• Journal of Digital Convergence
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• v.11 no.4
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• pp.397-402
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• 2013

The development case presented is about the development of smart education contents for development of creativity, and suggests the development contents and approach to design of software of teaching materials based on G-Learning which allow learner to interact depending on their dispositions. Above all, focusing on design approach in order to maximize interaction which is the characteristic of game, the education contents that enable learner to be immersed by education level as per learner's disposition have been developed, and it allows to compose the level of difficulty based contents according to level design plan. Also, it is the case that the contents allow for effective education by setting visual environment which enables learner to be immersed depending on learner's disposition with the realization of object which appears in respect of vision and visual Customizing of character.

• The Journal of Sustainable Design and Educational Environment Research
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• v.20 no.3
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• pp.25-32
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• 2021

This study analyzed the application articles of the Internet of Things (IoT) in the educational environment. It defined learning environmental data, utilization scenarios, and models that IoT can improve teaching and learning through Focus Group Interviews for academic experts, teachers, and technicians in related fields. In addition, the IoT pilot prototype was developed, verified, and drew implications from the perspective of collection, analysis, and utilization of real-time data based on the actual school settings. This study has significance as a priori case of building and applying a learning environment using the Internet of Things in real school settings considering relevant restrictions.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.223-225
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• 2012

본 논문에서는 안드로이드 기반 스마트폰을 이용하여 유아 및 아동을 대상으로 하는 학습용 동화 앱의 구현 내용을 소개하였다. 이미 상용화 되어 있는 학습용 앱의 기능 외에 게임적 요소를 접목하여 학습의 효과와 흥미를 높일 수 있도록 하였다. 듣고 쓸 수 있는 학습용 전자 동화책으로 평가할 수 있다. 안드로이드 마켓에 배포하여 서비스를 할 수 있으며 본 연구의 과정은 앱 설계 관련 프로젝트의 수행이나 학습용 앱 개발의 학습 모형을 제시한 사례로 활용할 수 있다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.130-133
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• 2006

본 연구에서는 진단분야에서의 시스템의 성능을 향상시키고 최적의 해를 찾고자 사례기반추론과 인공 신경망을 혼합한 시스템을 제안한다. 사례기반추론은 과거의 사례(경험)를 통해 현재의 제시된 문제를 해결하는 추론방식으로, 지식이 획득이 덜 복잡하고, 정형화되기 어려운 규칙이나 문제영역이 불분명한 분야에 효율적으로 활용되었다. 그러나 사례의 양이 방대해야 효율적인 추론을 할 수 있으며, 검색된 시간 또한 지연되는 단점이 있다. 이러한 문제를 보완하고자 본 논문에서는 인공 신경망의 학습을 통해 저장된 ANN Library를 생성하여, 사례기반추론에서의 부적절한 해를 유추하는 것을 방지하고, 효율적이고 신뢰성이 높은 해를 유추해 내는데 목적이 있다.

• Journal of the Korean Geographical Society
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• v.48 no.6
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• pp.994-1008
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• 2013

In this paper, we describe two exploratory examples in the use of Augmented Reality (AR) for geographical visualization regarding refinement of visual content in geography textbooks and learning motivation of geography students. Currently, teaching and learning materials with AR technology and their utilization in the geography classroom have become a new topic in geographical research themes, and this trend has increased. Adequate development and utilization of geographical materials is an important starting point for smart education research in geography. This paper describes the system and software, and the implication of marker AR applications for teaching and learning geography in the classroom. For the AR applications to be utilized in geography education, two marker based AR examples, virtual globe and visualization of topographical features, are presented and their utilization aspects are discussed. Finally, from the discussion stated in this paper, it can be inferred that AR is useful for exploring geographical materials, and marker based AR will contribute to progress in spatial science and geographical education research.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.47-61
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• 2001

Lazy loaming methods including CBR have relative advantages in comparison with eager loaming methods such as artificial neural networks and decision trees. However, they are very sensitive to irrelevant features. In other words, when there are irrelevant features, larry learning methods have difficulty in comparing cases. Therefore, their performance can be degraded significantly. To overcome this disadvantage, feature weighting methods for lazy loaming methods have been studied. Most of the existing researches, however, were focused on global feature weighting. In this research, we propose a new local feature weighting method, which we shall call CBDFW. CBDFW stores classification performance of randomly generated feature weight vectors. Then, given a new query case, CBDFW retrieves the successful feature weight vectors and designs a feature weight vector fur the query case. In the test on credit evaluation domain, CBDFW showed better classification accuracy when compared to the results of previous researches.

• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.336-341
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• 2003

1.연구배경 사회환경이 변화하고 정보통신기술 인프라가 성장함에 따라, 전통적 교수학습 방법에서 e-러닝, 사이버, 교육, 온라인 교육 등으로 불리는 디지털 기반 교육으로 패러다임의 전환이 이루어지고 있으며, 우리나라의 경우 초고속 인터넷망이 잘 구축되어 교육훈련 목적의 콘텐츠 및 학습과정을 효과적으로 전달할 토대를 갖추고 있다.(중략)

• Journal of the Korean Geographical Society
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• v.43 no.5
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• pp.761-774
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• 2008

Integration of GIS data and human expert knowledge into digital image processing has long been acknowledged as a necessity to improve remote sensing image analysis. We propose inductive machine learning algorithm for GIS data integration and rule-based classification method for land cover classification. Proposed method is tested with a land cover classification of a Landsat ETM+ multispectral image and GIS data layers including elevation, aspect, slope, distance to water bodies, distance to road network, and population density. Decision trees and production rules for land cover classification are generated by C5.0 inductive machine learning algorithm with 350 stratified random point samples. Production rules are used for land cover classification integrated with unsupervised ISODATA classification. Result shows that GIS data layers such as elevation, distance to water bodies and population density can be effectively integrated for rule-based image classification. Intuitive production rules generated by inductive machine learning are easy to understand. Proposed method demonstrates how various GIS data layers can be integrated with remotely sensed imagery in a framework of knowledge base construction to improve land cover classification.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.239-259
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• 2009

The study aims at investigating students' behaviors and perceptions regarding the collaborative learning based group project using the wiki environment. The study utilized Google Sites as a case, and analyzed file unloads, the use of web pages, navigation bars, and comments as well as surveys. The study discusses main characteristics of students' activities in the collaborative learning group project, which are drawn from the analysis of students' behaviors and perceptions. The study also provides implications for improvement of wiki environment to support collaborative learning in education.

• Information and Communications Magazine
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• v.33 no.10
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• pp.65-70
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• 2016

최근 스마트폰의 이용 사례가 증가함에 따라, 스마트폰에 내장되어 있는 다양한 센서를 이용하여 인간의 행동을 인식하기 위한 연구가 많은 각광을 받고 있다. 본고에서는 인간의 기본적인 행동 중에 앉기, 걷기, 달리기 등의 행동 특성을 스마트폰에 내장되어 있는 3축 가속도 센서를 통하여 분석하고 인간의 기본적 행동을 자동으로 인식하기 위한 방법에 대하여 비교 분석하는 것을 목적으로 한다. 구체적으로는 스마트폰에 내장되어 있는 3차원 가속도 센서로부터 추출된 데이터를 시간축에서 샘플링하여 인간의 행동을 인식하기 위한 기댓값 최대화 알고리즘, 랜덤 포레스트, 딥러닝 기반의 기계학습 방법을 비교하여 각 기계학습 알고리즘의 장단점을 분석한다.