Plenary Lecture
Image of the Inverse of the Belonging Probability for Early Volcanic Eruption and Forest Fire Detections
Professor Benabdellah Yagoubi
Laboratory of Signals and systems
Department of Electrical Engineering
University of Mostaganem
Algeria
E-mail: yagoubibenabdellah@yahoo.com
Abstract: Forest fires and volcanic eruptions are among many factors (natural or artificial) that are contributing to the global warming. Their early detection is, therefore, crucial to prevent farther damages. Various surveillance methods use observation of direct images of forest fires and volcanic eruptions. Some good results are obtained using these direct observations but they are, however, not very efficient in early detection. We will, therefore, try to show, in this talk, how to use the image of the inverse of the belonging probability (IIBP) to early detect forest fires and volcanic eruptions and to show its advantage over many other direct observation methods.
Brief Biography of the Speaker: Dr B. Yagoubi received the M. Sc degree in Electrical Engineering in 1985 from Bel-Abbes University, Algeria and the Ph. D degree (amorphous thin films) (1986-1989) in the Faculty of Sciences from Brunel University (UK). He was the head of the Signals and Systems Laboratory (1999-2003) and the head of the Department of Electrical Engineering (2005-2006). He is lecturing the theory of digital signal, systems modeling and identification, random processes and detection (1996-2016) at Mostaganem University, Algeria. He has been involved in some national projects such as forest fire detection, heart rate variability in the LF and HF bands to characterize the autonomous nervous system, and study and application of random processes. Currently, he is focusing on extracting useful information from mono-dimensional and multidimensional signals as well as on detection using the inverse of the belonging probability technique of a rare event to a Gaussian realization, as part of a national project. Current research interests are in real signals and models geometric representation based on Gram-Schmidt orthogonalization concept, as well as using a relative geometric space of observation. Further researches are in the use of the image of the inverse of the belonging probability (IIBP) in detection.