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Application of principal component analysis for identification of drugs packed in anthropomorphic phantom


Article Information

Title: Application of principal component analysis for identification of drugs packed in anthropomorphic phantom

Authors: Wei Li, Yu Zhong, Daoyang Yu, Dingjun Qu, Bai Sun, Minqiang Li, Jinhuai Liu

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2012

Volume: 7

Issue: 7

Language: English

Categories

Abstract

A method of feature extraction based on principal component analysis (PCA) to identify drugs packed in anthropomorphic phantom was proposed. An energy dispersive X-ray diffraction spectrometer was used to acquire the spectra of drugs and the other materials. Features of spectra were extracted by PCA which excels in analyzing high-dimensional data. Furthermore, the number of principal components selected as features was discussed. Combined with artificial neural network, a success rate of recognition between 93.3% and 100% was achieved. It indicates that this method is promising in detecting drug body packing.


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