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OCT Compound로 포매한 전립선 동결절편에서 RNA 추출방법 비교
전성윤(Sung Yoon Jeon),이형남(Hyoungnam Lee),김태정(Tae-Jung Kim),정은선(Eun Sun Jung),이교영(Kyo Young Lee),최영진(Yeong-Jin Choi) 대한비뇨기종양학회 2010 대한비뇨기종양학회지 Vol.8 No.1
Purpose: There are two methods commonly used for the extraction of total RNA. One is a Trizol method and the other is a column method. However, there have been few reports comparing the quality of total RNA extracted by these two methods in fresh frozen OCT compound-embedded (FFOE) tissues. We evaluate the two RNA extraction methods, to know the best quality of total RNA in FFOE tissues. Materials and Methods: Twenty- one fresh frozen human prostate tissues were used for RNA extraction by the classic method using Trizol reagent and the commercially available method, respectively. RNA purity and quality analysis were performed by spectrophotometry and automated electrophoresis system. Results: An A260:A280 ratio of all RNA from two methods were above of 1.8. The ratio of 28S/18S rRNA in Trizol method (tumor=0.93±0.25, nontumor=1.03±0.28) were higher than the column method (tumor=0.58±0.20, nontumor= 0.60±0.28, p<0.001). On gel images, 18S and 28S rRNA were separated and intact in Trizol method but they were not visible as intact bands but fragmented in column method. Conclusions: To purify the best quality RNA from the FFOE tissues for the molecular pathologic study, Trizol method is superior to the column method.
Implementation of Rule-based Smartphone Motion Detection Systems
Eon-Ju Lee(이언주),Seung-Hui Ryou(유승희),So-Yun Lee(이소윤),Sung-Yoon Jeon(전성윤),Eun-Hwa Park(박은화),Jung-Ha Hwang(황정하 ),Doo-Hyun Choi(최두현) 한국컴퓨터정보학회 2021 韓國컴퓨터情報學會論文誌 Vol.26 No.7
스마트폰에 내장된 각종 센서를 통해 획득할 수 있는 정보는 사용자의 움직임, 상황 등을 파악하고 분석하는데 유용하게 활용될 수 있다. 본 논문에서는 스마트폰의 가속도 센서와 자이로스코프 센서에서 얻은 정보를 분석하여 ‘I’, ‘S’, ‘Z’ 모션을 인식하는 두 가지 규칙기반 시스템을 제안한다. 먼저, 각 모션에 대한 가속도 및 각속도의 특성을 분석한다. 이를 기반으로 두 가지 종류의 규칙기반 모션 인식 시스템을 제안하고 이를 안드로이드 앱으로 구현하여 각 모션에 대한 성능을 비교한다. 두 가지 규칙기반시스템은 각 모션에 대해서 90% 이상의 인식률을 보이며 앙상블을 이용한 규칙기반 시스템은 다른 시스템보다 향상된 성능을 보인다. Information obtained through various sensors embedded in a smartphone can be used to identify and analyze user’s movements and situations. In this paper, we propose two rule-based motion detection systems that can detect three alphabet motions, ‘I’, ‘S’, and ‘Z’ by analyzing data obtained by the acceleration and gyroscope sensors in a smartphone. First of all, the characteristics of acceleration and angular velocity for each motion are analyzed. Based on the analysis, two rule-based systems are proposed and implemented as an android application and it is used to verify the detection performance for each motion. Two rule-based systems show high recognition rate over 90% for each motion and the rule-based system using ensemble shows better performance than another one.