The estimated cancer detection rate in Korean men 55 years or older was 3.36%. The significance of the high rate in this population should be determined through repeat screening and further surveillance in the future.

This paper presents new methods for estimating the axle weight of a moving vehicle, using two piezoelectric sensors and adaptive-footprint tire model. It is more difficult to weigh vehicles in motion accurately than to weigh standing vehicles. The difficulties in weighing moving vehicles result from sensor limitations as well as dynamic loading effects induced by vehicle/pavement interactions. For example, two identical vehicles with the same weight will generate sensor signals that differ in the shape and the peak value, depending the tire pressure, vehicle speed, road roughness, and sensor characteristics. This paper develops a method that is much less sensitive to these variable factors in determining the axle weight of a moving vehicle. In the developed method, first the piezoelectric sensor signal is reconstructed using the inverse dynamics of a high-pass filter representing the piezoelectric sensor. Then, the reconstructed signal, is normalized, using the nominal road/tire contact length obtained using an adaptive-footprint tire model, and then integrated. Experiments are performed with 3 vehicles of known weight ranging from 1,400 kg to 28,040 kg. The developed method is compared to two other algorithms. Results show that the developed method is most consistent and accurate.

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