Search Results for author: Taous-Meriem Laleg-Kirati

Found 12 papers, 0 papers with code

You can monitor your hydration level using your smartphone camera

no code implementations12 Feb 2024 Rose Alaslani, Levina Perzhilla, Muhammad Mahboob Ur Rahman, Taous-Meriem Laleg-Kirati, Tareq Y. Al-Naffouri

For both classification problems, we feed the pre-processed and augmented PPG data to a number of machine learning, deep learning and transformer models which models provide a very high accuracy, i. e., in the range of 95% to 99%.

Binary Classification Dimensionality Reduction +3

Modulating function based algebraic observer coupled with stable output predictor for LTV and sampled-data systems

no code implementations26 Jan 2024 Matti Noack, Ibrahima N'Doye, Johann Reger, Taous-Meriem Laleg-Kirati

This paper proposes an algebraic observer-based modulating function approach for linear time-variant systems and a class of nonlinear systems with discrete measurements.

Model-based versus model-free feeding control and water quality monitoring for fish growth tracking in aquaculture systems

no code implementations14 Jun 2023 Fahad Aljehani, Ibrahima N'Doye, Taous-Meriem Laleg-Kirati

We also show that the model predictive control decreases fish mortality and reduces food consumption in all different cases of unionized ammonia exposure.

Model Predictive Control Q-Learning

Feeding control and water quality monitoring in aquaculture systems: Opportunities and challenges

no code implementations14 Jun 2023 Fahad Aljehani, Ibrahima N'Doye, Taous-Meriem Laleg-Kirati

This paper reviews the main control design techniques for fish growth in aquaculture systems, namely algorithms that optimize the feeding and water quality of a dynamic fish growth process.

reinforcement-learning

Tracking Control of Optical Beam Transceivers using Mean Field Models

no code implementations26 Jan 2023 Ibrahima N'Doye, Taous-Meriem Laleg-Kirati

This paper proposes mean field models to maintain an accurate line-of-sight and tracking between transceivers mounted in mobile unmanned aerial vehicles (UAVs) platforms in the presence of underlying mechanical vibration effects.

Accelerating Extremum Seeking Convergence by Richardson Extrapolation Methods

no code implementations22 Mar 2022 Jan-Henrik Metsch, Jonathan Neuhauser, Jerome Jouffroy, Taous-Meriem Laleg-Kirati, Johann Reger

In this paper, we propose the concept of accelerated convergence that has originally been developed to speed up the convergence of numerical methods for extremum seeking (ES) loops.

Data-Driven State Estimation for Light-Emitting Diode Underwater Optical Communication

no code implementations30 Dec 2021 Yingquan Li, Zhenwen Liang, Ibrahima N'Doye, Xiangliang Zhang, Mohamed-Slim Alouini, Taous-Meriem Laleg-Kirati

Light-Emitting Diodes (LEDs) based underwater optical wireless communications (UOWCs), a technology with low latency and high data rates, have attracted significant importance for underwater robots.

Spatial Distribution Patterns of Clownfish in Recirculating Aquaculture Systems

no code implementations29 Dec 2021 Fahad Aljehani, Ibrahima N'Doye, Micaela S. Justo, John E. Majoris, Michael L. Berumen, Taous-Meriem Laleg-Kirati

This work proposes an efficient approach to analyze the spatial distribution status and motion patterns of juvenile clownfish \textit{(Amphiprion bicinctus)} maintained in aquaria at three stocking densities (1, 5, and 10 individuals/aquarium).

Optical Flow Estimation

Model-free LQR based PID controller for trajectory tracking of 2-DoF helicopter: comparison and experimental results

no code implementations19 Mar 2021 Nouha Rouis, Ibrahima N'Doye, Taous-Meriem Laleg-Kirati

This paper studies the performance of a model-free LQR based PID (i-LQR-PID) controller designed for tracking control problem of a 2-DoF laboratory helicopter.

QuPWM: Feature Extraction Method for MEG Epileptic Spike Detection

no code implementations3 Jul 2019 Abderrazak Chahid, Fahad Albalawi, Turky Nayef Alotaiby, Majed Hamad Al-Hameed, Saleh Alshebeili, Taous-Meriem Laleg-Kirati

Second, the extracted features are classified using a Support Vector Machine (SVM) for the purpose of epileptic spikes detection.

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