• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.119-130
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• 2017

The purpose of the study is discovering the effects of virtual competitors on user in AR (Augment Reality) home training system. Specifically, the current research examined their effects on immersion, perceived competition, and leaning motivation. The paper tested three unexplored relationship. First, introducing virtual competitors in home training system will enhance user's immersion. Second, presenting virtual competitors in home training system will increase user's perceived competition. Third, virtual competitors in home training system will raise user's learning motivation. For empirical analysis, we developed home training system, which could check and give feedback automatically, based on user's posture. Using this AR home training system, the study empirically shows how and why virtual competitors affect users. The results give implications not only on service design; but also on the idea that virtual other could affect user's behavior.

• Broadcasting and Media Magazine
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• v.26 no.3
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• pp.71-78
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• 2021

본 고는 혼합현실 기술을 활용한 스마트 홈트레이닝, 그리고 피트니스 코칭 시스템을 메타버스 환경에서 어떻게 구현할 수 있을지에 대한 아이디어를 공유해 보고자 하였다. 그래서 2장에서는 혼합현실, 확장현실의 개념과 그 현황에 대해서 알아보았다. 또한 3장에서는 피트니스 트레이닝 코칭 시스템이 메타버스 환경으로 들어올 수 있는지, 그럴 필요가 있는지를 확인하기 위하여 그 각각의 개념과 현황에 대해서 챙겨보았다. 4장에서는 혼합현실을 이용한 피트니스 코칭 시스템의 현황을 살펴보고, 5장에서는 구체적인 연계 방안을 제시하는 것으로 마무리하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.153-155
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• 2020

가상환경 홈 트레이닝 시스템은 바이러스, 날씨, 환경 등으로 인해 외부활동이 제한된 경우 실내에서도 실외에서 운동하는 것과 같은 효과를 얻기 위하여 구성하였다. 사용자는 실내에서도 vr 기기를 사용함으로써 가상환경을 통해 보다 실감나는 환경으로 운동을 할 수 있다

• Journal of the Korea Convergence Society
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• v.12 no.6
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• pp.233-239
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• 2021

Recently, the COVID-19 virus has caused people to stay indoors longer without going out. As a result of this, people's activity decreased sharply, and their weight gained. So people became more interested in health. Home training can be an alternative method to solve this problem. Accordingly, To find out the trends of home training, we collected articles from December 1, 2019, to November 30, 2020, using the news provided by BIG KINDS, a news analysis system. We analyzed frequency analysis, relational analysis according to weighting, and related word analysis with the program using the algorithm developed by BIG KINDS. In conclusion, first, it was found that home training is led by technology and the emergence of artificial intelligence. Second, it can be assumed that people mainly do home training using content and video services related to mobile carriers. Third, people had a high preference for Pilates in the sports category. It can be seen that the number of patent applications increased as the demand for exercise products related to Pilates increased. In the next study, we expect that this study will be used as primary data for various big data studies by supplementing the research methodology and conducting various analyses.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.864-865
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• 2023

IoT 홈 트레이닝 시스템은 집 안에서도 정확한 동작으로 운동을 보조해주도록 구성된 시스템으로 사용자가 올바른 자세로 운동을 할 수 있게 보조해준다. 또 앱을 통하여 실시간 운동량을 확인할 수 있으며, 운동 개수를 측정하여 운동에 집중할 수 있게 제공한다. 그러나 개발 측면에서는 각 센서의 위치에 따른 사람들의 신장 차이 등 다양한 변수가 발생하여 해결해야 할 필요가 있다.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.74-82
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• 2007

Context awareness using intelligent system is emphasized in order to provide automatic services in home automatic system. In this paper, we propose the intelligent context-aware system for home automation. To implement home automation, we first collect various events occuring in user's home, which are saved as a case form. We use the saved data as a training data of a neural network algorithm and then apply to intelligent context aware system for home automation. This system provide "right situations do right things" for user. Also this system has intelligent ability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1183-1189
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• 2021

There have been recently an increasing number of people working out at home. However, many of them do not have face-to-face guidance from experts, so they cannot effectively correct their wrong pose. This may lead to strain and injury to those doing home training. To tackle this problem, this paper proposes a video data-based pose classification and correction system for home training. The proposed system classifies poses using the multi-layer perceptron and pose estimation model, and corrects poses based on joint angels estimated. A voting algorithm that considers the results of successive frames is applied to improve the performance of the pose classification model. Multi-layer perceptron model for post classification shows the highest accuracy with 0.9. In addition, it is shown that the proposed voting algorithm improves the accuracy to 0.93.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.269-271
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• 2019

우리에겐 익숙하고 쉽게 느껴지지만, 누군가에겐 어려운 것들이 존재한다. 예로 시각 장애인에게는 거리를 돌아다니는 것, 거리를 달린다는 것은 상당한 용기가 필요한 일이다. 경북대학교 재학 중인 시각 장애인 김경훈 학우는 자신의 유튜브 채널에 등교하는 거리에 익숙해지도록 여러 번 걸어 다니며 연습하는 모습의 영상을 올린 적이 있다. 또 다른 시각장애인은 국민 청원에 트레이닝에 대한 지원 요청을 한 적이 있다. 우리는 이런 사례들을 조사하여 거리에 나가지 않아도, 위험요소를 생각하지 않아도 할 수 있는, 그 누구도 차별 받지 않고 모두가 자연스럽게 운동에 집중할 수 있는 홈 트레이닝 시스템을 구현하였다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.19-28
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• 2009

Computer system performance has always had the possibility of affecting business profitability, but with the advent of the World Wide Web where customers interact directly with Web servers, response time can have a direct and dramatic impact on business revenue. This paper is written in the operation environment and system analysis of HTS(Home Trading System) running K Securities. This paper also shows the method for performance improvement through investigation and analysis for the overall systems resources whether HTS has an appropriate performance or not. Performance analysis includes specially CPU analysis, Memory analysis, Disk Input/Output analysis and application analysis. Besides providing more detailed server specification for expansion from now on, system performance can be maintained with effect in the future. Through this study it is possible to manage the performance of HTS more easily and to solve problems such as a bottleneck more quickly.