• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.173-185
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• 2015

This study aims to investigate the characteristics and types of car accidents and establish a prediction model by analyzing 456 car accidents having occurred in the 11 tunnels in Busan, through statistical analysis techniques. The results of this study can be summarized as below. As a result of analyzing the characteristics of car accidents, it was found that 64.9% of all the car accidents took place in the tunnels between 08:00 and 18:00, which was higher than 45.8 to 46.1% of the car accidents in common roads. As a result of analyzing the types of car accidents, the car-to-car accident type was the majority, and the sole-car accident type in the tunnels was relatively high, compared to that in common roads. Besides, people at the age between 21 and 40 were most involved in car accidents, and in the vehicle type of the first party to car accidents, trucks showed a high proportion, and in the cloud cover, rainy days or cloudy days showed a high proportion unlike clear days. As a result of analyzing the principal components of car accident influence factors, it was found that the first principal components were road, tunnel structure and traffic flow-related factors, the second principal components lighting facility and road structure-related factors, the third principal factors stand-by and lighting facility-related factors, the fourth principal components human and time series-related factors, the fifth principal components human-related factors, the sixth principal components vehicle and traffic flow-related factors, and the seventh principal components meteorological factors. As a result of classifying car accident spots, there were 5 optimized groups classified, and as a result of analyzing each group based on Quantification Theory Type I, it was found that the first group showed low explanation power for the prediction model, while the fourth group showed a middle explanation power and the second, third and fifth groups showed high explanation power for the prediction model. Out of all the items(principal components) over 0.2(a weak correlation) in the partial correlation coefficient absolute value of the prediction model, this study analyzed variables including road environment variables. As a result, main examination items were summarized as proper traffic flow processing, cross-section composition(the width of a road), tunnel structure(the length of a tunnel), the lineal of a road, ventilation facilities and lighting facilities.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.10
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• pp.1535-1544
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• 2010

This study was conducted to evaluate the sanitation management practices in food manufacturing companies that supply food and food ingredients to school foodservice operations. Subjects consisted of 34 food manufacturing factories located in the Daegu and Gyeongbuk areas. Sanitation performance was self-evaluated using a Likert 5-point scale. The total mean score for factory sanitation performance was 4.72. Scores for perceived sanitation management performance in the factories were as follows: management of material (4.90); personal hygiene (4.78); management of work (4.71); management of workplace and vicinity (4.68); and food and raw material transportation (4.67). Participating companies that had HACCP certification programs scored high on the following sanitation inspection items: washing and sanitation guides, adequate equipment for correct hand washing, and sanitation of raw material delivery vans. The mean frequency for employee sanitation education was 2.8 times per month. Factory managers believed that their sanitation management programs kept their food safe and that the food was produced and delivered with a high degree of safety. However, they thought that food sanitation standardization was needed in order to supply high-quality and safe food items. In terms of traceability, 58.8% of the raw materials were traceable and 61.8% of the manufactured products were traceable. Sanitation management performance scores for the participating food manufacturing companies were high, although the soybean sprouts processing companies had comparatively low scores. Management reinforcement of employee sanitation education and a sense of duty and pride among factory employees will promote adequate and appropriate sanitation management performance for food safety and quality in factories that supply food and ingredients to school foodservice operations.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• Journal of Korean Society of Steel Construction
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• v.16 no.2 s.69
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• pp.285-293
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• 2004

As a special infrastructure, it is important that the suspension bridges which were designed by using the cable are carefully maintained and safely inspected after their construction, more than what is done in other cases of bridge structures. However, the structural analysis for their design and maintenance has considered only the simplified geometric shape of the structure. Particularly, it is not easy to make the modeling analyze the bridge structure including detailed steel deck plates. In this paper, we evaluated the structural behaviors and performances of the completed earth-anchored suspension bridge that was in a completed state through both the tension of hanger member and their computational analysis. We considered the frame system and the detailed steel deck plates that were especially added into the modeling to take more precision analysis about it. We also applied hanger tensions converted by the natural frequency and the natural frequency of the bridge when in normal vibration. Results of the vehicle loading test were used in the analysis. We compared the results by using our modeling with the result of the loading test and the hanger tension. Our prediction on the behavior of the structure emulates the behavior of the real structure. In applying the data measured by the typhoon "Maemi" which arrived in-land last year, we confirmed our analysis model for the possibility of applying effectively into the preliminary design and maintenance plan.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.157-165
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• 2011

With respect to the trend of highway traffic accident, highway accident is in decline, whileas, the fatality is on an increasing trend. Thus, many efforts to decrease highway traffic accidents and improve the safety, are required. In particular, in case of highway, the management standard by grade for accident black spot is designated. Thus, investing the effect factors by grade for highway traffic accident is required in detail. Thus, in this study, the factors affecting the traffic accidents among the environmental factors based on the graded data for the accident black spot in the applicable section targeting the Seoul-Pusan Express Highway, were reviewed; accident forecasting model which would analyze the characteristics of the accidents for determining the accident grade, was developed. As a result of establishing a model by using Quantification Theory of Type II, considering the characteristics of the dependent and independent variables based on the geometric structure, 'the fixed variable' among the variables relating to the accident, for the variables influencing over the accident grade, 'the type of vans, a chassis and people', 'the trailers, special vehicles and chassis people' and 'the negligence of watching and cloudy weather' were analyzed as common factors, in case of 'horizontal alignment', 'longitudinal slope' and, 'barricade' respectively.

• Convergence Security Journal
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• v.12 no.1
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• pp.97-107
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• 2012

Our nation, of which the term of dispatching troops is winded up at the end of this year, is facing presidential election time including the nuclear security summit meeting in March, opening of EXPO in May, and the general election. Hence, the possibility to select our nation at the strategy forming public opinion of military withdrawal through Taliban's terror is high. It coincides with public affair strategy of Taliban terror and learning effect by the past cases. If the possibility of terror threat of Taliban along with this is summarized, the period of threat will concentrate on and be heightened in the first half when the nuclear security summit meeting and EXPO open in our nation, and target and method have high possibility of collision terror of bomb carrying vehicle and suicide bomb on national government organizations or American facilities, and etc, and possibility of kidnapping on our people such as oversea tourists, missionaries, and so on. Terror groups joining the criminal act is to use Islam illegal aliens who already acquire base in our nation or entry maneuver of specialized terrorists connected to Al-Qaeda. Pretext of such terror is withdrawal of our military and western allies stationed in Afghanistan. Therefore, publicity terror of Taliban against our people living overseas and security measure of international events such as the world nuclear security summit meeting, Yeosu EXPO, and etc in the first half of this year should be thoroughly prepared, domestic illegal aliens' movement should be comprehended, and measure blocking international terrorists' relating to Taliban infiltration into our nation should be sought for. Also, there is need of early announcement of government's political will on our military stationed in Afghanistan.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.91-100
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• 2010

Existing traffic safety studies have focused on identifying the relationship among roadway crashes, highway design and incremental weather condition such as rainy/ice weather. However, it is hard to find researches that studied the effect of sun glare on traffic safety although there are abundant evidences demonstrating that fatal traffic crashes are attributed to the sun glare. Affecting drivers'vision particularly during the morning or the evening time when the sun positions close to the horizon, sun glare directly deteriorate drivers'judgmental capability. In this paper, we numerically analyze the effect of sun glare on the drivers'vision in time and space domains. Applied to the roadways around St Louis area in the United States, the GIS based simulation analysis identifies the time of day in a year and the segments of highways that are potentially influenced by the sun glare. This study evidentially confirms the fact that roadway bounded for West and East directions have longer time influenced by sun glare particularly during Spring and Fall season than other roadways. The computational result provides risky time periods of day at intersections or pedestrian crossings where the sun glare potentially endangers traffic safety, which be utilized to reduce the crashes due to the sun glare.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.8
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• pp.74-84
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• 2010

In this paper, we propose a preference-based shortest path algorithm which is combined with Ant Colony Optimization (ACO) and A* heuristic algorithm. In recent years, with the development of ITS (Intelligent Transportation Systems), there has been a resurgence of interest in a shortest path search algorithm for use in car navigation systems. Most of the shortest path search algorithms such as Dijkstra and A* aim at finding the distance or time shortest paths. However, the shortest path is not always an optimum path for the drivers who prefer choosing a less short, but more reliable or flexible path. For this reason, we propose a preference-based shortest path search algorithm which uses the properties of the links of the map. The preferences of the links are specified by the user of the car navigation system. The proposed algorithm was implemented in C and experiments were performed upon the map that includes 64 nodes with 118 links. The experimental results show that the proposed algorithm is suitable to find preference-based shortest paths as well as distance shortest paths.

• Journal of Korean Society of Transportation
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• v.32 no.1
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• pp.1-12
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• 2014

The tier 3 methodology used in estimation of greenhouse gas emissions from road sectors is based on mileage data. However, such data can neither accurately represent the mileage of regional unit nor have sufficient integrated data reflecting the characteristics by region, vehicle type, fuel type and road type. Such estimation of greenhouse gas emissions is not reliable. Accordingly, the purpose of this study is, firstly to accumulate activity data based on distance traveled which enables us to accurately estimate the amount of green gas emitted by regional unit(emission point), and secondly, to develop a methodology for estimation of greenhouse gas emissions using these data. To do this, the study utilizes the mileage data of Korea Transportation Safety Authority(TS), statistics of registered motor vehicles, statistical yearbook of traffic volume from the Ministry of Land, Infrastructure and Transport(MLIT), the Korea Transport Database of the Korea Transport Institute(KOTI), and average road speed by local government. Methodology for estimation by local government level(emission point) is meaningful, because it reflects traffic pattern data including flow in and out and internal traffics. Finally, to verify the methodology presented in this study, it is applied to Seoul. Both greenhouse gas estimates, one by multiplying the average mileage and the number of registered vehicles and the other by multiplying traffic volume and road extension, are less than the amount estimated by the methodology presented in this study.

• Journal of the Korean Society for Railway
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• v.20 no.1
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• pp.64-75
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• 2017

The role of a track subgrade is to provide bearing capacity and distribute load transferred to lower foundation soils. Track subgrade soils are usually compacted by heavy mechanical machines in the field, such that sometimes they are attributed to progressive residual settlement during the service after construction completion of the railway track. The progressive residual settlement generated in the upper part of a track subgrade is mostly non-recoverable plastic deformation, which causes unstable conditions such as track irregularity. Nonetheless, up to now no design code for allowable residual settlement of subgrade in a railway trackbed has been proposed based on mechanical testing, such as repetitive triaxial testing. At this time, to check the DOC or stiffness of the soil, field test criteria for compacted track subgrade are composed of data from RPBT and field compaction testing. However, the field test criteria do not provide critical design values obtained from mechanical test results that can offer correct information about allowable permanent deformation. In this study, a test procedure is proposed for permanent deformation of compacted subgrade soil that is used usually in railway trackbed in the laboratory using repetitive triaxial testing. To develop the test procedure, an FEA was performed to obtain the shear stress ratio (${\tau}/{\tau}_f$) and the confining stress (${\sigma}_3$) on the top of the subgrade. Comprehensive repetitive triaxial tests were performed using the proposed test procedure on several field subgrade soils obtained in construction sites of railway trackbeds. A permanent deformation model was proposed using the test results for the railway track.