Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Internet and Biometric Web Based Business Management Decision Support

Internet and Biometric Web Based Business Management Decision Support MICROBE MOOC material prepared under IO1/A5 Development of the MICROBE personalized MOOCs content and teaching materials Prepared by: A. Kaklauskas, A. Banaitis, I. Ubarte Vilnius Gediminas Technical University, Lithuania Project No: 2020-1-LT01-KA203-07810

INTERSPEECH 2006- ICSLP An Efficient Bispectrum Phase Entropy-based Algorithm for VAD

In this paper we propose a novel Voice Activity Detection (VAD) algorithm, based on the integrated bispectrum function (IBI), for improving Automated Speech Recognition (ASR) systems that work in noisy environments. In particular we use the combination of two features, IBI magnitude and IBI phase to formulate a robust and smoothed decision rule for speech/pause discrimination. The analysis performed on the new combined feature highlighted: i) the advantages of each individual feature, while compensating the drawback of each other, and ii) the higher ability for endpoint detection given by a lower variance of the decision function in pause/speech frames. The experiments conducted on the Spanish SpeechDat-Car database showed that the proposed algorithm outperforms ITU G.729, ETSI AMR1 and AMR2 and ETSI AFE standards as well as other recently reported VAD methods in speech/non-speech detection performance. Index Terms: voice activity detection, clustering analysis, bispectrum function, entropy