2024
|
Chakraborty, Chinmay; Othman, Soufiene Ben; Almalki, Faris A.; Sakli, Hedi FC-SEEDA: fog computing-based secure and energy efficient data aggregation scheme for Internet of healthcare Things Article de journal Dans: Neural Computing and Applications, vol. 36, no. 1, p. 241 – 257, 2024, (Cited by: 13). @article{Chakraborty2024241,
title = {FC-SEEDA: fog computing-based secure and energy efficient data aggregation scheme for Internet of healthcare Things},
author = {Chinmay Chakraborty and Soufiene Ben Othman and Faris A. Almalki and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146718108\&doi=10.1007%2fs00521-023-08270-0\&partnerID=40\&md5=48aee26da0372079072208a79460e665},
doi = {10.1007/s00521-023-08270-0},
year = {2024},
date = {2024-01-01},
journal = {Neural Computing and Applications},
volume = {36},
number = {1},
pages = {241 \textendash 257},
note = {Cited by: 13},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Lahmar, Ines; Zaier, Aida.; Yahia, Mohamed.; Tarig, Ali.; Boaullegue, Ridha. Fuzzy Divergence Weighted Ensemble Clustering With Spectral Learning Based On Random Projections For Big Data Article de journal Dans: IEEE Access, p. 1-1, 2024, ISSN: 2169-3536. @article{10415440,
title = {Fuzzy Divergence Weighted Ensemble Clustering With Spectral Learning Based On Random Projections For Big Data},
author = {Ines Lahmar and Aida. Zaier and Mohamed. Yahia and Ali. Tarig and Ridha. Boaullegue},
doi = {10.1109/ACCESS.2024.3359299},
issn = {2169-3536},
year = {2024},
date = {2024-01-01},
journal = {IEEE Access},
pages = {1-1},
abstract = {In many real-world applications, data are described by high-dimensional feature spaces, posing new challenges for current ensemble clustering methods. The goal is to combine sets of base clusters to enhance clustering accuracy, but this makes them susceptible to low quality. However, the reliability of present ensemble clustering in high-dimensional data still needs improvement. In this context, we propose a new fuzzy divergence-weighted ensemble clustering based on random projection and spectral learning. Firstly, random projection (RP) is used to create various dimensional data and find membership matrices via fuzzy c-means (FCM). Secondly, fuzzy partitions of random projections are ranked using entropy-based local weighting along with Kullback-Leibler (KL) divergence to detect any uncertainty. Then it used to evaluate the weight of each cluster. Finally, we create regularized graphs from these membership matrices and use spectral matrices to estimate the affinity matrices of these graphs using fuzzy KL divergence anchor graphs. Subsequently, obtaining the final clustering results is considered as an optimization problem, and the ensemble clustering results are obtained. The experimental results on high-dimensional data demonstrate the efficiency of our method compared to state-of-the-art methods.},
keywords = {Matrix converters;Entropy;Clustering algorithms;Uncertainty;Reliability;Weight measurement;Sparse matrices;Ensemble learning;Fuzzy systems;Spectral analysis;Fuzzy ensemble clustering;High-dimensional data;Random projection;Kullback-Leibler divergence entropy;Spectral learning},
pubstate = {published},
tppubtype = {article}
}
In many real-world applications, data are described by high-dimensional feature spaces, posing new challenges for current ensemble clustering methods. The goal is to combine sets of base clusters to enhance clustering accuracy, but this makes them susceptible to low quality. However, the reliability of present ensemble clustering in high-dimensional data still needs improvement. In this context, we propose a new fuzzy divergence-weighted ensemble clustering based on random projection and spectral learning. Firstly, random projection (RP) is used to create various dimensional data and find membership matrices via fuzzy c-means (FCM). Secondly, fuzzy partitions of random projections are ranked using entropy-based local weighting along with Kullback-Leibler (KL) divergence to detect any uncertainty. Then it used to evaluate the weight of each cluster. Finally, we create regularized graphs from these membership matrices and use spectral matrices to estimate the affinity matrices of these graphs using fuzzy KL divergence anchor graphs. Subsequently, obtaining the final clustering results is considered as an optimization problem, and the ensemble clustering results are obtained. The experimental results on high-dimensional data demonstrate the efficiency of our method compared to state-of-the-art methods. |
2023
|
Hassen, Walid Ben; Abdelkrim, Tayssir; Abdelkrim, Nouceyba; Tellili, Adel Control of an Uncertain Nonlinear System Proceedings Article Dans: 2023 IEEE International Workshop on Mechatronic Systems Supervision (IW_MSS), p. 1-4, 2023. @inproceedings{10369415,
title = {Control of an Uncertain Nonlinear System},
author = {Walid Ben Hassen and Tayssir Abdelkrim and Nouceyba Abdelkrim and Adel Tellili},
doi = {10.1109/IW_MSS59200.2023.10369415},
year = {2023},
date = {2023-11-01},
booktitle = {2023 IEEE International Workshop on Mechatronic Systems Supervision (IW_MSS)},
pages = {1-4},
abstract = {This article presents an advanced control approach for nonlinear and uncertain dynamic systems using two powerful methods: Backstepping and Adaptive Backstepping. Nonlinear and uncertain systems are common in many industrial applications, and achieving effective control for them is a major engineering challenge.The Backstepping method, a control technique based on recursion, is first introduced to stabilize nonlinear and uncertain dynamic systems. It allows for the design of successive control laws by progressively moving up the chain of the system’s state variables, stabilizing them one by one. This approach offers significant flexibility in handling a variety of nonlinear and uncertain systems.Next, Adaptive Backstepping is presented as an extension of the basic method. This approach takes into account uncertainties and parametric variations in the system, making it particularly well-suited for systems whose characteristics may change over time. Adaptive Backstepping automatically adjusts control laws to maintain system stability and performance, even in the presence of unknown disturbances and uncertainties.},
keywords = {Uncertain systems;Backstepping;Adaptive systems;Uncertainty;Mechatronics;Conferences;Control systems;Nonlinear systems;adaptive control;Lyapunov;uncertain},
pubstate = {published},
tppubtype = {inproceedings}
}
This article presents an advanced control approach for nonlinear and uncertain dynamic systems using two powerful methods: Backstepping and Adaptive Backstepping. Nonlinear and uncertain systems are common in many industrial applications, and achieving effective control for them is a major engineering challenge.The Backstepping method, a control technique based on recursion, is first introduced to stabilize nonlinear and uncertain dynamic systems. It allows for the design of successive control laws by progressively moving up the chain of the system’s state variables, stabilizing them one by one. This approach offers significant flexibility in handling a variety of nonlinear and uncertain systems.Next, Adaptive Backstepping is presented as an extension of the basic method. This approach takes into account uncertainties and parametric variations in the system, making it particularly well-suited for systems whose characteristics may change over time. Adaptive Backstepping automatically adjusts control laws to maintain system stability and performance, even in the presence of unknown disturbances and uncertainties. |
Abdelkrim, Tayssir; Hassen, Walid Ben; Abdelkrim, Nouceyba; Tellili, Adel Diagnosis and FTC : descriptor approach Proceedings Article Dans: 2023 IEEE International Workshop on Mechatronic Systems Supervision (IW_MSS), p. 1-9, 2023. @inproceedings{10369866,
title = {Diagnosis and FTC : descriptor approach},
author = {Tayssir Abdelkrim and Walid Ben Hassen and Nouceyba Abdelkrim and Adel Tellili},
doi = {10.1109/IW_MSS59200.2023.10369866},
year = {2023},
date = {2023-11-01},
booktitle = {2023 IEEE International Workshop on Mechatronic Systems Supervision (IW_MSS)},
pages = {1-9},
abstract = {In this paper we propose an approach of fault diagnosis and identification (FDI) and fault tolerant control(FTC) applied for time-delay continuous linear systems. To estimate the sensors faults descriptor approach is investigated. This method consists in augmenting the state system by considering the fault as an auxiliary state. The used observer can simultaneously estimate both the state system and sensors faults. The observer gains are then determined according to Linear Matrix Inequalities (LMI) technique. For fault tolerant control we present two control strategies which stabilize the system not only in free-fault case, but also in the fault occurrence. The first one consists in determine the state-feedback gain and the second one is based on the static output-feedback control. A numerical example is proposed to demonstrate the effectiveness and the merit of the given design.},
keywords = {Fault diagnosis;Linear systems;Mechatronics;Fault tolerant control;Observers;Sensor phenomena and characterization;Sensor systems;Observer;Faults estimation;Sensor faults;Descriptor approach;LMI;Time-delay system},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we propose an approach of fault diagnosis and identification (FDI) and fault tolerant control(FTC) applied for time-delay continuous linear systems. To estimate the sensors faults descriptor approach is investigated. This method consists in augmenting the state system by considering the fault as an auxiliary state. The used observer can simultaneously estimate both the state system and sensors faults. The observer gains are then determined according to Linear Matrix Inequalities (LMI) technique. For fault tolerant control we present two control strategies which stabilize the system not only in free-fault case, but also in the fault occurrence. The first one consists in determine the state-feedback gain and the second one is based on the static output-feedback control. A numerical example is proposed to demonstrate the effectiveness and the merit of the given design. |
Mechri, Walid; Simon, Christophe Study of Testing Strategy for Performance Analysis of Actuator Layer in Safety Instrumented System Article de journal Dans: Studies in Systems, Decision and Control, vol. 467, p. 201 – 211, 2023, (Cited by: 0). @article{Mechri2023201,
title = {Study of Testing Strategy for Performance Analysis of Actuator Layer in Safety Instrumented System},
author = {Walid Mechri and Christophe Simon},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162249994\&doi=10.1007%2f978-3-031-27540-1_18\&partnerID=40\&md5=79565be2964e3aae1459684b4c39d443},
doi = {10.1007/978-3-031-27540-1_18},
year = {2023},
date = {2023-01-01},
journal = {Studies in Systems, Decision and Control},
volume = {467},
pages = {201 \textendash 211},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Mechri, Walid; Simon, Christophe Experience Feedback and Probabilistic Graphical Model for Failure Causes Isolation Conférence 2023, (Cited by: 0). @conference{Mechri2023780,
title = {Experience Feedback and Probabilistic Graphical Model for Failure Causes Isolation},
author = {Walid Mechri and Christophe Simon},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177465282\&doi=10.1109%2fCoDIT58514.2023.10284473\&partnerID=40\&md5=bd55a7443889cebd39e98d67836b25c0},
doi = {10.1109/CoDIT58514.2023.10284473},
year = {2023},
date = {2023-01-01},
journal = {9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023},
pages = {780 \textendash 785},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Mechri, Walid; Simon, Christophe; Rajhi, Wahbi Alternating Test Strategy for Multi-State Safety System Performance Analysis Conférence 2023, (Cited by: 0). @conference{Mechri2023914,
title = {Alternating Test Strategy for Multi-State Safety System Performance Analysis},
author = {Walid Mechri and Christophe Simon and Wahbi Rajhi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177447130\&doi=10.1109%2fCoDIT58514.2023.10284360\&partnerID=40\&md5=e4a1396ea31962ac94a48648f5b07f5e},
doi = {10.1109/CoDIT58514.2023.10284360},
year = {2023},
date = {2023-01-01},
journal = {9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023},
pages = {914 \textendash 919},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Darghouthi, Amina; Khlifi, Abdelhakim; Chibani, Belgacem Equalizers Performance Enhancing in MISO-OTFS Configuration Conférence 2023. @conference{Darghouthi2023,
title = {Equalizers Performance Enhancing in MISO-OTFS Configuration},
author = {Amina Darghouthi and Abdelhakim Khlifi and Belgacem Chibani},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182943471\&doi=10.1109%2fIW_MSS59200.2023.10369509\&partnerID=40\&md5=21e89488c5488424bc138e4778068b81},
doi = {10.1109/IW_MSS59200.2023.10369509},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Troudi, Ikram; Chibani, Belgacem Bandwidth With FSS Antennas Enhancement Using MoM Approach Conférence 2023. @conference{Troudi2023,
title = {Bandwidth With FSS Antennas Enhancement Using MoM Approach},
author = {Ikram Troudi and Belgacem Chibani},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182929533\&doi=10.1109%2fIW_MSS59200.2023.10368792\&partnerID=40\&md5=b55e5a53552c8da68f321eb3b2813df4},
doi = {10.1109/IW_MSS59200.2023.10368792},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Monia, Ibrahim; Mohamed-Bechir, Dadi; Chibani, Rhaimi B. Benefits of high speed telecommunication in telemedicine for rural zone health problems Conférence 2023. @conference{Monia2023,
title = {Benefits of high speed telecommunication in telemedicine for rural zone health problems},
author = {Ibrahim Monia and Dadi Mohamed-Bechir and Rhaimi B. Chibani},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182936883\&doi=10.1109%2fIW_MSS59200.2023.10369855\&partnerID=40\&md5=322f722e9925bec89d638f3d33aaa6b2},
doi = {10.1109/IW_MSS59200.2023.10369855},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Sakli, Marwen; Essid, Chaker; Salah, Bassem Ben; Sakli, Hedi Deep learning methods for brain tumor segmentation Ouvrage 2023, (Cited by: 0). @book{Sakli2023168,
title = {Deep learning methods for brain tumor segmentation},
author = {Marwen Sakli and Chaker Essid and Bassem Ben Salah and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177072235\&doi=10.1201%2f9781003366249-11\&partnerID=40\&md5=0cc1ff26198bd491fb8fcaefc211571c},
doi = {10.1201/9781003366249-11},
year = {2023},
date = {2023-01-01},
journal = {Machine Learning and Deep Learning Techniques for Medical Image Recognition},
pages = {168 \textendash 193},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
|
Tbibe, Rabiaa; Soufiene, Ben Othman; Chakraborty, Chinmay; Sakli, Hedi Artificial intelligence techniques for cancer detection from medical images Ouvrage 2023, (Cited by: 0). @book{Tbibe2023115,
title = {Artificial intelligence techniques for cancer detection from medical images},
author = {Rabiaa Tbibe and Ben Othman Soufiene and Chinmay Chakraborty and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177030982\&doi=10.1201%2f9781003366249-8\&partnerID=40\&md5=ea1f5c7512f820cac0a9ff40e4f643b1},
doi = {10.1201/9781003366249-8},
year = {2023},
date = {2023-01-01},
journal = {Machine Learning and Deep Learning Techniques for Medical Image Recognition},
pages = {115 \textendash 127},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
|
Bahhar, Chayma; Ksibi, Amel; Ayadi, Manel; Jamjoom, Mona M.; Ullah, Zahid; Soufiene, Ben Othman; Sakli, Hedi Wildfire and Smoke Detection Using Staged YOLO Model and Ensemble CNN Article de journal Dans: Electronics (Switzerland), vol. 12, no. 1, 2023, (Cited by: 14; All Open Access, Gold Open Access). @article{Bahhar2023,
title = {Wildfire and Smoke Detection Using Staged YOLO Model and Ensemble CNN},
author = {Chayma Bahhar and Amel Ksibi and Manel Ayadi and Mona M. Jamjoom and Zahid Ullah and Ben Othman Soufiene and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145891697\&doi=10.3390%2felectronics12010228\&partnerID=40\&md5=19431d4589ca2c699f5ed05c80fe9a94},
doi = {10.3390/electronics12010228},
year = {2023},
date = {2023-01-01},
journal = {Electronics (Switzerland)},
volume = {12},
number = {1},
note = {Cited by: 14; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Elghaieb, Iheb; Souid, Abdelbaki; Zouinkhi, Ahmed; Sakli, Hedi Defeating Alzheimer’s: AI perspective from diagnostics to prognostics: Literature summary Ouvrage 2023, (Cited by: 0). @book{Elghaieb2023245,
title = {Defeating Alzheimer's: AI perspective from diagnostics to prognostics: Literature summary},
author = {Iheb Elghaieb and Abdelbaki Souid and Ahmed Zouinkhi and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177033937\&doi=10.1201%2f9781003366249-14\&partnerID=40\&md5=e88e4aebfaa4238050af8d02213be5b9},
doi = {10.1201/9781003366249-14},
year = {2023},
date = {2023-01-01},
journal = {Machine Learning and Deep Learning Techniques for Medical Image Recognition},
pages = {245 \textendash 256},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
|
Souid, Abdelbaki; Othman, Soufiene Ben; Hamroun, Mohamed; Sakli, Hedi Full Interpretability CBMIR to Help Minimize Radiologist Analysis Search Time Conférence 2023, (Cited by: 0). @conference{Souid20231136,
title = {Full Interpretability CBMIR to Help Minimize Radiologist Analysis Search Time},
author = {Abdelbaki Souid and Soufiene Ben Othman and Mohamed Hamroun and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167737946\&doi=10.1109%2fIWCMC58020.2023.10183105\&partnerID=40\&md5=e4d8ee981345e84ba778805d96cfe8d9},
doi = {10.1109/IWCMC58020.2023.10183105},
year = {2023},
date = {2023-01-01},
journal = {2023 International Wireless Communications and Mobile Computing, IWCMC 2023},
pages = {1136 \textendash 1141},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Souid, Abdelbaki; Hamroun, Mohamed; Soufiene, Ben Othman; Sakli, Hedi Efficient and fast lung disease predictor model Ouvrage 2023, (Cited by: 0). @book{Souid202390,
title = {Efficient and fast lung disease predictor model},
author = {Abdelbaki Souid and Mohamed Hamroun and Ben Othman Soufiene and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177033285\&doi=10.1201%2f9781003366249-6\&partnerID=40\&md5=66755c62f5866631c7e73797daefa727},
doi = {10.1201/9781003366249-6},
year = {2023},
date = {2023-01-01},
journal = {Machine Learning and Deep Learning Techniques for Medical Image Recognition},
pages = {90 \textendash 102},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
|
Souid, Abdelbaki; Othman, Soufiene Ben; Hamroun, Mohamed; Sakli, Hedi; Abdelkarim, Mohamed Naceur Explainable CBMIR features extractor module to ease Thoracic aortic aneurysm retrieving preventing potential Acute Aortic Dissection Conférence vol. 13, no. 1, 2023, (Cited by: 0). @conference{Souid2023,
title = {Explainable CBMIR features extractor module to ease Thoracic aortic aneurysm retrieving preventing potential Acute Aortic Dissection},
author = {Abdelbaki Souid and Soufiene Ben Othman and Mohamed Hamroun and Hedi Sakli and Mohamed Naceur Abdelkarim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179551511\&doi=10.1109%2fINISTA59065.2023.10310391\&partnerID=40\&md5=da47096b8ebf6a0326e3c3e3e3929882},
doi = {10.1109/INISTA59065.2023.10310391},
year = {2023},
date = {2023-01-01},
journal = {17th International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2023 - Proceedings},
volume = {13},
number = {1},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Souid, Abdelbaki; Soufiene, Ben Othman; Sakli, Hedi Computer vision approaches in radiograph image analysis: A targeted review of current progress, challenges, and future perspectives Ouvrage 2023, (Cited by: 0). @book{Souid2023152,
title = {Computer vision approaches in radiograph image analysis: A targeted review of current progress, challenges, and future perspectives},
author = {Abdelbaki Souid and Ben Othman Soufiene and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177074755\&doi=10.1201%2f9781003366249-10\&partnerID=40\&md5=416331147d67ad990d5c447ac859fc8d},
doi = {10.1201/9781003366249-10},
year = {2023},
date = {2023-01-01},
journal = {Machine Learning and Deep Learning Techniques for Medical Image Recognition},
pages = {152 \textendash 167},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
|
Sakli, Marwen; Essid, Chaker; Salah, Bassem Ben; Sakli, Hedi Deep Learning-Based Multi-Stage Analysis for Accurate Skin Cancer Diagnosis using a Lightweight CNN Architecture Conférence 2023, (Cited by: 0). @conference{Sakli2023,
title = {Deep Learning-Based Multi-Stage Analysis for Accurate Skin Cancer Diagnosis using a Lightweight CNN Architecture},
author = {Marwen Sakli and Chaker Essid and Bassem Ben Salah and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179555438\&doi=10.1109%2fINISTA59065.2023.10310615\&partnerID=40\&md5=8e0012f4b06db07df0bb207524b2b3b4},
doi = {10.1109/INISTA59065.2023.10310615},
year = {2023},
date = {2023-01-01},
journal = {17th International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2023 - Proceedings},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Ghabri, Haifa; Soufiene, Ben Othman; Sakli, Hedi Artificial intelligence used to recognize fetal planes based on ultrasound scans during pregnancy Ouvrage 2023, (Cited by: 0). @book{Ghabri2023103,
title = {Artificial intelligence used to recognize fetal planes based on ultrasound scans during pregnancy},
author = {Haifa Ghabri and Ben Othman Soufiene and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177059064\&doi=10.1201%2f9781003366249-7\&partnerID=40\&md5=5c83d6ea0a23768caaaf597345d278ad},
doi = {10.1201/9781003366249-7},
year = {2023},
date = {2023-01-01},
journal = {Machine Learning and Deep Learning Techniques for Medical Image Recognition},
pages = {103 \textendash 114},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
|
Sakl, Marwen; Essid, Chaker; Salah, Bassem Ben; Sakli, Hedi DL Methods for Skin Lesions Automated Diagnosis In Smartphone Images Conférence 2023, (Cited by: 0). @conference{Sakl20231142,
title = {DL Methods for Skin Lesions Automated Diagnosis In Smartphone Images},
author = {Marwen Sakl and Chaker Essid and Bassem Ben Salah and Hedi Sakli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167710093\&doi=10.1109%2fIWCMC58020.2023.10183254\&partnerID=40\&md5=114719a149be9621210ab8022b8b21ed},
doi = {10.1109/IWCMC58020.2023.10183254},
year = {2023},
date = {2023-01-01},
journal = {2023 International Wireless Communications and Mobile Computing, IWCMC 2023},
pages = {1142 \textendash 1147},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Benjemaa, Rabeb; Elhsoumi, Aicha; Abdelkrim, Mohamed Naceur Fault Tolerant Control for Uncertain Neutral Time-Delay System Article de journal Dans: Studies in Systems, Decision and Control, vol. 474, p. 285 – 301, 2023, (Cited by: 0). @article{Benjemaa2023285,
title = {Fault Tolerant Control for Uncertain Neutral Time-Delay System},
author = {Rabeb Benjemaa and Aicha Elhsoumi and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169137274\&doi=10.1007%2f978-981-99-3463-8_12\&partnerID=40\&md5=d15157c0625455a1fb4242b342f177ef},
doi = {10.1007/978-981-99-3463-8_12},
year = {2023},
date = {2023-01-01},
journal = {Studies in Systems, Decision and Control},
volume = {474},
pages = {285 \textendash 301},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Farah, Khamsa; Chabir, Karim; Abdelkrim, Mohamed Naceur High level Petri nets-based proposal of an integrated intrusion detection and prevention mechanism in network controlled systems Article de journal Dans: IET Communications, vol. 17, no. 4, p. 469 – 477, 2023, (Cited by: 0; All Open Access, Gold Open Access). @article{Farah2023469,
title = {High level Petri nets-based proposal of an integrated intrusion detection and prevention mechanism in network controlled systems},
author = {Khamsa Farah and Karim Chabir and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145026629\&doi=10.1049%2fcmu2.12557\&partnerID=40\&md5=3c38f15a52eaa975737ba76f5ad4a96e},
doi = {10.1049/cmu2.12557},
year = {2023},
date = {2023-01-01},
journal = {IET Communications},
volume = {17},
number = {4},
pages = {469 \textendash 477},
note = {Cited by: 0; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Ghabri, Haifa; Fathallah, Wyssem; Hamroun, Mohamed; Othman, Soufiene Ben; Bellali, Hedia; Sakli, Hedi; Abdelkrim, Mohamed Naceur AI-enhanced thyroid detection using YOLO to empower healthcare professionals Conférence vol. 13, no. 1, 2023, (Cited by: 0). @conference{Ghabri2023,
title = {AI-enhanced thyroid detection using YOLO to empower healthcare professionals},
author = {Haifa Ghabri and Wyssem Fathallah and Mohamed Hamroun and Soufiene Ben Othman and Hedia Bellali and Hedi Sakli and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182950474\&doi=10.1109%2fIW_MSS59200.2023.10369271\&partnerID=40\&md5=67e47b260997d2d01a4a6b578d9d3e3e},
doi = {10.1109/IW_MSS59200.2023.10369271},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
volume = {13},
number = {1},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Farah, Khamsa; Chabir, Karim; Abdelkrim, Mohamed Naceur High level petri nets modeling of advanced vehicle control Conférence 2023. @conference{Farah2023,
title = {High level petri nets modeling of advanced vehicle control},
author = {Khamsa Farah and Karim Chabir and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182941638\&doi=10.1109%2fIW_MSS59200.2023.10368635\&partnerID=40\&md5=0160db61a1a1c9bab0e8612c6871cc80},
doi = {10.1109/IW_MSS59200.2023.10368635},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Yahia, Samah; Salem, Yassine Ben; Abdelkrim, Mohamed Naceur A new approach for monitoring disease progression in Multiple Sclerosis Lesions using 3D Magnetic Brain Image Conférence 2023. @conference{Yahia2023,
title = {A new approach for monitoring disease progression in Multiple Sclerosis Lesions using 3D Magnetic Brain Image},
author = {Samah Yahia and Yassine Ben Salem and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182934544\&doi=10.1109%2fIW_MSS59200.2023.10368989\&partnerID=40\&md5=1db63676e6dd4ef5f174eddba821b57a},
doi = {10.1109/IW_MSS59200.2023.10368989},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Saada, Fadwa; Delouche, David; Chabir, Karim; Abdelkrim, Mohamed Naceur Comparative Analysis of DIDIM and IV Approaches using Double Least Squares Method Article de journal Dans: International Journal of Advanced Computer Science and Applications, vol. 14, no. 6, p. 788 – 796, 2023, (Cited by: 0; All Open Access, Gold Open Access). @article{Saada2023788,
title = {Comparative Analysis of DIDIM and IV Approaches using Double Least Squares Method},
author = {Fadwa Saada and David Delouche and Karim Chabir and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85165079578\&doi=10.14569%2fIJACSA.2023.0140684\&partnerID=40\&md5=b8d0dd29ee45ad9db274d0049bc9fceb},
doi = {10.14569/IJACSA.2023.0140684},
year = {2023},
date = {2023-01-01},
journal = {International Journal of Advanced Computer Science and Applications},
volume = {14},
number = {6},
pages = {788 \textendash 796},
note = {Cited by: 0; All Open Access, Gold Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Salem, Mariem Hadj; Bensalem, Yemna; Mansouri, Karim; Cauveau, Eric; Abdelkrim, Mohamed Naceur Polynomial battery control for photovoltaic systems Conférence 2023. @conference{Salem2023,
title = {Polynomial battery control for photovoltaic systems},
author = {Mariem Hadj Salem and Yemna Bensalem and Karim Mansouri and Eric Cauveau and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182930683\&doi=10.1109%2fIW_MSS59200.2023.10368884\&partnerID=40\&md5=d68fe8a5febb247a3a2be00007689a5d},
doi = {10.1109/IW_MSS59200.2023.10368884},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Kilani, Rim; Zouinkhi, Ahmed; Abdelkrim, Mohamed Naceur Monetization of Industrial IoT services using Blockchain and smart contract Conférence 2023. @conference{Kilani2023,
title = {Monetization of Industrial IoT services using Blockchain and smart contract},
author = {Rim Kilani and Ahmed Zouinkhi and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182931639\&doi=10.1109%2fIW_MSS59200.2023.10369375\&partnerID=40\&md5=68c38f57ca41b931bd0bec20a45124e4},
doi = {10.1109/IW_MSS59200.2023.10369375},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Mhamdi, Halima; Zouinkhi, Ahmed; Abdelkrim, Mohamed Naceur A Brief Overview of Blockchain Technology and Access Control in IoT Conférence 2023. @conference{Mhamdi2023,
title = {A Brief Overview of Blockchain Technology and Access Control in IoT},
author = {Halima Mhamdi and Ahmed Zouinkhi and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182931642\&doi=10.1109%2fIW_MSS59200.2023.10369788\&partnerID=40\&md5=84147ee67dd8fe576c7ea7ecac0adc04},
doi = {10.1109/IW_MSS59200.2023.10369788},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Benjemaa, Rabeb; Elhsoumi, Aicha; Abdelkrim, Mohamed Naceur State feedback control for LPV neutral time delay descriptor systems Conférence 2023. @conference{Benjemaa2023,
title = {State feedback control for LPV neutral time delay descriptor systems},
author = {Rabeb Benjemaa and Aicha Elhsoumi and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182928110\&doi=10.1109%2fIW_MSS59200.2023.10369343\&partnerID=40\&md5=a2e529e1caf90174007d9e29e5c7536a},
doi = {10.1109/IW_MSS59200.2023.10369343},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Salem, Mariem Hadj; Mansouri, Karim; Cauveau, Eric; Bensalem, Yemna; Abdelkrim, Mohamed Naceur Simulation of an Energy Management System and Control in a Multi-Source System Conférence 2023. @conference{HadjSalem2023,
title = {Simulation of an Energy Management System and Control in a Multi-Source System},
author = {Mariem Hadj Salem and Karim Mansouri and Eric Cauveau and Yemna Bensalem and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182917541\&doi=10.1109%2fIW_MSS59200.2023.10368935\&partnerID=40\&md5=147cd5876aa69b5aac36691ce4a8276e},
doi = {10.1109/IW_MSS59200.2023.10368935},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Saada, Fadwa; Chabir, Karim; Abdelkrim, Mohamed Naceur Examining DIDIM and IV Approaches through the Double Least Squares Method for Comparative Assessment Conférence 2023. @conference{Saada2023,
title = {Examining DIDIM and IV Approaches through the Double Least Squares Method for Comparative Assessment},
author = {Fadwa Saada and Karim Chabir and Mohamed Naceur Abdelkrim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182941796\&doi=10.1109%2fIW_MSS59200.2023.10369269\&partnerID=40\&md5=3b2e0c922b926ee775dfe3a963844772},
doi = {10.1109/IW_MSS59200.2023.10369269},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Mizouri, Hanin; Lamouchi, Rihab; Amairi, Messaoud Functional Interval Estimation for Uncertain Continuous-time Linear Parameter-Varying Multivariable Systems Conférence 2023. @conference{Mizouri2023,
title = {Functional Interval Estimation for Uncertain Continuous-time Linear Parameter-Varying Multivariable Systems},
author = {Hanin Mizouri and Rihab Lamouchi and Messaoud Amairi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182948352\&doi=10.1109%2fIW_MSS59200.2023.10369308\&partnerID=40\&md5=22538226eb9d2307c12e8b4aa894a2d4},
doi = {10.1109/IW_MSS59200.2023.10369308},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Lamouchi, Rihab; Akremi, Rihab; Amairi, Messaoud Functional Interval Observers Design for Linear Discrete-time Switched Systems Conférence 2023. @conference{Lamouchi2023,
title = {Functional Interval Observers Design for Linear Discrete-time Switched Systems},
author = {Rihab Lamouchi and Rihab Akremi and Messaoud Amairi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182941782\&doi=10.1109%2fIW_MSS59200.2023.10368636\&partnerID=40\&md5=d0650ec23ad255545a38e2df04ebd53e},
doi = {10.1109/IW_MSS59200.2023.10368636},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Mizouri, Hanin; Lamouchi, Rihab; Amairi, Messaoud L∞-Functional Interval Observers for Continuous-time Linear Parameter-Varying Multivariable Systems Conférence 2023, (Cited by: 0). @conference{Mizouri2023434,
title = {L∞-Functional Interval Observers for Continuous-time Linear Parameter-Varying Multivariable Systems},
author = {Hanin Mizouri and Rihab Lamouchi and Messaoud Amairi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167802741\&doi=10.1109%2fMED59994.2023.10185821\&partnerID=40\&md5=bedeb166743e9bb0e95812ae4b62239b},
doi = {10.1109/MED59994.2023.10185821},
year = {2023},
date = {2023-01-01},
journal = {2023 31st Mediterranean Conference on Control and Automation, MED 2023},
pages = {434 \textendash 439},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Moussa, Noura Ben; Chetoui, Manel; Amairi, Messaoud Fractional PID controllers tuned by Particle Swarm Optimization for Multi-Input-Single-Output systems control Conférence 2023. @conference{BenMoussa2023,
title = {Fractional PID controllers tuned by Particle Swarm Optimization for Multi-Input-Single-Output systems control},
author = {Noura Ben Moussa and Manel Chetoui and Messaoud Amairi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182929784\&doi=10.1109%2fIW_MSS59200.2023.10369692\&partnerID=40\&md5=f91c08bd3fce6c58d621708928e29cc3},
doi = {10.1109/IW_MSS59200.2023.10369692},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
|
Akremi, Rihab; Lamouchi, Rihab; Amairi, Messaoud; Dinh, Thach Ngoc; Raïssi, Tarek Functional interval observer design for multivariable linear parameter-varying systems Article de journal Dans: European Journal of Control, vol. 71, 2023, (Cited by: 1). @article{Akremi2023,
title = {Functional interval observer design for multivariable linear parameter-varying systems},
author = {Rihab Akremi and Rihab Lamouchi and Messaoud Amairi and Thach Ngoc Dinh and Tarek Ra\"{i}ssi},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85150867910\&doi=10.1016%2fj.ejcon.2023.100794\&partnerID=40\&md5=3e5eb3fa12a82a2fa717e52447d1be5e},
doi = {10.1016/j.ejcon.2023.100794},
year = {2023},
date = {2023-01-01},
journal = {European Journal of Control},
volume = {71},
note = {Cited by: 1},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Saafi, Omar; Dabbaghi, Boudour; Hamidi, Faical; Aoun, Mohamed Particle swarm optimization-based solutions for identification problems of autonomous hybrid switching systems Conférence 2023. @conference{Saafi2023b,
title = {Particle swarm optimization-based solutions for identification problems of autonomous hybrid switching systems},
author = {Omar Saafi and Boudour Dabbaghi and Faical Hamidi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182924528\&doi=10.1109%2fIW_MSS59200.2023.10369212\&partnerID=40\&md5=100bf547f598cc0f36cc7adc5d8c3fa0},
doi = {10.1109/IW_MSS59200.2023.10369212},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {In this paper we propose a new optimization technique based on an evolutionary method known as particle swarm optimization (PSO) for solving and specifying the switching instants of hybrid systems. The main objective is to minimize a performance measure that depends on these switching instants within a finite time interval. Our approach assumes that there is a predefined sequence of system modes and, at each switching instant, it is possible for a state-space variable to jump from one mode to another, resulting in an additional associated cost. Our approach is justified by numerical examples and compared with the results obtained by gradient-based methods. The results obtained by PSO are very promising, without requiring any a priori assumptions about the regularity of the objective function to be minimized. © 2023 IEEE.},
keywords = {Autonomous switching sequence, Hybrid switched systems, Hybrid switching systems, Hybrid systems, Identification problem, Numerical methods, Optimization techniques, Particle swarm, Particle swarm optimization, Particle swarm optimization (PSO), Swarm optimization, Switching instants, Switching sequence},
pubstate = {published},
tppubtype = {conference}
}
In this paper we propose a new optimization technique based on an evolutionary method known as particle swarm optimization (PSO) for solving and specifying the switching instants of hybrid systems. The main objective is to minimize a performance measure that depends on these switching instants within a finite time interval. Our approach assumes that there is a predefined sequence of system modes and, at each switching instant, it is possible for a state-space variable to jump from one mode to another, resulting in an additional associated cost. Our approach is justified by numerical examples and compared with the results obtained by gradient-based methods. The results obtained by PSO are very promising, without requiring any a priori assumptions about the regularity of the objective function to be minimized. © 2023 IEEE. |
Ounis, Walid; Chetoui, Manel; Najar, Salheddine; Aoun, Mohamed Programmable analogue fractional controller realization Conférence 2023. @conference{Ounis2023b,
title = {Programmable analogue fractional controller realization},
author = {Walid Ounis and Manel Chetoui and Salheddine Najar and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182938982\&doi=10.1109%2fIW_MSS59200.2023.10369104\&partnerID=40\&md5=be9f5355e8c0ceea37f41ef5482c9ee6},
doi = {10.1109/IW_MSS59200.2023.10369104},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {A fractional-order controller is an infinite-memory system. It is described by a continuous time irrational transfer function. Its realization is a delicate problem especially when its parameters are real time tunable. This paper presents a real-time programmable analogue fractional controller implementation. The controller is based on a sum of a novel real-time programmable analogue first-order low-pass filter. The signal within the circuit remains analogue and is not converted into discrete values. Real-time adjustments are made using digital potentiometers and operational amplifiers. The proposed first-order low-pass filter offers several advantages. In particular, the time constant and DC gain are independently adjusted without relying on the ohmic value of digital potentiometers. The time constant and DC gain depend on the resolution of the digital potentiometers. The high resolution of the digital potentiometer enables the circuit to achieve a wide bandwidth and allows for the use of small capacitors at lower frequencies. The proposed real-time programmable analogue fractional controller is experimented to achieve a fractional integrator. The circuit yields good similarity between theoretical simulations and experimental measurements. © 2023 IEEE.},
keywords = {Analog circuits, Continuous time systems, Controllers, Digital potentiometer, First order, First order low-pass filter, Fractional integrators, Fractional-order controllers, Higher order dynamics systems, Low pass filters, Low-pass filters, Operational amplifiers, Potentiometers (electric measuring instruments), Programmable analog circuit, Programmable analogs, Real- time, Signal processing, Timing circuits},
pubstate = {published},
tppubtype = {conference}
}
A fractional-order controller is an infinite-memory system. It is described by a continuous time irrational transfer function. Its realization is a delicate problem especially when its parameters are real time tunable. This paper presents a real-time programmable analogue fractional controller implementation. The controller is based on a sum of a novel real-time programmable analogue first-order low-pass filter. The signal within the circuit remains analogue and is not converted into discrete values. Real-time adjustments are made using digital potentiometers and operational amplifiers. The proposed first-order low-pass filter offers several advantages. In particular, the time constant and DC gain are independently adjusted without relying on the ohmic value of digital potentiometers. The time constant and DC gain depend on the resolution of the digital potentiometers. The high resolution of the digital potentiometer enables the circuit to achieve a wide bandwidth and allows for the use of small capacitors at lower frequencies. The proposed real-time programmable analogue fractional controller is experimented to achieve a fractional integrator. The circuit yields good similarity between theoretical simulations and experimental measurements. © 2023 IEEE. |
Aloui, Messaoud; Hamidi, Faical; Jerbi, Houssem; Aoun, Mohamed Estimating and enlarging the domain of attraction for polynomial systems using a deep learning tool Conférence 2023. @conference{Aloui2023b,
title = {Estimating and enlarging the domain of attraction for polynomial systems using a deep learning tool},
author = {Messaoud Aloui and Faical Hamidi and Houssem Jerbi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182927297\&doi=10.1109%2fIW_MSS59200.2023.10369522\&partnerID=40\&md5=244fee6b04ee656e55d354fe1fac648e},
doi = {10.1109/IW_MSS59200.2023.10369522},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {This Paper deals with the topic of non linear polynomial systems. It explains a way to estimate and enlarge the region of attraction of nonlinear polynomial systems. It provides a deep learning method for estimating the domain of attraction and uses the Particle Swarm Optimization Algorithm to enlarge this domain. Based on an analytic method found in literature, a dataset is generated, used then to train an artificial neural network, which will be an objective function of an optimization algorithm. This method dives an imitation to a previous complicated method, with less complexity and les elapsed time. The benchmark examples show the efficiency of the method and compare results with those obtained with the one using linear matrix inequalities. © 2023 IEEE.},
keywords = {Deep learning, Domain of attraction, Learning systems, Learning tool, Linear matrix inequalities, Linear polynomials, Lyapunov functions, Lyapunov's functions, Neural networks, Non linear, Particle swarm, Particle swarm optimization, Particle swarm optimization (PSO), Polynomial systems, Polynomials, Swarm intelligence, Swarm optimization},
pubstate = {published},
tppubtype = {conference}
}
This Paper deals with the topic of non linear polynomial systems. It explains a way to estimate and enlarge the region of attraction of nonlinear polynomial systems. It provides a deep learning method for estimating the domain of attraction and uses the Particle Swarm Optimization Algorithm to enlarge this domain. Based on an analytic method found in literature, a dataset is generated, used then to train an artificial neural network, which will be an objective function of an optimization algorithm. This method dives an imitation to a previous complicated method, with less complexity and les elapsed time. The benchmark examples show the efficiency of the method and compare results with those obtained with the one using linear matrix inequalities. © 2023 IEEE. |
Dabbaghi, Boudour; Hamidi, Faical; Jerbi, Houssem; Aoun, Mohamed Estimating and enlarging the domain of attraction for a nonlinear system with input saturation Conférence 2023. @conference{Dabbaghi2023b,
title = {Estimating and enlarging the domain of attraction for a nonlinear system with input saturation},
author = {Boudour Dabbaghi and Faical Hamidi and Houssem Jerbi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182924575\&doi=10.1109%2fIW_MSS59200.2023.10368596\&partnerID=40\&md5=672e47539c960bce9ba5743f75dc5c50},
doi = {10.1109/IW_MSS59200.2023.10368596},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {This paper focuses on the stabilization problem of a nonlinear system subject to actuator saturation. Such that the results are based on the differential algebraic representation and use of a convex hull description subject to the saturation effects. The contribution of this work is to estimate enlarging domain of attraction. Therefore, for find the largess domain of attraction, the block matrix-variable will be chosen. Numerical examples are provided to illustrate the efficiency of this new approach. © 2023 IEEE.},
keywords = {Actuator saturations, Algebra, Algebraic representations, Computational geometry, Convex hull, Differential algebraic, Differential algebraic representation, Domain of attraction, Input saturation, Nonlinear, Nonlinear systems, Stabilization problems},
pubstate = {published},
tppubtype = {conference}
}
This paper focuses on the stabilization problem of a nonlinear system subject to actuator saturation. Such that the results are based on the differential algebraic representation and use of a convex hull description subject to the saturation effects. The contribution of this work is to estimate enlarging domain of attraction. Therefore, for find the largess domain of attraction, the block matrix-variable will be chosen. Numerical examples are provided to illustrate the efficiency of this new approach. © 2023 IEEE. |
Ethabet, Haifa; Dadi, Leila; Raissi, Tarek; Aoun, Mohamed L∞ Set-membership Estimation for Continuous-time Switched Linear Systems Conférence 2023. @conference{Ethabet2023b,
title = {L∞ Set-membership Estimation for Continuous-time Switched Linear Systems},
author = {Haifa Ethabet and Leila Dadi and Tarek Raissi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182931405\&doi=10.1109%2fIW_MSS59200.2023.10369668\&partnerID=40\&md5=2fb780affae1b8628f3f526c9cabfef7},
doi = {10.1109/IW_MSS59200.2023.10369668},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {In this work, we focuses on the problem of designing an interval state estimation for continuous-time Switched Linear Systems (SLS) in the Unknown But Bounded Error (UBBE) context. To do so, we design a new structure of interval observers by introducing weighted matrices not only to give more degrees of design freedom but also to attenuate the conservatism caused by uncertainties. Observer gains are derived from the solution of Linear Matrix Inequalities (LMIs), based on the use of a common Lyapunov function, to ensure cooperativity and stability. An L∞ technique is then introduced to compensate the measurement noise and disturbances' effects and to enhance the precision of interval estimation. Finally, numerical simulations are given, evaluating the proposed methodology and demonstrating its effectiveness. © 2023 IEEE.},
keywords = {Bounded error context, Continous time, Continuous time systems, Continuous-time switched system, Interval observers, Linear matrix inequalities, Linear systems, Lyapunov functions, L∞ technique, matrix, Set-membership estimation, State estimation, Switched linear system, Switched system, Unknown but bounded},
pubstate = {published},
tppubtype = {conference}
}
In this work, we focuses on the problem of designing an interval state estimation for continuous-time Switched Linear Systems (SLS) in the Unknown But Bounded Error (UBBE) context. To do so, we design a new structure of interval observers by introducing weighted matrices not only to give more degrees of design freedom but also to attenuate the conservatism caused by uncertainties. Observer gains are derived from the solution of Linear Matrix Inequalities (LMIs), based on the use of a common Lyapunov function, to ensure cooperativity and stability. An L∞ technique is then introduced to compensate the measurement noise and disturbances’ effects and to enhance the precision of interval estimation. Finally, numerical simulations are given, evaluating the proposed methodology and demonstrating its effectiveness. © 2023 IEEE. |
Chetoui, Manel; Aoun, Mohamed Fourth-order cumulants based-least squares methods for fractional Multiple-Input-Single-Output Errors-In-Variables system identification Article de journal Dans: Fractional Calculus and Applied Analysis, vol. 26, no. 4, p. 1868 – 1893, 2023, (Cited by: 0). @article{Chetoui20231868b,
title = {Fourth-order cumulants based-least squares methods for fractional Multiple-Input-Single-Output Errors-In-Variables system identification},
author = {Manel Chetoui and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162025508\&doi=10.1007%2fs13540-023-00174-z\&partnerID=40\&md5=e432a1b99e5eefa5d83aa9d25a97537f},
doi = {10.1007/s13540-023-00174-z},
year = {2023},
date = {2023-01-01},
journal = {Fractional Calculus and Applied Analysis},
volume = {26},
number = {4},
pages = {1868 \textendash 1893},
abstract = {This paper presents new consistent methods for continuous-time Multiple-Input-Single-Output (MISO) Errors-In-Variables (EIV) systems by fractional models. The proposed idea is to use Higher-Order Statistics (HOS), such as fourth-order cumulants (foc), instead of noisy input and output measurements to obtain unbiased estimates. Firstly, all differentiation orders are assumed to be known a priori and linear coefficients are estimated. The developed estimator is based on minimizing the equation error and it is called fractional fourth-order based-least squares estimator (frac- foc- ls). Secondly, the global commensurability of the fractional MISO system is considered. The frac- foc- ls is combined with a non linear technique to estimate the global commensurate order along with linear coefficients. The developed algorithm is based on minimizing the output error and called fractional fourth-order cumulants based-least squares combined with global commensurate order optimization (frac- foc- gcools). The consistency of the developed estimators, in presence of high levels of noise corrupting both the input and output measurements, is assessed through a numerical example with the help of Monte Carlo simulations. © 2023, Diogenes Co.Ltd.},
note = {Cited by: 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents new consistent methods for continuous-time Multiple-Input-Single-Output (MISO) Errors-In-Variables (EIV) systems by fractional models. The proposed idea is to use Higher-Order Statistics (HOS), such as fourth-order cumulants (foc), instead of noisy input and output measurements to obtain unbiased estimates. Firstly, all differentiation orders are assumed to be known a priori and linear coefficients are estimated. The developed estimator is based on minimizing the equation error and it is called fractional fourth-order based-least squares estimator (frac- foc- ls). Secondly, the global commensurability of the fractional MISO system is considered. The frac- foc- ls is combined with a non linear technique to estimate the global commensurate order along with linear coefficients. The developed algorithm is based on minimizing the output error and called fractional fourth-order cumulants based-least squares combined with global commensurate order optimization (frac- foc- gcools). The consistency of the developed estimators, in presence of high levels of noise corrupting both the input and output measurements, is assessed through a numerical example with the help of Monte Carlo simulations. © 2023, Diogenes Co.Ltd. |
Jlidi, Mokhtar; Hamidi, Faiçal; Barambones, Oscar; Abbassi, Rabeh; Jerbi, Houssem; Aoun, Mohamed; Karami-Mollaee, Ali An Artificial Neural Network for Solar Energy Prediction and Control Using Jaya-SMC Article de journal Dans: Electronics (Switzerland), vol. 12, no. 3, 2023, (Cited by: 2; All Open Access, Gold Open Access, Green Open Access). @article{Jlidi2023b,
title = {An Artificial Neural Network for Solar Energy Prediction and Control Using Jaya-SMC},
author = {Mokhtar Jlidi and Fai\c{c}al Hamidi and Oscar Barambones and Rabeh Abbassi and Houssem Jerbi and Mohamed Aoun and Ali Karami-Mollaee},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147810422\&doi=10.3390%2felectronics12030592\&partnerID=40\&md5=9a904af7a421f01ee1b834ef748dcce0},
doi = {10.3390/electronics12030592},
year = {2023},
date = {2023-01-01},
journal = {Electronics (Switzerland)},
volume = {12},
number = {3},
abstract = {In recent years, researchers have focused on improving the efficiency of photovoltaic systems, as they have an extremely low efficiency compared to fossil fuels. An obvious issue associated with photovoltaic systems (PVS) is the interruption of power generation caused by changes in solar radiation and temperature. As a means of improving the energy efficiency performance of such a system, it is necessary to predict the meteorological conditions that affect PV modules. As part of the proposed research, artificial neural networks (ANNs) will be used for the purpose of predicting the PV system’s current and voltage by predicting the PV system’s operating temperature and radiation, as well as using JAYA-SMC hybrid control in the search for the MPP and duty cycle single-ended primary-inductor converter (SEPIC) that supplies a DC motor. Data sets of size 60538 were used to predict temperature and solar radiation. The data set had been collected from the Department of Systems Engineering and Automation at the Vitoria School of Engineering of the University of the Basque Country. Analyses and numerical simulations showed that the technique was highly effective. In combination with JAYA-SMC hybrid control, the proposed method enabled an accurate estimation of maximum power and robustness with reasonable generality and accuracy (regression (R) = 0.971, mean squared error (MSE) = 0.003). Consequently, this study provides support for energy monitoring and control. © 2023 by the authors.},
note = {Cited by: 2; All Open Access, Gold Open Access, Green Open Access},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In recent years, researchers have focused on improving the efficiency of photovoltaic systems, as they have an extremely low efficiency compared to fossil fuels. An obvious issue associated with photovoltaic systems (PVS) is the interruption of power generation caused by changes in solar radiation and temperature. As a means of improving the energy efficiency performance of such a system, it is necessary to predict the meteorological conditions that affect PV modules. As part of the proposed research, artificial neural networks (ANNs) will be used for the purpose of predicting the PV system’s current and voltage by predicting the PV system’s operating temperature and radiation, as well as using JAYA-SMC hybrid control in the search for the MPP and duty cycle single-ended primary-inductor converter (SEPIC) that supplies a DC motor. Data sets of size 60538 were used to predict temperature and solar radiation. The data set had been collected from the Department of Systems Engineering and Automation at the Vitoria School of Engineering of the University of the Basque Country. Analyses and numerical simulations showed that the technique was highly effective. In combination with JAYA-SMC hybrid control, the proposed method enabled an accurate estimation of maximum power and robustness with reasonable generality and accuracy (regression (R) = 0.971, mean squared error (MSE) = 0.003). Consequently, this study provides support for energy monitoring and control. © 2023 by the authors. |
Saafi, Omar; Dabbaghi, Boudour; Hamidi, Faical; Aoun, Mohamed Particle swarm optimization-based solutions for identification problems of autonomous hybrid switching systems Conférence 2023. @conference{Saafi2023,
title = {Particle swarm optimization-based solutions for identification problems of autonomous hybrid switching systems},
author = {Omar Saafi and Boudour Dabbaghi and Faical Hamidi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182924528\&doi=10.1109%2fIW_MSS59200.2023.10369212\&partnerID=40\&md5=100bf547f598cc0f36cc7adc5d8c3fa0},
doi = {10.1109/IW_MSS59200.2023.10369212},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {In this paper we propose a new optimization technique based on an evolutionary method known as particle swarm optimization (PSO) for solving and specifying the switching instants of hybrid systems. The main objective is to minimize a performance measure that depends on these switching instants within a finite time interval. Our approach assumes that there is a predefined sequence of system modes and, at each switching instant, it is possible for a state-space variable to jump from one mode to another, resulting in an additional associated cost. Our approach is justified by numerical examples and compared with the results obtained by gradient-based methods. The results obtained by PSO are very promising, without requiring any a priori assumptions about the regularity of the objective function to be minimized. © 2023 IEEE.},
keywords = {Autonomous switching sequence, Hybrid switched systems, Hybrid switching systems, Hybrid systems, Identification problem, Numerical methods, Optimization techniques, Particle swarm, Particle swarm optimization, Particle swarm optimization (PSO), Swarm optimization, Switching instants, Switching sequence},
pubstate = {published},
tppubtype = {conference}
}
In this paper we propose a new optimization technique based on an evolutionary method known as particle swarm optimization (PSO) for solving and specifying the switching instants of hybrid systems. The main objective is to minimize a performance measure that depends on these switching instants within a finite time interval. Our approach assumes that there is a predefined sequence of system modes and, at each switching instant, it is possible for a state-space variable to jump from one mode to another, resulting in an additional associated cost. Our approach is justified by numerical examples and compared with the results obtained by gradient-based methods. The results obtained by PSO are very promising, without requiring any a priori assumptions about the regularity of the objective function to be minimized. © 2023 IEEE. |
Ounis, Walid; Chetoui, Manel; Najar, Salheddine; Aoun, Mohamed Programmable analogue fractional controller realization Conférence 2023. @conference{Ounis2023,
title = {Programmable analogue fractional controller realization},
author = {Walid Ounis and Manel Chetoui and Salheddine Najar and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182938982\&doi=10.1109%2fIW_MSS59200.2023.10369104\&partnerID=40\&md5=be9f5355e8c0ceea37f41ef5482c9ee6},
doi = {10.1109/IW_MSS59200.2023.10369104},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {A fractional-order controller is an infinite-memory system. It is described by a continuous time irrational transfer function. Its realization is a delicate problem especially when its parameters are real time tunable. This paper presents a real-time programmable analogue fractional controller implementation. The controller is based on a sum of a novel real-time programmable analogue first-order low-pass filter. The signal within the circuit remains analogue and is not converted into discrete values. Real-time adjustments are made using digital potentiometers and operational amplifiers. The proposed first-order low-pass filter offers several advantages. In particular, the time constant and DC gain are independently adjusted without relying on the ohmic value of digital potentiometers. The time constant and DC gain depend on the resolution of the digital potentiometers. The high resolution of the digital potentiometer enables the circuit to achieve a wide bandwidth and allows for the use of small capacitors at lower frequencies. The proposed real-time programmable analogue fractional controller is experimented to achieve a fractional integrator. The circuit yields good similarity between theoretical simulations and experimental measurements. © 2023 IEEE.},
keywords = {Analog circuits, Continuous time systems, Controllers, Digital potentiometer, First order, First order low-pass filter, Fractional integrators, Fractional-order controllers, Higher order dynamics systems, Low pass filters, Low-pass filters, Operational amplifiers, Potentiometers (electric measuring instruments), Programmable analog circuit, Programmable analogs, Real- time, Signal processing, Timing circuits},
pubstate = {published},
tppubtype = {conference}
}
A fractional-order controller is an infinite-memory system. It is described by a continuous time irrational transfer function. Its realization is a delicate problem especially when its parameters are real time tunable. This paper presents a real-time programmable analogue fractional controller implementation. The controller is based on a sum of a novel real-time programmable analogue first-order low-pass filter. The signal within the circuit remains analogue and is not converted into discrete values. Real-time adjustments are made using digital potentiometers and operational amplifiers. The proposed first-order low-pass filter offers several advantages. In particular, the time constant and DC gain are independently adjusted without relying on the ohmic value of digital potentiometers. The time constant and DC gain depend on the resolution of the digital potentiometers. The high resolution of the digital potentiometer enables the circuit to achieve a wide bandwidth and allows for the use of small capacitors at lower frequencies. The proposed real-time programmable analogue fractional controller is experimented to achieve a fractional integrator. The circuit yields good similarity between theoretical simulations and experimental measurements. © 2023 IEEE. |
Aloui, Messaoud; Hamidi, Faical; Jerbi, Houssem; Aoun, Mohamed Estimating and enlarging the domain of attraction for polynomial systems using a deep learning tool Conférence 2023. @conference{Aloui2023,
title = {Estimating and enlarging the domain of attraction for polynomial systems using a deep learning tool},
author = {Messaoud Aloui and Faical Hamidi and Houssem Jerbi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182927297\&doi=10.1109%2fIW_MSS59200.2023.10369522\&partnerID=40\&md5=244fee6b04ee656e55d354fe1fac648e},
doi = {10.1109/IW_MSS59200.2023.10369522},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {This Paper deals with the topic of non linear polynomial systems. It explains a way to estimate and enlarge the region of attraction of nonlinear polynomial systems. It provides a deep learning method for estimating the domain of attraction and uses the Particle Swarm Optimization Algorithm to enlarge this domain. Based on an analytic method found in literature, a dataset is generated, used then to train an artificial neural network, which will be an objective function of an optimization algorithm. This method dives an imitation to a previous complicated method, with less complexity and les elapsed time. The benchmark examples show the efficiency of the method and compare results with those obtained with the one using linear matrix inequalities. © 2023 IEEE.},
keywords = {Deep learning, Domain of attraction, Learning systems, Learning tool, Linear matrix inequalities, Linear polynomials, Lyapunov functions, Lyapunov's functions, Neural networks, Non linear, Particle swarm, Particle swarm optimization, Particle swarm optimization (PSO), Polynomial systems, Polynomials, Swarm intelligence, Swarm optimization},
pubstate = {published},
tppubtype = {conference}
}
This Paper deals with the topic of non linear polynomial systems. It explains a way to estimate and enlarge the region of attraction of nonlinear polynomial systems. It provides a deep learning method for estimating the domain of attraction and uses the Particle Swarm Optimization Algorithm to enlarge this domain. Based on an analytic method found in literature, a dataset is generated, used then to train an artificial neural network, which will be an objective function of an optimization algorithm. This method dives an imitation to a previous complicated method, with less complexity and les elapsed time. The benchmark examples show the efficiency of the method and compare results with those obtained with the one using linear matrix inequalities. © 2023 IEEE. |
Dabbaghi, Boudour; Hamidi, Faical; Jerbi, Houssem; Aoun, Mohamed Estimating and enlarging the domain of attraction for a nonlinear system with input saturation Conférence 2023. @conference{Dabbaghi2023,
title = {Estimating and enlarging the domain of attraction for a nonlinear system with input saturation},
author = {Boudour Dabbaghi and Faical Hamidi and Houssem Jerbi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182924575\&doi=10.1109%2fIW_MSS59200.2023.10368596\&partnerID=40\&md5=672e47539c960bce9ba5743f75dc5c50},
doi = {10.1109/IW_MSS59200.2023.10368596},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {This paper focuses on the stabilization problem of a nonlinear system subject to actuator saturation. Such that the results are based on the differential algebraic representation and use of a convex hull description subject to the saturation effects. The contribution of this work is to estimate enlarging domain of attraction. Therefore, for find the largess domain of attraction, the block matrix-variable will be chosen. Numerical examples are provided to illustrate the efficiency of this new approach. © 2023 IEEE.},
keywords = {Actuator saturations, Algebra, Algebraic representations, Computational geometry, Convex hull, Differential algebraic, Differential algebraic representation, Domain of attraction, Input saturation, Nonlinear, Nonlinear systems, Stabilization problems},
pubstate = {published},
tppubtype = {conference}
}
This paper focuses on the stabilization problem of a nonlinear system subject to actuator saturation. Such that the results are based on the differential algebraic representation and use of a convex hull description subject to the saturation effects. The contribution of this work is to estimate enlarging domain of attraction. Therefore, for find the largess domain of attraction, the block matrix-variable will be chosen. Numerical examples are provided to illustrate the efficiency of this new approach. © 2023 IEEE. |
Ethabet, Haifa; Dadi, Leila; Raissi, Tarek; Aoun, Mohamed L∞ Set-membership Estimation for Continuous-time Switched Linear Systems Conférence 2023. @conference{Ethabet2023,
title = {L∞ Set-membership Estimation for Continuous-time Switched Linear Systems},
author = {Haifa Ethabet and Leila Dadi and Tarek Raissi and Mohamed Aoun},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182931405\&doi=10.1109%2fIW_MSS59200.2023.10369668\&partnerID=40\&md5=2fb780affae1b8628f3f526c9cabfef7},
doi = {10.1109/IW_MSS59200.2023.10369668},
year = {2023},
date = {2023-01-01},
journal = {2023 IEEE International Workshop on Mechatronics Systems Supervision, IW_MSS 2023},
abstract = {In this work, we focuses on the problem of designing an interval state estimation for continuous-time Switched Linear Systems (SLS) in the Unknown But Bounded Error (UBBE) context. To do so, we design a new structure of interval observers by introducing weighted matrices not only to give more degrees of design freedom but also to attenuate the conservatism caused by uncertainties. Observer gains are derived from the solution of Linear Matrix Inequalities (LMIs), based on the use of a common Lyapunov function, to ensure cooperativity and stability. An L∞ technique is then introduced to compensate the measurement noise and disturbances' effects and to enhance the precision of interval estimation. Finally, numerical simulations are given, evaluating the proposed methodology and demonstrating its effectiveness. © 2023 IEEE.},
keywords = {Bounded error context, Continous time, Continuous time systems, Continuous-time switched system, Interval observers, Linear matrix inequalities, Linear systems, Lyapunov functions, L∞ technique, matrix, Set-membership estimation, State estimation, Switched linear system, Switched system, Unknown but bounded},
pubstate = {published},
tppubtype = {conference}
}
In this work, we focuses on the problem of designing an interval state estimation for continuous-time Switched Linear Systems (SLS) in the Unknown But Bounded Error (UBBE) context. To do so, we design a new structure of interval observers by introducing weighted matrices not only to give more degrees of design freedom but also to attenuate the conservatism caused by uncertainties. Observer gains are derived from the solution of Linear Matrix Inequalities (LMIs), based on the use of a common Lyapunov function, to ensure cooperativity and stability. An L∞ technique is then introduced to compensate the measurement noise and disturbances’ effects and to enhance the precision of interval estimation. Finally, numerical simulations are given, evaluating the proposed methodology and demonstrating its effectiveness. © 2023 IEEE. |