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Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-2018. Results showed that the water quality of the Tigris River water is within the world health organization (WHO) specifications for drinking water except for Sulfate concentration. An artificial neural network (ANN) was used to develop the model for the three locations to predict SAR. The sum of the squared error function and the coefficient of determination (R2) were used to evaluate the amount of error in predicting values of SAR and performance evaluation of the model. The results showed that the highest value of the coefficient of determination was 0.992, 0.986, and 0.955 for Samarra, Baghdad, and Kut, respectively and the ANN analysis indicated that the prediction of SAR was effected by Sodium for three stations. Thus, the ANN model has been found to provide SAR prediction tool that can be used effectively to describe the suitability of river water quality for irrigation purposes.

Publication Date
Mon May 01 2023
Journal Name
Ain Shams Engineering Journal
Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
VARIATION OF SOME WATER QUALITY PARAMETERS OF HUWAIZA MARSH IN SOUTHERN IRAQ
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Huwaiza marsh is considered the largest marsh in the southern part of Iraq. It is located between 31° and 31.75° latitude and extends over the Iraqi-Iranian border; but the largest part lies in Iraq. It is located to the east of Tigris River in Messan and Basra governorates.
In this research, the variation of some water quality parameters at different locations of Huwaiza marsh were studied to find out its efficacy in the treatment of the contamination coming from the wastewater outfall of Kahlaa brokendown sewage treatment plant which lies on the Kahlaa River. This rive is the main feeder of Huwaiza marsh. Ten water quality sampling locations were chosen in this marsh. The water samples were taken during 2009 for three months; Janu

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Publication Date
Thu Nov 01 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment quality of life for patients with cerebro vascular accident
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Abstract : A descriptive study was conducted out patient in Neuralgic Hospital and Teaching Baghdad Teaching Hospital from 1st July / 2004 through October 1st / 2004 . in order to assess with QOL for CVA patients , the study aimed to identifying the QOL domain of ( physical , psychological , level of independence , social and environment ) and it relation with some demographic characteristic which is related to those patients .A purposive sample of ( 50 ) CVA patients who selected from out patient clinic of hospitals . A development questionnaire was structured and is adopted of WHO quality of life qu

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Publication Date
Sat Jun 01 2024
Journal Name
Baghdad Science Journal
Carbon Dioxide Availability in Inlands Rivers Is Driven by Dissolved Organic Carbon, Not Warming: A Case Study of Tigris River
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الانهار اصبحت مشبعة بثاني اوكسيد الكربون بشكل عالي وبذلك فهي تلعب دور مهم في كميات الكربون العالمية. لزيادة فهمنا حول مصادر الكربون المتوفرة في النظم البيئية النهرية، تم اجراء هذه الدراسة حول تأثير الكربون العضوي المذاب والحرارة (العوامل الرئيسية لتغير المناخ) كمحركات رئيسية لوفرة ثاني اوكسيد الكربون في الانهار. تم جمع العينات من خمسة واربعون موقع في ثلاثة اجزاء رئيسية لنهر دجلة داخل مدينة بغداد خلال فص

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Publication Date
Wed Sep 13 2023
Journal Name
E3s Web Of Conferences
Assessment of Soil and Water Properties in the Central Marshes Southern Iraq
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The Central Marshes are one of southern Iraq's most important wetlands and ecosystems. A study on evaluating soil quality and water quality in terms of chemical properties at certain sites in the southern Iraqi Central Marshes has been conducted to investigate their types and suitability for enhancing the agricultural reality of most field crops. Soil and water samples were collected from 15 sites and transferred to the laboratory. In the lab, the following parameters were determined: electrical conductivity (EC), total dissolved salts (TDS), organic materials (OM), pH, gypsum, and total sulfate content (SO3). The tests conducted on the samples indicated that it could be said that the soil of the Central Marshes

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Publication Date
Tue Jan 01 2013
Journal Name
Advances In Physics Theories And Applications
Studying the effects of Industrial Wastes on Tigris water in Al- Grea't City-Baghdad-Iraq
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Tigris River is one of the main important surface water resources in Iraq. This necessitates continuous study of its quality . The present study is concerned with the characteristics and quality of Tigris water passing through in Baghdad city. (eight) samples were collected from the river in the area Grea't City. The study periods were carried over four season, which has been sampled once represent the every season. First sampling 12-11-2012 represent the autumn season The second sampling 20-1-2013 to represent the winter season. The third in 25-3- 2013 to represent the Springer season. The fourth during 29-5-2013 to represent the summer spring season. In order to specify the water quality, a group of physical and chemical analyses have bee

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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Enhancing the Delta Training Rule for a Single Layer Feedforward Heteroassociative Memory Neural Network
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In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Publication Date
Wed Sep 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Suggested methods for prediction using semiparametric regression function
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Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

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Scopus
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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