• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.4
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• pp.81-90
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• 2005

Based on the landslide hazard scoring system of Korea Forest Research Institute, a GIS model for predicting landslide hazards was developed. The risk of landslide hazards was analyzed as the function of 7 environmental site factors for the terrain, vegetation, and geological characteristics of the corresponding forest stand sites. Among the environmental factors, slope distance, relative height and shapes of slopes were interpreted using the forestland slope interpretation module developed by Chung et al. (2002). The program consists of three modules for managing spatial data, analyzing landslide hazard and report-writing, A performance test of the model showed that 72% of the total landslides in Youngin-Ansung landslides area took place in the highly vulnerable zones of grade 1 or 2 of the landslide hazard scoring map.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.19-27
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• 2017

This research was aimed to analyze landslide susceptibility and compare the prediction accuracy using ensemble frequency ratio (FR) and logistic regression at the Inje area, Korea. The landslide locations were identified with the before and after aerial photographs of landslide occurrence that were randomly selected for training (70%) and validation (30%). The total twelve landslide-related factors were elevation, slope, aspect, distance to drainage, topographic wetness index, stream power index, soil texture, soil sickness, timber age, timber diameter, timber density, and timber type. The spatial relationship between landslide occurrence and landslide-related factors was analyzed using FR and ensemble model. The produced LSI maps were validated and compared using relative operating characteristics (ROC) curve. The prediction accuracy of produced ensemble LSI map was about 2% higher than FR LSI map. The LSI map produced in this research could be used to establish land use planning and mitigate the damages caused by disaster.

• Proceedings of the KSEG Conference
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• 2001.03a
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• pp.33-44
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• 2001

경기지역에 발생한 약 1,600개의 산사태를 1:50,000 지형도와 1:5,000 지형도를 이용해 정밀 조사하였다. 대부분의 산사태는 토석류(debris flow)로 분류되지만, 산사태 시작부는 전이형(translational) 사태의 성격을 띤다. 강우 이외에 산사태를 발생시키는 지질학적 요인을 찾고자 하루동안 250-300mm의 강우량을 가진 6개 지역을 세부연구지역으로 선정하였다. 이 지역 내 198개의 산사태를 대상으로 현장정밀 조사와 실내실험을 실시한 후, 이를 바탕으로 지구통계학 기법을 이용해 사태발생 원인을 선정하였고, 이에 대한 정량적 가중치를 각각 결정하였다. 분석결과에 의하면 7개 요소가 산사태 발생원인으로 선정되었고, 원인별 정량적 가중치를 부여한 산사태 발생확률을 계산식을 도출했다. 이를 통해 일부지역의 산사태 발생 확률을 구한 후, 실제 발생기록과 비교한 결과 90.74%의 정확성을 나타냈다.

• Proceedings of the Botanical Society of Korea Conference
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• 1989.08a
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• pp.23-32
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• 1989

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.281-292
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• 2014

This study examined the accuracy that produced using various types and combinations of landslide-related factors from landslide susceptibility index maps. A database of landslide-related factors was adopted by the landslide locations that obtained from aerial photographs, and the topographic factors that derived from airborne LiDAR observations and digital maps, and various soil, forest, and land cover. Landslide susceptibility index maps were calculated by logistic regression and frequency ratio from the landslide susceptibility index. The correlation between airborne LiDAR data and digital map was shown strong similarities with one another. Landslide susceptibility index maps indicated the existence of a strong correlation and high prediction accuracy, especially when the frequency ratio and airborne LiDAR were used. Therefore, we concluded that the Airborne LiDAR will contribute to the development of effective landslide prediction methods and damage reduction measures.

• Proceedings of the Technology Innovation Conference
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• 2005.02a
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• pp.179-199
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• 2005

본 연구의 목적은 모바일 뱅킹의 보안성, 유용성, 용이성과 이용에 대한 태도, 이용에 대한 행동의도 및 실제 이용과의 관계를 규명하고, 동일한 분석 방법으로 인터넷 뱅킹과 비교 분석하는 것이다. 이를 위해 인터넷 뱅킹의 이용은 기술수용모형에 의해 설명하고, 기술수용모형과 보안성을 통합한 연구모형을 인터넷 뱅킹과 모바일 뱅킹에 동일하게 적용하였다. 본 연구의 결과는 다음과 같다. 첫째, 모바일 뱅킹과 인터넷 뱅킹의 용이성은 모두 이용에 대한 태도에 영향을 미치지 않는 것으로 나타났다. 반면에 인터넷 뱅킹과 모바일 뱅킹의 유용성은 모두 이용에 대한 태도에 영향을 미치는 것으로 나타났다. 둘째, 모바일 뱅킹의 보안성은 유용성에 영향을 미치는 것으로 나타났지만, 인터넷 뱅킹의 경우에는 보안성이 유용성에 영향을 미치지 않는 것으로 나타났다. 셋째, 모바일 뱅킹의 보안성은 이용에 대한 태도와 부(-)의 관계를 갖지만, 유용성과는 정(+)의 관계를 갖는다. 마지막으로 모바일 뱅킹과 모바일 뱅킹의 평균차이를 분석한 결과를 보면 전반적으로 모바일 뱅킹과 인터넷 뱅킹 간에 유의한 차이를 보이고 있고, 인터넷 뱅킹의 평균이 더 높게 나타나고 있다.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.299-316
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• 2019

The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.

• Journal of Radiation Protection and Research
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• v.31 no.4
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• pp.219-235
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• 2006

Based on the fact that studies on the use of radiations have not been largely conducted reflected on the importance of the use of radiations, the survey was performed to investigate the attitude on the use of radiations for some university students who have a high level of knowledges among average persons in order to extract certain directions for the education program to provide right information. The survey was performed for 517 university students from Oct. 10 to Oct. 15, 2005. The results of this survey can be summarized as follows. 1. Students who have experienced in the radiation related education presented statical differences in the results according to the majoring and monthly incomes. 2. Regarding the survey on the attitude of the use of radiations, the item of 'I agree to build a general hospital or university hospital where I lives in' was presented as the highest points of $3.73{\pm}1.004$, and the lowest point was recorded in the item of 'I agree to build an atomic wastes treatment facility where I live in' as the point of $2.63{\pm}1.091$. 3. The level of attitudes on 'I agree to build an atomic power plant or atomic wastes treatment facility where I live in' presented lower levels than that of the attitude on 'I agree to build an atomic power plant or atomic wastes treatment facility in my country'. 4. The lowest level recorded in the level of attitudes on 'I agree to build an atomic wastes treatment facility where I live in 'presented a significant difference according to the sex and grade.

• Economic and Environmental Geology
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• v.37 no.5
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• pp.521-532
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• 2004

The aim of this study is to evaluate the susceptibility of landslides at Kangneung area, Korea, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified from interpretation of satellite image and field surveys. The topographic, soil, forest, geologic, lineament and land cover data were collected, processed and constructed into a spatial database using GIS and remote sensing data. Using frequency ratio model which is one of the probability model, the relationships between landslides and related factors such as slope, aspect, curvature and type of topography, texture, material, drainage and effective thickness of soil, type, age, diameter and density of wood, lithology, distance from lineament and land cover were calculated as frequency ratios. Then, the frequency ratio were summed to calculate a landslide susceptibility indexes and the landslide susceptibility maps were generated using the indexes. The results of the analysis were verified and cross-validated using actual landslide location data. The verification results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

• Smart Media Journal
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• v.12 no.8
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• pp.60-68
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• 2023

After COVID-19, hotel industry is rapidly experiencing changes in the business environment, and under the influence of the Fourth Industrial Revolution, hotel industry is striving to secure competitive advantages through differentiation, including the use of big data and the IoT in service provision, as well as the introduction of artificial intelligence(AI) robot services. This study analyzed the perceived value of AI robot services and their impact on usage attitudes and behavioral intentions of customers who have used hotels that have introduced AI robot services. The results of the study showed that the value of robot services perceived by customers who have used robot services in hotels is categorized into three dimensions: social, experiential, and functional, and all of them have a positive effect on usage attitudes, with social, functional, and experiential values having a positive effect on usage attitudes in that order. Attitude toward use was also analyzed to have a positive effect on behavioral intention, which is consistent with the value-attitude-behavior model. Therefore, it is necessary for hotels to improve the satisfaction of hotel guests through diversified services of AI robot service.