Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourteen parameters pH, DO, BOD, PO4, NO3,Ca, Mg, TH, K, Na, SO4,Cl, EC, Alk. The results indicated that the best correlation coefficient is 86.5% for BOD, and the most important parameter is Chloride Cl, and the best correlation coefficient is 95.4% for TDS and the most important parameters are total hardness TH and electrical conductivity EC, according to direct relation between these parameters and TDS.
This study was conducted in Diyala province for renal failure patients during the periods August 2015 - April 2016. Hundred renal failure patients were enrolled in the study after diagnosis by the consultant physician at Ibn-Sina Center for Dialysis in Baquba Teaching Hospital according to criteria adopted by the World Health Organization for diagnosis of renal failure disease. The number of males in patient’s sample was 61 (61%) and females was 39 (39%) with an age range of 10 – 88 year (44.7 ± 22.1 year). In addition, the study included 50 apparently healthy individuals and considered as a group control, in which the number of males and females was similar (25 individual), with an age range of 18 – 88 year (51.7 ± 17.3 year). The
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The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge
... Show MoreEffect of Chlorococcum humicola alcoholic algae extract was studied on the growth of, Pseudomonas aeruginosa, and Klebsiella pneumonia, which were isolated from contaminated water. The extract of Ch. humicola showed a high efficiency in reducing the numbers of the two types of bacteria. . The removal rate of K. pneumonia were 0.0, 48.4 and 57.0, The removal rate of P. aeruginosa were 63.1, 79.8 and 82.9% after24,48, 72 h respectively. The results improved that the K. pneumonia is more sensitive than P. aeruginosa for algae extract concentrations used in study ,and the beast effective time is 24h for the two bacterial species The aim of the study was to eliminate microorganisms using the Alcoholic algae extract. Especially P. aeruginosa and
... Show MoreA mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others
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A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the
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Economic organizations operate in a dynamic environment, which necessitates the use of quantitative techniques to make their decisions. Here, the role of forecasting production plans emerges. So, this study aims to the analysis of the results of applying forecasting methods to production plans for the past years, in the Diyala State Company for Electrical Industries.
The Diyala State Company for Electrical Industries was chosen as a field of research for its role in providing distinguished products as well as the development and growth of its products and quality, and because it produces many products, and the study period was limited to ten years, from 2010 to 2019. This study used the descriptive approa
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Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysi
The research aims to test the correlation relationships between wise leadership, and the business model, and to demonstrate its influence (wise leadership) on the business model. Therefore, two main hypotheses were put forward. The research was applied to a sample consisting of (87) managers and deputy managers, some of them are members on the board of directors of the researched company. The questionnaire was adopted as a basic tool for collecting data, in addition to personal interviews. A number of statistical methods were used to analyze the data and obtain results. The researcher showed a set of results, including: There is a significant correlation between wise leadership and business model. There is an influence of wise leadership on
... Show MoreLandSat Satellite ETM+ image have been analyzed to detect the different depths of regions inside the Tigris river in order to detect the regions that need to remove sedimentation in Baghdad in Iraq Country. The scene consisted of six bands (without the thermal band), It was captured in March ٢٠٠١. The variance in depth is determined by applying the rationing technique on the bands ٣ and ٥. GIS ٩. ١ program is used to apply the rationing technique and determined the results.