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IEEE International Conference on Consumer electronics (ICCE)

作者： Emad Danish Mohammed Alreshoodi Anil Fernando Bander Alzahrani Sami Alharthi Centre for Vision Speech and Signal Processing University of Surrey Guildford UK School of Computer Science and Electronic Engineering University of Essex Colchester UK Faculty of Computing and Information Technology King Abdulaziz University KSA

Based on random neural networks, a cross-layer prediction model is proposed for estimating the perceptual quality of mobile video in no reference mode. The model exploits key parameters affecting video quality. Simulation results show considerable predictability performance with R-squared correlation of 0.90 and 0.39 root mean squared error.

关键词： Quality of service Predictive models Quality assessment Video recording Neural networks Mobile communication Packet loss

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Fall detection using machine learning algorithms

Fall detection using machine learning algorithms

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International Conference on Software, Telecommunications and computer Networks (SoftCOM)

作者： Pranesh Vallabh Reza Malekian Ning Ye Dijana Capeska Bogatinoska Department of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing Jiangsu Province China College of Computer Nanjing University of Posts and Telecommunications Nanjing China Faculty of Computer Science and Engineering University of Information Science and Technology “St. Paul the Apostle” Ohrid Republic of Macedonia

ISBN: (纸本)9781509025787

In this paper, the recognition of and the differentiation between fall activities and activities of daily living (ADL) was performed using the MobiFall dataset. A large database was constructed to train and validate the model. Feature selection methods were implemented to reduce dimensionality. Five different classification algorithms were implemented and evaluated based on their accuracy' sensitivity, and specificity achieved. The k-Nearest Neighbors' algorithm obtained an overall accuracy of 87.5% with a sensitivity of 90.70%, and a specificity of 83.78%.

关键词： Feature extraction Accelerometers Sensors Hidden Markov models Machine learning algorithms Gyroscopes Acceleration

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Transparent solar antenna of 28 GHz using transparent conductive oxides (TCO) thin film

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Journal of Physics: Conference Series 2017年第1期852卷

作者： N I Mohd Ali N Misran M F Mansor M F Jamlos Department of Electrical Electronic and System Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia 43600 Bangi Selangor Malaysia Faculty of Engineering Technology Universiti Malaysia Perlis Kampus UniCITI Alam Sungai Chuchuh 02100 Padang Besar Perlis Malaysia School of Computer and Communication Engineering Universiti Malaysia Perlis Kampus Tetap Pauh Putra 02600 Arau Perlis Malaysia

This paper presents the analysis of 28GHz solar patch antenna using the variations of transparent conductive oxides (TCO) thin film as the radiating patch. Solar antenna is basically combining the function of antenna and solar cell into one device and helps to maximize the usage of surface area. The main problem of the existing solar antenna is the radiating patch which made of nontransparent material, such as copper, shadowing the solar cell and degrades the total solar efficiency. Hence, by using the transparent conductive oxides (TCO) thin film as the radiating patch, this problem can be tackled. The TCO thin film used is varied to ITO, FTO, AgHT-4, and AgHT-8 along with glass as substrate. The simulation of the antenna executed by using computer Simulation technology (CST) Microwave Studio software demonstrated at 28 GHz operating frequency for 5G band applications. The performance of the transparent antennas is compared with each other and also with the nontransparent patch antenna that using Rogers RT5880 as substrate, operating at the same resonance frequency and then, the material that gives the best performance is identified.

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Image encryption: Improved generalized discrete arnold transformation and nonlinear chaotic map

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ICIC Express Letters 2016年第5期10卷 1121-1127页

作者： Tian, Ye Lu, Zhimao Gao, Xueyao College of Information and Communication Engineering Harbin Engineering University No. 145 Nantong Street Nangang District Harbin150001 China Key Laboratory of Photonic and Electronic Bandgap Materials Ministry of Education School of Physics and Electronic Engineering Harbin Normal University No. 1 Shida Road Hulan District Harbin150025 China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology No. 2 Linggong Road Ganjingzi District Dalian116024 China School of Computer Science and Technology Harbin University of Science and Technology No. 52 Xuefu Road Nangang District Harbin150080 China

The development of computer networks makes image files transportation via network become more and more convenient. However, the security of most existing image encryption methods requires to be further improved. In this paper, we present an Image Encryption algorithm combining an Improved generalized discrete Arnold transformation and a Nonlinear Chaotic map (IEIANC). It adopts the scrambling and diffusion encryption framework. First, it designs an extra 256-bit key to make the key space large enough. Next, it utilizes an improved generalized discrete Arnold transformation to scramble image pixels, and divides the scrambled image into several blocks. Finally, it applies a nonlinear chaotic map to diffuse these blocks. The experimental results show the effectiveness of the proposed algorithm. © 2016 ICIC International.

关键词： Cryptography

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The status of KAGRA underground cryogenic gravitational wave telescope

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Journal of Physics: Conference Series 2019年第1期1342卷

作者： T. Akutsu M. Ando A. Araya N. Aritomi H. Asada Y. Aso S. Atsuta K. Awai M. A. Barton K. Cannon K. Craig W. Creus K. Doi K. Eda Y. Enomoto R. Flaminio Y. Fujii M.-K. Fujimoto T. Furuhata S. Haino K. Hasegawa K. Hashino K. Hayama S. Hirobayashi E. Hirose A. H. Hsieh Y. Inoue K. Ioka Y. Itoh T. Kaji T. Kajita M. Kakizaki M. Kamiizumi S. Kambara N. Kanda S. Kanemura M. Kaneyama G. Kang J. Kasuya Y. Kataoka N. Kawai S. Kawamura C. Kim H. Kim J. Kim Y. Kim N. Kimura T. Kinugawa S. Kirii Y. Kitaoka Y. Kojima K. Kokeyama K. Komori K. Kotake R. Kumar H. Lee Y. Liu N. Luca E. Majorana S. Mano M. Marchio T. Matsui F. Matsushima Y. Michimura O. Miyakawa T. Miyamoto A. Miyamoto K. Miyo S. Miyoki W. Morii S. Morisaki Y. Moriwaki T. Morozumi M. Musha S. Nagano K. Nagano K. Nakamura T. Nakamura H. Nakano M. Nakano K. Nakao T. Narikawa L.Nguyen Quynh W.-T. Ni T. Ochi J. Oh S. Oh M. Ohashi N. Ohishi M. Ohkawa K. Okutomi K. Oohara F. E.Peña Alleano I. Pinto N. Sago M. Saijo Y. Saito K. Sakai Y. Sakai Y. Sasaki M. Sasaki S. Sato T. Sato Y. Sekiguchi N. Seto M. Shibata T. Shimoda H. Shinkai A. Shoda K. Somiya E. Son A. Suemasa T. Suzuki H. Tagoshi H. Takahashi R. Takahashi A. Takamori H. Takeda H. Tanaka K. Tanaka T. Tanaka D. Tatsumi T. Tomaru T. Tomura F. Travasso K. Tsubono S. Tsuchida N. Uchikata T. Uchiyama T. Uehara S. Ueki K. Ueno T. Ushiba M. H. P. M. van Putten H. Vocca S. Wada T. Wakamatsu T. Yamada S. Yamamoto T. Yamamoto K. Yamamoto A. Yamamoto J. Yokoyama T. Yokozawa T. H. Yoon H. Yuzurihara S. Zeidler Z.-H. Zhu KAGRA Collaboration National Astronomical Observatory of Japan Mitaka Tokyo 181-8588 Japan Department of Physics University of Tokyo Bunkyo Tokyo 113-0033 Japan Earthquake Research Institute University of Tokyo Bunkyo Tokyo 113-0032 Japan Department of Advanced Physics Hirosaki University Hirosaki Aomori 036-8561 Japan National Astronomical Observatory of Japan Hida Gifu 506-1205 Japan Department of Physics Tokyo Institute of Technology Meguro Tokyo 152-8551 Japan Institute for Cosmic Ray Research University of Tokyo Hida Gifu 506-1205 Japan Research Center for the Early Universe University of Tokyo Bunkyo Tokyo 113-0033 Japan Institute for Cosmic Ray Research University of Tokyo Kashiwa Chiba 277-8582 Japan Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Department of Physics University of Toyama Toyama Toyama 930-8555 Japan Faculty of Engineering University of Toyama Toyama Toyama 930-8555 Japan Yukawa Institute for Theoretical Physics Kyoto University Sakyo Kyoto 606-8502 Japan Department of Physics Osaka City University Sumiyosi Osaka 558-8585 Japan Department of Physics Osaka University Toyonaka Osaka 560-0043 Japan Korea Institute of Science and Technology Information Yuseong Daejeon 34141 Korea Korea Astronomy and Space Science Institute (KASI) Yuseong Daejeon 34055 Korea National Institute for Mathematical Sciences Daejeon 34047 Korea Department of Computer Simulation Inje University Gimhae Gyeongsangnam 50834 Korea Department of Physics and Astronomy Seoul National University Seoul 151-742 Korea High Energy Accelerator Research Organization Tsukuba Ibaraki 305-0801 Japan Department of Physical Science Hiroshima University Higashihiroshima Hiroshima 903-0213 Japan Department of Applied Physics Fukuoka University Jonan Fukuoka 814-0180 Japan Department of Advanced Materials Science University of Tokyo Kashiwa Chiba 277-8582 Japan Istituto Nazionale di Fisica Nucleare Sapienza University Roma 00185 Italy Department of Ma

KAGRA is a 3-km interferometric gravitational wave telescope located in the Kamioka mine in Japan. It is the first km-class gravitational wave telescope constructed underground to reduce seismic noise, and the first km-class telescope to use cryogenic cooling of test masses to reduce thermal noise. The construction of the infrastructure to house the interferometer in the tunnel, and the initial phase operation of the interferometer with a simple 3-km Michelson configuration have been completed. The first cryogenic operation is expected in 2018, and the observing runs with a full interferometer are expected in 2020s. The basic interferometer configuration and the current status of KAGRA are described.

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Implementation of the ECG Biometric Identification By using Arduino Microprocessor

Implementation of the ECG Biometric Identification By using ...

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International Conference on Electrical engineering/electronics, computer, Telecommunications and Information technology

作者： Somsanouk Pathoumvanh Phoumy Indahak Khamphet Bounnady Viengxay Viravong Department of Electronic and Telecommunication Faculty of Engineering National University of Laos Sisattanak Dist. Vientiane Lao P.D.R Department of Information Technology and Computer Faculty of Engineering National University of Laos Sisattanak Dist. Vientiane Lao P.D.R Department of Electronic and Electrical Engineering Vientiane - Hanoi Friendship Vocational College Saysetha Dist. Lao P.D.R

ISBN: (纸本)9781467397506

This paper proposes the method of implementing the ECG biometrics for person identification system by using the Arduino Microprocessor. The Lead-I ECG data had been self-setup and collected, then the achieved ECG features are investigated on the Arduino Uno R3 microprocessor and e-health sensor board. After that, the simulation processes for the identification process are begun with the selection Single Beat ECG and analyzed by the Continuous Wavelet Transform (CWT). Then RMS value of total energy of the wavelet coefficients of each P, QRS, and T segment is calculated. Next, the Fisher Linear discriminant analysis (FLDA) is applied to all set of RMS value for dimension reduction. Lastly the normalized Euclidean distance is implemented as the classifier. The experimental results demonstrate that: our proposed method is achieved the accuracy of classification with 96%.

关键词： ECG Biometrics Biometrics feature extraction Person Identification

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A compact multispectral image capture unit for deployment on drones

A compact multispectral image capture unit for deployment on...

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IEEE Instrumentation and Measurement technology Conference

作者： Ezekiel Bokolonga Martin Hauhana Nicholas Rollings David Aitchison Mansour H. Assaf Sunil R. Das Satyendra N. Biswas Voicu Groza Emil M. Petriu School of Engineering and Physics University of the South Pacific (USP) Suva Fiji Faculty of Engineering University of Ottawa Ottawa ON Canada Department of Computer Science Troy University Montgomery AL USA Department of Electrical and Electronic Engineering Ahsanullah University of Science and Technology Dhaka Bangladesh University of Ottawa Ottawa ON CA

ISBN: (纸本)9781467392211

The design, implementation and evaluation of a lightweight portable multispectral imaging system for deployment on drones is presented in this paper. The dual cameras used enable concurrent capture of red, green, blue (RGB) and near-infrared (NIR) images using simultaneous triggering. The images are stored in native file generated format. A global positioning system (GPS) connected to the camera's controllers enables geo-tagging of the images via exchangeable image file format (EXIF) metadata. A second-order polynomial has been utilized in order to align and test the RGB and NIR images to attain subpixel accuracy. The system was implemented in the matrix laboratory (MATLAB) and the developed algorithm was verified for accuracy considering different environmental conditions and scenarios.

关键词： Cameras Multispectral imaging Arrays Sensors Drones Global Positioning System

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A Novel Online Bayes Classifier

A Novel Online Bayes Classifier

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Thi Thu Thuy Nguyen Tien Thanh Nguyen Xuan Cuong Pham Alan Wee-Chung Liew Yongjian Hu Tiancai Liang Chang-Tsun Li School of Information and Communication Technology Griffith University Australia Faculty of Computer Science and Engineering Water Resource University Hanoi Vietnam School of Electronic and Information Engineering South China University of Technology Guangzhou China Inst. of R&D GRG Banking Equip. Co. Ltd. Guangzhou China Department of Computer Science University of Warwick UK

We present VIGO, a novel online Bayesian classifier for both binary or multiclass problems. In our model, variational inference for multivariate Gaussian distribution technique is exploited to approximate the class conditional probability density functions of data in an online manner. Besides being a conservative learner with a low number of updates compared with many other popular algorithms, VIGO algorithm can be updated in a minibatch of an arbitrary size which makes it robust with noise data. Experiments over a large number of UCI datasets demonstrate the advantage of VIGO with many state-of-the-art methods presented in LIBOL - a prevalent library for online learning algorithms.

关键词： Classification algorithms Gaussian distribution Prediction algorithms Inference algorithms Data models Predictive models Approximation algorithms

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Angular analysis of the B+ → K∗+µ+µ− decay

arXiv

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arXiv 2020年

作者： Aaij, R. Beteta, C. Abellán Ackernley, T. Adeva, B. Adinolfi, M. Afsharnia, H. Aidala, C.A. Aiola, S. Ajaltouni, Z. Akar, S. Albrecht, J. Alessio, F. Alexander, M. Albero, A. Alfonso Aliouche, Z. Alkhazov, G. Cartelle, P. Alvarez Amato, S. Amhis, Y. An, L. Anderlini, L. Andreianov, A. Andreotti, M. Archilli, F. Artamonov, A. Artuso, M. Arzymatov, K. Aslanides, E. Atzeni, M. Audurier, B. Bachmann, S. Bachmayer, M. Back, J.J. Baker, S. Rodriguez, P. Baladron Balagura, V. Baldini, W. Leite, J. Baptista Barlow, R.J. Barsuk, S. Barter, W. Bartolini, M. Baryshnikov, F. Basels, J.M. Bassi, G. Batsukh, B. Battig, A. Bay, A. Becker, M. Bedeschi, F. Bediaga, I. Beiter, A. Belavin, V. Belin, S. Bellee, V. Belous, K. Belov, I. Belyaev, I. Bencivenni, G. Ben-Haim, E. Berezhnoy, A. Bernet, R. Berninghoff, D. Bernstein, H.C. Bertella, C. Bertolin, A. Betancourt, C. Betti, F. Bezshyiko, I. Bhasin, S. Bhom, J. Bian, L. Bieker, M.S. Bifani, S. Billoir, P. Birch, M. Bishop, F.C.R. Bizzeti, A. Bjørn, M. Blago, M.P. Blake, T. Blanc, F. Blusk, S. Bobulska, D. Boelhauve, J.A. Garcia, O. Boente Boettcher, T. Boldyrev, A. Bondar, A. Bondar, N. Borghi, S. Borisyak, M. Borsato, M. Borsuk, J.T. Bouchiba, S.A. Bowcock, T.J.V. Boyer, A. Bozzi, C. Bradley, M.J. Braun, S. Rodriguez, A. Brea Brodski, M. Brodzicka, J. Gonzalo, A. Brossa Brundu, D. Buonaura, A. Burr, C. Bursche, A. Butkevich, A. Butter, J.S. Buytaert, J. Byczynski, W. Cadeddu, S. Cai, H. Calabrese, R. Calefice, L. Diaz, L. Calero Cali, S. Calladine, R. Calvi, M. Gomez, M. Calvo Magalhaes, P. Camargo Camboni, A. Campana, P. Quezada, A.F. Campoverde Capelli, S. Capriotti, L. Carbone, A. Carboni, G. Cardinale, R. Cardini, A. Carli, I. Carniti, P. Akiba, K. Carvalho Vidal, A. Casais Casse, G. Cattaneo, M. Cavallero, G. Celani, S. Cerasoli, J. Chadwick, A.J. Chapman, M.G. Charles, M. Charpentier, P. Chatzikonstantinidis, G. Barajas, C.A. Chavez Chefdeville, M. Chen, C. Chen, S. Chernov, A. Chitic, S.-G. Chobanova, V. Cholak, S. Chrzaszcz, M. Rio de Janeiro Brazil Rio de Janeiro Brazil Center for High Energy Physics Tsinghua University Beijing China School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China University of Chinese Academy of Sciences Beijing China Beijing China Institute of Particle Physics Central China Normal University Wuhan Hubei China Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS IN2P3-LAPP Annecy France Université Clermont Auvergne CNRS IN2P3 LPC Clermont-Ferrand France Aix Marseille Univ CNRS IN2P3 CPPM Marseille France Université Paris-Saclay CNRS IN2P3 IJCLab Orsay France Palaiseau France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS IN2P3 Paris France I. Physikalisches Institut RWTH Aachen University Aachen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Heidelberg Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany School of Physics University College Dublin Dublin Ireland INFN Sezione di Bari Bari Italy INFN Sezione di Bologna Bologna Italy INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Firenze Firenze Italy INFN Laboratori Nazionali di Frascati Frascati Italy INFN Sezione di Genova Genova Italy INFN Sezione di Milano-Bicocca Milano Italy INFN Sezione di Milano Milano Italy INFN Sezione di Cagliari Monserrato Italy Universita degli Studi di Padova Universita e INFN Padova Italy INFN Sezione di Pisa Pisa Italy INFN Sezione di Roma Tor Vergata Roma Italy INFN Sezione di Roma La Sapienza Roma Italy Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Nikhef National Institute for Subatomic Physics VU University Amsterdam Amsterdam Netherlands Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences Kraków Poland AGH - University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland Warsaw Poland Horia Hulubei Nation

We present an angular analysis of the B+ → K∗+(→ KS0π+)µ+µ− decay using 9 fb−1 of pp collision data collected with the LHCb experiment. For the first time, the full set of CP-averaged angular observables is measured in intervals of the dimuon invariant mass squared. Local deviations from Standard Model predictions are observed, similar to those in previous LHCb analyses of the isospin-partner B0 → K∗0µ+µ− decay. The global tension is dependent on which effective couplings are considered and on the choice of theory nuisance parameters. © 2020, CC BY.

关键词： Hadrons

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Observation of the Bs0 → D∗±D decay

arXiv

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arXiv 2020年

作者： Aaij, R. Abellán Beteta, C. Ackernley, T. Adeva, B. Adinolfi, M. Afsharnia, H. Aidala, C.A. Aiola, S. Ajaltouni, Z. Akar, S. Albrecht, J. Alessio, F. Alexander, M. Alfonso Albero, A. Aliouche, Z. Alkhazov, G. Alvarez Cartelle, P. Amato, S. Amhis, Y. An, L. Anderlini, L. Andreianov, A. Andreotti, M. Archilli, F. Artamonov, A. Artuso, M. Arzymatov, K. Aslanides, E. Atzeni, M. Audurier, B. Bachmann, S. Bachmayer, M. Back, J.J. Baker, S. Baladron Rodriguez, P. Balagura, V. Baldini, W. Baptista Leite, J. Barlow, R.J. Barsuk, S. Barter, W. Bartolini, M. Baryshnikov, F. Basels, J.M. Bassi, G. Batsukh, B. Battig, A. Bay, A. Becker, M. Bedeschi, F. Bediaga, I. Beiter, A. Belavin, V. Belin, S. Bellee, V. Belous, K. Belov, I. Belyaev, I. Bencivenni, G. Ben-Haim, E. Berezhnoy, A. Bernet, R. Berninghoff, D. Bernstein, H.C. Bertella, C. Bertholet, E. Bertolin, A. Betancourt, C. Betti, F. Bettler, M.O. Bezshyiko, I. Bhasin, S. Bhom, J. Bian, L. Bieker, M.S. Bifani, S. Billoir, P. Birch, M. Bishop, F.C.R. Bizzeti, A. Bjørn, M. Blago, M.P. Blake, T. Blanc, F. Blusk, S. Bobulska, D. Boelhauve, J.A. Boente Garcia, O. Boettcher, T. Boldyrev, A. Bondar, A. Bondar, N. Borghi, S. Borisyak, M. Borsato, M. Borsuk, J.T. Bouchiba, S.A. Bowcock, T.J.V. Boyer, A. Bozzi, C. Bradley, M.J. Braun, S. Brea Rodriguez, A. Brodski, M. Brodzicka, J. Brossa Gonzalo, A. Brundu, D. Buonaura, A. Burr, C. Bursche, A. Butkevich, A. Butter, J.S. Buytaert, J. Byczynski, W. Cadeddu, S. Cai, H. Calabrese, R. Calefice, L. Calero Diaz, L. Cali, S. Calladine, R. Calvi, M. Calvo Gomez, M. Camargo Magalhaes, P. Camboni, A. Campana, P. Campora Perez, D.H. Campoverde Quezada, A.F. Capelli, S. Capriotti, L. Carbone, A. Carboni, G. Cardinale, R. Cardini, A. Carli, I. Carniti, P. Carus, L. Carvalho Akiba, K. Casais Vidal, A. Casse, G. Cattaneo, M. Cavallero, G. Celani, S. Cerasoli, J. Chadwick, A.J. Chapman, M.G. Charles, M. Charpentier, P. Chatzikonstantinidis, G. Chavez Barajas, C.A. Chefdeville, M. Chen, C. Rio de Janeiro Brazil Rio de Janeiro Brazil Center for High Energy Physics Tsinghua University Beijing China School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China University of Chinese Academy of Sciences Beijing China Beijing China Institute of Particle Physics Central China Normal University WuhanHubei China Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS IN2P3-LAPP Annecy France Université Clermont Auvergne CNRS IN2P3 LPC Clermont-Ferrand France Aix Marseille Univ CNRS IN2P3 CPPM Marseille France Université Paris-Saclay CNRS IN2P3 IJCLab Orsay France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS IN2P3 Paris France I. Physikalisches Institut RWTH Aachen University Aachen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Heidelberg Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany School of Physics University College Dublin Dublin Ireland INFN Sezione di Bari Bari Italy INFN Sezione di Bologna Bologna Italy INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Firenze Firenze Italy INFN Laboratori Nazionali di Frascati Frascati Italy INFN Sezione di Genova Genova Italy INFN Sezione di Milano-Bicocca Milano Italy INFN Sezione di Milano Milano Italy INFN Sezione di Cagliari Monserrato Italy Universita degli Studi di Padova Universita e INFN Padova Padova Italy INFN Sezione di Pisa Pisa Italy INFN Sezione di Roma Tor Vergata Roma Italy INFN Sezione di Roma La Sapienza Roma Italy Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Nikhef National Institute for Subatomic Physics VU University Amsterdam Amsterdam Netherlands Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences Kraków Poland AGH - University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland Warsaw Poland Horia Hulubei National Institute

A search for the Bs0 → D∗±D decay is performed using proton-proton collision data at centre-of-mass energies of 7, 8 and 13 TeV collected by the LHCb experiment, corresponding to an integrated luminosity of 9 fb−1. The decay is observed with a high significance and its branching fraction relative to the B0 → D∗±D decay is measured to be (Equation presented), where the first uncertainty is statistical, the second systematic and the third is due to the uncertainty on the ratio of the Bs0 and B0 hadronisation fractions. © 2020, CC BY.

关键词： Tellurium compounds

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