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Ahmed Osman

Researcher at American University of Sharjah

Publications -  128
Citations -  2430

Ahmed Osman is an academic researcher from American University of Sharjah. The author has contributed to research in topics: Fault (power engineering) & Smart grid. The author has an hindex of 21, co-authored 118 publications receiving 1844 citations. Previous affiliations of Ahmed Osman include Universiti Teknologi Malaysia & University of Calgary.

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Transmission line distance protection based on wavelet transform

TL;DR: In this paper, a digital distance-protection scheme for transmission lines based on analyzing the measured voltage and current signals at the relay location using wavelet transform with multiresolution analysis (MRA) is presented.
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Hybrid Traveling Wave/Boundary Protection for Monopolar HVDC Line

TL;DR: In this article, a hybrid protection algorithm based on traveling wave protection principle and boundary protection principle for a monopolar HVDC line is proposed, and the effect of border distortion, noise, high ground fault resistance, close-up faults, transients caused by lightning strokes and different dc line terminations are considered.
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Online INS/GPS integration with a radial basis function neural network

TL;DR: This paper aims to introduce a multi-sensor system integration approach for fusing data from INS and GPS utilizing artificial neural networks (ANN) utilizing radial basis function (RBF) neural networks, which generally have simpler architecture and faster training procedures than multi-layer perceptron networks.
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Protection of parallel transmission lines using wavelet transform

TL;DR: In this article, a new scheme to enhance the solution of the problems associated with parallel transmission line protection is presented, which depends on the three line voltages and the six line currents of the two parallel lines at each end Fault detection, fault discrimination, and calculation of the measured signals are done by using wavelet transform (WT) by comparing the magnitudes of the estimated current phasors of the corresponding phases on both lines.
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Malware Detection Based on Hybrid Signature Behaviour Application Programming Interface Call Graph

TL;DR: A new malware detection framework is proposed that combines Signature-Based with Behaviour-Based using API graph system and aims to improve accuracy and scan process time for malware detection.