• 전자공학회논문지B
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• 제33B권5호
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• pp.102-108
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• 1996

Adaptive resonance theory (ART2) characterized by its built-in mechanism of handling the stability-plasticity switching and by the adaptive learning without forgetting informations learned in the past, is based on an unsupervised template matching. We propose an improved tow-stage learning algorithm for aRT2: the original unsupervised learning followed by a new supervised learning. Each of the output nodes, after the unsupervised learning, is labeled according to the category informations to reinforce the template pattern associated with the target output node belonging to the same category some dominant classes from exhausting a finite number of template patterns in ART2 inefficiently. Experimental results on a set of 2545 FLIR images show that the ART2 trained by the two-stage learning algorithm yields better accuracy than the original ART2, regardless of th esize of the network and the methods of evaluating the accuracy. This improvement shows the effectiveness of the two-stage learning process.

• 한국전자통신학회논문지
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• 제8권4호
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• pp.569-574
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• 2013

스마트폰에서 어플리케이션을 실행하기 위해서는 많은 단계를 거치게 되며 그에 따라 많은 시간을 소비하게 된다. 따라서 본 논문에서는 ART2 알고리즘을 이용하여 잠금 상태에서 스마트폰의 어플리케이션을 쉽고 빠르게 구동하기 위한 방법을 제안한다. 자신이 원하는 그림과 설치되어있는 어플리케이션과의 대응 테이블을 만들기 위하여 학습 어플리케이션을 실행한다. 학습 어플리케이션의 동작 순서는 어플리케이션 실행 후, 화면 하단에서 빠른 실행을 하고자 하는 어플리케이션을 선택하고 좌측 상단에 위치하고 있는 입력 부분에 그림을 그린 후, 학습 버튼을 클릭한다. 그려진 그림의 배경은 0으로 그림은 1로 변환하고 ART2의 입력으로 사용할 수 있도록 일정한 크기로 정규화 한다. 정규화 된 데이터를 ART2의 입력 데이터로 적용한다. 학습이 끝난 후, 잠금 상태에서 액정 윗부분에 학습된 것과 같은 모양의 그림을 그려 해당 어플리케이션을 실행한다.

• International Journal of Contents
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• 제18권2호
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• pp.58-67
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• 2022

As the Internet rapidly evolves, online learning has emerged as the third largest scenario in the field of education. Online education, different from the two traditional learning scenarios of the school and society, is characterized with broader learning types and higher freedom. In today's post-pandemic era, art education, which relies on face-to-face teaching, is of particular significance to expand online education methods. Based on the UTAUT model, this paper posits seven hypotheses about the willingness to continue learning in online art education. After collecting valid data through a questionnaire, a detailed empirical analysis was conducted via SPSS and AMOS. The results of empirical analysis show that less than half of the respondents had experienced the online art education, mirroring that this is a market worth developing. Based on the findings, learning habit does not significantly impact art learners' willingness to continue learning online. This result and other verified hypotheses are detailed in the discussion part of this paper. This study proves that UTAUT can better explain user behavior than the traditional information system model prior to the improvement, and also has strong explanatory power in the field of art education. The conclusion also posits some operational suggestions from the perspective of practitioners in this field, thereby providing a theoretical basis for art education practitioners.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.84-87
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• 2003

This paper proposes the enhanced REF network, which arbitrates learning rate and momentum dynamically by using the fuzzy system, to arbitrate the connected weight effectively between the middle layer of REF network and the output layer of REF network. ART2 is applied to as the learning structure between the input layer and the middle layer and the proposed auto-turning method of arbitrating the learning rate as the method of arbitrating the connected weight between the middle layer and the output layer. The enhancement of proposed method in terms of learning speed and convergence is verified as a result of comparing it with the conventional delta-bar-delta algorithm and the REF network on the basis of the ART2 to evaluate the efficiency of learning of the proposed method.

• 한국통신학회논문지
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• 제30권2C호
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• pp.31-40
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• 2005

오류 역전파 알고리즘의 문제점과 ART 신경회로망의 문제점을 개선하기 위해 Jacobs가 제안한 delta-bar-delta 방법과 신경회로망을 결합한 자가 생성 지도 학습 알고리듬을 제안한다. 입력층과 은닉층에서는 ART-1과 ART-2 알고리듬을 이용하고, winner-take-all 방식은 완전 연결 구조이나 연결된 가중치만을 조정하도록 채택하였다. 실험을 위해 학생증, 주민등록증, 컨테이너의 영상으로 추출한 패턴을 신경회로망의 은닉층 노드에 대해 실험하였고, 실험결과 제안된 자기 생성 지도 학습알고리듬이 지역최소화, 학습 속도, 정체 현상이 기존의 방법보다 성능이 개선된 것을 확인하였다.

• 한국정보통신학회논문지
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• 제11권7호
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• pp.1380-1386
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• 2007

본 논문에서는 퍼지 기반 잡음 제거 방법과 ART2 기반 자가 생성 지도 학습 알고리즘을 이용한 운송 컨테이너 식별자 인식 시스템을 제안한다. 일반적으로 운송 컨테이너의 식별자들은 글자색이 검정색 또는 흰색으로 이루어져 있는 특징이 있다. 이러한 특성을 고려하여 원 컨테이너 영상에 대해 검은색과 흰색을 제외한 모든 부분을 잡음으로 처리하기 위해 퍼지를 이용한 잡음 판단 방법을 적용하여 식별자 영역과 잡음을 구별한다. 그리고 Sobel 마스크를 이용하여 에지를 검출하고, 추출된 에지를 이용하여 수직 블록과 수평 블록을 검출하여 컨테이너의 식별자 영역을 추출하고 이진화한다. 이진화된 식별자 영역에 대해 8 방향 윤곽선 추적 알고리즘을 적용하여 개별 식별자를 추출한다. 개별 식별자 인식을 위해 ART2 기반 자가 생성 지도 학습 알고리즘을 제안하여 개별 식별자 인식에 적용한다. ART2 기반 자가 생성 지도 학습 알고리즘은 일반화된 델타 학습 방법과 Delta-bar-Delta 알고리즘을 적용하여 학습 성능을 개선한다. 실제 컨테이너 영상을 대상으로 실험한 결과, 기존의 식별자 추출 방법보다 제안된 식별자 추출 방법이 개선되었다. 그리고 기존의 식별자 인식 알고리즘보다 제안된 ART2 기반 자가 생성 지도 학습 알고리즘이 식별자의 학습 및 인식에 있어서 우수한 성능이 있음을 확인하였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 춘계학술대회 논문집
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• pp.451-456
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• 1995

This study investigates the feasibility of the real time detection of tool breadage in face milling operation. The proposed methodology using an ART2 neural network overcomes a cumbersome task in terms of the learning or determining a threshold value. The features taken in the researchare the AR parameters modelled from a RLS, and those are proven to be good features for tool breakage from experiments. From the results of the off line application, we can conclude that an ART2 neural network can be well applied to the clustering of tool states in real time regardless of the unsupervised learning.

• 한국임상보건과학회지
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• 제2권4호
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• pp.231-238
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• 2014

Purpose. This study examines the effects of improving students self-esteem and sociability by conducting a Group Art Therapy Program for students with learning disabilities. This study focused on three students with learning disabilities, attending B middle school special education class located in K county. The study was conducted for two hours once a week (Friday) at B middle school during special education class from May 2, 2014 to July 18, 2014. Methods. For the tools of studying, Self-esteem and social strip forms/rubrics were filled, by students', before and after and data processing was inspected, paired t-Test using the SPSS / WIN (Ver.18.0) for quantitative analysis. Also, on the basis of content, analyzed data of the individuals' self-esteem social changes are shown in graph format. In addition, this qualitative study shows before and after of dynamic house, tree, person (K-H, T, P), dynamic family (KFD), dynamic school life of search phase (4-6 sessions) significant improvement of self-esteem and sociability in adolescents' with learning disabilities influenced by conducting a Group Art Therapy Program. Results. The result of this study can be summarized as follows. First, Group Art Therapy Program shows a statistically significant difference (p<.05) showing that self esteem average is 2.04 before Group Art Therapy Intervention but self esteem average is 2.92 after Group Art Therapy Intervention. Second, as a result of social strip pre-post, there wasn't statistically significant difference compared to self esteem pre-post result, although, post examination's average level was enhanced after Group Art Therapy Program in difference examination.(p>.05). Third, as a result of analysis the indicated pre-post change of Students' pre-post dynamic house, tree, person (HTP), dynamic family (KFD), a dynamic school daily life (KSD), students' family and interpersonal relationships, self-concept shows statistical significant changes. Conclusion. As the result of this study, Group Art Therapy Program shows effective improvement in students' self-esteem and social skills learning disabilities. However, a future study on larger and more diverse group of students' with learning disabilities are advised to be conducted in order to better understand the significance of the Group Art Therapy Program.

• 한국식생활문화학회지
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• 제35권2호
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• pp.173-180
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• 2020

This study evaluated methods of improving sustained learning participation by examining the structural relationship of school support consisting of professor support, friend-senior support and educational environment support, career decisionmaking self-efficacy, school satisfaction, and learning persistence depending on the characteristics of college students majoring in culinary art and food service. The study findings were as follows. First, the general characteristics of college students majoring in culinary art and food service were perceived significantly more by female students than by male students. Second, school support directly influenced the career decision-making self-efficacy and school satisfaction, but did not directly influence the learning persistence. Instead, school support influenced school satisfaction and learning persistence indirectly by the medium of career decision-making self-efficacy. Third, career decision-making self-efficacy directly influenced school satisfaction and learning persistence and indirectly influenced learning persistence by the medium of school satisfaction. Lastly, school satisfaction directly influenced the learning persistence, implying that school satisfaction is an important factor for the learning persistence of college students majoring in culinary art and food service. These results show that, because school members and environmental support cannot exclusively make learning persistence, diverse systems and programs must be developed and applied to improve the career decision-making self-efficacy and school satisfaction of college students majoring in culinary art and food service.

• 한국멀티미디어학회논문지
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• 제9권3호
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• pp.369-376
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• 2006

본 논문에서는 퍼지 RBF네트워크의 학습 성능을 개선하기 위하여 Delta-bar-Delta 알고리즘을 적용하여 학습률을 동적으로 조정하는 개선된 퍼지 RBF 네트워크를 제안한다. 제안된 학습 알고리즘은 일반화된 델타 학습 방법에 퍼지 C-Means 알고리즘을 결합한 방법으로, 중간층의 노드를 자가 생성하고 중간층과 출력층의 학습에는 일반화된 델타 학습 방법에 Delta-bar-Delta 알고리즘을 적용하여 학습률을 동적으로 조정하여 학습 성능을 개선한다. 제안된 RBF 네트워크의 학습 성능을 평가하기 위하여 컨테이너 영상에서 추출한 40개의 식별자를 학습 데이터로 적용한 결과, 기존의 ART2 기반 RBF 네트워크와 기존의 퍼지 RBF 네트워크 보다 학습 시간이 적게 소요되고, 학습의 수렴성이 개선된 것을 확인하였다.