Search results for: B. Touaibia

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Touaibia</title> <meta name="description" content="Search results for: B. Touaibia"> <meta name="keywords" content="B. Touaibia"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" type="button" data-toggle="collapse" data-target="#navbarMenu" aria-controls="navbarMenu" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="w-100"> <div class="d-none d-lg-flex flex-row-reverse"> <form method="get" action="https://waset.org/search" class="form-inline my-2 my-lg-0"> <input class="form-control mr-sm-2" type="search" placeholder="Search Conferences" value="B. 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Touaibia"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 4</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: B. Touaibia</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Optimization of the Dam Management to Satisfy the Irrigation Demand: A Case Study in Algeria </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Merouane%20Boudjerda">Merouane Boudjerda</a>, <a href="https://publications.waset.org/abstracts/search?q=B%C3%A9nina%20Touaibia"> Bénina Touaibia</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustapha%20K%20Mihoubi"> Mustapha K Mihoubi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In Algeria, water resources play a crucial role in economic development. But over the last decades, they are relatively limited and gradually decreasing to the detriment of agriculture. The agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Boukerdane dam’s reservoir system in North of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 34% to 60%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=water%20management" title="water management">water management</a>, <a href="https://publications.waset.org/abstracts/search?q=agricultural%20demand" title=" agricultural demand"> agricultural demand</a>, <a href="https://publications.waset.org/abstracts/search?q=Boukerdane%20dam" title=" Boukerdane dam"> Boukerdane dam</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20programming" title=" dynamic programming"> dynamic programming</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20network" title=" artificial neural network"> artificial neural network</a> </p> <a href="https://publications.waset.org/abstracts/126909/optimization-of-the-dam-management-to-satisfy-the-irrigation-demand-a-case-study-in-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/126909.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">131</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Optimization of Agricultural Water Demand Using a Hybrid Model of Dynamic Programming and Neural Networks: A Case Study of Algeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Boudjerda">M. Boudjerda</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Touaibia"> B. Touaibia</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20K.%20Mihoubi"> M. K. Mihoubi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=water%20management" title="water management">water management</a>, <a href="https://publications.waset.org/abstracts/search?q=agricultural%20demand" title=" agricultural demand"> agricultural demand</a>, <a href="https://publications.waset.org/abstracts/search?q=dam%20and%20reservoir%20operation" title=" dam and reservoir operation"> dam and reservoir operation</a>, <a href="https://publications.waset.org/abstracts/search?q=Foum%20el-Gherza%20dam" title=" Foum el-Gherza dam"> Foum el-Gherza dam</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20programming" title=" dynamic programming"> dynamic programming</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20network" title=" artificial neural network"> artificial neural network</a> </p> <a href="https://publications.waset.org/abstracts/117003/optimization-of-agricultural-water-demand-using-a-hybrid-model-of-dynamic-programming-and-neural-networks-a-case-study-of-algeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/117003.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">115</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Offshore Wind Assessment and Analysis for South Western Mediterranean Sea</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdallah%20Touaibia">Abdallah Touaibia</a>, <a href="https://publications.waset.org/abstracts/search?q=Nachida%20Kasbadji%20Merzouk"> Nachida Kasbadji Merzouk</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustapha%20Merzouk"> Mustapha Merzouk</a>, <a href="https://publications.waset.org/abstracts/search?q=Ryma%20Belarbi"> Ryma Belarbi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> accuracy assessment and a better understand of the wind resource distribution are the most important tasks for decision making before installing wind energy operating systems in a given region, there where our interest come to the Algerian coastline and its Mediterranean sea area. Despite its large coastline overlooking the border of Mediterranean Sea, there is still no strategy encouraging the development of offshore wind farms in Algerian waters. The present work aims to estimate the offshore wind fields for the Algerian Mediterranean Sea based on wind data measurements ranging from 1995 to 2018 provided of 24 years of measurement by seven observation stations focusing on three coastline cities in Algeria under a different measurement time step recorded from 30 min, 60 min, and 180 min variate from one to each other, two stations in Spain, two other ones in Italy and three in the coast of Algeria from the east Annaba, at the center Algiers, and to Oran taken place at the west of it. The idea behind consists to have multiple measurement points that helping to characterize this area in terms of wind potential by the use of interpolation method of their average wind speed values between these available data to achieve the approximate values of others locations where aren’t any available measurement because of the difficulties against the implementation of masts within the deep depth water. This study is organized as follow: first, a brief description of the studied area and its climatic characteristics were done. After that, the statistical properties of the recorded data were checked by evaluating wind histograms, direction roses, and average speeds using MatLab programs. Finally, ArcGIS and MapInfo soft-wares were used to establish offshore wind maps for better understanding the wind resource distribution, as well as to identify windy sites for wind farm installation and power management. The study pointed out that Cap Carbonara is the windiest site with an average wind speed of 7.26 m/s at 10 m, inducing a power density of 902 W/m², then the site of Cap Caccia with 4.88 m/s inducing a power density of 282 W/m². The average wind speed of 4.83 m/s is occurred for the site of Oran, inducing a power density of 230 W/m². The results indicated also that the dominant wind direction where the frequencies are highest for the site of Cap Carbonara is the West with 34%, an average wind speed of 9.49 m/s, and a power density of 1722 W/m². Then comes the site of Cap Caccia, where the prevailing wind direction is the North-west, about 20% and 5.82 m/s occurring a power density of 452 W/m². The site of Oran comes in third place with the North dominant direction with 32% inducing an average wind speed of 4.59 m/s and power density of 189 W/m². It also shown that the proposed method is either crucial in understanding wind resource distribution for revealing windy sites over a large area and more effective for wind turbines micro-siting. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=wind%20ressources" title="wind ressources">wind ressources</a>, <a href="https://publications.waset.org/abstracts/search?q=mediterranean%20sea" title=" mediterranean sea"> mediterranean sea</a>, <a href="https://publications.waset.org/abstracts/search?q=offshore" title=" offshore"> offshore</a>, <a href="https://publications.waset.org/abstracts/search?q=arcGIS" title=" arcGIS"> arcGIS</a>, <a href="https://publications.waset.org/abstracts/search?q=mapInfo" title=" mapInfo"> mapInfo</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20maps" title=" wind maps"> wind maps</a>, <a href="https://publications.waset.org/abstracts/search?q=wind%20farms" title=" wind farms"> wind farms</a> </p> <a href="https://publications.waset.org/abstracts/143652/offshore-wind-assessment-and-analysis-for-south-western-mediterranean-sea" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143652.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">145</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Quantified Metabolomics for the Determination of Phenotypes and Biomarkers across Species in Health and Disease</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Miroslava%20Cuperlovic-Culf">Miroslava Cuperlovic-Culf</a>, <a href="https://publications.waset.org/abstracts/search?q=Lipu%20Wang"> Lipu Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Ketty%20Boyle"> Ketty Boyle</a>, <a href="https://publications.waset.org/abstracts/search?q=Nadine%20Makley"> Nadine Makley</a>, <a href="https://publications.waset.org/abstracts/search?q=Ian%20Burton"> Ian Burton</a>, <a href="https://publications.waset.org/abstracts/search?q=Anissa%20Belkaid"> Anissa Belkaid</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohamed%20Touaibia"> Mohamed Touaibia</a>, <a href="https://publications.waset.org/abstracts/search?q=Marc%20E.%20Surrette"> Marc E. Surrette </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Metabolic changes are one of the major factors in the development of a variety of diseases in various species. Metabolism of agricultural plants is altered the following infection with pathogens sometimes contributing to resistance. At the same time, pathogens use metabolites for infection and progression. In humans, metabolism is a hallmark of cancer development for example. Quantified metabolomics data combined with other omics or clinical data and analyzed using various unsupervised and supervised methods can lead to better diagnosis and prognosis. It can also provide information about resistance as well as contribute knowledge of compounds significant for disease progression or prevention. In this work, different methods for metabolomics quantification and analysis from Nuclear Magnetic Resonance (NMR) measurements that are used for investigation of disease development in wheat and human cells will be presented. One-dimensional 1H NMR spectra are used extensively for metabolic profiling due to their high reliability, wide range of applicability, speed, trivial sample preparation and low cost. This presentation will describe a new method for metabolite quantification from NMR data that combines alignment of spectra of standards to sample spectra followed by multivariate linear regression optimization of spectra of assigned metabolites to samples’ spectra. Several different alignment methods were tested and multivariate linear regression result has been compared with other quantification methods. Quantified metabolomics data can be analyzed in the variety of ways and we will present different clustering methods used for phenotype determination, network analysis providing knowledge about the relationships between metabolites through metabolic network as well as biomarker selection providing novel markers. These analysis methods have been utilized for the investigation of fusarium head blight resistance in wheat cultivars as well as analysis of the effect of estrogen receptor and carbonic anhydrase activation and inhibition on breast cancer cell metabolism. Metabolic changes in spikelet’s of wheat cultivars FL62R1, Stettler, MuchMore and Sumai3 following fusarium graminearum infection were explored. Extensive 1D 1H and 2D NMR measurements provided information for detailed metabolite assignment and quantification leading to possible metabolic markers discriminating resistance level in wheat subtypes. Quantification data is compared to results obtained using other published methods. Fusarium infection induced metabolic changes in different wheat varieties are discussed in the context of metabolic network and resistance. Quantitative metabolomics has been used for the investigation of the effect of targeted enzyme inhibition in cancer. In this work, the effect of 17 β -estradiol and ferulic acid on metabolism of ER+ breast cancer cells has been compared to their effect on ER- control cells. The effect of the inhibitors of carbonic anhydrase on the observed metabolic changes resulting from ER activation has also been determined. Metabolic profiles were studied using 1D and 2D metabolomic NMR experiments, combined with the identification and quantification of metabolites, and the annotation of the results is provided in the context of biochemical pathways. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=metabolic%20biomarkers" title="metabolic biomarkers">metabolic biomarkers</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20network" title=" metabolic network"> metabolic network</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolomics" title=" metabolomics"> metabolomics</a>, <a href="https://publications.waset.org/abstracts/search?q=multivariate%20linear%20regression" title=" multivariate linear regression"> multivariate linear regression</a>, <a href="https://publications.waset.org/abstracts/search?q=NMR%20quantification" title=" NMR quantification"> NMR quantification</a>, <a href="https://publications.waset.org/abstracts/search?q=quantified%20metabolomics" title=" quantified metabolomics"> quantified metabolomics</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20alignment" title=" spectral alignment"> spectral alignment</a> </p> <a href="https://publications.waset.org/abstracts/46114/quantified-metabolomics-for-the-determination-of-phenotypes-and-biomarkers-across-species-in-health-and-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46114.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">338</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a 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Search results for: B. Touaibia