DOI QR코드

DOI QR Code

Suitable Health Pattern Type Mapping Techniques in Body Mass Index

  • Shin, Yoon-Hwan (Technology Commercialization Advisory Committee member for Technical Support Division of KIAT, Korea Institute for Advancement of Technology)
  • Received : 2016.01.20
  • Accepted : 2016.02.19
  • Published : 2016.02.29

Abstract

In this paper, we propose a technique that can be mapped to the most appropriate type of health patterns, depending on the health status of health promotion measures to establish a body mass index (BMI). When used as a mapping scheme proposed in this paper it is possible to contribute to effective healthcare and health promotion. BMI is widely used as a simple way to assess obesity because body fat increases the status and relevance. Despite normal weight determined by this and because of the social atmosphere has increased prefer the skinny tend to try to excessive weight loss. Since health can affect the health maintenance and promotion of the rest of your life, depending on whether and how much weight perception and health can be considered as very important. Therefore, this paper identifies the differences in perception and in this respect for the body mass index (BMI). And physical, mental and map the appropriate type of pattern in the relationship between body mass index (BMI) in order to facilitate the social and health conditions. Proposal to give such a mapping technique provides the opportunity to increase the efficiency of health care and health promotion.

Keywords

References

  1. Hyen Suk Cho, "The Relationship among BMI, Perceived Weight and Health Status" Journal of Korean J Rehabil Nurs, Vol.10, No.2, pp.99-107, December 2007.
  2. Seon Ah Kim, Jae Kyung Choi, Chang Kyu Park, Kueng Mi Choi, Be Long Cho, "Body Mass Index and Body Shape", The Korean Journal of Obesity, Vol.22, No.3, pp.155-160, September 2013. https://doi.org/10.7570/kjo.2013.22.3.155
  3. Su Jeung Yu, Kyung-Sook Lee, Joo Hyun Kim, Kyung Choon Lim, Jin Sook Park, "Health Promotion Behavior according to Body Mass Index and Self-Perception of Body Weight in Female Nursing Students", Journal of Korean Biological Nursing Science. Vol.16, No1, pp.60-68, February 2014. https://doi.org/10.7586/jkbns.2014.16.1.60
  4. Kyung Woo Park, "Sign Language Shape Recognition Using SOFM Neural Network," Journal of Chosun Natural Science, Vol.3, No.1, 38-42, January 2010.
  5. Yoon Hwan Shin, "Pattern Analysis of Biometric Data for the Needle Points Selection in Big Data Environments", PhD thesis, Chungbuk National University, August 2014.
  6. Hwang Ho Kim, Jin Young Choi, "An Efficient Search Algorithm for Flexible Manufacturing Systems (FMS) Scheduling Problem with Finite Capacity", Journal of the Korean Institute of Industrial Engineers, Vol.22, No.1, pp.10-16, January 2009.
  7. Min-Ho Lee, Won-Goo Lee, Yun-Soo Choi, Hwa-Mook Yoon, Sa-Kwang Song, Hanmin Jung, "Schema Mapping and Data Conversion System for Integrating Article Metadata", Journal of The Korea Society of Computer and Information, Vol.17, No.10, pp.129-136, October 2012. https://doi.org/10.9708/jksci/2012.17.10.129
  8. Seung-Hwan Ju, Hee-Suk Seo, "A study on User Authentication Technology of Numeric based Pattern Password", Journal of The Korea Society of Computer and Information, Vol.17, No.9, pp.65-73, August 2012. https://doi.org/10.9708/jksci/2012.17.9.065
  9. Jin-woo Park, "Performance Improvements of Performance Improvements of WiBro System Using the 64QAM SOFM Prefiltering", The journal of the Korea Institute of Maritime Information & Communication Sciences, Vol.14, No.5, pp.1125-1132, March 2010. https://doi.org/10.6109/jkiice.2010.14.5.1125