一般公差（未注公差）及其应用

为减化图样,阐述未注尺寸公差ＧＢ／Ｔ１８０４－９２和未注菜位公差即ＧＢ／Ｔ１１８４－１９９６的规定及应用。     

“线性尺寸一般公差”国标的分析和应用

着重分析“线性尺寸一般公差”新旧国家标准的区别,新标准的优缺点介绍,结合本单位实际,介绍一般公差的应用。     

形位公差在尺寸链计算中运用

在机械设计中,为保证零件正常装配,尺寸链计算是一个很重要的内容,在零件加工过程中,尺寸及形位误差客观存在,因此在零件的设计和装配中也必须考虑形位公差对尺寸链的影响。     

应用尺寸链解法分析尺寸公差和形位以差间的正反补偿关系

按尺寸链解法分析遵守最大实体原则要素尺寸公差与形位公差间的正反补偿关系。     

尺寸公差与摩擦系数

GB5763—1998《汽车用制动器衬片》由原国家质量技术监督局1998年8月19日批准，并于1999年2月1日实施的，是现行有效的强制性标准。     

关于正确使用对称结构标注法及其公差选择计算

扼要介绍有关对称结构尺寸公差值选择和计算以及在使用中应注意的问题。     

中国养老保险个人账户管理研究

鉴于世界各国普遍面临的严重的人口老龄化趋势,各国纷纷对其养老保险制度进行减轻国家财政压力、强调个人责任及发挥市场机制的改革趋势。本文通过对中国养老保险个人账户管理的分析比较,提出适合"统账结合"制度的养老保险基金管理模式改革建议,并对存在的现实障碍提出相关解决措施。     

多层次三维工艺模型的形位公差推理方法研究

基于模型的定义已成为机加工艺设计的研究热点,为解决三维环境下模型上制造信息的表达和形位公差主动推理的问题,本文提出了多层公差表示模型。利用加权有向图表达加工功能表面、基准、尺寸和公差。利用多色集合理论实现形位公差推理,最后用实例验证了该方法的有效性。     

高校教师个人所得税的纳税筹划

随着高校教师收入水平的不断提升,国家税务总局明确提出将高等院校作为个人所得税征管的重点。高等院校应根据高校教师收入的特点,设计合理的薪酬体系、福利制度,在合理合法的限度内尽可能降低高校教师的税收负担。本文简要阐述了高校教师收入及其薪酬体系的基本情况,在此基础上提出了高校教师个人所得税纳税筹划的途径,希望能在一定程度上降低高校教师的税收负担。     

不确定多时滞线性It随机系统的保性能控制

对一类具有多时滞的不确定线性随机系统,研究了保性能状态反馈控制律的设计问题。采用线性矩阵不等式方法和伊藤公式,导出了保性能控制律的存在条件。进而,通过设计一个线性无记忆的状态反馈控制器,使得对于所有系统容许的不确定,闭环系统是范数有界的。最后用数值例子说明了该方法的有效性。     

The Three Basic Types of Residuals for a Linear Model

We consider residuals for the linear model with a general covariance structure. In contrast to the situation where observations are independent there are several alternative definitions. We draw attention to three quite distinct types of residuals: the marginal residuals, the model‐specified residuals and the full‐conditional residuals. We adopt a very broad perspective including linear mixed models, time series and smoothers as well as models for spatial and multivariate data. We concentrate on defining these different residual types and discussing their interrelationships. The full‐conditional residuals are seen to play several important roles.     

Asymptotics for Autocovariances and Integrated Periodograms for Linear Processes Observed at Lower Frequencies

One of the most frequently used class of processes in time series analysis is the one of linear processes. For many statistical quantities, among them sample autocovariances and sample autocorrelations, central limit theorems are available in the literature. We investigate classical linear processes under a nonstandard observation pattern; namely, we assume that we are only able to observe the linear process at a lower frequency. It is shown that such observation pattern destroys the linear structure of the observations and leads to substantially different asymptotic results for standard statistical quantities. Central limit theorems are given for sample autocovariances and sample autocorrelations as well as more general integrated periodograms and ratio statistics. Moreover, for specific autoregressive processes, the possibilities to estimate the parameters of the underlying autoregression from lower frequency observations are addressed. Finally, we suggest for autoregressions of order 2 a valid bootstrap procedure. A small simulation study demonstrates the performance of the bootstrap proposal for finite sample size.     

Efficiency Gains and Cost Reductions from Individual Transferable Quotas: A Stochastic Cost Frontier for the Australian South East Fishery

In this paper efficiency gains and associated cost reductions from increases in traded quota are estimated with a stochastic cost frontier for the Australian South East Trawl Fishery (SETF). Estimation of this frontier also provides key information on the relative importance of input costs in the SETF, returns to scale, variations in costs as a result of trade in quota and the economic performance of each fishing vessel, year to year. Final estimations indicate that increases in the volume of quota traded have resulted in considerable efficiency gains and cost reductions in the SETF, ranging from 1.8 to 3.5 cents per kilogram for surveyed vessels for every 1% increase in the volume of quota traded, or 1–2.4% of total variable costs, with considerable gains also accruing to crew and skipper in the form of larger share payments. Mean vessel efficiency is relatively high in the SETF, estimated at over 90%, and increases further to 92% over the sample period with increased trades in quota.Jel Classification: Q22, Q28     

Linear Programming Models for the Measurement of Environmental Performance of Firms—Concepts and Empirical Results

I use linear programming models to define standardised, aggregate environmental performance indicators for firms. The best practice frontier obtained corresponds to decision making units showing the best environmental behaviour. Results are obtained with data from U.S. fossil fuel-fired electric utilities, starting from four alternative models, among which are three linear programming models that differ in the way they account for undesirable outputs (pollutants) and resources used as inputs. The results indicate important discrepancies in the rankings obtained by the four models. Rather than contradictory, these results are interpreted as giving different, complementary kinds of information, that should all be taken into account by public decision-makers.     

Linear mixed-effects model for longitudinal complex data with diversified characteristics

The increasing richness of data encourages a comprehensive understanding of economic and financial activities, where variables of interest may include not only scalar (point-like) indicators, but also functional (curve-like) and compositional (pie-like) ones. In many research topics, the variables are also chronologically collected across individuals, which falls into the paradigm of longitudinal analysis. The complicated nature of data, however, increases the difficulty of modeling these variables under the classic longitudinal framework. In this study, we investigate the linear mixed-effects model (LMM) for such complex data. Different types of variables are first consistently represented using the corresponding basis expansions so that the classic LMM can then be conducted on them, which generalizes the theoretical framework of LMM to complex data analysis. A number of simulation studies indicate the feasibility and effectiveness of the proposed model. We further illustrate its practical utility in a real data study on Chinese stock market and show that the proposed method can enhance the performance and interpretability of the regression for complex data with diversified characteristics.