On-site determination of heroin by portable near-infrared spectrometer

Chen, Yuemeng; Liu, Shan; Yang, Yu; Qian, Zhenhua; Wang, Binye; An, Chenyunyi; Liu, Cuimei; Min, Shungeng

doi:10.1080/00450618.2019.1653370

Cited by 10 publications

(8 citation statements)

References 18 publications

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“…The peaks from 960 to 980 nm and 1400-1420 nm are the first and second overtone of O-H, respectively; peaks in the range of 1490-1600 nm are attributed to the first overtone of N-H. In the literature, 5 results showed that the variables located in the ranges of 1100-1250 nm and 1350-1600 nm had a great influence on heroin.…”

Section: Resultsmentioning

confidence: 92%

“…LDA determines a vector ω such that ω t S B ω is maximized while ω t S W ω is minimized. This double objective is realized by the vector ω opt that maximizes the criterion: (5) It can be proved that the solution ω opt is the eigen vector associated to the sole eigen value of S W -1…”

Section: Theory Of Linear Discriminant Analysismentioning

confidence: 99%

“…Extreme learning machine (ELM) put forward by Huang 4 has been widely used in many areas, such as classification, 5 regression, 6 feature selection 7 and so on. Multi-layer extreme learning machine (ML-ELM) is one of the unsupervised learning methods using both deep learning and extreme learning machine.…”

Section: Introductionmentioning

confidence: 99%

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Rapid Recognition of Different Sources of Heroin Drugs by Using a Hand-Held Near-Infrared Spectrometer Based on a Multi-Layer Extreme Learning Machine Algorithm

Zhang¹,

Chunming²,

Chengyun³

et al. 2023

J. Braz. Chem. Soc.

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Rapid recognition of the sources of drugs can provide some valuable clues and the basis for determining the nature of the case. A novel recognition method was put forward to identify the sources of heroin drugs rapidly and non-destructively by using a hand-held near infrared (NIR) spectrometer and a multi-layer-extreme learning machine (ML-ELM) algorithm. In contrast to traditional linear discriminant analysis (LDA), support vector machine (SVM) and extreme learning machine (ELM) algorithms, the accuracy, sensitivity and specificity were the highest for the proposed ML-ELM algorithm. The prediction accuracy of the ML-ELM algorithm was 25.33, 20.00, 17.33% higher than that of LDA, SVM and ELM algorithm, respectively, for 4 cases. The ML-ELM models for recognizing the different sources of heroin drugs had the best generalization ability and prediction results. The experimental results indicated that the combination of the hand‑held NIR technology and ML-ELM algorithm can recognize the different sources of heroin drugs rapidly, accurately, and non-destructively on the spot.

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Section: Resultsmentioning

confidence: 92%

Section: Theory Of Linear Discriminant Analysismentioning

confidence: 99%

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Rapid Recognition of Different Sources of Heroin Drugs by Using a Hand-Held Near-Infrared Spectrometer Based on a Multi-Layer Extreme Learning Machine Algorithm

Zhang¹,

Chunming²,

Chengyun³

et al. 2023

J. Braz. Chem. Soc.

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“…Portable NIR spectroscopy offers significant potential for detecting illegal drugs and euphoriants (see Section 3.1.1). Alongside the successes reported in a laboratory setting, studies on establishing a method directly applicable on‐site are currently being performed [91–93] . Recent feasibility studies presenting the capacity of portable NIR spectrometers to perform accurate on‐site determination of heroin [92] and cocaine [93] should be noted.…”

Section: Miniaturized Nir Spectroscopy In Practical Applicationsmentioning

confidence: 99%

“…Alongside the successes reported in a laboratory setting, studies on establishing a method directly applicable on‐site are currently being performed [91–93] . Recent feasibility studies presenting the capacity of portable NIR spectrometers to perform accurate on‐site determination of heroin [92] and cocaine [93] should be noted. In two other recent investigations, a MicroNIR spectrometer was successfully used to detect amphetamine [94] and cocaine [95] in human oral liquids.…”

Section: Miniaturized Nir Spectroscopy In Practical Applicationsmentioning

confidence: 99%

Principles and Applications of Miniaturized Near‐Infrared (NIR) Spectrometers

Beć

Grabska

Huck

2020

Chemistry A European J

227

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This review article focuses on the principles and applications of miniaturized near‐infrared (NIR) spectrometers. This technology and its applicability has advanced considerably over the last few years and revolutionized several fields of application. What is particularly remarkable is that the applications have a distinctly diverse nature, ranging from agriculture and the food sector, through to materials science, industry and environmental studies. Unlike a rather uniform design of a mature benchtop FTNIR spectrometer, miniaturized instruments employ diverse technological solutions, which have an impact on their operational characteristics. Continuous progress leads to new instruments appearing on the market. The current focus in analytical NIR spectroscopy is on the evaluation of the devices and associated methods, and to systematic characterization of their performance profiles.

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Recent Chemometric Opportunities in Criminalistics

Thanni¹,

Sah²,

Harrington³

2021

Encyclopedia of Analytical Chemistry

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Recently, the growing applicability of chemometrics in various areas of civil and criminal investigations has been instrumental in resolving complex cases. As criminals become more inventive and measurement methods become more prevalent with onsite analysis and more sophisticated with increases in resolution and sensitivity, forensic analysts should be equipped with tools for advancing their laboratory analysis and investigations. The traditional mode of data analysis in criminalistics will not suffice for complex crime lab investigations, hence the need for the understanding and application of the statistical and chemometric tools is indispensable. Accurate interpretation of forensic evidence is critical for achieving justice. The use of chemometrics helps the analyst from designing effective and efficient experiments to the presentation of compelling evidence to the courts. This article highlights the most recent application of chemometrics in different forensic science areas and shows how pivotal statistical tools are to answering consequential questions in criminal investigations.

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On-site determination of heroin by portable near-infrared spectrometer

Cited by 10 publications

References 18 publications

Rapid Recognition of Different Sources of Heroin Drugs by Using a Hand-Held Near-Infrared Spectrometer Based on a Multi-Layer Extreme Learning Machine Algorithm

Rapid Recognition of Different Sources of Heroin Drugs by Using a Hand-Held Near-Infrared Spectrometer Based on a Multi-Layer Extreme Learning Machine Algorithm

Principles and Applications of Miniaturized Near‐Infrared (NIR) Spectrometers

Recent Chemometric Opportunities in Criminalistics

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