• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1420-1426
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• 2008

This paper derives medium access delay of each AC(Access Category) in a stationary station using inter-departure time of IEEE 802.11e WLAN(Wireless LAN). Inter-departure time of IEEE 802.11e WLAN is obtained using saturation throughput of IEEE 802.11e WLAN which was the topic of our prior work. By using a simple queueing model, we evaluate mean queue length and mean delay for each AC on stationary condition. We calculate performance of each AC using this simple model and validate results using simulation.

• The Korean Journal of Emergency Medical Services
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• v.22 no.3
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• pp.47-54
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• 2018

Purpose: The purpose of this study was to present evidence for quality management based on analysis of patient transportation and response intervals among emergency medical squads. Methods: The chi-square test was used to determine whether mental status and patient assessment affected direct medical control and hospital destination. One way analysis of variance was used to compare response intervals depending on mental status and patient assessment using data drawn from 1172 prehospital care reports. Results: There was a statistically significant relationship between mental status and direct medical control (p<.001); there was a statistically significant relationship between patient assessment and hospital destination (p=.011). However, there was no statistically significant relationship between mental status and hospital destination. The interval from arrival at the patient's side to departure from the scene showed a statistically significant difference (p<.001, p<.001), however, it took the longest time (16.8 minutes) in unresponsive patients. It showed a statistically significant difference (p<.001) in the interval from arrival at patient's side to departure from the scene depending on patient assessment; however, it took the longest time (9.6 minutes) in emergency patients. Conclusion: There was call for direct medical control based on patient assessment; however, patient transportation and response intervals were not appropriate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.1033-1041
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• 2017

Path travel time based on departure time (PTTDP) is key information in advanced traveler information systems (ATIS). Despite the necessity, forecasting PTTDP is still one of challenges which should be successfully conquered in the forecasting area of intelligent transportation systems (ITS). To address this problem effectively, a methodology to dynamically predict PTTDP between motorway interchanges is proposed in this paper. The method was developed based on the relationships between traffic demands at motorway tollgates and PTTDPs between TGs in the motorway network. Two different data were used as the input of the model: traffic demand data and path travel time data are collected by toll collection system (TCS) and dedicated short range communication (DSRC), respectively. The proposed model was developed based on k-nearest neighbor, one of data mining techniques, in order for the real applications of motorway information systems. In a feasible test with real-world data, the proposed method performed effectively by means of prediction reliability and computational running time to the level of real application of current ATIS.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.73-81
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• 2009

While various factors in passenger and freight demand analysis affect on destination choice, a key factor, in general. is an attractiveness measure by size variable (e.g., population. employment etc) in destination zone. In order to measure the attractiveness, some empirical studies suggested that disaggregate gravity model are more suitable than aggregate gravity model. This study proposes that truck travelers trip diary data among Korean commodity flow data could be used to estimate the behaviors of incorporating trip departure time, activity duration and attractiveness in destination. As a result, the main findings of size and distance variables coincide with the conventional gravity model having a positive effect of population variable and a negative effect of distance variable. Due to disaggregate gravity modeling, the unique findings of this study reports that small trucks are more likely to choose short distance and early morning, morning peak and afternoon peak departure time choice. On the other hand, large trucks are more likely to choose long distance and night time departure time choice.

• Communications of the Korean Mathematical Society
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• v.14 no.3
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• pp.611-625
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• 1999

We consider ΜΑΡ/G/ 1 finite capacity queue with mul-tiple thresholds on buffer. The arrival of customers follows a Markov-ian arrival process(MAP). The service time of a customer depends on the queue length at service initiation of the customer. By using the embeded Markov chain method and the supplementary variable method, we obtain the queue length distribution ar departure epochs and at arbitrary epochs. This gives the loss probability and the mean waiting time by Little's law. We also give a simple numerical examples to apply the overload control in packetized networks.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.137-146
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• 1993

We consider single server feedback queueing systems with priorities. In the model, there are J stations and job classes. Jobs of class i arrive at station i according to a Poisson process, and have a general service time distribution. We derive the generating functions of the number of jobs at each station just after a busy period and the formula for the mean sojourn time that a specific tagged job spends at station j from its arrival to departure from the system.

• Journal of Korean Society of Transportation
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• v.36 no.3
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• pp.203-215
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• 2018

This study suggests a method to construct large scale dynamic O/D reflecting the characteristic that the passengers' travel patterns change according to the land use patterns of the destination. There are limitations in the existing research about dynamic O/D estimation method, such as the difficulty of collecting data, which can be applied only to a small area, or limiting to a specific transportation network such as highway networks or public transportation networks. In this paper, we propose a method to estimate dynamic O/D without limitation of analysis area based on transportation resources that can be easily collected and used according to the big data era. Clustering analysis was used to calculate the departure time trip distribution ratio based on arrival time and departure time trip distribution function was estimated by each cluster. As a result of the comparison test with the survey data, the estimated distribution function was statistically significant.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.65-77
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• 2013

Recent advanced sensors and communication technologies have been widely applied to advanced safety vehicle (ASV) for reducing traffic accident and injury severity. To apply the advanced safety vehicle technologies, it is important to quantify the safety benefits, which is a fundamental for justifying application. This study proposed a methodology for quantifying the effectiveness of the advanced driver assistant system (ADAS), and applied the methodology to lane departure warning system (LDWS) and automatic emergency braking system (AEBS) which are typical advanced driver assistant systems. When the proposed methodology is applied to 2008-2010 gyeonggi-province crash data, LDWS would reduce about 10~14% of relevant crashes such as head-on, run-off-the road, rollover and fixed-object collisions on the road. In addition, AEBS could potentially prevent about 50% of total rear-end crashes. The outcomes of this study support decision making for developing not only vehicular technology but also relevant safety policies.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.435-444
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• 2005

This paper presents a lane-departure identification (LDI) algorithm for a traveling vehicle on a structured road. The algorithm makes up for the weak points of the former method based on EDF[1] by introducing a Lane Boundary Pixel Extractor (LBPE), the well known Hough transform, and liner regression. As a filter to extract pixels expected to be on lane boundaries, the LBPE plays an important role in enhancing the robustness of LDI. Utilizing the pixels from the LBPE the Hough transform provides the lane-related parameters composed of orientation and distance, which are used in the LDI. The proposed LDI is based on the fact the lane-related parameters of left and right lane boundaries are symmetrical as for as the optical axis of a camera mounted on a vehicle is coincident with the center of lane; as the axis deviates from the center of lane, the symmetrical property is correspondingly lessened. In addition, the LDI exploits a linear regression of the lane-related parameters of a series of successive images. It plays the key role of determining the trend of a vehicle's traveling direction and minimizing the noise effect. Except for the two lane-related parameters, the proposed algorithm does not use other information such as lane width, a curvature, time to lane crossing, and of feet between the center of a lane and the optical axis of a camera. The system performed successfully under various degrees of illumination and on various road types.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.1
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• pp.41-48
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• 2015

Being a cost-efficient solution for alleviating the traffic congestion in airspace, Air Traffic Flow Management (ATFM) has drawn more attentions from not only air traffic controllers but also researchers in the field of Air Traffic Management (ATM). Among other ATFM initiatives, it is believed that Ground Delay Program (GDP) could be effectively applied to reduce the congestion particularly in the relatively small airspace with dense traffic demand. This paper introduces a novel way that suggests flights to be delayed on the departing airports together with amount of the delays (in time) for those flights to be delayed. Adopting a fast-time simulation for predicting airspace delay of each flight for a given flight plan, the method is designed to iteratively and incrementally adjust the departure times in the plan towards reducing total airspace delays. Applying the method to Jeju airport with a hypothetically high demand, the paper demonstrates the airspace delay could be significantly reduced by applying GDP at Gimpo airport where more than 60% of Juju-bound flights departure. Although the simulation model needs to be calibrated and validated for the real-world application, the results clearly shows that the approach can possibly implemented as a tool for preparing the daily plan at the pre-tactical stage defined in the ICAO ATFM manual.