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Application of Artificial Neural Network for Predicting Iron Concentration in the Location of Al-Wahda Water Treatment Plant in Baghdad City
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Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model could be used to predict future iron concentrations as the results from the verification of the ANN model for years 2012 and 2013 indicated good accuracy with a coefficient of determination R2 = 0.8965.

 

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Analysis Of Sedimentation In Trunk Sewer With Laboratory Investigation Of Sewage Sediment Characteristics In Baghdad City
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Sediment accumulated in sewers is a major concern source as it induces numerous operational and environmental problems. For instance, during wet weather flow, the re-suspension of this sediment accompanied by the combined sewer overflow may cause huge pollutant load to the receiving water body. The characteristics of the sewer sediment are important as it shapes its behaviour and determines the extent of the pollution load. In this paper, an investigation of sewer sediment and its characterization is done for a case study in Baghdad city. Sediment depth covers more than 50% of the sewer cross-sectional area; several operational causes are comprised to cause this huge depths of sediment depositions. The testing and analysis of the s

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Publication Date
Thu Sep 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Investigation of several heavy metals in Al-Saddah agricultural drainage in Hilla city /Iraq
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Abstract<p>This study was done to determine the concentration of several heavy metals in the water of Al-Saddah agricultural drainage in Al-Saddah District in Babylon Province/Iraq. The concentrations of six heavy metals were measured (Pb, Cd, Cu, Hg, Fe, Zn). It was found that Pb concentration ranged from 0.06 mg/L at St.2 in autumn to 0.13 mg/L at St.2 in winter. Fe concentrations ranged from 0.04 mg/L at St.2 in autumn and winter to 0.41 at St.2 in Summer. Cd concentrations ranged from 0.008 mg/L at St.2 in summer to 0.05 mg/L at St.2 in winter. Cu concentrations ranged from 0.01 mg/L at St.1 in both autumn and winter to 0.63 mg/L at St.2 in winter. Hg concentrations was ranged from 0.002 mg/</p> ... Show More
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Publication Date
Sat Apr 01 2017
Journal Name
Iracst – International Journal Of Computer Networks And Wireless Communications (ijcnwc)
Optimizing Network Security Considerations with Transition to IPv6 in University of Baghdad, A Prototype
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It is believed that Organizations around the world should be prepared for the transition to IPv6 and make sure they have the " know how" to be able to succeed in choosing the right migration to start time. This paper focuses on the transition to IPv6 mechanisms. Also, this paper proposes and tests a deployment of IPv6 prototype within the intranet of the University of Baghdad (BUniv) using virtualization software. Also, it deals with security issues, improvements and extensions of IPv6 network using firewalls, Virtual Private Network ( VPN), Access list ( ACLs). Finally, the performance of the obtainable intrusion detection model is assessed and compared with three approaches.

Publication Date
Wed Feb 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
Performance Evaluation of the Organic Matter Removal Efficiency in Wastewater Treatment Plants; Case study Al- Diwaniyah WWTP in Iraq
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This study aims to assess the removal efficiency andestablish the BOD5 and COD statisticalcorrelation of the sewage flowing in Al-Diwaniyah wastewater treatment plant in Iraq during the study period (2005-2016). The strength of the influent wastewater entering the plant varied from medium to high in strength. High concentrations of BOD5 and COD in the effluent were obtained due to the poor performance of the plant. This was observed from the BOD5 /COD ratios that did not confirm with the typical ratios for the treated sewage. To improve the performance of this plant, regression equations for BOD5 and COD removal percentages were suggested which can be used to facilitate evaluation of liquid waste and optimal control process. The equations

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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Publication Date
Wed Jul 01 2015
Journal Name
Journal Of Engineering
Evaluation of Alum/Lime Coagulant for the Removal of Turbidity from Al- Ahdab Iraqi Oilfields Produced Water
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The removal of turbidity from produced water by chemical coagulation/flocculation method using locally available coagulants was investigated. Aluminum sulfate (alum) is selected as a primary coagulant, while calcium hydroxide (lime) is used as a coagulant aid. The performance of these coagulants was studied through jar test by comparing turbidity removal at different coagulant/ coagulants aid ratio, coagulant dose, water pH, and sedimentation time. In addition, an attempt has been made to examine the relationship between turbidity (NTU) and total suspended solids (mg/L) on the same samples of produced water. The best conditions for turbidity removal can be obtained at 75% alum+25% lime coagulant at coagulant dose of 80 m

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Publication Date
Tue Jun 11 2019
Journal Name
Al-kindy College Medical Journal
Application of Surgical Safety Checklist in Operating Theatre at Al-Kindy Teaching Hospital
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Background: A core set of checks have been incorporated into World Health Organization (WHO) WHO surgical safety checklist.  Lack of access to basic surgical care remains a major concern in low-income settings.

Objective: We use a WHO surgical safety checklist items to improve team communication and cooperation to help in reduction of morbidity and mortality of surgical procedures.

Methods: This is a prospective study involving 300 patients after applying the 19 items of the surgical safety checklist with different types of operations had been operated in the surgical theater at Al-Kindy Teaching Hospital during the period 1st of September 2016

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Publication Date
Wed Jan 01 2020
Journal Name
Iraqi National Journal Of Nursing Specialties
Women's Satisfaction Regarding Care Provided by Nurse-Midwives During Labor in Bint AL-Huda Hospital in AL Al-Nasiriyah City
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Objectives: To assess the woman satisfaction with nursing care during labor.

Methodology: A descriptive analytic study about conducted for a purposive (non probability) sample of one hundred  labor women interview validity and reliability of questionnaire are determined through panel of experts and pilot study. Descriptive and inferential statistical procedures were used to analyze the data, which collected by using interview technique.

Results: The study sample indicated that in general the women were satisfied in nursing care that provided during labor.

Recommendations: The study recommended educational tra

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