The traditional RBAC model already cannot express the complicated secure access control constraint of the workflow. Based on the traditional RBAC model, a new conditioned RBAC model named as CMWRBSAC is proposed on th...
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The traditional RBAC model already cannot express the complicated secure access control constraint of the workflow. Based on the traditional RBAC model, a new conditioned RBAC model named as CMWRBSAC is proposed on the basis of multi-weighted roles. A conditioned RBAC strategy is discussed on the basis of dynamic role assignment. A new concept of workflow access authorization is defined on the basis of roles with multi-weights, including the hierarchy weight, the degree weight and the sequence weight. Furthermore, in order to solve the problems of the sequence constraint of cooperative activating task by multi-roles and multi-users, a sort algorithm based on token and a sort algorithm based on weighted roles synthesis are presented respectively. Finally, an example is given to show the work processes of these algorithms. This model can express complicated workflow secure access control constraint.
A method for simultaneous analysis of the two components of compound paracetamol and diphenhydramine hydrochloride powdered drugs on near-infrared (NIR) spectroscopy is developed by using a radial basis function (RBF)...
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A method for simultaneous analysis of the two components of compound paracetamol and diphenhydramine hydrochloride powdered drugs on near-infrared (NIR) spectroscopy is developed by using a radial basis function (RBF) network. Nearest neighbor-clustering algorithm is used as the learning algorithm of RBF network. Comparisons of the results obtained from the RBF models with those from BP models show that it is feasible to use the RBF network in nondestructive quantitative analysis of the components of drugs.
It is well recognized that sequential pattern mining plays an essential role in many scientific and business domains. In this paper, a new extension of sequential pattern, attributes' sequential pattern, is propos...
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It is well recognized that sequential pattern mining plays an essential role in many scientific and business domains. In this paper, a new extension of sequential pattern, attributes' sequential pattern, is proposed. An attributes' sequential pattern is a sequence of attributes, whose values commonly occur in ascending order over data set. After each record in data set is transformed into an attributes' sequence according to their ordinal values, attributes' sequential patterns can be mined by means of mining sequential patterns. But our work is different from sequential pattern mining. One use of attributes' sequential patterns is to identify possible errors in data set for data cleaning, in which the values of attributes break the attributes' sequential patterns which most of the data conform to. Experiments verify the high efficiency of the method presented.
Three kinds of constrained traveling salesman problems (TSP) arising from application problems, namely the open route TSP, the end-fixed TSP, and the path-constrained TSP, are proposed. The corresponding approaches ba...
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Three kinds of constrained traveling salesman problems (TSP) arising from application problems, namely the open route TSP, the end-fixed TSP, and the path-constrained TSP, are proposed. The corresponding approaches based on modified genetic algorithms (GA) for solving these constrained TSPs are presented. Numerical experiments demonstrate that the algorithm for the open route TSP shows its advantages when the open route is required, the algorithm for the end-fixed TSP can deal with route optimization with constraint of fixed ends effectively, and the algorithm for the path-constraint could benefit the traffic problems where some cities cannot be visited from each other.
A novel hybrid algorithm based on the AFTER (Aggregated forecast through exponential re-weighting) and the modified particle swarm optimization (PSO) is proposed. The combining weights in the hybrid algorithm are trai...
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An operation template is proposed in this paper for describing the mapping between operations and a subset of natural numbers. With such operation template, a job shop scheduling problem (JSSP) can be transformed into...
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This paper presents a Case Based Reasoning (CBR) approach to identifying micro-architecture anti-patterns and replacing them with "good" patterns in order to improve the design of software system. The result...
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The use of computational-intelligence-based techniques in the optimization of agent initial positions in land combat simulations is studied. A novel method for the reduction of support vectors in the support vector ma...
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The use of computational-intelligence-based techniques in the optimization of agent initial positions in land combat simulations is studied. A novel method for the reduction of support vectors in the support vector machine (SVM) is presented. The optimization on the width of the Gaussian kernel function and the combination of the SVM with the radial basis function neural network are performed in the proposed method. Simulation results show that the proposed method can improve the running efficiency drastically compared with that using the traditional SVM with the same precision. We also summarize and present some experiences and trends in the study on the optimization problem in land combat simulation.
This paper is a survey for smart home research, from definition to current research status. First we give a definition to smart home, and then describe the smart home elements, typical research projects, smart home ne...
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ISBN:
(纸本)0780384032
This paper is a survey for smart home research, from definition to current research status. First we give a definition to smart home, and then describe the smart home elements, typical research projects, smart home networks research status, smart home appliances and challenges at last.
Both item-associations and user-associations mined from the rating table can be used to make personalized recommendation for the current user in rule-based recommend technique. Mining user-associations is the key for ...
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ISBN:
(纸本)0780384032
Both item-associations and user-associations mined from the rating table can be used to make personalized recommendation for the current user in rule-based recommend technique. Mining user-associations is the key for the recommendation based on user-associations. We find that the current user not only can be used to constrain the rule form in user-associations mining process, but also can be used to partition the rating table into two parts in order to accelerate user-associations mining. It is first proved that user-associations about the current user mined from the whole rating table are contained in those mined only from the data set that contain the current user's rating. Then, a user-association mining frame based on two-stage count called TSCF is proposed. TSCF frame can be implemented by using existing algorithms for mining association rules. And an algorithm TSCF-CL for mining user-associations is implemented by using the concept lattice. Last the performance comparison with ASARM algorithm shows that TSCF-CL can reach better time capacity.
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