• 신재생에너지
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• 제2권2호
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• pp.37-43
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• 2006

In this paper, the first forecasting system of wind power generation, KIER Forecaster is presented. KIER Forecaster has been constructed based on statistical models and was trained with wind speed data observed at Gosan Weather Station nearby Walryong Site. Due to short period of measurements at Walryong Site for training the model, Gosan wind data were substituted and transplanted to Walryong Site by using Measure-Correlate-Predict(MCP) technique. The results of One to Three-hour advanced forecasting models are consistent with the measurement at Walryong site. In particular, the multiple regression model by classification of wind speed pattern, which has been developed in this work, shows the best performance comparing with neural network and auto-regressive models.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2006년도 춘계학술대회
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• pp.323-324
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• 2006

In the present paper a forecasting system of wind power generation for Walryong Site, Jejudo is presented, which has been developed and evaluated as a first step toward establishing Korea Forecasting Model of Wind Power Generation. The forecasting model, KIER forecaster is constructed based on statistical models and is trained with wind speed data observed at Gosan Weather Station nearby Walryong Si to. Due to short period of measurements at Walryong Site for training statistical model, Gosan wind data were substituted and transplanted to Walryong Site by using Measure-Correlate-Predict technique. Three-hour advanced forecast ins shows good agreement with the measurement at Walryong site with the correlation factor 0.88 and MAE(mean absolute error) 15% under.

• 대한지구과학교육학회지
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• 제8권2호
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• pp.114-127
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• 2015

The nature of science has been recognized in a great deal in the field of science education. However, Most of the papers were going to study of teachers and students. to improve their recognition of the nature of science. The current study describes and analyzes Weather-Forecaster's understandings of the nature of science (NOS). Data used in this study were collected from 3 Weather-Forecasters using an semi-structured interview. The results of this study were as follows. First, the participants recognized that science has explored the phenomenon of unknown facts or observations and they were careful inductive perspective. Second, participants felt that science and society are associated with each other. Also, all participants were judged science verification process is required. Third, they are showed that science and technology interact closely with social relationships.

• 환경위생공학
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• 제24권3호
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• pp.37-54
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• 2009

The study has analyzed impacts and intensity of weather that affect $PM_{10}$ concentration based on PM10 forecast conducted by the city of Seoul in order to identify ways to improve the accuracy of PM10 forecast. Variables that influence $PM_{10}$ concentration include not only velocity and direction of the wind and rainfalls, but also those including secondary particulate matter, which were identified to greatly influence the concentration in complicated manner as well. In addition, same variables were found to have different impacts depending on seasons and conditions of other variables. The study found out that improving accuracy of $PM_{10}$ concentration forecast face some limits as it is greatly influenced by the weather. As an estimation, this study assumed that basic research units and artificially estimated pollutant emissions, study on mechanisms of secondary particulate matter productions, observatory compliment, and enhanced forecaster's expertise are needed for better forecast.

• The Plant Pathology Journal
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• 제24권1호
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• pp.46-51
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• 2008

With the goal of achieving better integrated pest management for hot pepper, a disease-forecasting system was compared to a conventional disease-control method. Experimental field plots were established at Asan, Chungnam, in 2005 to 2006, and hourly temperature and leaf wetness were measured and used as model inputs. One treatment group received applications of a protective fungicide, dithianon, every 7 days, whereas another received a curative fungicide, dimethomorph, when the model-determined infection risk (IR) exceeded a value of 3. In the unsprayed plot, fruits showed 18.9% (2005) and 14.0% (2006) anthracnose infection. Fruits sprayed with dithianon at 7-day intervals had 4.7% (2005) and 15.4% (2006) infection. The receiving model-advised sprays of dimethomorph had 9.4% (2005) and 10.9% (2006) anthracnose infection. Differences in the anthracnose levels between the conventional and model-advised treatments were not statistically significant. The efficacy of 10 (2005) and 8 (2006) applications of calendar-based sprays was same as that of three (2005 and 2006) sprays based on the disease-forecast system. In addition, we found much higher the IRs with the leaf wetness sensor from the field plots comparing without leaf wetness sensor from the weather station at Asan within 10km away. Since the wetness-periods were critical to forecast anthracnose in the model, the measurement of wetness-period in commercial fields must be refined to improve the anthracnose-forecast model.

• 한국농공학회논문집
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• 제59권5호
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• pp.93-99
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• 2017

A model was developed using Artificial Neural Networks (ANNs) based on Principal Component Analysis (PCA), to accurately predict the air humidity inside an experimental greenhouse located in Daegu (latitude $35.53^{\circ}N$, longitude $128.36^{\circ}E$, and altitude 48 m), South Korea. The weather parameters, air temperature, relative humidity, solar radiation, and carbon dioxide inside and outside the greenhouse were monitored and measured by mounted sensors. Through the PCA of the data samples, three main components were used as the input data, and the measured inside humidity was used as the output data for the ALYUDA forecaster software of the ANN model. The Nash-Sutcliff Model Efficiency Coefficient (NSE) was used to analyze the difference between the experimental and the simulated results, in order to determine the predictive power of the ANN software. The results obtained revealed the variables that affect the inside air humidity through a sensitivity analysis graph. The measured humidity agreed well with the predicted humidity, which signifies that the model has a very high accuracy and can be used for predictions based on the computed $R^2$ and NSE values for the training and validation samples.

• 대한지구과학교육학회지
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• 제16권1호
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• pp.30-42
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• 2023

이 연구는 초등 예비교사들이 작성한 과학 일기를 양적·질적 분석하여 초등 예비교사들이 지닌 과학의 본성에 대한 관점의 특징과 그 변화 과정을 분석하여 범주화하는데 그 목적이 있다. 이를 위해 초등 예비교사 13명이 쓴 과학 일기 112편을 분석하였다. 수집된 자료는 과학의 본성 4가지 영역의 연구 개념틀을 이용하여 영역별 빈도수를 분석하였고, VNOS-C 검사 분석틀을 이용하여 과학의 본성에 대한 관점 변화 양상을 귀납적으로 도출하여 유형화하였다. 그 결과 초등 예비교사들이 작성한 과학 일기에 나타난 과학의 본성에 대한 관점은 과학의 사고적 본성, 지식적 본성, STS적 본성, 탐구적 본성은 비교적 비슷한 비율로 서술되었으나 그 중 과학의 사고적 본성이 가장 높은 비율로 나타났고, 과학의 탐구적 본성이 가장 낮은 비율로 기술되었다. 과학 지식의 가변성, 경험적 증거의 중요성, 과학의 긍정적·부정적 작용에 대해서는 특히 집중적으로 언급되었다. 또한 초등 예비교사들의 과학의 본성에 대한 관점 변화 양상은 '고전적 관점 유지형', '현대적 관점 유지형', '회귀형', '발전형', '혼재형'으로 유형화 할 수 있었다. '과학 지식의 경험적 본성' 요소는 학생에 따라 변화 양상이 다양한 유형으로 나타났고, 대부분의 학생들이 과학 지식의 잠정성에 대해서는 현대적 관점을 여러 회기 동안 유지하였다.