• Electronics and Telecommunications Trends
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• v.10 no.4 s.38
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• pp.155-163
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• 1995

본 고에서는 광통신 시스템 송신단에 영향을 주는 파라미터를 분류하고 기술하였다. 광통신 시스템을 안정적으로 운영하기 위해서는 성능 관련 파라미터에 대한 기준값을 정해야 한다. 본 고에서는 송신단의 기준 파라미터로 평균결합전력을 선정하고 이 값에 영향을 주는 요인들을 분석했으며, ITU-T에서 권고한 평균결합전력값을 분석하였다. 또한 측정기를 이용하여 실제로 평균결합전력을 측정하는 방법에 대해서도 기술하였다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.2
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• pp.228-233
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• 2000

In this paper, we introduce a differential detection method using approximate average noise detection, which improves the noise reduction efficiency in a wireless optical interconnection. Approximate average noise detection reduces the output voltage fluctuation that may result from the instantaneous change of the coupling coefficients with the movement of some objects or human beings. This method is very useful for noise reduction in an environment with optical noise whose spatial distribution varies instantaneously.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.17 no.2
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• pp.53-58
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• 1981

Optical properties of sea water were studied in the northwestern water of Jeju Island, based on seven oceanographic stations in July, 1980. Submarine daylight intensity was measured at intervals of 5m depth in the upper 70m layer by using the underwater irradiameter(Kahlsico #268 WA360). The mean absorption coefficients of the sea water were appeared as 0.106(0.084-0.152), 0.135(0.106-0.184), 0.089(0.069-0.130) for clear, red, green, and blue color respectively. The transparency ranged from 11 to 19 meters(mean 16.1m). The mean water color in this area was 4.3(3-5) in Forel scales. The relation between absorption coefficient(k) and transparency(D) was k=1.66/D, k=2.12/D, k=1.38/D, and k=1.51/D for clear, red green, and blue color respectively. The rates of light penetration for clear, red, green, and blue color in four different depths were computed with reference to the surface light intensity respectively. The mean rates of light penetration in proportion to depths were as follows; clear : 56.57%(5m), 20.54%(15m), 4.60%(30m), 0.68%(50m). red : 50.14%(5m), 2.37%(30m), 0.23%(50m). green : 62.29%(5m), 26.43%(15m), 7.74%(30m), 1.56%(50m). blue : 59.29%(5m), 23.43%(15m), 6.10%(30m), 1.08%(50m).

• Journal of the korean academy of Pediatric Dentistry
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• v.32 no.4
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• pp.611-619
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• 2005

The aim of this study was to apply the quantitative light-induced fluorescence(QLF) and use of fluorescein-enhanced QLF method for quantitative assessment of early enamel demineralization in vitro, comparing effectiveness of light sources : argon laser, halogen lamp, light emitting diode (LED) and plasma arc lamp. Sixty extracted teeth were used, prepared by gentle pumicing and coating in an acid-resistant nail-varnish, except for an exposure to a demineralizing solution. Teeth were removed at regular intervals (24, 48 and 72hrs), air-dried and QLF image were taken. Mineral loss, as measured by difference of optical density, was recorded. For dyeenhanced QLF a 0.075% sodium fluorescein dye was applied after QLF examination and mineral loss was recorded. The following result were obtained : 1. Comparing with mean difference of optical density, plasma arc lamp was higher than other light sources in all group (p<0.05). 2. Comparing each group with mean difference of optical density, there was significant different using plasma are lamp and halogen lamp. 3. For use of dye-enhanced QLF, comparing with mean difference of optical density, plasma arc lamp were higher than other light sources in all group(p<0.05). 4. With this model dye-enhanced QLF compared with QLF in optical density, dye-enhanced QLF was higher than QLF in optical density. From the results presented in this paper, it was concluded that plasma light source was more effective compared with other light source for the detection and the quantification of early enamel caries.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.283-285
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• 2013

피부의 관리를 위한 방법 중 광을 이용한 케어는 비침습적인 방법으로 세포를 활성화 시켜 도움을 주는 매우 유용한 방법이다. 최근에는 낮은 에너지의 LED를 광원으로 이용하는 LLLT (Low Level Light Therapy)가 많이 적용이 된다. 본 논문에서는 피부 미용기기에서 많이 사용되고 있는 가시광 영역의 적색과 황색, 그리고 적외선 영역의 LED를 이용하여 array를 제작하였다. 제작된 LED array는 5V의 전압과 50mA의 전류로 구동되며, 적색이 평균 $10.7mW/cm^2$, 황색이 평균 $1.8mW/cm^2$, 적외선이 평균 $5.5mW/cm^2$의 광출력을 갖는다. 이를 배양된 human cell plate에 각각 10, 20, 40분의 시간으로 조사하였으며, LED array와 조사면 사이에 20 mm의 거리를 두어 균일한 광량이 조사 될 수 있도록 하였다. 실험결과, wound healing의 경우는 적색광을 조사하였을 때, injury line의 길이가 $604.36{\mu}m$에서 10분 조사 시 $368.92{\mu}m$, 20분 조사 시 $298.04{\mu}m$, 40분 조사 시 $491.22{\mu}m$로 줄어드는 효과를 보였으며 특히 20분간 조사하였을 경우의 효과가 가장 좋았다. Cell regeneration의 경우는 황색광을 20분간 조사하였을 경우에 UV 에 의해 손상된 세포 수가 가장 크게 줄어드는 것을 확인할 수 있었다. 결과적으로 photorejuvenation 효과를 줄 수 있는 wound healing과 cell regeneration에는 적색 및 황색광의 LED array를 20분간 조사하였을 때가 가장 효과적이었으며, 적외광의 경우에는 모든 실험에서 효과가 없음을 확인할 수 있었다.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.18 no.2
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• pp.61-67
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• 1982

Optical properties of sea water were studied in the southern sea of Korea, based on ten oceanographic stations in July, 1980. Submarine daylight intensity was measured at intervals of 5m depth in the upper 70m layer by using the underwater irradiameter (Kahlsico # 268 WA 360). The mean absorption coefficients of the sea water were shown as 0.102 (0.066~0.137), 0.119 (0.069~0.154), 0.091 (0.054~.0123), and 0.095 (0.056~0.129) for clear, red, green, and blue color respectively. The transparency ranged from 13 to 25 meters (mean 17.1 m). The mean water color in this area was 3.9 (3-5) in Forel scales. The relation between absorption coefficient (k) and transparency (D) was k=1.17/D, k=2.01/D, k=1.52/D, and k=1.60/D for clear, red, green, and blue color respectively. The rates of light penetration for clear, red, green, and blue color in four different depths were computed with reference to the surface light intensity respectively. The mean rates of light penetration in proportion to depths were as follows; clear : 57.3%(5m), 20.82%(15m), 5.16%(30m), 0.94%(50m). red : 52.2%(5m), 15.99%(15m), 2.99%(30m), 0.39%(50m). green : 60.9%(5m), 24.51%(15m), 7.11%(30m), 1.56%(50m). blue : 59.4%(5m), 22.92%(15m), 6.09%(30m), 1.29%(50m).

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.5-14
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• 2018

Recently the construction of solar plant showed a steady growth in influence of renewable energy policy. It is very important to determine the optimal location and aspect of solar panel using analyzed data of solar radiation to solar plant area beforehand. This study analyzed solar radiation in solar plant area using DEM acquired from UAV geospatial information. Mean solar radiation of 2017 was calculated as $1,474,466W/m^2$ and total solar radiation of 2017 considering solar plant area showed $33,639MW/m^2$ on analyzed result. It is important to analyze monthly solar radiation in aspect of maintenance works of solar plant. Monthly solar radiation of May to July was calculated over $160,000W/m^2$ and that of January to February and November to December showed under $80,000W/m^2$ in monthly solar radiation analysis of solar plant area. Also this study compared with solar radiation being calculated from UAV geospatial information and that of National Institute of Meteorological Sciences. And mean solar radiation of study area showed a little high in comparison with whole country data of National Institute of Meteorological Sciences, because the 93.7% of study area was composed of south aspect. Therefore this study can be applied to calculate solar radiation in new developed solar plant area very quickly using UAV.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.10 no.4
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• pp.237-241
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• 1977

Optical properties were studied in the Northwest Pacific near Kamchatka Peninsula based on ten oceanographic stations from September 20 to 24, 1976. Submarine light intensity was measured by usins a submarine illuminometer (RIGO, Type: 2501-A) ; equipped with a red filter (RIGO, Type: V-R-60, wave length: 600-620 nm). Light intensity in the upper 40 m depth layer was measured at 1 m depth intervals. The absorption coefficient for red color in the area ranged from 0. 178 to 0.376 (mean 0.278) : the Secchidisc depth in the area ranged from 9 to 12 meters (mean 10.6 meters). The relationship between absorption coefficient (m) and transparency depth (D) was m=5.347/D. The rates of light penetration for red color at three different depths are computed with reference to the surface light intensity. The mean rates of light penetration were $16.36\%\;(6.45\~23.5\%),\;3.65\%\;(1.38\~7.31\%)\;and\;0.276\%(0.048\~0.647\%) $ at the depths of s m, 10 m, and 20 m, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.444-444
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• 2022

하천 수심 계측은 수심을 사람이 직접 계측하거나 초음파 기반 유속계 (ADCP) 등 최신 계측기기를 이용하여 간접적으로 계측을 실시하고 있다. 하지만 사람이 직접 하천에서 수심을 측정하는 것은 위험이 동반되고, 수심자료의 측정오차가 크게 발생한다. 따라서 수심측정에서 직접 측정 방식의 한계를 극복하기 위해, 초분광 영상의 반사도와 수심이 높은 상관관계를 보이는 것을 활용하여, 초분광 영상 기반 수심 산정 기법을 개발하였다. 초분광 영상 기반 수심 산정 기법은 복수의 파장이 존재하는 초분광영상으로부터 두 개의 파장대의 밴드를 추출하여 모든 경우의 수에 대해 밴드비를 산정한 후, 실측수심과 밴드비 간의 회귀분석을 실시하여 상관계수가 가장 높은 회귀식을 찾아내는 방식이 최적 밴드비 분석법에 기반한다. 최적 밴드비 분석법을 통해 획득된 높은 상관성의 밴드비-수심 관계식을 이용하여 수심을 추정할 수 있다. 이러한 방법은 직접 수심 측정 방식에 비해, 높은 해상도와 밀도, 양질의 데이터를 수집할 수 있는 장점이 있다. 과거 연구에 따르면 저수심부에서의 높은 정확도의 수심추정 결과를 보였지만, 고수심부에서는 실측수심과의 오차도 높아지는 등 정확성이 떨어지는 경향을 보인다. 따라서 본 연구에서는 보다 효율적인 수심계측을 할 수 있도록 최적 밴드비 분석법을 활용한 수심추정에서 신뢰성 있는 수심의 범위를 파악할 수 있는 방법을 제시하고자 한다. 본 연구에서는 대상지역으로 낙동강 본류와 황강 지류 합류부로 선정하였고, 초음파 기반 유속계(ADCP)와 드론을 활용하여 실측수심과 초분광 영상을 취득하였다. 민감도 분석을 위한 수심자료를 0.5m 단위로 분할하였으며, 구간별로 최적 밴드비 분석을 실시하였다. 그 결과, 구간별로 산정된 상관계수와 평균제곱근오차 (RMSE)를 통해 정확도가 높은 구간을 구별할 수 있었다. 또한 해당 구간을 초과하는 수심은 초분광 영상을 통해 추정이 어려운 것으로 판단되며, 분석한 구간까지를 최대 추정 가능 수심으로 정의하였다. 마지막으로 검증을 위해 최대추정가능수심으로 판단된 구간까지의 데이터만 활용하여 최적 밴드비 분석법을 적용하여 상관계수나 평균제곱근오차 결과의 개선여부 확인을 통해, 본 연구에서 제시한 방법이 정확한 최대추정가능수심 구간을 산정할 수 있는지 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.514-517
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• 2017

In solar photovoltaic systems, power generation is greatly affected by the weather conditions, so it is essential to predict solar energy for stable load operation. Therefore, data on weather conditions are needed as inputs to machine learning algorithms for solar energy prediction. In this paper, we use 15 kinds of weather data such as the precipitation accumulated during the 3 hours of the surface, upward and downward longwave radiation average, upward and downward shortwave radiation average, the temperature during the past 3 hours at 2 m above from the ground and temperature from the ground surface as input data to the algorithm. We analyzed the statistical characteristics and correlations of weather data and extracted the downward and upward shortwave radiation averages as a major elements of a feature vector with high correlation of 70% or more with solar energy.