STUDY THE DISCHARGE CAPACITY OF THE MAIN COLLECTORS OF SEWERAGE FOR THE CITY OF FEZ

La ville de Fès s'est considérablement développée au cours des dernières années. En fait, le sol et la surface du terrain ont été artificiels. Par conséquent, une augmentation remarquable du coefficient de ruissellement a eu lieu et, par conséquent, la capacité de rejet des principaux collecteurs d'égouts a été affectée. Cette expansion urbaine est en quelque sorte particulière, car elle est réalisée en amont du réseau d'assainissement existant.Dans ce contexte, une procédure a été menée sur la base de la délimitation du réseau d'égouts des grands bassins versants, qui implique des paramètres de conception spécifiques à savoir la pente moyenne, le coefficient de ruissellement et le coefficient d'allongement afin d'estimer le débit de pointe qui peut être provoqué par un averse décennale (période de retour de 10 ans).Ces débits calculés seront ensuite comparés au débit des sections complètes (Qps), qui représentent les débits pouvant transporter chaque collecteur tout en gardant une vitesse de débit réelle (Vr) inférieure à 4,5 m / s.Les résultats prouvent que les collecteurs d'assainissement étudiés ne peuvent pas faire face à une éventuelle surcharge avec un pourcentage d'insuffisance compris entre 18,21% et 94,48%

Motor imagery task classification using a signal-dependent orthogonal transform based feature extraction

© Springer International Publishing Switzerland 2015. In this paper, we present the results of classifying electroencephalographic (EEG) signals into four motor imagery tasks using a new method for feature extraction. This method is based on a signal-dependent orthogonal transform, referred to as LP-SVD, defined as the left singular vectors of the LPC filter impulse response matrix. Using a logistic tree based model classifier, the extracted features are mapped into one of four motor imagery movements, namely left hand, right hand, foot, and tongue. The proposed technique-based classification performance was benchmarked against those based on two widely used linear transform for feature extraction methods, namely discrete cosine transform (DCT) and adaptive autoregressive (AAR). By achieving an accuracy of 67.35 %, the LP-SVD based method outperformed the other two by large margins (+25 % compared to DCT and +6 % compared to AAR-based methods)

Evaluation of circumferential properties of Jute/Epoxy tubes manufactured by filament winding based on the fiber orientation.

The introduction of bio-composites in the manufacture of tubes by the filament winding technique poses a real challenge for design engineers. This study aims to evaluate the mechanical properties in circumferential traction and in circumferential compression of Jute-Epoxy tubes whose winding angle is considered to be variable. The experimental study is carried out on 6 tube configurations of 92 mm in diameter. The tubes tested are made of 4 layers. The selected α fiber winding angles are (50 °, 55 °, 60 °, 65 °, 75 °, and 90 °). Circumferential tensile and stiffness tests are established according to the specifications of ASTM D2290 and ASTM D2412 respectively. The results obtained allowed us to analyze the influence of the winding angle on the properties of the tubes

Evaluation of circumferential properties of Jute/Epoxy tubes manufactured by filament winding based on the fiber orientation.

The introduction of bio-composites in the manufacture of tubes by the filament winding technique poses a real challenge for design engineers. This study aims to evaluate the mechanical properties in circumferential traction and in circumferential compression of Jute-Epoxy tubes whose winding angle is considered to be variable. The experimental study is carried out on 6 tube configurations of 92 mm in diameter. The tubes tested are made of 4 layers. The selected α fiber winding angles are (50 °, 55 °, 60 °, 65 °, 75 °, and 90 °). Circumferential tensile and stiffness tests are established according to the specifications of ASTM D2290 and ASTM D2412 respectively. The results obtained allowed us to analyze the influence of the winding angle on the properties of the tubes

Classification of Retinal Images Based on Statistical Moments and Principal Component Analysis

Early diagnosis of Diabetic Retinopathy (DR) has been suggested as a good measure of preventing blindness associated with Diabetes. Some of the reported methodologies of Retinal Images (RI) classification for early diagnosis of DR have been shown to involve several steps and approaches for effective and accurate diagnosis. Thus, this paper investigates the classification of RI using a two-stage procedure. The first stage includes the extraction of blood vessels from RI belonging to healthy and diabetes retinal images using a modified local entropy thresholding algorithm. In the second stage, different features are extracted including statistical moments and principal components. The set of extracted features is combined into one feature vector and fed into a Sequential Minimal Optimization (SMO) classifier. The obtained result is encouraging with an average accuracy of 68.33 %

Classification of retinal images based on statistical moments and principal component analysis

Early diagnosis of Diabetic Retinopathy (DR) has been suggested as a good measure of preventing blindness associated with Diabetes. Some of the reported methodologies of Retinal Images (RI) classification for early diagnosis of DR have been shown to involve several steps and approaches for effective and accurate diagnosis. Thus, this paper investigates the classification of RI using a two-stage procedure. The first stage includes the extraction of blood vessels from RI belonging to healthy and diabetes retinal images using a modified local entropy thresholding algorithm. In the second stage, different features are extracted including statistical moments and principal components. The set of extracted features is combined into one feature vector and fed into a Sequential Minimal Optimization (SMO) classifier. The obtained result is encouraging with an average accuracy of 68.33 %

Variation of soils erodibility according to physico-chemical and biogeographic parameters in Allal Al Fassi watershed, Middle Atlas, Morocco.

In order to the conservation of soil resources and the preservation of water and biodiversity, the study of the variation of soil erodibility according to physico-chemical and biogeographical parameters in Allal Al Fassi watershed is of great importance. The measurement of soil erodibility according to the Wischmeier and Smith model requiring a series of physico-chemical analyses of several intrinsic soil parameters (texture, structure, permeability, organic matter content, etc.) is performed on 9 transects with 150 samples. The first, the results are combined with the biogeographical parameters of the soils (slope, pedology, lithology and land use) and then are submitted to a multivariate statistical analysis, were able to highlight both the qualitative and quantitative characteristics of the watershed. Soil erodibility in Allal Al Fassi watershed is moderately strong, ranging from 0.05 to 0.38 t. ha. h. ha-1MJ-1.m-1. Statistical analysis shows that soil erodibility (K) is closely related to texture, organic matter content and especially land use. It is more important in farmland, unlike soils occupied by matorral. Soils become more erodible when the silty fraction dominates and clay and organic matter levels decrease

Quasi-Newton-Based Preconditioning and Damped Quasi-Newton Schemes for Nonlinear Conjugate Gradient Methods

In this paper, we deal with matrix-free preconditioners for Nonlinear Conjugate Gradient (NCG) methods. In particular, we review proposals based on quasi-Newton updates, and either satisfying the secant equation or a secant-like equation at some of the previous iterates. Conditions are given proving that, in some sense, the proposed preconditioners also approximate the inverse of the Hessian matrix. In particular, the structure of the preconditioners depends both on low-rank updates along with some specific parameters. The low-rank updates are obtained as by-product of NCG iterations. Moreover, we consider the possibility to embed damped techniques within a class of preconditioners based on quasi-Newton updates. Damped methods have proved to be effective to enhance the performance of quasi-Newton updates, in those cases where the Wolfe linesearch conditions are hardly fulfilled. The purpose is to extend the idea behind damped methods also to improve NCG schemes, following a novel line of research in the literature. The results, which summarize an extended numerical experience using large-scale CUTEst problems, is reported, showing that these approaches can considerably improve the performance of NCG methods