Word length and lexical activation: Longer is better.

Many models of spoken word recognition posit the existence of lexical and sublexical representations, with excitatory and inhibitory mechanisms used to affect the activation levels of such representations. Bottom-up evidence provides excitatory input, and inhibition from phonetically similar representations leads to lexical competition. In such a system, long words should produce stronger lexical activation than short words, for 2 reasons: Long words provide more bottom-up evidence than short words, and short words are subject to greater inhibition due to the existence of more similar words. Four experiments provide evidence for this view. In addition, reaction-time-based partitioning of the data shows that long words generate greater activation that is available both earlier and for a longer time than is the case for short words. As a result, lexical influences on phoneme identification are extremely robust for long words but are quite fragile and condition-dependent for short words. Models of word recognition must consider words of all lengths to capture the true dynamics of lexical activation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Tracking the mind during reading: The influence of past, present, and future words on fixation durations.

Reading requires the orchestration of visual, attentional, language-related, and oculomotor processing constraints. This study replicates previous effects of frequency, predictability, and length of fixated words on fixation durations in natural reading and demonstrates new effects of these variables related to 144 sentences. Such evidence for distributed processing of words across fixation durations challenges psycholinguistic immediacy-of-processing and eye-mind assumptions. Most of the time the mind processes several words in parallel at different perceptual and cognitive levels. Eye movements can help to unravel these processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

指纹考勤管理软件的研究与实现

针对企、事业单位原有的考勤系统，如打卡钟、磁卡、IC卡等考勤方式存在代打卡、卡丢失等不足和缺陷的实际，结合指纹识别技术，建立一套考勤、薪资、人事管理于一体的软件系统。给出了系统的体系结构和功能实现，能使企业考勤管理更加简便快捷、客观公正。并提出了进一步的发展方向和展望。     

基于交会图和多元统计法的神经网络技术在火山岩识别中的应用

针对火山岩储层的特殊性(复杂性、离散性和随机性),应用BP神经网络技术对火山岩测井解释中岩性识别问题进行了研究。该方法的技术关键是样本集和初始权重的建立,以及模型的优选。本文提出了一种基于交会图和多元统计法的学习样本生成方法,即根据取心岩样的地球化学和岩石学研究,用交会图技术建立样本集,采用聚类分析和距离判别法确定初始权重。将研究方法应用在松辽盆地杏山地区火山岩岩性识别问题中,取得了很好的效果,岩性解释符合率高于90%。文中通过四种岩性识别处理模式的对比研究,表明赋权重处理模式为最优处理模型。在神经网络模型预测过程中,需充分利用已有的地质经验和测井曲线信息建立典型可靠的样本文件,同时考虑神经网络方法中各种因素的影响,优选模型和计算参数才能使预测结果符合实际情况。     

时频域自动识别与压制高频噪声

本文在分析张宇等及钱忠平等提出的高频噪声判别准则基础上,利用夏洪瑞等根据在窄档等频距小波分频之后识别、压制高频噪声的思路,提出在时频域将代表地震道主要能量的几个频带的平均振幅绝对值作为正常子波的平均振幅绝对值,以此来识别和压制高频噪声的异常振幅。实际处理结果表明,此法不仅可以压制高频谐振及高频突发噪声,而且可以保护弱地震反射信号不受损害。     

一种新型火焰安全监控系统的设计与实现

介绍了一种新型火焰安全监控系统，并详述了系统实现的方法及火焰检测部分的软硬件设计．为燃烧器的管理和燃料安全提供了一种很好的方法。     

应用时频分析方法辨识时变系统的模态参数

应用Gabor展开及Hilbert变换进行时变线性系统模态参数的辨识。利用非平稳信号的Gabor变换将结构响应信号表示在时频面上，并通过Gabor展开重构分离模态分量，建立每一阶模态的时变线性模型。对单模态时变线性模型应用Hilbert变换来辨识随时间变化的模态频率和阻尼。通过对刚度和阻尼慢变的两自由度系统模态参数的仿真辨识验证辨识方法的有效性。仿真结果表明：本文方法为时变线性系统的模态参数辨识提供了一条新的途径。     

Acquisition and pattern recognition of spectrum information of welding metal transfer

With the creation of a pattern recognition system for metal transfer mode, this article has collected five kinds of spectrum signals in gas metal arc welding (MIG, MAG and CO₂) and take them as training samples. These samples have been pretreated by computer, several key characteristic parameters of the spectrum signal have been creatively extracted, and a corresponding recognition function and a minimum-distance-classifier have been constructed. The results show that the pattern recognition of several kinds of metal transfer modes for the metal gas arc welding can be done successfully, and relative important parameters in welding process, such as the frequency of droplet transfer and the approximate diameter of each droplet, can also be obtained.     

Phosphorus‐containing polyaryloxydiphenylsilanes with high flame retardance arising from a phosphorus–silicon synergistic effect

Polyaryloxydiphenylsilanes were prepared from phosphorus‐containing diols and diphenydichlorolsilane through solution polymerization. With a stoichiometric imbalance in feed monomers, the resulting polymers exhibited moderate melting points and good processing properties. The polymers prepared showed initial decomposition temperatures above 340 °C, excellent thermal stability, high char yields at 850 °C and very high limited oxygen index values of 56–59. The polymers' char yields and their (P + Si) contents showed linear relationships. © 2003 Society of Chemical Industry     

人工神经网络理论及其应用

简要介绍了人工神经网络的发展过程和基本理论，从神经网络具有自学习功能、联想存储功能和高速寻找优化解的能力三个方面论述了其特点和优越性，详细阐述了在模式识别、信号处理、自动控制、人工智能、自适应的人机接口、优化计算、通信以及其它方面的应用，探讨和分析了其发展前景。