Design and fabrication of novel micro electromagnetic actuator

This study designs, fabricates, and characterizes a novel micro electromagnetic actuator comprising a PDMS diaphragm, a polyimide-coated copper micro coil, and a permanent magnet. When an electrical current is passed through the micro coil, a magnetic force is induced between the coil and the magnet which causes the diaphragm to deflect, thereby creating an actuation effect. The experimental results demonstrate that the diaphragm deflection can be accurately controlled by regulating the current passed through the micro coil. It is shown that the maximum diaphragm deflection within elastic limits is 150 μm; obtained by passing a current of 0.6 A through a micro coil with a line width of 100 μm. The micro actuator proposed in this study is easily fabricated and is readily integrated with existing bio-medical chips due to its planar structure.     

Volatility model based on multi-stock index for TAIEX forecasting

Conventional time series models have been applied to handle many forecasting problems, such as financial, economic and weather forecasting. In stock markets, correct stock predictions will bring a huge profit for stock investors. However, conventional time series models produce forecasts based on some strict statistical assumptions about data distributions, and, therefore, they are not very proper to forecast financial datasets. This paper proposes a new forecasting model using adaptive learning techniques to predict TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock index) with multi-stock indexes (NASDAQ stock index and Dow Jones stock index). In verification, this paper employs seven year period of TAIEX stock index, from 1997 to 2003, as experimental datasets, and the root mean square error (RMSE) as evaluation criterion. The performance comparison results show that the proposed model outperforms the listing methods in forecasting Taiwan stock market. Besides, from statistical test results, it is showed that the volatility of Dow Jones and the NASDAQ affect TAIEX significantly.     

Fault-tree analysis for liquefied natural gas terminal emergency shutdown system

Natural gas, one of the cleanest, most efficient and useful of all energy sources, is a vital component of the world’s supply of energy. To make natural gas more convenient for storage and transportation, it is refined and condensed into a liquid called liquefied natural gas (LNG). In a LNG site, safety is a long-team and critical issue. The emergency shutdown (ESD) system in the LNG receiving terminal is used to automatically stop the pumps and isolate the leakage section. Fault-tree analysis (FTA) has been widely used for providing logical functional relationships among subsystems and components of a system and identifying the root causes of the undesired failures in a system. In the conventional FTA for the ESD system, we usually assume that exact failure probabilities of events are collected. However, in most real applications, first, the FTA for the ESD system needs to be made at a early design or manufacturing stage, certain new components normally used without failure data; secondly, sometimes the environmental change in the system during the operation periods. This makes more difficult to gather past exact failures data for the FTA. To complete the FTA of the ESD system under these uncertain situations, we apply the intuitionistic fuzzy sets (IFS) theory to the FTA. We generate the intuitionistic fuzzy fault-tree interval, and the intuitionistic fuzzy reliability interval for the ESD system. We also present an algorithm to find the critical components in the system based on IFS–FTA and determine weak paths in the ESD system, where the key improvement must be made.     

基于面向方面MDA的实时系统开发方法

实时系统有许多难以处理的横切整个系统的非功能需求。针对以上问题,提出基于面向方面模型驱动架构的实时系统开发方法。该方法在设计阶段将系统的非功能需求从功能需求中分离出,以降低系统开发的复杂性,提高系统的可重用性、可维护性和横切关注点的模块化程度。通过应用实例证明该方法是有效的。     

基于可疑行为识别的PE病毒检测方法

针对当前PE病毒难以防范及查杀的现象,对PE病毒关键技术进行分析,提取病毒典型特征的可疑行为,在此基础上提出一种Windows平台下的静态检测方法。该方法在对程序反编译处理的基础上,以指令序列与控制流图的分析为行为识别依据,完成基于可疑行为识别的病毒检测方法的设计。实验结果证明,该检测方法能有效检测混淆变换病毒。     

基于多兴趣Agent的信息检索模型的研究

基于agent的信息检索系统在海量网络信息检索中已经得到广泛的应用.提出了一个基于多兴趣agent新的信息检索模型,该模型对查询信息进行了兴趣预测并生成了用户兴趣项权重向量.实验表明,模型在预测用户兴趣的效果和推荐搜索信息的准确率方面比传统的单兴趣Agent检索系统IRHOIA有一定的改善.     

某型飞机振动传感器试验器的研制

为测试某型飞机振动传感器性能,采用背靠背比较法振动测试方法,基于苏试振动台(VT-500)、功率放大器(LA-800)、单轴向电荷输出型加速度标准传感器(Ymc222A25)、电荷放大器(Ymc8102T)、普源信号发生器(DG1032Z)以及研华PCI工控机与A/D板卡(PCI-1716L),搭建振动传感器试验器振动测试平台,以DG1032Z输出作为振动激励信号源,基于VC ++6.0开发出信号发生器远程控制与板卡信号采集软件,对试验器的功能进行试验验证,结果表明其有效性.所研制的试验器可实现振动信号源的产生与标准/被测信号的校准,从而为某型飞机振动传感器的测试与修理提供技术支撑.     

基于Henon映射的加密遥感图像的安全检索方案

遥感图像具有多时相、多语义、多波段等特点,鉴于遥感图像在商业行业及国防军事中的重要性,海量遥感图像密文检索的效率和精度,直接影响了遥感大数据使用的广泛性和实时性.对密文存储的遥感大数据的安全检索是其可用性最重要的标志之一.本文提出了一种基于Henon 映射的遥感图像可搜索加密方案,根据遥感图像的成像原理及多波段特征,采用改进的Henon 映射对每个波段的灰度值进行加密处理;并根据遥感图像的“大数据”特征,通过统计灰度值的区间信息来构造遥感图像的特征向量,并根据相似度匹配算法来检索目标图像.通过对Landsat 8遥感图像进行加密与检索实验,该方案有效地提高了检索密文遥感图像的安全性及准确性,且计算复杂度低、通信成本开销小.     

群集系统分群行为建模与控制研究进展

群集系统的分群行为表征为一个聚合的母群分裂成多个子群的现象, 探讨其产生机理和控制方法具有重要的理论意义和应用价值. 鉴于此, 从分群行为的理论建模和控制方法两个角度出发, 对近年来群集系统分群运动研究的主要成果进行综述, 回顾了目前分群运动理论建模研究的最新进展, 重点总结了分群运动的现有控制方法和结论, 并对分群控制研究中尚存在的问题进行了探讨, 最后就分群行为后续可能的研究方向进行了展望.