This research represents a practical attempt applied to calibrate and verify a hydraulic model for the Blue Nile River. The calibration procedures are performed using the observed data for a previous period and comparing them with the calibration results while verification requirements are achieved with the application of the observed data for another future period and comparing them with the verification results. The study objective covered a relationship of the river terrain with the distance between the assumed points of the dam failures along the river length. The computed model values and the observed data should conform to the theoretical analysis and the overall verification performance of the model by comparing it with another set of data. The model was calibrated using data from gauging stations (Khartoum, Wad Medani, downstream Sennar, and downstream Roseires) during the period from the 1st of May to 31 of October 1988 and the verification was done using the data of the same gauging stations for years 2003 and 2010 for the same period. The required available data from these stations were collected, processed and used in the model calibration. The geometry input files for the HEC-RAS models were created using a combination of ArcGIS and HEC-GeoRAS. The results revealed high correlation (R2 ˃ 0.9) between the observed and calibrated water levels in all gauging stations during 1988 and also high correlation between the observed and verification water levels was obtained in years 2003 and 2010. Verification results with the equation and degree of correlation can be used to predict future data of any expected data for the same stations.
It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna
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This study synthesized nanocomposite photocatalyst materials from a mixture of Cu2O nanoparticles, ZnO nanoparticles, and graphene oxide (GO) through coprecipitation and hydrothermal methods. This study aims to determine the optimum composition of Cu2O/ZnO/GO nanocomposites in degrading methylene blue. The nanocomposite was synthesized in two steps: 1 the synthesis of Cu2O and ZnO nanoparticles through the coprecipitation method and the preparation of GO through the modified Hummer method. 2 The preparation of Cu2O and ZnO nanoparticles mixtures with GO through the hydrothermal method to form Cu2O/ZnO/GO nanocomposites. The adsorption-photocatalysis process of methylene blue
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The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.
The coagulation and flocculation process using coated magnetic nanoparticles is considered one of the effective technologies for turbidity removal. This study investigates an application of magnetic nanoparticles coated with citric acid in the coagulation and flocculation process on Tigris River water in Baghdad, Iraq. Magnetic nanoparticles (MNP1) were synthesized by the co-precipitation method and coated with citric acid (MNP2). The prepared MNP1 and MNP2 were characterized by XRD, FTIR, AFM, FE-SEM, EDS, and zeta potential analysis. For coagulation process, the effect of different types of coagulants (alum, FeCl3, MNP1, MNP2), coagulant dosage (10–110 mg/l), and initial pH (3–9) were examined in this work. The best coagulant was MNP2
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n this paper, we formulate three mathematical models using spline functions, such as linear, quadratic and cubic functions to approximate the mathematical model for incoming water to some dams. We will implement this model on dams of both rivers; dams on the Tigris are Mosul and Amara while dams on the Euphrates are Hadetha and Al-Hindya.
In this paper has been building a statistical model of the Saudi financial market using GARCH models that take into account Volatility in prices during periods of circulation, were also study the effect of the type of random error distribution of the time series on the accuracy of the statistical model, as it were studied two types of statistical distributions are normal distribution and the T distribution. and found by application of a measured data that the best model for the Saudi market is GARCH (1,1) model when the random error distributed t. student's .
The issue of the research lies in the non-representation of the models developed for the communication process in the interaction and networking processes through social media, as the research sought to build a network model of communication according to the specific data and features of social media platforms in order to reach a special generalization to understand how the process of networking operates in cyberspace.
The researcher followed the analytical survey approach as she described the communication models outwardly in order to be able to build a networked communication model that represents the flow of post-reactive communication. Therefore, it has been named "Nebula - Sadeem" after the concept of post-space and cosmic g
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Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models
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