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Your search keyword '"Mesbah, Abderrahim"' showing total 33 results
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33 results on '"Mesbah, Abderrahim"'

1. The prescribed metric on the boundary of convex subsets of anti-de Sitter space with a quasi-circle as ideal boundary

Author

Mesbah, Abderrahim

Subjects
Mathematics - Differential Geometry, Mathematics - Geometric Topology
Abstract

Let $h^{+}$ and $h^{-}$ be two complete, conformal metrics on the disc $\mathbb{D}$. Assume moreover that the derivatives of the conformal factors of the metrics $h^{+}$ and $h^{-}$ are bounded at any order with respect to the hyperbolic metric, and that the metrics have curvatures in the interval $\left(-\frac{1}{\epsilon}, -1 - \epsilon\right)$, for some $\epsilon > 0$. Let $f$ be a quasi-symmetric map. We show the existence of a globally hyperbolic convex subset $\Omega$ (see Definition 3.1) of the three-dimensional anti-de Sitter space, such that $\Omega$ has $h^{+}$ (respectively $h^{-}$) as the induced metric on its future boundary (respectively on its past boundary) and has a gluing map $\Phi_{\Omega}$ (see Definition 4.5) equal to $f$., Comment: 15 pages, comments welcom. arXiv admin note: text overlap with arXiv:1902.04027 by other authors

Published
2024

2. Asymptotic behavior of Moncrief Lines in constant curvature space-times

Author

Belraouti, Mehdi, Mesbah, Abderrahim, and Messaci, Mohamed Lamine

Subjects
Mathematics - Geometric Topology
Abstract

We study the asymptotic behavior of Moncrief lines on $2+1$ maximal globally hyperbolic spatially compact space-time $M$ of non-negative constant curvature. We show that when the unique geodesic lamination associated with $M$ is either maximal uniquely ergodic or simplicial, the Moncrief line converges, as time goes to zero, to a unique point in the Thurston boundary of the Teichm\"uller space., Comment: Comments are welcome!

Published
2024

3. The induced metric and bending lamination on the boundary of convex hyperbolic 3-manifolds

Author

Mesbah, Abderrahim

Subjects
Mathematics - Geometric Topology
Abstract

Let $S$ be a closed hyperbolic surface and $M = \left ( 0,1 \right )$. Suppose $h$ is a Riemannian metric on $S$ with curvature strictly greater than $-1$, $h^{*}$ is a Riemannian metric on $S$ with curvature strictly less than $1$, and every contractible closed geodesic with respect to $h^{*}$ has length strictly greater than $2\pi$. Let $L$ be a measured lamination on $S$ such that every closed leaf has weight strictly less than $\pi$. Then, we prove the existence of a convex hyperbolic metric $g$ on the interior of $M$ that induces the Riemannian metric $h$ (respectively $h^{*}$) as the first (respectively third) fundamental form on $S \times \left\{ 0\right\}$ and induces a pleated surface structure on $S \times \left\{ 1\right\}$ with bending lamination $L$. This statement remains valid even in limiting cases where the curvature of $h$ is constant and equal to $-1$. Additionally, when considering a conformal class $c$ on $S$, we show that there exists a convex hyperbolic metric $g$ on the interior of $M$ that induces $c$ on $S \times \left\{ 0\right\}$, which is viewed as one component of the ideal boundary at infinity of $(M,g)$, and induces a pleated surface structure on $S \times \left\{ 0\right\}$ with bending lamination $L$. Our proof differs from previous work by Lecuire for these two last cases. Moreover, when we consider a lamination which is small enough, in a sense that we will define, and a hyperbolic metric, we show that the metric on the interior of M that realizes these data is unique., Comment: 29 pages, 6 figures. Comments are welcome!

Published
2023

6. Fast and Accurate Color Image Classification Based on Quaternion Tchebichef Moments and Quaternion Convolutional Neural Network

Author

El Alami, Abdelmajid, Mesbah, Abderrahim, Berrahou, Nadia, Berrahou, Aissam, Jamil, Mohammed Ouazzani, Qjidaa, Hassan, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Bekkay, Hajji, editor, Mellit, Adel, editor, Gagliano, Antonio, editor, Rabhi, Abdelhamid, editor, and Amine Koulali, Mohammed, editor

Published
2023
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7. Automobile Insurance Claims Auditing: A Comprehensive Survey on Handling Awry Datasets

Author

Soufiane, Ezzaim, EL Baghdadi, Salah-Eddine, Berrahou, Aissam, Mesbah, Abderrahim, Berbia, Hassan, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Bennani, Saad, editor, Lakhrissi, Younes, editor, Khaissidi, Ghizlane, editor, Mansouri, Anass, editor, and Khamlichi, Youness, editor

Published
2022
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19. The induced metric and bending lamination of the boundary of convex hyperbolic 3-manifolds with boundary

Author

Mesbah, Abderrahim

Subjects
Mathematics - Geometric Topology, FOS: Mathematics, Geometric Topology (math.GT)
Abstract

Let $S$ be a closed hyperbolic surface and $M = S \times (0,1)$. Suppose $h$ is a Riemannian metric on $S$ with curvature strictly greater than $-1$, $h^{*}$ is a Riemannian metric on $S$ with curvature strictly less than $1$, and every contractible closed geodesic with respect to $h^{*}$ has length strictly greater than $2\pi$. Let $L$ be a measured lamination on $S$ such that every closed leaf has weight strictly less than $\pi$. Then, we prove the existence of a convex hyperbolic metric $g$ on the interior of $M$ that induces the Riemannian metric $h$ (respectively $h^{*}$) as the first (respectively third) fundamental form on $S \times \left\{0\right\}$ and induces a pleated surface structure on $S \times \left\{1\right\}$ with bending lamination $L$. This statement remains valid even in limiting cases where the curvature of $h$ is constant and equal to $-1$. Additionally, when considering a conformal class $c$ on $S$, we show that there exists a convex hyperbolic metric $g$ on the interior of $M$ that induces $c$ on $S \times \left\{0\right\}$, which is one component of the boundary at infinity of $(M,g)$, and induces a pleated surface structure on $S \times \left\{1\right\}$ with bending lamination $L$. Our proof differs from previous work by Lecuire for these two last cases., Comment: 22 pages, 4 figures. Comments are welcome!

Published
2023
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28. Arrhythmia detection in inter-patient ECG signals using entropy rate features and RR intervals with CNN architecture.

Author

Berrahou, Nadia, El Alami, Abdelmajid, Mesbah, Abderrahim, El Alami, Rachid, and Berrahou, Aissam

Subjects
*ARRHYTHMIA, *CONVOLUTIONAL neural networks, *HEART beat, *ELECTROCARDIOGRAPHY, *SIGNAL classification, *DEEP learning, *MAXIMUM entropy method
Abstract

AbstractThe classification of inter-patient ECG data for arrhythmia detection using electrocardiogram (ECG) signals presents a significant challenge. Despite the recent surge in deep learning approaches, there remains a noticeable gap in the performance of inter-patient ECG classification. In this study, we introduce an innovative approach for ECG classification in arrhythmia detection by employing a 1D convolutional neural network (CNN) to leverage both morphological and temporal characteristics of cardiac cycles. Through the utilization of 1D-CNN layers, we automatically capture the morphological attributes of ECG data, allowing us to represent the shape of the ECG waveform around the R peaks. Additionally, we incorporate four RR interval features to provide temporal context, and we explore the potential application of entropy rate as a feature extraction technique for ECG signal classification. Consequently, the classification layers benefit from the combination of both temporal and learned features, leading to the achievement of the final arrhythmia classification. We validate our approach using the MIT-BIH arrhythmia dataset, employing both intra-patient and inter-patient paradigms for model training and testing. The model’s generalization ability is assessed by evaluating it on the INCART dataset. The model attains average accuracy rates of 99.13% and 99.17% for 2-fold and 5-fold cross-validation, respectively, in intra-patient classification with five classes. In inter-patient classification with three and five classes, the model achieves average accuracies of 98.73% and 97.91%, respectively. For the INCART dataset, the model achieves an average accuracy of 98.20% for three classes. The experimental outcomes demonstrate the superiority of the proposed model compared to state-of-the-art models in recognizing arrhythmias. Thus, the proposed model exhibits enhanced generalization and the potential to serve as an effective solution for recognizing arrhythmias in real-world datasets characterized by class imbalances in practical applications. [ABSTRACT FROM AUTHOR]

Published
2024
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