一种多功能网络监控与防御平台设计与实现

本文提出了一种多功能网络监控与防御系统。文中根据网络自身的结构,从骨干层、汇聚层、接入层三个层次分析,采用三层设计模式,它们相互独立又相互协作,共同构成高性能、多层次、多功能综合解决方案。形成深度防御体系,最大限度地保护企业和组织的网络安全。     

Speed up kernel discriminant analysis

Linear discriminant analysis (LDA) has been a popular method for dimensionality reduction, which preserves class separability. The projection vectors are commonly obtained by maximizing the between-class covariance and simultaneously minimizing the within-class covariance. LDA can be performed either in the original input space or in the reproducing kernel Hilbert space (RKHS) into which data points are mapped, which leads to kernel discriminant analysis (KDA). When the data are highly nonlinear distributed, KDA can achieve better performance than LDA. However, computing the projective functions in KDA involves eigen-decomposition of kernel matrix, which is very expensive when a large number of training samples exist. In this paper, we present a new algorithm for kernel discriminant analysis, called Spectral Regression Kernel Discriminant Analysis (SRKDA). By using spectral graph analysis, SRKDA casts discriminant analysis into a regression framework, which facilitates both efficient computation and the use of regularization techniques. Specifically, SRKDA only needs to solve a set of regularized regression problems, and there is no eigenvector computation involved, which is a huge save of computational cost. The new formulation makes it very easy to develop incremental version of the algorithm, which can fully utilize the computational results of the existing training samples. Moreover, it is easy to produce sparse projections (Sparse KDA) with a L ₁-norm regularizer. Extensive experiments on spoken letter, handwritten digit image and face image data demonstrate the effectiveness and efficiency of the proposed algorithm.     

Algorithms for computing the optimal transitive approximation of a proximity relation

Three ways for generating the optimal transitive approximations or a suboptimal transitive approximation are given in this paper. The first one can obtain all the optimal transitive approximations for any proximity relation. However, trying to find all the optimal transitive approximations can be very expensive. The second one gives a method to obtain a suboptimal transitive approximation which can frequently generate an optimal transitive approximation. Furthermore, starting from the transitive closure the third method is proposed which can obtain a locally optimal transitive approximation. Finally, numerical experiments are carried out to show the abilities of these algorithms and compare them to other existing approximation algorithms.     

WSN中的质心定位算法研究

节点定位是无线传感器网络（WSN）中的关键技术之一。通过对质心定位算法的分析,提出了一种改进的质心算法（CSA）——以距离未知节点最近的锚节点为基准找出差异性最大的估计点,采用三角质心和多边质心计算估计点坐标提高定位精度。通过MATLAB仿真表明算法是有效可行的。     

一种基于访问图优化的缓存替换算法

针对目前数据库缓存替换算法替换策略单一,无法预测即将执行SQL语句的不足,提出了一种基于访问图优先的缓存替换算法CG-ABR(Call Graph Optimizing Adaptive Buffer Replacement).该算法通过查询优化器获得当前数据访问类型,自动调整缓存替换算法以适应实时变化的访问类型,改进了缓存访问的管理方法,并根据SQL语句的应用逻辑执行顺序来构造访问图Call Graph,基于Call Graph以预测将要执行的SQL语句,替换出未来不会被访问的页面缓存,以达到缓存空间优化的目的.实验结果与分析表明,CG-ABR算法是有效的,对实时变化的访问类型有较好的缓存命中率,具有良好的应用价值.     

一种改进的Chord网络模型

经典的Chord模型中为维护Chord环路由信息而周期性执行的Stabilize操作产生了大量的消息转发。提出一种改进的Chord模型,通过使用优化的双向Finger表,使得只在节点加入或离开时才进行路由更新,降低了消息转发的开销,同时优化了路由定位算法。     

基于软件程序员课程开发的研究

软件程序员的培养是高职软件技术专业的主要培养对象。通过分析IT企业对程序员的需求及程序员必备的素质,结合软件程序员应有的核心能力,建立和完善面向高职院校的软件技术专业的人才培养的课程体系,为适应市场需求的程序员的培养进行了研究与实践。     

基于蚁群算法的网格资源发现模型研究

本文通过对传统的网格资源发现存在的问题进行分析,针对其不足,引入蚁群算法,提出基于蚁群算法的网格资源发现模型（AA_GRRM）,设计并分析AA_GRRM的体系结构,并对其关键模块分析设计,以提高网格资源发现效率。     

Interactive visualization of hyperspectral images of historical documents

This paper presents an interactive visualization tool to study and analyze hyperspectral images (HSI) of historical documents. This work is part of a collaborative effort with the Nationaal Archief of the Netherlands (NAN) and Art Innovation, a manufacturer of hyperspectral imaging hardware designed for old and fragile documents. The NAN is actively capturing HSI of historical documents for use in a variety of tasks related to the analysis and management of archival collections, from ink and paper analysis to monitoring the effects of environmental aging. To assist their work, we have developed a comprehensive visualization tool that offers an assortment of visualization and analysis methods, including interactive spectral selection, spectral similarity analysis, time-varying data analysis and visualization, and selective spectral band fusion. This paper describes our visualization software and how it is used to facilitate the tasks needed by our collaborators. Evaluation feedback from our collaborators on how this tool benefits their work is included.     

基于WEB嵌入式自适应智能控制系统的研究与开发

提出一种基于WEB嵌入式自适应智能控制系统设计方案,提供了各组成模块软硬件的详细设计与具体实现;系统采用主流的S3C2410作为处理器,通过I2C总线实现各硬部件的连接;开发的嵌入式WEB服务器模块,使得用户能够对温度传感器读数进行互联网远程监测和多路数字、模拟量输出智能控制;并且神经网络模块能够自适应地学习和控制温度读数与制冷设备输出数之间的关系。实验结果显示改进后的Hopfield算法的收敛性和记忆性得到了提高,并使该系统具有较大的应用价值。