@article {7202,
	title = {Tifinagh Handwriting Character Recognition Using a CNN Provided as a Web Service},
	journal = {International Journal of Cloud Applications and Computing (IJCAC) },
	volume = {12},
	number = {1},
	year = {2022},
	abstract = {
	Many cloud providers offer very high precision services to exploit Optical Character Recognition (OCR). However, there is no provider offers Tifinagh Optical Character Recognition (OCR) as Web Services. Several works have been proposed to build powerful Tifinagh OCR. Unfortunately, there is no one developed as a Web Service. In this paper, we present a new architecture of Tifinagh Handwriting Recognition as a web service based on a deep learning model via Google Colab. For the implementation of our proposal, we used the new version of the TensorFlow library and a very large database of Tifinagh characters composed of 60,000 images from the Mohammed Vth University in Rabat. Experimental results show that the TensorFlow library based on a Tensor processing unit constitutes a very promising framework for developing fast and very precise Tifinagh OCR web services. The results show that our method based on convolutional neural network outperforms existing methods based on support vector machines and extreme learning machine.

},
	url = {https://www.igi-global.com/article/tifinagh-handwriting-character-recognition-using-a-cnn-provided-as-a-web-service/297093},
	author = {Ouahab Kadri and Abderrezak Benyahia and Adel Abdelhadi}
}
@mastersthesis {7311,
	title = {Vers une Approche des Syst{\`e}mes Multi-Agents et M{\'e}thodes d\&rsquo;Emergence pour la Maintenance Syst{\'e}matique},
	year = {2021},
	author = {Adel Abdelhadi}
}
@article {7189,
	title = {HYBRID MULTI-AGENT AND IMMUNE ALGORITHM APPROACH TO HYBRID FLOW SHOPS SCHEDULING WITH SDST},
	journal = {ACADEMIC JOURNAL OF MANUFACTURING ENGINEERING},
	volume = {18},
	number = {3},
	year = {2020},
	abstract = {
	The existing literature on process scheduling issues have either ignored installation times or assumed that installation times on all machines is free by association with the task sequence. This working arrangement addresses hybrid flow shop scheduling issues under which there are sequence-dependent configuration times referred to as HFS with SDST. This family of production systems are common in industries such as biological printed circuit boards, metallurgy and vehicles and automobiles making. Due to the increasing complexity of industrialized sectors, simple planning systems have failed to create a realistic industrial scheduling. Therefore, a hybrid multi-agent and immune algorithm can be used as an alternative approach to solve complex problems and produce an efficient industrial schedule in a timely manner. We propose in this paper a multi-agent and immune hybrid algorithms for scheduling HFS with SDST. The findings of this paper suggest that the proposed algorithm outperforms some of the existing ones including PSO (particle swarm optimization), GA (Genetic Algorithm), LSA (Local Search Algorithm) and NEHH (Nawaz Enscore and Ham).

},
	url = {https://www.ajme.ro/PDF_AJME_2020_3/L15.pdf},
	author = {Adel Abdelhadi and Leila-Hayet Mouss and Ouahab Kadri}
}
@article {7175,
	title = {HYBRID MULTI-AGENT AND IMMUNE ALGORITHM APPROACH TO HYBRID FLOW SHOPS SCHEDULING WITH SDST},
	journal = {https://www.ajme.ro/PDF_AJME_2020_3/L15.pdf},
	volume = {18},
	number = {3},
	year = {2020},
	abstract = {
	The existing literature on process scheduling issues have either ignored installation times or assumed that installation times on all machines is free by association with the task sequence. This working arrangement addresses hybrid flow shop scheduling issues under which there are sequence-dependent configuration times referred to as HFS with SDST. This family of production systems are common in industries such as biological printed circuit boards, metallurgy and vehicles and automobiles making. Due to the increasing complexity of industrialized sectors, simple planning systems have failed to create a realistic industrial scheduling. Therefore, a hybrid multi-agent and immune algorithm can be used as an alternative approach to solve complex problems and produce an efficient industrial schedule in a timely manner. We propose in this paper a multi-agent and immune hybrid algorithms for scheduling HFS with SDST. The findings of this paper suggest that the proposed algorithm outperforms some of the existing ones including PSO (particle swarm optimization), GA (Genetic Algorithm), LSA (Local Search Algorithm) and NEHH (Nawaz Enscore and Ham).

},
	url = {https://www.ajme.ro/PDF_AJME_2020_3/L15.pdf},
	author = {Adel Abdelhadi and Leila-Hayet Mouss and Ouahab Kadri}
}
@article {3372,
	title = {Efficient Algorithms for the integration of Arabic Language in Mobile Phone ISSN 1793-8163},
	journal = {International Journal of Computer and Electrical Engineering (IJCEE)},
	volume = {Vol.3},
	number = {N{\textdegree}3},
	year = {2011},
	pages = {pp. 379-383},
	abstract = {This work appears in man-machine interface. Our goal is to study the integration of Arabic language in Mobile Phone, in order to achieve a man-machine interface Arabic. The correct display of Arabic character is essential in a MMI. Since Arabic characters change their forms according to their position in a word, then it is necessary to make a contextual analysis on every word, to find the correct form of each character. The transformation of two or more characters in one form, demand special treatment, as in the case of Arabic ligature LAM-ALEF. The Arabic language has a different direction of writing in relation to other languages embedded in mobile phone, which requires finding an algorithm that provides a bidirectional display of SMS messages. These messages may contain characters from different direction, from right to left, left to right or characters that have no direction. It allows you to make the message understandable.},
	url = {https://www.researchgate.net/publication/271303986_Efficient_Algorithms_for_the_integration_of_Arabic_Language_in_Mobile_Phone},
	author = {Adel Abdelhadi and Mouss Leila Hayet and Ouahab Kadri}
}
