skip to main content
10.1145/3358331.3358346acmotherconferencesArticle/Chapter ViewAbstractPublication PagesaiamConference Proceedingsconference-collections
research-article

Research of Drug Types Based on Raman Spectroscopy and PCA-KNN Algorithm

Published: 17 October 2019 Publication History

Abstract

As the number of synthetic drug abusers in China rising, problems and phenomena were encountered in practical use. A rapid and convenient method for the identification of methcathinone and ephedrine was needed. In this paper, Ion mobility spectrometry (IMS) and Raman spectroscopy were used in combination to characterize methcathinone and ephedrine from different sources. We use spectral data fusion combined with Principal Components Analysis (PCA) and K-Nearest Neighbors (KNN) algorithm to identify the two types of drugs. The experimental data show that the fusion data compared to the single spectral data were used to identify and effectively improve the recognition rate and accuracy for the identification of drugs. The results from this study demonstrated that the Raman-IMS combined with PCA-KNN model can used as a safe, rapid and reliable analysis method for identification of drugs.

References

[1]
C.Y. Li, Y. Wang, W.C. Zhao (2014). "The Harm and Determination of New Designer Methcathinone Anologs". Chinese Journal of Forensic Sciences.
[2]
Y. Chang, L.S. Gao (2011). "Summary of analytical methods of methcathinone". Forensic Science & Technology.
[3]
G.A. Elceman, Z. Karpas (1994). "Ion mobility spectrometry". CRC Press.
[4]
R.G. Ewing, D.A. Atkinson(2001). "A critical review of ion mobility spectsometry for the detection of explosives and explosive related compound". Talanta, 54, 515--29.
[5]
G.A. Harris, M. Kwasnik, F.M. Fernandez (2011). "Direct Analysis in Real Time Coupled to Multiplexed Drift Tube Ion Mobility Spectrometry for Detecting Toxic Chemicals". Anal Che, 83(6), 1908--15.
[6]
M.A. Makinen, O.A. Anttalainen, M.E. Sillanpaa (2010). "Ion Mobility Spectrometry and Its Applications in Detection of Chemical Warfare Agents". Anal Chem, 82(23), 9594--600.
[7]
S. Chen (2011). "The research of background subtraction algorithm of Raman spectrum and it application". Central South University.
[8]
A. Biancolillo, R. Bucci, A.L. Magri, et al (2014). "Data-fusion for multiplatform characterization of an Italian craft beer aimed at its authentication". Anal Chim Acta, 820, 23--31.
[9]
E. Borras, J. Ferre, R. Boque, et al (2015). "Data fusion methodologies for food and beverage authentication and quality assessment - a review". Anal Chim Acta, 891, 1--14.
[10]
J. Tan, R. Li, Z.T. Jiang (2015). "Chemometric classification of Chinese lager beers according to manufacturer based on data fusion of fluorescence, UV and visible spectroscopies". Food Chem, 184, 30--6.
[11]
B.H. Clowers, W.F. Siems, H.H. Hill, et al (2006). "Hadamard transform ion mobility spectrometry". Anal Chem, 78(1), 44--51.
[12]
J. Wang, F., Y. Jing, U., X. Sun, L (2012). "Rapid Analysis of Common Illicit Drugs and the Added Ingredients by Raman Spectroscopy". Journal of Light Scattering. 24(3), 312--5.
[13]
Lucien Birgé, Massart P (1997). From Model Selection to Adaptive Estimation[M]// Festschrift for Lucien Le Cam. Springer New York.
[14]
D. Groth, S. Hartmann, S. Klie (2013). "Principal components analysis". Computational Toxicology, 930, 527--47.
[15]
G.D. Guo, H. Wang, B. David, et al (2003). "KNN Model-Based Approach in Classification". Lecture Notes in Computer Science, 2888, 986--96.
[16]
J. Zavrel, W. Daelemans (1997). "Memory-based learning". The Meeting, 436--43.
[17]
P.Y. Xu, W.F. Su, A.G. Zhong (2014). "Density Functional Analysis and Spectral Properties Identification of Methcathinone". Contemporary Chemical Industry.
[18]
J. Zhao, Y. Peng, C.Y. Xu (2001). "Vibrational Study of Ephedrinum by Micro Raman Spectroscopy". Chinese Journal of Light Scattering.
[19]
J.H. Tan (2010). Research of ion mobility spectrometer based on positive Pulse corona discharge ion source. Tianjin University.

Index Terms

  1. Research of Drug Types Based on Raman Spectroscopy and PCA-KNN Algorithm

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    AIAM 2019: Proceedings of the 2019 International Conference on Artificial Intelligence and Advanced Manufacturing
    October 2019
    418 pages
    ISBN:9781450372022
    DOI:10.1145/3358331
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 17 October 2019

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Data fusion
    2. Drug control
    3. Fingerprinting
    4. Ion mobility spectrometry
    5. Principal component analysis
    6. Raman spectroscopy

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    AIAM 2019

    Acceptance Rates

    Overall Acceptance Rate 100 of 285 submissions, 35%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 103
      Total Downloads
    • Downloads (Last 12 months)19
    • Downloads (Last 6 weeks)5
    Reflects downloads up to 16 Feb 2025

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media