Advanced Materials Research Vols. 108-111

Abstract: Web information is main data source for the agricultural product quantity security system which is used to provide comprehensive analysis and early warning for national agriculture through large amounts of basic data. In this paper, Web information extraction architecture and a novel approach of wrapper construction are presented. The intelligence of wrapper is that both intensive and sparse data in web pages can be distinguished and extracted at one time. During the wrapper construction, hierarchical clustering is used to determine key information node and DOM technique and heuristic rules are applied to generate extraction expression according to different types of data. Experiments on a large of Web pages from different Web sites indicate that the extraction method, which has a high rate of recall and precision, is feasible and efficient.

Abstract: The early warning system for agricultural products quantity security requires storing and analyzing massive agricultural data. These data is of huge amount, heterogeneous, and has a wide-ranging source, thus the system should have an effective data collection mechanism. Based on all these requirements, how to construct an efficient early warning system has become a primary problem. In this paper, we focused our research on the architecture of the early warning system, and divided the system into application system, data collection system, and persistence system. Then we put forward reasonable architecture for each of them based on Web service and data warehouse. Finally, we emphasized on the discussion on the process of acquiring data from ministries based on the use of Web service adaptation technology. The proposed architectures are with fine flexibility and robustness, so they could be effectively used on the construction of the early warning system.

Abstract: Highway network operation monitoring and Emergency Management is an innovation which is required by the development of practical highway management process. It targets to promote the whole highway management level and the ability of public service. Based on the analysis of highway management condition and problem in China, and the directive ideas of Ministry of Transport, this article provided a basic orientation of the Highway network operation monitoring and emergency management system, analyzed the functional service of the system and the logical architecture as well as physical architecture, provided the four-layer architecture of Highway network operation monitoring and emergency management centre, which is categorized as national, regional, provincial, and municipal levels. In addition, the thesis also analyzed the system construction operational mechanism, and the data sharing and updating mechanism. The mentioned discuss on the architecture of the Highway network operation monitoring and emergency management system is valuable to the standardization, extendibility, and the sustainability of system construction. Finally, the current works on this system in China are briefly introduced.

Abstract: Dimensionality reduction is useful for improving the performance of Bayesian networks. In this paper we suggest an effective method of modeling categorical and numerical variables of the mixed data with different Bayesian classifiers. Such an approach reduces output sensitivity to input changes by applying feature extraction and selection, and empirical studies on UCI benchmarking data show that our approach has clear advantages with respect to the classification accuracy.

Abstract: Decision tree classification is one of the most widely-used methods in data mining which can provide useful decision-making analysis for users. But most of the decision tree methods have some efficiency bottle-necks and can only applied to small-scale datasets. In this paper, we present an new improved synthesized decision tree algorithm named CA which includes three important parts like dimension reduction, pre-clustering and decision tree method, and also give out its formalized specification. Through dimension reduction and synthesized pre-clustering methods, we can optimize the initial dataset and considerably reduce the decision tree’s input computation costs. We also improve the decision tree method by introducing parallel processing concept which can enhance its calculation precision and decision efficiency. This paper applies CA into maize seed breeding and analyzes its efficiency in every part comparing with original methods, and the results shows that CA algorithm is better.

Abstract: Logic minimization software is an important tool in digital integrate circuit design environment. The optimization of Multi-Valued Logic Functionisan extension of Binary-Valued Logic Function. For huge variable logic functions optimization, spending of memory is increaseon two power by input variables. This paper presents the description of binary vector of Multi-Valued variable and Multi-Valued Logic Function, transforms Multi-Valued cube into the Boolean expression with recursion fission and finally introduces the logic optimization algorithm of expanding products. It overpasses testing of Benchmark and right validate.

Abstract: With the rapid development of the society, more and more countries have been increasingly optimistic about wind power projects because of its advantages, such as non-polluting, renewable, energy-saving and emission reduction. While facing the temptation of high profit, it is necessary to assess the risks of wind power project investment scientifically. Therefore, this article combines with the risk characteristics of wind power project under the current social environment to build a evaluation index system of wind power project to evaluate the risk of wind power project based on BP neural network.

Abstract: Yunnan cherry-tomato and Xinjiang cherry-tomato were very similar in appearance. But they are different in taste and nutritive value. A nondestructive identification method of cherry-tomato variety based on multi-spectral image technology is proposed in this paper. Fifty Yunnan cherry-tomatoes and fifty Xinjiang cherry-tomatoes were selected, and photos were taken by Duncan MS3100 3CCD multi-spectral imager. Threshold based segmentation and mathematical morphology method were used to process the images. Nine characteristic variables were calculated to establish discriminant analysis model (DA) and least square-support vector machine model (LS-SVM). The prediction accuracy of discriminant analysis model was 72.5% and that of LS-SVM model was 80%. The results showed that LS-SVM model could identify Yunnan cherry-tomato and Xinjiang cherry-tomato well.

Abstract: Extension rule is a new method for computing the number of models for a given propositional formula. In some sense, it is actually an inverse propositonal resolution. In order to improve counting performance, we introduce some reasoning rules into extension rule based model counting and present a new algorithm RCER which combines the extension rule and the reasoning rule together. The experiment results show that the algorithm not only occupies less space but also increases the efficiency for solving model counting.

Abstract: Skype is a P2P overlay network for VoIP and other applications, which is widely used all over the world. Based on analysis of the operation mechanisms, the communication processes of Skype are discussed detailedly, and then a multiple-layer based system for Skype network traffic identification is designed. The System mainly consists of three entities, which include suspicious connection table, payload detection module and traffic detection module. The functional characteristics of all entities are introduced, and the attribute set for network behavior is depicted. Finally, experiment results show the usability of the system.