• 한국ITS학회:학술대회논문집
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• 2005.11a
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• pp.25-28
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• 2005

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.191-201
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• 2008

It has been employed TRANSYT-7F and NETSIM to evaluate the validity and effectiveness of improvement on TSM(Transportation Systems Management). But T7F is hard to describe platoon compression and dispersion in actually, and NETSIM takes a long time for network coding, calibration and have difficulty in setting up saturation flow. While Shockwave Model have advantage which can describe platoon compression and dispersion in actually and shorten hours, convenience of application. But Shockwave Model apply unrealistic traffic flow relation ship(U-K curve) and simplify platoon because of difficulty in calculating shockwave's position and cross. For solving limitation of existing shockwave models, It develop new model with 2-regime linear model, New platoon model, Extended shockwave, etc. For verifying the validity of the proposed model, it was compared with delay of T7F and NETSIM by offset variation. In conclusion, it is thought that proposed model have outstanding performance to simulate traffic phenomenon.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.1 s.35
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• pp.57-63
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• 2006

The purpose of this study is to correct data on 3 intersection ranging from Kwangchun INT. to Nongsung INT. by the means of VTR recording and site survey and to measure the responsiveness of performance index by diversifying the platoon dispersion factor in signal progression simulation. The results are as follows : 1. The value of platoon dispersion factor was 0.28-0.33. The value in up stream is lower than that of in down stream even on the same intersection. 2. The platoon index showed big changes, though performance index didn't according to platoon dispersion factor. Therefore the value of platoon dispersion factor which is inner variable in T7F can be fixed for 0.34. 3. There was only little divergence in performance index changes according to platoon dispersion factor in designing the progression or T7F model.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.185-196
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• 2007

The aim of this research is to develop a signal control algorithm using internal metering to minimize total delay that vehicles go through, in case a network is oversaturated. To calculate total delay on the network, the authors first detect vehicles' arrivals and departures in the network through the detecting system, and chase the vehicles' flow in the links with a platoon dispersion model. Following these, the authors calculate the queue length in all the inks of the network through the chase of vehicles, deduce the stopped time delay, and finally convert the stopped time delay to the approach delay with a time-space diagram. Based on this calculated delay, an algorithm that calculates the level of the internal metering necessary to minimize the deduced approach delay is suggested. To verify effectiveness of this suggested algorithm, the authors also conduct simulation with the micro-simulator VISSIM. The result of the simulation shows that the average delay per vehicle is 82.3 sec/veh and this delay is lower than COSMOS (89.9sec/veh) and TOD (99.1sec/veh). It is concluded that this new signal control algorithm suggested in this paper is more effective in controlling an oversaturated network.

• Korean Journal of Poultry Science
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• v.50 no.1
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• pp.41-50
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• 2023

Over the last decade, avian influenza (AI) has been considered an emerging disease that would become the next pandemic, particularly in countries like South Korea, with continuous animal outbreaks. In this situation, risk assessment is highly needed to prevent and prepare for human infection with AI. Thus, we developed the risk assessment matrix for a high-risk area of human infection with AI in South Korea based on the notion that risk is the multiplication of hazards with vulnerability. This matrix consisted of highly pathogenic avian influenza (HPAI) in poultry farms and the number of poultry-associated production facilities assumed as hazards of avian influenza and vulnerability, respectively. The average number of HPAI in poultry farms at the 229-municipal level as the hazard axis of the matrix was predicted using a negative binomial regression with nationwide outbreaks data from 2003 to 2018. The two components of the matrix were classified into five groups using the K-means clustering algorithm and multiplied, consequently producing the area-specific risk level of human infection. As a result, Naju-si, Jeongeup-si, and Namwon-si were categorized as high-risk areas for human infection with AI. These findings would contribute to designing the policies for human infection to minimize socio-economic damages.