Redesigning the Schedule Time Slots for Qatar University to Cope with Local Specificities

This study is concerned with the redesign of the class meeting pattern at Qatar University. It examines the existing meeting pattern based on its operational efficiency, its alignment with the strategic plan of the University, and its perception by the students and the faculty members. The analysis reveals serious limitations and shows the need for a new pattern with a full non-teaching day and no one-hour lectures. A capacity analysis proves the feasibility of such a pattern. Taking into consideration the specifications of the Qatari society, it was judged that the non-teaching day be split in two-half days. The present research recognizes the distinction between scheduling and class meeting patterns and aims to address the under-researched theme of having the meeting pattern as a variable rather than just an input to scheduling

Multi-Estimator Full Left Ventricle Quantification through Ensemble Learning

Cardiovascular disease accounts for 1 in every 4 deaths in United States. Accurate estimation of structural and functional cardiac parameters is crucial for both diagnosis and disease management. In this work, we develop an ensemble learning framework for more accurate and robust left ventricle (LV) quantification. The framework combines two 1st-level modules: direct estimation module and a segmentation module. The direct estimation module utilizes Convolutional Neural Network (CNN) to achieve end-to-end quantification. The CNN is trained by taking 2D cardiac images as input and cardiac parameters as output. The segmentation module utilizes a U-Net architecture for obtaining pixel-wise prediction of the epicardium and endocardium of LV from the background. The binary U-Net output is then analyzed by a separate CNN for estimating the cardiac parameters. We then employ linear regression between the 1st-level predictor and ground truth to learn a 2nd-level predictor that ensembles the results from 1st-level modules for the final estimation. Preliminary results by testing the proposed framework on the LVQuan18 dataset show superior performance of the ensemble learning model over the two base modules.Comment: Jiasha Liu, Xiang Li and Hui Ren contribute equally to this wor

The Ljapunov-Schmidt reduction for some critical problems

This is a survey about the application of the Ljapunov-Schmidt reduction for some critical problems

Unbiased Shape Compactness for Segmentation

We propose to constrain segmentation functionals with a dimensionless, unbiased and position-independent shape compactness prior, which we solve efficiently with an alternating direction method of multipliers (ADMM). Involving a squared sum of pairwise potentials, our prior results in a challenging high-order optimization problem, which involves dense (fully connected) graphs. We split the problem into a sequence of easier sub-problems, each performed efficiently at each iteration: (i) a sparse-matrix inversion based on Woodbury identity, (ii) a closed-form solution of a cubic equation and (iii) a graph-cut update of a sub-modular pairwise sub-problem with a sparse graph. We deploy our prior in an energy minimization, in conjunction with a supervised classifier term based on CNNs and standard regularization constraints. We demonstrate the usefulness of our energy in several medical applications. In particular, we report comprehensive evaluations of our fully automated algorithm over 40 subjects, showing a competitive performance for the challenging task of abdominal aorta segmentation in MRI.Comment: Accepted at MICCAI 201

Blow-up solutions for linear perturbations of the Yamabe equation

For a smooth, compact Riemannian manifold (M,g) of dimension N \geg 3, we are interested in the critical equation $$\Delta_g u+(N-2/4(N-1) S_g+\epsilon h)u=u^{N+2/N-2} in M, u>0 in M,$$ where \Delta_g is the Laplace--Beltrami operator, S_g is the Scalar curvature of (M,g), $h\in C^{0,\alpha}(M)$, and $\epsilon$ is a small parameter

Les Mélanomes Malins Nasosinusiens

Le mélanome malin nasosinusien est une tumeur rare prenant naissance au niveau des mélanocytes de la muqueuse respiratoire. Les auteurs rapportent deux observations de mélanomes malins nasosinusiens suivis et traités au service d\'ORL et de CCF de l\'hôpital Habib Thameur entre 1999 et 2005. Il s\'agit d\'un homme et d\'une femme âgés respectivement de 62 et 68 ans. La symptomatologie clinique est dominée par l\'obstruction nasale et l\'épistaxis. Le diagnostic est histologique après biopsie de la tumeur. Le traitement chirurgical est suivi d\'une radiothérapie externe dans les deux cas. L\'évolution est marquée par une récidive tumorale dans un cas. Primary mucosal melanoma of the nasal cavity and paranasal sinuses is an uncommun clinical entity occurring on the level of the melanocytes respiratory mucous membrane. The authors report two observations of malignant melanoma of sinonasal mucosa treated between 1999 and 2005. It acts of an old man and a woman respectively 62 and 68 years old, both presented with nasal obstruction and epistaxis. The diagnosis was histological after biopsy of the tumour. The surgical treatment was followed of an external radiotherapy in both cases. The evolution was marked by a local recurrence in one case. Journal Tunisien d\'ORL et de chirurgie cervico-faciale Vol. 16 2006: pp. 50-5

Le carcinome indifférencié des glandes salivaires

Le carcinome indifferencie primitif des glandes salivaires est rare. Son association avec le virus Epstein Barr, initialement decrite chez les esquimaux, est retrouvee dans la majorite des cas publies. Nous rapportons un nouveau cas tunisien survenu chez un homme age de 64 ans, revele par une tumefaction de la glande parotide gauche. Microscopiquement se discutait le caractere primitif ou secondaire de la tumeur, etaye par les examens complementaires. Le patient etait traite par une parotidectomie suivie d’un curage ganglionnaire et d’une radiotherapie. L’evolution etait favorable apres un an de recul.  Mots clès : Glande salivaire- Carcinome indifferencie- Virus Epstein Bar