Real-time lane departure warning system based on principal component analysis of grayscale distribution and risk evaluation model

A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.

Assessment of heavy metal pollution characteristics and human health risk of exposure to ambient PM_(2.5) in Tianjin,China

To examine the features of heavy metal pollution of PM2.5 （particulate matter less than 2.5 μm） in Tianjin, China, as well as the exposure risk of PM2.5 to human health, we analyzed ambient PM2.5samples collected from a campus of Nankai University in June, August, and October 2012. The concentrations of PM2.5 and heavy metals （Ni, Cu, Pb, Zn, Cr, Cd, Hg, As and Mn） in PM2.5 were analyzed by gravimetric analysis and inductively coupled plasma-mass spectrometry, respectively. The results show that the heavy metals contained in PM2.5 were, in descending order, Cu, Zn, Pb, Mn, Cr, Ni, Cd, As, and Hg. The proportion of Cd exceeded the secondary level of National Ambient Air Quality Standard of China （GB 3095-2012） by 1.3 times, while others were within the limit. Enrichment factor analysis indicated that Cu, Zn, Cd, Pb, and Hg are mainly from anthropogenic sources. Principal component analysis indicated that the main sources of the heavy metals are vehicle exhaust, chemical waste, and coal-burning activities. The nine heavy metals which may cause health issues by exposure through the human respiratory system and should be further examined are Cr, Cd, As, Ni, Cu, Pb, Mn, Zn, and Hg, in the order of decreasing risk levels. With reference to the U.S. EPA standard the risk levels of all nine metals were below the acceptable level （10 6/year）.

Power transmission risk assessment considering component condition

This paper proposes a new method for power transmission risk assessment considering historical failure statistics of transmission systems and operation failure risks of system components.Component failure risks are integrated into the new method based on operational condition assessment of components using the support vector data description(SVDD)approach.The traditional outage probability model of transmission lines has been modified to build a new framework for power transmission system risk assessment.The proposed SVDD approach can provide a suitable mechanism to map component assessment grades to failure risks based on probabilistic behaviors of power system failures.Under the new method,both up-todate component failure risks and traditional system risk indices can be processed with the proposed outage model.As a result,component failure probabilities are not only related to historical statistic data but also operational data of components,and derived risk indices can reflect current operational conditions of components.In simulation studies,the SVDD approach is employed to evaluate component conditions and link such conditions to failure rates using up-to-date component operational data,including both on-line and off-line data of components.The IEEE 24-bus RTS-1979 system is used to demonstrate that component operational conditions can greatly affect the overall transmission system failure risks.