• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.2
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• pp.737-744
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• 2019

The study aimed to effect of leisure support and leisure constraints on life satisfaction for extreme sports participants. A total of 368 adults from Seoul, In-chon, Gyeonggi, and Chungcheng-do were recruited. I conducted frequency, reliability, confirmatory factor, correction, and structure equaling modeling analyses using PASW Statistics 18.0 and AMOS 18.0. The results were as follows: (1) leisure support of extreme sport participants has no influence on leisure constraints; (2) leisure support of extreme sport participants had no influence on life satisfaction; (3) leisure constrain of extreme sports had a positive influence on life satisfaction. The article revealed which sport activity as like leisure activity had influence on life satisfaction, and leisure support of participants were related with life satisfaction. Therefore, we continue need to induce to join a extreme sport as it publicize a good benefits for extreme sport.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.813-814
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• 2009

익스트림 프로그래밍에서는 문서화 보다는 면대면 의사소통을 중시하기 때문에 직접 소통이 곤란한 상황에서는 빠른 정보 획득과 이해에 어려움을 갖는다. 이러한 문제점은 개발 중 나타나는 산출물을 프로젝트 개발 특성에 따른 분류와 단위화로 해결이 가능하다. 이를 위하여 본 연구에서는 익스트림 프로그래밍에서 사용자 스토리 중심의 개발 단위와 개발 수준별 산출물 유형을 식별하고 이를 기반으로 하는 사용자 스토리 바인더 생성 방안을 제안하였다. 아울러 자판기 사례를 통하여 적용을 보인다.

• Venture DIGEST
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• s.130
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• pp.30-31
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• 2009

반복되는 일상생활에서 벗어나 바람을 타며 날아오르는 새의 기분을 느껴보고 싶은가! 다양한 레포츠 활동을 꿈꿔온 당신의 로망을 실현시켜 줄 멋진 동호회가 여기 있다. 한글과컴퓨터(대표 김수진, www.haansoft.com, 이하 한컴)의 레포츠 동호회인 '까르페디엠'이 바로 그 주인공. 패러글라이딩을 위주로 서바이벌, 모터사이클 등 익스트림 레포츠를 즐기는 한컴 사내 동호회다.

• Journal of Navigation and Port Research
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• v.38 no.2
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• pp.147-154
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• 2014

The purpose of this study was to identify the correlation among participating in the extreme sports, the flow experience and the satisfaction of life. 420 participants of the extreme sports were selected by the Judgement Sampling Method. Factor analysis and multi-regression analysis have been conducted. The conclusion is as follows. First, the participants' life satisfaction is partially affected by the duration period and term. Second, period, frequency, duration partially effect to life satisfaction. Third, flow experience partially effect to life satisfaction.

• Journal of the Korea society of information convergence
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• v.1 no.1
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• pp.33-40
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• 2008

When performing a software development project, the most important thing is building a result with planned quality within development period. Particularly, if the project is delayed or has no good quality in the case of the content software development project which is sensitive to the release time and quality, it is immediately connected to the failure of the whole project. Extreme programming is a methodology that divides the development cycle into smaller units for reducing the risk factor of the project in which the development period is important. In this paper, we suggest the expanded extreme programming which can consider the development period and quality at the same time for content software development environment. The suggested methods are documentation mechanism that is upcoming during the development project and multiple role model which is extended from pair programming method.

• Electronics and Telecommunications Trends
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• v.28 no.1
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• pp.33-41
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• 2013

64bit 범용 서버의 활용 확산, 메모리 가격의 하락 등 하드웨어의 발전과 실시간성을 요구하는 응응 분야의 확대로 인해 인-메모리 컴퓨팅 기술에 대한 관심이 높아지고 있다. 인-메모리 컴퓨팅 기술은 응용 서비스의 클라우드화, 모바일화, 글로벌화로 인해 발생하는 익스트림 트랜잭션의 고성능 처리를 지원하기 위한 기반 기술로 활용이 확대되고 있다. 또한 빅데이터를 효과적으로 활용하기 위해서 빅데이터라는 원석을 보석으로 가공하는 데 있어서 실시간성을 제공하기 위한 기반 플랫폼으로서 활용이 시도되고 있다. 본고에서는 고성능 트랜잭션 처리를 필요로 하는 통신, 금융 등 특정 분야에서 주로 활용되던 인-메모리 DBMS(Datbase Management System) 기술이 익스트림 트랜잭션 서비스 환경, 빅데이터 실시간 분석 환경 등 새로운 서비스 환경을 지원하기 위한 기술 발전 동향에 대해 조사한다.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.623-632
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• 2018

Both investors and researchers are attentive to the prediction of stock price movement directions since the accurate prediction plays an important role in strategic decision making on stock trading. According to previous studies, taken together, one can see that different factors are considered depending on stock markets and prediction periods. This paper aims to analyze what data mining techniques show better performance with some representative index and stock price datasets in the Korea stock market. In particular, extreme gradient boosting technique, proving itself to be the fore-runner through recent open competitions, is applied to the prediction problem. Its performance has been analyzed in comparison with other data mining techniques reported good in the prediction of stock price movement directions such as random forests, support vector machines, and artificial neural networks. Through experiments with the index/price datasets of 12 years, it is identified that the gradient boosting technique is the best in predicting the movement directions after 1 to 4 days with a few partial equivalence to the other techniques.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.983-991
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• 2019

This study aims to analyze movies which contain various stories according to the size of their shots. To achieve this, it is needed to classify dataset according to the shot size, such as extreme close-up shots, close-up shots, medium shots, full shots, and long shots. However, a typical video storytelling is mainly composed of close-up shots, medium shots, full shots, and long shots, it is not an easy task to construct an appropriate dataset for extreme close-up shots. To solve this, we propose an image cropping method based on the region of interest (ROI) detection. In this paper, we use the face detection and saliency detection to estimate the ROI. By cropping the ROI of close-up images, we generate extreme close-up images. The dataset which is enriched by proposed method is utilized to construct a model for classifying shots based on its size. The study can help to analyze the emotional changes of characters in video stories and to predict how the composition of the story changes over time. If AI is used more actively in the future in entertainment fields, it is expected to affect the automatic adjustment and creation of characters, dialogue, and image editing.

• Journal of the HCI Society of Korea
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• v.5 no.1
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• pp.37-43
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• 2010

Twitter has been continuously growing since October, 2006. Especially, not only the users and the number of messages have been increasing but also a new concept in social networking called 'micro blogging' has diffused. Within Korea, service such as 'me2day' has already been introduced and the improvement of internet accessibility within mobile devices is expected to expand the 'micro blogs'. In this point, this research is executed to study the new medium, 'micro blog'. To do so, we collected and analyzed Twitter logs of Korean users. Especially, we were curious about the extreme heavy users using Twitter, despite of the linguistic and cultural barrier of the foreign service. Who they are, why and how they use the 'micro blog'. First, we reviewed the general aspect of followers and messages by collecting a certain number of random samples. Using the Lorenz curve we found out that there was the imbalance within the users and based on this phenomenon we deducted an extreme heavy user group. In order to perform further analysis, log analysis was performed on the extreme heavy users. As the result, the users used multiple mobile and desktop 'Twitter' clients. The usage pattern was similar to that of internet usage time but was used during their "micro" time. The users using 'Twitter' not only to spread messages about important information, special events and emotions, but also as a habitual 'chatting tool' to express ordinary personal chats similar to SMS and IM services. In this research, it is proved that 68% of the total messages were ordinary personal chats. Also, with 24% of the total messages were retweets, we were able to find out that virtually connected 'people' and 'relationships' acted as the dominant trigger of their articulation.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.886-887
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• 2016

최근 우리사회는 다양한 형태의 여가활동 및 생활체육에 대한 국민적 욕구와 열망과 더불어서, IoT기술발전 및 시장확대에 힘입어 다양한 스마트 자전거 제품이 등장하고 있다. 그러나 기존 제품의 경우 속도계 장치에 의한 주행기록을 분석할 수 없고, 스마트폰 앱의 경우에는 정확한 데이터 측정이 불가능하다. 이러한 문제점을 해결하기 위하여, 본 논문에서 개발한 스마트 자전거는 마그네틱 센서를 이용하여 거리, 속도, 시간 등을 측정/분석하고, 라이딩 정보를 어플리케이션에 저장하여 사용자가 라이딩 정보를 언제든 살펴볼 수 있다. 또한, 라이딩 속도에 따라서 LED의 색상이 변경되어 익스트림 라이딩 모드 및 LED제어, 스마트 자물쇠 기능 등을 제공한다.