数字化校园综合查询服务平台的设计与研究

本文在对数字化校园中心共享数据库及公共数据交换平台的研究基础之上设计了一种综合查询服务平台架构及查询服务功能,同时分析了查询实现过程。     

Blind estimation of the PN sequence in lower SNR DS-SS signals with residual carrier

This paper presents a method of singular value decomposition (SVD) plus digital phase lock loop (DPLL) to solve the difficult problem of blind pseudo-noise (PN) sequence estimation in low signal to noise ratios (SNR) direct sequence spread spectrum (DS-SS, DS) signals with residual carrier. Of course, the method needs to know the parameters of DS signal, such as the period and code rate of PN sequence. Firstly, the received signal is sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. Then, an autocorrelation matrix is computed and accumulated by the signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of this autocorrelation matrix. Furthermore, a DPLL is used to deal with the estimated PN sequence with residual carrier, it estimates and tracks the residual carrier, removes the residual carrier in the end. Theory analysis and computer simulation results show that this method can effectively realize the PN sequence estimation from the input DS signals with residual carrier in lower SNR.     

Usable optimistic fair exchange

Fairly exchanging digital content is an everyday problem. It has been shown that fair exchange cannot be achieved without a trusted third party (called the Arbiter). Yet, even with a trusted party, it is still non-trivial to come up with an efficient solution, especially one that can be used in a p2p file sharing system with a high volume of data exchanged.We provide an efficient optimistic fair exchange mechanism for bartering digital files, where receiving a payment in return for a file (buying) is also considered fair. The exchange is optimistic, removing the need for the Arbiter’s involvement unless a dispute occurs. While the previous solutions employ costly cryptographic primitives for every file or block exchanged, our protocol employs them only once per peer, therefore achieving an O(n) efficiency improvement when n blocks are exchanged between two peers. Our protocol uses very efficient cryptography, making it perfectly suitable for a p-2-p file sharing system where tens of peers exchange thousands of blocks and they do not know beforehand which ones they will end up exchanging. Therefore, our system yields up to one-to-two orders of magnitude improvement in terms of both computation and communication (40 s vs. 42 min, 1.6 MB vs. 200 MB). Thus, for the first time, a provably secure (and privacy-respecting when payments are made using e-cash) fair exchange protocol can be used in real bartering applications (e.g., BitTorrent) [14] without sacrificing performance.     

一种基于门限ECC的PKI/CA模型的设计

随着电子商务的发展,如何实现对网络用户的身份认证成为了一个非常迫切的问题,目前广泛采用的是基于PKI的认证技术,而在PKI认证体系中,认证中心CA是核心部分。本文提出了一个基于门限ECC的PKI/CA的设计,本方案在传统的CA方案上引入了入侵容忍机制,结合椭圆曲线密码体制和门限密码方案,提高了CA系统的可靠性和安全性。     

电子政务数据共享模式研究

互联网的广泛应用,改变了社会公众对政府信息需求的观念。加强电子政务数据共享是社会发展的必然要求。为了保证政务信息的有效共享,实现不同部门不同类型数据的转换和重用,提出了一种新的基于公开密钥基础设施体系构造数据共享模式。在新的数据共享模式中,使用电子凭证替代传统的纸质凭证,增加了行政审批事务办理的快捷性、安全性、低碳环保性。为了进一步提高电子凭证的效率,将其与云计算无缝融合。通过对具体应用案例的分析,表明新的数据共享模式具有安全性、可行性和实用性。     

数字图书馆网络安全防御系统的构建

数字图书馆为人们的日常工作学习提高了很多专业有效的数据,它拥有巨大的数据容量,但一旦受到攻击,将造成巨大损失,给人们带来诸多不便。本文针对如何有效的构建数字图书馆网络安全防御系统这一问题进行了相关分析探讨。首先列出了几大危害网络安全的因素,再根据这些因素从加强网络技术防护、规范人文管理两方面展开研究。     

RFID技术在智能交通管理中应用

本文主要介绍RFDI技术定义及系统工作原理,并重点关注RFID技术在智能交通领域的实际应用方式。同时RFID技术也成功解决了车辆自动识别和信息采集问题,为智能交通管理和服务系统的建立提供了强大的信息支撑和保障。     

中职学校提高《数字电路》课程教学质量的探讨

《数字电路》是中职电类专业的一门专业基础课程。结合目前中职学校教学现状中存在的问题,如何让学生把这门课学好,笔者从精选教材、课堂导入、教学手段、考核评价等方面进行了探讨。指出了只有充分激发起学生的学习兴趣和学习积极性,才是提高教学质量的关键。     

利用Applet制作电子相册

本文通过介绍Applet的体系结构和其生命周期以及如何创建和执行Applet程序,介绍了电子相册的制作过程。     

宽带功率放大器PGSC建模方法及预失真研究

针对宽带功率放大器的强记忆效应特性,提出一种功放建模和数字预失真方法——PGSC模型。利用广义记忆多项式(GMP)、特定交叉项(SCT)及记忆时刻信号交叉项(CIMT)3个基函数来构造功放行为模型及数字预失真器,并搭建实际测试平台对模型的精度及线性化效果进行验证。测试结果表明,与PMEC方法相比,PGSC方法建模时的归一化均方误差减少了2.1 dB,数字预失真时输出信号的三阶邻信道功率比降低了4.94/2.03 dB;与GMP方法相比,PGSC方法仅利用73%的系数即可得到更高的模型精度和更好的线性化效果。