构建以人为本的英语教学模式

传统的英语教育模式忽视了学生的个性意识、个性特点和个性需要,违背了人本主义的教育教学理念。如何提高教学效率一直是外语教师主要探讨的问题。文章运用人本主义的教学理念,结合实际探讨了如何构建以人为本的新型教学模式以改进英语教学,提高教学效率。以人为本的新型教学模式包括:创立民主愉悦的课堂教学环境、构建个性化的学习空间、设计师生共同探索的教学活动、建立协作性的教学模式。     

大学计算机专业“基础原理”课的教学探讨

本文针对现代大学生学习计算机专业“基础原理”课程存在的种种客观问题,通过分析这些问题找出其中原因,并介绍对这些问题所采取的解决方案。教学实践表明,这些方案对学生学习“基础原理课”起到了较好的效果,提高了这类课程的教学质量。     

斜腿刚构桥几何布局的优化设计

采用数学规划的方法从静力和动力两方面对斜腿刚构桥的几何布局进行优化设计。静力优化设计的优化目标是截面截面应力平方均值最小，动力优化设计的优化目标是结构自振周期平方和最小。采用了直接搜索法寻优。通过算例可知，这两种优化设计方法均可行，且均为刚性设计。     

深圳证券交易所不同指数收益率的波动比较

股票价格指数的波动的大小通常代表了它的风险程度,研究股指的波动对风险管理、投资组合以及价格预测有着十分重要的意义。文章采用时间序列分析方法,对深圳证券交易所的三种价格指数建立GARCH模型,并对这三种指数的波动率进行比较。     

存储区域网络iSCSI协议的通信机制研究

介绍了存储区域网络主要采用的组网协议,包括FC协议、FCIP协议、iFCP协议和iSCSI协议,着重研究了一种利用TCP/IPI网组建存储区域网络的协议-iSCSI协议,分析了iSCSI协议的通信机制,比较了在IP网络上实现iSCSI协议通信的3种方法,开发了一种iSCSI协议数据单元与TCP数据帧间的接口算法及其硬件设计,并用 VHDL语言成功进行了行为级的仿真。     

高等院校英语强化课程的评估体系与评估模式的构建

文章选取培正商学院的一年英语强化教改项目作为研究个案,根据(背景—输入—过程—输出CIPP)评估理论,利用质性评价和量性评价相结合的手段,对强化项目的背景和过程进行了评价。并由此构建出了一个针对高职高专院校公共外语教学的、具有自我约束并持续改进的课程评估体系。     

翻译理论新标准与语言学理论

语言学的发展一直在不断地影响着翻译理论的发展,只不过有时这种影响很间接,尼达的译学思想在中国翻译界一向占据着重要的地位,但这位大师最近宣布其观点已经发生根本变化,尼达学术观点的变化无疑会给目前译学建设带来一定的负面影响。本文着重从翻译理论的作用、翻译标准及语言学与翻译的关系三个角度对尼达翻译思想的转变加以分析;重新阐述理论在译学框架中的地位及作用,理论和实践的关系及翻译理论的意义。     

电力市场理论的若干基本概念辨析

本文通过对电力市场、电价与电力交易模式等电力经济基础概念的分析,指出了现有概念体系的不足,并提出了作者的认识,尤其是对电力市场一般与市场特殊作出详尽分析,力图为构建竞争性的电力市场经济理论奠定微观概念的基础。     

Generalized additive models for location, scale and shape

Summary.  A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y , as parametric and/or additive nonparametric (smooth) functions of explanatory variables and/or random-effects terms. Maximum (penalized) likelihood estimation is used to fit the (non)parametric models. A Newton–Raphson or Fisher scoring algorithm is used to maximize the (penalized) likelihood. The additive terms in the model are fitted by using a backfitting algorithm. Censored data are easily incorporated into the framework. Five data sets from different fields of application are analysed to emphasize the generality of the GAMLSS class of models.     

Factor analysis for ranked data with application to a job selection attitude survey

Summary.  Factor analysis is a powerful tool to identify the common characteristics among a set of variables that are measured on a continuous scale. In the context of factor analysis for non-continuous-type data, most applications are restricted to item response data only. We extend the factor model to accommodate ranked data. The Monte Carlo expectation–maximization algorithm is used for parameter estimation at which the E-step is implemented via the Gibbs sampler. An analysis based on both complete and incomplete ranked data (e.g. rank the top q out of k items) is considered. Estimation of the factor scores is also discussed. The method proposed is applied to analyse a set of incomplete ranked data that were obtained from a survey that was carried out in GuangZhou, a major city in mainland China, to investigate the factors affecting people's attitude towards choosing jobs.