Adaptive Edge Detectors for Piecewise Smooth Data Based on the minmod Limiter

We are concerned with the detection of edges—the location and amplitudes of jump discontinuities of piecewise smooth data realized in terms of its discrete grid values. We discuss the interplay between two approaches. One approach, realized in the physical space, is based on local differences and is typically limited to low-order of accuracy. An alternative approach developed in our previous work [Gelb and Tadmor, Appl. Comp. Harmonic Anal., 7, 101–135 (1999)] and realized in the dual Fourier space, is based on concentration factors; with a proper choice of concentration factors one can achieve higher-orders—in fact in [Gelb and Tadmor, SIAM J. Numer. Anal., 38, 1389–1408 (2001)] we constructed exponentially accurate edge detectors. Since the stencil of these highly-accurate detectors is global, an outside threshold parameter is required to avoid oscillations in the immediate neighborhood of discontinuities. In this paper we introduce an adaptive edge detection procedure based on a cross-breading between the local and global detectors. This is achieved by using the minmod limiter to suppress spurious oscillations near discontinuities while retaining high-order accuracy away from the jumps. The resulting method provides a family of robust, parameter-free edge-detectors for piecewise smooth data. We conclude with a series of one- and two-dimensional simulations.To David Gottlieb, on his 60th birthday, with friendship and appreciation.     

Self-Irradiation Cascade Simulations in Plutonium Metal: Model Behavior at High Energy

The Modified Embedded Atom Method model for Pu metal is revised so that it more accurately captures the behavior of the Ziegler-Biersack-Littmark model of ion-ion interactions. Two revision are tested with somewhat different stiffnesses in the 2-1000 eV range. The revised models show higher damage levels at 20 KeV than an earlier model, suggesting that the behavior of the models above 100 eV is dominating damage production, at least in the earlier stages of the cascade. Work was performed at Los Alamos National Laboratory under the auspices of the US Department of Energy, under contract DE-AC52-06NA25396.     

电梯门机控制系统的运行曲线设计

为了实现电梯轿厢门的开门和关门快速且平稳地运行，介绍了一种基于高性能微型机的门机控制系统结构和门位移的检测原理，以门位移量作为控制系统的反馈量，对门机运行速度进行了分区设计。在高速附近的变化区，门机速度匀速变化时，进行了门机开门和关门控制曲线的计算，推导出运行位移与门机速度具有二次曲线的关系，进而对微型机控制的软件流程进行了设计，达到了门机高低速运行的平稳过渡。最后，给出了实际运行系统的主电路电压波形。     

The validity of psychophysiological detection of information with the Guilty Knowledge Test: A meta-analytic review.

The authors performed a meta-analysis based on 169 conditions, gathered from 80 laboratory studies, to estimate the validity of the Guilty Knowledge Test (GKT) with the electrodermal measure. The over-all average effect size was 1.55, but there were considerable variations among studies. In particular, mock-crime studies produced the highest average effect size (2.09). Three additional moderators, were identified: Motivational instructions, deceptive ("no") verbal responses, and the use of at least 5 questions were associated with enhanced validity. Finally, a set of 10 studies that best approximated applications of the GKT under optimal conditions produced an average effect size of 3.12. The authors discuss factors that might limit the generalizability of these results and recommend further research of the GKT in realistic setups. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

一种探测二维电磁目标的新方法

电磁目标的探测对通信而言有着十分重要的意义。本文描述一种收敛迅速、结果准确、抗强随机噪声的探测二维电磁目标的新方法。首先从体等效原理出发得到一个积分方程组，此方程组可求解散射问题。随后，对此方程组求变分，变形后得到散射场变化与介电参数变化之间关系的矩阵方程，即反演方程。文中列举了几个例子，通过数值实验结果证明本法收敛速度快、反演精度高、适应复杂目标的能力强，能抗强随机噪声干扰     

A neural network model for fault detection in conjunction with a programmable logic controller

This paper discusses the feasibility of using neural networks as a tool in the fault detection process. A neural network is integrated with a state language programmable logic controller, an important device in an automatic control system. Time series data related to time spent in a state is gathered and used as input into a neural network, for the purpose of identifying when a fault has occurred. A feedforward neural network is used to identify which (if any) of three types of faults may have occurred. Experimental results related to sensitivity and accuracy measures are presented. A brief review of related applications and research is also presented.     

HCMOS器件γ辐射损伤电路分析

本文对最基本的HCMOS器件(反相器和与非门)作了γ辐射损伤实验。通过器件性能变化,分析了γ辐射对电路的作用。     

Sub-optimal solutions to track detection problem using graph theoretic concepts

This paper demonstrates how the problem of tracking targets, which appear as either straight or curved lines in two-dimensional display images (or data images) can be formulated in terms of a directed weighted graph model and how dynamic programming techniques can be efficiently applied to reach an optimal or sub-optimal solution. In general, track detection algorithms providing optimal solutions have good detective ability, but most of them suffer from the inability to detect discontinuous lines or to resolve efficiently pairs of crossing lines. A sub-optimal solution is provided that efficiently overcomes these weaknesses. We focus on modeling the track detection problem in terms of a graph, formulating fast sequential/parallel sub-optimal track detection algorithms and testing them on simulated data in order to show their detective ability. Moreover, we specify the conditions under which sub-optimal algorithms can perform at least as well as their corresponding optimal algorithms. This is significant for the track detection problem where fast, accurate and real-time detection is considered a necessity.     

螺杆泵的检测方法及检测标准制定

螺杆泵检测是避免不合格螺杆泵下井、螺杆泵早期失效和提高螺杆泵使用寿命与采油效益的重要技术手段。重点介绍了模拟不同工况的螺杆泵工作特性检测系统及检测定子通径为10－60mm的定子衬套偏心度检测仪的组成及其检测方法和原理。针对大庆油田的实际情况，在进行大量室内和现场试验的基础上，制定了GLB120－27、GLB40－42和GLB500－14型螺杆泵的检测标准。检测技术及其标准实施以来见到了明显效果。