采用高斯拟合的全局阈值算法阈值优化框架

采用最大类间方差法、最大熵法和最小误差法3种经典全局阈值方法获得的阈值,存在一定偏差.针对该问题,提出了一种采用高斯拟合的全局阈值算法阈值优化框架(TOF).本优化框架先利用全局阈值算法获得初始阈值,将图像粗分为背景和目标2个部分,然后分别计算各部分均值和方差来拟合出2个高斯分布.由于最佳阈值位于2个高斯分布的交点位置,为此本框架采用多次迭代方式来优化阈值,直至最终收敛到最佳阈值.为提高抗噪性能,结合三维直方图重建和降维思想,提出了一种鲁棒的采用高斯拟合的全局阈值算法阈值优化框架(RTOF).实验结果表明,对于以上经典全局算法,采用本优化方法均能收敛到一个最佳阈值,同时本算法还具有鲁棒的抗噪性能和较高的执行效率.     

扣件参数对小半径曲线钢轨波磨的影响

目的 研究扣件参数对小半径曲线钢轨波磨的影响,获得抑制钢轨波磨的有效措施。方法 建立小半径曲线DTVI2扣件的轮轨系统有限元模型,对扣件系统进行实体化建模,考虑轨下垫板之间的接触情况,同时模拟扣件系统中弹条预紧作用。采用复特征值分析和瞬时动态分析研究轮轨系统的摩擦自激振动特性,并将预测结果与现场测试结果对比,揭示该区段钢轨波磨产生的原因。最后开展轨下垫板材料属性以及扣件结构参数的影响分析,获得其对钢轨波磨的影响。结果 轮轨间饱和蠕滑力引起轮轨系统发生频率为500 Hz的不稳定振动,会导致波长为30 mm的钢轨波磨。轨下垫板杨氏模量在10~50 MPa区间,等效阻尼比先从‒0.015 2减小到‒0.016 9又增大到‒0.014 2;阻尼系数在0~0.000 1区间内,等效阻尼比从‒0.016 9增大到‒0.010 2;轨下垫板泊松比的变化没有引起系统等效阻尼比发生明显的变化;扣件间距在575~675 mm区间内,等效阻尼比从‒0.016 3降低到‒0.019 0;等效阻尼比随着弹条预紧力的增大而增大。结论 选取合适的轨下垫板杨氏模量可以减轻由轮轨摩擦自激振动导致的钢轨波磨;提高阻尼系数对轮轨系统的自激振动具有较强的抑制作用;而轨下垫板的泊松比对钢轨波磨的影响较小;适当减小扣件间距可以略微降低钢轨波磨的产生趋势;增大弹簧预紧力可以抑制由轮轨系统摩擦自激振动导致的钢轨波磨。     

优势关系下不协调目标信息系统的下近似约简

在基于优势关系下的不协调目标信息系统中引入了下近似约简的概念,并得到了下近似约简的判定定理以及辨识矩阵,建立了不协调目标信息系统的下近似约简的具体方法,同时通过实例验证了该方法的有效性,从而为优势关系下信息系统的知识发现提供了理论基础。     

Aggregating expert predictions in a networked environment

This paper describes an approach for combining the classifications or predictions of n local experts into a single composite prediction. We describe a Java-based application that allows a user to select up to n prediction experts that provide information for assigning an object to one of two predetermined groups. An advantage of this type of application is that it is capable of interacting with the Internet in a relatively seamless way. We examine the accuracy and robustness of our technique by comparing the classification accuracy of our technique, a maximum entropy-based aggregation technique, and four classification methods on a real-world, two-group data-set concerned with bank failure prediction. The classificaiton methods studied in this work include Quinlan's C4.5 decision-tree classifier, logistic regression, mahalanobis distance measures, and a neural network classifier. Our model includes a fundamental component (i.e., a transaction manager) that helps improve the general performance of applications that perform network-based classification. This component is found to provide reliable and secure connections along with ways to direct traffic across the Internet. Our results suggest three major contributions: (1) a transaction manager increases the flexibility of a network-based classifier since it is capable of transacting with one or more specific types of prediction expert(s) over the Internet; (2) our approach tends to be more accurate than the individual classification methods we examined; and, (3) our approach can outperform a recently introduced statistically based aggregation technique.Scope and purposeThe emergence of the Internet has produced a need for employing new types of programming and research tools that are capable of accessing information resources located throughout the world. There is only a limited amount of research available in this area and this work describes a network-based tool that solves a two-group classification problem. The two-group classification problem in discriminant analysis is concerned with developing a rule for predicting to which of k=2 mutually exclusive groups an observation of unknown origin belongs. This problem commonly occurs in business and other areas, and a plethora of statistical and artificial intelligence (AI) techniques exist to help decision-makers effectively analyze their data. A number of recent studies have compared the classificatory performance of various AI techniques to the more traditional statistical techniques, however, decision makers are left in somewhat of a quandary about which of the many available classification techniques to use to solve a specific classification problem. This paper proposes a new aggregation technique that focuses on combining or aggregating the predictions from multiple classification techniques into a single composite prediction. Our approach provides a simple method for aggregating expert predictions coming from remote locations by combining Java and Common Object Request Broker Architecture (CORBA) into a general classification tool. Object-oriented models developed using Java are platform independent and can be easily modified. CORBA provides the services necessary to establish and manage network connections. Computational results show that our technique outperforms a recently introduced maximum entropy-based aggregation technique using a real-world data set.     

Effects of post-deposition annealing on different DLC films

Amorphous hydrogenated carbon films have been deposited by plasma-enhanced chemical vapour deposition at different process pressures and substrate temperatures, resulting in film properties ranging from polymer-like to diamond-like. The deposition parameter combinations were chosen by experimental design to enable the determination of both deposition pressure and deposition temperature effects on the annealing behaviour. The deposited films have then been annealed in vacuum at successively higher temperatures. Changes in optical band gap, internal stress, film thickness and infrared (IR) absorption spectra have been recorded to assess the influence of deposition parameters on the thermal stability of diamond-like carbon (DLC) and to identify temperature-induced modifications in the bonding structure. The results show a large variation in thermal stability between the different DLC films; samples deposited at low pressure display the greatest stability. The internal stress of the films starts decreasing at very low annealing temperature (<100 °C for the majority of samples), in most cases long before any decrease in the optical band gap can be detected. This is explained by a movement of hydrogen from sp² to sp³ sites as detected by IR measurements.     

面向射频能量收集的小型化超材料整流天线设计

为了高效收集空间存在的射频能量,提出了一种新型的射频能量收集系统：首先,设计了一种单极子微带天线,其性能稳定且易于加工;其次,结合超材料理论设计了一种基于开口环形谐振器的超材料单元,其内环采用曲流技术,从而使天线小型化;最后通过将超材料单元加载在微带天线上对其进行了改进,能够进一步减小天线尺寸,改善带宽、增益等性能。系统由小型化超材料天线、匹配电路、整流电路及负载组成,对天线及整流电路进行仿真优化。经过实际加工测试,系统在2.45 GHz时输出电压为318 mV,对应的最大整流效率为13.5%。     

基于自适应遗传算法的模糊控制器应用研究

传统模糊控制器的设计主要依赖专家经验,存在较强的主观性和随意性,使得控制精度不高。为此,利用自适应遗传算法,优化设计了模糊控制器,并将其应用到三相异步电机的转差频率矢量调速系统中。仿真结果表明,控制效果好于PI控制。     

变速器试验台测控系统研发

设计了电封闭式变速器试验台测控系统,该系统以工业控制计算机为核心,基于虚拟仪器设计软件LabWindows开发平台研制,以PLC、数据采集卡为下位机,通过变频器控制驱动和负载电机,实现对汽车动力系统的模拟。系统按照参数实现对试验过程的自动控制,可根据需要对变速器进行多种项目的试验,实现了变速器综合性能的在线测试,该系统在实际运行中操作方便维护简便可靠性高。     

基于局部最小相关系数的自适应扩散迭代次数研究

针对典型Perona-Malik各向异性扩散去噪模型中采用固定迭代次数的不足,提出了一种自适应迭代次数确定算法,通过去噪后图像与噪声的局部最小相关系数来自动确定扩散迭代次数.实验结果表明:本文算法比传统算法去噪效果更好,同时也很好地保持了图像的边缘细节,且具有一定的通用性.     

低功耗设备常用储能元件的Peukert模型适用性分析

Peukert模型已被广泛用于铅酸电池、锂电池等储能元件的状态估计.然而,现有研究缺乏对低功耗设备常用储能元件和小电流工况的考虑,并且忽略了储能元件之间的横向对比分析.基于此,在小电流工况下,通过恒阻放电实验拟合建立了超级电容、碱性电池和锂亚电池的Peukert模型,验证并对比分析了Peukert模型对这三类储能元件的...