Dear Editor,This letter focuses on the problem of remaining useful life(RUL)prediction of equipment. Existing graph neural network(GCN)-based approaches merely provide the point estimation of RUL. However,the estimate...Dear Editor,This letter focuses on the problem of remaining useful life(RUL)prediction of equipment. Existing graph neural network(GCN)-based approaches merely provide the point estimation of RUL. However,the estimated RUL often varies widely due to the model parameters and the noise in data. It is important to know the uncertainty in predictions for reliable risk analysis and maintenance decision making.To map the relationship between noisy condition monitoring data and RUL with uncertainty.展开更多
The culture of professional degree graduate students is a new form of postgraduate education in China. It focuses on cultivating high-level and applied talents compared with original academic degree graduate students....The culture of professional degree graduate students is a new form of postgraduate education in China. It focuses on cultivating high-level and applied talents compared with original academic degree graduate students. Considering about the source of full-time professional degree graduate students in domain of software engineering and the current college educational system, this paper makes a few beneficial explorations about curriculum, practice teaching, process management and puts forward the mode and method to improve full-time professional degree graduate education in domain of Software Engineering.展开更多
Collaborative filtering (CF) is a technique commonly used for personalized recommendation and Web service quality-of-service (QoS) prediction. However, CF is vulnerable to shilling attackers who inject fake user profi...Collaborative filtering (CF) is a technique commonly used for personalized recommendation and Web service quality-of-service (QoS) prediction. However, CF is vulnerable to shilling attackers who inject fake user profiles into the system. In this paper, we first present the shilling attack problem on CF-based QoS recommender systems for Web services. Then, a robust CF recommendation approach is proposed from a user similarity perspective to enhance the resistance of the recommender systems to the shilling attack. In the approach, the generally used similarity measures are analyzed, and the DegSim (the degree of similarities with top k neighbors) with those measures is selected for grouping and weighting the users. Then, the weights are used to calculate the service similarities/differences and predictions. We analyzed and evaluated our algorithms using WS-DREAM and Movielens datasets. The experimental results demonstrate that shilling attacks influence the prediction of QoS values, and our proposed features and algorithms achieve a higher degree of robustness against shilling attacks than the typical CF algorithms.展开更多
基金supported by the Major Special Program of Chongqing Science&Technology Commission(CSTC 2019jscx-zdztzx X0031)Graduate Scientific Research and Innovation Foundation of Chongqing(CYB21068,CYS22128)。
文摘Dear Editor,This letter focuses on the problem of remaining useful life(RUL)prediction of equipment. Existing graph neural network(GCN)-based approaches merely provide the point estimation of RUL. However,the estimated RUL often varies widely due to the model parameters and the noise in data. It is important to know the uncertainty in predictions for reliable risk analysis and maintenance decision making.To map the relationship between noisy condition monitoring data and RUL with uncertainty.
基金the support of the research from the fourth batch of postgraduate key courses of Chongqing University (project number:201704008)"the research & practice of software engineering talent evaluation and improvement" of the key project of the teaching reform in Chongqing city (project number:162004)
文摘The culture of professional degree graduate students is a new form of postgraduate education in China. It focuses on cultivating high-level and applied talents compared with original academic degree graduate students. Considering about the source of full-time professional degree graduate students in domain of software engineering and the current college educational system, this paper makes a few beneficial explorations about curriculum, practice teaching, process management and puts forward the mode and method to improve full-time professional degree graduate education in domain of Software Engineering.
基金the Basic and Advanced Research Projects in Chongqing (cstc2015jcyjA40049)the National Natural Science Foundation of China (Grant No. 71102065)+1 种基金the Fundamental Research Funds for the Central Universities (106112014 CDJZR 095502)the China Scholarship Council.
文摘Collaborative filtering (CF) is a technique commonly used for personalized recommendation and Web service quality-of-service (QoS) prediction. However, CF is vulnerable to shilling attackers who inject fake user profiles into the system. In this paper, we first present the shilling attack problem on CF-based QoS recommender systems for Web services. Then, a robust CF recommendation approach is proposed from a user similarity perspective to enhance the resistance of the recommender systems to the shilling attack. In the approach, the generally used similarity measures are analyzed, and the DegSim (the degree of similarities with top k neighbors) with those measures is selected for grouping and weighting the users. Then, the weights are used to calculate the service similarities/differences and predictions. We analyzed and evaluated our algorithms using WS-DREAM and Movielens datasets. The experimental results demonstrate that shilling attacks influence the prediction of QoS values, and our proposed features and algorithms achieve a higher degree of robustness against shilling attacks than the typical CF algorithms.
