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We present in this paper a new method based on machine learning techniques using Python to determine a relationship between the electric field in free space, and the electric field wave in the vicinity of a cylinder bounding a series of successive layers made from different human tissues. The properties of each kind of tissue are consistent with the frequency of the applied wave. As a result, the values of the electric field are widely modified by the presence of the body, by many factors such as interference of the wave and its echo, superposition of waves, and absorption by material objects. The goal of our work is to estimate the value of the free electric field from the values of the same electric field in the matter and to determine the suitable area on the body to host the dosimeter to get better values of the electric field in a free space.

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Estimation and Characterization of the Exposition of Material Object in Terms of Electric Field

  • 会议论文

  • 发表日期：

    2025年

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  • Khalid El Yousfi,
  • Chakib Taybi,
  • Abdelhak Ziyyat,
  • Bachir Elmagroud

摘要

We present in this paper a new method based on machine learning techniques using Python to determine a relationship between the electric field in free space, and the electric field wave in the vicinity of a cylinder bounding a series of successive layers made from different human tissues. The properties of each kind of tissue are consistent with the frequency of the applied wave. As a result, the values of the electric field are widely modified by the presence of the body, by many factors such as interference of the wave and its echo, superposition of waves, and absorption by material objects. The goal of our work is to estimate the value of the free electric field from the values of the same electric field in the matter and to determine the suitable area on the body to host the dosimeter to get better values of the electric field in a free space.