多股流换热器传递函数系数的理论确定方法

用数值模拟方法对一四股流板翅式换热器分别施加流量、进口温度的阶跃变化,获得其出口温度动态的响应曲线;用理论方法研究了其传染函数的系数,从而得到了四股流换热器的传递函数,并对其结果进行了分析,所得的四股流板翅式换热器的传递函数系数炎其自动控制试验提供了理论依据。     

AIN基片上重掺杂硼的多晶硅膜电阻率温度特性

研究了ＡｌＮ基片上重掺杂硼的多晶硅膜电阻率温度特性。实验发现,膜电阻率随温度变化呈现出从ＮＴＣ过渡到ＰＴＣ的Ｕ型特性,转折温度ＴＭ的位置依赖工艺条件的变化。理论分析表明：晶界势垒使膜电阻率在温度变化上存在一个极小值,极小值对应的转折温度正比于晶界势垒。     

ROC Curves in Non‐Parametric Location‐Scale Regression Models

Abstract. The receiver operating characteristic (ROC) curve is a tool of extensive use to analyse the discrimination capability of a diagnostic variable in medical studies. In certain situations, the presence of a covariate related to the diagnostic variable can increase the discriminating power of the ROC curve. In this article, we model the effect of the covariate over the diagnostic variable by means of non‐parametric location‐scale regression models. We propose a new non‐parametric estimator of the conditional ROC curve and study its asymptotic properties. We also present some simulations and an illustration to a data set concerning diagnosis of diabetes.     

浅谈数学教学中的“问题解决”

浅谈数学教学中的“问题解决”张希来（南阳师专数学系，４７３０６１）“问题解决”被称为是继“现代化”和“回到基础”之后，国际数学教育界关注的热点，是数学教育改革的新潮流，目前在我国已经引起强烈反响，对此本文谈一些粗浅看法。ｌ“问题解决”的背景和意义１９...     

浅谈中国现代史教学中正面引导问题

浅谈中国现代史教学中正面引导问题张小满中国现代史距今时间较短，政治性较强，属于争论而仍未定论的问题较多，因此，在教学中对学生进行正面引导，对于学生形成正确的历史观、世界观、价值观，正确认识今天更有其重要性和现实意义．笔者在教学实践中认识到，要作到寓思...     

Improved attribute acceptance sampling plans based on maxima nomination sampling

This paper demonstrates the use of maxima nomination sampling (MNS) technique in design and evaluation of single AQL, LTPD, and EQL acceptance sampling plans for attributes. We exploit the effect of sample size and acceptance number on the performance of our proposed MNS plans using operating characteristic (OC) curve. Among other results, we show that MNS acceptance sampling plans with smaller sample size and bigger acceptance number perform better than commonly used acceptance sampling plans for attributes based on simple random sampling (SRS) technique. Indeed, MNS acceptance sampling plans result in OC curves which, compared to their SRS counterparts, are much closer to the ideal OC curve. A computer program is designed which can be used to specify the optimum MNS acceptance sampling plan and to show, visually, how the shape of the OC curve changes when parameters of the acceptance sampling plan vary. Theoretical results and numerical evaluations are given.     

Nonparametric covariate adjustment for receiver operating characteristic curves

The accuracy of a diagnostic test is typically characterized using the receiver operating characteristic (ROC) curve. Summarizing indexes such as the area under the ROC curve (AUC) are used to compare different tests as well as to measure the difference between two populations. Often additional information is available on some of the covariates which are known to influence the accuracy of such measures. The authors propose nonparametric methods for covariate adjustment of the AUC. Models with normal errors and possibly non‐normal errors are discussed and analyzed separately. Nonparametric regression is used for estimating mean and variance functions in both scenarios. In the model that relaxes the assumption of normality, the authors propose a covariate‐adjusted Mann–Whitney estimator for AUC estimation which effectively uses available data to construct working samples at any covariate value of interest and is computationally efficient for implementation. This provides a generalization of the Mann–Whitney approach for comparing two populations by taking covariate effects into account. The authors derive asymptotic properties for the AUC estimators in both settings, including asymptotic normality, optimal strong uniform convergence rates and mean squared error (MSE) consistency. The MSE of the AUC estimators was also assessed in smaller samples by simulation. Data from an agricultural study were used to illustrate the methods of analysis. The Canadian Journal of Statistics 38:27–46; 2010 © 2009 Statistical Society of Canada     

Smoothed empirical likelihood confidence intervals for the relative distribution with left‐truncated and right‐censored data

The study of differences among groups is an interesting statistical topic in many applied fields. It is very common in this context to have data that are subject to mechanisms of loss of information, such as censoring and truncation. In the setting of a two‐sample problem with data subject to left truncation and right censoring, we develop an empirical likelihood method to do inference for the relative distribution. We obtain a nonparametric generalization of Wilks' theorem and construct nonparametric pointwise confidence intervals for the relative distribution. Finally, we analyse the coverage probability and length of these confidence intervals through a simulation study and illustrate their use with a real data set on gastric cancer. The Canadian Journal of Statistics 38: 453–473; 2010 © 2010 Statistical Society of Canada     

Optimal Composite Markers for Time‐Dependent Receiver Operating Characteristic Curves with Censored Survival Data

Abstract. To increase the predictive abilities of several plasma biomarkers on the coronary artery disease (CAD)‐related vital statuses over time, our research interest mainly focuses on seeking combinations of these biomarkers with the highest time‐dependent receiver operating characteristic curves. An extended generalized linear model (EGLM) with time‐varying coefficients and an unknown bivariate link function is used to characterize the conditional distribution of time to CAD‐related death. Based on censored survival data, two non‐parametric procedures are proposed to estimate the optimal composite markers, linear predictors in the EGLM model. Estimation methods for the classification accuracies of the optimal composite markers are also proposed. In the article we establish theoretical results of the estimators and examine the corresponding finite‐sample properties through a series of simulations with different sample sizes, censoring rates and censoring mechanisms. Our optimization procedures and estimators are further shown to be useful through an application to a prospective cohort study of patients undergoing angiography.     

Assessing accuracy of a continuous screening test in the presence of verification bias

Summary.  In studies to assess the accuracy of a screening test, often definitive disease assessment is too invasive or expensive to be ascertained on all the study subjects. Although it may be more ethical or cost effective to ascertain the true disease status with a higher rate in study subjects where the screening test or additional information is suggestive of disease, estimates of accuracy can be biased in a study with such a design. This bias is known as verification bias. Verification bias correction methods that accommodate screening tests with binary or ordinal responses have been developed; however, no verification bias correction methods exist for tests with continuous results. We propose and compare imputation and reweighting bias-corrected estimators of true and false positive rates, receiver operating characteristic curves and area under the receiver operating characteristic curve for continuous tests. Distribution theory and simulation studies are used to compare the proposed estimators with respect to bias, relative efficiency and robustness to model misspecification. The bias correction estimators proposed are applied to data from a study of screening tests for neonatal hearing loss.