覆盖聚合物敏感膜的水平剪切型声表面波气体传感器机理分析

采用微扰理论分析了覆盖聚合物敏感膜的水平剪切型声表面波气体传感器(SH-SAW)的响应机理。以针对有机磷毒剂具有良好选择性的含氟多羟基聚硅氧烷(FPOL)膜材料为例,分析了聚合物膜厚以及传感器工作频率在敏感膜吸附气体时对传感器响应的影响。计算结果表明,SH-SAW气体传感器对于不同浓度的甲基磷酸二甲酯(DMMP)气体响应随FPOL膜厚和传感器工作频率的改变呈现非线性变化。为了获得线性特性的传感器响应及较小的声波衰减,在一定的DMMP气体浓度检测范围内,通过理论计算提取出了优化的FPOL敏感膜膜厚和传感器工作频率等参数。     

SAW分子印迹技术检测甲氟膦酸异丙酯研究

甲氟膦酸异丙酯(简称GB)是一种非常重要的含膦毒剂,该文以单6-脱氧(1,10-癸二巯基)-β-环糊精为敏感膜材料,采用自组装和分子印迹技术研制出对GB有选择性检测能力的SAW-MIP-GB传感器。该传感器集SAW传感器的高灵敏度、自组装膜的稳定性和分子印迹的专一选择性于一体,对GB的检测下限可达0.4mg/m3,检测的线性范围为0.4～13mg/m3,线性回归方程为y=0.2213x+0.8531,相关系数r=0.9967。     

聚甲基[3-（2-羟基-5-氟）苯基]丙基硅氧烷的合成及其应用

以对氟苯酚和3-溴丙烯为原料,无水乙醇为溶剂,经O-烷化、克莱森重排和硅氢加成得到了有机磷毒剂敏感材料聚甲基[3-(2-羟基-5-氟)苯基]丙基硅氧烷.研究了各因素对各步反应的影响,得到的较佳工艺条件为将对氟苯酚和溴丙烯于55℃回流4 h得到中间产物对氟烯丙基苯基醚(Ⅰ),接着将Ⅰ在200℃ 保温7 h得到2-烯丙基_4-氟苯酚(Ⅱ),然后将Ⅱ和含氢硅油在100℃反应4 h.利用FT-IR和1HNMR对各级反应产物结构进行了表征.将聚甲基[3-(2-羟基-5-氟)苯基]丙基硅氧烷料涂覆在QCM传感器上研究了其对有机磷毒剂模拟剂DMMP的响应特性.结果表明传感器响应迅速,对干扰气体、水和乙醇的响应低于含有苯酚官能团的聚合材料.     

沸石分子筛修饰的QCM类神经毒气传感器

研究了Cu2 -Beta型纳米分子筛对类神经毒剂DMMP有机气体的敏感特性,并结合高灵敏的石英谐振微天平(QCM)研制了DMMP气体的传感器.研究结果表明,选择Cu2 -Beta纳米分子筛作为敏感膜对DMMP气体的检测灵敏度大大提高,达到14.481 1 Hz/lg(C/ppm).在0.2 ppm DMMP气体浓度下,传感器的响应时间和恢复时间分别为40 s和100 s,响应达到103Hz.同时经过高温和水汽吹扫脱附处理,该传感器表现了较好的重复性.     

用In2O3薄膜制成的高感度半导体O3传感器

用In_2O_3作敏感膜研制出小型固态高感度(sensibilty)(10×10~(-9)~1×10~(-6)O_3传感器.研究了膜厚、气体湿度和工作温度等对传感器敏感特性的影响,发现AET(AdsorptionEffect Transistor)型O_3传感器具有灵敏的响应特性.并分析了薄膜表面的化学吸附及其对薄膜电导的影响,以及AET作用对O_3非常敏感的物理机制.     

SAW敏感膜材料SXFA的合成与吸附研究

声表面波化学传感器(SAW chemical sensor)是一种可用于化学战剂、爆炸物的气敏传感器.涂在SAW化学传感器上的敏感膜涂层与被测气体之间能发生可逆吸附作用,从而定量分析.本文采用水解法合成了烯丙基甲基聚硅氧烷,之后与六氟丙酮在110℃下进行反应,合成了聚(氧{甲基(4-羟基-4,4-双(三氟代甲基)丁-1-烯-1-醇)亚甲基硅氧烷})(SXFA)膜材料,采用溶剂挥发法﹑旋涂法将其涂膜,以甲基膦酸二甲酯(DMMP)为化学战剂模拟物,进行检测,频率计有3 kHz的偏移响应,同时对膜厚等因素对吸附的影响进行了探讨.     

声表面波NO2传感器的研究进展

NO2是一种主要的大气污染物,同时对人体健康也有较大的危害,针对其进行检测的传感器的研究和开发就显得十分重要.声表面波气体传感器具有便携性、快速响应、高灵敏度、高稳定性、低成本等特点,引起了国内外相关研究者的广泛关注.简要介绍了声表面波(SAW)气体传感器工作的基本原理、传感器敏感膜与NO2气体的作用机理以及SAW-NO2气体传感器的两种结构类型,综述了SAW-NO2气体传感器常用的几种敏感膜材料,并对SAW-NO2气体传感器的发展趋势做了展望.     

SAW传感器对神经性毒剂及模拟剂的检测进展

基于压电效应和化学特异选择性的有机敏感材料的声表面波(SAW)传感器,因其具有体积小、响应时间快、选择性好、可集成度高等优点而成为对气体实时、在线检测的重要手段之一。介绍了SAW传感器在神经性毒剂及其模拟剂检测中的应用,重点从SAW传感器测试电路、敏感膜材料、成膜方法及信号处理等方面介绍此领域的研究现状,并对发展趋势进行了展望。     

SAW-PECH传感器对有机硫类毒剂吸附行为的研究

研究了以聚环氧氯丙烷(Poly(epichlorohydrin),PECH)为敏感膜的声表面波(surface acoustic wave,SAW)双通道延迟线传感器对有机硫类毒剂吸附行为的特性.实验表明该传感器的灵敏性符合Arrhenius方程负的温度依赖性,PECH敏感膜对有机硫类毒剂是物理吸附;以理想气体多分子吸附BET理论为模型,对该敏感膜检测有机硫类毒剂的吸附机理进行了讨论,并计算出△E及PECH敏感膜的比表面积.     

基于聚合物-碳黑敏感膜的气体微传感器阵列研究

研究了一种使用聚合物-碳黑混合物作为敏感膜的新型化学气体传感器。通过将4种不同的聚合物敏感材料聚-4-乙烯基苯酚、聚环氧乙烷、聚已内酯和乙烯-醋酸乙烯酯共聚物与一定配比的碳黑混合物分别淀积在梳状微电极上,就可以获得这4种聚合物-碳黑化学电阻型气体微传感器阵列。用这4种传感器对4种气体体积分数为5×10-4的有机类气体(丙酮、乙醇、甲醇和甲苯)进行了测试,比较了传感器的电阻变化率。微传感器的响应值,即电阻的变化率最大接近1.9%;最小的优于0.01%。梳状微电极的形状适合低体积分数的探测。通过对4种传感器响应的主成分分析,可以完全分辨被检测的4种有机类气体。     

纯量反馈系统稳定零极近似相消的积分约束

导出了单输入单输出反馈控制系统误差响应基于名义系统稳定的零、极点近似相消的时间域积分约束，此积分约束是任何反馈控制系统均应满足的．这一约束给出了单输入单输出反馈系统固有折中的新的观点．名义系统稳定的零、极点近似相消的存在导致反馈控制系统的调节时间延长或者误差响应的无穷范数变大．因此，在反馈控制系统设计中，尽量避免补偿器的零、极点与名义系统的极、零点近似相消(即使这些零、极点是稳定的)．     

区域生长辅助的地图配准在室内定位中的应用

地图匹配（ MM）算法通过粒子滤波（ PF）利用室内地图信息来抑制基于惯性传感器的室内定位系统的误差累计。利用区域生长（ RG）算法结合当前步长和方向信息在地图上找到合理的落脚范围,并以此来判断粒子的有效性。这种方法能有效改善地图配准算法的实用性和计算复杂度。提出一种改进的零速度（ ZV）检测算法能准确提取步伐信息,间接提升了零速度更新（ ZUPT）算法和地图配准算法的精度。实验结果表明：该算法的定位误差小于1.0%,定位精度比单纯的航位推算（ DR）算法平均提高了5.97%。     

基于KW、MW及DW的决策支持系统架构研究

SDSS是较为先进的决策支持系统，但由于其模型库中的模型固定不变，因此在实际应用中具有一定的局限性。提出了集成数据仓库DW、知识仓库KW和模型仓库MW作为底部架构的体系结构，能有效解决这一问题。该架构简化了模型获得和编码任务，增强了决策的有效性和智能性，提高了决策效率。     

The impact of intellectual capital on the competitive advantage: Applied study in Jordanian telecommunication companies

This research investigates the impact of intellectual capital components on the competitive advantage in the Jordanian telecommunication companies. The empirical findings indicate that the relational capital and the structural capital have positive impact on competitive advantage. Both the relational capital and the structural capital account for 48.4% of the competitive advantage. It is unexpected to find that the human capital does not have a significant direct impact on competitive advantage. However, it is valid to state that the human capital indirectly and significantly influences competitive advantage as it is embedded in the relational capital. The effect of the relational capital on competitive advantage is moderated by gender and age. The effect is strongest among younger men. In the case of the structural capital its effect is moderated by gender only such that the effect is slightly stronger for females rather than males.     

基于多智体多库协同的一种虚拟现实仿真界面构建技术

一、引言计算机仿真接口界面,随着计算机软硬件的不断提高也在快速地变化着。从其发展趋势中我们不难看出这一点:从早期的命令行提示编辑Command Line,到全屏幕菜单编辑(Menu based Editor),再到图形用户界面Graphic User In-terface(GUI),界面在不断追求如何更好地适应用户、与用户更直接地交互。其具体特点包括自然而又丰富的色彩、逼真而又完美的几何造型、柔和而又动听的环境声响、质感而又具有力反馈的实物等。这些人们所需要的真实感,一种技术是难以胜任的,它需要各种软、硬件技术的综合与集成。从目前的趋     

An efficient soft-computing technique for extraction of EEG signal from tainted EEG signal

Electroencephalography (EEG) is the recording of electrical activity of neurons within the brain and is used for the evaluation of brain disorders. But, EEG signals are contaminated with various artifacts which make interpretation of EEGs clinically difficult. In this research paper, we use a soft-computing technique called ANFIS (Adaptive Neuro-Fuzzy Inference System) for the removal of EOG artifact, combined EOG and EMG artifact. Improvement in the output signal to noise ratio and minimum mean square error are used as the performance measures. The outputs of the proposed technique are compared with the outputs of techniques such as neural network, based on ADALINE (Adaptive Linear Neuron) and adaptive filtering method, which makes use of RLS (Recursive Least Squares) algorithm through wavelet transform (RLS-Wavelet). The obtained results show that the proposed method could significantly detect and suppress the artifacts.     

A divide and conquer matheuristic algorithm for the Prize-collecting Steiner Tree Problem

The Prize-collecting Steiner Tree Problem (PCSTP) is a well-known problem in graph theory and combinatorial optimization. It has been successfully applied to solve real problems such as fiber-optic and gas distribution networks design. In this work, we concentrate on its application in biology to perform a functional analysis of genes. It is common to analyze large networks in genomics to infer a hidden knowledge. Due to the NP-hard characteristics of the PCSTP, it is computationally costly, if possible, to achieve exact solutions for such huge instances. Therefore, there is a need for fast and efficient matheuristic algorithms to explore and understand the concealed information in huge biological graphs. In this study, we propose a matheuristic method based on clustering algorithm. The main target of the method is to scale up the applicability of the currently available exact methods to large graph instances, without loosing too much on solution quality. The proposed matheuristic method is composed of a preprocessing procedures, a heuristic clustering algorithm and an exact solver for the PCSTP, applied on sub-graphs. We examine the performance of the proposed method on real-world benchmark instances from biology, and compare its results with those of the exact solver alone, without the heuristic clustering. We obtain solutions in shorter execution time and with negligible optimality gaps. This enables analyzing very large biological networks with the currently available exact solvers.     

Wavelet-based envelope features with automatic EOG artifact removal: Application to single-trial EEG data

In this study, we propose an analysis system for single-trial classification of electroencephalogram (EEG) data. Combined with automatic EOG artifact removal and wavelet-based amplitude modulation (AM) features, the support vector machine (SVM) classifier is applied to the classification of left finger lifting and resting. Automatic EOG artifact removal is proposed to eliminate the EOG artifacts automatically by means of independent component analysis (ICA) and correlation coefficient. The features are then extracted from the discrete wavelet transform (DWT) data by the AM method. Finally, the SVM is used for the discriminant of wavelet-based AM features. Compared with EEG data without EOG artifact removal, band power features and LDA classifier, the proposed system achieves promising results in classification accuracy.     

基于CAN总线实时应用的可靠调度性研究

CAN总线是一种高级的串行通信协议,适用于各种分布式控制系统。在实时应用中,标准的CAN协议使用静态优先级算法,对传输信道的利用率比较低。对基于CAN总线通信的动态优先级调度算法进行研究后,提出了一种基于指数分配方式的MTS算法,在保证强实时性消息的同时兼顾了低优先级消息的公平性。     

VoIP认证与计费的设计与实现

基于RADIUS的VoIP认证系统，采用分散受理、集中管理的接入认证管理体系，数据集中存放在认证中心(RADIUS服务器)，用户身份认证由PC向网守发起，网守通过RADIUS协议向认证中心的认证服务器发起认证请求。这样，可以保证用户安全地使用网络资源，以确保用户身份的合法性。同时其落地话单经过处理，可进行计费及其它帐务处理。文中论述了RADIUS对VoIP的支持，提出了一个Gatekeeper与RADIUS结合的整体解决方案。