• 문화기술의 융합
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• 제8권6호
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• pp.79-88
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• 2022

본 연구는 초등교육에서 오프라인 환경과 실시간 온라인 환경이 통합된 하이브리드 교육을 운영함에 있어서 어떠한 요소를 중점적으로 고려해야 하는지를 탐색하는 목적을 지닌다. 이를 위해 하이브리드 교육을 운영해 본 경험을 지닌 8명의 초등교사를 대상으로 면담 등을 통해 주요 고려 요소를 확인하였다. 연구 결과, 운영에 앞서 하이브리드 교육의 특성이 무엇인지에 대한 개념에 대해 구체적인 안내나 교육을 통해 이해 수준을 높일 필요가 있음을 확인해 볼 수 있었다. 기반 구축이 제대로 이루어지지 않아 효과적인 운영이 어려웠기에 하드웨어 및 소프트웨어 테크놀로지를 포함한 환경 재설계를 고려할 필요가 있다. 특히, 환경 간의 동시성과 상호작용성을 기반으로 두 환경에서 학습자들이 연결되어 참여할 수 있는 활동을 고려해야 한다. 향후 교수학습 운영을 안내하는 설계 전략의 개발이 이루어질 필요가 있다.

• 컴퓨터교육학회논문지
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• 제12권5호
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• pp.35-47
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• 2009

유비쿼터스(Uniquitous)기술 기반의 U-learning 학습과 관련한 몇몇 연구에서 지적하는 것처럼 학습자의 상황성과 맥락성은 반드시 반영될 필요가 있다. 이를 위해 본 연구에서는 탐구학습 방법과 모바일 탐구학습 지원도구를 제안했다. 탐구학습은 학습자가 스스로 실제 현장에서 경험한 내용을 기초로 운영되므로 학습자를 자연스럽게 학습 상황과 맥락속에 위치하게 해 줄 수 있다. 본 연구에서는 교육과정의 일부를 탐구학습의 형태에 맞게 변형하여 적용했으며, 또한 연구에서 개발한 모바일 탐구학습 지원도구는 학습자가 탐구학습의 과정을 자연스럽게 밟아 갈 수 있도록 하는 가이드 기능과, 모바일 기술을 바탕으로 습득한 자료를 원격지 학습서버에 저장하여 재사용할 수 있도록 하여 학생들이 수행하는 탐구학습을 지원하였다. 이들은 학교현장에 적용되었고, 결과적으로 학생들의 학습 흥미와 학업성취도는 통계적으로 유의미한 범위에서 향상된 결과를 나타냈다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2006년도 추계 종합학술대회 논문집
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• pp.783-787
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• 2006

공간감각은 주위 환경과 그 환경에서의 물체에 대한 직관적 느낌으로, 유아기는 이러한 공간감각의 기초능력이 발달되는 매우 중요한 시기이다. 유아들은 공간에 대한 직접적이고 능동적인 탐색을 통해 공간감각을 발달시켜 나가므로, 신체적인 움직임을 통해 공간을 탐색하는 경험은 공간감각 향상에 필수적이다. 본 논문에서는 동작을 이용한 유아의 공간감각 계발을 위해 4가지 콘텐츠를 제안한다: 물방울게임, 골키퍼 게임, 웅덩이를 피하기, 도형 맞추기. 제안된 4가지 콘텐츠는 보다 넓은 공간을 활용한 활동을 제공하기 위해서 가상 학습 공간으로 구현되었다. 또한, 구현된 가상학습공간에는 유아의 행동을 인지하여 가상학습공간의 콘텐츠를 이용할 수 있는 실감형 인터페이스를 적용하고 있다. 유아들의 행동에 바탕을 둔 실감형 인터페이스를 사용하는 것은 유아들에게 공간감각 형성에 도움을 줄 뿐만 아니라, 학습에 대한 즐거움, 흥미를 제공하게 되는 매우 중요한 역할을 수행하게 된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.944-947
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• 1996

Realization of autonomous agents that organize their own internal structure in order to behave adequately with respect to their goals and the world is the ultimate goal of AI and Robotics. Reinforcement learning gas recently been receiving increased attention as a method for robot learning with little or no a priori knowledge and higher capability of reactive and adaptive behaviors. In this paper, we present a method of reinforcement learning by which a multi robots learn to move to goal. The results of computer simulations are given.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.307-312
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• 2004

In our fast-moving information and knowledge society, skills and know-how rapidly become outdated. Virtual learning environments play a key role in meeting today's growing demand for customized educational and vocational training and lift-long teaming. The scope of multimedia-based and web-supported education is illustrated by means of an interdisciplinary multimedia project 'New Statistics' funded by the German government. The project output contains more than 70 learning modules covering the complete curriculum of an introductory statistics course. All modules are based on a statistical laboratory and on a multitude of Java applets, animations and case studies. The paper focuses on presenting the statistical laboratory and the applets. These components present the main project pillars and are particularly suitable for international use, independently from the original project framework. This article also demonstrates the application of Java applets and other multimedia developments from the educational world to official statistics for interactive presentation of statistical information.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 가을 학술논문 발표대회
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• pp.184-185
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• 2021

Based on changes in capacity demanded by society as a result of the 4th industrial revolution, as well as changes in the environment due to COVID19, it is necessary to adopt new educational methods in Korean universities. In response to such changes, there have been attempts to apply innovative teaching methods, such as flipped learning and blended learning. However, most studies are limited to either learning effects and/or satisfaction. Accordingly, this study seeks to contribute to the changing educational methods by developing online and offline blended building construction curriculum. The results of this study are as follows: combined education was made possible by developing a curriculum by dividing the online and offline environments. It is determined that the developed curriculum will be efficient and appropriate for the new environments.

• 한국군사과학기술학회지
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• 제27권3호
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• pp.346-354
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• 2024

Deep learning models require high computing power due to a substantial amount of computation. It is difficult to use them in devices with limited computing environments, such as coastal surveillance equipments. In this study, a lightweight model is constructed by analyzing the weight changes of the convolutional layers during the training process based on MobileNet and then pruning the layers that affects the model less. The performance comparison results show that the lightweight model maintains performance while reducing computational load, parameters, model size, and data processing speed. As a result of this study, an effective pruning method for constructing lightweight deep learning models and the possibility of using equipment resources efficiently through lightweight models in limited computing environments such as coastal surveillance equipments are presented.

• 한국멀티미디어학회논문지
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• 제23권9호
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• pp.1139-1146
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• 2020

Recently, as e-learning technology advances, interaction and data exchange between lecturers and learners have become very important. In addition, accuracy of data delivery and efficiency of system implementation should be ensured. Considering these aspects, SignalR is the most suitable communication method for constructing an audience response system in e-learning. Existing audience response systems require separate wireless devices and have problems with system compatibility. SignalR, on the other hand, is capable of operating in all environments including PC programs, web, Android, and iOS, and has an advantage of being easy to develop applications. As such, SignalR is widely used in chatting functions for small scale, real-time communication system, and it has never been used to implement an audience response system. Thus, for the first time in this paper, an audience response system using SignalR was proposed and an experiment was conducted on whether it was applicable at the e-learning education field. Therefore, from the results fo an experiment, a variety of e-learning environments can be built through the audience response system using SignalR proposed in this paper.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.131-142
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• 2022

This study aims to explore how college students have adjusted to Internet-based learning (IBL) since the pandemic and how they have subjectively experienced their Internet-based classes including live-streaming and recorded classes. We conducted a qualitative study on 16 college students in South Korea. The analysis of the in-depth interviews revealed that despite early negative experiences regarding adjustment to IBL, the participants seemed to have developed an increased sense of control over their learning and simultaneously reported a greater need for self-discipline and social support in order to stay motivated. Also, instructors' digital competence and creative attempts to facilitate class communication and discussion appeared to have influence on successful IBL. Lastly, the participants' physical learning environments seemed to impact their online learning in terms of their level of alertness and motivation for study. Implications and suggestions were discussed.

• 한국멀티미디어학회논문지
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• 제25권2호
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• pp.145-156
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• 2022

Nowadays, the complexity of object tracking models among hardware applications has become a more in-demand duty to complete in various indeterminable environment tracking situations with multifunctional algorithm skills. In this paper, we propose a virtual city environment using AirSim (Aerial Informatics and Robotics Simulation - AirSim, CityEnvironment) and use the DQN (Deep Q-Learning) model of deep reinforcement learning model in the virtual environment. The proposed object tracking DQN network observes the environment using a deep reinforcement learning model that receives continuous images taken by a virtual environment simulation system as input to control the operation of a virtual drone. The deep reinforcement learning model is pre-trained using various existing continuous image sets. Since the existing various continuous image sets are image data of real environments and objects, it is implemented in 3D to track virtual environments and moving objects in them.