This article presents a new robust automated image processing method for detecting cracks in surface images of concrete structures. This method involves two steps: (1) development of an image filter for detecting major cracks using genetic programming (GP), and (2) elimination of residual noise after filtering and detection of indistinct cracks by iterative applications of the image filter to the local regions surrounding the cracks. The proposed method can be used for the accurate detection of cracks in surface images recorded under various conditions. Moreover, the widths of the detected cracks can be quantified on the basis of the spatial derivatives of the brightness patterns. The estimated crack widths are in good agreement with those measured manually.
The Pd–C/Pb(OAc)2 system catalyzes selective O2-oxidation of ArCH(R)CH2OH to ArCH(R)COOH (useful intermediates for drug synthesis) in high yields without contamination of ArCOOH. The turnover number (substrate/Pd) is improved to 85 and >1800 by recycling the catalyst and using a special reactor, respectively. Alkanols are also efficiently oxidized to alkanoic acids by the title catalyst system.
An image processing technique to capture motions of crowds is proposed and it is applied to understanding pedestrian-induced lateral vibration in a footbridge. Firstly, an outline of recording sequential images of vibration in the bridge is described and, then an image processing for human-head recognition from a single image of crowd is developed. In this method, conventional template matching techniques with human-head templates are extended by employing some selected templates, an updated search-algorithm and a classifier for clustering. Consequently, more than 50% of human-heads could be identified by the proposed method. Then, motions of detected human-heads, together with the bridge response, are tracked. Finally, interaction between the motions of pedestrians and the vibration of the bridge is discussed, with the emphasis on synchronization between the responses of the pedestrians and the bridge.
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