• International journal of advanced smart convergence
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• v.9 no.4
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• pp.184-191
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• 2020

With the emergence of the 4th Industrial Revolution, core technologies that will lead the 4th Industrial Revolution such as AI (artificial intelligence), big data, and Internet of Things (IOT) are also at the center of the topic of the general public. In particular, there is a growing trend of attempts to present future visions by discovering new models by using them for big data analysis based on data collected in a specific field, and inferring and predicting new values with the models. In order to obtain the reliability and sophistication of statistics as a result of big data analysis, it is necessary to analyze the meaning of each variable, the correlation between the variables, and multicollinearity. If the data is classified differently from the hypothesis test from the beginning, even if the analysis is performed well, unreliable results will be obtained. In other words, prior to big data analysis, it is necessary to ensure that data is well classified according to the purpose of analysis. Therefore, in this study, data is classified using a decision tree technique and a random forest technique among classification analysis, which is a machine learning technique that implements AI technology. And by evaluating the degree of classification of the data, we try to find a way to improve the classification and analysis rate of the data.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.1
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• pp.82-91
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• 2021

The topic of this paper was analyzed as "t -test" and "multiple regression analysis" for 303 helicopter pilot trainees from aviation schools in the county for "improvement of education through correlation analysis of helicopter pilots' situational awareness and education satisfaction." In addition to the factors for overcoming situational awareness and situational awareness, the level of satisfaction of the instructor and the level of satisfaction of the learning management system (LMS) is the confidence interval p<.05, 95%. It was analyzed to be significant at the level of 05, 95%. Therefore, it was analyzed that in order to improve the "quality of the instructor" in future education, institutional supplementation and "learning management system (LMS)" need to be established including VR and AR so that pilot trainees can use it at all times.

• Archives of Plastic Surgery
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• v.49 no.3
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• pp.339-345
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• 2022

Background Patients that undergo mastectomy for breast cancer with reconstruction may be prone to prolonged opioid use. As risk factors are not well-established, this article sought to better understand the risk factors that may be associated with this. Methods Patients that underwent breast reconstruction between 2010 and 2018 were identified in PearlDiver, a national insurance claims database. Patient demographics and comorbidities were elucidated, and various complications were then identified. Descriptive statistics as well as a multivariate analysis was used to evaluate the association of risk factors and complications. Results Breast reconstruction patients of 24,765 were identified from this database. Obesity, tobacco use, benzodiazepine use, and anticonvulsant use were all associated with prolonged opioid prescriptions greater than 90 days after both alloplastic and autologous reconstruction. Conclusion Prolonged opioid use continues to remain a topic of concern, and particularly in cancer patients that undergo breast reconstruction. Providers should be aware of potential risk factors for this to reduce this chance following breast reconstruction surgery.

• Journal of Korea Multimedia Society
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• v.24 no.7
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• pp.953-965
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• 2021

The research of combining virtual reality technology with the design elements of children's picture book education is a relatively new topic in virtual reality technology in recent years. Based on the combination of picture book design elements with virtual reality technology and the development of a children's picture book teaching game, this article analyzes the effectiveness of the application of virtual reality technology in children's teaching, and explores the usability of picture book design elements in teaching [1]. Through literature research methods, practical research methods and investigation research methods, this paper lucubrates the application of virtual reality technology in the design elements of children's picture book education so as to provide adequate theoretical and practical support for the research theme. The spatial positioning, vision, sound, and functional requirements of children's picture book games play a leading role in teaching. Practical statistics have proved that it is easier to promote children's mastery of teaching knowledge in a virtual environment. Moreover, use VR's game management function and setting function to solve the boringness of traditional education methods and the limitations of the teaching environment. The feasibility of game operation provides a virtual teaching platform system for children's education, and the teaching effect is remarkable.

• Asia-Pacific Journal of Business
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• v.12 no.4
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• pp.299-312
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• 2021

Purpose - The purpose of this study is to analyze Trade Structure after Korea and Colombia FTA, and identify its problems and suggest measures that can be taken by the government and corporations to reinforce economic cooperation. Design/methodology/approach - To improve the level of contribution of the study, an empirical analysis is necessary. However, due to limited data access, the study will approach the topic of trade relations between Korea and Colombia with various statistics and literature. Findings - First, there is an urgent need for changes in import-export goods between Korea and Colombia, as trade is focused on specific items. Second, although foreign direct investment from Korea to the Colombia is centered in manufacturing and wholesale & retail, there should be different investment strategies by industries. Third, it is necessary to reinforce commercial cooperation. Research implications or Originality - The Free Trade Agreement between Korea and Colombia entered into force in 2016. Under the agreement, both countries will eliminated all tariffs within ten years after it takes effect. Reinforcing economic cooperation with Colombia is extremely important for Korea in terms of entering and dominating Colombian market. However, there is still a lack of research on the Colombia, and corporations that aim to enter Colombian market face difficulties due to lack of information. This study analyzes the recent trends of problems of trade between Korea and Colombia and suggests solutions for boosting trade to provide proper strategic guidelines for Korea that are planning to expand to Colombian market.

• Journal of Korean Public Health Nursing
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• v.35 no.3
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• pp.356-367
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• 2021

Purpose: This study aimed to identify the confidence and educational needs of clinical nurses in care for the family of dying patients. Methods: The subjects of this study were 218 clinical nurses working at two tertiary general hospitals located in D city, Korea, and the data were collected through online questionnaires. The collected data were analyzed using descriptive statistics, t-test, analysis of variance (ANOVA), Scheffe test and 𝝌² test using the SPSS WIN 20.0 program. Results: 97.6% of clinical nurses recognized the need for family care for dying patients, but 76.7% had never received any education on family care for dying patients. The average score of dying patients' confidence in family care was 3.09. About 90% of clinical nurses were willing to participate in family nursing education for dying patients. The group with more than 5 years of clinical experience was significantly higher than the group with less than 5 years of clinical experience. Conclusion: This study recognized the necessity of family nursing for dying patients highly. It is necessary to develop and apply an educational program based on the education topic that recognizes the need highly.

• Journal of agricultural medicine and community health
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• v.48 no.3
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• pp.189-204
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• 2023

Objectives: The goals of this study are to exploring critical factors and methods to improve Korean Community Care through the cases of GyeongsangNamdo. Methods: For this study, we performed in-depth interviews with 90 people involved in Community Care services of 6 regions, and the collected data were analyzed. The collected data were analyzed utilizing NVivo12. In the end, we reconfirmed the process through Topic Modeling analysis. Results: We conducted descriptive statistics and qualitative data analysis collected through surveys and in-depth interviews. In the case of qualitative analysis, we extracted principle codes (Need, Lack, Absence), and sorted the contents into sub-categories. The response rate of 'Need to strengthen capabilities' was the highest, 'Need to communicate and share information' was the second, and 'Need for integrated operation and a control tower' was the third. Conclusion: As a result, we find the critical factors to improve Community Care. Based on them, we should conduct follow-up researches to propose concrete methods to apply to diverse regions.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1249-1252
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• 2022

In this paper, we propose a conceptual framework that identifies video frames in motion containing the movement of people and vehicles in traffic videos. The automatic selection of video frames in motion is an important topic in security and surveillance video because the number of videos to be monitored simultaneously is simply too large due to limited human resources. The conventional method to identify the areas in motion is to compute the differences over consecutive video frames, which has been costly because of its high computational complexity. In this paper, we reduced the overall complexity by examining only the keyframes (or I-frames). The basic assumption is that the time period between I-frames is rather shorter (e.g., 1/10 ~ 3 secs) than the usual length of objects in motion in video (i.e., pedestrian walking, automobile passing, etc.). The proposed method estimates the possibility of videos containing motion between I-frames by evaluating the difference of consecutive I-frames with the long-time statistics of the previously decoded I-frames of the same video. The experimental results showed that the proposed method showed more than 80% accuracy in short surveillance videos obtained from different locations while keeping the computational complexity as low as 20 % compared to the HM decoder.

• Asian Journal for Public Opinion Research
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• v.11 no.2
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• pp.145-162
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• 2023

This research investigates how users of Bilibili, a video sharing website based in China have responded to carbon neutrality. By conducting quantitative textual analyses on 3,311 comments on Bilibili using LDA topic extraction and content statistics, this research discovers that: (1) Bilibili users have assigned more weight to geopolitical topics (56.3%) than energy (22.0%) and environmental topics (21.7%). (2) When assessing carbon neutrality, Bilibili users considered geopolitical (53.8%) and energy factors (15.8%) more heavily than factors related to the class (9.2%), economy (8.9%), environment (8.7%), and definition (3.6%). (3) More Bilibili users had negative (64.6%) attitudes towards carbon neutrality, with only a small portion of them expressing positive (26.8%) and neutral (8.6%) attitudes. (4) Negative attitudes towards carbon neutrality were mainly driven by geopolitical concerns about the West's approach to China, other countries' free-riding on China's efforts and the West's manipulation of rules, doubts about the feasibility of energy transition and suspicion of capitalists exploiting consumers through this concept. This research highlights the geopolitical concerns behind the environmental attitudes of Chinese people, deepening our understanding to psychological constructs and crisis sensitivity of Chinese people towards environmental issues.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.89-108
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• 2023

This study provides a comprehensive analysis of recent studies conducted on the topic of nowcasting in order to enhance the accuracy and promptness of official statistical data. Furthermore, we propose an alternative approach involving the utilization of real-time data and its corresponding collection methods to effectively operate a real-time nowcasting model capable of accurately capturing the current economic condition. We explore high-frequency real-time data that can predict economic indicators in both the public and private sectors and propose a pipeline for data collection processing and modeling that is based on cloud platforms. Furthermore we validate the essential elements required for the implementation of real-time nowcasting, as well as their data management protocols to ensure the reliability and consistency needed for accurate forecasting of official statistical indicators.