• Journal of the Korean Geophysical Society
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• v.2 no.1
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• pp.27-38
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• 1999

The errors between track segments or at the cross-over points of shipborne gravity were successfully reduced by applying a cross-over error adjustment technique using satellite gravity. The integration of shipborne and satellite altimeter-implied free-air gravity anomalies after the cross-over error adjustment resulted in a high resolution gravity map which contains both short and long wavelength components. The successful adjustment of the cross-over errors in the shipborne gravity using the satellite gravity suggests that the shipborne gravity can be combined with the satellite anomalies characterized by a stable and long wavelength component. The resulting free-air anomaly map is evenly harmonized with both short and long wavelength anomalies. Thus the corrected anomaly map can be better used for the geological interpretation. Free-air anomalies with more than 140 mGal in total variations generally correspond to the seafloor topographic changes in their regional patterns. A series of gravity highs are aligned from the Korea Plateau to the Oki Island, which are interpreted to be caused by seamounts or volcanic topographies. The gravity minima along the western and southern shelf edge are associated not only with the local basement morphology and thick sediment fill at the continental margin, but also possibly with the crustal edge effect known for passive continental margins. Series of NE-trending linear anomalies are possibly caused by a swarm of volcanic intrusions followed the initial opening of the Ulleung Basin. The linear high anomalies in the Ulleung Plateau are terminated by the straightly NNW-trending anomalies with a sharp gradient in its western boundary which indicates a fault-line scarp. The opposite side adjoined with the fault-line scarp shows no correlation with the fault-line scarp in geometry indicating that the block might be horizontally slided from the north. A gravity high in contrast to the deepening in seafloor toward the northeastern central Ulleung Basin is probably responsible for the thin crust and shallow seated mantle. The gravity minima along the western and southern shelf edge are associated not only with the local basement morphology and thick sediment fill at the continental margin, but also possibly with the crustal edge effect known for passive continental margins. Series of NE-trending linear anomalies are possibly caused by a swarm of volcanic intrusions followed the initial opening of the Ulleung Basin. The linear high anomalies in the Ulleung Plateau are terminated by the straightly NNW-trending anomalies with a sharp gradient in its western boundary which indicates a fault-line scarp. The opposite side adjoined with the fault-line scarp shows no correlation with the fault-line scarp in geometry indicating that the block might be horizontally slided from the north. A gravity high in contrast to the deepening in seafloor toward the northeastern central Ulleung Basin is probably suggestive of a thin crust and shallow seated mantle.

• Journal of the Korean Vacuum Society
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• v.18 no.1
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• pp.66-72
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• 2009

The detection methods are required to monitor and diagnose the abnormality on the insulation condition inside a gas-insulated switchgear (GIS). Due to a good sensitivity to the products decomposed by partial discharges (PDs) in $SF_6$ gas, the development of a SWNT gas sensor is actively in progress. However, a few numerical studies on the diffusion mechanism of the $SF_6$ decomposition products by PD have been reported. In this study, we modeled $SF_6$ decomposition process in a chamber by calculating temperature, pressure and concentration of the decomposition products by using a commercial CFD program in conjunction with experimental data. It was assumed that the mass production rate and the generation temperature of the decomposition products were $5.04{\times}10^{-10}$ [g/s] and over 773 K respectively. To calculate the concentration equation, the Schmidt number was specified to get the diffusion coefficient functioned by viscosity and density of $SF_6$ gas instead rather than setting it directly. The results showed that the drive potential is governed mainly by the gradient of the decomposition concentration. A lower concentration of the decomposition products was observed as the sensors were placed more away from the discharge region. Also, the concentration increased by increasing the discharge time. By installing multiple sensors the location of PD is expected to be identified by monitoring the response time of the sensors, and the information should be very useful for the diagnosis and maintenance of GIS.

• Economic and Environmental Geology
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• v.44 no.6
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• pp.493-502
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• 2011

We study the deep structure of Korean Peninsula by estimating Moho depth and crustal thickness from using land and oceanic topography and free-air gravity anomaly data. Based on Airy-Heiskanen isostatic hypothesis, the correlated components between the terrain gravity effects and free-air gravity anomalies by wavenumber correlation analysis(WCA) are extracted to estimate the gravity effects that will be resulted from isostatic compensation for the area. With the resulting compensated gravity estimates, Moho depth that is a subsurface between the crust and mantle is estimated by the inversion in an iterative method with the constraints of 20 seismic depth estimates by the receiver function analysis, to minimize the uncertainty of non-uniqueness. Consequently, the average of the resulting crustal thickness estimate of Korean Peninsula is 32.15 km and the standard deviation is 3.12 km. Moho depth of South Korea estimated from this study is compared with the ones from the previous studies, showing they are approximately consistent. And the aspects of Moho undulation from the respective study are in common deep along Taebaek Mountains and Sobaek Mountains and low depth in Gyeongsang Basin relatively. Also, it is discussed that the terrain decorrelated free-air gravity anomalies inferring from the intracrustal characteristics of the crust are compared to the heat flow distributions of South Korea. The low-frequency components of terrain decorrelated Free-air gravity anomalies are highly correlated with the heat flow data, especially in the area of Gyeongsang basin where high heat flow causes to decrease the density of the rocks in the lower crust resulting in lowering the Moho depth by compensation. This result confirms that the high heat sources in this area coming from the upper mantle by Kim et al. (2008).

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.245-256
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• 2021

This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.

• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.138-153
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• 2018

The purpose of this study was to analyze , which was made in the late Joseon Dynasty to specify the vegetation landscape of the Donhwamun Gate area in Changdeokgung Palace. The study results can be summarized as below. First, based on "Jieziyuan Huazhuan(芥子園畵傳)", the introductory book of tree expression delivered from China in the 17th century, allowed the classification criteria of the trees described in the picture to be established and helped identify their types. As a result of the classification, there were 10 species and 50 trees in the Donhwamun Gate area of . Second, it was possible to measure the real size of the trees described in the picture through the elevated drawing scale of . The height of the trees ranged from a minimum of 4.37 m to a maximum of 22.37 m. According to the measurement results, compared to the old trees currently living in Changdeokgung Palace, the trees described in the picture were found to be produced in almost actual size without exaggeration. Thus, the measured height of the trees turned out to be appropriate as baseline data for reproduction of the vegetation landscape. Third, through the Rubber Sheeting Transformation of , it was possible to make a ground plan for the planting of on the current digital topographic map. In particular, as the transformed area of was departmentalized and control points were added, the precision of transformation improved. It was possible to grasp the changed position of planting as well as the change in planting density through a ground plan of planting of . Lastly, it was possible to produce a three-dimensional vegetation landscape model by using the information of the shape of the trees and the ground plan for the planting of . Based on the three-dimensional model, it was easy to examine the characteristics of the three-dimensional view of the current vegetation via the view axis, skyline, and openness to and cover from the adjacent regions at the level of the eyes. This study is differentiated from others in that it verified the realism of and suggested the possibility of ascertaining the original form of the vegetation landscape described in the painting.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.2
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• pp.89-100
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• 2021

This study evaluated the degree of interaction between the people and the environment using perceived naturalness measure. The seventh-grade index of Hemeroby was divided into subclasses of land cover according to degrees of human influence. The grade was standardized for each indicator to evaluate the current state of urban parks in Seoul by applying probability density function and weight. User evaluation was conducted on six distinctive parks selected. In the results, three implications were found between spatial evaluation according to the perceived naturalness. First, park users evaluated highly for the spaces such as broad-leaved forest, coniferous forest and mixed forest evaluated highly in the Hemeroby grade index. Park users generally recognized that various types of trees in the area had high naturalness. The density of trees is one of the factors in perceived naturalness. Second, water spaces were highly evaluated for naturalness in the Hemeroby grade index. However, the perceived naturalness of water spaces such as inland wetlands, pond and reservoir evaluated in various ways depending on environmental conditions around the park. Third, perceived naturalness is easily evaluated through vertical landscape elements such as trees rather than horizontal landscapes such as grassland. The perceived naturalness is similar to the naturalness evaluation using land cover. However the study found the perceived naturalness for a specific space was different from the Hemeroby index. Perceived naturalness by the user includes the content that the individual sees, hears, and experiences. Park users are usually structuring naturalness through evaluating the value of urban green spaces based on personal perception. Therefore there is no absolute standard criterion for evaluating the naturalness of urban green spaces. A deeper study is needed that considers user bundles or user groups with conflicting interests on the perceived naturalness in urban parks. These studies will be essential data on the direction of naturalness urban park service should provide.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1653-1667
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• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.383-391
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• 2021

To develop a cultivation method for the mass production of sweetpotato cultivars, 'Juhwangmi' (orange tuber) and 'Sinjami' (puple tuber), the yield of tuber roots and content of various functional substances were analyzed according to planting intervals and growing periods. For 'Juhwangmi, the total yield of tubers was increased by respectively 36% and 54% and the yield of tubers over 300 g was increased by respectively 170% and 221% in the 140-day and 160-day cultivation plots compared with that in the 120-day cultivation plot at the 70×20 cm planting interval. Similarly, the total content of beta-carotene in the tubers increased as the cultivation period was extended. In particular, beta-carotene content at the 70×20 cm planting interval was the highest. For 'Sinjami', at the same planting interval, the total yield of tubers and yield of tubers over 300 g significantly increased as the growing period was extended. Within the same cultivation period, the yield of tubers over 300 g and the total anthocyanin content of 'Sinjami' were higher at the 70×30 and 70×35 cm planting intervals than at the 70×20 and 70×25 cm planting intervals in the 140-day and 160-day cultivation plots. Moreover, the total polyphenol and flavonoid content was significantly higher in 'Sinjami' than in 'Juhwangmi', and the values were the highest in the 160-day cultivation plots. In particular, the content of these two functional substances in tubers over 300 g was the highest at the 70×30 and 70×35 cm planting intervals.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.357-364
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• 2022

We investigated the early growth characteristics of Quercus rubra planted in six regions (Hwaseong, Yangpyeong, Pyeongchang, Samcheok, Chungju, and Gimje) in South Korea in relation to soil physicochemical properties and meteorological factors. Q. rubra (1-0) were planted at a density of 3,000 trees ha^-1. The average height, root collar diameter (RCD), and volume of 8-year-old Q. rubra planted in 2014 were 3.52 m, 3.84 cm, and 0.0023 m³, respectively. The growth parameters of Q. rubra were the highest and lowest in Hwaseong and Pyeongchang, respectively. Correlation analysis among the soil physicochemical properties, meteorological factors, and plantation growth characteristics found that pH was the only soil factor negatively correlated with RCD, and the other soil factors were not significantly correlated with the growth characteristics. However, growth characteristics were positively correlated to average temperature from March to October and daily maximum temperature; and they were negatively correlated to altitude, topology, and the number of rainy days from March to October. In particular, the trees planted in Hwaseong area showed the best early growth characteristics because this area had the highest daily maximum temperature, the x average temperature from March to October, the low altitude, and it is located close to the foot of a mountain. In Pyeongchang, the early growth characteristics were negatively affected by winter cold damage because of the high altitude, low daily minimum temperature, and damage by wild animals. In Hwaseong, meteorological factors such as temperature and altitude were more highly correlated to growth characteristics of Q. rubra than the physicochemical soil properties. These results will provide useful information for determining suitable sites for Q. rubra plantations and for predicting early growth characteristics in response to environmental factors.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.