The vulnerability of structures to unforeseen events

A structure is vulnerable to an unforeseen event if it is not sufficiently robust. One insight into the lack of robustness is gained through the vulnerability of a structure to disproportionate collapse. In this paper, the importance of assessing the vulnerability of a structure to unforeseen events is highlighted and the nature of unforeseen events examined. A theory of structural vulnerability which examines the form of the structure to determine the most vulnerable sequence of failure events is briefly described. The potential for damage to propagate through a structure is examined through a new measure of hazard potential and vertical pushover analysis. An analysis of an example structure shows that such an approach is able to capture the weaknesses in a structure either due to form or external actions.     

Modular multi-channel data acquisition systems

A flexible approach to complexity-reduced multi-channel data acquisition from a large quantity of sensors, essential for connecting computers with real world objects, is discussed and the obtained experience in this area is summarized. Data acquisition from wideband, event timing, and large distributed clusters of signal sources are discussed with emphasis on methods and algorithms providing for data gathering from large sensor systems. We discuss special signal digitizing techniques, including pseudorandomized multiplexing, time-to-digital conversions, and signal sample value-taking at time instants when the input signal crosses a sinusoidal reference function. The versatility of the data acquisition systems is achieved by using modular system design. To achieve the maximum from the suggested data acquisition technology, the acquired data processing is based on the theory of digital alias-free signal processing. The text was submitted by the authors in English.     

Implementing a hybrid simulation model for a Kanban-based material handling system

Plant floor material handling is a loose loop in most assembly plants. Simulation offers a quick, controllable and tunable approach for prototyping complex material handling processes in manufacturing environments. This paper proposes a hybrid simulation approach, using both discrete event and agent-based technologies, to model complex material handling processes in an assembly line. A prototype system is implemented using a commercial multi-paradigm modeling tool. In this prototype, JIT principles are applied to both the production and the material handling processes. The system performance is evaluated and system optimization directions are suggested. The proposed hybrid modeling approach facilitates the implementation of a responsive and adaptive environment in that various “what-if” scenarios can be simulated under different simulation configurations and real-time situations.     

Diagnosability Analysis of a Class of Hierarchical State Machines

This paper addresses the problem of fault detection and isolation for a particular class of discrete event dynamical systems called hierarchical finite state machines (HFSMs). A new version of the property of diagnosability for discrete event systems tailored to HFSMs is introduced. This notion, called L₁-diagnosability, captures the possibility of detecting an unobservable fault event using only high level observations of the behavior of an HFSM. Algorithms for testing L₁-diagnosability are presented. In addition, new methodologies are presented for studying the diagnosability properties of HFSMs that are not L₁-diagnosable. These methodologies avoid the complete expansion of an HFSM into its corresponding flat automaton by focusing the expansion on problematic indeterminate cycles only in the associated extended diagnoser.

一个模拟网格上并行作业调度的离散事件系统

为评估计算网格上并行作业的无中心式调度,设计了基于离散事件的模拟系统J3S.离散事件包括作业提交、开始和终止,作业状态可以是等待、运行或完成.事件引起作业状态的变化 ,并触发网格层次或本地层次调度.作业由网格工作负荷模型产生,该模型基于并行计算机工作负荷模型构建.网格层次调度通过网格调度器之间的协作完成.本地层次调度模拟改进的装填法,使作业可有不同的调度优先级.网格资源性能可有差异,作业执行性能依赖作业指派.模块化实现使J3S可模拟网格上并行作业的无中心式调度的各种场景.     

基于序列聚类的事件流数据特征分析

事件流是近年来兴起的一种对实时进入系统的海量数据进行分析查询的应用,而数据特征是评价系统所需要的负载模型的重要部分。以网络安全监控为背景,提出一种将事件流聚集成时间序列并进行相似性聚类来分析数据特征的方法。通过适当的粒度聚合,将事件流转化成时间序列,选取周期性的时间序列作为代表消除随机干扰,给出基于序列线性相似性的聚类算法。聚类试验表明,具有相似时间特征的事件流可以被有效地聚集到同一类中。     

Ad Hoc入侵检测监视节点的自适应选择算法

提出一种监视节点基于事件触发机制的自适应选择算法(ETBAS),引入监视节点的监视状态,通过事件触发使非监视节点进入唤醒状态进行入侵检测,或使监视节点进入睡眠状态停止入侵检测。触发事件包括相邻节点的推选、节点能源低于某个阈值、网络拓扑结构的变化等。ETBAS具有自适应性,无论监视节点离开网络还是新节点进入网络,通过与相邻节点的信息交互,都能实现局部网络监视节点的自动更新。     

移动位置服务中一种空间智能发布系统模型

与现有的位置服务模式相比,基于Push(推)模式的位置服务有着更加广阔的市场前景,是目前国内外研究的焦点.该模式的位置服务依赖于现存的空间发布系统,而目前空间发布系统由于条件的限制不能有效地完成空间事件的预订和发布.阐述了目前空间发布系统中两种常见的空间事件以及空间事件的预订,随后提出一种空间智能发布系统模型,有效地解决了无线通信的带宽限制问题并提高了空间发布系统的性能.     

事件演算在行动推理中的应用

事件演算是基于一阶谓词演算的行动推理理论.它可作为描述事件的一个工具,在行动推理的应用中显示出其强大的表示能力和实现能力.在事件演算中,可以对行动进行公理化,可以描述行动的时间性、并发性、连续变化及知识,而且还可用Prolog实现.讨论介绍与这些应用相关的基本概念、思想和方法等,并且通过一个送咖啡的例子说明了如何通过事件演算来描述和实现.