Engine engineering database system is an oriented C AD applied database management system that has the capability managing distributed data. The paper discusses the security issue of the engine engineering database ma...Engine engineering database system is an oriented C AD applied database management system that has the capability managing distributed data. The paper discusses the security issue of the engine engineering database management system (EDBMS). Through studying and analyzing the database security, to draw a series of securi ty rules, which reach B1, level security standard. Which includes discretionary access control (DAC), mandatory access control (MAC) and audit. The EDBMS implem ents functions of DAC, MAC and multigranularity audit. DAC solves the problems o f role inheritance, right contain, authorization identify and cascade revoke, et c; MAC includes subject and object security setup rule, security modify rule and multilevel relation access operation rule, etc; Audit allows making the sub ject, object or operation type as different audit object to implement flexible a nd multigranularity audit method. The model is designed act as a security agent to access daemon database. At present, the model is implemented which runs on th e Windows 2000 environments.展开更多
Modular technology can effectively support the rapid design of products, and it is one of the key technologies to realize mass customization design. With the application of product lifecycle management(PLM) system in ...Modular technology can effectively support the rapid design of products, and it is one of the key technologies to realize mass customization design. With the application of product lifecycle management(PLM) system in enterprises, the product lifecycle data have been effectively managed. However, these data have not been fully utilized in module division, especially for complex machinery products. To solve this problem, a product module mining method for the PLM database is proposed to improve the effect of module division. Firstly, product data are extracted from the PLM database by data extraction algorithm. Then, data normalization and structure logical inspection are used to preprocess the extracted defective data. The preprocessed product data are analyzed and expressed in a matrix for module mining. Finally, the fuzzy c-means clustering(FCM) algorithm is used to generate product modules, which are stored in product module library after module marking and post-processing. The feasibility and effectiveness of the proposed method are verified by a case study of high pressure valve.展开更多
文摘Engine engineering database system is an oriented C AD applied database management system that has the capability managing distributed data. The paper discusses the security issue of the engine engineering database management system (EDBMS). Through studying and analyzing the database security, to draw a series of securi ty rules, which reach B1, level security standard. Which includes discretionary access control (DAC), mandatory access control (MAC) and audit. The EDBMS implem ents functions of DAC, MAC and multigranularity audit. DAC solves the problems o f role inheritance, right contain, authorization identify and cascade revoke, et c; MAC includes subject and object security setup rule, security modify rule and multilevel relation access operation rule, etc; Audit allows making the sub ject, object or operation type as different audit object to implement flexible a nd multigranularity audit method. The model is designed act as a security agent to access daemon database. At present, the model is implemented which runs on th e Windows 2000 environments.
基金Project(51275362)supported by the National Natural Science Foundation of ChinaProject(2013M542055)supported by China Postdoctoral Science Foundation Funded
文摘Modular technology can effectively support the rapid design of products, and it is one of the key technologies to realize mass customization design. With the application of product lifecycle management(PLM) system in enterprises, the product lifecycle data have been effectively managed. However, these data have not been fully utilized in module division, especially for complex machinery products. To solve this problem, a product module mining method for the PLM database is proposed to improve the effect of module division. Firstly, product data are extracted from the PLM database by data extraction algorithm. Then, data normalization and structure logical inspection are used to preprocess the extracted defective data. The preprocessed product data are analyzed and expressed in a matrix for module mining. Finally, the fuzzy c-means clustering(FCM) algorithm is used to generate product modules, which are stored in product module library after module marking and post-processing. The feasibility and effectiveness of the proposed method are verified by a case study of high pressure valve.
