Physically based modeling approach has been widely developed in recent years for the simulation of dam failure process due to the lack of field data. This paper provides and describes a physically-based model depending on dimensional analysis and hydraulic simulation methods for estimating the maximum water level and the wave propagation time from breaching of field test dams. The field physical model has been constructed in Dabbah city to represent the collapse of the Roseires dam in Sudan. Five cases of a dam failure were studied to simulate water flood conditions by changing initial water height in the reservoir (0.8, 1.0, 1.2, 1.4 and 1.5 m respectively).The physical model working under five cases, case 5 had the greatest influence of the water wave movement in the canal downstream. The results showed the collapse of the dam and the sides of the canal due to the high water levels recorded 277.001, 277.084 and 277.161 m Above Mean Sea Level (AMSL) at section 13 in the canal. The wave vanishing time was 70 minutes from the beginning of the failure at a distance of 590 m downstream. The dam collapse leads to cover the sides of the canal completely, especially at the distance of 371 m.
A digital elevation model (DEM) is a digital representation of ground surface topography or terrain. It can be represented as a raster (a grid of squares) and it is commonly estimated by utilizing remote sensing techniques, or from land surveying. In this research a 3D building of Baghdad university campus have been performed using DEM, where the easting, northing, and elevation of 400 locations have been obtained by field survey using global positioning system (GPS). The image of the investigated area has been extracted from QuickBird satellite sensor (with spatial resolution of 0.6 m). This image has been geo-referenced by selecting ground control points of the GPS. The rectification is running, using 1st order polynomial transformation.
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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Autoría: Nuha Mohsin Dhahi. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 5, 2022. Artículo de Revista en Dialnet.
Adsorption studies were carried out to test the ability of the Iraqi rice bran (Amber type) to adsorb some metals divalent cations (Cd2+, Co2+, Cu2+, Fe2+, Ni2+, Pb2+, and Zn2+) as an alternative tool to remove these pollutants from water. The Concentrations of these ions in water were measured using flame and flamless atomic absorption spectrophotometry techniques. The applicability of the adsorption isotherm on Langmuir or Freundlisch equation were tested and found to be dependent on the type of ions. The results showed different adsorptive behavior and different capacities of the adsorption of the ions on the surface of the bran. The correlation between the amounts adsorbed and different cation parameters including (electronegativity, io
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The job that confronts players with the effectiveness of shooting with an air rifle is high, so it requires necessary functional adaptations that differ in their degrees from other sports. Regular training in air rifle shooting leads to physiological changes in most of the body's internal systems, and changes and responses can be identified. The functional accompanying physical activity through the presence of body components that reflect these physiological changes in the form of changes in some components, and the importance of research lies in studying the physiological changes accompanying the maximum physical effort and the consequent development of the level of achievement in the effectiveness of shooting with air rifle and body
... Show MoreResearchers have increased interest in recent years in determining the optimum sample size to obtain sufficient accuracy and estimation and to obtain high-precision parameters in order to evaluate a large number of tests in the field of diagnosis at the same time. In this research, two methods were used to determine the optimum sample size to estimate the parameters of high-dimensional data. These methods are the Bennett inequality method and the regression method. The nonlinear logistic regression model is estimated by the size of each sampling method in high-dimensional data using artificial intelligence, which is the method of artificial neural network (ANN) as it gives a high-precision estimate commensurate with the dat
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In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .