Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
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Development of a New Personal Magnetic Field Exposure Estimation Method for Use in Epidemiological EMF Surveys among Children under 17 Years of Age

  • Yang, Kwang-Ho (Electrical Environment Research Center, Advanced Power Grid Research Division, Korea Electrotechnology Research Institute (KERI)) ;
  • Ju, Mun-No (Advanced Power Grid Research Division, KERI) ;
  • Myung, Sung-Ho (Advanced Power Grid Research Division, KERI) ;
  • Shin, Koo-Yong (Transmission & Distribution Lab., Korea Electric Power Research Institute (KEPRI), KEPCO) ;
  • Hwang, Gi-Hyun (Dept. of Computer Engineering, Dongseo University) ;
  • Park, June-Ho (School of Electrical and Electronic Engineering, Pusan National University)
  • Received : 2010.05.28
  • Accepted : 2011.11.30
  • Published : 2012.05.01
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Abstract

A number of scientific researches are currently being conducted on the potential health hazards of power frequency electric and magnetic field (EMF). There exists a non-objective and psychological belief that they are harmful, although no scientific and objective proof of such exists. This possible health risk from ELF magnetic field (MF) exposure, especially for children under 17 years of age, is currently one of Korea's most highly contested social issues. Therefore, to assess the magnetic field exposure levels of those children in their general living environments, the personal MF exposure levels of 436 subjects were measured for about 6 years using government funding. Using the measured database, estimation formulas were developed to predict personal MF exposure levels. These formulas can serve as valuable tools in estimating 24-hour personal MF exposure levels without directly measuring the exposure. Three types of estimation formulas were developed by applying evolutionary computation methods such as genetic algorithm (GA) and genetic programming (GP). After tuning the database, the final three formulas with the smallest estimation error were selected, where the target estimation error was approximately 0.03 ${\mu}T$. The seven parameters of each of these three formulas are gender (G), age (A), house type (H), house size (HS), distance between the subject's residence and a power line (RD), power line voltage class (KV), and the usage conditions of electric appliances (RULE).

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References

  1. NRPB, National Radiological Protection Board, ELE Electromagnetic Fields and the Risk of Cancer, Volume 12, pp. 12-35, 2001
  2. Wertheimer N., Leeper E., 'Electrical wiring configurations and childhood cancer', Am J Epidemiology, 109, pp.273-284, 1979 https://doi.org/10.1093/oxfordjournals.aje.a112681
  3. ICNIRP, International Commission on NON-Ionizing Fadiation Protection Guidelines for Limiting Exposure to Time Varying Electric, Magnetic and Electromagnetic Fields (up to 300GHz), Health Phys. 74, pp. 494-522, 1998
  4. Chung-Yi Li, Gabor Mezei, Fung-Chang Sung, Michael Silva, Pei-Chen Lee, Pei-Chen and Li-Mei Chen, "Assessment of Non-Response Bias in a Survey of Residential Magnetic Field Exposure in Taiwan", Bioelectromagnetics, 28, pp. 340-348, 2007 https://doi.org/10.1002/bem.20306
  5. S. Tofani and G. D'Amore, "Extremely-Low- Frequency and Very-Low-Frequency Magnetic Fields Emitted by Video Display Units", Bioelectromagnetics, 12, pp. 35-45, 1991 https://doi.org/10.1002/bem.2250120106
  6. Yoshika Kurokawa, Hirshi Nitta, Hideki Lmai, and Michinori Kabuto, "Acute Exposure to 50 Hz Magnetic Fields With Harmonics and Transient Components: Lack of Effects on Nighttime Hormonal Secretion in Men", Bioelectromagnetics, 24, pp. 12- 20, 2003 https://doi.org/10.1002/bem.10084
  7. Cindy Sage, Olle Johansson, and S. Amy Sage, "Personal Digital Assistant (PDA) Cell Phone Units Produce Elevated Extremely-Low Frequency Electromagnetic Field Emissions", Bioelectromagnetics, 28, pp. 386-392, 2007 https://doi.org/10.1002/bem.20315
  8. Aksel Straume, Ander Johnsson, and Gunnhild Oftedal, "ELF-Magnetic Flux Densities Measured in a City Environment in Summer and Winter", Bioelectromagnetics, 29, pp. 20-28, 2008 https://doi.org/10.1002/bem.20357
  9. K. llonen, A. Markkanen, G. Mezei, and Jukka Juutilainen, "Indoor Transformer Stations as Predictors of Residential ELF Magnetic Field Exposure", Bioelectromagnetics, 29, pp. 213-218, 2008 https://doi.org/10.1002/bem.20385
  10. Jorgen H. Skotte and Henrik I. Hjollund, "Exposure of Welders and Other Metal Workers to ELF Magnetic Fields", Bioelectromagnetics, 18, pp. 470-477, 1997 https://doi.org/10.1002/(SICI)1521-186X(1997)18:7<470::AID-BEM2>3.0.CO;2-#
  11. Jun Zhang, Indira Nair, and Jack Sahl, "Effects Function Analysis of ELF Magnetic Field Exposure in the Electric Utility Work Environment", Bioelectromagnetics, 18, pp. 365-375, 1997 https://doi.org/10.1002/(SICI)1521-186X(1997)18:5<365::AID-BEM4>3.0.CO;2-0
  12. Jack D. Sahl, Michael A. Kelsh, Robert W. Smith, and Deborah A. Aseltine, "Exposure to 60 Hz Magnetic Fields in the Electric Utility Work Environment", Bioelectromagnetics, 15, pp. 21-32, 1994 https://doi.org/10.1002/bem.2250150107
  13. L. Davis. Ed, "A Handbook of Genetic algorithms", New York: Van Nostrand Reinhold, 1991.
  14. M. Srinivas and L. M. Patnaik, "Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms", IEEE Trans. on Systems, Man and Cybernetics, Vol. 24, No.4, pp. 656-667, April, 1994 https://doi.org/10.1109/21.286385
  15. W. M. Spears, "Evolutionary Programming IV", The MIT Press, 1995
  16. Vittorio Maniezzo, "Genetic Evaluation of the Topology and Weight Distribution of Neural Networks", IEEE Trans. on Neural Networks, Vol. 5, No. 1, pp. 39-53, Jan, 1994 https://doi.org/10.1109/72.265959
  17. A. Varsek, T. Urbancic, and B. Filipic, "Genetic Algorithm in Controller Design and Tuning", IEEE Trans. on Systems, Man, and Cybernetics, Vol. 23, No. 5, pp. 1330-1339, Sept./Oct. 1993 https://doi.org/10.1109/21.260663
  18. Fogel, D. B., Evolutionary Computation: Towards New Philosophy of Machine Intelligence. IEEE Press, Piscataway, NJ, 1995.
  19. Goldberg, D. E., Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley Publishing Company, INC., 1989.
  20. Fogel, D. B., Fogel, L. J., Atmas, J. W., Meta-Evolutionary Programming. Proceedings 2sth Asilomar Conference on Systems, Signals and Computers, 540-545, 1991.
  21. Renders, J. M., Flasse, S. P., "Hybrid Methods Using Genetic Algorithms for Global Optimization", IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, 26 (2)., 1996.
  22. M. Ju, K. Yang and S. Myung, "Occupational and Residential Exposures to ELF Magnetic Fields over a 24-h Period Among a Sample of Urban Populations in Korea", IEEE Trans. Electromagnetic Compatibility, Vol. 52, No. 4, pp.843-848, Nov. 2010 https://doi.org/10.1109/TEMC.2010.2044884

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