螺杆挤压机混合能力的分析

分析螺槽中熔体的流动状态 ,运用加权平均总应变来评价螺杆挤压机的混合能力 ,进而提出提高混合能力的途径。对于单螺纹螺杆 ,稍长的计量段 ,稍浅的计量段螺槽及较高的螺杆转速 ,有利于混合作用 ;开发新型螺杆 ,如犁钉分流混合螺杆 ;研制高效混合型螺杆挤压机 ,如球窝型高效混合型螺杆挤压机     

An efficient approach for face recognition based on common eigenvalues

In this paper, a simple technique is proposed for face recognition among many human faces. It is based on the polynomial coefficients, covariance matrix and algorithm on common eigenvalues. The main advantage of the proposed approach is that the identification of similarity between human faces is carried out without computing actual eigenvalues and eigenvectors. A symmetric matrix is calculated using the polynomial coefficients-based companion matrices of two compared images. The nullity of a calculated symmetric matrix is used as similarity measure for face recognition. The value of nullity is very small for dissimilar images and distinctly large for similar face images. The feasibility of the propose approach is demonstrated on three face databases, i.e., the ORL database, the Yale database B and the FERET database. Experimental results have shown the effectiveness of the proposed approach for feature extraction and classification of the face images having large variation in pose and illumination.     

Graph regularized multiset canonical correlations with applications to joint feature extraction

Multiset canonical correlation analysis (MCCA) is a powerful technique for analyzing linear correlations among multiple representation data. However, it usually fails to discover the intrinsic geometrical and discriminating structure of multiple data spaces in real-world applications. In this paper, we thus propose a novel algorithm, called graph regularized multiset canonical correlations (GrMCCs), which explicitly considers both discriminative and intrinsic geometrical structure in multiple representation data. GrMCC not only maximizes between-set cumulative correlations, but also minimizes local intraclass scatter and simultaneously maximizes local interclass separability by using the nearest neighbor graphs on within-set data. Thus, it can leverage the power of both MCCA and discriminative graph Laplacian regularization. Extensive experimental results on the AR, CMU PIE, Yale-B, AT&T, and ETH-80 datasets show that GrMCC has more discriminating power and can provide encouraging recognition results in contrast with the state-of-the-art algorithms.     

HEGM: A hierarchical elastic graph matching for hand gesture recognition

A hierarchical scheme for elastic graph matching applied to hand gesture recognition is proposed. The proposed algorithm exploits the relative discriminatory capabilities of visual features scattered on the images, assigning the corresponding weights to each feature. A boosting algorithm is used to determine the structure of the hierarchy of a given graph. The graph is expressed by annotating the nodes of interest over the target object to form a bunch graph. Three annotation techniques, manual, semi-automatic, and automatic annotation are used to determine the position of the nodes. The scheme and the annotation approaches are applied to explore the hand gesture recognition performance. A number of filter banks are applied to hand gestures images to investigate the effect of using different feature representation approaches. Experimental results show that the hierarchical elastic graph matching (HEGM) approach classified the hand posture with a gesture recognition accuracy of 99.85% when visual features were extracted by utilizing the Histogram of Oriented Gradient (HOG) representation. The results also provide the performance measures from the aspect of recognition accuracy to matching benefits, node positions correlation and consistency on three annotation approaches, showing that the semi-automatic annotation method is more efficient and accurate than the other two methods.     

基于不可分小波分解的图像配准方法

张量积小波强调的是图像中水平和垂直方向的高频信息,而不可分小波具有各向同性,可以提取图像中各个方向的边缘,能获得比较完整的图像轮廓,将这种特点应用于图像配准时,能准确定位图像仿射不变点的位置。为此,提出一种通过求取不可分小波分解后的高频子图像配准参数来配准原图像的方法,把图像的配准问题转化为其不可分小波分解后的高频子图像配准问题。从不可分小波分解的快速算法理论出发,证明该配准方法的正确性。构造一组四通道不可分小波滤波器组,在此基础上给出配准的方法和步骤。实验结果表明,该方法具有较好的配准效果,其求取图像配准参数的运算量比直接求取原图像配准参数运算量的1/4还少,与基于张量积小波分解的图像配准方法相比,具有较高的配准精度。     

快速鲁棒特征算法的CUDA加速优化

提出一种基于统一计算设备架构(Compute Unified Device Architecture,CUDA)的快速鲁棒特征(Speed-up Robust Feature,SURF)图像匹配算法。分析了SURF算法的并行性,在图像处理单元(Graphics Processing Unit,GPU)的线程映射和内存模型方面对算法的构建尺度空间、特征点提取、特征点主方向的确定、特征描述子的生成及特征匹配5个步骤进行CUDA加速优化。实验表明,相比适用于CPU的SURF算法,文中提出的适用于GPU的SURF算法在处理30MB的图片时性能提高了33倍。适用于GPU的SURF算法拓展了SURF算法在遥感等领域的快速应用,尤其是大影像的快速配准。     

改进贝叶斯分类的智能短信分类方法

随着移动通信技术的不断发展,手机的普及率在不断上升,而短信作为传统的移动通信服务,长久以来一直在人们的日常生活中占据着极为重要的位置。可以说,短信在一定程度上记录了人们生活的轨迹。但是,现有的短信管理系统仅对短信进行以联系人为特征分类、以时间为顺序显示的简单非智能化的管理,导致了用户手机中各类短信混杂不清,短信的管理效率极低。通过研究短信的特征,分析传统的基于文档频率的特征值提取方法和基于互信息的特征值提取方法的优势与不足,提出了一种适用于短信的基于词频和互信息的特征值提取方法,并结合短信长度实现了一种改进的贝叶斯分类算法。实验证明,算法在进行短信分类时可以得到相当可观的召回率和准确率。     

基于Web挖掘的用户兴趣建模方法的研究

基于用户兴趣的不同,研究如何针对用户的浏览行为来获取用户的有效兴趣数据,并根据现有用户兴趣模型存在的不足,结合Web挖掘中的相关技术,先显式构建用户兴趣模型,后隐式更新用户兴趣模型,从而实现能适应用户兴趣变化的用户兴趣模型。     

Decentralized weighted control for a class of large‐scale systems with multi‐modes

In this paper, the control synthesis problem for a class of large‐scale systems with multi‐modes that are called large‐scale switched systems is addressed. By introducing the concept of decentralized switching signal and the relevant decentralized average dwell time, the asymptotic stability and weighted ?₂ gain performance are investigated. It should be noted that the decentralized switching covers general switching cases for large‐scale switched systems, namely, it admits both time‐dependent switching signal and arbitrary switching signal blended in the decentralized switching. Then, on the basis of the analysis results, the decentralized weighted control scheme including state feedback controller gains and switching signals is studied. Several design algorithms are proposed to meet different controller design problems. Finally, numerical examples are provided to illustrate theoretical findings within this paper. Copyright © 2013 John Wiley & Sons, Ltd.     

球窝型动态混合器结构和机理的研究

介绍研制的题示混合器结构及其混合机理。在分析球窝流场各节点速度分布的基础上,用加权平均总应变和分流混合度作为评定指标,对球窝型混合器的混合行为进行分析。通过对比实验证明球窝型混合器对于高粘流体具有良好的混合功效。