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CMIS: Crime Map Information System for Safety Environment

IOP Conference Series: Materials science and Engineering 2016年第1期160卷

作者： Shahreen Kasim Hanayanti Hafit Ng Peng Yee Rathiah Hashim Husni Ruslai Kamaruzzaman Jahidin Mohammad Syafwan Arshad Soft Computing and data Mining Centre Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia GATES IT Solution Sdn Bhd Lot 4 Kompleks Usahawan Teknologi MARA Industrial Centre Technovation Park UTM Jalan Pontian Lama 81300 Skudai Johor Darul Ta'zim Terap Consultancy Sdn Bhd No. 92 Jalan Waja Indah 2 Taman Waja Indah 09000 Kulim Kedah Darul Aman

Crime Map is an online web based geographical information system that assists the public and users to visualize crime activities geographically. It acts as a platform for the public communities to share crime activities they encountered. Crime and violence plague the communities we are living in. As part of the community, crime prevention is everyone's responsibility. The purpose of Crime Map is to provide insights of the crimes occurring around Malaysia and raise the public's awareness on crime activities in their neighbourhood. For that, Crime Map visualizes crime activities on a geographical heat maps, generated based on geospatial data. Crime Map analyse data obtained from crime reports to generate useful information on crime trends. At the end of the development, users should be able to make use of the system to access to details of crime reported, crime analysis and report crimes activities. The development of Crime Map also enable the public to obtain insights about crime activities in their area. Thus, enabling the public to work together with the law enforcer to prevent and fight crime.

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Using Feature Selection to Improve the Utility of Differentially Private data Publishing

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Procedia computer science 2014年 37卷 511-516页

作者： Yasser Jafer Stan Matwin Marina Sokolova School of Electrical Engineering and Computer Science University of Ottawa Canada Institute for Big Data Analytics Dalhousie University Canada Institute for Computer Science Polish Academy of Sciences Faculty of Medicine University of Ottawa Canada

Protection of patient's privacy is an obligation enforced by laws and regulations in the US, Canada, and other jurisdictions. With exponential growth of exchange of personal health information (PHI) brought about by e-health, there is a need for smart algorithms that help the data publisher to protect PHI. Within exiting privacy models, differential privacy is considered one of the strongest privacy protection techniques that does not make any assumption about the attacker's background knowledge. One way to achieve differential privacy in the non-interactive mode is to derive a contingency table of the raw data over the database domain, to add noise to each count, and to publish the resulting noisy table of counts. This approach, however, is not suitable for high-dimensional data with large domains as the added noise substantially destroys the utility of the data. In this work, we show that when the K-anonymity is preceded by feature selection, it is possible to obtain a contingency table with higher counts. As a result, when noise is added to satisfy differential privacy, its distorting effect is minimized and high utility of the data is preserved. We propose the TOP_Diff algorithm which offers a trade-off between anonymization level K and the privacy budget ɛ, and enables us to publish privacy preserving datasets with high utility. Our approach is capable of handling both numerical and categorical features.

关键词： Privacy Feature Selection K-anonymity Differential Privacy Classification

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A novel method for mining class association rules with itemset constraints

A novel method for mining class association rules with items...

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6th International Conference on Computational Collective Intelligence, ICCCI 2014

作者： Nguyen, Dang Vo, Bay Le, Bac Division of Data Science Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Computer Science Department University of Science VNU Ho Chi Minh Viet Nam

ISBN: (纸本)9783319112886

Mining class association rules with itemset constraints is very popular in mining medical datasets. For example, when classifying which populations are at high risk for the HIV infection, epidemiologists often concentrate on rules which include demographic information such as sex, age, and marital status in the rule antecedents. However, two existing methods, post-processing and pre-processing, require much time and effort. In this paper, we propose a lattice-based approach for efficiently mining class association rules with itemset constraints. We first build a lattice structure to store all frequent itemsets. We then use paternity relations among nodes to discover rules satisfying the constraint without re-building the lattice. The experimental results show that our proposed method outperforms other methods in the mining time. © Springer International Publishing Switzerland 2014.

关键词： data mining

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Multi-Swarm bat algorithm

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Research Journal of Applied sciences, Engineering and Technology 2015年第12期10卷 1389-1395页

作者： Taha, Ahmed Majid Chen, Soong-Der Mustapha, Aida Soft Computing and Data Mining Center Universiti Tun Hussein Onn Malaysia Parit Raja Batu Pahat Johor 86400 Malaysia College of Information Technology Universiti Tenaga Nasional Kajang Selangor 43000 Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja Batu Pahat 86400 Malaysia

In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. The problem happens when search process converges to non-optimal solution due to the loss of diversity during the evolution process. MSBA was designed with improved ability in exploring new solutions, which was essential in reducing premature convergence. The exploration ability was improved by having a number of sub-swarms watching over the best local optima. In MSBA, when the quality of best local optima does not improve after a pre-defined number of iterations, the population is split equally into several smaller sub-swarms, with one of them remains close to the current best local optima for further exploitation while the other sub-swarms continue to explore for new local optima. The proposed algorithm has been applied in feature selection problem and the results were compared against eight algorithms, which are Ant Colony Optimization (ACO), Genetic Algorithm (GA), Tabu Search (TS), Scatter Search (SS), Great Deluge Algorithm (GDA) and stander BA. The results showed that the MSBA is much more effective that it is able to find new best solutions at times when the rest of other algorithms are not able to. © Maxwell Scientific Organization, 2015.

关键词： Bat algorithm Bio-inspired algorithms data mining Feature selection Multi-swarm Optimization

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Observation of the decay Bs0→D¯0K+K−

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Physical Review D 2018年第7期98卷 072006-072006页

作者： R. Aaij B. Adeva M. Adinolfi C. A. Aidala Z. Ajaltouni S. Akar P. Albicocco J. Albrecht F. Alessio M. Alexander A. Alfonso Albero S. Ali G. Alkhazov P. Alvarez Cartelle A. A. Alves, Jr. S. Amato S. Amerio Y. Amhis L. An L. Anderlini G. Andreassi M. Andreotti J. E. Andrews R. B. Appleby F. Archilli P. d’Argent J. Arnau Romeu A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni S. Bachmann J. J. Back S. Baker V. Balagura W. Baldini A. Baranov R. J. Barlow S. Barsuk W. Barter F. Baryshnikov V. Batozskaya B. Batsukh V. Battista A. Bay J. Beddow F. Bedeschi I. Bediaga A. Beiter L. J. Bel N. Beliy V. Bellee N. Belloli K. Belous I. Belyaev E. Ben-Haim G. Bencivenni S. Benson S. Beranek A. Berezhnoy R. Bernet D. Berninghoff E. Bertholet A. Bertolin C. Betancourt F. Betti M. O. Bettler M. van Beuzekom Ia. Bezshyiko S. Bifani P. Billoir A. Birnkraut A. Bizzeti M. Bjørn T. Blake F. Blanc S. Blusk D. Bobulska V. Bocci O. Boente Garcia T. Boettcher A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato F. Bossu M. Boubdir T. J. V. Bowcock C. Bozzi S. Braun M. Brodski J. Brodzicka D. Brundu E. Buchanan A. Buonaura C. Burr A. Bursche J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese R. Calladine M. Calvi M. Calvo Gomez A. Camboni P. Campana D. H. Campora Perez L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini P. Carniti L. Carson K. Carvalho Akiba G. Casse L. Cassina M. Cattaneo G. Cavallero R. Cenci D. Chamont M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis M. Chefdeville V. Chekalina C. Chen S. Chen S.-G. Chitic V. Chobanova M. Chrzaszcz A. Chubykin P. Ciambrone X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier V. Coco J. Cogan E. Cogneras L. Cojocariu P. Collins T. Colombo A. Comerma-Montells A. Contu G. Coombs S. Coquereau G. Corti M. Corvo C. M. Costa Sobral B. Couturier G. A. Cowan D. C. Craik A. Crocombe M. Cruz Torres R. Currie C. D’Ambrosio F. Da Cunha Marinho C. L. Da Silva E. Dall’Occo J. Dalseno A. Danilina A. Davis O. De Aguiar Francisco K. De Bruyn S. Nikhef National Institute for Subatomic Physics Amsterdam Netherlands 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 University of Michigan Ann Arbor Michigan USA (associated with Institution Syracuse University Syracuse New York USA) Clermont Université Université Blaise Pascal CNRS/IN2P3 LPC Clermont-Ferrand France University of Cincinnati Cincinnati Ohio USA INFN Laboratori Nazionali di Frascati Frascati Italy 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 Petersburg Nuclear Physics Institute (PNPI) Gatchina Russia Imperial College London London United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil INFN Sezione di Padova Padova Italy LAL Université Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Center for High Energy Physics Tsinghua University Beijing China INFN Sezione di Firenze Firenze Italy Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland INFN Sezione di Ferrara Ferrara Italy University of Maryland College Park Maryland USA School of Physics and Astronomy University of Manchester Manchester United Kingdom Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Aix Marseille Université CNRS/IN2P3 CPPM Marseille France Institute for High Energy Physics (IHEP) Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Physik-Institut Universität Zürich Zürich Switzerland Department of Physics University of Warwick Coventry United Kingdom National Center for Nuclear Research (NCBJ) Warsaw Poland INFN Sezione di Pisa Pisa I

The first observation of the Bs0→D¯0K+K− decay is reported, together with the most precise branching fraction measurement of the mode B0→D¯0K+K−. The results are obtained from an analysis of pp collision data corresponding to an integrated luminosity of 3.0 fb−1. The data were collected with the LHCb detector at center-of-mass energies of 7 and 8 TeV. The branching fraction of the B0→D¯0K+K− decay is measured relative to that of the decay B0→D¯0π+π− to be B(B0→D¯0K+K−)B(B0→D¯0π+π−)=(6.9±0.4±0.3)%, where the first uncertainty is statistical and the second is systematic. The measured branching fraction of the Bs0→D¯0K+K− decay mode relative to that of the corresponding B0 decay is B(Bs0→D¯0K+K−)B(B0→D¯0K+K−)=(93.0±8.9±6.9)%. Using the known branching fraction of B0→D¯0π+π−, the values of B(B0→D¯0K+K−)=(6.1±0.4±0.3±0.3)×10−5 and B(Bs0→D¯0K+K−)=(5.7±0.5±0.4±0.5)×10−5 are obtained, where the third uncertainties arise from the branching fraction of the decay modes B0→D¯0π+π− and B0→D¯0K+K−, respectively.

关键词： Branching fraction Hadronic decays Bottom mesons Bottom quark Hadron colliders Probability theory

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Observation of Bs0→D¯*0ϕ and search for B0→D¯0ϕ decays

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Physical Review D 2018年第7期98卷 071103(R)-071103(R)页

作者： R. Aaij B. Adeva M. Adinolfi C. A. Aidala Z. Ajaltouni S. Akar P. Albicocco J. Albrecht F. Alessio M. Alexander A. Alfonso Albero S. Ali G. Alkhazov P. Alvarez Cartelle A. A. Alves, Jr S. Amato S. Amerio Y. Amhis L. An L. Anderlini G. Andreassi M. Andreotti J. E. Andrews R. B. Appleby F. Archilli P. d’Argent J. Arnau Romeu A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni S. Bachmann J. J. Back S. Baker V. Balagura W. Baldini A. Baranov R. J. Barlow S. Barsuk W. Barter F. Baryshnikov V. Batozskaya B. Batsukh V. Battista A. Bay J. Beddow F. Bedeschi I. Bediaga A. Beiter L. J. Bel N. Beliy V. Bellee N. Belloli K. Belous I. Belyaev E. Ben-Haim G. Bencivenni S. Benson S. Beranek A. Berezhnoy R. Bernet D. Berninghoff E. Bertholet A. Bertolin C. Betancourt F. Betti M. O. Bettler M. van Beuzekom Ia. Bezshyiko S. Bifani P. Billoir A. Birnkraut A. Bizzeti M. Bjørn T. Blake F. Blanc S. Blusk D. Bobulska V. Bocci O. Boente Garcia T. Boettcher A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato F. Bossu M. Boubdir T. J. V. Bowcock C. Bozzi S. Braun M. Brodski J. Brodzicka D. Brundu E. Buchanan A. Buonaura C. Burr A. Bursche J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese R. Calladine M. Calvi M. Calvo Gomez A. Camboni P. Campana D. H. Campora Perez L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini P. Carniti L. Carson K. Carvalho Akiba G. Casse L. Cassina M. Cattaneo G. Cavallero R. Cenci D. Chamont M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis M. Chefdeville V. Chekalina C. Chen S. Chen S.-G. Chitic V. Chobanova M. Chrzaszcz A. Chubykin P. Ciambrone X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier V. Coco J. Cogan E. Cogneras L. Cojocariu P. Collins T. Colombo A. Comerma-Montells A. Contu G. Coombs S. Coquereau G. Corti M. Corvo C. M. Costa Sobral B. Couturier G. A. Cowan D. C. Craik A. Crocombe M. Cruz Torres R. Currie C. D’Ambrosio F. Da Cunha Marinho C. L. Da Silva E. Dall’Occo J. Dalseno A. Danilina A. Davis O. De Aguiar Francisco K. De Bruyn S. D Nikhef National Institute for Subatomic Physics Amsterdam Netherlands 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 University of Michigan Ann Arbor Michigan USA (associated with Syracuse University Syracuse New York USA) Clermont Université Université Blaise Pascal CNRS/IN2P3 LPC Clermont-Ferrand France University of Cincinnati Cincinnati Ohio USA INFN Laboratori Nazionali di Frascati Frascati Italy 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 Petersburg Nuclear Physics Institute (PNPI) Gatchina Russia Imperial College London London United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil INFN Sezione di Padova Padova Italy LAL Université Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Center for High Energy Physics Tsinghua University Beijing China INFN Sezione di Firenze Firenze Italy Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland INFN Sezione di Ferrara Ferrara Italy University of Maryland College Park Maryland USA School of Physics and Astronomy University of Manchester Manchester United Kingdom Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Aix Marseille Université CNRS/IN2P3 CPPM Marseille France Institute for High Energy Physics (IHEP) Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Physik-Institut Universität Zürich Zürich Switzerland Department of Physics University of Warwick Coventry United Kingdom National Center for Nuclear Research (NCBJ) Warsaw Poland INFN Sezione di Pisa Pisa Italy Centro

The first observation of the Bs0→D¯*0ϕ decay is reported, with a significance of more than seven standard deviations, from an analysis of pp collision data corresponding to an integrated luminosity of 3 fb−1, collected with the LHCb detector at center-of-mass energies of 7 and 8 TeV. The branching fraction is measured relative to that of the topologically similar decay B0→D¯0π+π− and is found to be B(Bs0→D¯*0ϕ)=(3.7±0.5±0.3±0.2)×10−5, where the first uncertainty is statistical, the second systematic, and the third from the branching fraction of the B0→D¯0π+π− decay. The fraction of longitudinal polarization in this decay is measured to be fL=(73±15±4)%. The most precise determination of the branching fraction for the Bs0→D¯0ϕ decay is also obtained, B(Bs0→D¯0ϕ)=(3.0±0.3±0.2±0.2)×10−5. An upper limit, B(B0→D¯0ϕ)<2.0 (2.3)×10−6 at 90% (95%) confidence level is set. A constraint on the ω−ϕ mixing angle δ is set at |δ|<5.2° (5.5°) at 90% (95%) confidence level.

关键词： Branching fraction Hadronic decays Quark mixing Bottom mesons Bottom quark CP violation Polarization Hadron colliders

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A visualization for the dynamic behaviors of the mixture of water mass for northwestern pacific near Japan

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International Journal of Modeling, Simulation, and Scientific Computing 2015年第2期6卷 213-214页

作者： Kun Zhao Satoshi Nakada Naohisa Sakamoto Koji Koyamada Chandrajit Bajaj Yoichi Ishikawa Toshiyuki Awaji Teiji In Sei-Ichi Saitoh Graduate School of Engineering Kyoto University KyotoKyoto Prefecture606-8501Japan Institute for the Promotion of Excellence in Higher Education Kyoto University KyotoKyoto Prefecture606-8501Japan Department of Computer Science The Institute for Computational Engineering and Sciences University of Texas at Austin AustinTexas78712USA Department of Geophysics Division of Earth and Planetary Sciences Kyoto University KyotoKyoto Prefecture606-8501Japan Data Research Center for Marine-Earth Sciences Japan Agency for Marine-Earth Science and Technology Yokosuka Kanakawa Prefecture237-0061Japan Japan Marine Science Foundation Tokyo Tokyo Metropolis110-0008Japan Laboratory of Marine Bioresource and Environment Sensing Faculty of Fisheries Sciences Hokkaido University SapporoHokkaido Prefecture060-0808Japan

(1)This article,published on 20 June 2013,had the following title:A VASUALIZATION FOR THE DYNAMIC BEHAVIORS OF THE MIXTURE OF WATER MASS FOR NORTHWESTERN PACIFIC NEAR JAPAN Here“VASUALIZATION”should be“VISUALIZATIO... 详细信息

关键词： northwestern dynamic NORTH

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Updated determination of D0–D¯0 mixing and CP violation parameters with D0→K+π− decays

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Physical Review D 2018年第3期97卷 031101(R)-031101(R)页

作者： R. Aaij B. Adeva M. Adinolfi Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero S. Ali G. Alkhazov P. Alvarez Cartelle A. A. Alves, Jr. S. Amato S. Amerio Y. Amhis L. An L. Anderlini G. Andreassi M. Andreotti J. E. Andrews R. B. Appleby F. Archilli P. d’Argent J. Arnau Romeu A. Artamonov M. Artuso E. Aslanides M. Atzeni G. Auriemma M. Baalouch I. Babuschkin S. Bachmann J. J. Back A. Badalov C. Baesso S. Baker V. Balagura W. Baldini A. Baranov R. J. Barlow C. Barschel S. Barsuk W. Barter F. Baryshnikov V. Batozskaya V. Battista A. Bay L. Beaucourt J. Beddow F. Bedeschi I. Bediaga A. Beiter L. J. Bel N. Beliy V. Bellee N. Belloli K. Belous I. Belyaev E. Ben-Haim G. Bencivenni S. Benson S. Beranek A. Berezhnoy R. Bernet D. Berninghoff E. Bertholet A. Bertolin C. Betancourt F. Betti M. O. Bettler M. van Beuzekom Ia. Bezshyiko S. Bifani P. Billoir A. Birnkraut A. Bizzeti M. Bjørn T. Blake F. Blanc S. Blusk V. Bocci T. Boettcher A. Bondar N. Bondar I. Bordyuzhin S. Borghi M. Borisyak M. Borsato F. Bossu M. Boubdir T. J. V. Bowcock E. Bowen C. Bozzi S. Braun J. Brodzicka D. Brundu E. Buchanan C. Burr A. Bursche J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese R. Calladine M. Calvi M. Calvo Gomez A. Camboni P. Campana D. H. Campora Perez L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini P. Carniti L. Carson K. Carvalho Akiba G. Casse L. Cassina M. Cattaneo G. Cavallero R. Cenci D. Chamont M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis M. Chefdeville S. Chen S. F. Cheung S.-G. Chitic V. Chobanova M. Chrzaszcz A. Chubykin P. Ciambrone X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier V. Coco J. Cogan E. Cogneras V. Cogoni L. Cojocariu P. Collins T. Colombo A. Comerma-Montells A. Contu G. Coombs S. Coquereau G. Corti M. Corvo C. M. Costa Sobral B. Couturier G. A. Cowan D. C. Craik A. Crocombe M. Cruz Torres R. Currie C. D’Ambrosio F. Da Cunha Marinho C. L. Da Silva E. Dall’Occo J. Dalseno A. Davis O. De Aguiar Francisco K. De Bruyn S. De Ca European Organization for Nuclear Research (CERN) Geneva Switzerland 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 Clermont Université Université Blaise Pascal CNRS/IN2P3 LPC Clermont-Ferrand France University of Cincinnati Cincinnati OH United States Fakultät Physik Technische Universität Dortmund Dortmund Germany School of Physics and Astronomy University of Glasgow Glasgow United Kingdom ICCUB Universitat de Barcelona Barcelona Spain Nikhef National Institute for Subatomic Physics Amsterdam The Netherlands Petersburg Nuclear Physics Institute (PNPI) Gatchina Russia Imperial College London London United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Sezione INFN di Padova Padova Italy LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France Center for High Energy Physics Tsinghua University Beijing China Sezione INFN di Firenze Firenze Italy Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Universita e INFN Ferrara Ferrara Italy University of Maryland College Park MD United States School of Physics and Astronomy University of Manchester Manchester United Kingdom Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Institute for High Energy Physics (IHEP) Protvino Russia Syracuse University Syracuse NY United States Physik-Institut Universität Zürich Zürich Switzerland Sezione INFN di Roma La Sapienza Roma Italy Department of Physics University of Warwick Coventry United Kingdom Pontifícia Universidade Católica do Rio de Janeiro (PUC-Rio) Rio de Janeiro Brazil (associated with Institution Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil) Yandex School of Data Analysis Moscow Russia Institute of Theoretical

We report measurements of charm-mixing parameters based on the decay-time-dependent ratio of D0→K+π− to D0→K−π+ rates. The analysis uses a data sample of proton-proton collisions corresponding to an integrated luminosity of 5.0 fb−1 recorded by the LHCb experiment from 2011 through 2016. Assuming charge-parity (CP) symmetry, the mixing parameters are determined to be x′2=(3.9±2.7)×10−5, y′=(5.28±0.52)×10−3, and RD=(3.454±0.031)×10−3. Without this assumption, the measurement is performed separately for D0 and D¯0 mesons, yielding a direct CP-violating asymmetry AD=(−0.1±9.1)×10−3, and magnitude of the ratio of mixing parameters 1.00<|q/p|<1.35 at the 68.3% confidence level. All results include statistical and systematic uncertainties and improve significantly upon previous single-measurement determinations. No evidence for CP violation in charm mixing is observed.

关键词： Particle mixing & oscillations

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Privacy-aware filter-based feature selection

Privacy-aware filter-based feature selection

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IEEE International Conference on Big data

作者： Yasser Jafer Stan Matwin Marina Sokolova School of Electrical Engineering and Computer Science University of Ottawa Canada Institute for Big Data Analytics Dalhousie University Canada Polish Academy of Sciences Institute for Computer Science Poland Faculty of Medicine University of Ottawa Canada

ISBN: (纸本)9781479956678

A large amount of digital information collected and stored in databases creates new opportunities for knowledge discovery and data mining. The datasets, however, may contain personally identifiable information that needs to be protected. With high dimensionality of many large datasets, dimensionality reduction such as feature selection becomes indispensible. In this work, we aim at incorporating privacy into the very process of feature selection and as such, propose a privacy-aware filter-based feature selection method (PF-IFR). Our method enables data custodians to define a trade-off measure for controlling the amount of privacy and efficacy using filter-based feature selection techniques.

关键词： Correlation Privacy Accuracy data privacy Filtering algorithms Educational institutions Publishing

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Study of the production of Λ_b^0 band ~0 hadrons in pp collisions and first measurement of the Λ_b^0→J/ψpK^- branching fraction

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Chinese Physics C 2016年第1期40卷 1-16页

作者： O.Kochebina M.Kolpin I.Komarov R.F.Koopman P.Koppenburg M.Kozeiha L.Kravchuk K.Kreplin M.Kreps G.Krocker P.Krokovny F.Kruse W.Krzemien W.Kucewicz M.Kucharczyk V.Kudryavtsev A.K.Kuonen K.Kurek T.Kvaratskheliya D.Lacarrere G.Lafferty A.Lai D.Lambert G.Lanffanchi C.Langenbruch B.Langhans T.Latham C.Lazzeroni R.Le Gac J.van Leerdam J.-P.Lees R.Lefevre A.Leflat J.Lefrancois E.Lemos Cid O.Leroy T.Lesiak B.Leverington Y.Li T.Likhomanenko M.Liles R.Lindner C.Linn F.Lionetto B.Liu X.Liu D.Loh I.Longstaff J.H.Lopes D.Lucchesi M.Lucio Martinez H.Luo A.Lupato E.Luppi O.Lupton A.Lusiani F.Machefert F.Maciuc O.Maev K.Maguire S.Malde A.Malinin G.Manca G.Mancinelli P.Manning A.Mapelli J.Maratas J.F.Marchand U.Marconi C.Marin Benito P.Marino J.Marks G.Martellottil M.Martin M.Martinelli D.Martinez Santos F.Martinez Vidal D.Martins Tostes A.Massafferri R.Matev A.Mathad Z.Mathe C.Matteuzzi A.Mauri B.Maurin A.Mazurov M.McCann J.McCarthy A.McNab R.McNulty B.Meadows F.Meier M.Meissner D.Melnychuk M.Merk E Michielin D.A.Milanes M.-N.Minard D.S.Mitzel J.Molina Rodrigue I.A.Monroy S.Monteil M.Morandin P.Morawski A.Morda M.J.Morello J.Moron A.B.Morris R.Mountain F.Muheim D.Miiller J.Muller K.Muller V.Muller M.Mussini B.Muster P.Naik T.Nakada R.Nandakumar A.Nandi I.Nasteva M.Needham N.Neri S.Neubert N.Neufeld M.Neuner A.D.Nguyen T.D.Nguyen C.Nguyen-Mau V.Niess R.Niet N.Nikitin T.Nikodem D.Ninci A.Novoselov D.P.O'Hanlon A.Oblakowska-Mucha V.Obraztsov S.Ogilvy O.Okhrimenko R.Oldeman C.J.G.Onderwater B.Osorio Rodrigues J.M.Otalora Goicochea A.Otto P.Owen A.Oyanguren A.Palano F.Palombo M.Palutan J.Panman A.Papanestis M.Pappagallo L.L.Pappalardo C.Pappenheimer C.Parkes G.Passaleva G.D.Patel M.Patel C.Patrignani A.Pearce A.Pellegrino G.Penso M.Pepe Altarelli S.Perazzini P.Perret L.Pescatore K.Petridis A.Petrolini M.Petruzzo E.Picatoste Olloqui B.Pietrzyk T:.Pilar D.Pinci A.Pistone A.Piucci S.Playfer M.Plo Casasus T.Poikela F.Polci A.Poluektov I.Polyakov E.Polycarpo A.Popov D.Popov B.Popovici C.Potterat E.Price J.D.Price J.Prisciandaro A.Pritchard Centro Brasileiro de Pesquisas Ffsicas(CBPF) Rio de JaneiroBrazil Universidade Federal do Rio de Janeiro(UFRJ) Rio de JaneiroBrazil Center for High Energy Physics Tsinghua UniversityBeijingChina LAPP Universite Savoie Mont-BlancCNRS/IN2P3Annecy-Le-VieuxFrance Clermont Universite Universite Blaise PascalCNRS/IN2P3LPCclermont-FerrandFrance CPPM Aix-Marseille UniversitYCNRS/IN2P3MarseilleFrance LAL Universite Paris-SudCNRS/IN2P3OrsayFrance LPNHE Universite Pierre et Marie CurieUniversite Paris DiderotCNRS/IN2P3ParisFrance Fakultat Physik Technische Universitat DortmundDortmundGermany Max-Planck-lnstitut fur Kernphysik(MPIK) HeidelbergGermany Physikalisches Institut Ruprecht-Karls-Universitat HeidelbergHeidelbergGermany School of Physics University College DublinDublinIreland Sezione INFN di Bari BariItaly Sezione INFN di Bologna BolognaItaly Sezione INFN di Cagliari CagliariItaly Sezione INFN di Ferrara FerraraItaly Sezione INFN di Firenze FirenzeItaly Laboratori Nazionali dell'INFN di Prascati FrascatiItaly Sezione INFN di Genova GenovaItaly Sezione INFN di Milnno Bicocca MilunoItaly Sezione INFN di Milano MilanoItaly Sezione INFN di Padova PadovaItaly Sezione INFN di Pisa PisaItaly Sezione INFN di Roma Tor Vergata RomaItaly Sezione INFN di Roma La Sapienza RomaItaly Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences Krak6wPoland AGH-University of Science and Technology Faculty of Physics and Applied Computer ScienceKrakowPoland National Center for Nuclear Research(NCBJ) WarsawPoland Horia Hulubei National Institute of Physics and Nuclear Engineering Bucharest-MagureleRomania Petersburg Nuclear Physics Institute(PNPI) GatchinaRussia Institute of Theoretical and Experimental Physics(ITEP) MoscowRussia Institute of Nuclear Physics Moscow State University(SINP MSU)MoscowRussia Institute for Nuclear Research of the Russian Academy of Sciences(INR RAN) MoscowRussia Budker Institute of Nuclear Physics(SB RAS)and Novosibirsk State University No

The product of the ∧0/b （-B/0） differential production cross-section and the branching fraction of the decay ∧0/b→ J/ψ pK-（-B/0→ J/ψ-K＊（892）0）is measured as a function of the beauty hadron transverse momentum, PT, and rapidity, y. The kinematic region of the measurements is pT〈20 GeV/c and 2.0 〈g〈*** measurements use a data sample corresponding to an integrated luminosity of 3fb-1 collected by the LHCb detector in pp collisions at centre-of-mass energies √s=7 TeV in 2011 and √s=8 TeV in 2012. Based on previous LHCb results of the fragmentation fraction ratio,f∧0/b/fd,the branching fraction of the decay ∧0/b→ J/ψ pK-is measured to be B（∧0/b→ J/ψ pK-）=（3.17±0.04±0.07±0.34＋0.45/-0.28）×10-4,where the first uncertainty is statistical, the second is systematic, the third is due to the uncertainty on the branching fraction of the decay -B/0 →J/ψ-K＊（892）0,and the fourth is due to the knowledge of f∧0/b/*** sum of the asymmetries in the production and decay between ∧0/b and ∧0/bis also measured as a function of PT and *** previously published branching fraction of ∧0/b→ J/ψ pπ-,relative to that of ∧0/b→ J/ψ pK-,is updated. The branching fractions of ∧0/b→P＋c（→ J/ψp）K-are determined.

关键词： production cross-section branching fraction b hadrons proton-proton collisions

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