Solving the small sample size problem in face recognition using generalized discriminant analysis

The goal of face recognition is to distinguish persons via their facial images. Each person's images form a cluster, and a new image is recognized by assigning it to the correct cluster. Since the images are very high-dimensional, it is necessary to reduce their dimension. Linear discriminant analysis (LDA) has been shown to be effective at dimension reduction while preserving the cluster structure of the data. It is classically defined as an optimization problem involving covariance matrices that represent the scatter within and between clusters. The requirement that one of these matrices be nonsingular restricts its application to datasets in which the dimension of the data does not exceed the sample size. For face recognition, however, the dimension typically exceeds the number of images in the database, resulting in what is referred to as the small sample size problem. Recently, the applicability of LDA has been extended by using the generalized singular value decomposition (GSVD) to circumvent the nonsingularity requirement, thus making LDA directly applicable to face recognition data. Our experiments confirm that LDA/GSVD solves the small sample size problem very effectively as compared with other current methods.     

试谈低pH值元明粉生产技术

从生产实际出发，通过一系列分析研究，找出了低pH值元明粉的生产方法。     

基于神经网络基础上的两种系统安全综合评价方法

从工业企业生产发展的特点出发,在界定安全评价概念的基础上，从系统论的角度简要介绍了运用三层BP神经网络技术进行安全综合评价的方法和安全模糊综合评价方法。通过对这两种较为流行的安全评价方法进行分析，指出了传统评价方法的不合理性，辨证说明了这两种评价方法的优越性。     

A three‐dimensional model describing stress‐temperature induced solid phase transformations: solution algorithm and boundary value problems

An always increasing knowledge on material properties as well as a progressively more sophisticated production technology make shape memory alloys (SMA) extremely interesting for the industrial world. At the same time, SMA devices are typically characterized by complex multi‐axial stress states as well as non‐homogeneous and non‐isothermal conditions both in space and time. This aspect suggests the finite element method as a useful tool to help and improve application design and realization. With this aim, we focus on a three‐dimensional macroscopic thermo‐mechanical model able to reproduce the most significant SMA features (Int. J. Numer. Methods Eng. 2002; 55 : 1255–1264), proposing a simple modification of such a model. However, the suggested modification allows the development of a time‐discrete solution algorithm, which is more effective and robust than the one previously discussed in the literature. We verify the computational tool ability to simulate realistic mechanical boundary value problems with prescribed temperature dependence, studying three SMA applications: a spring actuator, a self‐expanding stent, a coupling device for vacuum tightness. The effectiveness of the model to solve thermo‐mechanical coupled problems will be discussed in a forthcoming work. Copyright © 2004 John Wiley & Sons, Ltd.     

从事放射性个人剂量监测分析与防护调查

为了能及时了解放射性工作人员的受照剂量，以便能够更好地保障放射工作人员的健康与安全，采用热释光测量法对包头地区从事放射性工作的工作人员进行了个人剂量监测，并对他们的剂量当量频数分布进行了统计与分析，对工作环境的防护进行了调查对比，就今后的工作提出建议。     

BFG的热值及温度与0号机出力和效率的关系

分析煤气温度、干煤气热值和湿煤气热值之间的关系，得到0号机组长期达不到额定出力和效率的原因，在此基础上提出解决问题的方法。     

标准偏差的六种估计及其精密度

介绍了对标准偏差进行估计的6种方法，分析估计精密度，给出应用实例。     

遗落的明珠——浅谈岑参山水写景诗的艺术价值

唐代诗人岑参以边塞诗闻名于中国古代诗坛，同时他的山水写景诗写得也毫不逊色，取得了极高的艺术成就，特别是其清淡、清新、清旷、清丽的“四清”并行的艺术风格尤为突出。由于历史和个人原因，岑参的山水写景诗历来鲜为人知，但这并不能否定其特有的艺术价值。     

基于奇异值分解和神经网络的个性化信息模式识别

随着信息资源的持续增长，信息获取系统为特定用户提供特定信息服务的需求越来越重要。该文提出了基于奇异值分解和神经网络的个性化信息模式识别的方法，可以方便地获取用户信息需求的特征，并且利用这些特征信息完成个性化的信息识别和匹配，即实现个性化信息的模式识别，进而实现信息的个性化获取和管理。该文中的算法实现简单，可以方便地应用到目前的一些信息管理、服务系统中。     

Mining for trigger events with survival analysis

This paper discusses a new application of data mining, quantifying the importance of responding to trigger events with reactive contacts. Trigger events happen during a customer’s lifecycle and indicate some change in the relationship with the company. If detected early, the company can respond to the problem and retain the customer; otherwise the customer may switch to another company. It is usually easy to identify many potential trigger events. What is needed is a way of prioritizing which events demand interventions. We conceptualize the trigger event problem and show how survival analysis can be used to quantify the importance of addressing various trigger events. The method is illustrated on four real data sets from different industries and countries.