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이은서,배희철,김현종,한효녕,이용귀,손지연,Lee, E.S.,Bae, H.C.,Kim, H.J.,Han, H.N.,Lee, Y.K.,Son, J.Y. 한국전자통신연구원 2020 전자통신동향분석 Vol.35 No.1
Artificial intelligence (AI) is expected to bring about a wide range of changes in the industry, based on the assessment that it is the most innovative technology in the last three decades. The manufacturing field is an area in which various artificial intelligence technologies are being applied, and through accumulated data analysis, an optimal operation method can be presented to improve the productivity of manufacturing processes. In addition, AI technologies are being used throughout all areas of manufacturing, including product design, engineering, improvement of working environments, detection of anomalies in facilities, and quality control. This makes it possible to easily design and engineer products with a fast pace and provides an efficient working and training environment for workers. Also, abnormal situations related to quality deterioration can be identified, and autonomous operation of facilities without human intervention is made possible. In this paper, AI technologies used in smart factories, such as the trends in generative product design, smart workbench and real-sense interaction guide technology for work and training, anomaly detection technology for quality control, and intelligent manufacturing facility technology for autonomous production, are analyzed.
손지연,김현,이은서,박준희,Son, J.Y.,Kim, H.,Lee, E.S.,Park, J.H. 한국전자통신연구원 2021 전자통신동향분석 Vol.36 No.1
The future society will be changed through an artificial intelligence (AI) based intelligent revolution. To prepare for the future and strengthen industrial competitiveness, countries around the world are implementing various policies and strategies to utilize AI in the manufacturing industry, which is the basis of the national economy. Manufacturing AI technology should ensure accuracy and reliability in industry and should be explainable, unlike general-purpose AI that targets human intelligence. This paper presents the future shape of the "autonomous factory" through the convergence of manufacturing and AI. In addition, it examines technological issues and research status to realize the autonomous factory during the stages of recognition, planning, execution, and control of manufacturing work.
강민경,김소정,김유미,박수민,변고영,송은혜,신지혜,이은별,이은서,정진선,김건희,이수연 이화여자대학교 간호과학대학 2019 이화간호학회지 Vol.- No.53
Purpose: This study aimed to identify the relationship among sleep, resilience, and interpersonal relations of college students. Methods: Data were collected by using a structured questionnaire consisting of Korean Sleep Scale, Connor-Davidson Resilience Scale-10, and Relationship Change Scale between September 21st, 2018 to September 30th, 2018. Subjects were 185 college students who currently attend universities in a city. Collected data were analyzed using descriptive statistics, t-test, one-way ANOVA, Tukey’s test and Pearson’s correlation coefficient using the SPSS 25.0 program. Results: The mean score of sleep was 34.93±6.35, the mean score of resilience was 23.17±6.95, and the mean score of interpersonal relations were 3.65±0.38. In sleep, there were significant differences according to grade and major. In resilience, there were significant differences according to gender and grade. Sleep was negatively related to resilience (r=-.319, p<.001) and interpersonal relations (r=-.226, p=.002). Interpersonal relations were positively correlated to resilience (r=.348, p<.001). Conclusion: The results suggest that concrete measures to promote interpersonal relations need to be sought in consideration of the relations among college students' sleep, resilience, and interpersonal relations. Also, it is expected that the study will be used as basic data to improve the interpersonal relations of college students in the desirable direction by improving the sleep and resilience of college students.
대학생의 인터넷중독 및 스마트폰 중독 정도와 미술 치료 인식에 대한 조사 연구
박혜원,송승윤,윤하영,이경현,이소영,이지원,진예은,최시온,허은서,황다빈,신주현,이인영 이화여자대학교 간호학회 2018 이화간호학회지 Vol.- No.52
Purpose: Investigate the level of Internet and smart phone addiction of college students and difference of their perception on the art therapy. Method: Data was collected using 4 categories of questionnaires. Participants of this study were 383 college students who are currently attending universities located in seoul, Kyung-Ki and Incheon. The Chi-square test, One-way Analysis of Variance, Scheffé test were performed using IBM SPSS Statistics 23.0 Result: First, the study has established that the status of attending universities, grade, people who living with, age affected the level of Internet addiction of college students. In terms of the level of smart phone addiction of college students, the status of attending universities, gender, age were the affective factors. Second, there was a significant difference on the perception of the advantages of the art therapy and the level of acknowledging it, depending on the level of Internet addiction. Finally, depending on the level of smartphone addiction, there was a significant difference in the level of perception of the art therapy, expectation toward the art therapy and the helpfulness of art therapy. The more the participants are close to the addicted level, the more they want to experience the art therapy. Conclusion: These results suggest. First, it is necessary to use bigger group of participants. Second, it is necessary to improve the research methods for college students. Third, nurse should offer holistic care toward the patients regarding their general characteristics by adapting this study. Finally, it is necessary to improve the art therapy programs for the college students who are addicted to the Internet and smartphone and to develop researches proving the effectiveness of these programs.