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.17
no.6
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pp.54-66
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2018
In this study, vehicle speeds at acceleration and deceleration lanes of rest areas for drowsy drivers were investigated to analyze effects of acceleration and deceleration lane lengths, grades and curve radius. In addition, we used VISSM to analyze proper lengths of rest area's acceleration and deceleration lanes. Several VISSIM scenarios with different lengths of acceleration and deceleration lane were constructed. Through VISSIM simulation, we collected individual vehicle speed data to analyze speed changes by different lengths of acceleration and deceleration lanes. As a result of the vehicle speed change investigation, grades and curve radii of the rest area affected the speed, most of all lengths of acceleration and deceleration lane showed a great effect on the vehicle speed. In the case of short lengths of acceleration and deceleration lane, speed variation among vehicles was significant. If the deceleration lane length is short, the vehicle enters a state in which the speed is not sufficiently reduced, and if the acceleration lane length is short, the vehicle enters a state in which the speed is not sufficiently accelerated showing high risks of conflicts and accidents. It is recommended that 245m length of deceleration lane and 370m length of acceleration lane should be installed at least to secure safety and manage conflicts relevantly.
Journal of the Korean Society of Marine Environment & Safety
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v.25
no.4
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pp.405-412
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2019
SOLAS requires that ECDIS be installed on ships of more than 500 gross tonnage engaged in international navigation until the first inspection arriving after July 1, 2018. Several accidents related to the use of ECDIS have occurred with its installation as a new major navigation instrument. The 12 incident reports issued by MAIB, BSU, BEAmer, DMAIB, and DSB were analyzed, and the cause of accident was determined to be related to the operation of the navigator and the ECDIS system. The text was analyzed using the R-program to quantitatively analyze words related to the cause of the accident. We used text mining techniques such as Wordcloud, Wordnetwork and Wordweight to represent the importance of words according to their frequency of derivation. Wordcloud uses the N-gram model as a way of expressing the frequency of used words in cloud form. As a result of the uni-gram analysis of the N-gram model, ECDIS words were obtained the most, and the bi-gram analysis results showed that the word "Safety Contour" was used most frequently. Based on the bi-gram analysis, the causative words are classified into the officer and the ECDIS system, and the related words are represented by Wordnetwork. Finally, the related words with the of icer and the ECDIS system were composed of word corpus, and Wordweight was applied to analyze the change in corpus frequency by year. As a result of analyzing the tendency of corpus variation with the trend line graph, more recently, the corpus of the officer has decreased, and conversely, the corpus of the ECDIS system is gradually increasing.
Journal of the Korean Society of Marine Environment & Safety
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v.23
no.7
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pp.801-809
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2017
The purpose of this study is to contribute to the prevention of ship collisions by investigating real ship collision cases and statistically analyzing causes of human error for captains and Officers of the Watch (OOW). This study encompassed a total of 109 cases for 218 vessels, which were suitable for the analysis of ship accidents between merchant ships or merchant ships and fishing boats over the 7 years from 2010 to 2016. Data was collected while classifying vessels according to type, Give-way and Stand-on vessels, along with the cause of human error. Factors causing human error were identified after focusing on the cause of each collision given by the OOW ; frequency and cross tabulation analyses were conducted using SPSS, a statistical analysis tool. As a result, the main causes of human error by an OOW in a ship collision situation were that lookout was neglected in a Give-way vessel including radar surveillance (74.3 %) or continuous observation of an opponent vessel was carried out (17.4 %). A major factor for Stand-on vessels was failure to act to avoid collision with another vessel (63.3 %). In particular, most neglect for lookout type merchant ships occurred after the opponent ship was first observed, and a common cause of lookout neglect and neglect of duty was a focus on other tasks during navigational watch time.
Owing to the increase of FTA, food trade, and versatile preferences of consumers, food import has increased at tremendous rate every year. While the inspection check of imported food accounts for about 20% of the total food import, the budget and manpower necessary for the government's import inspection control is reaching its limit. The sudden import food accidents can cause enormous social and economic losses. Therefore, predictive system to forecast the compliance of food import with its preemptive measures will greatly improve the efficiency and effectiveness of import safety control management. There has already been a huge data accumulated from the past. The processed foods account for 75% of the total food import in the import food sector. The analysis of big data and the application of analytical techniques are also used to extract meaningful information from a large amount of data. Unfortunately, not many studies have been done regarding analyzing the import food and its implication with understanding the big data of food import. In this context, this study applied a variety of classification algorithms in the field of machine learning and suggested a data preprocessing method through the generation of new derivative variables to improve the accuracy of the model. In addition, the present study compared the performance of the predictive classification algorithms with the general base classifier. The Gaussian Naïve Bayes prediction model among various base classifiers showed the best performance to detect and predict the nonconformity of imported food. In the future, it is expected that the application of the abnormality detection model using the Gaussian Naïve Bayes. The predictive model will reduce the burdens of the inspection of import food and increase the non-conformity rate, which will have a great effect on the efficiency of the food import safety control and the speed of import customs clearance.
The purpose of this study was to examine the effects of job characteristics and health on accident experience by analyzing the data of transportation workers according to age. The analysis used data from 'the fourth Korean Working Conditions Survey(KWCS)'. A total of 1,997 transport workers data were finally analyzed, and correlation analysis, crossover analysis and logistic regression analysis were performed. It was confirmed that there was no correlation between the age of the transport workers and the accident experience. In the relationship between the characteristics of transportation workers and the experience of the accident, it was found that, in the case of older workers, there was a significant effect in the order of 'at mistake someone else hurt', 'musculoskeletal problem', 'cardiovascular problem' and 'repetitive movements of hands or arms', the model explaining power was 56.9%(p <.01). In the case of non-older workers, it was found that 'depression and anxiety disorder', 'relationship between job and safety', 'at mistake someone else hurt' and 'labor union', the model explaining power was 21.8%(p <.01). Therefore, in order to promote prevent accidents of transportation workers in future, it is necessary to consider various variables such as health and job characteristics besides age.
Park, Seonghyeon;Sung, Deokyong;Lee, Changho;Jung, Hyuksang;Youg, Seungkyong
Journal of The Korean Society For Urban Railway
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v.6
no.4
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pp.249-257
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2018
The number of deaths for railway traffic accidents is mainly caused by working close to the track, or when unauthorized passage pass through the track. The safety fences are being used to ensure safety for workers close to the track, and to improve the efficiency of the work, without interfering with the passage of trains. However, a safety fence for railway tracks needs to be examined to see if it will interfere with the passage of trains. The purpose of this study is to analyze the safe distance between train and safety fence developed in Korea. In addition, the lateral load condition of wind pressure by trains is estimated and numerical analysis is carried out according to the installation intervals of railway safety fences. It has been confirmed that the proper spacing between the train and the railway safety fence should be at least 200 mm from the vehicle limit, and that the proper spacing of railway safety fence must be calculated in consideration of the wind pressure by trains.
Lee, Kang Kyong;Kim, Geum Ryul;Yoon, Sang Don;Seol, Hyeon Ju
Convergence Security Journal
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v.21
no.1
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pp.177-189
/
2021
Defense R&D is a key process for securing weapons systems determined by mid- and long-term needs to cope with changing future battlefield environments. In particular, the test and evaluation provides information necessary to determine whether or not to switch to mass production as the last gateway to research and development of weapons systems and plays an important role in ensuring performance linked to the life cycle of weapons systems. Meanwhile, if you look at the recent changes in the operational environment of the Korean Peninsula and the defense acquisition environment, you can see three main characteristics. First of all, continuous safety accidents occurred during the operation of the weapon system, which increased social interest in the safety of combatants, and the efficient execution of the limited defense budget is required as acquisition costs increase. In addition, strategic approaches are needed to respond to future battlefield environments such as robots, autonomous weapons systems (RAS), and cyber security test and evaluation. Therefore, in this study, we would like to present strategies for improving the testing and evaluation of weapons systems by considering the characteristics of the security environment that has changed recently. To this end, the improvement strategy was derived by analyzing the complementary elements of the current weapon system operational test and evaluation system in a multi-dimensional model and prioritized through the hierarchical analysis method (AHP).
Journal of the Korean Association of Geographic Information Studies
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v.23
no.4
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pp.173-183
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2020
In the midst of the aging of underground facilities in urban areas and anxiety about road excavation safety accidents, the Ministry of Land, Infrastructure and Transport began to build Underground Geospatial Infomation Map from 2015 as part of the 「ground subsidence prevention measures」 and efficient use of underground spaces. So, the scope is spreading every year. The current Underground Geospatial Infomation Map information is web-based and is operated in a desktop environment, so it is true that there are some limitations in its use in a field environment such as an excavation construction site. The Underground Geospatial Infomation Map, built and operated in a web-based environment, is a large-scale 3D data. Therefore, in order to service by transmitting data to the field without delay, it is necessary to lighten the Underground Geospatial Infomation Map data. In addition, the current Underground Geospatial Infomation Map is not unified in data formats such as 3DS and COLLADA, and the coordinate system method is also different in relative coordinates and absolute coordinates. In this study, by analyzing domestic and overseas prior research and technical use cases, a mobile Underground Geospatial Infomation Map data format and a lightweight method were presented, and a technology development was conducted to create a mobile underground space integration map in the presented format. In addition, the weight reduction rate was tested by applying 3D data compression technology so that data can be transmitted quickly in the field, and technology was developed that can be used by decompressing 3D data compressed in the field. finally, it aims to supplement the technology experimentally developed in this study and conduct additional research to produce it as software that can be used in the excavation site and use it.
Korean Journal of Construction Engineering and Management
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v.23
no.1
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pp.64-72
/
2022
The retaining wall structure is essential for construction work that performs underground excavation. Displacement management of the retaining wall structure is important regardless of the size of the construction. However, in the case of small-scale construction sites with an excavation depth of less than 10m, displacement management of retaining wall structure not properly performed due to problems such as 1) companies' smallness, 2) lack of capacity of construction managers, 3) complexity of installation, dismantling and displacement of measuring instruments. As a result of analyzing previous research, it was analyzed that it is difficult to apply this to a small - scale construction site because most of the previous research has problems in using an expensive 3D scanner or installing many measuring instruments. This study aims to propose a conceptual design of a displacement measurement system for retaining wall structure based on laser sensor and to verify the displacement recognition performance of core technology applied to the conceptual design. A conceptual design was proposed using a 2D laser scanner. As a result of verifying the displacement recognition of the 2D laser scanner, a displacement of 15mm was analyzed to be sufficiently understandable. In the future, if the proposed conceptual design is developed and applied to the small-scale construction site, it is thought that it will contribute to the reduction of safety accidents at small-scale construction sites.
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