• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.77-93
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• 2022

In this study, we present an algorithm that analyzes the risk by reflecting regional characteristics for factors affected by direct and indirect damage from heavy-snow. Factors affected by heavy-snow damage by 29 regions are selected as influencing variables, and the concept of sensitivity is derived through the relationship with the amount of damage. A snow damage risk prediction model was developed using a machine learning (XGBoost) algorithm by setting weather conditions (snow cover, humidity, temperature) and sensitivity as independent variables, and setting the risk derived according to changes in the independent variables as dependent variables.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.453-459
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• 2022

This study attempted to explore the realization and research direction of a successful metaverse environment in the future by analyzing international research trends of the metaverse using topic modeling. A total of 208 papers among WoS and ScienceDirect papers using metaverse as keywords were selected, and quantitative frequency analysis and topic modeling were performed. As a result, it was confirmed that research has rapidly increased after 2022. The main keywords of the research topics were 'second', 'life', 'learning', 'reality', 'metaverse', 'virtual', 'blockchain', 'nft', 'medical', 'avatar', etc. The topic keywords 'Second life & Education' and 'Virtual Reality & Medical' accounted for a large proportion of 57%, followed by 'Blockchain & Cryptocurrency', 'Avatar & Interaction', and 'Sensing and Device'. As a result of semantic analysis, current metaverse research is focused on application and utilization, and research on underlying technologies and devices is also active. Therefore, it is necessary to identify the commonalities and differences between domestic and foreign studies, and to study the application method considering the domestic environment. In addition, new jurisprudence research is more necessary along with predicting new problems. It is expected that the results of study will provide the right research direction for domestic researchers in the era of digital transformation and contribute to the realization of a digital society.

• Smart Structures and Systems
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• v.29 no.4
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• pp.599-616
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• 2022

Bridge displacement contains vital information for bridge condition and performance. Due to the limits of direct displacement measurement methods, the indirect displacement reconstruction methods based on the strain or acceleration data are also developed in engineering applications. There are still some deficiencies of the displacement reconstruction methods based on strain or acceleration in practice. This paper proposed a novel method based on long short-term memory (LSTM) networks to reconstruct the bridge dynamic displacements with the strain and acceleration data source. The LSTM networks with three hidden layers are utilized to map the relationships between the measured responses and the bridge displacement. To achieve the data fusion, the input strain and acceleration data need to be preprocessed by normalization and then the corresponding dynamic displacement responses can be reconstructed by the LSTM networks. In the numerical simulation, the errors of the displacement reconstruction are below 9% for different load cases, and the proposed method is robust when the input strain and acceleration data contains additive noise. The hyper-parameter effect is analyzed and the displacement reconstruction accuracies of different machine learning methods are compared. For experimental verification, the errors are below 6% for the simply supported beam and continuous beam cases. Both the numerical and experimental results indicate that the proposed data fusion method can accurately reconstruct the displacement.

• Educational Technology International
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• v.23 no.1
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• pp.67-96
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• 2022

Although blogs have been used in online learning environments with optimistic expectations, the distributed nature of blogs can pose some challenges. Currently, we do not have a robust collection of tested blogging strategies to help students interact more effectively with each other when blogs are used as a primary form of engagement in an online class. Thus, the purpose of the study was to test an early iteration of an instructional blogging strategy, "Featured Student Profiles," which is designed to help students become acquainted with each other better and encourage them to visit and comment on each other's blogs. Sixteen pre-service teachers who were enrolled in an online course in which student blogs are the primary medium of peer interactions, participated in the study. Using a design case approach, seven students participated in interviews and all student blog interactions were analyzed. Thematic analysis was applied to analyze the interview data and identify salient themes of students' blogging experiences overall under the study strategy. The findings indicated that students took the most direct and efficient path they experienced to complete the blog task. Their peer interaction patterns varied, but several shifted from random to targeted relationships as the semester progressed. Although all students perceived the strategy as a positive approach to peer awareness, there was no clear evidence of its effect on student interactions.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.130-130
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• 2023

제트류는 다양한 크기와 운동량의 에디가 복잡하게 혼합되어 이루어져 있으며, 이를 정확하게 모델링하고 이해하기 위해서는 제트류의 다양한 특성들을 잘 반영하여 연구를 수행해야 한다. 다양한 연구 수행 방법 중 수치해석 방법은 상대적으로 공간 및 시간적 비용이 적게 들어서 널리 사용되고 있다. 이러한 수치해석 방법에는 DNS(Direct Numerical Simulation), LES(Large Eddy Simulation), RANS(Reynolds Averaged Navier Stokes) 등이 있으며, 그중 LES는 난류 모델링을 사용하는 RANS 방법에 비해 더욱 정확한 흐름 모델링을 제공하는 장점이 있다. 이러한 LES는 대규모 에디는 직접 해석하면서, 일정 크기 이하의 에디는 모델링을 사용해 해석하는 것이 특징이다. 하지만, LES를 사용하기 위해서는 적절한 그리드 크기를 결정하는 것이 중요하며, 이는 모델의 정확성과 연산 비용에 큰 영향을 미친다. 하지만, 여전히 적절한 그리드 크기를 결정하는 것은 어려운 문제이다. 이러한 LES 모델링을 사용할 때 적절한 그리드 크기를 결정하기 위해서는 정확한 시간 평균 속도 변동을 연구하는 것이 앞서 선행되어야 한다. 따라서, 본 연구에서는 기계학습 기반 접근 방식을 사용하여 난류 제트 내 시간 평균 속도 변동을 예측하는 연구를 진행하였다. 즉, 난류 제트 역학을 이해하는 데 중요한 파라미터인 시간 평균 유속을 이용하여 시간 평균 속도 변동을 예측하는 데 초점을 맞추었다. 모델의 성능은 평균 제곱 오차와 R-제곱 등 다양한 지표를 사용하여 평가되었다.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.293-298
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• 2023

The military is facing a continuous decrease in personnel, and in order to cope with potential accidents and challenges in operations, efforts are being made to reduce the direct involvement of personnel by utilizing the latest technologies. Recently, the use of various sensors related to Manned-Unmanned Teaming and artificial intelligence technologies has gained attention, emphasizing the need for flexible utilization methods. In this paper, we propose four dataset construction methods that can be used for effective training of robots that can be deployed in military operations, utilizing not only RGB image data but also data acquired from IR image sensors. Since there is no publicly available dataset that combines RGB and IR image data, we directly acquired the dataset within buildings. The input values were constructed by combining RGB and IR image sensor data, taking into account the field of view, resolution, and channel values of both sensors. We compared the proposed method with conventional RGB image data classification training using the same learning model. By employing the proposed image data fusion method, we observed improved stability in training loss and approximately 3% higher accuracy.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.571-575
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• 2022

본 논문에서는 통계청에서 매월 작성되는 온라인쇼핑동향조사를 위해, 언어모델 전이학습 기반 분류모델 학습 방법론을 이용하여, 관세청 제공 전자상거래 수입 목록통관 자료를 처리하기 위해서 해외 직접 구매 상품군 분류 모델을 구축한다. 최근에 텍스트 분류 태스크에서 많이 이용되는 BERT 기반의 언어모델을 이용하며 기존의 색인어 정보 분석 과정이나 사례사전 구축 등의 중간 단계 없이 해외 직접 판매 및 구매 상품군을 94%라는 높은 예측 정확도로 분류가 가능해짐을 알 수 있다.

• The Journal of Industrial Distribution & Business
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• v.13 no.1
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• pp.1-9
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• 2022

Purpose: This study aims to find empirical evidence and clarity on the phenomenon of the direct and indirect effect of perceived behavioral control on fraud prevention through whistleblowing intention. This study also aims to understand the influence of organizational ethical culture moderating between whistleblowing intention and fraud prevention. Research design, data, methodology: The samples of this research are 236 respondents consisting of the Head of the Finance Subdivision and Head of the Reporting Planning Subdivision and the finance staff who were determined using the purposive sampling method. The data obtained were analyzed using the Structural Equation Modeling technique. Results: The study results show that perceived behavioral control positively and significantly affects whistleblowing intention. In addition, perceived behavioral control does not affect fraud prevention mediated by whistleblowing intention. Furthermore, organizational ethical culture moderates whistleblowing intention and has a positive and significant effect on fraud prevention. Conclusions: This study concludes that the phenomenon of scandal that often occurs on a television is not a habit that must be followed. It requires an active role from the community as a form of concern for whistleblowing. Futher researchers can add other construct variables, such as good corporate governance to assess the performance improvement of the organizational layers, both internally and externally

• Human Ecology Research
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• v.61 no.1
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• pp.1-13
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• 2023

Household chaos, represented by high levels of disorganization and instability in the home, has been linked with suboptimal outcomes for preschoolers. The aim of this study was to examine the roles that sleep problems and executive function play in the association between household chaos and preschoolers' aggression and prosocial behavior. The sample for the study consisted of 420 preschoolers and their mothers. The mothers provided reports on the level of chaos in the home and their preschoolers' sleep problems, executive function, and social behavior, including aggression and prosocial behavior. The data was analyzed using structural equation modeling. When preschoolers' sleep problems and executive function were included in the model as mediators, the results indicated that household chaos did not have direct effects on preschoolers' aggression and prosocial behavior. Such effects were instead serially mediated by preschoolers' sleep problems and executive function, respectively. The higher the degree of household chaos, the more preschoolers displayed sleep problems and deficits in executive function, resulting in more aggression and less prosocial behavior. The findings from this study emphasize the significance of reducing household chaos in order to reduce preschoolers' aggression and promote prosocial behavior. They also underscore the need to identify additional variables that mediate the impact of household chaos on preschoolers' social outcomes.

• Journal of the Daesoon Academy of Sciences
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• v.19
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• pp.81-98
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• 2005

Nepal's role in the expansion of Mahayana Buddhism beyond the Himalaya is very significant. Nepal became the center of Mahayana Buddhism after the Muslim invasion of Nalanda Mahavihara in the 1199 A.D., which she maintained almost for 300 years. During this period, Nepal had produced a large number of profound Buddhist scholars. Most of them were the teachers of eminent Tibetan Buddhists. Some of the Nepalese Gurus also has continued lineage in Tibet until now. During that time, every Tibetan had desire to go to Nepal for higher Buddhist learning. As a matter of fact, many Tibetans made arduous journey across the Himalaya to fulfill the dream. Tibetan studied various forms of tantra, precepts, logic, doctrine, Sutra, Sadhana, Doha, Charyagiti, meditation etc. under direct supervision of Nepalese teachers. Great Tibetan scholars such as Marpa, Rwa Lo, Chag Lo, Khon phu ba, Klog Lo, Gos Lo, and others were the product of Nepal's scholarly tradition. They have significant place in the history of Tibet. Nepalese scholars also frequently visited Tibet where they taught Buddhism in various monasteries. They also had major role in propagating tantra in Tibet. Tibetans firmly believe that it is not possible to attain enlightenment without practicing tantra. The contribution of Nepalese scholars was so profound that Tibet produced many eminent scholars who developed scholastic tradition in Tibet. But after 14th century, Nepal's scholarly tradition ceased to continue. Then after, Tibetans started to call them 'the dull'.