14505582
An Object-Dependent and Context Constraints-Aware Access Control Approach Based on RBAC
The universal adoption of the Internet requires a fine grained access control in the sharing of sensitive resources. However, existing access control mechanisms are inflexible and do not help in alleviating the management task of administrating users’ access to resources based on security policies. In this paper, we propose an approach to implement fine-grained access control based on RBAC while considering specific context constraints. The approach is object-dependent and policy-enforced through binding policies to particular object. In the policies, context constraints are incorporated to support separation of duties (SoD). Furthermore, the implement of the approach is described in detail and an application to meet specific access control requirements of comprehensive knowledge management system in an aviation enterprise is presented.
16303483
A Case Study of Enterprise Application Integration Based on Workflow Management System
Work flow management system (WFMS) is a flexible tool for enterprise application integration (EAI). The EAI implement with work flow technology is cheap and convenient. This enlarges the view of enterprises and gives them an opportunity to integrate their legacy applications by advanced IT technology. By study on environment and stratagem of enterprises, this paper establishes a solution of the EAI based on work flow management system and presents an EAI framework with an embedded workflow management component to support business-to-business operations. Nowadays, however, such system is not common. A case study of EAI implement in Tianjin Port is presented and a brief overview of the current enterprise applications and information systems in this enterprise are also presented.
35490802
Mining Condensed and Lossless Association Rules by Pruning Redundancy
There are excessive and disordered rules generated by traditional approaches of association rule mining, many of which are redundant, so that they are difficult for users to understand and make use of. Han et al pointed out the bottleneck of association rules mining is not on whether we can derive the complete set of rules under certain constraints efficiently but on whether we can derive a compact but high quality set of rules. To solve this problem, a new method was represented, which is based on statistics and probability to get a condensed rules set by removing redundant rules. Our set of rules is more concise, more intelligible and easier to manage and use than others. Especially, the condensed set is lossless so that its switch to original rules-set can be realized. Itpsilas important because the switch keeps the information complete. Experiments on some datasets show that the number of rules in rules-set has been reduced greatly.
15609476
An Online Personalized Recommendation Model Based on Bayesian Networks
It is one of an important method of using Bayesian networks in electronic commercial recommended system. But the models of Bayesian networks for describing recommended system have a problem that it could not learn online. The paper puts forward an online personalized recommended model based on Bayesian networks. The paper uses a partial ordering to represent previous structure and find posterior distributions of every node on the orders to realize online structure learning. It also uses a correctional function to revise log likelihood for online parameter learning. The experiment shows that the model can be learned online for personalized recommended system.
18595985
Fault-tolerant peer-to-peer search on small-world networks
This paper presents a small world architecture for P2P networks (SWAN) for content discovery in multi-group P2P systems. A semi-structured P2P algorithm of SWAN is utilized to create and find long-range shortcuts toward remote peer groups. In SWAN, not every peer node needs to be connected to remote groups, but every peer node can easily find which peer nodes have external connections to a specific peer group. From our analysis and simulation, SWAN has the advantages of both structured and unstructured P2P networks, and can achieve good performance in both stable and dynamic environments.
11138089
Research on System Architecture and Interfaces in Heterogeneous Network Platform
The paper proposes an architecture for heterogeneous network platform based on adaptation layer according to service capability requirements and characteristics of modern service industry. In order to shield the diversity of heterogeneous networks to provide open interfaces in the adaptation layer, an abstract method of service capability is proposed to get a set of SCF components and sub-platforms. The basic service capabilities can be also integrated to generate new services by the service integration method. Some interfaces and service applications illustrate that the abstract method and interfaces are reasonably effective on the platform for the applications of modern service industry.
2746167
Modelling and simulation of Network Enabled Capability on service-oriented architecture
Network Enabled Capability (NEC) is the UK Ministry of Defence’s response to the quickly changing conflict environment in which its forces must operate. In NEC, systems need to be integrated in context, to assist in human activity and provide dependable inter-operation. In this paper, we present our research work in the NECTISE project with a focus on the modelling and simulation of service-oriented architecture (SOA) for delivering dependable and sustainable military capability. The simulation results indicate that the proposed architectural model can provide a high-level of reliability and sustainability in the provision of capability in a dynamic environment. Moreover, a NEC demonstration system for regional surveillance is introduced in this paper to illustrate the use of SOA to achieve NEC.
34356811
Reduce Feature Based NN for Transient Stability Analysis of Large-Scale Power Systems
Aiming at the existence of relativity between repeat or similar samples and character parameters during diagnosis of character data, this paper presents an effective data analysis approach for character data compression from bi-direction, which can reduce the burden of learning machine without losing the connotative character knowledge of character data. At the first step of the algorithm, basing on the theory of component analysis, the paper adopt a principal component analysis approach to reduce the dimension of data horizontally, then after comparison of existing clustering algorithms, put forward an immune clustering algorithm based on similarity measurement of principle component core for vertical reduction by using related mechanism of clone selection as well as immune network self-stabilization in organism natural immune system for reference. Finally, to analyze machine behavior quantitatively, a pattern discrimination model based on a cerebellar model articulation controller neural network ( NN ) was developed. Simulation experiments proved the effectiveness of this algorithm.
15166655
The Vector Data Management of GIS Based on PDA
Traditionally, vector data of GIS based on PDA is managed with a traditional pyramid model to promote displaying speed. However, this pyramid model does not flexible or practical enough to solve many problems, neither the data file designing and data processing method are discussed before. Therefore, in this paper, an improved pyramid model is proposed and a new data format for the model is designed, also, the data processing method is discussed. The experimental results show that, this solution is practical and efficient.