自适应邻域选择的数据可分性降维方法

针对现有基于流形学习的降维方法对局部邻域大小选择的敏感性,且降至低维后的数据不具有很好的可分性,提出一种自适应邻域选择的数据可分性降维方法。该方法通过估计数据的本征维度和局部切方向来自适应地选择每一样本点的邻域大小;同时,使用映射数据时的聚类信息来汇聚相似的样本点,保证降维后的数据具有良好的可分性,使之实现更好的降维效果。实验结果表明,在人工生成的数据集上,新方法获得了较好的嵌入结果;并且在人脸的可视化分类和图像检索中得到了期望的结果。     

基于双重局部保持的不完整多视角嵌入学习方法

现有的多视角降维方法多数假设数据是完整的,但该假设在实际应用中难以实现。为解决不完整多视角数据降维问题,提出一种新的不完整多视角嵌入学习方法。基于多视角数据的一致性与同一视角下样本间的线性相关性学习一组重构系数,对缺失样本进行线性重构,通过学习所有视角的公共低维嵌入,保持原始空间的局部几何结构。在此基础上,设计一种惩罚参数来度量重构样本的可靠度,从而权衡缺失样本对学习结果的负面影响。实验结果表明,该方法在Yale、ORL和COIL-20数据集上NMI值分别达到65.63%、73.23%和78.27%,较MVL-IV算法分别提升8.37%、16.71%和20.24%。     

面向高光谱分类的局部几何稀疏保持嵌入EI北大核心CSCD

大量维数约简(Dimensionality reducion, DR)方法表明保持数据间稀疏特性的同时,确保几何结构的保持能更有效提取出具有鉴别性的特征,为此本文提出一种联合局部几何近邻结构和局部稀疏流形的维数约简方法.该方法首先通过局部线性嵌入方法重构每个样本以保持数据的局部线性关系,同时计算样本邻域内的局部稀疏流形结构,在此基础上通过图嵌入框架保持数据的局部几何近邻结构和稀疏结构,最后在低维嵌入空间中使类内数据尽可能聚集,提取低维鉴别特征,从而提升地物分类性能.在Indian Pines和PaviaU高光谱数据集上的实验结果表明,本文方法相较于传统维数约简方法能明显提高地物的分类性能,总体分类可达到83.02%和91.20%,有利于实际应用.     

张量图像上的正交张量监督近邻保持嵌入

正交张量近邻保持嵌入是一种有效的张量图像的降维工具,但仍存在监督判别信息不足的问题.为此提出正交张量监督近邻保持嵌入OTSNPE(OrthogonalTensorSupervisedNeighborhoodPreservingEmbedding)降维算法.该算法首先将二维图像看成二阶张量空间的点;然后在同类样本中选择近邻并进行线性重构;最后通过特征保持提取投影方向.投影后的特征既能有效地保持张量图像像点之间的空间关系,又能较好地保持蕴含在张量图像之间的类内局部重构关系和近邻关系.在AR和YaleB人脸数据集上的实验验证了该算法的有效性.     

基于特征子空间邻域的局部保持流形学习算法*

局部保持流形学习算法通过保持局部邻域特性来挖掘隐藏在高维数据中的内在流形结构。然而,对于缺乏足够训练样本的高维数据集,或者高维数据集存在非线性结构和高维数据特征中存在冗余、干扰特征,使得在原特征空间中利用欧式距离定义的邻域关系并不能真实反映数据的内在流形结构,从而影响算法的性能。提出利用正约束寻找特征子空间的方法,使得在此子空间中更多的同类样本紧聚,并进一步在该子空间中构建邻域关系来挖掘高维数据的内在流形,形成基于特征子空间邻域特性的局部保持流形学习算法(NFS-LPP和NFS-NPE)。它们在一定程度上克服了高维小样本数据集难以正确挖掘内在流形结构的问题,在Yale和ORL人脸库上的分类和聚类实验验证了其有效性。     

基于自适应稀疏邻域重构的无监督主动学习算法

在很多信息处理任务中,人们容易获得大量的无标签样本,但对样本进行标注是非常费时和费力的。作为机器学习领域中一种重要的学习方法,主动学习通过选择最有信息量的样本进行标注,减少了人工标注的代价。然而,现有的大多数主动学习算法都是基于分类器的监督学习方法,这类算法并不适用于无任何标签信息的样本选择。针对这个问题,借鉴最优实验设计的算法思想,结合自适应稀疏邻域重构理论,提出基于自适应稀疏邻域重构的主动学习算法。该算法可以根据数据集各区域的不同分布自适应地选择邻域规模,同步完成邻域点的搜寻和重构系数的计算,能在无任何标签信息的情况下较好地选择最能代表样本集分布结构的样本。基于人工合成数据集和真实数据集的实验表明,在同等标注代价下,基于自适应稀疏邻域重构的主动学习算法在分类精度和鲁棒性上具有较高的性能。     

基于局部线性嵌入的最大散度矩阵算法

提出一种基于局部线性嵌入的最大散度矩阵算法——FSLLE。引入线性映射解决局部线性嵌入算法的样本外学习问题,通过自适应动态地确定局部线性空间邻域参数,最大化地融合样本数据的类别信息和局部结构信息矩阵,以获取髙维数据的最佳分类低维子空间。在JAFFE人脸表情库对该算法进行测试,结果表明,FSLLE算法能根据流形结构动态地确定局部邻域的大小,具有较好的表情识别率。     

保邻域结构的拉普拉斯特征映射延拓

针对拉普拉斯特征映射的新增样本点延拓问题,提出一种基于邻域信息的新增样本点延拓方法：假设新增样本点与邻域保持线性关系,使用稀疏编码方法求解线性系数,再由这些系数在低维空间重构得到新增样本点的低维表示。使用1-NN分类算法对新增样本点的低维表示进行分类,实验结果表明,与基于全局信息的稀疏编码重构方法相比,基于邻域信息的稀疏编码重构算法使用更少的时间取得更高的分类准确率,说明该方法的有效性。此外,该方法可以推广至其他非线性降维方法的新增样本点问题。     

基于自适应近邻参数的局部线性嵌入

局部线性嵌入算法是一种有效的非线性降维方法。文中提出一种自适应的局部线性嵌入方法。该方法通过分析数据集中任意样本所在局部区域的线性重构误差,确定该局部区域的近似线性块,然后根据位于此局部线性块上的样本来选择局部线性嵌入的近邻参数。实验结果表明,在不同的数据集上,采用多个评价标准,自适应的局部线性嵌入方法相比普通的局部线性嵌入方法,取得更好的结果。     

改进的有监督的局部线性嵌入算法及实验演示

流形学习方法中的LLE算法可以将高维数据在保持局部邻域结构的条件下降维到低维流形子空间中．并得到与原样本集具有相似局部结构的嵌入向量集合。LLE算法在数据降维处理过程中没有考虑样本的分类信息。针对这些问题进行研究,提出改进的有监督的局部线性嵌人算法（MSLLE）,并利用MatLab对该改进算法的实现效果同LLE进行实验演示比较。通过实验演示表明,MSLLE算法较LLE算法可以有利于保持数据点本身内部结构。     

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.     

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.     

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.     

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.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and     

Editorial:Brain-machine interface(BMI) and cyborg intelligence

正Brain-machine interfaces(BMIs)aim at building a direct communication pathway between the brain and an external device,and represent an area of research where significant progress has been made during the past decade.Based on BMIs,mind information can be read out by neural signals to control     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate     

SCIENCE CHINA Information Sciences SUBJECT INDEX TO VOLUME 57(2014)

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