Efficient management of treated sewage effluents protects the environment and reuse of municipal, industrial, agricultural and recreational as compensation for water shortages as a second source of water. This study was conducted to investigate the overall performance and evaluate the effluent quality from Al- Rustamiya sewage treatment plant (STP), Baghdad, Iraq by determining the effluent quality index (EQI). This assessment included daily records of major influent and effluent sewage parameters that were obtained from the municipal sewage plant laboratory recorded from January 2011 to December 2018. The result showed that the treated sewage effluent quality from STP was within the Iraqi quality standards (IQS) for disposal and the overall efficiency indicated a positive efficiency of the STP within the order BOD > COD > TSS > chloride. The results revealed that the effluent quality index (EQI) lied under a good water category for both effluent disposal and irrigation use. The multiple linear regression model (MLR) was used for the prediction of EQI and the results provided good estimates for the EQI data sets with a high coefficient of determination (R2=98%). From this analysis, EQI is highly significantly interrelated with TSS, BOD5, and COD within the values 88.9%, 78.6%, and 76.3% respectively. The artificial neural network (ANN) model was developed to predict the effluent quality index based on the selected sewage characteristics. Results provided good estimates for the EQI data sets with a high coefficient of determination (R2=99.8%) and lower relative error and TSS was more effective on the EQI model other than parameters with the relative importance 47.3%. So, the MLR and ANN models were found to provide an effective tool in efficient predicting EQI that can be used effectively to monitor effluent parameters and describe the suitability of treated sewage to quality achieved according to Iraqi quality standards (IQS) for effluent disposal and Food Agriculture Organization (FAO) standards for irrigation purposes.
This research aims to numerically solve a nonlinear initial value problem presented as a system of ordinary differential equations. Our focus is on epidemiological systems in particular. The accurate numerical method that is the Runge-Kutta method of order four has been used to solve this problem that is represented in the epidemic model. The COVID-19 mathematical epidemic model in Iraq from 2020 to the next years is the application under study. Finally, the results obtained for the COVID-19 model have been discussed tabular and graphically. The spread of the COVID-19 pandemic can be observed via the behavior of the different stages of the model that approximates the behavior of actual the COVID-19 epidemic in Iraq. In our study, the COV
... Show MoreThe two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo
... Show MoreThis paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them
The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in
... Show MoreThe study aimed to spread the culture of efficient performance between nursing staffs, which would contribute and achieve health care quality, and to clarify the role of nursing in improving the quality of high-quality health care, as well as to clarify how to reach national standards for the quality of health care in Iraq, Therefore, the study dealt with the efficiency of nursing performance as an explanatory variable, and the quality of health care as a dependent variable. The fact that the health sector is the foundation for building a healthy society free from diseases, so hospital of IBN AL-NAFIS as an institution and it's nursing teams were taken as a community for this study. The results to be objective and reflect the rea
... Show MorePraise be to Allaah.
My research has included the following: The field of application of semantics when fundamentalists are the book and the Sunnah. Imam Ibn Hajar agreed with the majority of fundamentalists that what is meant from the year (one word denotes one side on two things onwards), and agreed that the significance of the year specific to the rest of its members is not a definite and definite formulas of the public has the singular known as (the) Astragharism, and the plural known as ( The nationality stating that dumping, pluralism is defined as (add), and nakra, if it occurs in the context of the condition, denial and prohibition, the names of the condition, the connected names, and the word (all - all). And the year in whic
The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from
... Show MoreIn this paper we introduce a brief review about Box-Jenkins models. The acronym ARIMA stands for “autoregressive integrated moving averageâ€. It is a good method to forecast for stationary and non stationary time series. According to the data which obtained from Baghdad Water Authority, we are modelling two series, the first one about pure water consumption and the second about the number of participants. Then we determine an optimal model by depending on choosing minimum MSE as criterion.
Simulation experiments are a means of solving in many fields, and it is the process of designing a model of the real system in order to follow it and identify its behavior through certain models and formulas written according to a repeating software style with a number of iterations. The aim of this study is to build a model that deals with the behavior suffering from the state of (heteroskedasticity) by studying the models (APGARCH & NAGARCH) using (Gaussian) and (Non-Gaussian) distributions for different sample sizes (500,1000,1500,2000) through the stage of time series analysis (identification , estimation, diagnostic checking and prediction). The data was generated using the estimations of the parameters resulting f
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