Applied Mechanics and Materials Vols. 121-126

Abstract: According to the analysis of security factors for regional power grid, this paper established a comprehensive evaluation index system for grid security. Combined with AHP and entropy model, calculated the combination weight of indicators to determine the model, then established a comprehensive evaluation theory system for grid security on the basis of loud centroid theory. The applicability of the model just created was demonstrated well by an example calculation, providing the theoretical basis for further strengthening the grid security management.

Abstract: TSP has been studied in many methods by various algorithms. with the increase of the TSP scale, there are some problems appear in the related solution ,such as solving the optimal solution and so on. With the increasing calculation nodes, the convergence degree and computing difficulty of TSP will increase enormously. Artificial fish is an optimize algorithm based on biology model putting forward at present. Proposed a solution for TSP based on the Artificial fish algorithm, describes the mathematic model of TSP, and Expounds the steps of the algorithm in details. by testing the algorithm, we know that, the algorithm can obtain the best solution, in global search, convergence rate,,but the robustness has to be improved in the future.

Abstract: In solving complex optimization problems, intelligent optimization algorithms such as immune algorithm show better advantages than traditional optimization algorithms. Most of these immune algorithms, however, have disadvantages in population diversity and preservation of elitist antibodies genes, which will lead to the degenerative phenomenon, the zigzag phenomenon, poor global optimization, and low convergence speed. By introducing the catastrophe factor into the ACAMHC algorithm, we propose a novel catastrophe-based antibody clone algorithm (CACA) to solve the above problems. CACA preserves elitist antibody genes through the vaccine library to improve its local search capability; it improves the antibody population diversity by gene mutation that mimics the catastrophe events to the natural world to enhance its global search capability. To expand the antibody search space, CACA will add some new random immigrant antibodies with a certain ratio. The convergence of CACA is theoretically proved. The experiments of CACA compared with the clone selection algorithm (ACAMHC) on some benchmark functions are carried out. The experimental results indicate that the performance of CACA is better than that of ACAMHC. The CACA algorithm provides new opportunities for solving previously intractable optimization problems.

Abstract: In order to improve the fitting of garment on shoulder, the measurement of 275 young females aged from 20-24 were taken with 3D-body scanner; the position data relating to the shoulder was conducted using cluster analysis, and extracted 5 characteristic indices that contained almost information of shoulder shape; the rationality of clustering shoulder shape to 4 different types was tested and verified through using one-way analysis of variance; then established the Fisher Discriminant Analysis (FDA) model to identify the young females’ shoulder shape. The result showed that the forecasting model of Fisher Discriminant Analysis (FDA) had excellent performance, high prediction accuracy, so it provided a new method to identify young females’ shoulder shape.

Abstract: Paper unavailable due to copyright issues.

Abstract: To combat the problems of disparity image inpainting, an improved exemplar-based image inpainting method is proposed. The original stereo image we select which corresponds to disparity image is decomposed by TV-based decomposition and the structural information is obtained. The patch priority in the position corresponding to the disparity image is calculated by using the structural information, which reflects true characteristics of the original stereo image and disparity image. Experimental results show that inpainting performance is better with the guidance of this patch priority for disparity image.

Abstract: First-order linear filter is a wide application algorithm to detect edge in digital image. However it dosen’t make good effort to the image where contrast varies much, or luminance takes on non-uniform. In this paper, a fuzzy inference system (FIS) is made up and used to detect edges. The experiment shows that FIS is much better in edge detection when the image with high contrast variation than with the linear Sobel operator. The FIS is also more precise in edge detection than Sobel operator.

Abstract: It is much more complex and difficult for edge detection of noise image compared to edge detection of normal image，the analysis and study of edge detection of noise image has universal significance and practical value. Wavelet transform possesses good time-frequency localization characteristic and multi-scale analytical ability, mathematical morphology is a new subject based on set theory, which is very suitable for analyzing and describing geometrical feature of signal. Combining the advantages of wavelet transform and mathematical morphology, the paper proposes an edge detection algorithm, which mainly focused on noise image. For edge detection based on mathematical morphology, constructs an anti-noise operator of edge detection by improving existing operators and employs different direction linear structure elements; edge detection based on mathematical morphology can reserve details of edge effectively, ensure the continuity and integrity of edge detected. Experimental results show the proposed algorithm can suppress the interference of different density and different types of noise more effectively in comparison with several classical edge detection algorithm, thus improving the detection accuracy and robustness for different images.

Abstract: We are witnessing the rapid development of Cloud Computing techniques and services. Cloud Storage is widely applied in nowadays research and industry community. One of the most hottest topic in cloud storage is the data reliability. To ensure reliability under the condition of inexpensive hardware, several techniques are discussed and applied. We simplify and analyze the data reliability by a markov model, which includes the discussion of correlated failures and rack-aware placement. Our model aims to tell the effect of rack-aware placement for cloud storage systems.

Abstract: According to IT investments into performance process model, the paper measures the manufacturing enterprises informatiaztion process efficiencies by value chain DEA model from relevant data indicators of manufacturing enterprises in China. The enterprise informatization consists two processes: IT investments transformation into IT assets and IT assets transformation into the IT impact, which happen inside the enterprises. So, the value chain DEA model is suitable to measure the two processes efficiencies. Finally, the paper analyzes enterprise informatization factors that influence the two processes efficiencies, in order to provide theoretical guidance to improve informatization process efficiencies of Manufacturing Enterprises.