• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.95-106
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• 2016

Biometric data may appear different depending on the person and sasang Medicine has a close relationship with the Department. Biometric data not only mean a human heart rate, a blood pressure, a heart rate, and the past medical history, degree of aging, body mass index, but also is used as a reference measure for determining the state of health of the person. So biometric data should be reproduced for the application purposes, depending on their applications. In previous studies, because the biometric data is changed in real time and applies only to snap shut at the time of the continuity of the current time is excluded. Therefore, in this study in order to solve this problem, we propose a biometric data patton analysis model comprising a continuity of time in the big data environment consisting of biometric data. The proposed model can help determine the choice of needle position carefully when using the electronic acupuncture for care and health promotion.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.173-182
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• 2010

Recently, the society confronts unpredictable disasters and the aspects varies in diverse ways. As a pessimistic perception on the social safety starts emerging, the UT utilized actional system for disaster is viewed as a solution. Therefore, in this paper, I provided UT applied forecast prototype which is a portion of u-Gov's application services. Also, as one of UT applied policy subject, I distinguished and analyzed the differences between e-Gov and u-Gov and, finally, suggested u-Gov's reform in order to surpass e-Gov's limitation and amelioration for possible problems during prototype materialization.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8A
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• pp.683-690
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• 2011

The conventional sensor tag data filtering algorithm uses time window based data filtering for each tag data. However, this approach shows many performance problems such as low error and event detection rate and larger storage size requirement. In this paper, we propose a collaborative sensor tag data filtering algorithm to improve sensor data processing performance. simulation study shows that the proposed sensor tag filtering algorithm outperforms the conventional filtering algorithm in terms of the processing time, the size of required data storage memory and accuracy of error and event detection rate.