• Investigative Magnetic Resonance Imaging
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• v.16 no.1
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• pp.47-54
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• 2012

Purpose : This study was performed to evaluate the characteristics of rat mesenchymal stem cells (RMSCs) transduced with human ferritin gene and investigate $in$ $vitro$ MRI detectability of ferritin-transduced RMSCs. Materials and Methods: The RMSCs expressing both myc-tagged human ferritin heavy chain subunit (myc-FTH) and green fluorescence protein (GFP) were transduced with lentiviurs. Transduced cells were sorted by GFP expression using a fluorescence-activated cell sorter. Myc-FTH and GFP expression in transduced cells were detected by immunofluorescence staining. The cell proliferative ability and viability were assessed by MTT assay. The RMSC surface markers (CD29+/CD45-) were analyzed by flow cytometry. The intracellular iron amount was measured spectrophotometically and the presence of ferritin-iron accumulation was detected by Prussian blue staining. $In$ $vitro$ magnetic resonance imaging (MRI) study of cell phantoms was done on 9.4 T MR scanner to evaluate the feasibility of imaging the ferritin-transduced RMSCs. Results: The myc-FTH and GFP genes were stably transduced into RMSCs. No significant differences were observed in terms of biologic properties in transduced RMSCs compared with non-transduced RMSCs. Ferritin-transduced RMSCs exhibited increased iron accumulation ability and showed significantly lower $T_2$ relaxation time than non-transduced RMSCs. Conclusion: Ferritin gene as MR reporter gene could be used for non-invasive tracking and visualization of therapeutic mesenchymal stem cells by MRI.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.33-38
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• 2014

The FCM based hybrid RBF network is a heterogeneous learning network model that applies FCM algorithm between input and middle layer and applies Max_Min algorithm between middle layer and output. The Max-Min neural network uses winner nodes of the middle layer as input but shows inefficient learning in performance when the input vector consists of too many patterns. To overcome this problem, we propose a dynamic learning rate control based on fuzzy logic. The proposed method first classifies accurate/inaccurate class with respect to the difference between target value and output value with threshold and then fuzzy membership function and fuzzy decision logic is designed to control the learning rate dynamically. We apply this proposed RBF network to the character recognition problem and the efficacy of the proposed method is verified in the experiment.

• Korean Journal of Legislative Studies
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• v.25 no.1
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• pp.5-44
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• 2019

The 2018 midterm elections were considered a referendum for Trump Presidency, especially because Latino community has been feeling that the anti-immigration, anti-Latino policies of Trump administration are harmful to the community. News Media and pundits predicted the boost of the Latino turnout and its positive effects on Democratic candidates at all levels. The purpose of this paper is to provide an overview of Latino demographics and Latino public opinion and to analyze the election results with exit poll data and actual aggregate data. The data analysis shows that, compared to 2014 midterm elections, Latino turnout and the support for Democratic candidates actually increased in most counties and precincts, which is more salient in the areas with heavy Latino concentration.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2164-2178
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• 1998

본 논문에서는 한 사이클에 여러 개의 명령들이 다중 이슈되어 명령어 수준에서 병렬처리되는 ILP 프로세서의 성능을 측정하고 평가하는 시스템을 개발한다. 개발되는 시스템은 C 컴파일러와 시뮬레이터로 구성된다. C 컴파일러는 C 소스 프로그램을 입력으로 받아 3-주소 코드형태의 중간언어를 생성한다. 생성된 중간언어는 ILP 프로세서의 환경 파라미터와 함께 시뮬레이터에 입력되어 시뮬레이션된 후 메모리 내용, 수행된 클럭 수 및 명령 트레이스, 수행된 명령들의 동적 빈도수, 분기명령의 예측률, profiling 정보 등을 생성한다. 개발된 성능측정 시스템의 동작 검증을 위하여 순차이슈 되어 정적으로 스케쥴링 되는 조건실행 방식의 성능과 분기처리 방식의 성능을 측정하여 분석한다.

• Korean Journal of Legislative Studies
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• v.27 no.2
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• pp.5-40
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• 2021

In the 4.7 by-election in 2021, the ruling Democratic Party suffered a record devastating defeat, breaking the trend of a post-intermediate evaluation confirmed in the recent election. Why did the Democratic Party lose by a large margin unlike the recent election trend? In order to find answers to these questions, this study analyzes the voting behavior of individual voters based on the voter consciousness survey data conducted after the 4.7 by-election, while examining the background and causes of such voter choices. As a result of the study, in the 4.7 by-election, as confirmed in previous studies, public opinion against the ruling government was strong, and negative elections were held. However, if we look at the process and results of this by-election in more detail, we can see that it is different from the general by-election. In the past by-elections, the government judgement was due to the passive participation of the ruling party-oriented voters in elections with low political weight, or the active judgement psychology that was maximized in situations where the political burden was less. However, in this by-election, on the contrary, in an election with a high political weight, the active judgement psychology of the Democratic Party and non-partisan voters had an effect on strengthening the midterm evaluation character of the election. In addition, it can be seen that the gathering of conservative voters who support the opposition also had a strong influence on the reinforcement of the midterm evaluation character of the election.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.302-302
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• 2009

미국 DOE(Department of energy) 산하 EERE(the office of energy efficiency and renewable energy)에서는 시행되고 있는 일반 프로그램 평가(General Program Evaluation) 중 하나인 과정 평가(Process Evaluation)는 프로그램의 수행의 효율성과 유효성을 평가하기 위해 수행된다. EERE에서는 프로그램 별로 매 2~3년에 한번, 프로그램의 진행에 장애요인을 시행하기 위해 부정기적으로 과정평가를 수행하여 프로그램의 진행과정을 개선할 것을 제안하고 있다. 과정평가의 방법론으로는 사례연구(case study), 내용분석(content analysis), 메타평가(meta evaluation), 델파이분석(delphi-analysis), 외부 동료평가(peer review) 등의 방법론이 사용될 수 있다. 특히, EERE는 "Peer Review Guide(2004)"을 발간하여 과정평가에서 있어 외부 동료평가의 방법론을 정리하였다. 과정평가를 통해 프로그램 수행결과의 중간점검과 동시에 프로그램의 발전을 위하 전문가의 제언을 수집할 수 있다. 따라서 과정평가의 결과는 프로그램의 개선에 도움을 줄 수 있으며, 장기 과제인 경우 프로그램 관리에 효과적으로 사용될 수 있다. 우리나라의 경우, 사업 수행 시 '진도보고'나 '중간결과 발표' 등을 통하여 동일한 내용의 평가를 시행하고 있으나, 평가의 항목.시기.예산 등에 대한 지침(guideline)이 구축되었다고 볼 수 없는 상황이다. 한국의 신재생에너지 보급사업은 국가적인 중요도, 투입예산의 규모 및 수행기간 등을 고려할 때 과정평가를 통해 정기적으로 사업의 진행과정을 점검할 필요가 있다 하겠다. 따라서 신재생에너지 분야의 사업의 관리에 적용될 수 있는 EERE의 과정평가를 한국의 상황에 맞게 수정하고 이를 정규적으로 시행하는 방안에 대한 논의가 필요하다 하겠다.

• Annual Conference on Human and Language Technology
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• 2013.10a
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• pp.146-151
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• 2013

이중언어 사전 구축 방법을 평가하는 방법에는 정확률, 재현율, MRR(Mean Reciprocal Rank) 등이 있다. 이들 방법들은 평가 집합에 있는 대역어를 정확하게 찾는 것에 초점을 맞추고 있다. 그러나 어떤 대역어가 얼마나 많이 사용되는지는 전혀 고려하지 않는다. 즉 자주 사용되는 대역어를 빨리 찾을 수 있는 방법이 좋은 방법이라고 말할 수 있다. 이와 같은 문제를 해결하기 위해서 본 논문에서는 이중언어 사전 구축의 새로운 평가 방법인 등급 재현율을 제안한다. 등급 재현율(rated recall)은 대역어가 학습 말뭉치에 나타난 정도를 반영하는 재현율이며, 자주 사용되는 대역어를 얼마나 정확하게 찾는지를 파악할 수 있는 좋은 측도이다. 본 논문에서는 문맥벡터와 중간언어를 이용한 이중언어 사전 구축 시스템의 성능을 평가하고 기존의 방법과 비교 분석하였다.

• Journal of Korea Fair Competition Federation
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• no.4
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• pp.20-26
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• 1995

• JOURNAL OF ELECTRICAL WORLD
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• s.409
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• pp.52-57
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• 2011

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1096-1100
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• 2010

In this paper, we propose an automatic segmentation of the meniscus based on active shape model using interpolated shape information in MR images. First, the statistical shape model of meniscus is constructed to reflect the shape variation in the training set. Second, the generation technique of interpolated shape information by using the weight according to shape similarity is proposed to robustly segment the meniscus with large variation. Finally, the automatic meniscus segmentation is performed through the active shape model fitting. For the evaluation of our method, we performed the visual inspection, accuracy measure and processing time. For accuracy evaluation, the average distance difference between automatic segmentation and semi-automatic segmentation are calculated and visualized by color-coded mapping. Experimental results show that the average distance difference was $0.54{\pm}0.16mm$ in medial meniscus and $0.73{\pm}0.39mm$ in lateral meniscus. The total processing time was 4.87 seconds on average.