检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Khamis, Sami S. Sulai, Ibrahim A. Hamilton, Paul Afach, S. Buchler, B.C. Budker, D. Figueroa, N.L. Folman, R. Gavilán-Martín, D. Givon, M. Grujić, Z.D. Guo, H. Hedges, M.P. Kimball, D.F. Jackson Kim, D. Klinger, E. Kornack, T. Kryemadhi, A. Kukowski, N. Lukasiewicz, G. Masia-Roig, H. Padniuk, M. Palm, C.A. Park, S.Y. Peng, X. Pospelov, M. Pustelny, S. Rosenzweig, Y. Ruimi, O.M. Segura, P.C. Scholtes, T. Semertzidis, Y.K. Shin, Y.C. Stalnaker, J.E. Tandon, D. Weis, A. Wickenbrock, A. Wilson, T. Wu, T. Zhang, J. Zhao, Y. Department of Physics and Astronomy University of California Los AngelesCA90095 United States Department of Physics and Astronomy Bucknell University LewisburgPA17837 United States Helmholtz Institute Mainz Mainz55099 Germany GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt64291 Germany Johannes Gutenberg-Universität Mainz Mainz55128 Germany Research School of Physics Australian National University CanberraACT2601 Australia Department of Physics University of California BerkeleyCA94720 United States Department of Physics Ben-Gurion University of the Negev Be’er Sheva84105 Israel Institute of Physic Belgrade University of Belgrade Belgrade11080 Serbia State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronics Center for Quantum Information Technology Peking University Beijing100871 China Centre for Quantum Computation and Communication Technology Research School of Physics The Australian National University Acton2601 Australia Department of Physics California State University – East Bay HaywardCA94542-3084 United States Center for Axion and Precision Physics Research IBS Daejeon34051 Korea Republic of Department of Physics KAIST Daejeon34141 Korea Republic of Institut FEMTO-ST UMR 6174 CNRS SupMicroTech-ENSMM Université de Franche-Comté Besançon25030 France Twinleaf LLC 300 Deer Creek Drive PlainsboroNJ08536 United States Department of Computing Math & Physics Messiah University MechanicsburgPA17055 United States Friedrich Schiller University Jena Institute of Geosciences Burgweg 11 JenaD-07749 Germany Institute of Physics Jagiellonian University in Krakow prof. Stanislawa Lojasiewicza 11 Kraków30-348 Poland Jagiellonian University Doctoral School of Exact and Natural Sciences Lojasiewicza 11 Kraków30-348 Poland Department of Physics and Astronomy Oberlin College OberlinOH44074 United States School of Physics and Astronomy University of Minnesota Minneapolis

We present an analysis method to search for exotic low-mass field (ELF) bursts generated during large energy astrophysical events such as supernovae, binary black hole or binary neutron star mergers, and fast radio bursts using the Global Network of Optical Magnetometers for Exotic physics searches (GNOME). In our model, the associated gravitational waves or electromagnetic signals herald the arrival of the ELF burst that interacts via coupling to the spin of fermions in the magnetometers. This enables GNOME to serve as a tool for multi-messenger astronomy. The algorithm employs a model-agnostic excess-power method to identify network-wide candidate events to be subjected to a model-dependent generalized likelihood-ratio test to determine their statistical significance. We perform the first search with this technique on GNOME data coincident with the binary black hole merger S200311bg detected by LIGO/Virgo on the 11th of March 2020 and find no significant events. We place the first lab-based limits on combinations of ELF production and coupling parameters. Copyright © 2024, The Authors. All rights reserved.

关键词： Magnetometers

来源：评论

学校读者我要写书评

暂无评论

Spectrally-Constrained Sequences: Bounds and Constructions

Spectrally-Constrained Sequences: Bounds and Constructions

引用

作者： Liu, Zilong Guan, Yong Liang Parampalli, Udaya Hu, Su School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore 5G Innovation Centre Institute for Communication Systems University of Surrey GuildfordGU2 7XH United Kingdom Department of Computing and Information Systems University of Melbourne MelbourneVIC3010 Australia National Key Laboratory On Communications University of Electronic Science and Technology of China Chengdu611731 China

We investigate spectrally-constrained sequences (SCSs), which are applicable to the communication and radar systems operating over non-contiguous carriers or frequency slots. Typical examples of such systems are overlay cognitive radio or cognitive radar networks. First, we derive the periodic- and aperiodic-correlation lower bounds for single-channel SCSs and multi-channel SCSs by convex optimization in the frequency domain. Each of these bounds reduces to a Welch bound when the number of forbidden carriers is set to zero. We then propose systematic constructions of optimal unimodular single-channel SCSs with the aid of cyclic difference sets and the theory of maximal-length shift register sequences. © 2018 IEEE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Blockchain based Consensus Checking in cloud Storage

Blockchain based Consensus Checking in Cloud Storage

引用

International Symposium on Autonomous Decentralized systems (ISADAS)

作者： Guanqiu Qi Zhiqin Zhu Matthew Haner Jaesung Sim Jian Sun Yi Chai Yinong Chen Li Yongfu Mathematics and Computer Information Science Mansfield University of Pennsylvania Mansfield PA 16933 USA College of Automation Chongqing University of Posts and Telecommunications Chongqing 400065 China School of Electronic and Information Engineering Southwest University Chongqing 400715 China Ministry of Education Key Laboratory of Complex System Safety and Control (Chongqing University) Chongqing 400044 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287 USA

ISBN: (数字)9781728116723

ISBN: (纸本)9781728116730

In cloud computing, data is duplicated to prevent data loss. One way to achieve data consistency in such a distributed computing systems is to use a blockchain. Based on practical Byzantine fault tolerance (PBFT), a specific type of blockchain, this paper proposes a synchronous Byzantine fault tolerance (SBFT) algorithm that not only maintains data consistency, but also has much higher efficiency than other general blockchain algorithms. We provide experimental results that demonstrate the algorithm's data consistency, efficiency, and reliability.

关键词： cloud computing Fault tolerance Fault tolerant systems Peer-to-peer computing

来源：评论

学校读者我要写书评

暂无评论

Pulsar candidate selection using ensemble networks for FAST drift-scan survey

arXiv

引用

arXiv 2019年

作者： Wang, Hongfeng Zhu, Weiwei Guo, Ping Li, Di Feng, Sibo Yin, Qian Miao, Chenchen Tao, Zhenzhao Pan, Zhichen Wang, Pei Zheng, Xin Deng, Xiaodan Liu, Zhijie Xie, Xiaoyao Yu, Xuhong You, Shanping Zhang, Hui Image Processing and Pattern Recognition Laboratory College of Information Science and Technology Beijing Normal University Beijing100875 China CAS Key Laboratory of FAST Chinese Academy of Science Beijing100101 China School of Information Management Dezhou University Dezhou253023 China Image Processing and Pattern Recognition Laboratory School of Systems Science Beijing Normal University Beijing100875 China University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Information and Computing Science Guizhou Province Guizhou Normal University Guiyang550001 China School of Physics and Electronic Science Guizhou Normal University Guiyang550001 China

The Commensal Radio Astronomy Five-hundred-meter Aperture Spherical radio Telescope (FAST) Survey (CRAFTS) utilizes the novel drift-scan commensal survey mode of FAST and can generate billions of pulsar candidate signals. The human experts are not likely to thoroughly examine these signals, and various machine sorting methods are used to aid the classification of the FAST candidates. In this study, we propose a new ensemble classification system for pulsar candidates. This system denotes the further development of the pulsar image-based classification system (PICS), which was used in the Arecibo Telescope pulsar survey, and has been retrained and customized for the FAST drift-scan survey. In this study, we designed a residual network model comprising 15 layers to replace the convolutional neural networks (CNNs) in PICS. The results of this study demonstrate that the new model can sort >96% of real pulsars to belong the top 1% of all candidates and classify > 1.6 million candidates per day using a dual-GPU and 24-core computer. This increased speed and efficiency can help to facilitate real-time or quasi-real-time processing of the pulsar-search data stream obtained from CRAFTS. In addition, we have published the labeled FAST data used in this study online, which can aid in the development of new deep learning techniques for performing pulsar searches. Copyright © 2019, The Authors. All rights reserved.

关键词： Pulsars

来源：评论

学校读者我要写书评

暂无评论

Spatiotemporal Knowledge Distillation for Efficient Estimation of Aerial Video Saliency

arXiv

引用

arXiv 2019年

作者： Li, Jia Fu, Kui Zhao, Shengwei Ge, Shiming State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Institute of Information Engineering Chinese Academy of Sciences Beijing100095 China School of Cyber Security at University of Chinese Academy of Sciences Beijing100095 China

—The performance of video saliency estimation techniques has achieved significant advances along with the rapid development of Convolutional Neural Networks (CNNs). However, devices like cameras and drones may have limited computational capability and storage space so that the direct deployment of complex deep saliency models becomes infeasible. To address this problem, this paper proposes a dynamic saliency estimation approach for aerial videos via spatiotemporal knowledge distillation. In this approach, five components are involved, including two teachers, two students and the desired spatiotemporal model. The knowledge of spatial and temporal saliency is first separately transferred from the two complex and redundant teachers to their simple and compact students, and the input scenes are also degraded from high-resolution to low-resolution to remove the probable data redundancy so as to greatly speed up the feature extraction process. After that, the desired spatiotemporal model is further trained by distilling and encoding the spatial and temporal saliency knowledge of two students into a unified network. In this manner, the inter-model redundancy can be further removed for the effective estimation of dynamic saliency on aerial videos. Experimental results show that the proposed approach outperforms ten state-of-the-art models in estimating visual saliency on aerial videos, while its speed reaches up to 28,738 FPS on the GPU platform. Copyright © 2019, The Authors. All rights reserved.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

The packing problem of uncertain multicasts

The packing problem of uncertain multicasts

引用

作者： Ren, Bangbang Guo, Deke Xie, Junjie Li, Wenxin Yuan, Bo Liu, Yunfei Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha China School of Computer Science and Technology Dalian University of Technology Dalian China Guangxi Cooperative Innovation Center of Cloud Computing and Big Data Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin China

Multicast performs better than unicast in delivering the same content from a fixed single source to a set of destinations. Many efforts have been made to optimize such kind of deterministic multicast, such as minimizing the transmission cost of each multicast session. In practice, it is not necessary that the source of each multicast session has to be in a specific location, as long as certain constraints are satisfied. Accordingly, applications usually meet a novel multicast with uncertain sources, ie, uncertain multicast. That is, multiple nodes have the responsibility to act as the root node of a multicast session. Prior proposals have addressed an uncertain multicast by constructing the minimum cost forest. However, it is still unknown how to efficiently share the network resources, when a set of uncertain multicast occupies the network simultaneously. To tackle such a challenging issue, we present the packing problem of uncertain multicasts (MPU) to minimize the total transmission cost, under the constraint of link capacity. We prove that the MPU problem is NP-hard. An intrinsic solution is constructing the minimum cost forest for each uncertain multicast individually. This method, however, is inefficient and may be infeasible because of the constraint of link capacity. Thus, we design 2 dedicated greedy methods, named priority-based and adjusting congested link, to approximate the optimal solution. The comprehensive results indicate that both of our 2 methods can find a feasible solution for the MPU problem. Moreover, given a set of uncertain multicasts, the adjusting congested link method can generate a desired transmission structure for each uncertain multicast and achieve the least total cost when packing them. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： Routing algorithms

来源：评论

学校读者我要写书评

暂无评论

GPU PaaS computation model in aneka cloud computing environments

arXiv

引用

arXiv 2018年

作者： Ilager, Shashikant Wankar, Rajeev Kune, Raghavendra Buyya, Rajkumar Laboratory School of Computing and Information Systems University of Melbourne Australia School of Computer and Information Sciences University of Hyderabad Hyderabad India Advanced Data Processing Research Institute Department of Space Secunderabad India

Due to the surge in the volume of data generated and rapid advancement in Artificial Intelligence (AI) techniques like machine learning and deep learning, the existing traditional computing models have become inadequate to process an enormous volume of data and the complex application logic for extracting intrinsic information. computing accelerators such as Graphics processing units (GPUs) have become de facto SIMD computing system for many big data and machine learning applications. On the other hand, the traditional computing model has gradually switched from conventional ownership-based computing to subscription-based cloud computing model. However, the lack of programming models and frameworks to develop cloud-native applications in a seamless manner to utilize both CPU and GPU resources in the cloud has become a bottleneck for rapid application development. To support this application demand for simultaneous heterogeneous resource usage, programming models and new frameworks are needed to manage the underlying resources effectively. Aneka is emerged as a popular PaaS computing model for the development of cloud applications using multiple programming models like Thread, Task, and MapReduce in a single *** platform. Since, Aneka addresses MIMD application development that uses CPU based resources and GPU programming like CUDA is designed for SIMD application development, here, the chapter discusses GPU PaaS computing model for Aneka clouds for rapid cloud application development *** platforms. The popular opensource GPU libraries are utilized and integrated it into the existing Aneka task programming model. The scheduling policies are extended that automatically identify GPU machines and schedule respective tasks accordingly. A case study on image processing is discussed to demonstrate the system, which has been built using PaaS Aneka SDKs and CUDA library. Copyright © 2018, The Authors. All rights reserved.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

Perspectives on adaptive dynamical systems

arXiv

引用

arXiv 2023年

作者： Sawicki, Jakub Berner, Rico Loos, Sarah A.M. Anvari, Mehrnaz Bader, Rolf Barfuss, Wolfram Botta, Nicola Brede, Nuria Franović, Igor Gauthier, Daniel J. Goldt, Sebastian Hajizadeh, Aida Hövel, Philipp Karin, Omer Lorenz-Spreen, Philipp Miehl, Christoph Mölter, Jan Olmi, Simona Schöll, Eckehard Seif, Alireza Tass, Peter A. Volpe, Giovanni Yanchuk, Serhiy Kurths, Jürgen Potsdam Institute for Climate Impact Research Telegrafenberg Potsdam14473 Germany Fachhochschule Nordwestschweiz FHNW Leonhardsstrasse 6 Basel4009 Switzerland Department of Physics Humboldt-Universität zu Berlin Newtonstraße 15 Berlin12489 Germany DAMTP University of Cambridge Wilberforce Road CambridgeCB3 0WA United Kingdom Fraunhofer Institute for Algorithms and Scientific Computing Schloss Birlinghoven Sankt-Augustin53757 Germany Institute of Systematic Musicology University of Hamburg Germany Transdisciplinary Research Area: Sustainable Futures University of Bonn Bonn53113 Germany University of Bonn Bonn53113 Germany Department of Computer Science and Engineering Chalmers University of Technology Göteborg412 96 Sweden Department of Computer Science University of Potsdam An der Bahn 2 Potsdam14476 Germany Scientific Computing Laboratory Center for the Study of Complex Systems Institute of Physics Belgrade University of Belgrade Pregrevica 118 Belgrade11080 Serbia The Ohio State University Department of Physics and Electrical and Computer Engineering 191 West Woodruff Ave ColumbusOH43210 United States ResCon Technologies LLC 1275 Kinnear Rd. Suite 239 ColumbusOH43212 United States Trieste Italy Research Group Comparative Neuroscience Leibniz Institute for Neurobiology Magdeburg Germany Theoretical Physics Saarland University Saarbrücken66123 Germany Center for Biophysics Saarland University Saarbrücken66123 Germany Department of Mathematics Imperial College London United Kingdom Center for Adaptive Rationality Max Planck Institute for Human Development Lentzeallee 94 Berlin14195 Germany Max Planck Institute for Brain Research Max-von-Laue-Straße 4 Frankfurt am Main60438 Germany Technical University of Munich School of Life Sciences Alte Akademie 8 Freising85354 Germany Department of Mathematics School of Computation Information and Technology Technical University of Munich Boltzmannstraße 3 Garching bei München8574

Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems like the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges, and give perspectives on future research directions, looking to inspire interdisciplinary approaches. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamical systems

来源：评论

学校读者我要写书评

暂无评论

An API for development of user-defined scheduling algorithms in aneka PaaS cloud software: user defined schedulers in aneka PaaS cloud software

arXiv

引用

arXiv 2018年

作者： Sandhu, Rajinder Toosi, Adel Nadjaran Buyya, Rajkumar CLOUDS Laboratory School of Computing and Information Systems University of Melbourne Australia Department of Computer Science and Engineering Jaypee University of Information Technology Waknaghat India Faculty of Information Technology Monash University Australia

cloud computing has been developed as one of the prominent paradigm for providing on demand resources to the end user based on signed service level agreement and pay as use model. cloud computing provides resources using multitenant architecture where infrastructure is generated from multiple or single geographical distributed cloud datacenters. Scheduling of cloud application requests to cloud infrastructure is one of the main research area in cloud computing. Researchers have developed many scheduling applications for which they have used different simulators available in the market such as cloudSim. Performance of any scheduling algorithm will be different when applied to real time cloud environment as compared to simulation software. Aneka is one of the prominent PaaS software which allows users to develop cloud application using various programming models and underline infrastructure. In this chapter, a scheduling API is developed over the Aneka software platform which can be easily integrated with the Aneka software. Users can develop their own scheduling algorithms using this API and integrate it with Aneka software so that they can test their scheduling algorithm in real cloud environment. The proposed API provides all the required functionalities to integrate and schedule private, public or hybrid cloud with the Aneka software. Copyright © 2018, The Authors. All rights reserved.

关键词： Scheduling

来源：评论

学校读者我要写书评

暂无评论

Building quantum neural networks based on a swap test

引用

Physical Review A 2019年第1期100卷 012334-012334页

作者： Jian Zhao Yuan-Hang Zhang Chang-Peng Shao Yu-Chun Wu Guang-Can Guo Guo-Ping Guo Key Laboratory of Quantum Information Chinese Academy of Sciences School of Physics University of Science and Technology of China Hefei Anhui 230026 People's Republic of China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei Anhui 230026 People's Republic of China School of the Gifted Young University of Science and Technology of China Hefei Anhui 230026 People's Republic of China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China Origin Quantum Computing Hefei Anhui 230026 People's Republic of China

An artificial neural network, consisting of many neurons in different layers, is an important method to simulate the human brain. Usually, one neuron has two operations: one is linear, the other is nonlinear. The linear operation is the inner product and the nonlinear operation is represented by an activation function. In this work, we introduce a kind of quantum neuron whose inputs and outputs are quantum states. The inner product and activation operator of the quantum neurons can be realized by quantum circuits. Based on the quantum neuron, we propose a model of a quantum neural network in which the weights between neurons are all quantum states. We also construct a quantum circuit to realize this quantum neural network model. A learning algorithm is proposed meanwhile. We show the validity of the learning algorithm theoretically and demonstrate the potential of the quantum neural network numerically.

关键词： Machine learning Quantum gates

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：