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Semi-supervised dimensionality reduction based on local estimation error 基于局部估计误差的半监督降维
International Journal of High Performance Computing and Networking Pub Date : 2019-05-08 DOI: 10.1504/IJHPCN.2019.10021107
Xianfa Cai, Jia Wei, Guihua Wen, Zhiwen Yu, Yongming Cai, Jie Li
{"title":"Semi-supervised dimensionality reduction based on local estimation error","authors":"Xianfa Cai, Jia Wei, Guihua Wen, Zhiwen Yu, Yongming Cai, Jie Li","doi":"10.1504/IJHPCN.2019.10021107","DOIUrl":"https://doi.org/10.1504/IJHPCN.2019.10021107","url":null,"abstract":"The construction of a graph is extremely important in graph-based semi-supervised learning. However, it is unstable by virtue of sensitivity to the selection of neighbourhood parameter and inaccuracy of the edge weights. Inspired by the good performance of the local learning method, this paper proposes a semi-supervised dimensionality reduction based on local estimation error (LEESSDR) algorithm by utilising local learning projections (LLP) to semi-supervised dimensionality reduction. The algorithm sets the edge weights through minimising the local estimation error and can effectively preserve the global geometric structure as well as the local one of the data. Since LLP does not require its input space to be locally linear, even if it is nonlinear, LLP maps it to the feature space by using kernel functions and then obtains its local estimation error in the feature space. The effectiveness of the proposed method is verified on two popular face databases with promising classification accuracy and favourable robustness.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132040372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Leveraging many simple statistical models to adaptively monitor software systems 利用许多简单的统计模型自适应地监视软件系统
International Journal of High Performance Computing and Networking Pub Date : 2007-08-29 DOI: 10.1504/IJHPCN.2011.038708
M. A. Munawar, Paul A. S. Ward
{"title":"Leveraging many simple statistical models to adaptively monitor software systems","authors":"M. A. Munawar, Paul A. S. Ward","doi":"10.1504/IJHPCN.2011.038708","DOIUrl":"https://doi.org/10.1504/IJHPCN.2011.038708","url":null,"abstract":"Self-managing systems require continuous monitoring to ensure correct operation. Detailed monitoring is often too costly to use in production. An alternative is adaptive monitoring, whereby monitoring is kept to a minimal level while the system behaves as expected, and the monitoring level is increased if a problem is suspected. To enable such an approach, we must model the system, both at a minimal level to ensure correct operation, and at a detailed level, to diagnose faulty components. To avoid the complexity of developing an explicit model based on the system structure, we employ simple statistical techniques to identify relationships in the monitored data. These relationships are used to characterize normal operation and identify problematic areas. \u0000 \u0000We develop and evaluate a prototype for the adaptive monitoring of J2EE applications. We experiment with 29 different fault scenarios of three general types, and show that we are able to detect the presence of faults in 80% of cases, where all but one instance of non-detection is attributable to a single fault type. We are able to shortlist the faulty component in 65% of cases where anomalies are observed.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133399700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 32
Queuing algorithm for speculative Network Processors 推测网络处理器的排队算法
International Journal of High Performance Computing and Networking Pub Date : 2006-08-11 DOI: 10.1504/IJHPCN.2006.013479
J. Foag, T. Wild
{"title":"Queuing algorithm for speculative Network Processors","authors":"J. Foag, T. Wild","doi":"10.1504/IJHPCN.2006.013479","DOIUrl":"https://doi.org/10.1504/IJHPCN.2006.013479","url":null,"abstract":"This paper presents a queuing algorithm which is tailored for usage in speculative Network Processors (NPs). The queuing system uses Weighted-Fair Queuing queues (WFQ) which are extended by Priority Queues (PQ). While WFQ represents a common implementation in current routers supporting differentiated services, PQs allow to compensate extended protocol processing times due to mispredictions in a speculative system. When applying this concept, the generation of delay-jitter which would limit applicability of speculative packet processing for Real-Time (RT) traffic can be avoided. Utilising the presented queuing system in conjunction with speculative protocol processing in an NP, a latency reduction of up to 14.9% can be achieved compared to systems which support traditional packet processing methodologies.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115842388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Adaptive time/space sharing with SCOJO SCOJO的自适应时间/空间共享
International Journal of High Performance Computing and Networking Pub Date : 2006-08-11 DOI: 10.1504/IJHPCN.2006.013481
A. Sodan, Xuemin Huang
{"title":"Adaptive time/space sharing with SCOJO","authors":"A. Sodan, Xuemin Huang","doi":"10.1504/IJHPCN.2006.013481","DOIUrl":"https://doi.org/10.1504/IJHPCN.2006.013481","url":null,"abstract":"Time-shared execution of parallel jobs via gang scheduling is known to yield better average response times than space sharing. We incorporate adaptive CPU/node-resource allocation to consider varying system load and to reduce fragmentation. As main innovations, our SCOJO approach provides a clear model how to adapt, and considers realistic job mixes with moldable, malleable and rigid jobs. Our adaptive SCOJO significantly decreases response times and average slowdowns, while using a lower multiprogramming level than standard gang scheduling uses best and, therefore, decreasing the memory pressure. These benefits apply though the realistic job mixes limit the flexibility in resource allocation.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122478323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
MPI scalability of a large memory LES code MPI可伸缩性的一个大内存LES代码
International Journal of High Performance Computing and Networking Pub Date : 2006-08-11 DOI: 10.1504/IJHPCN.2006.013484
M. Uddin, A. Pollard
{"title":"MPI scalability of a large memory LES code","authors":"M. Uddin, A. Pollard","doi":"10.1504/IJHPCN.2006.013484","DOIUrl":"https://doi.org/10.1504/IJHPCN.2006.013484","url":null,"abstract":"Large Eddy Simulations (LES) of co-flowing round jets with 33.6 million grid points are carried out using 16 Sun 1 GHz UltraSPARC III Cu processors. An in-depth processor scalability analysis is carried out for an MPI based code for a finite-volume solution of time dependent Navier-Stokes equations. Particular attention is paid to the effect of initial conditions on the spatial development of the co-flowing jet at a Reynolds number of 7,300. The evolution of the turbulence structures is quantified using various discrimination techniques, which compared well with the flow visualisation experiments of Villermaux et al. (1998).","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121594715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A new fast parallel statistical measurement technique for computational cosmology 一种新的计算宇宙学快速并行统计测量技术
International Journal of High Performance Computing and Networking Pub Date : 2005-12-01 DOI: 10.1504/IJHPCN.2006.013485
R. Thacker, H. Couchman
{"title":"A new fast parallel statistical measurement technique for computational cosmology","authors":"R. Thacker, H. Couchman","doi":"10.1504/IJHPCN.2006.013485","DOIUrl":"https://doi.org/10.1504/IJHPCN.2006.013485","url":null,"abstract":"Higher order cumulants of point processes require significant computational effort to calculate, particularly when evaluated using standard methods such as counts-in-cells. While newer techniques based on tree algorithms are more efficient, they still suffer from shot noise problems in homogeneous systems. We present a new algorithm for calculating higher order moments using Fourier methods. A filtering technique is used to suppress noise, and this approach allows us to calculate skew and kurtosis even when the point process is highly homogeneous. The algorithm can be implemented efficiently in a shared memory parallel environment provided a data-local random sampling technique is used.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114971805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Wide area data replication for scientific collaborations 科学合作的广域数据复制
International Journal of High Performance Computing and Networking Pub Date : 2005-11-13 DOI: 10.1504/IJHPCN.2008.020857
A. Chervenak, R. Schuler, C. Kesselman, S. Koranda, B. Moe
{"title":"Wide area data replication for scientific collaborations","authors":"A. Chervenak, R. Schuler, C. Kesselman, S. Koranda, B. Moe","doi":"10.1504/IJHPCN.2008.020857","DOIUrl":"https://doi.org/10.1504/IJHPCN.2008.020857","url":null,"abstract":"Scientific applications require sophisticated data management capabilities. We present the design and implementation of a data replication service (DRS), one of a planned set of higher-level data management services for Grids. The capabilities of the DRS are based on the publication capability of the lightweight data replicator (LDR) system developed for the LIGO Scientific Collaboration. We describe LIGO publication requirements and LDR functionality. We also describe the design and implementation of the DRS in the Globus Toolkit Version 4.0 environment and present performance results.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128119490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 124
Reducing the bandwidth requirements of P2P keyword indexing 降低P2P关键字索引对带宽的要求
International Journal of High Performance Computing and Networking Pub Date : 2005-10-02 DOI: 10.1504/IJHPCN.2009.027462
John Casey, Wanlei Zhou
{"title":"Reducing the bandwidth requirements of P2P keyword indexing","authors":"John Casey, Wanlei Zhou","doi":"10.1504/IJHPCN.2009.027462","DOIUrl":"https://doi.org/10.1504/IJHPCN.2009.027462","url":null,"abstract":"This paper describes the design and evaluation of a federated, peer-to-peer indexing system, which can be used to integrate the resources of local systems into a globally addressable index using a distributed hash table. The salient feature of the indexing systems design is the efficient dissemination of term-document indices using a combination of duplicate elimination, leaf set forwarding and conventional techniques such as aggressive index pruning, index compression, and batching. Together these indexing strategies help to reduce the number of RPC operations required to locate the nodes responsible for a section of the index, as well as the bandwidth utilization and the latency of the indexing service. Using empirical observation we evaluate the performance benefits of these cumulative optimizations and show that these design trade-offs can significantly improve indexing performance when using a distributed hash table.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129977009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Real-time human action recognition using depth motion maps and convolutional neural networks 实时人体动作识别使用深度运动地图和卷积神经网络
International Journal of High Performance Computing and Networking Pub Date : 1900-01-01 DOI: 10.1504/IJHPCN.2016.10011433
Jiang Li, Xiaojuan Ban, Guang Yang, Yitong Li, Yu Wang
{"title":"Real-time human action recognition using depth motion maps and convolutional neural networks","authors":"Jiang Li, Xiaojuan Ban, Guang Yang, Yitong Li, Yu Wang","doi":"10.1504/IJHPCN.2016.10011433","DOIUrl":"https://doi.org/10.1504/IJHPCN.2016.10011433","url":null,"abstract":"This paper presents an effective approach for recognising human actions from depth video sequences by employing depth motion maps (DMMs) and convolutional neural networks (CNNs). Depth maps are projected onto three orthogonal planes, and frame differences under each view (front/side/top) are then accumulated through an entire depth video sequence generating a DMM. We build a model architecture of multi-view convolutional neural network (MV-CNN) containing multiple networks to deal with three DMMs (DMMf, DMMs, DMMt). The output of full-connected layer under each view is integrated as feature representation, which is then learned in the last softmax regression layer to predict human actions. Experimental results on MSR-Action3D dataset and UTD-MHAD dataset indicate that the proposed approach achieves state-of-the-art recognition performance and is appropriate for real-time recognition.","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129601430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Device classification based data encryption for internet of things 基于设备分类的物联网数据加密
International Journal of High Performance Computing and Networking Pub Date : 1900-01-01 DOI: 10.1504/ijhpcn.2020.10032465
T. P. Sharma, N. A. Rishabh
{"title":"Device classification based data encryption for internet of things","authors":"T. P. Sharma, N. A. Rishabh","doi":"10.1504/ijhpcn.2020.10032465","DOIUrl":"https://doi.org/10.1504/ijhpcn.2020.10032465","url":null,"abstract":"","PeriodicalId":384857,"journal":{"name":"International Journal of High Performance Computing and Networking","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127884222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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