23372402
Information Concept Lattice and Its Reductions
In this paper, the combination of formal concept analysis and rough set theory is considered. The notion of information concept lattice is presented and some properties are given. We present the reduction theory of information concept lattice and obtain the reduction method. Information concept lattice is compared with rough set theory and concept lattice.
6342666
SOWAC: a service-oriented workflow access control model
Workflow access control is the fundamental issue in workflow security. With the development of enterprise globalization and the constant re-engineering and optimizing of enterprise business, the organization becomes more dynamic and its business process is frequently changing. As a result, workflow access control turns more complicated and entails a comparatively operational mechanism. To solve the problem, in view of decoupling workflow access control model from workflow model, we propose a service-oriented workflow access control (SOWAC) model in this paper. In the SOWAC model, service is the abstraction of a task and the unit for applying access control. We present the elements of the SOWAC model and illustrate the enforcement of SOWAC with an example workflow. Then the dynamic separation of duty for the SOWAC model is proposed based on the authorization history of services. By applying SOWAC in a real workflow management system, we show that the SOWAC model is practical and effective.
46077798
A Component-Based Analytical Performance Model of IP-Based SAN
In this paper we propose a component-based analytical performance model for IP-based SAN. This model evaluates and analyzes the behavior of IP network, cache, RAID and disks under multiple synchronous I/O workloads by using closed queueing networks. The theoretical results are compared with the results from a real IP-based SAN using a variety of synthetic workloads. These experiments prove that the component-based method is an appropriate way to build performance model for a complex storage system. Using the model, we can find out that the bottleneck of SAN performance is network or storage node under different workloads or applications. We also identify areas for future research in the performance analysis of real IP-based SAN.
2507502
An Analytical Performance Model of IP-SAN
In this paper we propose a component-based analytical performance model for IP-SAN. We model four key components within IP-SAN individually and they are IP network, cache, RAID and disks. We validate these component models and compose them to give an entire IP-SAN performance model. The entire IP-SAN model analyzes the performance of an IP-SAN configuration under multiple synchronous workloads by using closed queueing network model and under asynchronous workload by using open queueing network model. We also validate the entire IP-SAN performance model against a real IP-SAN system. The theoretical results are compared with the results from a real IP-SAN using a variety of synthetic workloads. These experiments prove that the component-based method is an appropriate way to build performance model for a complex storage system. To our knowledge, this is the first exploration into building analytical performance model for entire IP-SAN system and validating against a real system. We also identify areas for future research in the performance analysis of real IP-SAN.
17469824
Extending OBDD graphs for composite event matching in content-based pub/sub systems
Content-based publish/subscribe offers a convenient abstraction for the information producers and consumers, supporting a large-scale system design and evolution by integrating several distributed independent application systems. Its core problem is how to match events by predicates on the content of events. In this paper, we propose three matching models, extend the simple matching to the multi-semantic matching and introduce the temporal constraint variable. The multi-semantic matching allows using different operations in accordance with different semantics; the temporal constraint variable supports processing the discrete events in the temporal sequence. Then, we extend OBDD graphs into hierarchy coloured OBDD graphs and prove the equivalence of the transformation. At last, based on OBDD graphs the composite matching algorithm is presented and analysed. By experiments, we show the proposed algorithm is efficient.
17485840
A framework for application server based Web services management
Web services are considered as solution for solving the interoperability problem and the challenge of integration. How to manage Web services more efficiently is a key problem to the applications based on Web services at present. This paper presents a framework for application server based Web services management named FASWSM. The main contribution of FASWSM is Web service adaptation, so that a Web service can be plugged into the application server (AS) as a Web service adapter which enables a Web service to be managed by the application server. Therefore, the Web services management efforts are greatly reduced by leveraging various services provided by the AS. The FASWSM also provides mechanisms for dynamical reconfiguration which improve the extensibility and flexibility of Web services management. The FASWSM has been applied to OnceAS 2.0 application server, and the experiments data show that FASWSM outperforms JAX-RPC in terms of Web service invocation.
9032052
Deriving Event Relevance from the Ontology Constructed with Formal Concept Analysis
In this paper, we present a novel approach to derive event relevance from event ontology constructed with Formal Concept Analysis (FCA), a mathematical approach to data analysis and knowledge representation. The ontology is built from a set of relevant documents and according to the named entities associated to the events. Various relevance measures are explored, from binary to scaled, and from symmetrical to asymmetrical associations. We then apply the derived event relevance to the task of multi-document summarization. The experiments on DUC 2004 data set show that the relevant-event-based approaches outperform the independent-event-based approach.
9167227
A hierarchical naive Bayes mixture model for name disambiguation in author citations
Because of name variations, an author may have multiple names and multiple authors may share the same name. Such name ambiguity affects the performance of document retrieval, web search, database integration, and may cause improper attribution to authors. This paper presents a hierarchical naive Bayes mixture model, an unsupervised learning approach, for name disambiguation in author citations. This method partitions a collection of citations1 into clusters, with each cluster containing only citations authored by the same author, thus disambiguating authorship in citations to induce author name identities. Three types of citation features are used: co-author names, paper title words, and journal or proceeding title words. The approach is illustrated with 16 name datasets that are constructed based on the publication lists collected from author homepages and DBLP computer science bibliography.
30164221
Limited feedback design for MIMO broadcast channels with ARQ mechanism
We investigate the design of a limited feedback mechanism for multiple-input-multiple-output (MIMO) broadcast systems that are equipped with automatic repeat request (ARQ) capabilities. Given multiple antennas at the base-station (BS) and single antenna subscribers, we focus on maximizing the ergodic system sum capacity and propose an adaptive feedback bit allocation scheme under the constraint of total feedback bandwidth. Furthermore, we develop two efficient feedback allocation schemes based on asymptotic analysis. We present simulation results that verify the effectiveness of the proposed adaptive allocation schemes.
8041290
A New Hybrid Approach for Analysis of Factors Affecting Crude Oil Price
In this paper, a new hybrid approach is presented to analyze factors affecting crude oil price using rough set and wavelet neural network. Related factors that affect crude oil price are found using text mining technique and Brent oil price is chosen as the decision price because it plays an important role in world crude oil markets. The relevant subsets of the factors are discovered by rough set module and the main factors are got, and then the important degrees of these are measured using wavelet neural network. Based on the novel hybrid approach, the predictability of crude oil price is discussed.
44484550
Research on Models of Concept and Relation between Concepts Adapted for Semantic Disambiguation of Natural Language