人工免疫原理在网络入侵检测系统中的研究

文章分析了人工免疫系统的原理,简单建立了一种基于否定选择算法的网络入侵检测系统,引入了一种用于异常事件识别的r-字符块匹配规则,并对规则存在的漏洞进行了分析。     

基于循环谱理论的BPSK直扩信号检测

研究了扩频信号的周期平稳性及其循环谱密度函数;在推导出BPSK扩频信号的循环谱密度函数的基础上,提出利用循环谱理论对BPSK直扩信号进行检测,并用MATLAB进行仿真验证。     

一种变步长D-Rake多用户检测器

在时变多径衰落信道下,接收到的CDMA信号功率变化较大,此时D-Rake盲自适应多用户检测器性能显著下降,将变步长LMS算法与基于主分量的相干合并引入到D-Rake(DecorrelatingRake)检测器中,构成一种变步长D-Rake,称之为VD-Rake(Variablestep-sizeDecorrelatingRake)检测器。该检测器能克服原D-Rake检测器对信号功率变化较敏感等缺点,有效地改善了D-Rake检测器的性能。     

低温送风系统末端装置诱导器的研究及性能评价

研究了在低温送风系统中诱导器(IDU)的结构特点、工作原理、送风方式,分析了诱导器送风口射流速度的特性,得出了诱导器空调系统的优缺点。     

MEG钻井液在吐哈油田小井眼侧钻井中的应用

吐哈油田小井眼开窗侧钻井主要采用混原油钻井液,不利于环境保护。从研究MEG单体的作用机理入手,以钻井液润滑性、抑制防塌性为主要评价指标,对MEG钻井液配方进行了优选,并对优选配方钻井液性能进行了评价。该钻井液在4口小井眼开窗侧钻井进行了试验应用。结果表明:应用井无阻、卡现象,平均钻井周期缩短了7.2d;在未混原油的情况下钻井液润滑系数比乳化原油(15%~20%)钻井液降低了34.6%;油层保护效果好,其中温5-41C井日产油14.4t,同比温五区块平均产量提高了128.4%,神218C井是神229区块目前唯一的自喷井。表明优选出的MEG钻井液具有优良的润滑性、抑制防塌性及良好的储层保护效果,特别适合强水敏地层及大斜度井和水平井等特殊复杂工艺井的钻进。     

高性能调度技术中应用程序调度模型设计--地理空间信息网格调度技术的研究

地理空间信息网格调度技术，要比传统的高性能计算中的调度技术复杂，原因是如果将全部网格资源作为一个应用程序的调度和执行目标，必将导致通信延迟、成本昂贵、执行低效等。为此，综合考虑应用程序特性、机器特性等，研究设计了地理空间信息网格高性能调度技术中的应用程序调度模型，包括地理空间信息网格应用程序分析；资源特性分析；应用程序分解；性能预测；资源调度；机器选择；任务映射；任务调度；任务调度器和调度器管理模块。以实现为不同的应用程序匹配不同的计算资源，提高计算资源的利用率和应用程序的执行效率。     

通信性能评估的仿真实验研究

研究了流量控制和差错控制对通信性能的综合影响，着重分析了停止-等待协议和连续ARQ协议的优缺点，讨论了信道利用率和帧长的关系。介绍了几种多点接人技术的基本原理，如CSMA和CSMA／CD，并给出了各自相应的性能仿真曲线。所设计的通信性能评估实验，仿真界面形象丰富，与实验知识点紧密结合，可以大大提高实验教学的效率和质量。     

Reciprocal Relationships Between Collective Efficacy and Team Performance in Women's Ice Hockey.

This study examined reciprocal relationships between collective efficacy and team performance over a season of competition in women's intercollegiate ice hockey within weekends where the opponent was constant for 2 games. Collective efficacy beliefs within 12 teams were assessed prior to both games for at least 7 weekends. Team performance indexes produced an overall measure of performance for each game. The average influence of Saturday collective efficacy on Saturday performance was moderate and positive after controlling for Friday performance. The average influence of Friday performance on Saturday collective efficacy was small and positive after removing the influence of Friday collective efficacy from Friday performance. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).     

Implicit Motor Learning in Parkinson's Disease.

Objective: This study examined whether disruption of performance is moderated in Parkinson's disease (PD) patients who acquire their motor behaviors in an implicit manner. Method: Twenty-seven patients with PD learned a hammering task in errorless (implicit) or errorful (explicit) conditions and were tested for robustness of motor performance under a secondary task load, which required them to continuously count backward as they performed the hammering task. Results: Patients in the errorless (implicit) motor learning condition exhibited robustness to secondary task loading, whereas patients in the errorful (explicit) motor learning condition did not. Conclusions: Implicit motor learning techniques should be considered by PD rehabilitation specialists in cases in which existing disruption to movements is exacerbated by conscious control. (PsycINFO Database Record (c) 2010 APA, all rights reserved)