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Journal of Network Intelligence 2020年第4期5卷 218-225页

作者： Ye, Li Meng, Xiaojing Hang, Yongxin Tayeb, Shahab School of Architecture and Design China University of Mining and Technology No1 Daxue Road XuzhouJiangsu China School of Medical Information and Engineering Xuzhou Medical University No 209 Tongshan Road XuzhouJiangsu China China University of Mining and Technology No1 Daxue Road XuzhouJiangsu China Department of Electrical and Computer Engineering California State University Fresno United States

In order to improve the quality of student online education associated to the area of art literacy, it is necessary to track and identify their browsing data processes in real time. A visual tracking method for such activity, based on Hilbert’s spectrum anal-ysis, is proposed. A data mining model, a platform for online education that supports art literacy, has been constructed. The approach utilizes the spectral feature extraction method for data visualization pattern recognition, and Hilbert’s spectrum feature extraction algorithm. By using information fusion and feature matching, students in the same time period are scanned for spectral feature fusion and adaptive matching, and the fea-tures of Hilbert’s spectrum are extracted by segmentation. The extracted information is processed by visual spectral feature recognition, information recovery is realized, and visual tracking of browsing data for the cohort completed. The simulation results show that this method can effectively realize visual tracking and recognition of the students’ browsing data and improve the ability of data mining and information analysis. The research aims to show that the quality of online education of artistic literacy is improved through such practice. © 2020, Taiwan Ubiquitous Information. All rights reserved.

关键词： Data mining

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Localized resolution of identity approach to the analytical gradients of random-phase approximation ground-state energy: Algorithm and benchmarks

arXiv

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arXiv 2021年

作者： Tahir, Muhammad N. Li, Jia Zhu, Tong Shang, Honghui Blum, Volker Ren, Xinguo Guangdong Provincial Key Laboratory of Thermal Management Engineering and Materials Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of Chemistry Duke University DurhamNC27708 United States State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China

We develop and implement a formalism which enables calculating the analytical gradients of particle-hole random-phase approximation (RPA) ground-state energy with respect to the atomic positions within the atomic orbital basis set framework. Our approach is based on a localized resolution of identity (LRI) approximation for evaluating the two-electron Coulomb integrals and their derivatives, and the density functional perturbation theory for computing the first-order derivatives of the Kohn-Sham (KS) orbitals and orbital energies. Our implementation allows one to relax molecular structures at the RPA level using both Gaussian-type orbitals (GTOs) and numerical atomic orbitals (NAOs). Benchmark calculations show that our approach delivers high numerical precision compared to previous implementations. A careful assessment of the quality of RPA geometries for small molecules reveals that post-KS RPA systematically overestimates the bond lengths. We furthermore optimized the geometries of the four low-lying water hexamers – cage, prism, cyclic and book isomers, and determined the energy hierarchy of these four isomers using RPA. The obtained RPA energy ordering is in good agreement with that yielded by the coupled cluster method with single, double and perturbative triple excitations, despite that the dissociation energies themselves are appreciably underestimated. The underestimation of the dissociation energies by RPA is well corrected by the renormalized single excitation correction. © 2021, CC BY.

关键词： Approximation algorithms

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Preface

Smart Innovation, Systems and Technologies

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Smart Innovation, Systems and Technologies 2021年 197卷 vii-viii页

作者： Mealha, Óscar Rehm, Matthias Rebedea, Traian Department of Communication and Art Digital Media and Interaction Research Center University of Aveiro Aveiro Portugal Department of Computer Science University Politehnica of Bucharest Bucharest Romania Department of Architecture Design and Media Technology Aalborg University Aalborg Denmark

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A Pipelining Loop Optimization Method for Dataflow architecture

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Journal of computer Science & technology 2018年第1期33卷 116-130页

作者： Xu Tan Xiao-Chun Ye Xiao-Wei Shen Yuan-Chao Xu Da Wang Lunkai Zhang Wen-Ming Li Dong-Rui Fan Zhi-Min Tang State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 1000J9 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125 China College of Information Engineering Capital Normal University Beijing 100048 China Department of Computer Science The University of Chicago Chicago IL 60637 U.S.A.

With the coming of exascale supercomputing era, power efficiency has become the most important obstacle to build an exascale system. Dataflow architecture has native advantage in achieving high power efficiency for scientific applications. However, the state-of-the-art dataflow architectures fail to exploit high parallelism for loop processing. To address this issue, we propose a pipelining loop optimization method （PLO）, which makes iterations in loops flow in the processing element （PE） array of dataflow accelerator. This method consists of two techniques, architecture-assisted hardware iteration and instruction-assisted software iteration. In hardware iteration execution model, an on-chip loop controller is designed to generate loop indexes, reducing the complexity of computing kernel and laying a good f（mndation for pipelining execution. In software iteration execution model, additional loop instructions are presented to solve the iteration dependency problem. Via these two techniques, the average number of instructions ready to execute per cycle is increased to keep floating-point unit busy. Simulation results show that our proposed method outperforms static and dynamic loop execution model in floating-point efficiency by 2.45x and 1.1x on average, respectively, while the hardware cost of these two techniques is acceptable.

关键词： dataflow model control-flow model loop optimization exascale computing scientific application

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Energy-consumption prediction of genetic programming algorithms using a fuzzy rule-based system 18

Energy-consumption prediction of genetic programming algorit...

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2018 Genetic and Evolutionary Computation Conference, GECCO 2018

作者： Chávez, F. Fdez De Vega, F. Díaz, J. García, J.A. Rodriguez, F.J. Castillo, P.A. Centro Universitario de Mérida Universidad de Extremadura Spain Department of Architecture and Computer Technology University of Granada Spain

ISBN: (纸本)9781450357647

Energy awareness has gained momentum over the last decade in the software industry, as well as in environmentally concious society. Thus, algorithm designers and programmers are paying increasing attention this issue, particularly when handheld devices are considered, given their battery-consuming characteristics. When we focus on Evolutionary Algorithms, few works have attempted to study the relationship between the main features of the algorithm, the problem to be solved and the underlying hardware where it runs. This work presents a preliminary analysis and modeling of energy consumption of EAs. We try to predict it by means of a fuzzy rule-based system, so that different devices are considered as well as a number of problems and Genetic Programming parameters. Experimental results performed show that the proposed model can predict energy consumption with very low error values. © 2018 Copyright held by the owner/author(s).

关键词： Genetic programming

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swMD: Performance Optimizations for Molecular Dynamics Simulation on Sunway Taihulight

swMD: Performance Optimizations for Molecular Dynamics Simul...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Kun Li Shigang Li Bei Wang Yifeng Chen Yunquan Zhang State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing Department of Computer Science ETH Zurich HCST Key Lab at School of EECS Peking University Beijing

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

Molecular dynamics is an extensively utilized computational tool for solids, liquids and molecules simulation. Currently, much research on molecular dynamics simulation focuses on simplifying forces or parallelizing tasks to reduce the overheads of forces computation. However, the molecular dynamics simulation still remains challenging since the communication and neighbor list construction are time-consuming in the existing algorithm. In this paper, we propose a swMD optimization strategy including a new communication mode called ghost communication to reduce superfluous communication overheads and an innovative neighbor list algorithm to improve the construction efficiency of it. Moreover, we accelerate computation by utilizing many-core resources on Sunway Taihulight and present an auto-tuning Producer-Consumer pairing algorithm to make neighbor list construction happen in fast register communication. Compared to traditional methods, swMD optimization strategy obtains a maximal 82.2% and an average of 79.4% performance improvement. We also evaluate the scalability up to 266,240 cores and the results demonstrate the high efficiency of swMD optimization strategy on communication, computation and neighbor list construction respectively.

关键词： Heuristic algorithms computer architecture Computational modeling Microprocessors Program processors Registers Surface treatment

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A Survey on Quantum Cryptography

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Chinese Journal of Electronics 2018年第2期27卷 223-228页

作者： LI Jian LI Na ZHANG Yu WEN Shuang DU Wei CHEN Wei MA Wenping School of Computer Science Beijing University of Posts and Telecommunications Jilin Medical University School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Department of Optics and Optical Engineering University of Science and Technology of China School of Telecommunications Engineering Xidian University

Quantum cryptography(QC) as an important technology to protect the security of the future network communication, has gained extensive attention from both academia and industry in recent years. This paper provides a concise up-to-date review of QC, including Quantum key distribution(QKD), Quantum authentication, Quantum public-key cryptography(QPKC), and so on. Our aim is to pave a comprehensive and solid starting ground for interested readers. We firstly clarify the definition of QC. Secondly, we present the current understanding of QC from different levels, including the basic knowledge of quantum information processing, QC protocols and the attacks in QC. Finally, we discuss the challenges and opportunities in this hopeful field.

关键词： Quantum cryptography Quantum key distribution Quantum authentication Quantum publickey cryptography

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Comparing the design neurocognition of mechanical engineers and architects: A study of the effect of designer's domain 22

Comparing the design neurocognition of mechanical engineers ...

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22nd International Conference on Engineering Design, ICED 2019

作者： Vieira, Sonia Liliana da Silva Gero, John S. Delmoral, Jessica Gattol, Valentin Fernandes, Carlos Fernandes, António A. INEGI Institute of Science and Innovation in Mechanical and Industrial Engineering Porto Portugal Department of Computer Science School of Architecture University of North Carolina Charlotte United States AIT Austrian Institute of Technology Vienna Austria FMUP Faculty of Medicine University of Porto Portugal FEUP Faculty of Engineering University of Porto Portugal

New tools from neuroscience allow design researchers to explore design neurocognition. By taking the advantage of EEG's temporal resolution we give up spatial resolution to focus on the performance of time-related design tasks. This paper presents results from an experiment using EEG to measure brain activation to study mechanical engineers and architects to compare their design neurocognition. In this study, we adopted and extended the tasks described in a previous fMRI study of design neurocognition reported in the literature. The block experiment consists of a sequence of 3 tasks: problem solving, basic design and open design using a physical interface. The block is preceded by a familiarizing pre-task using the physical interface and then extended to a fourth task using free-hand sketching. Brainwaves were collected from both mechanical engineers and architects. Results comparing 36 mechanical engineers and architects while designing were produced. These results indicate design cognition differences between the two domains in task-related power between the problem-solving task and the design tasks, in temporal resolution and transformed power. © 2019 Design Society. All rights reserved.

关键词： Design

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Author Correction: Aerial additive manufacturing with multiple autonomous robots

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Nature 2024年第7998期626卷 E5页

作者： Ketao Zhang Pisak Chermprayong Feng Xiao Dimos Tzoumanikas Barrie Dams Sebastian Kay Basaran Bahadir Kocer Alec Burns Lachlan Orr Talib Alhinai Christopher Choi Durgesh Dattatray Darekar Wenbin Li Steven Hirschmann Valentina Soana Shamsiah Awang Ngah Clément Grillot Sina Sareh Ashutosh Choubey Laura Margheri Vijay M Pawar Richard J Ball Chris Williams Paul Shepherd Stefan Leutenegger Robert Stuart-Smith Mirko Kovac Department of Aeronautics Imperial College London London UK. School of Engineering and Materials Science Queen Mary University of London London UK. Department of Computing Imperial College London London UK. Department of Architecture and Civil Engineering University of Bath Bath UK. Department of Computer Science University College London London UK. Materials and Technology Centre of Robotics Swiss Federal Laboratories for Materials Science and Technology (Empa) Dübendorf Switzerland. Department of Informatics Technical University of Munich Garching Germany. Stuart Weitzman School of Design University of Pennsylvania Philadelphia PA USA. Department of Aeronautics Imperial College London London UK. m.kovac@imperial.ac.uk. Materials and Technology Centre of Robotics Swiss Federal Laboratories for Materials Science and Technology (Empa) Dübendorf Switzerland. m.kovac@imperial.ac.uk.

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Transformer-Based Deep Learning for Mesoscale Eddy Detection in Sea Surface Temperature Maps

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年

作者： Ji, Chen Xu, Wenyang Zheng, Xiangtian Ahmed, Yasmeen Jamal, Saad Ahmed Imam, Fakhar Ali, Mohammed Saleh Muthanna, Maha Ibrahim Ullah, Sajid Kucher, Dmitry E. Nanjing University School of Geography and Ocean Science Nanjing210046 China Nanjing Institute of Technology Nanjing211167 China Mississippi State University Department of Building Construction Science College of Architecture Art & Design MS39762 United States Paris Lodron Universitat Salzburg Institute for Research and Advanced Studies Universidade de Evora Department of Computer Science University of South Brittany Department of Geoinformatics PortugalZ_GIS France Austria University of the Punjab Lahore Pakistan Tashkent State University of Economics Department of International Business Management Tashkent Uzbekistan Nangarhar University Department of Water Resources and Environmental Engineering Nangarhar 2600 Afghanistan RUDN University Department of Environmental Management Institute of Environmental Engineering Moscow117198 Russia

Mesoscale eddies are dynamic oceanic phenomena significantly influencing marine ecosystems' energy transfer, nutrients, and biogeochemical cycles. These eddies' precise identification and categorization can improve climate modeling, ocean circulation research, and environmental surveillance. This study presents an innovative methodology for mesoscale eddy detection utilizing Transformer-based deep learning models, namely Swin Transformer U-Net (Swin-Unet) and SegFormer, to categorize ocean eddies from Sea Surface Temperature (SST) maps sourced from the Copernicus Marine Environment Monitoring Service (CMEMS). In contrast to traditional convolutional neural networks (CNNs) that have prevailed in the domain, Transformer-based models provide superior global attention mechanisms, facilitating greater feature extraction and segmentation precision. The models are trained on labeled SST datasets and assessed using Intersection over Union (IoU), Dice coefficient, precision, recall, and F1-score. Experimental findings demonstrate that Transformer-based designs surpass conventional CNN-based techniques, yielding enhanced generalization and superior accuracy in classifying cyclonic and anticyclonic eddies. This study illustrates the efficacy of attention based segmentation algorithms for resilient oceanographic applications. © 2008-2012 IEEE.

关键词： Semantic Segmentation

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