• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.797-807
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• 2016

The discussion in this paper aims to introduce an approach to detect drowsiness with Android based smartphones using the OpenCV platform tools. OpenCV for Android actually provides powerful tools for real-time body's parts tracking. We discuss here about the maximization of the accuracy in real-time eye tracking. Then we try to develop an approach for detecting eye blink by analyzing the structure and color variations of human eyes. Finally, we introduce a time variable to capture drowsiness.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.317-327
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• 2005

The flood is the most general and frequently occurs among natural disasters. Generally flood by the rainfall which extends superexcellently for the occurrence but flash flood from severe rain storm gets up an absurd drowsiness at grade hour. This paper aims to 1 hour real-time flash flood and predict possibility at the area where is the possible flood will occur from the rainfall hour mountain after acquiring data in GIS(Geographic Information System) base by GcIUH(Geomorphoclimatic Instantaneous Unit Hydrograph). The flash flood occurrence is set up at 0.5m, 0.7m and 1.0m in standard depth. And this study suggests standard flood alarm which designed by probable flood according to duration time. The research result shows real-time flash flood evaluation has the suitable standard in the basin when comparing with the existing official warning announcement system considering topographical information.