• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.37-45
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• 2019

In recent years, the emergence of virtual reality (VR Virtual Reality) technology has provided a new model of safety education, enabling users to learn and respond to disasters in a virtual safety education environment. However, the related VR products related to domestic and foreign R & D are relatively simple, there is no practical training on specific accident, and it is not practical enough to play a sufficient role in safety education. In this paper, the problems and disadvantages of VR technology applied in the field of automobile safety education as an example of automobile accident among the types of disasters are examined, and a system framework of automotive safety education based on VR technology is proposed. The vehicle safety education system proposed in this paper will help users to improve driving safety consciousness, to acquire safety knowledge in driving, and to acquire driving safety skill which is very important for automobile safety education. In addition, the design and production methods of safety education based on VR technology are considered to have important reference implications for the application of modern teaching and teaching theory by integrating with VR technology and developing related teaching materials products and finally introducing education.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.128-133
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• 2021

Currently, autonomous vehicle markets are commercializing a third-level autonomous vehicle, but there is a possibility that an accident may occur even during fully autonomous driving due to stability issues. In fact, autonomous vehicles have recorded 81 accidents. This is because, unlike level 3, autonomous vehicles after level 4 have to judge and respond to emergency situations by themselves. Therefore, this paper proposes a vehicle crisis detection system(VCDS) that collects and stores information outside the vehicle through CNN, and uses the stored information and vehicle sensor data to output the crisis situation of the vehicle as a number between 0 and 1. The VCDS consists of two modules. The vehicle external situation collection module collects surrounding vehicle and pedestrian data using a CNN-based neural network model. The vehicle crisis situation determination module detects a crisis situation in the vehicle by using the output of the vehicle external situation collection module and the vehicle internal sensor data. As a result of the experiment, the average operation time of VESCM was 55ms, R-CNN was 74ms, and CNN was 101ms. In particular, R-CNN shows similar computation time to VESCM when the number of pedestrians is small, but it takes more computation time than VESCM as the number of pedestrians increases. On average, VESCM had 25.68% faster computation time than R-CNN and 45.54% faster than CNN, and the accuracy of all three models did not decrease below 80% and showed high accuracy.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.515-524
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• 2022

The turnout system of the sleeper floating tracks (STEDEF) on urban transit is a Anti-vibration track composed of a wooden sleeper embedded in a concrete bed and a sleeper resilience pad under the sleeper. Therefore, deterioration and changes in spring stiffness of the sleeper resilience pad could be cause changes in sleeper support conditions. The damage amount of manganese crossings that occurred during the current service period of about 21 years was investigated to be about 17% of the total amount of crossings, and it was analyzed that the damage amount increased after 15 years of use (accumulated passing tonnage of about 550 million tons). In this study, parameter analysis (wheel position, sleeper support condition, and dynamic wheel load) was performed using a three-dimensional numerical model that simulated real manganese crossing and wheel profile, to analyze the damage type and cause of manganese crossing that occurred in the actual field. As a result of this study, when the voided sleeper occurred in the sleeper around the nose, the stress generated in the crossing nose exceeded the yield strength according to the dynamic wheel load considering the design track impact factor. In addition, the analysis results were evaluated to be in good agreement with the location of damage that occurred in the actual field. Therefore, in order to minimize the damage of the manganese crossing, it is necessary to keep the sleeper support condition around the nose part constant. In addition, by considering the uniformity of the boundary conditions under the sleepers, it was analyzed that it would be advantageous to to replace the sleeper resilience pad together when replacing the damaged manganese crossing.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.185-192
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• 2023

In this study, fluctuating wind velocity for time history analysis is simulated by a single variate, single-dimensional random process using the KBC2022 spectrum about across-wind direction. This study analyzed and obtained the inelastic dynamic response for structures modeled as a single-degree-of-freedom system. It is assumed that the wind response is excellent in the primary mode, the change in vibration owing to plasticization is minor, along-wind vibration and across-wind vibration are independent, and the effect of torsional vibration is small. The numerical results, obtained by the Newmark-𝛽 method, shows the time-history responses and trends of maximum displacements. As a result of analyzing the inelastic dynamic response of the structure with the second stiffness ratio(𝛼) and yield displacement ratio (𝛽) as variables, it is identified that as the yield displacement ratio (𝛽) increases when the second stiffness ratio is constant, the maximum displacement ratio decreases, then reaches a minimum value, and then increases. When the stiffness ratio is greater than 0.5, there is a yield point ratio at which the maximum displacement ratio is less than 1, indicating that the maximum deformation is reduced compared to the elastically designed building even if the inelastic behavior is permitted in the inelastic wind design.

• Journal of The Korean Association For Science Education
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• v.29 no.6
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• pp.730-740
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• 2009

The purpose of this study was to investigate secondary science teachers' brain activation and functional connectivity during scientific observation on the biological phenomena. Twenty six right-handed healthy science teachers volunteered to be in the present study. To investigate science teachers' brain activities during the tasks, 3.0T fMRI system with block design was used to measure BOLD signals in their brains. The SPM2 software package was applied to analyze the acquired initial image data from the fMRI system. The results have shown that the left inferior frontal gyrus, the bilateral superior parietal lobule, the left inferior parietal lobule, the left precuneus, the left superior occipital gyrus, the right middle occipital gyrus, the right precuneus, the left inferior occipital gyrus and bilateral fusiform gyrus were significantly activated during participants' scientific observation. The network model consisted of eleven nodes (ROIs) and its ten connections. These results suggested the notion that scientific observation needs a connective cooperation among several brain regions associated with observing over just a sensory receiving process.

• Progress in Medical Physics
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• v.26 no.4
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• pp.250-257
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• 2015

Multi-leaf collimator (MLC) systems are frequently used to deliver photon-based radiation, and allow conformal shaping of treatment beams. Many proton beam centers currently make use of aperture and snout systems, which involve use of a snout to shape and focus the proton beam, a brass aperture to modify field shape, and an acrylic compensator to modulate depth. However, it needs a lot of time and cost of preparing treatment, therefore, we developed the manual MLC for solving this problem. This study was carried out with the intent of designing an MLC system as an alternative to an aperture block system. Radio-activation and dose due to primary proton beam leakage and the presence of secondary neutrons were taken into account during these iterations. Analytical calculations were used to study the effects of leaf material on activation. We have fabricated tray model for adoption with a wobbling snout ($30{\times}40cm^2$) system which used uniform scanning beam. We designed the manual MLC and tray and can reduce the cost and time for treatment. After leakage test of new tray, we upgrade the tray with brass and made the safety tool. First, we have tested the radio-activation with usually brass and new brass for new manual MLC. It shows similar behavior and decay trend. In addition, we have measured the leakage test of a gantry with new tray and MLC tray, while we exposed the high energy with full modulation process on film dosimetry. The radiation leakage is less than 1%. From these results, we have developed the design of the tray and upgrade for safety. Through the radio-activation behavior, we figure out the proton beam leakage level of safety, where there detects the secondary particle, including neutron. After developing new design of the tray, it will be able to reduce the time and cost of proton treatment. Finally, we have applied in clinic test with original brass aperture and manual MLC and calculated the gamma index, 99.74% between them.

• Fire Science and Engineering
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• v.17 no.4
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• pp.76-85
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• 2003

In this study, we write down the definitions, their causes and the techniques of analysis as a theoretical consideration of common cause failures, and investigate the limitation and the importance of the common cause failures by applying to the analysis on the fire protection as a representative safety facility. As you can know in the reliability analysis, most impressive cause is the malfunctions of pumping operations; especially the common cause failure of two pumps is dominant. In other words, it is possible to assess system-reliability as twice as actual without CCF From these, CCF is extraordinarily important and the results are highly dependent on the CCF factor. And although it would increase with multiple installations, the reliability are not defined as linear with those multiplications. In addition, the differences in results due to the models for analysis are not significant, whereas the various sources of data produce highly different results. Therefore, we conclude that the reliabilities are dependent on the quality of the usable data much better than the variety of models. As a result, the basic and engineering device for the preventions of CCF of the multiple facilities is to design it as reliably as to design the fire-water pump. That is to say, we must assess those reliabilities using PFD whether they are appropriate to SIL (Safety Integrity Level) which is required for the reliability in SIS (Safety Instrumented System). The result of the analysis on the reliability of the fire-water supply with CCF shows that PFD is 3.80E-3, so that it cannot be said to be designed as safely as in the level of SIL5. However, without CCF, PFD is 1.82E-3 which means that they are designed as unsafely as before.

• Publications of The Korean Astronomical Society
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• v.34 no.3
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• pp.31-40
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• 2019

We study the internal structure under the artificial mountain of Heumkyeonggak-nu, a Korean water-powered clock in the early Joseon dynasty. All the puppets on the artificial mountain are driven by the rotational force generated by the water wheel at their designated time. We design a model that work with three parts of the artificial mountain. At the upper part of the artificial mountain to the east, west, north and south, there are four puppets called the Four Mystical Animal Divinity and four ladies called the Jade Lady respectively. The former rotates a quarter every double hour and the latter rings the bell every hour. In the middle part of this mountain is the timekeeping platform with four puppets; the Timekeeping Official (Hour Jack), the Bell-, Drum-, and Gong-Warriors. The Hour Jack controls time with three warriors each hitting his own bell, drum, and gong, respectively. In the plain there are 12 Jade Lady puppets (the lower ladies) combined with 12 Oriental Animal Deity puppets. In his own time a lady doll pops out of the hole and her animal doll gets up. Two hours later, the animal deity lies down and his lady hides in the artificial plain. These puppets are regularly moved by the signal such as iron balls, bumps, levers, and so on. We can use balls and bumps to explain the concept of the Jujeon system. Iron balls were used to manipulate puppets of the timekeeping mechanism in Borugak-nu, another Korean water-powered clock in Joseon dynasty, which was developed earlier than Heumgyeonggak-nu. According to the North Korea's previous study (Choi, 1974), it is obvious that bumps were used in the internal structure of Heumgyeonggak-nu. In 1669, The armillary clock made by Song, I-young was also utilized bumps. Finally we presented mock-ups of three timekeeping systems.