2003
DOI: 10.1366/000370203322102960
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Spectral Code Index (SPECOIND): A General Infrared Spectral Database Search Method

Abstract: A new spectral code that can be used by Relational Database Management Systems (RDBMS) as an index for infrared (IR) spectra searches in Relational Database (RDB ) is presented and its suitability is evaluated. Spectral codes are constructed for all spectra in the database as the spectral indexes and three query strings are created with the same theory used for the creation of the index code for the query spectrum . Some effects of parameters used to create index strings and query strings are discussed. All sp… Show more

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Cited by 12 publications
(10 citation statements)
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“…In Figure b, when the three PCA spectra are compared with eight Raman spectra, the situation is much more complicated, and an algorithm approach is thus preferred. An algorithm-based comparison is to recognize a digital value to indicate the similarity or difference, among a suspected spectrum and the standard spectra, akin to an index . Fortunately, the correlation of PCA analysis can be used for this comparison and justification.…”
Section: Resultsmentioning
confidence: 99%
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“…In Figure b, when the three PCA spectra are compared with eight Raman spectra, the situation is much more complicated, and an algorithm approach is thus preferred. An algorithm-based comparison is to recognize a digital value to indicate the similarity or difference, among a suspected spectrum and the standard spectra, akin to an index . Fortunately, the correlation of PCA analysis can be used for this comparison and justification.…”
Section: Resultsmentioning
confidence: 99%
“…Taking the PCA spectrum of PC1 from the first round of PCA for example, we compare it with the eight standard spectra, in order to identify the type of plastic . To avoid the comparison bias and to increase the accuracy, we pretreat the spectrum, as discussed above.…”
Section: Resultsmentioning
confidence: 99%
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“…After the 1 st round of PCA, the PCA spectrum, such as of PC1, is combined with 10 standard spectra, in order to identify it, akin to indexing. 31 To avoid the comparison bias and to increase the accuracy, we pre-treat all the PCA spectra and Raman spectra, using techniques including cosmic ray removal, smoothening, baseline correction, interpolating to adjust the wavenumber ( x -axis) and normalising the intensity ( y -axis). Most of these pre-treatments can be conducted using either the operational software (WITec Project, such as cosmic ray removal) or Origin.…”
Section: Methodsmentioning
confidence: 99%
“…In general, there are mainly two kinds of SMA. The first kind matches spectra by the similarity of spectral peak information (SMA-P), [7][8][9] so peak detection is an essential step for subsequent analysis. The thresholds of signal-to-noise ratio, peak height, peak width and peak shape index are commonly used for peak detection.…”
Section: Introductionmentioning
confidence: 99%