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Hong L.,Huaihai Institute of Technology | Hong L.,Jiangsu Province R and D Institute of Marine Resources
Journal of Information and Computational Science | Year: 2013

Clonal Selection Algorithm (CSA) has been applied widely in intelligent computationfield, but the global convergence theoretical analysis and research works about CSA were rare relatively. The global convergence of an improved clonal selection algorithm is investigated in this paper. Through the definition of global convergence in probability, the classical homogeneous Markov chain analyses is replaced by a new pure probability and iterative formula method, and the convergence results of the improved clonal selection algorithm are obtained. This method makes the global convergence research greatly simplified and enriches new contents for the theoretical foundation of the clonal selection algorithm. Copyright © 2013 Binary Information Press. Source


Lichao F.,Huaihai Institute of Technology | Lichao F.,Jiangsu Province R and D Institute of Marine Resources | Chunwei G.,Harbin Institute of Technology | Yunpeng W.,Harbin Institute of Technology | And 2 more authors.
Advanced Materials Research | Year: 2013

Cement paste with addition of a small amount of (0.9wt%) nano-TiO2 were prepared. Flexural strength and compressive strength testing results showed that by adding a small amount of nano TiO2 with good dispersion, the 28-day flexural strength and compressive strength of cement paste modified by nano-TiO2 was increased by 16.12%, and 14.15%, respectively. © (2013) Trans Tech Publications, Switzerland. Source


Wang X.,China Institute of Technology | Li H.,China Institute of Technology | Li H.,Jiangsu Province R and D Institute of Marine Resources | Zhang S.,China Institute of Technology
International Journal of Digital Content Technology and its Applications | Year: 2012

Collaborative filtering is one of the most successful and widely used methods of automated product recommendation in online stores. With the gradual increase of customers and products in electronic commerce systems, the time consuming nearest neighbor collaborative filtering search of the target customer in the total customer space resulted in the failure of ensuring the real time requirement of recommender system. Sparsity of source data set is the major reason causing the poor quality. In order to provide high-quality recommendations even when data are sparse, this paper proposed a personalization recommendation algorithm based on rough set, The algorithm refine the user ratings data using attribution reduction, then uses a new similarity measure based on the quality of approximation of classification to find the target users' neighbors, and then generates recommendations. To prove our algorithm's effectiveness, the authors conduct experiments on the public dataset. Theoretical analysis and experimental results show that this method is efficient and effective. Source


Li H.,China Institute of Technology | Li H.,Jiangsu Province R and D Institute of Marine Resources | Zhang S.,China Institute of Technology | Wang X.,China Institute of Technology
International Journal of Digital Content Technology and its Applications | Year: 2012

Outlier detection has attracted substantial attention in many applications and research areas, and it has become a hot issue in the field of data mining. The task of outlier detection is to find small groups of data objects that are exceptional when compared with rest large amount of data. This paper proposes a new outlier detection algorithm combining the rough set and information entropy technology. The approach can obtain similar outlier sets by means of searching in an attributes subspace, which leads the analysis of outlier detection to focus on narrower and more specific object fields. This algorithm divides the original attribute space into several segments. Then to select those subjects with largest relative entropy and negative relative cardinality to be the outlier date set. To prove our algorithm's effectiveness, the authors conduct experiments on the public data sets. Theoretical analysis and experimental results show that this method is efficient and effective. Source


Shi J.,China Institute of Technology | Li H.,China Institute of Technology | Li H.,Jiangsu Province R and D Institute of Marine Resources | Hu Y.,China Institute of Technology | Huang E.,University of Detroit Mercy
International Journal of Digital Content Technology and its Applications | Year: 2012

Cloud computing is clearly one of today's most enticing technology areas due, at least in part, to its cost-efficiency and flexibility. The cloud infrastructure provider in a cloud computing platform must provide security and isolation guarantees to a service provider, who builds the service(s) for such a platform. As a new internet-based super computing model, the cloud computing technology has aroused great concern, and facing an increasing number of security threats at the same time. We describe how the combination of existing research thrusts has the potential to alleviate many of the concerns impeding adoption. In particular, we discuss some key technologies in cloud computing such as control to data in cloud computing, security and privacy guarantees for cloud data, virtualized safe technology, trusted cloud computing, encrypted data storage. Those methods improve the high availability of data. Protection measures from the data storage to transmission are taken to ensure safety. Source

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