• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.923-931
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• 2009

The purpose of this study is to testify construct validity of Self-directed Learning Perception Inventory for middle school students(Lee, 2008). For the purpose, First, test was done with 1202 middle students sampled from nationwide. As a result of confirmatory factor analysis using structural equation model, we confirmed 7 factor model was generally appropriate and acceptable. Second, in order to test criterion-related validity, test was done with 530 middle school students sampled form Seoul, Gyeonggido, Chungchongdo. The inventory has criterion-related validity enough to be a tool for measurement. Reliability of this inventory was .94 and retest reliability was .91. The limitation of this and suggestion for future research were discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.75-81
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• 2022

Autonomous vehicles, which can dramatically solve the lack of parking spaces, are making great progress through deep reinforcement learning. Activation functions are used for deep reinforcement learning, and various activation functions have been proposed, but their performance deviations were large depending on the application environment. Therefore, finding the optimal activation function depending on the environment is important for effective learning. This paper analyzes 12 functions mainly used in reinforcement learning to compare and evaluate which activation function is most effective when autonomous vehicles use deep reinforcement learning to learn parking. To this end, a performance evaluation environment was established, and the average reward of each activation function was compared with the success rate, episode length, and vehicle speed. As a result, the highest reward was the case of using GELU, and the ELU was the lowest. The reward difference between the two activation functions was 35.2%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.625-627
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• 2018

본 연구는 전 연령 및 아동을 대상으로 하는 모바일 AR(Augmented Reality, 증강현실) 기반의 스마트폰 어플리케이션을 설계 제안하고, 아동이 사용가능한 교육용 책 교구를 설명한다. 현재 시중에 출시된 어플리케이션에 대해 분석하고, 사용자의 동기유발과 집중력 향상을 목적으로 학습 구조를 도출한다. 학습의 집중을 위한 단순한 사용자 인터페이스를 설계하여, 증강현실 기술과 접목한다. 본 연구를 통해 사용자는 책이 가진 지식의 보고를 유지하며 스마트 폰을 통한 자율학습을 유지할 수 있다. 경제적 소비 감소와 스마트 폰의 활용도를 기대할 수 있다.

• English Language & Literature Teaching
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• v.10 no.1
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• pp.127-152
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• 2004

The purpose of this study is to elaborate design strategies for a Web-based self-directed cooperative distance language learning community. Research was done regarding the theoretical foundations for self-directed cooperative language learning and Web-based learning communities. The components of a Web-based community for self-directed cooperative language learning system are also investigated. As a result of this study, design strategies for Web-based communities are suggested. There are performance and supporting environments(synchronous/asynchronous) for self- directed cooperative language learning. There are also cultural experiences and communication factors in the performance field. Furthermore, matching communicators, finding and offering information, language learning content and other supporting agents are important in the supporting environment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.138-138
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• 2020

전세계적으로 자율운항선박 기술개발이 활발하게 이루어지고 있으며, IMO(국제해사기구)에서는 자율운항선박 도입을 위한 제도적 측면에서 검토 중이다. 우리나라도 해수부-산업부 공동으로 자율운항선박 기술개발사업을 진행 중이며, 2025년까지 자율화등급 3수준의 기술개발을 목표로 한다. 본 연구는 자율운항선박 항해에 기초가 될 충돌회피 시점을 도출하고자 한다. 이를 위해 우리나라 연안의 해상교통조사 자료를 이용하여 선박운항자의 피항시점(CPA, TCPA, 위험도, 이격거리, 선수방향차이 등)을 파악하고자 한다. 피항시점은 자율운항시스템의 기초학습자료로 이용할 수 있을 것으로 예상된다.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.569-572
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• 2010

맞춤형 이러닝은 학습효과의 증진을 위한 방안으로 개인 맞춤형, 개인화 혹은 적응화 등의 개념이 제안되고 확장되었다. 본 논문에서는 초기 선호도, 흥미도 혹은 검색습관을 고려하는 방식으로부터, 특정한 학습객체를 자율 선택하여 반복 학습할 수 있도록 개념단위를 적용한 방식, 학습자의 능력을 고려한 최적 난이도 학습객체를 제공하는 방식 등 다양하게 제안되고 있는 현대적 개인 맞춤형 이러닝 체계들을 비교 분석한다. 개별 시스템에 따라 '평가'에 국한되거나 '평가'와 '학습'을 연계하는 경우가 존재하며, 이에 따른 적용에 의하여 학습환경과 맞춤형 제공방식 및 학습효과를 상호 연계할 수 있음을 밝힌다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.74-81
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• 2024

In the near future, autonomous ships, ships controlled by shore remote control centers, and ships operated by navigators will coexist and operate the sea together. In the advent of this situation, a method is required to evaluate the safety of the maritime traffic environment. Therefore, in this study, a plan to evaluate the safety of navigation through ship control simulation was proposed in a maritime environment, where ships directly controlled by navigators and autonomous ships coexisted, using autonomous operation technology. Own ship was designed to have autonomous operational functions by learning the MMG model based on the six-DOF motion with the PPO algorithm, an in-depth reinforcement learning technique. The target ship constructed maritime traffic modeling data based on the maritime traffic data of the sea area to be evaluated and designed autonomous operational functions to be implemented in a simulation space. A numerical model was established by collecting date on tide, wave, current, and wind from the maritime meteorological database. A maritime meteorology model was created based on this and designed to reproduce maritime meteorology on the simulator. Finally, the safety evaluation proposed a system that enabled the risk of collision through vessel traffic flow simulation in ship control simulation while maintaining the existing evaluation method.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.107-114
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• 2022

In this paper, proposes a delivery robot that can be autonomous driving learning. The proposed robot is designed to be used in park-type apartments without ground parking facilities. Compared to the existing apartments with complex ground and underground routes, park-type apartments have a standardized movement path, allowing the robot to run stably, making it suitable for students' initial education environment. The delivery robot is configured to enable delivery of parcels through machine learning technology for route learning and autonomous driving using cameras and LiDAR sensors. In addition, the control MCU was designed by separating it into three parts to enable learning by level, and it was confirmed that it can be used as a delivery robot for learning through operation tests such as autonomous driving and obstacle recognition. In the future, we plan to develop it into an educational delivery robot for various delivery services by linking with the precision indoor location information recognition technology and the public technology platform of the apartment.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.72-79
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• 2019

Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

• Journal of the Korean School Mathematics Society
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• v.10 no.3
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• pp.323-340
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• 2007

This study set out to analyze the learning types that most students were engaged in after school, to review the efficiency of private education through academic institutions or tutoring, and to examine the directions in the after-school learning in math under the current system. It also aimed to analyze the impacts of those after-school learning activities on school classes and to suggest some plans to help public education get back on the track. In the study the after-school learning activities in the math subject were categorized into taking classes at academic institutions, tutoring, and autonomous learning. The grades of the subject students were compared and analyzed for three semesters to find the directions right for the school classes.