Illumination invariant extraction for face recognition using neighboring wavelet coefficients

The features of a face can change drastically as the illumination changes. In contrast to pose position and expression, illumination changes present a much greater challenge to face recognition. In this paper, we propose a novel wavelet based approach that considers the correlation of neighboring wavelet coefficients to extract an illumination invariant. This invariant represents the key facial structure needed for face recognition. Our method has better edge preserving ability in low frequency illumination fields and better useful information saving ability in high frequency fields using wavelet based NeighShrink denoise techniques. This method proposes different process approaches for training images and testing images since these images always have different illuminations. More importantly, by having different processes, a simple processing algorithm with low time complexity can be applied to the testing image. This leads to an easy application to real face recognition systems. Experimental results on Yale face database B and CMU PIE Face Database show that excellent recognition rates can be achieved by the proposed method.     

Generalized Adjusted Rand Indices for cluster ensembles

In this paper, Adjusted Rand Index (ARI) is generalized to two new measures based on matrix comparison: (i) Adjusted Rand Index between a similarity matrix and a cluster partition (ARImp), to evaluate the consistency of a set of clustering solutions with their corresponding consensus matrix in a cluster ensemble, and (ii) Adjusted Rand Index between similarity matrices (ARImm), to evaluate the consistency between two similarity matrices. Desirable properties of ARI are preserved in the two new measures, and new properties are discussed. These properties include: (i) detection of uncorrelatedness; (ii) computation of ARImp/ARImm in a distributed environment; and (iii) characterization of the degree of uncertainty of a consensus matrix. All of these properties are investigated from both the perspectives of theoretical analysis and experimental validation. We have also performed a number of experiments to show the usefulness and effectiveness of the two proposed measures in practical applications.     

模糊综合评价法在供水管网安全评价中的应用

针对供水管网的安全隐患及特点,将模糊理论与综合评价方法相结合,通过MATLAB7.7的GUI界面,建立了可视化、直观性的安全模糊综合评价系统.进而以北方某市区域供水管网的安全评价为例,结合实际数据,建立了行之有效的3个层次、7个评价指标的评价体系,计算了该区域供水管网的安全等级.     

小波变换提取电力电容器局部放电信号研究

为了消除电力电容器局部放电信号的噪声,提高电力电容器局部放电信号在线检测的有效性,提出基于小波变换阈值消噪方法的电力电容器局部放电信号提取方法。选择合适的小波基函数和分解层数对信号进行小波分解,确定合适的阈值规则以及阈值估计方法对小波分解系数进行阈值量化处理,从而得到消噪后的局部放电信号。以均方根误差RMSE和信噪比RSN为衡量指标,分析了小波基函数、分解层数、阈值规则和阈值估计方法等对消噪效果的影响。结果表明,当选择db2小波作为最优小波基函数,分解层数定为6层时,利用最大最小准则阈值估计法估计的阈值在软阈值规则下能有效提取电力电容器局部放电信号,达到了最优去噪效果。     

论刑事诉讼非法证据范围的界定

新《刑事诉讼法》首次在法律层面确立了我国的非法证据排除规则。研究整个非法证据排除规则,首先需要厘清的是"非法证据"的范围问题。通过考察非法证据排除规则的发源地美国对于"非法证据"范围的界定得知,规则的目的决定规则的适用范围。制约侦查权之滥用及保障被追诉人的合法权利,是我国确立非法证据排除规则的目的和根本价值取向。     

高有机物污染原水深度处理工艺选择和运行优化

P市地表原水受到有机物污染,水中CODMn经常高达10mg/L以上,为此,在G水厂的扩建工程中,采用了两级臭氧—生物活性炭深度处理工艺,以保证出水水质安全。水厂运行结果表明,在活性炭吸附饱和后,一级炭池出水CODMn仍有3～5mg/L,需二级臭氧—生物活性炭处理才能使出厂水CODMn小于3mg/L。当前后臭氧分级投加比例为3∶2时,有机物的去除率最高。