《塑料成型模具设计》课程的教学实践

针对《塑料成型模具设计》课程的特点和目前的教学条件,从教学观念、教学方法、教学手段等方面进行了一系列探索与实践。     

Testing the Goodness of Fit of Parametric Regression Models with Random Toeplitz Forms

ABSTRACT: We introduce a class of Toeplitz‐band matrices for simple goodness of fit tests for parametric regression models. For a given length r of the band matrix the asymptotic optimal solution is derived. Asymptotic normality of the corresponding test statistic is established under a fixed and random design assumption as well as for linear and non‐linear models, respectively. This allows testing at any parametric assumption as well as the computation of confidence intervals for a quadratic measure of discrepancy between the parametric model and the true signal g;. Furthermore, the connection between testing the parametric goodness of fit and estimating the error variance is highlighted. As a by‐product we obtain a much simpler proof of a result of 34 ) concerning the optimality of an estimator for the variance. Our results unify and generalize recent results by 9 ) and 15 , 16 ) in several directions. Extensions to multivariate predictors and unbounded signals are discussed. A simulation study shows that a simple jacknife correction of the proposed test statistics leads to reasonable finite sample approximations.     

现代人与室内装饰艺术

从现代室内装饰设计的角度,阐述现代人审美观念逐步走向成熟的一些具体特征。强调“以人为本”的理念,诠释“内容”与“形式”的融合,反映现代人审美心理的宽松和多元化,以及呈现“前瞻”多样化设计,追求永远不变“个性化”的特点。     

Bayes model averaging with selection of regressors

Summary. When a number of distinct models contend for use in prediction, the choice of a single model can offer rather unstable predictions. In regression, stochastic search variable selection with Bayesian model averaging offers a cure for this robustness issue but at the expense of requiring very many predictors. Here we look at Bayes model averaging incorporating variable selection for prediction. This offers similar mean-square errors of prediction but with a vastly reduced predictor space. This can greatly aid the interpretation of the model. It also reduces the cost if measured variables have costs. The development here uses decision theory in the context of the multivariate general linear model. In passing, this reduced predictor space Bayes model averaging is contrasted with single-model approximations. A fast algorithm for updating regressions in the Markov chain Monte Carlo searches for posterior inference is developed, allowing many more variables than observations to be contemplated. We discuss the merits of absolute rather than proportionate shrinkage in regression, especially when there are more variables than observations. The methodology is illustrated on a set of spectroscopic data used for measuring the amounts of different sugars in an aqueous solution.     

Bounding Analysis as an Inadequately Specified Methodology

The bounding analysis methodology described by Ha-Duong et al. (this issue) is logically incomplete and invites serious misuse and misinterpretation, as their own example and interpretation illustrate. A key issue is the extent to which these problems are inherent in their methodology, and resolvable by a logically complete assessment (such as Monte Carlo or Bayesian risk assessment), as opposed to being general problems in any risk-assessment methodology. I here attempt to apportion the problems between those inherent in the proposed bounding analysis and those that are more general, such as reliance on questionable expert elicitations. I conclude that the specific methodology of Ha-Duong et al. suffers from logical gaps in the definition and construction of inputs, and hence should not be used in the form proposed. Furthermore, the labor required to do a sound bounding analysis is great enough so that one may as well skip that analysis and carry out a more logically complete probabilistic analysis, one that will better inform the consumer of the appropriate level uncertainty. If analysts insist on carrying out a bounding analysis in place of more thorough assessments, extensive analyses of sensitivity to inputs and assumptions will be essential to display uncertainties, arguably more essential than it would be in full probabilistic analyses.     

大学英语教学与双语教学的接轨

根据中国教育发展的特点不难看出:双语教学是大学英语改革发展的必然趋势。大学英语教学与双语课程的教学进行接轨,英语教学再上新台阶具有重要的意义。     

在服装三维设计和模拟中的模型设计研究

模型的设计在三维服装设计和模拟中起着十分重要的作用.提高服装设计仿真的速度、改善仿真的效果都与模型的设计方法有着十分密切的关系.文章研究了建模的一般方法,并就网格边界线三维建模的数据计算和仿真问题进行了比较深入的探讨.     

浅谈中医英语翻译中的几个问题

中医英语翻译时应该注意根据不同的语境,在既体现中医理论的精髓又充分考虑读者群的认知和接受能力的前提下,采用各种方法实现译文与原文之间的关联,达到跨文化交际的最佳效果。     

高校非计算机专业计算机教育多元化的探讨

文章以素质教育为出发点 ,对当前计算机教育中不利于学生个性发展的因素进行了较全面的分析 ,并从教学方法、课程设置体系、教学评估体系、课后学习几个方面 ,探讨了计算机教育多元化问题。     

景观设计的“四维”价值体系探讨

在景观设计学走向多元而综合的今天,设计作品要想有持久的生命力,就必须满足社会的需求,遵循生态原则,植根于当地文化,并且反映美学和艺术的新观念。只有综合平衡各要素,使景观设计作品具备美学、社会、文化和自然的“四维”价值,并使之得到最大化的满足,才能实现景观设计至上的理想追求。