基于视觉传达的复杂图像自动化特征监控方法

传统特征监控方法在处理多分辨率复杂图像时无法找到最合理的分块数量,导致监控效率低,因此设计一种基于视觉传达的复杂图像自动化特征监控方法。首先对复杂图像的结构进行分析,利用视觉子描述图像结构,采用滤波响应得到图像块线结构外观属性,计算有效偏离位移,随后基于视觉传达进行图像预处理,利用图像二值化法消除噪音,最后经过多点监控和双向监控实现图像特征自动化提取与监控。通过设计实验,分别使用设计的方法和传统方法对多分辨率复杂图像进行处理,实验结果表明,设计的自动化特征监控方法能根据复杂图像的具体特征点情况对图像进行分块,达到较好的处理加速效果,验证了方法的有效性。

我国高水平艺术体操运动员训练负荷特征与监控

艺术体操是体操项目中比较能够展现柔美的项目,对运动员的体能水平有相对较高的要求。我国对于运动员的训练负荷研究了多种监控方法,对高水平的艺术体操运动员逐个进行体能训练,定期测试运动员的体能指标。其目的是为了让运动员能够优秀的完成整套动作,为完善监控系统提供合理数据。让运动员在国际各大比赛中能够取得好成绩,适应当今社会对于艺术体操运动员的要求。

Linux平台下基于特征库的Webmail监控系统

由于不同的Webmail提供商采用的邮件格式各不相同,使得Webmail监控相对基于SMTP协议的邮件监控而言一直是监控的难点。本文通过分析常见Webmail的通信特征,提出了一种Linux平台下基于动态Webmail特征库的邮件监控系统,将各种常用Webmail的标志组成一个可扩展的特征库,通过检测网络中数据流是否含有特征库中特征的方式,达到识别网络中Webmail活动并提取信息的目的。系统在Linux平台下开发,部署在骨干网出口处。由于骨干网上数据流量很大,所以系统采用零拷贝技术来捕获网络数据流,大大减少了数据流捕获时间,提高了系统的整体性能。

Resistivity and thermal infrared precursors associated with cemented backfill mass

The stability of cemented backfill mass is important to keep miners and equipment safe in underground backfill miming.The stress-strain behavior, resistivity and thermal infrared(TIR) characteristics of backfill mass under uniaxial compression were investigated. The monitoring system consisted of a TIR observation system, a stress-strain monitoring system and a resistivity measurement system. Precursory information for impending failure of cemented backfill mass was collected, including TIR, strain and resistivity precursors. The sensitivity and difference of different monitoring information to the same failure event were compared.The results show that the time-space evolution process of the resistivity and TIR is basically the same as the whole process from compression deformation to failure of backfill mass, and the time variation of resistivity and TIR is obviously characterized by stage.The resistivity precursor turns out earlier than the TIR and the strain. The resistivity relation with loading compression is anti-symmetry, decreasing as the compression stress increases before the peak strength of backfill mass. However, when the backfill mass enters into the phase of failure, the resistivity starts to increase as the stress increases. The change of the resistivity growth direction can be regarded as the resistivity-caution-point for the failure of backfill mass under uniaxial compression. It is also indicated that the TIR information mainly represents the surface temperature evolution in the process of compression before the backfill enters into the plastic-yield state. It can be a valuable tool to obtain the precursors for failure of cemented backfill mass for backfill mines.

Seismic signal recognition using improved BP neural network and combined feature extraction method

Seismic signal is generally employed in moving target monitoring due to its robust characteristic.A recognition method for vehicle and personnel with seismic signal sensing system was proposed based on improved neural network.For analyzing the seismic signal of the moving objects,the seismic signal of person and vehicle was acquisitioned from the seismic sensor,and then feature vectors were extracted with combined methods after filter processing.Finally,these features were put into the improved BP neural network designed for effective signal classification.Compared with previous ways,it is demonstrated that the proposed system presents higher recognition accuracy and validity based on the experimental results.It also shows the effectiveness of the improved BP neural network.

Motion cue based pedestrian detection with two-frame-filtering

This study proposes a motion cue based pedestrian detection method with two-trame-filtering （Tff） for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff processing filters the gradient magnitude image by the variation map. Summa- tions of the Tff gradient magnitudes in cells are applied to train a pre-deteetor to exclude most of the background regions. Histogram of Tff oriented gradient （HTffOG） feature is proposed for pedestrian detection. Experimental results show that this method is effective and suitable for real-time surveil- lance applications.

Analyses of Characteristics of Long-Term Monitoring of Arterial Pressure and Pulse

Long-term observations of pulse and arterial blood pressure taken from a patient＇s daily self-control diary have been analyzed in the paper. The diary was kept in the morning and in the evening. It contains regular observational data collected during over 13 years. Statistical estimates of series and their spectral responses were obtained. A difference between the morning and evening series was noted. Spectral harmonics with the period of 7 days was typical of the evening series. The morning series are characterized by a ＂lunar＂ component with the -27.35-day period. The examined series were also compared with the daily series of atmospheric pressure and daily Wolf numbers. Seasonal pulse and arterial pressure pattern and average monthly self-control tabulated data obtained during 13 years are presented in the paper.

Pure Multiplicative Noises Induced Population Extinction in an Anti-tumor Model under Immune Surveillance

The dynamical characters of a theoretical anti-tumor model under immune surveillance subjected to a pure multiplicative noise are investigated. The effects of pure multiplicative noise on the stationary probability distribution （SPD） and the mean first passage time （MFPT） are analysed based on the approximate Fokker-Planck equation of the system in detail. For the anti-tumor model, with the multiplieative noise intensity D increasing, the tumor population move towards to extinction and the extinction rate can be enhanced. Numerical simulations are carried out to check the approximate theoretical results. Reasonably good agreement is obtained.

Real-time monitoring of brake shoe keys in freight cars

Condition monitoring ensures the safety of freight railroad operations. With the development of machine vision technology, visual inspection has become a principal means of condition monitoring. The brake shoe key （BSK） is an important component in the brake system, and its absence will lead to serious accidents. This paper presents a novel method for automated visual inspection of the BSK condition in freight cars. BSK images are first acquired by hardware devices. The subsequent in- spection process is divided into three stages： first, the region-of-interest （ROI） is segmented from the source image by an im- proved spatial pyramid matching scheme based on multi-scale census transform （MSCT）. To localize the BSK in the ROI, cen- sus transform （CT） on gradient images is developed in the second stage. Then gradient encoding histogram （GEH） features and linear support vector machines （SVMs） are used to generate a BSK localization classifier. In the last stage, a condition classifier is trained by SVM, but the features are extracted from gray images. Finally, the ROI, BSK localization, and condition classifiers are cascaded to realize a completely automated inspection system. Experimental results show that the system achieves a correct inspection rate of 99.2% and a speed of 5 frames/s, which represents a good real-time performance and high recognition accuracy.