Strong diagnosability of regular networks under the comparison model

Diagnosability has played an important role in the reliability of multiprocessor systems. The strongly t-diagnosable system is (t+1) diagnosable except when all of the neighbors of a node are simultaneously faulty. In this paper, we discuss the in-depth properties of diagnosability for t-regular and t-connected networks under the comparison model. We show that a t-regular and t-connected multiprocessor system with at least 2t+6 nodes, for t?4, is strongly t-diagnosable under the comparison model if the following two conditions hold: (1) the system is triangle free, and (2) there are at most t−2 common neighbors for each pair of distinct nodes in the system.     

A comparison of multiprocessor task scheduling algorithms with communication costs

Both parallel and distributed network environment systems play a vital role in the improvement of high performance computing. Of primary concern when analyzing these systems is multiprocessor task scheduling. Therefore, this paper addresses the challenge of multiprocessor task scheduling parallel programs, represented as directed acyclic task graph (DAG), for execution on multiprocessors with communication costs. Moreover, we investigate an alternative paradigm, where genetic algorithms (GAs) have recently received much attention, which is a class of robust stochastic search algorithms for various combinatorial optimization problems. We design the new encoding mechanism with a multi-functional chromosome that uses the priority representation—the so-called priority-based multi-chromosome (PMC). PMC can efficiently represent a task schedule and assign tasks to processors. The proposed priority-based GA has show effective performance in various parallel environments for scheduling methods.     

残差噪声模型在PMC技术中的应用

PMC技术在提高语音识别的鲁棒性方面发挥重要作用。但PMC技术仍存在一些难点：如何获得精确的卷积噪声模型；如何在低信噪比情况下提高识别性能。该文提出了PMC技术的改进方法：引入新的残差噪声模型以及伪干净语音模型，结合信号增强技术，能有效地提高系统的鲁棒性。实验是在英国剑桥大学的HTK语音识别工具包的基础上进行，结果表明，新的PMC技术在噪声环境下能显著提高识别性能。     

PMC故障模型的方程诊断

首次建立起PMC方程模型的定义(即PMC模型的方程描述).PMC模型是一种最常见的系统级故障模型,针对传统的图论诊断算法离不开"t-可诊断性"和"相信大多数"(即假定系统中故障机的台数少于处理机总台数的一半)的特点,文中引入"绝对故障基"等概念,并充分运用"集团"工具,在不以"t-可诊断性"和"相信大多数"作前提假设的情况下,找到了求PMC模型全体相容故障模式的具体方法——方程诊断算法.     

基于互测PMC模型的强t-可诊断系统集团算法

定义了基于互测PMC模型的强t-可诊断系统，提出了一系列的性质和定理，提出了系统级故障诊断的集团算法，从而减少了系统级故障诊断的复杂度。     

PMC在数控系统中的开发及应用

以数控机床主轴控制系统为例,分析了运用FANUC数控系统中的内装式可编程机床控制器(PMC)对机床动作的逻辑控制开发。同时,讨论了PMC在机床中的应用。这种方式代替了传统的控制方式,从而大大减少了电气元件的数量,简化了控制方式,提高了系统的可靠性及可维护性。     

PMC管理服务质量评价

上世纪90年代末期PMC管理模式传入我国,经过十多年的发展目前虽然在一些项目中逐步推广,但仍然处于起步阶段.为推动PMC在国内的快速发展,不断提升我国的项目管理质量,本文诠释了PMC管理模式的主要内容,提出了PMC管理方式的工作流程;构造了以PMC委托管理合同为基础,以达到客户满意为目标的项目管理质量评价体系.根据指标体系的具体特点,提出了通过专家调查与层次分析相结合的指标权重确定方法,并建立了模糊综合评价模型对PMC管理服务质量进行定量计算.     

刀具寿命结束的报警处理

介绍Fanuc系统刀具寿命结束时发出报警的方式;对该报警处理不当使得系统自动加工程序中止,造成正在加工工件报废的原因;以及如何修改相关的PMC和NC程序,避免工件报废事件的发生.     

Local diagnosability of generic star-pyramid graph

The problem of fault diagnosis in network has been discussed widely. In this paper, we study the local diagnosability of a generic star-pyramid graph. We prove that under the PMC model the local diagnosability of each vertex in a generic star-pyramid graph is equal to its degree and the generic star-pyramid has the strong local diagnosability property. Then we study the local diagnosability of a faulty graph. After showing some properties of the graph, we prove that a generic star-pyramid graph keeps the strong property no matter how many edges are faulty under the condition that each vertex is incident with at least four fault-free edges.     

Electrically Conductive Carbon Nanofiber Composites with High-Density Polyethylene and Glass Fibers

Carbon nanofibers are being investigated for incorporation into composites to improve mechanical, thermal, and electrical properties. The difficulties in making such composites are issues of dispersion of the nanofiber and wetting of the nanofibers by the matrix. The processing methods developed to date tend to be complex, involving multiple steps. This paper reports on a study to make electrically conductive composites with small volume fraction of vapor-grown carbon nanofibers (VGCF). The matrix is a high-density polyethylene (HDPE); the effect of adding glass fibers to this composite is also studied. Certain types of the VGCF fibers did not produce conductive composites with standard mixing techniques; however, VGCF nanofibers heat treated with a post-processing surface treatment produced conductive composites without extensive or vigorous dispersion techniques. The results indicate that surface treatments and dispersion methods are important factors in producing conductive composites. It is demonstrated that small volume fractions of nanofiber can be used to produce conductive composites without extensive processing steps.