数控机床功能的扩展

本文主要分析了HEIDENHAIN TNC 310数控铣床系统中圆弧铣削指令及螺纹铣削指令,对螺纹铣削功能进行延伸,扩展到圆弧三轴联动,并对螺纹铣削指令格式进行了修改,从而具有圆弧三轴联动铣削功能。     

Numerical evaluation of tests based on different heteroskedasticity-consistent covariance matrix estimators

This article considers the issue of performing tests in linear heteroskedastic models when the test statistic employs a consistent variance estimator. Several different estimators are considered, namely: HC0, HC1, HC2, HC3, and their bias-adjusted versions. The numerical evaluation is performed using numerical integration methods; the Imhof algorithm is used to that end. The results show that bias-adjustment of variance estimators used to construct test statistics delivers more reliable tests when they are performed for the HC0 and HC1 estimators, but the same does not hold for the HC3 estimator. Overall, the most reliable test is the HC3-based one.     

A procedure for testing the equality of k dependent correlation coefficients

A procedure is proposed for testing the equality of k dependent correlation coefficients. The procedure is simulated utilizing Monte Carlo techniques; and, a method for post hoc probing is also suggested.     

Standard errors for EM estimation

The EM algorithm is a popular method for computing maximum likelihood estimates. One of its drawbacks is that it does not produce standard errors as a by-product. We consider obtaining standard errors by numerical differentiation. Two approaches are considered. The first differentiates the Fisher score vector to yield the Hessian of the log-likelihood. The second differentiates the EM operator and uses an identity that relates its derivative to the Hessian of the log-likelihood. The well-known SEM algorithm uses the second approach. We consider three additional algorithms: one that uses the first approach and two that use the second. We evaluate the complexity and precision of these three and the SEM in algorithm seven examples. The first is a single-parameter example used to give insight. The others are three examples in each of two areas of EM application: Poisson mixture models and the estimation of covariance from incomplete data. The examples show that there are algorithms that are much simpler and more accurate than the SEM algorithm. Hopefully their simplicity will increase the availability of standard error estimates in EM applications. It is shown that, as previously conjectured, a symmetry diagnostic can accurately estimate errors arising from numerical differentiation. Some issues related to the speed of the EM algorithm and algorithms that differentiate the EM operator are identified.     

数控加工与编程数字化教学资源建设

为培养高职数控技术专业学生的数控加工与编程能力,通过调研典型制造型企业,以其岗位能力需求为基础,以企业的实践过程为任务流程,规划了数控加工与编程课程的教学体系,并构建了基于网络化教学平台的数字化教学资源库。     

英汉数字文化习俗差异的对比分析

世界上每个民族都有自己的数字文化,由于英汉两个民族的历史和文化存在很大差异,英汉数字文化鲜明地体现了民族文化的心理、传统与特色。通过对一些有代表性的英汉数字词语的文化内涵对比分析,我们可以对英汉两个民族的文化习俗差异窥之一斑。     

海洋钻井隔水管顶张力分析

隔水管系统足海洋钻井的主要设备之-本丈对描述隔水管运动的四阶非线性偏徽分方程和边界条件进行了简化，并应用有限差分法对隔水管的受力情况进行数值分析.作用在隔水管上的顶张力，使用四种海况进行研究，并编制了相应的计算程序.通过实例计葬，与美国应力工程服务奋司的计葬结果进行比较，结果完全-致.末文提供的动态分析方法及计葬程序具有方法简便、精确度高和机时省千优点，对设计和校核隔水管系统具有实用价值.     

Nonparametric estimation of welfare changes

In this article, I propose a simple nonparametric method of estimating welfare measures with no structural assumptions on the demand system. The method is illustrated for both the single good and the multiple good case, using simulated data. Standard errors of the welfare changes are derived using standard bootstrap techniques. The compensating variation and deadweight loss resulting from a housing price increase is evaluated using Canadian mortgage data. The GAUSS coding, which is very short, is included.     

Stochastic Bounds with a Low Rank Decomposition

We investigate how we can bound a discrete time Markov chain (DTMC) by a stochastic matrix with a low rank decomposition. In the first part of the article, we show the links with previous results for matrices with a decomposition of size 1 or 2. Then we show how the complexity of the analysis for steady-state and transient distributions can be simplified when we take into account the decomposition. Finally, we show how we can obtain a monotone stochastic upper bound with a low rank decomposition.     

Two Moments of the Logitnormal Distribution

We display the first two moment functions of the Logitnormal(μ, σ²) family of distributions, conveniently described in terms of the Normal mean, μ, and the Normal signal-to-noise ratio, μ/σ, parameters that generate the family. Long neglected on account of the numerical integrations required to compute them, awareness of these moment functions should aid the sensible interpretation of logistic regression statistics and the specification of “diffuse” prior distributions in hierarchical models, which can be deceiving. We also use numerical integration to compare the correlation between bivariate Logitnormal variables with the correlation between the bivariate Normal variables from which they are transformed.