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Research of Software Testing Model based on Correlation Defect
Jin Jiangang,Sun Shibao,Bao Xiaoan 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.2
Analysis of existing research results of defect testing, software defects during testing should consider the relevance of the defect test software, the design of a Markov chain with the right to test the model, the design of a multi-objective algorithm weights given Markov chain with the right test strategy based on defects associated with the state transition strategy based on multi-objective test weight matrix. The experimental results show that this strategy compared with Controlled Markov Chain testing strategy that can significantly reduce test cases and improve the defect detection rate.
Research into a RFID Neural Network Localization Algorithm
Jiangang Jin 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.5
The accuracy of indoor positioning algorithm has been the focus of research. In this paper, a particle swarm optimization algorithm based on particle swarm optimization algorithm and K -means algorithm is proposed. In this paper, firstly, the indoor positioning RFID model is constructed, and the positioning equation is constructed, then reduce the clustering algorithm to avoid human interference, through the K - means algorithm to form a particle swarm algorithm to initialize the particle swarm algorithm, finally, the particle swarm optimization algorithm is used to train all the parameters of RBF neural network, and then the optimal output model is obtained. Simulation results show that the algorithm can effectively improve the positioning accuracy, reduce energy consumption, and improve the positioning accuracy of 10%.
Efficient Keyword Search Scheme in Encrypted Cloud Computing Environment
Jiangang Shu,Xingming Sun,Lu Zhou,Jin Wang 보안공학연구지원센터 2014 International Journal of Grid and Distributed Comp Vol.7 No.5
With the increasing popularity of cloud computing, more and more sensitive or private information has been outsourced onto the cloud server. For protecting data privacy, sensitive data usually has to be encrypted before outsourcing, which makes traditional search techniques based on plaintext useless. In response to the search over encrypted data, searchable encryption is a good solution in Information Security. However, most of existing searchable encryption schemes only support exact keyword search. That means they don’t support searching for different variants of the query word, which is a significant drawback and greatly affects data usability and user experience. Recently, a fuzzy keyword search scheme proposed by some researchers aims at addressing the problems of minor typos and format inconsistence but couldn’t solve the problem above. In this paper, we formalize the problem of semantic keyword-based search over encrypted cloud data while preserving privacy. Semantic keyword-based search will greatly improves the user experience by returning all the documents containing semantically close keywords related to the query word. In our solution, we use the stemming algorithm to construct stem set, which reduces the dimension of index. And the symbol-based trie is also adopted in index construction to improve the search efficiency. Through rigorous privacy analysis and experiment on real dataset, our scheme is secure and efficient.
Research of Data-Aiming Mining Algorithm in Cloud Environment
Jiangang Jin 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.4
Cloud computing contains a huge amount of data, which are featured as being widely distributed, heterogeneous, and dynamic. Thus, aiming at how to mine useful parts in these information, this paper proposes an Apriori algorithm based on cloud computing and introduces cost-sensitive learning and non-filter matrix to find k frequency set and uses the method of generating association rules to improve effectiveness of data mining. Simulation experiments show that mining algorithm in this paper is highly effective and suitable for data mining in the context of cloud computing.
Jin Yi,Su Guodong,Yu Jiangang 대한화학회 2021 Bulletin of the Korean Chemical Society Vol.42 No.6
A Mannich reaction of 2,2,2-trifluoroethylamine hydrochloride, paraformaldehyde and acetophenone was described both in oil bath and microwave-heating conditions to give main products varied from trifluoroethyl derived tertiary to secondary amine. In the microwave-heating manner, the reaction was carried out in a commercial available microwave oven and took only 10 min to complete this transformation. After a simple post-treatment including washing and recrystallization, the product of trifluoroethyl derived secondary amine was obtained in high yield (71.4%).