基于超级节点模式的多Agent入侵检测模型

分析了入侵检测方面的新问题,简述了超级节点和多Agent数据融合,进而提出了基于超级节点多Agent入侵检测模型,讨论了其实现方法.仿真实验表明,此模型在入侵检测方面具有很好的性能.     

浅析超重车辆对公路桥梁的危害及防治

加强超重车辆过桥的管理工作任重而道远,我们要认真采取加固补强措施,配合超重车辆过桥,坚决杜绝各类重大事故的发生,以保证道路的畅通,保障我国经济的平稳高速发展.     

旧水泥混凝土路面加铺沥青面层的疲劳损伤分析

结合107国道河南省郑州至许昌段旧水泥混凝土路面所铺筑的沥青混凝土加铺层试验路情况,根据现场检测和室内试验数据,采用疲劳损伤力学方法对沥青混凝土加铺层处治机理及效果进行比较分析,探讨地基支承、接缝传荷、加铺层厚度、加筋等因素对沥青混凝土加铺层疲劳损伤寿命的影响,有利于在施工中采取有效措施延长旧水泥混凝土路面加铺沥青面层的寿命.     

既有钢筋混凝土双曲拱桥承载能力评估

钢筋混凝土双曲拱桥主要建造于20世纪60年代末和70年代初,由于当初建造时荷载标准较低,再加上多年超载运营,桥梁损伤严重,承载能力下降,对交通运输安全构成严重威胁.依据实桥荷载试验所得的力学特性参数,首先采用基于敏感性分析的参数修正法修正计算模型,并对该计算模型进行验证.然后利用验证后的计算模型和承载能力系数法对桥梁结构的承载能力进行评估.最后通过对一实际既有钢筋混凝土双曲拱桥承载能力的评估分析结果可以看出:本文所述方法对于既有双曲拱桥承载能力的评估具有良好的效果.     

车牌定位的一种神经网络方法

汽车牌照自动识别（LPR）是ITS中的一项关键技术。对实时采集的图像，能自动地提取车牌照信息，有利于快速、高效进行车辆监控和管理，真正实现交通管理的智能化。而车牌定位又是车牌识别的必要的先决条件，直接影响LPR的成功与否。针对国标GA36—1992，结合图像的边缘特征，给出了一种快速可行的车牌照定位方法，供同行们参考。     

汽车油箱改进

通过对油箱进行改进,使得汽车在发生事故时,能有效预防因油箱损坏漏油而发生爆炸,从而保证了人的生命安全。     

浅谈我省检测机构的内部质量控制

针对目前我省检测市场及检测机构存在的问题和不足进行了分析,对如何加强内部质量控制提出了自已的看法,为检测行业健康有序发展提供了有益的借鉴.     

红外探水在厦门海底隧道中的应用

在厦门海底隧道施工中采用红外探测仪进行探水短期预报。介绍了红外探水技术的基本原理和布点方法,通过实例分析了分部红外探测得到的红外辐射场强值和绘出的红外探测曲线,得出探测结论,并和实际情况进行验证,说明探水效果良好,为隧道顺利施工提供科学依据。结合应用情况,提出了当前红外探水技术发展中亟待解决的问题。     

Nonlinear Statistical Process Monitoring Based on Control Charts with Memory Effect and Kernel Independent Component Analysis

A novel nonlinear combination process monitoring method was proposed based on techniques with memory effect (multivariate exponentially weighted moving average (MEWMA)) and kernel independent component analysis (KICA). The method was developed for dealing with nonlinear issues and detecting small or moderate drifts in one or more process variables with autocorrelation. MEWMA charts use additional information from the past history of the process for keeping the memory effect of the process behavior trend. KICA is a recently developed statistical technique for revealing hidden, nonlinear statistically independent factors that underlie sets of measurements and it is a two-phase algorithm: whitened kernel principal component analysis (KPCA) plus independent component analysis (ICA). The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed combined method based on MEWMA and KICA can effectively capture the nonlinear relationship and detect small drifts in process variables. Its performance significantly outperforms monitoring method based on ICA, MEWMA-ICA and KICA, especially for long-term performance deterioration.     

Efficient Accurate Context-Sensitive Anomaly Detection

For program behavior-based anomaly detection, the only way to ensure accurate monitoring is to construct an efficient and precise program behavior model. A new program behavior-based anomaly detection model, called combined pushdown automaton （CPDA） model was proposed, which is based on static binary executable analysis. The CPDA model incorporates the optimized call stack walk and code instrumentation technique to gain complete context information. Thereby the proposed method can detect more attacks, while retaining good performance.