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조성억,고철환,JOH, SUNG-OK,KOH, CHUL-HWAN The Korean Society of Oceanography 1991 韓國海洋學會誌 Vol.26 No.3
MAPP a computer program provides an estimate of the annual production of macroalgae. The calculation of the annual production is based on the Photosynthesis-Irradiance relationship under different temperature conditions and annual changes of algal biomass. The production in a given time was obtained from the multiplication of biomass by the production rate measured by in situ experiments. The annual production, $P_{yr}$, is calculated from $P_{yr}{\;}={\;}{\int}B_t{\cdot}P_r{\;}dt$, where, $P_t$ = f(T,L)and T, L = f(t). The program is written in Pascal language to facilitate the usage with personal computers. The data of the photosynthetic rates and biomass of Sargassum confusum measured at Ohori, on the east coast of Korea, was used for an example.
단변량 및 다변량 LSTM을 이용한 농업용 저수지의 저수율 예측
조성억,이양원,Sunguk Joh,Yangwon Lee 대한원격탐사학회 2023 大韓遠隔探査學會誌 Vol.39 No.5
Out of the total 17,000 reservoirs in Korea, 13,600 small agricultural reservoirs do not have hydrological measurement facilities, making it difficult to predict water storage volume and appropriate operation. This paper examined univariate and multivariate long short-term memory (LSTM) modeling to predict the storage rate of agricultural reservoirs using remote sensing and artificial intelligence. The univariate LSTM model used only water storage rate as an explanatory variable, and the multivariate LSTM model added n-day accumulative precipitation and date of year (DOY) as explanatory variables. They were trained using eight years data (2013 to 2020) for Idong Reservoir, and the predictions of the daily water storage in 2021 were validated for accuracy assessment. The univariate showed the root-mean square error (RMSE) of 1.04%, 2.52%, and 4.18% for the one, three, and five-day predictions. The multivariate model showed the RMSE 0.98%, 1.95%, and 2.76% for the one, three, and five-day predictions. In addition to the time-series storage rate, DOY and daily and 5-day cumulative precipitation variables were more significant than others for the daily model, which means that the temporal range of the impacts of precipitation on the everyday water storage rate was approximately five days.
호텔의 조직사회화가 구성원의 경력몰입 및 이직 의도에 미치는 영향
조성억 ( Sungauk Cho ),최정길 ( Jeonggil Choi ),신혜령 ( Hyeryeong Shin ) 관광경영학회 2020 관광경영연구 Vol.100 No.-
The main objective of this study is to examine the effect of organizational socialization on career commitment and turnover intention of hotel employees. Particularly, we aim to explore career commitment as the important variable which has been overlooked in relevant research context. The researchers surveyed employees of five-star hotels in Seoul and a total of 236 valid responses were received from a sample of 300 hotel employees. SPSS 18 statistics package was used to analyze the data collected and factor analysis, reliability analysis, correlation analysis, and regression analysis were conducted. The results show that organizational socialization has significantly positive effects on career commitment, and career commitment has significantly negative effects on turnover intention. However, the sub-factors of organizational socialization had different effects on turnover intention. Performance proficiency positively affects turnover intention, while the extent to which the organizational goals/values are understood has no significant effect on turnover intention of employees. The consequent theoretical and managerial implications, and suggestions on future research are elaborated in detail in the conclusion.
Sentinel-1 SAR 영상과 인공지능 기법을 이용한 연안해역의 고해상도 해상풍 산출
조성억 ( Sung-uk Joh ),안지혜 ( Jihye Ahn ),이양원 ( Yangwon Lee ) 대한원격탐사학회 2021 大韓遠隔探査學會誌 Vol.37 No.5
해상풍 데이터는 최근 들어서 신재생 에너지 개발의 일환으로 해상 풍력발전 단지가 각광받으면서 더욱 중요성을 더하고 있다. 본 연구에서는 2015~2020년 부울경(부산, 울산, 경남) 연안해역을 촬영한 Sentinel-1 영상 368장과 저해상도 수치모델의 UV 컴포넌트를 이용한 DNN (Deep Neural Network) 모델을 개발하여 해상풍 데이터를 공간해상도 10 m 수준으로 정밀하게 생산하는 방법을 제시하였다. 이를 통해 기존의 CMOD (C-band Model) 함수에 비해 40% 정도 오차가 감소하였으며, U 컴포넌트와 V 컴포넌트는 각각 상관계수 0.901, 0.826의 비교적 높은 정확도를 나타냈다. 본 연구에서 부울경 해역(해안선으로부터 3 km 버퍼 영역)에 대해 산출한 10 m 해상도의 바람장 지도를 작성해 보면, 내륙에서 외해로 갈수록 풍속이 강해지는 일반적인 경향을 따르면서도 공간적으로 상세화된 바람 패턴을 잘 나타낼 수 있었다. 이러한 고해상도 해상풍 지도는 해상 풍력발전을 위한 상세조사뿐 아니라, SAR를 활용한 전천후 연안 방재 및 연안레저 정보 제공을 지원할 수 있을 것으로 기대한다. Sea wind is recently drawing attraction as one of the sources of renewable energy. This study describes a new method to produce a 10 m resolution sea wind field using Sentinel-1 images and low-resolution NWP (Numerical Weather Prediction) data with artificial intelligence technique. The experiment for the South East coast in Korea, 2015-2020, showed a 40% decreased MAE (Mean Absolute Error) than the generic CMOD (C-band Model) function, and the CC (correlation coefficient) of our method was 0.901 and 0.826, respectively, for the U and V wind components. We created 10m resolution sea wind maps for the study area, which showed a typical trend of wind distribution and a spatially detailed wind pattern as well. The proposed method can be applied to surveying for wind power and information service for coastal disaster prevention and leisure activities.