant signal for B0→μ+μ− and Bs0→μ+μ−γ decays is found and the upper limits B(B0→μ+μ−)<2.6×10−10 and B(Bs0→μ+μ−γ)<2.0×10−9 at 95% confidence level are determined, where the latter is limited to the range mμμ>4.9 GeV/c2. Additionally, the ratio between the B0→μ+μ− and Bs0→μ+μ− branching fractions is measured to be Rμ+μ−<0.095 at 95% confidence level. The results are in agreement with the Standard Model predictions.

关键词： Branching fraction Flavor changing neutral currents Rare decays Bottom mesons

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Sensitivity Analysis of a Simulation Model for Managing Contact Centers with Impatient Customers

Sensitivity Analysis of a Simulation Model for Managing Cont...

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2017 International Conference on Applied Mathematics, Modeling and Simulation (AMMS2017)

作者： Chia-Hung Wang Bin Zhu College of Information Science and Engineering Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications

Having worked as the primary contact points among customers and companies in the last decades, contact centers become a great investment for many organizations. This paper aims to study a queuing system with abandonments for managing the modern contact centers, where the impatient customers would probably abandon their calls if their patience expires before they reach a service agent. We develop an Arena simulation model to determine the system performance of interest. To figure out some useful managerial insights, we conduct a sensitivity analysis of the proposed system through a series of numerical experiments. The contribution of this study is to help managers achieve a better understanding of the optimal design and operation at the real-world contact centers.

关键词： arena simulation queueing system contact center balking reneging

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