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Developing a multi-label tinyML machine learning model for an active and optimized greenhouse microclimate control from multivariate sensed data

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Artificial Intelligence in Agriculture 2022年第1期6卷 129-137页

作者： Ilham Ihoume Rachid Tadili Nora Arbaoui Mohamed Benchrifa ahmed idrissi Mohamed Daoudi Solar Energy and Environment Laboratory Mohammed V University in RabatFaculty of SciencesB.P 1014RabatMorocco

In the uncertainties within which the worldwide food security lies nowadays,the agricultural industry is raising a crucial need for being equipped with the state-of-the-art technologies for a more efficient,climate-resilient and sustainable *** traditional production methods have to be revisited,and opportunities should be given for the innovative solutions henceforth brought by big data analytics,cloud computing and internet of things(IoT).In this context,we develop an optimized tinyML-oriented model for an active machine learningbased greenhouse microclimate management to be integrated in an on-field *** design an experimental strawberry greenhouse from which we collect multivariate climate data through installed *** obtained values'combinations are labeled according to a five-action multi-label control strategy,then used to prepare a machine learning-ready *** dataset is used to train and five-fold cross-validate 90 Multi-Layer Perceptrons(MLPs)with varied hyperparameters to select the most performant–yet optimized–model instance for the addressed *** multi-label control approach enables designing highly scalable models with reduced computational complexity,comprising only n control neurons instead of(1+∑n k=1Cn k)neurons(usually generated from a classic single-label approach from n input variables).Our final selected model incorporates 2 hidden layers with 7 and 8 neurons respectively and 151 parameters;it scored a mean accuracy of 97%during the cross-validation phase,then 96%on our supplementary test *** model enables an intelligent and autonomous greenhouse management with the less required *** can be efficiently deployed in microcontrollers within real world operating conditions.

关键词： Agricultural greenhouse Microclimate control Machine learning Optimization TinyML

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A direct power control of a DFIG based-WECS during symmetrical voltage dips

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Protection and Control of Modern Power Systems 2020年第1期5卷 36-47页

作者： Sara Mensou ahmed Essadki Tamou Nasser Badr Bououlid idrissi Research Center of Engineering and Health Sciences and Technologies from ENSET Mohammed V UniversityRabatMorocco Research Center of Engineering and Health Sciences and Technologies from ENSIAS Mohammed V UniversityRabatMorocco Electromechanical Engineering Department of ENSAM Moulay Ismaïl UniversityMeknèsMorocco.

The Wind Energy Conversion System(WECS)based Doubly Fed Induction Generator(DFIG)has experienced a rapid development in the world,which leads to an increasing insertion of this source of energy in the electrical *** sudden and temporary drop of voltage at the network can affect the operation of the DFIG;the voltage dips produce high peak currents on the stator and rotor circuits,without protection,the rotor side converter(RSC)will suffer also from over-current limit,consequently,the RSC may even be destroyed and the generator be *** this paper a new Direct Power Control(DPC)method was developed,in order to control the stator powers and help the operation of the aero-generator during the faults grid;by injecting the reactive power into the network to contribute to the return of voltage,and set the active power to the optimum value to suppress the high peak *** DPC method was designed using the nonlinear Backstepping(BS)controller associated with the Lyapunov function to ensure the stability and robustness of the system.A comparison study was undertaken to verify the robustness and effectiveness of the DPC-BS to that of the classical vector control(VC)using Proportional-Integral(PI)*** were simulated under the Simulink®software.

关键词： Wind energy Doubly-fed induction aero-generator Voltage dips DPC strategy Backstepping technique Lyapunov function

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COVID-19 and Pregnancy—Series of Cases and Review of Literature

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Open Journal of Obstetrics and Gynecology 2021年第10期11卷 1397-1410页

作者： Yassir Ait Benkaddour Ousmane Omar Bâ Bouchra Fakhir Aboubacar Sidibé Abderraouf Soummani ahmed Rhassane El Adib Houssam Rebahi Nadia El idrissi Slitine Fadl Mrabih Maoulainine Fatima Ezzahra Hazmiri Department of Obstetrics and Gynecology UHC Mohammed VI Marrakesh Morocco Department of Maternity Anesthesia Intensive Care Unit UHC Mohammed VI Marrakesh Morocco Department of Pediatrics UHC Mohammed VI Marrakesh Morocco Department of Histology-Embryology-Cytogenic UHC Mohammed VI Marrakesh Morocco

Objectives: To bring out the clinical, biological, and therapeutic aspects of pregnant women and women in the post-partum infected by the SARS COVID-19 in the University hospital of Marrakesh. To study the vertical transmission of the virus if it exists, and the impact on the newborn. Methods: It is a prospective observational study on women infected by COVID-19 virus admitted in the gynecology obstetrics department of the University hospital of Marrakesh during the period between March 1st and July 15th. Data collection was insured thanks to a customized form containing the medical history, clinical criteria, biological and, radiological findings as well as the treatment and maternal and neo-natal outcomes. Results: The clinical, biological and radiological presentation of COVID-19 infection in pregnant and post-partum women doesn’t seem to be different from general population. Pregnant and post-partum women don’t seem to be more at risk to develop severe features of the disease. Vertical transmission via placenta is possible. COVID-19 infection may cause premature labor, premature rupture of membranes, preeclampsia or fetal distress

关键词： COVID-19 Pregnancy Post-Partum

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