Hydraulic metal structure health diagnosis based on data mining technology

In conjunction with association rules for data mining, the connections between testing indices and strong and weak association rules were determined, and new derivative rules were obtained by further reasoning. Association rules were used to analyze correlation and check consistency between indices. This study shows that the judgment obtained by weak association rules or non-association rules is more accurate and more credible than that obtained by strong association rules. When the testing grades of two indices in the weak association rules are inconsistent, the testing grades of indices are more likely to be erroneous, and the mistakes are often caused by human factors. Clustering data mining technology was used to analyze the reliability of a diagnosis, or to perform health diagnosis directly. Analysis showed that the clustering results are related to the indices selected, and that if the indices selected are more significant, the characteristics of clustering results are also more significant, and the analysis or diagnosis is more credible. The indices and diagnosis analysis function produced by this study provide a necessary theoretical foundation and new ideas for the development of hydraulic metal structure health diagnosis technology.

The analysis of application of data mining technology in the system of intrusion detection

With the economic development and the popularity of application of electronic computer, electronic commerce has rapid development. More and more commerce and key business has been carried on the lnternet because Internet has the features of interaction, openness, sharing and so on. However, during the daily commerce, people worry about the security of the network system. So a new technology which can detect the unusual behavior in time has been invented in order to protect the security of network system. The system of intrusion detection needs a lot of new technology to protect the data of the network system. The application of data mining technology in the system of intrusion detection can provide a better assistant to the users to analyze the data and improve the accuracy of the checking system.

Analysis on The Application of Data Mining Technology in Computer Network Virus Defense

With the rapid development of computer network,the society has entered the information and digital era,it plays an important role in speeding up the pace of social development and providing more convenient services for people.However, the security problem of computer network is becoming more and more serious. All kinds of network viruses pose a great threat to the security of computer network.As the most advanced data processing technology currently, data mining technology can effectively resist the invasion of network virus to computer system,and plays an important role in improving the security of the computer network.This paper starts with the concept of data mining technology and the characteristics of computer network virus,and makes an in-depth analysis on the specific application of data mining technology in the computer network virus defense.

Call for Papers Special Issue of Tsinghua Science and Technology on Data Mining and Knowledge Discovery

Tsinghua Science and Technology is founded and published since 1996. It is an international academic journal sponsored by Tsinghua University and is published bimonthly. This journal aims at presenting the up-to-date scientific achievements in computer science, and other information technology fields. It is indexed by Ei and other abstracting and indexing services. From 2013, the journal commits to the open access at IEEE Xplore Digital Library.

Application of bioinformatics in tropical medicine

Bioinformatics is a usage of information technology to help solve biological problems by designing novel and incisive algorithms and methods of analyses.Bioinfonnatics becomes a discipline vital in the era of post-genomics. In this review article,the application of bioinformatics in tropical medicine will be presented and discussed.

Cluster analysis of Qian Jing-hua’s experience in treatment of lung cancer

Objective to analyze the rule of drug use in treating lung cancer disease by using the theory of fuzheng and dispelling evil in traditional Chinese medicine by data mining.Methods:By following Dr.Qianjinghua's outpatient department,we collected the prescription for the treatment of lung cancer by using frequency analysis,association rule analysis and cluster analysis.Results:746 prescriptions were included in this study,commonly used drugs 170 flavors.Traditional Chinese medicine with a high frequency of use were Baihuasheshecao(Hedyotis diffusa),Maorenshen(Actinidia valvata Dunn),Shishangbai(Selaginella doederleinii Hieron),Shijianchuan(Salvia chinensis Benth),Huangqi(Astragali Radix),Sanyeqing(Tetrastlgma hemsleyanum),Baimaoteng(HerbaSolani),Zhuling(Polyporus),Nvzhenzi(Ligustrum lucidum Ait)etc.Through the analysis of association rule,we find out the core prescription according to the support degree(10%,20%,30%)and the confidence degree,and set the correlation degree to 8 and punishment degree to 2.Finally:The core prescription efficacy of the drug group was analyzed and the theoretical connotation of preventive treatment of disease was obtained.Conclusion:The core prescription of preventive treatment of disease is to clear up heat and detoxification on the basis of strengthening the spleen,replenishing qi and tonifying kidney.The use of blood supplements and yin tonics throughout the course is reduced during treatments.The treatments also pay attention to the function of spleen and stomach of lung cancer patients,and adjust heat and detoxification force according to different conditions of patients and pay attention to the relief of patients’emotions.