双组分环氧胶粘剂在我厂的应用

简单介绍了双组分环氧胶粘剂的特点、组成及固化反应机理 ,并且详细叙述了我厂双组分环氧胶粘剂的组分、配制工艺和灌胶工艺以及讨论了双组分环氧胶粘剂在我厂的应用情况 ,为我厂的军品及民用电器产品的灌封胶接提供了广泛的前景     

锌系工件的静电粉末涂装和工艺管理

讨论了锌系工件喷涂的相关工艺、现场管理、技术参数、质量检验和环境要求等。     

HMM-based state classification of a user with a walking support system using visual PCA features

The improvement of safety and dependability in systems that physically interact with humans requires investigation with respect to the possible states of the user’s motion and an attempt to recognize these states. In this study, we propose a method for real-time visual state classification of a user with a walking support system. The visual features are extracted using principal component analysis and classification is performed by hidden Markov models, both for real-time fall detection (one-class classification) and real-time state recognition (multi-class classification). The algorithms are used in experiments with a passive-type walker robot called “RT Walker” equipped with servo brakes and a depth sensor (Microsoft Kinect). The experiments are performed with 10 subjects, including an experienced physiotherapist who can imitate the walking pattern of the elderly and people with disabilities. The results of the state classification can be used to improve fall-prevention control algorithms for walking support systems. The proposed method can also be used for other vision-based classification applications, which require real-time abnormality detection or state recognition.     

An ExPosition of multivariate analysis with the singular value decomposition in R

ExPosition is a new comprehensive R package providing crisp graphics and implementing multivariate analysis methods based on the singular value decomposition (svd). The core techniques implemented in ExPosition are: principal components analysis, (metric) multidimensional scaling, correspondence analysis, and several of their recent extensions such as barycentric discriminant analyses (e.g., discriminant correspondence analysis), multi-table analyses (e.g.,multiple factor analysis, Statis, and distatis), and non-parametric resampling techniques (e.g., permutation and bootstrap). Several examples highlight the major differences between ExPosition and similar packages. Finally, the future directions of ExPosition are discussed.     

Prediction of multicomponent adsorption equilibrium of gas mixtures including supercritical components

A new model to predict the adsorption equilibrium of mixtures containing supercritical components was presented. The difference in the adsorption mechanism between the supercritical components and the condensable components was accounted for in the new model. Lateral interaction in the adsorbed phase was also considered in the local isotherm. The new model was verified by the experimental data of the mixture CH₄/CO₂/C₂H₆ on activated carbon JX101 collected for 283-313 K and pressures up to . It was also verified with the experimental data published previously in literature. Considerable improvement in the prediction precision was achieved in using the new model to predict the adsorption of mixtures on activated carbon.     

A new approach of audio emotion recognition

A new architecture of intelligent audio emotion recognition is proposed in this paper. It fully utilizes both prosodic and spectral features in its design. It has two main paths in parallel and can recognize 6 emotions. Path 1 is designed based on intensive analysis of different prosodic features. Significant prosodic features are identified to differentiate emotions. Path 2 is designed based on research analysis on spectral features. Extraction of Mel-Frequency Cepstral Coefficient (MFCC) feature is then followed by Bi-directional Principle Component Analysis (BDPCA), Linear Discriminant Analysis (LDA) and Radial Basis Function (RBF) neural classification. This path has 3 parallel BDPCA + LDA + RBF sub-paths structure and each handles two emotions. Fusion modules are also proposed for weights assignment and decision making. The performance of the proposed architecture is evaluated on eNTERFACE’05 and RML databases. Simulation results and comparison have revealed good performance of the proposed recognizer.     

基于类标记扩展的半监督网络流量特征选择算法

针对网络流量特征选择过程中存在的样本标记瓶颈问题,以及现有半监督方法无法选择强相关的特征的不足,提出一种基于类标记扩展的多类半监督特征选择(SFSEL)算法。该算法首先从少量的标记样本出发,通过K-means算法对未标记样本进行类标记扩展;然后结合基于双重正则的支持向量机(MDrSVM)算法实现多类数据的特征选择。与半监督特征选择算法Spectral、PCFRSC和SEFR在Moore数据集进行了对比实验,SFSEL得到的分类准确率和召回率明显都要高于其他算法,而且SFSEL算法选择的特征个数明显少于其他算法。实验结果表明: SFSEL算法能够有效地提高所选特征的相关性,获取更好的网络流量分类性能。     

基于局部重构的无监督特征选择方法

利用局部线性嵌入(LLE)算法中获得局部邻域之间的重构关系与使用最小角回归方法解决L1归一化问题都使用回归方法,针对在通过映射获得低维嵌入空间与通过特征选择获得低维空间上有着一致的思想,提出一种能保持局部重构关系的无监督谱特征选择方法.该方法利用最小二乘法计算样本的邻域重构系数,并用这些系数表示样本之间的关系,通过解决稀疏特征值问题获得能够保持样本间关系的低维嵌入空间,最后通过解决L1归一化问题实现自动特征选择.通过在四个不同数据集上的聚类实验结果证明,该方法能更准确地评价每个特征的重要性,能自动适应不同的数据集,受参数影响更小,可以明显提升聚类效果.     

基于文档文字特征的碎纸机碎片拼接算法

针对经碎纸机粉碎的文档碎片,提出拼接复原的模型并研制了相应的算法。首先研究文档碎片边界像素特征,据此提出碎片横向拼接的两种算法;然后,研究行高、字体间间距以及字体大小等文本特征,据此提出针对经横向拼接形成的水平残条的纵向拼接算法。最后根据算法编写Matlab程序,并进行实验,结果表明该算法效果良好。     

采用主监视窗扩展技术的增强现实三维注册方法

在增强现实三维注册中,采用重新检测策略时顿卡现象严重。提出一种采用主监视窗扩展技术的增强现实三维注册方法。在检测阶段,引入特征点可信度和主监视窗,并设计主监视窗的分割、扩展和调控策略,大幅提升了计算速度;在跟踪阶段,采用基于图像金字塔的光流算法进行特征点跟踪。实验证明,该方法不仅有效缓解了顿卡现象,也提升了系统整体的实时性。