Advanced Materials Research Vols. 655-657

Abstract: Due to the inaccuracy of reasoning conclusion because of the discrepancy among the cases ontology in the process of case reuse or revision, a new reasoning method for fault diagnosis based on ACO and CBR is proposed by this paper. This method uses CBR to reason new cases firstly, if it can match successfully brings to the corresponding results, else use ACO to reason the cases which have not matching in the case-library. As a result, the accuracy and efficiency of fault diagnosis are improved greatly and use the characteristic of the strong memory in CBR to repair the shortcoming of ACO reasoning method that can improve it capability. The method adopting fault cause-symptom matrix to describe the cases and case-library has many good characteristics of conciseness, convenience and extendibility.

Abstract: To better share agricultural information in existed agricultural informatization condition, and to meet agro-departments new needs about local self-governed and global shared data management during standardized production of the sweet corn, this paper provides a method of integrated sharing of heterogeneous data sources to apply to standardized product of the sweet corn. This method solves the data integration and sharing problems during standardized production of the sweet corn. In this paper, the expert system for sweet corn standard production which is ability to combine heterogeneous data is constructed. This system is proved to be reliable, perform well and it is easy to operate.

Abstract: Yunnan province has rich natural resources with high species diversities because of its unique ecological environments, while the abundance of genera of seed plants endemic in Yunnan ranked the top one in China. But there are several shortcomings influence the research and the protection on genera of seed plants endemic in Yunnan. Firstly, the storage of relevant knowledge and data of genera of seed plants endemic in Yunnan is dispersion; secondly, the structure of the data system is poor; thirdly, the format and standard database is not unified. In order to improve the above shortcomings, this paper will built an ontology knowledge database for Yunnan genera of seed plants endemic based on ontology, geography ontology and ontology integration technologies. This new ontology knowledge database will apply new technologies and theoretical basis for the further macroscopic research on Yunnan genera of seed plants endemic. And it will apply scientific decision and research methods for optimization adjustment on distribution of genera of seed plants endemic in Yunnan.

Abstract: Workflow management technology is an important computer technology in enterprise business process management. At present, there was a few of Workflow Engine which supported BPEL4WS specification. Base on the current research case of workflow, the aim of our study bring a Workflow platform support BPEL4WS Specification.According to the analysis of the web service’s new features and issues, we look into the dynamic workflow based on web services from the angles of service-oriented. We introduce the basic concepts, elements , activity, fault handler and compensate mechanism of BPEL4WS.This paper presents a design schem of framework of a web service-based dynamic workflow engine.

Abstract: On the basis of studying characteristics of chaotic sequences, the paper improved iterative process of the chaos, processed the chaotic chebyshev sequences by over-sampling and applied in speech signals transmission system, achieved encryption and decryption of chaotic sequences of voice signals. The results showed that the application of over-sampling technique in chaotic spread spectrum communication could greatly enhance the confidentiality of wireless communications.

Abstract: In this paper, we discuss a technique based on semantic constraints to improve the performance and portability of a reformulation-based question answering system. First, we present a method for acquiring semantic-based reformulations automatically. The goal is to generate patterns from correlative articles based on lexical, syntactic and semantic constraints. and a method to evaluate and re-rank candidate answers that satisfy these constraints is adopted. The evaluation on questions from TREC QA tracks 2003 and 2004 shows that the automatically acquired semantic patterns allows us to avoid the manual work of formulating semantically equivalent reformulations, while still reach an acceptable performance.

Abstract: In this paper we propose a data transmission mechanism that supports fairness and Quality of Service (QoS) in a wireless sensor networks (WSNs). In this mechanism the received or measured data traffics will be assigned a priority level according to its transmission urgency. And the load prediction algorithm is used to support the fairness between different priority traffics. For this, the buffer length values of the nodes are continuously monitored for some period. Based on the buffer length variations for this period, the order of transmission is determined. FQSM also adapts cross-layer concept to rearrange the data transmission order in each sensor node's buffer, saves energy consumption by allowing few nodes in data transmission, and prolongs the network lifetime

Abstract: As a branch of natural computing, membrane computing has attracted much attention in various disciplines. But the programmability of membrane computing models is an ongoing and challenging issue in this area. This paper develops the automatic design of membrane computing models through predefining the membrane structure and initial objects and introducing a modified quantum-inspired evolutionary algorithm with a local disturbance to select an appropriate subset from a redundant evolution rule set. The main idea of the presented method is that multiple membrane computing models, instead of only one model like in the literature, can be designed by applying one redundant evolution rule set. The effectiveness of the design method is verified by the experiments.

Abstract: With the rapid expansion of negative information in the Internet, the content rating technology is developed. This paper proposed a rating supervision model based on content rating considering trust model. We firstly analyze the behavior and reputation of network entities from the following dimensions: data dimension, time dimension and application dimension, and then applied artificial neural network to construct the trust model referred to the trust relationship in human society network. At last, we proposed the rating supervision model based on the trust model. It is proved that the rating supervision model can not only meet the standard of PICS, but also take the behavior and reputation of network entities into consideration. As a result, the rating supervision model can provide a variety of security services to enhance the credibility of the information by combination of rating label and network entity reputation.

Abstract: Many safety applications needed safety warning information to be disseminated to all vehicles in an area quickly. A path prediction model was built from the fused evidences by evidence theory, in which the basic probability assignment function of the local load and the old path load could be achieved using fuzzy set. And the loads became the evidences of the dissemination path prediction respectively. The prediction result with the maximal confidence was regarded as the quasi-real-time dissemination path load. Simulations show that the average end-to-end delay of safety information under heavy load with path prediction is less than the half of the delay without path prediction. However, the average packets loss rate of two schemes is almost the same.