• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.883-890
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• 2022

Purpose: Currently, in the case of domestic fire fighting facility design, it is difficult to secure highquality manpower due to low design costs and overheated competition between companies, so there is a limit to improving the fire safety performance of buildings. Accordingly, AI-based firefighting design solutions were studied to solve these problems and secure leading fire engineering technologies. Method: Through AutoCAD, which is widely used in existing fire fighting design, the procedures required for basic design and implementation design were processed, and AI technology was utilized through the YOLO v4 object recognition deep learning model. Result: Through the design process for fire fighting facilities, the facility was determined and the drawing design automation was carried out. In addition, by learning images of doors and pillars, artificial intelligence recognized the part and implemented the function of selecting boundary areas and installing piping and fire fighting facilities. Conclusion: Based on artificial intelligence technology, it was confirmed that human and material resources could be reduced when creating basic and implementation design drawings for building fire protection facilities, and technology was secured in artificial intelligence-based fire fighting design through prior technology development.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Korean Society of Radiology
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• v.15 no.5
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• pp.697-704
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• 2021

It is hard to get Filaments which are materials of the 3D printing Fused Deposition Modeling(FDM) method as radiation shielding in Korea. and also related research is insufficient. This study aims to provide basic data for the development of radiation shields using 3D printing by evaluating the physical properties and radiation shielding capabilities of filaments containing metal particles. after selecting five metal filaments containing metal particle reinforcement materials, the radiation shielding rate was calculated according to the Korean Industrial Standard's protective equipment test method to evaluate physical properties such as tensile strength, density, X-ray Diffraction(XRD), and weight measurement using ASTM's evaluation method. In the tensile strength evaluation, PLA + SS was the highest, ABS + W was the lowest, and ABS + W is 3.13 g/cm³ which value was the highest among the composite filaments in the density evaluation. As a result of the XRD, it may be confirmed that the XRD peak pattern of the particles on the surface of the specimen coincides with the pattern of each particle reinforcing material powder metal, and thus it was confirmed that the printed specimen contained powder metal. The shielding effect for each 3D printed composite filament was found to have a high shielding rate in proportion to the effective atomic number and density in the order of ABS + W, ABS + Bi, PLA+SS, PLA + Cu, and PLA + Al. In this study, it was confirmed that the metal particle composite filament containing metal powder as a reinforcing material has radiation shielding ability, and the possibility of using a radiation shielding filament in the future.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of Radiation Protection and Research
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• v.40 no.3
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• pp.162-167
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• 2015

Although the perfomance indicators of the nuclear power plants in Korea show optimal, it requires detailed analysis and discussion centered on the radiation dose. As analysis methods, analysis on the radiation dose of nuclear power plants over the past five years was assessed by comparing the relevant radiation dose of radiation workers and per capita average annual radiation dose of the world's major nuclear power stations was also analyzed. The radiation workers over the annual radiation dose limit of 50 mSv were not. The contrast ratio of the radiation exposure according to the reactor type was the normal operation of PHWR was 6.2% higher than those of the PWR. This shows the radiation work of PHWR during normal driving operation is much more than those of PWR. According to the Performance Indicators of the World Association of Nuclear Operator, the annual radiation dose per unit in 2013 showed 527 man-mSv of Korea is the best country among the major nuclear power generating states, the world average was 725 man-mSv. The annual per capita radiation dose is about 80% less than 1 mSv of the public dose limit and also the average per capita dose showed a very low level as 0.82 mSv. Workers in related organizations showed 1.07 mSv, the non-destructive inspection agency workers showed 3.87 mSv. The remarkable results were due to radiation reduced program such as development of radiation shielding and radiation protection. In conclusion, the radiation exposured dose of nuclear power plants workers in Korea showed a trend which is ideally reduced. But more are expected to be difficul and the psychological insecurity against the operation of the nuclear power plants is existed to the residents near the nuclear power plants. So the radiation dose reduction policy and radiation dose follow up study of nuclear power plants will be continously excuted.

• Journal of the Korean GEO-environmental Society
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• v.15 no.2
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• pp.67-74
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• 2014

Recently, the number of road construction is increasing by industrial development. According to this industrial tendency, the number of traffic accidents are consistently increasing due to increasing number of vehicle on the road. This is mainly because traffic accidents are occurred by various parameter such as negligence of driver, vehicle defects, state of unstable road, natural environment etc. Lane department of vehicles from guardrail is occurring frequently. This type of accident is caused by vehicle performance improvement and shape of vehicle, weak guardrail installation and maintenance. Guardrail has the purpose on prevention such as prevention of traffic accident and prevention of deviating out of road, minimizing damage of driver and vehicle by collision as well as entry into the road through guardrail. Stability evaluation test of guardrail verifies the behavior of guardrail through the crash of truck. At this time, the crash condition has 100 km/h of velocity and $15^{\circ}$ of impact angle. In the case of ground condition, filling slope condition has relatively high bearing capacity of infinite ground towards the test. Guardrail is generally installed on road of shoulder in fill slope in korea. It is possible for stability problem to deteriorate ground bearing capacity in Guardrail in fill slope. The existed study towards stability of guardrail has been carried out in the infinite ground. However, the study on the behavior of fill slope with guardrail is not performed by vehicle collision. Therefore, In this study, the numerical analysis using LS-DYNA was executed for verification on behavior of fill slope with guardrail through vehicle collision. This numerical analysis was carried out with change of embedded depth on installed guardrail post in shoulder of fill slope by vehicle collision and 8 tonf truck crash providing at NCAN (National Crash Analysis Center). As the result, displacement and stress on fill slope are decreased in accordance with the increase of embedded depth of guardrail post. Ground bearing capacity is deteriorated at depth of 450 mm form shoulder of road on fill slope.