Two types of limit cycles of a resonant converter modelled by a three-dimensional system

In this paper, the long-run dynamics of a resonant converter is studied. The modelling of the resonant converter can be done using various approximations and the long-run dynamics of the two dimensional cases were earlier analysed. In this paper, we discuss results that can be extended to the three dimensional case. It seems that limit cycles describe the long-run dynamics in important situations in the three dimensional case, too. Our objective is to relate the limit cycles found previously in the two-dimensional case to those found now in the three dimensional approximation.     

Heterogeneous catalysis by new bead‐shaped polymer‐supported multisite phase transfer catalysts

Three different new insoluble bead‐shaped polymer‐supported multisite phase transfer catalysts containing two, four and six active sites have been prepared and characterized by FTIR, TGA, [chloride ion] and SEM analyses. The presence of number of active sites in each catalyst and their corresponding catalytic ability were studied by determining pseudo‐first order rate constants for C‐alkylation of phenylacetonitrile (PAN) and four different substituted PAN as the substrate using a low concentration of NaOH (25% w/w) at 50 °C. The observed rate constants were compared with rate constants of same reactions catalyzed by single‐site catalyst under identical reaction conditions. From comparative study, the efficiency of catalysts were found to be in the order six‐site>four‐site>two‐site>single‐site thus confirming number of active sites in each catalyst. Further, the detailed kinetic profile of C‐alkylation of PAN has been investigated using the superior six‐site catalyst by varying stirring speed, [substrate], [catalyst], [NaOH], and temperature. Based on the observed kinetic and activation parameters, an interfacial mechanism was proposed. © 2008 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 47: 771–785, 2009     

基于集成最小二乘支持向量机方法的近红外光谱分析

针对近红外（Near Infrared,NIR）光谱测量中的小样本问题。本文提出了一种集成最小二乘支持向量机（Ensemble Least Squares Support Vector Machine,ELS-SVM）新算法。首先使用随机子空间算法（Random Subspace Method,RSM）原始高维变量空间划分为若干个低维度的子空间,然后分别在各个子空间建立最小二乘支持向量机（LS-SVM）模型,最后构造一个集成结果来进行预测。针对一批柴油样本的实验结果表明,本法对柴油十六烷值的预测精度优于传统的LS-SVM方法。     

Inexact inverse subspace iteration for generalized eigenvalue problems

n this paper, we present an inexact inverse subspace iteration method for computing a few eigenpairs of the generalized eigenvalue problem Ax=λBx. We first formulate a version of inexact inverse subspace iteration in which the approximation from one step is used as an initial approximation for the next step. We then analyze the convergence property, which relates the accuracy in the inner iteration to the convergence rate of the outer iteration. In particular, the linear convergence property of the inverse subspace iteration is preserved. Numerical examples are given to demonstrate the theoretical results.     

带约束条件和多余参数的线性模型的比较

对于带约束条件和多余参数的两个线性模型ｅ１＝Ｌ（Ｘ１β＋Ｚ１γ，Ｖ１，Ｌ１）和ｄ２＝Ｌ（Ｘ２β＋Ｚ２δ，Ｖ２，Ｌ２），其中Ｖ１和Ｖ２是已知对称的正定矩阵，γ和δ是多余参数，Ｌ１和Ｌ２是已知的约束矩阵，文中给出了一种新的比较准则，并得到了几个充要条件。     

Optimal expansion of subspaces for eigenvector approximations

We consider the problem of how to expand a given subspace for approximating an eigenvalue and eigenvector of a matrix A. Specifically, we consider which vector in the subspace, after multiplied by A, provides optimal expansion of the existing subspace for the eigenvalue problem. We determine the optimal vector, when the quality of subspace for approximation is measured by the angle between the subspace and the eigenvector. We have also derived some characterization of the angle that might lead to more practically useful choice of the expansion vector.     

Incorporating the learning effect into data envelopment analysis to measure MSW recycling performance

The effect of organizational learning, which results in continuous improvement of organizational performance over time, has been widely discussed. The cumulative learning effect may form as a source of intellectual capital. Thus far, the static data envelopment analysis (DEA) model has not been used to examine the longitudinal learning effect. Therefore, a two-stage approach is developed together with the estimation of a latent learning effect using time-series data; the estimated learning effect is then used as an input in the DEA Slacks-Based Measure (SBM) model. The proposed DEA SBM model can be used to investigate the efficiency of the organizational learning effect of Municipal Solid Waste (MSW) recycling systems.