Semilinear heat equation with singular terms

The main goal of this paper is to analyze the existence and nonexistence as well as the regularity of positive solutions for the following initial parabolic problem ∂tu − ∆u = µ u |x| 2 f u in ΩT := Ω × (0, T), u = 0 on ∂Ω × (0, T), u(x, 0) = u0(x) in Ω, where Ω ⊂ RN, N ≥ 3, is a bounded open, σ ≥ 0 and µ > 0 are real constants and f ∈ L m(ΩT), m ≥ 1, and u0 are nonnegative functions. The study we lead shows that the existence of solutions depends on σ and the summability of the datum f as well as on the interplay between µ and the best constant in the Hardy inequality. Regularity results of solutions, when they exist, are also provided. Furthermore, we prove uniqueness of finite energy solutions

Learner-Centered Teaching: A Case Study of its Implementation in Physics and Chemistry Classes in Moroccan High Schools

Following the international call of the learner-centered approach, the Moroccan educational system has undergone a paradigm shift in teaching methods. Physics and chemistry textbooks used in Moroccan high schools highly valorise learning strategies development, self-directed learning, and discovery learning, which promote the learner’s autonomy. This study provides an overview of the learner-centeredness principles, and it is based on data collection which is accomplished using a questionnaire administered to 35 physics and chemistry high school teachers. It focuses on analysing the teachers’ attitudes towardsthis approach. The study shows that majority of the teachers are motivated towards implementing the learner-centered approach, but very few of them rely on both teacher and student-centered teaching simultaneously to cater for students’ learning needs. This paper recommends the use of active learning to cater for a successful educational system

Parallel Algorithm for Brain Tissues Segmentation in T1-Weighted MR Images on 3D Reconfigurable Mesh Computer

In this paper, we propose a parallel algorithm for brain tissues segmentation from T1-weighted Magnetic Resonance Images (MRI) on Massively Parallel architecture named reconfigurable mesh computer (MCR), this brain tissues are already extracted using our method named Threshold Morphologic Brain Extraction method (TMBE)[1]. The use of this massively parallel architecture is introduced in order to improve the complexities of the corresponding algorithms. The image of size (M x N x K) to be processed must be stored on the RMC of the same size, one Voxel per Processing Element (PE). The proposed method consists in the brain tissues segmentation using parallel version of the modified fuzzy c-means MFCM [2], named PMFCM. This algorithm is directly applied on the extracted volume. The corresponding parallel program of the proposed algorithm is validated on a 3D Reconfigurable Mesh emulator [3]

Vers une accélération performante des applications de traitement d’images sur architectures parallèles

Les systèmes parallèles et distribués sont devenus, depuis quelques années, des incontournables issues pour le domaine du calcul de haute performance. Selon les problèmes et les contextes considérés, plusieurs architectures parallèles et techniques algorithmiques de distribution de données et de traitements sont apparus. Dans ce papier nous nous proposons, à travers une revue de littérature et un retour d’expérience, quelques aspects fondamentaux liés aux différents enjeux mis au cours de cette transformation de paradigme séquentiel-parallèle ainsi que les différentes contraintes auxquels la communauté technique et scientifique doit vaincre. L’accent est mis sur les applications et les algorithmes de traitement d’images accélérés via des architectures parallèles de type GPU. Une validation concrète, à travers une étude comparative de performances de trois algorithmes de classification floue appliqués à la segmentation d’images médicales, est présenté

PhDAY 2020 -FOO (Facultad de Óptica y Optometría)

Por cuarto año consecutivo los doctorandos de la Facultad de Óptica y Optometría de la Universidad Complutense de Madrid cuentan con un congreso propio organizado por y para ellos, el 4º PhDAY- FOO. Se trata de un congreso gratuito abierto en la que estos jóvenes científicos podrán presentar sus investigaciones al resto de sus compañeros predoctorales y a toda la comunidad universitaria que quiera disfrutar de este evento. Apunta en tu agenda: el 15 de octubre de 2020. En esta ocasión será un Congreso On-line para evitar que la incertidumbre asociada a la pandemia Covid-19 pudiera condicionar su celebración

A New Distributed Type-2 Fuzzy Logic Method for Efficient Data Science Models of Medical Informatics

The paper aims to propose a distributed method for machine learning models and its application for medical data analysis. The great challenge in the medicine field is to provide a scalable image processing model, which integrates the computing processing requirements and computing-aided medical decision making. The proposed Fuzzy logic method is based on a distributed approach of type-2 Fuzzy logic algorithm and merges the HPC (High Performance Computing) and cognitive aspect on one model. Accordingly, the method is assigned to be implemented on big data analysis and data science prediction models for healthcare applications. The paper focuses on the proposed distributed Type-2 Fuzzy Logic (DT2FL) method and its application for MRI data analysis under a massively parallel and distributed virtual mobile agent architecture. Indeed, the paper presents some experimental results which highlight the accuracy and efficiency of the proposed method