• Title/Summary/Keyword: 혼합 학습환경

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Learning Behavior of Virtual Robot using Compensation Signal (보상신호를 수반하는 가상로봇의 학습행위 연구)

  • Hwang, Su-Chul
    • 전자공학회논문지 IE
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    • v.44 no.3
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    • pp.35-41
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    • 2007
  • In this paper we suggest a model that the virtual robot based on artificial intelligence performs learning with compensation signals and compare the leaning speed of the virtual robot according to the compensation method after applying it to three type environments. As a result our model has showed that positive compensation is superior to hybrid one mixed positive and negative if there are enough time for learning in case of more or less complicated environment with the numerous foods, obstacles and robots. Otherwise hybrid method is better than positive one.

Virtual World On-line Lecture System based on Mixed Reality (혼합현실 기반의 가상 세계 온라인 강의 시스템)

  • Kwon, Oh-Young;Seo, Hyo-Seok;Teles, Gustavo
    • The Journal of Korean Institute for Practical Engineering Education
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    • v.3 no.1
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    • pp.97-102
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    • 2011
  • Learning system on virtual environment gives the immersive feeling that lacks in existing E-Learning system, excites user's interest, and offers dangerous and expensive education contents. In this paper, we classified the learning categories into four classes: realtime lecture, anytime study, practice education, and the activity of study group. We built the on-line lecture system using Second Life that supports 3D virtual world and mixed reality. We provided virtual learning environment as running developed virtual world on-line lecture system.

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Layered Object Detection using Gaussian Mixture Learning for Complex Environment (혼잡한 환경에서 가우시안 혼합 모델을 이용한 계층적 객체 검출)

  • Lee, Jin-Hyeong;Kim, Heon-Gi;Jo, Seong-Won;Kim, Jae-Min
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.435-438
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    • 2007
  • 움직이는 객체를 검출하기 위해서 정확한 배경을 사용하기 위해 널리 사용되는 방법으로는 가우시안 혼합 모델이다. 가우시안 혼합 모텔은 확률적 학습 방법을 사용하는데, 이 방법은 움직이는 배경일 경우와 이동하던 물체가 정지하는 경우 배경을 정확히 모델링하지 못한다. 본 논문에서는 확률적 모델링을 통해 혼잡한 배경을 모델링하고 객체의 계층적 처리를 통해 보다 정확한 배경으로 갱신할 수 있는 학습 방법을 제안한다.

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The Design and Implementation of a Blended-Learning System (통합교육 학습 시스템의 설계 및 구현)

  • Kim, Eun-Kyung;Han, Jae-Il
    • Proceedings of the Korea Information Processing Society Conference
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    • 2005.11a
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    • pp.817-820
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    • 2005
  • 온라인 교육은 오프라인 교육의 한 가지 방식의 교수방법에서 탈피하여 테크놀로지를 이용하여 교육의 효과를 높일 수 있는 구체적인 대안이 될 것이라고 예측되었다. 하지만 최근 들어, 사람이 아닌 PC와 의사소통을 해야 하기 때문에 집중력을 확보하기가 어렵고 인간미가 없다는 점등의 문제가 지적되고 있다. 이 문제점을 해결하기 위해서 교수자들은 온라인 환경이 갖는 장점과 오프라인 환경이 갖는 장점을 혼합한 통합교육을 시도하고 있다. 본 본문에서는 학습자들의 학업성취도와 수업만족도를 높이기 위해 온라인 수업과 오프라인 교실수업을 혼합한 통합교육에 멘토링 기능을 추가하여 학습모델 설계 및 학습 지원 시스템을 설계하였다.

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e-learning Technology Based on Mixed Reality (혼합현실기반 이러닝 기술 동향)

  • Seo, Hui-Jeon;Kim, Yong-Hun;Lee, Su-Ung;Lee, Jun-Seok
    • Electronics and Telecommunications Trends
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    • v.22 no.4 s.106
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    • pp.87-95
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    • 2007
  • 급속한 정보통신 기술의 발달로 인하여 유비쿼터스 컴퓨팅의 기술, 네트워크 인프라, 3D 기술, 가상현실 기술 등 미래 콘텐츠 기술을 적용한 새로운 디지털 사용자 환경이 구축되고 있다. 교육 및 지식 분야에서도 동영상 기반이나 플래시 기반의 단순하고 일방형의 교육 콘텐츠를 벗어난 새로운 고품질의 이러닝 콘텐츠가 요구되고 있다. 또한 개인의 체험 중심의 학습경험과 지식을 스스로 구성해나가는 새로운 학습방법을 지원하는 이러닝 기술의 필요성이 증대되고 있다. 이에 대한 대안의 하나로 실재감과 몰입감을 촉진함으로써 학습효과를 향상시킬 수 있는 혼합현실기반의 이러닝 시스템의 개발이 시도되고 있다. 본 고에서는 혼합현실 이러닝 기술 개발 방향을 모색하기 위하여 국내외 혼합현실 이러닝 기술 동향, 시스템 사례, 교육적 효과에 대하여 살펴보고자 한다.

Adaptation of Classification Model for Improving Speech Intelligibility in Noise (음성 명료도 향상을 위한 분류 모델의 잡음 환경 적응)

  • Jung, Junyoung;Kim, Gibak
    • Journal of Broadcast Engineering
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    • v.23 no.4
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    • pp.511-518
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    • 2018
  • This paper deals with improving speech intelligibility by applying binary mask to time-frequency units of speech in noise. The binary mask is set to "0" or "1" according to whether speech is dominant or noise is dominant by comparing signal-to-noise ratio with pre-defined threshold. Bayesian classifier trained with Gaussian mixture model is used to estimate the binary mask of each time-frequency signal. The binary mask based noise suppressor improves speech intelligibility only in noise condition which is included in the training data. In this paper, speaker adaptation techniques for speech recognition are applied to adapt the Gaussian mixture model to a new noise environment. Experiments with noise-corrupted speech are conducted to demonstrate the improvement of speech intelligibility by employing adaption techniques in a new noise environment.

A Study on the Current Status and Improvement of Online Classes for Students with Developmental Disabilities during the COVID-19 Pandemic -in chungbuk- (코로나19 상황 속 발달 장애 학생의 온라인 학습 실태와 개선방안 -충북지역을 중심으로-)

  • Kim, Hyun-Jin
    • The Journal of the Korea Contents Association
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    • v.21 no.6
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    • pp.350-358
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    • 2021
  • The purpose of this study is to analyze the status of rights for online learning of students with developmental disabilities in the COVID-19 situation and suggest plans to promote the rights focusing on parents with children with disabilities. This research conducted the mixed method, which utilizes the survey of 200 parents with children in chungbuk, who have developmental disabilities, and FGI of six parents. The survey analysis shows that 50.5% of the respondents could not support their children due to telecommuting. The most urgent support system for learning assistance was identified as support for assistive personnel. As a result of the analysis of FGI, two categories of "status of online classes in the COVID-19," "improving non-contact learning environment considering the nurturing environment," "diversifying teaching methods such as video classes," "introducing of a contextual assessment," and "enhancing health support." Based on these findings, the study proposed to review legal grounds for online classes for disabled students, expand the dispatch of learning support personnel and prepare plans to promote the online learning environment.

학습용이성 측면에서의 PC통신 소프트웨어 사용편이성 평가 연구

  • 윤철호
    • Proceedings of the ESK Conference
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    • 1997.04a
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    • pp.123-131
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    • 1997
  • 이 연구에서는 서로 다른 사용자 인터페이스의 대화 방식에 따라 PC통신 소프트웨어 의 사용편이성이 어떻게 달라지는가를 살펴보고자 한다. 이를 위해 현재 국내에서 이 용되고있는 3개의 PC통신소프트웨어를 대상으로 남녀대학생 18명에 의한 사용편이성 평가 시험을 실시하였다. 시험은 강사에 의한 1:1 방식에 의해 실시하였다. 평가척도로 는 학습소요시간, 시험소요시간, 정답률을 이용하였다. 실험결과, 윈도우환경에서 구현 되는 메뉴, 아이콘, 명령어를 혼합한 대화방식의 소프트웨어보다도 도스환경에서 구현된 명령어 대화방식의 소프트웨어가 학습용이성 측면에서의 사용편이성이 높을 수 있다는 점이 시사되었다.

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Differences in Presence, Immersion, and Situation Interest in Small Group Learning Using Augmented Reality Based on the Degree of Tool Sharing (증강현실을 활용한 소집단 학습에서 도구 공유 정도에 따른 현존감, 몰입, 상황흥미의 차이)

  • Taehee Noh;Jaewon Lee
    • Journal of the Korean Chemical Society
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    • v.68 no.2
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    • pp.93-106
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    • 2024
  • This study investigated differences in presence, immersion, and situational interest in small group learning using augmented reality, based on the degree of tool sharing. 84 eighth-grade students participated in small groups of four. Each group was randomly assigned to one of three environments based on marker and device sharing: the shared environment (shared marker and device usage), the mixed environment (shared marker and individual device usage), and the individual environment (individual marker and device usage). Small group learning using augmented reality was conducted for three class periods, focusing on the "Characteristics of Matter" unit. One-way ANOVA results for the dependent variables revealed that, compared to the shared environment, presence and situational interest were significantly higher in the mixed environment, while immersion and situational interest were significantly higher in the individual environment. MANOVA results for the sub-components of each dependent variable showed significant differences in realness for presence, antecedents and experiences for immersion, and instant enjoyment, novelty, and total interest for situational interest. Analysis of interviews and classroom observations indicated that students in shared and individual environments tended to use their devices individually when utilizing augmented reality. However, in mixed environments, students showed a tendency to use their devices collaboratively, leading to more active interactions. Based on these findings, environments for using tools to enhance the effectiveness of small group learning using augmented reality are discussed.

Dynamic Control of Learning Rate in the Improved Adaptive Gaussian Mixture Model for Background Subtraction (배경분리를 위한 개선된 적응적 가우시안 혼합모델에서의 동적 학습률 제어)

  • Kim, Young-Ju
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.366-369
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    • 2005
  • Background subtraction is mainly used for the real-time extraction and tracking of moving objects from image sequences. In the outdoor environment, there are many changeable factor such as gradually changing illumination, swaying trees and suddenly moving objects, which are to be considered for the adaptive processing. Normally, GMM(Gaussian Mixture Model) is used to subtract the background adaptively considering the various changes in the scenes, and the adaptive GMMs improving the real-time performance were worked. This paper, for on-line background subtraction, applied the improved adaptive GMM, which uses the small constant for learning rate ${\alpha}$ and is not able to speedily adapt the suddenly movement of objects, So, this paper proposed and evaluated the dynamic control method of ${\alpha}$ using the adaptive selection of the number of component distributions and the global variances of pixel values.

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