• Journal of Radiation Protection and Research
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• v.49 no.1
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• pp.29-39
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• 2024

Background: The gamma emission tomography (GET) device has been reported a reliable technique to inspect partial defects within spent nuclear fuel (SNF) of pin-by-pin level. However, the existing GET devices have low accuracy owing to the high attenuation and scatter probability for SNF inspection condition. The purpose of this study is to design and optimize a Yonsei single-photon emission computed tomography version 2 (YSECT.v.2) for fast inspection of SNF in water storage by acquisition of high-quality tomographic images. Materials and Methods: Using Geant4 (Geant4 Collaboration) and DETECT-2000 (Glenn F. Knoll et al.) Monte Carlo simulation, the geometrical structure of the proposed device was determined and its performance was evaluated for the ¹³⁷Cs source in water. In a Geant4-based assessment, proposed device was compared with the International Atomic Energy Agency (IAEA)-authenticated device for the quality of tomographic images obtained for 12 fuel sources in a 14 × 14 Westinghouse-type fuel assembly. Results and Discussion: According to the results, the length, slit width, and septal width of the collimator were determined to be 65, 2.1, and 1.5 mm, respectively, and the material and length of the trapezoidal-shaped scintillator were determined to be gadolinium aluminum gallium garnet and 45 mm, respectively. Based on the results of performance comparison between the YSECT.v.2 and IAEA's device, the proposed device showed 200 times higher performance in gamma-detection sensitivity and similar source discrimination probability. Conclusion: In this study, we optimally designed the GET device for improving the SNF inspection accuracy and evaluated its performance. Our results show that the YSECT.v.2 device could be employed for SNF inspection.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.205-215
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• 2024

Manually mapping fractures in construction stone mines is challenging, time-consuming, and hazardous. In this method, there is no physical access to all points. In contrast, digital image processing offers a safe, cost-effective, and fast alternative, with the capability to map all joints. In this study, two methods of detecting the trace of discontinuities using image processing in construction stone mines are presented. To achieve this, we employ two modified Hough transform algorithms and the degree of neighborhood technique. Initially, we introduced a method for selecting the best edge detector and smoothing algorithms. Subsequently, the Canny detector and median smoother were identified as the most efficient tools. To trace discontinuities using the mentioned methods, common preprocessing steps were initially applied to the image. Following this, each of the two algorithms followed a distinct approach. The Hough transform algorithm was first applied to the image, and the traces were represented through line drawings. Subsequently, the Hough transform results were refined using fuzzy clustering and reduced clustering algorithms, along with a novel algorithm known as the farthest points' algorithm. Additionally, we developed another algorithm, the degree of neighborhood, tailored for detecting discontinuity traces in construction stones. After completing the common preprocessing steps, the thinning operation was performed on the target image, and the degree of neighborhood for lineament pixels was determined. Subsequently, short lines were removed, and the discontinuities were determined based on the degree of neighborhood. In the final step, we connected lines that were previously separated using the method to be described. The comparison of results demonstrates that image processing is a suitable tool for identifying rock mass discontinuity traces. Finally, a comparison of two images from different construction stone mines presented at the end of this study reveals that in images with fewer traces of discontinuities and a softer texture, both algorithms effectively detect the discontinuity traces.

• Geophysics and Geophysical Exploration
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• v.27 no.2
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• pp.144-153
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• 2024

Recent research is increasingly focused on utilizing seismic waves for structure health monitoring (SHM). Specifically, seismic interferometry, a technique applied in geophysical surveys using ambient noise, is widely applied in SHM. This method involves analyzing the response of buildings to propagating seismic waves. This enables the estimation of changes in structural stiffness and the evaluation of the location and presence of damage. Analysis of seismic interferometry applied to SHM, along with case studies, indicates its highly effective application for assessing structural stability and monitoring building conditions. Seismic interferometry is thus recognized as an efficient approach for evaluating building integrity and damage detection in SHM and monitoring applications.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.3
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• pp.166-175
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• 2024

In this paper, the Window-Masking Method and HAT (Hardware Attached Top) CPU SoM (System on Module) are used to improve the performance and reduce the weight of the MANET (Mobile Ad-hoc Network) network synchronization system using time division redundancy. We propose converting it into a RISC-V based soft-core MCU and mounting it on an FPGA, a hardware accelerator. It was also verified through experiment. In terms of performance, by applying the proposed technique, the synchronization acquisition range is from -50dBm to +10dBm to -60dBm to +10dBm, the lowest input level for synchronization is increased by 20% from -50dBm to -60dBm, and the detection delay (Latency) is 220ns. Reduced by 43% to 125ns. In terms of weight reduction, computing resources (48%), size (33%), and weight (27%) were reduced by an average of 36% by replacing with soft-core MCU.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.192-198
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• 2023

This paper proposes an algorithm for autonomous mobile robots to effectively navigate obstacles. In order to detect obstacles infrared sensors and cameras are employed. The infrared sensor is utilized to calculate the distance to obstacles while the captured images from the camera are used to determine the width of obstacles. To compute obstacle width, binary image processing, contour detection, and the minimum area rectangle technique are employed. Using the distance to obstacles and obstacle width, the avoidance angle is calculated, and this angle is incorporated into steering control. The proposed obstacle avoidance algorithm was implemented on an autonomous robot, and experimental results demonstrated a maximum reduction in avoidance time by 8.5 seconds compared to using only infrared sensors when the obstacle width is 30cm.

• Tribology and Lubricants
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• v.40 no.4
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• pp.133-138
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• 2024

This study evaluates the structural safety of wind turbine blades, analyzes the behavior of composite laminate structures with and without defects, and assesses surface erosion wear. The NREL 5 MW standard is applied to assign accurate composite material properties to each blade section. Modeling and analysis of the wind turbine blades reveal stable behavior under individual load conditions (gravity, motor speed, wind speed), with the web bearing most of the load. Surface erosion wear analysis in which microparticle impacts are simulated on the blade coating shows a maximum stress and maximum displacement of 14 MPa and 0.02 mm, respectively, indicating good initial durability, but suggest potential long-term performance issues due to cumulative effects. The study examines defect effects on composite laminate structures to compare the stress distribution, strain, and stiffness characteristics between normal and cracked states. Although normal conditions exhibit stable behavior, crack defects lead to fiber breakage, high-stress concentration in the vulnerable resin layer, and decreased rigidity. This demonstrates that local defects can compromise the safety of the entire structure. The study utilizes finite element analysis to simulate various load scenarios and defect conditions. Results show that even minor defects can significantly alter stress distributions and potentially lead to catastrophic failure if left unaddressed. These findings provide valuable insights for wind turbine blade safety evaluations, surface protection strategies, and composite structure health management. The methodology and results can inform the design improvements, maintenance strategies, and defect detection techniques of the wind energy industry.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.77-89
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• 2024

Knee osteoarthritis (OA) is a very common musculoskeletal disorder worldwide. The assessment of knee osteoarthritis, which requires a rapid and accurate initial diagnosis, is determined to be different depending on the currently dispersed classification system, and each classification system has different criteria. Also, because the medical staff directly sees and reads the X-ray pictures, it depends on the subjective opinion of the medical staff, and it takes time to establish an accurate diagnosis and a clear treatment plan. Therefore, in this study, we designed the stenosis length measurement algorithm and Osteophyte detection and length measurement algorithm, which are the criteria for determining the knee osteoarthritis grade, separately using CNN, which is a deep learning technique. In addition, we would like to create a grading system that integrates and complements the existing classification system and show results that match the judgments of actual medical staff. Based on publicly available OAI (Osteoarthritis Initiative) data, a total of 9,786 knee osteoarthritis data were used in this study, eventually achieving an Accuracy of 69.8% and an F1 score of 76.65%.

• Particle and aerosol research
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• v.20 no.2
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• pp.35-45
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• 2024

This study demonstrated the applicability of laser-induced breakdown spectroscopy (LIBS) to determine elements (C, H, and O) and their ratios of aerosols, enabling to discriminate various types of carbonaceous aerosols. The elements of carbonaceous aerosols which were collected on Ag membrane filter under Argon environment were successfully detected by using the LIBS. The LIBS responses (emission lines of C, H, and O in the LIBS spectra) to increasing carbonaceous aerosols were evaluated. The sensitivity of emission lines varied with different elements. Limit of detection (LOD) values for C, H, and O elements for aerosols collected on the filter were found to be 3.17 ㎍, 0.15 ㎍, and 2.25 ㎍, respectively. The spectral data (elemental ratios) obtained using LIBS were in reasonable agreements with the nominal atomic ratios (H/C and O/C) of various carbonaceous aerosols. Further, LIBS spectra were investigated by using principal component analysis (PCA) method to identify types of various carbonaceous aerosols. Our results suggested the possibility of the LIBS technique to detect and/or to discriminate various carbonaceous aerosols and to determine their elemental ratios (H/C and O/C).

• Journal of Sensor Science and Technology
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• v.33 no.5
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• pp.288-297
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• 2024

Currently, numerous studies are being conducted on metal oxide semiconductor (MOS) gas sensors for hydrogen detection, using Palladium (Pd) and Pd-based alloy nanoparticles (NPs) owing to their hydrogen absorption ability. Furthermore, several studies have reported that Pd-Iridium (Ir) alloys possess high hydrogen absorption capabilities in their bulk state. However, Ir growth is limited to above 2 nm and it does not mix extensively with other metals. Furthermore, as the hydrogen absorption capacity decreases with the reduction in particle size, it is necessary to synthesize nanoparticles of an appropriate size. Therefore, the synthesis of Pd-Ir alloy NPs larger than 10 nm is challenging. In this study, we report the synthesis of Pd-Ir NPs with an average diameter of 19 nm using a hydrothermal technique for the first time and fabricated Pd-Ir alloy NPs through calcination at 500℃ in Ar and air. To confirm alloy formation and oxidation behavior, X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) were performed. In addition, we synthesized Pd-Ir@CeO₂ core-shell nanoparticles (CSNPs) as hydrogen gas-sensing materials. The Pd-Ir core was partially oxidized during heat treatment at 500℃ in air, and Pd-Ir@CeO₂ CSNPs were finally changed into Pd-Ir(alloy)/PdO-IrO₂@CeO₂ CSNPs, which exhibited higher sensitivity and selectivity toward H₂ gas compared to totally oxidized PdO-IrO₂@CeO₂ CSNPs and pure CeO₂ NPs. The enhanced gas-sensing performance was attributed to the hydrogen absorption effect of the Pd-Ir(alloy) NPs.

• Nuclear Engineering and Technology
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• v.56 no.10
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• pp.4423-4436
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• 2024

The development and assessment of pharmaceutical dosage forms make considerable use of gamma-scintigraphy. Gamma scintigraphy is an imaging technique that is integrated with CT to assess and evaluate the targeting of drugs to various delivery sites, the impact of treatment, and the severity of the disease. A small number of radioisotopes were tagged with the delivery system and emitted radiation can be visualized by the gamma camera which forms a 2-D image displaying the tissue-specific distribution of radioactivity. The isotopes that are used widely include Technetium-99 m (99Tc), Iodine (131I), Fluorodeoxyglucose (18F-FDG), Fluoromisonidazole (18F-FMISO) and Gallium (Ga67), Indium (111In). This review mainly covers different applications of gamma scintigraphy for the assessment of drug targeting via different routes to different organs and their visualization by gamma scintigraphy. The review mainly focuses assessment of drug targeting in the tumor tissue, thyroid gland, brain, pulmonary pathway, skin deposition, detection of renal impairment as well as cardiac diseases, drug release from formulations, drug deposition in arthritis, drug retention in the scalp, and behavior of formulation when administered via intra-vaginal route. Various pre-clinical and clinical studies were included in the review that demonstrates the importance and future of gamma scintigraphy in sensing drug delivery.