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10th IEEE International Conference on Cognitive Informatics and Cognitive computing, ICCI*CC 2011

作者： Zhang, Lixiao Luo, Xiangfeng Zhang, Jun Ye, Feiyue Xu, Weimin School of Computer Engineering and Science Shanghai University Shanghai 200072 China High Performance Computing Center Shanghai University Shanghai 200072 China Shanghai Sanda University Shanghai 200072 China

ISBN: (纸本)9781457716966

The measurement of textual complexity is a fundamental issue on e-learning, online question-answering, web search and browsing, etc. But it is still a challenge because the measuring process includes a series of cognitive mechanisms. According to the properties of cognitive principles in human text reading process, the different derivatives of textual keywords are given. Based on the categorical invariance in human conception learning, textual invariance is defined, and then the measuring method of textual complexity is developed which is consistent with the view of categorical invariance in human concept learning. Experiments prove that there is a strong correlation between the text understanding difficulty given by human and the textual complexity measured by our method. That is to say, the proposed method can reflect human's reading experience to some extent. © 2011 IEEE.

关键词： category invariace human concept learning text understanding textual complexity

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A framework of user-driven data analytics in the cloud for course management

A framework of user-driven data analytics in the cloud for c...

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18th International Conference on computers in Education: Enhancing and Sustaining New Knowledge Through the Use of Digital Technology in Education, ICCE 2010

作者： Zhang, Jie Tjhi, William Chandra Lee, Bu Sung Lee, Kee Khoon Vassileva, Julita Looi, Chee Kit School of Computer Engineering Nanyang Technological University Singapore A Star Institute of High Performance Computing Singapore Department of Computer Science University of Saskatchewan Canada Centre of Excellence for Learning Innovation National Institute of Education Singapore

ISBN: (纸本)9789834251253

In this paper, we describe our goal of an effective course management system for assisting course managers to make informed decisions about what materials should be most appropriate to be presented to students (learners) and what learning strategies or methods should be used for the students. The system is supported by our design of a novel framework for user-driven data analytics in the cloud. Different modules of the framework will be illustrated in detail in the context of course management.

关键词： Learning systems

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Algorithm of Walsh-Hadamard transform with optical approach

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Journal of Information and Computational science 2013年第14期10卷 4427-4434页

作者： Shen, Yunfu Jiang, Benpeng High Performance Computing Center School of Computer Engineering and Science Shanghai University Shanghai 200444 China

In this paper, the fast algorithm to Walsh-Hadamard transform (WHT) is studied from the point of view of the optical computation. Firstly, MSD addition and butterfly calculation in discrete WHT are presented in detail. Then the design and implementation scheme of fast algorithm of WHT is proposed and the software simulations to fast WHT are carried out optically. Meanwhile, the computational complexity of the algorithms in time and space are analyzed. The analysis shows that the problem of WHT with large-scale data can be solved in a few of clock cycles with optical computational method. The scheme also provides a good way for the design of fast optical Walsh-Hadamard transformer and an application in ternary optical computer. 1548-7741/Copyright © 2013 Binary Information Press.

关键词： Hadamard transforms

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Emerging theory and phenomena in thermal conduction: A selective review

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science China(Physics,Mechanics & Astronomy) 2022年第11期65卷 2-17页

作者： Jie Chen Jia He Dongkai Pan Xiaotian Wang Nuo Yang Jiaojiao Zhu Shengyuan A.Yang Gang Zhang Center for Phononics and Thermal Energy Science China-EU Joint Lab for NanophononicsMOE Key Laboratory of Advanced Microstructured MaterialsSchool of Physics Science and EngineeringTongji UniversityShanghai 200092China School of Energy and Power Engineering Huazhong University of Science and Technology(HUST)Wuhan 430074China School of Physical Science and Technology Southwest UniversityChongqing 400715China Research Laboratory for Quantum Materials Singapore University of Technology and DesignSingapore 487372Singapore Institute of High Performance Computing Agency for ScienceTechnology and Research(A*STAR)Singapore 138632Singapore

Recently, emerging phonon phenomena have been discovered and rapidly developed, which have become an active hot research topic. In this review article, we present state-of-the-art advances in several fascinating phonon transport phenomena. First, we summarize the recent progress on the wave nature of phonons, including phonon coherence and its effects on thermal conductivity and the topological properties of phonons. Then, we discuss the particle nature of phonons, including the weak coupling of phonons and the high-order phonon anharmonicity. Finally, we present the summary and a brief outlook. This review presents the advanced understanding of some emerging phonon phenomena in solid materials, which provides new opportunities for further advancement in a wide variety of applications.

关键词： phonon transport coherence topological phonon high-order phonon interaction

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Online Demand Peak Shaving with Machine-Learned Advice in Cyber-Physical Energy Systems

Online Demand Peak Shaving with Machine-Learned Advice in Cy...

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2023 IEEE International Conference on Dependable, Autonomic and Secure computing, 2023 International Conference on Pervasive Intelligence and computing, 2023 International Conference on Cloud and Big Data computing, 2023 International Conference on Cyber science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Fengl, Minxi Li, Wei Qin, Boyu Zomaya, Albert Y. Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia Xi'an Jiaotong University State Key Laboratory of Electrical Insulation and Power Equipment Department of Electrical Engineering China

ISBN: (纸本)9798350304602

With the deep integration of cyber tools, control algorithms are increasingly employed in cyber-physical energy systems to enhance management, cost efficiency, and robustness. Effective demand load management is crucial in cyber-physical energy systems as it directly impacts operational costs. Failure to adequately manage spiky or seasonal demand loads can lead to significant expenses on monthly utility bills. In this study, we propose AMPAMOD, a randomized online algorithm with machine-learned advice, to optimize battery operations and mitigate highly dynamic peak loads. AMPAMOD utilizes limited advice from machine learning algorithms to guide our online algorithm and ensure cost-effective peak load management. The theoretical analysis shows that our solution has minimal advice complexity, a linear computational cost, and an improved competitive ratio. Finally, we conduct extensive trace-driven experiments on real-world datasets. AMPAMOD achieves a peak shaving success rate of over 90%, outperforming baselines by at least 50%. These experimental results confirm theoretical findings and demonstrate the potential of AMPAMOD. © 2023 IEEE.

关键词： Cyber Physical System

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A K-Nearest Centroid Neighbor with atention Classifier 5

A K-Nearest Centroid Neighbor with atention Classifier

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5th International Conference on computer science and Artificial Intelligence, CSAI 2021

作者： Huang, Rui Ma, Ying Wang, Tian Li, GuoQi Yan, Ming Department of Computer and Information Engineering Xiamen University of Technology China Institute of High Performance Computing Agency for Science Technology and Research Singapore Singapore School of Information Science and Engineering Hunan First Normal University China Department of Precision Instrument Center for Brain Inspired Computing Research

ISBN: (纸本)9781450384155

Among classic algorithms of data mining, the K-nearest neighbor based methods are simple and effective pattern classification algorithms. However, most KNN-based methods do not fully take into account the impact of different training sample points on classification, lead to inaccurate classification. To address this issue, we propose a scheme named Attention-based local mean K-Nearest Centroid Neighbor Classifier (ALMKNCN), combining nearest centroid neighbor with attention mechanism, the influence of each training sample on the query sample is fully considered. Given the query pattern, we first calculate the local centroid mean vector for each class, and then use the idea of attention mechanism to calculate the weight of pseudo-distance between each class and test sample. Finally, based on attention coefficient, the distances between the query sample and local mean vectors are weighted to determine the class of the query sample. Extensive experiments on UCI and KEEL data sets are carried out by comparing ALMKNCN to the state-of-art KNN-based methods. The experimental results demonstrate that the proposed ALMKNCN outperforms the related competitive KNN-based methods with more effectiveness. © 2021 ACM.

关键词： Data mining

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GIRAFFE: A scalable distributed coordination service for large-scale systems 16

GIRAFFE: A scalable distributed coordination service for lar...

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16th IEEE International Conference on Cluster computing, CLUSTER 2014

作者： Shi, Xuanhua Lin, Haohong Jin, Hai Zhou, Bing Bing Yin, Zuoning Di, Sheng Wu, Song Services Computing Technology and System Lab School of Computer Science and Technology Huazhong University of Science and Technology China Centre for Distributed and High Performance Computing School of Information Technologies University of Sydney Australia GraphSQL Inc. Australia INRIA Argonne National Laboratory United States

ISBN: (纸本)9781479955480

The scale of cloud services keeps increasing over time, significantly introducing huge challenges in system manageability and reliability. Designing coordination services in cloud is the right track to solve the above problems. However, existing coordination services (e.g., Chubby and ZooKeeper) only perform well in read-intensive scenario and small ensemble scales. To this end, we propose Giraffe, a scalable distributed coordination service. There are three important contributions in our design. (1) Giraffe organizes coordination servers using interior-node-disjoint trees for better scalability. (2) Giraffe employs a novel Paxos protocol for strong consistency and fault-tolerance. (3) Giraffe supports hierarchical data organization and in-memory storage for high throughput and low latency. We evaluate Giraffe on a high performance computing test-bed. The experimental results show that Giraffe gains much better write performance than ZooKeeper when server ensemble is large. Giraffe is nearly 300% faster than ZooKeeper on update operations when ensemble size is 50 servers. Experiments also show that Giraffe reacts and recovers more quickly than ZooKeeper against node failures. © 2014 IEEE.

关键词： Distributed cloud

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Research on key technologies of edge cache in virtual data space across WAN

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Frontiers of computer science 2023年第1期17卷 15-34页

作者： Jiantong HUO Yaowen XU Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China College of Software Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China College of Computer Science and Technology Zhejiang UniversityHangZhou 310013China

The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing Center in Guangzhou, National Supercomputing Center in Jinan, National Supercomputing Center in Changsha, Shanghai Supercomputing Center, and computer Network Information Center in Chinese Academy of sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).

关键词： virtual data space system wide area network edge cache redundant data transmission

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Study and Analysis of Hadoop Cluster Optimization based on configuration properties

Study and Analysis of Hadoop Cluster Optimization based on c...

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International Conference on Innovations in Power and Advanced computing Technologies

作者： Motahar Reza Badrinath Tripathy Harsh Ranjan G. Anant Kumar High Performance Computing Lab School of Computer Science and Engineering National Institute of Science and Technology Berhampur-761008 India

ISBN: (纸本)9781509056835

Hadoop framework consists of multiple components. One set of configuration parameters may not be suitable for all types of applications. Hence, for optimum performance, each framework parameter needs to be carefully chosen and adjusted. This paper highlights some of the important configuration properties related to Block size, memory allocation, CPU allocation, Number of MapReduce jobs, Job scheduling and JVM which should be tuned for improved Hadoop application performance. The result of some Benchmark problems are analyzed.

关键词： Hadoop framework JVM CPU Allocation Benchmark

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SOCA-DOM:A Mobile System-on-Chip Array System for Analyzing Big Data on the Move

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Journal of computer science & Technology 2022年第6期37卷 1271-1289页

作者： Le-Le Li Jiang-Yi Liu Jian-Ping Fan Xue-Hai Qian Kai Hwang Yeh-Ching Chung Zhi-Bin Yu Center for Heterogeneous and Intelligent Computing Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518055China School of Science and Engineering The Chinese University of Hong KongShenzhenShenzhen 518172China Center for High Performance Computing Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Shenzhen 518055China Ming Hsieh Department of Electrical and Computer Engineering University of Southern CaliforniaLos Angeles CA 90089-0001U.S.A. Department of Computer Science University of Southern CaliforniaLos AngelesCA 90089-0001U.S.A. School of Data and Science The Chinese University of Hong KongShenzhenShenzhen 518172China

Recently,analyzing big data on the move is *** requires that the hardware resource should be low volume,low power,light in weight,high-performance,and highly scalable whereas the management software should be flexible and consume little hardware *** meet these requirements,we present a system named SOCA-DOM that encompasses a mobile system-on-chip array architecture and a two-tier“software-defined”resource manager named ***,we design an Ethernet communication board to support an array of mobile ***,we propose a two-tier software architecture for Chameleon to make it ***,we devise data,configuration,and control planes for Chameleon to make it“software-defined”and in turn consume hardware resources on ***,we design an accurate synthetic metric that represents the computational power of a computing *** employ 12 Apache Spark benchmarks to evaluate ***,SOCA-DOM consumes up to 9.4x less CPU resources and 13.5x less memory than Mesos which is an existing resource *** addition,we show that a 16-node SOCA-DOM consumes up to 4x less energy than two standard Xeon *** on the results,we conclude that an array architecture with fine-grained hardware resources and a software-defined resource manager works well for analyzing big data on the move.

关键词： edge computing mobile architecture resource management big data analytics software-defined systems

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