Abstract:
Equal Salt Deposit Density (ESDD) is a main factor to classify contamination severity and draw pollution distribution map. The precise ESDD forecasting plays an important role in the safety, economy and reliability of power system. To cope with the problems existing in the ESDD predicting by multivariate linear regression (MLR), back propagation (BP) neural network and least squares support vector machines (LSSVM), a nonlinear combination forecasting model based on wavelet neural network (WNN) for ESDD is proposed. The model is a WNN with three layers, whose input layer has three neurons and output layer has one neuron, namely, regarding the ESDD forecasting results of MLR, BP and LSSVM as the inputs of the model and the observed value as the output. In the interest of better reflection of the influence of each single forecasting model on ESDD and increase of the accuracy of ESDD prediction, Morlet wavelet is used to con-struct WNN, error backpropagation algorithm is adopted to train the network and genetic algorithm is used to determine the initials of the parameters. Simulation results show that the accuracy of the proposed combina-tion ESDD forecasting model is higher than that of any single model and that of traditional linear combina-tion forecasting (LCF) model. The model provides a new feasible way to increase the accuracy of pollution distribution map of power network.

Abstract:
For reducing the exhaust noise in a radial rotatable diesel particulate filter (DPF), the finite element method was applied to establish the acoustic model. Depending on the model, muffling characteristics and transmission loss curve were gotten. By grey relational analysis, the effects of structure parameters on muffling characteristics in the radial rotatable diesel particulate filter were studied. The result indicated that the radial rotatable diesel particulate filter was capable of muffling. And the high frequency muffling effect, which the average magnitude was about 20 dB, was obviously stronger than the low one. The result also showed that diameter ratio and the expansion cone angle were two major influencing factors of muffling characteristics in radial rotatable diesel particulate filter. It helps to improve the muffling ability by using the smaller value of each factor.

Abstract:
We discuss the uniformly asymptotic estimate of the finite-time ruin probability for all times in a generalized compound renewal risk model, where the interarrival times of successive accidents and all the claim sizes caused by an accident are two sequences of random variables following a wide dependence structure. This wide dependence structure allows random variables to be either negatively dependent or positively dependent. 1. Introduction In this section, we will introduce a generalized compound renewal risk model, some common classes of heavy-tailed distributions, and some dependence structures of random variables (r.v.s), respectively. 1.1. Risk Model It is well known that the compound renewal risk model was first introduced by Tang et al. [1], and since then it has been extensively investigated by many researchers, for example, Ale？kevi？ien？ et al. [2], Zhang et al. [3], Lin and Shen [4], Yang et al. [5], and the references therein. In the paper, we consider a generalized compound renewal risk model which satisfies the following assumptions. Assumption The interarrival times of successive accidents are nonnegative, identically distributed, but not necessarily independent r.v.s with finite mean . Assumption The claim sizes and their number caused by th accident are and , , respectively, where are nonnegative and identically distributed r.v.s with common distribution and finite mean , and are not necessarily independent r.v.s, but and are mutually independent for all , , while are independent, identically distributed (i.i.d.), and positive integer-valued r.v.s with common distribution and finite mean . Assumption The sequences , , and are mutually independent. Denote the arrival times of the th accident by , , which can form a nonstandard renewal counting process with mean function . Hence the total claim amount at time and the total claim amount up to time are, respectively, and then the insurer’s surplus process is given by where is the initial surplus and is the constant premium rate. The finite-time ruin probability within time is defined as Clearly, the ruin can only arise at the times , , then Let be a nonnegative r.v., the random time ruin probability is In order for the ultimate ruin not to be certain, we assume the safety loading condition holds, namely, In the generalized compound renewal risk model above, if all the sequences , , and are i.i.d. r.v.s, then the model is reduced to the standard compound renewal risk model introduced by Tang et al. [1], if , then the model is the renewal risk model, see Tang [6], Leipus and ？iaulys [7],

Abstract:
By assuming that the native structure of a protein is known and representing each intermediate conformation as a collection of fully folded structures in which each of them contains a set of interacting secondary structure elements, we show that it is possible to significantly reduce the conformation space while still being able to predict the most energetically favorable folding pathway of large proteins with hundreds of residues at the mesoscopic level, including the pig muscle phosphoglycerate kinase with 416 residues. The model is detailed enough to distinguish between different folding pathways of structurally very similar proteins, including the streptococcal protein G and the peptostreptococcal protein L. The model is also able to recognize the differences between the folding pathways of protein G and its two structurally similar variants NuG1 and NuG2, which are even harder to distinguish. We show that this strategy can produce accurate predictions on many other proteins with experimentally determined intermediate folding states.Our technique is efficient enough to predict folding pathways for both large and small proteins at the mesoscopic level. Such a strategy is often the only feasible choice for large proteins. A software program implementing this strategy (SSFold) is available at http://faculty.cs.tamu.edu/shsze/ssfold webcite.As early studies revealed that an unfolded protein can fold spontaneously to a three-dimensional structure under suitable environmental conditions [1,2], traditional approaches to understanding protein folding have focused on the prediction of the native structure. As more studies showed the existence of intermediates and interaction among residues during the protein folding process [3,4], there is substantial interest to understand the time order of events during the formation of the tertiary structure. From the free energy point of view, each conformation of a protein is associated with a free energy and the protein folds from

Abstract:
In this paper, we obtain some new exponential inequalities for partial sums and their finite maximum of acceptable random variables by the results of Sung et al. (J. Korean Stat. Soc., 40, 109-114, 2011) and in different ways from theirs. The inequalities we obtained improve the existing corresponding results and, in some sense, are optimal. In addition, we introduce some concepts and examples of widely acceptable random variables to extend our results mentioned above. Mathematics Subject Classification (2000) 60F15, 62G20

Abstract:
Segmentation of moving objects efficiently from video sequence is very important for many applications. Background subtraction is a common method typically used to segment moving objects in image sequences taken from a statistic camera. Some existing algorithms cannot adapt to changing circumstances and require manual calibration in terms of specification of parameters or some hypotheses for changing background. An adaptive motion segmentation method is developed according to motion variation and chromatic characteristics, which prevents undesired corruption of the background model and does not consider the adaptation coefficient. RGB color space is selected instead of introducing complex color models to segment moving objects and suppress shadows. A color ratio for 4-connected neighbors of a pixel and multi-scale wavelet transformation are combined to suppress shadows. The mentioned approach is scene-independent and high correct segmentation. It has been shown that the approach is robust and efficient to detect moving objects by experiments.

Abstract:
Let X denote a discrete distribution as Poisson, binomial or negative binomial variable. The score confidence interval for the mean of X is obtained based on inverting the hypothesis test and the central limit theorem is discussed and recommended widely. But it has sharp downward spikes for small means. This paper proposes to move the score interval left a little (about 0.04 unit), called by moved score confidence interval. Numerical computation and Edgeworth expansion show that the moved score interval is analogous to the score interval completely and behaves better for moderate means; for small means the moved interval raises the infimum of the coverage probability and improves the sharp spikes significantly. Especially, it has unified explicit formulations to compute easily.

Abstract:
Ethnic difference of disease prevalence has attracted great attentions in recent years in China, but few researches have summarized analysis available on ethnic difference of disease prevalence in rural China. The PubMed Central, Wiley Inter science, Science direct, Biomed central, CNKI and Springer-link were searched to identify studies published between January 1984 and October 2014 on ethnic inequality of health status in rural China. Distinct ethnic differences of disease prevalence exist in rural China. Results across disciplines put different explanations on the ethnic differences from ethnicity, infant feeding, and inequality in maternal health services utilization angles. The ethnic inequality of health status in rural China can be reduced by policy makers to allocate more resources towards health service in ethnic rural China.