GM模型的几何性质及统计检验

以空间向量几何理论为基础，详细地分析了Ｇａｕｓｓ－Ｍａｒｋｏｖ线性模型的几何性质；在实现了模型图形化描述的基础上，利用各解向量的几何及统计性质构造出了不同情形下的统计检验方法和相应的检验统计量，为全面、深入地研究和灵活运用该模型提出了一种简洁直观的数学方法     

反求工程的产品几何建模技术研究

分析了目前在反求工程产品几何建模中广泛应用的曲面模型的局限性，指出反求工程为实现创新功能必须采用产品特征模型，提出了基于实体造型的特征建模方法。这种方法可以避免曲面模型的缺陷，拓宽反求工程的应用范围，是实现三维重构的新方法。探讨了有关的理论和关键技术。     

等离子熔积直接成形形状特性的基础研究

系统分析了熔积成形技术中影响成形形状特性的原因,研究了转移弧电流、扫描速度和起弧高度对成形精度的影响机理.实验表明,以上参数对等离子熔积直接成形形状特性的影响显著,对改善零件的成形精度起决定性的作用;通过优化成形工艺参数,焊道表面质量得到显著好转.     

CF均布型炉箅的开发与应用

介绍了固定层间歇式煤气炉炉箅设计开发指导思想与CF均布型炉箅结构特点及应用情况。     

Discourse cues to deception in the case of multiple receivers

Behavioral cues to deception are instrumental in detecting deception. As one of the primary sources of deception behavior, text has been analyzed at the level of sub-sentence or message but not the discourse of interaction. Additionally, empirical studies on cues to deception in the case of multiple receivers remain nonexistent. To fill these voids, we propose a discourse framework and six hypotheses about deception behaviors in a multi-receiver environment. The deception behaviors are operationalized by discourse features based on an analysis of real-world data. The results of statistical analysis validate the efficacy of discourse features in discriminating deceivers from truth-tellers.     

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     

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.     

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。