• Journal of the HCI Society of Korea
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• v.10 no.2
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• pp.13-19
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• 2015

Display technology has recently made enormous progress. In particular, display companies are competing each other to develop flexible display. Curved display, as a precursor of flexible display, are now used for smart phones and TVs. Curved monitors have been just introduced in the market, and are used for office work or entertainment. The aim of the current study was to investigate whether the curvature of a 42" multi-monitor affects postural control when it is used for entertainment purpose. The current study used two curvature levels (flat and 600mm). Ten college students [mean(SD) age = 20.9 (1.5)] with at least 20/25 visual acuity, and without color blindness and musculoskeletal disorders participated in this study. In a typical VDT environment, each participant played a car racing video game using a steering wheel and pedals for 30 minutes at each curvature level. During the video game, a pressure mat on the seat pan measured the participant's COP (Center of Pressure), and from which four measures (Mean Velocity, Median Power Frequency, Root-Mean-Square Distance, and 95% Confidence Ellipse Area) were derived. A larger AP (Anterior-Posterior) RMS distance was observed in the flat condition, indicating more forward-backward upper body movements. It can be partly due to more variability in visual distance across display, and hence longer ocular accommodation time in the case of the flat display. In addition, a different level of presence or attention between two curvature conditions can lead to such a difference. Any potential effect of such a behavioral change by display curvature on musculoskeletal disorders should be further investigated.

• The Korean Journal of Food And Nutrition
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• v.29 no.2
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• pp.206-217
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• 2016

This study was conducted to assess the recognition and consumption of health functional food (HFF) of the college students in the Northern Gyeonggi-do area (Republic of Korea). To accomplish this, a survey was conducted to investigate 360 college students (183 males and 177 females) regarding their general characteristics, as well as the recognition, knowledge, considerations, purchases and consumption of HFF. Most male and female students (68.9% and 61.6%, respectively) were unaware of the HFF certification mark, however, more females(58.8%) were aware of the legal HFF definition compared to males (36.6%). The HFF advertising routes for males and females were 'TV radio' (43.2% and 43.5%, respectively) and 'internet smart phones' (19.7% and 27.1%, respectively). The main factor considered for selection and the most serious problem concerning HFF by males and females were 'effectiveness' (36.1% and 43.6%, respectively) and 'hype (exaggerated advertisement)' (35.0% and 55.9%, respectively). The main purchase route by males and females was 'pharmacy' (35.2% and 27.8%, respectively). The main reason for HFF product purchase by males and females was 'health promotion' (38.8% and 29.4%, respectively) and the main reason for not purchasing an HFF product was 'no health problem'(34.8% and 36.7%, respectively). The percentage of HFF consumption was 46.0% in males and 69.8% in females. The main HFF product consumed by males and females was 'vitamin mineral' (36.9% and 43.5%, respectively). The main reason for HFF consumption by males was 'health promotion' (31.0%) and females was 'recovery from fatigue' (21.8%). The main reason for not consuming HFF by males and females was 'no health problem' (38.4% and 41.5%, respectively). These results suggest the need to provide correct information concerning HFF to college students. Based on these results, greater efforts should be made to provide meaningful information regarding factors affecting purchase and consumption patterns for college students related to the research and development of HFF in the Northern Gyeonggi-do area.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.