一类带有种痘年龄的流行病模型

A simple SI epidemic model with age of vaccination is discussed in this paper. Both varing birth rate,the mortality rate caused by disease and vaccine waning rate are considered in this model.We prove that the global dynamics is completely determined by the basic reproductive number R(Ψ)(Ψdenotes per capita vaccination rate).If R(0)＜1, the disease-free equilibrium is a global attractor;If R(Ψ)＜1,the disease-free equilibrium is locally asymptotically stable;If R(Ψ)＞1,an unique endemic equilibrium exists and is locally asymptotically stable under certain condition.     

带有脉冲免疫和传染年龄的传染病模型的全局吸引性

讨论了带有脉冲免疫和传染年龄的传染病模型.传染类的恢复率是传染年龄的函数,当染病再生数小于1时,文章得到无病周期解是全局吸引的.如果总人口规模变化,也可得到类似的结论.最后,提出了带有脉冲免疫和传染年龄传染病模型待解决的问题.     

带有脉冲免疫和传染年龄的肝病模型的全局渐近稳定性

讨论了带有脉冲免疫的肝病模型，并在传染类中引入了传染年龄，且传染类的恢复率是依赖这个年龄的，最后给出了元病周期解全局渐近稳定性的条件．     

基于人脸重要特征和SVM的人脸识别方法

提出了一种基于人脸重要特征的人脸识别方法,首先选取人脸的重要特征并将其具体化,对得到的重要特征进行主成分分析,然后用支持向量机(Support Vector Machine,SVM)设计重要特征分类器来确定测试人脸图像中重要特征,同时设计支持向量机(SVM)人脸分类器,确定人脸图像的所属类别.对ORL人脸图像数据库进行仿真实验,结果表明,该方法要优于一般的基于整体特征的人脸识别方法并有较强的鲁棒性.     

带有脉冲免疫和传染年龄的SIV传染病模型解的存在性

我们建立带有脉冲免疫和传染年龄的SIV传染病模型,这类传染病在潜伏期具有传染性,总人口规模依赖时间,并且传染类的康复率和传染年龄有关.我们证明此类模型解存在唯一.     

利用完全辅助信息的模型校正信息论方法 (英)

本文我们提出了使用调查数据中完全辅助信息的模型校正K-L相对熵最小化方法．在估计有限总体均值时我们的估计渐近等价于MC估计(Wu and Sitter(2001))．我们方法一个有吸引力的优点是,导出的权具有特征:pi>0和■pi=0 ．这使得可把此方法应用于估计分布函数和分位数．导出的分布函数估计量FMKL(y)渐近等价于广义回归估计,且本身是一分函数布．     

基于概率弹性匹配的多姿态人脸认证

为解决多姿态情况下的人脸认证问题,提出了基于概率弹性匹配的方法.首先从多尺度密集采样的图像中提取局部特征,并将局部区域的位置信息保存到特征向量中.然后用高斯混合模型在图像集中训练得到人脸特征的空间外观分布,并将人脸图像中的每一个局部区域表示成与其最相似的高斯分量,从而形成一个基于高斯混合模型表示的人脸特征.通过统计两个人脸特征向量的差向量来训练支撑向量机分类器从而实现多姿态人脸认证.在通用图像库中的实验验证了方法的有效性.     

基于肤色模型法的人脸定位技术研究

基于JAVA语言对人脸识别首要环节的定位技术进行代码开发,在传统肤色模型法的基础上,对采集到的大量图像进行深入研究,运用图像精准化微调和图像增强处理的方法,提高了传统肤色模型法在实际运用中的精准率,实现了人脸在视频图像中的定位。     

带有标准发生率和信息干预的时滞SIRS传染病模型的稳定性分析

本文考虑一类具有标准发生率和信息干预的时滞SIRS传染病模型.通过分析模型的特征方程,讨论无病平衡点和地方病平衡点局部渐近稳定性.应用Halanay不等式对无病平衡点的全局渐近稳定性进行证明.通过构造适当的Lyapunov函数讨论地方病平衡点全局渐近稳定性.最后通过数值模拟分析一些重要参数对疾病传播的影响.     

带有信息的区间删失数据下AFT模型的参数估计

在生存分析研究中,多数文章假定感兴趣的失效时间和删失时间是独立的,但这一假设在实际情况中未必合理。如果忽略失效时间与删失时间的相依性,可能会导致错误的结论。所以本文考虑在带有信息的K型区间删失数据下,采用基于两步估计的极大似然估计方法对误差项服从标准正态分布的加速失效时间模型(accelerated failure time model,AFT)进行参数估计。同时还进行了数值模拟以验证提出方法的有效性。最后,应用所提出的方法分析艾滋病的临床试验数据。     

信息技术时代的工程力学和材料研究

论述了信息技术的重要性和发展方向,讨论了科学和工程基础研究的主要任务,建议了２１世纪力学和材料科学的研究方向     

Classification Modulo Invariance,With Application to Face Recognition

This article presents techniques for constructing classifiers that combine statistical information from training data with tangent approximations to known transformations; it demonstrates the techniques by applying them to a face recognition task. Our approach is to build Bayes classifiers with approximate class-conditional probability densities for measured data. The high dimension of the measurements in modern classification problems such as speech or image recognition makes inferring probability densities from feasibly sized training datasets difficult. We address the difficulty by imposing severely simplifying assumptions and exploiting a priori information about transformations to which classification should be invariant. For the face recognition task, we used a five-parameter group of such transformations consisting of rotation, shifts, and scalings. On the face recognition task, a classifier based on our techniques has an error rate that is 20% lower than that of the best algorithm in a reference software distribution.     

稀疏表示及其在人脸识别中的应用

稀疏表示是近年来新兴的一种数据表示方法,是对人类大脑皮层编码机制的模拟。稀疏表示以其良好的鲁棒性、抗干扰能力、可解释性和判别性等优势,广泛应用于模式识别领域。基于稀疏表示的分类器在人脸识别领域取得了令人惊喜的成就,它将训练样本看成字典,寻求测试样本在字典下的最稀疏的表示,即用尽可能少的训练样本的线性组合来重构测试样本。但是经典的基于稀疏表示的分类器没有考虑训练样本的类别信息,以致被选中的训练样本来自许多类,不利于分类,因此基于组稀疏的分类器被提出。组稀疏方法考虑了训练样本的类别相似性,其目的是用尽可能少类别的训练样本来表示测试样本,然而这类方法的缺点是同类的训练样本或者同时被选中或者同时被丢弃。在实际中,人脸受到光照、表情、姿势甚至遮挡等因素的影响,样本之间关系比较复杂,因此最后介绍局部加权组结构稀疏表示方法。该方法尽量用来自于与测试样本相似的类的训练样本和来自测试样本邻域的训练样本来表示测试样本,以减轻不相关类的干扰,并使得表示更稀疏和更具判别性。     

A Semi-Supervised Learning Algorithm for Growing Neural Gas in Face Recognition

In many classification applications and face recognition tasks, there exist unlabelled data available for training along with labelled samples. The use of unlabelled data can improve the performance of a classifier. In this paper, a semi-supervised growing neural gas is proposed for learning with such partly labelled datasets in face recognition applications. The classifier is first trained on the labelled data and then gradually unlabelled data is classified and added to the training data. The classifier is retrained; and so on. The proposed iterative algorithm conforms to the EM framework and is demonstrated, on both artificial and real datasets, to significantly boost the classification rate with the use of unlabelled data. The improvement is particularly great when the labelled dataset is small. Comparison with support vector machine classifiers is also given. The algorithm is computationally efficient and easy to implement.     

基于可拓分析的信息模式识别方法

采用可拓评判方法,应用物元概念和关联函数,确定了玉米螟种群动态分级识别的的经典域物元和节域物元,提出了一种新的基于可拓分析的信息模式识别方法,并探讨了其应用.应用结果表明,历史拟合率达100%,1995、1996两年预报,其结果与实际一致.说明该识别方法具有良好的应用前景,一种全新的模式识别分类器.     

信息经济时代的客户知识模型

客户知识由客户界定，沟通渠道，客户需求，客户行为以及客户赢利价值五个层次组成。其中每个知识层次都是包含该层次具体内容的客户知识子集。客户知识的掌握是一个过程，它从了解客户的基本信息以实现对客户进行界定开始，到识别客户对企业的赢利价值这一客户知识的核心。客户知识是制定“以客户为中心”的整合营销行动计划的基础。     

A Tale of Two Countries: Some Systems Perspectives on Japan and the United Kingdom in the Age of Information Technology

The British still excel in agriculture just as, a century or so ago, they did in manufacturing and, 30 years ago, in computing. The Japanese, who are also good at agriculture, came to excel in manufacturing and probably now lead the world in information technology. Now Britain is trying to catch up. The paper presents some views of the situation.     

Mining performance data through nonlinear PCA with optimal scaling

Performance data are usually collected in order to build well‐defined performance indicators. Since such data may conceal additional information, which can be revealed by secondary analysis, we believe that mining of performance data may be fruitful. We also note that performance databases usually contain both qualitative and quantitative variables for which it may be inappropriate to assume some specific (multivariate) underlying distribution. Thus, a suitable technique to deal with these issues should be adopted. In this work, we consider nonlinear principal component analysis (PCA) with optimal scaling, a method developed to incorporate all types of variables, and to discover and handle nonlinear relationships. The reader is offered a case study in which a student opinion database is mined. Though generally gathered to provide evidence of teaching ability, they are exploited here to provide a more general performance evaluation tool for those in charge of managing universities. We show how nonlinear PCA with optimal scaling applied to student opinion data enables users to point out some strengths and weaknesses of educational programs and services within a university. Copyright © 2009 John Wiley & Sons, Ltd.     

Issues in Managing Information Technology

This paper describes three case studies which investigated issues relating to the implementation and management of advanced information technology. The benefits derived from information technology were found to vary from one organization to another. These studies provide further evidence to support earlier research findings that senior management has an important role to play in the effective exploitation of information technology, and that the investment approach taken by an organization has a significant effect on the development of computer-based information systems. The effectiveness of a system depends not only on applying the appropriate technology, but also on how successfully technical and behavioural issues are resolved.