通用的软件产品线领域与应用特征模型演化同步框架

软件产品线领域特征模型和应用特征模型都会发生独立的演化,在产品线的整体演化过程中必须使其始终保持一致,然而,分别为基于不同描述方式的特征模型创建同步设施往往费时、容易出错。因此,提出一个通用的软件产品线领域与应用特征模型的演化同步框架,该框架提供一套统一的特征模型元模型描述方式,并且基于该元模型提出了演化同步规则。 不同的软件产品线开发组织使用该框架时仅需定义特定的特征描述与通用描述方式之间的转换。最后,通过一个实例对框架的可用性进行了验证。     

A new approach for improved identification of measurement bias

This work presents a technique that can completely and accurately identify measurement bias in cases where it is not possible to use the method of Rollins and Davis (1992, 1993) and where the method of Narasimhan and Mah (1987) fail to perform accurately. This technique makes use of information contained in the relationship between individual measurements and the corresponding nodal imbalance. The performance of this method is demonstrated on a problem from the literature that has been difficult for other methods to handle. In addition, this article discusses how the new technique can be used as a visual monitoring tool for identifying biased measured variables.     

Testing Gaussianity and Linearity For Random Fields in the Frequency Domain

We consider tests of Gaussianity and linearity for random fields on Z ^d , where Z is the set of integers and d ≥ 1. As in the time series case, the idea is to test the constancy (zero or otherwise) of the modulus of the k th-order normalized spectrum ( k > 2). We derive the asymptotic normality of the real part, the imaginary part and the modulus of the estimated normalized k th-order spectrum at fixed frequencies. This leads to the formation of likelihood-ratio tests. The test statistics are simple and intuitively plausible, and their asymptotic distributions are given in terms of deviations from Gaussianity and linearity.     

基于稀疏模型的人脸姿态估计

针对现有的人脸姿态估计方法易受"自遮挡"影响,采用改进的ASM算法提取人脸特征点,并利用人脸形态的几何统计知识来估计人脸特征点的深度值。以人脸主要特征点建立人脸稀疏模型,在利用相关人脸特征点近似估计人脸姿态后,通过最小二乘法精确估计三维人脸空间姿态。实验结果表明,对于"自遮挡"情况,该方法仍有较好的估计结果,与同类方法比较具有良好的姿态估计精度。     

一种新的岭估计解法及精度评定

在多元线性回归模型中,经典最小二乘解称为最优线性无偏估计解,系数矩阵的复共线性导致最小二乘参数解变得极不稳定.针对测量系统中的病态问题求解,结合岭估计和主成分估计的优势,推导出一种新的岭估计解法,验证了该方法的可行性.利用均方误差极小化,得出不同岭参数的求解公式及新估计的精度评定方法.通过算例证明了在均方误差有意义下,...     

Shape from focus based on 3D structure tensor using optical microscopy

Shape from focus (SFF) is a widely used passive optical method for 3D shape reconstruction. In SFF, a focus measure, which is used to estimate the relative focus level, plays a critical role in depth estimation. In this article, we present a new focus measure for accurate 3D shape estimation in optical microscopy based on the analysis of 3D structure tensor. First, the 3D tensors are computed from the input image sequence for each pixel. Then, each tensor is decomposed into point, curve, and surface tensors by decomposing tensors into eigenvalues and eigenvectors. Finally, the surfaceness is used to measure the quality of sharpness. The proposed focus measure provides accurate focus values and better resistance against noise. The proposed measure is evaluated by conducting experiments using image sequences of simulated and microscopic real objects. The comparative analysis demonstrates the effectiveness of the proposed focus measure in recovering 3D shape.     

基于DRGAN和支持向量机的合成孔径雷达图像目标识别

为解决SAR图像目标识别中样本缺乏和方位角敏感问题,提出了一种基于DRGAN和SVM的SAR图像目标识别算法。首先,采用多尺度分形特征对SAR图像进行增强,经过分割得到目标二值图像,基于Hu二阶矩估计目标的方位角。然后对估计得到的目标方位角进行量化编码,结合原始图像作为输入,对设计的DRGAN模型参数进行训练与优化。由于DRGAN中的深度生成模型将目标姿态与外观表示进行解耦设计,故可利用该模型将SAR图像样本变换到同一方位角区间。基于变换后的训练样本分别提取归一化灰度特征,利用SVM训练分类器。采用MSTAR数据集在多个不同操作条件下对提出的算法进行测试,实验结果表明,在带变体的标准操作条件下,能够达到97.97%的分类精度,优于部分基于CNN模型的分类精度,在4种扩展操作条件下的分类精度分别为97.83%,91.77%,97.11%和97.04%,均优于传统方法的分类精度。在SAR图像目标方位角估计存在一定误差的情况下,训练得到的GAN模型作为SAR图像目标旋转估计器,能够使得在不进行复杂样本预处理的前提下,仍然取得较高的SAR图像目标识别精度。     

供水管网状态估计研究进展

系统地总结了供水管网状态估计的研究内容，包括参数估计、校核评估、数据（样本）设计。20年来国内外学者根据优化和统计分析理论并结合现场试验，提出了系统的理论分析和数值方法，近年来管网不确定分析理论被引入到管网校核评估和管网率定的样本数据设计中。此外还介绍了国外供水管网状态估计的精度标准。指出虽然相关理论研究有了较大进展，但应用研究相当薄弱，大型管网模型成功率定的实例还鲜有报道，今后应加强实用研究。     

软件工程在电梯控制系统中的实现方法

将软件工程的方法应用到电梯控制系统中．使电梯控制系统具备可观察性．可控制性和可测试性，从而提高电梯控制系统的稳定性和可靠性。     

无损检测中关于结构混凝土强度推定(统计)方法的探讨

文章通过不同的抽样统计(推定)方法在混凝土强度无损检测中的工程应用,以及对不同推定方法的比较,分析了产生不同检测结果的原因,以供读者参考。