• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.1834-1845
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• 2021

Liquid lead-bismuth cooled fast reactor is one of the most promising reactor types among the fourth-generation nuclear energy systems. The flow and heat transfer characteristics of lead-bismuth eutectic (LBE) are completely different from ordinary fluids due to its special thermal properties, causing that the traditional Reynolds analogy is no longer recommended and appropriate. More accurate turbulence flow and heat transfer model for the liquid metal lead-bismuth should be developed and applied in CFD simulation. In this paper, a specific CFD solver for simulating the flow and heat transfer of liquid lead-bismuth based on the k - 𝜀 - k_𝜃 - 𝜀_𝜃 model was developed based on the open source platform OpenFOAM. Then the advantage of proposed model was demonstrated and validated against a set of experimental data. Finally, the simulation of LBE turbulent flow and heat transfer in a 7-pin wire-wrapped rod bundle with the k - 𝜀 - k_𝜃 - 𝜀_𝜃 model was carried out. The influence of wire on the flow and heat transfer characteristics and the three-dimensional distribution of key thermal hydraulic parameters such as temperature, cross-flow velocity and Nusselt number were studied and presented. Compared with the traditional SED model with a constant Pr_t = 1.5 or 2.0, the k - 𝜀 - k_𝜃 - 𝜀_𝜃 model is more accurate on predicting the turbulence flow and heat transfer of liquid lead-bismuth. The average relative error of the k - 𝜀 - k_𝜃 - 𝜀_𝜃 model is reduced by 11.1% at most under the simulation conditions in this paper. This work is meaningful for the thermal hydraulic analysis and structure design of fuel assembly in the liquid lead-bismuth cooled fast reactor.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.65-77
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• 2018

It is very important to understand the factors affecting the occurrence of vacant houses in research on them. The purpose of this study is to analyze the factors affecting the rural vacancy occurrence. This study set 121 research areas and selected eight independent variables (Aged house rate, housing transaction rate, house diffusion ratio, local extinction index, net migration rate, regional aging index, the ratio of the number of employees to population and financial independence rate) and one dependent variable (vacant house rate). As a result of the study, first, both Model 1 for the entire general agricultural fishing village area and Model 2 for the county (gun) area were statistically significant, there was no problem with the independence of residual. Second, local extinction index and aged house rate had a statistically significant positive (+) relationship in both Model 1 and Model 2. Third, diffusion ratio of house had a statistically significant positive (+) relationship only in Model 1, and housing transactions rate had a statistically significant negative (-) relationship in Model 2. The implications of the study were drawn as follows: First, the increase in the house diffusion ratio without growth in households and population suggests the increase of the probability of the vacancy occurrence in the area, and the higher the aged house rate, the higher the probability of the vacancy occurrence. Second, for the revitalization of housing transactions, it is necessary to have an investment inflow in the area for mid- to long-term development. Third, local extinction index has a significant relationship with vacant house rate, it is necessary to introduce a local revitalization policy from a long-term perspective for the permanence of the area.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.909-917
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• 2017

In this study, we investigated the relationship between catches of yellowtail and water temperature at the set net fisheries of Gyeongsangbuk-do (Gyeongbuk) and Gangwon-do (Gangwon) off the east coast of Korea from May-November, 1980-2010. We also analyzed the water temperature and fluctuation of catches during the northward moving period (May-August) and southward moving period (September-November) using NOAA satellite images. Although the total catches fluctuated year by year, catches increased during the southward moving period when the water alongside the coast warmed. Yellowtail catches during the southward period in fall were higher than those during the northward period in spring or summer. The catch when the water temperature decreased was larger in Gyeongbuk than in Gangwon for all periods However, the catch when the water temperature increased was much larger in Gangwon than in Gyeongbuk. This indicates that high summer temperatures (> $25^{\circ}C$) affected the coast of Gangwon, with high water temperature ($20^{\circ}C$) maintained in the region during fall. Therefore, the increased catch in Gangwon was due to longer yellowtail presence caused by increased water temperature.

• Korean Journal of Plant Resources
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• v.34 no.5
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• pp.462-469
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• 2021

Maesa japonica (Thunb.) Moritzi & Zoll. is a rare evergreen shrub that occurs in west Gotjawal, Jeju island, Korea. This study was conducted to investigate effects of an artificial shading on flowering and growth characteristics of M. japonica seedlings. The level of shading had been set to be 35%, 55% and 75% using shading net. The stage of flowering and flowering ratio, seedling height, the number of leaves and stems, leaf area were measured. Flowering timings were delayed by shading. The number of flowering seedlings per plot and inflorescences per seedling were the most in 55% shading level. Tendency of decreased seedling height with increased shading level was shown. The number of leaves and stems were the fewest values in 75% shading level. The increased biomass with decreased shading level was statistically significant. Aboveground and underground biomass were 2.1 and 1.7 times higher in shading 35% than in shading 75%, respectively. Meanwhile, all seedlings in non-shading plots were dead in winter. Such might be speculated as results of the light stress. As a result, we conclude that M. japonica vitally demands the shading for growth and the optimal shading levels for growth and flowering are 35% and 55%, respectively.

• The Journal of Industrial Distribution & Business
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• v.12 no.1
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• pp.47-62
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• 2021

Purpose: Our purpose in this study was to examine the strategies for the development of watermelon industry using unstructured big data analysis. That is, this study was to look the change of issues and consumer's perception about watermelon using big data and social network analysis and to investigate ways to strengthen the competitiveness of watermelon industry based on that. Methodology: For this purpose, the data was collected from Naver (blog, news) and Daum (blog, news) by TEXTOM 4.5 and the analysis period was set from 2015 to 2016 and from 2017-2018 and from 2019-2020 in order to understand change of issues and consumer's perception about watermelon or watermelon industry. For the data analysis, TEXTOM 4.5 was used to conduct key word frequency analysis, word cloud analysis and extraction of metrics data. UCINET 6.0 and NetDraw function of UCINET 6.0 were utilized to find the connection structure of words and to visualize the network relations, and to make a cluster of words. Results: The keywords related to the watermelon extracted such as 'the stalk end of a watermelon', 'E-mart', 'Haman', 'Gochang', and 'Lotte Mart' (news: 015-2016), 'apple watermelon', 'Haman', 'E-mart', 'Gochang', and' Mudeungsan watermelon' (news: 2017-2018), 'E-mart', 'apple watermelon', 'household', 'chobok', and 'donation' (news: 2019-2020), 'watermelon salad', 'taste', 'the heat', 'baby', and 'effect' (blog: 2015-2016), 'taste', 'watermelon juice', 'method', 'watermelon salad', and 'baby' (blog: 2017-2018), 'taste', 'effect', 'watermelon juice', 'method', and 'apple watermelon' (blog: 2019-2020) and the results from frequency and TF-IDF analysis presented. And in CONCOR analysis, appeared as four types, respectively. Conclusions: Based on the results, the authors discussed the strategies and policies for boosting the watermelon industry and limitations of this study and future research directions. The results of this study will help prioritize strategies and policies for boosting the consumption of the watermelon and contribute to improving the competitiveness of watermelon industry in Korea. Also, it is expected that this study will be used as a very important basis for agricultural big data studies to be conducted in the future and this study will offer watermelon producers and policy-makers practical points helpful in crafting tailor-made marketing strategies.

• The korean journal of orthodontics
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• v.52 no.1
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• pp.3-19
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• 2022

Objective: The purpose of this study was to investigate the accuracy of one-step automated orthodontic diagnosis of skeletodental discrepancies using a convolutional neural network (CNN) and lateral cephalogram images with different qualities from nationwide multi-hospitals. Methods: Among 2,174 lateral cephalograms, 1,993 cephalograms from two hospitals were used for training and internal test sets and 181 cephalograms from eight other hospitals were used for an external test set. They were divided into three classification groups according to anteroposterior skeletal discrepancies (Class I, II, and III), vertical skeletal discrepancies (normodivergent, hypodivergent, and hyperdivergent patterns), and vertical dental discrepancies (normal overbite, deep bite, and open bite) as a gold standard. Pre-trained DenseNet-169 was used as a CNN classifier model. Diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis, t-stochastic neighbor embedding (t-SNE), and gradient-weighted class activation mapping (Grad-CAM). Results: In the ROC analysis, the mean area under the curve and the mean accuracy of all classifications were high with both internal and external test sets (all, > 0.89 and > 0.80). In the t-SNE analysis, our model succeeded in creating good separation between three classification groups. Grad-CAM figures showed differences in the location and size of the focus areas between three classification groups in each diagnosis. Conclusions: Since the accuracy of our model was validated with both internal and external test sets, it shows the possible usefulness of a one-step automated orthodontic diagnosis tool using a CNN model. However, it still needs technical improvement in terms of classifying vertical dental discrepancies.

• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.267-275
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• 2020

Even ordinary-looking plays can have a profound meaning. Based on this assumption, Eugene Pink (1960) has established an analytical model of play with five elements, namely "delight", "meaning", "community", "rules" and "tools." It was an effort to reflect on the true meaning of play beyond the cortical entertaining nature of play. In this study, it was carried out that all the texts containing images and performance from the EBS character "Pengsu" were selected, since he emerged as a new star in 2019. And also his play structure was analyzed by applying the Pink's model. As a result, Pengsu's play structure was confirmed to be systematic and complete as a play prototype because it was well-organized with five elements of play. It was regarded as a successful character that skillfully attracts participants to the play world. Among the components of the play, "fun" was found to be his funny appearance, sudden and unconventional behavior, "meaning" was the elimination of authoritarianism, self-esteeming and energizing, "community" was a multi-platform media user who crossed off-on-line, analog-digital-line, "rules" was to set his concept fixed as a young stranger with an ego to unreveal his identity, and "tools" was shown as his character itself and continual discourse. It shows that until now, Pengsu has a social net function of quite spreading the positive meaning of encouragement and comfort, advice and guide, consideration and forgiveness, introspection and nirvana to all members of our society, including the youth who are struggling with uncertainty and anxiety by showing rather exaggerated and stimulating performance that precisely combines these play elements.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.339-352
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• 2023

Prediction of the time-related traits of pebble flow inside pebble-bed HTGRs is of great significance for reactor operation and design. In this work, an image-driven approach with the aid of a convolutional neural network (CNN) is proposed to predict the remaining time of initially loaded pebbles and the time interval of paired flow images of the pebble bed. Two types of strategies are put forward: one is adding FC layers to the classic classification CNN models and using regression training, and the other is CNN-based deep expectation (DEX) by regarding the time prediction as a deep classification task followed by softmax expected value refinements. The current dataset is obtained from the discrete element method (DEM) simulations. Results show that the CNN-aided models generally make satisfactory predictions on the remaining time with the determination coefficient larger than 0.99. Among these models, the VGG19+DEX performs the best and its CumScore (proportion of test set with prediction error within 0.5s) can reach 0.939. Besides, the remaining time of additional test sets and new cases can also be well predicted, indicating good generalization ability of the model. In the task of predicting the time interval of image pairs, the VGG19+DEX model has also generated satisfactory results. Particularly, the trained model, with promising generalization ability, has demonstrated great potential in accurately and instantaneously predicting the traits of interest, without the need for additional computational intensive DEM simulations. Nevertheless, the issues of data diversity and model optimization need to be improved to achieve the full potential of the CNN-aided prediction tool.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2139-2146
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• 2023

During reactor operation, the divertor must withstand unprecedented simultaneous high heat fluxes and high-energy neutron irradiation. The extremely severe service environment of the divertor imposes a huge challenge to the bonding quality of divertor joints, i.e., the joints must withstand thermal, mechanical and neutron loads, as well as cyclic mode of operation. In this paper, potassium-doped tungsten (KW) is selected as the plasma facing material (PFM), oxygen-free copper (OFC) as the interlayer, oxide dispersion strengthened copper (ODS-Cu) alloy as the heat sink material, and reduced activation ferritic/martensitic (RAFM) steel as the structural material. In this study, a vacuum brazing technology is proposed and optimized to bond Cu and ODS-Cu alloy with the silver-free brazing material CuSnTi. The most appropriate brazing parameters are a brazing temperature of 940 ℃ and a holding time of 15 min. High-quality bonding interfaces have been successfully obtained by vacuum brazing technology, and the average shear strength of the as-obtained KW/Cu and ODS-Cu alloy joints is ~268 MPa. And a fabrication route for manufacturing the flat-type divertor target based on brazing technology is set. For evaluating the reliability of the fabrication technologies under the reactor relevant condition, the high heat flux test at 20 MW/m² for the as-manufactured flat-type KW/Cu/ODS-Cu/RAFM mockup is carried out by using the Electron-beam Material testing Scenario (EMS-60) with water cooling. This paper reports the improved vacuum brazing technology to connect Cu to ODS-Cu alloy and summarizes the production route, high heat flux (HHF) test, the pre and post non-destructive examination, and the surface results of the flat-type KW/Cu/ODS-Cu/RAFM mockup after the HHF test. The test results demonstrate that the mockup manufactured according to the fabrication route still have structural and interfacial integrity under cyclic high heat loads.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.93-98
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• 2023

In paddy rice farming, water management is a critical task. To suppress weed emergence during the early stages of growth, fields are deeply flooded, and after transplantation, the water level is reduced to promote rooting and stimulate stem generation. Later, water is drained to prevent the production of sterile tillers. The adequacy of water supply is influenced by various factors such as field location, irrigation channels, soil conditions, and weather, requiring farmers to frequently check water levels and control the ingress and egress of water. This effort increases if the fields are scattered in remote locations. Automated irrigation systems have been considered to reduce labor and improve productivity. However, the net income from rice production in 2022 was about KRW 320,000/10a on average, making it financially unfeasible to implement high-cost devices or construct new infrastructure. This study focused on developing an IoT-Based irrigation valve that can be easily integrated into existing agricultural infrastructure without additional construction. The research was carried out in three main areas: Firstly, an irrigation valve was designed for quick and easy installation on existing agricultural pipes. Secondly, a power circuit was developed to connect a low-power Cat M1 communication modem with an Arduino Nano board for remote operation. Thirdly, a cloud-based platform was used to set up a server and database environment and create a web interface that users can easily access.