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Oussama Djedidi
21
Documents
Presentation
Oussama Djedidi has a Ph.D. in Computer engineering and automation from Aix-Marseille University and is currently working on using AI techniques in engineering applications and physics, notably predicting the remaining useful life (RUL) of embedded systems and using Deep Learning in intelligent sensors for the detection of gases and their concentration. During his thesis, he worked on the development of methods for monitoring and diagnosis of embedded systems used in the touchscreens of avionics cockpits of the future and established a proof of concept for modeling and monitoring framework.
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Adaptive Estimation of the Thermal Behavior of CPU-GPU SoCs for Prediction and DiagnosisProceedings of the International Conference on Integrated Modeling and Analysis in Applied Control and Automation, 2019–IMAACA 2019, Sep 2019, Lisbon, Portugal. pp.93-98
Conference papers
hal-02311475v2
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Failure Prognosis of Embedded Systems Based on Temperature Drift AssessmentIMAACA 2019 – Proceedings of the International Conference on Integrated Modeling and Analysis in Applied Control and Automation, 2019, Sep 2019, Lisbon, Portugal. pp.11-16
Conference papers
hal-02311476v1
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Data Analysis-Based Gas Identification with a Single Metal Oxide Sensor Operating in Dynamic Temperature RegimeALLSENSORS 2020, The Fifth International Conference on Advances in Sensors, Actuators, Metering and Sensing, Nov 2019, Valencia, Spain. pp.20-23
Conference papers
hal-02575436v1
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A Novel Easy-to-construct Power Model for Embedded and Mobile Systems15th International Conference on Informatics in Control, Automation and Robotics, Jul 2018, Porto, Portugal. ⟨10.5220/0006915805410545⟩
Conference papers
hal-01856579v1
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Constructing an Accurate and a High-Performance Power Profiler for Embedded Systems and SmartphonesMSWIM '18: 21st ACM Int'l Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems, Oct 2018, Montreal QC Canada, Canada. pp.79-82, ⟨10.1145/3242102.3242139⟩
Conference papers
hal-03604237v1
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Constructing an Accurate and a High-Performance Power Profiler for Embedded Systems and SmartphonesMSWIM '18: 21st ACM Int'l Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems, Oct 2018, Montreal QC Canada, France. pp.79-82, ⟨10.1145/3242102.3242139⟩
Conference papers
hal-03604220v1
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Constructing an Accurate and a High-Performance Power Profiler for Embedded Systems and SmartphonesMSWIM '18 21st ACM Int'l Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems, Oct 2018, Montreal, Canada. ⟨10.1145/3242102.3242139⟩
Conference papers
hal-01907145v1
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Modélisation orientée diagnostic des composants électroniques embarquésCongrès National de la Recherche des IUT (CNRIUT’2018), Jun 2018, Aix en Provence, France
Conference papers
hal-01902905v1
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Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation14th International Conference on Informatics in Control, Automation and Robotics, Jul 2017, Madrid, France. pp.338-345, ⟨10.5220/0006470803380345⟩
Conference papers
hal-03604233v1
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Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation14th International Conference on Informatics in Control, Automation and Robotics, Jul 2017, Madrid, Spain. pp.338-345, ⟨10.5220/0006470803380345⟩
Conference papers
hal-01770233v1
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Data-driven monitoring of Systems On Chip for Multifunction Modular Cockpit Display5th Summer School on INtelligent signal processing for FrontIEr Research and Industry (INFIERI 2019), May 2019, Wuhan, China.
Conference poster
hal-02144441v1
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Incremental modeling of embedded processors for feature estimation and diagnosticsSciences de l'ingénieur [physics]. Aix Marseille université - LIS, 2019. Français. ⟨NNT : ⟩
Theses
tel-03569248v1
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Modélisation Incrémentale des Processeurs Embarqués pour l'Estimation des Caractéristiques et le DiagnosticAutomatique. Aix-Marseille Université (AMU), 2019. Français. ⟨NNT : ⟩
Theses
tel-02472080v1
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