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2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery最新文献

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Least Squares Support Vector Machines for performance degradation modeling of, CNC equipments 基于最小二乘支持向量机的数控设备性能退化建模
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI: 10.1109/CYBERC.2009.5342155
Yuming Xu, C. Deng, Jun Wu
{"title":"Least Squares Support Vector Machines for performance degradation modeling of, CNC equipments","authors":"Yuming Xu, C. Deng, Jun Wu","doi":"10.1109/CYBERC.2009.5342155","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5342155","url":null,"abstract":"Due to the applications of high technology, a catastrophic failure of Computerized numerical control (CNC) machine tool rarely happens at normal operation conditions. Traditional reliability assessment methods based on time-to-failure distributions have the difficulty to estimate the reliability precisely. This paper presents a novel reliability assessment methodology that estimates the reliability of machine tool with machining performance degradation while only small samples are required. To analyze a performance degradation process on the machine tool, Least Squares Support Vector Machines (LS-SVM) is introduced. Parameter optimization and a two-stage searching method of the parameter scope are proposed to improve the LS-SVM regression performance. A performance degradation model based on LS-SVM is built and a machining performance degradation experiment on OTM650 machine tool is used to study the feasibility of the developed technique. The results show that the proposed reliability assessment methodology is effective.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114739554","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: 5
Human ear recognition based on block segmentation 基于分块分割的人耳识别
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI: 10.1109/CYBERC.2009.5342143
W. Xiaoyun, Yu Weiqi
{"title":"Human ear recognition based on block segmentation","authors":"W. Xiaoyun, Yu Weiqi","doi":"10.1109/CYBERC.2009.5342143","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5342143","url":null,"abstract":"A new human ear recognition approach based on block segmentation is proposed in this paper. In this method, an original ear image is partitioned into several smaller sub-images, then the sub-images are extracted by features, As a result, the lower dimension space features that can replace the original images are obtained. Finally the pattern classification can be implemented by the nearest neighbor classifier. To verify the effectiveness of the block segmentation approach, a various experiments are conducted based on four feature extraction methods. USTB human ear database is applied to test the algorithms. The experimental results indicate that the recognition rates are significantly improved. The recognition rate of the moment invariants based on block segmentation achieves 100% in the experiments. The statistics feature extraction is easy to actualize, and the computational speed of recognition is the fastest.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116485624","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: 18
An adaptive feedback timing control algorithm of delay-constrained data aggregation in wireless sensor networks 无线传感器网络中时延约束数据聚合的自适应反馈定时控制算法
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI: 10.1109/CYBERC.2009.5342205
Zhikui Chen, Song Yang, Xiaodi Huang, Yang Liu
{"title":"An adaptive feedback timing control algorithm of delay-constrained data aggregation in wireless sensor networks","authors":"Zhikui Chen, Song Yang, Xiaodi Huang, Yang Liu","doi":"10.1109/CYBERC.2009.5342205","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5342205","url":null,"abstract":"Wireless sensor networks (WSNs) play an increasingly important role in civilian and military settings. With the limited energy supply, sensor nodes do neither large calculations nor further transmissions. Data aggregation can reduce the redundancy of packets and save energy to prolong the lifetime of sensor networks. This paper proposes a novel mechanism for the delay-ranged feedback timing control (DRFT) that tackles the problem of the waiting period of aggregation nodes. In order to increase the possibility of aggregating the data completely, DRFT not only assigns longer aggregation time to the nodes with more children nodes, but also adaptively adjusts the waiting time to meet various queries and different requirements. Theoretical analysis and simulation results demonstrate that DRFT can achieve a good trade-off between energy consumption and query delay.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122873339","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: 3
A MES pre-processor design in multi-source information, fusion 一种MES预处理设计，实现了多源信息的融合
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI: 10.1109/CYBERC.2009.5342151
Jinyuan Yang, Xinhan Huang, Min Wang
{"title":"A MES pre-processor design in multi-source information, fusion","authors":"Jinyuan Yang, Xinhan Huang, Min Wang","doi":"10.1109/CYBERC.2009.5342151","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5342151","url":null,"abstract":"In multi-sources information fusion, because of the diversity of evidences, especially the imperfect evidences, it's difficult to get a satisfied result. To avoid and reduce the influence of the mistaken or conflicting information on the final precision of fusion, a pre-processor of evidence sources is proposed and proved. A MES (measurement of evidence support) pre-processor is designed. Firstly, the reliability of every evidence source is analyzed from itself generalized basic belief assignment (gbba) to identify the centre of the whole evidence sources. Then the distance measurement between every evidences and the centre evidence is confirmed according to the relation support. The identification algorithm of computing reliability is also presented. The evidence source with larger distance won't be sent into the fusion to achieve the faster and more precise information result. Finally we apply the new tool coupling with the fusion rule based on Dezert and Smarandache Theroy (DSmT) to P2DX robot perception. Experiment results show the effectiveness and robustness of this method.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122136731","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
A novel cross layer design approach for video transmission over wireless ad hoc networks 一种新的无线自组织网络视频传输的跨层设计方法
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI: 10.1109/CYBERC.2009.5342211
Zheng Wu, W. Wong, Jiankang Wu
{"title":"A novel cross layer design approach for video transmission over wireless ad hoc networks","authors":"Zheng Wu, W. Wong, Jiankang Wu","doi":"10.1109/CYBERC.2009.5342211","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5342211","url":null,"abstract":"Video transmission over wireless ad hoc networks is very sensitive to temporal dynamics of the wireless channel. In order to achieve good end to end performance, it is necessary for upper layers to quickly adapt to the variations of the wireless links. Based on this motivation, we propose a novel cross layer design (CLD) which employs an adaptive link estimator to ensure reliable transmissions. The link-quality estimation scheme can provide accurate link quality information for routing decisions and predicts the link characteristics for the next time interval by using a Kalman filter. Through simulations and experiments we demonstrate that the proposed cross layer approach can quickly adapt to the temporal dynamics of the links, accurately predict the link characteristics and improve the robustness of video transmission over mobile ad hoc networks.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132520872","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
A location and tracking algorithm based on BP neural network with NLOS propagation 基于NLOS传播的BP神经网络定位与跟踪算法
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI: 10.1109/CYBERC.2009.5342192
Ma Yongyi, Zhou Kanglei
{"title":"A location and tracking algorithm based on BP neural network with NLOS propagation","authors":"Ma Yongyi, Zhou Kanglei","doi":"10.1109/CYBERC.2009.5342192","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5342192","url":null,"abstract":"In this paper we proposed a location and tracking algorithm with non-line of sight (NLOS) errors for mobile station (MS). The algorithm is able to correct the NLOS errors using the Back Propagation (BP) neural network on TDOA measurements, and the positions of MS can be estimated by the Chan's algorithm. Furthermore, cooperating the correlation detection gate, the MS is tracked by the algorithm. Simulations results show that the proposed algorithm could be efficiently locate the MS not only in the static state but also in the dynamic state.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128773885","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: 3
Decision fusion with censoring wireless sensors under Rice fading channels Rice衰落信道下滤波无线传感器的决策融合
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI: 10.1109/CYBERC.2009.5342182
Yuan Xiao-guang, Yang Wan-hai, Shi Lin
{"title":"Decision fusion with censoring wireless sensors under Rice fading channels","authors":"Yuan Xiao-guang, Yang Wan-hai, Shi Lin","doi":"10.1109/CYBERC.2009.5342182","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5342182","url":null,"abstract":"This paper addressed the issue of fusing decisions transmitted via Rice fading channels, with censoring transmission strategies. We derived an optimal likelihood ratio rule based on the channel state information. However, acquiring channel information may be too expensive for resource-constraint sensor networks. Under this circumstance, suboptimal likelihood ratio fusion rule is proposed, requiring only the information of channel statistics. In addition, when the signal-to-noise ratio (SNR) of channels is quite low, the reduced forms are also derived. Results from both theoretical analysis and simulations show that suboptimal fusion rules need much less information and computation, which only causes slight performance degradation. Suboptimal fusion rules are practicable for decision fusion systems in resource-constraint censoring wireless sensor networks.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124346175","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
Dynamic parameter branching process model of worm propagation 蠕虫传播的动态参数分支过程模型
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI: 10.1109/CYBERC.2009.5342174
Qiwen Liu, Lansheng Han, Mengsong Zou
{"title":"Dynamic parameter branching process model of worm propagation","authors":"Qiwen Liu, Lansheng Han, Mengsong Zou","doi":"10.1109/CYBERC.2009.5342174","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5342174","url":null,"abstract":"Enormous adverse impacts of Internet worms have attracted strong interest from the academia to model their propagation. This paper presents a dynamic parameter branching process to characterize the spread of scanning worm on the Internet. Firstly, the paper demonstrates that the spread of scanning worm is a typical branching process with dynamic parameters rather than a static parameter. Secondly, by analyzing the influential factors, the paper quantifies dynamic parameters during the propagation. Finally, an explicit expression of the expectation and the probability distribution of the total infected number is proposed. Simulation test verifies the expectation matches the statistics much better than previous models, and the probability distribution explains the deviation between models and statistics. Combining of both the determinism and the randomness, the dynamic parameter branching process model illustrates the essence of the worm propagation.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116909869","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
An efficient parallel FP-Growth algorithm 一种高效的并行FP-Growth算法
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-12-01 DOI: 10.1109/CYBERC.2009.5342148
Min Chen, Xuedong Gao, Huifei Li
{"title":"An efficient parallel FP-Growth algorithm","authors":"Min Chen, Xuedong Gao, Huifei Li","doi":"10.1109/CYBERC.2009.5342148","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5342148","url":null,"abstract":"FP-Growth algorithm recursively generates huge amounts of conditional pattern bases and conditional FP-trees when the dataset is huge. In such a case, both the memory usage and computational cost are expensive, such that, the FP-tree can not meet the memory requirement. In this work, we propose a novel parallel FP-Growth algorithm, which is designed to run on the computer cluster. To avoid memory overflow, this algorithm finds all the conditional pattern bases of frequent items by the projection method without constructing an FP-tree. Hereafter, it splits the mining task into number of independent sub-tasks, executes these sub-tasks in parallel on nodes and then aggregates the results back for the final result. Our algorithm works independently at each node. As a result, it can efficiently reduce the inter-node communication cost. Experiments show that this parallel algorithm not only avoids the memory overflow but accelerate the computational speed. In addition, it achieves much better scalability than that of the FP-Growth algorithm.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129214156","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: 26
A CUDA-based parallel implementation of K-nearest neighbor algorithm 基于cuda的k近邻算法并行实现
2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery Pub Date : 2009-10-01 DOI: 10.1109/CYBERC.2009.5399145
Shenshen Liang, Ying Liu, Cheng Wang, Liheng Jian
{"title":"A CUDA-based parallel implementation of K-nearest neighbor algorithm","authors":"Shenshen Liang, Ying Liu, Cheng Wang, Liheng Jian","doi":"10.1109/CYBERC.2009.5399145","DOIUrl":"https://doi.org/10.1109/CYBERC.2009.5399145","url":null,"abstract":"Recent developments in Graphics Processing Units (GPUs) have enabled inexpensive high performance computing for general-purpose applications. Due to GPU's tremendous computing capability, it has emerged as the co-processor of the CPU to achieve a high overall throughput. CUDA programming model provides the programmers adequate C language like APIs to better exploit the parallel power of the GPU. K-nearest neighbor (KNN) is a widely used classification technique and has significant applications in various domains, especially in text classification. The computational-intensive nature of KNN requires a high performance implementation. In this paper, we present a CUDA-based parallel implementation of KNN, CUKNN, using CUDA multi-thread model, where the data elements are processed in a data-parallel fashion. Various CUDA optimization techniques are applied to maximize the utilization of the GPU. CUKNN outperforms the serial KNN on an HP xw8600 workstation significantly, achieving up to 46.71X speedup including I/O time. It also shows good scalability when varying the dimension of the reference dataset, the number of records in the reference dataset, and the number of records in the query dataset.","PeriodicalId":222874,"journal":{"name":"2009 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115622995","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: 37
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