Daily rainfall-runoff modelling by neural networks in semi-arid zone: case of Wadi Ouahrane’s basin

This research work will allow checking efficiency of formal neural networks for flows’ modelling of wadi Ouahrane’s basin from rainfall-runoff relation which is non-linear. Two models of neural networks were optimized through supervised learning and compared in order to achieve this goal, the first model with input rain, and the second one with rain and input ETP. These neuronal models were compared with another overall model, the GR4j model. Then, it has been optimized and compared with the three first models, a third model of neural network with rain, ETP and soil moisture (calculated by the model GR4j) input.The neuronal models were optimized with algorithm of Levenberg Marquarld (LM), while the GR4j model was optimized with SCE-UA method. The Nash criterion (%) and the correlation coefficient of Pearson (R) allowed appreciating performances of these models.Keywords: modeling; neural network; supervised learning; algorithm of Levenberg Marquarld; GR4

Optimisation of one stage electrostatic precipitator for welding fume filtration

AbstractIn addition to huge installations of electrostatic precipitators (ESP), as those employed for dust filtration in blast furnaces and cement factories, there are also small devices as the ones used for fume filtration in welding shops. The aim of this paper is to optimize the geometric characteristics and the electric operating conditions of a “one-stage” precipitator intended for the filtration of welding fumes. The experimental bench is composed of 2 units, each consisting in an horizontal wire (tungsten, diameter 0.1 mm), energized from a high-voltage supply (+15 kV, 5 mA), and equally distant from two vertical plate electrodes (aluminium, length 200 mm × variable width) connected to the ground. Two “one-factor-at-a-time” experiments paved the way for a composite experimental design that enabled the optimization of ESP geometry, i.e. the inter-electrode interval and width of the collecting electrodes

Long term hemodialysis aggravates lipolytic activity reduction and very low density, low density lipoproteins composition in chronic renal failure patients

<p>Abstract</p> <p>Background</p> <p>Dyslipidemia, particularly hypertriglyceridemia is common in uremia, and represents an independent risk factor for atherosclerosis.</p> <p>Methods</p> <p>To investigate the effects of hemodialysis (HD) duration on very low density lipoprotein (VLDL) and low density lipoprotein (LDL) compositions and lipopolytic activities, 20 patients on 5 to 7 years hemodialysis were followed-up during 9 years. Blood samples were drawn at T0 (beginning of the study), T1 (3 years after initiating study), T2 (6 years after initiating study) and T3 (9 years after initiating study). T0 was taken as reference.</p> <p>Results</p> <p>Triacylglycerols (TG) values were correlated with HD duration (r = 0.70, P < 0.05). An increase of total cholesterol was noted at T2 and T3. Lowered activity was observed for lipoprotein lipase (LPL) (-44%) at T3 and hepatic lipase (HL) (-29%) at T1, (-64%) at T2 and (-73%) at T3. Inverse relationships were found between HD duration and LPL activity (r = -0.63, P < 0.05), and HL activity (r = -0.71, P < 0.01). At T1, T2 and T3, high VLDL-amounts and VLDL-TG and decreased VLDL-phospholipids values were noted. Increased LDL-cholesteryl esters values were noted at T1 and T2 and in LDL-unesterified cholesterol at T2 and T3.</p> <p>Conclusion</p> <p>Despite hemodialysis duration, VLDL-LDL metabolism alterations are aggravated submitting patients to a greater risk of atherosclerosis.</p

Międzyregionalne planowanie i analiza zasobów wodnych z użyciem modelu oceny i planowania (WEAP) dla rzeki Seybouse (Annaba) i przybrzeżnych obszarów na wschód od Konstantyny (El-Taref)

Water is seen as key factor for development. Its scarcity raises concerns at all scales. In regards to water resources, Annaba and El-Taref are intimately connected, the different activities (groundwater and superficial), focused on increasing supply, have been considered as a response to water demand. The actual system use of water resources is not able to sustain water needs that are more and more growing in different expansion sectors. Consequently, a strategy should therefore be sought to integrate the various sectoral needs in available water resources in order to reach the economic and ecological sustainability. We will try to respond to this problem by use of Water Evaluation and Planning (WEAP) model. This study is the first attempt to estimate water demand and analysis of multiple and competing uses of hydro-system in Seybouse’s Wadi basin and to make comparison with proposed water storage estimates. This model was applied according to five different scenarios which reflect the best and worst conditions of the supply and demand, not only to evaluate water demand deficit, but also to help planners to the alternative management. The model stimulation showed that the area study is sensitive to a serious water scarcity by 2030. It is possible to observe an improvement with integration of other management strategies for a best operating system.Woda jest uznawana za kluczowy czynnik rozwoju. Jej brak rodzi problemy w wielu wymiarach. W odniesieniu do zasobów wodnych prowincje Annaba i El-Taref są ściśle powiązane. W odpowiedzi na rosnące potrzeby rozważane są różne działania (w stosunku do wód podziemnych i powierzchniowych) zmierzające do zwiększenia zasilania. Istniejące systemowe użytkowanie zasobów wodnych nie jest w stanie zaspokoić potrzeb wodnych, które ciągle rosną w rozwijających się sektorach gospodarki. Należy więc poszukiwać strategii integrowania różnych branżowych potrzeb celem osiągnięcia równowagi gospodarczej i środowiskowej. Autorzy podjęli próbę rozwiązania tego problemu, stosując model oceny i planowania zasobów wodnych (WEAP – ang. Water Evaluation and Planning). Te badania są pierwszą próbą oszacowania potrzeb wodnych oraz analizy rozlicznych i konkurujących ze sobą użytkowników zlewni rzeki Seybouse oraz próbą porównania ich z przeprowadzonym szacunkiem zasobów. Modelowanie realizowano według pięciu różnych scenariuszy, które odzwierciedlają najlepsze i najgorsze warunki dostawy i zapotrzebowania nie tylko na potrzeby oceny deficytu wody, ale także, by wspierać planistów w alternatywnych formach zarządzania. Symulacja modelu wykazała, że obszar badań będzie podatny na poważne niedobory wody do roku 2030. Można zaobserwować poprawę wynikającą z integracji innych strategii zarządzania w celu osiągnięcia najlepszego systemu operacyjnego

Prognozowanie ładunku zawiesiny z zastosowaniem regularyzowanej sieci neuronowej: przykład rzeki Isser w Algierii

In the management of water resources in different hydro-systems it is important to evaluate and predict the sediment load in rivers. It is difficult to obtain an effective and fast estimation of sediment load by artificial neural network without avoiding over-fitting of the training data. The present paper comprises the comparison of a multi-layer perception network once with non-regularized network and the other with regularized network using the Early Stopping technique to estimate and forecast suspended sediment load in the Isser River, upstream of Beni Amran reservoir, northern Algeria. The study was carried out on daily sediment discharge and water discharge data of 30 years (1971–2001). The results of the Back Propagation based models were evaluated in terms of the coefficient of determination (R2) and the root mean square error (RMSE). Results of the comparison indicate that the regularizing ANN using the Early Stopping technique to avoid over-fitting performs better than non-regularized networks, and show that the overtraining in the back propagation occurs because of the complexity of the data introduced to the network.Ocena i przewidywanie ładunku zawiesiny w rzekach są istotne w zarządzaniu zasobami wodnymi w różnych hydrosystemach. Trudno jest uzyskać efektywne i szybkie oszacowanie ładunku zawiesiny za pomocą sztucznych sieci neuronowych bez uniknięcia przepełnienia danymi. W niniejszej pracy porównano wyniki zastosowania wielowarstwowej sieci w dwóch wariantach – sieci nieregularyzowanej i sieci regularyzowanej z użyciem techniki Early Stopping do oceny i prognozowanie ładunku zawiesiny w rzece Isser powyżej zbiornika Beni Amran w północnej Algierii. Badania bazowały na notowaniach dobowego odpływu zawiesiny i danych dotyczących odpływu wody w ciągu 30 lat (1971–2001). Wyniki modeli opartych na metodzie wstecznej propagacji oceniono za pomocą współczynnika determinacji (R2) i pierwiastka ze średniego błędu kwadratowego. Porównanie wyników dowodzi, że sieć neuronowa regularyzowana przy pomocy techniki Early Stopping celem uniknięcia przeładowania sprawdza się lepiej niż sieć nieregularyzowana. Wyniki wskazują, że przeładowanie wstecznej propagacji ma miejsce z powodu złożoności danych wprowadzonych do sieci

Lecithin: cholesterol acyltransferase activity and chemical composition of HDL2 and HDL3 in patients with chronic renal failure treated by haemodialysis

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