• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.635-648
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• 2020

The purpose of this study was to identify the effects of image of nurse, clinical performance, and major satisfaction of nursing students on their nursing professionalism. The subjects of this study were 303 sophomores and juniors majoring in nursing in G city, who were surveyed between October 15 and 19, 2018. The collected data were analyzed using descriptive statistics, t-test, ANOVA, and multiple regression analysis. According to the results, nursing professionalism showed a significant positive correlation with image of nurse (r=.70, p<.001), clinical performance (r=.23, p<.001), and major satisfaction (r=.62, p<.001), clinical performance had a positive correlation with image of nurse (r=.14, p=.015), and major satisfaction had a positive correlation with image of nurse (r=.55, p<.001) and clinical performance (r=.14, p=.012). Factors affecting nursing professionalism included major satisfaction (β=.32, p<.001), social image (β=.31, p<.001), professional image (β=.21, p<.001), and clinical performance (β=.09, p=.018), in order, with 59.9% explanation power. To establish positive nursing professionalism in nursing students, it is necessary to develop a variety of systematic educational programs to enhance their image of nurse, major satisfaction, and clinical performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.100-107
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• 2021

This study was a descriptive research to investigate the effects of resilience and personality types on the major satisfaction of nursing students. The participants of this study were nursing students who were attending two universities in D city. Data collection was conducted from September 8 to October 6, 2020. The SPSS/WIN 26.0 program was used for data analysis. Frequency and percentage, mean and standard deviation, Pearson's correlation, independent sample t-test, one-way ANOVA, and multiple regression were used for analysis. The results of this study showed that the average recovery elasticity of nursing students was 3.50 points (5 points), personality type was 2.28 points (4 points), and major satisfaction was 3.12 points (5 points). Personality type A was found in 122 people and personality type B in 136 people. It was found that there was a positive correlation between resilience and major satisfaction, which indicates that the higher the resilience, the higher the major satisfaction. The major satisfaction of nursing students was found to be a significant factor influencing college life satisfaction and human relationships in personality type A, showing 46.2% explanatory power. In personality type B, it was found to be a significant influencing factor in grade and human relationships, showing 42.5% explanatory power. From the above study results, it can be inferred that the development of a college application program that can improve human relationships and increase resilience in college life is required to inspire major satisfaction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.193-202
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• 2017

This study was conducted to investigate the levels of academic stress, ego-resilience, and health promoting behaviors of nursing students, and to examine the relationship between these variables. The participants were 208 nursing students(freshman/sophomore). Data were collected from April 3 to April 21, 2017 by self-administered questionnaires. Data were analyzed using the SPSS WIN 19.0 program(SPSS Inc., Chicago, IL, USA). The results of this study were as follows: the mean academic stress score was $3.17{\pm}0.55$, ego-resilience was $2.70{\pm}0.38$, and health promoting behaviors was $2.47{\pm}0.32$. There were significant differences in health promoting behaviors based on residence status, satisfaction with major, satisfaction with school life and health status. There was a negative correlation between health promoting behaviors and academic stress(r=-0.36, p=0.000), while there was a positive correlation between health promoting behaviors and ego-resilience(r=0.60, p=0.000). Variables such as ego-resilience, academic stress, satisfaction with school life, residence status, health status and satisfaction with major explained 43.3% of the variance in health promoting behaviors. Based on these results, it is necessaryto develop interventions and programs to reduce academic stress and increase ego-resilience to improve health promotion in nursing students.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.125-132
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• 2023

In this study, we compared the performance of machine learning models for predicting Vapor Pressure Deficits (VPD) in greenhouses that affect pore function and photosynthesis as well as plant growth due to nutrient absorption of plants. For VPD prediction, the correlation between the environmental elements in and outside the greenhouse and the temporal elements of the time series data was confirmed, and how the highly correlated elements affect VPD was confirmed. Before analyzing the performance of the prediction model, the amount and interval of analysis time series data (1 day, 3 days, 7 days) and interval (20 minutes, 1 hour) were checked to adjust the amount and interval of data. Finally, four machine learning prediction models (XGB Regressor, LGBM Regressor, Random Forest Regressor, etc.) were applied to compare the prediction performance by model. As a result of the prediction of the model, when data of 1 day at 20 minute intervals were used, the highest prediction performance was 0.008 for MAE and 0.011 for RMSE in LGBM. In addition, it was confirmed that the factor that most influences VPD prediction after 20 minutes was VPD (VPD_y__71) from the past 20 minutes rather than environmental factors. Using the results of this study, it is possible to increase crop productivity through VPD prediction, condensation of greenhouses, and prevention of disease occurrence. In the future, it can be used not only in predicting environmental data of greenhouses, but also in various fields such as production prediction and smart farm control models.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.1068-1069
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• 2023

해상 경로를 통해 물건을 운송하는 일이 증가함에 따라 컨테이너의 효율적인 관리의 필요성이 커지고 있다. 이에 본 연구에서는 스스로 내부 온도와 진동, 습도 등을 감지하고 조절하는 스마트 컨테이너와, 현실과 가상 세계를 잇는 디지털 트윈 기술을 활용해 컨테이너의 관리를 효율적으로 할 수 있도록 돕는 서비스를 제공하고자 한다.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.263-273
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• 2016

This study was done to identify the relationship between emotional labor, self-esteem, and major satisfaction of clinical practice among nursing students. Participants were 199 nursing students who had clinical practice that located in B- city and K- do during the period from August 3rd to 17th, 2015. The average mean scores for self esteem, emotional labor, and major satisfaction were 3.53, 3.26 and 3.46 (5 scale). Pearson's correlation revealed self esteem had a significant positive effect on major satisfaction, while emotional labor had a negative effect on major satisfaction. Factors having a significant influence on major satisfaction included self esteem, satisfaction of college life, and level of academic scores. These factors explained 34.0% of variance in major satisfaction. Thus, the satisfaction of college life, self esteem, and academic score were required to manage for major satisfaction of nursing students.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.297-306
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• 2019

The purpose of this study was to investigate the convergence between ego-resilience, major satisfaction and clinical competency of nursing students. This study used data from 183 nursing college students who experienced clinical practice at a college located in G city of Korea. Clinical competency was positively correlated with ego-resilience (r = .446, p <.000), major satisfaction (r = .439, p <.000). The factors influencing clinical competency were ego - resilience and major satisfaction, and explanatory power was 29.1%. Based on the above results, it is necessary to improve the convergence education program and diversify the teaching and learning methods to improve the major satisfaction, ego - resilience and clinical competency of nursing students.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.3
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• pp.207-215
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• 2023

This study was compared the soil environment and growth and yield of onion (Allium cepa L.) treated with non-mulching (NM) and mulching polyethylene film (PEF) and two biodegradable films (BFI and BFII) commonly used in farmhouses. Visual observation confirmed the degradation of BFI and BFII films after 150 days after tansplanting (DAT). BFII increased light penetration into the films and reduced the weight maintenace after 180 DAT, with a high decompostion at 30 days after soil tilling. Soil moisture contents much fluctuated between -14 kP and - 0 kPa in NM plots, increasing the minimum soil temperature of BFI plots. Mulching treatments decreased soil organic matter contents but did not subtantially increase soil mineral nutrients, soil bulk density, and number of bacteria compared to those of NM plots. Onion root growth was increased by PEF and BFI treatments at an early growth stage, 60 DAT, with the most remarkable stem extension observed for PEF and BFI treatments after 150 DAT. PEF and BFI treatments increased the bulb's diameter, length, weight, and lodging at 180 DAT. BFI treatments exhibited a high portion of the "very large" category producing with 55.3 tons ha^-1 based on the classification into bulb size, followed by PE (49.3 tons), NM (9.4 tons), and BFII treatments (2.7 tons) at 230 DAT.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.366-366
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• 2022

유역의 하천유량과 같은 수문 시계열을 모의 또는 예측하기 위한 수문 모델링에서 최근 기계 학습 방법을 활용한 연구가 활발하게 적용되고 있는 추세이다. 이러한 데이터 기반 모델링 접근법은 입출력 자료에서 관찰된 패턴을 학습하며, 특히, 장단기기억(Long Short-Term Memory, LSTM) 네트워크는 많은 연구에서 수문 시계열 예측에 대한 적용성이 검증되었으나, 장기간의 고품질 관측자료를 활용할 때 더 나은 예측성능을 보인다. 그러나 우리나라의 경우 장기간 관측된 고품질의 하천유량 자료를 확보하기 어려운 실정이다. 따라서 본 연구에서는 LSTM 네트워크의 학습 시 가용한 모든 유역의 자료를 통합하여 학습시켰을 때 하천유량 예측성능을 개선할 수 있는지 판단해보고자 하였다. 이를 위해, 우리나라 13개 댐 유역을 대상으로 대상 유역의 자료만을 학습한 모델의 예측성능과 모든 유역의 자료를 학습한 모델의 예측성능을 비교해 보았다. 학습은 2001년부터 2010년까지 기상자료(강우, 최저·최고·평균기온, 상대습도, 이슬점, 풍속, 잠재증발산)를 이용하였으며, 2011년부터 2020년에 대해 테스트 되었다. 다지점 통합학습을 통해 테스트 기간에 대해 예측된 각 유역의 일 하천유량의 KGE 중앙값이 0.74로 단일지점 학습을 통해 예측된 KGE(0.72)보다 다소 개선된 결과를 보여주었다. 다지점 통합학습이 하천유량 예측에 큰 개선을 달성하지는 못하였으며, 추가적인 가용 자료 확보와 LSTM 구성의 개선을 통해 추가적인 연구가 필요할 것으로 판단된다.

• Environmental engineer
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• v.23 s.237
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• pp.8-11
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• 2006

2006년 5월 9일(화), 10일(수) 양일간 국회 의원회관 1층 중앙홀에서 환경을 고려한 첨단기술로 탄생한 친환경상품 전시회가 미래학자인 공성진(한나라당, 강남(을))의원이 주최로 마련된다. 이재오 한나라당 원내대표, 이경재 국회 환경노동위원장, 김용갑 국회 산업자원위원장, 이치범 환경부 장관, 이상영 친환경상품진흥원장 등의 내빈들이 참석하는 이번 전시회는 재사용되는 부스를 비롯, 비목재펄프 사용, 콩기름 인쇄 등 전시회 자체도 친환경적으로 설계되어 더욱 눈길을 끈다. 또한 국민대학교 디자인 대학원의 윤호섭 교수와 그린디자인 전공 학생들의 작품 전시까지 곁들여져 우리의 환경에 대해 다시금 생각해 보는 계기를 제공한다.