浅谈目的论对徽文化翻译的启示

徽州以其特有的人文特色闻名于世,要将徽文化推广出去,翻译是必不可少的过程,在翻译过程中既要兼顾文化效益又要兼顾经济效益。翻译目的论注重的不是译文与原文是否对等,而是强调译文应该在分析原文基础上,以译文预期功能为目的,选择最佳的处理方法。本文旨在翻译目的论的原则指导下,从物质、精神和制度三个方面选择体现徽文化特色的概念阐述并进行翻译,从而达到双方兼顾的作用。     

两晋军府与尚书机构关系考论

两晋时期军府制度逐渐发展定型,并对以尚书制度为核心的国家政治体制产生重大影响,其表现为：在中央层面,加兵公常领录尚书事,或兼领尚书令;地方镇将常兼领尚书省长官。这样,在国家政治生活中就出现了军府制断尚书事,甚至在非常时期成为替代尚书省的“国务总汇”机构,以及军府掾属权过尚书干涉政务等等不正常的现象。这些现象的产生,在一定程度上表明了两晋时期国家政治体制的孱弱。     

深圳十年规划建设理论与实践初探

本文根据深圳十年规划与建设经验,对市场经济条件下的城市规划理论、乡镇城市化、开放型城市的交通与电讯网络、城市生态环境的保护、投资软硬环境的建设,以及如何提高城市规划的科学水平等问题作了探讨。     

六端口技术自校准方法解的不唯一性证明

本文就六端口技术自校准方法进行了分析讨论,用解析方法和计算机模拟方法分别证明了自校准方法解的不唯一性.从而否定了自校准方法是六端口技术最突出的优点之一这个传统概念.     

Modular-transform based clustering

Spectral clustering uses eigenvectors of the Laplacian of the similarity matrix. It is convenient to solve binary clustering problems. When applied to multi-way clustering, either the binary spectral clustering is recursively applied or an embedding to spectral space is done and some other methods, such as K-means clustering, are used to cluster the points. Here we propose and study a K-way clustering algorithm – spectral modular transformation, based on the fact that the graph Laplacian has an equivalent representation, which has a diagonal modular structure. The method first transforms the original similarity matrix into a new one, which is nearly disconnected and reveals a cluster structure clearly, then we apply linearized cluster assignment algorithm to split the clusters. In this way, we can find some samples for each cluster recursively using the divide and conquer method. To get the overall clustering results, we apply the cluster assignment obtained in the previous step as the initialization of multiplicative update method for spectral clustering. Examples show that our method outperforms spectral clustering using other initializations.     

Developing a variables repetitive group sampling plan based on process capability index C pk with unknown mean and variance

In this paper, variables repetitive group sampling plans are developed based on the process capability index C _pk when the quality characteristic follows a normal distribution with unknown mean and variance. The sampling plan parameters such as the sample size and the acceptance constant are determined to minimize the average sample number. Symmetric and asymmetric cases, in percent defectives due to two specification limits, are dealt with for specified combinations of acceptable quality level and limiting quality level. Tables are provided and examples are given to use proposed plans in practice.     

Statistical Properties of a Modified Accelerated Design for Phase I Cancer Clinical Trials

We consider the semiparametric profile likelihood inference for the distribution function under doubly censored data. For further developments of the statistical inference based on the profile likelihood ratio and alternative tools such as the score or Wald-type inference, we discuss the structures of the profile likelihood estimators and their derivatives included in the score function and the Fisher function of the profile likelihood, establishing the consistencies of their estimators.     

An augmented data scoring algorithm for maximum likelihood

The expectation-maximization (EM) method facilitates computation of max¬imum likelihood (ML) and maximum penalized likelihood (MPL) solutions. The procedure requires specification of unobservabie complete data which augment the measured or incomplete data. This specification defines a conditional expectation of the complete data log-likelihood function which is computed in the E-stcp. The EM algorithm is most effective when maximizing the iunction Q{0) denned in the F-stnp is easier than maximizing the likelihood function.

The Monte Carlo EM (MCEM) algorithm of Wei & Tanner (1990) was introduced for problems where computation of Q is difficult or intractable. However Monte Carlo can he computationally expensive, e.g. in signal processing applications involving large numbers of parameters. We provide another approach: a modification of thc standard EM algorithm avoiding computation of conditional expectations.     

Model Averaging for Prediction With Fragmentary Data

ABSTRACT

One main challenge for statistical prediction with data from multiple sources is that not all the associated covariate data are available for many sampled subjects. Consequently, we need new statistical methodology to handle this type of “fragmentary data” that has become more and more popular in recent years. In this article, we propose a novel method based on the frequentist model averaging that fits some candidate models using all available covariate data. The weights in model averaging are selected by delete-one cross-validation based on the data from complete cases. The optimality of the selected weights is rigorously proved under some conditions. The finite sample performance of the proposed method is confirmed by simulation studies. An example for personal income prediction based on real data from a leading e-community of wealth management in China is also presented for illustration.     

关于教育产业化若干问题的探讨

本文依据现代教育学和现代经济学的理论,论述“教育能否产业化以及如何产业化”等问题,认为教育服务是一种准公共产品,教育是一种产业,但具有不同于一般产业的特殊性;按照我国实际情况,当前只能逐步推进部分教育产业化。