基于三角划分的多连通域图形匹配研究

由若干个多边形通过组合产生的具有多个连通域的多连通域图形识别问题是工程图纸识别与理解所要解决的重要问题。首先,通过建立包围多边形、连通多边形概念,完成对多连通域图形的表示;然后,依据最近距离、无遮挡、包含原则添加辅助线,实现三角划分,解决了包含连通的定位问题。在匹配过程中,首先通过匹配包围多边形实现多连通域图形的外轮廓定位;然后通过匹配连通多边形删除连通域,逐步收缩图形,实现图形匹配。应用此方法,解决了多连通域图形的旋转、缩放匹配问题,在汽车线束图纸识别中取得了良好的应用效果。     

基于分层思想的快速边缘匹配方法及射影重建

特征匹配在目标识别、视觉导航、运动分析等立体视觉领域中具有重要的作用.提出了一种基于分层思想的快速边缘匹配方法.主要采取两点匹配策略保证其快速性:一是把分层匹配思想用于边缘匹配中;二是在点的匹配过程中提出了边缘约束.具体包括3步:首先,在第一层匹配每条边缘上梯度变化最大的点,由于数量少,因此匹配速度快且正确率达到100%;然后,在第二层采取区域扩张的方法,从已匹配的少数种子点出发向外扩张搜索,得到所有匹配的边缘;最后,提出边缘约束的方法匹配边缘上的点,将候选匹配点仅限制在几个像素,大大减少了搜索范围且提高了匹配正确率.大量实际景象的匹配结果表明,结合分层思想和边缘约束极大提高了匹配速度,边缘点的匹配正确率高达98%.实验结果给出了立体边缘匹配效果图和三维射影重构图.     

一种基于特征参数匹配的工程图形矢量化方法

本文针对工程图形矢量化的特点和目前一般光栅图形矢量化存在的问题，提出了一种基于特征参数匹配的科形矢量化方法。     

基于域映射模式的信息化平台匹配理论

从企业信息化应用角度出发,应用域映射理论和方法对管理系统与信息系统关系进行分析,在深入研究企业建模和信息系统开发建模的基础上,提出管理域和信息域的互映射机制、过程和方式,进而提出信息化平台匹配理论,并对映射一致性的测度方法进行研究,以此作为信息化产品选型过程的理论和方法论指导.     

一种基于极线约束的激光条纹匹配算法

本文介绍一种基于极线约束的激光条纹匹配算法。先通过双CCD摄像机摄取两幅图像 ,然后对图像进行预处理。处理之后的两幅图像是在不同视角下摄取的两条单像素宽的激光条纹 ,在极线约束和连续性约束的理论基础上 ,提出了一种直线和曲线求交的匹配方法 ,从而实现了激光条纹的快速精确匹配和激光扫描线的三维重建。     

基于泽尼克矩耦合颜色空间加权度量的商标检索算法

目的 针对商标检索系统中利用单一特征进行识别和度量时,往往难以充分表征商标特征,易出现检索精度和鲁棒性不高等问题,文中拟设计一种泽尼克（Zernike）矩耦合颜色空间加权度量的商标检索方案。方法 首先,利用Zernike矩作为商标的形状描述符,充分描述商标的形状信息。随后,利用颜色空间来描述图像中像素空间信息的颜色分布特征。然后,分别将输入商标的Zernike矩特征、颜色空间特征与存储在数据库中的特征进行匹配,以计算Zernike矩特征的加权Euclidean距离与颜色空间度量。最后,联合颜色空间度量与Euclidean距离,综合考虑形状与颜色特征,形成新的距离测量规则,输出与查询商标相似的商标。结果 实验数据表明,与当前商标检索算法相比较,所提算法具有更高的检索准确率与鲁棒性,表现出更为理想的Precision-Recall以及平均准确率（Mean Average Precision, MAP）。结论 所提算法返回的图像与查询图像相似度较高,在商标注册、侵权保护等方面中具有一定的参考价值。     

基于光谱角匹配和加权自相关约束能量最小化 算法的水面目标探测方法

为实现对高光谱图像海面舰艇目标进行有效探测,通过对传统的目标探测算法进行改进,解决了加权自相关约束能量最小化算法(Constrained Energy Minimization, CEM)对于大目标地物提取效果不佳的问题.对高光谱图像做降维和端元提取处理,并利用提取的端元进行光谱角匹配(Spectral Angle Mapping, SAM)分类来确定两个重要的分类:舰船类和海水类;从所有像元中减去舰船类像元作为背景像元,通过基于纯背景像元加权自相关矩阵的SAM-CEM算法计算探测结果;通过分类图像来获得只包含海水和舰船的灰度图像,并进行二值化和数学形态学处理,寻找范围最大的白色区域为海水区域;通过对目标探测图像进行二值化,利用舰船目标在海水中的特点,去除不在海水区域内的虚警目标,从而确定最终的舰船目标.实验结果表明:该算法能够更好地增强目标信号而抑制背景信号,从而避免了加权自相关CEM算法中目标信号作为背景信号参与运算而对探测结果的影响,在对海面舰艇的目标探测中取得了令人满意的结果.     

A universal measure of the conformity of a mesh with respect to an anisotropic metric field

In this paper, a method is presented to measure the non‐conformity of a mesh with respect to a size specification map given in the form of a Riemannian metric. The measure evaluates the difference between the metric tensor of a simplex of the mesh and the metric tensor specified on the size specification map. This measure is universal because it is a unique, dimensionless number which characterizes either a single simplex of a mesh or a whole mesh, both in size and in shape, be it isotropic or anisotropic, coarse or fine, in a small or a big domain, in two or three dimensions. This measure is important because it can compare any two meshes in order to determine unequivocally which of them is better. Analytical and numerical examples illustrate the behaviour of this measure. Copyright © 2004 John Wiley & Sons, Ltd.     

Measuring the conformity of non‐simplicial elements to an anisotropic metric field

This paper extends an approach for measuring the element conformity of simplices to non‐simplicial elements of any type, in spaces of arbitrary dimension. Element non‐conformity is defined as the difference between a given size specification map, in the form of a Riemannian metric tensor, and the actual metric tensor of the element. An approach to the measurement of non‐conformity coefficients of non‐simplicial elements based on sub‐simplex division is proposed. An analysis of the measure's behaviour presented for quadrilaterals, hexahedra, prisms and pyramids shows that the measure is sensitive to size, stretching and orientation variations, as well as to other types of element shape degeneration. Finally, numerical applications show that the metric conformity measure can be used as a quality measure to quantify the discrepancy between a whole non‐simplicial mesh and a complex anisotropic size specification map. Copyright © 2005 John Wiley & Sons, Ltd.     

基于EMD和AR模型的滚动轴承故障诊断方法

提出了基于EMD(Empirical Mode Decomposition)和AR模型的滚动轴承故障诊断方法。该方法用EMD将滚动轴承振动信号分解成若干个平稳的IMF(Intrinsic Mode Function)分量，对每一个IMF分量建立AR模型，以模型的自回归参数和残差的方差作为特征向量建立Mahalanobis距离判别函数，进而判断滚动轴承的工作状态和故障类型。实验结果分析表明，该方法能有效地应用于滚动轴承的故障诊断。     

A Semiparametric Mixed Model Approach to Phase I Profile Monitoring

Profile monitoring is an approach in quality control best used where the process data follow a profile (or curve). The majority of previous studies in profile monitoring focused on the parametric (P) modeling of either linear or nonlinear profiles, with both fixed and random effects, under the assumption of correct model specification. More recently, in the absence of an obvious P model, nonparametric (NP) methods have been employed in the profile monitoring context. For situations where a P model is adequate over part of the data but inadequate of other parts, we propose a semiparametric procedure that combines both P and NP profile fits. We refer to our semiparametric procedure as mixed model robust profile monitoring (MMRPM). These three methods (P, NP and MMRPM) can account for the autocorrelation within profiles and treat the collection of profiles as a random sample from a common population. For each approach, we propose a version of Hotelling's T² statistic for use in Phase I analysis to determine unusual profiles based on the estimated random effects and obtain the corresponding control limits. Simulation results show that our MMRPM method performs well in making decisions regarding outlying profiles when compared to methods based on a misspecified P model or based on NP regression. In addition, however, the MMRPM method is robust to model misspecification because it also performs well when compared to a correctly specified P model. The proposed chart is able to detect changes in Phase I data and has easily calculated control limits. We apply all three methods to the automobile engine data of Amiri et al.⁵ and find that the NP and the MMRPM methods indicate signals that did not occur in a P approach. Copyright © 2012 John Wiley & Sons, Ltd.     

A Benders decomposition approach to the weighted number of tardy jobs scheduling problem on unrelated parallel machines with production costs

This paper addresses the problem of scheduling on-time jobs on unrelated parallel machines with machine production costs. The objective is to maximise the net profit which is the sum of the weights of on-time jobs and the cost of using the machines. This scheduling problem is very important and frequent in industrial settings. It is herein solved using an exact approach that applies Benders decomposition to obtain tight upper and lower bounds and uses the bounds within a branch and bound. The computational investigation shows the efficacy of the approach in solving large instances. Most importantly, the proposed approach provides a new venue for solving large-scale scheduling problems.     

应用试验模态参数修正理论模型的最佳矩阵逼近法

本文从特征方程和模态正交条件出发，给出了一种应用模态参数识别结果修正理论模型的最佳矩阵逼近方法。该方法通过对识别出的模态矩阵进行奇异值分解并结合特征方程和模态正交条件导出了修正理论模型的通解表达式。在此基础上，给出了最佳逼近解的定义，研究了最佳逼近解的存在性和唯一性，给出了最佳修正质量矩阵和刚度矩阵的具体表达式，讨论了保证修正后的质量矩阵和刚度矩阵仍具有带状性质的方法．数值计算表明，本文方法具有较高的修正精度，对于大误差模型也有较好的修正能力。     

基于生态位理论的员工竞争力评判模型构建

以生态学中的生态位理论为基础,建立企业员工三维生态位评价指标体系。以 AHP层次分析法确定指标权重,利用模糊综合评价法构建企业员工竞争力模糊评判模型,为企业管理者提供了一种新的员工竞争力的测评方法。通过案例研究,收集数据,对A公司员工竞争力状况进行模糊评判,评判结果为“优”,验证了该模型的可行性和科学性。     

A Constraint Mapping Approach to the Structural Optimization of an Expensive Model using Surrogates

The use of response surface methods are well established in the global optimization of expensive functions, the response surface acting as a surrogate to the expensive function objective.In structural design however, the change in objective may vary little between the two models: it is more often the constraints that change with models of varying fidelity. Here approaches are described whereby the coarse model constraints are mapped so that the mapped constraints more faithfully approximate the fine model constraints. The shape optimization of a simple structure demonstrates the approach.     

A Unified Approach to Sparse Tweedie Modeling of Multisource Insurance Claim Data

Abstract

Actuarial practitioners now have access to multiple sources of insurance data corresponding to various situations: multiple business lines, umbrella coverage, multiple hazards, and so on. Despite the wide use and simple nature of single-target approaches, modeling these types of data may benefit from an approach performing variable selection jointly across the sources. We propose a unified algorithm to perform sparse learning of such fused insurance data under the Tweedie (compound Poisson) model. By integrating ideas from multitask sparse learning and sparse Tweedie modeling, our algorithm produces flexible regularization that balances predictor sparsity and between-sources sparsity. When applied to simulated and real data, our approach clearly outperforms single-target modeling in both prediction and selection accuracy, notably when the sources do not have exactly the same set of predictors. An efficient implementation of the proposed algorithm is provided in our R package MStweedie, which is available at https://github.com/fontaine618/MStweedie. Supplementary materials for this article are available online.     

A continuous damage fracture model to predict formability of sheet metal

A continuous damage fracture model, which consists of a fracture criterion and a continuum damage constitutive law was proposed in this paper to calculate formability of sheet metal. In this model, an extension of the McClintock void growth model was selected as the fracture criterion to be incorporated with a coupled damage‐plasticity Gurson‐type constitutive law. Also, by introducing a Lode angle dependent parameter to define the loading asymmetry condition, the shear effect was phenomenologically taken into account. The proposed fracture model was implemented in user defined material subroutines in ABAQUS. The model was calibrated and correlated by the uniaxial tension, shear and notched specimens tests. Application of the fracture criterion for the Limit dome height tests was discussed and the simulation results were compared with the experimental data.