栅元有效共振积分的CUDA算法设计与实现

核反应堆中需要实时精确地计算堆芯和增殖材料的有效共振积分或群截面来实现反应堆的安全控制。整个计算过程因为涉及大量的积分运算和庞大的核素截面数据,采用常规的计算方法,计算时耗相当大。基于统一计算设备架构(CUDA)平台,利用图形处理器(GPU)的计算能力,对整个计算过程进行并行化分解,多线程同时运算,大幅度提升计算速度,降低时耗。实验结果表明,在GPU上并行计算所得结果与原始数据没有明显差异,且加速效果显著。     

基于系统辨识的自适应控制技术的应用

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.     

Evaluating Social Navigation Visualization in Online Geographic Maps

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.     

亭子口水电站跌坎消力池减压模型试验研究

采用1:40减压模型,通过测试流态、水下噪声和脉动压力等水力参数,对亭子口水电站闸墩尾部跌坎式底流消力池的空化空蚀特性进行了研究。成果表明：闸墩尾部区域存在强度为发展阶段的剪切流空化,采用8.00 m高度的跌坎消力池后,消力池底板空蚀破坏的可能性较小;但消力池边墙与闸墩内壁侧扩距离较小时,边墙空蚀破坏的可能性较大;消力池边墙与闸墩内壁侧扩距离增至4.20 m时,边墙空蚀破坏的可能性显著降低。     

TYPHOON PROCESS AND ITS IMPACT ON THE SURFACE CIRCULATION IN THE NORTHERN SOUTH CHINA SEA

A severe typhoon Utor,occurring between July 3 and 8,2001,brought heavy rainfall,strong wind and storm surge.Utor was responsible for tremendous destruction and economic losses in Philippines,Taiwan and Guangdong.An air-sea model system (MM5 and Princeton Ocean Model(POM))was built to simulate meteorological dynamics and ocean circulation in the South China Sea(SCS).In the POM the output of MM5 was used as the input data.With an increased number of vertical levels,a high-resolution planetary boundary layer scheme and updated landuse/vegetation data,the accuracy of computing wind,temperature and other meteorological fields are improved in near surface and upper levels in MM5 simulations.The simulated trajectory and wind speed of Utor are close to the observed results.The simulated distribution of rainfall is accorded well with measured data in the Pearl River Delta(PRD)area.At different meteorological stations in Hong Kong,the wind,temperature and sea surface pressure are well simulated.The simulated ocean surface current and surface temperature fields have an obvious rightward-biased response to the typhoon Utor,and the maximum velocity and the lowest temperature region appear in the 30 km of the right side of the typhoon track.The typhoon Utor could make the water 50m under the surface ocean unwell to surface and the ocean surface temperature decrease by about 2°C.     

基于阈值的彩色目标图像的提取与测量

幅彩色图像提供了很多不同的信息,但是为了更好地研究我们所感兴趣的目标图像,需要将它们以图像斑块的形式单独提取出来,从而排除研究所不需要的干扰信息和背景信息,使得研究上作更容易、更准确。通过合理的选取阈值及提取关系,如大于等于阈值、小于等于阈值等,可从图像中提取研究所关心的目标图像及其边界,并测量所提取的目标图像的总面积及目标图像各斑块的面积和周长,由此可研究其分布规律与分布密度;并可在测量的基础上对目标图像斑块进行统计,统计出在一定面积或周长范围内目标图像斑块的个数,为相应的研究提供定量分析。     

基于ASP技术的校园网新闻发布系统的设计与实现

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.     

基于Moodle的网络教学模式构建与使用

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.     

Mining partial periodic correlations in time series

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.