严寒地区高速铁路混凝土基床聚氨酯保温特性试验研究

基于严寒区京沈客专朝阳试验段路基基床的温度监测资料分析,研究不同厚度聚氨酯保温板对高速铁路路基混凝土基床温度变化特性影响.测试结果表明:①铺设聚氨酯保温板能够有效阻断严寒区环境与路基基床间的热量传递,保温效果与板厚相关;②地温大多数时间呈阳高阴低现象,同时阴、阳坡路基温差波动幅度随埋深逐渐减小;③基床表层阴、阳面各测点的温度变化起始时间一致,而阴面的冻结时间比阳面晚一个月.由此表明,保温板能够有效降低环境与混凝土道床之间的热交换,但是对路基阴、阳坡的影响存在差异.建议在严寒地区高速铁路路基阳、阴坡可以采取不同厚度的聚氨酯保温板,减小阴阳坡地温差异,保持季冻土路基温度变化稳定.     

基于动态冲击试验的通勤类飞机座椅符合性验证技术

国产某型民用通勤类飞机为了取得欧洲航空安全局(EASA)型号合格证,机上座椅需进行设计更改并补充进行应急着陆情况下的动态要求符合性验证.通过对适航条款及相应标准的解读,研究了基于动态试验的航空座椅动态要求适航验证技术,其主要包括座椅动态性能基本要求、试验构型及工况筛选、试验规划、合格判据和试验结果分析等内容.结果表明,该型机旅客座椅满足适航规章对座椅的动态性能要求.该项旅客座椅动态性能试验的成功为型号取得EASA型号合格证奠定了良好的基础,该型飞机也即将成为第一个取得欧洲型号合格证的国产飞机.     

Density estimation in the uniform deconvolution model

We consider the problem of estimating a probability density function based on data that are corrupted by noise from a uniform distribution. The (nonparametric) maximum likelihood estimator for the corresponding distribution function is well defined. For the density function this is not the case. We study two nonparametric estimators for this density. The first is a type of kernel density estimate based on the empirical distribution function of the observable data. The second is a kernel density estimate based on the MLE of the distribution function of the unobservable (uncorrupted) data.     

铁路运输客货管理机制的探讨

随着我国加入WTO和铁路全面参与运输市场竞争,必须尽快构建适应市场需求的铁路客货管理的动力机制和运作机制,以激发企业和员工搞好营销的内在活力,同时要构建铁路客运和货运的服务质量评价指标,以及相应的质量监督和考核管理办法,做到各项管理活而不乱、管而不死,使铁路客货运输服务质量不断提高,以满足不断增长的经济和社会发展需要。     

新财务清算政策下提高铁路城际列车效益的思考

近年来,铁路短途城际客运得到了很大的发展,开行城际列车已成为铁路运输企业新的经济增长点。新财务清算政策实施后,开行城际列车的效益受到一定程度的影响,针对存在的问题,就如何提高其效益水平进行了讨论。提出了完善开行结构、增加营业收入、减少客运付费、降低成本支出等建议措施。     

控制费用为“取最大”形式的可控排序问题

本文讨论了一类新的加工时间可控的单机排序问题,其目标函数为正则函数与最大不满意程度函数之和,不满意函数刻划了对工件实际加工时间偏离其额定加工时间不满意的程度,本文对这类问题提出了几个多项式算法。     

Asymptotically optimal estimation of smooth functionals for interval censoring, part 1

Estimation in the interval censoring model is considered. A class of smooth functionals is introduced, of which the mean is an example. The asymptotic information lower bound for such functionals can be represented as an inner product of two functions. In case 1, i.e. one observation time per unobservable event time, both functions can be given explicitly. We mainly consider case 2, with two observation times for each unobservable event time, in the situation that the observation times can not become arbitrarily close to each other. For case 2, one of the functions in the inner product can only be given implicitly as solution to a Fredholm integral equation. We study properties of this solution and, in a sequel to this paper, prove that the nonparametric maximum likelihood estimator of the functional asymptotically reaches the information lower bound.     

Likelihood-based specification analysis of continuous-time models of the short-term interest rate

An extensive collection of continuous-time models of the short-term interest rate is evaluated over data sets that have appeared previously in the literature. The analysis, which uses the simulated maximum likelihood procedure proposed by Durham and Gallant (2002), provides new insights regarding several previously unresolved questions. For single factor models, I find that the volatility, not the drift, is the critical component in model specification. Allowing for additional flexibility beyond a constant term in the drift provides negligible benefit. While constant drift would appear to imply that the short rate is nonstationary, in fact, stationarity is volatility-induced. The simple constant elasticity of volatility model fits weekly observations of the three-month Treasury bill rate remarkably well but is easily rejected when compared with more flexible volatility specifications over daily data. The methodology of Durham and Gallant can also be used to estimate stochastic volatility models. While adding the latent volatility component provides a large improvement in the likelihood for the physical process, it does little to improve bond-pricing performance.     

Robustness issues in multilevel regression analysis

A multilevel problem concerns a population with a hierarchical structure. A sample from such a population can be described as a multistage sample. First, a sample of higher level units is drawn (e.g. schools or organizations), and next a sample of the sub‐units from the available units (e.g. pupils in schools or employees in organizations). In such samples, the individual observations are in general not completely independent. Multilevel analysis software accounts for this dependence and in recent years these programs have been widely accepted. Two problems that occur in the practice of multilevel modeling will be discussed. The first problem is the choice of the sample sizes at the different levels. What are sufficient sample sizes for accurate estimation? The second problem is the normality assumption of the level‐2 error distribution. When one wants to conduct tests of significance, the errors need to be normally distributed. What happens when this is not the case? In this paper, simulation studies are used to answer both questions. With respect to the first question, the results show that a small sample size at level two (meaning a sample of 50 or less) leads to biased estimates of the second‐level standard errors. The answer to the second question is that only the standard errors for the random effects at the second level are highly inaccurate if the distributional assumptions concerning the level‐2 errors are not fulfilled. Robust standard errors turn out to be more reliable than the asymptotic standard errors based on maximum likelihood.     

改进模糊综合评价模型在供应商选择中的应用

本文在分析现有的供应商评价方法的基础上，提出一种基于改进的模糊综合评价模型，使得评价的结果更为客观、科学，而且计算较为简便，为供应商的选择提供了一种全新的思路。最后用一个简单的案例进行了分析和讨论。