基于客户服务器模式的邮政远程教育平台监控系统

设计实现了如何利用客户服务器架构来开发邮政远程教育平台监控系统,着重介绍了系统的整体方案,并用Java语言和VC＋＋语言实现了系统功能。     

基于JMF实时传输的远程授课系统的设计与实现

在简要介绍多媒体实时传输关键技术的基础上,对在JMF平台上实现音视频数据实时处理传输技术的远程授课系统的硬件结构和软件层次结构设计以及RTP流的发送和接收作了详细阐述,提出了一套从硬件到软件的完整设计和实现方案。为保证系统高度的实时性,采用了对音频和视频建立不同的虚拟信道,以负责不同媒体信息的传输,每个信道根据其媒体信息特点,赋予相应的服务质量参数,保证了信息的高效传输。     

钻井布局方案最优化方法

本文研究钻井布局最优方案,提高已有井的使用率。通过建立非线性规划模型分别在欧式距离(l∞模距离)和纵横距离(l2模距离)下求解具体布局方案。     

On the Performance of Punctured Turbo Codes

IntroductionTurbo codes, first introduced by Berrou et al.[1],have attracted the attention of many researchers for theirremarkable coding gains close to theoretical limits, yetadmitting a relatively simple iterative decodingtechnique[2]. Since then, abundant of fruitful results on theperformance of turbo codes have been published, in whicha distance spectrum interpretation was presented by [3]and a super trellis structure of turbo codes was derived by[4]. An analytical…     

基于Internet的交互式远程教育研究

详细论述了远程教育的技术、远程教育的几种模式、远程教育的研究内容和远程教育的发展趋势,以及目前远程教育存在的问题。     

基于乘客流量概率分布的轨道车站合理间距优化模型

车站间距规划是城市轨道交通规划和设计的重要内容。在已有优化方法局限性分析的基础上，建立了以轨道线路系统总成本最少化为优化目标，并考虑乘客流量和乘行距离随车站间距概率分布的合理间距优化模型，提出了模型的算法，得到了各影响因素常见组合情况下的车站合理间距，分析了各因素变化对合理间距的影响，为实际工作中车站间距的合理确定提供了理论支持。     

相位法测距中精粗测量数据衔接方法的讨论

讨论了相位法光电测距中有关精、粗测量数据衔接方法的问题,给出了一种通用而可靠的精、粗测量数据衔接的新方法,并对两种数据衔接方法衔接所得结果给予了比较．     

远程教育与个别化学习

个别化学习随着现代远程教育的发展而日渐突出 .其原因有四个 :教育信息传播媒体的演进引发教育方法和模式的演变 ;现代教育理论和学习理论提出最好的学习是自主的个别化的探索学习 ;现代社会的发展要求人才具有个性和创造性 ;网络技术的运用利于学习者构建个性化学习环境 .个别化学习可以从宏观和微观两方面去定义 .从微观上看 ,个别化学习是指具有不同学习风格和学习策略的学习者在个性化的学习环境中所进行的自主学习 .远程教育中的个别化学习需要五个要素 :明确的学习目的 :学习的元学习、元认知能力 ;学习者的自我管理能力 ;构建完整的个性化学习环境 ;反馈评价机制     

茂兰喀斯特山地南方铁杉种群结构和动态初探

基于大小结构分析法、矩阵模型和分布格局距离方法，研究了茂兰喀斯特山地南方铁杉种群的结构和动态特征：①该种群为中衰型种群；②其空间分布格局表现为聚块内个体呈剧烈聚集分布，而聚块个体呈均匀分布；③南方铁杉种群密度（ＤＳ）有随种群个体径级（ＤＧ）增大而增加的趋势：ＤＳ＝０．００３５ＤＧ１．７３２９；④南方铁杉为先锋种群，能于山顶特殊生境中与其它物种一起于一定时期内形成稳定群落，但其终将为阔叶树种取代；⑤在某种程度上，种群的空间分布格局距离法和矩阵模型能够较好地应用于中亚热带森林种群研究．     

Spectral analysis of phylogenetic data

The spectral analysis of sequence and distance data is a new approach to phylogenetic analysis. For two-state character sequences, the character values at a given site split the set of taxa into two subsets, a bipartition of the taxa set. The vector which counts the relative numbers of each of these bipartitions over all sites is called a sequence spectrum. Applying a transformation called a Hadamard conjugation, the sequence spectrum is transformed to the conjugate spectrum. This conjugation corrects for unobserved changes in the data, independently from the choice of phylogenetic tree. For any given phylogenetic tree with edge weights (probabilities of state change), we define a corresponding tree spectrum. The selection of a weighted phylogenetic tree from the given sequence data is made by matching the conjugate spectrum with a tree spectrum. We develop an optimality selection procedure using a least squares best fit, to find the phylogenetic tree whose tree spectrum most closely matches the conjugate spectrum. An inferred sequence spectrum can be derived from the selected tree spectrum using the inverse Hadamard conjugation to allow a comparison with the original sequence spectrum. A possible adaptation for the analysis of four-state character sequences with unequal frequencies is considered. A corresponding spectral analysis for distance data is also introduced. These analyses are illustrated with biological examples for both distance and sequence data. Spectral analysis using the Fast Hadamard transform allows optimal trees to be found for at least 20 taxa and perhaps for up to 30 taxa. The development presented here is self contained, although some mathematical proofs available elsewhere have been omitted. The analysis of sequence data is based on methods reported earlier, but the terminology and the application to distance data are new.