复杂场景实时目标检测方法

针对含有非平稳背景的复杂场景,提出一种基于空间混合高斯模型的实时目标检测方法.该方法以混合高斯模型作为颜色分布的统计框架,并在空间邻域中利用背景与前景隶属度之间的竞争确定像素的归属,提高了检测准确率;同时通过基于偏差均值的匹配判断和低权重模型的移除提升了混合高斯统计框架的性能,以实时地对运动目标进行准确的检测.实验结果表明,文中方法对非平稳背景有很好的适应能力,在检测准确率和运行效率上均优于其他检测方法.     

基于语义识别的不良倾向性信息过滤系统的设计与实现

文章基于自然语言理解和神经网络技术,通过对实际应用的分析,建立了三个领域知识的规则库,设计了一个针对BBS站点的过滤系统原型,实现了对网络上某一特定内容信息的过滤和监控功能,达到了较好的实用效果。     

基于双闭环系统的起重机位置控制技术研究

传统的起重机位置控制技术大多是以位移或速度为反馈量构成的单闭环控制,只能对系统的一个状态量进行控制,易造成系统的超调、振荡,难以实现真正意义上的位置控制;研究采用位移和速度的双闭环位置控制技术[1],以位移环为外环、速度环为内环,位移环根据位移的当前值与给定值的差,通过位移调节器给速度环提供给定速度,速度环通过速度调节器控制系统的运动速度,最终实现对系统的位置控制;通过对单闭环控制和双闭环控制的仿真结果对比分析,双闭环系统的位置和速度的控制精度均比单闭环精度高,最后通过实验,证明了双闭环系统在实践上的可行性。     

Filiform corrosion attack on pretreated aluminum alloy with tailored surface of epoxy coating

In the study, on the basis of material analysis of 6016 aluminum alloy widely used in Europe automotive industry, the influences of surface pretreatment on filiform corrosion and adhesion of epoxy coating/aluminum alloy interface were investigated, and the effect of rolling direction and coating property on filiform corrosion was also examined. The alloy surfaces were pretreated with etching solution, and then, respectively, with Aminopropyl silane solution, Aminopropyl phosphonate solution, and hexamethyldisiloxane plasma.The results showed that the susceptibility of pretreated surface to filiform corrosion was basically consistent with the distribution of intermetallic particles, and that water permeation and the tensility of coating were necessary for filament to grow. HMDSO plasma pretreatment could not only efficiently cover the matrix of 6016 aluminum alloy and cathodic intermetallic particles containing Al, Si, Mn, and Fe, but also apparently promote the adhesion of epoxy coating/aluminum alloy, as a result, the specimens with plasma pretreatment exhibited the superior performance in the filiform corrosion and peeling tests, so it was suitable to apply for the pretreatment of aluminum alloy in automotive industry.     

地下环境中电子设备的腐蚀与防护

程环境中电子设备所承受的湿度、温度、腐蚀性气体、空气沉积物、微生物等环境应力因素及其腐蚀效应，概述总结了电子设备腐蚀机制及主要类型，并提出电子设备设计与使用中抑制腐蚀的措施.     

基于循环检测的气动退化图像混合域去噪算法

气动退化图像中存在先验信息未知以及噪声成分复杂不易进行滤波处理的问题,为此,提出一种气动退化图像混合域去噪算法。设计针对高斯噪声、泊松噪声、固定值脉冲噪声和随机值脉冲噪声的混合检测方法,使用改进的滤波方法在空域去除固定值脉冲噪声和随机值脉冲噪声,进行非下采样轮廓波变换多层分解,在变换域使用阈值方法去除高斯噪声和泊松噪声。进行噪声循环检测,设定迭代停止条件控制算法循环从而实现算法自适应。仿真实验结果表明,该算法的噪声检测性能和滤波性能较好,图像细节信息得到正确恢复。同时,算法复杂度较低,实时性较好,可满足气动退化图像去噪处理的需要。     

基于STL文件的Laplacian网格优化算法

针对直接重构得到且以STL文件格式存储的网格模型质量不高的问题, 提出了一种基于Laplacian坐标的网格模型全局优化算法。该算法在提高三角面片质量的同时可以很好地保持原网格模型的局部几何特征, 其核心思想是通过在最小二乘意义下求解由权重控制的包含顶点位置和拉普拉斯坐标双重约束的线性系统来对网格顶点进行重新定位。从实验结果可以看出, 该算法较以往的Lapacian优化算法在对网格细节特征的保持上有一定优势。     

蓝宝石光纤温度传感器测温上限的瓶颈分析及解决方案

通过与热电偶、非接触式辐射测温仪的对比分析,指出基于黑体辐射原理的蓝宝石光纤温度传感器在某些特殊测温场合的不可替代性.介绍了国内蓝宝石光纤温度传感器的研究情况,分析制约其应用和发展的测温上限瓶颈,最后提出解决该问题的初步方案.实验证明该方案能够实现高达2 700℃的温度测量,1 000℃以上最大稳态误差不超过50℃.     

PAIDD: a hybrid P2P-based architecture for improving data distribution in social networks

Rapid growth in social networks(SNs)presents a unique scalability challenge for SN operators because of the massive amounts of data distribution among large number of concurrent online users.A request from any user may trigger hundreds of server activities to generate a customized page and which has already become a huge burden.Based on the theoretical model and analytical study considering realistic network scenarios,this article proposes a hybrid P2P-based architecture called PAIDD.PAIDD fulfills effective data distribution primarily through P2P connectivity and social graph among users but with the help of central servers.To increase system efficiency,PAIDD performs optimized content prefetching based on social interactions among users.PAIDD chooses interaction as the criteria because user’s interaction graph is measured to be much smaller than the social graph.Our experiments confirm that PAIDD ensures satisfactory user experience without incurring extensive overhead on clients’network.More importantly,PAIDD can effectively achieve one order of magnitude of load reduction at central servers.     

利用置信规则库构建WSN节点故障检测模型

在无线传感器网络(wireless sensor network, WSN)节点故障检测领域的研究过程中,故障检测准确率会受节点数据的不确定性和专家知识模糊性的影响。针对这一问题,本文提出了一种基于置信规则库(belief rule base, BRB)的WSN节点故障检测方法。首先,根据WSN工作原理及节点工作特性描述WSN节点故障检测过程;然后,从空间和时间2个维度对节点数据提取特征,建立基于空间和时间相关性的WSN节点故障检测模型;最后,利用Intel Lab Data无线传感器数据集进行案例研究以验证模型的有效性。结果证明,本文方法能够统筹利用专家知识和节点数据实现WSN节点故障检测。