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유재성,박세환,윤주만,신수철,원충연,최철,이상훈 전력전자학회 2005 전력전자학회 논문지 Vol.10 No.2
This paper presents a strategy to drive built in-type spindle induction motor which is used as CNC(Computer Numerical Control) in the industry. Gopinath model flux estimator which is composed of current model to be profitable in the low speed range and voltage model to be profitable in the high speed range is used for rotor flux estimation. Moreover this paper presents to drive the spindle motor in the high speed range by using the flux weakening control. High speed operation of spindle motor in the field weakening region is verified through simulations and experiments. 본 논문에서는 산업체 CNC(Computer Numerical Control) 분야에서 사용되는 빌트인 타입 스핀들 모터를 구동하기 위한 기법을 제시하였다. 저속 영역에서 유리한 전류 모델과 고속 영역에서 유리한 전압 모델을 혼합해서 사용하는 고피나스 모델 자속추정기는 회전자 자속추정을 위하여 이용하였다. 그리고 약계자 제어를 사용하여 스핀들 모터를 고속 운전하였다. 시뮬레이션과 실험을 통해 약계자 영역에서의 스핀들 모터 고속운전을 확인하였다.
Estrogen activity of Silkworm (Bombyx mori) Pupa water extract and its fractions
유재성,Gyeong-Jong Jo,Jung-woo Jin,Hyo-Jung Yang,박용일,Ye-Seul Na,Kyung-Su Nam,Kyung-Soo Keum,Young-Kug Choo 경희대학교 융합한의과학연구소 2008 Oriental Pharmacy and Experimental Medicine Vol.8 No.3
This study was conducted to evaluate the estrogen activity of silkworm (Bombyx mori) pupa extracts and their fractions. Powdered samples of freeze-dried silkworm pupa were extracted at room temperature (RT), 40 ºC, 60 ºC, 80 ºC, and 100 ºC in water (D.W), chloroform, ethyl acetate, and methanol for 6h and then filtered (0.45 um). The extracts were then freeze-dried. The estrogenic activity of these extracts was then investigated by competition binding assays using estrogen receptor α (ERα) and ERβ, and by evaluating their effects on the proliferation of the human breast cancer cell line, MCF-7. Among the extracts evaluated, water extracts prepared at RT showed the highest binding affinity to ERα (IC50, 1.76 ug/ml) and ERβ (IC50, 0.07 ug/ml). In addition, MCF-7 cells that were treated with 62.5 ug/ml of the RT extract showed the greatest increase in proliferation (2-fold; 1291.79%) when compared to control cells (659.82%). Next, the water extract that was prepared at RT (sample 1) was dissolved in D.W. and further fractionated using a Dowex 50W - 8X (H+) column. The flow-through and wash were then pooled together and freeze-dried (sample 2). The bound materials were then eluted with 20 mM NaCl, after which they were applied to a Dowex 1X2 - 200 (Cl-) column and washed with D.W. to remove the sodium ions. The eluants were then freeze-dried (sample 3). Of these fractions, sample 2 showed the highest binding affinity to ERα (IC50, 1.44 ug/ml) and ERβ (IC50, 1.18 ug/ml). In addition, MCF-7 cells that were treated with sample 2 (15.6 ug/ml) showed the largest increase in growth (1159.39%) when compared to control cells (525.26%). Taken together, these results suggest that the fraction of the RT water extract of silkworm pupa referred to as sample 2 may be useful as a phytoestrogen.
Unit Root Test를 기반으로 한 장기 시계열 데이터의 Non-Stationary 발생에 따른 구조 변화 검정 및 시각화 연구
유재성,주재걸 한국정보처리학회 2019 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.8 No.7
Structural change of time series means that the distribution of observations is relatively stable in the period of constituting the entire time series data, but shows a sudden change of the distribution characteristic at a specific time point. Within a non-stationary long-term time series, it is important to determine in a timely manner whether the change in short-term trends is transient or structurally changed. This is because it is necessary to always detect the change of the time series trend and to take appropriate measures to cope with the change. In this paper, we propose a method for decision makers to easily grasp the structural changes of time series by visualizing the test results based on the unit root test. Particularly, it is possible to grasp the short-term structural changes even in the long-term time series through the method of dividing the time series and testing it. 시계열의 구조 변화란, 전체 시계열 자료를 구성하는 기간에서 관측치들의 분포가 상대적으로 안정적이다가, 특정 시점에서 분포 특성의 급격한 변화를 보이는 것을 의미한다. 비정상(non-stationary) 장기 시계열 안에서도, 단기적인 추세의 변화가 일시적인 것인지, 아니면 구조적으로 변한 것인지를 적시에 판단하는 것은 중요하다. 이는 시계열 추세의 변화를 상시 감지하여, 변화에 맞는 적정한 대응을 할 필요가 있기 때문이다. 본 연구에서는 단위근 검정법을 기반으로 한 검정 결과를 시각화함으로써, 의사결정자가 시계열의 구조 변화를 손쉽게 파악할 수 있는 방안을 제시하였다. 특히 시계열을 분할한 후 검정하는 방법을 통해, 장기 시계열일 때에도 단기 구조 변화를 파악할 수 있도록 하였다.