• Analytical Science and Technology
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• v.15 no.5
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• pp.399-409
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• 2002

A system software on-line spectral analysis of atomic emission spectrometer. The system program consisted of a control part for the optical instruments and the spectrum analysis part the artificial intelligence method to reduce nonlinear error of the wavelengths. McPHERSON 207 Monochromator controlled GPIB communication protocol, and the detector signal was measured from PMT by using A/D Amplifier that was made by Photon_Tek. co.. HNN(Hybrid Neural Network) of artificial intelligence technique was applied to the qualitative analysis of P, Cu, Fe, Cr, and that was accurately applied to the quantitative analysis of Cd with 10 ppb level better than the conventional methods.

• Journal of Astronomy and Space Sciences
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• v.21 no.2
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• pp.121-128
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• 2004

As the first step of the real time monitoring system of the solar radio disturbance, we constructed the control system of the solar radio telescope. An 1.8m antenna built by Korean Astronomy Observatory has been used, and the observed radio flux is transformed to the digital signal by the powermeter. We have also developed a computer program CBNUART in order to control the telescope system and the powermeter. As the sun rises, the telescope begins to observe the sun, and ends the observation automatically at sunset. The CBNUART enables the telescope automatically to go to the position of the sunrise for the beginning the observation and come back to the setposition after the ending the observation at the sunset. An active tracking routine is adopted in order to improve the tracking accuracy of the control system, and we used an optical telescope equipped in front of the antenna for control test. The tracking test shows that our control system can track with the accuracy of arc seconds, and the 50 minute pointing test shows that the pointing accuracy of right ascension and declination are 1.12 and 0.08 arc minutes respectively.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.232-237
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• 2010

In this paper, a slit light laser range finding method using perspective warping calibration is proposed. This approach has an advantage to acquire relatively high accuracy, although the optical system is nonlinear. In the calibration, we detect the calibration points which are marked on the calibration panel and acquire the center position of the slit light laser in the image, which are used for computing the real positions of the slit light by using perspective warping. A calibration file is obtained by integrating the calibration data with the transition of the panel. The range data is acquired by interpolating the center position of the slit light laser to the calibration coordinates. Experimental results show that the proposed method provides the accuracy of 0.08mm error in depth range of 130mm with the low cost optical system.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.43 no.3
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• pp.247-254
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• 2017

Optical Coherence Tomography (OCT) is a non-invasive imaging method that utilizes the optical scattering and interference for visualizing the surface as well as cross-sectional structures of tissue. OCT has been used for diagnosing diseases in early stage in various medical fields, but an application in cosmetics is still at early stage. In this study, OCT was adopted to evaluate skin texture and wrinkle. Results showed similar patterns of evaluation with PRIMOS in the assessment using replica. In addition, OCT produced smaller errors at different angles compared to the PRIMOS in the assessment using 3-dimensional models of wrinkles. The resolution of the image was also high enough to differentiate the images of before and after the application of makeup products. Possible use of OCT in the evaluation of fine wrinkle assessment was studied in this research. Further development of methods is necessary to provide more evidences of the effectiveness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.15-21
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• 2020

In this paper, the observation performance of the electro-optical telescope system which surveils the unknown space objects, is analyzed by the Modeling & Simulation(M&S). The operation concept for the observation of the unknown space objects using two telescope systems is considered and the M&S models are constructed. Based on the operation concept for observing the unknown space objects, the estimated orbit is generated by Initial Orbit Determination(IOD) and the observation performance is analyzed according to the offset compensation cycle for the estimated orbit. The result of the M&S based analysis in this paper shows that the observation performance increases with the shorter offset compensation cycle, and decreases with the longer offset compensation cycle. Therefore, to improve the performance of the telescope system which surveils the unknown space objects, the observation system with accurate initial orbit determination or shorter offset compensation cycle should be designed and constructed.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.37-45
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• 2021

Flooding damage may occur due to an unexpected increase in rainfall in summer. Previously, the roughness coefficient, which is a major factor of conveyance, was calculated through on-site measurement, but in case of on-site measurement, there are many limits in accurately grasping changes in vegetation. In this study, the vegetation index (NDVI) was calculated using the Sentinel-2 optical images, and the modified roughness coefficient was calculated through the density and distribution area of the vegetation. Then the calculated roughness coefficient was applied to HEC-RAS 1D model and verified by comparing the results with the water level at the water level station directly downstream of the Soyang River dam. As a result, the error rate of the water level decreased about 14% compared to applying the previous roughness coefficient. Through this, it is expected that it will be possible to refine the flood level of rivers in consideration of seasonal flood characteristics and to efficiently maintain rivers in specific sections.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.213-213
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• 2021

한국농어촌공사 농어촌연구원은 하천 및 해안분야의 다양한 수리모형실험을 수행할 수 있는 대형 수리모형실험 시설을 2018년에 구축완료하였다. 국내 최대 규모의 실험장뿐만 아니라 첨단 광학용 계측장비(PIV 및 LDV 시스템)를 연계한 전용실험수로, 대형유사실험수로 등 7종의 기능별 실험수로를 갖추고 있어 다양한 수리현상 분석을 수행할 수 있다. 최근에는 산사태의 주요 원인중 하나인 토석류 실험, 방조제 주변의 침·퇴적 실험 등을 수행하였으며, 본 연구에서는 3D 지형스캐너를 활용한 방조제 주변의 지형변동 수리모형실험에 대하여 소개를 하고자 한다. 방조제는 조수가 육지쪽으로 밀려들어와 내부개발지역이나 농지 등을 해수로부터 보호하기 위해 설치되는 외곽시설이다. 이러한 방조제 전면의 빠른 유속에 의한 침식은 배후지의 안전에 상당히 큰 문제를 야기시킨다. 방조제의 침식을 방지하기 위하여 방조제 전면에 수제공을 설치하여 수제공과 수제공 사이의 느려진 유속에 의해 방조제 전면에 토사를 퇴적시키는 방법이 있다. 본 연구에서는 방조제 전면에 수제공의 길이를 달리 설치하여 수제공 주변의 침·퇴적현상을 이동상 실험을 수행하여 분석하였다. 일반적으로 토사의 침·퇴적고를 계측하는 방법으로 일정한 격자망을 구성하여 각 지점별로 실험 전·후의 토사의 표고차를 수작업으로 계측한다. 이 경우는 실험자가 직접 측정하는 계측오차가 발생하게 되고 측정할 수 있는 지점의 수가 한계가 있어 전체적인 토사의 변화양상을 분석하기엔 어려움이 있다. 이를 해결하기 위하여 본 연구에서는 농어촌연구원이 보유하고 있는 3D 지형스캐너를 활용하여 토사의 표고차를 측정하였다. 실험에 사용한 3D 지형스캐너의 최대 측정거리는 스캐너가 설치된 중심점으로부터 반경 80m에 해당하며, 해상도는 1.6mm~50mm의 범위로 수작업으로 격자망을 구성하여 측정하는 것보다 상당히 높은 수준의 결과를 취득할 수 있으며 계측시간을 단축할 수 있는 장점이 있다. 하지만, 펄스레이저에 의한 지형스캔 방식은 수면과 같이 레이저가 투과할 수 없는 경우에는 계측이 불가능하며, 어두운 계열의 색을 스캔하는 경우 결과 분석에 주의할 필요가 있다. 본 연구에서는 이동상 재료로 안트라사이트(검은색)를 포설하였고, 검은색 계열의 실험사에도 3D 지형스캐너가 우수한 결과를 제공하는 것을 확인하였다.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.233-243
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• 2021

Photovoltaic panels are hazardous electronic waste that has heavy metal as one of the hazardous components. Each year, hazardous electronic waste is increasing worldwide and every heavy rainfall exposes the photovoltaic panel to become the source of heavy metal soil contamination. the development needs a monitoring technology for this hazardous exposure. this research use relationships between SAR temporal baseline and coherence of Sentinel-1 satellite to detected photovoltaic panel. Also, the photovoltaic plant detection tested using the difference between that photovoltaic panel and the other difference surface of coherence. The author tested the photovoltaic panel and its environment to calculate differences in coherence relationships. As a result of the experiment, the coherence of the photovoltaic panel, which is assumed to be a permanent scatterer, shows a bias that is biased toward a median value of 0.53 with a distribution of 0.50 to 0.65. Therefore, further research is needed to improve errors that may occur during processing. Additionally, the author found that the change detection using a temporal baseline is possible as the rate of reduction of coherence of photovoltaic panels differs from those of artificial objects such as buildings. This result could be an efficient way to continuously monitor regardless of weather conditions, which was a limitation of the existing optical satellite image-based photovoltaic panel detection research and to understand the spatial distribution in situations such as photovoltaic panel loss.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.