On transitive orientations with restricted covering graphs

We consider the problem of finding a transitive orientation of a comparability graph, such that the edge set of its covering graph contains a given subset of edges. We propose a solution which employs the classical technique of modular tree decomposition. The method leads to a polynomial time algorithm to construct such an orientation or report that it does not exist.     

一种改进的人脸图像检测与识别中的预处理方法

在局部二值化基础上采用了基于灰度比对、对称相似度测量和方差投影相结合的方法进行人脸预处理,改进了对称相似度测量的具体实现方法,并与几何归一化交叉进行。改进后的方法在保证速度的前提下增强了系统的适用范围,特别是对大角度倾斜的人脸预处理更具优势。     

Experimental approaches for the estimation of uncertainty in analysis of trace inorganic contaminants in foodstuffs by ICP-MS

Total Diet Studies to estimate dietary exposure to food contaminants need to evaluate laboratory measurements data variance. In this process it is critical that data from analytical methods are reliable to correctly scrutinize and compare values over time and between countries. In Europe it is widely recognized that the evaluation of measurement uncertainty is an important parameter when assessing the sources of analytical data variability. Two approaches are considered to estimate uncertainty in analytical measurement. Arsenic, Lead, Chromium and Cadmium, content in several food matrix determined by Inductively Coupled Mass Spectrometry (ICP-MS) microwave digestion assisted, are used as examples. The aim of the present research work is to compare both approaches accepted by Eurolab and GUM: Mathematical modeling to assess uncertainty components based on a classical model (bottom up) and an empirical method (top down), based on either experimental data obtained from a single laboratory validation data or inter-laboratory data from Proficiency Testing schemes. Relative expanded uncertainty calculated by both approaches agree when U (%) <20%. These values are concordant with RSD_R reported in collaborative studies of EN 15763 (2009), which were assumed as target uncertainty. The top down approach described is simple and easy to use when compared with the mathematical modeling approach providing considerable benefits to those who assess data produced by several laboratories.     

Measuring the global construction industry: improving the quality of data

In the context of a truly global market for construction, an international strategy is required to ensure that national and international statistical systems are able to provide accurate and valid information. In many parts of the world the collection of reliable national information on construction activity is not an easy task, and the measurement of comparable, cross-national data can be problematic. This paper considers possible strategies for the improvement of data collection systems in the context of user needs.     

基于颜色特征的图像检索技术研究

在基于内容的图像检索中,颜色作为图像的一种重要视觉信息,已得到广泛应用.相对于图像的几何特征而言,颜色具有一定的稳定性,对缩放、平移、旋转具有相当强的鲁棒性.本文从颜色检索的几个关键技术入手,对颜色模型的选择与量化、颜色直方图以及相似性度量等方面进行了详细的讨论,最后,阐述了本技术的局限性和目前存在的问题.     

Comparability problems in the analysis of multiway data

Almost all methods for the analysis of multiway data assume that the comparison of any two entries in the data array under study reflects or represents meaningful content-specific information. This is especially the case if one wants the data analysis to yield insight into the real mechanisms underlying the data. Violation of this assumption may imply data-analytic results that are of doubtful quality at best and worthless in the worst-case scenario. In the present paper, we first clarify why comparability is a key assumption in most methods for multiway data analysis. Next, we list a number of reasons why this assumption is very often violated in practice. We then review a few possible approaches that have been advanced to deal with problems of comparability, and discuss their advantages and shortcomings. We conclude by clarifying that any satisfactory solution to comparability problems requires a very careful reflection about the data collection and the ultimate goal of the data analysis.     

改进的奇异值求解算法及其在目标识别中的应用

提出一种改进的奇异值求解算法,并研究了其在图像目标识别中的应用。对该算法和对飞机类型的识别进行了实验分析,结果表明：该算法比常规的奇异值求解法在时间复杂度方面有了改进,目标识别速度得到了提高。     

基于相似性滤波的红外小目标检测

针对天空红外图像的特点,利用背景像素点和目标像素点的灰度值在空间分布上与其邻域像素灰度值之间的差异,提出相似性滤波的方法,相似性滤波的方法,算法简单,图像中的背景干扰能够被极大抑制,图像中点目标的对比度和图像的信噪比被显著提高。为减小噪声影响,一种自适应的噪声处理方法被给出,它对图像中的高斯噪声和脉冲噪声分别处理,在提高去噪效果的同时保留了图像的边缘信息。仿真结果表明提出的算法对红外点目标的背景具有极好的抑制能力。     

彩色环境下基于惯性矩的椭圆检测算法

提出了在彩色环境下检测椭圆的新算法。首先分析了椭圆的解析结构,根据物理学中惯性矩的概念,推演出一个类椭圆区域的理想椭圆,用该理想椭圆与边缘检测获得的边缘点拟合,求出一个区域的理想椭圆;然后将求得的理想椭圆与区域边缘点集合用近似度和逼近度两个指标拟合,得到与类椭圆区域最匹配的精确椭圆;最终得到类椭圆区域的边界轮廓,该轮廓可以很好地代替目标的真正边界。该算法可以快速检测完整椭圆和椭圆弧。