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Rabat, Morocco

Kerroum M.A.,University Mohameddal | Hammouch A.,University Mohammeduissi | Aboutajdine D.,University Mohameddal
World Academy of Science, Engineering and Technology

Texture information plays increasingly an important role in remotely sensed imagery classification and many pattern recognition applications. However, the selection of relevant textural features to improve this classification accuracy is not a straightforward task. This work investigates the effectiveness of two Mutual Information Feature Selector (MIFS) algorithms to select salient textural features that contain highly discriminatory information for multispectral imagery classification. The input candidate features are extracted from a SPOT High Resolution Visible(HRV) image using Wavelet Transform (WT) at levels (l = 1,2). The experimental results show that the selected textural features according to MIFS algorithms make the largest contribution to improve the classification accuracy than classical approaches such as Principal Components Analysis (PCA) and Linear Discriminant Analysis (LDA). Source

Achelhi K.,University Mohameddal | Laghzizil A.,University Mohameddal | Saoiabi A.,University Mohameddal
Desalination and Water Treatment

The presence of heavy metals in the environment is a major issue for ecosystems and human health. Among possible remediation strategies, this study was devoted to the preparation of hybrid materials based on hydroxyapatite in order to obtain an improved Zn immobilization property. In particular, we have developed carboxylate–hydroxyapatite nanocomposites, which associate a good affinity towards Zn(II) species compared to the pure hydroxyapatite. Results of Zn sorption have been discussed in this study and compared to Pb(II). © 2014, © 2014 Balaban Desalination Publications. All rights reserved. Source

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