• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.92-105
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• 2016

This study aims to establish a simulation method for CCTV (Closed Circuit Television) sight area. The simulation incorporates variables for computing CCTV sight area including CCTV specifications and installation. Currently CCTV is used for traffic, crime prevention and fire prevention by local governments. However, new locations are selected by administrator decision rather than analysis of the optimal location. In order to determine optimum location, a method to CCTV compute range is needed, which incorporates specifications according to CCTV purpose. For this purpose, limitations of previous research methods must be recognized and the simulation method must supplement these limitations. Here in this study, we derived CCTV sight area variables for realistic analysis to complement the limitations of previous studies. A total of eight elements were derived from image device sensors and installation: wide angle, height, angle, setting height, setting angle, and others. This research implemented a 3D simulation technique that can be applied to the derived factors and automate them using ArcObject and Visual C#. This simulation method can calculate sight range in accordance with CCTV specifications. Furthermore, when installing additional CCTVs, it can derive optimal allocation position. The results of this study will provide rational choices for specification selection and CCTV location by interagency collaborative projects.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.8
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• pp.572-577
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• 2011

The unit load has simply been used to estimate total pollutant loading from non-point sources, however, it does not count on the variable pollutant loading according to land use characteristics and rainfall intensity. Since pollutant emission from the watershed is strongly dependent on the rainfall intensity, it is necessary to find out the relationship between pollutant loading and rainfall intensity. The objective of this study is to develop simple and easy method to compute non-point source pollution loads with consideration of rainfall intensity. Two non-point source removal facility at Gyeongan-dong (Gwangju-si) and Mohyeon-myeon (Yongin-si), Gyeonggi-do was selected to monitor total rainfall, rainfall intensity, runoff characteristics and water quality from June to November, 2010. Most of Event Mean Concentrations (EMC) of measured water quality data were higher in Gyeongan which has urban land use than in Mohyeon which has rural land use. For the case of TP (Total Phosphorus), Mohyeon has higher values by the influence of larger chemical uses such as fertilizer. The relationship between non-point source pollution load and rainfall intensity is perfectly well explained by cubic regression with 0.33~0.81 coefficients of determination($R^2$). It is expected that the pollution loading function based on the long-term monitoring would be very useful with good accuracy in computing non-point source pollution load, where a rainfall intensity is highly variable.

• Geophysics and Geophysical Exploration
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• v.2 no.2
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• pp.86-95
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• 1999

This paper presents an efficient three-dimensional (3-D) modeling algorithm using the extended approximation to an electric field integral equation. Numerical evaluations of Green's tensor integral are performed in the spatial wavenumber domain. This approach makes it possible to reduce computing time, to handle smoothly varying conductivity model and to remove singularity problems encountered in the integration of Green's tensor at a source point. The responses obtained by 3-D modeling algorithm developed in this study are compared with those by the full integral equation for a thin-sheet EM scattering. The extensive analyses on the performance of modeling algorithm are made with the conductivity contrasts and source frequencies. These results show that the modeling algorithm are accurate up to the conductivity contrast of 1:16 and the frequency range of 100 Hz-100 kHz. The extended Born approximation, however, may produce inaccurate results for some source and model configurations in which the electric field is discontinuous across the conductivity boundary. We performed the modeling of a composite model of which conductivity varies continuously and this shows the modeling algorithm developed in this study is efficient for 3-D EM modeling. For a cross-hole source-receiver configuration a composite model of which conductivity varies continuously can be successfully simulated using this algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.2
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• pp.52-62
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• 2013

Design Hourly Factor(DHF) is defined as the ratio of design hourly volume(DHV) to Average Annual Daily Traffic(AADT). Generally DHV used the 30th rank hourly volume. But this case DHV is affected by holiday volumes so the road is at risk for overdesigning. Computing K factor is available for counting 8,760 hour traffic volume, but it is impossible except permanent traffic counts. This study applied three method to make DHF, using 30th rank hourly volume to make DHF(method 1), using peak hour volume to make DHF(method 2). Another way to make DHF, rank hourly volumes ordered descending connect a curve smoothly to find the point which changes drastic(method 3). That point is design hour, thus design hourly factor is able to be computed. In addition road classified 3 type for national highway using factor analysis and cluster analysis, so we can analyze the characteristic of DHF by road type. DHF which was used method 1 is the largest at any other method. There is no difference in DHF by road type at method 2. This result shows for this reason because peak hour is hard to describe the characteristic of hourly volume change. DHF which was used method 3 is similar to HCM except recreation road but 118th rank hourly volume is appropriate.

• Journal of Korea Water Resources Association
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• v.30 no.1
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• pp.83-93
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• 1997

The purpose of the study is to analyze the sensitivity of the parameters that affect the runoff and water quality in the studied drainage basins. SWMM model is applied to the four drainage basins located at Namgazwa and Sanbon in Seoul and Gray Haven and Kings Creek in the USA. first of all, the optimum values of the parameters which have least simulation error to the observed data, are detected by iteration procedure. These are used as the standard values which are compared against the procedure. These are used as the standard values which are compared against the varied parameter values. In order to catch the effectiveness of the parameters to the computing result, the parameters are changed step by setp, and the results are compared to the standard results in flowerate and quality of the sewer. The study indicates that the discharge is greatly affected by the types of runoff surface, i.e., impervious area remarkably affects the peak flow and runoff volume while the surface storage affects the runoff volume at mild sloped basins. In addition, the major parameters affecting the pollution concentrations and loadings are the contaminant accumulation coefficient per unit area per time and the continuous dry weather days. Furthermore, the factors that affect the water quality during the initial rainfall period are the rainfall intensity, transport capacity coefficient and its power coefficient. Consequently, in order to simulate the runoff-water quality, it is needed to evaluate previous data in the research performed for the studied basins. To accurately estimated from the tributary areas and the rational computation methods of the pollutants calculation should be introduced.

• Journal of Korea Water Resources Association
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• v.38 no.3 s.152
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• pp.213-222
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• 2005

This study is a sensitivity analysis of the parameters which affect the simulation results under various design rainfall conditions, using the SWMM model, for three selected basins in urban areas. The sensitivity of the peak flow rate is defined by $S_Q$ (=1.0 - (min. ratio of peak flow rate/max. ratio of peak flow rate)), and the rainfall conditions are classified in terms of design rainfall frequency, duration, and distribution. The simulation results show that in most conditions the parameters - the impermeable area ratio, the sewer slope, and the initial infiltration capacity - have more significant effects on the results than other parameters. As the design rainfall frequency increases, the sensitivity of the sewer slope and sewer roughness increases, while the parameters related with the surface runoff decrease. When the rainfall duration increases, the sensitivities of most parameters of surface runoff and sewer flow decrease. Also, at the 1st quarterly Huff rainfall distribution condition, the impermeable area ratio has high sensitivity, but at the 4th quarterly condition the parameters related with sewer flow show higher sensitivities. These tendencies can be explained by considering the procedure for computing the effective rainfall and kinematic wave on the surface and sewer flow.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.55-63
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• 2019

Recently, the use of real-world image data has been increasing to express realistic virtual environments in various application fields such as education, manufacturing, and construction. In particular, with increasing interest in digital twins like smart cities, realistic 3D urban models are being built using real-world images, such as aerial images. However, the captured aerial image includes shadows from the sun, and the 3D city model including the shadows has a problem of distorting and expressing information to the user. Many studies have been conducted to remove the shadow, but it is recognized as a challenging problem that is still difficult to solve. In this paper, we construct a virtual environment dataset including the height map of buildings using 3D spatial information provided by VWorld, and We propose a new shadow detection method using height map and deep learning. According to the experimental results, We can observed that the shadow detection error rate is reduced when using the height map.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.67-78
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• 2017

Traffic congestion cost is increasing annually. Specifically congestion caused by the CDB traffic contains more than a half of the total congestion cost. Recent advancement in the field of Big Data, AI paved the way to industry revolution 4.0. And, these new technologies creates tremendous changes in the traffic information dissemination. Eventually, accurate and timely traffic information will give a positive impact on decreasing traffic congestion cost. This study, therefore, focused on developing both recurrent and non-recurrent congestion prediction models on urban roads by adopting Recurrent Neural Network(RNN), a tribe in machine learning. Two hidden layers with scaled conjugate gradient backpropagation algorithm were selected, and tested. Result of the analysis driven the authors to 25 meaningful links out of 33 total links that have appropriate mean square errors. Authors concluded that RNN model is a feasible model to predict congestion.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.109-118
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• 2019

The purpose of this study is to deliver both market-practical and civil-centric political implication for sharing economy by investigating the nature of consumer-adoption for car-sharing service. With the global interest and market proliferation of the sharing economy, various service models for sharing idle resources have also been released in Korea. Particularly, in case of car sharing service, public - private partnership projects are spreading rapidly in various local governments including Seoul, along with the growing demand for alternative transportation system centering on the urban area. This study conducted an empirical study on the process of accepting the car sharing service by analyzing the data collected from users of the car sharing service "Sharing Car(Nanum Car)" of Seoul Metropolitan Government. A survey was conducted on 281 users in their twenties who are in the age of main use among the experienced users of the "Sharing Car(NaNum)" residing in Seoul. The result of analysis on the relationship between these users' perceived value and intention to use the vehicle sharing service would provide implications for establishing consumer(citizen)-centeric policies as well as market implications.

• Journal of The Korea Institute of Healthcare Architecture
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• v.28 no.4
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• pp.41-50
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• 2022

Purpose: This study aims to suggest an analysis model finding the relationship between building scale characteristics of Public-use facilities and infectious disease outbreaks around senior leisure welfare facilities and the features and their scopes where quarantine resources are to be concentrated. Methods: Reviewing previous studies found the user characteristics of senior leisure welfare facilities and scale characteristics of urban architectures. The data preprocessing was performed after collecting building data and infectious disease outbreak data in the analysis area. This study derived data for attributes of building size and frequency of infectious disease outbreaks in Public-use facilities around senior leisure welfare facilities. A computing algorithm was implemented to analyze the correlation between the building size characteristics and the infectious disease outbreak frequency as per the change of the spatial scope. Results: The results of this study are as follows: First, the suggested model was to analyze the correlation between the infection frequency and the number of senior leisure welfare facilities, the number of Public-use facilities, building area, total floor area, site area, height, building-to-land ratio, and floor area ratio varied as per the change of spatial scope. Second, correlation results varied between the infection frequency and the number of senior leisure welfare facilities, the number of Public-use facilities, building area, total floor area, site area, height, building-to-land ratio, and floor area ratio. Third, a negative correlation appeared in the analysis between the number of senior leisure welfare facilities and infection frequency. And positive correlations appeared noticeably in the study between the number of Public-use facilities, building area, total floor area, height, building-to-land ratio, and floor area ratio. Implications: This study can be used as primary data on the utilization of limited quarantine resources by analyzing the relationship between the Public-use facilities around the senior leisure welfare facilities and the spread of infectious diseases. In addition, it suggests that infectious disease prevention measures are necessary considering the spatial scope of the analysis area and the size of buildings.