基于IGA的最大模糊熵SAR图像双阈值分割

将基于免疫遗传算法的最大模糊熵双阈值方法应用到合成孔径雷达(SAR)图像分割中。此方法采用像素点邻域的平均灰度值分布所构成的直方图进行阈值的选取,有效地利用了图像的空间信息。为了快速搜索到最优参数,采用免疫遗传算法进行全局寻优。实验结果表明,该算法可以有效的分割出SAR图像中的目标和阴影,并且具有执行时间短、鲁棒性强的优点。     

基于改进的PCNN多目标图像分割算法

脉冲耦合神经网络(Pulse-coupled neural network,PCNN)可有效地用于图像分割.为获得满意分割效果,PCNN需要选取适当的参数,目前其参数往往通过反复试凑确定.针对这一问题,基于改进的PCNN模型,提出结合图像灰度直方图,以最大交叉熵函数作自适应遗传算法的适应度函数,采用自适应遗传算法搜索最优门限阈值函数的图像分割算法.实验结果表明,该算法可以有效地实现多目标图像分割,且分割效果优于多阈值Ostu算法.     

基于二维熵阈值的图像分割及其快速算法

阈值分割是图像分割技术中的一种重要方法,在图像处理和模式识别中广为应用.本文提出了一种基于二维熵阈值的图像分割快速算法.该算法能够有效地区分图像中边界、背景和物体三种区域,并使得传统二维阈值方法的复杂度从O(W2S2)降至O(W2/3S2/3).     

基于粒子群的图像分割

图像分割是图像处理的关键问题之一,为了能够快速有效地选取最优阈值进行图像分割,引入了粒子群算法（PSO）对阈值分割进行优化,提出基于PSO的最大熵图像分割,基于PSO的最大类间方差图像分割以及基于PSO的最小误差图像分割,并进行了分析和研究,可以得出该三种方法可以准确、快速地获取最优阈值进行图像分割。     

基于改进共生生物搜索算法的林火图像多阈值分割

针对传统多阈值分割方法计算复杂度随着阈值个数的增加而增长,以及对给定图像进行多阈值分割操作时效率很低等问题,提出了一种基于共生生物搜索（SOS）算法结合Kapur熵的多阈值分割方法。首先将精英反策略（EOBL）引入到SOS算法的共栖阶段,从而改善传统SOS算法处理复杂优化问题时易陷入局部最优的问题;然后引入莱维飞行策略扩大SOS算法的的搜索范围,增强其搜索轨迹的随机性;最终将得到的改进共生生物搜索（MSOS）算法应用到林火图像最佳阈值的选取问题上。实验结果表明,与粒子群优化算法、和声搜索算法、蝙蝠算法等对比算法相比,所提算法能更好地分割图像,在实际工程问题中具有一定的实用性和价值。     

引力搜索算法在多阈值图像分割中的应用研究

针对求解高维阈值图像分割计算复杂的问题,提出了一种基于引力搜索算法的多阈值图像分割方法,该方法以大津法（Otsu）设计为适应度函数,利用引力搜索算法快速搜索得到待分割图像的最优阈值,然后根据最优阈值进行图像分割。结合人眼视觉可知,引力搜索算法能够结合应用于图像分割,且能取得较好的效果。实验测试结果表明,该方法与布谷鸟算法、人工蜂群算法比较,引力搜索算法的收敛速度更快,寻优的阈值质量较高。     

基于改进模糊指数熵双阈值的3维人体图像分割优化算法

由于3维人体图像数据量大,导致分割耗时严重;人体组织间灰度差异相对较小,致使分割效果不佳。针对上述3维分割的两大难点问题,提出了改进的模糊指数熵函数来改善分割结果,并以加权免疫遗传算法（WIGA）对阈值进行优化搜索,从而提出了一种基于改进模糊指数熵双阈值的3维图像分割优化算法。真实人体胸部数据的分割结果表明,与传统熵函数及模糊隶属度函数相比,改进的最大模糊指数熵函数得到的阈值分割效果更好,且提出的WIGA算法的耗时仅为传统穷尽搜索法的14%。在与简单遗传算法（SGA）和免疫遗传算法（IGA）耗时基本相同的情况下,100次阈值计算结果表明,本文算法更加精确、稳定。     

快速最大熵多阈值图像分割算法

阈值方法是一种重要的图像分割方法,在图像分割中得到了广泛的应用。最大熵算法虽然是图像分割阈值法中较好的方法之一,但是,由于传统的最大熵算法通常用穷举法求解,使得处理多阈值问题时运算速度太慢,难以满足应用需求。为了快速有效地确定阈值,提出一种改进的最大熵算法。通过递推公式将穷举法求解过程中需要重复计算的变量,预先计算后存入二维表备用,使整体计算量减少了一个数量级。通过对测试图像的分割实验,表明该算法与传统的最大熵算法相比运算速度有非常显著的提高,能够满足一般的应用需求。     

基于混沌遗传算法的二维最大熵图像分割

研究了基于二维最大熵的图像分割算法,针对基于二维最大熵的图像分割算法存在的计算复杂度高、计算时间长等问题,提出了一种基于混沌遗传算法的二维最大熵算法。该方法利用类似载波的方法将混沌序列映射至双阈值的二维空间,之后利用混沌遗传算法搜索最佳阈值进行图像分割。实验结果表明,由于该方法考虑了点灰度和区域灰度均值,且采用了有效的全局搜索算法,所以不仅得到了令人满意的分割效果,而且大大提高了计算速度,是一种实用有效的图像分割方法。     

一种改进的快速医学图像分割方法*

为了确定医学图像的最佳灰度直方图熵,提出了一种基于改进演化算法的快速分割方法,能够自适应调整交叉和变异概率,既保证了种群的多样性,又克服了传统演化算法局部最优、收敛过快的缺点。搜索到的最佳阈值不仅比传统演化算法稳定性好,还有效地缩短了搜索时间,快速地实现了医学图像分割,而且分割后的图像可读性强。实验结果表明,该方法速度快、分割效果好。     

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.