Visitor-artwork network analysis using object detection with image-retrieval technique

Recent museum exhibitions are becoming a means by which to satisfy visitor demands. In order to provide visitor-centric exhibitions, artwork must be analyzed based on the behavior of visitors, and not merely according to museum professionals' points of view. This study aims to analyze the relationship between museum visitors and artwork via a network analysis based on visitor behavior using object detection techniques. Cameras installed in a museum recorded visitors, and an object detector with a content-based image-retrieval technique tracked visitors from the videos. The durations spent with different artworks were measured, and the data was converted into a bipartite graph. The relationships between different artwork types were analyzed with a visitor-centered artwork network. Based on the visitors’ behavior, significant artworks were identified and the artwork network was compared to the arrangement of the museum. The tendency of edges in the artwork network was also examined considering visitors' preferences for artworks. The method used here makes it possible to collect quantitative data, with the results possibly used as a basis and for reference when analyzing artwork in a visitor-centered approach.     

基于模型缩聚的θ指标损伤识别方法

为实现大型三维空间结构的损伤检测,提出了一种基于模型缩聚技术的检测方法。该方法利用有限数量的加速度传感器,得到大型三维桁架结构的自振频率和模态振型,以完成损伤的识别。数值仿真结果表明：该方法在损伤的定位识别和定量识别上能达到预期的适用性和可靠性。     

Robust lane recognition for structured road based on monocular vision

A robust lane detection and tracking system based on monocular vision is presented in this paper.First,the lane detection algorithm can transform raw images into top view images by inverse perspective mapping(IPM),and detect both inner sides of the lane accurately from the top view images.Then the system will turn to lane tracking procedures to extract the lane according to the information of last frame.If it fails to track the lane,lane detection will be triggered again until the true lane is found.In this system,θ-oriented Hough transform is applied to extract candidate lane markers,and a geometrical analysis of the lane candidates is proposed to remove the outliers.Additionally,vanishing point and region of interest(ROI)dynamically planning are used to enhance the accuracy and efficiency.The system was tested under various road conditions,and the result turned out to be robust and reliable.     

某建筑物火灾后主体结构检测鉴定与处理

通过对某二层住宅楼火灾后主体结构的检测鉴定与处理,分析火灾对建筑物的影响,探讨火灾后建筑结构的检测鉴定方法,提出火灾后建筑结构的处理方法,为同类建筑结构的火灾后检测鉴定及处理提供参考.     

视觉检测系统中亮度不均匀背景的一种去除方法

刀具形状视觉检测系统中，照明不均匀对测量结果影响很大。针对这种情况，提出了基于二维二阶多项式拟合并去除不均匀背景的方法。遵循最小均方程差原理，给出了二维二阶拟合的矩阵表达式。在编制的程序中，拟合点以人机交互形式由鼠标点击选出，程序自动记录所选点的图象人材与亮度值信息，然后拟合出背景曲面，并以二值图象形式给出去除背景后的目标图象。对一幅光照模型未知的网络图象进行了背景去除，实验结果良好。     

线材轧制技术的新进展

介绍了ＤａｎｉｅｌｉＭｏｒｇａｒｄｓｈａｍｍａｒ公司与Ｍｏｒｇａｎ公司提供的线材生产的新设备、新技术。并对其做了分析比较，特别对实现无序轧制多品种生产进行了讨论，指出新型高效线材轧机、高速切头飞剪和相关技术的采用，将推进线材轧制技术的新进展。     

滚珠丝杠的智能化研究进展

数控机床进给系统的智能化的状态检测、故障诊断以及自修复的能力可以提高数控机床工作的稳定性和可靠性,减少数控机床加工过程中出现的问题。滚珠丝杠是数控机床进给系统的重要组成部分,其精度与性能直接影响着数控机床的加工质量,滚珠丝杠的智能化发展也对数控机床的智能化发展有着非常重要的作用。综述了滚珠丝杠智能化的研究现状,分析了滚珠丝杠的动态测量和静态测量区别及优缺点;概述了基于数学模型和基于人工智能两个方面的故障诊断技术在滚珠丝杠中的应用;阐述了滚珠丝杠弹流润滑的机制以及通过润滑剂添加剂进行自修复的方法,阐明了滚珠丝杠的状态检测与故障诊断技术及自修复技术所存在的问题,展望了滚珠丝杠智能化的发展方向。     

Accelerated electrospark deposition and the wear behavior of coatings

Electrospark deposition (ESD) is a coating process that is featured by low heat input to the substrate. Low coating efficiency and other limitations influence its wider application. The present paper introduces newly designed ESD equipment, by which a higher coating rate can be reached. The relationship among coating thickness, surface roughness, and process parameters such as pulse energy, pulse frequency, and deposition time are presented. Electrospark deposition coating by the new equipment on AISI 1045 steel (with WC-8% Co as electrode) increases the wear resistance by 5 to 8 times. The micromechanism is investigated by scanning electron microscopy observation.     

研究合金定向凝固组织的脉冲磁场设备的研制

介绍了脉冲电磁场发生设备的工作原理 ,设计等。并介绍了其如何与合金的定向凝固设备结合 ,以实现对合金的定向凝固组织在脉冲电磁场作用下的研究。