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High-performance content-based image retrieval using DFS strategy 使用DFS策略的高性能基于内容的图像检索
2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 2013-12-01 DOI: 10.1109/GrC.2013.6740420
Ja-Hwung Su, Chung-Chieh Hsu, J. Ying
{"title":"High-performance content-based image retrieval using DFS strategy","authors":"Ja-Hwung Su, Chung-Chieh Hsu, J. Ying","doi":"10.1109/GrC.2013.6740420","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740420","url":null,"abstract":"Image data is becoming more and more popular due to the prevalence of image capture devices. How to retrieve the images effectively and efficiently from a large number of images has been a challenging issue in recent years. To deal with such issue, the major purpose of this paper is to propose a concept- and content-aware image retrieval approach using Depth-First Search (DFS) strategy to conduct effective and efficient image semantic retrieval. For effectiveness and efficiency, since the search space is reduced into specific subspaces, the retrieval cost is decreased and the retrieval quality is increased. For semantic retrieval, our proposed method can detect the potential concepts to satisfy the user's semantic need. In the experimental result, it reveals that our proposed approach is more effective and efficient than traditional ones using Breadth-First-Search (BFS) strategy.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134619611","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
An introduction to the variable neighborhood and the related adaptive determination algorithm 介绍了变量邻域及相关的自适应确定算法
2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 2013-12-01 DOI: 10.1109/GrC.2013.6740430
Fang Wang, Wei Pan, Lifeng Wu, Yong Guan
{"title":"An introduction to the variable neighborhood and the related adaptive determination algorithm","authors":"Fang Wang, Wei Pan, Lifeng Wu, Yong Guan","doi":"10.1109/GrC.2013.6740430","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740430","url":null,"abstract":"The neighborhood-based multi-granulations rough set (NMGRS) is the latest extended model of the multi-granulations rough set (MGRS), which makes the MGRS can deal with real-value data. As one of the most important parameters, the neighborhood size has a significant impact on attribute reduction. However, the common methods to get a neighborhood size rely on keeping trying different values and experiences. And all the attributes are assigned the same value, which ignores their differences on the distribution and the contribution to the decision. Therefore, this paper proposes a new algorithm which assigns adaptively different attributes different neighborhood sizes (it is defined as the variable neighborhood) according to the data distributions. The minimal between class distances of each attribute is regarded as a very important indicator to form such a neighborhood size. The results of experiments on different types of data sets prove that the proposed algorithm can get a better attribute reduction and further make the NMGRS more pervasive and practical.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115354132","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
The analysis and prediction of stock price 股票价格的分析与预测
2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 2013-12-01 DOI: 10.1109/GrC.2013.6740438
Tao Xing, Yuan Sun, Qian Wang, Guo Yu
{"title":"The analysis and prediction of stock price","authors":"Tao Xing, Yuan Sun, Qian Wang, Guo Yu","doi":"10.1109/GrC.2013.6740438","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740438","url":null,"abstract":"Nowadays, the stock market has attracted more and more people's attention with its high risk and high returns, and forecasting method of stock price also emerge in an endless stream, such as nonlinear regression. In this paper, we introduce a kind of method based on Hidden Markov Model to forecast stock price trend. Which is different from the existing stock prediction, this paper attempts to find the hidden relationship existing between the stock prices, and corresponds to the Hidden Markov Model. The experimental result shows that, this method can get pretty accurate result, particularly effective in short period prediction.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121113643","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: 21
Combining SURF with MSER for image matching 结合SURF和MSER进行图像匹配
2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 2013-12-01 DOI: 10.1109/GrC.2013.6740423
Lei Tao, Xiaojun Jing, Songlin Sun, Hai Huang, Na Chen, Yueming Lu
{"title":"Combining SURF with MSER for image matching","authors":"Lei Tao, Xiaojun Jing, Songlin Sun, Hai Huang, Na Chen, Yueming Lu","doi":"10.1109/GrC.2013.6740423","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740423","url":null,"abstract":"Many local features such as Speeded Up Robust Features (SURF) have been widely utilized in image matching due to their notable performances. However, the original SURF algorithm ignores the geometric relationship among SURF features. To overcome this drawback, an improved method combining SURF with Maximally Stable Extremal Regions (MSER) for image matching is proposed in this paper. By combining SURF features into groups and measuring the geometric similarity among features, the discriminative power of the grouped features has been significantly increased. Simulations show that the proposed method outperforms the original SURF algorithm both in match ratio and repeatability.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127497496","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
Towards sharing disks between host OS and virtual machine with volume snapshot technology 利用卷快照技术实现主机操作系统与虚拟机之间的磁盘共享
2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 2013-12-01 DOI: 10.1109/GrC.2013.6740434
Yan Wen, Jinjing Zhao, Hua Chen, Minhuan Huang
{"title":"Towards sharing disks between host OS and virtual machine with volume snapshot technology","authors":"Yan Wen, Jinjing Zhao, Hua Chen, Minhuan Huang","doi":"10.1109/GrC.2013.6740434","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740434","url":null,"abstract":"The virtual machine technology is experiencing a resurgence of interest for diverse uses including shared hosting, server consolidation and OS compatibility. Disk sharing has been proposed to try to minimize the disk space consumption of the virtual disks. Existing disk sharing technologies on the PC platforms, however, cannot allow the host OS and the virtual machine to modify the shared disk concurrently to avoid potential data collision. To address this limitation, this paper proposes a new disk sharing mechanism to share the disk of the host OS with the virtual machine. Our approach introduces the volume snapshot technology to isolate the modification effect between the host OS and the virtual machine. In this way, we can enable the concurrent accesses to the same volumes while the data consistency can be guaranteed. The evaluation results demonstrate the feasibility of our approach while the performance evaluation shows the I/O performance achieves 89.18% of native speed on average.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124439241","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
Incremental induction of medical diagnostic rules 医疗诊断规则的增量归纳
2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 2013-10-29 DOI: 10.1109/GrC.2013.6740427
S. Tsumoto, S. Hirano
{"title":"Incremental induction of medical diagnostic rules","authors":"S. Tsumoto, S. Hirano","doi":"10.1109/GrC.2013.6740427","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740427","url":null,"abstract":"This paper proposes a method for incremental updates of medical differential diagnosis, which consists of inclusive and exclusive rules. Since the addition of an example is classified into one of four possibilities, four patterns of an update of accuracy and coverage are observed, which give two important inequalities of accuracy and coverage for induction of probabilistic rules. By using these two inequalities, the proposed method classifies a set of formulae into four subrule layers. Inclusive rules will be updated by using these rule layers. However, since exclusive rules should cover all the examples of a decision, the update algorithm is implemented by enumerative operation for elementary attribute-value pairs. The proposed method was evaluated on datasets regarding headaches, meningitis and CVD, and the results show that the proposed method outperforms the conventional methods.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114732427","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
Performance-driven live migration of multiple virtual machines in datacenters 数据中心中多个虚拟机的性能驱动实时迁移
2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 2013-02-20 DOI: 10.1109/GrC.2013.6740417
T. K. Sarker, Maolin Tang
{"title":"Performance-driven live migration of multiple virtual machines in datacenters","authors":"T. K. Sarker, Maolin Tang","doi":"10.1109/GrC.2013.6740417","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740417","url":null,"abstract":"Live migration of multiple Virtual Machines (VMs) has become an indispensible management activity in datacenters for application performance, load balancing, server consolidation. While state-of-the-art live VM migration strategies focus on the improvement of the migration performance of a single VM, little attention has been given to the case of multiple VMs migration. Moreover, existing works on live VM migration ignore the inter-VM dependencies, and underlying network topology and its bandwidth. Different sequences of migration and different allocations of bandwidth result in different total migration times and total migration downtimes. This paper concentrates on developing a multiple VMs migration scheduling algorithm such that the performance of migration is maximized. We evaluate our proposed algorithm through simulation. The simulation results show that our proposed algorithm can migrate multiple VMs on any datacenter with minimum total migration time and total migration downtime.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122527479","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: 39
MC framework: High-performance distributed framework for standalone data analysis packages over Hadoop-based cloud MC框架:用于基于hadoop的云上的独立数据分析包的高性能分布式框架
2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 1900-01-01 DOI: 10.1109/GrC.2013.6740375
Chao-Chun Chen, Nguyen Huu Tinh Giang, Tzu-Chao Lin, Min-Hsiung Hung
{"title":"MC framework: High-performance distributed framework for standalone data analysis packages over Hadoop-based cloud","authors":"Chao-Chun Chen, Nguyen Huu Tinh Giang, Tzu-Chao Lin, Min-Hsiung Hung","doi":"10.1109/GrC.2013.6740375","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740375","url":null,"abstract":"The Hadoop MapReduce is the programming model of designing the scalable distributed computing applications, that provides developers can attain automatic parallelization. However, most complex manufacturing systems are arduous and restrictive to migrate to private clouds, due to the platform incompatible and tremendous complexity of system reconstruction. For increasing the efficiency of manufacturing systems with minimum efforts on modifying source codes, a high-performance framework is designed in this paper, called Multi-users-based Cloud-Adaptor Framework (MC-Framework), which provides the simple interface to users for fairly executing requested tasks worked with traditional standalone data analysis packages in MapReduce-based private cloud environments. Moreover, this framework focuses on multiuser workloads, but the default Hadoop scheduling scheme, i.e., FIFO, would increase delay under multiuser scenarios. Hence, a new scheduling mechanism, called Job-Sharing Scheduling, is designed to explore and fairly share the jobs to machines in the private cloud. Then, we prototype an experimental virtual-metrology module of a manufacturing system as a case study to verify and analysis the proposed MC-Framework. The results of our experiments indicate that our proposed framework enormously improved the time performance compared with the original package.","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","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":"130093575","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 fuzzy data mining approach for remote sensing image recommendation 遥感图像推荐的模糊数据挖掘方法
2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 1900-01-01 DOI: 10.1109/GrC.2013.6740410
E. H. Lu, Jung-Hong Hong, Z. Su, Chun-Hao Chen
{"title":"A fuzzy data mining approach for remote sensing image recommendation","authors":"E. H. Lu, Jung-Hong Hong, Z. Su, Chun-Hao Chen","doi":"10.1109/GrC.2013.6740410","DOIUrl":"https://doi.org/10.1109/GrC.2013.6740410","url":null,"abstract":"Nowadays research on Remote Sensing Images (RS-Images) ranking and recommendation for meeting the user-specific Area-Of-Interest (AOI) has received a log of attentions due to a wide range of potential applications. In this paper, we propose a novel approach named Fuzzy rs-Image Recommender (FIR) to rank and recommend relevant RS-Images according to the queried AOI. In FIR, we first propose two features named Available Space (AS) and Image Extension (IE) as two indicators to represent the relationships between AOI and RS-Image. Then, we mine the fuzzy association rules between the proposed indicators and user rating score. Finally, we propose two fuzzy inference strategies named FIR with Weightarea (FIR_area) and FIR with Weightall(FIR_all) to rank and recommend the relevant RS-Images to users. To our best knowledge, this is the first work on RS-Image recommendation that considers the issues of feature extraction and fuzzy rule mining, simultaneously. Through comprehensive experimental evaluations, the results show that the proposed FIR approach outperforms the state-of-the-art approach Hausdorff in terms of Normalized Discounted Cumulative Gain (NDCG).","PeriodicalId":415445,"journal":{"name":"2013 IEEE International Conference on Granular Computing (GrC)","volume":"8 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":"114958085","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
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