Simulation of Strength Distribution in Ground Ceramics by Incorporating Residual Stress Effect

Strength of ground ceramics may be affected by residual stress as well as surface flaws induced by grinding. Strength prediction for ground ceramics is convenient for mechanical design of ceramic components. In this article, a numerical procedure based on fracture mechanics was proposed to estimate strength distribution of ground ceramics by considering grinding-induced residual stress. Bending strength and residual stress of ground ceramics were measured for three grinding-conditions. By comparison of simulated results with experimental ones, it was revealed that strength characteristics in experiments were well simulated by using the proposed procedure.     

Semiparametric Estimation in Time‐Series Regression with Long‐Range Dependence

Abstract. We consider semiparametric estimation in time‐series regression in the presence of long‐range dependence in both the errors and the stochastic regressors. A central limit theorem is established for a class of semiparametric frequency domain‐weighted least squares estimates, which includes both narrow‐band ordinary least squares and narrow‐band generalized least squares as special cases. The estimates are semiparametric in the sense that focus is on the neighbourhood of the origin, and only periodogram ordinates in a degenerating band around the origin are used. This setting differs from earlier studies on time‐series regression with long‐range dependence, where a fully parametric approach has been employed. The generalized least squares estimate is infeasible when the degree of long‐range dependence is unknown and must be estimated in an initial step. In that case, we show that a feasible estimate which has the same asymptotic properties as the infeasible estimate, exists. By Monte Carlo simulation, we evaluate the finite‐sample performance of the generalized least squares estimate and the feasible estimate.     

Motion and structure interpretation of an optical switch

This paper focuses on tracking, reconstruction and motion estimation of a well-defined MEMS optical switch from a microscopic view. For out-of-view reconstruction, a homography capable of transforming feature points and feature lines between a microscopic image and a CAD model of the switch is implemented. The homography between two sequential microscopic images is decomposed and factorized for motion estimation. Optical flow has also been explored to provide rough estimations of rotation centre and angle. The paper also illustrates motion parameter optimization principles to deal with uncertainty inherent in micro world. After non-linear optimization, estimation accuracy for rotation angle and rotation centre can reach 0.06° and pixel level, respectively.     

Robustness of classification rules that incorporate additional information

The discrimination problem for two normal populations with the same covariance matrix when additional information on the population is available is considered. A study of the robustness properties against training sample contamination of classification rules that incorporate this additional information is performed. These rules have received recently attention where their total misclassification probability (TMP) is proved to be lower than Fisher's linear discriminant rule. The results of a simulation study on the TMP which compares the behaviour of the new rules against Fisher's rule and some of its robustified versions under different types of contamination are presented. These results show that the rules that incorporate the additional information not only have lower TMP, but they also prevent against some types of contamination. In order to achieve prevention from all types of contamination a robustifed version of these rules is recommended.     

RTK技术在控制测量中的应用研究

GPS RTK(Real Time Kinematic)技术的快速定位功能为其应用创造了良好的条件,但其定位精度验后估计的欠缺又使其应用受到一定的限制。本文针对此问题进行了研究,给出了GPS RTK测量成果的精度估计方法,并对GPS RTK测量技术用于控制测量的可行性进行了探讨,导出了相应的测量限差,为CPS RTK测量技术用于控制测量提供了理论依据和技术规定。     

Bootstrapping the Local Periodogram of Locally Stationary Processes

Abstract. Locally stationary processes are non‐stationary stochastic processes the second‐order structure of which varies smoothly over time. In this paper, we develop a method to bootstrap the local periodogram of a locally stationary process. Our method generates pseudo local periodogram ordinates by combining a parametric time and non‐parametric frequency domain bootstrap approach. We first fit locally a time varying autoregressive model so as to capture the essential characteristics of the underlying process. A locally calculated non‐parametric correction in the frequency domain is then used so as to improve upon the locally parametric autoregressive fit. As an application, we investigate theoretically the asymptotic properties of the bootstrap method proposed applied to the class of local spectral means, local ratio statistics and local spectral density estimators. Some simulations demonstrate the ability of our method to give accurate estimates of the quantities of interest in finite sample situations and an application to a real‐life data‐set is presented.     

Grouped Approach for the Design of H.264/AVC Motion Estimation Architectures

This letter presents a novel approach for organizing computational resources into groups within H.264/AVC motion estimation architectures, leading to reductions of up to 75% in the equivalent gate count with respect to state‐of‐the‐art designs.     

Quadtree-based genetic algorithm and its applications to computer vision

Many computer vision problems can be formulated as optimization problems. Presented in this paper is a new framework based on the quadtree-based genetic algorithm that can be applied to solve many of these problems. The proposed algorithm incorporates the quadtree structure into the conventional genetic algorithm. The solutions of image-related problems are encoded through encoding the corresponding quadtrees, and therefore, the 2D locality within a solution can be preserved. Examples addressed using the proposed framework include image segmentation, stereo vision, and motion estimation. In all cases, encouraging results are obtained.     

Measurement of the coolant flow rate using correlation of temperature fluctuations

The transit time of the coolant, and thus its velocity, has been measured using the temperature fluctuation at the outlet of a reactor core. An impulse response function estimation is introduced, which substitutes the widely used cross-correlation measurement technique. It is shown in theory and practice that the time delay estimation is improved when using the impulse response function instead of the cross-correlation function in parameter estimation. Extremely low velocities (down to 2 cm/sec) have been measured in a natural circulation regime in a research reactor.