Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and the water quality index used to assess the quality of water for drinking purposes, in addition to finding the model based on past information to predict the quality of treated wastewater produced in each WTP using an artificial neural network (ANN) approach. The selected parameters for this study were turbidity, total hardness, total solids, suspended solids, and alkalinity. The results showed that all the WTPs possessed a high rate of efficiency in the removal of turbidity from raw water. Also, the results of the water quality index for all WTPs were classified over a study period of three years from 2015 to 2017 as being a good water quality and based on these results, the water treatment plants can be considered to be doing efficient water treatment process. The ANN model has been found at all WTPs to have a coefficient of determination (R2) for expected models was more than 0.7 to provide a WQI prediction tool that can be used with a moderate level of predictive acceptance to describe the suitability of WTP water quality for drinking purposes.
Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm 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 sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.
The centers of cities and historical quarter are exposed to a severe threat to the values of the physical and legal urban environment as a result of the value deterioration and the emergence, emergence and spread of new values on the intellectual and urban context, which generates the loss of the urban environment for its spatio-temporal continuity, flexibility, adaptation and continuity, and thus urban obsolescence, Hence the problem of the research in “the lack of comprehensiveness of studies on the phenomenon of urban obsolescence and its impact on the decline in the values of the quality of the built environment in historic
... Show MoreMachine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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In this paper, Cu2S/CdS solar cells were prepared with different thickness of CdS layer, these layers were prepared by using chemical spray pyrolysis technique. The chemical spray solution was prepared by mixing cadmium chloride CdCl2 and thiourea CS(NH2)2 of molar concentration 0.1 M/L, the CdS layer was formed after the solution was sprayed on hot Aluminum substrate at temperature 400°C. Experimentally the type of CdS film was found as n–type depending on the results of Hall Effect, the value of the Hall factor (RH) is about – 1.348 x 10–6 m3/C and the density of the majority charge carriers (N) is about 4.64x1018 cm–3. The prepared film was tested by using X-Ray
... Show MoreA field experiment was conducted in Al-Yusufiya district - Al-Mahmoudiya district, Baghdad province during the winter season 2021, to study improving the efficiency and management of water use and the productivity of lettuce under different irrigation systems. The Nested-Factorial Experiments design was used, where the main plots include the first factor, irrigation levels (I1) 50%, (I2) 75%, (I3) 100, (I4) 125%, (I5) 150% ETpan. After depleting 35% of the available water and in terms of climatic data from the American Evaporative Basin, Class A. Then the main factor is divided into three replicates, and the coefficients of the second factor are distributed randomly within each replicate, which includes the irrigation system: surface drip i
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett
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Diyala River is one of the important rivers that provide water for the Governorate of Diyala. In this research, the morphology and sediment transport of this river were studied using HEC-Ras software. The selected length of the river in the present study is 193 km and extended from Diyala Weir to the confluence of Tigris River and Diyala River. The fieldwork period extended from June 2020 till August 2020, where suspended-load and bed-load samples were collected and surveyed some cross-sections. The one-dimensional sediment transport model has been calibrated for five years, from 2014 to 2019. The results were compared with the measured cross-sections in 2019, and the suitable value of (maximum depth
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This study was conducted to examine the discharge capacity of the reach of the Tigris River between Kut and Amarah Barrages of 250km in length. The examination includes simulation the current capacity of the reach by using HEC-RAS model. 247cross sections surveyed in 2012 were used in the simulation. The model was calibrated using observed discharges of 533, 800, 1025 and 3000m3/s discharged at Kut Barrage during 2013, 1995, 1995 and 1988, respectively, and its related water level at three gauge stations located along the reach. The result of calibration process indicated that the lowest Root Mean Square Error of 0.095 can be obtained when using Manning’s n coefficient of 0.026, 0.03 for th
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Infection with cryptosporidiosis endangers the lives of many people with immunodeficiency, especially HIV patients. Nitazoxanide is one of the main therapeutic drugs used to treat cryptosporidiosis. However, it is poorly soluble in water, which restricts its usefulness and efficacy in immunocompromised patients. Surfactants have an amphiphilic character which indicates their ability to improve the water solubility of the hydrophobic drugs. Our research concerns the synthesis of new cationic Gemini surfactants that have the ability to improve the solubility of the drug Nanazoxide. So, we synthesized cationic Gemini surfactants. N1,N1,N3,N3-tetramethyl-N1,N3-bis(2-octadecanamidoethyl)propane-1,3-diaminium bromide (CGSPS18) and 2,2‘-(etha
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