Vaccine multispectral rapid detection method based on quantum Fourier transform

A technology of Fourier transform and detection method, applied in the fields of quantum computing and vaccine activity detection, can solve the problems of difficult data processing and low light intensity requirements, and achieve the effect of reducing limitations, shortening detection period, and reliable detection data.

Pending Publication Date: 2022-01-07
CHINA THREE GORGES UNIV
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  • Description
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Problems solved by technology

The invention uses quantum Fourier transform to deal with the data processing problems brought about by large-scale spectral detection, has low requirements on light inte

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  • Vaccine multispectral rapid detection method based on quantum Fourier transform
  • Vaccine multispectral rapid detection method based on quantum Fourier transform
  • Vaccine multispectral rapid detection method based on quantum Fourier transform

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Embodiment Construction

[0049] Below in conjunction with specific embodiment, the present invention is described in further detail:

[0050] figure 1 It is a system structure diagram of an embodiment of the present invention, a vaccine multispectral rapid detection method based on quantum Fourier transform, the method is based on a vaccine multispectral rapid detection system, and the system includes a vaccine sample 100, a multispectral acquisition module 200, and a vaccine multispectral Database 300, quantum Fourier transform module 400, neural network learning module 500, vaccine multispectral feature matrix 600 and vaccine multispectral analysis result output module 700;

[0051] The multi-spectral acquisition module 200 irradiates the vaccine sample 100 with multi-light waves without interference to collect multi-spectrum under the condition of low light control, and applies a preprocessing algorithm to filter, denoise, and amplify the multi-spectral image. The vaccine multi-spectral database 30...

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Abstract

The invention relates to a vaccine multispectral rapid detection method based on quantum Fourier transform, which is based on a vaccine multispectral rapid detection system and comprises the following steps that 1, a multispectral acquisition module acquires multispectral data of a vaccine sample; 2, the multispectral acquisition module inputs the data into a vaccine multispectral database; 3, a quantum Fourier transform module performs data transformation on the vaccine multispectral database; 4, a neural network learning module learns and extracts the single-type spectral features of the vaccine sample; 5, multispectral cross learning is conducted on the multispectral characteristic matrix of the vaccine sample by a neural network learning module; and 6, a vaccine detection result is outputted. The method can be applied to large-scale, accurate, rapid and lossless vaccine detection.

Description

technical field [0001] The invention relates to the fields of vaccine activity detection and quantum computing, in particular to a vaccine multispectral rapid detection method based on quantum Fourier transform. Background technique [0002] Vaccines refer to biological products made from various pathogenic microorganisms for vaccination. Since the birth of vaccines, they have played a pivotal role in the human struggle against viruses, reducing a large number of deaths. Without vaccines, it will be difficult for humans to defeat many viruses such as smallpox, hepatitis, rabies, diphtheria, tetanus, whooping cough, measles and the new crown. Commonly used vaccines include live attenuated vaccines, inactivated vaccines, toxoid vaccines, subunit vaccines and polypeptide vaccines, vector vaccines, nucleic acid vaccines, and edible vaccines. The development and production of vaccines is a long, complex and costly process. The storage temperature of normal vaccines is 2-8 degr...

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Application Information

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IPC IPC(8): G01N21/25G01N21/31G01N21/33G01N21/64G01N21/65G01N21/73G01N24/08G06N3/04G06N3/08
CPCG01N21/25G01N21/3103G01N21/33G01N21/64G01N21/65G01N21/73G01N24/088G06N3/04G06N3/08
Inventor 蔡政英左紫怡蔡文娟陈滢潞
Owner CHINA THREE GORGES UNIV
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