• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.780-783
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• 2009

The application of MOST150 technology has been required to satisfy the demand for the automotive infotainment system and the higher bandwidth requirements caused by the increase of the multimedia processing capacity. The Ethernet technology applied gateway was implemented for an efficient transmission of multimedia, a vehicle diagnosis, an external communication, a data processing between the MOST150 and the CAN communication method applied to many existing vehicles. The new algorithm and application were suggested in order to efficiently perform the data processing between other types of communication systems. The existing MOST150 frame is mainly composed of the Control Channel, the Legacy Packet Channel(async) and the Synchronous /Isochronous Channels and performs the data processing through these sequential channels. With the sense of this process, this study suggested the new algorithm that the Mapping method of the IETF's QoS Management was applied to the MOST150 technology for the efficient QoS.

• Structural Monitoring and Maintenance
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• v.2 no.3
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• pp.283-300
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• 2015

Visual condition inspections remain paramount to assessing the current deterioration status of a bridge and assigning remediation or maintenance tasks so as to ensure the ongoing serviceability of the structure. However, in recent years, there has been an increasing backlog of maintenance activities. Existing research reveals that this is attributable to the labour-intensive, subjective and disruptive nature of the current bridge inspection method. Current processes ultimately require lane closures, traffic guidance schemes and inspection equipment. This not only increases the whole-of-life costs of the bridge, but also increases the risk to the travelling public as issues affecting the structural integrity may go unaddressed. As a tool for bridge condition inspections, Unmanned Aerial Vehicles (UAVs) or, drones, offer considerable potential, allowing a bridge to be visually assessed without the need for inspectors to walk across the deck or utilise under-bridge inspection units. With current inspection processes placing additional strain on the existing bridge maintenance resources, the technology has the potential to significantly reduce the overall inspection costs and disruption caused to the travelling public. In addition to this, the use of automated aerial image capture enables engineers to better understand a situation through the 3D spatial context offered by UAV systems. However, the use of UAV for bridge inspection involves a number of critical issues to be resolved, including stability and accuracy of control, and safety to people. SLAM (Simultaneous Localisation and Mapping) is a technique that could be used by a UAV to build a map of the bridge underneath, while simultaneously determining its location on the constructed map. While there are considerable economic and risk-related benefits created through introducing entirely new ways of inspecting bridges and visualising information, there also remain hindrances to the wider deployment of UAVs. This study is to provide a context for use of UAVs for conducting visual bridge inspections, in addition to addressing the obstacles that are required to be overcome in order for the technology to be integrated into current practice.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.314-324
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• 2021

Competition between ports around the world is intensifying to attract transshipment cargo. However, recently, there have been concerns about the departure of transshipment cargo volume at Busan Port, such as the lifting of the cabotage policy in China's shipping sector and the implementation of a safe fare system. In terms of operation, terminal congestion and vehicle waiting time are seriously occurring due to imbalance in the transshipment volume of each terminal and vehicles concentrated in a specific time period. In this paper, we propose a method of inter-terminal transportation (ITT) using buffer space to solve the problem caused by inefficient ITT systems and presented a mixed integer programming (MIP) for the problem. The effect of using the buffer space was analyzed for various work volumes and capacity fluctuation ranges by applying the terminal congestion pattern and ITT vehicle in/out pattern based on the Busan New Port data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.68-83
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• 2019

The number of pedestrian traffic accident fatalities is three times the number of car accidents in South Korea. Serious accidents are caused especially at intersections when the vehicle turns to their right. Various pedestrian collision warning services have been developed, but they are insufficient to prevent dangerous pedestrians. In this study, P2CWS is developed to warn approaching vehicles based on the pedestrians' characteristics. In order to evaluate the performance of the service, actual pedestrian data were collected at the intersection of Daejeon, and comparative analysis was carried out according to pedestrian characteristics. As a result, the performance analysis showed a higher accordance when the characteristics of the pedestrian is considered. Accordingly, we can conclude that identifying pedestrian characteristics in predicting the pedestrian crossing is important.

• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.596-603
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• 2018

The traffic congestion is frequently occurring due to increasing demand for vehicles and development of subcenter in roads of domestic-downtown. The design of a Great depth underground double-deck tunnel planned for construction as a solution however it's mainly for a compact-car. Its low height and small section cause causalities when fire occurs. From this study, the delay system for fire smoke diffusion is developed to minimize the occurrence of casualties when fire occurs in the Great depth underground double-deck tunnel and the CFD(Computational Fluid Dynamics) is used to find the optimal installation interval and the blockage ratio to maximize the system effects. The study analyzed the shorter the installation interval of the system, the higher the smoke delay effect but the efficiency-change tends to be slight above a certain distance and the larger the blockage ratio, the higher the effect but the efficiency-difference is slight according to installation interval.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.213-225
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• 2018

For constructing three-dimensional (3D) spatial information occlusion region problem arises in the process of taking the texture of the building. In order to solve this problem, it is necessary to investigate the automation method to automatically recognize the occlusion region, issue it, and automatically complement the texture. In fact there are occasions when it is possible to generate a very large number of structures and occlusion, so alternatives to overcome are being considered. In this study, we attempt to apply an approach to automatically create an occlusion region based on learning by patterning the blocked region using the recently emerging deep learning algorithm. Experiment to see the performance automatic detection of people, banners, vehicles, and traffic lights that cause occlusion in building walls using two advanced algorithms of Convolutional Neural Network (CNN) technique, Faster Region-based Convolutional Neural Network (R-CNN) and Mask R-CNN. And the results of the automatic detection by learning the banners in the pre-learned model of the Mask R-CNN method were found to be excellent.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1131-1142
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• 2018

The autonomous vehicles are being developed and operated widely because of the advantages of reducing the traffic accident and saving time and cost for driving. The vehicle localization is an essential component for autonomous vehicle operation. In this paper, localization algorithm based on sensor fusion is developed for cost-effective localization using in-vehicle sensors, GNSS, an image sensor and reference images that made in advance. Information of the reference images can overcome the limitation of the low positioning accuracy that occurs when only the sensor information is used. And it also can acquire estimated result of stable position even if the car is located in the satellite signal blockage area. The particle filter is used for sensor fusion that can reflect various probability density distributions of individual sensors. For evaluating the performance of the algorithm, a data acquisition system was built and the driving data and the reference image data were acquired. Finally, we can verify that the vehicle positioning can be performed with an accuracy of about 0.7 m when the route image and the reference image information are integrated with the route path having a relatively large error by the satellite sensor.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.4
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• pp.523-530
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• 2019

Pavement distress and traffic accidents are caused by pot-hole. In addition, direct and indirect damages of road users are increasing, such as loss of life due to personal injury and damage to vehicles. Generally, the asphalt concrete pavements are continuously aging from the production process to the terminal performance period. Aging causes stripping due to cracks and moisture penetration and weakening the pavement structure to induce pot-hole. In this study, adhesion performance and moisture sensitivity were evaluated according to aging degree in order to investigate the effect of aging on asphalt pavement. As a result of the study, the viscosity of the asphalt binder was increased with aging and the bond strength of the aged was increased 2~3 times than that of the unaged. The results of accelerated aging test showed an increases in indirect tensile strength and the increase in the TSR (Tensile Strength Ratio) by 4.2~8.9 %. As a result, it is noted that the anti-stripping and adhesion performances of the aged asphalt concrete are improved compared to the unaged one under the aging conditions of asphalt binder coated on aggregates.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.83-95
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• 2019

Recently, a variety of IoT data is collected by attaching geosensors to many vehicles that are on the road. IoT data basically has time and space information and is composed of various data such as temperature, humidity, fine dust, Co2, etc. Although a certain sensor data can be retrieved using time, latitude and longitude, which are keys to the IoT data, advanced search engines for IoT data to handle high-level user queries are still limited. There is also a problem with searching large amounts of IoT data without generating indexes, which wastes a great deal of time through sequential scans. In this paper, we propose a unified spatial index model that handles both grid and trajectory queries using a cell-based space-filling curve method. also it presents a visualization method that helps user grasp intuitively. The Trajectory query is to aggregate the traffic of the trajectory cells passed by taxi on the road searched by the user. The grid query is to find the cells on the road searched by the user and to aggregate the fine dust. Based on the generated spatial index, the user interface quickly summarizes the trajectory and grid queries for specific road and all roads, and proposes a Web-based prototype system that can be analyzed intuitively through road and heat map visualization.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.391-398
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• 2019

In general, truck-involved crashes increase severity in terms of both injury level and crash impact level. Recently, although the frequency and fatality of truck-involved crashes in Korea are rising, their associative studies are very limited. Therefore, the objective of this study is to identify critical factors influencing on injury severity of truck-involved crashes on Korean freeway system. To carry out this objective, this study uses an ordered probit model (OPM) based on a 6-year crash dataset from 2012 to 2017. From the analysis, eight variables were found to have a great effect on injury severity: older driver, crash speed, rear-end collision, number of vehicles involved, drowsy driving, nighttime (0:00 to 6:00) driving, overturn or rollover, and vehicle's fire after crash. However, injury severity was less severe in crashes under snowy condition and crashes to traffic facilities (i.e., crash alone).