• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.610-621
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• 2021

The soil creep, primarily caused by earthquakes and torrential rainfall events, has widely occurred across the country. The Korea Forest Service attempted to quantify the soil creep susceptible areas using a discriminant value table to prevent or mitigate casualties and/or property damages in advance. With the advent of advanced computer technologies, machine learning-based classification models have been employed for managing mountainous disasters, such as landslides and debris flows. This study aims to quantify the soil creep susceptibility using several classifiers, namely the k-Nearest Neighbor (k-NN), Naive Bayes (NB), Random Forest (RF), and Support Vector Machine (SVM) models. To develop the classification models, we downscaled 292 data from 4,618 field survey data. About 70% of the selected data were used for training, with the remaining 30% used for model testing. The developed models have the classification accuracy of 0.727 for k-NN, 0.750 for NB, 0.807 for RF, and 0.750 for SVM against test datasets representing 30% of the total data. Furthermore, we estimated Cohen's Kappa index as 0.534, 0.580, 0.673, and 0.585, with AUC values of 0.872, 0.912, 0.943, and 0.834, respectively. The machine learning-based classifications for soil creep susceptibility were RF, NB, SVM, and k-NN in that order. Our findings indicate that the machine learning classifiers can provide valuable information in establishing and implementing natural disaster management plans in mountainous areas.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.27-35
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• 2019

This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.109-118
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• 2019

Road information is one of the most significant geospatial data for applications such as transportation, city planning, map generation, LBS (Location-Based Service), and GIS (Geographic Information System) database updates. Robust technologies to acquire and update accurate road information can contribute significantly to geospatial industries. In this study, we analyze the limitations of ACO (Ant Colony Optimization) road extraction, which is a recently introduced object-based road extraction method using high-resolution satellite images. Object-based ACO road extraction can efficiently extract road areas using both spectral and morphological information. This method, however, is highly dependent on object descriptor information and requires manual designations of descriptors. Moreover, reasonable iteration closing point needs to be specified. In this study, we perform improved ACO road extraction on VHR (Very High Resolution) optical satellite image by proposing an optimization stopping criteria and descriptors that complements the limitations of the existing method. The proposed method revealed 52.51% completeness, 6.12% correctness, and a 51.53% quality improvement over the existing algorithm.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1101-1117
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• 2018

The clear sky radiance (CSR) is one of the baseline products of the Himawari-8 which was launched on October, 2014. The CSR contributes to numerical weather prediction (NWP) accuracy through the data assimilation; especially water vapor channel CSR has good impact on the forecast in high level atmosphere. The focus of this study is the quality analysis of the CSR of the Himawari-8 geostationary satellite. We used the operational CSR (or clear sky brightness temperature) products in JMA (Japan Meteorological Agency) as observation data; for a background field, we employed the CSR simulated using the Radiative Transfer for TOVS (RTTOV) with the atmospheric state from the global model of KMA (Korea Meteorological Administration). We investigated data characteristics and analyzed observation minus background statistics of each channel with respect to regional and seasonal variability. Overall results for the analysis period showed that the water vapor channels (6.2, 6.9, and $7.3{\mu}m$) had a positive mean bias where as the window channels(10.4, 11.2, and $12.4{\mu}m$) had a negative mean bias. The magnitude of biases and Uncertainty result varied with the regional and the seasonal conditions, thus these should be taken into account when using CSR data. This study is helpful for the pre-processing of Himawari-8/Advanced Himawari Imager (AHI) CSR data assimilation. Furthermore, this study also can contribute to preparing for the utilization of products from the Geo-Kompsat-2A (GK-2A), which will be launched in 2018 by the National Meteorological Satellite Center (NMSC) of KMA.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.201-206
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• 2019

Korea is constructing geospatial information application system for geospatial information utilization, but it is trying to establish a system for joint use of geospatial information system centering on Ministry of Land Transport and Transport due to the problem of sharing. The purpose of this study is to investigate and analyze the geospatial information application system operated by local governments, and to suggest the application of geospatial information application system using unmanned aerial images. As a result of the research, it was found that the functions of existing spatial information application system are concentrated on the public services and it is difficult to share and utilize data between administrative departments. In addition, the utilization of the system using unmanned aerial image has been suggested, and additional functions such as vector display, area calculation, and report generation have been derived to improve the usability of geospatial information application system. If additional functions of spatial information application system are added through further studies in the future, it will be possible to use it as a basic data of field survey and policy decision in related fields. And non-experts will be able to improve the efficiency of work by utilizing highly accurate geospatial information in various fields.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.27-35
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• 2018

The passive containment cooling system (PCCS) has been designed to remove the released decay heat during the accident by means of the condensation heat transfer phenomenon to guarantee the safety of the nuclear power plant. The heat removal performance of the PCCS is mainly governed by the condensation heat transfer of the steam-air mixture. In this study, the heat removal performance of the PCCS was evaluated by using the MARS-KS code with a new empirical correlation for steam condensation in the presence of a noncondensable gas. A new empirical correlation implemented into the MARS-KS code was developed as a function of parameters that affect the condensation heat transfer coefficient, such as the pressure, the wall subcooling, the noncondensable gas mass fraction and the aspect ratio of the condenser tube. The empirical correlation was applied to the MARS-KS code to replace the default Colburn-Hougen model. The various thermal-hydraulic parameters during the operation of the PCCS follonwing a large-break loss-of-coolant-accident were analyzed. The transient pressure behavior inside the containment from the MARS-KS with the empirical correlation was compared with calculated with the Colburn-Hougen model.

• Ecology and Resilient Infrastructure
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• v.5 no.4
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• pp.246-256
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• 2018

In order to analyze hydraulic characteristics of discharge coefficient, hydraulic jump height, and hydraulic jump length, accompanied sediment transport, in the under-flow type vertical lift gate, the hydraulic model experiment and dimensional analysis were performed. The correlations between Froude number and hydraulic characteristics were schematized according to the presence and absence of sediment transport; the correlation of hydraulic characteristics and non-dimensional parameters was analyzed and multiple regression formulae were developed. In the hydraulic characteristics accompanied the sediment transport, by identifying the aspect different from the case that the sediment transport is absent, we verified that it is necessary to introduce variables that can express the characteristics of sediment transport. The multiple regression equations were suggested and each determination coefficient appeared high as 0.749 for discharge coefficient, 0.896 for hydraulic jump height, and 0.955 for hydraulic jump length. In order to evaluate the applicability of the developed hydraulic characteristic equations, 95% prediction interval analysis was conducted on the measured and the calculated by regression equations, and it was determined that NSE (Nash-Sutcliffe Efficiency), RMSE (root mean square), and MAPE (mean absolute percentage error) are appropriate, for the accuracy analysis related to the prediction on hydraulic characteristics of discharge coefficient, hydraulic jump height and length.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.23-32
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• 2019

In this paper, we proposed a multi-chain Time of Arrival (ToA) positioning method to estimate positions using all received Loran-C signals from multiple chains without constraining to a single chain. Conventionally, we have to choose only one chain among several available chains for position estimation using Loran-C. Therefore, the number of signals to be used for positioning is limited to three to five. In general, if more signals are used for positioning estimation, its performance tends to be improved in terms of accuracy and availability. To validate the proposed method for multi-chain Loran-C, we firstly carried out a static positioning test in land. By analyzing the test results, we confirmed that the proposed method works well under a multi-chain Loran-C scenario. Subsequently, another mobile positioning test was conducted on board a vessel under a practical application scenario. From this second test, we successfully demonstrated that the multi-chain ToA positioning method even in situations where the conventional single-chain Loran-C approach fails for positioning.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.263-268
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• 2019

Methanol is a toxic alcohol used in various products such as antifreeze, detergent, disinfectant and industrial solvent. In the human body, methanol is oxidized to formaldehyde and formic acid, which can lead to metabolic acidosis, optic nerve impairment, and death. In this study, the methanol levels in detergents (n=191) and rinse aids (n=13) were analyzed by gas chromatography-headspace-mass spectrometry (GC-HS-MS). Limit of detection was 1.09 mg/kg, accuracy and precision were 91.1-97.9% and <10%, and it was suitable for quantitative analysis. This analysis method was simple and fast with a higher recovery rate than the conventional MFDS (Ministry of Food and Drug Safety) method of diluting the sample in water and putting it in a headspace vial.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.156-162
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• 2021

The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.