基于图像优化局部保留投影的人脸表情识别

提出了一种基于图像优化局部保留投影的人脸表情识别方法。该算法在降维过程中将图像结构信息融入到LPP目标函数中,称之为GOLPP。与LPP不同,GOLPP通过降维处理,获得图像结构信息的同时将投影最优化,这样可从原始表情数据中提取更具判决性的表情信息。基于JAFFE和CED-WYU（1.0）两个表情数据库的识别结果表明,基于GOLPP的特征提取方法能有效地提高识别率。     

保局投影在图像隐密检测中的应用

为解决图像隐密检测中图像特征维数过高导致的"维数灾难"问题,在保持图像特征内在低维结构的基础上降低特征向量的维数,方便构造更有效的分类器,提出了一种基于保局投影(locality preserving projections,LPP)降维的图像隐密检测算法,对待测图像进行小波变换形成图像特征后,利用LPP算法实现对图像高维特征的降维,得到图像特征集的低维流形.使用支持向量机(SVM)算法将降维后的特征映射到分类特征空间,实现对正常图像和隐密图像分类.实验结果表明,与不使用降维算法的检测方案相比,基于LPP降维的检测算法能够显著地提高检测的准确率.     

基于局部二元模式的人脸表情识别

提出了一种基于局部二元模式（LBP）和局部保全投影（LPP）相结合的面部表情识别方法。使用LBP算子对图像分块处理,综合人脸局部和整体的特征;再使用LPP对表情特征降维,最后采用支持向量机对面部表情分类。在日本女性人脸表情库上实验表明,本文提出的方法有更好的识别率和更快的识别速度。     

基于局部保持投影的人脸超分辨率方法研究

通常,人脸图像能够看作是嵌入到高维空间中的低维流形的点的集合。流形学习被用于很多降维方法中,局部保持投影（LPP）便是其中的一种。针对局部保持投影方法进行了研究,将局部保持投影算法融入到超分辨率方法中,并将其结合到人脸图像的复原上。介绍现有的基于LPP的人脸图像的超分辨率算法。     

基于Curvelet及LPP的人脸识别算法

基于人脸图像的曲线奇异性及高维图像数据带来的计算复杂性．提出一种结合Curvelet变换与LPP的人脸识别方法。首先通过Curvelet变换对人脸图像降维,利用LPP将图像投影到最优子空间中,利用支持向量机进行分类识别,实验结果表明该算法的识别效果优于小波变换结合LPP方法、LPP方法。     

基于改进的自适应局部保持投影算法的人脸识别

局部保持投影(LPP)通过构造近邻图来保持样本的局部结构,在构造近邻图的过程中,LPP会遇到两个参数K和σ的选择问题。近邻图的构建对算法的识别效果起着重要的作用,因而这两个参数的选择会在很大程度上影响LPP的识别率。为了避免参数的选择对识别率造成影响,提出了一种基于改进的自适应局部保持投影的人脸识别算法。首先,构造无参数的近邻图,其能够自适应地选取样本的近邻点并确定其相应的边权。其次,由于在计算过程中出现了矩阵维数过高的问题,因此采用QR分解进行降维处理。最后,利用共轭正交化使得投影轴具有统计不相关性,以降低特征矢量间的统计相关性,提高识别率。在ORL人脸库和YALE人脸库上进行了实验,结果表明改进的算法在识别率方面整体上好于LPP算法、DLPP算法、LMMC算法。     

基于自适应最近邻的局部保持投影算法

局部保持投影（LPP）是一种新的数据降维技术,但其本身是一种非监督学习算法,对于分类问题效果不是太好。基于自适应最近邻,结合LPP算法,提出了一种有监督的局部保持投影算法（ANNLPP）。该方法通过修改LPP算法中的权值矩阵,在降维的同时,增加了类别信息,是一种有监督学习算法。通过二维数据可视化和UMIST、ORL 人脸识别实验,表明该方法对于分类问题具有较好的降维效果。     

2DPCA+2DLDA和改进的LPP相结合的人脸识别算法

针对局部保持投影（LPP）算法无监督且只保留局部信息的特性,提出一种2DPCA+2DLDA和改进的LPP相结合的人脸识别算法。将训练集样本用2DPCA+2DLDA算法进行投影,保留数据整体空间信息和分类信息;引入类内、类间信息对LPP算法的关系矩阵进行优化,使LPP成为有监督的非线性学习方法,采用改进的LPP（ILPP）算法对训练集图像进行二次投影,提取样本的局部流形信息,并作为人脸识别信息进行鉴别。在Yale和ORL人脸库的测试结果验证了该方法的有效性。     

基于Gabor变换与改进SLLE的人脸表情识别

本文通过Gabor变换进行人脸表情图像的特征提取,并利用局部线性嵌入（LLE）系列算法进行数据降维操作.LLE算法是一种非线性降维算法,它可以使得降维后的数据保持原有的拓扑结构,在人脸表情识别中有广泛的应用.因为LLE算法没有考虑样本的类别信息,因此有了监督的局部线性嵌入（SLLE）算法.但是SLLE算法仅仅考虑了样本的类别信息却没有考虑到各种表情之间的关系,因此本文提出一种改进的SLLE算法,该算法认为中性表情是其他各种表情的中心.在JAFFE库上进行人脸表情识别实验结果表明,相比LLE算法和SLLE算法,该算法获得了更好的人脸表情识别率,是一种有效算法.     

优化局部保留投影及其在表情识别中的应用

提出一种基于优化局部保留投影(OLPP)的人脸表情识别方法。OLPP方法在降维过程中将图像结构信息融入LPP目标函数,通过降维处理,在获得图像结构信息的同时将投影最优化,从而能从原始表情数据中提取更多更具判决性的有效表情信息。JAFFE和CED- WYU(1.0)2个表情数据库的识别结果表明,基于OLPP的特征提取方法能有效提高识别率。     

Call for Papers The 6^th International Conference on Grid and Cooperative Computing

Recent years have seen rapid advances in various grid-related technologies, middleware, and applications. The GCC conference has become one of the largest scientific events worldwide in grid and cooperative computing. The 6th international conference on grid and cooperative computing (GCC2007) Sponsored by China Computer Federation (CCF),Institute of Computing Technology, Chinese Academy of Sciences (ICT) and Xinjiang University ,and in Cooperation with IEEE Computer Soceity ,is to be held from August 16 to 18, 2007 in Urumchi, Xinjiang, China.     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

法律信息库系统

本文分析了法律数据库的结构和特点，介绍了采用面向对象设计方法和超文本数据库技术开发和实现法律信息库系统将作为重要网络资源之一为不同用户进行法律咨询服务。     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

International Journal of Automation and Computing Table of Contents

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Information for authors

正SCIENCE CHINA Information Sciences(Sci China Inf Sci),cosponsored by the Chinese Academy of Sciences and the National Natural Science Foundation of China,and published by Science China Press,is committed to publishing highquality,original results of both basic and applied research in all areas of information sciences,including computer science and technology;systems science,control science and engineering(published in Issues with odd numbers);information and communication engineering;electronic science and technology(published in Issues with even numbers).Sci China Inf Sci is published monthly in both print and electronic forms.It is indexed by Academic OneFile,Astrophysics Data System(ADS),CSA,Cabells,Current Contents/Engineering,Computing and Technology,DBLP,Digital Mathematics Registry,Earthquake Engineering Abstracts,Engineering Index,Engineered Materials Abstracts,Gale,Google,INSPEC,Journal Citation Reports/Science Edition,Mathematical Reviews,OCLC,ProQuest,SCOPUS,Science Citation Index Expanded,Summon by Serial Solutions,VINITI,Zentralblatt MATH.     

Erratum to: Fast global kernel fuzzy c-means clustering algorithm for consonant/vowel segmentation of speech signal

正Erratum to:J Zhejiang Univ-Sci C(ComputElectron)2014 15(7):551-563doi:10.1631/jzus.C1300320The original version of this article unfortunately contained mistakes.Algorithm 6 should be as follows:Algorithm 6 FGKFCM-F clustering Input:(1)X={x_1,x_2,…,x_N},,x_iR~d,i=1,2,…,N,the dataset;(2)C,1C≤N,the number of clusters;(3)ε0,the stopping criterion;     

Journal of Zhejiang University-SCIENCE C (Computers & Electronics) Total contents

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A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.