Ground shaking intensity varies spatially in earthquakes, and many studies have estimated correlations of intensity from past earthquake data. This paper presents a framework for quantifying uncertainty in the estimation of correlations and true variability in correlations from earthquake to earthquake. A procedure for evaluating estimation uncertainty is proposed and used to evaluate several methods that have been used in past studies to estimate correlations. The results indicate that a weighted least squares algorithm is most effective in estimating spatial correlation models and that earthquakes with at least 100 recordings are needed to produce informative earthquake-specific estimates of spatial correlations. The proposed procedure is also used to distinguish between estimation uncertainty and the true variability in model parameters that exist in a given data set. The estimation uncertainty is seen to vary between well-recorded and poorly recorded earthquakes, whereas the true variability is more stable.

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Previous report on ergonomics experiment has verified that vision stress induced by vision task under ambient illumination can be reduced effectively by introducing AG or AGAR to LCDs. In this paper, we analyzed the contrast of LCD of surface treatment of AG, AR and AGAR under ambient illumination. By using AGAR surface treatment, the contrast can be improved to higher than 10, a necessary minimum contrast for comfort reading. We believe this as one reason of the vision stress reduction of LCD of AGAR treatment.

Facet-based Radar Cross Section (RCS) analysis codes has been come to maturity in today's highfrequency EM environment . Facetbased analysis is sometimes adequate for conventional high-signature object. But in the prediction of low-observable object , the significant RCS prediction errors-facet noise can occur when using facet models. In this paper, three kind of models are studied.