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.     

Animations showing Lego manipulative tasks: Three potential moderators of effectiveness

Evidence suggests that transient visual information, such as animations, may be more challenging to learn than static visualizations. However, when a procedural-manipulative task is involved, our evolved embodied cognition seems to reverse this transitory challenge. Hence, for object manipulative tasks, instructional animations may be more suitable than statics. We investigated this argument further by comparing animations with statics using a Lego task shown to university students, by examining three potential moderators of effectiveness: (a) the environment of manipulation (virtual or physical), (b) the quality of visual information (focused or unfocused), and (c) the presence of hands (no hands or with hands). In Experiment 1 we found an advantage of animation over statics, and no differences among the environments. In Experiment 2, we again observed an animation advantage, a small advantage of focused static information compared to unfocused static information, and a positive effect of not showing the hands.     

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.     

动力环境集中监控系统可靠性的提高

为实现电源设备乃至通信机房的少人或无人值守和集中维护,必须建立一套完善的电信局动力环境集中监控系统。文中结合番禺区电信局的实际,讨论了提高系统运行可靠性的几点措施,包括硬件方面与软件方面的手段,关键在于加强系统的运行管理。     

动力环境网络监控精细管理

叙述动力环境运行质量分析管理，包括故障管理，性能管理和专题分析管理，以动力环境网络监控细致八微、言之有据的月度分析管理实例展现了其精细管理的效果。     

基于ADSP21XXC运行环境下FFT的实现

介绍了数字信号处理器ADSP21XX芯片的特点以及实现FFT(快速离散付里叶变换)的方法，给出了ADSP21XX的C和汇编混合编程的特点及技巧。     

核电材料在模拟反应堆环境中应力腐蚀破裂测试技术与性能评价

简要介绍了采用慢应变速率试验，Ｕ型弯曲和Ｃ形环试验等技术，分别对８００合金，３０４和３１６及３１６Ｔｉ不锈钢Ａ５３３Ｂ压力容器用多在模拟核反应堆环境中的应力腐蚀破裂敏感性性进行的试验研究的一些主要结果；并结合电化学测试和表面膜俄歇电子能谱分析结果进行了讨论。     

Corrosion behaviour of low-Si alloyed steels in neutral reducing conditions at 90 °C

Electrochemical investigations on low-Si alloyed steels with Si content ranging from 0.25 to 3.2 wt.% were carried out in a 0.1 M NaCl borate-buffered solution (pH 8.4) in reducing conditions at 90 °C. Silicon as an alloying element was proved to degrade at first the steel ability to passivate. For longer immersion times, protective effects developed more efficiently on the steel containing 3.2 wt.% silicon. Passive layers electrochemically formed in the transpassive domain on the steel containing 3.2% Si were shown to be significantly different from those grown at rest potential.