• Journal of the Korean Society for Railway
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• v.10 no.2 s.39
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• pp.224-230
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• 2007

The performance and applicability of FDS code is analyzed for flow simulation in railway tunnel. FDS has been built in NIST(USA) for simulation of fire-driven flow. RANS and DNS's results are compared with FDS's. AJL non-linear ${\kappa}-{\epsilon}$[7,8] model is employed to calculate the turbulent flow for RANS. DNS data by Moser et al.[9] are used to prove the FDS's applicability in the near wall region. Parallel plate is used for simplified model of railway tunnel. Geometrical variables are non-dimensionalized by the height (H) of parallel plate. The length of streamwise direction is 50H and the length of spanwise direction is 5H. Selected Re numbers are 10,667 for turbulent flow and 133 for laminar low. The characteristics of turbulent boundary layer are introduced. AJL model's predictions of turbulent boundary layer are well agreed with DNS data. However, the near wall turbulent boundary layer is not well resolved by FDS code. Slip conditions are imposed on the wall but wall functions based on log-law are not employed by FDS. The heavily dense grid distribution in the near wall region is necessary to get correct flow behavior in this region for FDS.

• The Korean Journal of Emergency Medical Services
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• v.8 no.1
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• pp.5-17
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• 2004

A descriptive-correlational study was conducted to examine the job satisfaction and organizational commitment of emergency medical technicians(EMTs) and to identify the relationship between job satisfaction and organizational commitment. Subjects of this study werw 85 EMTs who passed first grade qualification examination and work at hospitals or fire stations in Gwangju and Chonnam province. Data were collected using a structured questionnaire by a postal survey from Sept. 10 to Oct. 20, 2003. For data analysis, descriptive statistics, ANOVA. t-test, and Pearson Correlation were used. The mean score of subjects' job satisfaction was 3.04 and the mean score of organizational commitment was 3.33. There was no significant differences on job satisfaction and organizational commitment by general characteristics of subjects. Job satisfaction was significantly differed by their careers as a EMT, current working place, and types of duty. Organizational commitment was significantly differed by their current working place, types of duty, and level of mean allowance. There was statistically significant positive correlation between job satisfaction and organizational commitment. These findings provide implications to improve job satisfaction and organizational commitment for EMTs. Further studies are recommended.

• Journal of muscle and joint health
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• v.15 no.2
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• pp.175-182
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• 2008

Purpose: The purpose of the study was to identify low pain prevalence rate and factors affecting low back pain in emergency medical technicians. Method: A descriptive relationship research design was utilized. The participants were 74 emergency medical technicians who worked at fire stations in W and J city and agreed to participate in this study. Data were collected between April and August 2008 using a questionnaire, which included demographic factors, severity of low back pain using a visual analog scale, factors related to low back pain and health behavior, and BMI. Descriptive statistics and multiple regression were performed for data analysis. Results: 85.1% of emergency medical technicians experienced low back pain. The mean score of low back pain was relatively low (M=4.0, SD=2.33). Significant factors affecting low back pain were found to be age, marital status, exercise, hours of standing work, and BMI. These variables explained 35.1% of variance in low back pain (F=8.45, p<.001). Conclusion: These results suggest that further research is needed to develop interventions for prevention and management of low back pain among emergency medical technicians.

• The Korean Journal of Emergency Medical Services
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• v.25 no.1
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• pp.159-175
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• 2021

Purpose: This study aimed to obtain, categorize, and analyze baseline data regarding the subjective perception of ambulances from the consumers' perspective, which can be utilized for improving emergency medical service systems. Methods: Fifty people aged 20 to 40 years old were selected as P samples. Data from 35 statements of Q-cards and Q-sample distribution plots were gathered using Q-sort and analyzed using the PC-QUANL program for major factor analysis. Results: We found four unique characteristics which accounted for 57.57% of the total variation: "Considerate of emergency situations," "Identifying emergency patients," "Trusting emergency vehicles," and "Sympathizing with emergency patients." Conclusion: Organizations that provide emergency medical services using ambulances should plan and render patient care according to the four types of public perception of ambulances.

• The Korean Journal of Emergency Medical Services
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• v.28 no.1
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• pp.63-76
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• 2024

Purpose: To analyze trends related to demography and EMS and to provide supporting data for the appropriate deployment of EMS providers. Methods: In this cross-sectional study, data on patients transported by 119 EMS, demographics, and EMS factors were collected using the Korean Statistical Information Service (KOSIS) and the National Fire Agency annual report from 2017 to 2021. Results: During the study period, the total number of patients and those with severe disorders transported via 119 EMS showed an increasing trend. The total fertility rate and population during the same period tended to decrease, and the population density and number of households increased; however, there was a disparity between regions. The main demographic factors affecting the number of patients transported were population density and total fertility rate, while the main EMS factors were the number of ambulances and provision of emergency medical information services(hospital guidance, pharmacy information, and first aid guidance). Conclusion: From the perspective of EMS providers' force deployment, it is necessary to consider population density, population, number of households, total fertility rate, and number of emergency medical institutions and to strengthen the role of diverting the use of 119 EMS by minor patients by providing emergency medical information.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.134-141
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• 2023

We present a novel method aimed at refining ground truth data through regularization and modification, particularly applicable when working with the original ground truth set. Enhancing the performance of deep neural networks is achieved by applying regularization techniques to the existing ground truth data. In many machine learning tasks requiring pixel-level segmentation sets, accurately delineating objects is vital. However, it proves challenging for thin and elongated objects such as blood vessels in X-ray coronary angiography, often resulting in inconsistent generation of ground truth data. This method involves an analysis of the quality of training set pairs - comprising images and ground truth data - to automatically regulate and modify the boundaries of ground truth segmentation. Employing the active contour model and a recursive ground truth generation approach results in stable and precisely defined boundary contours. Following the regularization and adjustment of the ground truth set, there is a substantial improvement in the performance of deep neural networks.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.3
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• pp.135-142
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• 2001

This study attempts to categorizes the factors of forest fire occurrences based on regional meteorologic data and general forest no characteristics of 18 cities and guns in Kangwon province. lo accomplish this goal, some statistical analyses such as analysis of variance, correspondence analysis and multidimensional scaling were adopted. To reveal the forest fires pattern of study region, a categorization process was conducted by employing the quantification approach which modified and quantified the metric-data of fire occurrence dates. Also, The fire occurrence similarity was compared by using multidimensional scaling for each study region. The major results are summarized as follows: It was found that the meteorological factors emerged as different to each region are average and maximum temperature, minimum dew point temperature and average and maximum wind speed. In the result of correspondence analysis representing relationships between fire causes and study regions, Kangrung is caused by arsonist, Chulwon, Hwachen and Yanggu caused by military factor, Sokcho and Chunchen caused by the debris burning, and Samchuk caused by general man-caused fires, respectively. Finally, the forest fire occurrence pattern of this study regions were divided into five areas such as, group I including Samchuk, Kangryung, Chunchen, Wonju, Hongchen and Hhoingsung, group II including Donghae, Taebaek, Yangyang and Pyongchang, group III including Jungsun, Chulwon and Whachen, group Ⅵ including Gosung, Injae and Yanggu, and group V including Shokcho and Youngwol.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.29-39
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• 2020

Forest fire is a critical disaster that causes massive destruction of forest ecosystem and economic loss. Hence, accurate estimation of the burned area is important for evaluation of the degree of damage and for preparing baseline data for recovery. Since most of the area size damaged by wildfires in Korea is less than 1 ha, it is necessary to use satellite or drone images with a resolution of less than 10m for detecting the damage area. This paper aims to detect wildfire-damaged area from a Kompsat-3 image using the indices such as NDVI (normalized difference vegetation index) and FBI (fire burn index) and to examine the classification characteristics according to the methods such as Otsu thresholding and ISODATA(iterative self-organizing data analysis technique). To mitigate the salt-and-pepper phenomenon of the pixel-based classification, a gaussian filter was applied to the images of NDVI and FBI. Otsu thresholding and ISODATA could distinguish the burned forest from normal forest appropriately, and the salt-and-pepper phenomenon at the boundaries of burned forest was reduced by the gaussian filter. The result from ISODATA with gaussian filter using NDVI was closest to the official record of damage area (56.9 ha) published by the Korea Forest Service. Unlike Otsu thresholding for binary classification,since the ISODATA categorizes the images into multiple classes such as(1)severely burned area, (2) moderately burned area, (3) mixture of burned and unburned areas, and (4) unburned area, the characteristics of the boundaries consisting of burned and normal forests can be better expressed. It is expected that our approach can be utilized for the high-resolution images obtained from other satellites and drones.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.39-55
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• 2019

In this study, we have proposed an improved method to detect forest fires by correcting the reflected signals of day images using the middle-wavelength infrared (MWIR) channel. The proposed method is allowed to remove the reflected signals only using the image itself without an existing data source such as a land-cover map or atmospheric data. It includes the processing steps for calculating a solar-reflected signal such as 1) a simple correction model of the atmospheric transmittance for the MWIR channel and 2) calculating the image-based reflectance. We tested the performance of the method using the MODIS product. When compared to the conventional MODIS fire detection algorithm (MOD14 collection 6), the total number of detected fires was improved by approximately 17%. Most of all, the detection of fires improved by approximately 30% in the high reflection areas of the images. Moreover, the false alarm caused by artificial objects was clearly reduced and a confidence level analysis of the undetected fires showed that the proposed method had much better performance. The proposed method would be applicable to most satellite sensors with MWIR and thermal infrared channels. Especially for geostationary satellites such as GOES-R, HIMAWARI-8/9 and GeoKompsat-2A, the short acquisition time would greatly improve the performance of the proposed fire detection algorithm because reflected signals in the geostationary satellite images frequently vary according to solar zenith angle.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.5
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• pp.519-526
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• 2018

In this study, an algorithm to predict evacuation routes in support of shipboard lifesaving activities is presented. As the first step of algorithm development, the feasibility and necessity of an evacuation route prediction algorithm are shown numerically. The proposed algorithm can be explained in brief as follows. This system continuously obtains and analyzes passenger movement data from the ship's monitoring system during non-disaster conditions. In case of a disaster, evacuation route prediction information is derived using the previously acquired data and a prediction tool, with the results provided to rescuers to minimize casualties. In this study, evacuation-related data obtained through fire evacuation trials was filtered and analyzed using a statistical method. In a simulation using the conventional evacuation prediction tool, it was found that reliable prediction results were obtained only in the SN1 trial because of the conceptual and structural nature of the tool itself. In order to verify the validity of the algorithm proposed in this study, an industrial engineering tool was adapted for evacuation characteristics prediction. When the proposed algorithm was implemented, the predicted values for average evacuation time and route were very similar to the measured values with error ranges of 0.6-6.9 % and 0.6-3.6 %, respectively. In the future, development of a high-performance evacuation route prediction algorithm is planned based on shipboard data monitoring and analysis.