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The most used algorithms for the identification of electron-ionization mass spectra are INCOS and probability based matching (PBM). For unknown spectra of high purity, approximately 75% of rank 1 answers are correct for both algorithms, matched against the National Institute of Standards and Technology 62,235 spectrum database. With matching criteria that(More)
The high success of the "uncertified" mass spectrometry spectral collection started in 1956 demonstrated qualitatively that a partial reference mass spectrum, even one measured routinely, can be of real value. Correct matchings were still possible despite reference errors, which almost never led to close matches that were incorrect. This study shows(More)
This paper presents the design and implementation of a neural fuzzy controller suitable for real-time control of an autonomous mobile robot. The neural fuzzy controller is developed based on the Generalized Dynamic Fuzzy Neural Networks (GDFNN) learning algorithm of Wu et al. (IEEE Transactions on Fuzzy System 9 (4), 2001, 578–594). Not only the parameters(More)
The simultaneous collection of multiple spectra using tandem (MS/MS) and multidimensional (MS/MS/MS) mass spectrometry from multiple precursors is demonstrated to yield correspondingly enhanced sensitivity. This approach utilizes Hadamard transform deconvolution and takes advantage of the multichannel dissociation capability of Fourier-transform mass(More)
Recent reports from the National Institute of Science and Technology (NIST) state that its large (53,994) collection of mass spectra is unique in "consisting almost entirely of complete spectra." Our study of the 1989 Registry of Mass Spectral Data of 139,859 different spectra shows that its 53,994 spectra containing the most peaks average 108 peaks per(More)
The computer-searchable data base of reference mass spectra described earlier has been increased in size by 76%, so that it now contains 139,859 different spectra of 118,144 different compounds. The average number of peaks per spectrum is 53. All spectra were examined for errors by the Probability Based Matching (PBM) and the Quality Index (QI) algorithms(More)
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