By a News Reporter-Staff News Editor at Information Technology Newsweekly -- A new study on Information Technology is now available. According to news reporting from Duisburg, Germany, by VerticalNews journalists, research stated, "This paper investigates two new multisensor data fusion algorithms for object detection in monitoring of industrial processes. The goals were to reduce the rate of false detection and obtain reliable decisions on the presence of target objects."
The news correspondents obtained a quote from the research from the University of Duisburg-Essen, "The monitoring system uses acceleration sensors and is used as a sensor-cluster. In principle the approach can include arbitrary data acquisition techniques. Two approaches were proposed. The first uses a short-time Fourier transform (STFT) as a prefilter to extract relevant features from the acceleration signals. The features extracted from different sensor channels are first classified using support vector machine (SVM)-based filters. A novel decision fusion process to combine individual decisions was developed. The second approach uses a continuous wavelet transform (CWT) as a prefilter to extract relevant features from the acceleration signals. The features extracted from different sensor signals are subjected to further prefiltering processes before SVM-based classification. The individual decision functions are then combined in a decision fusion module. The classification system was trained and validated using real industrial data. The two approaches were tested using the same data and their performance and modeling complexity are compared."
According to the news reporters, the research concluded: "The developed approaches show strong improvements in detection and false alarm rates."
For more information on this research see: Improved process monitoring and supervision based on a reliable multi-stage feature-based pattern recognition technique. Information Sciences, 2014;259():282-294. Information Sciences can be contacted at: Elsevier Science Inc, 360 Park Ave South, New York, NY 10010-1710, USA. (Elsevier - www.elsevier.com; Information Sciences - www.elsevier.com/wps/product/cws_home/505730)
Our news journalists report that additional information may be obtained by contacting L. Al-Shrouf, University of Duisburg Essen, Chair Dynam & Control, D-47057 Duisburg, Germany. Additional authors for this research include M.S. Saadawia and D. Soffker.
Keywords for this news article include: Europe, Germany, Duisburg, Information Technology
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