An efficient fault-containing self-stabilizing algorithm for finding a maximal independent set

An independent set is a useful structure because, in some situations, it defines a set of mutually compatible operations, i.e., operations that can be executed simultaneously. We design a fault-containing self-stabilizing algorithm that finds a maximal independent set for an asynchronous distributed system. Our algorithm is an improvement on the self-stabilizing algorithm in Shukla et al. [1995]. In the single-fault situation, the worst-case stabilization time of Shukla's algorithm is /spl Omega/(n), where n is the number of nodes in the system, whereas the worst-case stabilization time of our algorithm is O(/spl Delta/), where /spl Delta/ is the maximum node degree in the system. Compared also with the fault-containing algorithm that is induced from applying the general transformer in Ghosh et al. [1996] to Shukla's algorithm, our algorithm is also seen to be faster in stabilization time, in the single-fault situation. Therefore, our algorithm can be considered to be the most efficient fault-containing self-stabilizing algorithm for the maximal independent set finding up to this point.     

Effect of trimethylsilane flow rate on the growth of SiC thin-films for fiber-optic temperature sensors

We have investigated the effect of trimethylsilane ([(CH/sub 3/)/sub 3/SiH] or 3MS) flow rate on the growth of SiC thin-film on single-crystal sapphire substrate for fiber-optic temperature sensor. The SiC film thickness was in the range of 2-3 /spl mu/m. The variation of the 3MS flow rate affected the structural properties of the SiC films. This, in turn, changed the optical properties and temperature sensing performance of the sensors. Optical reflection from the SiC thin-film Fabry-Pe/spl acute/rot interferometers showed one-way phase shifts in resonant minima on all measured samples. Linear fits to the resonant minima (at 660 to 710 nm) versus temperature provide the corresponding thermal expansion coefficient, /spl kappa//sub /spl phi//, of 1.7-1.9/spl times/10/sup -5///spl deg/C. With the optimized 3MS flow rate, the SiC temperature sensor exhibits a temperature accuracy of /spl plusmn/2.8/spl deg/C from 22 to 540/spl deg/C. The short-term SiC sensor stability at 532/spl deg/C for two weeks shows a very small standard deviation of 0.97/spl deg/C.     

A multiple electrostatic electrodes torsion micromirror device with linear stepping angle effect

Torsion micromirror devices that can achieve linear stepping angle effects play an important role in optical MEMS applications. However, traditional torsion micromirror devices driven by a single electrostatic electrode have difficulty meeting this requirement due to their nonlinear angle-voltage transfer characteristics. In this regard, the concept of a multiple-electrodecontrolled micromirror is proposed to eliminate this drawback. Through this novel design, linear stepping angles can be easily achieved by a set of linearly varied or constantly applied voltages. A simple mathematical model has been developed to predict the angle-voltage transfer characteristics of the proposed device and has been simulated with finite element simulations. The corresponding control strategies of this device, named the linear control strategy and the digital control strategy, are also proposed in this paper. The Cronos/MEMSCAP Multi-User MEMS Process (MUMPs) was used in conjunction with flip-chip bonding technology to fabricate the proposed torsion micromirror device. Experimental data indicates that the relative stepping angle error, between the fabricated device and the mathematical model, are within 5%.     

Intelligent remote monitoring and diagnosis of manufacturing processes using an integrated approach of neural networks and rough sets

This research develops a methodology for the intelligent remote monitoring and diagnosis of manufacturing processes. A back propagation neural network monitors a manufacturing process and identifies faulty quality categories of the products being produced. For diagnosis of the process, rough set is used to extract the causal relationship between manufacturing parameters and product quality measures. Therefore, an integration of neural networks and a rough set approach not only provides information about what is expected to happen, but also reveals why this has occurred and how to recover from the abnormal condition with specific guidelines on process parameter settings. The methodology is successfully implemented in an Ethernet network environment with sensors and PLC connected to the manufacturing processes and control computers. In an application to a manufacturing system that makes conveyor belts, the back propagation neural network accurately classified quality faults, such as wrinkles and uneven thickness. The rough set also determined the causal relationships between manufacturing parameters, e.g., process temperature, and output quality measures. In addition, rough set provided operating guidelines on specific settings of process parameters to the operators to correct the detected quality problems. The successful implementation of the developed methodology also lays a solid foundation for the development of Internet-based e-manufacturing.     

Recurrent Neuro-Fuzzy Modeling and Fuzzy MDPP Control for Flexible Servomechanisms

This paper considers the nonlinear system identification and control for flexible servomechanisms. A multi-step-ahead recurrent neuro-fuzzy model consisting of local linear ARMA (autoregressive moving average) models with bias terms is suggested for approximating the dynamic behavior of a servomechanism including the effects of flexibility and friction. The RLS (recursive least squares) algorithm is adopted for obtaining the optimal consequent parameters of the rules. Within each fuzzy operating region, a local MDPP (minimum degree pole placement) control law with integral action can be constructed based on the estimated local model. Then a fuzzy controller composed of these local MDPP controls can be easily constructed for the servomechanism. The techniques are illustrated using computer simulations.     

Finding Optimal Ordering of Sparse Matrices for Column-Oriented Parallel Cholesky Factorization

In this paper, we consider the problem of finding fill-preserving sparse matrix orderings for parallel factorization. That is, given a large sparse symmetric and positive definite matrix A that has been ordered by some fill-reducing ordering, we want to determine a reordering that is appropriate in terms of preserving the sparsity and minimizing the cost to perform the Cholesky factorization in parallel. Past researches on this problem all are based on the elimination tree model, in which each node represents the task for factoring a column, and thus, can be seen as a coarse-grained task dependence model. To exploit more parallelism, Joseph Liu proposed a medium-grained task model, called the column task graph, and showed that it is amenable to the shared-memory supercomputers. Based on the column task graph, we devise a greedy reordering algorithm, and show that our algorithm can find the optimal ordering among the class of all fill-preserving orderings of the given sparse matrix A.     

战略模拟中群决策方法管理平台的设计与实现

在综合集成的战略决策模拟环境中，多人研讨是主要的工作方式，利用多个领域的专家们的经验和智慧来对战略问题做出定性定量结合的判断。该文在分析典型群决策过程的基础上，分析和提出了战略决策研讨与模拟环境SDS2002中的群决策方法管理平台的服务机制，并给出了基于Bxchange 2000 Server的实现方案。     

智能在线电导率分析仪的设计与实现

介绍了一个利用单片机技术的智能在线电导率分析仪的设计 ,给出了系统的硬件结构和软件设计的思路。本设计符合工厂应用的要求 ,可以由用户自己定义、自己设计 ,以满足不同的要求     

结构测试中的路径产生

通常在结构测试的过程中首先就是测试路径的产生，接着是生成指定路径的测试用例。文章阐述了一种路径产生的方法，重点讨论了控制关系和非约束边集合在路径产生中的作用。     

基于VC的棒材自动计数方法的研究与应用

本文提出了一种利用图像技术实现棒材的自动计数的方法，该方法以Visual C 6.0为开发平台，实现了对棒材端面图像分割，然后对分割得到的二值图像实施形态学运算，使粘连部分彼此分离，最后通过8－邻域标注计数。