工程制图课程体系和教学方法改革的思路与实践

在阐述工程制图课程重要和特殊地位的基础上 ,概括指出了目前我国工程制图课程改革的三种教学模式 ,并列举了国外部分院校课程改革的实例 ,总结出教改共识。在明确课程改革基本思想的前提下 ,具体提出课程改革的总体思路和实践过程 :整合课程内容 ,形成新的课程体系 ,构建基础平台 ;改革教学手段 ,更新教学方法 ,保证教学质量 ,提高教学效率     

ADDITIVE MODELS WITH PREDICTORS SUBJECT TO MEASUREMENT ERROR

This paper develops a likelihood‐based method for fitting additive models in the presence of measurement error. It formulates the additive model using the linear mixed model representation of penalized splines. In the presence of a structural measurement error model, the resulting likelihood involves intractable integrals, and a Monte Carlo expectation maximization strategy is developed for obtaining estimates. The method's performance is illustrated with a simulation study.     

《读书人是幸福人》说课设计

说课,是检验教师教学基本功的手段之一,它不同于一般的发言稿和课堂教学,它要求说者比较系统地介绍自己的教学设计及其理论依据(包括大纲依据、课程标准依据、教学法依据、教育学和心理学依据等),而不是宣讲教案,也不是浓缩课堂。它的核心在于说理,在于说清为什么要这样教,用什么理论来支持教学,说课的重点在于教学重点和教学难点的突破上。说案不同于教案。     

An empirical likelihood goodness-of-fit test for time series

Summary. Standard goodness-of-fit tests for a parametric regression model against a series of nonparametric alternatives are based on residuals arising from a fitted model. When a parametric regression model is compared with a nonparametric model, goodness-of-fit testing can be naturally approached by evaluating the likelihood of the parametric model within a nonparametric framework. We employ the empirical likelihood for an α -mixing process to formulate a test statistic that measures the goodness of fit of a parametric regression model. The technique is based on a comparison with kernel smoothing estimators. The empirical likelihood formulation of the test has two attractive features. One is its automatic consideration of the variation that is associated with the nonparametric fit due to empirical likelihood's ability to Studentize internally. The other is that the asymptotic distribution of the test statistic is free of unknown parameters, avoiding plug-in estimation. We apply the test to a discretized diffusion model which has recently been considered in financial market analysis.     

Analytical approximations for iterated bootstrap confidence intervals

Standard algorithms for the construction of iterated bootstrap confidence intervals are computationally very demanding, requiring nested levels of bootstrap resampling. We propose an alternative approach to constructing double bootstrap confidence intervals that involves replacing the inner level of resampling by an analytical approximation. This approximation is based on saddlepoint methods and a tail probability approximation of DiCiccio and Martin (1991). Our technique significantly reduces the computational expense of iterated bootstrap calculations. A formal algorithm for the construction of our approximate iterated bootstrap confidence intervals is presented, and some crucial practical issues arising in its implementation are discussed. Our procedure is illustrated in the case of constructing confidence intervals for ratios of means using both real and simulated data. We repeat an experiment of Schenker (1985) involving the construction of bootstrap confidence intervals for a variance and demonstrate that our technique makes feasible the construction of accurate bootstrap confidence intervals in that context. Finally, we investigate the use of our technique in a more complex setting, that of constructing confidence intervals for a correlation coefficient.     

Improved Monte Carlo inference for models with additive error

Some statistical models defined in terms of a generating stochastic mechanism have intractable distribution theory, which renders parameter estimation difficult. However, a Monte Carlo estimate of the log-likelihood surface for such a model can be obtained via computation of nonparametric density estimates from simulated realizations of the model. Unfortunately, the bias inherent in density estimation can cause bias in the resulting log-likelihood estimate that alters the location of its maximizer. In this paper a methodology for radically reducing this bias is developed for models with an additive error component. An illustrative example involving a stochastic model of molecular fragmentation and measurement is given.     

CO_2增加与未来气温变化

近几十年来．由于人类活动导致大气中ＣＯ２含量呈明显上升趋势，预计到下世纪中叶ＣＯ２浓度将达到４５０ｐｐｍ左右，下世纪末，将达到工业革命前的两倍，各种数值模式表明，届时全球气温将升高１．５－４．５℃。     

最优验血方法的判定

本文对Ｎ个人验血的检验方法进行研究．得到如下结果：（１）设普查对象的阳性概率为ｐ，对当时，采用分组检验最优；当ｐ≥０．３０７８时，采用单个检验最优、（２）当采用分组检验时，分组人数或时，检验次数最少．     

关联理论视角下的隐喻翻译研究——以《抗击新冠肺炎疫情的中国行动》英译为例

借助Pragglejaz团队的“隐喻识别程序”对《抗击新冠肺炎疫情的中国行动》白皮书中的隐喻进行分类描述,从认知关联视角切入对各类隐喻翻译进行案例分析。为实现白皮书类外宣文本国际传播的最佳社会效益,最大语境效果、共同的语境假设以及交际传播的目的是译者在实现隐喻跨语际转换时的重要考量准则。     

治疗腰痛的气功功法和功理

本文扼要论述腰痛治疗三个层次的气功功法和功理.