• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.155-160
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• 2016

The education applications for English learning have been developing consistently by utilizing the smart-phone owing to the development of internet and ICT. Smart technology based study platform, the mobile learning which enables for the students to study beyond the time and space is expected to bring forth new paradigm of education in tune with the environment change and trends. But it is found that the current applications are mostly the contents patterned for English study institution information with single channel or made for thinking study concept with only the simple language learning once they were checked. Therefore, the understanding on the English study process shall be changed and the study on the platform service is required by accessing in the viewpoint of thinking exercise learning. This study is purposed to explore the scope and strategy of mobile learning UX platform development and suggest the service model via prototype for English study.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.329-330
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• 2020

본 논문에서는 Azure 클라우드 플랫폼의 가상서버 호스팅을 이용해 데이터 수집 환경을 구축하고, Azure에서 제공하는 자동화된 기계학습(Automated Machine Learning, AutoML)을 기반으로 데이터 분석 방법에 관한 연구를 수행했다. 가상 서버 호스팅 환경에 LAMP(Linux, Apache, MySQL, PHP)를 설치하여 데이터 수집환경을 구축했으며, 수집된 데이터를 Azure AutoML에 적용하여 자동화된 기계학습을 수행했다. Azure AutoML은 소모적이고 반복적인 기계학습 모델 개발을 자동화하는 프로세스로써 기계학습 솔루션 구현하는데 시간과 자원(Resource)를 절약할 수 있다. 특히, AutoML은 수집된 데이터를 분류와 회귀 및 예측하는데 있어서 학습점수(Training Score)를 기반으로 보유한 데이터에 가장 적합한 기계학습 모델의 순위를 제공한다. 이는 데이터 분석에 필요한 기계학습 모델을 개발하는데 있어서 개발 초기 단계부터 코드를 설계하지 않아도 되며, 전체 기계학습 시스템을 개발 및 구현하기 전에 모델의 구성과 시스템을 설계해볼 수 있기 때문에 매우 효율적으로 활용될 수 있다. 본 논문에서는 NPU(Neural Processing Unit) 학습에 필요한 데이터 수집 환경에 관한 연구를 수행했으며, Azure AutoML을 기반으로 데이터 분류와 회귀 등 가장 효율적인 알고리즘 선정에 관한 연구를 수행했다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.109-112
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• 2001

기존의 K-means 알고리즘은 학습벡터가 단일군집에 할당되는 방법이 crisp 이므로 다른 군집에 할당될 확률을 무시하게 된다. 따라서 군집화 작업과 관련하여 반복적인 코드북 설계 과정에서 각 학습벡터를 다중 군집으로 할당하는 Fuzzy c-means를 사용한다. 또한 Fuzzy c-means 알고리즘의 학습과정에서 구해지는 각 클래스 의 프로토타입에 가중치를 곱하여 다음 학습의 프로토타입으로 사용함으로써 Fuzzy c-means 알고리즘 적용 결과 얻어지는 코트북의 성능을 기존 알고리즘과 비교하여 개선된 Fuzzy c-means 알고리즘을 찾기 위한 근거를 마련한다.

• Journal of the Korea Convergence Society
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• v.6 no.3
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• pp.127-134
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• 2015

In this paper, we design a semantic-based syllabus template including learning ontologies. A syllabus has been considered as a important blueprint of teaching in universities. However, the current syllabus has no importance in real world because most of all syllabus management systems provide simple functionalities such as, creation, modification, and retrieval. In this paper, our approach consists of definition of hierarchical structure of syllabus and semantic relationships of syllabuses, formalization of learning goals, learning activity, and learning evaluation using Bloom's taxonomy and design of learning subject ontologies for improving the usability of syllabus. We prove the correctness of our proposed methods according to implementing a real syllabus for JAVA programing course and experiments for retrieving syllabuses.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.219-229
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• 2017

The study was conducted to find out lexical complexity and syntactic complexity for Korean learners by telling stories to see pictures. The results were as follows. First, there was no meaningful difference according to nationality. Second, we checked the differences on lexical complexity and syntactic complexity according to Korean studying period, only number of difference words showed meaningful difference among lexical complexity sub variables, but there was no difference among syntactic complexity sub variables. Third, we also checked correlation among staying period of Korea, Korean studying period, and other language related variables. It showed meaningful correlation staying period in Korea and other language related variable except Korean studying period and TTR. The directions for teaching Korean learners were suggested on the point of converge view according to results.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.55-64
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• 2019

The purpose of this descriptive research is to get basic data for educational program after investigating convergent effect of psychological capital on learning satisfaction of nursing freshmen. Using SPSS 21, T-test, ANOVA, Pearson's correlation coefficient and hierarchical multiple regression of the 164 collected data were carried out. The mean scores of psychological capital and learning satisfaction were above the middle, and the 'hope' was the highest among subdomains of psychological capital. There was a positive correlation between psychological capital and learning satisfaction(r=.665, p<.001). School performance(${\beta}=.311$), school life satisfaction(${\beta}=.191$) and psychological capital(${\beta}=.522$) were the significant factors of learning satisfaction in hierarchical multiple regression(F=37.651, p=.004). The explanatory rate of variables on learning satisfaction was 57.4%. It is needed applying these results in developing learning satisfaction programs, but it isn't appropriate to generalize these results conducted on nursing freshmen in one university.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.15-20
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• 2024

Path planning for unmanned aerial vehicles (UAV) is crucial in avoiding collisions with obstacles in complex environments that include both static and dynamic obstacles. Path planning algorithms like RRT and A^* are effectively handle static obstacle avoidance but have limitations with increasing computational complexity in high-dimensional environments. Reinforcement learning-based algorithms can accommodate complex environments, but like traditional path planning algorithms, they struggle with training complexity and convergence in higher-dimensional environment. In this paper, we proposed a reinforcement learning model utilizing a cell decomposition algorithm. The proposed model reduces the complexity of the environment by decomposing the learning environment in detail, and improves the obstacle avoidance performance by establishing the valid action of the agent. This solves the exploration problem of reinforcement learning and improves the convergence of learning. Simulation results show that the proposed model improves learning speed and efficient path planning compared to reinforcement learning models in general environments.

• Journal of Science Education
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• v.42 no.2
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• pp.95-105
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• 2018

The purpose of this study was to develop a digital textbook on 'structure and contraction mechanism of skeletal muscle' with the learning model for biomimicry-based convergence. The unit of 'structure and contraction mechanism of skeletal muscle' is a part of Life Science I in high school. The convergence learning model was designed with three phases of biomimicry-based convergence (Exploration-Design-Implementation) including 3D modeling & printing. The developed digital textbook was composed of 8 sessions which contains the following learning contents : Exploration of skeletal muscle, creative designing of skeletal muscle using sketch application and 3D modeling, convergent implementing of the designed using 3D printing, exploration of muscle contraction, creative designing of muscle contraction using sketch application and 3D modeling, and convergent implementing of the designed using 3D printing. Each session is also involved in the contents of gallery widgets, media widgets, keynote widgets, sketch widgets, the cloud, polling widgets, and review widgets for interactive and mobile learning. After administering the developed digital textbook to 20 high school students, it was shown a positive effectiveness on life science learning for high school students. Moreover, the digital textbook was evaluated as to promote student's abilities on creative designs and implementation related to biomimicry-based convergence. The digital textbook was also shown a favorable response on students' interest and self-directed learning on life science.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.327-338
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• 2023

The purpose of this study is to develop and apply curriculum activities using non-face-to-face wearable technology in a pandemic situation. It is to improve the creative convergence learning ability of college students. Based on the results of 5 preliminary studies, 8 courses were conducted for 16 university students at A University in Seoul. In conclusion, real-time non-face-to-face interaction with professional professors in each field played a major role in improving the creative convergence learning competency of college students. This point shows the possibility of future-oriented creative convergence talent development along with the expandability of wearable technology in university education.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.827-829
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• 2021

현대사회의 시설물 중 다수가 콘크리트를 사용하여 건설되었고, 재료적 성질로 인해 균열, 박락, 백태 등의 손상이 발생하고 있고 시설물 관리가 요구되고 있다. 하지만, 현재 시설물 관리는 사람의 육안 점검을 정기적으로 수행하고 있으나, 높은 시설물이나 맨눈으로 확인할 수 없는 시설물의 경우 관리가 어렵다. 이에 본 논문에서는 다양한 영상장비를 활용해 시설물의 이미지에서 균열을 분류하는 알고리즘을 제안한다. 균열 분류 알고리즘은 산업 이상 감지 데이터 세트인 MVTec AD 데이터 세트를 사전 학습하고 L2 auto-encoder를 사용하여 균열을 분류한다. MVTec AD 데이터 세트를 사전학습시킴으로써 균열, 박락, 백태 등의 특징을 학습시킬 수 있을 것으로 기대한다.