Entity

Time filter

Source Type

Thiès Nones, Senegal

Sun L.,University of Ottawa | Nistor I.,University of Ottawa | Seidou O.,University of Ottawa | Sambou S.,Cheikh Anta Diop University | Tamba S.,Ecole Polytechnique de Thies
Proceedings, Annual Conference - Canadian Society for Civil Engineering | Year: 2013

Daily discharge prediction is critical for dam operation and flood prevention. In operational hydrology, simple and robust techniques are sought to provide one to seven days forecasts of the discharge at key stations. In this paper, Multiple Linear Regression (including regular MLR and Stepwise regression), Back Propagation Artificial Neural Network (BP ANN) and linear Kalman Filter (KF) have been used to predict the daily discharge of the Senegal River at Bakel (Senegal, West Africa) at one to seven days lead. Inputs are the discharges at three upstream stations (Oualia, Gourbassi and Manantali). The Root-Mean-Square Error (RMSE) and Nash-Sutcliffe efficiency coefficient (NS) were used as assessment criteria. For BP ANN, the 1988-2002 measured daily discharge was used for learning process while 2003-2006 was used for validation. The whole time series from 1988 to 2006 was used in KF as no learning process is used for this method. The regression coefficients of MLR were updated based on the whole series also. All three methods provided satisfactory performances with Nash-Sutcliffe efficiency coefficients greater than 0.8 for a lead time of up to 7 days. Both KF and MLR (mainly Stepwise) outperformed BP ANN. The best prediction delay for all methods is two to three days. Kalman filter seems more stable when the prediction delay increases.


Webb G.,Vanderbilt University | Browne C.,Vanderbilt University | Huo X.,Ryerson University | Seydi O.,Ecole Polytechnique de Thies | And 2 more authors.
PLoS Currents | Year: 2015

A differential equations model is developed for the 2014 Ebola epidemics in Sierra Leone and Liberia. The model describes the dynamic interactions of the susceptible and infected populations of these countries. The model incorporates the principle features of contact tracing, namely, the number of contacts per identified infectious case, the likelihood that a traced contact is infectious, and the efficiency of the contact tracing process. The model is first fitted to current cumulative reported case data in each country. The data fitted simulations are then projected forward in time, with varying parameter regimes corresponding to contact tracing efficiencies. These projections quantify the importance of the identification, isolation, and contact tracing processes for containment of the epidemics. © 2015, Public Library of Science. All Rights Reserved.


Niang O.,Ecole Polytechnique de Thies | Niang O.,University Paris Est Creteil | Niang O.,University Gaston Berger | Thioune A.,University Gaston Berger | And 5 more authors.
IEEE Transactions on Image Processing | Year: 2012

The major problem with the empirical mode decomposition (EMD) algorithm is its lack of a theoretical framework. So, it is difficult to characterize and evaluate this approach. In this paper, we propose, in the 2-D case, the use of an alternative implementation to the algorithmic definition of the so-called sifting process used in the original Huang's EMD method. This approach, especially based on partial differential equations (PDEs), was presented by Niang in previous works, in 2005 and 2007, and relies on a nonlinear diffusion-based filtering process to solve the mean envelope estimation problem. In the 1-D case, the efficiency of the PDE-based method, compared to the original EMD algorithmic version, was also illustrated in a recent paper. Recently, several 2-D extensions of the EMD method have been proposed. Despite some effort, 2-D versions for EMD appear poorly performing and are very time consuming. So in this paper, an extension to the 2-D space of the PDE-based approach is extensively described. This approach has been applied in cases of both signal and image decomposition. The obtained results confirm the usefulness of the new PDE-based sifting process for the decomposition of various kinds of data. Some results have been provided in the case of image decomposition. The effectiveness of the approach encourages its use in a number of signal and image applications such as denoising, detrending, or texture analysis. © 1992-2012 IEEE.


Niang O.,Ecole Polytechnique de Thies | Niang O.,University Paris Est Creteil | Niang O.,University Gaston Berger | Delechelle E.,University Paris Est Creteil | Lemoine J.,University Paris Est Creteil
IEEE Transactions on Signal Processing | Year: 2010

In this paper, we propose an alternative to the algorithmic definition of the sifting process used in the original Huang's empirical mode decomposition (EMD) method. Although it has been proven to be particularly effective in many applications, EMD method has several drawbacks. The major problem with EMD is the lack of theoretical Framework which leads to difficulties for the characterization and evaluation this approach. On top of the mathematical model, there are other concerns with mode mixing and transient phenomena, such as intermittency or pure tones separation. This paper follows a previous published nonlinear diffusion-based filtering to solve the mean-envelope estimation in sifting process. The major improvements made in this present work are a non-iterative resolution scheme for the previously proposed partial differential equation (PDE), a new definition of the stopping function used in the PDE framework, and finally an automatic regularization process based on inverse problem theory to deal with mode mixing or transient detection problem. Obtained results confirm good properties of the new version of the PDE-based sifting process and its usefulness for decomposition of various kinds of data. The efficiency of the method is illustrated on some examples using informative and pathological signals for which standard EMD algorithm fails. © 2006 IEEE.


Mbodji S.,Cheikh Anta Diop University | Mbodji S.,Bambey University | Ly I.,Ecole Polytechnique de Thies | Diallo H.L.,University Of Thies | And 3 more authors.
Research Journal of Applied Sciences, Engineering and Technology | Year: 2012

This study presents a new technic based on the junction recombination velocity (Sf) for the evaluation of the series and shunt resistances. Associating Sf and Sb, the back surface recombination velocity, we resolved the continuity equation in the base of the solar cell under monochromatic illumination and plotted I-V and P-V curves. Using single I-V curve, two equivalent electric circuits of the solar are proposed and lead to expressions of R s and R sh. Computations of Rs and Rsh and comparison with published data are given. © Maxwell Scientific Organization, 2012.

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