• Journal of the Korean Society for Library and Information Science
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• v.38 no.4
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• pp.85-104
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• 2004

This study is supposed to the way to add and enlarge the elements related to educational domain in metadata of school library information system (DLS) by using the concept of learning object which the education information service agencies have adapted. This study is to propose the methods which can be accessed according to the units of learning content in order that they can be applied to the teaching and learning situations, and describe and index the total traits of interior data elements included in the information resources. Thus, the metadata of the existing DLS through the additional elements : , , and was made to access the information resources according to the teaching and learning situations and to accept the concept of interior learning units by means of the element.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.11
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• pp.411-418
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• 2018

With the proliferation of artificial intelligence technology, it is becoming important to obtain, store, and utilize scientific data in research and science sectors. A number of methods for extracting meaningful objects such as graphs and tables from research articles have been proposed to eventually obtain scientific data. Existing extraction methods using heuristic approaches are hardly applicable to electronic documents having heterogeneous manuscript formats because they are designed to work properly for some targeted manuscripts. This paper proposes a prototype of an object extraction system which exploits a recent deep-learning technology so as to overcome the inflexibility of the heuristic approaches. We implemented our trained model, based on the Faster R-CNN algorithm, using the Google TensorFlow Object Detection API and also composed an annotated data set from 100 research articles for training and evaluation. Finally, a performance evaluation shows that the proposed system outperforms a comparator adopting heuristic approaches by 5.2%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.237-240
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• 2009

감시 시스템은 지역의 특성에 따라 다양한 환경 및 설치 조건을 가지게 되며, 지능적 처리 요구에 따라 객체 분류를 필요로 한다. 본 논문에서는 검출된 객체로부터 특징 정보의 자율적 추출 및 학습을 이용하여 객체를 분류하기 위한 방안을 제시하고자 한다. 다양한 환경 및 설치 조건에서도 감시 시스템의 입력과 처리에 대한 추가적 보정 과정이 필요하지 않으며, 연속적으로 입력되는 객체의 형태와 움직임 정보를 효과적으로 활용하여 객체의 특징 추출 및 분류가 가능하게 된다.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.61-70
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• 2003

Currently many companies and cyber-universities are investing large amount of time and efforts to develop a standard for Web-based learning contents. Among various standards proposed, SCORM(Sharable Content Object Reference Model) has been especially interested regarding web contents and LCMS(Learning Content Management System), In contrast with corporate and adult education, many seem to be skeptical that SCORM could be applied to K-12 education. In the study, opportunities and limitations of the concept for the learning object in 'SCORM' are examined through analyzing relevant studies and cases. In addition, this study examines the learning object in the pedagogical Perspective, and derives suggestions for applying them to K-12 education.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.10
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• pp.883-892
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• 2021

This paper provides a process for developing deep learning-based aerial object detection models that can run in realtime on onboard. To improve object detection performance, we pre-process and augment the training data in the training stage. In addition, we perform transfer learning and apply a weighted cross-entropy method to reduce the variations of detection performance for each class. To improve the inference speed, we have generated inference acceleration engines with quantization. Then, we analyze the real-time performance and detection performance on custom aerial image dataset to verify generalization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.571-575
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• 2015

This paper propose a temporal histogram -based behavior pattern analysis algorithm to analyze the movement features of moving objects from the image inputted in real-time. For the purpose of tracking and analysis of moving objects, it needs to be performed background learning which separated moving objects from the background. Moving object is extracted as a background learning after identifying the object by using the center of gravity and the coordinate correlation is performed by the object tracking. The start frame of each of the tracked object, the end frame, the coordinates information and size information are stored and managed by the linked list. Temporal histogram defines movement features pattern using x, y coordinates based on time axis, it compares each coordinates of objects for understanding its movement features and behavior pattern. Behavior pattern analysis system based on temporal histogram confirmed high tracking rate over 95% with sustaining high processing speed 45~50fps through the demo experiment.

• 한국정보교육학회:학술대회논문집
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• 2005.08a
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• pp.107-115
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• 2005

통계 학습에서 자바 애플릿의 활용은 통계간을 직관적으로 이해할 수 있어 학습의 효과를 높일 수 있다. 통계 영역의 그래프를 공부하는데 통계값의 의미를 눈으로 보면서 이해하고 직접 조작하며 학습을 하면 보다 능률적일 것이다. 이에 본 연구에서는 통계 영역의 교육과정을 분석하여 그래프 객체를 정의하고, 객체의 속성과 메소드를 분석하여 클래스를 구성한 후 클래스 사이의 관계를 파악하여 클래스 계층구조를 설계하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.335-336
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• 2021

디자인 패턴은 클래스와 객체를 활용한 23가지의 개발자 의도를 만족시켜주는 최선의 실천법들을 정리한 것이다. 디자인 패턴은 설계 경험과 객체지향 패러다임의 기반 지식들을 필요하므로 실질적인 패턴 학습에 어려움이 있다. 디자인 패턴 학습에 대한 도움을 제시해 줄 수 있는 가이드라인으로 기술 습득 모델에 활용하는 드라이퍼스 모델을 적용하는 것을 제안하고자 한다. 드라이퍼스 단계별 모델을 기반으로 단계 별 디자인 패턴 학습 단계를 제시한다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.70-72
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• 2005

최근 초고속 통신망과 같은 우리나라의 발달된 인터넷 인프라를 활용할 수 있는 e-Learning 콘텐츠 활발히 개발되고 있다. 본 논문은 기존에 개발된 콘텐츠와 평가를 포함한 교수,학습 활동 계획을 관리할 수 있는 ICT 교육 통합 지원 시스템을 구성하는 서브시스템 중 교수,학습 콘텐츠 관리 시스템을 설계, 구현하였다. 이를 위하여 이미 개발되고 중앙교수학습센터 및 시,도 교수학습 지원센터 등에서 제공되고 공유되는 학습자료를 활용하기 위해 KERIS 등에서 제시한 표준을 본 시스템의 설계에 반영하였다. 교수,학습 콘텐츠 관리 모듈은 학습객체를 분류 저장 데이터베이스화 하였으며 실제 활용이 매우 쉬어 특별한 훈련이나 교육을 받지 않아도 기초적인 수준의 PC 활용 능력만 있다면 누구나 쉽게 교수,학습 콘텐츠를 수집하여 활용할 수 있도록 하였다. 본 시스템은 기 개발된 학습객체의 재사용으로 인한 효율성 증가는 물론 교과, 단원 학습 주제별로 구조화하여 저장 관리하여 교사의 교수활동 준비 시간을 줄임으로써 실제 학교 현장에서 활용하여 ICT 활용 교수,학습 활동 개선에 도움이 될 것으로 기대한다.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.421-428
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• 2006

Intelligent Tutoring System(ITS), which offers individualized learning environment that consider many learners' variable, is realized by the effective alternative to take the place of domain expert. Accordingly, research on Learning Companion System(LC) is currently noticing. However, to develop LCS which applies effective interaction, it is necessary to combine several LCs, and personalized knowledge base have to be made first. Therefore, in this paper, we propose the 'Knowledge Base Object Medel', which is based on connectionist' in cognition structure, represents learner's knowledge to self-learnig object, and grows adaptive object by proprietor, verify the validity. This model lays the groundwork for design of personalized knowledge base, offers clue to development of adaptive ITS using knowledge base object.