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of the laser on the radiation characteristics
of the collision between high-energy electrons and laser pulses, a compactly
focused circularly polarized laser and single electron collision model was
established based on the Lorentz equation and the electron radiation equation.
The motion trajectory of electrons in Cartesian coordinate system is obtained
by numerical calculation using MATLAB. Based on the results of simulation
calculation, the relationship between the waist radius of tightly focused
circularly polarized laser pulse and the peak radiation power between electrons
is deeply studied. The results show that when the beam waist radius is small,
the peak radiation power increases with the increase of the beam waist radius,
and reaches the maximum peak radiation power atb0=
1.7λ0
. Then, the increase of the
beam waist radius will cause the slow decrease of the peak radiation power. In
addition, an optimal observation θ angle range[144°，151.5°] is found, and high radiation power can be
observed in this observation range, and the collision between electrons and
circularly polarized laser pulses can generate ultrashort attosecond pulses.
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Acne is a chronic inflammation of the skin veins of Propionibacterium, which endangers human health. Although there are acne identification methods on the market, their instruments are large and expensive, and there is currently no civilian-level acne identification system in use. This paper proposes a facial acne recognition scheme based on multispectral imaging technology, that is, using multispectral camera equipment to collect multispectral image information for normal and acne skin of different severity on the face, multispectral image analysis of the collected information by image processing method, and obtain spectral information through spectral inversion algorithm. The reflectance lines of normal and acne of different severities are then compared with the trend of the lines detected by the high-precision spectrometer under the same experimental conditions. Finally, a three-degree and four-level classification model of facial acne in the support vector machine was established with an accuracy rate of 90%, which verified the feasibility of non-invasive identification and classification of facial acne based on multispectral imaging technology.
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