• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.485-491
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• 1997

This paper describes the relationship between skin impedance signal, behavioral signal, and subjective evaluation depending on arousal level. Nz and reaction time had similar trend with mKSS level, but eyeblink rate was different from these two parameters. eye-blink rate increased slowly from mKSS level 1 to 5, and had high increasing rate at mKSS 7. But it showed steep descent at mKSS level 9. Each subject showed different eye-blink rates, but changing rates of EBR was similar at eachm KSS level. Therefore it suggests that rising rate of EBR can be used arousal level criterion. From the result of reaction time test. human performance was decreased rapidly above the mKSS level 5, and false positive and false negative data was observed above the mKSS level 3. It is desirable to give a subject some stimuli such as sound or aroma to rise arousal level between mKSS level 3 and mKSS level 5.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.477-484
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• 1997

In this paper, we proposed the compensation method to evaluate arousal level in different initial arousal states. Arousal level was measured by the relationship between IRI and Nz. Since Nz is affected by BI which is directly proportional to initial arousal state of subjects, the arousal level is underestimated To overcome this problem, we proposed the compensation method using modified Karolinska sleepiness scale, and determined compensation coefficients derived from this scale with five arousal levels. Applying these coefficients to portable arousal monitoring system, the proposed method in this paper could be useful for real-time evaluation and control of arousal level. As a result the developed system can detect and control the arousal state from initial drowsing sate.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.19-22
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• 1997

This paper studies the arousal effects of aroma and warning sound using EDA(Electrodermal Activity:EDA), Aroma stimulus started at Nz value over 1.2. Warning sound was prepared according to the arousal evaluation and control criteria. As a result, the warning sound could be controlled the arousal level in all the mKSS state. Aroma stimulus was able to prevent drowsy more than warning sound in the mKSS 3 state(the first stage of drowsiness). Therefor, aroma stimulus was can be used for arousal control at that state. Futhermore, arousal control was shown to be more effective with presentation of both aroma and warning sounds than each presentation.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.