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Study of ϒ production in pPb collisions at √sNN=8.16 TeV

Journal of High Energy Physics 2018年第11期2018卷 1页

作者： Aaij, R. Abellán Beteta, C. Adeva, B. Adinolfi, M. Aidala, C.A. Ajaltouni, Z. Akar, S. Albicocco, P. Albrecht, J. Alessio, F. Alexander, M. Alfonso Albero, A. Alkhazov, G. Alvarez Cartelle, P. Alves, A.A. Amato, S. Amerio, S. Amhis, Y. An, L. Anderlini, L. Andreassi, G. Andreotti, M. Andrews, J.E. Appleby, R.B. Archilli, F. d’Argent, P. Arnau Romeu, J. Artamonov, A. Artuso, M. Arzymatov, K. Aslanides, E. Atzeni, M. Audurier, B. Bachmann, S. Back, J.J. Baker, S. Balagura, V. Baldini, W. Baranov, A. Barlow, R.J. Barsuk, S. Barter, W. Bartolini, M. Baryshnikov, F. Batozskaya, V. Batsukh, B. Battig, A. Battista, V. Bay, A. Beddow, J. Bedeschi, F. Bediaga, I. Beiter, A. Bel, L.J. Belin, S. Beliy, N. Bellee, V. Belloli, N. Belous, K. Belyaev, I. Ben-Haim, E. Bencivenni, G. Benson, S. Beranek, S. Berezhnoy, A. Bernet, R. Berninghoff, D. Bertholet, E. Bertolin, A. Betancourt, C. Betti, F. Bettler, M.O. van Beuzekom, M. Bezshyiko, Ia. Bhasin, S. Bhom, J. Bifani, S. Billoir, P. Birnkraut, A. Bizzeti, A. Bjørn, M. Blago, M.P. Blake, T. Blanc, F. Blusk, S. Bobulska, D. Bocci, V. Boente Garcia, O. Boettcher, T. Bondar, A. Bondar, N. Borghi, S. Borisyak, M. Borsato, M. Bossu, F. Boubdir, M. Bowcock, T.J.V. Bozzi, C. Braun, S. Brodski, M. Brodzicka, J. Brossa Gonzalo, A. Brundu, D. Buchanan, E. Buonaura, A. Burr, C. Bursche, A. Buytaert, J. Byczynski, W. Cadeddu, S. Cai, H. Calabrese, R. Calladine, R. Calvi, M. Calvo Gomez, M. Camboni, A. Campana, P. Campora Perez, D.H. Capriotti, L. Carbone, A. Carboni, G. Cardinale, R. Cardini, A. Carniti, P. Carson, L. Carvalho Akiba, K. Casse, G. Cassina, L. Cattaneo, M. Cavallero, G. Cenci, R. Chamont, D. Chapman, M.G. Charles, M. Charpentier, Ph. Chatzikonstantinidis, G. Chefdeville, M. Chekalina, V. Chen, C. Chen, S. Chitic, S.-G. Chobanova, V. Chrzaszcz, M. Chubykin, A. Ciambrone, P. Cid Vidal, X. Ciezarek, G. Clarke, P.E.L. Clemencic, M. Cliff, H.V. Closier, J. Coco, V. Coelho, J.A.B. Cogan, J. Cogneras, E. Cojocariu, L. Collins, P. Colombo, T. Comerma-Montells, A. Contu, A. Coombs, G. Centro Brasileiro de Pesquisas Físicas (CBPF) Rio de Janeiro Brazil Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Center for High Energy Physics Tsinghua University Beijing China Institute Of High Energy Physics (ihep) Beijing China Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS IN2P3-LAPP Annecy France Clermont Université Université Blaise Pascal CNRS/IN2P3 LPC Clermont-Ferrand France Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France LAL Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay 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 Max-Planck-Institut für Kernphysik (MPIK) 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 INFN Sezione di 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 and 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 National Center for Nuclear Research (NCBJ) Warsaw Poland Horia Hulubei National Institute of Physics and Nuclear Engineering Bucharest

The production of ϒ(nS) mesons (n = 1, 2, 3) in pPb and Pbp collisions at a centre-of-mass energy per nucleon pair sNN=8.16 TeV is measured by the LHCb experiment, using a data sample corresponding to an integrated luminosity of 31.8 nb⁻¹. The ϒ(nS) mesons are reconstructed through their decays into two opposite-sign muons. The measurements comprise the differential production cross-sections of the ϒ(1S) and ϒ(2S) states, their forward-to-backward ratios and nuclear modification factors. The measurements are performed as a function of the transverse momentum p_T and rapidity in the nucleon-nucleon centre-of-mass frame y^* of the ϒ(nS) states, in the kinematic range p_T < 25 GeV/c and 1.5 < y^* < 4.0 (−5.0 < y^* < −2.5) for pPb (Pbp) collisions. In addition, production cross-sections for ϒ(3S) are measured integrated over phase space and the production ratios between all three ϒ(nS) states are determined. Suppression for bottomonium in proton-lead collisions is observed, which is particularly visible in the ratios. The results are compared to theoretical models.[Figure not available: see fulltext.] © 2018, The Author(s).

关键词： Heavy Ion Experiments

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127.5 kbps Transmission using OLED with 7 kHz 3dB modulation bandwidth in visible light communication system 8

127.5 kbps Transmission using OLED with 7 kHz 3dB modulation...

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8th International Conference on Advanced Technologies for Communications, ATC 2015

作者： Thai, Pham Quang Thanh, Nguyen Trung Shigeru, Shimamoto Liu, Jiang Wende, Zhong Faculty of Electronics and Electrical Engineering Ho Chi Minh City University of Technology Ho Chi Minh Viet Nam Department of Communications and Computer Institute Waseda University Tokyo Japan School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781467383745

In this paper, a visible light communications (VLC) system prototype using OLED was realized and tested. Using simple DPPM technique and comparator, our prototype was able to transmit up to 127.5 kbps data rate using an OLED with only 7 kHz 3 dB modulation bandwidth. Exploiting the frequency response of OLED, we were able to achieve a better data rate to modulation bandwidth ratio than other recent reports using OLED for VLC. © 2015 IEEE.

关键词： Light modulation

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Human Action Recognition using Factorized Spatio-Temporal Convolutional Networks

Human Action Recognition using Factorized Spatio-Temporal Co...

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IEEE International Conference on computer Vision

作者： Lin Sun Kui Jia Dit-Yan Yeung Bertram E. Shi Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Faculty of Science and Technology University of Macau Department of Computer Science and Engineering Hong Kong University of Science and Technology

ISBN: (纸本)9781467383929

Human actions in video sequences are three-dimensional (3D) spatio-temporal signals characterizing both the visual appearance and motion dynamics of the involved humans and objects. Inspired by the success of convolutional neural networks (CNN) for image classification, recent attempts have been made to learn 3D CNNsfor recognizing human actions in videos. However, partly due to the high complexity of training 3D convolution kernels and the need for large quantities of training videos, only limited success has been reported. This has triggered us to investigate in this paper a new deep architecture which can handle 3D signals more effectively. Specifically, we propose factorized spatio-temporal convolutional networks (F_(ST)CN) thatfactorize the original 3D convolution kernel learning as a sequential process of learning 2D spatial kernels in the lower layers (called spatial convolutional layers), followed by learning 1D temporal kernels in the upper layers (called temporal convolutional layers). We introduce a novel transformation and permutation operator to make factorization in F_(ST)CN possible. Moreover to address the issue of sequence alignment, we propose an effective training and inference strategy based on sampling multiple video clips from a given action video sequence. We have tested F_(ST)CN on two commonly used benchmark datasets (UCF-101 and HMDB-51). Without using auxiliary training videos to boost the performance, F_(ST)CN outperforms existing CNN based methods and achieves comparable performance with a recent method that benefits from using auxiliary training videos.

关键词： Training Videos Video sequences Seeds video clips Image classification Sequence Alignment Kernel Three Dimensions factorization

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Dual-Band Balanced BPF With Enhanced Common-Mode Suppression Using Double-Layer Substrate

Dual-Band Balanced BPF With Enhanced Common-Mode Suppression...

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2015年全国微波毫米波会议

作者： Wang Kai Zhu Lei Wong Sai Wai Chen Dong Guo Zaicheng School of Electronic and Information Engineering South China University of Technology Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau School of Electronic Science and Engineering Nanjing University of Posts and Telecommunications

A dual-band balanced bandpass filter(BPF) with enhanced common-mode suppression is proposed in this letter. The dual-band differential-mode(DM) bandpass response is obtained using a double-layer substrate. The stubloaded stepped-impedance resonators(SIRs) are both used in the top and bottom layers to constitute a dual-band BPF with two controllable passbands. The slotline portion in the middle layer is excited under the DM operation. Moreover, the even-symmetrical field along the slotline is highly attenuated under the common-mode(CM) excitation, thus achieving excellent CM suppression over the desired DM passbands. To verify our proposed concept, a balanced dual-band BPF, operating at 1.9 and 2.8 GHz, is designed and fabricated, and the simulated and measured results are in good agreement.

关键词： Balanced filter Dual-band bandpass filter Common-mode suppression

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An Interval Type-2 Fuzzy Logic Based System for Improved Instruction within Intelligent E-Learning Platforms

An Interval Type-2 Fuzzy Logic Based System for Improved Ins...

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IEEE International Conference on Fuzzy Systems

作者： Khalid Almohammadi Bo Yao Abdulkareem Alzahrani Hani Hagras Daniyal Alghazzawi School of Computer Science and Electronic Engineering University of Essex Faculty of Computing and Information Technology King Abdulaziz University

ISBN: (纸本)9781467374293

E-learning is becoming increasingly more popular. However, for such platforms (where the students and tutors are geographically separated), it is necessary to estimate the degree of students' engagement with the course contents. Such feedback is highly important and useful for assessing the teaching quality and adjusting the teaching delivery in large-scale online learning platforms. When the number of attendees is large, it is essential to obtain overall engagement feedback, but it is also challenging to do so because of the high levels of uncertainty associated with the environments and students. To handle such uncertainties, we present a type-2 fuzzy logic based system using visual RGB-D features including head pose direction and facial expressions captured from a low-cost but robust 3D camera (Kinect v2) to estimate the engagement degree of the students for both remote and on-site education. This system enriches another self-learning type-2 fuzzy logic system which provides the instructors with suggestions to vary their teaching means to suit the level of course students and improve the course instruction and delivery. This proposed dynamic e-learning environment involves on-site students, distance students, and a teacher who delivers the lecture to all attending onsite and remote students. The rules are learned from the students' behavior and the system is continuously updated to give the teacher the ability to adapt the lecture delivery instructional approach to varied learners' engagement levels. The efficiency of the proposed system has been evaluated through various real-world experiments in the University of Essex iClassroom on a sample of thirty students and six teachers. These experiments demonstrate the efficiency of the proposed interval type-2 fuzzy logic based system to handle the faced uncertainties and produce superior improved average learners' engagements when compared to type-1 fuzzy systems and nonadaptive systems.

关键词： Interval type-2 fuzzy logic systems Elearning student engagement

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GLPCA: dimensionality reduction for image retrieval

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Journal of Computational Information Systems 2015年第6期11卷 2269-2277页

作者： Feng, Lin Hao, Xiuqi Wang, Huibing School of Computer Science and Technology Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China School of Innovation Experiment Dalian University of Technology Dalian China

With the development of information age, image information has been widely applied in various fields, and content-based image retrieval (CBIR) has become a hot topic to research. However, after extracting the underlying visual image feature, the dimensions of the image feature will be high, which will lead to a higher computation complexity and space complexity in the process of image retrieval. In order to solve this problem, a novel manifold learning algorithm, named globally and locally consistent principal component analysis (GLPCA) algorithm, is proposed. Compared with the traditional dimensionality reduction algorithms such as principal component analysis (PCA) and linear discriminant analysis (LDA), GLPCA considers the global and local characteristics of the data structure comprehensively, and it has better performance on both linear and nonlinear data. The experiment results on Corel image data set show the excellent performance of GLPCA algorithm in image retrieval. Copyright © 2015 Binary Information Press.

关键词： Principal component analysis

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A robust clustering algorithm based on extreme learning machine

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Journal of Information and Computational Science 2015年第13期12卷 4951-4958页

作者： Du, Meng Zhang, Jing Wu, Bin Feng, Lin School of Computer Science and Technology Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China School of Innovation Experiment Dalian University of Technology Dalian China

Original ELM-AE algorithm combines Extreme Learning Machine (ELM) with Auto Encoder (AE) to map data to a nonlinear high-dimensional space. This procedure can extract better sample characteristics when solving unsupervised clustering problems. ELM-AE adopts a solution procedure which is similar to ELM to improve the solution speed. However, ELM-AE has some problems. The solution of the system is not stable because of the random input-layer weights. Meanwhile, if the number of hidden layers is small, model fitting effect will be significantly reduced. To solve the above problems, we propose a Robust ELM-AE (RELM-AE) clustering algorithm. This method trains Restricted Boltzmann Machine (RBM) to get stable input-layer weights, and then minimizes the output error to obtain the output-layer weights. Compared with the original model of ELM-AE, this method achieves more stable and accurate results, which makes it more suitable for solving unsupervised clustering problems. ©, 2015, Journal of Information and Computational Science. All right reserved.

关键词： Clustering algorithms

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Multi-label dimensionality reduction and classification with extreme learning machines

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Journal of Systems engineering and electronics 2014年第3期25卷 502-513页

作者： Lin Feng Jing Wang Shenglan Liu Yao Xiao Faculty of Electronic Information and Electrical Engineering School of Computer Science and TechnologyDalian University of Technology School of Innovation Experiment Dalian University of Technology

In the need of some real applications, such as text categorization and image classification, the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the research of multi-label classification algorithms. Considering the fact that the high dimensionality of the multi-label datasets may cause the curse of dimensionality and wil hamper the classification process, a dimensionality reduction algorithm, named multi-label kernel discriminant analysis （MLKDA）, is proposed to reduce the dimensionality of multi-label datasets. MLKDA, with the kernel trick, processes the multi-label integrally and realizes the nonlinear dimensionality reduction with the idea similar with linear discriminant analysis （LDA）. In the classification process of multi-label data, the extreme learning machine （ELM） is an efficient algorithm in the premise of good accuracy. MLKDA, combined with ELM, shows a good performance in multi-label learning experiments with several datasets. The experiments on both static data and data stream show that MLKDA outperforms multi-label dimensionality reduction via dependence maximization （MDDM） and multi-label linear discriminant analysis （MLDA） in cases of balanced datasets and stronger correlation between tags, and ELM is also a good choice for multi-label classification.

关键词： multi-label dimensionality reduction kernel trick classification.

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RETRACTED ARTICLE: Potential of support vector regression for solar radiation prediction in Nigeria

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Natural Hazards 2015年第2期77卷 1055-1068页

作者： Olatomiwa, Lanre Mekhilef, Saad Shamshirband, Shahaboddin Petkovic, Dalibor Power Electronics and Renewable Energy Research Laboratory (PEARL) Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur Malaysia Department of Electrical and Electronic Engineering Federal University of Technology Minna Nigeria Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Department for Mechatronics and Control Faculty of Mechanical Engineering University of Niš Nis Serbia

In this paper, the accuracy of soft computing technique in solar radiation prediction based on series of measured meteorological data (monthly mean sunshine duration, monthly mean maximum and minimum temperature) taking from Iseyin meteorological station in Nigeria was examined. The process, which simulates the solar radiation with support vector regression (SVR), was constructed. The inputs were monthly mean maximum temperature (Tmax), monthly mean minimum temperature (Tmin) and monthly mean sunshine duration ( $$ \bar{n} $$ ). Polynomial and radial basis functions (RBF) are applied as the SVR kernel function to estimate solar radiation. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR with polynomial basis function compared to RBF. The SVR coefficient of determination R 2 with the polynomial function was 0.7395 and with the radial basis function, the R 2 was 0.5877.

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A new disocclusion filling approach in depth image based rendering for stereoscopic imaging

A new disocclusion filling approach in depth image based ren...

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International Conference on Control, Automation and Information Sciences (ICCAIS)

作者： Hanxiong Yin Liming Zhang Guibo Luo Yuesheng Zhu Faculty of Science and Technology University of Macau Macao China School of Electronic and Computer Engineering Peking University Shenzhen China

ISBN: (纸本)9781479998937

Depth image based rendering (DIBR) is one of the key techniques in converting the 2D videos into the stereoscopic 3D ones. Warping process is the major step in DIBR, which generates the virtual left and right views with a number of black disocclusion areas. The disocclusion filling process is the main task in DIBR. In this paper, an improved disocclusion filling approach is proposed, which is based on the texture and gradient analysis. Inpainting algorithm is applied first based on the background texture and depth information to repair the disocclusion areas, which can be effectively reduce the large sizes of the disocclusion areas. Then a new gradient direction template is proposed and applied to fill the left disocclusion areas. Experiments are conducted to compare with other disocclusion filling approaches. Our results are promising.

关键词： Filling Maintenance engineering Videos Extrapolation Image color analysis Stereo image processing Three-dimensional displays

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