基于乘客多运动行为的公交客流计数判定方法

针对基于单目视觉的公交乘客人数统计判定方法不稳定、计数结果不准确的现状,结合公交车门附近乘客运动行为的复杂性和多样性,以及乘客运动行为对计数判定方法的干扰,给出一种基于乘客多运动行为分析的计数判定方法。采用轨迹聚类的方式对乘客运动行为进行分析,结合轨迹的空间特征和方向特征计算轨迹距离,并使用层次聚类方法进行聚类。分析聚类结果中每一类别所对应乘客类的运动行为,讨论各乘客类的运动行为对常用计数判定准则的影响,由此提出一种改进的公交车客流计数判定方法。利用采集的乘客上下公交车视频图像进行实验,结果表明,该方法能获得较高的统计精度和较好的稳定性。     

基于SKPCA的卫星整流罩空调系统传感器故障检测研究

针对卫星整流罩空调系统对传感器故障检测的高可靠性的要求,在分析常见故障模式的基础上,采用了基于统计量核主元分析（ SKPCA）的故障检测方法,建立整流罩空调系统传感器故障检测模型,对整流罩空调系统传感器容易出现的偏置故障进行了验证实验。实验结果验证了SKPCA方法在整流罩空调系统传感器故障检测中的正确性和有效性。     

一种基于密度的不确定数据离群点检测算法

不确定数据普遍存在于如移动计算、RFID技术和传感器网络等大量应用之中.由于不确定数据的离群点检测算法可以提高服务质量,提出一种基于密度的不确定数据离群检测算法RLOF.该算法引入一种R2-tree结构,有效降低了计算局部离群因子时的时间复杂度,同时降低了不确定数据集中的数据更新成本以及海量数据维护成本.理论分析和实验结果充分证明了该算法是有效可行的.     

线性时滞系统稳定的充分必要条件

提出一个新的线性时滞系统稳定的充分必要条件,与以前的结论不同的是,我们的结论的表达形式更容易数值计算。开发相应的二种收敛算法,解决系统时滞独立稳定判断和时滞相关稳定的时滞界估计。本文给出范数有界不确定性时,系统稳定的充分条件。文末给出的数值实例证明本文结果降低计算复杂度,改进了时滞估计保守性。     

基于Web的集群管理系统结构

介绍高性能计算集群管理现状, 并根据目前管理缺点与不足, 对集群管理系统进行了总体框架设计, 利用Linux中/proc文件系统、MySQL数据库及Web技术, 对管理数据采集、数据存储及应用接口进行了功能设计, 最终实现了在统一Web界面中对集群系统运行实时情况、历史数据统计与分析进行管理.     

基于改进Kalman滤波的可见光极小目标TBD跟踪方法

针对无人机可见光图像极小目标跟踪问题,本文提出一种基于改进卡尔曼滤波的 (Tracking before detection,TBD)跟踪方法。首先利用检测算法定位目标位置作为卡尔曼滤波的测量值,检测过程中的匹配相似度参数作为卡尔曼滤波测量噪声协方差矩阵的参照依据,其次利用卡尔曼滤波建立跟踪框架预测下一帧的目标位置,最后检测模块以预测位置为 参考位置进行局部搜索,完成整个检测跟踪过程。为了提高跟踪效率,本文根据检测和预测位置积累误差判决检测模式,误差超过门限值则采取全局检测模式消除积累误差,否 则使用局部检测模式,降低TBD跟踪算法的运算复杂度。仿真实验证明,本文方法可以有效检测跟踪极小目标,提高跟踪的实时处理能力。     

On Constrained MMVC of Discrete‐Time First‐Order Linear Stochastic Systems with PSI I: The Critically Stable Case

This paper is devoted to the study of the modified minimal variance control (MMVC) of discrete‐time first‐order linear critically stable stochastic systems with prospective strong intervention (PSI) and control input constraints. Due to different evolutionary characteristics of systems with PSI, that is, the two modes of tending to infinity and having bounded oscillations, the discrete‐time first‐order linear critically stable systems can be partitioned into two types regarding the signs of a key system parameter a. A necessary and sufficient condition for the state mean convergence of a system with a = 1 is derived and the corresponding design of MMVC is formulated. For the critical stable system with a =? 1, its oscillation amplitudes of state means can be effectively suppressed or the means can converge under control. Finally, the effectiveness and advantages of the proposed control strategies comparing with MVC are confirmed by numerical simulations.     

Build It (and Customize and Market It) and They Will Come

ABSTRACT

Like other academic libraries, the University Library System of the University of Pittsburgh (ULS) continues to invest in providing anytime, anywhere access to research materials in electronic format. While there are obvious benefits for users in this concomitant increase in complexity for these same users, with many of them, especially undergraduates, turning to the speed and simplicity of Google and away from the complexity of library sponsored electronic resources. Seeking ways to both maximize our investment in full text resources, and promote easy access to this universe of electronic resources for our users, the ULS felt strongly that a navigational solution had to be found, and in 2004 began the process of implementing a federated search tool.

This article discusses the collaborative process between the University Library System and its federated search vendor, and discusses the decision making process behind the customizations made by the ULS to its federated search system. The article also addresses the process of working with a professional marketing organization to developing a marketing message and supporting materials to promote its federated search system, and finally briefly looks at usability and usage statistics to assess the degree to which the Zoom! federated search system has met the goal of providing fast, easy access to high quality information. doi:10.1300/J136v12n03_07     

Adaptive Decentralized NN Control of Nonlinear Interconnected Time‐Delay Systems with Input Saturation

In this paper, a novel decentralized adaptive neural control scheme is proposed for a class of interconnected large‐scale uncertain nonlinear time‐delay systems with input saturation. Radial basis function (RBF) neural networks (NNs) are used to tackle unknown nonlinear functions. Then, the decentralized adaptive NN tracking controller is constructed by combining Lyapunov–Krasovskii functions and the dynamic surface control (DSC) technique, along with the minimal‐learning‐parameters (MLP) algorithm. The stability analysis subject to the effect of input saturation constraints are conducted with the help of an auxiliary design system based on the Lyapunov–Krasovskii method. The proposed controller guarantees uniform ultimate boundedness (UUB) of all of the signals in the closed‐loop large‐scale system, while the tracking errors converge to a small neighborhood around the origin. An advantage of the proposed control scheme lies in the number of adaptive parameters of the whole system being reduced to one and in the solution of the three problems of “computational explosion,” “dimension curse,” and “controller singularity”. Finally, simulation results along with comparisons are presented to demonstrate the advantages, effectiveness, and performance of the proposed scheme.     

基于工作流和数理统计的引供水事故应急预案系统

针对引供水工程中如何预防事故和提高事故处理能力的问题,研究并提出了基于面向服务和工作流模型的自动化事故应急预案系统,实现事故的早期侦测、智能诊断和处理流程的自动化、规范化.在已发生的各种事故处理信息的基础上,通过数理统计模型对单个事故预案的各个步骤以及全局事故的险情种类、时间、地域等各个属性进行统计、分析、挖掘,得出预案自优化和事故预防的建议报告,实现事故预警和处理中的决策支持.