Applied Mechanics and Materials Vols. 644-650

Abstract: Because driver decision-making is a complicated process, static factors and dynamic factors should be considered in research on driving model in Intelligent Transportation microscopic study. In this paper, Grey relation entropy analysis method is used to judge the degree of importance in the whole factors.Experiment in this paper provides Grey relation entropy analysis is very effective to calculate the rank of these impact factors of driver decision-making.

Abstract: This paper focuses on intelligent analysis of small samples in geotechnical engineering, the calculation process of SVM is simplified by applying LSSVM, the generalization performance of SVM is maintained utmost by using leave one out method, the approximation performance of SVM is optimized by applying wavelet kernel constructed from Marr wavelet, the parameters of SVM is optimized quickly and comprehensively through applying chaotic ants swarm algorithm, the convergence of chaotic ants swarm algorithm is accelerated by reconstituting part of ant-matrix in the process of optimization, and lastly the effectiveness of chaotic ants swarm optimize LSSVM algorithm is proven through practical engineering.

Abstract: An anti-plane Green function is formulated for steady state solution of a circular lining impacted by a vertical interfacial point source in an elastic quarter space. Series forms of scattering and stationary wave of the circular lining are constructed with Fourier wave function expansion method. Basic solution of the anti-plane point source is employed to represent displacement fields of incident wave. Stress-free conditions on the quarter bounds are satisfied by using image method. Displacement and stress continuity conditions of the lining are expanded as Fourier series to determine definite equations of unknown coefficients of wave function series.

Abstract: This paper presents an improved Local Binary Pattern (LBP) operator for feature extraction f which considers both sign and magnitude information of the local difference of neighborhood and center pixels. The image is first divided into small blocks from which improved LBP histograms are extracted and concatenated into a single feature histogram. Then, the Principal Component Analysis (PCA) method is used to reduce feature dimensions. Finally, the recognition is performed by a nearest-neighbor classifier with Chi square statistic as the dissimilarity measurement. Experiments on AR face image databases by the leave-one-out (LOO) procedure illustrate that this method has higher recognition rate and more robust than the original LBP.

Abstract: In order to improve the accuracy of news recommendation, this paper established a comprehensive user interest model. First,this paper established a stable user interest model based on user browsing habits .Then,the paper also advanced freshness-based tentative recommendations on the basis of news timeliness and mainstream to get the user's temporary interest model. Finally,the paper combined these two models to establish a comprehensive user interest model. Experimental results proved that the proposed method can recommend specific news articles that best meet the user's reading preferences from a large number of the latest published news.

Abstract: Steady state responses of a circular cavity and a semi-circular canyon subjected by plane SH wave in an elastic quarter are presented by using Fourier-Hankel wave function expansion method and image method with Fourier series expansion on the boundary conditions to determine linear algebraic equations of unknown wave function coefficients. Especially, displacement and stress component expressions are formulated for incident, reflected, scattering waves, respectively. This method can provide an analytical ideas and methods for further studies of elastodynamic interface problems.

Abstract: In this article, we present and discuss a class of new reduced order method based on He’s variational iteration procedure. We introduce two transformations and in a single space variable, and then formulate a second-order coupled system of equations. We can obtain the analytical approximate solutions for the scalar unknown u, time derivative and second-order space derivative, simultaneously. Moreover, an extension problem in two space variables is also proposed. Finally, we show some examples to illustrate the effectiveness of our procedure.

Abstract: Z. Pawlak’s classical rough set theory has been widely applied in analyzing ordinary information systems and decision tables. In this theory, a relative reduct can be considered as a minimum set of attributes that preserves a certain classification property. This paper investigates three different classification properties, and proposes three distinct definitions accordingly. According to the three classification properties, we can define three distinct definitions respectively. Based on the common structure of the specific definitions of relative reducts and discernibility matrices, general definitions of relative reducts and discernibility matrices are suggested.

Abstract: Z. Pawlak’s rough set theory has been widely applied in analyzing ordinary information systems and decision tables. While few studies have been conducted on attribute selection problem in incomplete decision systems because of its complexity. Therefore, it is necessary to investigate effective algorithms to tackle this issue. In this paper, In this paper, a new rough conditional entropy based uncertainty measure is introduced to evaluate the significance of subsets of attributes in incomplete decision systems. Moreover, some important properties of rough conditional entropy are derived and three attribute selection approaches are constructed, including an exhaustive approach, a heuristic approach, and a probabilistic approach. In the end, a series of experiments on practical incomplete data sets are carried out to assess the proposed approaches. The final experimental results indicate that two of these approaches perform satisfyingly in the process of attribute selection in incomplete decision systems.

Abstract: Although hard disk drives have been popular over several decades, there still exists the deficiency because of their slow speeds and high power consumptions. By contrast, flash-based solid state disks exhibit good performance and low power consumption. However, the limited lifetimes become a fatal flaw of solid state disks. In order to take full advantage of hard disk drives and solid state disks, we design a hybrid storage system to make them work in a complementary manner. Further, we propose a data placement scheme for this system to determine the data placement on the underlying solid state disks or hard disk drives based on the data access statistics. Experiment results show that the lifetime of solid state disks and the response time of the system can be significantly improved compared with the alone storage media.