O
Oussama Djedidi
Researcher at Aix-Marseille University
Publications - 9
Citations - 69
Oussama Djedidi is an academic researcher from Aix-Marseille University. The author has contributed to research in topics: Support vector machine & Redundancy (engineering). The author has an hindex of 3, co-authored 9 publications receiving 21 citations. Previous affiliations of Oussama Djedidi include University of the South, Toulon-Var & Centre national de la recherche scientifique.
Papers
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Journal ArticleDOI
Accurate detection and discrimination of pollutant gases using a temperature modulated MOX sensor combined with feature extraction and support vector classification
TL;DR: This work describes a novel approach relying on a single physical sensor coupled with two heaters in conjunction with data-driven algorithms for detecting the presence of one of the three dangerous gases individually or in mixtures.
Journal ArticleDOI
A temporal-based SVM approach for the detection and identification of pollutant gases in a gas mixture
Mohand Djeziri,Mohand Djeziri,Oussama Djedidi,Oussama Djedidi,Nicolas Morati,Nicolas Morati,Jean-Luc Seguin,Jean-Luc Seguin,Marc Bendahan,Marc Bendahan,T. Contaret,T. Contaret +11 more
TL;DR: In this article, a Temporal-based Support Vector Machine (SVM) was used for the detection and identification of several toxic gases in a gas mixture, such as carbon monoxide (CO), ozone (O3) and nitrogen dioxide (NO2).
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Failure Prognosis Based on Relevant Measurements Identification and Data-Driven Trend-Modeling: Application to a Fuel Cell System
TL;DR: A failure prognosis method is achieved through the trend modeling of the identified HI using a data-driven and updatable state model, and the remaining useful life is predicted through the calculation of the times of crossing of the predicted HI and the failure threshold.
Journal ArticleDOI
Power profiling and monitoring in embedded systems: A comparative study and a novel methodology based on NARX neural networks
Oussama Djedidi,Mohand Djeziri +1 more
TL;DR: An overview of the most used models in the literature is presented and a comparative analysis of these models according to a set of criteria, such as the modeling assumptions, the necessary instrumentation necessary, the accuracy, and the complexity of implementation is offered.
Dissertation
Modélisation Incrémentale des Processeurs Embarqués pour l'Estimation des Caractéristiques et le Diagnostic
TL;DR: Le developpement d’outils de surveillance and de diagnostic des systemes electroniques embarques, en particuliers les SoC, est devenu l’un des verrous scientifiques a lever pour assurer une large utilisation of ces systemes dans les equipements a risque en toute securite.