基于三次B样条曲线的特色照相系统算法模型

给出了一套娱乐性照相系统的算法模型,其原型为哈哈镜.模型以三次B样条曲线为基础,主要为内存和计算能力有限的手机、PDA等手持设备设计.模型的基本思想是将图像抽象成一组直线的集合,将图像的变化看作是这组直线的变化;对这组直线的变化建立数学模型,使图像的变化变成可以描述并且可控制的数学表达式;再将这个教学表达式映射成图像的变化.为了增加模型的实用性,最后又对这个模型进行了优化,将图像的变化转变成图像像素坐标的变化,以变化模板的方式替代了复杂的计算,从而使模型更具有实际使用价值.     

基于遗传算法的航空发动机性能曲线逼近

绘制性能曲线是检验航空发动机是否合格的重要工作步骤.利用标准性能曲线板手工绘制往往具有较大的作图和读数误差.变换标准曲线的数值计算方法会带来变换计算量大,求解Y值复杂的问题.求解过程中变换测量点,求出平移和旋转量后,反向变换标准曲线获得实测曲线.通过对平移和旋转量进行编码,采用遗传算法实现了性能曲线逼近.     

基于椭圆曲线的盲数字签名及其身份识别

椭圆曲线密码体制以其特有的优越性被广泛用于进行数据加密和构建数字签名方案。同样,它也可以用来构建盲数字签名方案。介绍了椭圆曲线密码体制的相关知识,基于求解椭圆曲线离散对数问题的困难性,设计了一种基于椭圆曲线离散对数问题的盲数字签名方案,并在此基础上设计了一种身份识别协议,该方案可以同时满足盲数字签名的正确性、匿名性、不可伪造性和不可追踪性等特性要求。从理论上分析该方案是安全的,并具有一定的实用价值。     

Analyzing CAD competence with univariate and multivariate learning curve models

Understanding how learning occurs, and what improves or impedes the learning process is of importance to academicians and practitioners; however, empirical research on validating learning curves is sparse. This paper contributes to this line of research by collecting and analyzing CAD (computer-aided design) procedural and cognitive performance data for novice trainees during 16-weeks of training. The declarative performance is measured by time, and the procedural performance by the number of features used to construct a design part. These data were analyzed using declarative or procedural performance separately as predictors (univariate), or a combination of declarative or procedural predictors (multivariate). Furthermore, a method to separate the declarative and procedural components from learning curve data is suggested.     

Fast Object Segmentation by Growing Minimal Paths from a Single Point on 2D or 3D Images

In this paper, we present a new method for segmenting closed contours and surfaces. Our work builds on a variant of the minimal path approach. First, an initial point on the desired contour is chosen by the user. Next, new keypoints are detected automatically using a front propagation approach. We assume that the desired object has a closed boundary. This a-priori knowledge on the topology is used to devise a relevant criterion for stopping the keypoint detection and front propagation. The final domain visited by the front will yield a band surrounding the object of interest. Linking pairs of neighboring keypoints with minimal paths allows us to extract a closed contour from a 2D image. This approach can also be used for finding an open curve giving extra information as stopping criteria. Detection of a variety of objects on real images is demonstrated. Using a similar idea, we can extract networks of minimal paths from a 3D image called Geodesic Meshing. The proposed method is applied to 3D data with promising results.

高分辨率超声Lamb波频散曲线测量与板厚估计

超声Lamb波在工业无损检测与 评价中具有广阔的应用前景。但受制于超声导波多模式频散与混叠的影响,如何实现高分辨率超声导波的模式分离与频散曲线提取,进而定量分析材料的健康状况一直是研究的热点与难点。本文旨在将现代信号处理中广泛采用的谱估计技术应用于超声Lamb波阵列信号分析,并通过提取频散曲线定量测量板厚度。以经典参数谱估计法中的Yule-Walker法与Burg法为例,实验测量和分析了3 mm,4 mm和 5 mm厚铝板中的宽带多模式Lamb波信号,准确地提取了铝板中的宽带Lamb波频散曲线,并比较了两种经典谱估计方法与二维傅氏变换法的性能,最终实现了铝板厚度估计。