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Kenitra, Morocco

Timouyas M.,Mohammed 5 Souissi University | Hammouch A.,Mohammed 5 Souissi University | Eddarouich S.,Regional Educational Center | Touahni R.,IbnTofail University | Sbihi A.,Abdelmalek Essaadi University
International Conference on Multimedia Computing and Systems -Proceedings | Year: 2014

In this paper, we present a new unsupervised colour image segmentation algorithm using competitive and morphological concepts. The algorithm is carried out in three processing stages. It starts by an estimation of the density function, followed by a training competitve neural network with a new criterion of resemblance called Mahalanobis distance which detects local maxima of the density function, and ends by the extraction of modal regions using an original method based on the morphological concept. The so detected modes are then used for the classification process. Compared to the K-means clustering or to the clustering approaches based on the different competitive learning schemes, the proposed algorithm has proven, under a number of real and synthetic test images, that it is automatic, has a fast convergence and does not need priori information about the data structure. © 2014 IEEE. Source


Mitta N.,AMD Inc | Gouri R.,AMD Inc | Lamari H.,AMD Inc | Moalige B.,IbnTofail University
Journal of Emerging Technologies in Web Intelligence | Year: 2014

Securing a wireless communication has generally a vital importance, particularly when this communication is in a hostile environment like in wireless sensor networks (WSNs). The problem is how to create cryptographic keys between sensor nodes to ensure secure communications. Limited resources of sensor nodes make a public key cryptosystem such as RSA not feasible. So, most solutions rely on a symmetric cryptosystem. In this paper, we propose a new key mana-gement scheme based on symmetric cryptography which is well adapted to the specific properties of WSNs. The evalu-ation of our solution shows that it minimizes memory occupation, ensures scalability, and resists against the hardest attack: com-promised nodes. © 2014 Academy Publisher. Source


Chbab Y.,Laboratory of Biotechnology | Elghaza S.,Laboratory of Biotechnology | Ahd M.,IbnTofail University | Chaouch A.,Laboratory of Biotechnology | And 2 more authors.
BioTechnology: An Indian Journal | Year: 2013

The straw is a feed with a poor nutritional value. It is poor in nitrogenous matter, in fat and in minerals. It is hardly digestible and a little part can be ingested by ruminants. As a consequence, it cannot match the physiological and production needs of the animal. The development of the straw is important to supply an increasing demand. Indeed, we made a treatment of the wheat straw by urea (5 %) and molasses (10 %). The analytical control showed a clear improvement of the food quality and the nutritional value of the treated straw compared to the control (blank) feeds. A remarkable increase was recorded for total nitrogenous matter, total sugars and fats. Concerning minerals, we noticed relatively high values for phosphorus, calcium and some magnesium. © 2013 Trade Science Inc. - India. Source


Elkhadir Z.,IbnTofail University | Chougdali K.,GREST Research Group | Benattou M.,IbnTofail University
International Review on Computers and Software | Year: 2016

Due to the fast growing of computer networks the potential for attacking those networks also became important. Therefore, all enterprises should implement various systems that supervise their network infrastructure security. To detect any eventual attacks, many Intrusion Detection Systems (IDSs) have been used in recent years. However, the most of them operate more often on enormous network traffic data with multiple redundant features. As a result, the IDS generates a high false alarms rate, which makes the intrusion detection inefficient and imprecise. To overcome that, several techniques for data dimensionality reduction have been proposed, such as Principal Component Analysis (PCA). Nonetheless, the classical PCA approach that is based on the L2-norm maximization is very sensitive to outliers. As a solution to this weakness, we propose to introduce a new variant of PCA called PCA Lp-norm using conjugate gradient algorithm to solve the Lp-norm optimization problem. The main idea behind this new method relies on the Lp-norm, which is more robust to the presence of outliers in data. Extensive experiments on two well-known datasets namely KDDcup99 and NSL-KDD prove the effectiveness of the proposed approach in terms of network attacks detection, false alarms reduction and CPU time minimization. © 2016 Praise Worthy Prize S.r.l. - All rights reserved. Source


Kassim S.A.E.,IbnTofail University | Achour M.E.,IbnTofail University | Costa L.C.,University of Aveiro | Lahjomri F.,Abdelmalek Essaadi University
Journal of Electrostatics | Year: 2014

Several DC electrical conductivity models have been proposed to explain the properties of composite materials. In particular, generalized effective medium model was used, but, in many cases, the obtained parameters do not fit accurately the data. In this paper, we extended the study to Mamunya model, with adjustable parameters. Using different carbon black nanocomposites, we obtained a good agreement with the experimental results, but only for concentrations above the percolation critical concentration. Below this point, the fit is not accurate. © 2014 Elsevier B.V. Source

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