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β - Casein 의 이차구조에 관한 chaotropic Salts 의 영향
송경빈,Srinivasan Damodaran ( Kyung Bin Song,Srinivasan Damodaran ) 생화학분자생물학회 1992 BMB Reports Vol.25 No.5
To elucidate the effect of chaotropic salts on the conformation of β-casein, CD studies of β-casein at various NaC1O₄ concentrations were performed. Addition of NaC1O₄ up to 1 M caused the increase of β-sheet content from 15 to 35% due to alteration of water structure. Reversibility experiments indicate that increased secondary structure of β-casein in the presence of chaotropic salt might be a form of non-classic sheet-like structure.
전력수요예측을 위한 다양한 퍼지 최소자승 선형회귀 모델
송경빈,Song, Kyung-Bin 한국조명전기설비학회 2007 조명·전기설비학회논문지 Vol.21 No.7
전력수요예측은 전력계통의 운용을 위해 필수적이다. 따라서 다양한 방법이 제시되어 왔으며, 특히 특수일의 수요예측은 평일과 구분되며, 부하 패턴을 축출하기에 충분한 자료 확보가 어려워 예측 오차가 크게 나타난다. 본 논문에서는 특수일의 부하예측 정확도를 개선하기 위해 퍼지 최소자승 선형회귀 모델을 분석한다. 4종류의 퍼지 최소자승 선형회귀 모델에 대해 분석과 사례연구를 통하여 가장 정확한 모델을 제시한다. The load forecasting has been an important part of power system Accordingly, it has been proposed various methods for the load forecasting. The load patterns of the special days is quite different than those of ordinary weekdays. It is difficult to accurately forecast the load of special days due to the insufficiency of the load patterns compared with ordinary weekdays, so we have proposed fuzzy least squares linear regression algorithm for the load forecasting. In this paper we proposed four models for fuzzy least squares linear regression. It is separated by coefficients of fuzzy least squares linear regression equation. we compared model of H1 with H4 and prove it H4 has accurately forecast better than H1.
송경빈(Kyung-Bin Song),임종훈(Jong-Hun Lim) 대한전기학회 2013 전기학회논문지 Vol.62 No.12
Short-term load forecasting for Chusok and New Year"s consecutive holidays is very difficult, due to the irregular characteristics compared with ordinary weekdays and insufficient holidays historical data. During consecutive holidays of New Year and Chusok, most of industries reduce their operation rates and their electrical load levels. The correlation between businesses" operation rates and their loads during consecutive holidays of New Year and Chusok is analysed and short-term load forecasting algorithm for consecutive holidays considering businesses" operation rates of industries is proposed. Test results show that the proposed method improves the accuracy of short-term load forecasting over fuzzy linear regression method.
연구노트 : 청미래덩굴 뿌리 열수 추출물로부터 칼슘 결합 물질의 분리
송경빈 ( Kyung Bin Song ),이지혜 ( Ji Hye Lee ),전소정 ( So Jeong Jeon ) 한국식품저장유통학회 ( 구 한국농산물저장유통학회 ) 2010 한국식품저장유통학회지 Vol.17 No.4
청미래덩굴 뿌리(Smilacis rhizoma)로부터 칼슘과 결합하는 물질을 분리하고자 열수로 추출한 추출물을 ion exchange, normal-phase HPLC 및 gel filtration chromatogarphy를 이용하여 칼슘 결합 물질을 순차적으로 분리하였다. 그 결과 ion exchange chromatography에서 7개의 major peaks를 얻었으며, 이 중 F6 fraction이 0.083 mM로 칼슘과 가장 높은 결합력을 가졌다. 또한 F6를 NH2 column으로 분획한 결과 F61에서 0.130 mM의 가장 높은 칼슘함량을 나타내었으며, 최종적으로 Superdex(TM)를 이용하여 F611 fraction으로 분리하였다. 따라서 청미래덩굴 뿌리 추출물 중 F611 fraction을 이용하여 biomineral을 제조함으로써 칼슘 보충제나 기능성 성분의 원료로써 식품산업에 활용될 수 있다고 판단된다. We isolated a calcium-binding substance from Smilacis rhizoma hot-water extract using ion exchange, normal phase HPLC, and gel filtration chromatography; fractions were analyzed for calcium-binding activity. Fractions (F6) with the highest calcium-binding activity from the resource Q coulmn were pooled and further purified on an NH2 column. Two major peaks were separated and the fraction (F61) with the higher calcium-binding activity was then loaded onto a Superdex(TM) column. A single peak (F611) with calcium-binding activity was finally obtained. These results suggest that the isolated calcium-binding fraction could be used as a functional food additive, similar to a calcium supplement, in the food industry.
송경빈(Kyung-Bin Song) 대한전기학회 2014 전기학회논문지 Vol.63 No.4
Short-term load forecasting(STLF) for electric power demand is essential for stable power system operation and efficient power market operation. We improved STLF method by using hourly temperature as an input data. In order to using hourly temperature to STLF algorithm, we calculated temperature-electric power demand sensitivity through past actual data and combined this sensitivity to exponential smoothing method which is one of the STLF method. The proposed method is verified by case study for a week. The result of case study shows that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.
송경빈(Kyung-Bin Song) 대한전기학회 2010 전기학회논문지 Vol.59 No.6
Short-term electric load forecasting of power systems is essential for the power system stability and the efficient power system operation. An accurate load forecasting scheme improves the power system security and saves some economic losses in power system operations. Due to scarcity of the historical same type of holiday load data, most big electric load forecasting errors occur on load forecasting for the holidays. The fuzzy linear regression model has showed good accuracy for the load forecasting of the holidays. However, it is not good enough to forecast the load of the election day. The concept of the load variation rate for the load forecasting of the election day is introduced. The proposed algorithm shows its good accuracy in that the average percentage error for the short-term 24 hourly loads forecasting of the election days is 2.27%. The accuracy of the proposed 24 hourly loads forecasting of the election days is compared with the fuzzy linear regression method. The proposed method gives much better forecasting accuracy with overall average error of 2.27%, which improved about average error of 2% as compared to the fuzzy linear regression method.