University of Mohammed First

Oujda, Morocco

University of Mohammed First

Oujda, Morocco
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Abrigach F.,Laboratory of Applied Chemistry and Environment LCAE | Karzazi Y.,Laboratory of Applied Chemistry and Environment LCAE | Benabbes R.,University of Mohammed First | El Youbi M.,University of Mohammed First | And 7 more authors.
Medicinal Chemistry Research | Year: 2017

A series of new pyrazolic heterocyclic compounds were prepared in good and excellent yields and characterized by proton and carbon nuclear magnetic resonance, infrared, and mass spectroscopy studies. These products were screened in vitro against three bacterial pathogens, namely Bacillus subtilis, Micrococcus luteus, and Escherichia coli and antifungal potential, against Fusarium oxysporum f.sp.albedinis. A considerable and excellent activity was recorded with respect to the two studied microorganisms. A good correlation was obtained between the experimental results and the theoretical predictions of bioavailability using Petra/Osiris/Molinspiration suite (Petra/Osiris/Molinspiration containing Lipinski’s rule-of-five). The quantitative structure activity relationship approach has been analyzed to support the Petra/Osiris/Molinspiration results and composite indexes of some quantum chemical parameters were constructed in order to characterize the inhibition performance of the tested molecules. © 2017 Springer Science+Business Media New York


Benjelloun M.,University of Mons | Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First
International Journal of Imaging and Robotics | Year: 2016

As the size of 3D object databases grows rapidly, the emerging issue related to 3D shape retrieval in a distributed database is interesting to consider. In this paper, we propose extended methods designed for centralized databases, especially those based upon Bagof- Features (BoF) approach for shape indexing. Such methods use a visual dictionary (codebook) for computing the descriptor of a given 3D object. This codebook is obtained by clustering a set of features obtained from all the objects of the database. Such clustering, however, does not suit distributed databases very well, particularly because it gets too timeconsuming. Our solution consists in associating a local codebook to each database and then generating a distributed codebook from the local codebooks only instead of directly dealing with all the objects of each distributed database. Experimental results show that the obtained relevance with our proposed approach is very close to the case of a centralized codebook. © 2016 by IJIR (CESER PUBLICATIONS).


Benjelloun M.,University of Mons | Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First
International Journal of Imaging and Robotics | Year: 2014

The need of efficient methods for 3D shape retrieval that satisfies simultaneously the computational efficiency (Fastness) and the quality of the retrieval results (Relevance), is an active topic in various research communities. Designing such methods is a great challenge. In order to satisfy the computational efficiency without affecting the performance, we propose in this paper a novel approach that adjusts the compromise "Fastness/Relevance". Our key idea is to reduce the research space during the retrieval process, by ignoring 3D-objects that are not similar to the query. To do this, we propose to cooperate two existing methods. The first one satisfies the condition of the fastness while the second one satisfies the condition of the relevance. First, we use the fastness method to reduce the research space. Then, the second method is used to perform the retrieval in the reduced research space. For experimental tests, we have applied our approach to BF-SIFT and CM-BOF methods. The obtained experimental results, on the PSB database, show that our approach efficiently adjusts the compromise "Fastness/Relevance". © 2014 by IJIR.


Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First | Tadonki C.,MINES ParisTech
Proceedings of 2012 International Conference on Complex Systems, ICCS 2012 | Year: 2012

In this work, we present a new technique to speed up 3D shape retrieval. Instead of performing an exhaustive search over the whole database, which implies a systematic comparison of the query object with all 3D objects in the database, we restrict the pattern matching to a subset of 'good candidates' (the most similar to the query). Assuming that the database has been partitioned into several classes, our retrieval algorithm focuses on the class containing objects that are similar to that of the query. Thus, the systematic pattern matching is performed within the selected class only. The key idea is to index each class by a suitable referent object that will be used to seek the right class on a search request with a given 3D object. In this paper, we describe how to choose the best representative within a class, and then couple it with a 3D retrieval method proposed in the literature. We illustrate the efficiency of our approach trough some experiments. © 2012 IEEE.


Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First | Tadonki C.,MINES ParisTech
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

Recent investigations illustrate that view-based methods, with pose normalization pre-processing get better performances in retrieving rigid models than other approaches and still the most popular and practical methods in the field of 3D shape retrieval [9,10,11,12]. In this paper we present an improvement of the BF-SIFT method proposed by Ohbuchi et al [1]. This method is based on bag-of-features to integrate a set of features extracted from 2D views of the 3D objects using the SIFT (Scale Invariant Feature Transform [2]) algorithm into a histogram using vector quantization which is based on a global visual codebook. In order to improve the retrieval performances, we propose to associate to each 3D object its local visual codebook instead of a unique global codebook. The experimental results obtained on the Princeton Shape Benchmark database [3] show that the proposed method performs better than the original method. © 2012 Springer-Verlag.


Salhi K.,University of Mohammed First | Jaara E.M.,University of Mohammed First | Alaoui M.T.,University of Mohammed First
Proceedings - Computer Graphics, Imaging and Visualization: New Techniques and Trends, CGiV 2016 | Year: 2016

In this paper, we present two approaches of the image texture pretreatment. The reason behind it is to reduce the number of the grey level in the image, by assigning to each pixel a value that characterizes the local information of the neighborhood of this same pixel. This coding process will allow us to reduce the size of the co-occurrence matrix and also minimize the extraction time of Haralick features. We compare these pretreatment approaches by applying them on our unsupervised segmentation method of the image texture, which is based on both Kohonen maps and mathematical morphology. Our comparative study covers the results obtained by each pretreatment approach taking into consideration the execution time and the error rate. © 2016 IEEE.


Salhi K.,University of Mohammed First | Jaara E.M.,University of Mohammed First | Alaoui M.T.,University of Mohammed First
Lecture Notes in Electrical Engineering | Year: 2016

This paper present a comparative study of two method for unsupervised texture image classification, which is based on both Kohonen maps and mathematical morphology, using two texture features extraction methods, namely, Haralick extraction method based on Grey Level Co-occurrence Matrix (GLCM), and extraction features from the fractal dimension using differential box counting method. These features are then used to train the Kohonen Network, which will be represented by the underlying probability density function (pdf). Under the assumption that each modal region of the presentation pdf represents a homogeneous region in the texture image, segmentation of this map is made by morphological watershed transformation. Our comparative study covers the results obtained by the two methods of extraction taking into account the execution time and the error rate. © Springer International Publishing Switzerland 2016.


Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First
International Conference on Multimedia Computing and Systems -Proceedings | Year: 2014

This paper addresses the problem of 3D shape retrieval in large databases of 3D objects (large scale retrieval). While this problem is emerging and interesting as the size of 3D object databases grows rapidly, the main two issues the community has to focus on are: computational efficiency of 3D object retrieval and the quality of retrieved results. In this work we are interested by the problem of the computational efficiency where we propose to accelerate the BF-SIFT method by exploiting the potential of the GPU to reduce the computation times of the shape indexing of the query and the shape matching using the GPU. Experimental results show that the execution time is significantly reduced, this promises that the large scale retrieval can be achieved using the GPU. © 2014 IEEE.


Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

Despite of the variety of approaches proposed in the literature in order to improve the execution time of the 3D shape retrieval [14,15], the challenge that still remains is to design a 3D shape retrieval method that allows the large scale retrieval and, in the same time, respects the relevance of the obtained results. In this work, we deal with the problem of the large scale of 3D shape retrieval by proposing new implementations on multi-core environment. At our knowledge, a few partial works based on HPC (High Performance Computing), have been proposed in the literature [1,2]. The proposed solutions are designed for the GPU (Graphical Processing Unit) and concern only the step of the extraction of the SIFT salient local features. In order to optimally exploit the potential of the multi-core architectures, we have studied different data distributions. Experimental results, under OpenMP environment, show that the large scale retrieval can be achieved using the multi-core environment. © 2013 Springer-Verlag.


Dadi E.W.,University of Mohammed First | Daoudi E.M.,University of Mohammed First
Research Journal of Applied Sciences, Engineering and Technology | Year: 2014

This study addresses the problem of 3D shape retrieval. While this problem is interesting and emerging as the size of 3D object databases grows rapidly, the main two issues the community has to focus on are: Computational efficiency of 3D object retrieval and the quality of retrieval results. In this study we deal with the two considerations, especially the first one namely computational efficiency, by proposing a new technique to retrieve efficiently the 3D-objects in the classified databases which contains 3D objects of different categories. This technique can be coupled with any 3D retrieval method. In this study, we use the Clock Matching Bag-of-Features 3D retrieval method proposed by Lian et al. (2010) since it gives the best result comparing with several methods in particular the view based methods. Instead of systematically matching the object-query with all 3D objects of the target database, our approach restricts the pattern matching on a subset of "good candidates" (the most similar to the query). For a database classified in several classes the retrieval will be oriented to the right class that contains similar objects to the query. In this case, the matching process will be not systematically performed with all objects among the database, but only with objects of right class. Our key idea is to represent each class by one representative that will be used to orient the retrieval process to the right class. Experimental results illustrate the efficiency of our approach. © Maxwell Scientific Organization, 2014.

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