Discrete choice in commuter space: Small area analysis of diurnal population change in the Tokyo Metropolitan Region

Considerations of metropolitan commuting have often related to urban space as a continuum, and to commuting itself as a process. This approach has led to escalating complexity in the measurement, modeling and analysis of commuting, often with no commensurate results. The present study extends an alternative approach that considers commuter space of a metropolis as a discrete set of small areas. Each small area throughout the metropolis is a nighttime location of some households and, as a possible discrete destination choice of individuals within households, each subarea is also a daytime location of some persons. Each subarea, therefore, may be thought of as attaining two values, corresponding to its daytime (e.g., noontime) and nighttime (e.g., midnight) populations. The diurnal demographic shift of subareas, as a set of binary events, or toggles, between daytime and nighttime populations, is associated with commuter access throughout the metropolis. Diurnal shift offers structural simplicity aimed at estimating small-area daytime populations across a metropolitan region that might suitably precede and complement conventional continuum considerations of commuting. Using data for the Tokyo Metropolitan Region, we identify average household size as the nighttime indicator of small-areas, and daytime population density as their daytime indicator. The potential for the estimation of daytime populations across metropolitan regions where daytime population data are unavailable, is underscored by the clear tendency towards inverse relation of these two indicators of diurnal shift.     

基于OWPB和LS-SVM的电路板故障诊断系统

针对雷达电路板检修困难的问题,提出了基于最优小波包基和最小二乘支持向量机相结合的雷达电路板故障诊断方法。利用小波变换对采样数据进行去噪处理,通过小波包分解选择最优小波包基提取熵值作为故障特征向量,并作为基于最小二乘支持向量机的雷达故障诊断模型的输入向量,经诊断模型输出后,完成雷达电路板故障诊断。基于此方法设计了雷达电路板故障诊断系统,提高了雷达故障诊断的正确性和效率。     

Construction and properties of spline dyadic wavelet filters

This paper focuses on the construction and properties of spline dyadic wavelet that equals its reconstruction wavelet. A general construction method of finite spline dyadic low-pass and high-pass filters is given. It proves that finite spline dyadic low-pass filters are symmetric about 0 or 1/2, but there are no finite spline high-pass filters possessing symmetry with respect to 0 or 1/2. It further shows that there exist infinite spline high-pass filters possessing symmetry with respect to 0 or 1/2, which can be constructed. Their energy is concentrated and so finite symmetric spline dyadic wavelet filter that equals its reconstruction filter can be obtained approximately. Construction examples for quadratic and cubic spline dyadic wavelet filters are given.     

Modeling and control of discrete event systems using finite state machines with variables and their applications in power grids

Control theories for discrete event systems modeled as finite state machines have been well developed to address various fundamental control issues. However, finite state machine model has long suffered from the problem of state explosion that renders it unsuitable for some practical applications. In an attempt to mitigate the state explosion problem, we propose an efficient representation that appends finite sets of variables to finite state machines in modeling discrete event systems. We also present the control synthesis techniques for such finite state machines with variables (FSMwV). We first present our notion and means of control under this representation. We next present our algorithms for both offline and online synthesis of safety control policies. We then apply these results to the control of electric power grids.     

2D representation of facial surfaces for multi-pose 3D face recognition

The increasing availability of 3D facial data offers the potential to overcome the intrinsic difficulties faced by conventional face recognition using 2D images. Instead of extending 2D recognition algorithms for 3D purpose, this letter proposes a novel strategy for 3D face recognition from the perspective of representing each 3D facial surface with a 2D attribute image and taking the advantage of the advances in 2D face recognition. In our approach, each 3D facial surface is mapped homeomorphically onto a 2D lattice, where the value at each site is an attribute that represents the local 3D geometrical or textural properties on the surface, therefore invariant to pose changes. This lattice is then interpolated to generate a 2D attribute image. 3D face recognition can be achieved by applying the traditional 2D face recognition techniques to obtained attribute images. In this study, we chose the pose invariant local mean curvature calculated at each vertex on the 3D facial surface to construct the 2D attribute image and adopted the eigenface algorithm for attribute image recognition. We compared our approach to state-of-the-art 3D face recognition algorithms in the FRGC (Version 2.0), GavabDB and NPU3D database. Our results show that the proposed approach has improved the robustness to head pose variation and can produce more accurate 3D multi-pose face recognition.     

Sink placement on a 3D terrain for border surveillance in wireless sensor networks

With their distributed nature and redundant operation capability, wireless sensor networks are very suitable for border surveillance scenarios that track intruders trying to breach to a safe side. In such scenarios, keeping the operation going on for as long as possible is the most important aspect of the network. We propose that by placing sink at a carefully selected coordinate will results in a longer living network. We also place restrictions on the candidate locations so that the sensing quality of the network is above a useful predetermined value and the sink is placed in a relatively safe location to avoid destruction. In order to find the suitable coordinates we propose a modified lifetime metric which takes quality and safety measures into account. We also propose a genetic algorithm which uses a discrete event simulator-in-the-loop over a three dimensional terrain to find locations for the sink that fits the given quality and safety restrictions. Using a three dimensional underlying terrain makes the proposed approach more realistic. The results obtained for various sensor network scenarios indicate that the proposed algorithm can find locations that increase the lifetime by also considering the sensing quality and safety.     

灰度投影积分极值法的矩形检测

现有的矩形识别方法存在检测速度慢、识别率低和精度不足等问题,不能满足现代工业在线检测发展的需求。为此,提出一种灰度投影积分极值法的矩形检测方法,把待检测图像沿0~π方向进行投影得到灰度投影积分(GPI)矩阵,求得GPI矩阵中极值点的位置,将其保存为新的矩阵GPIEV,并在GPIEV矩阵中搜索平行线重构矩形。实验结果表明,该方法具有较好的抗干扰能力,且运算速度快,能够满足实时处理的要求。     

一种新的NSCT超分辨率图像复原技术

考虑到非下采样Contourlet变换具有多尺度性和多方向性,提出了一种基于非下采样Contourlet变换的图像复原算法.首先对给出的序列低分辨率图像进行图像配准,对配准图像进行非下采样Contourlet变换,分解成低频及高频部分,对低频和高频分别采取不同的融合策略进行融合,再对融合后的高频和低频进行非下采样Contourlet变换逆变换得到融合图像.对融合后的图像再进行非下采样Contourlet变换,分别对高频细节和低频进行插值,再经非下采样Contourlet逆变换复原成高分辨率的图像.实验表明,该算法在主观效果和客观评价上均优于传统复原算法,是一种可行的图像复原新算法.     

小波变换提取电力电容器局部放电信号研究

为了消除电力电容器局部放电信号的噪声,提高电力电容器局部放电信号在线检测的有效性,提出基于小波变换阈值消噪方法的电力电容器局部放电信号提取方法。选择合适的小波基函数和分解层数对信号进行小波分解,确定合适的阈值规则以及阈值估计方法对小波分解系数进行阈值量化处理,从而得到消噪后的局部放电信号。以均方根误差RMSE和信噪比RSN为衡量指标,分析了小波基函数、分解层数、阈值规则和阈值估计方法等对消噪效果的影响。结果表明,当选择db2小波作为最优小波基函数,分解层数定为6层时,利用最大最小准则阈值估计法估计的阈值在软阈值规则下能有效提取电力电容器局部放电信号,达到了最优去噪效果。