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Anyang, South Korea

Kim S.-Y.,Sungkyul University | So W.-Y.,Seoul Womens University
Journal of Sports Science and Medicine | Year: 2012

Increased physical activity (PA) is the relationship with improved cognitive and memory functions of the brain. The physical education (PE) classes held in school comprise a type of PA. However, there is no epidemiological evidence showing a relationship between school performance and the number of PE classes attended per week in adolescent students. Therefore, the purpose of this study is to examine whether the number of PE classes attended per week is related with school performance in Korean adolescent students. In 2009, 75,066 adolescent students from middle school first grade to high school third grade participated in the 5th Korea Youth Risk Behavior Webbased Survey (KYRBWS-V) project. The relationship between school performance and the number of PE classes attended per week was assessed using multivariate logistic regression analysis after adjusting for covariate variables such as gender, age, body mass index, parents' education level, family's economic status, vigorous and moderate PA, and muscle strengthening exercises. The odds ratio (OR) for attending <3 PE classes per week and school performance was 1.125 for good school performance, 1.147 for average school performance, 1.146 for poor school performance, and 1.191 for very poor school performance, when compared to very good school performance. It was concluded that attending ≥3 PE classes per week was positively correlated with improved school performance and that attending <3 PE classes per week was negatively correlated with school performance in Korean adolescent students. © Journal of Sports Science and Medicine. Source


Seo D.,Sungkyul University
Journal of Internet Banking and Commerce | Year: 2016

The E-car and IT industry can be good examples to realize growth potential by amalgamating technology and capital of the EU with high-quality labor force (not the consumption but the Innovation) and Hub-Spoke market of emerging economies of the CEEC. They started to apply the membership of EU since 1998. The EU accommodated 10 nations as new members of EU in May of 2004 as they fulfilled the requirements of the ‘Copenhagen Convergence Condition’. The EU would like to realize its potential trade and investment opportunities with the CEEC from this enlargement. Since the crisis of the global finance or IT like Nokia in 2008, they have focused on the Innovation and consumption. The paper analyzed the impact for the Innovation and Consumption of Eastern enlargement of EU on trade, investment and technology cooperation patterns of Korea to formulate a pan-European marketing strategy with a special emphasis on the mobile phone industry or motorcar. This is why a new collaborative workplace has enabled the creation of hubs in the emerging regional small markets (Visegrad + Eastern European-Balkan countries) and the central large markets (Germany + CEE). But TNCs may even be merged by mega-innovative companies in the pan-European marketing unless they successfully adapt the changing patterns of demand in according to new commercialization of competing firms. The public policy in a knowledge-based economy is required to shift the role of restraining to fostering in terms of promoting linkage effect for avoiding the chasm. © Daesung Seo, 2016. Source


Chin S.,Sungkyul University | Kim K.-Y.,Wayne State University
Computers in Industry | Year: 2010

To realize truly customer-oriented wearable products, individual users' unique characteristics and features should be properly captured and represented. This research focuses on an efficient methodology to generate low polygonal virtual human face models, which overcome the limitation of existing high polygonal models. To determine individuals' characteristics in the conceptual design stage of wearable products. A computerized and personalized 3D facemodel should be efficiently generated and be able to interact with wearable products. This research formulates a computerized 3D face via a 3D feature-based transformation. The developed algorithm is able to concisely and efficiently create a 3D face by using frontal and lateral pictures of users. The performance of this algorithmis well adapted both to typical PCs and to mobile devices. The generated virtual face models can serve as communication media in a multidevice based collaborative design environment. Through experiments, the validity of the proposed modeling method is considerably acceptable with respect to the quality of the similarity between 3D faces and individual pictures. Finally, this paper discusses how the developed personalized face modeling can be successfully utilized for customer-oriented wearable product design by showing compatible matching of a hairstyle product as a user study. © 2010 Elsevier B.V. All rights reserved. Source


Kim Y.S.,Sungkyul University
Expert Systems with Applications | Year: 2010

In this article, the performance of classification methods was empirically compared while varying the number of classes of dependent variables, the number of independent variables, the types of independent variables, the number of classes of the independent variables, and the sample size. Our study employed 324 simulated examples, with artificial neural networks and decision trees as the data mining techniques, and logistic regression as the statistical method. In the performance study, we use the misclassification errors as the metric and come up with some additional findings: (i) for continuous independent variables, a statistical technique (i.e., logistic regression) was superior to data mining techniques (i.e., artificial neural network and decision tree) when dependent variable has binary values, while the artificial neural network was best when the number of classes of dependent variable was three or more; (ii) for continuous and categorical independent variables, logistic regression performs better than artificial neural network and decision tree in the case of small number of independent variables and small sample size, while artificial neural network was best in other cases; and (iii) the artificial neural network performance improved faster than that of other methods as the number of independent variables and the number of classes of dependent variables increases. © 2009 Elsevier Ltd. All rights reserved. Source


Kim S.-G.,Yonsei University | Yun G.-H.,Sungkyul University | Yook J.-G.,Yonsei University
IEEE Transactions on Microwave Theory and Techniques | Year: 2012

In this paper, a compact vital signal sensing method using oscillation frequency deviation at 2.4-GHz industrial-scientific-medical band is proposed to detect vital signals, such as heartbeat and respiration signal. The oscillation circuit of the proposed vital sensor system has been realized by a planar resonator, which functions as a positive feedback element, as well as a near-field radiator to sense vital signals, simultaneously. The periodic movement of a body by respiration exercise causes the impedance variation of the radiator within the near-field range. The impedance variation results in a corresponding change in the oscillation frequency, and this variation has been utilized for sensing of the vital signals. In addition, a surface acoustic wave filter and power detector have been used to increase the sensitivity of the system and to transform the frequency variation to voltage waveform. The experimental results show that the proposed vital sensor placed 20 mm from the body can detect the heartbeat waveform very accurately. © 2006 IEEE. Source

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