• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.809-812
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• 2021

Air bubbles which may be generated during the PCB coating process can be a major cause of malfunction. so it is necessary to detect the bubbles in advance. In previous studies, candidates for bubbles were extracted using the brightness characteristics of bubbles, and the candidates were verified using CNN(Convolutional Neural Networks). In this paper, we propose a bubble detection method using a transfer learning-based CNN model. The VGGNet is adopted and sigmoid is used as a classification layer, and the last convolutional layer and classification layer are trained together when transfer learning is applied. The performance of the proposed method is F1-score 0.9044, which shows an improvement of about 0.17 compared to the previous study.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2743-2759
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• 2020

A detailed computational fluid dynamics (CFD) simulation analysis model was developed using ANSYS CFX 16.1 and analyzed to simulate the basic design and internal flow characteristics of a 180 MW small modular reactor (SMR) with a natural circulation flow system. To analyze the natural circulation phenomena without a pump for the initial flow generation inside the reactor, the flow characteristics were evaluated for each output assuming various initial powers relative to the critical condition. The eddy phenomenon and the flow imbalance phenomenon at each output were confirmed, and a flow leveling structure under the core was proposed for an optimization of the internal natural circulation flow. In the steady-state analysis, the temperature distribution and heat transfer speed at each position considering an increase in the output power of the core were calculated, and the conceptual design of the SMR had a sufficient thermal margin (31.4 K). A transient model with the output ranging from 0% to 100% was analyzed, and the obtained values were close to the T_hot and T_cold temperature difference value estimated in the conceptual design of the SMR. The K-factor was calculated from the flow analysis data of the CFX model and applied to an analysis model in RELAP5/MOD3.3, the optimal analysis system code for nuclear power plants. The CFX analysis results and RELAP analysis results were evaluated in terms of the internal flow characteristics per core output. The two codes, which model the same nuclear power plant, have different flow analysis schemes but can be used complementarily. In particular, it will be useful to carry out detailed studies of the timing of the steam generator intervention when an SMR is activated. The thermal and hydraulic characteristics of the models that applied porous media to the core & steam generators and the models that embodied the entire detail shape were compared and analyzed. Although there were differences in the ability to analyze detailed flow characteristics at some low powers, it was confirmed that there was no significant difference in the thermal hydraulic characteristics' analysis of the SMR system's conceptual design.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.20-29
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• 2021

This study aims to explore the issue of drones and crime in newspaper articles. BIG KINDS, an online news archive of the Korea Press Foundation, collected 1,213 newspaper articles that met the terms of "drone" and "crime" in 11 central and 28 regional comprehensive newspapers between January 1, 1990 and May 1, 2021. Among them, we perform keyword frequency, centrality analysis, network structure construction, CONCOR analysis, and density matrix analysis on 117 key keywords. According to the analysis, the main issues were classified into eight, and the report analysis on drones and crimes in newspaper articles showed that the government's policy-making and social problems on protecting people's privacy, preventing illegal filming, securing navigation safety, social security and resolution. This study attempts to expand the field of humanities and social studies related to drones and crime, and specifically suggests the current status and counterplan against drone-related crimes as policy implications and media implications.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.2
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• pp.61-72
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• 2022

Purpose : This study aimed to identify the educational effects of the International Development Cooperation and Healthcare course from 2018 to 2020. Methods : Changes in awareness of international development cooperation (understanding international development cooperation as well as government Official Development Assistance [ODA], thoughts on aid, and thoughts on government's aid scale) were analyzed using web-based surveys. The pre-course survey was conducted 1-2 weeks before the semester started, and the post-course survey was conducted 1-2 weeks after the semester ended. All data were analyzed using the SPSS 26.0 program, and statistical significance was set at p< .05. Results : A total of 314 people participated in the survey before taking the course, and 286 people participated in the survey after taking the course. Analysis of the changes in students' awareness of international development cooperation showed that all items (understanding international development cooperation and government ODA, as well as having thoughts on aid and government's aid scale) were improved. Regarding changes in awareness according to general characteristics, thoughts on aid were statistically significant according to all characteristics except for 2018. Regarding government's aid scale, awareness scores increased after taking the course in students who majored in healthcare, fine arts and athletics, broadcasting and media studies, and digital contents. Conclusion : This study showed that changes in awareness of international development cooperation were largest in second-year students. Compared to changes regarding international development cooperation, government ODA, and thoughts on aid, changes regarding thoughts on government's aid scale were minor. In the future, it is necessary to develop class content suitable for the first-year level and to supplement and operate content that can change the way of thinking on government's aid scale.

• Informatization Policy
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• v.29 no.4
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• pp.3-25
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• 2022

The governance structure of public broadcasters is the hottest topic in domestic media policy. This study examines the flow of discussions by period by synthesizing the research literature on the governance structure of domestic public broadcasting since 2000. As a result, active discussion on the governance structure of public broadcasting was confirmed to have appeared following the conservative governments after 2008, derived from the "crisis theory of public broadcasting." In addition, the discussion was conducted centered on the public values of public broadcasting and direction of system improvement, political independence of public broadcasting, composition of the board of directors, and presidential election system. This study suggested that future discussions on the governance structure of public broadcasting should expand the existing discussion of political independence to encompass the values, responsibilities, and systems of public broadcasting that presuppose citizen participation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.51-58
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• 2023

The purpose of this study is to identify various variables that affect the intention to use the metaverse, which has recently attracted attention. In particular, while previous studies have focused only on the variables that have a positive effect on the spread of the metaverse, this study tried to examine both the use and resistance perspectives by examining the psychological variables of consumers who reject specific changes, such as innovation resistance. By constructing consumer characteristics and innovation characteristic variables that affect innovation diffusion, the relationship between innovation resistance, attitude toward the metaverse, and intention to use the metaverse was examined. As a result of the study, it was found that innovation propensity, social image, and conformity had a negative effect on resistance to the metaverse. In addition, innovation propensity, social image, suitability, relative advantage, complexity, and observability mediate innovation resistance and attitudes toward the metaverse, and were finally revealed as variables that have positive or negative influences on the intention to use the metaverse.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.4
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• pp.359-370
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• 2022

Objective: This study is intended to design a commercially available passive sampler and conduct performance test on its use as a media for evaluating a working environment. Methods: This study was conducted to select adsorbents, design models, and evaluate storage stability and sampling rates for the development of new types of passive samplers. Results: The impurity detection, adsorbent capacity and breakthrough volume of five types of activated carbon were tested for selection of an adsorbent. One product was selected in consideration of the efficiency of purchase. A number of passive samplers were designed in a radial style and a badge style using plastic as a material. The final two prototypes were made using molds or 3D printing. For the storage stability evaluation, samples were stored at different temperature for 1~21 days and then analyzed. Most of the chemicals had excellent storage stability when refrigerated. However, some chemicals such as dichloromethane and methyl ethyl ketone need to be analyzed as soon as possible after sampling. Conclusion: In this study, new types of passive samplers for 66 chemical compounds were developed. The evaluation of storage stability and sampling rates showed different results depending on the properties of the chemical substance. For some chemicals such as methyl ethyl ketone and dimethylformamide, activated carbon is inappropriate as an absorbent. In future studies, additional experiments are required on chemicals that are difficult to collect with activated carbon.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.9
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• pp.381-390
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• 2022

Influenced by a culture that prefers non-face-to-face activity during the COVID-19 pandemic, chatbot usage is accelerating. Chatbots have been used for various purposes, not only for customer service in businesses and social conversations for fun but also for mental health. Chatbots are a platform where users can easily talk about their depressed moods because anonymity is guaranteed. However, most relevant research has been on social media data, especially Twitter data, and few studies have analyzed the commercially used chatbots data. In this study, we identified the characteristics of depressive discourse in user-chatbot interaction data by analyzing the chats, including the word 'depress,' using the topic modeling algorithm and the text-mining technique. Moreover, we compared its characteristics with those of the depressive moods in the Twitter data. Finally, we draw several design guidelines and suggest avenues for future research based on the study findings.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.77-84
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• 2022

The purpose of this study is to confirm the influence of E-service quality of fresh product quality, logistics quality, and website quality on customer satisfaction and repurchase intentions. For the analysis, we used SPSS 23.0 to perform multiple regression analysis with 284 people who have purchased fresh food from China E-Services. The research results show that the better the E-service quality, the more positive (+) impact it has on customer satisfaction. In the relationship between E-service quality and purchase intention, customer satisfaction has a media effect. Through the analysis of the results, in order to improve customer satisfaction, it is necessary to focus on the quality of fresh food, provide excellent logistics, and allow customers to use convenient websites. This study only studies the general environment of E-services in the fresh food market, and will recommend specific implementation for one company in the future.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.487-498
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• 2022

Depth map is an image that contains distance information in 3D space on a 2D plane and is used in various 3D vision tasks. Many existing depth estimation studies mainly use narrow FoV images, in which a significant portion of the entire scene is lost. In this paper, we propose a technique for generating 360° omnidirectional RGBD images from a sparse set of narrow FoV images. The proposed generative adversarial network based image generation model estimates the relative FoV for the entire panoramic image from a small number of non-overlapping images and produces a 360° RGB and depth image simultaneously. In addition, it shows improved performance by configuring a network reflecting the spherical characteristics of the 360° image.