Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045126
Surat Khan, Bin Zhang, Faizullah Khan, Siqi Chen
To predict the market trends, to improve enterprise performance, and for the smarter business outcomes, Business intelligence (BI) "an integrated set of tools, technologies and programmed products that are used to collect, integrate, analyze and make data available", become the basic need for the businesses. Due Economic, technological and human resource constraints, the SMEs are not able to achieve the benefits of BI. In this paper we proposes, firstly Bl-in-Cloud computing Model for SMEs, to meet their goals for profitability, revenue, cost reduction, and risk management, Secondly the regional telecom operator as Bl-in-Cloud platform and Service provider, under the supervision of regulatory authorities, with the support of government and concerned bodies.
{"title":"Business intelligence in the cloud: A case of Pakistan","authors":"Surat Khan, Bin Zhang, Faizullah Khan, Siqi Chen","doi":"10.1109/CCIS.2011.6045126","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045126","url":null,"abstract":"To predict the market trends, to improve enterprise performance, and for the smarter business outcomes, Business intelligence (BI) \"an integrated set of tools, technologies and programmed products that are used to collect, integrate, analyze and make data available\", become the basic need for the businesses. Due Economic, technological and human resource constraints, the SMEs are not able to achieve the benefits of BI. In this paper we proposes, firstly Bl-in-Cloud computing Model for SMEs, to meet their goals for profitability, revenue, cost reduction, and risk management, Secondly the regional telecom operator as Bl-in-Cloud platform and Service provider, under the supervision of regulatory authorities, with the support of government and concerned bodies.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125416237","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}
Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045114
Shelly, N. S. Raghava
Cloud computing is one of the highly researched areas today, with an objective of taking advantage of various computational resources. In this paper we have used cloud computing environment with the aim to speed up the matching process of biometric traits. We have used iris recognition, a biometric technique, as it is one of the strongest method of authentication. Also Iris recognition is stable over time. We have used Hadoop [1], an open source cloud computing environment, to develop this model. Hadoop implements Map/Reduce [1] framework in Java. Map/Reduce make easy to process large amount of data on cloud. The results shows that there is an effective speedup and efficiency gain of Iris template matching on Hadoop process over sequential process.
{"title":"Iris recognition on Hadoop: A biometrics system implementation on cloud computing","authors":"Shelly, N. S. Raghava","doi":"10.1109/CCIS.2011.6045114","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045114","url":null,"abstract":"Cloud computing is one of the highly researched areas today, with an objective of taking advantage of various computational resources. In this paper we have used cloud computing environment with the aim to speed up the matching process of biometric traits. We have used iris recognition, a biometric technique, as it is one of the strongest method of authentication. Also Iris recognition is stable over time. We have used Hadoop [1], an open source cloud computing environment, to develop this model. Hadoop implements Map/Reduce [1] framework in Java. Map/Reduce make easy to process large amount of data on cloud. The results shows that there is an effective speedup and efficiency gain of Iris template matching on Hadoop process over sequential process.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127756756","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}
Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045066
Cho Cho Khaing, Thinn Thu Naing
The widespread popularity of Cloud computing as a preferred platform for the deployment of web applications has resulted in an enormous number of applications moving to the cloud, and the huge success of cloud service providers. The data center storage management plays a vital role in cloud computing environments. Especially the PC cluster-based data storage is necessary to manage data on low cost storage servers in which storage space can be reduced. This system presents an efficient data storage approach to work out many nodes in a cluster using Cloud-based Distributed File System (CDFS) compatible file system with variable chunk size to facilitate massive data processing. This system introduces the implementation enhancement on MapReduce to improve the system throughput and the scalability to keep on working with the amount of existing physical storage capacity when the number of users and files increase. Then CDFS also reduces the storage space in the storage server using Huffman Compression.
{"title":"The efficient data storage management system on cluster-based private cloud data center","authors":"Cho Cho Khaing, Thinn Thu Naing","doi":"10.1109/CCIS.2011.6045066","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045066","url":null,"abstract":"The widespread popularity of Cloud computing as a preferred platform for the deployment of web applications has resulted in an enormous number of applications moving to the cloud, and the huge success of cloud service providers. The data center storage management plays a vital role in cloud computing environments. Especially the PC cluster-based data storage is necessary to manage data on low cost storage servers in which storage space can be reduced. This system presents an efficient data storage approach to work out many nodes in a cluster using Cloud-based Distributed File System (CDFS) compatible file system with variable chunk size to facilitate massive data processing. This system introduces the implementation enhancement on MapReduce to improve the system throughput and the scalability to keep on working with the amount of existing physical storage capacity when the number of users and files increase. Then CDFS also reduces the storage space in the storage server using Huffman Compression.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121340418","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}
Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045129
Qifeng Li, Bing Li
The Open Source Software (OSS) management has attracted considerable attention in the last few years. Project management for effective software process improvement must be achieved based on quantitative data. However, because data collection for measurement requires high costs and collaboration with developers, and data dumps may require a huge effort to understand schemas and tables. It is difficult to collect coherent, quantitative data continuously and to utilize the data for practicing software process improvement. In this paper, we report our results of mining data acquired from SourceForge.net, the largest open source software hosting website. In the process we describe Mailing list Crawler (MC) which automatically collects Mailing lists repositories in widely used software development support systems. Providing integrated measurement results graphically, MC can help developers/managers keep projects under control in real time.
{"title":"Mining Open Source Software data using regular expressions","authors":"Qifeng Li, Bing Li","doi":"10.1109/CCIS.2011.6045129","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045129","url":null,"abstract":"The Open Source Software (OSS) management has attracted considerable attention in the last few years. Project management for effective software process improvement must be achieved based on quantitative data. However, because data collection for measurement requires high costs and collaboration with developers, and data dumps may require a huge effort to understand schemas and tables. It is difficult to collect coherent, quantitative data continuously and to utilize the data for practicing software process improvement. In this paper, we report our results of mining data acquired from SourceForge.net, the largest open source software hosting website. In the process we describe Mailing list Crawler (MC) which automatically collects Mailing lists repositories in widely used software development support systems. Providing integrated measurement results graphically, MC can help developers/managers keep projects under control in real time.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133511584","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}
Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045049
Sisi Chen
Mutual information (MI) is always used as the indicator of nonlinear correlation between the variables. The computation of MI can be finished only the continuous-value variables are discretized. In this paper, one new strategy of computing the MI between variables is proposed. The probability density estimation (PDE) is used to determine the density functions in our method. An approximate technology is applied to replace the computation of integral. Finally, MI based on PDE can be obtained. Through the artificially experimental simulations, the performance and rationality of our new method are demonstrated. The experimental results show that our method is feasible, effective and efficient.
{"title":"Measuring the correlation between variables based on the probability density function estimation","authors":"Sisi Chen","doi":"10.1109/CCIS.2011.6045049","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045049","url":null,"abstract":"Mutual information (MI) is always used as the indicator of nonlinear correlation between the variables. The computation of MI can be finished only the continuous-value variables are discretized. In this paper, one new strategy of computing the MI between variables is proposed. The probability density estimation (PDE) is used to determine the density functions in our method. An approximate technology is applied to replace the computation of integral. Finally, MI based on PDE can be obtained. Through the artificially experimental simulations, the performance and rationality of our new method are demonstrated. The experimental results show that our method is feasible, effective and efficient.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133300705","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}
Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045048
Ye Liang
When we take cognizance of the regular track of moving objects within a limited area, we put forward an improved moving objects indexing model in mobile computing environment based on Time-Parameterized R-tree (GG TPR-tree). With the GG TPR-tree, we can index moving objects which are neighbors and will run to the same direction in the future to improve the efficiency. So, we put forward the indexing model for the moving objects, and moving objects indexing maintenance algorithm and moving objects indexing update algorithm. Experimental results show that the performance of GG TPR-tree's indexing moving inexing is better than the other indexing model on managing a great capacity of moving objects within a limited area.
{"title":"Improved moving objects indexing model in mobile computing environment","authors":"Ye Liang","doi":"10.1109/CCIS.2011.6045048","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045048","url":null,"abstract":"When we take cognizance of the regular track of moving objects within a limited area, we put forward an improved moving objects indexing model in mobile computing environment based on Time-Parameterized R-tree (GG TPR-tree). With the GG TPR-tree, we can index moving objects which are neighbors and will run to the same direction in the future to improve the efficiency. So, we put forward the indexing model for the moving objects, and moving objects indexing maintenance algorithm and moving objects indexing update algorithm. Experimental results show that the performance of GG TPR-tree's indexing moving inexing is better than the other indexing model on managing a great capacity of moving objects within a limited area.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130953959","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}
Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045034
Xiaoru Wang, Junping Du, Jie Liu
This paper proposes and evaluates a new semantics based segmentation algorithm for scene images. This algorithm has two phases: the initial segmentation based on color-spatial information and region merging based semantics information. The initial segmentation uses an automatic region growth method without the need of seeds. It avoids the loss of detailed color information of the scene images by using non-quantized colors in region growth. This paper also innovatively includes the underlying semantics of the scene images during the region merging. The experiments show the new segmentation algorithm is very efficient and effective and could get a very accurate segmentation for scene images. The main regions also match well to people's visual perception.
{"title":"A semantics based segmentation algorithm for scene images","authors":"Xiaoru Wang, Junping Du, Jie Liu","doi":"10.1109/CCIS.2011.6045034","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045034","url":null,"abstract":"This paper proposes and evaluates a new semantics based segmentation algorithm for scene images. This algorithm has two phases: the initial segmentation based on color-spatial information and region merging based semantics information. The initial segmentation uses an automatic region growth method without the need of seeds. It avoids the loss of detailed color information of the scene images by using non-quantized colors in region growth. This paper also innovatively includes the underlying semantics of the scene images during the region merging. The experiments show the new segmentation algorithm is very efficient and effective and could get a very accurate segmentation for scene images. The main regions also match well to people's visual perception.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115748472","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}
Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045147
Wen Gong, Wan-sen Wang
In order to accurately build the learner's learning style in E-Learning, according to the needs and preferences to provide personalized learning materials and harmonious human-computer interaction environment. This paper combines Felder-Silverman learning style with support vector machine technology, and use machine learning technologies for learners to build dynamic learning style. Through the analysis of the Emotion and recognition interaction of the personalized E-Learning based on statistical learning theory and support vector machine technology, it demonstrates the correctness and feasibility using support vector machine to build learning styles. The combination of support vector machine, emotion and recognition interaction in the personalized E-Learning makes great contribution to build human-computer interaction environment.
{"title":"Application research of support vector machine in E-Learning for personality","authors":"Wen Gong, Wan-sen Wang","doi":"10.1109/CCIS.2011.6045147","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045147","url":null,"abstract":"In order to accurately build the learner's learning style in E-Learning, according to the needs and preferences to provide personalized learning materials and harmonious human-computer interaction environment. This paper combines Felder-Silverman learning style with support vector machine technology, and use machine learning technologies for learners to build dynamic learning style. Through the analysis of the Emotion and recognition interaction of the personalized E-Learning based on statistical learning theory and support vector machine technology, it demonstrates the correctness and feasibility using support vector machine to build learning styles. The combination of support vector machine, emotion and recognition interaction in the personalized E-Learning makes great contribution to build human-computer interaction environment.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122645875","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}
Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045128
Xinhua Yu, Shaozhong Cao
As an industrial field-bus, and because of reliable communication, real-time, flexibility, strong anti-jamming capability, long transmission distance etc, CAN bus is widely applied in all kinds of control field. The high-speed printing presses with multiple color as the background, this paper presents the communication of CAN bus used in synchronization control of multi-motor based on DSP, the combination of PC and DSP controllers by a CAN bus communication card, realizes many sets of permanent magnet synchronous motors coordination synchronous control, makes the synchronous control system more accurate and more flexible. This means of communication lay a foundation for better application in a lot of distributed control system.
{"title":"The communication of CAN bus used in synchronization control of multi-motor based on DSP","authors":"Xinhua Yu, Shaozhong Cao","doi":"10.1109/CCIS.2011.6045128","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045128","url":null,"abstract":"As an industrial field-bus, and because of reliable communication, real-time, flexibility, strong anti-jamming capability, long transmission distance etc, CAN bus is widely applied in all kinds of control field. The high-speed printing presses with multiple color as the background, this paper presents the communication of CAN bus used in synchronization control of multi-motor based on DSP, the combination of PC and DSP controllers by a CAN bus communication card, realizes many sets of permanent magnet synchronous motors coordination synchronous control, makes the synchronous control system more accurate and more flexible. This means of communication lay a foundation for better application in a lot of distributed control system.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114430639","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}
Pub Date : 2011-10-13DOI: 10.1109/CCIS.2011.6045076
Shun-Fa Yang, Wei-Yu Chen, Yao-Tsung Wang
Cloud computing can reduce mainframe management costs, so more and more users choose to build their own cloud hosting environment. In cloud computing, all the commands through the network connection, therefore, information security is particularly important. In this paper, we will explore the types of intrusion detection systems, and integration of these types, provided an effective and output reports, so system administrators can understand the attacks and damage quickly. With the popularity of cloud computing, intrusion detection system log files are also increasing rapidly, the effect is limited and inefficient by using the conventional analysis system. In this paper, we use Hadoop's MapReduce algorithm analysis of intrusion detection System log files, the experimental results also confirmed that the calculation speed can be increased by about 89%. For the system administrator, IDS Log Cloud Analysis System (called ICAS) can provide fast and high reliability of the system.
{"title":"ICAS: An inter-VM IDS Log Cloud Analysis System","authors":"Shun-Fa Yang, Wei-Yu Chen, Yao-Tsung Wang","doi":"10.1109/CCIS.2011.6045076","DOIUrl":"https://doi.org/10.1109/CCIS.2011.6045076","url":null,"abstract":"Cloud computing can reduce mainframe management costs, so more and more users choose to build their own cloud hosting environment. In cloud computing, all the commands through the network connection, therefore, information security is particularly important. In this paper, we will explore the types of intrusion detection systems, and integration of these types, provided an effective and output reports, so system administrators can understand the attacks and damage quickly. With the popularity of cloud computing, intrusion detection system log files are also increasing rapidly, the effect is limited and inefficient by using the conventional analysis system. In this paper, we use Hadoop's MapReduce algorithm analysis of intrusion detection System log files, the experimental results also confirmed that the calculation speed can be increased by about 89%. For the system administrator, IDS Log Cloud Analysis System (called ICAS) can provide fast and high reliability of the system.","PeriodicalId":128504,"journal":{"name":"2011 IEEE International Conference on Cloud Computing and Intelligence Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115044083","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}
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