Abstract:The formal reasoning of the fuzzy propositional modal logic based on plausibility degree is considered,and the description of the associated Kripke semantics is given. The fuzzy constraint is introdu ced and used as a basic expression, the set of reasoning rules based on fuzzy constraint is given and a formal reasoning system is established, and in which the notation of the satisfiability is introduced. The relationship between the fuzzy reasoning and the satisfiability of the associated fuzzy constraints set is studied, and the soundness and completeness of the fuzzy reasoning based on satisfiability are proved.

Abstract:In applications of CMM (capability maturity model for software), it is a sticking point to implement enforceable software process models, which reflect the characteristics of organizations and their software processes, by transforming CMM software process model. Model driven architecture (MDA) supports model transformation and can be used in CMM practices, but the first step is to build a software process metamodel for CMM. This paper presents a software process metamodel for CMM based on SPEM(software process engineering metamodel), named SPM-CMM. SPM-CMM provides abstract syntaxes and rule semantics for CMM software process, and also supports of modeling of CMM integration with UML CASE tools.

Abstract:Connector is an important concept in software architecture design, but it doesn’t get explicit support from runtime. This paper describes the work on supporting user-defined connector in J2EE application server PKUAS. The PKUAS connector model takes advantage of the Aspect technology. A construct named Advice is used to model crosscutting concerns related to interaction behaviours. These advices are organized into connector and are invoked dynamically at runtime. At deployment time, PKUAS will generate a client-side connector object and publish it to a naming service. Application clients download the connector object to a local machine to manage the component interactions. Runtime connectors correspond well to those in the design time, thus narrowing the concept gap greatly. This flexible and modular approach effectively facilitates the separation of concerns.

Abstract:Software statistical testing is concerned with testing software systems based on their usage models. In the context of UML(unified modeling language)-based development, it is desired that the usage models can be derived from the UML analysis artifacts. This paper presents a method that derives the software Markov chain usage models from the reasonably annotated UML artifacts. The method utilizes the annotated use case diagrams, the annotated sequence diagrams, and the use case execution sequence relations. These annotations and the use case execution sequence relations are called statistical testing constraints. The method presents an algorithm that derives the Markov chain usage models from the UML artifacts and the statistical testing constraints. The framework of the support tool, UMGen, is also presented. The usage models can be used to generate software statistical test cases and estimate the software reliability.

Abstract:Software framework (SF) brings forth lots of conveniences for software reuse in specific domains. It is well-known that a framework is much harder to be developed than a common reusable component. Based on the conception of component-based software framework (CBSF) that provides black-box reuse approach, a development process for geo-workflow domain is in discussion. A geo-workflow application is one sort of workflow management systems applied in the geographic information domain, and can be implemented through reusing component-based geo-workflow framework (CBGWF). From the methodological point of view, the following steps are necessary to develop a CBGWF: domain analysis, domain design, framework design and implementation. The outputs of them are domain models with identified variabilities, domain-specific software architecture (DSSA), and products of software framework, respectively. In the context of geo-workflow, domain variabilities, which are identified and classified first, involve variabilities of geospatial data types, variabilities of geospatial data management, variabilities of geospatial operations, variabilities of processes, and variabilities of geospatial data representation. These variabilities can be organized in a tree view. Then, using HMB style, DSSA and architecture of CBGWF are designed, where the former can be regarded as a template of the latter. Finally, the framework component development based on EJB component model and the reuse of CBGWF are described in brief. Compared with other geo-workflow systems, the main advantage consists in its flexibility caused by the extensibility of CBGWF.

Abstract:Confidence score describes how confident a question-answering system is about its response. This paper presents a Maximum Entropy Model based algorithm which uses several factors to train an ME model, and then the ME model is used to calculate the confidence of other questions. Efficiency of this method has been proved by the TREC11’s QA evaluation, where the performance of the system has been improved dramatically after confidence ranking.

Abstract:In this paper a new robust fuzzy clustering neural networks (RFCNN) is presented to resolve the sensitivity of the fuzzy clustering neural network (FCNN) to outliers in real datasets. The new objective function of RFCNN is obtained by introducing Vapnik’s ε-insensitive loss function, and RFCNN’s update rules are derived by using Lagrange optimization theory. Compared with the FCNN algorithm, RFCNN is much more robust to outliers in the datasets. Experimental results demonstrate the effectiveness of RFCNN.

Abstract:Finding meaningful low-dimensional embedded in a high-dimensional space is a classical problem. Isomap is a nonlinear dimensionality reduction method proposed and based on the theory of manifold. It not only can reveal the meaningful low-dimensional structure hidden in the high-dimensional observation data, but can recover the underlying parameter of data lying on a low-dimensional submanifold. Based on the hypothesis that there is an isometric mapping between the data space and the parameter space, Isomap works, but this hypothesis has not been proved. In this paper, the existence of isometric mapping between the manifold in the high-dimensional data space and the parameter space is proved. By distinguishing the intrinsic dimensionality of high-dimensional data space from the manifold dimensionality, and it is proved that the intrinsic dimensionality is the upper bound of the manifold dimensionality in the high-dimensional space in which there is a toroidal manifold. Finally an algorithm is proposed to find the underlying toroidal manifold and judge whether there exists one. The results of experiments on the multi-pose three-dimensional object show that the method is effective.

Abstract:RANSAC algorithm is one of the most widely used robust estimator in the field of computer vision, but, it’s efficiency is low. The paper gives a preview model parameters evaluation RANSAC algorithm (PERANSAC): a preview model parameters evaluation selection is added to the RANSAC algorithm. With guaranteeing the same confidence of the solution as RANSAC, a very large number of erroneous model parameters obtained from the contaminated samples are discarded in the preview evaluation selection. PERANSAC algorithm is evaluated on both synthetic data and real-world images, a significant increase in speed is shown, and the solutions are the same as RANSAC’s.

Abstract:This paper gives a novel approach to recognize Chinese fonts based on Empirical Mode Decomposition (EMD). By analyzing and comparing a great number of Chinese characters, 8 basic strokes are selected to characterize the structural attributes of Chinese fonts. Based on them, stroke feature sequences of each text block are calculated. Once decomposed by EMD, their first two intrinsic mode functions (IMFs), which are of the highest frequencies, are used to calculate the stroke energy of all the 8 basic strokes, forming the average of the energy of the two IMFs over the length of the sequence. To distinguish bold fonts from their regular fonts, average of the pixel's gray levels of the text is calculated and appended to the feature vector to form a 9 dimensional feature. Finally, the minimum distance classifier is used to recognize the fonts. Experiments show encouraging recognition rates.

Abstract:With the rapid growth of Internet, the structures and resolutions of Internet namespaces are facing with new challenges. IP address is overloaded in semantics because it is used to represent both the location and the identity of a device. The namespace resolution system DNS can’t satisfy many new application demands with its unique service model, slow update speed, and weak capability in resource description. Many network middleboxes, such as NAT, various agents and firewalls, also destroy the Internet architecture and the Internet namespaces. Based on these, researchers bring forth many solutions to improve the structures and resolutions of Internet namespaces. This paper analyzes the problems in the structures and resolutions of current Internet namespaces, and then makes categories, surveys, and comparisons on the improvement solutions to them. Finally, future research trends on this area are discussed.

Abstract:After referring to the IP-DiffServ adaptive pricing mechanism of NSF CAREER, this paper presents an optimal adaptive resource pricing mechanism on the base of market and plan. Based on the service plan and service layout, it prices the service class by providing the users more performances with lower cost and by making ISP win the most benefits. While calculating user perceived benefit, the burden factor is taken into account, then it can lead to an orderly distributed traffic according to the service plan. Experimental results indicate that the improvement to the value evaluation formula of service class of NSF CARRER is reasonable and effective.

Abstract:Many computing or data intensive scientific applications require a mechanism of sharing and coordinated use of diverse resource as part of their sophisticated problem solving processes. This paper describes the design and implementation of the chemical evolving research of the Galaxy under Grid environment, which is an important part of China Virtual Observatory application system. Through this exemplification, this paper shows a mechanism of the sharing and coordinated use of resourced that support e-Science applications by integrating Grid rvices and Grid service workflow into Grid environment. Such a mechanism could be beneficial for modeling and managing scientific processes of experimental investigation, evidence accumulation and result assimilation.

Abstract:In Mobile Ad Hoc Networks (MANET), network partitioning can cause sudden and severe disruptions to ongoing data accesses, and consequently data availability is decreased. A new distributed clustering algorithm is presented in this paper for dynamically organizing mobile nodes into clusters in which the probability of path availability can be bounded. Based on this clustering algorithm, a data replication algorithm is proposed to improve data availability. Theoretic analysis indicates that the algorithm has a proper complexity. Simulation results show that the clusters created by the clustering algorithm have desirable properties and the data availability is improved effectively by the clustering-based data replication algorithm.

Abstract:A novel unicast QoS routing algorithm is proposed to address the two additive constraints routing problem. The algorithm is based on the concept of Pareto optimal and dynamic weight coefficient mechanism. Normally to attain a high performance, the algorithm only needs to run 2~3 times of the Dijkstra algorithm. Extensive simulations have shown that the algorithm is very efficient and converges quickly.

Abstract:Coupled with the explosion of number of the network-oriented applications, Intrusion Detection as an increasingly popular area is attracting more and more research efforts. Although a number of algorithms have already been presented to tackle this problem, they are unable to achieve balanced detection performance for different types of intrusion and cannot respond as quickly as expected. Employing random forests algorithm (RFA)in intrusion detection, this paper devises an improved variation - IRFA and presents an IRFA based model for intrusion detection in information exchanged through network connections. The feasibility in balanced detection and the effectiveness of this approach are verified by experiments based on DARPA data sets.

Abstract:Dynamic power management (DPM) is a design methodology aiming at reducing power consumption of electronic systems. The effectiveness of a power management scheme depends critically on the power management policy and control algorithm. In this work, it is found that the exponential distribution supposition taken by traditional queuing theory is not suitable to DPM, and the timeout policy is enough for DMP. The reason that the simple timeout policy could reduce much energy consumption of computer devices is the self-similarity nature of computer service requests. This paper proposes an adaptive control algorithm for DPM of embedded operating system when the idle time length fits Pareto distribution. It adopts the Trimmed Mean Estimator to realize the robust efficient estimation of the tail index parameter of Pareto distribution for small sample size, and is implemented using window-size-based adaptive control method. Simulation results show that the algorithm presented in this paper is robust. The competitive ratio is reduced to 1.24 and even 1.47 when the delay is smaller than 0.10. Overhead of the adaptive control algorithm is low.

Abstract:The class-based garbage collection approach is to improve the efficiency of the runtime environment for server applications. The class-based garbage collection algorithm is intended to reduce the overhead of dynamic object creation through an object-reuse technology, and the unique techniques of thread cache and lease protocol etc. can further reduce the pause time of the server applications and provide them better smoothness and good memory usage. The virtual machines run on top of the class-based garbage collector can be implemented to support fine grade parallelism between the mutator threads and the garbage collection threads.

Abstract:Based on the worst-case response time schedulability analysis for fault-tolerant real-time systems, a new fault-tolerant priority assignment algorithm is proposed. This algorithm can be used, together with the schedulability analysis, to effectively improve system fault resilience when the two traditional fault-tolerant priority assignment policies can’t improve system fault resilience. A fault-tolerant priority configuration search algorithm is also presented for the proposed analysis. The effectiveness of the proposed approach is evaluated by simulation.