现行高校英语测试：问题与思考

目前我国有几种大型英语测试，如大学英语四、六级考试，英语专业四、八级考试，公共英语等级考试等，这些考试不可避免地存在一些共同的问题，即：考试制度不合理、信度和效度低、考试题型单一、阅卷评分有误差等。就上述问题提出了几点改革的设想。     

A combination multiple comparisons and subset selection procedure to identify treatments that are strictly inferior to the best

This paper considers the problem of identifying which treatments are strictly worse than the best treatment or treatments in a one-way layout, which has many important applications in screening trials for new product development. A procedure is proposed that selects a subset of the treatments containing only treatments that are known to be strictly worse than the best treatment or treatments. In addition, simultaneous confidence intervals are obtained which provide upper bounds on how inferior the treatments are compared with these best treatments. In this way, the new procedure shares the characteristics of both subset selection procedures and multiple comparison procedures. Some tables of critical points are provided for implementing the new procedure, and some examples of its use are given.     

通信网告警加权关联规则挖掘算法的研究

关联规则挖掘算法是通信网告警相关性分析中的重要方法。在处理数量庞大的告警数据库时,算法的效率显得至关重要,而经典的FP-growth算法会产生大量的条件模式树,加权算法MINWAL(O)则需要多次扫描数据库,使得在通信网环境下挖掘关联规则的难度非常大。该文提出了一种高效的基于加权频繁模式树的通信网告警关联规则挖掘算法,算法性能测试表明,该算法与已有的加权关联规则挖掘算法相比较,节约了大量的存储空间,提高了算法的挖掘速度,对通信网的故障诊断和故障定位有着积极的意义。     

Application of copulas to multivariate control charts

The most popular multivariate control chart for monitoring the mean of a distribution is probably the Hotelling T² rule. Unfortunately, this rule relies on the assumption that the distribution under control is Gaussian, which is rarely true in practice. The objective of this paper is to propose a new approach for the non-normal multivariate case. It consists in the construction of a tolerance region obtained from a density level set estimation. The method follows a “plug-in” approach in which the density of the observations is previously estimated. This estimation is conducted using copulas modeling, an increasingly popular tool in multivariate modeling.     

Variable Selection for Kernel Classification

In this article, a variable selection procedure, called surrogate selection, is proposed which can be applied when a support vector machine or kernel Fisher discriminant analysis is used in a binary classification problem. Surrogate selection applies the lasso after substituting the kernel discriminant scores for the binary group labels, as well as values for the input variable observations. Empirical results are reported, showing that surrogate selection performs well.     

A bound connected with 26 factorial search designs of resolution 3.1

In this paper, we give a lower bound for the number of treatments required

for a plan to be a main effect plus one plan for 2^m (m = 6) factorial experiments, The lower bound problem is important in the event of generating new designs with similar properties or when one wants to study the criteria of optimality for such designs.     

Two-stage DEA models with undesirable input-intermediate-outputs

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still lacks of more systematical investigation on two-stage DEA with undesirable variables. For instance, depending on its operating model, even whether an intermediate variable is desirable or undesirable can be questionable for a particular two-stage system. Furthermore, most of the existing studies on two-stage systems focus on the case where only the final outputs are undesirable. In this work, we try to systematically examine two-stage DEA models with undesirable input-intermediate-outputs. Particularly, we utilize the free-disposal axioms to construct the production possibility sets (PPS) and the corresponding DEA models with undesirable variables. The proposed models are then used to illustrate some theoretical perspectives by using the data of China׳s listed banks.     

Variables acceptance reliability sampling plan for repairable items

Traditionally, acceptance reliability sampling plans have been developed for non-repairable items. However, the functions required for items become more and more complex and, accordingly, the items are composed of several components and tend to be repairable. In this paper, we consider variables acceptance reliability sampling plan for repairable items. We develop a variables acceptance sampling plan based on the failure and repair data observed during the testing period. It is shown that the developed sampling plan improves the reliability characteristic of the population and that the lifetimes of items before and after the reliability sampling test are stochastically ordered.     

A multidimensional view on poverty in the European Union by partial order theory

Poverty can be seen as a multidimensional phenomenon described by a set of indicators, the poverty components. A one-dimensional measure of poverty serving as a ranking index can be obtained by combining the component indicators via aggregation techniques. Ranking indices are thought of as supporting political decisions. This paper proposes an alternative to aggregation based on simple concepts of partial order theory and illustrates the pros and cons of this approach taking as case study a multidimensional measure of poverty comprising three components – absolute poverty, relative poverty and income – computed for the European Union regions. The analysis enables one to highlight conflicts across the components with some regions detected as controversial, with, for example, low levels of relative poverty and high levels of monetary poverty. The partial order approach enables one to point to the regions with the most severe data conflicts and to the component indicators that cause these conflicts.     

跨文化视野下的学科会聚

学科的交叉和会聚需要理论的支撑.它包括三个方面的内容:(1)中心项(Central Item),学科会聚与交叉必有一个主要的领域、学科或学说,这是确定首席专家的依据;(2)关联域(Context),即构成该学科会聚的以中心项为主的相关领域,这是确定准入人员、准入项目的依据;(3)学科间性(Inter-disciplinity),这是学科交叉会聚所产生的新的质素,即新的前沿性领域、新的关节点,也是学科会聚所要探索的新知识.一个新的科研群体是否有前景、有地位,主要取决于对"学科间性"这一新的知识宝库的把握程度.学科会聚背后是人才的会聚,而人才会聚时所释放出的凝聚力或离心力都远远大于一般素质的人员,因而除了科研群体的共同信念外,上述三个理论可以说也是处理科研群体人事关系的依据.此外,还必须有共同的跨文化的视野.因为学科的分化是在希腊及近代的西方文化语境下发生的,而学科的交叉与会聚已超出单一的语境.凝聚于一个群体的学者有不同的文化背景;作为研究对象的客体,有的涉及不同文化的价值认同(例如生命科学、环境问题).特别是人文社会科学或者人文社会科学与自然科学的交叉学科,有无跨文化的视野可以说是研究成败的关键因素之一.