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Treatability influence of municipal sewage effluent on surface water quality assessment based on Nemerow pollution index using an artificial neural network
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Abstract<p>Assessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspension solids (SS), chloride, cl, hydrogen ion concentration, pH, sulfate, SO4-2, nitrate, NO3- and phosphate, PO4-3. Taking these criteria into account, samples of water from the sampling sites were graded as C, indicating the pollutant of the waste treatment. Then the water quality map using neural network model was based on the results of water quality assessment. The results showed that the model North Al-Rustumiyia for line F2 was more efficient and R2 was 0.965 with the impotence parameter was chloride (CL).</p>
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Operational assessment of biological wastewater treatment using advanced return-mass reactors based on principal component cluster analysis
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Abstract<p>In this study, field results data were conducted, implemented in 64 biofilm reactors to analyses extract organic matter nutrients from wastewater through a laboratory level nutrient removal process, biofilm layer moving process using anaerobic aerobic units. The kinetic layer biofilm reactors were continuously operating in Turbo 4BIO for BOD COD with nitrogen phosphorous. The Barakia plant is designed to serve 200,000 resident works on biological treatment through merge two process (activated sludge process, moving bed bio reactio MBBR) with an average wastewater flow of 50,000 m3/day the data were collected annually from 2017-2020. The water samples were analysis in the central labor</p> ... Show More
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Publication Date
Mon Jul 09 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ESTIMATION OF WATER POLLUTION AND CULTIVATED PLANTS ON THE DIYALA RIVER WITH HEAVY ELEMENTS DURING THE SUMMER BY FLAME ATOMIC ABSORPTION: ESTIMATION OF WATER POLLUTION AND CULTIVATED PLANTS ON THE DIYALA RIVER WITH HEAVY ELEMENTS DURING THE SUMMER BY FLAME ATOMIC ABSORPTION
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This study was carried out to measure the percentage of heavy metals pollution in the water of the Diyala river and to measure the percentage of contamination of these elements in the leafy vegetables grown on both sides of the Diyala river, which are irrigated by the contaminated river water (celery, radish, lepidium, green onions, beta vulgaris subsp, and malva). Laboratory analysis was achieved to measure the ratio of heavy element contamination (Pb, Fe, Ni, Cd, Zn and Cr) using flame atomic absorption spectrophotometer during the summer months of July and August for the year 2017. The study showed that the elements of zinc, chromium, nickel and cadmium were high concentrations and exceeded. The maximum concentration of these

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Analyzing the Pragmatics of Argumentation in the Arabic Novel Using Artificial Intelligence: An Applied Study on the Granada Trilogy
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Publication Date
Tue Mar 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Semi-parametric regression function estimation for environmental pollution with measurement error using artificial flower pollination algorithm
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

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Publication Date
Fri Oct 02 2009
Journal Name
Noise And Health
Expert system to predict effects of noise pollution on operators of power plant using neuro-fuzzy approach
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Ration power plants, to generate power, have become common worldwide. One such one is the steam power plant. In such plants, various moving parts of heavy machines generate a lot of noise. Operators are subjected to high levels of noise. High noise level exposure leads to psychological as well physiological problems; different kinds of ill effects. It results in deteriorated work efficiency, although the exact nature of work performance is still unknown. To predict work efficiency deterioration, neuro-fuzzy tools are being used in research. It has been established that a neuro-fuzzy computing system helps in identification and analysis of fuzzy models. The last decade has seen substantial growth in development of various neuro-fuzzy systems

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Publication Date
Sun Oct 01 2023
Journal Name
Applied Sciences
Multiobjective Optimization of Stereolithography for Dental Bridge Based on a Simple Shape Model Using Taguchi and Response Surface Methods
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Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi me

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
The effect of wastewater disposal on the water quality and phytoplankton in Erbil wastewater channel.
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In this study, phytoplankton density, chlorophyll-a, and selected physico- chemical parameters were investigated in Erbil wastewater channel. The surveys were carried out monthly from May 2003 to April 2004. Samplings were established on three sites from headwaters to the mouth. The results showed that pH was in alkaline side of neutrality, with significant differences (P<0.05) between sites 1 and 3. TSS concentration decreased from site 1 toward site 2 (mean value, 80.15 to 25.79 mg.l-1). A clear gradual increase in mineral content (TDS) observed from site one of the channel towards the mouthpart. Soluble reactive phosphate has a concentration maximum mean value reached 48.4 µg.l-1 which is recorded in site 2. A high positive relat

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Modeling of Corrosion Rate Under Two Phase Flow in Horizontal Pipe Using Neural Network
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The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w

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Publication Date
Sat Jan 15 2011
Journal Name
International Journal Of Poultry Science
Influence of Source of Oil Added to Diet on Egg Quality Traits of Laying Quail
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This experiment was performed to investigate the influence of different oils in the diets of laying quail on their egg quality characteristics. One hundred and twenty 7-wk old Japanese quails (Coturnix coturnix japonica) were allocated to four groups with three replicates containing 10 quail each (30 quail per each treatment group). They were fed for 13 weeks (including one week of adaptation period) on diets containing 3% oil from different sources, viz. either sunflower (T1), linseed (T2), maize (T3), or fish oil (T4). Inclusion the diet of laying quail with fish oil (T4) and maize oil (T2) resulted in significant increase with respect to egg weight, yolk weight, albumen weight, yolk diameter, yolk height, albumen diameter, albumen height

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