Monitoring the Coefficient of Variation Using the Side Sensitive Group Runs Chart

Many quality characteristics have means and standard deviations that are not independent. Instead, the standard deviations of these quality characteristics are proportional to their corresponding means. Thus, monitoring the coefficient of variation (CV), for these quality characteristics, using a control chart has gained remarkable attention in recent years. This paper presents a side sensitive group runs chart for the CV (called the SSGR CV chart). The implementation and optimization procedures of the proposed chart are presented. Two optimization procedures are developed, i.e. (i) by minimizing the average run length (ARL) when the shift size is deterministic and (ii) by minimizing the expected average run length (EARL) when the shift size is unknown. An application of the SSGR CV chart using a real dataset is also demonstrated. Additionally, the SSGR CV chart is compared with the Shewhart CV, runs rules CV, synthetic CV and exponentially weighted moving average CV charts by means of ARLs and standard deviation of the run lengths. The performance comparison is also conducted using EARLs when the shift size is unknown. In general, the SSGR CV chart surpasses the other charts under comparison, for most upward and downward CV shifts. Copyright © 2015 John Wiley & Sons, Ltd.     

Effect of magnesium sulfate on the durability of limestone mortars based on quaternary blended cements

Currently, the use of blended cements incorporating various supplementary cementing materials, preserved in aggressive environments has become common. This paper describes the investigation results conducted on the evaluation of the resistance to magnesium sulfate solution (MgSO₄) of limestone mortars containing simultaneously; limestone filler, blast furnace slag and natural pozzolan. In this study, the deterioration of limestone mortars due to sulfate attack was evaluated by measuring changes in weight, length and compressive strength at the ages of 30, 60, 90, 120 and 180 days of immersion in exposure environments. The X-ray diffraction was also used in order to determine the different mineral phases. It is noteworthy that, the pH variation of the conservation solutions has been monitored during tests. The exposure solution was renewed monthly until the end of tests. The results showed that, the resistance to sulfate attack of mortars made with quaternary binders was better than that of mortars based on ordinary Portland cement.     

电子商务下全球闭环供应链超网络模型

建立了一个由制造商、零售商、消费者与回收商构成的全球闭环供应链超网络均衡模型.回收商回收、处置废弃产品、并将生产出的新产品销售给零售商与消费者.模型中的交易方式包括传统交易与网上交易.考虑有多种交易货币,模型设定了不同货币对基础货币的增值率.首先对各层决策者的行为进行了研究,探计了它们之间的相互作用,又运用变分不等式的...     

Weighted and extended total variation for image restoration and decomposition

In various information processing tasks obtaining regularized versions of a noisy or corrupted image data is often a prerequisite for successful use of classical image analysis algorithms. Image restoration and decomposition methods need to be robust if they are to be useful in practice. In particular, this property has to be verified in engineering and scientific applications. By robustness, we mean that the performance of an algorithm should not be affected significantly by small deviations from the assumed model. In image processing, total variation (TV) is a powerful tool to increase robustness. In this paper, we define several concepts that are useful in robust restoration and robust decomposition. We propose two extended total variation models, weighted total variation (WTV) and extended total variation (ETV). We state generic approaches. The idea is to replace the TV penalty term with more general terms. The motivation is to increase the robustness of ROF (Rudin, Osher, Fatemi) model and to prevent the staircasing effect due to this method. Moreover, rewriting the non-convex sublinear regularizing terms as WTV, we provide a new approach to perform minimization via the well-known Chambolle's algorithm. The implementation is then more straightforward than the half-quadratic algorithm. The behavior of image decomposition methods is also a challenging problem, which is closely related to anisotropic diffusion. ETV leads to an anisotropic decomposition close to edges improving the robustness. It allows to respect desired geometric properties during the restoration, and to control more precisely the regularization process. We also discuss why compression algorithms can be an objective method to evaluate the image decomposition quality.     

A class of high-resolution algorithms for incompressible flows

We present a class of a high-resolution Godunov-type algorithms for solving flow problems governed by the incompressible Navier-Stokes equations. The algorithms use high-resolution finite volume methods developed in LeVeque (SIAM J Numer Anal 1996;33:627-665) for the advective terms and finite difference methods for the diffusion and the Poisson pressure equation. The high-resolution algorithm advects the cell-centered velocities using the divergence-free cell-edge velocities. The resulting cell-centered velocity is then updated by the solution of the Poisson equation. The algorithms are proven to be robust for constant-density flows at high Reynolds numbers via an example of lid-driven cavity flow. With a slight modification for the projection operator in the constant-density solvers, the algorithms also solve incompressible flows with finite-amplitude density variation. The strength of such algorithms is illustrated through problems like Rayleigh-Taylor instability and the Boussinesq equations for Rayleigh-Bénard convection. Numerical studies of the convergence and order of accuracy for the velocity field are provided. While simulations for two-dimensional regular-geometry problems are presented in this study, in principle, extension of the algorithms to three dimensions with complex geometry is feasible.     

基于梯度自适应函数的彩色图像变分去噪方法

分析了彩色图像的全变分降噪模型,该模型在降噪的同时可以保持好图像的特征信息,但对于噪声较大的图像具有明显的"阶梯效应".Blomgren的基于梯度自适应函数的去噪模型只能处理灰度图像,因此提出改进的基于彩色图像的梯度自适应函数去噪模型.实验证明,改进的模型有效地解决了"阶梯效应"的发生,提高了模型的去噪能力和边缘保持能力.     

基于压缩传感的背景差分方法研究

近年来国际上出现了一种新的信息获取理论——压缩传感理论（CS）,不同于传统的奈奎斯特采样定理,它指出只要信号具有稀疏性或可压缩性,就可以通过少量随机采样点来恢复原始信号。基于对CS理论基础的深入分析,提出一种运用背景差分进行运动目标检测的新方法,此方法可以显著减少信号采样点数和传输带宽,而且一定程度上了克服了由于如光照变化而造成的误检测,仿真结果证实了该文算法的可行性。     

基于分块思想的最小化总变差去噪新算法

现有的图像分块方法在处理前将源噪声图像分割成不同的小块,分别独立进行去噪,最后将所有小块拼接。该方法所得图像的去噪效果有一定程度的提高,但在相邻分块结合处存在不连续。对去噪方法的现状进行了分析,并结合最小化总变差及分块思想,提出新的去噪方法:在每小块处理过程中,分块值参与判断终止,整幅图像值计算去噪图像;对各块所得去噪图像取均值,得到最终的结果;对新算法进行优化,提高了算法运行效率。分析实验结果表明,该方法在计算效率和信噪比上均有显著提高。     

一种基于联合轮廓特征矢量的目标识别方法

针对基于形状特征进行目标识别的方法存在的不足,提出一种联合轮廓不变矩特征和轮廓几何特征的识别方法;针对不同的待识别目标,采集足够数量的训练样本,统计每一个轮廓特征的均值、标准差和变异系数;并据此对这些轮廓特征进行动态筛选和加权,建立起待识别目标的联合轮廓特征矢量模型.在线识别时,提取场景目标的联合轮廓特征矢量,对其进行...