基于可见光与红外数据融合的地形分类

针对单传感器地形分类效果不佳的问题,提出一种基于可见光与红外数据融合的地形分类方法。分别对可见光图像与红外图像提取特征,使用最近邻分类器和最小距离分类器进行后验概率估计,将来自不同特征、不同分类器的后验概率加权组合,通过散度计算得到特征的权重,实验确定分类器的权重,并在最小距离的后验概率估计中,使用马氏距离代替欧氏距离。实验结果表明,该方法对水泥路和沙子路的识别率分别达到99.33%和96.67%,均高于同类方法。     

支持向量机中引入后验概率的理论和方法研究

目前支持向量机解决模式识别问题是广大学者研究的热点，样本的后验概率在模式识别中至关重要，但是传统的支持向量机技术不提供后验概率，针对这一问题进行了3个方面的研究：（1）在给出样本点后验概率的基础上，将大规模优化问题分解成最大似然函数和最大分类边界两个规模优化问题；（2）给出了一种新的用后验概率修正最优分离超平面的方法，并且分析了该新方法的合理性；（3）用图像分类的3组实例说明本方法的有效性。     

基于概率扩散的多光谱遥感图像分类模型

为了提高遥感图像分类精度,提出了一种基于概率扩散模型的多光谱遥感图像自动分类技术。该方法首先通过比较模糊C均值分类器（FCM）的有效性函数来自动确定最优分类数目,然后利用基于形态学的各向异性概率扩散模型来调整中心像元隶属类别的概率,最后根据概率扩散的隶属概率向量图,并按照最大后验概率估计（MAP）对像元进行分类。由于各向异性扩散具有保边缘平滑的特点,因此,该概率扩散模型不仅能够有效地抑制同质区域内部“斑点”的产生。而且使得图像上重要的边缘特征得到了较好地保留。实验结果表明,该分类算法不仅能够避免分类图像中“斑点”噪声的影响,而且分类后的总体精度达到了77．76％和Kappa系数达到了0．7198,均优于未经过概率扩散的最大后验概率估计分类算法,因而具有一定的实用价值。     

基于高斯马尔可夫随机场的MAP估计在高斯噪声滤波中的应用

提出了基于高斯马尔可夫随机场(GMRF)的最大后验概率(MAP)估计在图像高斯噪声滤波中的应用方法。根据高斯噪声的先验特点，建立基于高斯马尔可夫随机场的退化图像恢复模型，从而将图像高斯噪声滤波问题转化为求解最大后验概率问题。先验概率可以根据马尔可夫随机场(MRF)和吉布斯分布(GD)的等效性, 用GD的概率估计。为了求解最大后验概率，第一，通过期望最大化(EM）算法对GMRF模型进行参数估计。第二，用共轭梯度法将目标函数最小化。实验结果表明，与其他滤波器（如高斯滤波、维纳滤波等）相比，本文所阐述的方法在滤除高斯噪声、保持图像原有结构方面效果更好。     

图像分类中的概率乘积核函数

Bag-of-Features(BOF)模型使用编码矢量的某一特定统计值表征图像,与基于传统核函数的支持向量机相配合完成对图像的分类,所带来的问题是会丢弃大量判别信息以及最优核函数的选择.因此,本文将硬分配编码矢量服从的多项分布、软分配编码矢量服从Dirichlet分布,并以此作为图像的内容描述,利用最大似然算法估计其中参数,然后使用概率乘积核函数计算图像两两之间的核函数,最后使用支持向量机对图像进行分类.公开图像数据集上的实验结果表明,本文算法取得了更优的分类性能.     

基于Parzen核估计的最大后验概率分类方法

从概率密度函数的角度出发,利用Parzen窗法估计总体样本的概率密度分布,将核方法和Parzen窗法引入最大后验概率方法中,提出一种基于Parzen核估计的最大后验概率的高性能多分类方法。该方法不需要考虑样本数据的具体分布情况,能够得到分类的可信度,给出推理的不确定性依据。在3个国际标准UCI数据集和3个人脸数据集上的实验结果表明,该方法具有较好的分类效果。     

后验概率改进Fisher向量的高性能图像检索算法

提出了一种高性能的图像检索方法,结合纹理分类和改进的Fisher向量实现图像检索。首先,将图像划分为互不重叠的图像子块,对每一图像子块依据纹理复杂度进行分类,对不同类别的图像子块提取不同的特征。其次,采用基于后验概率改进的Fisher向量进行特征编码,依据乘积量化和非对称距离计算方法,分段计算两特征向量之间的距离,快速求取相似度指标,据此进行图像检索。在Holidays数据集上进行图像检索的实验结果表明,该方法的查准率和召回率高,且耗费的查询时间少。     

基于迭代条件模型算法的图像超分辨率重建

图像超分辨重建是从一系列降质的低分辨率图像中获取高分辨率的图像。在最大后验概率算法基础上提出了一种基于马尔可夫随机场的超分辨率重建算法,并通过迭代条件模型实现超分辨率图像重建。实验结果表明,与传统的超分辨率重建算法相比,该算法是一种快速的计算最大后验概率的方法,采用Potts-Strauss模型作为图像的先验概率密度函数,经过五、六次的迭代就能达到理想的迭代效果,解决了最大后验概率算法计算量大的缺点,是一种高效的超分辨率重建算法,具有一定的实用价值。     

基于CSI改进的WKNN室内定位方法

传统的加权K最近邻算法中以距离作为权值,随着数据维度的增加,计算距离与真实距离的误差越来越大。针对这一问题,提出了一种贝叶斯后验概率的加权K最近邻算法——贝叶斯后验概率(Bayes ian Posterior Probability-Weighted K-Nearest Neighbor,BPP-WKNN)方法。首先用支持向量机算法分类选取测试点的近邻指纹点,其次计算测试点到每个近邻指纹点的贝叶斯后验概率,最后以贝叶斯后验概率的大小作为权值进行BPPWKNN算法定位。实验果表明:与基于曼哈顿距离的加权K最近邻算法和基于欧氏距离的加权K最近邻算法相比,改进后的BPP-WKNN定位算法的定位精确度和稳定性更高;利用支持向量机算法的稀疏性定位完成时间分别缩短了49%与42%。     

基于形状不变矩的t-混合模型的图像分类

提出一种基于物体形状不变矩特征,采用t-混合模型计算后验概率的统计形状分类的方法:采用Hu形状不变矩作为图像特征,用t-混合模型的EM迭代算法,估计出模型中未知参数,计算出形状类别的后验概率。实验结果表明,物体序列的形状不变矩具有良好的统计分布性质,按其后验概率分类的准确性较高。     

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.