• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.129-136
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• 2020

PM2.5 which is a very tiny air particulate matter even smaller than PM10 has been issued in the environmental problem. Since PM2.5 can cause eye diseases or respiratory problems and infiltrate even deep blood vessels in the brain, it is important to predict PM2.5. However, it is difficult to predict PM2.5 because there is no clear explanation yet regarding the creation and the movement of PM2.5. Thus, prediction methods which not only predict PM2.5 accurately but also have the interpretability of the result are needed. To predict hourly PM2.5 of Seoul city, we propose a method using random forest with the adjusted bootstrap number from the time series ground data preprocessed on different sources. With this method, the prediction model can be trained uniformly on hourly information and the result has the interpretability. To evaluate the prediction performance, we conducted comparative experiments. As a result, the performance of the proposed method was superior against other models in all labels. Also, the proposed method showed the importance of the variables regarding the creation of PM2.5 and the effect of China.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.251-258
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• 1998

The purpose of this study is to develop the District-level Planning Support System (DPSS) by using GIS. The district-level planning which is related for district-level control of city, needs the various parcel-level information which is composing the urban physical environment. The information has to be stored and analyzed for recognizing the study area, then the district-level planning will be efficiently managed. The use of GIS in the process of district-level planning is restricted for the creation of thematic map. GIS is not used for the analysis of spatial patterns and planning process. This study evaluates the characteristics of current district-level planning and the basic components of urban physical environment. And the database model is built. The topology among components is defined by using the spatial relationship. Then the spatial query machine for district-level planing is developed by using ArcView 3.1, Avenue and Dialog Extension. This spatial query machine is applied for case study. This study shows 1) the possibility of the district-level planning support system for analyzing spatial relationship, 2) the needs of the up-to-date topographic map showing current building's footlines and the complete integration with cadastral maps, it will reduce the uncertainty in the spatial decision making process, 3) the methodology for the construction of spatial decision making rules, 4) the further study for the using of raster, network, image and three dimension data.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.211-224
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• 2002

As system become larger and more complex, it is important to correctly analyze and specify user's requirements. Use case modeling is widely used in Object-Oriented Analysis and Design(OOAD) and Component-Based Development(CBD). It is useful to mitigate the complexity of the requirements analysis. However, use cases are difficult to be structured, to explicitly represent non-functional requirements, and to analyze what is affected by changes of use cases. To alleviate these problems, we propose scenario-based goal-oriented approach for use case modeling. The approach is to apply goal-oriented analysis method to use case model. Since goal-oriented analysis method is not systematic and heuristics is considerably involved, we adopted scenarios as the basis for the goal extraction. The proposed method is applied to City Bus Information Subsystem(CBIS) in Intelligent Transport Systems(ITS) domain. The proposed approach helps software engineer to analyze what is affected by use case's changes and represent non-functional requirements.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.4
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• pp.291-312
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• 2014

The purpose of this national study is to identify the factors affecting the public library use among the Korean adult population. The study constructed a model of three types of factors to explain the frequency of public library visits: an individual's socio-demographic characteristics, input and output measures of the local library, and the community size and library investment of the local government. The data were collected from both a national representative sample of 1,000 adults of 18 years old or above who participated in a web survey and the 2013 National Library Statistics of Korea. It was found that a more frequent public library visit occurred when a person who read more and lived closer to the library, which was newly established in a small to medium-sized scale, who lives in a city with a greater population and with more library staff members serving a fewer patrons. Implications for future public library constructions and for public services were suggested based on the study findings.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.25-35
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• 2013

There is a need to provide appropriate transportation safety services to foreigners residing in Korea. The main purpose of this study is to enhance transportation safety services for foreigners. In order to identify the risk of traffic accidents, analysis of traffic accidents was conducted using a survey of foreigner travel behavior. According to the results of this model, the study suggests directions to achieve improvement of traffic safety services for foreigners who are unfamiliar with the transportation systems. The study results show that the risk of traffic accidents is influenced by two factors: comprehension of transport geography and of traffic laws. Necessity of policy is influenced by two factors: comprehension of transportation system and the risk of traffic accidents. Intention of using policy is influenced by two factors: the risk of traffic accidents and necessity of policy. Effect of policy is affected by the intention of using policy. The results also demonstrate that the traffic safety services for foreigner can be described as endogenous variables which are approximately 88% of the traffic safety education, 85% of the demanded multicultural district, and 75% of the portal traffic information. Compared with existing research, this study provides a systematic methodology to evaluate effects and the order of priority in establishing traffic safety policies for foreigners.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.97-105
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• 2022

This study deals with the credibility of citizens when investing in uncertain project companies, as well as the Social Performance Compensation Project (SIB) and the IT sharing economy. This allows the convergence of the three sectors to address investment inequalities in economic effectiveness and social security. Activates the model of the overall Social Impact Bond (SIB) process that successfully activates the exchange of information. The empirical presentation of the operations and techniques for social IT service finance examines how the innovation ecosystem can be created with social performance and reward projects. The analysis shows that small sharing institutions or citizens can participate directly to create the ability to connect with private investors, identify the possibility of recognizing non-shared barriers to participation, and show the great impact of citizen trust in IT sharing projects in uncertain areas. As a result, for the sake of social sharing and IT cooperation promoted by the City of Seoul, before the project has the ability to design directly, it will be responsible for reliability and safety in the planning of the project. Therefore, non-shared citizens can also participate in the platform that has been effectively constructed and created.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.222-231
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• 2024

Purpose: The purpose of this study is to study how to activate the use of public transportation by identifying the main factors that reduce the use of public transportation due to external influences such as COVID-19 infectious diseases. Method: This study analyzed the connection between the traffic behavior and the characteristics of public transportation use in the metropolitan area changed by COVID-19 with COVID-19 indicators, and analyzed social and environmental factors affecting traffic. Results: It was analyzed that the traffic behavior in the metropolitan area moves from commercial areas to tourist resort areas, the number of COVID-19 deaths affects the use of public transportation, and the lower the deviation between population density, agricultural and forestry areas, and gender ratios due to social and environmental factors, the more significant differences are shown. Conclusion: In the future, it will be able to be activated as a basic analysis model for revitalizing the city's transportation system, regional bases, and various social and economic indicators, such as quarantine of public transportation and social distancing, and can be used as basic data for establishing public transport policy directions according to major influencing factors.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.120-132
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• 2022

Recently, the rapid increase in vacant houses in urban areas has caused various problems such as worsening urban landscape, causing safety accidents, crime accidents, and hygiene problems. According to the Statistics Korea Future Population Estimation results, the growth rate of Korean population and households is expected to continue to decrease, which is likely to lead to an increase in the occurrence of vacant houses. If the problem caused by the occurrence of vacant houses is neglected, it causes not only a physical decline such as a deterioration of the residential environment but also a social and economic decline. In order to solve this problem, it is necessary to grasp the spatial distribution characteristics of vacant houses at the local level considering the existence of regional characteristics and spatial influence. Therefore, in this study, in order to measure global spatial autocorrelation, the analysis was conducted centering on the old downtown area of Busan, where there are many vacant houses through Moran's I and Geographically Weighted Regression(GWR). In addition, the distribution of vacant houses in different spatial units in Eup_Myeon_Dong and Census was analyzed to evaluate the possibility of Modifiable Areal Unit Problem(MAUP), which differ in the results of spatial analysis as the spatial analysis units change. As a result of the analysis, the occurrence of vacant houses by Eup_Myeon_Dong in the old downtown area of Busan had spatial heterogeneity, and the spatial analysis results of vacant houses were different as the spatial analysis units were different. Accordingly, in order to understand the exact distribution characteristics of vacant house occurrence, spatial dimensions using the GWR model should be considered, and it is suggested that consideration of the MAUP is necessary.