RSView32软件平台的应用及扩展

概述了RSView32工控软件的特点和使用方法 ,并通过贵溪冶炼厂的一个液位自动控制系统的人机界面设计说明了如何在控制系统中使用RSView32软件。文章特别介绍了如何用VBA程序设计来扩展其功能     

Repair of Cracked Aluminum Overhead Sign Structures with Glass Fiber Reinforced Polymer Composites

Transportation departments have been using aluminum overhead sign structures since the 1950s. It is well documented that cracks develop in the welds between diagonal and chord members due to fatigue stresses from wind-induced vibration of the slender members. The cracks propagate to complete failure of the members, which can cause collapse of the truss and inflict injuries. The original design of overhead sign structures did not consider fatigue as a limit state. In addition, field welding of aluminum structures for any possible repairs is prohibited. A repair method for the cracked aluminum welded connections between diagonals and chord members using glass fiber reinforced polymer composites (GFRPs) is proposed. The static load carrying capacity of the welded connection, and the cracked connection repaired with GFRP composites are established. The paper describes the surface preparation of the aluminum tubular members, and the architecture and application sequence of the GFRP composite to retrofit the connection. Experimental results are presented from static tests of welded aluminum connections, welded aluminum connections retrofitted with GFRP composites, and new aluminum connections that depend only on GFRP composite elements for their strength. The results from monotonic static tests carried out on cracked welded specimens from actual sign structures show that the retrofitted connection with GFRP reinforcement achieved 1.17 to 1.25 times the capacity of the welded aluminum connection without any visible cracks. This result, and the minimal traffic disruption anticipated in the actual field application, makes this retrofit method a good candidate for implementation.     

Towards subject independent continuous sign language recognition: A segment and merge approach

This paper presents a segment-based probabilistic approach to robustly recognize continuous sign language sentences. The recognition strategy is based on a two-layer conditional random field (CRF) model, where the lower layer processes the component channels and provides outputs to the upper layer for sign recognition. The continuously signed sentences are first segmented, and the sub-segments are labeled SIGN or ME (movement epenthesis) by a Bayesian network (BN) which fuses the outputs of independent CRF and support vector machine (SVM) classifiers. The sub-segments labeled as ME are discarded and the remaining SIGN sub-segments are merged and recognized by the two-layer CRF classifier; for this we have proposed a new algorithm based on the semi-Markov CRF decoding scheme. With eight signers, we obtained a recall rate of 95.7% and a precision of 96.6% for unseen samples from seen signers, and a recall rate of 86.6% and a precision of 89.9% for unseen signers.     

材料在红色旅游景区导视系统中的情感表达

随着人们情感需求的日益膨胀,导视系统也不再仅仅只关注于功能性。更需要关注它与任何环境之间的关系,做情感化设计。尤其红色旅游景区,导视系统更应该凸显其艺术性,注重人们的心理感受。与景区格调一致。完美烘托主题。而材料是事物的基础及艺术的载体。文章通过对常用材料情感特征进行分析研究。结合红色景区的特点,探索适于红色景区导视系统情感表达的材料。     

基于Haar—like矩形特征的交通标志识别

针对道路交通标志识别系统中的识别精度和识别实时性问题,提出一种基于Haar—like矩形特征的交通标志识别算法。为了提高提取速度,用积分图像先对样本库进行处理,提取Haar-like矩形特征做为特征向量。提取的特征向量因维数过高．应用PCA降维法对数据进行降维。将降维后的特征向量用来对支持向量机训练。实验结果表明,Hart-like矩形特征向量具有形式简单．计算速度快等优点。在小样本的目标识别中,利用SVM进行分类识别,取得很好的识别效果．并在识别耗时上有所优化。     

结合Bi-2DPCA与CNN的美式手语识别

针对现有美式手语（ASL）识别算法准确率低和模型训练时间长的问题,提出一种结合双向二维主成分分析（Bi-2DPCA）与卷积神经网络（CNN）并基于贝叶斯优化的识别算法。利用Bi-2DPCA算法对原始图像做数据降维处理,提取行、列方向的特征图,使用卷积神经网络对特征图进行训练分类,同时采用贝叶斯优化算法对模型超参数进行自动调参。在24分类ASL数据集上的实验结果表明,该算法的识别准确率达到99.15%,训练时间相比传统CNN算法减少90.3%。     

基于球面全景图的空战环境漫游研究

研究鱼眼图像的拼接算法,实现利用两幅鱼眼图像生成球面虚拟空间,然后探讨基于球面虚拟图的多视点漫游问题,利用反投影模板技术有效地提高全景图浏览的速度,采用缩放的方法改进了行进间的浏览效果,从而提高虚拟漫游的沉浸感,具有一定的实用意义。     

Radiometric normalization and image mosaic generation of ASTER thermal infrared data: An application to extensive sand sheets and dune fields

Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) have a significant advantage over previous datasets because of the combination of high spatial resolution (15-90 m) and enhanced multispectral capabilities, particularly in the thermal infrared (TIR) atmospheric window (8-12 μm) of the Earth where common silicate minerals are more easily identified. However, the 60 km swath width of ASTER can limit the effectiveness of accurately tracing large-scale features, such as eolian sediment transport pathways, over long distances. The primary goal of this paper is to describe a method for generating a seamless and radiometrically accurate ASTER TIR mosaic of atmospherically corrected radiance and from that, extract surface emissivity for arid lands, specifically, sand seas. The Gran Desierto in northern Sonora, Mexico was used as a test location for the radiometric normalization technique because of past remote sensing studies of the region, its compositional diversity, and its size. A linear approach was taken to transform adjacent image swaths into a direct linear relationship between image acquisition dates. Pseudo-invariant features (PIFs) were selected using a threshold of correlation between radiance values, and change-pixels were excluded from the linear regression used to determine correction factors. The degree of spectral correlation between overlapping pixels is directly related to the amount of surface change over time; therefore, the gain and offsets between scenes were based only on regions of high spectral correlation. The result was a series of radiometrically normalized radiance-at-surface images that were combined with a minimum of image edge seams present. These edges were subsequently blended to create the final mosaic. The advantages of this approach for TIR radiance (as opposed to emissivity) data include the ability to: (1) analyze data acquired on different dates (with potentially very different surface temperatures) as one seamless compositional dataset; (2) perform decorrelation stretches (DCS) on the entire dataset in order to identify and discriminate compositional units; and (3) separate brightness temperature from surface emissivity for quantitative compositional analysis of the surface, reducing seam-line error in the emissivity mosaic. The approach presented here is valid for any ASTER-related study of large geographic regions where numerous images spanning different temporal and atmospheric conditions are encountered.     

基于方向直方图的手语识别方法研究

传统的手语识别方法基本都是利用离散的各帧静态图像进行识别,存在一定局限性,根据普通摄像头获得的视频图像,并采用方向直方图来获得单帧的静态特征矢量和各帧图像间的动态特征矢量.实现手语的识别.首先针对头两帧图像,通过手部边缘轮廓提取算法找到手的区域,然后从中提取出能表现手部形状的静态特征矢量.同时,对连续帧的图像做动作评估,获得手部移动的动态特征欠量.最后,将手部形状的静态特征与动态特征结合,采用使用欧氏距离作为矢量问匹配程度的度量算法以实现手语识别.实验对5个人的5种手语分别进行测试,均能正确识别,结果验证了该方法的有效性.     

SignMT: An alternative language learning tool

Learning a second language is very difficult, especially, for the disabled; the disability may be a barrier to learn and to utilize information written in text form. We present the SignMT, Thai sign to Thai machine translation system, which is able to translate from Thai sign language into Thai text. In the translation process, SignMT takes into account the differences between Thai and Thai sign language in terms of both syntax and semantic to ensure the accuracy of translation. SignMT was designed to be not only an automatic interpreter but also a language learning tool. It provides meaning of each word in both text and image forms which is easy to understand by the deaf. The grammar information and the order of the sentence are presented in order to help the deaf in learning Thai, their second language. With SignMT, deaf students are less dependent on a teacher, have more freedom to experiment with their own language, and improve their knowledge and learning skill.