• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.859-873
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• 2023

Wildfires cause a lot of environmental and economic damage to the Earth over time. Various experiments have examined the harmful effects of wildfires. Also, studies for detecting wildfires and pollutant emissions using satellite remote sensing have been conducted for many years. The wildfire product for the Geostationary Environmental Monitoring Spectrometer (GEMS), Korea's first environmental satellite sensor, has not been provided yet. In this study, a false-color composite for better expression of wildfire smoke was created from GEMS and used in a U-Net model for wildfire detection. Then, a classification model was constructed to distinguish yellow dust from the wildfire smoke candidate pixels. The proposed method can contribute to disaster monitoring using GEMS images.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.161-167
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• 2004

Maritime safety and marine environmental protection are the most important topic in marine society. But, so many marine accidents have been occurred with the development of marine transportation industry. On the other side, ship is being operated under a highly dynamic environment and many factors are related with ship's collision Nowadays, the increasing tendency to the human errors of ship's collision is remarkable, and the investigation of the human errors has been heavily concentrated. This study analysed on the human errors of ship's collision related to the negligence of lookout and classified basic error type using GEMS(Generic Error Modeling System) dynamic model.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Journal of the Korean earth science society
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• v.39 no.1
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• pp.53-66
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• 2018

The information of surface reflectance ($R_{sfc}$) is important for the heat balance and the environmental/climate monitoring. The $R_{sfc}$ sensitivity to error-induced variables for the Geostationary Environment Monitoring Spectrometer (GEMS) retrieval from geostationary-orbit satellite observations at 300-500 nm was investigated, utilizing polar-orbit satellite data of the MODerate resolution Imaging Spectroradiometer (MODIS) and Ozone Mapping Instrument (OMI), and the radiative transfer model (RTM) experiment. The variables in this study can be cloud, Rayleigh-scattering, aerosol, ozone and surface type. The cloud detection in high-resolution MODIS pixels ($1km{\times}1km$) was compared with that in GEMS-scale pixels ($8km{\times}7km$). The GEMS detection was consistent (~79%) with the MODIS result. However, the detection probability in partially-cloudy (${\leq}40%$) GEMS pixels decreased due to other effects (i.e., aerosol and surface type). The Rayleigh-scattering effect in RGB images was noticeable over ocean, based on the RTM calculation. The reflectance at top of atmosphere ($R_{toa}$) increased with aerosol amounts in case of $R_{sfc}$<0.2, but decreased in $R_{sfc}{\geq}0.2$. The $R_{sfc}$ errors due to the aerosol increased with wavelength in the UV, but were constant or slightly decreased in the visible. The ozone absorption was most sensitive at 328 nm in the UV region (328-354 nm). The $R_{sfc}$ error was +0.1 because of negative total ozone anomaly (-100 DU) under the condition of $R_{sfc}=0.15$. This study can be useful to estimate $R_{sfc}$ uncertainties in the GEMS retrieval.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.22 no.4
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• pp.170-177
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• 2012

Amethyst gems represents thermal effects of far-infrared emission, promotes the body's metabolism, and attracts attention as an eco-friendly interior material. In this paper, amethyst increase the value of jeweling by applying the characteristic purple motif, furthermore, I will intend to develop of design model. Metal crafting of brooch & necklace in the works performed based on the organic three-dimensional shape of the Rhino CAD Data. It was made possible through the precise laminated wax processing and then combining the amethyst. I researched the ornament modeling by applying the 'Golden Ratio', and suggesting utilizing method for interior jewel modeling, and also, is expected that this paper on the amethyst modeling design can contribute to the manufacturers' productivity.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.15-20
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• 2008

Hydraulic analysis of water distribution system can be divided into demand-driven analysis and pressure-driven analysis. Demanddriven analysis can give unrealistic results to simulate hydraulic conditions under abnormal operating conditions such as sudden demand increase and pipe failure. In Korea, demand-driven analysis has been used to establish emergency water supply plan in many water projects, but it is necessary to use pressure-driven analysis for establishment of emergency water supply plan. In this study, WaterGEMS model that was developed for pressure-driven analysis is used to evaluation of emergency water supply plan of J city. As the results, it was able to draw up more efficient plan for water supply in small block, and established emergency water supply plan of J city was determined to be appropriate.

• Journal of the Korean Society of Safety
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• v.20 no.1 s.69
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• pp.153-157
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• 2005

The injury accidents in fishing vessels account for $67.2\%$ of all marine injury casualties$(1997\~2001)$ and is on an increasing trend every year. Also, it is remarkable for the injury accidents to be basically caused by human errors. This study aims to investigate the human error of injury accidents in fishing vessels and presents the injury preventing program in them. Human errors were analysed by the methods such as SHELL & Reason Hybrid Model, GEMS Model adopted by International Maritime Organization(IMO). Based on the analysis, the following propositions were made to reduce the fishing vessels accidents by human errors : improvement of hazard awareness and quality of personnel, establishment of safety management system, and enforcement of vessels inspection.

• Journal of Navigation and Port Research
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• v.34 no.2
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• pp.145-152
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• 2010

The management of safety at sea is based on a set of internationally accepted regulations and codes, governing or guiding the design and operation of ships. The regulations most directly concerned with human safety and protection of the environment are, in general, agreed internationally through the International Maritime Organization(IMO). IMO has continuously dealt with safety problems and, recognized that the human element is a key factor in both safety and pollution prevention issues(IMO, 2010). This paper proposes a human error analysis methodology which is based on the human error taxonomy and theories (SHELL model, GEMS model and etc.) that were discussed in the IMO guidelines for the investigation of human factors in marine casualties and incidents. In this paper, a cognitive process model, a human error analysis technique and a marine accident causal chains focused on human factors are discussed, and towing vessel collision accidents are analyzed as a case study in order to examine the applicability of the human error analysis technique to marine accidents. Also human errors related to those towing vessel collision accidents and their underlying factors are discussed in detail.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1491-1506
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• 2021

To estimate errors in GEMS retrievals for bromine monoxide (BrO) total vertical column densities(VCDs), we perform a sensitivity test using synthetic spectra generated by a radiative transfer model. Hourly synthetic data are produced for 00-07 UTC on the first day of every month in Jul 2013- Jun 2014. Solution errors estimated by the optimal estimation method tend to decrease with increasing air mass factors (AMFs) but increase when AMFs are larger than 5. Interference errors induced by formaldehyde (HCHO) absorption appear to be larger with smaller BrO AMFs. Total BrO retrieval errors estimated by combining solution and interference errors show an average of 26.74±30.18% for all data samples and 60.39±133.78% for those with solar zenith angles higher than 80°. Due to interfering spectral features and measurement errors not considered in thisstudy, errorsin BrO retrievals from actual GEMS measurements may have different magnitudes from our estimates. However, the variability of errors assessed in this study is still expected to appear in the actual BrO retrievals.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.4
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• pp.488-495
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• 2017

In this study, we conducted the kinetic hydration modeling of OPC and the final product according to the substitution ratio of GGBS by using the geochemical code, GEMS, in order to calculate the thermodynamic equilibrium. The thermodynamic data was used by GEMS's 3rd party database, Cemdata18, and the cement hydration model, the Parrot & Killoh model was applied to simulate the hydration process. In OPC modeling, ion concentration of pore solution and hydration products by mass and volume were observed according to time. In the GGBS modeling, as the substitution rate increases, the amount of C-S-H, which contributes the long-term strength, increases, but the amount of Portlandite decreases, which leads to carbonation and steel corrosion. Therefore, it is necessary to establish prevention of some deterioration.