Harmonizing a chemometric procedure for the classification of illicit heroin using manufacturing impurities: preliminary investigation of heroin simulated links

Autor:	Kar Weng Chan, Richard C.S. Wong, Guan Huat Tan
Rok vydání:	2013
Předmět:	Normalization (statistics) Illicit heroin Computer science Sample classification Principal component analysis Two sample Data mining Pretreatment method Cluster analysis computer.software_genre computer Pathology and Forensic Medicine Hierarchical clustering
Zdroj:	Australian Journal of Forensic Sciences. 45:153-163
ISSN:	1834-562X 0045-0618
DOI:	10.1080/00450618.2012.721806
Popis:	This paper describes the steps involved in harmonizing a statistical method for the classification of illicit heroin using manufacturing impurity data. Sixteen linked samples were prepared from each of the five unrelated heroin seizures. Five links, totaling 80 samples were subjected to two sample weight approaches for liquid–liquid extraction. A wide range of intra-batch variations were observed in the dataset and this was probably due to the poor extraction efficiency and weight differences. Notwithstanding this, this paper aims to find the best clustering technique (pretreatment and clustering tool) that is able to minimize the intra-batch variation without undermining the inter-batch variation for sample classification. Three pretreatment methods were first evaluated by principle component analysis (PCA) and normalization coupled with standardization was found to be able to show promising results. Subsequently, hierarchical cluster analysis (HCA) was chosen to evaluate the pretreated data as this tech...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8b4d34057e4828376596da611e82d725 https://doi.org/10.1080/00450618.2012.721806 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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