VoIP系统SIP—QoS代理服务器设计方案

文中以解决VoIP系统的语音质量问题为目标,深入研究了基于SIP的VoIP系统QoS控制技术。参照IMS网络结构,考虑通信业务的QoS要求,研究以SIP为信令协议的VoIP系统如何进行呼叫控制、资源预留和策略决策,融人到SIP用户代理、SIP代理服务器,提出了一个具有QoS能力的SIP代理服务器的设计方案,增加了策略决策功能（PDF）等网络实体,支持QoS的能力得到增强。文中详细讨论了支持QoS的siP网络的增强能力,具有QoS能力的SIP代理服务器的功能结构,QoS功能模块,以及QoS资源授权和预留决策过程。     

基于阈值的彩色目标图像的提取与测量

幅彩色图像提供了很多不同的信息,但是为了更好地研究我们所感兴趣的目标图像,需要将它们以图像斑块的形式单独提取出来,从而排除研究所不需要的干扰信息和背景信息,使得研究上作更容易、更准确。通过合理的选取阈值及提取关系,如大于等于阈值、小于等于阈值等,可从图像中提取研究所关心的目标图像及其边界,并测量所提取的目标图像的总面积及目标图像各斑块的面积和周长,由此可研究其分布规律与分布密度;并可在测量的基础上对目标图像斑块进行统计,统计出在一定面积或周长范围内目标图像斑块的个数,为相应的研究提供定量分析。     

数字签名在教务系统中的应用研究

数字签名技术是一项重要的信息安全技术,它采用特定密码算法对发送数据进行加密处理,生成一段附加信息,随原文一起发送,接收方通过对附加信息进行验证判断原文真。本文针对高职院校教学系统特点,探讨了数字签名在教学管理系统中的应用。     

基于小波阈值的sEMG信号消噪方法研究

在表面肌电（sEMG）信号采集过程中,不可避免的会出现噪声,特别是人体运动时,肌肉动态收缩,采集的结果含噪就会更多。针对含噪情况,提出基于小波阈值的sEMG信号消噪方法。通过选择肌电信号的采集位置,在采用高精度的肌电采集系统的基础上,采集正常行走过程中胫骨前肌的sEMG信号,利用matlab小波工具箱,用dbN小波函数进行分解后,用detcoef函数提取不同尺度的细节系数,将与噪声相关的细节系数进行强制阈值消噪,对信号相关的细节系数用minimaxi阈值规则进行软阈值消噪,并与分层阚值得到的降噪信号进行比较,分层阈值得到的降噪信号过于光滑,降噪后的信号能量保留成份仅为46．48％,失去了原信号本身的一些信息。而采用软闯值消噪,不仅较好的去除了噪声,而且与原信号保持了很好的相似性,能量保留成份达到86．38％,说明比分层阈值具有更好的消噪效果。     

一种基于身份的N-R消息恢复盲签名方案

消息恢复签名方案因其具有消息恢复能力而具有特殊的意义,本文在基于身份的公钥密码体制的基础上,提出了一种基于身份的消息恢复盲签名方案。本文最后证明了该方案的正确性,并进行了效率和安全性分析。     

基于值域二次哈希方法的布鲁姆过滤器

本文针对扩展式布鲁姆过滤器(EBF)内存消耗过大,提出一种基于值域哈希二次过滤的布鲁姆过滤器数据结构(VHBF)和相关算法,VHBF通过在布鲁姆过滤器中对集合中的每个特征进行k次哈希,并将此k次哈希值转化为相应特征的镜像特征。然后对此镜像进行二次过滤运算,运算后的结果保存在另一布鲁姆过滤器中。在对特征进行检索时,由于无需保存特征本身,因而空间效率比EBF更高。实验表明,VHBF的假阳性误判率的比扩展型布鲁姆过滤器(EBF)低,而VHBF内存消耗也低于EBF。     

New (t, n) threshold directed signature scheme with provable security

Directed signature scheme allows only a designated verifier to check the validity of the signature issued to him; and at the time of trouble or if necessary, any third party can verify the signature with the help of the signer or the designated verifier as well. Due to its merits, directed signature scheme is widely used in situations where the receiver’s privacy should be protected. Threshold directed signature is an extension of the standard directed signature, in which several signers may be required to cooperatively sign messages for sharing the responsibility and authority. To the best of our knowledge, threshold directed signature has not been well studied till now. Therefore, in this paper, we would like to formalize the threshold directed signature and its security model, then present a new (t, n) threshold directed signature scheme from bilinear pairings and use the techniques from provable security to analyze its security.     

A Convertible Multi-Authenticated Encryption scheme for group communications

Recently, Wu et al. proposed a Convertible Multi-Authenticated Encryption (CMAE) scheme, which allows a signing group with multiple signers to generate a multi-authenticated ciphertext signature on the chosen message so that only a designated verifier can recover and verify the message. In case of later dispute, the verifier can convert the multi-authenticated ciphertext signature into an ordinary one that can be verified by anyone. In this study, a CMAE scheme for group communications is proposed. This is presented by first reviewing the concepts of group-oriented encryption schemes and the merits of Wu et al.’s scheme. This shows that not only can a multi-authenticated ciphertext signature be generated by a signing group, but also the message can be recovered and verified by a verifying group with multiple verifiers. The security of the proposed scheme is based solely on the DDH problem, which provides higher security confidence than using the CDH problem in Wu et al.’s CMAE scheme.     

Instance weighting versus threshold adjusting for cost-sensitive classification

In real-world classification problems, different types of misclassification errors often have asymmetric costs, thus demanding cost-sensitive learning methods that attempt to minimize average misclassification cost rather than plain error rate. Instance weighting and post hoc threshold adjusting are two major approaches to cost-sensitive classifier learning. This paper compares the effects of these two approaches on several standard, off-the-shelf classification methods. The comparison indicates that the two approaches lead to similar results for some classification methods, such as Naïve Bayes, logistic regression, and backpropagation neural network, but very different results for other methods, such as decision tree, decision table, and decision rule learners. The findings from this research have important implications on the selection of the cost-sensitive classifier learning approach as well as on the interpretation of a recently published finding about the relative performance of Naïve Bayes and decision trees.     

Small sample improvements in the threshold cointegration test using residual-based moving block bootstrap

A residual-based moving block bootstrap procedure for testing the null hypothesis of linear cointegration versus cointegration with threshold effects is proposed. When the regressors and errors of the models are serially and contemporaneously correlated, our test compares favourably with the Sup LM test proposed by Gonzalo and Pitarakis. Indeed, shortcomings of the former motivated the development of our test. The small sample performance of the bootstrap test is investigated by Monte Carlo simulations, and the results show that the test performs better than the Sup LM test.