Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-06-06 Cooperative journals: 《计算机应用研究》
Abstract: In Attribute-Based Access Control (ABAC) , how to respond quickly to the retrieved access control request is very important, and it is undoubtedly time-consuming to traverse all attribute values in each rule of the policy set until finding the appropriate rule. Therefore, the paper proposes an ABAC retrieval method based on binary sequence, and uses binary identification and binary coding to represent attribute based access control policies and access control requests. Through the logical operation of binary identification, select the appropriate group. In the group, find the appropriate rules by matching the binary code of access control request with the binary code of all rules, reduce the process of matching the attributes of rules in the policy set with the attributes of access control request, and improve the efficiency of policy retrieval. In the experiment, this paper compares the efficiency of similar retrieval methods from three aspects: strategy preprocessing, strategy evaluation time and total strategy retrieval time. The results show that the strategy retrieval method proposed in this paper has higher retrieval efficiency.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-08-13 Cooperative journals: 《计算机应用研究》
Abstract: Fault diagnosis is very important in ensuring system stability. Most of traditional fault diagnosis research ignored characteristics of local structure. For that problem under PMC model, the definition of node diagnosis was introduced. And through the study by nodes diagnosis, obtained the sufficient condition of the node diagnosiability and got a new t-diagnosis algorithm called STFDA. Finally, an analysis from the angle of node diagnosis of n-dimensional hypercube network and n-dimensional star network was performed in order to test the validity of the sufficient conditions. Algorithm performed a fault diagnosis to the two kinds of network at last. Indeed, the implementation of the sufficient condition and algorithm got the help of a new structure called ST. And algorithm’s time complexity was proved to be O(N δ) , with δ equal to the maximum degree of node in network, which was significantly reduced compared with others algorithm.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-24 Cooperative journals: 《计算机应用研究》
Abstract: This paper proposed a novel neural network to solve nonsmooth nonconvex optimization problems with equality and inequality constraints. It was proved that when the objective function has a lower bound, the neural network converges to a feasible domain in a finite time. Meanwhile, the solution trajectory of neural network converges to optimal solution set of the corresponding optimization problems, which finally converge to critical point set of optimization problems. Comparing with traditional neural network which based on penalty function, the neural network model does not need to calculate any penalty parameters. Finally, the effectiveness of the proposed model is verified by simulation experiments.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-05-02 Cooperative journals: 《计算机应用研究》
Abstract: Aiming at the low precision problem while the cost is introduced into attribute reduction of decision-theoretic rough set, it is studied the balance between the total cost and the precision in classification. The total cost of the classification and the approximate classification quality are used as the constrained criteria in the attribute reduction procedure, combined with simulated annealing method, it is proposed a DTRS attribute reduction algorithm constrained by cost-sensitive and classification quality (hereinafter referred as ARACOQ) . The simulation experiments are carried out by using UCI data set, the results verify the effectiveness of the ARACOQ algorithm, it can find an attribute reduction set with the highest classification precision within the affordable cost range.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-04-17 Cooperative journals: 《计算机应用研究》
Abstract: Due to the envelope fitting problem exists in the process of empirical mode decomposition, this paper proposed an improved algorithm which could eliminate the undershoot phenomenon exactly. By introducing "pseudo-extreme points", this algorithm increased the number of extreme points and formed new extreme value sequence. Then it got new envelope by using the new extreme value sequence interpolation. The envelope fitted by this method was closer to the original signal and has better smoothness. Finally, A contrast result between cubic spline interpolation and this algorithm showed that the number of undershoots decreased by about 77.5%, which proved that this algorithm could effectively reduce the number of undershoot points. In addition, fitting the envelope could tightly wrap the original signal and have a better envelope.