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환경과 어학능력점수에 따른 한국 성인 학습자들의 영어불안감 양상
고지은(Jieun Ko),최윤덕(YunDeok Choi),이혜문(Haemoon Lee) 한국응용언어학회 2020 응용 언어학 Vol.36 No.4
This paper presents the unique patterns of anxiety observed in adult Korean English as a Foreign Language (EFL) learners. Through the survey consisting of 40 questions, 135 participants’ anxiety about EFL was examined in relation to the English-using environment -both inside and outside of the classroom-and TOEIC scores. The statistical analysis showed that there was no significant difference in anxiety depending on the English using environment. However, unlike previous research, participants with higher test scores tended to show higher levels of anxiety than those with lower test scores, and the effect of the test scores on anxiety was significant. In addition, there was no significant interaction effect between the English using environment and the test scores on anxiety. The concluding discussions include that the Korean learners’ goal for high proficiency test scores led to their conscious processing of their declarative knowledge or self-monitoring in all types of English environments, which in turn led to high levels of anxiety as their explicit and conscious knowledge increased up to the proficiency test score level expected by society.
고지은(Jieun Ko),이성길(Sungkil Lee) 한국정보과학회 2021 정보과학회논문지 Vol.48 No.5
본 논문은 다트 던지기 기법을 통하여 샘플링 영역을 결정하는 격자구조 샘플링 방식을 제안한다. 영상처리, 컴퓨터 그래픽스 등 다양한 분야에서 활용되는 확률적 샘플링 기법은 샘플이 균일한 랜덤분포를 가질수록 고품질의 이미지를 생산한다. 이 중 블루노이즈의 특성을 가진 패턴은 낮은 주파수 영역을 제거하며 계단 현상 문제를 해결하는데 중요한 역할을 한다. 다만 이 특성을 가진 패턴은 샘플링 생성 부하가 높아 격자구조 샘플링과 같은 패턴이 제안되었으나 격자 구조로 인하여 랜덤성이 낮다. 본 논문은 격자구조에서 샘플링 영역을 다트 던지기 기법을 통해 결정하여 랜덤성을 높이는 방식을 제안한다. 샘플링 영역을 무작위로 샘플링할 영역을 결정한 후 그 영역 내에서 랜덤하게 샘플의 위치를 결정한다. This paper presents a stratified sampling technique in which sampling areas are chosen through the dart-throwing technique. Stochastic sampling techniques, which are used in various fields such as image processing and computer graphics, produce images of high quality as samples distribute uniformly and randomly. The blue-noise pattern removes low-frequency areas that are critical in the aliasing problem, but computing such a pattern is costly. To address this issue, stratified sampling methods have been proposed; however, the method demonstrates low randomness due to the structure. This paper proposes a technique to increase randomness by determining the sampling area in the stratified structure through the dart-throwing technique. Our method randomly samples areas in which samples are jittered.
전아영,고지은,김종영,Jeon, A Young,Ko, Jieun,Kim, Jong-Young 한국결정성장학회 2013 韓國結晶成長學會誌 Vol.23 No.1
본 연구팀에서는 층상형 페로브스카이트 구조를 갖는 Ruddlesden-Popper 구조의 $K_2La_2Ti_3O_{10}$의 박리화를 통해 Aurivillius 구조의 $Bi_{4-x}La_xTi_3O_{12}$(x~2) 페로브스카이트 산화물을 성공적으로 합성하였다. 박리화된 란타늄 티타네이트 나노시트는 BiOCl 나노결정구조와 반응시켜 $Bi_{4-x}La_xTi_3O_{12}$(x~2) 결정을 얻어내었다. 박리화된 나노시트 현탁액은 $K_2La_2Ti_3O_{10}$으로부터 수소화된 $H_2La_2Ti_3O_{10}$의 층간에 에틸아민을 삽입시킴으로써 얻어내었다. 투과전자현미경(TEM) 분석을 통해, 란타늄 티타네이트가 에틸아민에 의해 박리화된 것을 확인할 수 있었다. X-선 회절분석(XRD)을 통해, 박리화된 란타늄 티타네이트와 BiOCl의 재적층과정을 거쳐 $700^{\circ}C$ 이상의 열처리 조건에서 $Bi_{4-x}La_xTi_3O_{12}$(x~2)로 형성된 것을 확인할 수 있었다. We have successfully synthesized $Bi_{4-x}La_xTi_3O_{12}$ (x~2) having Aurivillius-type layered perovskite structure from exfoliated layered perovskite oxide of $K_2La_2Ti_3O_{10}$ with Ruddlesden-Popper structure. The reaction between the exfoliated lanthanum titanate nanosheets and BiOCl nanocrystal resulted in the formation of polycrystalline $Bi_{4-x}La_xTi_3O_{12}$ (x~2) after heating above $700^{\circ}C$. Colloidal suspension of the nanosheets could be obtained by intercalating ethylamine (EA) into the protonated lanthanum titanate, $H_2La_2Ti_3O_{10}$, derived from $K_2La_2Ti_3O_{10}$. Transmission electron microscopic (TEM) analysis show that the exfoliated lanthanium titanate nanosheets have a thickness of a few nano meters. According to X-ray diffraction (XRD) analysis, the exfoliated lanthanium titanate was found to be transformed into $Bi_{4-x}La_xTi_3O_{12}$ (x~2) after restacking with BiOCl and subsequent thermal treatment at > $700^{\circ}C$.
서상우(Sangwoo Seo),김승현(Seunghyeon Kim),고지은(Jieun Ko),김창익(Changick Kim) 대한전자공학회 2020 대한전자공학회 학술대회 Vol.2020 No.11
Domain generalization aims to generalize a model to a previously unseen domain. Generalizing the model by narrowing the gap between the domains of training data and test data is an essential task for applying the neural network model to reality. In this paper, we adopt meta-dropout technique to domain generalization settings that can perturb the training examples. We parameterize and train noise so that general decision boundaries can be more accurately predicted. Experimental results on the PACS dataset have shown that the proposed method yields superior performance than existing methods.