PATTERN RECOGNITION VIA ROBUST SMOOTHING WITH APPLICATION TO LASER DATA

Nowadays airborne laser scanning is used in many territorial studies, providing point data which may contain strong discontinuities. Motivated by the need to interpolate such data and preserve their edges, this paper considers robust nonparametric smoothers. These estimators, when implemented with bounded loss functions, have suitable jump‐preserving properties. Iterative algorithms are developed here, and are equivalent to nonlinear M‐smoothers, but have the advantage of resembling the linear Kernel regression. The selection of their coefficients is carried out by combining cross‐validation and robust‐tuning techniques. Two real case studies and a simulation experiment confirm the validity of the method; in particular, the performance in building recognition is excellent.     

The variability of rainfall acidity

Two years of rainfall acidity data for the eastern United States were analyzed. The data consist of rainfall-event pH measurements from a nine station monitoring network. A spatio-temporal stochastic model, including deterministic components for seasonal variation and rainfall washout, and stochastic components for spatial, temporal, and measurement variation, was fitted to the data. The fitted autocorrelation structure from this model was used, in the process known as Kriging, to obtain BLUE contour maps of seasonal and rainfall adjusted yearly average pH over the monitoring region.     

Rank-order tests for the parallelism of several regression surfaces

For testing the hypothesis that several (s?2) linear regression surfaces X_ki=α_k+β_kc_ki+Z_ki (k=1,…,s) are parallel to one another, i.e., β₁=?=β_s, a class of rank-order tests are considered. The tests are shown to be asymptotically distribution-free, and their asymptotic efficiency relative to the general likelihood ratio test is derived. Asymptotic optimality in the sense of Wald is also discussed.     

一种新的内插算法的研究

有效的插值算法是现代医学三维成像中的一个焦点。针对ＣＴ断层图像的特点，文中提出了一种新的分区域位置映射插值算法，阐明了算法的基本思路及实施步骤，最后给出实验结果。     

Estimation and Confidence Regions for Parameter Sets in Econometric Models1

This paper develops a framework for performing estimation and inference in econometric models with partial identification, focusing particularly on models characterized by moment inequalities and equalities. Applications of this framework include the analysis of game‐theoretic models, revealed preference restrictions, regressions with missing and corrupted data, auction models, structural quantile regressions, and asset pricing models. Specifically, we provide estimators and confidence regions for the set of minimizers Θ_I of an econometric criterion function Q(θ). In applications, the criterion function embodies testable restrictions on economic models. A parameter value θthat describes an economic model satisfies these restrictions if Q(θ) attains its minimum at this value. Interest therefore focuses on the set of minimizers, called the identified set. We use the inversion of the sample analog, Q_n(θ), of the population criterion, Q(θ), to construct estimators and confidence regions for the identified set, and develop consistency, rates of convergence, and inference results for these estimators and regions. To derive these results, we develop methods for analyzing the asymptotic properties of sample criterion functions under set identification.     

Examination and visualisation of the simplifying assumption for vine copulas in three dimensions

Vine copulas are a highly flexible class of dependence models, which are based on the decomposition of the density into bivariate building blocks. For applications one usually makes the simplifying assumption that copulas of conditional distributions are independent of the variables on which they are conditioned. However this assumption has been criticised for being too restrictive. We examine both simplified and non‐simplified vine copulas in three dimensions and investigate conceptual differences. We show and compare contour surfaces of three‐dimensional vine copula models, which prove to be much more informative than the contour lines of the bivariate marginals. Our investigation shows that non‐simplified vine copulas can exhibit arbitrarily irregular shapes, whereas simplified vine copulas appear to be smooth extrapolations of their bivariate margins to three dimensions. In addition to a variety of constructed examples, we also investigate a three‐dimensional subset of the well‐known uranium data set and visually detect the fact that a non‐simplified vine copula is necessary to capture its complex dependence structure.     

Methods for Uncertainty Analysis: A Comparative Survey

This paper presents a survey and comparative evaluation of methods which have been developed for the determination of uncertainties in accident consequences and probabilities, for use in probabilistic risk assessment. The methods considered are: analytic techniques, Monte Carlo simulation, response surface approaches, differential sensitivity techniques, and evaluation of classical statistical confidence bounds. It is concluded that only the response surface and differential sensitivity approaches are sufficiently general and flexible for use as overall methods of uncertainty analysis in probabilistic risk assessment. The other methods considered, however, are very useful in particular problems.     

汉语连读变调的研究

目前对汉语第三声调自主音段的分析成为争端:是把音段作为单位还是声调丛处理,Yip(1989)认为作为单位处理更好,并引例说明曲折调作为单位扩展,同时解释了曲折调有从左至右,从右至左扩展的边缘效虚.然而,Chan(1991)对比两种语言,在分析的基础上指出:扩展既可从调根层又可从调终端层发生.Yip表明曲折调是底层单位.Chan声称平调才是底层调,平调的组合派生出曲折调,因此这一课题还需进一步研究.     

3D object recognition: Representation and matching

Three-dimensional object recognition entails a number of fundamental problems in computer vision: representation of a 3D object, identification of the object from its image, estimation of its position and orientation, and registration of multiple views of the object for automatic model construction. This paper surveys three of those topics, namely representation, matching, and pose estimation. It also presents an overview of the free-form surface matching problem, and describes COSMOS, our framework for representing and recognizing free-form objects. The COSMOS system recognizes arbitrarily curved 3D rigid objects from a single view using dense surface data. We present both the theoretical aspects and the experimental results of a prototype recognition system based on COSMOS.     

基于场所理论的春熙路商业步行街设计分析

罗格·特兰西克的场所理论认为,构成场所实体形态的三个主要要素是空间形态、建筑立面以及 街道铺装和家具,这些要素如果都能在建筑中得到正确体现,将会营造出良好的场所精神。改造后的春熙路商业 步行街虽然取得了一定经济效益,但在营造独特的场所精神方面却是失败的。