• 정보처리학회논문지A
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• 제13A권6호
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• pp.555-560
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• 2006

초창기 원격교육은 단순히 현장강의를 녹화하는 방식을 사용하였으나 최근의 원격교육은 학습 효율을 극대화할 수 있는 추가적인 기능을 제공하는데 주력하고 있다. 텍스트, 그래픽, 사운드, 애니메이션 등 멀티미디어 정보의 활용은 이러한 추가적인 기능을 부여하는데 필수적인 요소로 간주된다. 본 논문에서는 이러한 멀티미디어 정보 활용은 물론, 특히 실행파일 시연 기능을 수행할 수 있는 인코더/디코더를 설계하고 구현하고자 한다. 이 기능에 의해 교수자로서는 강의도중 필요한 모든 종류의 실행파일 또는 응용 프로그램 데이터 파일을 자유로이 시연할 수 있으며, 학습자 역시 스스로 해당 실행파일을 자유로이 실행해 봄으로써 상대적으로 높은 학습효과를 성취할 수 있다.

• 전기전자학회논문지
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• 제12권1호
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• pp.65-74
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• 2008

패턴 분류에 많이 사용되는 기법 중의 하나인 메모리 기반 추론 알고리즘은 단순히 메모리에 저장하고 분류 시에 저장된 패턴과 테스트 패턴간의 거리를 계산하여 가장 가까운 학습패턴의 클래스로 분류하는 기법이기 때문에 패턴의 개수가 늘어나면 메모리가 증가하고 또한 추가로 패턴이 발생할 경우 처음부터 다시 수행해야하는 문제점을 가지고 있다. 이러한 문제점을 해결하기 위하여 이미 학습한 대표패턴을 기억하고 새로 들어오는 패턴에 대해서만 학습하는 점진적 학습 방법을 제안한다. 즉 추가로 학습패턴이 발생할 경우 매번 전체 학습 패턴을 다시 학습하는 것이 아니라, 새로 추가된 데이터만을 학습하여 대표패턴을 추출하여 메모리사용을 줄이는 iMPA(incremental Multi Partition Averaging)기법을 제안하였다. 본 논문에서 제안한 기법은 대표적인 메모리기반 추론 기법인 k-NN 기법과 비교하여 현저하게 줄어든 대표패턴으로 유사한 분류 성능을 보여주며, 점진적 특성을 지닌 NGE 이론을 구현한 EACH 시스템과 점진적인 실험에서도 탁월한 분류 성능을 보여준다.

• Journal of Advanced Marine Engineering and Technology
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• 제21권1호
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• pp.66-70
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• 1997

In this paper a new learning algorithm for curvature smoothing and improved generalization for multi-layer neural networks is proposed. To enhance the generalization ability a constraint term of hidden neuron activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. When the total cost consisted of the output error and hidden error is minimized by gradient-descent methods, the additional descent term gives not only the Hebbian learning but also the synaptic weight decay. Therefore it incorporates error back-propagation, Hebbian, and weight decay, and additional computational requirements to the standard error back-propagation is negligible. From the computer simulation of the time series prediction with Santafe competition data it is shown that the proposed learning algorithm gives much better generalization performance.

• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.412-419
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• 2022

The amount of digital text data is growing exponentially, and many machine learning solutions are being used to monitor and manage this data. Artificial intelligence and machine learning are used in many areas of our daily lives, but the underlying processes and concepts are not easy for most people to understand. At a time when many experts are needed to run a machine learning solution, no-code machine learning tools are a good solution. No-code machine learning tools is a platform that enables machine learning functions to be performed without engineers or developers. The latest No-Code machine learning tools run in your browser, so you don't need to install any additional software, and the simple GUI interface makes them easy to use. Using these platforms can save you a lot of money and time because there is less skill and less code to write. No-Code machine learning tools make it easy to understand artificial intelligence and machine learning. In this paper, we examine No-Code machine learning tools and compare their features.

• 한국정보통신학회논문지
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• 제24권2호
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• pp.204-211
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• 2020

본 논문에서는 약한 지도학습을 통한 주 객체 위치 검출을 위한 최적의 딥러닝 네트워크 구조를 제안한다. 제안된 네트워크는 약한 지도학습을 통한 주 객체의 위치 검출 정확도를 향상시키기 위해 컨벌루션 블록을 추가하였다. 추가적인 딥러닝 네트워크는 VGG-16을 기반으로 합성곱 층을 더해주는 5가지 추가적인 블록으로 구성되며 객체의 실제 위치 정보가 필요하지 않는 약한 지도 학습의 방법으로 학습하였다. 또한 객체의 위치 검출에는 약한 지도학습의 방법 중, CAM에서 GAP이 필요하다는 단점을 보완한 Grad-CAM을 사용하였다. 제안한 네트워크는 CUB-200-2011 데이터 셋을 이용하여 성능을 테스트하였으며 Top-1 Localization Error를 산출하였을 때 50.13%의 결과를 얻을 수 있었다. 또한 제안한 네트워크는 기존의 방법보다 주 객체를 검출하는데 더 높은 정확도를 보인다.

• Educational Technology International
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• 제19권1호
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• pp.123-151
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• 2018

This study aims to examine the effects of self-directed learning readiness (SDLR) on academic performance and the perceived usefulness for each elements of flipped learning. Based on their SDLR scores, 69 students were assigned to a high SDLR group and a low SDLR group. Academic performance was measured by the completion rate of a pre-class online learning and the final exam score, and perceived usefulness for each element of flipped learning was measured by a survey designed by the researcher. For academic performance, the high SDLR group showed a significantly higher completion rate than the low SDLR group, but no significant difference was observed in their final exam scores. Students in the high SDLR group perceived in-class student-centered activities as more useful than those in the low SDLR group. Additional qualitative analyses indicated that students needed more support from instructors and well-prepared peers. Finally, this study suggested that more examination on the various learning characteristics that may influence the effectiveness of flipped learning should be done.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.6-8
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• 2022

딥러닝을 활용한 객체 인식으로 이미지를 사용하는 많은 시스템에서 기존에 제공하던 방식을 넘어서 다양한 솔루션이 제공되고 있다. 많은 연구를 통하여 그 활용성을 입증하고 있으며, 실제 관제 시스템에서는 이를 사용하여 사람의 업무를 더욱 편리하게 하는 등 가능성을 보여주고 있다. 하지만, 하드웨어에 집중된 성능에 따라 모델의 개발도 일부 한계를 맞이하고 있으며 새롭게 업데이트되지 못한 많은 모델의 사용과 추가적 활용에 따른 용이성이 떨어지고 있다. 본 논문에서는 기존의 정형화된 객체 인식의 결괏값 이후에 인식된 국소 이미지 데이터의 HSV 색상 히스토그램을 통한 학습과 가중치를 활용하여 색상의 감성적 영역 및 객체의 추가적 정보를 제공하여 활용도와 정확성을 높일 방법을 제안한다.

• International Journal of Computer Science & Network Security
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• 제21권11호
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• pp.248-256
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• 2021

The article discusses the evolution of the development of distance learning in world practice; investigated the essence and modern content of the concepts of "distance learning" and "distance education"; studied the principles of distance learning in the educational process; analyze the use of distance learning in higher educational institutions of Ukraine; substantiated the effectiveness of introducing distance learning into the higher education system; formed new management approaches in the distance learning system; proposals for the organization and improvement of distance learning at the university were developed on the basis of the analysis.

• International journal of advanced smart convergence
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• 제11권2호
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• pp.142-152
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• 2022

We study confirmed the relationship between the adversity index, entrepreneurial orientation, and organizational learning competency perceived by organizational members as follows. First, the adversity index showed a positive (+) effect on entrepreneurial orientation (hypothesis 1) and organizational learning competency (hypothesis 2). Second, the entrepreneurial orientation was statistically significant in organizational learning competency (hypothesis 3). Third, the partial mediating role of entrepreneurial orientation (Hypothesis 4) was confirmed in the process of the adversity index affecting organizational learning competency. Meanwhile, the main implications of this study are as follows. First, it is the aspect that provides additional theoretical implications in the reality that studies on the adversity index and entrepreneurial orientation that affect organizational learning competency are lacking. Second, it is the aspect that the importance of adversity index and start-up orientation was confirmed in improving organizational learning competency based on securing differentiated competitiveness for the advancement of the organization's sustainability management system. In addition, it is the aspect of drawing practical implications for strategic human resource management and human resource development to systematically improve it.

• Educational Technology International
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• 제15권2호
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• pp.49-69
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• 2014

The purpose of this study was to investigate the effect of co-regulated learning on the improvement of self-regulated learning skills in collaborative learning environments. One group pretest-posttest design was used in this study. The subjects were 49 undergraduate students who enrolled in 'Educational Evaluation' course. To facilitate students' co-regulated learning activities, group worksheets were developed. Students performed collaborative tasks in group by using the group worksheets over the 6 weeks. The results showed that the difference between means of the pretest and posttest was no statistically significant. It indicates that co-regulated learning activities did not have a significant effect on the improvement of self-regulated learning skills in collaborative learning environments. However, the results of additional analysis revealed that the difference between means of the pretest and posttest in case of 19 students with low self-regulated learning level was statistically significant. On the other hand, there was no statistically significant difference between means of the pretest and posttest in case of 19 students with high self-regulated learning level. It is interpreted that co-regulated learning activities positively affected the improvement of self-regulated learning skills of students with low self-regulated learning level.