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학문 목적 한국어 학습자를 위한 독서 수업 개발과 적용
권혜경 ( Kwon¸ Hyekyoung ) 한국독서학회 2020 독서연구 Vol.0 No.57
이 연구의 목적은 학문 목적 한국어 학습자들이 교육용 교재의 한계에서 벗어나 자율적으로 한국어 도서를 선택하여 읽음으로 읽기에 대한 흥미와 관심을 향상시킬 수 있는 독서 수업을 개발하는 데 있다. 이를 위하여 학습자를 위한 독서 수업을 설계하고 실제 B대학교의 한국어 학습자 36명을 대상으로 수업을 적용하고 그 결과를 분석하였다. 학습자들은 15주 동안의 수업에서 각각 2권의 책을 읽었으며 개별적으로 읽은 독서량은 평균 412페이지였다. 또한 설문 조사 결과 학습자들은 독서수업을 통해 글의 이해 능력이 더 좋아졌다(69%), 한국어 수준이 향상되었다(55%), 나의 읽기 속도가 빨라졌다(42%)고 답했다. 결과적으로 학습자들은 독서 수업을 통해 한국어 실력이 향상되었을 뿐만 아니라 한국어로 된 단행본을 스스로 완독했다는 사실에 매우 만족하였다. 또한 다수의 학습자들이 수업이 끝난 후에도 계속 독서를 하고 싶다는 의사를 적극적으로 표현하였다. This study aims to develop a reading class in which Korean learners in academia can devote their attention to and raise their interest in reading. This can be achieved by allowing them to select and read Korean books autonomously, free from the limitations of educational textbooks. To this end, a reading class for learners was designed, said class was applied to 36 Korean language learners at B University, and the results were analyzed. The learners read two books for 15 weeks, during which time, on average, each individual read 412 pages. The results of a survey revealed that the learners felt that the reading class improved their ability to understand texts (69%), their Korean level (55%), and their reading speed (42%). Consequently, learners were considerably satisfied that they could read books in Korean by themselves and that they also improved their Korean proficiency through the reading class. In addition, many learners actively expressed their desire to continue reading Korean books after this class was over.
Semi-Supervised Nonnegative Matrix Factorization
Hyekyoung Lee,Jiho Yoo,Seungjin Choi IEEE 2010 IEEE signal processing letters Vol.17 No.1
<P>Nonnegative matrix factorization (NMF) is a popular method for low-rank approximation of nonnegative matrix, providing a useful tool for representation learning that is valuable for clustering and classification. When a portion of data are labeled, the performance of clustering or classification is improved if the information on class labels is incorporated into NMF. To this end, we present semi-supervised NMF (SSNMF), where we jointly incorporate the data matrix and the (partial) class label matrix into NMF. We develop multiplicative updates for SSNMF to minimize a sum of weighted residuals, each of which involves the nonnegative 2-factor decomposition of the data matrix or the label matrix, sharing a common factor matrix. Experiments on document datasets and EEG datasets in BCI competition confirm that our method improves clustering as well as classification performance, compared to the standard NMF, stressing that semi-supervised NMF yields semi-supervised feature extraction.</P>
A Retrospective Study of Bimodal Benefits of Cochlear Implant Children
Hyekyoung Hwang,Timothy Kim,Leehwa Park,오수희 한국청각언어재활학회 2022 Audiology and Speech Research Vol.18 No.1
Purpose: Bimodal children showed various improvements in speech, language, and music perception. The purpose of this study is to investigate bimodal benefits and bimodal hearing aid fitting of cochlear implant children with a retrospective chart review. Methods: A total of 44 charts of cochlear implant children were retrospectively reviewed in this study. Hearing thresholds, word recognition scores, and hearing aid fitting procedures were reviewed and summarized. Results: Bimodal children showed 4%points improvements in word recognition scores and 30~40 gains across frequencies with hearing aids. For bimodal hearing aid fitting, all children used desired sensation level v5 fitting formula with wide frequency bands. Real ear measurements were performed to match with targets and loudness balancing across ears was also conducted. Hearing thresholds with and without hearing aids were not correlated with word recognition scores in bimodal condition. Conclusion: Bimodal children showed improved hearing thresholds with hearing aids and little bimodal benefits in word recognition tests. Additional protocols including speech in noise tests, subjective questionnaires are recommended to evaluate bimodal benefits.
Persistent Brain Network Homology From the Perspective of Dendrogram
Hyekyoung Lee,Hyejin Kang,Chung, M. K.,Bung-Nyun Kim,Dong Soo Lee IEEE 2012 IEEE transactions on medical imaging Vol.31 No.12
<P>The brain network is usually constructed by estimating the connectivity matrix and thresholding it at an arbitrary level. The problem with this standard method is that we do not have any generally accepted criteria for determining a proper threshold. Thus, we propose a novel multiscale framework that models all brain networks generated over every possible threshold. Our approach is based on persistent homology and its various representations such as the Rips filtration, barcodes, and dendrograms. This new persistent homological framework enables us to quantify various persistent topological features at different scales in a coherent manner. The barcode is used to quantify and visualize the evolutionary changes of topological features such as the Betti numbers over different scales. By incorporating additional geometric information to the barcode, we obtain a single linkage dendrogram that shows the overall evolution of the network. The difference between the two networks is then measured by the Gromov-Hausdorff distance over the dendrograms. As an illustration, we modeled and differentiated the FDG-PET based functional brain networks of 24 attention-deficit hyperactivity disorder children, 26 autism spectrum disorder children, and 11 pediatric control subjects.</P>
다채널 뇌파 분류를 위한 주성분 분석 기반 선형동적시스템
이혜경(Hyekyoung Lee),최승진(Seungjin Choi) 한국정보과학회 2002 한국정보과학회 학술발표논문집 Vol.29 No.2Ⅱ
EEG-based brain computer interface (BCI) provides a new communication channel between human brain and computer. The classification of EEG data is an important task in EEG-based BCI. In this paper we present methods which jointly employ principal component analysis (PCA) and linear dynamical system (LDS) modeling for the task of EEG classification. Experimental study for the classification of EEG data during imagination of a left or right hand movement confirms the validity of our proposed methods.