Abstract:
A CPW-fed ultra-wideband antenna was designed. The antenna was etched on a single-layer copper-cladding substrate, of which the material was FR4 with relative permittivity of 4.4, and the magnitude was 40.0 mm × 50.0 mm × 1.6 mm. The parameters of the antenna are simulated and optimized with HFSS. This paper proposes a new trapezoidal CPW-fed UWB antenna that the bandwidth (return loss ≤ ?10 dB) covers 2.7 - 9.3 GHz range, which means a relative bandwidth of 110% with good radiation patterns and gain. Simulated and measured results for return loss, radiation pattern and gain were presented. A good agreement has been obtained between the simulation and experiment and the proposed antenna meets the requirements of the ultra-wideband antenna.

Abstract:
Taking cultural knowledge tests as the case study, this research carries out a series of empirical investigations to verify the moderating effects of item order arranged by difficulty on the relationship between test anxiety and test performance. Groups classified according to test anxiety take tests with two major types of item order: item order arranged according to item bank calibrated item difficulty and item order adjusted according to individual examinee’s perceived item difficulty. The means of those test results are compared between groups to see whether the differences are significant. The investigations obtain the following findings: the higher the test taker’s level of test anxiety, the higher significance of the moderating effects and vice versa; item order adjusted according to individual examinee’s perceived item difficulty may have a more significant moderating effect than item order arranged according to item bank calibrated item difficulty has.

Abstract:
This paper presents a three-dimensional canonical correlation analysis (TCCA) method, and applies it to feature fusion for image recognition. It is an extension of traditional canonical correlation analysis (CCA) and two-dimensional canonical correlation analysis (2DCCA). Considering two views of a three-dimensional data, the TCCA can directly find the relations between them without reshaping the data into matrices or vectors, We stress that TCCA dramatically reduce the computational complexity, compared to the CCA and 2DCCA. To evaluate the algorithm, we are using Gabor wavelet to generate the three-dimensional data, and fusing them at the feature level by TCCA. Some experiments on ORL database and JAFEE database and compared with other methods, the results show that the TCCA not only the computing complexity is lower, the recognition performance is better but also suitable for data fusion.

Abstract:
This study carries out empirical researches among Mainland Chinese high school students to explore the impact of parent’s socioeconomic status on perceived parental pressure and test anxiety. The discoveries of the study include: perceived parental pressure has significant impact on test anxiety; parents’ occupations, parents’ income and mother’s education have significant impact on perceived parental pressure; parents’ occupations, parents’ income and mother’s education have significant impact on test anxiety. There are sufficient evidences to support the notion that the ethic stressing family glory and material success can be a major source of perceived parental pressure and test anxiety in China. Another finding of the study is that there may exist a mediation relationship among parent’s socioeconomic status, perceived parental pressure, and test anxiety. By controlling perceived parental pressure, the mediator variable, the impact of parent’s socioeconomic status on test anxiety can be greatly reduced.

Abstract:
We prove some limit properties of the harmonic mean of a random transition probability for finite Markov chains indexed by a homogeneous tree in a nonhomogeneous Markovian environment with finite state space. In particular, we extend the method to study the tree-indexed processes in deterministic environments to the case of random enviroments. 1. Introduction A tree is a graph which is connected and doesn't contain any circuits. Given any two vertices , let be the unique path connecting and . Define the graph distance to be the number of edges contained in the path . Let be an infinite tree with root . The set of all vertices with distance from the root is called the th generation of , which is denoted by . We denote by the union of the first generations of . For each vertex , there is a unique path from to and for the number of edges on this path. We denote the first predecessor of by . The degree of a vertex is defined to be the number of neighbors of it. If every vertex of the tree has degree , we say it is Cayley’s tree, which is denoted by . Thus, the root vertex has neighbors in the first generation and every other vertex has neighbors in the next generation. For any two vertices and of tree , write if is on the unique path from the root to . We denote by the farthest vertex from satisfying and . We use the notation and denote by the number of vertices of . In the following, we always let denote the Cayley tree . A tree-indexed Markov chain is the particular case of a Markov random field on a tree. Kemeny et al. [1] and Spitzer [2] introduced two special finite tree-indexed Markov chains with finite transition matrix which is assumed to be positive and reversible to its stationary distribution, and these tree-indexed Markov chains ensure that the cylinder probabilities are independent of the direction we travel along a path. In this paper, we omit such assumption and adopt another version of the definition of tree-indexed Markov chains which is put forward by Benjamini and Peres [3]. Yang and Ye[4] extended it to the case of nonhomogeneous Markov chains indexed by infinite Cayley’s tree and we restate it here as follows. Definition 1 (T-indexed nonhomogeneous Markov chains (see [4])). Let be an infinite Cayley tree, a finite state space, and a stochastic process defined on probability space , which takes values in the finite set . Let be a distribution on and a transition probability matrix on . If, for any vertex , then will be called -valued nonhomogeneous Markov chains indexed by infinite Cayley’s tree with initial distribution (1) and

Abstract:
We prove a central limit theorem for th-order nonhomogeneous Markov information source by using the martingale central limit theorem under the condition of convergence of transition probability matrices for nonhomogeneous Markov chain in Cesàro sense. 1. Introduction Let be an arbitrary information source taking values on alphabet set with the joint distribution for . If is an th-order nonhomogeneous Markov information source, then, for , Denote where and are called the m-dimensional initial distribution and the th-order transition probabilities, respectively. Moreover, are called the th-order transition probability matrices. In this case, There are many of practical information sources, such as language and image information, which are often th-order Markov information sources and always nonhomogeneous. So it is very important to study the limit properties for the th-order nonhomogeneous Markov information sources in information theory. Yang and Liu [1] proved the strong law of large numbers and the asymptotic equipartition property with convergence in the sense of a.s. the th-order nonhomogeneous Markov information sources. But the problem about the central limit theorem for the th-order nonhomogeneous Markov information sources is still open. The central limit theorem (CLT) for additive functionals of stationary, ergodic Markov information source has been studied intensively during the last decades [2–9]. Nearly fifty years ago, Dobrushin [10, 11] proved an important central limit theorem for nonhomogeneous Markov information resource in discrete time. After Dobrushin's work, some refinements and extensions of his central limit theorem, some of which are under more stringent assumptions, were proved by Statuljavicius [12] and Sarymsakov [13]. Based on Dobrushin's work, Sethuraman and Varadhan [14] gave shorter and different proof elucidating more the assumptions by using martingale approximation. Those works only consider the case about th-order nonhomogeneous Markov chain. In this paper, we come to study the central limit theorem for th-order nonhomogeneous Markov information sources in Cesàro sense. Let be an th-order nonhomogeneous Markov information source which is taking values in state space with initial distribution of (3) and mth order transition probability matrices (5). Denote We also denote the realizations of by . We denote the th-order transition matrix at step by where . For an arbitrary stochastic square matrix whose elements are , we will set the ergodic -coefficient equal to where . Now we extend this idea to the th-order stochastic

Abstract:
This paper is concerned with the connection between G-Brownian Motion and analytic functions. We introduce the complex version of sublinear expectation, and then do the stochastic analysis in this framework. Furthermore, the conformal G-Brownian Motion is introduced together with a representation, and the corresponding conformal invariance is shown.

Abstract:
In situ time-resolved FTIR spectroscopy was used to study the reaction mechanism of partial oxidation of methane (POM) to synthesis gas and the reaction of CH4/O2/He (2/1/45, molar ratio) gas mixture with adsorbed CO species over Rh/SiO2, Ruγ-Al2O3 and Ru/SiO2 catalysts at 500–600°C. It was found that CO is the primary product of POM reaction over reduced and working state Rh/SiO2 catalysts. Direct oxidation of CH4 is the main pathway of synthesis gas formation over Rh/SiO2 catalyst. CO2 is the primary product of POM over Ru/gg-Al2O3 and Ru/SiO2 catalysts. The dominant reaction pathway for synthesis gas formation over Ruγ-Al2O3 catalyst is via the reforming reactions of CH4 with CO2 and H2O. For the POM reaction over Rh/SiO2 and Ru/gg-Al2O2 catalysts, consecutive oxidation of surface CO species is an important pathway of CO2 formation.