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Zhang X.,Hubei University | Zhang X.,National Engineering Research Center for Multimedia Software | Zhang X.,Wuhan Institute of Posts and Telecommunications science | Wu C.,Hubei University | Wu C.,National Engineering Research Center for Multimedia Software
Proceedings - 2013 4th International Conference on Digital Manufacturing and Automation, ICDMA 2013 | Year: 2013

Cloud computing has attracted much interest recently from both industry and academic. More and more Internet applications are moving to the cloud environment. This paper proposes a Petri nets based test case selection model for service composition in cloud, Petri nets are used to establish testing model for basic services, components, test cases and other components. Aspect-orientation is used to weave testing crosscutting concerns of cloud application, which includes component testing concern and testing concern of service composition. Based on this, the test cases selection model for service composition is given, and the operation semantics and related theories of Petri nets help prove its effectiveness and feasibility. © 2013 IEEE.


Zhang X.Y.,Hubei University | Zhang X.Y.,National Engineering Research Center for Multimedia Software | Zhang X.Y.,Wuhan Institute of Posts and Telecommunications science | Wu C.L.,Hubei University | Wu C.L.,National Engineering Research Center for Multimedia Software
Advanced Materials Research | Year: 2013

Cloud computing has attracted much interest recently from both industry and academic. More and more Internet applications are moving to the cloud environment. This paper proposes an aspect oriented method to model and analyze self-recovery of cloud application according to its characteristics. Petri nets are used as the formal description language for cloud application, and use it to describe its basic elements, such as, cloud module, resource service, physical machine, virtual machine, etc. Aspect oriented programming method is used to extract self-recovery process as the core and crosscutting concerns. On this basis, the self-recovery approach is presented, the related theories and tools of Petri nets are used to verify the correctness of proposed method. Experiments show that the proposed solutions have better performance in supporting the self-healing Web service composition. © (2013) Trans Tech Publications, Switzerland.


Chang J.,Wuhan University | Chang J.,National Engineering Research Center for Multimedia Software | Hu R.,Wuhan University | Hu R.,National Engineering Research Center for Multimedia Software | And 2 more authors.
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | Year: 2011

A method of video features correlation analysis is proposed, by using the latent self-correlations and cross-correlation which exist in the visual features and semantics, it can retain the core element of the semantic structure in video content , and eliminate the interference induced by the redundant relationships. It is proved in practice that proposed method make better outcome of semantic-based video retrieval, and to improve the computational efficiency by reducing the size of matrix.


Huang L.,Hubei University | Wu C.L.,Hubei University | Wu C.L.,National Engineering Research Center for Multimedia Software
Advanced Materials Research | Year: 2013

The resource getting core of knowledge Service System is the search engine, but the most studies only put attention to improve efficiency, so as to mass resources retrieval results still allows the user to face cognitive overload problem when the user to use searcher to get knowledge, how to provide personalized search results become a research focus. This paper provide a new personalized search ranking method, which use semantic tag and user profile to personalized the search results. The experimental results indicate that the method is effective. © (2013) Trans Tech Publications, Switzerland.


Wu C.,Wuhan University | Wu C.,National Engineering Research Center for Multimedia Software | Wu J.,Wuhan University | Wu J.,National Engineering Research Center for Multimedia Software | And 5 more authors.
Journal of Computational Information Systems | Year: 2013

Linked course data (LCD) is a E-learning web-site that allows search and catalog of engineering education and computer science education resources for higher education and educators and students. In this paper, we propose a new LCD that can give different and personal knowledge recommendation for users with different educational background and accomplish this function automatically. We describe architecture of linked course data grounded in background knowledge from the Linked Open Data cloud. We represent a object's meaning by mapping properties to classes in an appropriate ontology, linking strings to literal constants, implied measurements, or entities in the linked data cloud and discovering or and identifying relations between properties. We explore semantic relationships among knowledge and set up user profile by user log, then classify them and establish user model. Copyright © 2013 Binary Information Press.


Chen Y.,Hubei University | Wu C.,Hubei University | Wu C.,National Engineering Research Center for Multimedia Software | Xie M.,Hubei University | And 3 more authors.
Journal of Computers | Year: 2011

Recommender systems are being widely applied in many fields, such as e-commerce etc, to provide products, services and information to potential customers. Collaborative filtering as the most successful approach, which recommends contents to the current customers mainly is based on the past transactions and feedback of the similar customer. However, it is difficult to distinguish the similar interests between customers because the sparsity problem is caused by the insufficient number of the transactions and feedback data, which confined the usability of the collaborative filtering. This paper proposed the direct similarity and the indirect similarity between users, and computed the similarity matrix through the relative distance between the user's rating; using association retrieval technology to explore the transitive associations based on the user's feedback data, realized a new collaborative filtering approach to alleviate the sparsity problem and improved the quality of the recommendation. In the end, we implemented experiment based on Movielens data set, the experiment results indicated that the proposed approach can effectively alleviate the sparsity problem, have good coverage rate and recommendation quality. © 2011 ACADEMY PUBLISHER.


Chen Y.,Hubei University | Chen Y.,National Engineering Research Center for Multimedia Software | Wu C.,Hubei University | Wu C.,National Engineering Research Center for Multimedia Software | And 6 more authors.
Journal of Computational Information Systems | Year: 2011

Last.FM and MovieLens allow user to share items they like with family, friends, or the online community at large. An important facet of these services is that users manually annotate the items using so called tags, which describe the contents of the items or provide additional contextual and semantical information. There are many researches about using tag to improve the quality of recommendation. However, Unlike attributes which are "global" descriptions of items, tags are "local" descriptions of items given by the users, the different people use the different tags for the same item, but the tags maybe represent the same means. In this paper, we use tag grouping method to group the tag according to the similarity of co-occurrence distributions. Based on it, this paper proposed an approach to group synonymy tags and fusing the relationship between users-tag with the collaborative filtering algorithms. The results of the empirical evaluation show that the approach is effectiveness in augmenting recommendation. Copyright © 2011 Binary Information Press.


Guo X.,Wuhan University | Guo X.,National Engineering Research Center for Multimedia Software | Wu C.,Wuhan University | Wu C.,National Engineering Research Center for Multimedia Software | And 4 more authors.
Journal of Computational Information Systems | Year: 2011

User Modeling is a key technology of personalization recommender. A rational user model can not only improve the recommended service standard, but also build a stable user relationship. It improves the degree of user's loyalty and prevents the user outflow. This paper respectively analyzed the disadvantage of the modeling technique of BN (Bayesian Network) and the ontology modeling technique. It proposed a new technique of user modeling based on ontology and BN. Firstly, It generated a personalized ontology from the domain ontology by ontology mapping technology as part of the user model; and then used statistical methods and BN to detect the users' cognitive ability, learning style, and so on. Finally, it combined the above methods to build a user model which can express the users' personalization characterization and the semantic relationship between users' domain knowledge. The experiment results indicate that this approach can improve the performance of recommender system. © 2005 by Binary Information Press.


Zhang X.,Wuhan University | Zhang X.,National Engineering Research Center for Multimedia Software | Zhang X.,Wuhan Institute of Posts and Telecommunications science | Wu C.,Wuhan University | Wu C.,National Engineering Research Center for Multimedia Software
WIT Transactions on Information and Communication Technologies | Year: 2014

This paper proposes a method to model and analyze failure model for cloud application according to its characteristics. Petri nets are used as the formal description language for cloud application, and use it to describe its basic elements, such as, cloud module, resource service, physical machine, virtual machine, and so on. We formally model the basic relationship between cloud modules, the interaction between physical machine and virtual machine. The correctness of constructed model is analyzed based on the operation characteristics and the state space of the constructed model. Finally, a specific example is used to explain the model and analyze processes of cloud computing. © 2014 WIT Press.


Guo X.,Wuhan University | Hu R.,National Engineering Research Center for Multimedia Software
10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010 | Year: 2010

With the rapid development of industrialization, security situation becomes more and more serious in China. Many cities have established crime prevention systems in order to maintain social stability. With the number of crime prevention system increasing, we need to assess their effectiveness in a scientific and objective manner. In this paper, we first introduce the effectiveness evaluation model based on the concept of risk entropy (the origin of the idea) in crime prevention system. We then apply the Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation methods in the model analysis. We not only solve the problem of interference on subject factors in traditional qualitative method for crime prevention system, but also improve the assessment objectively. In the next stage, we conduct the simulation experiment according to the specific examples of crime prevention system. The case study shows that the assessment results are consistent with the reality and this method can be reasonably used for the effectiveness evaluation of crime prevention system. We believe this work contributes to the theoretical framework guiding the design, development, and deployment of the crime prevention system.

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