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2014 IEEE 17th International Conference on Computational Science and Engineering最新文献

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Improving Prediction Robustness of VAB-SVM for Cross-Project Defect Prediction 改进VAB-SVM跨项目缺陷预测的鲁棒性
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.198
Duksan Ryu, Okjoo Choi, Jongmoon Baik
{"title":"Improving Prediction Robustness of VAB-SVM for Cross-Project Defect Prediction","authors":"Duksan Ryu, Okjoo Choi, Jongmoon Baik","doi":"10.1109/CSE.2014.198","DOIUrl":"https://doi.org/10.1109/CSE.2014.198","url":null,"abstract":"Software defect prediction is important for improving software quality. Defect predictors allow software test engineers to focus on defective modules. Cross-Project Defect Prediction (CPDP) uses data from other companies to build defect predictors. However, outliers may lower prediction accuracy. In this study, we propose a transfer learning based model called VAB-SVM for CPDP robust in handling outliers. Notably, this method deals with the class imbalance problem which may decrease the prediction accuracy. Our proposed method computes similarity weights of the training data based on the test data. Such weights are applied to Boosting algorithm considering the class imbalance. VAB-SVM outperformed the previous research more than 10% and showed a sufficient robustness regardless of the ratio of outliers.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125143046","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: 10
A New Error Concealment Algorithm for H.264/AVC 一种新的H.264/AVC错误隐藏算法
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.206
Zhixin Shen, Xingang Liu, Lingyun Lu, Xun Wang
{"title":"A New Error Concealment Algorithm for H.264/AVC","authors":"Zhixin Shen, Xingang Liu, Lingyun Lu, Xun Wang","doi":"10.1109/CSE.2014.206","DOIUrl":"https://doi.org/10.1109/CSE.2014.206","url":null,"abstract":"With the development of communications and network technologies, video streaming service is becoming increasingly important. However, in the transmission of high compressed video, bit-stream is easily damaged by channel errors which will lead to the decline of the video sequence. Error concealment is an effective approach to reduce the influence in error-prone network and notably improve the video quality. This paper presents a novel error concealment algorithm for temporal video error concealment with H.264/AVC standard. This method exploits both spatial and temporal information in the reference and current frame. To increase the accuracy, the macro block (MB) is divided into 16 4x4 blocks. The reference frame is classified by k-means clustering algorithm. The lost blocks are recovered by the neigh boring blocks which belong to the same class of the lost block. The experimental result shows that our method can achieve a better performance than the existing methods.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122954850","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: 8
Uncorrelated Weighted Median Filtering for Noise Removal in SuperDARN 非相关加权中值滤波在超校正噪声去除中的应用
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.196
Clarence Goh, J. Devlin, Dennis Deng, A. McDonald, M. Kamarudin
{"title":"Uncorrelated Weighted Median Filtering for Noise Removal in SuperDARN","authors":"Clarence Goh, J. Devlin, Dennis Deng, A. McDonald, M. Kamarudin","doi":"10.1109/CSE.2014.196","DOIUrl":"https://doi.org/10.1109/CSE.2014.196","url":null,"abstract":"Super DARN operating frequencies from 10MHz-15MHz are susceptible to clutter originating from unwanted altitude backscatter, man-made noise exhibiting a Gaussian distribution and correlated speckle noise from pulses emitted from other similar Super DARN radars operating at the same frequency. The paper focuses on removing man-made clutter and uncorrelated speckle noise noise by prior measurement of received noise signal. Based on noise information, an uncorrelated weighted median filter is proposed and used to remove unwanted clutter.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131414203","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
Discovering Regional Taxicab Demand Based on Distribution Modeling from Trajectory Data 基于轨迹数据分布建模的区域出租车需求挖掘
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.296
Qi Zhou, Junming Zhang, Jinglin Li, Shangguang Wang
{"title":"Discovering Regional Taxicab Demand Based on Distribution Modeling from Trajectory Data","authors":"Qi Zhou, Junming Zhang, Jinglin Li, Shangguang Wang","doi":"10.1109/CSE.2014.296","DOIUrl":"https://doi.org/10.1109/CSE.2014.296","url":null,"abstract":"Taxicab demand discovering is one of the most fundamental issues of taxicab services. Most of the regions in one city suffer the demand and supply disequilibrium problem. It causes the difficulty in scheduling taxicabs for taxicab companies. It will be solved by modeling the regional demand of taxicabs by using trajectory data. In this paper, we propose a method to model regional taxicab demand. Firstly, the method uses the KS measures to test the distribution of taxicab service rate. Then, it uses the Parzen window to estimate the probability density function of the rate. We have implemented our method with experiments based on real trajectory data. The results show the effectiveness of our method.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121751111","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
Lessons from Experimental Methodology of Cache Hierarchy Changes with the Memory Technology 缓存层次结构随存储技术变化实验方法的启示
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.357
Yanjiang Wei, Rui Wang, Danfeng Zhu, Zhongzhi Luan, D. Qian
{"title":"Lessons from Experimental Methodology of Cache Hierarchy Changes with the Memory Technology","authors":"Yanjiang Wei, Rui Wang, Danfeng Zhu, Zhongzhi Luan, D. Qian","doi":"10.1109/CSE.2014.357","DOIUrl":"https://doi.org/10.1109/CSE.2014.357","url":null,"abstract":"Caching is an important technique to improve computer system performance by storing the most recently used data and instructions for main memory. Cache is widely used in modern computer systems and will continue to be an irreplaceable unit to narrow the speed gap between processor and main memory. With the increasing capacity of main memory and the number of processor cores, the cache technology has great development. In this paper, we have some lessons of cache hierarchy changes with the memory technology from experimental methodology. We design a serial of experiments and try to answer some questions about cache designs. Our experiments results indicate that more levels of cache does not necessarily means better performance for all benchmarks, that last level cache miss rate has no direct connection with the system performance, that the average performance of exclusive cache hierarchy is more effective than that of inclusive cache.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116498705","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
LPA Based Hierarchical Community Detection 基于LPA的分层团体检测
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.65
Tao Wu, Leiting Chen, Yayong Guan, Xin Li, Yuxiao Guo
{"title":"LPA Based Hierarchical Community Detection","authors":"Tao Wu, Leiting Chen, Yayong Guan, Xin Li, Yuxiao Guo","doi":"10.1109/CSE.2014.65","DOIUrl":"https://doi.org/10.1109/CSE.2014.65","url":null,"abstract":"Community structure has many practical applications, and identifying communities could help us to understand and exploit networks more effectively. Generally, real-world networks often have hierarchical structures with communities embedded within other communities. However, there are few effective methods can identify these structures. This paper proposes an algorithm HELPA to detect hierarchical community structures. HELPA is based on coreness centrality to update node's possible community labels, and uses communities as nodes to build super-network. By repeat the procedure, the proposed algorithm can effectively reveal hierarchical communities with different size in various network scales. Moreover, it overcomes the high complexity and poor applicability problem of similar algorithms. To illustrate our methodology, we compare it with many classic methods in real-world networks. Experimental results demonstrate that HELPA achieves excellent performance.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132589079","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
Evaluating Open IaaS Cloud Platforms Based upon NIST Cloud Computing Reference Model 基于NIST云计算参考模型的开放IaaS云平台评估
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.350
Qing Lei, Yingtao Jiang, Mei Yang
{"title":"Evaluating Open IaaS Cloud Platforms Based upon NIST Cloud Computing Reference Model","authors":"Qing Lei, Yingtao Jiang, Mei Yang","doi":"10.1109/CSE.2014.350","DOIUrl":"https://doi.org/10.1109/CSE.2014.350","url":null,"abstract":"Free and open in nature, open cloud platforms have enjoyed their wide acceptance in academic institutions and enterprises. Fair and insightful comparisons of these available open cloud platforms, however, can still be a challenging task, mainly due to lack of an appropriate evaluation methodology. In this paper, we thus attempt to perform a quantitative evaluation on open IaaS platforms, and such a method of evaluation is based on the standpoint and the perspective of the end software consumers. In essence, based on ISO/IEC 25010:2011 and NIST Cloud Computing Reference Model, we develop a number of rules to score the key features of the open cloud platforms. As an example to showcase this method, the quantitative results and the scores of a few well-known IaaS platforms are reported.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133186794","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
FMA-RRSS: Fingerprint Matching Algorithm Based on Relative Received Signal Strength in Indoor Wi-Fi Positioning FMA-RRSS:基于相对接收信号强度的室内Wi-Fi定位指纹匹配算法
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.212
Guangyu Dong, Kai Lin, Keqiu Li, Huayong Luo, Xiangwen Zhang
{"title":"FMA-RRSS: Fingerprint Matching Algorithm Based on Relative Received Signal Strength in Indoor Wi-Fi Positioning","authors":"Guangyu Dong, Kai Lin, Keqiu Li, Huayong Luo, Xiangwen Zhang","doi":"10.1109/CSE.2014.212","DOIUrl":"https://doi.org/10.1109/CSE.2014.212","url":null,"abstract":"Indoor positioning based on Wi-Fi signal attracts a lot of attention in the location field. However, accuracy of positioning is often affected due to the instability of indoor Wi-Fi signal. In order to overcome this problem and reduce the errors, we present a new indoor WiFi-based positioning algorithm called FMA-RRSS which is the abbreviation of Fingerprint Matching Algorithm Based on Relative Received Strength Signal. In this paper, we propose a new position-determined model to produce location information from WiFi signal. Combined with the traditional solution of fingerprint database in indoor positioning, we use relative RSS value representing location information to estimate a clients actual position. We set up a positioning system and implement the FMA-RRSS in the actual WiFi environment. The experimental results show the improvement of positioning accuracy, fingerprint training complexity and response time of matching algorithm compared with other traditional indoor positioning algorithm like RADAR and Free Loc.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129950886","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
Modeling Geospatial Sensor Knowledge under a Semantic Sensor Web Environment 语义传感器Web环境下地理空间传感器知识建模
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.215
Xiaoliang Meng, Yuwei Wang, Yunhao Wu
{"title":"Modeling Geospatial Sensor Knowledge under a Semantic Sensor Web Environment","authors":"Xiaoliang Meng, Yuwei Wang, Yunhao Wu","doi":"10.1109/CSE.2014.215","DOIUrl":"https://doi.org/10.1109/CSE.2014.215","url":null,"abstract":"In recent years, developments in Internet of things and ubiquitous computing have created new opportunities to promote sensors participation in environmental, military and personalized monitoring. Up to now, sensor networks have been proposed for various applications, which are however characterized by a lack of interoperability. In this context, the paper gives a survey on semantic sensor web, and proposes a general method for modeling geospatial sensor knowledge by adding semantic annotations and rule reasoning to the Sensor ML (Sensor Model Language) described sensor information within OGC (Open Geospatial Consortium) SWE (Sensor Web Enablement) framework. We describe the air quality monitoring instance which gives a solution for automatically reporting the health implications and cautionary statements to the nearby people. This work constitutes an essential step towards the geospatial knowledge modeling of interoperable and intelligent sensor networks.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124839492","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
A Fruit Recognition Method via Image Conversion Optimized through Evolution Strategy 基于进化策略优化的图像转换水果识别方法
2014 IEEE 17th International Conference on Computational Science and Engineering Pub Date : 2014-12-19 DOI: 10.1109/CSE.2014.278
M. Vogl, Jang-Yoon Kim, Shin-Dug Kim
{"title":"A Fruit Recognition Method via Image Conversion Optimized through Evolution Strategy","authors":"M. Vogl, Jang-Yoon Kim, Shin-Dug Kim","doi":"10.1109/CSE.2014.278","DOIUrl":"https://doi.org/10.1109/CSE.2014.278","url":null,"abstract":"This research is to propose a fast and highly accurate object recognition method especially for fruit recognition applications to be used in a mobile environment. Conventional techniques are based on one or more of the basic features that characterize an object: color, shape, texture and intensity, causing performance or accuracy limitations in a mobile environment. Thus, this paper presents a combined approach that transforms basic features into their associated code fields to generate an object code that could be used as a search key in a feature database. Parameters used in the experiment have been optimized by using Evolution Strategies and an increase in accuracy by up to 10% has been achieved. A fruit database consisting of 36 different classes of fruits and 1108 fruit images overall has been used to obtain the experimental results. The results show an average accuracy of more than 98% and performance increase compared to different approaches on fruit image recognition.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"60 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134095709","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: 9
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