浅析ACE（获取竞争优势）与精益生产

ACE（获得竞争优势）使用简单和可视的方法来改进过程,将精益思想运用到精益生产之上。本文仅对ACE应用于精益生产的过程做了简单的评述与研究．致力于将联合技术公司内部应用的ACE的成功之处发扬光大,为广大的生产型企业能够简单明确的改进生产流程,在当前的市场环境下获得更多的竞争优势。     

Identifying Nonlinear Relationships in Regression using the ACE Algorithm

This paper introduces an alternating conditional expectation (ACE) algorithm: a non-parametric approach for estimating the transformations that lead to the maximal multiple correlation of a response and a set of independent variables in regression and correlation analysis. These transformations can give the data analyst insight into the relationships between these variables so that this can be best described and non-linear relationships uncovered. Using the Bayesian information criterion (BIC), we show how to find the best closed-form approximations for the optimal ACE transformations. By means of ACE and BIC, the model fit can be considerably improved compared with the conventional linear model as demonstrated in the two simulated and two real datasets in this paper.     

Event history modeling of world fertility survey data∗

Event history analysis seems ideally suited for the analysis of World Fertility Survey, WFS, data, which consists of full birth histories and related information, but it has not been much used for this purpose. This may be because event history analysis has practical drawbacks for WFS data, namely partial dates, computational burden, the need to take account of five clocks at once and the difficulty of interpreting coefficients.

We propose a modeling strategy for the event history analysis of WFS data which overcomes these problems, and we apply it to the previously unanalyzed WFS data from Iran. This yields estimates of the time of onset of fertility decline and the extent to which it was due to compositional changes in the population. It also enables us to determine whether it was a period effect, a cohort effect, or both. These results would have been hard to obtain using other approaches. In addition, the usefulness of ACE as an exploratory tool for determining the best coding of independent variables is illustrated.     

核心能力困境、组织僵化与动态核心能力的构建--基于知识管理的视角

培育动态核心能力是解决企业所面临的核心能力困境与组织僵化两大难题的关键。在分析知识、能力与资产的关系基础上提出 ACE 范式,可将核心能力解构为新资产引入能力、软性资产培育能力和能力系统自我更新能力三个部分。从知识管理的视角可给出构建动态核心能力的具体路径,即建立多层级的知识转化系统以及基于知识创新的核心能力更新系统。     

Adverse Childhood Experiences and Substance Use History among Vulnerable Older Adults Living in Public Housing

ABSTRACT

Previous research shows strong correlations between adverse childhood experiences (ACE) and later life health. The current study examines the relationship between ACEs and substance use among older adults living in public housing. Results show that about one-third of participants had four or more ACEs, and ACE score predicted likelihood of substance use history. Over half of older adults with four or more ACEs experienced substance abuse in their lifetime compared to one out of ten older adults with less than four ACEs. Findings shed light on a vulnerable group and point to next steps in research and practice.     

Modeling IS Planning Benefits Using ACE

This paper addresses the dearth of research on the determinants of IS planning benefits. Data were collected using a questionnaire survey of top IS executives from 450 companies in Singapore. Of the 103 responses (representing a response rate of 23%), 65 companies undertook IS planning. To test the hypothesis that the determinant-benefit relationships are likely to be nonlinear, the Alternating Conditional Expectations (ACE) algorithm was used. This appears to be the first use of ACE in IS planning research. IS sophistication, communications culture, technology forecasting, top management support, and firm size were found to be nonlinearly related to IS planning benefits (e.g., improved competitiveness, operations, and resource management). For example, IS sophistication affects improved competitiveness positively, and improved resource management negatively. It seems that IS sophistication is directed more at improving competitiveness, even though this may result in less efficient resource management due to bureaucratic procedures. However, at higher levels of IS sophistication, competitiveness stagnates and may even decrease, possibly due to bureaucratic bottlenecks. Implications of our results are discussed.     

Variance reduction for quantile estimates in simulations via nonlinear controls

Linear controls are a well known simple technique for achieving variance reduction in computer simulation. Unfortunately the effectiveness of a linear control depends upon the correlation between the statistic of interest and the control, which is often low. Since statistics often have a nonlinear relation-ship with the potential control variables, nonlinear controls offer a means for improvement over linear controls. This paper focuses on the use of nonlinear controls for reducing the variance of quantile estimates in simulation. It is shown that one can substantially reduce the analytic effort required to develop a nonlinear control from a quantile estimator by using a strictly monotone transformation to create the nonlinear control. It is also shown that as one increases the sample size for the quantile estimator, the asymptotic multivariate normal distribution of the quantile of interest and the control reduces the effectiveness of the nonlinear control to that of the linear control. However, the data has to be sectioned to obtain an estimate of the variance of the controlled quantile estimate. Graphical methods are suggested for selecting the section size that maximizes the effectiveness of the nonlinear control     

ACE基因多态性与2型糖尿病的关联研究

目的探讨血管紧张素转化酶(ACE)基因I/D多态性在湖北汉族2型糖尿病发生发展中的作用。方法采用同胞对和随机病例-对照两种实验设计。征集湖北地区汉族49个同胞对及163例随机病例-对照,测定身高、体重、血压、空腹血糖等生理生化指标,应用聚合酶链反应(PCR)方法测定基因型。结果两种实验设计中对照组与病例组的基因型和基因频率均无显著差异。结论ACE基因在湖北汉族人群2型糖尿病的发生发展中可能不起主要作用。     

利用VB实现Windows 2000安全信息的设置

介绍Windows2000系统的对象的安全描述符的格式,并以VB开发工具为例,利用API函数实现window2000中对象的安全信息的自动设置的基本原理和方法.     

Variance Reduction Using Nonlinear Controls and Transformations

Nonlinear regression-adjusted control variables are investigated for improving variance reduction in statistical and system simulations. To this end, simple control variables are piecewise sectioned and then transformed using linear and nonlinear transformations. Optimal parameters of these transformations are selected using linear or nonlinear least-squares regression algorithms. As an example, piecewise power-transformed variables are used in the estimation of the mean for the twovariable Anderson-Darling goodness-of-fit statistic W ₂ ². Substantial variance reduction over straightforward controls is obtained. These parametric transformations are compared against optimal, additive nonparametric transformations obtained by using the ACE algorithm and are shown, in comparison to the results from ACE, to be nearly optimal.