Single-Sequence的边界约束条件

在VLSI物理设计中,分层设计和连线优化都要求某些模块放置在布局的边界位置。该文针对一般的具有不可二划分结构的布图规划问题,在SS编码的基础上解决VLSI物理设计中有边界约束的布局布图规划的问题;证明SS的放置顺序是表示模块的数字在SS中出现的位置先后顺序;提出模块放置在四个边界(上、下、左、右边界)在SS编码中应满足的充要条件及证明;并给出模块位于四个边界在SS编码中相应的表达式和计算方法。     

视觉特性与道路绿地设计

“以人为本”成为环境设计的基本观点 ,并逐渐在园林景观设计中引起重视。笔者探讨了在道路绿地景观的规划设计中如何运用人性化设计理念 ,着重于从路者的动态视觉观赏角度 ,结合人的生理、心理特点 ,研究速度等因素对道路绿地景观尺度及形式等方面的影响 ,以提高景观设计的科学性与合理性。     

地理原则能论证“麦克马洪线”的有效性吗？——评析20世纪五六十年代印度政府对“麦克马洪线”的一个观点

“麦克马洪线”问题是中印边界争端中的重要问题。这一历史遗留问题对中印关系起到极大的破坏性作用。20世纪五六十年代，印度政府坚持所谓的地理原则能论证“麦克马洪线”的有效性。本文详细分析了所谓地理原则的内涵，并从理论和实践两个方面阐明：所谓的地理原则论不但不能论证“麦克马洪线”的有效性，而且是导致中印边界冲突和战争的直接原因。     

人才选拔过程中面试方法的应用

面试是一种古老而常新的选拔人才的方法，无论是在历史上还是在今天，面试在人才选拔过程中都有着重要的作用。面试主要特点在于其对象的单一性、内容的灵活性、信息的复合性、交流的直接性与互动性以及判断的主观性。面试的重要问题有三，一是考什么，二是怎么考，三是由谁来考。     

Tests of independence in incomplete multi-way tables using likelihood functions

Kang (2006) and Kang and Larsen (in press) used the log likelihood function with Lagrangian multipliers for estimation of cell probabilities in two-way incomplete contingency tables. This paper extends results and simulations to three-way and multi-way tables. Numerous studies cross-classify subjects by three or more categorical factors. Constraints on cell probabilities are incorporated through Lagrangian multipliers. Variances of the MLEs are derived from the matrix of second derivatives of the log likelihood with respect to cell probabilities and the Lagrange multiplier. Wald and likelihood ratio tests of independence are derived using the estimates and estimated variances. In simulation results in Kang and Larsen (in press), for data missing at random, maximum likelihood estimation (MLE) produced more efficient estimates of population proportions than either multiple imputation (MI) based on data augmentation or complete case (CC) analysis. Neither MLE nor MI, however, lead to an improvement over CC analysis with respect to power of tests for independence in two-way tables. Results are extended to multidimensional tables with arbitrary patterns of missing data when the variables are recorded on individual subjects. In three-way and higher-way tables, however, there is information relevant for judging independence in partially classified information, as long as two or more variables are jointly observed. Simulations study three-dimensional tables with three patterns of association and two levels of missing information.     

Asymptotics for a class of generalized multicast autoregressive processes

We propose a new class of generalized multicast autoregressive (GMCAR, for short, hereafter) models indexed by a multi-casting tree where each individual produces exactly the same number of offspring. This class includes standard bifurcating autoregressive processes (BAR, cf. Cowan and Staudte (1986)) and multicast autoregressive (MCAR, cf. Hwang and Choi (2009)) models as special cases. Accommodating non-Gaussian, non-negative and count data, the class includes various models such as nonlinear autoregression, conditionally heteroscedastic process and conditional exponential family. The pathwise stationarity of the GMCAR model is discussed. A law of large numbers and a central limit theorem are established which are in turn used to derive asymptotic distributions associated with martingale estimating functions.     

Tree-structured analysis of treatment effects with large observational data

Treatment effect in an observational study of relatively large scale can be described as a mixture of effects among subgroups. In particular, analysis for estimating the treatment effect at the level of an entire sample potentially involves not only differential effects across subgroups of the entire study cohort, but also differential propensities – probabilities of receiving treatment given study subjects’ pretreatment history. Such complex heterogeneity is of great research interest because the analysis of treatment effects can substantially depend on the hidden data structure for effect sizes and propensities. To uncover the unseen data structure, we propose a likelihood-based regression tree method which we call marginal tree (MT). The MT method is aimed at a simultaneous assessment of differential effects and propensity scores so that both become homogeneous within each terminal node of the resultant tree structure. We assess simulation performances of the MT method by comparing it with other existing tree methods and illustrate its use with a simulated data set, where the objective is to assess the effects of dieting behavior on its subsequent emotional distress among adolescent girls.     

美语间接陈述句中的混合时态

本文重点探讨和论述了美国英语间接陈述句中的混合时态运用问题 ,并列用笔者所阅读到的大量的权威资料阐述了多种间接陈述句中混合时态的使用情况 ,从而证明这些用法不仅是正确的 ,而且正逐步广泛地在美国英语中使用。