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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
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2012
Volume: 7
Issue: 5
Language: English
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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