制造业项目结构分解过程模型研究

针对项目分解中工作分解结构方法的不足,以制造业项目为例,考虑项目产品本身的构造及特点的基础上,综合项目产品的工艺装配过程、产品数据管理技术以及项目组织结构,构建了项目结构分解的过程模型,并对该模型进行了详细分析,应用该模型能够更加科学、合理地进行项目分解,确定项目范围。     

Production efficiency in Indian agriculture: An assessment of the post green revolution years

In this paper we use the nonparametric method of Data Envelopment Analysis (DEA) to obtain Pareto-Koopmans measures of technical efficiency of individual states over the years 1970–71 through 2000–01 in a multi-output, multi-input model of agricultural production. We disaggregate overall efficiency into two distinct components representing output and input efficiencies and identify the contribution of individual outputs and inputs to the measured level of overall efficiency. Because introduction of modern inputs has been a major component of the process of modernization of Indian agriculture, we examine to what extent different states succeeded in utilizing the modern inputs compared to the traditional inputs. Variations in the DEA efficiency scores across states and over years is explained in terms of differences in various institutional and demographic factors in a second stage regression analysis.     

Longitudinal Analysis of Inhibitors of Manufacturer Delivery Performance

This article examines demand, manufacturing, and supply factors proposed to inhibit manufacturer delivery execution. Extant research proposes many factors expected to harm delivery performance. Prior cross‐sectional empirical research examines such factors at the plant level, generally finding factors arising from dynamic complexity to be significant, but factors arising from detail complexity to be insignificant. Little empirical research examines the factors using product‐level operating data, which arguably makes more sense for analyzing how supply chain complexity factors inhibit delivery. For purposes of research triangulation, we use longitudinal product‐level data from MRP systems to examine whether the factors inhibit internal manufacturing on time job rates and three customer‐oriented measures of delivery performance: product line item fill rates, average delivery lead times, and average tardiness. Our econometric models pool product line item data across division plants and within distinct product families, using a proprietary monthly dataset on over 100 product line items from the environmental controls manufacturing division of a Fortune 100 conglomerate. The data summarize customer ordering events of over 900 customers and supply chain activities of over 80 suppliers. The study contributes academically by finding significant detail complexity inhibitors of delivery that prior studies found insignificant. The findings demonstrate the need for empirical research using data disaggregated below the plant‐level unit of analysis, as they illustrate how some factors previously found insignificant indeed are significant when considered at the product‐level unit of analysis. Managers can use the findings to understand better which drivers and inhibitors of delivery performance are important.     

利用数控增益放大器提高A/D转换器的分辨率

文章介绍利用数控增益放大器LH0086大幅度提高A／D转换器分辨率的方法,可将8位A／D转换器的分辨率提高到接近16位A／D的水平,适用于高速数据系采集系统,给出了相应的硬件原理图和软件框图。     

基于Bayes后验概率的自变量与异常点的同时识别

本文基于自变量与异常点识别隐变量的联合Bayes后验概率,给出了自变量与异常点同时识别的一般方法,且利用Gibbs抽样降低了Bayes后验概率的计算复杂度。其次,针对多值序次数据模型自变量与异常点的同时识别展开详细讨论,给出了同时识别的具体过程。最后通过模拟算例展示了本文方法的有效性。     

三阶段DEA模型管理无效率估计注记

由于能够同时调整外部环境与随机误差等因素对效率计算的影响,由Fried et al.(2002)提出的三阶段DEA模型得到了广泛应用。但在对其中的管理无效率进行估计时,国内一些学者误用了Jondrow et al. (1982)的公式。本文给出了适用公式,并进一步给出了使用李双杰等(2007)提出的统一分布假设的三阶段DEA模型管理无效率的估计公式。     

非平衡数据集的改进SMOTE再抽样算法

非平衡数据集的不均衡学习特点通常表现为负类的分类效果不理想。改进SMOTE再抽样算法,将过抽样和欠抽样方式有机结合,有针对性地选择近邻并采用不同策略合成样本。实验表明,分类器在经此算法处理后的非平衡数据集的正负两类上,均可获得较理想的分类效果。     

Bayesian Estimation and Model Choice in Item Response Models

Item response models are essential tools for analyzing results from many educational and psychological tests. Such models are used to quantify the probability of correct response as a function of unobserved examinee ability and other parameters explaining the difficulty and the discriminatory power of the questions in the test. Some of these models also incorporate a threshold parameter for the probability of the correct response to account for the effect of guessing the correct answer in multiple choice type tests. In this article we consider fitting of such models using the Gibbs sampler. A data augmentation method to analyze a normal-ogive model incorporating a threshold guessing parameter is introduced and compared with a Metropolis-Hastings sampling method. The proposed method is an order of magnitude more efficient than the existing method. Another objective of this paper is to develop Bayesian model choice techniques for model discrimination. A predictive approach based on a variant of the Bayes factor is used and compared with another decision theoretic method which minimizes an expected loss function on the predictive space. A classical model choice technique based on a modified likelihood ratio test statistic is shown as one component of the second criterion. As a consequence the Bayesian methods proposed in this paper are contrasted with the classical approach based on the likelihood ratio test. Several examples are given to illustrate the methods.     

Improved approaches to interval estimation of effective doses for a logistic dose-response curve

Asymptotic confidence (delta) intervals and intervals based upon the use of Fieller's theorem are alternative methods for constructing intervals for the <$>gamma<$>% effective doses (ED<$>_gamma<$>). Sitter and Wu (1993) provided a comparison of the two approaches for the ED<$>_{50}<$>, for the case in which a logistic dose response curve is assumed. They showed that the Fieller intervals are generally superior. In this paper, we introduce two new families of intervals, both of which include the delta and Fieller intervals as special cases. In addition we consider interval estimation of the ED<$>_{90}<$> as well as the ED<$>_{50}<$>. We provide a comparison of the various methods for the problem of constructing a confidence interval for the ED<$>_gamma<$>.     

Coverage probabilities of nonparametric simultaneous confidence bands for a survival function

Simultaneous confidence bands provide a useful adjunct to the popular Kaplan–Meier product limit estimator for a survival function, particularly when results are displayed graphically. They allow an assessment of the magnitude of sampling errors and provide a graphical view of a formal goodness-of-fit test. In this paper we evaluate a modified version of Nair's (1981) simultaneous confidence bands. The modification is based on a logistic transformation of the Kaplan–Meier estimator. We show that the modified bands have some important practical advantages.