• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.40 no.3
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• pp.46-56
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• 2022

This study aimed to analyze the locational characteristics of heritage sites in Seoul in order to identify flood susceptibility by type. As for the location factors related to flood susceptibility, elevation, slope, distance to streams, and topographic location were analyzed. Literature review was supplemented for the historical and humanistic environments of heritage sites. The results of the study are as follows. First, heritage sites in Seoul are distributed throughout the city, and are especially highly dense in the Hanyangdoseong fortress. It was also confirmed that heritage sites were concentrated around Jung-gu, Jongno-gu, Jingwan-dong, and Ui-dong in the quantitative spatial analyses. Second, types of heritage sites at the circumstance susceptible to flood damage were related to commerce and distribution, traffic, modern traffic and communication, geological monument, residence, government office, and palace. Third, heritage types with locational characteristics that showed low flood susceptibility were found to be natural scenic spots, telecommunication, ceramics, Buddhism, tombs, and tomb sculptural heritage assets. In a time when risk factors that can damage the value of heritage are gradually increasing due to anthropogenic influences along with changes in the natural environment, this study provides basic data for vulnerability analysis that reflects the unique characteristics of heritage assets. The results can contribute to more comprehensive and comprehensive insights for the management and protection of heritage by including the humanities and social science data together with natural factors in the analysis.

• Journal of the Korean Society of Safety
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• v.33 no.3
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• pp.77-82
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• 2018

This paper aims to analyze the accident based on changing patterns of traffic culture index. For this purpose, this paper particularly focuses on classifying the traffic culture patterns and developing the traffic accidents using panel count data model. The main results are as follows. First, the traffic culture patterns are divided into 'increasing', 'decreasing' and 'other' patterns. The null hypotheses that the number of accident are the same over patterns are rejected. Second, 4 fixed effect negative binomial models which are all statistically significant are developed. Third, the regions with 'increasing' pattern are analyzed to be mostly the counties, and to demand the traffic law enforcement. Fourth, the regions with 'decreasing' pattern are evaluated to be mainly the districts and to require such the traffic culture as turn signal usage. Finally, the regions with 'other' pattern are analyzed to be mostly the cities and to ask for enhancing the level of traffic culture.

• 지역과문화
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• v.7 no.2
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• pp.173-202
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• 2020

This study aims to enhance the family-friendliness of the region by examining the relationship between family relations and the community environment, and objectively comparing the local environment surrounding the family. To this end, we reviewed the areas of socio-cultural and economic sectors that affect the family relationship satisfaction, and in particular, analyzed the trend of changes in regional index by utilizing the Korean Family Happiness Composite Index (KFHCI) developed as a community indicators. This index utilizes community indicators published in the National Statistical Portal's "e-Region indicators," and these variables are related to family relationship satisfaction. Therefore, this study compared the seven areas of the Family Happiness Composite Index (Population Family, Health Culture, Education, Income Consumption, Employment Labor, Housing Transportation, Environment and Social Integration) by region, and examined the trends for 10 years. According to the study, the average score of KFHCI's entire region was rising from 2008 to 2018. Overall, the community environment that affects family relationship satisfaction is also improving. The regions belonging to the upper level were Jeonnam, Gangwon, Chungnam, Jeonbuk, and Gyeongbuk. Areas belonging to the lower level are Seoul, Busan, Daegu, Incheon, and Gwangju. In almost sectors, the lower-level regions did not have sufficient physical infrastructure compared to population density and over-density, and improved little by little, but not enough to reflect the needs of local people and improve the quality of life. In the future, we should develop more regular and complementary indicators to develop customized policies for each region that can improve the quality of family relationships. It will also be necessary to study the impact of each index field when a socioeconomic crisis occurs due to social disasters, and try to change indicators

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.257-262
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• 2021

Accidents caused by black ice occur frequently every winter, and the fatality rate is very high compared to other traffic accidents. Therefore, a systematic method is needed to predict the black ice formation before accidents. In this paper, we proposed a black ice prediction model based on heterogenous and multi-type data. To this end, 12,574,630 cases of 46 types of land, infrastructure, transport public data and meteorological public data were collected. Subsequently, the data cleansing process including missing value detection and normalization was followed by the establishment of approximately 600,000 refined datasets. We analyzed the correlation of 42 factors collected to predict the occurrence of black ice by selecting only 21 factors that have a valid effect on black ice prediction. The prediction model developed through this will eventually be used to derive the route-specific black ice risk index, which will be utilized as a preliminary study for black ice warning alart services.

• Journal of the Korean Society of Safety
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• v.28 no.2
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• pp.78-83
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• 2013

The traffic culture index is used as a major index in evaluating the traffic safety services of local governments and also serve as important data for the planning and implementation of traffic safety services. However, as the traffic culture index gradually became a standard for comparison among local governments, in part, certain cases arose which questioned the grounds for selecting variables for the index and the validity of the index in terms of its influential relationship between evaluation items. This study analyzed the index's influential relationship by utilizing a PLS structural equation model based on the evaluation results of the 2011 traffic culture index. A variable-linking model was created which recognized the relativity taking into account of the indirect effects between latent variables and this model was proven to be a model suitable in explaining the traffic culture index with a 97.8% explanation power. It was found that traffic safety(0.530), driving behavior(0.527), pedestrian behavior(0.187) and vulnerable road users(0.147), in such order, had an effect on the traffic culture index. It was also found that human casualties due to traffic accidents under "traffic safety" and traffic light compliance rate under "driving behavior" had an important effect. The study showed that motor vehicle share in illegal parking in school zones did not have a valid explanation power regarding "vulnerable road users".

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.103-110
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• 2007

Ubiquitous computing is a vogue word, and its service is very popular in Korea. However, present ubiquitous service(u-Service) is thought to be more oriented to the provider's point of view, not the consumer's. To complement this problem, an online survey was performed for internet users, which consists of 24 single choice questions on six fields such as transportation, healthcare, environment/city-management, culture/education, administration, and industry. 2463 people joined the survey, who were grouped according to their age, resident region, level of education, and sex. Each group's demand for specific field of u-Service was examined. General level of demand was higher in case of the elderly and male than the younger and female for overall u-Service.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.13-25
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• 2016

High-speed railway (Korea Train Express) has had a deep impact on the regional economy of Korea. Current high-speed rail research is mostly theoretical, there is a lack of quantitative research using a precise algorithm to study the effect of high-speed railway on the regional economy. This paper analyses the influence of high-speed rail on the regional economy, with a focus on the Daegu area. Quantitative analysis using department store indexes and regional medical records is performed to calculate the economic influence of high-speed rail. The result shows that high-speed railway effects the regional economy though regional consumption growth and medical care trends.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.149-161
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• 2011

The purpose of this study is to present the direction of improving the Korean Government 2.0 services by evaluating the quality of the service and analyzing its effects on user satisfaction. Recently, on the extension of e-government, Government 2.0, which is the government service combined with Web 2.0, has emerged as a new paradigm. However, there are very few studies on the impact of Government 2.0 on general society and industries. Especially, there is little or no practical analysis and evaluation for the quality of Government 2.0 service. Because the service quality is typically used as the leading indicator of user satisfaction, this study applies it to the Government 2.0 for the validation of the existingtheory in a particular subject. The service quality was measured by the tangibles, reliability, responsiveness of revised SERVQUAL, the efficiency and security of the E-S-QUAL. Inconclusion, this study has empirically significant implications for providing a theoretical foundation for measuring the quality of the Government 2.0 service.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.113-121
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• 2015

Remote sensing technology using a multi-spectral satellite imagery can be utilized for the analysis of urban heat island effect in large area. However, weather condition of Korea mostly has a lot of clouds and it makes periodical observation using time-series of satellite images difficult. For this reason, we proposed the analysis of urban heat island effect using time-series of Landsat TM images and ATC model. To analyze vegetation condition and urbanization, NDVI and NDBI were calculated from Landsat images. In addition, land surface temperature was calculated from thermal infrared images to estimate the parameters of ATC model. Furthermore, the parameters of ATC model were compared based on the land cover map created by Korean Ministry of Environment to analyze urban heat island effect relating to the pattern of land use and land cover. As a result of a correlation analysis between calculated spectral indices and parameters of ATC model, MAST had high correlation with NDVI and NDBI (-0.76 and 0.69, respectively) and YAST also had correlation with NDVI and NDBI (-0.53 and 0.42, respectively). By comparing the parameters of ATC model based on land cover map, urban area had higher MAST and YAST than agricultural land and grassland. In particular, residential areas, industrial areas, commercial areas and transportation facilities showed higher MAST than cultural facilities and public facilities. Moreover, residential areas, industrial areas and commercial areas had higher YAST than the other urban areas.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.149-169
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• 2018

Korea is currently accumulating a large amount of data in public institutions based on the public data open policy and the "Government 3.0". Especially, a lot of data is accumulated in the tourism field. However, the academic discussions utilizing the tourism data are still limited. Moreover, the openness of the data of restaurants, hotels, and online tourism information, and how to use SNS Big Data in tourism are still limited. Therefore, utilization through tourism big data analysis is still low. In this paper, we tried to analyze influencing factors on foreign tourists' satisfaction in Korea through numerical data using data mining technique and R programming technique. In this study, we tried to find ways to revitalize the tourism industry by analyzing about 36,000 big data of the "Survey on the actual situation of foreign tourists from 2013 to 2015" surveyed by the Korea Culture & Tourism Research Institute. To do this, we analyzed the factors that have high influence on the 'Satisfaction', 'Revisit intention', and 'Recommendation' variables of foreign tourists. Furthermore, we analyzed the practical influences of the variables that are mentioned above. As a procedure of this study, we first integrated survey data of foreign tourists conducted by Korea Culture & Tourism Research Institute, which is stored in the tourist information system from 2013 to 2015, and eliminate unnecessary variables that are inconsistent with the research purpose among the integrated data. Some variables were modified to improve the accuracy of the analysis. And we analyzed the factors affecting the dependent variables by using data-mining methods: decision tree(C5.0, CART, CHAID, QUEST), artificial neural network, and logistic regression analysis of SPSS IBM Modeler 16.0. The seven variables that have the greatest effect on each dependent variable were derived. As a result of data analysis, it was found that seven major variables influencing 'overall satisfaction' were sightseeing spot attraction, food satisfaction, accommodation satisfaction, traffic satisfaction, guide service satisfaction, number of visiting places, and country. Variables that had a great influence appeared food satisfaction and sightseeing spot attraction. The seven variables that had the greatest influence on 'revisit intention' were the country, travel motivation, activity, food satisfaction, best activity, guide service satisfaction and sightseeing spot attraction. The most influential variables were food satisfaction and travel motivation for Korean style. Lastly, the seven variables that have the greatest influence on the 'recommendation intention' were the country, sightseeing spot attraction, number of visiting places, food satisfaction, activity, tour guide service satisfaction and cost. And then the variables that had the greatest influence were the country, sightseeing spot attraction, and food satisfaction. In addition, in order to grasp the influence of each independent variables more deeply, we used R programming to identify the influence of independent variables. As a result, it was found that the food satisfaction and sightseeing spot attraction were higher than other variables in overall satisfaction and had a greater effect than other influential variables. Revisit intention had a higher ${\beta}$ value in the travel motive as the purpose of Korean Wave than other variables. It will be necessary to have a policy that will lead to a substantial revisit of tourists by enhancing tourist attractions for the purpose of Korean Wave. Lastly, the recommendation had the same result of satisfaction as the sightseeing spot attraction and food satisfaction have higher ${\beta}$ value than other variables. From this analysis, we found that 'food satisfaction' and 'sightseeing spot attraction' variables were the common factors to influence three dependent variables that are mentioned above('Overall satisfaction', 'Revisit intention' and 'Recommendation'), and that those factors affected the satisfaction of travel in Korea significantly. The purpose of this study is to examine how to activate foreign tourists in Korea through big data analysis. It is expected to be used as basic data for analyzing tourism data and establishing effective tourism policy. It is expected to be used as a material to establish an activation plan that can contribute to tourism development in Korea in the future.