• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.591-601
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• 2020

The self-organizing map (SOM) is a unsupervised learning method projecting high-dimensional data into low-dimensional nodes. It can visualize data in 2 or 3 dimensional space using the nodes and it is available to explore characteristics of data through the nodes. To understand the structure of data, cluster analysis is often used for nodes obtained from SOM. In cluster analysis, the optimal number of clusters is one of important issues. To help to determine it, various cluster validity indexes have been developed and they can be applied to clustering outcomes for nodes from SOM. However, while SOM has an advantage in that it reflects the topological properties of original data in the low-dimensional space, these indexes do not consider it. Thus, we propose a new cluster validity index for SOM based on connectivity between nodes which considers topological properties of data. The performance of the proposed index is evaluated through simulations and it is compared with various existing cluster validity indexes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2C
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• pp.31-40
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• 2005

we propose an enhanced self-generation supervised algorithm that by combining an ART algorithm and the delta-bar-delta method. Form the input layer to the hidden layer, ART-1 and ART-2 are used to produce nodes, respectively. A winner-take-all method is adopted to the connection weight adaption so that a stored pattern for some pattern is updated. we test the recognition of student identification, a certificate of residence, and an identifier from container that require nodes of hidden layers in neural network. In simulation results, the proposed self-generation supervised learning algorithm reduces the possibility of local minima and improves learning speed and paralysis than conventional neural networks.

• Annual Conference on Human and Language Technology
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• 1995.10a
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• pp.39-42
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• 1995

문장 안에서 한 단어가 가지는 올바른 의미를 얻기 위해 모듈화된 신경망을 이용하였다. 앞부분에 놓인 신경망은 코호넨 신경망으로 사용자의 지도가 개입되지 않은 상태로 자율학습(Unsupervised learning)이 이루어지고, 뒤에 놓인 신경망은 앞에서 결과로 얻은 2차원의 자기 조직화 형상지도(Self-organizing feature map)를 바탕으로 역전파 신경망을 이용한 지도학습(Supervised learning)을 하게 하였다. 입력 자료는 구문분석된 문장의 조사 정보를 활용하여 입력 위치를 정해준 명사의 의미표지와 동사의 의미표지를 사용하였다. 중의성이 있는 단어를 가지는 문장은 중의성의 가지수 만큼 테스트 입력 자료가 되어 신경망을 통과하여 의미를 결정하도록 한다.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.187-197
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• 2020

Recently, various methods of text embedding using deep learning algorithms have been proposed. Especially, the way of using pre-trained language model which uses tremendous amount of text data in training is mainly applied for embedding new text data. However, traditional pre-trained language model has some limitations that it is hard to understand unique context of new text data when the text has too many tokens. In this paper, we propose self-supervised learning-based fine tuning method for pre-trained language model to infer vectors of long-text. Also, we applied our method to news articles and classified them into categories and compared classification accuracy with traditional models. As a result, it was confirmed that the vector generated by the proposed model more accurately expresses the inherent characteristics of the document than the vectors generated by the traditional models.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.316-318
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• 2001

본 논문에서는 자기조직화 형상지도(Self-organizing Feature Maps)를 사용하여 움직이는 물체에 대해 움직임의 특성을 자동으로 분석하였다. Kohonen Network는 자기조직을 형성하는 unsupervised learning 알고리즘으로서, 이 논문에서는 생태계에서의 데이터를 Patternizing하고, Clustering 하는데 사용한다. 본 논문에서 Kohonen 신경망의 학습에 사용한 데이터는 CCD 카메라로 물고기의 움직임을 추적한 좌표 데이터이며, diazinon 0.1 ppm을 처리한 물고기 점 데이터와 처리하지 않은 점 데이터를 각각 낮.밤 약 10시간동안 수집하여, \circled1처리전 낮 데이터 \circled2처리전 밤 데이터 \circled3처리전 낮 데이터 \circled4처리후 밤 데이터 각각 4개의 group으로 분류한 후, Kohonen Network을 사용하여 물고기의 행동 차이를 분석하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.170-180
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• 2011

The purposes of this study are to find out the effectiveness of the tutoring program and the level of self-regulated learning ability in tutoring program attending students. This study has been performed for team-tutoring program attending students(n=183) who are in 15 department, D college in Daegu. Following results were drawn thought correlation analyses of variables obtained during the survey period. The results were as follows; There was statistically significant difference among perception controlling ability, purpose controlling ability, and action controlling ability. In over 20 ages, organization, meta-perception stratagem, arrangement, self-effectiveness, controlling learning time ability were higher than of lower 20 ages(p<0.05). In tutors, demonstration, organization, meta-perception stratagem, arrangement, checking, purpose intentions, self- effectiveness, achievement, controlling action, help requirement ability were higher than tutees(p<0.05). As results, the tutoring program was effective for both tutors and tutees in college students. Further studies in an education program for students in all years should be implemented to examine tutoring effects. Implementation of tutoring should address the frustrations and difficulties encountered by the students to facilitate better outcomes.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.514-517
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• 2023

본 연구는 인 컨택스트 러닝 (In-Context Learning)을 오디오-언어 작업에 적용하기 위한 멀티모달 (Multi-Modal) 딥러닝 모델을 다룬다. 해당 모델을 통해 학습 단계에서 오디오와 텍스트의 소통 가능한 형태의 표현 (Representation)을 학습하고 여러가지 오디오-텍스트 작업을 수행할 수 있는 멀티모달 딥러닝 모델을 개발하는 것이 본 연구의 목적이다. 모델은 오디오 인코더와 언어 인코더가 연결된 구조를 가지고 있으며, 언어 모델은 6.7B, 30B 의 파라미터 수를 가진 자동회귀 (Autoregressive) 대형 언어 모델 (Large Language Model)을 사용한다 오디오 인코더는 자기지도학습 (Self-Supervised Learning)을 기반으로 사전학습 된 오디오 특징 추출 모델이다. 언어모델이 상대적으로 대용량이기 언어모델의 파라미터를 고정하고 오디오 인코더의 파라미터만 업데이트하는 프로즌 (Frozen) 방법으로 학습한다. 학습을 위한 과제는 음성인식 (Automatic Speech Recognition)과 요약 (Abstractive Summarization) 이다. 학습을 마친 후 질의응답 (Question Answering) 작업으로 테스트를 진행했다. 그 결과, 정답 문장을 생성하기 위해서는 추가적인 학습이 필요한 것으로 보였으나, 음성인식으로 사전학습 한 모델의 경우 정답과 유사한 키워드를 사용하는 문법적으로 올바른 문장을 생성함을 확인했다.

• Journal of the Korean School Mathematics Society
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• v.13 no.1
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• pp.69-88
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• 2010

This paper is the case study how we can apply the appropriate teaching method in order to correct the misconception of middle and high school students in preservice teachers' education. Through the review of previous research and literature, we categorized students' misconception and sought the teaching method to teach preservice teachers. During this process, we did according to PBL and preservice teachers also tried to find the teaching method for students. And thus we were able to suggest the appropriate teaching method which was effective in correcting the misconception of middle & high school students along with their fine understanding of mathematical concepts. Further, preservice teachers acknowledged cooperative teaching & learning and the importance of it as well as the self-directed teaching and learning.

• The Korean Nurse
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• v.16 no.1 s.87
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• pp.39-45
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• 1977

이 Resendahl의 문헌을 읽고 나는 두 가지 면에서 모든 간호학도에게 이 글을 읽기를 강권하고 싶은 생각이 났다. 첫째는 ; 오늘날 우리가 지향하는 이상적인 간호사업을 이룩하기 위하여, 둘째는 ; 현시대와 사외가 우리에게 요구하는 건강사업을 독자적이고 지도적 입장에서 이룩하기 위한 전략에 기본적인 원리로서 교수나 학생, 또한 임상간호학자(임상간호원)가 자기가 하는 일을 원숙하게 이행해 나가기 위해서는 깊이 동감할 수 있고 귀히 참고할 만한 문헌이라고 생각하여 여기 옮겨본다. 1976년 11월 하순 어느 눈 내리는 조용한 주일 아침 탈고하다.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.239-245
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• 2021

In order to analyze the educational effect of learning mentoring conducted for 4 weeks by the Korea Educational Broadcasting System(EBS) for elementary school students, the changes in self-directed learning skills and emotional stability were analyzed through pre-test and post-test for 27 students who participated in the EBS learning mentoring. As a result, it was found that students' self-directed learning ability and emotional stability were both improved. In addition, the students showed high satisfaction with the mentor who guided their learning and taught them. Therefore, in order to reduce the learning gap of underprivileged students in the distance learning situation, the EBS learning mentoring project should be continuously promoted, and the mentoring period and the number of students and teachers participating in mentoring should be significantly increased.