The MENA Scholarship Program (MSP) offers scholarships to professionals for short courses in the Netherlands.
Current application round
Application round 1 is open from 5 February to 24 March 2020.
Day: March 12, 2020
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UNESCO-RUSSIA MENDELEEV INTERNATIONAL PRIZE IN THE BASIC SCIENCES
The proposed UNESCO-Russia Mendeleev International Prize in the Basic Sciences, financially supported by the Russian Federation, aims to bolster basic sciences education, research, international cooperation, and, consequently, the use and applications of these disciplines, which are fundamental for providing solutions to many of the development challenges that Member States face as they implement the United Nations 2030 Agenda for Sustainable Development and other related international agenda, such as the Paris Agreement on climate Change and the Sendaï Framework on Disaster Risk Reduction. Such a Prize will give recognition to achievements that are conducive to socio-economic transformation and development on a regional or global scale, by underpinning:
- excellence in research in the basic sciences fields;
- basic sciences education and popularization;
- international or regional cooperation in the basic sciences.
The Prize shall be awarded annually to two individual award-winners for their breakthrough discoveries, outstanding innovations and avid promotion of the basic sciences, driving or with potential to drive in the future, socio-economic transformation and development of human societies. The Prize consists of a monetary reward of US $250,000 for each of the two winners, representing a total monetary prize value of $500,000. A gold medal and a diploma will be given to each of the recipients.
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Faculty of technology : Doctoral student article in sciences Abdelkader Zitouni -Electronic
Title of the article
Classification of textured images based on new information fusion methods
The name of the journal
IET Image ProcessingYear: 2019
Abstract
This work presents supervised classification algorithms based on information fusion for textured-images segmentation. Gabor features are efficient in finding class boundaries, whereas grey-Level co-occurrence matrix features are favorable in the areas within the classes. Moreover, the wavelets can represent textures at different scales and offer great discriminatory power between textures with strong resemblances. This motivates us to combine these three kinds of features with improving image segmentation. In the first step, the proposed method applied those three feature extraction strategies on textured images to get more information. After that in the second step, the estimated feature vector of each pixel is sent to the neural networks classifier for pre-labelling. Then, in the third step of the proposed method, a classifier fusion method used to combine the scores obtained by the neural networks for each pixel. Finally, in the last step, to obtain more precise segmentation results, the scores within a sliding window are combined. The performance of the proposed segmentation algorithms was evaluated on synthetic images from Brodatz and DTD datasets. The obtained classification results from the proposed fusions system lead to higher classification precision compared to applying a single classifier on the textured images.
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Faculty of technology : Doctoral student article in Third cycle “DLMD” Tahar Merizgui -Electronic
Title of the article
Effect of magnetic iron(III) oxide particle addition with MWCNTs in kenaf fibre-reinforced epoxy composite shielding material in ‘E’, ‘F’, ‘I’ and ‘J’ band microwave frequencies
The name of the journal
Materials Research Express
Year:2019
Abstract
Mechanically toughened electromagnetic shielding composite material was prepared with MWCNTs and Iron(III) oxide nano particles. The principal aim of this research work is explicating the advantage of magnetic particle addition along with conductive MWCNTs in EMW shielding. The kenaf fibre, MWCNTs and Iron(III) oxide particles were surface-treated by APTMS for effective dispersion and adhesion on matrix medium. The EM wave shielding composites were prepared using hand layup method. The mechanical results shows addition of kenaf fibre increased the tensile, flexural and impact properties. Similarly additions of MWCNTs and iron(III) oxide particles increased the electrical permittivity and magnetic permeability of epoxy matrix. The hysteresis graphs showed improved magnetization and retentivity in epoxy composites. The maximum EM wave shielding effectiveness of 82.5% (14.5 dB) was observed for composite designation ‘E’ in J band microwave frequency. The SEM images showed improved adhesion of fibre and dispersion of particle in epoxy matrix.
