指纹识别PDA的设计与实现

PDA是一种轻便、灵巧,具有很强的可移动性的设备,随着指纹技术的发展。其已经在金融保险、门禁、身份识别等领域得到了广泛的应用,详细地分析了指纹识别PDA设计的功能,并且详细地分析了指纹采集、指纹预处理、指纹特征提取、指纹识别等核心技术,设计实现了一个功能强大的指纹识别PDA。     

基于支持向量回归的动力电池参数辨识

根据铅酸蓄电池在放电过程中内部电化学反应导致外部电特性变化的特点,提出一种基于支持向量机原理的电解液密度辨识模型。利用支持向量机理论非线性回归的特性,简化测量电解液密度的过程,在恶劣环境下检测动力电池的电解液密度更显其优越性。预测实验表明,采用改进的交叉验证预测模型具有泛化能力强、稳定性好的特点,并且在小样本的条件下能达到预期的辨识精度。     

基于硬件滤波电路的无刷直流电机转子位置辨识

反电动势过零检测是无刷直流电机无位置传感器控制中转子位置检测的主要方法之一,为消除PWM因素的影响,需要对转子位置检测电路进行滤波处理。本文采用硬件滤波器对反电动势过零检测电路进行滤波,既要考虑深度滤波带来的相移问题又要兼顾消除噪声的影响,分析滤波器的幅频特性和相频特性,根据反电动势过零检测指标要求设计滤波器参数,并用于无刷直流电机转子位置辨识和无位置传感器控制中。仿真结果和实验结果表明,所采用的滤波器及其参数能较好地检测出转子位置,可以明显提高无位置传感器无刷直流电机驱动系统的控制性能。     

使用程序静态分析技术识别Web程序中的用例结构

本文利用程序静态分析技术对Web程序中的用例识别进行了深入研究。对Web页面的用户行为进行了深入分析并建模,从行为模型中提取出描述整个系统中用户行为的事件流图,结合采用现有的从目的成功语句出发、以必经结点为基础的用例识别方法,从各个Web页面中提取的独立控制流图,形成全局控制流图,进行全局用例识别。与以前已有工作相比,本文考虑了Web程序的特点,尤其是前端程序如何实现用户行为,并在前端程序中进行精确的用例识别。本文采用目前使用较为广泛的JSP程序进行了实验,结果表明该方法能够有效识别JSP程序中的用例结构。     

基于语义分类的比较句识别与比较要素抽取研究

比较是人们常用的评估不同事物优劣、异同的表达方式,利用机器识别比较句并进一步抽取比较要素是语言信息处理领域一项新颖又有实用价值的课题。该文依据比较句与比较要素之间是一种“你中有我,我中有你”的共生关系,将比较句识别与比较要素抽取两个任务合二为一完成;根据词意分类,构建由领域词典、情感词典、标记词典、普通词典构成的词典系统;根据汉语比较句句义分类,构建比较句识别与比较要素抽取规则库。以第四届中文倾向性评测(COAE2012)发布的测试语料为实验对象,该系统取得了较好的实验(评测)结果。     

观点句中评价对象/属性的缺省项识别方法研究

在多对象、多属性的评论文本中,评价对象和评价属性的缺省识别对于观点挖掘有着重要的作用。针对情感观点句中评价对象和评价属性的缺省问题,该文提出一种有效的缺省项识别方法。首先构造缺省项识别规则集,用于获取待识别的缺省项侯选集;将缺省项识别问题看作一个二元分类问题,选用词法和依存句法作为特征,使用决策树分类算法C4.5训练分类器模型,在测试集上对待识别的缺省项进行判别。实验结果表明,使用依存句法特征集分类的F值优于词法特征集约2%。将词法和依存句法两类特征融合与单类特征相比,分类精确率和F值分别提高了10%和5%左右,说明词法特征和依存句法特征的融合有利于缺省项识别。     

The use of neural networks for fitting complex kinetic data

In this paper the use of neural networks for fitting complex kinetic data is discussed. To assess the validity of the approach two different neural network architectures are compared with the traditional kinetic identification methods for two cases: the homogeneous esterification reaction between propionic anhydride and 2-butanol, catalysed by sulphuric acid, and the heterogeneous liquid-liquid toluene mononitration by mixed acid. A large set of experimental data obtained by adiabatic and heat flux calorimetry and by gas chromatography is used for the training of the neural networks. The results indicate that the neural network approach can be used to deal with the fitting of complex kinetic data to obtain an approximate reaction rate function in a limited amount of time, which can be used for design improvement or optimisation when, owing to small production levels or time constraints, it is not possible to develop a detailed kinetic analysis.     

复配菌对原油除蜡降黏效果分析

为提高含蜡原油流动性能,从辽河油田附近经受原油污染的土壤中筛选出两株原油降解菌。经过16S rRNA基因序列比对鉴定,菌株为纤维微菌属(Cellulosimicrobiumsp.)和假单孢菌(Pseudomonassp.),命名为7#和12#。将筛选出的7#菌与12#菌优化复配使用,研究结果表明:复配菌对液体石蜡有乳化效果,当复配菌体积比为1∶1时,乳化率最高达到77.5%;最适的生长温度为35～40℃,p H=6～8,最佳接种量(体积分数)为4%,复配菌体积比为1∶1,且培养基在初始pH,即pH=7时复配菌生长状态最佳。复配菌在37℃,pH=7条件下对原油处理7 d后,除蜡率为61.32%,降黏率达到31.58%;显微镜观察蜡晶变小,进一步说明菌株能够降解石蜡,破坏蜡晶结构,提高含蜡原油的流动性能。     

Modeling and control of Wiener-type processes

We develop a simple relay feedback method to identify Wiener-type nonlinear processes. It separates the identification problem of the nonlinear static function from that of the linear dynamic subsystem to simplify the identification procedure significantly. Owing to the separation, the unmeasurable output of the linear dynamic subsystem can be obtained in a straightforward manner. Then, determining the model structure of the nonlinear static function becomes very simple and the estimates are robust to additive output noises. We can identify the whole activated region of the nonlinear static function as well as the ultimate information of the linear dynamic subsystem from only one relay feedback test. More information on the linear dynamic subsystem can be estimated by well-established linear system identification methods from additional tests. We use a nonlinear control strategy to compensate the nonlinear dynamics of the Wiener process so that the design parameters can be determined by usual tuning rules developed for linear processes and a high control performance can be achievable as in linear processes.     

Model falsification using set‐valued observers for a class of discrete‐time dynamic systems: a coprime factorization approach

This article introduces a new method for model falsification using set‐valued observers, which can be applied to a class of discrete linear time‐invariant dynamic systems with time‐varying model uncertainties. In comparison with previous results, the main advantages of this approach are as follows: The computation of the convex hull of the set‐valued estimates of the state can be avoided under certain circumstances; to guarantee convergence of the set‐valued estimates of the state, the required number of previous steps is at most as large as the number of states of the nominal plant; and it provides a straightforward nonconservative method to falsify uncertain models of dynamic systems, including open‐loop unstable plants. The results obtained are illustrated in simulation, emphasizing the advantages and shortcomings of the suggested method. Copyright © 2013 John Wiley & Sons, Ltd.