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作者： Tang, Jianhua Quek, Tony Q. S. Chang, Tsung-Hui Shim, Byonghyo Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Normal University Changsha410081 China Institute of New Media and Communications Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore487372 Singapore Department of Electronic Engineering Kyung Hee University Yongin17104 Korea Republic of School of Science and Engineering Chinese University of Hong Kong Shenzhen518172 China Shenzhen Research Institute of Big Data Shenzhen518172 China Department of Electrical and Computer Engineering Institute of New Media and Communications Seoul National University Seoul08826 Korea Republic of

Recently, cloud radio access network (C-RAN) with caching as a service (CaaS) was proposed to merge the functionalities of communication, computing, and caching (CCC) together. In this paper, we dissect the interactions of CCC in C-RAN with CaaS from two dimensions: physical resource dimension and time dimension. In the physical resource dimension, we identify how to segment the baseband unit (BBU) pool resources (i.e., computation and storage) into different types of virtual machines (VMs). In the time dimension, we address how the long-term resource segmentation in the BBU pool impacts on the short-term transmit beamforming at the remote radio heads. We formulate the problem as a stochastic mixed-integer nonlinear programming (SMINLP) to minimize the system cost, including the server cost, VM cost and wireless transmission cost. After a series of approximation, including sample average approximation, successive convex approximation, and semidefinite relaxation, the SMINLP is approximated as a global consensus problem. The alternating direction method of multipliers (ADMM) is utilized to obtain the solution in a parallel fashion. Simulation results verify the convergence of our proposed algorithm, and also confirm that the proposed scheme is more cost-saving than that without considering the integration of CCC. © 1972-2012 IEEE.

关键词： Integer programming

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Adaptive Multi-Feature Budgeted Profit Maximization in Social Networks

arXiv

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arXiv 2020年

作者： Chen, Tiantian Guo, Jianxiong Wu, Weili The Department of Computer Science Erik Jonsson School of Engineering and Computer Science University of Texas at Dallas RichardsonTX75080 United States The BNU-UIC Institute of Artificial Intelligence and Future Networks Beijing Normal University at Zhuhai Guangdong Zhuhai519087 China The Guangdong Key Lab of AI and Multi-Modal Data Processing BNU-HKBU United International College Guangdong Zhuhai519087 China

Online social network has been one of the most important platforms for viral marketing. Most of existing researches about diffusion of adoptions of new products on networks are about one diffusion. That is, only one piece of information about the product is spread on the network. However, in fact, one product may have multiple features and the information about different features may spread independently in social network. When a user would like to purchase the product, he would consider all of the features of the product comprehensively not just consider one. Based on this, we propose a novel problem, multi-feature budgeted profit maximization (MBPM) problem, which first considers budgeted profit maximization under multiple features propagation of one product. Given a social network with each node having an activation cost and a profit, MBPM problem seeks for a seed set with expected cost no more than the budget to make the total expected profit as large as possible. We mainly consider MBPM problem under the adaptive setting, where seeds are chosen iteratively and next seed is selected according to current diffusion results. We study adaptive MBPM problem under two models, oracle model and noise model. The oracle model assumes conditional expected marginal profit of any node could be obtained in O(1) time and a (1 − 1/e) expected approximation policy is proposed. Under the noise model, we estimate conditional expected marginal profit of a node by modifying the EPIC algorithm and propose an efficient policy, which could achieve a (1 − e−(1−∊)) expected approximation ratio. Several experiments are conducted on six realistic datasets to compare our proposed policies with their corresponding non-adaptive algorithms and some heuristic adaptive policies. Experimental results show efficiencies and superiorities of our policies. Copyright © 2020, The Authors. All rights reserved.

关键词： Diffusion

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Experimental Study on Flow Characteristics in a Compound Open Channel with Flexible Vegetation

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IOP Conference Series: Earth and Environmental Science 2021年第1期697卷

作者： Xiaoxiao Guo Hefang Jing Weihong Wang Juntao Wu Qiaoling Zhang Research Institute of Numerical Computation and Engineering Applications North Minzu University Yinchuan China School of Mathematics and Information Science North Minzu University Yinchuan China The Key Laboratory of Intelligent Information and Big Data Processing of Ningxia Province North Minzu University Yinchuan China

In order to study the effect of flexible vegetation for the flow in open channels with flood plains, a series of experiments were carried out in a laboratory flume with a two-stage floodplain. Four cases, i.e., dense parallel arrangement, normal parallel arrangement, sparse parallel arrangement and no vegetation condition, were designed with fixed water depth and discharge. By using three dimensional (3D) laser Doppler velocimeter (LDV) and other instruments, under the condition of the four cases,3D flow velocities, water level and turbulence intensity were measured, The experimental results show that, compared with the non-vegetation situation, the arrangement of grasses on the floodplain will increase the water surface gradient, hydraulic gradient and turbulence intensity to a certain extent.

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Investigation of the Salinity Distribution of the Soil along West Main Canal in Ningxia, China

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IOP Conference Series: Earth and Environmental Science 2021年第1期697卷

作者： Juntao Wu Hefang Jing Weihong Wang Xiaoxiao Guo Xinxia Guo Research Institute of Numerical Computation and Engineering Applications North Minzu University Yinchuan China School of Mathematics and Information Science North Minzu University Yinchuan China The Key Laboratory of Intelligent Information and Big Data Processing of Ningxia Province North Minzu University Yinchuan China

As one of the main irrigation canals in Ningxia, West Main Canal plays a very important role in the irrigation of the land nearby the canal, such as farms, meadows, and tree farms. Because of the long-term use of the Yellow River water for irrigation, the soil salinization in this area become more serious. In this paper, the problem of soil salinization along the West Main Canal in Ningxia is taken as the research object. 82 sample points in the studied area are chosen and a total number of 164 soil samples are measured for the eight main salt ions and pH value. Correlation analysis and principal component analysis are employed to study the distribution of the soil salinity ions and pH value. In addition, two dimensional interpolation is applied to obtain the spatial distribution of the total saltiness. It can be found that Cl−, SO42−, Ca2+, Na+ and HCO3− are the main salt ions and the main soluble salts are NaCl, KCl, CaSO4, Na2SO4 and CaCl2 in the soil of the studied area. The spatial distribution of the total soil salt is mainly in the patterns of north high and south low, far high and near low, up high and down low.

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The First GECAM Observation Results on Terrestrial Gamma-ray Flashes and Terrestrial Electron Beams

arXiv

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arXiv 2023年

作者： Zhao, Y. Liu, J.C. Xiong, S.L. Xue, W.C. Yi, Q.B. Lu, G.P. Xu, W. Lyu, F.C. Sun, J.C. Peng, W.X. Zheng, C. Zhang, Y.Q. Cai, C. Xiao, S. Xie, S.L. Wang, C.W. Tan, W.J. An, Z.H. Chen, G. Du, Y.Q. Huang, Y. Gao, M. Gong, K. Guo, D.Y. He, J.J. Li, B. Li, G. Li, X.Q. Li, X.B. Liao, J.Y. Liang, J. Liang, X.H. Liu, Y.Q. Ma, X. Qiao, R. Song, L.M. Song, X.Y. Sun, X.L. Wang, J. Wang, J.Z. Wang, P. Wen, X.Y. Wu, H. Xu, Y.B. Yang, S. Zhang, B.X. Zhang, D.L. Zhang, F. Zhang, P. Zhang, H.M. Zhang, Z. Zhao, X.Y. Zheng, S.J. Zhang, K.K. Han, X.B. Wu, H.Y. Hu, T. Geng, H. Zhang, H.B. Lu, F.J. Zhang, S.N. Yu, H. Department of Astronomy Beijing Normal University Beijing Beijing100875 China Key Laboratory of Particle Astrophysics Institute of High Energy Physics Chinese Academy of Sciences Beijing Beijing100049 China University of Chinese Academy of Sciences Beijing Beijing100049 China School of Physics and Optoelectronics Xiangtan University Hunan Xiangtan411105 China School of Earth and Space Sciences University of Science and Technology of China Anhui Hefei230026 China Electronic Information School Wuhan University Hubei Wuhan430072 China Key Laboratory of Transportation Meteorology of China Meteorological Administration Nanjing Joint Institute for Atmospheric Sciences Jiangsu Nanjing210000 China College of Physics Hebei Key Laboratory of Photophysics Research and Application Hebei Normal University Hebei Shijiazhuang050024 China Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University GuiZhou Guiyang550001 China School of Physics and Electronic Science Guizhou Normal University GuiZhou Guiyang550001 China Institute of Astrophysics Central China Normal University HuBei Wuhan430079 China School of Computing and Artificial Intelligence Southwest Jiaotong University SiChuan Chengdu611756 China College of Electronic and Information Engineering Tongji University Shanghai Shanghai201804 China Innovation Academy for Microsatellites Chinese Academy of Sciences Shanghai Shanghai201304 China National Space Science Center Chinese Academy of Sciences Beijing Beijing100190 China Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing Beijing100029 China

Gravitational-wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a space-borne instrument dedicated to monitoring high-energy transients, including Terrestrial Gamma-ray Flashes (TGFs) and Terrestrial Electron Beams (TEBs). We implemented a TGF/TEB search algorithm for GECAM, with which 147 bright TGFs, 2 typical TEBs and 2 special TEB-like events are identified during an effective observation time of ∼9 months. We show that, with gamma-ray and charged particle detectors, GECAM can effectively identify and distinguish TGFs and TEBs, and measure their temporal and spectral properties in detail. A very high TGF-lightning association rate of ∼80% is obtained between GECAM and GLD360 in east Asia region. Copyright © 2023, The Authors. All rights reserved.

关键词： Electron beams

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Deep-learning based motion-corrected image reconstruction in 4D magnetic resonance imaging of the body trunk

Deep-learning based motion-corrected image reconstruction in...

引用

Asia-Pacific Signal and Information processing Association Annual Summit and Conference (APSIPA)

作者： Thomas Küstner Jiazhen Pan Christopher Gilliam Haikun Qi Gastao Cruz Kerstin Hammernik Bin Yang Thierry Blu Daniel Rueckert René Botnar Claudia Prieto Sergios Gatidis Medical Image And Data Analysis (MIDAS) Tübingen Germany School of Biomedical Engineering and Imaging Sciences King’s College London St. Thomas’ Hospital London UK Institute of Signal Processing and System Theory University of Stuttgart Stuttgart Germany RMIT University Melbourne Australia Imperial College London London United Kingdom Chinese University Hong Kong Hong Kong Hong Kong

ISBN: (数字)9789881476883

ISBN: (纸本)9781728181301

Respiratory and cardiac motion can cause artifacts in magnetic resonance imaging of the body trunk if patients cannot hold their breath or triggered acquisitions are not practical. Retrospective correction strategies usually cope with motion by fast imaging sequences with integrated motion tracking under free-movement conditions. These acquisitions perform sub-Nyquist sampling and retrospectively bin the data into the respective motion states, yielding subsampled and motion-resolved k-space data. The motion-resolved k-spaces are linked to each other by non-rigid deformation fields. The accurate estimation of such motion is thus an important task in the successful correction of respiratory and cardiac motion. Usually this problem is formulated in image space via diffusion, parametric-spline or optical flow methods. Image-based registration can be however impaired by aliasing artifacts or by estimation from low-resolution images. Subsequently, any motion-corrected reconstruction can be biased by errors in the deformation fields. In this work, we propose a novel deep-learning based motion-corrected 4D (3D spatial + time) image reconstruction which combines a non-rigid registration network and a(3+1)D reconstruction network. Non-rigid motion is estimated directly in k-space based on an optical flow idea and incorporated into the reconstruction network. The proposed method is evaluated on in-vivo 4D motion-resolved magnetic resonance images of patients with suspected liver or lung metastases and healthy subjects.

关键词： Image reconstruction Three-dimensional displays Strain Imaging Two dimensional displays Magnetic resonance imaging Estimation

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Visual Tracking Algorithm Based on Color Name Histogram

Visual Tracking Algorithm Based on Color Name Histogram

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作者： Chenchen Yue Wangsheng Yu Zhiqiang Hou Sugang Ma College of Computer Science and Technology Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Information and Navigation Institute of Air Force Engineering University

Aimed at the problem that traditional histogram is sensitive to illumination changes in visual tracking,combined with the CN(Color Name) feature,we proposed a new feature(denotes CNH,Color Name Histogram) based on color ***,the method projected the original RGB image to CN space to obtain robust 11 feature ***,we counted the each pixel numbers of feature ***,normalizing the amount of pixels in each *** addition,we adopted a feature adaptive fusion method to combine CNH and HOG(Histogram of Oriented Gradient).In order to prove validity of the proposed algorithm,we use Staple(Sum of Template And Pixel-wise Learners) algorithm frame to make a controlled *** contrast with the reference algorithms,the success of our algorithm increases by 1.5% and the precision increases by 1.7%.The results show that this method retains the advantages of traditional histogram which is insensitive to target deformation,but also enhances the robustness to illumination change.

关键词： Visual tracking Color histogram Color name Feature fusion

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The background model of the CUPID-Mo0vββ experiment

arXiv

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arXiv 2023年

作者： Augier, C. Barabash, A.S. Bellini, F. Benato, G. Beretta, M. Bergé, L. Billard, J. Borovlev, Yu A. Cardani, L. Casali, N. Cazes, A. Celi, E. Chapellier, M. Chiesa, D. Dafinei, I. Danevich, F.A. De Jesus, M. de Marcillac, P. Dixon, T. Dumoulin, L. Eitel, K. Ferri, F. Fujikawa, B.K. Gascon, J. Gironi, L. Giuliani, A. Grigorieva, V.D. Gros, M. Helis, D.L. Huang, H.Z. Huang, R. Imbert, L. Johnston, J. Juillard, A. Khalife, H. Kleifges, M. Kobychev, V.V. Kolomensky, Yu G. Konovalov, S.I. Kotila, J. Loaiza, P. Ma, L. Makarov, E.P. Mariam, R. Marini, L. Marnieros, S. Navick, X.-F. Nones, C. Norman, E.B. Olivieri, E. Ouellet, J.L. Pagnanini, L. Pattavina, L. Paul, B. Pavan, M. Peng, H. Pessina, G. Pirro, S. Poda, D.V. Polischuk, O.G. Pozzi, S. Previtali, E. Redon, Th Rojas, A. Rozov, S. Sanglard, V. Scarpaci, J.A. Schmidt, B. Shen, Y. Shlegel, V.N. Singh, V. Tomei, C. Tretyak, V.I. Umatov, V.I. Vagneron, L. Velázquez, M. Welliver, B. Winslow, L. Xue, M. Yakushev, E. Zarytskyy, M. Zolotarova, A.S. Université Lyon 1 CNRS IN2P3 IP2I-Lyon VilleurbanneF-69622 France National Research Centre Kurchatov Institute Kurchatov Complex of Theoretical and Experimental Physics Moscow117218 Russia Dipartimento di Fisica Sapienza Università di Roma P.le Aldo Moro 2 RomeI-00185 Italy INFN Sezione di Roma Tor Vergata Via della Ricerca Scientifica 1 RomeI-00133 Italy Gran Sasso Science Institute L’AquilaI-67100 Italy AssergiI-67100 Italy Department of Physics University of California BerkeleyCA94720 United States Université Paris-Saclay CNRS IN2P3 IJCLab Orsay91405 France Nikolaev Institute of Inorganic Chemistry Novosibirsk630090 Russia Dipartimento di Fisica Università di Milano-Bicocca MilanoI-20126 Italy INFN Sezione di Milano-Bicocca MilanoI-20126 Italy Institute for Nuclear Research of NASU Kyiv03028 Ukraine Institute for Astroparticle Physics Karlsruhe Institute of Technology Karlsruhe76021 Germany Nuclear Science Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States IRFU CEA Université Paris-Saclay Gif-sur-YvetteF-91191 France Fudan University Shanghai200433 China Massachusetts Institute of Technology CambridgeMA02139 United States Institute for Data Processing and Electronics Karlsruhe Institute of Technology Karlsruhe76021 Germany Department of Physics University of Jyväskylä PO Box 35 JyväskyläFI-40014 Finland Finnish Institute for Educational Research University of Jyväskylä P.O. Box 35 JyväskyläFI-40014 Finland Center for Theoretical Physics Sloane Physics Laboratory Yale University New HavenCT06520-8120 United States Department of Nuclear Engineering University of California BerkeleyCA94720 United States Physik Department Technische Universität München GarchingD-85748 Germany Department of Modern Physics University of Science and Technology of China Hefei230027 China LSM Laboratoire Souterrain de Modane Modane73500 France Laboratory of Nuclear Problems JINR Moscow region Dubn

CUPID-Mo, located in the Laboratoire Souterrain de Modane (France), was a demonstrator for the next generation 0vββ decay experiment, CUPID. It consisted of an array of 20 enriched Li2100MoO4 bolometers and 20 Ge light detectors and has demonstrated that the technology of scintillating bolometers with particle identification capabilities is mature. Furthermore, CUPID-Mo can inform and validate the background prediction for CUPID. In this paper, we present a detailed model of the CUPID-Mo backgrounds. This model is able to describe well the features of the experimental data and enables studies of the 2vββ decay and other processes with high precision. We also measure the radio-purity of the Li2100MoO4 crystals which are found to be sufficient for the CUPID goals. Finally, we also obtain a background index in the region of interest of 3.7 −0.8+0.9 (stat)+1.5−0.7 (syst) × 10−3 counts/ΔEFWHM/moliso/yr, the lowest in a bolometric 0vββ decay experiment. Copyright © 2023, The Authors. All rights reserved.

关键词： Bolometers

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Correction: The role of [68Ga]Ga-PSMA PET/CT in primary staging of newly diagnosed prostate cancer: predictive value of PET-derived parameters for risk stratification through machine learning

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Clinical and Translational Imaging 2024年第1期13卷 93-93页

作者： Jafari, Esmail Dadgar, Habibollah Zarei, Amin Samimi, Rezvan Manafi-Farid, Reyhaneh Divband, GhasemAli Nikkholgh, Babak Fallahi, Babak Amini, HamidReza Ahmadzadehfar, Hojjat Keshavarz, Ahmad Assadi, Majid The Persian Gulf Nuclear Medicine Research Center Department of Nuclear Medicine Molecular Imaging and Theranostics School of Medicine Bushehr Medical University Hospital Bushehr University of Medical Sciences Bushehr Iran Cancer Research Center RAZAVI Hospital Imam Reza International University Mashhad Iran Khatam PET/CT Center Tehran Iran Research Center for Nuclear Medicine Shariati Hospital Tehran University of Medical Sciences Tehran Iran Department of Nuclear Medicine Klinikum Westfalen Dortmund Germany Department of Nuclear Medicine Institute of Radiology Neuroradiology and Nuclear Medicine University Hospital Knappschaftskrankenhaus Bochum Germany IoT and Signal Processing Research Group ICT Research Institute Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran

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基于MeerKAT和FAST探索球状星团:脉冲星偏振研究（英文）

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Science Bulletin 2025年第10期 1568-1571页

作者：张蕾 Federico Abbate 李菂 Andrea Possenti Matthew Bailes Alessandro Ridolfi Paulo C.C.Freire Scott M.Ransom 张永坤郭猛尼盟萌胡佳乐冯毅王培张洁支启军 National Astronomical Observatories Chinese Academy of Sciences Centre for Astrophysics and Supercomputing Swinburne University of Technology INAF-Osservatorio Astronomico di Cagliari Max-Planck-Institut für Radioastronomie New Cornerstone Science Laboratory Department of AstronomyTsinghua University ARC Center of Excellence for Gravitational Wave Discovery (OzGrav) Swinburne University of Technology Faculty of Physics University of Bielefeld National Radio Astronomy Observatory National Supercomputing Center in Jinan Qilu University of Technology Jinan Institute of Supercomputing Technology Research Center for Intelligent Computing Platforms Zhejiang Laboratory Institute for Astronomy School of PhysicsZhejiang University College of Physics and Electronic Engineering Qilu Normal University Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guizhou Normal University

Magnetic fields are pervasive throughout the Universe. They are integral to a wide array of astrophysical processes that span various physical scales and field strengths. The Galactic magnetic field,in particular, holds significant importance in shaping the evolution of our Galaxy. However, our understanding of its behavior on small scales remains poor, especially when considering its penetration into the Galactic halo [1].

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