The AlAdhaim Dam is located 133 kilometers northeast of Baghdad. It is a multipurpose dam and joints the Iraqi dam system in 2000. It has a storage capacity of 1.5 billion m³. The dam has an ogee spillway with a length of 562 m, a crest level of 131.5 m.a.m.s.l. and a maximum discharge capacity of 1150 m³/s at its maximum storage height of 143 m.a.m.s.l. This research aimed to investigate the hydrodynamics performance of the spillway and the stilling basin of AlAdhiam Dam by using numerical simulation models under gated situations. It was suggested to modify the dam capacity by increasing the dam's storage capacity by installing gates on the crest of the dam spillway. The FLUENT program was used to

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

The ground-state properties of exotic ¹⁸N and ²⁰F nuclei, including the neutron, proton and matter densities and related  radii are investigated using the two-body model of   within Gaussian (GS) and Woods Saxon (WS) wave functions. The long tail is evident in the computed neutron and matter densities of these nuclei. The plane wave Born approximation (PWBA) is  calculate the elastic form factors of these exotic nuclei. The variation in the proton density distributions due to the presence of the extra neutrons in ¹⁸N and ²⁰F leads to a major difference between the elastic form factors of these exotic nuclei and their stable isotopes ¹⁴N and ¹⁹F. The reaction c

Structure of unstable 21,23,25,26F nuclei have been investigated
using Hartree – Fock (HF) and shell model calculations. The ground
state proton, neutron and matter density distributions, root mean
square (rms) radii and neutron skin thickness of these isotopes are
studied. Shell model calculations are performed using SDBA
interaction. In HF method the selected effective nuclear interactions,
namely the Skyrme parameterizations SLy4, Skeσ, SkBsk9 and
Skxs25 are used. Also, the elastic electron scattering form factors of
these isotopes are studied. The calculated form factors in HF
calculations show many diffraction minima in contrary to shell
model, which predicts less diffraction minima. The long tail

The High Power Amplifiers (HPAs), which are used in wireless communication, are distinctly characterized by nonlinear properties. The linearity of the HPA can be accomplished by retreating an HPA to put it in a linear region on account of power performance loss. Meanwhile the Orthogonal Frequency Division Multiplex signal is very rough. Therefore, it will be required a large undo to the linear action area that leads to a vital loss in power efficiency. Thereby, back-off is not a positive solution. A Simplicial Canonical Piecewise-Linear (SCPWL) model based digital predistorters are widely employed to compensating the nonlinear distortion that introduced by a HPA component in OFDM technology. In this paper, the genetic al

Sand production in unconsolidated reservoirs has become a cause of concern for production engineers. Issues with sand production include increased wellbore instability and surface subsidence, plugging of production liners, and potential damage to surface facilities. A field case in southeast Iraq was conducted to predict the critical drawdown pressures (CDDP) at which the well can produce without sanding. A stress and sanding onset models were developed for Zubair reservoir. The results show that sanding risk occurs when rock strength is less than 7,250 psi, and the ratio of shear modulus to the bulk compressibility is less than 0.8 1012 psi2. As the rock strength is increased, the sand free drawdown and depletion becomes larger. The CDDP

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

There are several methods that are used to solve the traditional transportation problems whose units of supply, demand quantities, and cost transportation are known exactly. These methods obtain basic solution, and develop it to the best solution through a series of consecutive calculations to obtain the optimal solution.
The steps are more complex with fuzzy variables, so this paper presents the disadvantages of solutions of the traditional ways with existence of variables in the fuzzy form.
This paper also presents a comparison between the results that emerged after using different conversion ranking formulas to convert from fuzzy form to crisp form on the same numerical example with a full fuzz

  In this paper, the restricted least squares method is employed to estimate the parameters of the Cobb-Douglas production function and then analyze and interprete the results obtained.         A practical application is performed on the state company for leather industries in Iraq for the period (1990-2010).         The statistical program SPSS is used to perform the required calculations.

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA