• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3874-3897
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• 2023

A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High-Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next-generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds-averaged Navier-Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.447-452
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• 2023

In this paper, gain enhancement of a double dipole quasi-Yagi antenna using a meanderline array structure was studied. A 4×1 meanderline array structure consisting of a meanderline conductor- shaped unit cell is located above the second dipole of the double dipole quasi-Yagi antenna. It was designed to have gain over 7 dBi in the frequency range between 1.70 and 2.70 GHz in order to compare the performance with the case using a conventional strip director. As a result of comparison, the average gain of the double dipole quasi-yagi antenna with the proposed meander line array structure was larger compared to the case with the conventional strip director. A double dipole quasi-Yagi antenna using the proposed meanderline array structure was fabricated on an FR4 substrate and its characteristics were compared with the simulation results. Experiment results show that the frequency band for a VSWR less than 2 was 1.55-2.82 GHz, and the frequency band for gain over 7 dBi was measured to be 1.54-2.83 GHz. The frequency bandwidth with gain over 7 dBi increased, and average gain also slightly increased, compared to the conventional case using a strip director.

• Applied Chemistry for Engineering
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• v.34 no.5
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• pp.522-528
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• 2023

In this work, adhesive tapes were prepared for the dicing process in semiconductor manufacturing. Compounds with different numbers of photoreactive groups (f = 1 to 3) were synthesized and incorporated into acrylic copolymers to formulate UV-curable acrylic adhesives. Structural confirmation of the synthesized photoreactive compounds (f = 2 or 3) was performed using nuclear magnetic resonance (NMR) spectroscopy. The introduction of the photoreactive compounds into the acrylic adhesive was accomplished by urethane reactions, and the successful synthesis of the UV-curable acrylic adhesive was verified by Fourier transform infrared (FT-IR) measurements. To evaluate the performance of the adhesive, the peel strength was evaluated before and after UV irradiation using a silicon wafer as a substrate. The adhesive exhibited high peel strength (~2000 gf/25 mm) before UV exposure, which was significantly reduced (~5 gf/25 mm) after UV exposure. Interestingly, the adhesive containing multifunctional photoreactive compounds showed the most significant reduction in peel strength. In addition, surface residue measurements by field emission scanning electron microscopy (FE-SEM) showed minimal surface residue (~0.2%) after UV exposure. Overall, these results contribute to the understanding of the behavior of UV-curable acrylic adhesives and pave the way for potential applications in semiconductor manufacturing processes.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.33 no.6
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• pp.294-302
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• 2023

Ni-Mn-Zn ferrite, Ni_0.5-xMn_xZn_0.5Fe₂O₄ (0 ≤ x ≤ 0.5), was synthesized using the sol-gel method to investigate the crystal structure, microstructure, magnetic properties, high-frequency characteristics, and electromagnetic (EM) wave absorption characteristics as a function of Mn substitution. As the Mn content increased, a continuous decrease in saturation magnetization (M_S) was observed with little change in coercivity (H_C). Samples for each composition (x) exhibited strong EM wave absorption performance with first and second strong EM wave absorption regions satisfying minimum reflection loss, RL_min < -40 dB in the 1.5~2.5, 6~11 GHz range, respectively. The EM wave absorption in Ni-Mn-Zn ferrite depends on magnetic loss, and adjusting µ' and µ'' spectra by Mn substitution or H field allows control of the EM wave absorption frequency.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.130-144
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• 2023

Recently, various positioning technologies are being researched based on signal-based positioning and image-based positioning to obtain accurate indoor location information. Among these, various studies are being conducted on image positioning technology that determines the location of a mobile terminal using images acquired through cameras and sensor data collected as needed. For video-based positioning, a method of determining indoor location is used by matching mobile terminal photos with virtual landmark images, and for this purpose, it is necessary to build indoor spatial information about various landmarks such as billboards, vending machines, and ATM machines. In order to construct indoor spatial information on various landmarks, a panoramic image in the form of a road view and accurate 3D survey results were obtained through c 13 buildings of the Electronics and Telecommunications Research Institute(ETRI). When comparing the 3D total station final result and the terrestrial lidar panoramic image coordinates, the coordinates and distance performance were obtained within about 0.10m, confirming that accurate landmark construction for use in indoor positioning was possible. By utilizing these terrestrial lidar achievements to perform 3D landmark modeling necessary for image positioning, it was possible to more quickly model landmark information that could not be constructed only through 3D modeling using existing as-built drawings.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.3
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• pp.245-256
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• 2022

The purpose of this study is to provide comprehensive insights on the current research trends in entrepreneurship based on topic modeling and keyword co-occurrence analysis. This study queried Web of Science database with 'entrepreneurship' and collected 14,953 research articles between 2002 and 2021. The study used R program for topic modeling and VOSviewer program for keyword co-occurrence analysis. The results of this study are as follows. First, as a result of keyword co-occurrence analysis, 5 clusters divided: entrepreneurship and innovation cluster, entrepreneurship education cluster, social entrepreneurship and sustainability cluster, enterprise performance cluster, and knowledge and technology transfer cluster. Second, as a result of the topic modeling analysis, 12 topics found: start-up environment and economic development, international entrepreneurship, venture capital, government policy and support, social entrepreneurship, management-related issues, regional city planning and development, entrepreneurship research, and entrepreneurial intention. Finally, the study identified two hot topics(venture capital and entrepreneurship intention) and a cold topic(international entrepreneurship). The results of this study are useful to understand current research trends in entrepreneurship research and provide insights into research of entrepreneurship.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Membrane Journal
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• v.34 no.1
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• pp.38-49
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• 2024

Wastewater treatment using membrane bioreactors has been extensively used to alleviate water shortage and pollution by improving the quality of the treated water discharged into the environment. However, membrane biofouling persistently holds back an MBR process by reducing the process efficiency. Herein, we synthesized carbon nanospheres (CNSs) with many hydrophilic oxygen groups and utilized them as an additive to prepare high-performance ultrafiltration (UF) membranes with hydrophilicity and porous pore structure. CNSs were found to form crescent-shaped pores on the membrane surface, increasing the mean surface pore size by about 40% without causing significant defects larger than bubble points, as the CNS content increased by 4.6 wt%. In addition, the porous pore structure of CNS composite membranes was also attributable to the CNS's isotropic morphologies and relatively low particle number density because the aforementioned properties contributed to preventing the polymer solution viscosity from soaring with the loading of CNS. However, too porous structure compromised the mechanical properties, such that CNS2.3 was the best from a comprehensive consideration including the pore structure and mechanical properties. As a result, CNS2.3 showed not only 2 times higher water permeability than CNS0 but also 5 times longer operation duration until membrane cleaning was required.

• Information Systems Review
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• v.24 no.2
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• pp.67-88
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• 2022

This study proposed a research model that can explain the usage intentions of users and non-users by considering the performance aspects of personal mobility and external environmental factors based on the SOR (Stimulus-Organism-Response) model, A survey was conducted targeting domestic users and non-users, and research models and hypotheses were verified through Partial Least Square (PLS) and Artificial Neural Network (ANN). As a result of the analysis, it was confirmed that the users' perceived satisfaction and perceived trust had a positive effect on their intention to use, and that perceived risk and environmental value had a significant relationship with perceived satisfaction and perceived trust. For non-users, it was found that there was a positive correlation between perceived satisfaction and intention to use, and it was verified that perceived risk and environmental value, like users, were significant antecedents of perceived satisfaction and perceived trust. Among the remaining variables, the perceived mobility of users and the perceived ease of use of non-users were respectively presented as important influencing factors on perceived satisfaction.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1764-1776
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• 2021

Objective: This study aimed to validate a deep learning-based fully automatic calcium scoring (coronary artery calcium [CAC]_auto) system using previously published cardiac computed tomography (CT) cohort data with the manually segmented coronary calcium scoring (CAC_hand) system as the reference standard. Materials and Methods: We developed the CAC_auto system using 100 co-registered, non-enhanced and contrast-enhanced CT scans. For the validation of the CAC_auto system, three previously published CT cohorts (n = 2985) were chosen to represent different clinical scenarios (i.e., 2647 asymptomatic, 220 symptomatic, 118 valve disease) and four CT models. The performance of the CAC_auto system in detecting coronary calcium was determined. The reliability of the system in measuring the Agatston score as compared with CAC_hand was also evaluated per vessel and per patient using intraclass correlation coefficients (ICCs) and Bland-Altman analysis. The agreement between CAC_auto and CAC_hand based on the cardiovascular risk stratification categories (Agatston score: 0, 1-10, 11-100, 101-400, > 400) was evaluated. Results: In 2985 patients, 6218 coronary calcium lesions were identified using CAC_hand. The per-lesion sensitivity and false-positive rate of the CAC_auto system in detecting coronary calcium were 93.3% (5800 of 6218) and 0.11 false-positive lesions per patient, respectively. The CAC_auto system, in measuring the Agatston score, yielded ICCs of 0.99 for all the vessels (left main 0.91, left anterior descending 0.99, left circumflex 0.96, right coronary 0.99). The limits of agreement between CAC_auto and CAC_hand were 1.6 ± 52.2. The linearly weighted kappa value for the Agatston score categorization was 0.94. The main causes of false-positive results were image noise (29.1%, 97/333 lesions), aortic wall calcification (25.5%, 85/333 lesions), and pericardial calcification (24.3%, 81/333 lesions). Conclusion: The atlas-based CAC_auto empowered by deep learning provided accurate calcium score measurement as compared with manual method and risk category classification, which could potentially streamline CAC imaging workflows.