DDOS(分布式拒绝服务)研究与探讨

由于目前网络安全问题的日趋严重, ＤＤＯＳ（ Ｄｉｓｔｒｉｂｕｔｅｄ Ｄｅｎｉａｌ ｏｆ Ｓｅｒｖｉｃｅ,分布式拒绝服务攻击）的攻击手段严重威胁 Ｉｎｔｅｒｎｅｔ的安全。文章详细地介绍了什么是 ＤＤＯＳ及其造成的危害,Ｗ理论上分析了其体系结构和运作情况,并实际列举了一些著名的ＤＤＯＳ 工具及其特点,尝试提出有关ＤＤＯＳ的攻击检测规则和相关的检测工具。     

基于负载分布的路由算法(LPR)

给出基于路由分布的路由算法,将有效带宽分散于候选路由集中,以匹配到达的虚电路请求服务质量的分布特点。这一方案与传统的负载均衡化和负载打包相比,具有高效的负载公布,较好地支持了应用的实时服务质量。     

实时高性能CORBA的体系框架研究

CommonObjectRequestBrokerArchitecture（CORBA）标准是分布对象管理系统的一个重要标准,但现有的CORBA标准不支持实时应用系统开发,实时应用对CORBA的发展提出了新的需求。文章立足于现有的CORBA标准做了进一步分析,讨论了传统的CORBA标准对实时应用支持的不足之处,并提出实时务性能CORBA应该具有的特征及其对传统CORBA标准的改进之处。     

ITS9000 MX测试程序库的研制

本文介绍了ITS9000MX测试程序库的设计与实现,提出了基于ATPG的测试程序设计方法。     

Internet防火墙及其Linux实现

该文阐述了Ｉｎｔｅｒｎｅｔ防火墙技术的原理,介绍了若干种防火墙的体系结构,给出了Ｌｉｎｕｘ操作系统下的防火墙软件及其使用实例。     

鲁棒的多体印刷英文识别系统的实现

文章讨论了设计一个实用的多体英文识别系统中解决的主要问题。该系统能识别多达260种字体,包括斜体和黑体等字体,对训练集的识别率达到99%,对实际文本测试的错误率比TH-OCR2000低56%。文章详细阐述了文本行字切分,特征提取和分类器设计,以及后处理所使用的常用技术,对各种技术的特点进行了分析和比较,并提出了一些新的技术。文章对于OCR系统的设计具有一定的指导意义。     

专家系统软件开发生存期模型分析

文章根据专家系统类软件的特点,在分析已有软件开发生存期模型优缺点基础上,提出了一种适用于专家系统的开发模型,它以瀑布模型为基本框架,在不同开发阶段引入了快速原型开发模型和面向对象技术以克服瀑布模型的缺点。实践表明这种开发模型是可行的。     

安全电子邮件系统的设计与实现

随着电子邮件越来越广泛的应用,电子邮件的安全性问题也越显突出,本文提出了一种提供数据加密和数字签名的安全电子邮件系统,并详细讨论了其设计与实现技术.     

A recurrent neural fuzzy network for word boundary detection invariable noise-level environments

This paper discusses the problem of automatic word boundary detection in the presence of variable-level background noise. Commonly used robust word boundary detection algorithms always assume that the background noise level is fixed. In fact, the background noise level may vary during the procedure of recording. This is the major reason that most robust word boundary detection algorithms cannot work well in the condition of variable background noise level. In order to solve this problem, we first propose a refined time-frequency (RTF) parameter for extracting both the time and frequency features of noisy speech signals. The RTF parameter extends the (time-frequency) TF parameter proposed by Junqua et al. from single band to multiband spectrum analysis, where the frequency bands help to make the distinction between speech signal and noise clear. The RTF parameter can extract useful frequency information. Based on this RTF parameter, we further propose a new word boundary detection algorithm by using a recurrent self-organizing neural fuzzy inference network (RSONFIN). Since RSONPIN can process the temporal relations, the proposed RTF-based RSONFIN algorithm can find the variation of the background noise level and detect correct word boundaries in the condition of variable background noise level. As compared to normal neural networks, the RSONFIN can always find itself an economic network size with high-learning speed. Due to the self-learning ability of RSONFIN, this RTF-based RSONFIN algorithm avoids the need for empirically determining ambiguous decision rules in normal word boundary detection algorithms. Experimental results show that this new algorithm achieves higher recognition rate than the TF-based algorithm which has been shown to outperform several commonly used word boundary detection algorithms by about 12% in variable background noise level condition, It also reduces the recognition error rate due to endpoint detection to about 23%, compared to an average of 47% obtained by the TF-based algorithm in the same condition.