• Journal of the Korean GEO-environmental Society
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• v.6 no.2
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• pp.5-14
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• 2005

In the present study, the liquefaction potential in the area of the Incheon international airport was assessed by applying the data of both standard penetration tests and laboratory tests to the modified Seed & Idriss method. The analysis was performed against the non-plastic silty soil layer and silty sand soil layer existing within the depth of 20m and under the ground water level, having the standard penetration value(N) of below 20. Also, each set of data was mapped using the GIS(Geographic Information System) and the safety factor against the liquefaction potential ($FS_{liquefaction}$) was obtained by overlapping those layers. Throughout the analysis, it was found that there exists a potential hazard zone for the liquefaction, showing partially that the safety factor against the liquefaction potential is 1.0 to 1.5 below the standard safety factor criterion. It is further thought to be necessary that the liquefaction potential for the corresponding hazard zone be additionally assessed in detail.

• Proceedings of the CALSEC Conference
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• 2001.08a
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• pp.577-590
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• 2001

Designing Seal Windows System ㆍReduced (by a factor of at least 10) the time for evaluating each design alternative ㆍIncreased quality by 20％ (measured as the number of errors that are caught before they propagate) ㆍFound and corrected errors prior to production with an estimated $1-2 million in annual savings in warranty costs ㆍCaptured the state of a design, particularly the parameters that were used to make decisions ㆍEliminated geographic and temporal obstacles ㆍDecreased wasted time caused by slow communication paths(omitted)

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06d
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• pp.40-45
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• 1998

본 논문은 한국산 박새(Parus major)의 소리(song)를 이용해서 태백산맥을 경계로 동서간의 지리적 변이에 관한 논문이다. 박새 소리의 지리적인 변이를 알아보기 위하여 지역간 음절의 시간과 주파수 요인을 비교하고, factor의 군집화의 지역간의 변이정도를 알아보기 위하여 Cluster Analysis와 discriminant Analysis를 실시하였다. 그 결과 태백산맥을 경계로 동쪽지역여과 서쪽지역은 영덕군과 청송군, 삼척시와 태백시를 중심으로 해서 지리적인 변이를 나타냈다.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.86-102
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• 2012

For predictive flooded area susceptibility mapping, this study applied and verified probability model and the frequency ratio using a geographic information system (GIS) and frequency raio. Flooded areas were identified in the study area of field surveys, For predictive flooded area susceptibility mapping, this study applied and verified probability model and the frequency ratio using a geographic information system (GIS) and frequency raio. Flooded areas were identified in the study area of field surveys, and maps of the topography, geology, landcover and green infrastructure were constructed for a spatial database. The factors that influence flooded areas occurrence, such as slope gradient, slope, aspect and curvature of topography and distance from darinage, were calculated from the topographic database. Lithology and distance from fault were extracted and calculated from the geology database. The frequency ratio coefficient is overlaid for flooded areas susceptibility mapping as each factor's ratings. Then the flooded areas susceptibility map was verified and compared using the existing flooded areas. As the verification results, the frequency ratio model showed 82% in prediction accuracy. The method can be used to reduce hazards associated with flooded areas and to plan land use.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.1
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• pp.57-66
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• 2001

This study used four theoretical models, such as two-point linear model, linear regression model, quadratic regression model and cubic regression model which are presented from The Ministry of Science and Technology, for extraction of urban surface temperature from Landsat TM band 6 image. Through correlation and regression analysis between result of four models and AWS(automatic weather station) observation data, this study could verify spatial distribution characteristic of urban surface temperature using GIS spatial analysis method. The result of analysis for surface temperature by landcover showed that the urban and the barren land belonged to the highest surface temperature class. And there was also -0.85 correlation in the result of correlation analysis between surface temperature and NDVI. In this result, the meteorological environmental characteristics wuld be regarded as one of the important factor in urban planning.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.3-9
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• 2007

Recently, the efforts of systematic understanding and utilization of geographic phenomenon for human life as a important factor among activity of mankind are increasing. It is necessary to express topography connected with space. Especially, the technology of geographic analysis using DEM can supply the information rapidly and accurately about elevation and terrain slope of the subject area under the necessity of high 3D quality geographic information. In this study, creating more precise DEM derived from LiDAR data, quantitative analysis on the subject area about elevation and terrain slope is done under comparison with Digital Topographic map Scale 1:1000. LiDAR data is more detailed than Digital Topographic map to express the elevation of the subject area ($39.89{\sim}77.48m$), and terrain slope by analysis using DEM derived from LiDAR data come out minutely about 90%. It can be concluded that the LiDAR data is very applicable and accurate for 3D topographic terrain slope analysis.

• Journal of Preventive Medicine and Public Health
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• v.54 no.4
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• pp.238-244
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• 2021

Objectives: Previous pandemics have demonstrated that several demographic, geographic, and socioeconomic factors may play a role in increased infection risk. During this current coronavirus disease 2019 (COVID-19) pandemic, our aim was to examine the association of timing of lockdown at the county level and aforementioned risk factors with daily case rate (DCR) in the United States. Methods: A cross-sectional study using publicly available data was performed including Americans with COVID-19 infection as of May 24, 2020. The United States counties with >100 000 population and >50 cases per 100 000 people were included. The independent variable was the days required from the declaration of lockdown to reach the target case rate (50/100 000 cases) while the dependent (outcome) variable was the DCR per 100 000 on the day of statistical calculation (May 24, 2020) after adjusting for multiple confounding socio-demographic, geographic, and health-related factors. Each independent factor was correlated with outcome variables and assessed for collinearity with each other. Subsequently, all factors with significant association to the outcome variable were included in multiple linear regression models using stepwise method. Models with best R² value from the multiple regression were chosen. Results: The timing of mandated lockdown order had the most significant association on the DCR per 100 000 after adjusting for multiple socio-demographic, geographic and health-related factors. Additional factors with significant association with increased DCR include rate of uninsured and unemployment. Conclusions: The timing of lockdown order was significantly associated with the spread of COVID-19 at the county level in the United States.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.453-464
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• 2021

The purpose of this study is to analyze the effects of geographic and Feng Shui characteristics of Gwanggyo New City on residential satisfaction and whether residential value has a significant medium effect. It is meaningful to present theoretical, institutional, and practical implications of this research as basic data. According to the results of our analysis of questionnaires completed by residents of Gwanggyo New City, geographic and Feng Shui characteristics showed a significant positive effect on residential value and satisfaction and a significant mediating effect on residential value. Rather than professional Feng Shui factors, general geographical factors have a relatively larger influence on residential value and residential satisfaction, identified as a more significant factor for ordinary residents. Study findings are valuable as basic data in order to suggest institutional and practical implications for policy design to develop cities and improve residential satisfaction.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.47-56
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• 2004

The purpose of this study is to estimate soil loss amount according to the rainfall-runoff erosivity factor frequency and to analyze the hazard zone that has high possibilities of soil erosion in the watershed. RUSLE was used to analyze soil loss quantity. The study area is Gwanchon that is part of Seomjin river basin. To obtain the frequency rainfall-runoff erosivity factor, the daily maximum rainfall data for 39 years was used. The probability rainfall was calculated by using the Normal distribution, Log-normal distribution, Pearson type III distribution, Log-Pearson type III distribution and Extreme-I distribution. Log-Pearson type III was considered to be the most accurate of all, and used to estimate 24 hours probabilistic rainfall, and the rainfall-runoff erosivity factor by frequency was estimated by adapting the Huff distribution ratio. As a result of estimating soil erosion quantity, the average soil quantity shows 12.8 and $68.0ton/ha{\cdot}yr$, respectively from 2 years to 200 years frequency. The distribution of soil loss quantity within a watershed was classified into 4 classes, and the hazard zone that has high possibilities of soil erosion was analyzed on the basis of these 4 classes. The hazard zone represents class IV. The land use area of class IV shows $0.01-5.28km^2$, it ranges 0.02-9.06% of total farming area. Especially, in the case of a frequency of 200 years, the field area occupies 77.1% of total fanning area. Accordingly, it is considered that soil loss can be influenced by land cover and cultivation practices.