Defining syntax-directed translations by tree bimorphisms

We introduce a class of tree bimorphisms that define exactly the translations performed by syntax-directed translation schemata. We also show that these “quasi-alphabetic” tree bimorphisms preserve recognizability, and that their class is closed under composition and inverses.     

The role of latent and active failures in workplace slips, trips and falls: an information processing approach

The vast majority of the published workplace slips, trips and falls (STF) literature is exceedingly narrow in its focus and often ignores wider systems issues in workplace STF aetiology. There is little recognition within the published literature of the importance of latent failures or the upstream organisational and cultural contexts within which workplace STF occur. This is unfortunate, as a systems approach to workplace STF analysis, that is inclusive of latent design and work organisation factors that often shape worker behaviour patterns related to STF risk (e.g. rushing, risk taking), is fundamental to the development of effective prevention measures. The aims of this paper are to provide an understanding of workplace STF causation that is cognisant of the potential role of both active and latent failures in STF causation. The paper presents an ergonomics model for workplace STF analysis that highlights information processing in STF aetiology, the STF incident process and the interaction between latent and active failures in STF causation. The paper draws upon ergonomics research conducted in a range of occupational contexts to illustrate the key features of the model as it applies to workplace STF. Implications of the model for analysis and prevention of STF are discussed.     

Worst-case optimal algorithm for XPath evaluation over XML streams

We consider the XPath evaluation problem: Evaluate an XPath query Q on a streaming XML document D; i.e., determine the set Q(D) of document elements selected by Q. We mainly consider Conjunctive XPath queries that involve only the child and descendant axes. Previously known in-memory algorithms for this problem use O(|D|) space and O(|Q||D|) time. Several previously known algorithms for the streaming version use Ω(dn) space and Ω(dn|D|) time in the worst case; d denotes the depth of D, and n denotes the number of location steps in Q. Their exponential space requirement could well exceed the O(|D|) space used by the in-memory algorithms. We present an efficient algorithm that uses O(d|Q|+nc) space and O((|Q|+dn)|D|) time in the worst case; c denotes the maximum number of elements of D that can be candidates for output, at any one instant. For some worst case Q and D, the memory space used by our algorithm matches our lower bound proved in a different paper; so, our algorithm uses optimal memory space in the worst case.     

对等数据管理系统中模式映射的备份机制

针对对等数据管理系统中节点因自治性而动态离开和返回网络造成模式映射路径频繁断裂的问题,提出一种基于模式映射备份机制的离开节点绕过方法,向下游节点提供以树状结构组织的上游映射信息。当映射路径中有节点离开时,其下游节点的查询以此映射信息和备份的上游映射,绕过离开节点。仿真和分析的结果表明,映射备份机制的引入提高了查询的可达性,从而可以从更多的局部数据库中获得返回结果。     

基于PicoBlaze的多软核网络处理结构研究

介绍一种基于多个8位CPU软核PicoBlaze的网络处理结构.该结构利用现场可编程门阵列(FPGA)的并行性和网络协议分层结构的特点,可以实现一些相对复杂的网络处理功能,并且易于扩展和开发.通过在FPGA上完整实现一个远程启动服务器端的设计实例,阐明具体的设计方法.     

基于似然比测试的语音激活检测算法

针对低信噪比和噪声变化情况下语音激活检测算法性能下降的问题,提出一种新的参数更新和取值算法。该算法采用Laplacian-Gaussian混合模型对带噪语音频谱的概率分布进行建模,模型参数从带噪语音中估计得到,噪声功率参数通过跟踪语音的音节间隙进行平滑。实验结果表明,该算法在-5dB信噪比情况下,可以达到95％以上的检测率,具有优越的跟踪性能。     

基于多核的IPSec并行处理技术研究与实现

IPSec VPN网关需要进行大量加解密运算,对网络传输带宽产生较大影响。该文提出基于多核处理器的IPSec协议并行处理模型,将IPSec网络报文调度到多个处理器单元上运行,从而提高传输带宽。在Linux操作系统上对该模型进行具体实现,经过测试,在双核处理器上,IPSec VPN网关获得了接近倍速的性能提升。     

基于贝叶斯最大化后验估计方法的图片合成模型研究

在图像处理应用中,常常需要根据一些列相关的输入图片生成一张新的图片。现有的研究大都设定一些启发式规则用于图片的合成过程。为了提高图片合成的性能,提出了一种基于改进的贝叶斯方法的图片合成模型。在给定理想的图片合成模型后,对传感器误差和图片误差进行了分析。由于图片误差和几何误差之间是相关的,因此分析了它们之间的关系。在根据已有数据对模型进行后验估计时,通过最小化能量来得到模型的先验参数。在目标函数的优化过程中,基于现有研究通过重新赋权值的迭代方法进行优化问题的求解。最后,通过大量的实验表明,所提出的图片合成模型与相关方法相比具有更好的图片合成和渲染效果。     

传感器输出特性的线性化回归程序设计

介绍了用面向对象程序设计方法编制的线性回归数据处理程序 ,该程序用于传感器实验数据的回归处理和特性曲线的绘制     

一种中文文档的非受限无词典抽词方法

本文提出了一种非受限无词典抽词模型,该模型通过自增长算法获取中文文档中的汉字结合模式,并引入支持度、置信度等概念来筛选词条。实验表明:在无需词典支持和利用语料库学习的前提下,该算法能够快速、准确地抽取中文文档中的中、高频词条。适于对词条频度敏感,而又对计算速度要求很高的中文信息处理应用,例如实时文档自动分类系统。