• Title/Summary/Keyword: 뇌 기반 학습

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Prediction of Cognitive Impairment Using Blood Gene Expression Based on Machine Learning (혈액 유전자 발현을 이용한 기계학습 기반 인지장애 예측)

  • Lee, Seungeun;Zhou, Yu;Kang, Kyungtae
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2022.07a
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    • pp.61-62
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    • 2022
  • 알츠하이머성 치매는 현존하는 치료법이 없어 경도인지장애 단계에서의 예방이 중요하다. 지금까지의 알츠하이머 연구는 대부분이 뇌영상 마커와 뇌척수액 마커에 집중되어 있었으며, 경도 인지 장애 단계에서의 탐색은 더욱 적었다. 이러한 점에서 혈액 유전자 발현을 이용한 경도 인지장애 단계 예측은 인지 능력에 따른 관련 유전자 식별과 접근 가능한 진단 및 치료 바이오 마커 탐색에 기여할 수 있다. 그러나 유전자 발현 데이터의 경우 환자 수에 비해 높은 차원을 가지기 때문에 과적합을 막고 질병 관련 유전자를 식별하기 위해서는 데이터에서의 의미 있는 차원만을 뽑아내는 차원 축소가 선행되야 한다. 본 연구는 유전자 발현데이터에서의 인지장애 분류를 위해 차원 축소기법과 신경망을 적용하여 인지 장애 정도를 예측하였다. 그 결과, Lasso 이용 차원축소와 신경망을 이용하여 97%의 정확도로 정상과 조기 경도 인지장애, 후기 경도 인지장애 환자를 분류 할 수 있었으며, 더 적은 차원에서도 분류가 가능했다. 이는 혈액 유전자 발현을 이용해 경도 인지장애 단계를 예측한 첫 번째 연구이며, 인지능력 저하에 따른 혈액 유전자 발현의 연관성을 확인하고 향후 조기 진단, 치료 표적 탐색에 기여한다.

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Feature Analysis of Multi-Channel Time Series EEG Based on Incremental Model (점진적 모델에 기반한 다채널 시계열 데이터 EEG의 특징 분석)

  • Kim, Sun-Hee;Yang, Hyung-Jeong;Ng, Kam Swee;Jeong, Jong-Mun
    • The KIPS Transactions:PartB
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    • v.16B no.1
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    • pp.63-70
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    • 2009
  • BCI technology is to control communication systems or machines by brain signal among biological signals followed by signal processing. For the implementation of BCI systems, it is required that the characteristics of brain signal are learned and analyzed in real-time and the learned characteristics are applied. In this paper, we detect feature vector of EEG signal on left and right hand movements based on incremental approach and dimension reduction using the detected feature vector. In addition, we show that the reduced dimension can improve the classification performance by removing unnecessary features. The processed data including sufficient features of input data can reduce the time of processing and boost performance of classification by removing unwanted features. Our experiments using K-NN classifier show the proposed approach 5% outperforms the PCA based dimension reduction.

Automatic Extraction of Image Bases Based on Non-Negative Matrix Factorization for Visual Stimuli Reconstruction (시각 자극 복원을 위한 비음수 행렬 분해 기반의 영상 기저 자동 추출)

  • Cho, Sung-Sik;Park, Young-Myo;Lee, Seong-Whan
    • Korean Journal of Cognitive Science
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    • v.22 no.4
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    • pp.347-364
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    • 2011
  • In this paper, we propose a automatic image bases extraction method for visual image reconstruction from brain activity using Non-negative Matrix Factorization (NMF). Image bases are basic elements to construct and present a visual image. Previous method used brain activity that evoked by predefined 361 image bases of four different sizes: $1{\times}1$, $2{\times}1$, $1{\times}2$, $2{\times}2$, and $2{\times}2$. Then the visual stimuli were reconstructed by linear combination of all the results from these image bases. While the previous method used 361 predefined image bases, the proposed method automatically extracts image bases which represent the image data efficiently. From the experiments, we found that the proposed method reconstructs the visual stimuli better than the previous method.

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Implementation of Autonomous IoT Integrated Development Environment based on AI Component Abstract Model (AI 컴포넌트 추상화 모델 기반 자율형 IoT 통합개발환경 구현)

  • Kim, Seoyeon;Yun, Young-Sun;Eun, Seong-Bae;Cha, Sin;Jung, Jinman
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.5
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    • pp.71-77
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    • 2021
  • Recently, there is a demand for efficient program development of an IoT application support frameworks considering heterogeneous hardware characteristics. In addition, the scope of hardware support is expanding with the development of neuromorphic architecture that mimics the human brain to learn on their own and enables autonomous computing. However, most existing IoT IDE(Integrated Development Environment), it is difficult to support AI(Artificial Intelligence) or to support services combined with various hardware such as neuromorphic architectures. In this paper, we design an AI component abstract model that supports the second-generation ANN(Artificial Neural Network) and the third-generation SNN(Spiking Neural Network), and implemented an autonomous IoT IDE based on the proposed model. IoT developers can automatically create AI components through the proposed technique without knowledge of AI and SNN. The proposed technique is flexible in code conversion according to runtime, so development productivity is high. Through experimentation of the proposed method, it was confirmed that the conversion delay time due to the VCL(Virtual Component Layer) may occur, but the difference is not significant.

Brain Correlates of Emotion for XR Auditory Content (XR 음향 콘텐츠 활용을 위한 감성-뇌연결성 분석 연구)

  • Park, Sangin;Kim, Jonghwa;Park, Soon Yong;Mun, Sungchul
    • Journal of Broadcast Engineering
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    • v.27 no.5
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    • pp.738-750
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    • 2022
  • In this study, we reviewed and discussed whether auditory stimuli with short length can evoke emotion-related neurological responses. The findings implicate that if personalized sound tracks are provided to XR users based on machine learning or probability network models, user experiences in XR environment can be enhanced. We also investigated that the arousal-relaxed factor evoked by short auditory sound can make distinct patterns in functional connectivity characterized from background EEG signals. We found that coherence in the right hemisphere increases in sound-evoked arousal state, and vice versa in relaxed state. Our findings can be practically utilized in developing XR sound bio-feedback system which can provide preference sound to users for highly immersive XR experiences.

Development of mobile-application based cognitive training for Menopausal Women with Cognitive Complaints (갱년기 여성을 위한 앱 기반의 인지기능훈련 프로그램 개발)

  • Kim, Ji-Hyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.5
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    • pp.150-166
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    • 2020
  • Based on the theory of cognitive reserve, we undertook this study to develop a cognitive function training program for woman in menopausal transition with complaints of declining in cognitive function. The program was established by applying the analysis, design, and development stages of the network-based instructional system designed by Jung. The cognitive function training program developed by us is an was an 8-week program composed of cognitive and video training using a mobile application. The program consists of 24 sessions, each with 20-30 minutes of duration, to be completed 3 sessions per week. The contents of the cognitive function training comprise of memory, attention, language function, and scenario-based problem-solving for executive functions, all of which are cognitive areas found to be the most vulnerable for menopausal women. The educational contents were developed for eight subject areas, one subject area per week, including the definition of menopause, its causes and symptoms, menopause and brain function, etc. During the pilot test, the cognitive function training program was applied to 10 menopausal women who complained of cognitive function decline. The results indicated that, after eight weeks of training, the overall cognitive function of participants increased, revealing statistically significant differences (t=-3.04, p=.014) after the program was completed. The mobile app-based cognitive function training program might not only improve patients' memory functions but also potentially reduce the incidence of dementia.

Analyses on Elementary Students' Science Attitude and Topics of Interest in Free Inquiry Activities according to a Brain-based Evolutionary Science Teaching and Learning Model (뇌 기반 진화적 과학 교수학습 모형을 적용한 초등학교 학생의 자유 탐구 활동에서 과학 태도와 흥미 주제 영역 분석)

  • Lim, Chae-Seong;Kim, Jae-Young;Baek, Ja-Yeon
    • Journal of Korean Elementary Science Education
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    • v.31 no.4
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    • pp.541-557
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    • 2012
  • Interest is acknowledged to be a critical motivational variable that influences learning and achievement. The purpose of this study was to investigate the interest of the elementary students when free inquiry activities were performed through a brain-based evolutionary scientific teaching and learning model. For this study, 106 fifth grade students were chosen and performed individually free inquiry activities. The results of this study were as follows: First, after free inquiry activities, as to free inquiry science related attitude, a statistically significant difference was not observed. But they came to have positive feelings about the free inquiry. Especially students marked higher mean score in openness showed consistency in sub-areas of free inquiry science related attitude. Second, students had interests in various fields, especially they had many interests in area of biology. They chose inquiry subjects that seems to be easily accessible from surrounding and as an important criterion of free inquiry they thought the possibility that they could successfully perform it. And students who belong to the high level in the science related attitudes and academic achievement diversified more topics. Third, most of students failed to further their topics. However, the students who specifically and clearly extended their topics suggested appropriate variables in their topics. On the other hand, students who couldn't elaborate their topics were also failed to suggest further topics and their performance of inquiry was more incomplete. In conclusion, the experiences of success in free inquiry make the science attitude of students more positive and help them extend their inquiry. These results have fundamental implications for the authentic science inquiry in the elementary schools and for the further research.

The Effects of Brain-Based STEAM Teaching-Learning Program on Creativity and Emotional Intelligence of the Science-Gifted Elementary Students and General Students (뇌 기반 STEAM 교수-학습 프로그램이 초등과학영재와 초등일반학생의 창의성과 정서지능에 미치는 효과)

  • Ryu, Je Jeong;Lee, Kil-Jae
    • Journal of Korean Elementary Science Education
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    • v.32 no.1
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    • pp.36-46
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    • 2013
  • The creative thinking and emotional trainings are very important educational issues in the knowledge-information-based future society. Recently STEAM education is suggested as one of the educational solutions to prepare the future society. The aims of this study are to develop STEAM teaching-learning program and analyze its effects on the creativity and emotional intelligence of science-gifted and general students in elementary school. Four different subject matters based on the 2007-revised curriculum were selected to construct the brain-based STEAM teaching-learning program consisting of 12 class hours. The program was applied to 50 elementary general students and 19 science-gifted elementary students. The findings of this research are as follows. The brain-based STEAM programs is effective to improve the creativity and emotional intelligence of science-gifted and general elementary students after class. The creativity of two groups was not statistically different before the class. However after class, the creativity of gifted-science students is significantly higher than that of general students. The emotional intelligence of gifted-science students was higher than that of general students before the class. Therefore in oder to analyze the different effects of the program on two groups in emotional intelligence, the test results of both group of students were analyzed by ANCOVA after class. This analysis also showed that the program is more effective in gifted-science students to improve the emotional intelligence compared to general students.

The Analysis of Researches on the Brain-based Teaching and Learning for Elementary Science Education (초등과학교육에의 적용을 위한 뇌-기반 학습 연구의 교육적 의미 분석)

  • Choi, Hye Young;Shin, Dong-Hoon
    • Journal of Korean Elementary Science Education
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    • v.33 no.1
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    • pp.140-161
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    • 2014
  • The purpose of this study was to analyze 181 papers about brain-based learning appeared in domestic scientific journals from 1989 to May of 2012 and suggest application conditions in elementary science education. The results of this study summarizes as follows; First, learning activity suggested by brain-based learning study is mainly explained by working of brain function. Learning activity explained by brain-based learning study are divided into 'learning according to specialized brain function, learning according to brain function integration and learning beyond specialization and integration of hemispheres'. Second, it searched how increased knowledge of brain structure and function affects learning. Analysis from this point of view suggests that brain-based learning study affects learning in many ways especially emotion, creativity and learning motivation. Third, brain-based learning study suggests various possibilities of learning activity reflecting brain plasticity. Plasticity which is one of most important characteristics of brain supports the validity of learning activity as learning disorder treatment and explains the possibility of selective increment of brain function by leaning activity and the need of whole-brain approach to learning activity. Fourth, brain-based learning brought paradigm shifts in education field. It supports learning sophistication on the understanding of student's learning activity, guides learning method that reflects the characteristics of subject and demands reconstruction of curriculum. Fifth, there are many conditions to apply brain-based learning in elementary science education field, learning environment that fits brain-based learning, change of perspectives on teaching and learning of science educators and development of brain-based learning curriculum are needed.

Analyses of Elementary School Students' Interests and Achievements in Science Outdoor Learning by a Brain-Based Evolutionary Approach (뇌기반 진화적 접근법에 따른 과학 야외학습이 초등학생들의 흥미와 성취도에 미치는 영향)

  • Park, Hyoung-Min;Kim, Jae-Young;Lim, Chae-Seong
    • Journal of Korean Elementary Science Education
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    • v.34 no.2
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    • pp.252-263
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    • 2015
  • This study analyzed the effects of science outdoor activity applying a Brain-Based Evolutionary (ABC-DEF) approach on elementary school students' interest and academic achievement. Samples of the study were composed of 3 classes of 67 sixth graders in Seoul, Korea. Unit of 'Ecosystem and Environment' was selected as a object of the research. Textbook- and teachers' guidebook-based instruction was implemented in comparison group, brain-based evolutionary approach within classroom in experimental group A, and science outdoor learning by a brain-based evolutionary approach in experimental group B. In order to analyze the quantitative differences of students' interests and achievements, three tests of 'General Science Attitudes', 'Applied Unit-Related Interests', and 'Applied Unit-Related Achievement' were administered to the students. To find out the characteristics which would not be apparently revealed by quantitative tests, qualitative data such as portfolios, daily records of classroom work, and interview were also analyzed. The major results of the study are as follows. First, for post-test of interest, a statistically significant difference between comparison group and experimental group B was found. Especially, the 'interests about biology learning' factor, when analyzed by each item, was significant in two questions. Results of interviews the students showed that whether the presence or absence of outdoor learning experience influenced most on their interests about the topic. Second, for post-test of achievement, the difference among 3 groups according to high, middle, and low levels of post-interest was not statistically significant, but the groups of higher scores in post-interest tends to have higher scores in post-achievement. It can be inferred that outdoor learning by a brain-based evolutionary approach increases students' situational interests about leaning topic. On the basis of the results, the implications for the research in science education and the teaching and learning in school are discussed.