An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

基于Internet的远程教育系统模型研究

随着计算机网络技术的发展，远程教学系统的结构发生了重大的变化，逐步由原来的客户机／服务器(C／S)结构转变为基于Internet的浏览器／服务器(B／S)结构。本文提出了基于CORBA技术的B／S结构系统模型。分析了其运行过程，并与传统的结构进行了比较，指明了其优越性。在本文的结尾。指出了使用这种技术的一个具体例子。     

汽车计算平台工程国外相关标准概述

结合我国汽车计算平台工程,分析了国外相关的标准现状和基本框架,并为今后工作的开展提出了建议.     

令牌多环网性能—可靠性综合评价

网络的性能与可靠性已分别得到广泛的研究,然而,怎样分析具有容错机制的环网的性能仍属有待开拓的研究领域,本文提出了一种分析具有自修复机制的多环网络系统的方法,并给出了报文传输时间分布的拉氏变换式,平均等待时间及平均队列长度公式,分析结果可用于评估故障与修复过程对实时令牌环网的实时响应特性的影响,对基于LAN的分布式实时系统设计具有指导意义。     

海洋石油开发工业污染物产生系数和排放系数研究

污染物产生系数和排放系数是工程环境影响评价的重要指标,但对于海洋石油开发工程环境影响评价来说,迄今尚无具权威性的系数可资使用。在我国近海石油开发工程污染源系统调查的基础上,对海洋石油开发行业污染物产生系数和排放系数的定义、计算方法、应用范围及应用方式进行了探讨,研究结果可为海洋石油开发工程项目环境影响评价及环境保护管理,以及行业或企业有关标准的制定提供参考。     

Public grid computing participation: An exploratory study of determinants

Using the Internet, “public” computing grids can be assembled using “volunteered” PCs. To achieve this, volunteers download and install a software application capable of sensing periods of low local processor activity. During such times, this program on the local PC downloads and processes a subset of the project's data. At the completion of processing, the results are uploaded to the project and the cycle repeats.     

Minimum spanning trees made easier via multi-objective optimization

Many real-world problems are multi-objective optimization problems and evolutionary algorithms are quite successful on such problems. Since the task is to compute or approximate the Pareto front, multi-objective optimization problems are considered as more difficult than single-objective problems. One should not forget that the fitness vector with respect to more than one objective contains more information that in principle can direct the search of evolutionary algorithms. Therefore, it is possible that a single-objective problem can be solved more efficiently via a generalized multi-objective model of the problem. That this is indeed the case is proved by investigating the computation of minimum spanning trees.This work was supported by the Deutsche Forschungsgemeinschaft (DFG) as part of the Collaborative Research Center Computational Intelligence (SFB 531) and by the German-Israeli Foundation (GIF) in the project Robustness Aspects of Algorithms.     

网格计算及其应用

网络计算给互联网带来了新的活力，它是一种新型的分布计算技术，致力于解决复杂度很高的新应用问题，文中简述了网格计算的定义、体系结构、关键问题、当前几个有代表性的网格系统以及网格应用实例，并分析了风格计算发展趋势。     

可编程光学二值双轨逻辑门

基于双轨逻辑,本文提出一种可级联的并行二值逻辑门。所有十六种二值逻辑运算可以采用偏振半波相延编程来实现。也提出了用电光晶体实现实时编程的方法。本文中给出了实验结果。