工作流管理系统的过程定义:活动-条件法

本文提出一种有足够强的建模能力、便于用户理解与计算机实现的过程定义方法 :活动 -条件法 .以及该方法的数据结构表示和一些重要算法     

结合高阶微分的非局部均值图像去噪算法

非局部均值算法是近年来去噪效果优秀并且引起广泛研究的算法, 但是该算法对于弱纹理, 弱边缘不能很好地保持。在非局部均值算法的基础上, 利用高阶微分可以很好地反映图像的弱边界和振荡等特征的特点, 改进了非局部均值算法。改进的算法能够在去噪的同时保留更多的细节、纹理和弱边缘。     

SCAN, an exploratory program for preliminary analysis of bioassay and immunoassay data

We describe the program SCAN which has been designed for use in conjunction with analysis of variance of immunoassay or bioassay data and which may also be used with more general one-way analysis of variance. Data within treatment groups are examined for outliers and normality of distribution. Overall statistics for normality and homogeneity of variance are also computed. Contributions of individual groups to these statistics are tabulated to permit the detection of aberrant groups. Means and variances are available in a form which facilitates detection of any response error relationship.     

基于主动学习的微博聚类分析

K Means聚类算法由于无法准确确定初始化聚类中心,容易造成 聚类结果准确率低下。对微博数据聚类时,可能会导致无法正确反映兴趣热点。本文 设计了基于主动学习的聚类算法,在确定初始聚类中心过程中应用Min Max主动学习策略, 使 得算法每次在很小数量的查询后都会提供数据点供用户进行初始中心点确认,并在K Means算 法中重新计算聚类中心时设置其权重值,从而减少迭代的数量,提高聚类结果的准确 率,并将这一算法运用于微博聚类分析,得出微博热门话题。     

一种用于数据挖掘的差异粒子群算法

聚类分析是数据挖掘的一种重要方法。本文受鸟群聚集行为的启发,提出了一种新的聚类方法——差异粒子群聚类算法(DPSC)。DPSC算法将样本数据转化为具有行为能力的粒子,通过促使不同类别的粒子相互分离,而同类的粒子高度聚集,最终在粒子的运动中涌现出整个数据群体的内部组织结构,从而完成对样本数据的聚类。在三个标准数据集和六个人工复杂数据集上同K-Means、PSO和PSO+K-Means算法进行了比较,结果显示DPSC算法的聚类性能更优异。     

区间直觉梯形模糊几何Heronian平均算子及应用

针对决策信息为区间直觉梯形模糊数（IVITFN）且属性间存在相互关联的多属性群决策（MAGDM）问题,提出了一种区间直觉梯形模糊几何加权Heronian平均算子（IVITFGWHM）的决策方法。基于IVITFN的运算法则和几何Heronian平均（GHM）算子,定义了IVITFGHM算子和IVITFGWHM算子。研究了这些算子的一些性质,建立基于IVITFGWHM算子的MAGDM模型,结合排序方法进行决策。通过MAGDM算例验证了该算子的有效性与可行性。     

轮胎成型机计算机监控系统软件设计

本文介绍了轮胎成型机计算机控制系统的组成,工作原理以及工艺程序编译软件和监控软件的编制原理及方法.     

TCP连接性能的FCM聚类分析

分析了模糊聚类中的FCM(Fuzzy C-Means)算法,利用该算法对一个TCP连接日志的抽样数据进行聚类,利用聚类中心对任选的两组数据集进行分类,并对聚类结果进行了分析。     

基于PVLAN技术的防ARP欺骗技术探讨

随着网络用户对安全关注度的提高,以太网用户群的安全性因其使用的网络协议存在缺陷而受到了极大影响.对以太网使用的ARP协议原理进行了研究,由此提出了一种采用PVLAN技术实现对ARP欺骗进行防护的措施.     

区间直觉模糊几何Bonferroni平均算子及其应用

研究了决策信息为区间直觉模糊数（IVIFN）且属性间存在相互关联的多属性群决策（MAGDM）问题,提出一种基于区间直觉模糊几何加权Bonferroni平均（IVIFGWBM）算子的决策方法。介绍了IVIFN的概念和运算法则,基于这些运算法则和几何Bonferroni平均（GBM）算子,定义了区间直觉模糊几何Bonferroni平均（IVIFGBM）算子和IVIFGWBM算子。研究了这些算子的一些性质,建立基于IVIFGWBM算子的MAGDM模型,结合排序方法进行决策。将该方法应用在一个MAGDM问题中,结果表明了该方法的有效性与可行性。     

面向对象的可扩充向量与矩阵库

本文介绍了一种可扩充、可移植的向量与矩阵库，它利用面向对象语言Ｃ＋＋开发，适用于不同数据类型的向量和矩阵运算。文章对该库的基本结构、主要特征及扩充途径作了简要描述，并用实例演示了基于该库的应用程序编写方法。     

Enhancement of historical printed document images by combining Total Variation regularization and Non-local Means filtering

This paper proposes a novel method for document enhancement which combines two recent powerful noise-reduction steps. The first step is based on the Total Variation framework. It flattens background grey-levels and produces an intermediate image where background noise is considerably reduced. This image is used as a mask to produce an image with a cleaner background while keeping character details. The second step is applied to the cleaner image and consists of a filter based on Non-local Means: character edges are smoothed by searching for similar patch images in pixel neighborhoods. The document images to be enhanced are real historical printed documents from several periods which include several defects in their background and on character edges. These defects result from scanning, paper aging and bleed-through. The proposed method enhances document images by combining the Total Variation and the Non-local Means techniques in order to improve OCR recognition. The method is shown to be more powerful than when these techniques are used alone and than other enhancement methods.     

An automated hybrid approach using clustering and nature inspired optimization technique for improved tumor and tissue segmentation in magnetic resonance brain images

In the domain of human brain image analysis, identification of tumor region and segmentation of tissue structures tend to be a challenging task. Automated segmentation of Magnetic Resonance (MR) brain images would be of great assistance to radiologist, as they minimize the complication evolved due to human interface and offer quicker segmentation results. Automated algorithms offer minimal time duration and lesser manual intervention to a radiologist during clinical diagnosis. Moreover, larger volumes of patient data could be assessed with the aid of an automated algorithm and one such algorithm is proposed through this research to identify the tumor region bounded between normal tissue regions and edema portions. The proposed algorithm offers a better support to a radiologist in the process of diagnosing the pathologies, since; it utilizes both optimization and clustering techniques. Bacteria Foraging Optimization (BFO) and Modified Fuzzy K − Means algorithm (MFKM) are the optimization and clustering techniques used to render efficient MR brain image analysis. The proposed combinational algorithm is compared with Particle Swarm Optimization based Fuzzy C − Means algorithm (PSO based FCM), Modified Fuzzy K − Means (MFKM) and conventional FCM algorithm. The suggested methodology is evaluated using the comparison parameters such as sensitivity, Specificity, Jaccard Tanimoto Co − efficient Index (TC) and Dice Overlap Index (DOI), computational time and memory requirement. The algorithm proposed through this paper has produced appreciable values of sensitivity and specificity, which are 97.14% and 93.94%, respectively. Finally, it is found that the proposed BFO based MFKM algorithm offers better MR brain image segmentation and provides extensive support to radiologists.     

利用H∞范数的最优异步自学习控制频域方法

利用H∞范数对异步自学习控制系统进行了深入的研究.基于用H∞语言重新改写的问 题提法,给出了四个引理与一个定理的严格证明,得到了渐近稳定时控制器存在的一个充分条 件,并给出了计算实例.     

A formal application model for code and test generation

The considered model is used in manual development of application specifications and is based on the Letichevsky theory of basic protocols and a respective symbolic verification tools. Means to limit the behavioral characteristics of the model still matching the source requirements are discussed. If the model is verified successfully, the executable code of the application and the respective test code are generated from the model. The technique of using the developed model is described.     

浅析校园网综合布线系统设计

目的:该文主要讨论校园网综合布线系统。方法:先了解综合布线系统的定义及组成,并详细分析综合布线系统的结构和设计原则。结果:基于校园网综合布线系统的基本原则,建立一套完备、全面的布线设计方案并提出详细的设计流程。结论:该文通过对校园网综合布线系统设计方案的讨论,使得我们对综合布线系统有一个全面的了解,并提出其在校园网建设中的重要作用。     

机电一体化培训和教育中的电子移动学习课件开发(英文)

Knowledge is essential for the competitiveness of individuals as well as organizations.Thus the application of the latest methodologies and technologies are utilized to support knowledge acquisition,warehousing,distribution,and transfer.Means and methods of web 2.0 are useful to support this procedure.Especially,highly complex and very dynamic knowledge domains have to be accessible and applicable in the framework of learning network communities,including the stakeholders of training and education.Mechatronics for example is such an interdisciplinary,dynamic field of research and application.Based on intelligence,software,and hardware it is requiring special approaches for developing a courseware based learning and knowledge transfer environment.After defining the specifics of mechatronics education and postgraduate training in the context of e-education,the concepts of the development and utilization of mechatronic courseware can be deduced from e-learning 2.0 and mobile learning facilities,possibilities,and abilities.Mechatronic courseware will be developed by using authoring software and embedding the material into learning management systems with respect to general methods and rules of modern system and software development.As an example,the courseware is used for vocational training and further education especially in cooperation networks of educational institutions and SME.     

神经正切核K‑Means聚类

针对K-Means聚类算法利用均值更新聚类中心,导致聚类结果受样本分布影响的问题,提出了神经正切核K-Means聚类算法（NTKKM）。首先通过神经正切核（NTK）将输入空间的数据映射到高维特征空间,然后在高维特征空间中进行K-Means聚类,并采用兼顾簇间与簇内距离的方法更新聚类中心,最后得到聚类结果。在car和breast-tissue数据集上,对NTKKM聚类算法的准确率、调整兰德系数（ARI）及FM指数这3个评价指标进行统计。实验结果表明,NTKKM聚类算法的聚类效果以及稳定性均优于K?Means聚类算法和高斯核K-Means聚类算法。NTKKM聚类算法与传统的K-Means聚类算法相比,准确率分别提升了14.9%和9.4%,ARI分别提升了9.7%和18.0%,FM指数分别提升了12.0%和12.0%,验证了NTKKM聚类算法良好的聚类性能。     

办公自动化网络系统安全设计分析

目的:该文主要讨论办公自动化网络系统的安全设计分析。方法:先了解办公自动化的定义及组成,并通过分析威胁办公自动化安全的各因素找到最合理的解决方法。结果基于网络安全设计的基本原则,建立一套安全措施,对办公自动化系统进行全面彻底的保护。结论:该文通过对办公自动化系统安全设计方案的讨论,使得我们对办公自动化实现Internet上的安全有一个全面的了解,并提出其不足之处并加以完善。     

彩色多聚焦图像融合演示平台

针对多聚焦图像融合演示和源图像获取手段单一的问题,应用Visual C++和Matlab混合编程的方法为彩色多聚焦图像融合设计了一个演示平台。该平台增加了多聚焦图像素材的获取途径和融合算法效果的演示手段,并且采用了基于小波变换的彩色多聚焦图像改进融合算法,充分利用到区域相关性和高频方向特性。实验演示结果表明,演示平台操作简单方便,融合演示效果较好,具有较强的实用性。