Download Computer-Enhanced Analytical Spectroscopy by Carla M. Wong, Hal R. Brand (auth.), Henk L. C. Meuzelaar, PDF

By Carla M. Wong, Hal R. Brand (auth.), Henk L. C. Meuzelaar, Thomas L. Isenhour (eds.)

June 1986 introduced jointly a number of the world's leaders in laptop­ stronger analytical spectroscopy at Snowbird, Utah, for what the attendees made up our minds to name "The First Hidden top Symposium." With the striking advances in either laptop and software program, it really is attention-grabbing to watch that, whereas many computational features of spectroscopic research became regimen, the various extra basic difficulties stay unsolved. the gang that assembled integrated a lot of those that began attempting to interpret chemical spectroscopy while desktops have been ponderous, gradual, and never very obtainable, in addition to beginners who by no means knew the day that spectrometers have been introduced with no connected desktops. The synergism used to be very good. Many new principles, in addition to this quantity, resulted from interactions one of the individuals. the belief was once that development will be made on extra fundamen­ tal difficulties now that undefined, software program, and arithmetic have been coming jointly on a extra subtle point. the sensation used to be that the extent of class is now enough and that it's only a question of time ahead of automatic spectral interpretation surpasses all however the such a lot complicated human experts.

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C. M. Wong, R. W. Crawford, J. C. Kunz and T. P. Kehler, "Application of Artificial Intelligence to Triple-Quadrupole Mass Spectrometry," IEEE Trans. Nucl. Sci. NS-31 (I), 804-810 (1984). 6. C. M. Wong, R. W. Crawford, S. M. Lanning, and H. R. Brand, "Artificial Intelligence for Optimization of Real-Time Data from Pyrolysis Experiments," 32nd Annual Conference on Mass Spectrometry and Allied Topics, May 27-June I, 1984, San Antonio, Texas, pp. 372373. 7. C. M. Wong, S. M. Lanning, H. R. Brand and R.

It can be seen that a few features become somewhat better resolved than in the original spectrum. On strong deconvolution (y' = 13 cm - 1), several other bands become resolved; however, the features around 1775 cm- 1 show evidence of side lobes; see Fig. C. The number of bands contributing to the spectrum in this region (N = 17) and their center wavenumbers were estimated from this spectrum, and used to fit the mildly deconvolved spectrum shown in Fig. B. The results of curvefitting this spectrum are shown in Fig.

9) SIBARE measures how closely the areas of bands calculated by the fitting program, A~alc, match the areas of the bands used to synthesize the original (undeconvolved) spectrum, A itrue • For real spectra, the true band areas are unknown. We therefore also studied whether the standard deviation between the original and synthesized spectrum could be used to determine the value of y' needed for optimum quantitative accuracy. 5cm-1 and Yi=30cm- 1 for all bands. 2. For spectra deconvolved with a small y', the quantitative data are very poor (as shown, for example, in Fig.

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