• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1249-1252
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• 2021

이 시스템은 openCV와 딥러닝 학습모델을 이용하여 횡단보도의 상황을 파악하고 횡단보도위의 객체를 추출하여 자동으로 신호를 제어할 수 있다.보행자를 인식하여 노인, 장애인 등 보행속도가 느린 보행자들을 위해 횡단보도의 신호를 추가하여 보행자의 교통사고를 줄일 수 있다. 또한 교통흐름도 고려하여 차량운전자와 보행자 모두에 도움이 되는 시스템 구현을 목표로 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2780-2792
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• 2010

In this study, we examine what components of e-learning environment affect e-learners' satisfaction. We focus on the task based approach to perceived website complexity(PWC). We study about the role of e-tutor using the internet, telephone, text message and e-mail etc. To test our model, we collected 235 data from online learners of Korea Culture & Content Agency using survey method. The research was conducted by SPSS15.0. Our results show that the relationship between PWC and e-learner satisfaction was negative. The rules of e-tutor are supporting e-learning service and facilitating recommendation intention. This study provides implications to design future e-learning service, understand user's herd behavior and evaluate learning process developed.

• Journal of Industrial Convergence
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• v.19 no.3
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• pp.27-34
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• 2021

In the era of the 4th industrial revolution, the age of artificial intelligence, the development of ICT technology is having various effects on the online and offline educational environment. The universal access of online education changes the educational paradigm and converts it to a learner-centered service. At the time when a new educational environment is required to change, interest in flip learning is increasing. Even adult learner's online learning needs is also shown very high. The purpose of this study was to investigate how repetitive learning activities through flip learning for middle-aged online learners of K-Cyber University has a relationship and structural relationship between the effects of learning immersion and learning interest on learning satisfaction. Through this study, there is significance in research to suggest direction for learning satisfaction based on flip learning. For further studies, if a model of analysis of various factors that can be measured is specified and applied, it can be used as a research background that can maximize learning satisfaction based on flip learning.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.507-512
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• 2008

This study investigated the navigation ability of patients with MCI in Virtual Environments(VE) and on the visual functioning. The participants consisted of elderly adults with/without MCI. Neuropsychological tests(RCFT, BVRT, TMT, and Digit Span), the Groton Maze Learning Test(12trials), and the VE navigation learning task(6 trials) were performed. As a result, there were significant group differences for the RCFT and BVRT, but not for the GMLT. For the VE task, there was a significant difference between the MCI and normal group and no interactions between the groups and trials were found. The VE task was correlated with The RCFT, the BVRT, and the GMLT and omnibus the RCFT and the BVRT accounted for 45% of VE performances. Thus, we concluded that patients with MCI are inferior to VE navigation and visual retention/memory play a role in navigation abilities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.482-494
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• 2016

This study examines the longitudinal trends regarding awareness of informatization, Information Technology (IT) use, and attitudes towards IT among older adults aged 60 or over. Surveys were conducted in 2004 and 2014 at senior welfare centers in Seoul, Korea. The trends between 2004 and 2014 showed that the rate of Internet use increased among older adults who lived alone, were aged 70 or over, had middle education level, had low income, or were unemployed. Older adults had positive attitudes towards IT, and users were more positive than non-users. The levels of IT use were low among users, and their reasons for IT use were for psychological, emotional, and practical purposes. For non-users of IT, their passive tendencies toward IT use and informatization were amplified. As such, the state of IT use and attitudes toward it among older adults in Seoul were longitudinally different, and the differences in awareness and ability between users and non-users tended to increase.

• The Journal of Korean Medical History
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• v.24 no.1
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• pp.1-8
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• 2011

As the value of living a complete life has spread, the importance of elderly education as a part of continuing education is ever increasing. As much as the bodily health, the activity to prevent dementia or healthy brain is being emphasized, the math utilizing traditional material was suggested to devise the curriculum appropriate for the emotional/cognitive level of the elderly. This could induce interests of the elderly, and ultimately improved the concept of self-consciousness and self-esteem. Also, a plan for effective application of such 'silver math' should be prepared, and the execution of a fusion study for a medical approach of its effects is proposed.

• Journal of the International Relations & Interdisciplinary Education
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• v.1 no.2
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• pp.1-11
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• 2021

The purpose of this study is to inspect the case of university convergence education on elderly education. The Center for Academic Continuing Education (ZAWiW) at Ulm University in Germany aims to inquiry the diversity and differentiation of university and related institutions for senior education by analyzing the linkages between various major areas related to the subject of the elderly and cooperation models between generations. Various topics related to research and life in the elderly are being conducted with a focus on the participation of elderly learners. Through seasonal academy and Ulm 3rd Generation University, connection between regions and universities and interdisciplinary convergence are being actively provided. It can lead to a differentiated strategy of the university for the education of the elderly.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.463-464
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• 2019

본 논문은 기계학습을 기반으로 아두이노와 시리얼통신을 통한 사용자의 동작인식을 이용해 보다 간단하게 인터넷상의 원하는 동영상을 찾을 수 있는 검색시스템을 제작하고자 하였다. 이 검색시스템은 Python을 기반으로 SVM(Support Vector Machine)을 이용한 패턴 분류를 사용하였으며 이를 통해 사용자의 동작을 입력받아 문자를 예측 할 수 있다. 사용자는 이 검색시스템을 사용하기 위하여 우선 문자에 대한 사용자의 동작입력을 통해 학습 데이터 셋을 만들어야 하며 그것을 SVM을 이용하여 학습 모델과 식별자를 만들고, 만들어진 분류기를 통하여 동작인식을 바탕으로 문자의 결과를 예측 할 수 있다. 최종적으로 사용자의 동작인식을 거쳐 만들어진 문자열을 이용해 인터넷 동영상 사이트인 Youtube를 통해 웹 크롤링하여 문자열과 관련 있는 동영상을 찾아준다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1020-1023
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• 2021

본 논문에서는 기존의 책상에서 발생하는 문제점을 개선하고 효율적인 공부를 할 수 있도록 도와주는 "학습 능률을 높이는 스마트 책상" 시스템을 제안한다. 제안하는 시스템의 주요 기능은 다음과 같다. 첫째, 아두이노와 Linear actuator를 사용하여 책상의 높낮이와 책받침의 각도를 조절한다. 둘째, 심박 센서를 통해 사용자의 집중도를 확인하고 이와 연동된 어플리케이션으로 각종 센서와 모듈을 제어하여 최적의 공부환경을 조성한다. 셋째, 책상 위 모든 동작이 어플리케이션을 통해 자동으로 수행되어 Human task를 감소시킨다. IoT 기술과 집중력 관리 알고리즘을 활용한 제안 시스템을 통해 학습자의 책상 앞 올바른 자세 교정과 학습 시 높은 집중력을 유지시키는데 도움을 줄 수 있을 것으로 기대된다.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.33-48
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• 2023

In this paper we consider automatic speech recognition (ASR) for Korean speech data in which elderly persons randomly speak a sequence of words such as animals and vegetables for one minute. Most of the speakers are over 60 years old and some of them are dementia patients. The goal is to compare deep-learning based ASR models for such data and to find models with good performance. ASR is a technology that can recognize spoken words and convert them into written text by computers. Recently, many deep-learning models with good performance have been developed for ASR. Training data for such models are mostly composed of the form of sentences. Furthermore, the speakers in the data should be able to pronounce accurately in most cases. However, in our data, most of the speakers are over the age of 60 and often have incorrect pronunciation. Also, it is Korean speech data in which speakers randomly say series of words, not sentences, for one minute. Therefore, pre-trained models based on typical training data may not be suitable for our data, and hence we train deep-learning based ASR models from scratch using our data. We also apply some data augmentation methods due to small data size.