The performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD). In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performance has compared with the correlation coefficient (r). The suitable structure design of neural network model is examined through many trials, error, preparations and evaluation steps. Two prediction models of organic and sediment loading are presented. Result found that the estimating of the organic and sediment loading by ANN model could be successful. Moreover, results showed that influent discharge rate have more effect on organic and sediment loading predicting to other parameters.
Abstract
The critical success factors of the means of the most modern in determining the main directions for organizations to achieve competitive advantage. and can be a critical success factors in organizations that overlap in the functional areas of the organization. that successful organizations use these factors to get to the uniqueness and distinction. as the entrance of critical success factors with the capacity Evaluative phase correction because discovery increases the perception of managers of what is important to the organization and using them to get to the Strategic Entrepreneurship. as it begins in terms of permanence of success and
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The study aims to find out the degree of practicing professional leadership of the faculty’s deans, deputies, and heads of the scientific divisions at Al-Qaseem University. The study has adopted the descriptive analytical method. To achieve the objective of the study, the researcher developed a questionnaire consisting of (45) items distributed to six fields that were applied to a sample of (116) faculty deans, deputies, and the head of division at Al-Qaseem University. The results showed there is a high practicing degree of the study sample individuals of the professional leadership on the questionnaire’s fields as a whole, strategic thinking field came at the first rank, while the innovation, creat
... Show MoreEstimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling the Symmetric gray scale texture image and estimating by using
... Show MoreAbstract: This study aims to investigate the backscattering electron coefficient for SixGe1-x/Si heterostructure sample as a function of primary electron beam energy (0.25-20 keV) and Ge concentration in the alloy. The results obtained have several characteristics that are as follows: the first one is that the intensity of the backscattered signal above the alloy is mainly related to the average atomic number of the SixGe1-x alloy. The second feature is that the backscattering electron coefficient line scan shows a constant value above each layer at low primary electron energies below 5 keV. However, at 5 keV and above, a peak and a dip appeared on the line scan above Si-Ge alloy and Si, respectively, close to the interfacing line
... Show MoreThis study investigated the prevalence of quinolones resistance proteins encoding genes (qnr genes) and co-resistance for fluoroquinolones and β-lactams among clinical isolates of Klebsiella pneumoniae. Out of 150 clinical samples, 50 isolates of K. pneumoniae were identified according to morphological and biochemical properties. These isolates were collected from different clinical samples, including 15 (30%) urine, 12 (24%) blood, 9 (18%) sputum, 9 (18%) wound, and 5 (10%) burn. The minimum inhibitory concentrations (MICs) assay revealed that 15 (30%) of isolates were resistant to ciprofloxacin (≥4µg/ml), 11 (22%) of isolates were resistant to levofloxacin (≥8 µg/ml), 21 (42%) of isolates were re
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