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서포트 벡터 머신을 이용한 NCAM-LAMP 고해상도 중기예측시스템 지점 시계열 자료의 통계적 보정
권수영 ( Su-young Kwon ),이승재 ( Seung-jae Lee ),김만일 ( Man-il Kim ) 한국농림기상학회 2021 한국농림기상학회지 Vol.23 No.4
NCAM-LAMP 중기예측 자료의 통계적 후처리와 개선을 위하여 R 기반의 지점 시계열 자료 검증 체계를 구축하였다. 이 시계열 검증체계를 이용하여 기상청 AWS 관측 자료와 NCAM-LAMP, KMA GDAPS 중기예측 모델 자료를 비교하였다. 이를 위해 관측 지점에 가장 근접한 모델 위도 및 경도 자료를 추출하여 총 9개 지점을 선정하였다. 각 지점에 대해 NCAM-LAMP, GDAPS 모델의 기온, 강수량, 풍속 일평균 예측 자료를 관측과 비교한 결과, 모델들은 풍속의 과대예측 경향을 뚜렷이 보였으며, 기온과 강수의 경우에는 두 모델의 예측력이 월별 및 변수별로 다르게 나타났다. 이를 바탕으로 본 연구에서는 통계적 기법을 개발하여 NCAM-LAMP가 가지고 있는 오차를 줄이고자 하였다. 모델 오차를 줄이기 위해 일반적으로 쓰이는 MOS (Model Output Statistics)기법 중에 인공지능 SVM (Support vector machine) 방식을 8∼10월 기간에 적용한 결과, 8월에 비해서 10월이, 기온 변수에 비해서 바람과 강수 변수가 개선된 효과를 보여 주었다. 이러한 결과는 풍속의 과대예측을 줄이고, 농림 가뭄기주와 산사태 예측을 개선시키며, 지역 수치예보 모델이 시간 적분됨에 따라 영역 내 예측가능성이 점점 저하되는 현상을 완화시키는데 SVM 방법이 일정 부분 기여할 수 있음을 가리키며, 현업 표출 중인 NCAM Agro-Meteogram 개선에도 도움을 줄 것으로 기대된다. Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine(SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.
시동병(是動病).소생병(所生病)의 배속(配屬)에 관(關)한 고찰(考察)
이봉효,김성진,정창환,권수영,임성철,이경민,김재수,이윤경,정태영,고경모,이상남,Lee, Bong-Hyo,Kim, Seong-Jin,Jung, Chang-Hwan,Kwon, Su-Young,Lim, Sung-Chul,Lee, Kyung-Min,Kim, Jae-Su,Lee, Yoon-Kyoung,Jung, Tae-Young,Ko, Kyung-Mo,Lee, Sa 대한침구의학회 2008 대한침구의학회지 Vol.25 No.5
Objectives : The purpose of this study is to find the principal of the assignment of Sidong disease and Sosaeng disease(是動病 所生病) into 12 meridians and suggest the author's opinion. Methods : 1. The authors investigated the conception of Sidong disease and Sosaeng disease through several literatures. 2. The authors investigated the line course of 12 meridians(經脈流注) and their Sidong disease and Sosaeng disease. 3. The authors classified Sidong disease and Sosaeng disease following the study by Kim et al. 4. The authors suggested the opinions about the diseases that are difficult to be understood direct relation with the course of meridian. Results : 1. The result of classification of Sidong disease and Sosaeng disease into 5 shows that the percentages were 32.96% for meridian's own disease(本經病), 13.97% for organic own disease(本臟腑病), 12.85% for other organic own disease(他臟腑病), 20.67% for related organic disease(有關器官病), 19.55% for etc.(其他病). 2. Therefore, 19.55% of the whole Sidong disease and Sosaeng disease is that which occurred on the site that is not related directly with the meridian. Conclusions : 1. The exterior and interior relation(表裏關係) and mutual communication between organ and bowel(臟腑相通) are associated with the basic principal of the assignment of Sidong disease and Sosaeng disease that is not related with the course of meridian. 2. The cause of assignment of Sidong disease and Sosaeng disease can be explained according to the profound medical theories.
임상 간호사의 감정노동, 감성지능 및 사회적 지지가 직무스트레스에 미치는 영향
김주현(Kim, Joo Hyun),이용미(Lee, Yong-Mi),정혜영(Joung, Hye Young),추현심(Choo, Hyun Sim),원수진(Won, Su Jin),권수영(Kwon, Sue Young),배혜진(Bae, Hye Jin),안혜경(Ahn, Hye Kyung),김은미(Kim, Eun Mi),장현정(Jang, Hyun Jung) 기본간호학회 2013 기본간호학회지 Vol.20 No.2
Purpose: The purpose of this study was to investigate the effects of emotional labor, emotional intelligence and social support on job stress in clinical nurses. Methods: Participants were 123 clinical nurses and data were collected from October to December, 2011 and analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation coefficients and multiple regression with SPSS 18.0. Results: A positive correlation was found between job stress and emotional labor. Emotional labor showed a significant negative correlation with emotional intelligence and social support, whereas a positive correlation was found between emotional intelligence and social support. The strongest predictor of job stress was emotional labor. In addition, institution satisfaction (dissatisfaction) and the reason for selecting the job (opportunities for service) accounted for 21% of variance in job stress. Conclusion: The results of this study suggest that it is important to manage emotional labor as well as to improve job satisfaction in order to reduce job stress in clinical nurses.