• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.129-141
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• 2019

In recent years, fast growing cities in Korea are showing signs of being vulnerable to more disasters as their population and facilities increase and intensify. In particular, fire is one of the most common disasters in Korea's cities, along with traffic accidents. Therefore, in this study, we analyze what type of factors affect the fire that threatens urban people. Fire data were acquired for 10 years, from 2007 to 2017, in Jinju, Korea. Spatial distribution pattern of fire occurrence in Jinju was assessed through the spatial autocorrelation analysis. First, spatial autocorrelation analysis was carried out to grasp the spatial distribution pattern of fire occurrence in Jinju city. In addition, correlation and multiple regression analysis were used to confirm spatial dependency and abnormality among factors. Based on this, OLS (Ordinary Least Square) regression analysis was performed using space weighting considering fire location and spatial location of each facility. As a result, First, LISA (Local Indicator of Spatial Association) analysis of the occurrence of fire in Jinju shows that the most central commercial area are fire department, industrial area, and residential area. Second, the OLS regression model was analyzed by applying spatial weighting, focusing on the most derived factors of multiple regression analysis, by integrating population and social variables and physical variables. As a result, the second kind of neighborhood living facility showed the highest correlation with the fire occurrence, followed by the following in the order of single house, sales facility, first type of neighborhood living facility, and number of households. The results of this study are expected to be useful for analyzing the fire occurrence factors of each facility in urban areas and establishing fire safety measures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.135-145
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• 2022

This paper presented a method to build a predictable smart ammunition logistics system using the 4th industrial technology for ammunition logistics, which is the core functions in the field of defense and logistics. We have analyzed the current level of ammunition logistics with various perspectives such as domestic and overseas logistics policies, technology trends, ammunition logistics characteristics, the smart logistics certification measures by Ministry of Land, Infrastructure and Transport. As a result it is considered that the current ammunition logistics needs needs improvement. To improve this, we presented a direction based on the implications derived after analyzing various ongoing programs such as wired/wireless-based automation, smart ammunition depots, and logistics innovation of the army, navy, and air force that can be applied to the ammunition logistics. In order to implement a data-based smart ammunition logistics management system that can achieve innovation and efficiency of total life cycle while meeting changes in the battlefield environment, we presented 4 objectives such as "automation and modernization of field work", "3D-based storage management & improvement of issuing at war," and "data management for prediction-oriented ammunition management". it is expected that there will be benefits such as improvement of operational continuity, guarantee of ammunition reliability, budget reduction, improvement of inefficiencies such as delay, waiting, and double work, and reduction of accidents.

• Journal of Platform Technology
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• v.11 no.2
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• pp.54-65
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• 2023

Due to the nature of electric vehicles, the batteries used for electric vehicles have a very large rated capacity. If an electric vehicle runs for a long time or an electric vehicle is abandoned due to a traffic accident, the electric vehicle battery becomes a waste battery. Even in vehicles that are being abandoned, the remaining capacity of waste batteries for electric vehicles is sufficient for other purposes. Waste batteries for automobiles are very expensive, so they need to be recycled and reused, but there was a problem that the standards for measuring the performance grade of waste batteries for recycling and reuse were insufficient. As a method for measuring the remaining capacity of waste battery, the most stable and reliable method is to measure the remaining capacity of battery using full charge and discharge. However, the inspection method by the full charging and discharging method varies depending on the capacity of the battery, but it takes more than a day to inspect, and many people are making great efforts to solve this problem. In this paper, an electric vehicle battery residual capacity analysis technique using voltage deviation between cells was studied and analyzed as a method to reduce inspection time for electric vehicle batteries. To this end, a full charging and discharging-based capacity measurement system was constructed, experimental data were collected using a nose or waste battery, and the correlation between the voltage deviation and the remaining capacity of the battery pack was analyzed to verify whether it can be used for battery inspection.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.281-293
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• 2020

Recently, large and small fires have been happening more often in Korea. Fire is one of the most frequent disasters along with traffic accidents in korean cities, and this frequency is closely related to the land use and the type of facilities. Therefore, in this study, the significance of fires was analyzed by considering land use, facility types, human and social factors and using 10 years of fire data in Jinju city. Based on this, OLS (Ordinary Least Square) regression analysis, SLM (Spatial Lag Model) and SEM (Spatial Error Model) using space weights, were compared and analyzed considering the location of the fire and each factor, then a statistical model with high suitability was presented. As a result, LISA analysis of spatial distribution patterns of fires in Jinju city was conducted, and it was proved that the frequency of fires was high in the order as follow, central commercial area, industrial area and residential area. Multiple regression analysis was performed by integrating demographic, social, and physical variables. Therefore, the three models were compared and analyzed by applying spatial weighting to the derived factors. As a result of the significance test, the spatial error model was analyzed to be the most significant. The facilities that have the highest correlation with fire occurrence were second type neighborhood facilities, followed by detached house, first type neighborhood facilities, number of households, and sales facilities. The results of this study are expected to be used as significant data to identify factors and manage fire safety in urban areas. Also, through the analysis of the standard deviation ellipsoid, the distribution characteristics of each facility in the residential area, industrial area, and central commercial area among the use areas were analyzed. In, the second type neighborhood facility with the highest fire risk was concentrated in the center. The results of these studies are expected to be used as useful data for identifying factors and managing fire safety in urban areas.