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Observation of the suppressed Λb0→DpK− decay with D→K+π− and measurement of its CP asymmetry

Physical Review D 2021年第11期104卷 112008-112008页

作者： R. Aaij A. S. W. Abdelmotteleb C. Abellán Beteta F. J. Abudinen Gallego 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 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 M. Barbetti R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels S. Bashir 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 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 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 L. Calero Diaz 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 G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli D. Cervenkov 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. Cic 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 Michigan 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 E

A study of Λb0 baryon decays to the DpK− final state is presented based on a proton-proton collision data sample corresponding to an integrated luminosity of 9 fb−1 collected with the LHCb detector. Two Λb0 decays are considered, Λb0→DpK− with D→K−π+ and D→K+π−, where D represents a superposition of D0 and D¯0 states. The latter process is expected to be suppressed relative to the former, and is observed for the first time. The ratio of branching fractions of the two decays is measured, and the CP asymmetry of the suppressed mode, which is sensitive to the Cabibbo-Kobayashi-Maskawa angle γ, is also reported.

关键词： Hadronic decays CP violation

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Advanced diagnosis of rotor faults in large induction motors based on internal flux measurement

Advanced diagnosis of rotor faults in large induction motors...

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： Khalid Saad Galina Mirzaeva Department of Electrical Electronic and Information Engineering (DEI) University of Bologna Bologna (BO) Italy Faculty of Physics and Applied Computer Science AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9781479983988

Most of the existing electrical techniques of condition monitoring and fault diagnosis are based on stator current and/or stray flux measurement external to the motor. In this paper we propose a new diagnosis method for rotor bar faults based on flux measurements inside the main air gap of large induction motors. Theoretical analysis is presented, of both healthy motor and a motor with a broken rotor bar. Based on this, the fault detection method is proposed, which utilizes both time and space domain analysis of the air gap flux, to achieve superior rotor fault detection at early stages. The proposed method is demonstrated by extensive simulations. The method is experimentally validated using a specially instrumented laboratory scale induction motor. The prospective applications include large induction motors used in mining machines, in which internal Hall Effect Flux Sensors (HEFS) instrumentation is both feasible and justified.

关键词： Aerospace electronics Rotors Stators Instruments Air gaps Torque Industries

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A motor imagery based brain-computer interface system via swarm-optimized fuzzy integral and its application

A motor imagery based brain-computer interface system via sw...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Shang-Lin Wu Yu-Ting Liu Kuang-Pen Chou Yang-Yin Lin Jie Lu Guangquan Zhang Chun-Hsiang Chuang Wen-Chieh Lin Chin-Teng Lin Brain Research Center Institute of Electrical Control Engineering Institute of Computer Science and Engineering Electronic Systems Research Division National Chung-Shan Institute of Science and Technology (NCSIST) Taoyuan Taiwan Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Department of Computer Science National Chiao-Tung University Hsinchu Taiwan

ISBN: (纸本)9781509006274

A brain-computer interface (BCI) system provides a convenient means of communication between the human brain and a computer, which is applied not only to healthy people but also for people that suffer from motor neuron diseases (MNDs). Motor imagery (MI) is one well-known basis for designing Electroencephalography (EEG)-based real-life BCI systems. However, EEG signals are often contaminated with severe noise and various uncertainties, imprecise and incomplete information streams. Therefore, this study proposes spectrum ensemble based on swam-optimized fuzzy integral for integrating decisions from sub-band classifiers that are established by a sub-band common spatial pattern (SBCSP) method. Firstly, the SBCSP effectively extracts features from EEG signals, and thereby the multiple linear discriminant analysis (MLDA) is employed during a MI classification task. Subsequently, particle swarm optimization (PSO) is used to regulate the subject-specific parameters for assigning optimal confidence levels for classifiers used in the fuzzy integral during the fuzzy fusion stage of the proposed system. Moreover, BCI systems usually tend to have complex architectures, be bulky in size, and require time-consuming processing. To overcome this drawback, a wireless and wearable EEG measurement system is investigated in this study. Finally, in our experimental result, the proposed system is found to produce significant improvement in terms of the receiver operating characteristic (ROC) curve. Furthermore, we demonstrate that a robotic arm can be reliably controlled using the proposed BCI system. This paper presents novel insights regarding the possibility of using the proposed MI-based BCI system in real-life applications.

关键词： Electroencephalography Feature extraction Wireless sensor networks Wireless communication Electrodes Particle swarm optimization Microcontrollers

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Mixture of Bilateral-Projection Two-dimensional Probabilistic Principal Component Analysis

Mixture of Bilateral-Projection Two-dimensional Probabilisti...

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IEEE Conference on computer Vision and Pattern Recognition

作者： Fujiao Ju Yanfeng Sun Junbin Gao Simeng Liu Yongli Hu Baocai Yin College of Metropolitan Transportation Beijing University of Technology Discipline of Business Analytics The University of Sydney Business School The University of Sydney Faculty of Electronic Information and Electrical Engineering College of Computer Science Dalian University of Technology

ISBN: (纸本)9781467388528

The probabilistic principal component analysis (PPCA) is built upon a global linear mapping, with which it is insufficient to model complex data variation. This paper proposes a mixture of bilateral-projection probabilistic principal component analysis model (mixB2DPPCA) on 2D data. With multi-components in the mixture, this model can be seen as a 'soft' cluster algorithm and has capability of modeling data with complex structures. A Bayesian inference scheme has been proposed based on the variational EM (Expectation-Maximization) approach for learning model parameters. Experiments on some publicly available databases show that the performance of mixB2DPPCA has been largely improved, resulting in more accurate reconstruction errors and recognition rates than the existing PCA-based algorithms.

关键词： principal components analysis Clustering algorithms mixtures component analysis reconstruction error Probability Bayesian inference complex structure

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Minimizing median difference quantization error for image compression

Minimizing median difference quantization error for image co...

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International Conference on Information and Communication technology Convergence (ICTC)

作者： N. S. A. M Taujuddin Rosziati Ibrahim Suhaila Sari Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Batu Pahat Johor Malaysia Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Batu Pahat Johor Malaysia

ISBN: (纸本)9781509013265

This research emphasis on problem of quantization process in transform-based image compression. In specifying the quantizer, the size of interval is giving huge impact to the quantization performance. Generally, high quantization error will occurred if large interval is used at high difference value bin. Thus, quantizer needs to be design carefully to outfit the value as efficient as possible to reduce the quantization error. Contrary to the traditional approach, that apply uniform or non-uniform quantization step size, the proposed one utilize the high occurrence of zero coefficient by re-allocate the non-zero coefficient in a group for quantization. Then the proposed coder employ quantization error minimization mechanism by calculating the difference median quantization error at each quantization interval class. The results are then compared to the standard transform based algorithm and we found that the proposed algorithm compress the image effectively without harming the quality of the compressed image.

关键词： Quantization (signal) Image coding Image reconstruction Image quality Standards Boats Wavelet coefficients

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Satellite Image Edge Detection for Population Distribution Pattern Identification using Levelset with Morphological Filtering Process

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IOP Conference Series: Materials Science and engineering 2017年第1期180卷

作者： Harsiti T A Munandar A Suhendar A G Abdullah D Rohendi Information System Dept. Information Technology Faculty Universitas Serang Raya Banten – INDONESIA Informatics Engineering Dept. Information Technology Faculty Universitas Serang Raya Banten – INDONESIA Electrical and Electronic Engineering Dept. - Faculty of Technology and Vocational Education Universitas Pendidikan Indonesia Bandung INDONESIA Computer Scince Education Dept. – Math. and Naturan Science Faculty Universitas Pendidikan Indonesia Bandung INDONESIA

Population distribution pattern is directly related with economic gap of a region. Analysis of population distribution pattern is usually performed by studying statistical data on population. This study aimed to analyze population distribution pattern using image analysis concept, i.e. using satellite images. Levelset and morphological image filtering methods were used to analyze images to see distribution pattern. The research result showed that Levelset and morphological image filtering could remove a lot of noises in analysis result images and form object edge contours very clearly. The detected object contours were used as references to recognize population distribution pattern based on satellite image analysis. The pattern made based on the research result didn't show optimal result because Levelset performed image segmentation based on the contours of the analyzed objects. Other segmentation methods should be combined with it to produce clearer population distribution pattern.

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A study on fast motion estimation algorithm

A study on fast motion estimation algorithm

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IEEE Global Conference on Consumer electronics (GCCE)

作者： Masahiro Hiramori Ryota Bandou Shuhei Iwade Hiroshi Makino Tutomu Yoshimura Yoshio Matsuda the Graduate School of Information Science and Technology Osaka Institute of Technology Osaka Japan the Department of Computer Science Osaka Institute of Technology Osaka Japan the Department of Electrical and Electronic Systems Engineering Faculty of Engineering Osaka Institute of Technology Osaka Japan the Graduate School of Natural Science and Technology Kanazawa University Ishikawa Japan

ISBN: (纸本)9781509023349

This paper presents a new fast motion estimation algorithm. It searches groups of 4-pixels simultaneously and uses the value concatenated the absolute difference of upper 2-bit with the exclusive OR of the lower 6-bit. The search accuracy results show that the sum of absolute difference value is increased 4 of 7 video sequences when compared to the full-search algorithm with 4-bit absolute difference accumulator. The circuit was described in Verilog HDL and synthesized to Altera EP4CE30F23I7 FPGA. The synthesis results show that the required cycle is reduced by 61%, the circuit size is reduced by 15.2% and the operating frequency is increased from 334.67 MHz to 616.90 MHz when compared to the full-search algorithm with 4-bit absolute difference accumulator.

关键词： Motion estimation Detectors Video sequences Conferences Consumer electronics Registers Frequency estimation

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An ensemble sinusoidal parameter adaptation incorporated with L-SHADE for solving CEC2014 benchmark problems

An ensemble sinusoidal parameter adaptation incorporated wit...

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Congress on Evolutionary Computation

作者： Noor H. Awad Mostafa Z. Ali Ponnuthurai N. Suganthan Robert G. Reynolds School of Electrical & Electronic Engineering Nanyang Technological University Singapore School of Computer Information Systems Jordan University of Science & Technology Jordan Jordan King Hussein Faculty of Computing Sciences Princess Sumayya University for Technology College of Engineering Wayne State University

An effective and efficient self-adaptation framework is proposed to improve the performance of the L-SHADE algorithm by providing successful alternative adaptation for the selection of control parameters. The proposed algorithm, namely LSHADE-EpSin, uses a new ensemble sinusoidal approach to automatically adapt the values of the scaling factor of the Differential Evolution algorithm. This ensemble approach consists of a mixture of two sinusoidal formulas: A non-Adaptive Sinusoidal Decreasing Adjustment and an adaptive History-based Sinusoidal Increasing Adjustment. The objective of this sinusoidal ensemble approach is to find an effective balance between the exploitation of the already found best solutions, and the exploration of non-visited regions. A local search method based on Gaussian Walks is used at later generations to increase the exploitation ability of LSHADE-EpSin. The proposed algorithm is tested on the IEEE CEC2014 problems used in the Special Session and Competitions on Real-Parameter Single Objective Optimization of the IEEE CEC2016. The results statistically affirm the efficiency and robustness of the proposed approach to obtain better results compared to L-SHADE algorithm and other state-of-the-art algorithms.

关键词： Sociology Statistics Algorithm design and analysis Indexes Optimization Benchmark testing Evolutionary computation

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DAC-h3: A proactive robot cognitive architecture to acquire and express knowledge about the world and the self

arXiv

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arXiv 2017年

作者： Moulin-Frier, Clément Fischer, Tobias Petit, Maxime Pointeau, Grégoire Puigbo, Jordi-Ysard Pattacini, Ugo Low, Sock Ching Camilleri, Daniel Nguyen, Phuong Hoffmann, Matej Chang, Hyung Jin Zambelli, Martina Mealier, Anne-Laure Damianou, Andreas Metta, Giorgio Prescott, Tony J. Demiris, Yiannis Dominey, Peter Ford Verschure, Paul F.M.J. Laboratory for Synthetic Perceptive Emotive and Cognitive Systems Universitat Pompeu Fabra Barcelona08002 Spain Barcelona Spain Personal Robotics Laboratory Department of Electrical and Electronic Engineering Imperial College London SW7 2AZ United Kingdom Robot Cognition Laboratory INSERM U846 Stem Cell and Brain Research Institute Bron69675 France Italian Institute of Technology iCub Facility Via Morego 30 Genova Italy Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague Department of Computer Science University of Sheffield United Kingdom

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users. Copyright © 2017, The Authors. All rights reserved.

关键词： Human robot interaction

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Search for CP violation in Ξb−→pK−K− decays

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Physical Review D 2021年第5期104卷 052010-052010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 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. Cogneras 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 United States associated to 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 P

A search for CP violation in charmless three-body Ξb−→pK−K− decays is performed using pp collision data recorded with the LHCb detector, corresponding to integrated luminosities of 1 fb−1 at a center-of-mass energy s=7 TeV, 2 fb−1 at s=8 TeV and 2 fb−1 at s=13 TeV. A good description of the phase-space distribution is obtained with an amplitude model containing contributions from Σ(1385), Λ(1405), Λ(1520), Λ(1670), Σ(1775) and Σ(1915) resonances. The model allows for CP -violation effects, which are found to be consistent with zero. The branching fractions of Ξb−→Σ(1385)K−, Ξb−→Λ(1405)K−, Ξb−→Λ(1520)K−, Ξb−→Λ(1670)K−, Ξb−→Σ(1775)K− and Ξb−→Σ(1915)K− decays are also reported. In addition, an upper limit is placed on the product of ratios of Ωb− and Ξb− fragmentation fractions and the Ωb−→pK−K− and Ξb−→pK−K− branching fractions.

关键词： Baryons CP violation

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