• Journal of the Korea Computer Graphics Society
• /
• v.26 no.4
• /
• pp.1-8
• /
• 2020

Motion synthesis using physics-based controllers can generate a character animation that interacts naturally with the given environment and other characters. Recently, various methods using deep neural networks have improved the quality of motions generated by physics-based controllers. In this paper, we present a control policy learned by deep reinforcement learning (DRL) that enables Luxo, the mascot character of Pixar animation studio, to run towards a random goal location while imitating a reference motion and maintaining its balance. Instead of directly training our DRL network to make Luxo reach a goal location, we use a reference motion that is generated to keep Luxo animation's jumping style. The reference motion is generated by linearly interpolating predetermined poses, which are defined with Luxo character's each joint angle. By applying our method, we could confirm a better Luxo policy compared to the one without any reference motions.

• Geophysics and Geophysical Exploration
• /
• v.23 no.2
• /
• pp.97-114
• /
• 2020

Recently, many studies have been actively conducted on the application of machine learning in all branches of science and engineering. Studies applying machine learning are also rapidly increasing in all sectors of seismic exploration, including interpretation, processing, and acquisition. Among them, fault detection is a critical technology in seismic interpretation and also the most suitable area for applying machine learning. In this study, we introduced various machine learning techniques, described techniques suitable for fault detection, and discussed the reasons for their suitability. We collected papers published in renowned international journals and abstracts presented at international conferences, summarized the current status of the research by year and field, and intensively analyzed studies on fault detection using machine learning. Based on the type of input data and machine learning model, fault detection techniques were divided into seismic attribute-, image-, and raw data-based technologies; their pros and cons were also discussed.

• Geophysics and Geophysical Exploration
• /
• v.25 no.2
• /
• pp.59-70
• /
• 2022

Recent studies demonstrate that machine learning has expanded in the field of seismic interpretation. Many convolutional neural networks have been developed for seismic sequence identification, which is important for seismic interpretation. However, expense and time limitations indicate that there is insufficient data available to provide a sufficient dataset to train supervised machine learning programs to identify seismic sequences. In this study, patch division and data augmentation are applied to mitigate this lack of data. Furthermore, to obtain spatial information that could be lost during patch division, an artificial channel is added to the original data to indicate depth. Seismic sequence identification is performed using a U-Net network and the Netherlands F3 block dataset from the dGB Open Seismic Repository, which offers datasets for machine learning, and the predicted results are evaluated. The results show that patch-based U-Net seismic sequence identification is improved by data augmentation and the addition of an artificial channel.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.16 no.1
• /
• pp.21-31
• /
• 2016

The changes to Ubiquitous Network Environment leads existing learning environment to Smart Learning Environment. Expecially, Smart Learning Environment is in changing paradigm existing teacher centered environment and learner centered environment, recently the demand of Smart Learning Environment for learners are growing up. This study analyzed Learning Environments for Smart Learning Environment focused on the learners through analyzing Ubiquitous Network Environment that is concentrated on the physical aspects and the non-physical aspects. Also, we suggested learning several ways that can be effectively applied based on the environmental characteristics of Smart Learning.

• Communications of Mathematical Education
• /
• v.10
• /
• pp.97-106
• /
• 2000

학습의 도구로써 컴퓨터의 활용은 학습 내용뿐만 아니라 수학적 지식의 획득 과정에 있어서도 변화를 시도하고 있다. 특히 물리적인 환경에서 시 ${\cdot}$ 공간적인 제약으로 인한 구체적 조작활동을 한계성을 극복하기 위해 개발된 기하학습 소프트웨어인 GSP와 Cabri-Geometry II는 새로운 관점에서의 기하학습을 가능케 한다. 본고에서는 기하학습의 도구로써 컴퓨터의 역할과 GSP의 기능적 특성 및 초등학교 수학교수 ${\cdot}$ 학습과정에서 GSP의 활용할 수 있는 방안에 대해서 살펴본다.

• Review of Korea Contents Association
• /
• v.1 no.2
• /
• pp.22-35
• /
• 2003

최근 컴퓨터와 인터넷의 급속한 보급으로 인해 물리적 시공간의 한계를 뛰어 넘어 언제, 어디서나 자신에게 필요한 학습활동을 할 수 있는 기반이 조성되면서 e-러닝(e-Learning)에 대한 관심이 커지고 있다. e-러닝은 '학습 선택권의 확장'과 '학습 기회의 확대'를 통해 궁극적으로 언제(anytime), 어디서(anywhere), 누구나(anyone) 학습할 수 있는 '열린 학습'을 지향하며 기존 교육 패턴과는 전혀 다른 새로운 패러다임을 요구하고 있다[1. 즉, e-러닝의 성패는 '기존 방식과는 다른 방식으로 교육을 설계할 수 있느냐?'와 '학습자들의 학습 습관이 어느 정도 변화했느냐?'에 따라 달라진다. 또한 기업에서는 e-러닝을 조직의 비즈니스 전략과 유기적으로 연동시키는 전략이 성패의 갈림길이다 할 수 있다. (중략)

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2021.06a
• /
• pp.14-15
• /
• 2021

물리 시뮬레이션 기반의 캐릭터 동작 제어 문제를 강화학습을 이용하여 해결해 나가는 연구들이 계속해서 진행되고 있다. 이에 따라 이 문제를 강화학습을 이용하여 풀 때, 영향을 미치는 요소에 대한 연구도 계속해서 진행되고 있다. 우리는 지금까지 이뤄지지 않았던 상태 표현 방식에 따른 강화학습에 미치는 영향을 분석하였다. 첫째로, root attached frame, root aligned frame, projected aligned frame 3 가지 좌표계를 정의하였고, 이에 대해 표현된 상태를 이용하여 강화학습에 미치는 영향을 분석하였다. 둘째로, 동역학적 상태를 나타내는 캐릭터 관절의 위치, 각도에 따라 학습에 어떠한 영향을 미치는지 분석하였다.

• Journal of The Korean Association For Science Education
• /
• v.42 no.5
• /
• pp.557-566
• /
• 2022

This study analyzed paired middle school students' verbal and physical interactions in small group learning using augmented reality. Twelve 8th graders were paired to take classes of solubility and melting/boiling points based on augmented reality. These classes were videotaped and recorded. After the classes, all the students participated in a semi-structured interview. The results were analyzed in three sections; individual statement units of verbal interaction, interaction units of verbal interaction and physical interaction. In the individual statement units of verbal interaction, the proportion of information question/explanation was found to be high. In the interaction units of verbal interaction, the proportion of simple interaction was the highest, followed by elaborated interaction. Beneath the elaborate interaction, the proportion of cumulative interaction was found to be the highest, followed by reformative interaction. In the physical interaction, writing a worksheet and gazing at a virtual object were higher. On the basis of the results, effective ways to form a proper environment in small group learning using augmented reality are discussed.

• Geophysics and Geophysical Exploration
• /
• v.25 no.4
• /
• pp.177-188
• /
• 2022

Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO₂ storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.

• 대한공업교육학회지
• /
• v.32 no.1
• /
• pp.73-92
• /
• 2007

The purpose of this study was to develop ICT(Information and Communication Technology) teaching-learning materials for motorcycle safety education. Physical subjects which are relevant with motorcycle dynamics were introduced to increase the safety awareness through integrated learning such as the combination of technology and science. The results of this study were as follows : (1) Utilizing the physics basic theories which are relevant to motorcycle dynamics, the lesson plan of motorcycle ICT teaching-learning materials, which were included to plan and instruction action plan, was developed. (2) Flash animation or movie was developed to apply physics knowledge to technology in driving motorcycle. This is able to improve the attitude of driving motorcycle of students. (3) Through the contents of appendix of motorcycle safety driving section in this web-site developed here, junior and senior high school students would be able to strengthen their cognitive domain of motorcycle by themselves. (4) Using the web-site of this study, both teachers and students would be able to freely interact through an online bulletin board.