Zobrazeno 1 - 10
of 2 402
pro vyhledávání: '"A. Otmane"'
Real-time object detection in indoor settings is a challenging area of computer vision, faced with unique obstacles such as variable lighting and complex backgrounds. This field holds significant potential to revolutionize applications like augmented
Externí odkaz:
http://arxiv.org/abs/2409.01871
This work investigates the offline formulation of the contextual bandit problem, where the goal is to leverage past interactions collected under a behavior policy to evaluate, select, and learn new, potentially better-performing, policies. Motivated
Externí odkaz:
http://arxiv.org/abs/2405.14335
Publikováno v:
Proceedings of the 31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2023), pp. 181-186
The rapid growth of e-commerce has placed considerable pressure on customs representatives, prompting advanced methods. In tackling this, Artificial intelligence (AI) systems have emerged as a promising approach to minimize the risks faced. Given tha
Externí odkaz:
http://arxiv.org/abs/2406.04349
Autor:
Azeroual, Otmane, Koltay, Tibor
This paper presents multi- and interdisciplinary approaches for finding the appropriate AI technologies for research information. Professional research information management (RIM) is becoming increasingly important as an expressly data-driven tool f
Externí odkaz:
http://arxiv.org/abs/2405.12997
Autor:
Otmane Sarti, Emilia Otal, Fouad El Mansouri, Hajar Ghannam, Salaheddine Elmoutez, Mustapha El Hadri, Mohamed Saidi, José Morillo
Publikováno v:
Waste Management Bulletin, Vol 2, Iss 4, Pp 41-55 (2024)
Carbonating metallurgical slags plays a pivotal role in achieving efficient mineral CO2 sequestration and waste valorization. This research introduces a novel integrated approach that combines the carbonation of Ladle Furnace Slag (LFS) with the simu
Externí odkaz:
https://doaj.org/article/e581fcfd82a14f28a65c15f17001ce4d
Autor:
Otmane Zouirech, Fatima El Kamari, Amira Metouekel, Azeddin El Barnossi, Farhan Siddique, Sumaira Nadeem, Karima Mikou, Mohammed Bourhia, Hiba-Allah Nafidi, Turki M. Dawoud, Musaab Dauelbait, Badiaa Lyoussi, Elhoussine Derwich
Publikováno v:
International Journal of Food Properties, Vol 27, Iss 1, Pp 838-857 (2024)
This work intended to study differences in oil yield and co-extraction of antioxidant and antibacterial compounds of Nigella sativa L. seed oil as a function of two main extraction processes: mechanical pressing and solvent extraction, including hexa
Externí odkaz:
https://doaj.org/article/1374282793004a1daef821fb2e539d12
Autor:
Chebbac Khalid, Abchir Oussama, Chalkha Mohammed, El Moussaoui Abdelfattah, El kasmi-alaoui Mohammed, Lafraxo Soufyane, Chtita Samir, Alanazi Mohammed M., Alanazi Ashwag S., Hefnawy Mohamed, Zouirech Otmane, Ouaritini Zineb Benziane, Guemmouh Raja
Publikováno v:
Open Chemistry, Vol 22, Iss 1, Pp 592-9 (2024)
The objective of this study is to determine the larvicidal activity of essential oils (EOs) extracted from three plants of the genus Artemisia against the mosquito Culex pipiens (C. pipiens) using in vitro and in silico studies. A total number of 20
Externí odkaz:
https://doaj.org/article/b336eeb7761544c39b842da5ef83eb4d
An increasingly important building block of large scale machine learning systems is based on returning slates; an ordered lists of items given a query. Applications of this technology include: search, information retrieval and recommender systems. Wh
Externí odkaz:
http://arxiv.org/abs/2308.01566
Publikováno v:
Romanian Journal of Internal Medicine, Vol 62, Iss 3, Pp 323-330 (2024)
Background: Aldosterone synthase (CYP11B2) is crucial for aldosterone production, and variations in its gene may influence type 2 diabetes mellitus (T2DM) development. This study explores the link between two single nucleotide polymorphisms (SNPs) in
Externí odkaz:
https://doaj.org/article/9f953de7f465464b84c84335a541c023
Autor:
Khelifa Khelifi Otmane, Taieb Bessaad
Publikováno v:
Heliyon, Vol 10, Iss 23, Pp e40260- (2024)
In this paper, a novel predictive controller design approach within augmented structure base on convex optimization of an extra parameter is proposed in order to improve the transient response of discrete-time linear systems subject to input constrai
Externí odkaz:
https://doaj.org/article/c9316969b9db4e71bb49f81187c25133