GSM-MRF based classification approach for real-time moving object detection

Statistical and contextual information are typically used to detect moving regions in image sequences for a fixed camera. In this paper, we propose a fast and stable linear discriminant approach based on Gaussian Single Model （GSM） and Markov Random Field （MRF）, The performance of GSM is analyzed first, and then two main improvements corresponding to the drawbacks of GSM are proposed： the latest filtered data based update scheme of the background model and the linear classification judgment rule based on spatial-temporal feature specified by MRF. Experimental results show that the proposed method runs more rapidly and accurately when compared with other methods.     

基于噪声与阴影抑制多模态背景模型的运动物体检测

针对场景照明变化、模型初始化以及阴影等问题, 提出了一种用于视频监视系统运动物体检测的统计多模态背景模型. 通过相隔固定的帧差值阈值化得到背景样本值, 并采用高斯核密度估计方法计算背景灰度的概率密度函数. 利用像素的邻域信息来去除由于摄像机抖动和场景小运动产生的噪声. HMMD色彩信息用来检测和抑制运动投射阴影. 实验结果验证了算法在交通监控前景物体分割中的有效性.     

Parameter estimation of cutting tool temperature nonlinear model using PSO algorithm

INTRODUCTION In modern metal cutting theory,research on cutting tool is one of the major concerns.To under-stand the characteristics of a new cutting tool,many experiments(such as cutting force experiment,cut-ting temperature experiment,anti-striking experiment,etc.)should be conducted to obtain an enormous amount of experiment data.The development of a proper cutting tool temperature model is a very dif-ficult task due to the large number of interrelated parameters(cutting speed,feed,dept…     

A conceptual model for supporting para-teacher learning in an Indian non-governmental organization (NGO)

Non-governmental organizations (NGOs) are being recognized globally for their influential role in realizing the UN Millennium Development Goal of education for all in developing countries. NGOs mostly employ untrained para-educators for grassroots activities. The professional development of these teachers is critical for NGO effectiveness, yet para-teacher learning in such contexts is rarely researched. To facilitate much-needed research on para-teacher professional development, this article offers a contextually relevant on- the-job learning model for para-teachers. The model suggests that para-educators can effectively learn when their work and learning are integrated by systematizing a simple daily cyclical routine of lesson planning, enactment and reflection for everyday instruction. It also suggests other supports to stimulate learning alongside the cyclical routine.     

Lower extremity injuries in vehicle-pedestrian collisions using a legform impactor model

Though the bumper of a vehicle plays a major role in protecting the vehicle body against damage in low speed impacts, many bumpers, particularly in large vehicles, are too stiff for pedestrian protection. In designing a bumper for an automobile, pedestrian protection is as important as bumper energy absorption in low speed collisions. To prevent lower extremity injuries in car-pedestrian collisions, it is important to determine the loadings that car front structures impart on the lower extremities and the mechanisms by which injury is caused by these loadings. The present work was focused on gaining more insight into the injury mechanisms leading to both ligament damage and bone fracture during bumper-pedestrian collisions. The European Enhanced Vehicle-safety Committee （EEVC） legform impactor model was introduced and validated against EEVCAVG17 criteria. The collision mechanism between a bumper and this legform impactor was investigated numerically using LS-DYNA software. To identify the effect of the bumper beam material on leg injuries, four analyses were performed on bumpers that had the same assembly but were made from different materials.