Introduction of a nonlinearity measure for principal component models

Although principal component analysis (PCA) is an important tool in standard multivariate data analysis, little interest has been devoted to assessing whether the underlying relationship within a given variable set can be described by a linear PCA model or whether nonlinear PCA must be utilized. This paper addresses this deficiency by introducing a nonlinearity measure for principal component models. The measure is based on the following two principles: (i) the range of recorded process operation is divided into smaller regions; and (ii) accuracy bounds are determined for the sum of the discarded eigenvalues. If this sum is within the accuracy bounds for each region, the process is assumed to be linear and vice versa. This procedure is automated through the use of cross-validation. Finally, the paper shows the utility of the new nonlinearity measure using two simulation studies and with data from an industrial melter process.     

Theoretical analysis of RAIM in the occurrence of simultaneous two-satellite faults

Most algorithms on receiver autonomous integrity monitoring (RAIM) are under the assumption of a single-satellite fault, because there is an extremely small probability that significant simultaneous multiple-satellite faults may occur. However, after the implementation of the Galileo system in a few years, there will be more satellites in view for the user to utilise together with GPS satellites, and a combination of them will bring better performance for RAIM. On the other hand, with the help of wide area augmentation system and the use of dual-frequency operation, pseudo-range errors will be reduced greatly. Thus, tighter alert limits are required for RAIM, and formerly `small' errors should not be neglected. All of those factors make it necessary to consider simultaneous multiple-satellite faults. A detailed theoretical analysis of RAIM under the condition of two-satellite faults for both vertical and horizontal directions is presented. The characteristic/max slopes for every pair of satellites are then deduced in order to calculate the tighter vertical/horizontal protection level for RAIM     

一种抗NLOS的TDOA定位算法

本文提出了一种抗非视线传播(Non-Line-of-Sight)干扰的TDOA定位算法。该算法采用退火与遗传算法相结合的方式，在满足给定条件的空间内搜索源点坐标值。数值仿真表明，该算法具备抗NLOS干扰的能力，与传统TDOA算法相比，该算法无需知道各基站的非视线传播干扰分布，是一种实用有效的定位算法。     

Linear demosaicing inspired by the human visual system.

There is an analogy between single-chip color cameras and the human visual system in that these two systems acquire only one limited wavelength sensitivity band per spatial location. We have exploited this analogy, defining a model that characterizes a one-color per spatial position image as a coding into luminance and chrominance of the corresponding three colors per spatial position image. Luminance is defined with full spatial resolution while chrominance contains subsampled opponent colors. Moreover, luminance and chrominance follow a particular arrangement in the Fourier domain, allowing for demosaicing by spatial frequency filtering. This model shows that visual artifacts after demosaicing are due to aliasing between luminance and chrominance and could be solved using a preprocessing filter. This approach also gives new insights for the representation of single-color per spatial location images and enables formal and controllable procedures to design demosaicing algorithms that perform well compared to concurrent approaches, as demonstrated by experiments.     

Sphere packing with a geometric based compression algorithm

An efficient algorithm for the random packing of spheres can significantly save the cost of the preparation of an initial configuration often required in discrete element simulations. It is not trivial to generate such random packing at a large scale, particularly when spheres of various sizes and geometric domains of different shapes are present. Motivated by the idea of compression complemented by an efficient physical process to increase packing density, shaking, a new approach, termed compression algorithm, is proposed in this work to randomly fill any arbitrary polyhedral or cylindrical domains with spheres of various sizes. The algorithm features both simplicity and high efficiency. Tests show that it takes 181 s on a 1.4-GHz PC to complete the filling of a cylindrical domain with a total number of 26,787 spheres, achieving a packing density of 52.89%.     

Local residence time,residence revolution,and residence volume distributions in twin‐screw extruders

This work was aimed at studying the overall, partial, and local residence time distributions (RTD); overall, partial and local residence revolution distributions (RRD) and overall, partial and local residence volume distributions (RVD) in a co‐rotating twin screw extruder, on the one hand; and establishing the relationships among them, on the other hand. Emphasis was placed on the effects of the type and geometry of mixing elements (a gear block and various types of kneading elements differing in staggering angle) and process parameters on the RTD, RRD and RVD. The overall and partial RTD were directly measured in‐line during the extrusion process and the local ones were calculated by deconvolution based on a statistical theory. The local RTD allowed comparing the mixing performance of mixing elements. Also it was confirmed both experimentally and theoretically that specific throughput, defined as a ratio of throughput (Q) over screw speed (N), controlled all the above three types of residence distributions, be they local, partial or overall. The RRD and RVD do not provide more information on an extrusion process than the corresponding RTD. Rather they are different ways of representing the same phenomena. POLYM. ENG. SCI., 48:19–28, 2008. © 2007 Society of Plastics Engineers