• Therapeutic Science for Rehabilitation
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• v.10 no.4
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• pp.53-63
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• 2021

Objective : This study aimed to develop a Korean version of the Flow State Scale for Occupational Task (K-FSSOT), to measure the level of a flow experience of a subject in occupational therapy activities. Methods : To develop a measure of K-FSSOT, validity and reliability were verified through a systematic development process. The validity was verified by calculating the content validity index (CVI) through the content validity of 10 occupational therapists and a question-and-answer survey of 20 patients. Reliability was verified by investigating the internal consistency and examination-re-test reliability of 33 patients. Results : The item-CVI for each question in the content feasibility study was .90 to 1.00, and the scale-CVI, which is the average of the whole item, was found to be appropriate at .97. The verification of reliability indicated that the intrinsic value of the entire question was high at .855, and the test-retest reliability value was high at .894 (p<.01), showing a high correlation, and very high reliability. Conclusion : K-FSSOT could be used as a useful tool to measure the level of a flow experience of the target in performing occupational therapy activities for occupational therapists concerned about the participation and flow experience of the target.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.159-165
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• 2022

The purpose of this study is to examine racism in the movie ≪Green Book≫ and to find solutions to racism through discussion with students. Set in 1962 in the United States, this film depicts the process of forming a good bond with the black pianist Dr. Shirley and the driver Tony in a racist society. This study utilized the subject of race, one of the subjects covered in the humanities class in the global era of S University in the second semester of 2021. This is because, since the outbreak of racism, the problem of racism has continued to arise in the current COVID-19 pandemic situation. Therefore, the researcher looked at racism and intercultural education as a theoretical background, and looked at cases of racism in movies and cases of racism that have occurred today. The history of racism and discrimination dates back to medieval Europe and was caused by religious conflicts and was attributed to white supremacy. As a solution to this racial discrimination, international organizations suggested intercultural education. And the reason why film was used in this study is because it aims to provoke students' interest and motivation for learning by targeting first-year university students called the digital native generation who were born and grew up with the Internet. In this study, students' solutions to racism were presented using discussion, and then the researcher's solutions were presented.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.1
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• pp.44-49
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• 2022

In this paper, we investigated current (I)- and voltage (V)-sweeping properties in a double-stack structure, Ge₂Sb₂Te₅/Ti/W-doped Ge₈Sb₂Te₁₁, a candidate medium for applications to multilevel phase-change memory. 200-nm-thick and W-doped Ge₂Sb₂Te₅ and W-doped Ge₈Sb₂Te₁₁ films were deposited on p-type Si(100) substrate using magnetron sputtering system, and the sheet resistance was measured using 4 point-probe method. The sheet resistance of amorphous-phase W-doped Ge₈Sb₂Te₁₁ film was about 1 order larger than that of Ge₂Sb₂Te₅ film. The I- and V-sweeping properties were measured using sourcemeter, pulse generator, and digital multimeter. The speed of amorphous-to-multilevel crystallization was evaluated from a graph of resistance vs. pulse duration (t) at a fixed applied voltage (12 V). All the double-stack cells exhibited a two-step phase change process with the multilevel memory states of high-middle-low resistance (HR-MR-LR). In particular, the stable MR state is required to guarantee the reliability of the multilevel phase-change memory. For the Ge₂Sb₂Te₅ (150 nm)/Ti (20 nm)/W-Ge₈Sb₂Te₁₁ (50 nm), the phase transformations of HR→MR and MR→LR were observed at t<30ns and t<65ns, respectively. We believe that a high speed and stable multilevel phase-change memory can be optimized by the double-stack structure of proper Ge-Sb-Te films separated by a barrier metal (Ti).

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.155-160
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• 2022

This paper intends to focus on the practical activities and historical significance of network art, that is, 'net art' as an artistic form that depends on network technology. This is because the appearance of net art, which constructs a new interactive art that cooperates and exchanges with each other beyond the boundaries of time and space, can be a contemporary alternative in overcoming the limitations of traditional art. Another important research area to be considered in this paper is net art curating, as well as considering the significance of net art in art history. As new media art that is defined as a 'process' rather than a complete object, net art is a digital art that requires functions such as aesthetic appropriation, dissemination, and mediation performed online, unlike physical presentations with high perfection in exhibition halls. It is accompanied by a new social and cultural curatorial. This appearance requires both artists and curators to reorganize the strategy that net art curating in technoculture should have. Therefore, this paper attempts to question the creative strategies of net art in the wave of globalization in the 21st century, and to examine the artistic meaning and critical value of the experimental net art curatorial method that emerged through the realm of new technology and media. For this purpose, this paper demonstrated key examples of net art works and exhibition projects that started with Fluxus in the 1960s and are spreading all over the world in the 2000s.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.353-376
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• 2023

The global pandemic and the development of virtual and augmented reality technologies have led a metaverse boom that enables a lot of interactions in virtual worlds, and is being utilized in various fields such as business, government, and education etc. Despite the growing interest in the metaverse, its scope and definition are still unclear and the concept is still evolving, making it challenging to establish its governance. Governmental entities are also investing intensively in public metaverses to make public value and promote social welfare, but they are underutilized due to lack of systematic governance. Therefore, in this study, we propose a public metaverse governance framework and identify the relative importance of the factors. Furthermore, since a public metaverse should be accessible to anyone who wants to use, we explore the factors of shadow work and examine the ways to minimize it. Based on the socio-technical system theory, we derived public metaverse governance factors from previous literature and topic modeling and then generate a framework with 23 factors through expert interviews. We then tested relative priority of the factors using the analytic hierarchical process (AHP) from the experts. As a result, the top five overall rankings are: 'roles and responsibilities', 'standardization/modularization', 'collaboration and communication', 'law and policies', and 'availability/accessibility'. The academic implications of this study are that it provides a comprehensive framework for public metaverse governance, and then the practical implications include suggesting prioritized considerations for metaverse operations in the public sector.

• Journal of the Korean Society for information Management
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• v.39 no.4
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• pp.23-48
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• 2022

The purpose of this study is to investigate the flow of domestic information literacy education research using keyword network analysis and topic modeling and to explore the direction of information literacy education in the future. For this reason, 306 academic papers related to information literacy education published in academic journals of the library and information science field in Korea were chosen. And through the preprocessing process for abstracts of the paper, total keyword appearance frequency, keyword appearance frequency by period, and keyword simultaneous occurrence frequency were analyzed. Subsequently, keyword network analysis analyzed the degree centrality, between centrality, and eigenvector centrality of keywords. Using structural topic modeling analysis, 15 topics -curriculum, information literacy effect, contents of information literacy education, school library education, information media literacy, information literacy ability evaluation index, library anxiety, public library program, health information literacy ability, digital divide, library assisted instruction improvement, research trend, information literacy model, and teacher role-were derived. In addition, the trend of topics by year was analyzed to confirm the change in relative weight by topic. Based on these results, the direction of information literacy education and the suggestions for follow-up research were presented.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.87-98
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• 2022

In recent years, frequent localized heavy rainfalls, which have a lot of rainfall in a short period of time, have been increasingly causing flooding damages. To prevent damage caused by localized heavy rainfalls, Hydrological Quantitative Precipitation Forecast (HQPF) was developed using the Local ENsemble prediction System (LENS) provided by the Korea Meteorological Administration (KMA) and Machine Learning and Probability Matching (PM) techniques using Digital forecast data. HQPF is produced as information on the impact of heavy rainfall to prepare for flooding damage caused by localized heavy rainfalls, but there is a tendency to overestimate the low rainfall intensity. In this study, we improved HQPF by expanding the period of machine learning data, analyzing ensemble techniques, and changing the process of Probability Matching (PM) techniques to improve predictive accuracy and over-predictive propensity of HQPF. In order to evaluate the predictive performance of the improved HQPF, we performed the predictive performance verification on heavy rainfall cases caused by the Changma front from August 27, 2021 to September 3, 2021. We found that the improved HQPF showed a significantly improved prediction accuracy for rainfall below 10 mm, as well as the over-prediction tendency, such as predicting the likelihood of occurrence and rainfall area similar to observation.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.3-12
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• 2022

Image deblurring aims to remove image blur, which can be generated while shooting the pictures by the movement of objects, camera shake, blurring of focus, and so forth. With the rise in popularity of smartphones, it is common to carry portable digital cameras daily, so image deblurring techniques have become more significant recently. Originally, image deblurring techniques have been studied using traditional optimization techniques. Then with the recent attention on deep learning, deblurring methods based on convolutional neural networks have been actively proposed. However, most of them have been developed while focusing on better performance. Therefore, it is not easy to use in real situations due to the speed of their algorithms. To tackle this problem, we propose a novel deep learning-based deblurring algorithm that can be operated in real-time on HD resolution. In addition, we improved the training and inference process and could increase the performance of our model without any significant effect on the speed and the speed without any significant effect on the performance. As a result, our algorithm achieves real-time performance by processing 33.74 frames per second at 1280×720 resolution. Furthermore, it shows excellent performance compared to its speed with a PSNR of 29.78 and SSIM of 0.9287 with the GoPro dataset.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.129-148
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• 2023

Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.

• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.4
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• pp.242-248
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• 2022

Recently, through the development of CAD/CAM technology, it is also being used for fabricating dentures. Compared to conventional methods, when digital dentures are fabricated, the fabrication process is facilitated, and the number of visits to hospitals is reduced and errors are reduced. In this case, the vertical dimension was increased using a CAD program in a patient who needed vertical dimension recovery due to the use of old dentures, and the final denture was fabricated using a monolithic disc through the milling method. The centric relation was recorded using existing dentures, and using the information from the intraoral scan and the existing denture model scan, a trial denture was fabricated and delivered to the patient to evaluate the midline and occlusion. Based on the evaluation of the trial denture, the final denture was fabricated using a milling method and a monolithic disc, and the final denture showed satisfactory results functionally and aesthetically.