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介绍基于系统辨识的自适应控制系统模型在莱钢2#精炼炉合金下料系统中的应用,通过不断地调整控制过程中的参数值,使控制系统的瞬态响应过程达到最优,消除了生产过程中人为因素的影响,提高了生产的均一性和稳定性.  相似文献   
23.
Social navigation enables emergent collaboration between independent collaborators by exposing the behavior of each individual. This is a powerful idea for web-based visualization, where the work of one user can inform other users interacting with the same visualization. Results from a crowdsourced user study evaluating the value of such social navigation cues for a geographic map service are presented. Results show significantly improved performance for participants who interacted with the map when the visual footprints of previous users were visible.  相似文献   
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在互联网飞速发展的今天,校园网站建设已成为各个学校信息化建设的重要组成部分.本文针对学校的实际应用需求,提出了一个适用于校园的校园网新闻的发布系统设计方案.实践证明该方案高效可行.  相似文献   
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本文介绍一种功能强大、开源免费的学习管理系统(LMS)- -Moodle,阐述了利用该系统的功能模块进行课程设计的方法和构建网络教学模式的流程,并提出了这种教学模式在实际使用过程中的建议.  相似文献   
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Recently, periodic pattern mining from time series data has been studied extensively. However, an interesting type of periodic pattern, called partial periodic (PP) correlation in this paper, has not been investigated. An example of PP correlation is that power consumption is high either on Monday or Tuesday but not on both days. In general, a PP correlation is a set of offsets within a particular period such that the data at these offsets are correlated with a certain user-desired strength. In the above example, the period is a week (7 days), and each day of the week is an offset of the period. PP correlations can provide insightful knowledge about the time series and can be used for predicting future values. This paper introduces an algorithm to mine time series for PP correlations based on the principal component analysis (PCA) method. Specifically, given a period, the algorithm maps the time series data to data points in a multidimensional space, where the dimensions correspond to the offsets within the period. A PP correlation is then equivalent to correlation of data when projected to a subset of the dimensions. The algorithm discovers, with one sequential scan of data, all those PP correlations (called minimum PP correlations) that are not unions of some other PP correlations. Experiments using both real and synthetic data sets show that the PCA-based algorithm is highly efficient and effective in finding the minimum PP correlations. Zhen He is a lecturer in the Department of Computer Science at La Trobe University. His main research areas are database systems optimization, time series mining, wireless sensor networks, and XML information retrieval. Prior to joining La Trobe University, he worked as a postdoctoral research associate in the University of Vermont. He holds Bachelors, Honors and Ph.D degrees in Computer Science from the Australian National University. X. Sean Wang received his Ph.D degree in Computer Science from the University of Southern California in 1992. He is currently the Dorothean Chair Professor in Computer Science at the University of Vermont. He has published widely in the general area of databases and information security, and was a recipient of the US National Science Foundation Research Initiation and CAREER awards. His research interests include database systems, information security, data mining, and sensor data processing. Byung Suk Lee is associate professor of Computer Science at the University of Vermont. His main research areas are database systems, data modeling, and information retrieval. He held positions in industry and academia: Gold Star Electric, Bell Communications Research, Datacom Global Communications, University of St. Thomas, and currently University of Vermont. He was also a visiting professor at Dartmouth College and a participating guest at Lawrence Livermore National Laboratory. He served on international conferences as a program committee member, a publicity chair, and a special session organizer, and also on US federal funding proposal review panel. He holds a BS degree from Seoul National University, MS from Korea Advanced Institute of Science and Technology, and Ph.D from Stanford University. Alan C. H. Ling is an assistant professor at Department of Computer Science in University of Vermont. His research interests include combinatorial design theory, coding theory, sequence designs, and applications of design theory.  相似文献   
27.
The rapid evolution of information and communication technology opens a wide spectrum of opportunities to change our surroundings into an Ambient Intelligent (AmI) world. AmI is a vision of future information society, where people are surrounded by a digital environment that is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user friendliness, user empowerment, and more effective service support, with an aim to bring information and communication technology to everyone, every home, every business, and every school, thus improving the quality of human life. AmI unprecedentedly enhances learning experiences by endowing the users with the opportunities of learning in context, a breakthrough from the traditional education settings. In this survey paper, we examine some major characteristics of an AmI learning environment. To deliver a feasible and effective solution to ambient learning, we overview a few latest developed enabling technologies in context awareness and interactive learning. Associated practices are meanwhile reported. We also describe our experience in designing and implementing a smart class prototype, which allows teachers to simultaneously instruct both local and remote students in a context-aware and natural way.  相似文献   
28.
本文论述了编制高效能空气净化器产品评价技术要求国家标准的意义和作用,介绍了标准研制的总体思路和原则,高效能空气净化器的定性和定量评价指标要求,测试、计算和评价方法等,通过国标的研制与实施,将引领并促进高效能空气净化器产品的生产与应用.  相似文献   
29.
该文介绍了一个基于CNA总线的嵌入式Web监控水、电、气在线遥控监控系统的架构方案,重点阐述其监控水、电、气管理系统的设计思路,对其中涉及的关键技术进行了较为详细的叙述。  相似文献   
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