• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.11 no.5
• /
• pp.193-201
• /
• 2011

This paper presents the holistic notion and model of an open social u-learning community, anchored with open content, providing an interactive online study group experience akin to sitting with study buddies on a world-wide campus quad. The interactive social u-learning community design helps conceptualize and maximize advantages of ubiquitous environment in learning. The model is enabled by state-of-the-art web technologies; real-time collaboration technologies for a highly interactive experience; intelligent recommender systems to help learners connect with relevant content and other learners; and mining and analytics to assess learner outcomes. Hence, u-learning design is highly scalable yet interactive and engaging.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.83-86
• /
• 2019

This study proposes a methodology for predicting co-authorship of contributors to a highly anticipated paper through link analysis and learning, taking into account the result of collaborative research. Previous studies predict the co-authorship with high accuracy, but this shows limitations in that the quality of the predicted relationship is not considered. Therefore, to solve the above problem, we propose three steps to predict the co-authorship that will help with the expected performance: (1) Construct a heterogeneous graph to measure results of collaborative research. (2) Analyze and learn links based on results of collaborative research. (3) Predict links that are anticipated to have high expectation. It is expected to be useful for increasing confidence in the predicted co-authorship.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2022.06a
• /
• pp.1286-1289
• /
• 2022

최근 영상 군집화 분야는 딥러닝 모델에게 Self-supervision을 주거나 unlabeled 영상에 유사-레이블을 주는 방식으로 연구되고 있다. 또한, 고차원 컬러 자연 영상에 대해 잘 압축된 특징 벡터를 추출하는 것은 군집화에 있어 중요한 기준이 된다. 본 연구에서는 자연 영상에 대한 Convolutional Auto Encoder의 특징 추출 성능을 평가하기 위해 설계한 실험 방법을 소개한다. 특히 모델의 특징 추출 능력을 순수하게 확인하기 위하여 Self-supervision 및 유사-레이블을 제공하지 않은 채 Naive한 모델의 결과를 분석할 것이다. 먼저 실험을 위해 설계된 4가지 비지도학습 모델의 복원 결과를 통해 모델별 학습 정도를 확인한다. 그리고 비지도 모델이 다량의 unlabeled 영상으로 학습되어도 더 적은 labeled 데이터로 학습된 지도학습 모델의 특징 추출 성능에 못 미침을 특징 벡터의 군집화 및 분류 실험 결과를 통해 확인한다. 또한, 지도학습 모델에 데이터셋 간 교차 학습을 수행하여 출력된 특징 벡터의 군집화 및 분류 성능도 확인한다.

• Journal of The Korean Association For Science Education
• /
• v.41 no.4
• /
• pp.297-310
• /
• 2021

This study explores the characteristics of within-school and across-school science teacher professional learning communities (hereafter, PLC) qualitatively. In-depth focus group interviews were conducted with science teachers belonging to seven PLCs within the science core school and three PLCs across schools. Interview questions include identity and motivation, major activities, and outcomes of PLC, as well as shortcomings and support plans for PLC. The results include both within-school and across-school science teacher PLCs formed for professional development related to science teaching and learning. Both science PLCs participated in the study showed the characteristics of a 'practice community' that developed a cooperative relationship through reciprocal participation, focusing on shared issues among members. Regarding issues, within-school PLCs focused on microscopic problems such as curriculum reconstruction of subject-matter, while across-school PLCs focused on macro problems such as teacher professional development. Regarding activities and roles as PLC, within-school and across-school science PLCs shared such features as collaborative professional development, and interpersonal education such as mentoring for novice teachers. In terms of PLC's influence and outcomes, science teacher PLCs has a positive effect not only on the teachers themselves, but also on the students and the teacher culture in the school. In addition, science teacher PLCs need improvement of the physical conditions for community operation, and software support such as protocol provision for PLC operation and joint research or re-education with universities. In particular, joint research between universities and science teacher PLCs shows the future orientation of the PLC as an 'inquiry community'. Based on the results, the necessity of active support for science PLC, the necessity of developing a cooperative system between science teacher PLC and universities, and ways to spread the PLC of science core schools to that of general schools were proposed.

• Journal of the Korea Computer Industry Society
• /
• v.5 no.9
• /
• pp.947-958
• /
• 2004

In this paper, various platforms are designed, where instructors and students can communicate each other to educate, ask and answer the questions interactivel under the WEB 3-based remote real-time instrurtions. The proposed system maximizes involvements among the students, instrurtors and administrators, which facilitate the understanding and progressive developments of the lessons and tasks to be performed. In the proposed education system, the instructors work as overseers for the study and the students benefit from comparative learning and pattern design. Also, the advantages of WBI are maximized, and the common factors among the mutual components are extracted and reused to avoid the confusion for the students. The advantages of the components are maximized and applied to the proposed system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.05a
• /
• pp.161-166
• /
• 2001

학생들에게 사고의 다양성과 창의성을 신장시킬 수 있는 가장 좋은 대안의 하나가 정보통신기술(ICT)을 활용한 수업을 들 수 있는데 아직까지 정보통신 기술을 활용한 수업이 실제적으로 학생들에게 어떠한 인지적, 정의적 영향을 미치는가에 대한 구체적인 연구결과는 없다. 따라서 상호작용이 풍부한 ICT 활용 수업이 정보화 사회가 요구는 자기 주도적 학습 능력을 얼마나 신장시키는지를 규명하기 위해 ICT활용 수업을 실시하기 위한 기초 자료를 제작한 후 홈페이지를 통한 정보 안내하기, 인터넷을 활용한 문제해결학습, 정보분석형 가상실습, 공동 협력 프로젝트 수업, 웹토론형 수업을 실시하여 ICT활용교육이 정보활용, 정보검색 능력, 학업성취도 향상 등에 어떠한 영향을 미치는지를 연구하였다.

• Journal of the Korean earth science society
• /
• v.29 no.6
• /
• pp.506-519
• /
• 2008

This article explores the potential learning materials and methods of science practice from exhibits, and how those are presented in natural history museums as a feasible science inquiry community. The idea of science inquiry community was offered as a form of science practice that ended with science learning. A grasp of 'scientific practice to learning' is understood as a way to conceive scientific methods as well as facts and understanding knowledge. To get educational implications on the scientific practice of 'earthquake' as a socioscientific topic in the communities, we analyzed 1) the relationship between earth science curriculum and exhibits related to 'earthquake', 2) the educational goals and intentions of educators, and 3) the characteristics of the exhibits in the American Museum of Natural History and in the Smithsonian National Museum of Natural History. The results of this study showed that those museums presented the exhibits consisting of various and practical cases and events of 'earthquakes' as a socioscientific topic related to their curriculum. At the target museum, it was clearly stated that the pursuing educational goals focused on relations with local interests and socioscientific issues. For making earthquakes relevant to visitors, delivering lived experiences with raw data and interactive media was emphasized in exhibit characteristics.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.05a
• /
• pp.224-226
• /
• 2023

본 논문에서는 연합학습 모델을 타겟으로 하는 특성 추론 공격 및 방어 기법과 관련된 연구들을 소개한다. 연합학습 시스템에 특화된 2가지 특성 추론 공격 및 이에 대한 방어 기법들에 대해 정리하고, 향후 연구 방향을 조망하고자 한다.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.3
• /
• pp.75-82
• /
• 2018

Recently, emerging countries have been paying attention to Korean economic development policy, trying to adopt the Korean regional innovation model. Korea is also interested in exporting its regional innovation model and enhancing economic cooperation with those countries. This paper aims to analyze the capacity-building programs of the Korean regional innovation model for emerging countries and suggests policies for it. For this purpose, the local innovators' participation patterns in the process of collaborative learning/networking/interaction are investigated with a focused group-interview method. From an analysis of the programs supported by Korean organizations, this study finds that the correlation coefficient between the training time of capacity building and the participation rate of local members' collaborative learning is very high (0.975). Since the correlation coefficient between the participation rates of collaborative learning and networking is relatively low (0.667), a policy to link local collaborative learning to networking should be provided. As the correlation coefficient between the participation rates of networking and interaction is high (0.950), networking is a key to regional innovation. This study recommends activity programs to promote networking among local innovators, rather than training and consulting programs. As introduced in the Chungnam Techno Park case, this study suggests that the capacity-building program should include programs to initiate a collaborative learning network, to create a local-demand, regional innovation model, and to operate the regional innovation platform, which should be done by local innovators in the emerging countries.

• Geophysics and Geophysical Exploration
• /
• v.26 no.4
• /
• pp.171-184
• /
• 2023

Machine learning (ML)-based cavity detection using a large amount of survey data obtained from vehicle-mounted ground penetrating radar (GPR) has been actively studied to identify underground cavities. However, only simple image processing techniques have been used for preprocessing the ML input, and many conventional seismic and GPR data processing techniques, which have been used for decades, have not been fully exploited. In this study, based on the idea that a cavity can be identified using diffraction, we applied ML-based diffraction separation to GPR data to increase the accuracy of cavity detection using the YOLO v5 model. The original ML-based seismic diffraction separation technique was modified, and the separated diffraction image was used as the input to train the cavity detection model. The performance of the proposed method was verified using public GPR data released by the Seoul Metropolitan Government. Underground cavities and objects were more accurately detected using separated diffraction images. In the future, the proposed method can be useful in various fields in which GPR surveys are used.