• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.479-485
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• 2022

At the Korea Institute of Radiological and Medical Sciences, physical human phantoms were developed to evaluate various radiation protection quantities, based on the mesh-type reference computational phantoms of the International Commission on Radiological Protection. The physical human phantoms were fabricated such that a radiophotoluminescent glass dosimeter (RPLGD) with a Tin filter, namely GD-352M, could be inserted into them. A Tin filter is used to eliminate the overestimated signals in low-energy photons below 100 keV. The measurement uncertainty of the RPLGD reader system based on GD-352M should be analyzed for obtaining reliable protection quantities before using it for practical applications. Generally, the measurement uncertainty of RPLGD systems without Tin filters is analyzed for quality assurance of radiotherapy units using a high-energy photon beam. However, in this study, the measurement uncertainty of GD-352M was analyzed for evaluating the protection quantities. The measurement uncertainty factors in the RPLGD include the reference irradiation, regression curve, reproducibility, uniformity, energy dependence, and angular dependence, as described by the International Organization for Standardization (ISO). These factors were calculated using the Guide to the Expression of Uncertainty in Measurement method, applying ISO/ASTM standards 51261(2013), 51707(2015), and SS-ISO 22127(2019). The measurement uncertainties of the RPLGD reader system with a coverage factor of k = 2 were calculated to be 9.26% from 0.005 to 1 Gy and 8.16% from 1 to 10 Gy. A blind test was conducted to validate the RPLGD reader system, which demonstrated that the readout doses included blind doses of 0.1, 1, 2, and 5 Gy. Overall, the E_n values were considered satisfactory.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.610-619
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• 2022

Hydrogen is emerging as an alternative fuel for eco-friendly ships because it reacts with oxygen to produce electrical energy and only water as a by-product. However, unlike regular fossil fuels, hydrogen has a material with a high risk of explosion due to its low ignition point and high flammability range. In order to safely use hydrogen in ships, it is an essential task to study the flow characteristics of hydrogen leakage and diffusion need to be studied. In this study, a numerical analysis was performed on the effect of leakage, ventilation, etc. on ventilation performance when hydrogen leaks in an enclosed space such as inside a ship. ANSYS CFX ver 18.1, a commercial CFD software, was used for numerical analysis. The leakage rate was changed to 1 q, 2 q, and 3 q at 1 q = 1 g/s, the ventilation rate was changed to 1 Q, 2 Q and 3 Q at 1 Q = 0.91 m/s, and the ventilation method was changed to type I, type II, type III to analyze the ventilation performance was analyzed. As the amount of leakage increased from 1 q to 3 q, the HMF in the storage room was about 2.4 to 3.0 times higher. Furthermore, the amount of ventilation to reduce the risk of explosion should be at least 2 Q, and it was established that type III was the most suitable method for the formation of negative pressure inside the hydrogen tank storage room.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.331-340
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• 2022

Early afterdepolarization (EAD), a significant cause of fatal ventricular arrhythmias including Torsade de Pointes (TdP) in long QT syndromes, is a depolarizing afterpotential at the plateau or repolarization phase in action potential (AP) profile early before completing one pace. AP duration prolongation is related to EAD but is not necessarily accounted for EAD. Several computational studies suggested EAD can form from an abnormality in the late plateau and/or repolarization phase of AP shape. In this sense, we hypothesized the slope during repolarization has the characteristics to predict TdP risk, mainly focusing on the maximum slope during repolarization (dVm/dt_{max_repol}). This study aimed to predict the sensitivity of dVm/dt_{max_repol} to ion channel conductances as a TdP risk metric through a population simulation considering multiple effects of simultaneous reduction in six ion channel conductances of g_NaL, g_Kr, g_Ks, g_to, g_K1, and g_CaL. Additionally, we verified the availability of dVm/dt_{max_repol} for TdP risk prediction through the correlation analysis with qNet, the representative TdP metric. We performed the population simulations based on the methodology of Gemmel et al. using the human ventricular myocyte model of Dutta et al. Among the sixion channel conductances, dVm/dt_{max_repol} and qNet responded most sensitively to the change in g_Kr, followed by g_NaL. Furthermore, dVm/dt_{max_repol} showed a statistically significant high negative correlation with qNet. The dVm/dt_{max_repol} values were significantly different according to three TdP risk levels of high, intermediate, and low by qNet (p<0.001). In conclusion, we suggested dVm/dt_{max_repol} as a new biomarker metric for TdP risk assessment.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.365-372
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• 2022

Compared to sensors mainly used in human activity recognition (HAR) systems, inertial measurement unit (IMU) sensors are small and light, so can achieve lightweight system at low cost. Therefore, in this paper, we propose a binary neural network (BNN) based gait pattern analysis system using IMU sensor, and present the design and implementation results of an FPGA-based accelerator for computational acceleration. Six signals for gait are measured through IMU sensor, and a spectrogram is extracted using a short-time Fourier transform. In order to have a lightweight system with high accuracy, a BNN-based structure was used for gait pattern classification. It is designed as a hardware accelerator structure using FPGA for computation acceleration of binary neural network. The proposed gait pattern analysis system was implemented using 24,158 logics, 14,669 registers, and 13.687 KB of block memory, and it was confirmed that the operation was completed within 1.5 ms at the maximum operating frequency of 62.35 MHz and real-time operation was possible.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.429-440
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• 2021

With the recent development of deep convolutional neural network learning, deep learning techniques applied to single image super-resolution are showing good results. One of the existing deep learning-based super-resolution techniques is RDN(Residual Dense Network), in which the initial feature information is transmitted to the last layer using residual dense blocks, and subsequent layers are restored using input information of previous layers. However, if all hierarchical features are connected and learned and a large number of residual dense blocks are stacked, despite good performance, a large number of parameters and huge computational load are needed, so it takes a lot of time to learn a network and a slow processing speed, and it is not applicable to a mobile system. In this paper, we use the residual dense structure, which is a continuous memory structure that reuses previous information, and the residual dense channel attention block using the channel attention method that determines the importance according to the feature map of the image. We propose a method that can increase the depth to obtain a large receptive field and maintain a concise model at the same time. As a result of the experiment, the proposed network obtained PSNR as low as 0.205dB on average at 4× magnification compared to RDN, but about 1.8 times faster processing speed, about 10 times less number of parameters and about 1.74 times less computation.

• Membrane and Water Treatment
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• v.14 no.3
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• pp.129-140
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• 2023

The appropriate injection of H₂O₂ is essential to produce hydroxyl radicals (OH·) by mixing H₂O₂ quickly and exposing the resulting H₂O₂ solution to UV irradiation. This study focused on evaluating mixing device of H₂O₂ as a design factor of UV/H₂O₂ AOP pilot plant using a surface water. The experimental investigation involved both experimental and model-based analyses to evaluate the mixing effect of different devices available for the H₂O₂ injection of a tubular hollow pipe, elliptical type of inline mixer, and nozzle-type injection mixer. Computational fluid dynamics analysis was employed to model and simulate the mixing devices. The results showed that the elliptical type of inline mixer showed the highest uniformity of 95%, followed by the nozzle mixer with 83%, and the hollow pipe with only 18%, after passing through each mixing device. These results indicated that the elliptical type of inline mixer was the most effective in mixing H₂O₂ in a bulk. Regarding the pressure drops between the inlet and outlet of pipe, the elliptical-type inline mixer exhibited the highest pressure drop of 15.8 kPa, which was unfavorable for operation. On the other hand, the nozzle mixer and hollow pipe showed similar pressure drops of 0.4 kPa and 0.3 kPa, respectively. Experimental study showed that the elliptical type of inline and nozzle-type injection mixers worked well for low concentration (less than 5mg/L) of H₂O₂ injection within 10% of the input value, indicating that both mixers were appropriate for required H₂O₂ concentration and mixing intensity of UV/ H₂O₂ AOP process. Additionally, the elliptical-type inline mixer proved to be more stable than the nozzle-type injection mixer when dealing with highly concentrated pollutants entering the UV/H₂O₂ AOP process. It is recommended to use a suitable mixing device to meet the desired range of H₂O₂ concentration in AOP process.

• Land and Housing Review
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• v.14 no.3
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• pp.93-106
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• 2023

This study attempted to simulate changes in the thermal environment according to the type of apartment complex in Korea using CFD techniques and evaluate the thermal environment by type of apartment. First, apartment complex types in the 2000s and 2010s were referred from previous studies and four types of apartment complex were extracted from. Second, the layout of the apartment complex and temperature changes were analyzed by the direction of wind inflow. Third, a standardized model was created from each type using tower type, plate type, and mixed driving. Last, CFD simulations were performed by setting up the inflow of wind from a total of eight directions. The temperature was relatively low in the type consisting of only the tower type and the type of placing the tower type in the center of the complex, regardless of the direction of the wind. It was due to the good inflow of wind from these types to the inside of the complex. It can be interpreted because wind flows easily into the complex in these types. The findings showed that wind flow and resulting temperature distribution patterns differed depending on the building type and complex layout type, confirming the need for careful consideration of the complex layout in the early design stage. The results are expected to be used as basic data for creating a sustainable residential environment in the early design stage of apartment complexes in the future.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.225-236
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• 2019

Viewing and approaching problems based on computational thinking can be improved through informatics education, which is essential for students to live in a future society. The purpose of this study is to analyze the operation status of informatics subjects that have become general electives in the 2015 revised curriculum, and to contribute to enhancing the effect of future informatics subject. To achieve this goal, a questionnaire was conducted for 400 students who graduated from high school in 2015-2016, and five students and five informatics subjects teachers were interviewed. Operation period of Infomatics subject, contents, method and evaluation method were analyzed. As a result, the operation of informatics subjects varied greatly from the second semester of the first year to the second semester of the third year. The most common method was teaching type, but the percentage of self-study was high in the second semester of the third year. The contents of the study did not learn all the contents, and the use rate of textbooks was low in the class. This study confirmed that the informatics subject class did not proceed in the form of observing the curriculum similarly to other subjects excluded. It is also significant that for the first time, the operational status of informatics subjects was analyzed.

• Journal of Industrial Convergence
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• v.21 no.3
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• pp.195-202
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• 2023

This study analyzes the results of a survey based on classes conducted in the field to understand the educational needs of learners, and reflects the elements necessary for SW education. In this study, various experimental elements according to learning motivation and learning achievement were constructed and designed through previous studies. As a survey applied to this study, experimental elements in three categories: Faculty Competences(FC), Learner Competences(LC), and Educational Conditions(EC) were analyzed by primary area and secondary major, respectively. As a result of analyzing CT-based SW education by area, the development of educational materials, understanding of lectures, and teaching methods showed high satisfaction, while communication with students, difficulty of lectures, and the number of students were relatively low. The results of the analysis by major were found to be more difficult and less interesting in the humanities than in the engineering field. In this study, Based on these statistical results proposes the need for non-major SW education to improve into an interesting curriculum for effective liberal arts education in the future in terms of enhancing learners' problem-solving skills.