Advanced Materials Research Vols. 532-533

Abstract: In this study, the evaluation index system of library service quality is established and the representation method of knowledge rule is analyzed firstly. Then, a knowledge rule mining method for the evaluation of library service quality based on an improved genetic algorithm is proposed. In the algorithm, selection operator, help operator, crossover operator and mutation operator are used to generate new knowledge rules. Knowledge rules are evaluated by their accuracy, coverage and reliability. Experimental results show that this knowledge rule mining method is feasible and valid. It is helpful for us to evaluate the library service quality fairly and objectively.

Abstract: Automatically extracting keywords from webpage is greatly important for focused spider. There are already quite many researches on automatically extracting keywords from content-intensive web pages. However, it is still a challenge to extract keywords automatically from hyperlink-intensive web pages (hub pages). The web page author will often use all kinds of visual strengthening means to prominently demonstrate some glossaries connected with the subject. Therefore, this paper proposes a visual model of web pages, DOM-PIXEL, which regards DOM leaf node of webpage as an image element expressed by a vision vector, in which each component corresponds to one visual emphasis means; the pixel value is from the visual energy. The pixel value reflects the relevance of the corresponding DOM node with respect to subject. These parts strengthened by page author will be highlighted with particular “color” in DOM-PIXEL image. Then, the only request for keywords extraction algorithm is to find these “particular points” with particular “color” automatically. Just because of the intrinsic anti-noise ability of DOM-PIXEL and its visual energy transfer rule, the visual model based keywords extraction algorithm (VisualKEA) proposed in this paper significantly promotes the performance on hub pages.

Abstract: In order to solve the problem of high non-uniformity of LED display images which is caused by the edges of LED display panel during module splicing, transitional compensation algorithm is proposed by improving the existed correction technique named the correction technique based on CCD. First, introduce the three development stages of the LED display panel. Then, the realization progress of the transitional compensation algorithm is described in detail after elaborating the principle of transitional compensation. Finally, the algorithm is emplaned in a LED video control system to control the LED display panel whose display area is 1280×960, and which is spliced by 30×20 LED modules whose size are 64×32. Experimental results show that this algorithm is able to reduce non-uniformity of LED display images from 29.3% before correcting to 0.95%.

Abstract: Energy-saving is one of the inevitable problems of the routing design in WSN, while Data Fusion technology is widely utilized in energy constraint WSN to reduce the amount of messages exchanged between sensor nodes. This paper proposes a new algorithm based on Integrated Genetic and BP Neural Network(IGBP), IGBP uses the global search capability of GA to remedy the deficiency of BP artificial neural network. First, IGBP generates the best individuals in different networks by GA algorithm. Then it chooses the most optimize individual measure by Mean Squared Error to construct the BP network which was supplied to train of the WSN. Using the optimize individual nodes as initialization value training the BP network, it will enhance the learning rates of convergence and avoid falling into the local minimums .The simulation results show that the IGBP algorithm has made great progress in balancing the consumption of energy so as to prolong the network lifetime.

Abstract: When mapping large-scale battlefield terrain, in order to make a real-time show it on the computer it is required to keep the vector data (points, lines, areas) at the high curvature and delete the vector data at the low curvature as much as possible. This article puts forward a simplified algorithm to calculate the average curvature of the space mesh points with level of detail (LOD) model technique as well as the visualization implementation of this algorithm. Then according to this algorithm, work out the curvature value of the mesh points, delete the center points of the low curvature and triangularize the cavity left so as to simplify LOD model and reduce dramatically the number of the vector data (points, lines, areas) in the field of view of the large-scale battlefield terrain. Experiments show the average curvature algorithm put forward in this article can better solve the contradiction between the big vector data and the limited real-time processing capacity of the computer. As a result, it can meet the requirements of mapping great number of real-time data of the large-scale battlefield terrain by 3 D visualization.

Abstract: A PSO-algorithm-based job scheduling method that takes production cost as optimization object is presented in this paper. The cost optimization model of HFSP, in which production cost is considered as an optimal factor, is constructed. PSO is used to take global optimization, make the production task assignment and find which machine the jobs should be assigned at each stage, which is also called the process route of the job. After that the local assignment rules are used to determine the job’s starting time and processing sequence at each stage. The total production cost converted by time-based scheduling results is comprehensively considering the processing cost, waiting costs, and the products storage costs. The numerical results show the effectiveness of the algorithm after comparing between multi-group programs.

Abstract: The traditional LPT-based image mosaic algorithm has such problems as huge calculation load and narrow applied fields, etc. In view of that, this paper puts forward a mosaic algorithm based on SUSAN Corner Detection Algorithm and LPT, which will firstly make corner detection, and then, with the corner as the coordinate transform central point, choose proper search strategy to further reduce the calculation load. The result of experimentation shows that this algorithm is effective.

Abstract: Simplex method is one of the most useful methods to solve linear program. However, before using the simplex method, it is required to have a base feasible solution of linear program and the linear program is changed to thetypical form. Although there are some methods to gain the base feasible solution of linear program, artificial variablesare added and the times of calculating are increased with these calculations. In this paper, an extended algorithm of the simplex algorithm is established, the definition of feasible solution in the new algorithm is expended, the test number is not the same sign in the process of finding problem solution. Explained the principle of the new algorithm and showed results of LP problems calculated by the new algorithm.

Abstract: Shape context is not rotation invariant as a local visual feature. To solve this problem, 2-D and 1-D Fourier Transformation has been performed on the feature. Based on the property of Fourier Transformation, a fast and efficient method is presented in the cost matrix computation of these improved shape context feature. The analysis shows the time complexity is much lower and the experiments show effective and efficiency of this new algorithm.

Abstract: A numeric method of solving nonlinear equation group is proposed. The problem of solving nonlinear equation group is equivalently changed to the problem of function optimization, and then a solution is obtained by adaptive genetic algorithm, considering it as the initial solution of Levenberg-Marquardt algorithm, a more accurate solution can be obtained, as a result, time efficiency is improved.