Publicaciones

• Article dans une revue

Fast binary support vector machine learning method by samples reduction

Abdelhamid Djeffal, Chaouki Babahenini, Abdelmalik Taleb-Ahmed

Support vector machine is a well-known method of statistical learning by its good accuracy; however, its training time is very poor especially in case of huge databases. Many research works aim to reduce training samples to improve training time without significant loss in accuracy. In this paper,...

International Journal of Data Mining, Modelling and Management, 2017, 9 (1), pp.1-16. ⟨10.1504/IJDMMM.2017.082555⟩. ⟨hal-03429978⟩

• Article dans une revue

New use of the HITS algorithm for fast web page classification

Mohamed Nadjib Meadi, Chaouki Babahenini, Abdelmalik Taleb-Ahmed

The immense number of documents published on the web requires the utilization of automatic classifiers that allow organizing and obtaining information from these large resources. Typically, automatic web pages classifiers handle millions of web pages, tens of thousands of features, and hundreds of...

Turkish Journal of Electrical Engineering and Computer Sciences, 2017, 25 (3), pp.2015-2032. ⟨10.3906/ELK-1501-236⟩. ⟨hal-03428798⟩

• Communication dans un congrès

Calculation of greenhouse gas emissions of jatropha oil and jatropha biodiesel as alternative fuels for electricity production in Côte d’Ivoire

Atta Pascal Atta, Yao N'Guessan, Céline Morin, Anne Jaecker-Voirol, Georges Descombes

The electricity in Côte d’Ivoire is mainly produced from fossil energy sources. This causes damages on environment due to greenhouse gas emissions (GHG). The aim of this paper is to calculate the greenhouse gas (GHG) emissions of jatropha oil and jatropha biodiesel as alternative fuels for...

Technologies and Materials for Renewable Energy, Environment and Sustainability TMREES16 Fall Meeting, Nov 2016, Paris, France. ⟨10.1063/1.4976287⟩. ⟨hal-01505012⟩

• Communication dans un congrès

Apport des systèmes multi-agents à l'interaction tangible sur table interactive RFID

Christophe Kolski, Emmanuel Adam, Sophie Lepreux, Yoann Lebrun, René Mandiau

Journée Interaction Homme-Machine et Intelligence Artificielle, Mar 2017, Paris, France. ⟨hal-03388956⟩

• Article dans une revue

Sensing user context and habits for run-time energy optimization

Ismat Chaib Draa, Smail Niar, Jamel Tayeb, Emmanuelle Grislin-Le Strugeon, Mikael Desertot

Optimizing energy consumption in modern mobile handheld devices plays a very important role as lowering energy consumption impacts battery life and system reliability. With next-generation smartphones and tablets, the number of sensors and communication tools will increase and more and more...

EURASIP Journal on Embedded Systems, 2017, 2017, pp.4. ⟨10.1186/s13639-016-0036-8⟩. ⟨hal-03401216⟩

• Article dans une revue

Iterative aggregation and disaggregation algorithm for pseudo-polynomial network flow models with side constraints

François Clautiaux, Said Hanafi, Rita Macedo, Marie-Emilie Voge, Cláudio Alves

This paper develops a general solution framework based on aggregation techniques to solve NP-Hard problems that can be formulated as a circulation model with specific side constraints. The size of the extended Mixed Integer Linear Programming formulation is generally pseudo-polynomial. To...

European Journal of Operational Research, 2017, 258, pp.467 - 477. ⟨10.1016/j.ejor.2016.09.051⟩. ⟨hal-01410170v2⟩

• Communication dans un congrès

Timetable Optimization during Railway Infrastructure Maintenance

Luis Diego Arenas Pimentel, Paola Pellegrini, Said Hanafi, Joaquin Rodriguez

Maintenance activities are necessary to maintain the functionality of the railway infrastructure. Commonly, timetables are elaborated by considering the infrastructure unavailability periods caused by the performance of maintenance activities. However, sometimes unplanned maintenance activities...

7th International Conference on Railway Operations Modelling and Analysis - Rail Lille, Apr 2017, Lille, France. 20p. ⟨hal-01470312⟩

• Article dans une revue

An efficient hybrid approach to the remote sensing land cover classification

Ehlem Zigh, B Kouninef, Rachid Nourine, Abdelmalik Taleb-Ahmed, Mohammed Kadiri

The support vector machine (SVM) is considered as one of the powerful algorithm in machine learning, so, it is has been widely used in remote sensing land cover classification field. However, this technique suffers from its sensitivity to the parameters setting and training set. For that, we...

International Journal of Imaging and Robotics, 2017, 17 (1), pp.27-42. ⟨hal-03667415⟩

• Article dans une revue

Quantification of Movement-Related EEG Correlates Associated with Motor Training: A Study on Movement-Related Cortical Potentials and Sensorimotor Rhythms

Mads Jochumsen, Cecilie Rovsing, Helene Rovsing, Sylvain Cremoux, Nada Signal, Kathryn Allen, Denise Taylor, Imran K. Niazi

The ability to learn motor tasks is important in both healthy and pathological conditions. Measurement tools commonly used to quantify the neurophysiological changes associated with motor training such as transcranial magnetic stimulation and functional magnetic resonance imaging pose some...

Frontiers in Human Neuroscience, 2017, 11, pp.604. ⟨10.3389/fnhum.2017.00604⟩. ⟨hal-02342023⟩

• Communication dans un congrès

Vers la caractérisation du collage des alliages d'aluminium en mise en forme à froid

André Dubois, Oussama Filali, Mirentxu Dubar, Cédric Hubert, Laurent Dubar, Tat Thang Pham

Les alliages d'aluminium sont des matériaux qui ont une forte tendance aux collages lors de leur mise en forme : une rupture du film lubrifiant séparant la pièce et l'outil peut avoir des conséquences dramatiques sur l'opération de formage (rayures et fissures en surface de la pièce...

CFM 2017 - 23ème Congrès Français de Mécanique, Aug 2017, Lille, France. ⟨hal-03465771⟩