A new strategy for inspecting roundness features

This article addresses the problem of inspection of roundness error (in contrast to the measurement of roundness error) and the idea of GO-NOGO inspection software. A new approach is presented in which the formalism of linear programming is applied through reexpressing the initial geometrical problem and adding further constraints. The ultimate position is to provide a set of constraints from which the required inspection information can be obtained by examining only the feasibility of the mathematical progrma, with no need to consider its iteration toward optimality. Feasibility may be explored using an existing, although not widely known, algorithm to guide the GO-NOG decision. The basis of the algorithm is given along with practical examples of how it works, Tests indicate that on real data it usually involves a computational effort only modestly higher than using an exchange algorithm to find an optimal fit. Thus, it appears quite practical for applications to the relatively small computer of a standard instrument.     

基于功率特征的抗密集多假目标干扰跟踪技术

针对密集多假目标干扰下,真假目标识别困难、跟踪精度低的问题,提出了基于功率特征的抗干扰技术。首先,对干扰条件下的雷达量测进行信号似然比预处理,剔除杂波;然后,进行角度卡方检验及同源量测融合,以充分利用虚假目标信息;最后,根据真假目标功率特征构建“分贝数冶加权因子,并结合位置信息,实现真实目标的功率/ 位置双重加权,从而大大削弱干扰信号的影响,达到抗干扰的目的。仿真实验表明,该技术能较好地适应密集多假目标干扰环境,并取得较高的跟踪精度。     

主题特征格分析:一种用户生成文本质量评估方法

本文设计了一种用户生成文本的质量分析框架.首先,基于主题分析构建商品类别主题特征集合.其次,利用主题特征与商品分类的强关联关系,构建形式化概念分析的形式背景,将分类-主题概念格化简并生成主题特征格,以此构建五个质量特征并生成质量评估模型.最后,在真实评论数据上的实验结果表明新方法具有更高预测精度.     

Entity Burst Discriminative Model for Cumulative Citation Recommendation

Knowledge base acceleration-cumulative citation recommendation (KBA-CCR) aims to detect citation-worthiness documents from a chronological stream corpus for a set of target entities in a knowledge base. Most previous works only consider a number of semantic features between documents and target entities in the knowledge base, and then use powerful machine learning approaches such as logistic regression to classify relevant documents and non-relevant documents. However, the burst activities of an entity have been proved to be a significant signal to predict potential citations. In this paper, an entity burst discriminative model (EBDM) is presented to substantially exploit such burst features. The EBDM presents a new temporal representation based on the burst features, which can capture both temporal and semantic correlations between entities and documents. Meanwhile, in contrast to the bag-of-words model, the EBDM can significantly decrease the number of non-zero entries of feature vectors. An extensive set of experiments were conducted on the TREC-KBA-2012 dataset. The results show that the EBDM outperforms the performance of the state-of-the-art models.     

基于特征信息建模技术

提出一种新的基于特征信息建模方法,该方法能在多级抽象层次上完备地描述产品信息,并提供良好的产品数据表达和数据转换机制,使CAD/CAM集成和并行设计的实现成为可能。笔者运用这种建模技术研制了板材折弯FMC运行控制软件自动生成系统,在产品信息集成与共享基础上,该系统集设计、分析、工艺规划、制造过程于一体,并具有良好的总体结构。     

支持概念设计的表面蒙面算法

提出一种针对任意多边形边界内嵌任意形状、任意多个内特征的“递归式”三维平面三角划分方法 ,该算法主要应用于产品概念设计中零件的可视化处理。在提出“有效线段”概念及相关三维平面“内外点的判定”方法的基础上 ,提出针对不同内外特征形状的一整套三角划分方法。较之一般的三角剖分算法 ,本方法着重提高了算法的简单性、通用性及处理问题的有效性 ,本文的研究成果已成功应用于“86 3”课题 :基于广义映射原理的绿色产品设计自动化软件系统中     

基于改进的SIFT特征的图像双向匹配算法

图像匹配是计算机视觉中许多领域的基础,特征提取则是图像匹配的基础,其中不变量特征是一个重要的理论。SIFT是最有效的尺度、旋转、亮度不变量局部特征之一,但算法复杂、计算时间长。分析了SIFT的计算时间分配,通过计算关键点的邻域梯度直方图时动态修改采样步长,大大提高了SIFT的计算速度。分析了基于SIFT特征的图像匹配算法,提出了双向匹配算法,提高了图像匹配的准确率。实验结果表明所提出的方法是有效的。     

基于彩色图像的运动目标分割方法

针对彩色图像Hue-saturation-intensity颜色模型各分量所携带的颜色信息不同的特点,结合区域分割算法在彩色图像中提取区域颜色特征,并将区域颜色特征作为局部阈值分割方法的阈值特征,提出一种基于图像区域颜色特征的运动目标分割方法。分割试验显示了该运动目标分割方法的有效性和可行性。提出融合梯度算子和子区合并技术进行区域分割的方法,子区合并技术能够在一定程度上防止两个独立的区域被错误的合并成一个区域, 这种区域分割方法和常用的Region growing算法的对比分割试验显示该方法对灰度变化不均匀的区域进行分割的效果优于Region growing算法。     

超密集网中一种基于人工蜂群的节能分簇算法

超密集网络中,密集部署的低功率基站将会加大系统的能耗,并且造成紧缺频谱资源的浪费.探寻干扰协调和系统节能的可行性方法在超密集网络架构下提出基站的休眠—唤醒—活跃机制,减小了休眠基站直接转为活跃状态的开启时间;另外,提出一种基于人工蜂群染色分簇算法,尽可能使用最少的颜色给拓扑图中的小区染色,并对簇内活跃基站进行优化功率分配.经仿真表明,休眠—唤醒—活跃机制能够提升系统的能源效率,染色分簇算法也可以改善用户的频谱效率和吞吐量.     

Exploring residential satisfaction in shrinking cities: a decision-tree approach

The number of cities experiencing population decline has been increasing worldwide. Despite the existence of theoretical propositions of shrinkage as an opportunity to increase levels of residential satisfaction, the issue has not been addressed empirically. This article contributes to fill this gap by assessing, through survey, the residential satisfaction of inhabitants of four shrinking Portuguese cities.

Data were analysed by means of a tree-decision approach: the Chi-squared Automatic Interaction Detection analysis. A sense of safety is the feature that best discriminates inhabitants’ level of residential satisfaction. The results show that shrinkage due to deindustrialisation processes is detrimental to residential satisfaction.