Applied Mechanics and Materials Vols. 380-384

Abstract: Iris localization is to detect outer-and-inner boundaries of iris in an iris image. In the paper, an improved algorithm was proposed to quickly and effectively locate outer-and-inner boundaries. As for this algorithm, the first is to block an iris image and extract its sub-image blocks which cover pupil; the second is to set a binary threshold of pupil by adopting the method of Maximum Variance between Clusters; the third is to get the value outer-boundary-points of iris, on the basis of gray gradient of key Regions-of-interest; the last is to select some characteristic pixels in regions of interest respectively and fit outer-and-inner boundaries of iris according to curve fitting.

Abstract: According to the problem of multi-UCAV air-combat task allocation in uncertain environment, first consider the uncertainty elementsin the air-combat, the model of air-combat situation based on interval information is built, and combinat air combat situation predominance and attack gains, Finally, the model for task allocation of Multi-UCAV cooperative combat is built. Then Analysy to solve the problem used SMAA, the results show the feasibility and effectiveness of the method.

Abstract: Many applications have provided functions of automatic searching and reading barcodes in complex scenes with a camera. However state of the art barcode detection systems are limited to their serious requirement, such as shooting angle, light intensity and revolution. This paper proposes an effective solution for automatic barcode localization by exploiting ELM (extreme learning machine) and multichannel Gabor filtering techniques. We first employ Gabor filter to extract texture feature of the barcode, and then the barcode regions and the background region in texture image are use to train the ELM classifier. Finally, we apply our method to the barcode image database, which consists of several different barcode symbologies. Experiment shows our method is superior to the General morphology method and has desirable properties in accuracy, rotation invariance and robustness to noise.

Abstract: Image segmentation is a key step in image processing and image analysis and occupies an important position in image engineering.In this paper, basing on maximum variance between-class, an adaptive and multi-objective image segmentation method is proposed. The concrete implement is to determine adaptively the optimum number of threshold of image using the idea of variance decomposition,while calculating the weighted ratio of within class difference and class difference existing in each classification image. By comparing the ratio, the optimum number of target for image can be get. The experimental results show that the sub-images after segmentation are relatively clear and the differences between classes are obvious.

Abstract: nverse problems are important interdisciplinary subject, which receive more and more attention in recent years in the areas of mathematics, computer science, information science and other applied natural sciences. There is close relationship between inverse problems and ill-posedness. Regularization is an important strategy when computing the ill-posed problems to maintain the stability of the computation.This paper compares a new regularization method,which is called Adaptive regularization, with the traditional Tikhonov regularization method. The conclusion that Adaptive regularization method is a stronger regularization method than the traditional Tikhonov regularization method can be made by computing some numerical examples.

Abstract: Aiming at the problem that some products show no failure in the random truncation test period,the mean rank order method is introduced to determine the sequence number of failure time and the method of approximate median order is used to calculate the empirical cumulative distribution function.To solve the poser that model of failure distribution of the same batch of data is not the single one,this study uses analytic hierarchy process (AHP) and entropy weight-TOPSIS,including both objective and subjective factors,to find out the datas optimun distribution.Through taking an example,It proved that this method is simple to use and has good applicability.

Abstract: A queuing model is proposed to analyze the performance of IEEE 802.11 Distributed Coordination Function (DCF). By regarding the network performance in the unsaturated case as the expected mean of the network performance in the different saturated cases, the proposed model extends the application scenarios from the saturated case to the nonsaturated case. The queuing model can be used to analyze the network performance and QoS parameters of the stations for different traffic conditions. In addition, this model also applies to the cases in shadow channels. Compared to the existing work based on the classic Markov model, the proposed model is more general and can be used in more complex and practical scenarios.

Abstract: Considering the involving stakeholders in public rental housing construction under the CCIT model, which is the basics of constructing the financial structure and analysing the main body involved in the risk, and then construct the assessment system. This paper proposes a model based on the analytic hierarchy process (AHP) and grey clustering risk assessment method. Firstly by analyzing the clustering index in the financing mode of risk subject, we can quantify the weight of indicators of every layers, and then using the gray clustering to get clustering analysis, drawing the value at risk ,finally , this article quantitatively analyses the CCIT mode in public rental housing construction in the use of the degree of risk..

Abstract: Particle Swarm Optimization (PSO) has attracted many researchers attention to solve variant benchmark and real-world optimization problems because of its simplicity, effective performance and fast convergence. However, it suffers from premature convergence because of quickly losing diversity. To enhance its performance, this paper proposes a novel disruption strategy, originating from astrophysics, to shift the abilities between exploration and exploitation. The proposed Disruption PSO (DPSO) has been evaluated on a set of nonlinear benchmark functions and compared with other improved PSO. Comparison results confirm high performance of DPSO in solving various nonlinear functions.

Abstract: On this paper, a simple introduction about the concept of the domination set in graphs and the research progress is presented. The definition of stochastic dominating set is introduced as well; We designed several strategies to compute the stochastic dominating set, and analyzed the domination rate using probability theory in the broadcasting model. These strategies have important theory value to solve network communication redundancy package problem.