系统科学在大型技术装备项目中的应用

本文论述了系统科学的理论和方法在大型技术装备项目管理中的应用和发展,着重介绍了项目规划的方案优选和项目管理组织体系、计划控制系统,质量控制系统、项目管理信息系统。从这个项目管理系统的总体看,随着加工的进展,系统内信息不断扩大和加深,形成生产管理信息回路,而且采用人-机结合的信息网络,为配合项目管理发挥了重要作用。     

Inclusion of persons with disabilities in mainstream employment: is it really all about the money? A case study of four large companies in Norway and Sweden

This study investigates how large companies respond to public policy measures to ensure the inclusion of persons with disabilities in mainstream employment based on a case study of four companies in Norway and Sweden. The qualitative interviews, which were conducted with company managers, government representatives in Norway, and non-governmental organisations in Sweden, revealed three overarching themes: (1) ‘legitimacy’, (2) ‘financial interests’ and (3) ‘non-financial support’. The results indicate a more proactive response from the Swedish companies, especially regarding persons with intellectual and learning difficulties. The Norwegian companies reveal a high commitment to their own employees. These findings cannot be explained solely using neo-institutional theory, which holds that organisations demonstrate ‘conformity with powerful institutional myths to strengthen support and secure survival'. The results indicate that inclusive targeted corporate policies and programmes, advisory support, and the agency and value choices of the management might matter more.     

Inferences on functions of Pareto parameters with application to income inequality measures

The Theil, Pietra, Éltetö and Frigyes measures of income inequality associated with the Pareto distribution function are expressed in terms of parameters defining the Pareto distribution. Inference procedures based on the generalized variable method, the large sample method, and the Bayesian method for testing of, and constructing confidence interval for, these measures are discussed. The results of Monte Carlo study are used to compare the performance of the suggested inference procedures from a population characterized by a Pareto distribution.     

Hypothesis Testing in a Rayleigh Diffusion Model

Applying the large and moderate deviations for the log-likelihood ratio of the Rayleigh diffusion model, we give the negative regions in testing Rayleigh diffusion model and obtain the decay rates of the error probabilities.     

Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets

We develop an econometric methodology to infer the path of risk premia from a large unbalanced panel of individual stock returns. We estimate the time‐varying risk premia implied by conditional linear asset pricing models where the conditioning includes both instruments common to all assets and asset‐specific instruments. The estimator uses simple weighted two‐pass cross‐sectional regressions, and we show its consistency and asymptotic normality under increasing cross‐sectional and time series dimensions. We address consistent estimation of the asymptotic variance by hard thresholding, and testing for asset pricing restrictions induced by the no‐arbitrage assumption. We derive the restrictions given by a continuum of assets in a multi‐period economy under an approximate factor structure robust to asset repackaging. The empirical analysis on returns for about ten thousand U.S. stocks from July 1964 to December 2009 shows that risk premia are large and volatile in crisis periods. They exhibit large positive and negative strays from time‐invariant estimates, follow the macroeconomic cycles, and do not match risk premia estimates on standard sets of portfolios. The asset pricing restrictions are rejected for a conditional four‐factor model capturing market, size, value, and momentum effects.     

In-Sample Inference and Forecasting in Misspecified Factor Models

This article considers in-sample prediction and out-of-sample forecasting in regressions with many exogenous predictors. We consider four dimension-reduction devices: principal components, ridge, Landweber Fridman, and partial least squares. We derive rates of convergence for two representative models: an ill-posed model and an approximate factor model. The theory is developed for a large cross-section and a large time-series. As all these methods depend on a tuning parameter to be selected, we also propose data-driven selection methods based on cross-validation and establish their optimality. Monte Carlo simulations and an empirical application to forecasting inflation and output growth in the U.S. show that data-reduction methods outperform conventional methods in several relevant settings, and might effectively guard against instabilities in predictors’ forecasting ability.     

Validation of Nonparametric Two-sample Bootstrap in ROC Analysis on Large Datasets

The nonparametric two-sample bootstrap is applied to computing uncertainties of measures in receiver operating characteristic (ROC) analysis on large datasets in areas such as biometrics, speaker recognition, etc. when the analytical method cannot be used. Its validation was studied by computing the standard errors of the area under ROC curve using the well-established analytical Mann–Whitney statistic method and also using the bootstrap. The analytical result is unique. The bootstrap results are expressed as a probability distribution due to its stochastic nature. The comparisons were carried out using relative errors and hypothesis testing. These match very well. This validation provides a sound foundation for such computations.     

大面阵CCD航测相机图像去黑斑的处理

在大面阵数字航测相机的使用过程中,存在影像光照不均匀的问题.由于硬件设计很难达到预想的效果,在光照过于强烈的情况下,还会产生CCD过饱和的现象,通过增加遮光片可以解决这一问题,但全色波段的影像会产生黑斑.而通过马斯克匀光的方法去除中心的黑斑,提高影像的质量.并且将图像中心的反差增大,加大对比度,增大图像灰度的动态范围.