The measurement data of the raw water quality of Tigris River were statistically analyzed to measure the salinity value in relation to the selected raw water quality parameters. The analyzed data were collected from five water treatment plants (WTPs) assembled alongside of the Tigris River in Baghdad: Al-Karkh, Al-Karama, Al-Qadisiya, Al-Dora, and Al-Wihda for the period from 2015 to 2021. The selected parameters are total dissolved solid (TDS), electrical conductivity (EC), pH and temperature. The main objective of this research is to predicate a mathematical model using SPSS software to calculate the value of salinity along the river, in addition, the effect of electrical conductivity on the salinity value was estimated. Multiple linear regression (MLR) and artificial neural network (ANN) models were used to estimate the mathematical models for calculating water salinity value in Tigris River and to present the highest effective parameter that effect on water salinity. In general, the results showed an increase in the water salinity level downstream of the Tigris River towards the south of Baghdad and the EC is the most significant effect on water salinity, and MLR and ANN analyses present a good indication of the mathematical models with highest coefficient of correlation (R2) as (0.999 and 0.998), respectively. In addition, the regression equations proved good performance in predicting the salinity value with error percentage less than 10% for all WTPs.
A computational investigation has been carried out on the design and properties of the electrostatic mirror. In this research, we suggest a mathematical expression to represent the axial potential of an electrostatic mirror. The electron beam path under zero magnification condition had been investigated as mirror trajectory with the aid of fourth – order – Runge – Kutta method. The spherical and chromatic aberration coefficients of mirror has computed and normalized in terms of the focal length. The choice of the mirror depends on the operational requirements, i.e. each optical element in optical system has suffer from the chromatic aberration, for this case, it is use to operate the mirror in optical system at various values
... Show MoreThe injection of Low Salinity Water (LSWI) as an Enhanced Oil Recovery (EOR) method has recently attracted a lot of attention. Extensive research has been conducted to investigate and identify the positive effects of LSWI on oil recovery. In order to demonstrate the impact of introducing low salinity water into a reservoir, simulations on the ECLIPSE 100 simulator are being done in this work. To simulate an actual reservoir, an easy static model was made. In order to replicate the effects of injecting low salinity water and normal salinity, or seawater, the reservoir is three-phase with oil, gas, and water. It has one injector and one producer. Five cases were suggested to investigate the effect of low salinity water injection with differen
... Show MoreIn the current study, two sites were selected from the city of Adhamiya, central Baghdad. The first site is the Adhamiya Corniche, which includes a sample of river water and the second includes domestic sewage in the same area. The total density of benthic invertebrates was 775 ind/m2, which is divided into 15 taxa. Biological indices were found, such as the stability index, the abundance index, the biodiversity index (Shannon’s index), the homogeneity index, and the invader’s guide. The result showed an increase in the density of benthic invertebrates, as well as an increase in the diversity of these organisms.
The logistic regression model of the most important regression models a non-linear which aim getting estimators have a high of efficiency, taking character more advanced in the process of statistical analysis for being a models appropriate form of Binary Data.
Among the problems that appear as a result of the use of some statistical methods I
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In this article we study a single stochastic process model for the evaluate the assets pricing and stock.,On of the models le'vy . depending on the so –called Brownian subordinate as it has been depending on the so-called Normal Inverse Gaussian (NIG). this article aims as the estimate that the parameters of his model using my way (MME,MLE) and then employ those estimate of the parameters is the study of stock returns and evaluate asset pricing for both the united Bank and Bank of North which their data were taken from the Iraq stock Exchange.
which showed the results to a preference MLE on MME based on the standard of comparison the average square e
... Show MoreThe study aims to discuss the relation between imported inflation and international trade of Iraqi economy for the period (1990-2015) by using annual data. To achieve the study aim, statistical and Econometrics methods are used through NARDL model to explain non-linear relation because it’s a model assigned to measure non-linear relations and as we know most economic relations are non-linear, beside explaining positive and negative effects of imported inflation, and to reach the research aim deductive approach was adopted through using descriptive method to describe and determine phenomenon. Beside the inductive approach by g statistical and standard tools to get the standard model explains the
... Show MoreThe spread of novel coronavirus disease (COVID-19) has resulted in chaos around the globe. The infected cases are still increasing, with many countries still showing a trend of growing daily cases. To forecast the trend of active cases, a mathematical model, namely the SIR model was used, to visualize the spread of COVID-19. For this article, the forecast of the spread of the virus in Malaysia has been made, assuming that all Malaysian will eventually be susceptible. With no vaccine and antiviral drug currently developed, the visualization of how the peak of infection (namely flattening the curve) can be reduced to minimize the effect of COVID-19 disease. For Malaysians, let’s ensure to follow the rules and obey the SOP to lower the
Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
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