Modeling of laser-induced breakdown spectroscopic data analysis by an automatic classifier
Tóm tắt
Laser-induced breakdown spectroscopy (LIBS) is a multi-elemental and real-time analytical technique with simultaneous detection of all the elements in any type of sample matrix including solid, liquid, gas, and aerosol. LIBS produces vast amount of data which contains information on elemental composition of the material among others. Classification and discrimination of spectra produced during the LIBS process are crucial to analyze the elements for both qualitative and quantitative analysis. This work reports the design and modeling of optimal classifier for LIBS data classification and discrimination using the apparatus of statistical theory of detection. We analyzed the noise sources associated during the LIBS process and created a linear model of an echelle spectrograph system. We validated our model based on assumptions through statistical analysis of “dark signal” and laser-induced breakdown spectra from the database of National Institute of Science and Technology. The results obtained from our model suggested that the quadratic classifier provides optimal performance if the spectroscopy signal and noise can be considered Gaussian.
Tài liệu tham khảo
citation_title=Principles of Instrumental Analysis; citation_publication_date=2007; citation_id=CR1; citation_author=S Crouch; citation_author=DA Skoog; citation_publisher=Thomson Brooks/Cole
Götz, M., Kononets, M., Bodenstein, C., Riedel, M., Book, M., Palsson, O.P.: Automatic water mixing event identification in the Koljö Fjord observatory data. Int J Data Sci Anal (2018).
https://doi.org/10.1007/s4106
citation_journal_title=Int. J. Data Sci. Anal.; citation_title=Data science: the impact of statistics; citation_author=C Weihs, K Ickstadt; citation_volume=6; citation_publication_date=2018; citation_pages=189-194; citation_doi=10.1007/s41060-018-0102-5; citation_id=CR3
citation_journal_title=NMR Biomed.; citation_title=Near-optimal region selection for feature space reduction: novel preprocessing methods for classifying MR spectra; citation_author=AE Nikulin, B Dolenko, T Bezabeh, RL Somorjai; citation_volume=11; citation_publication_date=1998; citation_pages=209-216; citation_doi=10.1002/(SICI)1099-1492(199806/08)11:4/5<209::AID-NBM510>3.0.CO;2-5; citation_id=CR4
citation_journal_title=Vib. Spectrosc.; citation_title=Classification of human gliomas by infrared imaging spectroscopy and chemometric image processing; citation_author=C Beleites, G Steiner, MG Sowa, R Baumgartner, S Sobottka, G Schackert, R Salzer; citation_volume=38; citation_publication_date=2005; citation_pages=143-149; citation_doi=10.1016/j.vibspec.2005.02.020; citation_id=CR5
citation_journal_title=Appl. Spectrosc.; citation_title=Raman spectroscopy and genetic algorithms for the classification of wood types; citation_author=BK Lavine, CE Davidson, AJ Moores, PR Griffiths; citation_volume=55; citation_publication_date=2001; citation_pages=960-966; citation_doi=10.1366/0003702011953108; citation_id=CR6
citation_journal_title=Appl. Opt.; citation_title=Laser-induced breakdown spectroscopy for the classification of unknown powders; citation_author=EG Snyder, CA Munson, JL Gottfried, FC Lucia, Gullett B Jr, A Miziolek; citation_volume=47; citation_publication_date=2008; citation_pages=G80-G87; citation_doi=10.1364/AO.47.000G80; citation_id=CR7
Sunku, S., Rao, E.N., Kumar, G.M., Tewari, S.P., Rao, S.V.: Discrimination methodologies using femtosecond LIBS and correlation techniques. Proc. SPIE (2013).
https://doi.org/10.1117/12.2015749
citation_journal_title=Trans. Mass-Data Anal. Images Signals; citation_title=Classification of LIBS protein spectra using multi-layer perceptrons; citation_author=T Vance, D Pokrajac, A Marcano, Y Markushin, S McDaniel, N Melikechi, A Lazarevic; citation_volume=2; citation_publication_date=2010; citation_pages=96-111; citation_id=CR9
Pokrajac, D., Vance, T., Lazarevic, A., Marcano, A., Markushin, Y., Melikechi, N., Reljin, N.: Performance of multilayer perceptrons for classification of LIBS protein spectra. In: Proceedings of 10th Symposium Neural Network Applications in Electrical Engineering (NEUREL), Belgrade, Serbia, pp. 171–174 (2010)
Vance, T., Reljin, N., Lazarevic, A., Pokrajac, D. Kecman, V., Melikechi, N., Marcano, A., Markushin, Y., McDaniel, S.: Classification of LIBS protein spectra using support vector machines and adaptive local hyperplanes. In: Proceedings of 2010 IEEE world congress on computational intelligence, Barcelona, Spain, pp. 1–7 (2010)
citation_journal_title=Vib. Spectrosc.; citation_title=The classification of Phyllanthus Niruri Linn. According to location by infrared spectroscopy; citation_author=S Dharmaraj, AS Jamaludin, HM Razak, R Valliappan, NA Ahman, GL Harn, Z Ismail; citation_volume=41; citation_publication_date=2006; citation_pages=68-72; citation_doi=10.1016/j.vibspec.2005.12.012; citation_id=CR12
Tripathi, M.: Echelle Spectrographs: A Flexible Tool for Spectroscopy: Raman and LIBS Spectroscopy. Andor Technology.
http://www.andor.com/pdfs/echelle_spectrograph.pdf
(2005). Accessed 06 July 2017
citation_title=Diffraction Grating Handbook; citation_publication_date=2005; citation_id=CR14; citation_author=C Palmer; citation_author=E Loewen; citation_publisher=Newport Corporation
citation_title=Diffraction Gratings and Applications; citation_publication_date=1997; citation_id=CR15; citation_author=E Loewen; citation_author=E Popov; citation_publisher=Marcel Dekker Inc.
citation_journal_title=SPIE Proc.; citation_title=Echelle efficiency and blaze characteristics; citation_author=M Bottema; citation_volume=240; citation_publication_date=1981; citation_pages=171-176; citation_doi=10.1117/12.965652; citation_id=CR16
citation_journal_title=IEEE Trans. Image Proc.; citation_title=CCD noise removal in digital images; citation_author=K Faraji, WJ MacLean; citation_volume=5; citation_publication_date=2006; citation_pages=2676-2685; citation_doi=10.1109/TIP.2006.877363; citation_id=CR17
CCD Image Sensor Noise Sources. Eastman Kodak Company application note MTD/PS-0233, Rochester.
https://www.uni-muenster.de/imperia/md/content/ziv/multimedia/downloads/kodak___noise_sources.pdf
(2001). Accessed 29 Jan 2019
citation_title=Digital Signal Processing: A Computer-Based Approach; citation_publication_date=2006; citation_id=CR19; citation_author=SK Mitra; citation_publisher=McGraw-Hill
citation_journal_title=Proc. Phys. Soc.; citation_title=Fluctuations of photon beams: the distribution of photo-electrons; citation_author=L Mandel; citation_volume=74; citation_publication_date=1959; citation_pages=233-243; citation_doi=10.1088/0370-1328/74/3/301; citation_id=CR20
citation_title=Probability: An Introduction; citation_publication_date=1986; citation_id=CR21; citation_author=G Grimmett; citation_author=D Welsh; citation_publisher=Oxford Science Publications
citation_title=Handbook of the Poisson Distribution; citation_publication_date=1967; citation_id=CR22; citation_author=FA Haight; citation_publisher=Wiley
citation_title=Fundamental of Digital Image Processing; citation_publication_date=1989; citation_id=CR23; citation_author=KA Jain; citation_publisher=Prentice-Hall
Tian, H.: Noise analysis in CMOS image sensors. Ph.D. dissertation, Stanford University, Stanford, CA (2000)
citation_title=Digital Signal Processing; citation_publication_date=1996; citation_id=CR25; citation_author=JG Proakis; citation_author=DG Manolakis; citation_publisher=Prentice-Hall
citation_journal_title=Proc. SPIE Solid State Sens. Arrays Dev. Appl. II; citation_title=Modeling and estimation of FPN components in CMOS image sensors; citation_author=A El Gamal, B Fowler, H Min, X Liu; citation_volume=3301; citation_publication_date=1998; citation_pages=168-177; citation_id=CR26
citation_title=Detection Estimation and Modulation Theory Part I; citation_publication_date=2013; citation_id=CR27; citation_author=HLV Trees; citation_author=KL Bell; citation_publisher=Wiley
citation_title=An Introduction to Support Vector Machines and Other Kernel-based Learning Methods; citation_publication_date=2000; citation_id=CR28; citation_author=N Cristianini; citation_author=J Shawe-Taylor; citation_publisher=Cambridge University Press
citation_title=Principal Component Analysis; citation_publication_date=2002; citation_id=CR29; citation_author=IT Jolliffe; citation_publisher=Springer
citation_title=A: First Course in Multivariate Statistics; citation_publication_date=1997; citation_id=CR30; citation_author=B Flury; citation_publisher=Springer
Andor
$$^{TM}$$
Technology: Mechelle User’s Guide. Andor Technology, Belfast (2008)
citation_title=Laser-Induced Breakdown Spectroscopy (LIBS) Fundamentals and Applications; citation_publication_date=2006; citation_id=CR32; citation_author=AW Miziolek; citation_author=V Palleschi; citation_author=I Schechater; citation_publisher=Cambridge University Press
citation_journal_title=J. Am. Stat. Assoc.; citation_title=The Kolmogorov–Smirnov test for goodness of fit; citation_author=FJ Massey; citation_volume=46; citation_publication_date=1951; citation_pages=68-78; citation_doi=10.1080/01621459.1951.10500769; citation_id=CR33
citation_journal_title=J. Am. Stat. Assoc.; citation_title=On the Kolmogorov–Smirnov test for normality with mean and variance unknown; citation_author=HW Lilliefors; citation_volume=62; citation_publication_date=1967; citation_pages=399-402; citation_doi=10.1080/01621459.1967.10482916; citation_id=CR34
citation_title=The Oxford Dictionary of Statistical Terms; citation_publication_date=2006; citation_id=CR35; citation_author=Y Dodge; citation_publisher=Oxford University Press
citation_title=Time Series Analysis: Forecasting and Control; citation_publication_date=1994; citation_id=CR36; citation_author=GEP Box; citation_author=GM Jenkins; citation_author=GC Reinsel; citation_publisher=Prentice Hall
https://www-s.nist.gov/srmors/viewTableH.cfm?tableid=90N
(2017). Accessed 06 June 2017
citation_journal_title=J. Stat. Model. Anal.; citation_title=Power comparisons of Shapiro–Walk, Kolmogorov–Smirnov, Lilliefors and Anderson–Darling tests; citation_author=M Razali, YN Wah; citation_volume=2; citation_publication_date=2011; citation_pages=21-33; citation_id=CR38
citation_journal_title=Appl. Spectrosc.; citation_title=Automatic classification of laser-induced breakdown spectroscopy (LIBS) data of protein biomarker solutions; citation_author=D Pokrajac, A Lazarevic, V Kecman, A Marcano, Y Markushin, T Vance, N Reljin, S McDaniel, N Melikechi; citation_volume=68; citation_publication_date=2014; citation_pages=1067-1075; citation_doi=10.1366/14-07488; citation_id=CR39
Pořízka, P., Klus, J., Mašek, J., Rajnoha, M., Prochazka, D., Modlitbová, P., Novotný, J., Burget, R., Novotný, K., Kaiser, J.: Multivariate classification of echellograms: a new perspective in laser-induced breakdown spectroscopy analysis. Sci. Rep. 7, 3160 (2017).
https://doi.org/10.1038/s41598-017-03426-0
Ali, A., Khan, M.Z., Rehan, I., Rehan, K., Muhammad, R.: Quantitative classification of quartz by laser induced breakdown spectroscopy in conjunction with discriminant function analysis. J. Spectrosc. 2016, 1835027 (2016).
https://doi.org/10.1155/2016/1835027
citation_journal_title=Chemom. Intell. Lab. Syst.; citation_title=Classification of steel samples by laser-induced breakdown spectroscopy and random forest; citation_author=T Zhang, D Xia, H Tang, X Yang, Y Li; citation_volume=157; citation_publication_date=2016; citation_pages=196-201; citation_doi=10.1016/j.chemolab.2016.07.001; citation_id=CR42
citation_journal_title=Anal. Lett.; citation_title=Classification of Chinese herbal medicine by laser-induced breakdown spectroscopy with principal component analysis and artificial neural network; citation_author=J Wang, X Liao, P Zheng, S Xue, R Peng; citation_volume=51; citation_publication_date=2018; citation_pages=575-586; citation_doi=10.1080/00032719.2017.1340949; citation_id=CR43
citation_journal_title=Appl. Spectrosc.; citation_title=Laser-induced breakdown spectroscopy detection and classification of biological aerosols; citation_author=JD Hybl, GA Lithgow, SG Buckley; citation_volume=57; citation_publication_date=2003; citation_pages=1207-1215; citation_doi=10.1366/000370203769699054; citation_id=CR44
citation_journal_title=Appl. Opt.; citation_title=Calibrating the ChemCam laser-induced breakdown spectroscopy instrument for carbonate minerals on Mars; citation_author=NL Lanza, RC Wiens, SM Clegg, AM Ollila, SD Humphries, HE Newsom, JE Barefield; citation_volume=49; citation_publication_date=2010; citation_pages=C211-C217; citation_doi=10.1364/AO.49.00C211; citation_id=CR45
citation_journal_title=Stat. Surv.; citation_title=A survey of cross-validation procedures for model selection; citation_author=S Arlot, A Celisse; citation_volume=4; citation_publication_date=2010; citation_pages=40-79; citation_doi=10.1214/09-SS054; citation_id=CR46
citation_title=Feature Selection for Knowledge Discovery and Data Mining; citation_publication_date=1998; citation_id=CR47; citation_author=H Liu; citation_author=H Motoda; citation_publisher=Kluwer
Bamgbade, A., Somorjai, R., Dolenko, B., Pranckeviciene, E., Nikulin, A., Baumgartner, R.: Evidence accumulation to identify discriminatory signatures in biomedical spectra. In: Proceedings of 10th conference on artificial intelligence in medicine, 23–27, pp. 463–467 (2005)
citation_journal_title=J. Appl. Prob.; citation_title=Two dependent Poisson processes whose sum is still a Poisson process; citation_author=J Jacod; citation_volume=12; citation_publication_date=1975; citation_pages=170-172; citation_doi=10.2307/3212423; citation_id=CR49
citation_journal_title=Proc. ICASSP-91; citation_title=Optimal detection of non-Gaussian random signals in Gaussian noise; citation_author=D Kletter, PM Schultheiss, H Messer; citation_volume=2; citation_publication_date=1991; citation_pages=1305-1308; citation_id=CR50
Nuttall, A.H.: Optimum detection of random signal in non-Gaussian noise for low input signal to noise ratio. Naval Undersea Warfare Center Division.
http://www.dtic.mil/dtic/tr/fulltext/u2/a422595.pdf
(2017). Accessed 6 July 2017
citation_title=Non-Gaussian Statistical Communication Theory; citation_publication_date=2012; citation_id=CR52; citation_author=D Middleton; citation_publisher=Wiley