• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2797-2801
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• 2023

CdZnTeSe (CZTS) has attracted attention for applications in X- and gamma-ray detectors owing to its improved properties compared to those of CdZnTe (CZT). In this study, we grew and processed single crystals of CZT and CZTS using the Bridgeman method to confirm the feasibility of using a dosimeter for high-energy X-rays in radiotherapy. We evaluated their linearity and precision using the coefficient of determination (R²) and relative standard deviation (RSD). CZTS showed sufficient RSD values lower than 1.5% of the standard for X-ray dosimetry, whereas CZT's RSD values increased dramatically under some conditions. CZTS exhibited an R² value of 0.9968 at 500 V/cm, whereas CZT has an R² value of 0.9373 under the same conditions. The X-ray response of CZTS maintains its pulse shape at various dose rates, and its properties are improved by adding selenium to the CdTe matrix to lower the defect density and sub-grain boundaries. Thus, we validated that CZTS shows a better response than CZT to high-energy X-rays used for radiotherapy. Further, the applicability of an onboard imager, a high-energy X-ray (>6 MV) image, is presented. The proposed methodology and results can guide future advances in X-ray dose detection.

• Journal of IKEEE
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• v.26 no.1
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• pp.43-49
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• 2022

This paper compares the sensorless control performance according to the applied voltage waveform by injecting sinusoidal, triangular, and square waveform in the harmonic injection sensorless control method. By injecting various voltage shape waveform with a frequency of 1kHz, the error amount of the estimated angle for each waveform is compared and analyzed. For the experiment, the HILS(hardware in the loop simulation) system was used. The hardware is the control board, and the inverter and motor models implemented in Simulik are located in the real-time simulator. The control algorithm is implemented by the FPGA control board, which includes a PWM interrupt service routine with a frequency of 10 kHz, harmonic injection and position detection sensorless algorithm.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.43.1-43.1
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• 2020

Cassiopeia A (Cas A) is a young supernova remnant (SNR) where we observe the interaction of SNR blast wave with circumstellar medium. From the early optical studies, dense, slowly-moving, N-rich "quasi-stationary flocculi" (QSF) have been known. These are probably dense CNO-processed circumstellar knots that have been engulfed by the SNR blast wave. We have carried out near-infrared, high-resolution (R=45,000) spectroscopic observations of ~40 QSF, and here we present the result on a QSF knot (hereafter 'Knot 24') near the SNR boundary of Cas A. The average [Fe II] 1.644 um spectrum of Knot 24 has a remarkable shape with a narrow (~8 km/s) line superposed on the broad (~200 km/s) line emitted from shocked gas. The spatial morphology and the line parameters indicate that Knot 24 has been partially destroyed by a shock wave and that the narrow line is emitted from the unshocked material heated/ionized by the shock radiation. This is the first detection of the emission from the pristine circumstellar material of the Cas A supernova progenitor. We also detected H Br gamma and other [Fe II] lines corresponding to the narrow [Fe II] 1.644 um line. For the main clump where we can clearly identify the shock emission associated with the unshocked material, we analyze the observed line ratios using a shock model that includes radiative precursor. The analysis indicates that the majority of Fe in the unshocked material is in the gas phase, not depleted onto dust grains as in the general interstellar medium. We discuss the non-depletion of Fe in QSF and its implications on the immediate progenitor of the Cas A supernova.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.75-75
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• 2022

Traditional agriculture mostly focused on activity in the field, but current agriculture faces problems such as reduction of agricultural inputs, labor shortage and so on. Accordingly, traditional agricultural experiments generally considered the simple treatment effects, but current agricultural experiments need to consider the several and complicate treatment effects. To analyze such several and complicate treatment effects, data collection has the first priority. Remote sensing is a quite effective tool to collect information in agriculture, and recent easier availability of UAVs (Unmanned Aerial Vehicles) enhances the effectiveness. LAI (Leaf Area Index) is one of the most important information for evaluating the condition of crop growth. In this study, we utilized UAV with multispectral camera to evaluate plant-based LAI of sweetcorn in a small-scale field experiment and discussed the feasibility of a new experimental design to analyze the several and complicate treatment effects. The plant-based SR measured by UAV showed the highest correlation coefficient with LAI measured by a canopy analyzer in 2018 and 2019. Application of linear mix model showed that plant-based SR data had higher detection power due to its huge number of data although SR was inferior to evaluate LAI than the canopy analyzer. The distribution of plant-based data also statistically revealed the border effect in treatment plots in the traditional experimental design. These results suggest that remote sensing with UAVs has the advantage even in a small-scale experimental plot and has a possibility to provide a new experimental design if combined with various analytical applications such as plant size, shape, and color.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.137-147
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• 2023

LiDAR is used in autonomous driving and various industrial fields to measure the size and distance of an object. In addition, the sensor also provides intensity images based on the amount of reflected light. This has a positive effect on sensor data processing by providing information on the shape of the object. LiDAR guarantees higher performance as the resolution increases but at an increased cost. These conditions also apply to LiDAR intensity images. Expensive equipment is essential to acquire high-resolution LiDAR intensity images. This study developed artificial intelligence to improve low-resolution LiDAR intensity images into high-resolution ones. Therefore, this study performed parameter analysis for the optimal super-resolution neural network model. The super-resolution algorithm was trained and verified using 2,500 LiDAR intensity images. As a result, the resolution of the intensity images were improved. These results can be applied to the autonomous driving field and help improve driving environment recognition and obstacle detection performance

• Advances in nano research
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• v.15 no.5
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• pp.441-449
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• 2023

Heavy metals, widely present in the environment, have become significant pollutants due to their excessive use in industries and technology. Their non-degradable nature poses a persistent environmental problem, leading to potential acute or chronic poisoning from prolonged exposure. Recent research has focused on separating heavy metals, particularly from industrial and mining sources. Industries such as metal plating, mining operations, tanning, wood and chipboard production, industrial paint and textile manufacturing, as well as oil refining, are major contributors of heavy metals in water sources. Therefore, removing heavy metals from water is crucial, especially for safe water supply in swimming and water sports. Iron oxide nanoparticles have proven to be highly effective adsorbents for water contaminants, and efforts have been made to enhance their efficiency and absorption capabilities through surface modifications. Nanoparticles synthesized using plant extracts can effectively bind with heavy metal ions by modifying the nanoparticle surface with plant components, thereby increasing the efficiency of heavy metal removal. This study focuses on removing lead from industrial wastewater using environmentally friendly, cost-effective iron nanoparticles synthesized with Genovese basil extract. The synthesis of nanoparticles is confirmed through analysis using Transmission Electron Microscope (TEM) and X-ray diffraction, validating their spherical shape and nanometer-scale dimensions. The method used in this study has a low detection limit of 0.031 ppm for measuring lead concentration, making it suitable for ensuring water safety in swimming and water sports.

• Journal of Biomedical Engineering Research
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• v.45 no.2
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• pp.95-100
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• 2024

Vitiligo is a condition characterized by the destruction or dysfunction of melanin-producing cells in the skin, resulting in a loss of skin pigmentation. Facial vitiligo, specifically affecting the face, significantly impacts patients' appearance, thereby diminishing their quality of life. Evaluating the efficacy of facial vitiligo treatment typically relies on subjective assessments, such as the Facial Vitiligo Area Scoring Index (F-VASI), which can be time-consuming and subjective due to its reliance on clinical observations like lesion shape and distribution. Various machine learning and deep learning methods have been proposed for segmenting vitiligo areas in facial images, showing promising results. However, these methods often struggle to accurately segment vitiligo lesions irregularly distributed across the face. Therefore, our study introduces a framework aimed at improving the segmentation of vitiligo lesions on the face and providing an evaluation of vitiligo lesions. Our framework for facial vitiligo segmentation and lesion evaluation consists of three main steps. Firstly, we perform face detection to minimize background areas and identify the face area of interest using high-quality ultraviolet photographs. Secondly, we extract facial area masks and vitiligo lesion masks using a semantic segmentation network-based approach with the generated dataset. Thirdly, we automatically calculate the vitiligo area relative to the facial area. We evaluated the performance of facial and vitiligo lesion segmentation using an independent test dataset that was not included in the training and validation, showing excellent results. The framework proposed in this study can serve as a useful tool for evaluating the diagnosis and treatment efficacy of vitiligo.

• Korean Journal of Heritage: History & Science
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• v.54 no.1
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• pp.206-219
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• 2021

The warming of the climate is increasing the damage caused by termites to wooden buildings, cultural properties and houses. A group removal system can be installed around the building to detect and remove termite damage; however, if the site is not visited regularly, every one to two months, you cannot observe whether termites have spread within, and it is difficult to take prompt effective action. In addition, since the system is installed and operated in an exposed state for a long period of time, it may be ineffective or damaged, resulting in a loss of function. Furthermore if the system is installed near a cultural site, it may affect the aesthetic environment of the site. In this study, we created a detection system that uses wood, cellulose, magnets, and magnetic sensors to determine whether termites have entered the area. The data was then transferred to a low power LoRa Network which displayed the results without the necessity of visiting the site. The wood was made in the shape of a pile, and holes were made from the top to the bottom to make it easier for termites to enter and produce a cellulose sample. The cellulose sample was made in a cylindrical shape with a magnet wrapped in cellulose and inserted into the top of a hole in the wood. Then, the upper part of the wood pile was covered with a stopper to prevent foreign matter from entering. It also served to block external factors such as light and rainfall, and to create an environment where termites could add cellulose samples. When the cellulose was added by the termites, a space was created around the magnet, causing the magnet to either fall or tilt. The magnetic sensor inside the stopper was fixed on the top of the cellulose sample and measured the change in the distance between the magnet and the sensor according to the movement of the magnet. In outdoor experiments, 11 cellulose samples were inserted into the wood detection system and the termite inflow was confirmed through the movement of the magnet without visiting the site within 5 to 17 days. When making further improvements to the function and operation of the system it in the future, it is possible to confirm that termites have invaded without visiting the site. Then it is also possible to reduce damage and fruiting due to product exposure, and which would improve the condition and appearance of cultural properties.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.2
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• pp.81-94
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• 2005

The purpose of this study is to test the applicability of landscape metrics for quantifying and monitoring the landscape structure in the Geumho River watershed, which has undergone heavy environmental disturbances. Landscape metrics were computed from land cover maps(1985, 1999) for the forest patches. The number of variables were reduced from 12 metrics to 3 factors through factor analysis. These factors accounted for above 91% of the variation in the original metrics. We also determined the relative effects of land development on the changes of forest landscape structure using multiple linear regression analysis. At the forest patches, the conversion of forest to urban areas and agriculture resulted in increased fragmentation. Patch area and patch size decreased. and patch density increased as a result of the conversion of forest to agriculture($R^2=0.696$, p<0.01). The heterogeneity of patch size and complexity of patch shape mainly decreased as a result of the conversion of forest to urban areas($R^2=0.405$, p<0.01). The density of core area and edge showed the tendency increase, but there was no relationship with the conversion of forest to urban area and agriculture The future research will be needed to analyze correlations between landscape structures and specific environmental and socioeconomic landscape functions.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.4
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• pp.334-341
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• 2003

When the pressure tubes(f are in contact with the calandria tube(CT) in the pressurized heavy water reactor(PHWR), the temperature difference between inner and outer wall of W results in a thermal diffusion of hydrogen (deuterium) and hydride blisters are formed on the outer surface of PT. Because the hydride blisters and zirconium matrix are acoustically continuous, it is not easy to distinguish the blisters from the matrix with conventional ultrasonic method. An ultrasonic velocity ratio method was developed to detect small hydride blisters on the zirconium pressure tube. Hydride blisters were grown in the PT specimen using a steady state thermal diffusion device. The flight times of longitudinal echo and reflected shear echo from the outer surface were measured accurately. The velocity ratio of the longitudinal wave to the shear wave was calculated and displayed using contour plot. Compared to the conventional flight time method of longitudinal wave, the velocity ratio method shows superior sensitivity to detect smaller blisters as well as better images for the blister shapes. Detectable limit of the outer shape of the hydride blisters was conservatively estimated as $500{\mu}m$, with the same specifications of ultrasonic transducer used in the actual PHWR pressure tube inspection.