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PhjKKJUBVTCNdQwC4ilr
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, temperature 46.4 °C, pressure 21 Mpa, and flowrate 27,000 m3/day which is nearly closed to suggested oily content 8.5 ppm. An artificial neural network (ANN) technique was employed in this study to estimate the oil content in the treatment process. An artificial neural network model was remarkably accurate at simulating the process under investigation. A low mean squared error (MSE) and relative error (RE) equal to 1.55 × 10−7 and 2.5, respectively, were obtained during the training phase, whilst the testing results demonstrated a high coefficient of determination (R2) equal to 0.99.</p>
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Publication Date
Tue Nov 18 2025
Journal Name
Al–bahith Al–a'alami
News Coverage in the Iraqi Electronic Press for Internal Crises: (An Analytical Study of Al-Zaman and Al-Sabah Electronic Newspapers for the period from 1/ 3/ 2013 to 31/ 3/ 2013)
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The research study focused on the need to clarify the relationship between the Websites of Iraqi Newspapers and their roles in covering the internal crises in Iraq. The selection of Iraqi websites for the newspapers Al-Zaman and Al-Sabah was adopted as one of the most important media with a wide audience; and as a model of hot news and continuous coverage of those sites since 2003 so far. As a result, this necessitated the emergence of new types of methods of editing and writing news stories related to Iraq.

Consequently, the enormous and rapidly changing amount of Iraq news, the process of preparing and creating news has become a complex industry

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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Tue Jun 15 2021
Journal Name
Arab World English Journal
Impoliteness and Threat Responses in an Iraqi-Kurdish EFL Context
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This study shows impoliteness as a form of face-threatening that can be intentionally caused by verbal threats in a particular setting. It investigates: what strategies and mitigators do Iraqi-Kurdish English as a foreign language (EFL) learners use in situations of threat responses? The present investigation paper aims to examine impoliteness strategies and mitigators by these learners when they respond to threatening situations in their context. Thus, it fills a gap in pragmatics literature by investigating the reactions to threats in an Iraqi-Kurdish EFL context. To this end, 50 participants have participated in this study. An open-ended questionnaire in the form of a Discourse Completion Task (DCT) is used to elicit responses fr

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Publication Date
Wed Sep 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Time Dependent Behavior of Engineered Cementitious Composite Concrete Produced from Portland Limestone Cement
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Publication Date
Wed Jan 20 2021
Journal Name
Earth And Environmental Science
Time Dependent Behavior of Engineered Cementitious Composite Concrete Produced from Portland Limestone Cement
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Conventional concretes are nearly unbendable, and just 0.1 percent of strain potential makes them incredibly brittle and stiff. This absence of bendability is a significant cause of strain failure and has been a guiding force in the production of an elegant substance, bendable concrete, also known as engineered cement composites, abbreviated as ECC. This type of concrete is capable of displaying dramatically increased flexibility. ECC is reinforced with micromechanical polymer fibers. ECC usually uses a 2 percent volume of small, disconnected fibers. Thus, bendable concrete deforms but without breaking any further than conventional concrete. This research aims to involve this type of concrete, bendable concrete, that will give solut

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Publication Date
Tue Nov 15 2022
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
A-mechanical properties of engineered cementitious composite concrete produced from Portland limestone cement
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Conventional concretes are almost unbending, and even a small amount of strain potential leaves them brittle. This lack of bendability is a major source of strain loss, and it has been the main goal behind the development of bendable concrete, often known with engineered ce ment composites, or ECC. This form of concrete has a lot more flexibility than regular concrete. Micromechanical polymer fibers are used to strengthen ECC. In most cases, ECC uses a 2% amount of thin, separated fibers. As a result, bendable concrete deforms but unlike traditional concrete, it does not crack. This study aims to include this kind of concrete, bendable concrete, which can be used to solve concrete problems. Karasta (CK) and Tasluja (CT) Portland Lime

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
The Biofilm Inhibitory Potential of Compound Produced from Chlamydomonas reinhardtii Against Pathogenic Microorganisms
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Microalgae present much usefulness for antimicrobial research because of its enormous biodiversity and rapid growth rate. From this study results it is reaveled that Chlamydomonas reinhardtii were isolated from a pond of water in the province of Diwaniyah. The culture supernatants were obtained when extracted with methanol solvent. Antimicrobial activity of extracts was tested for pathogens, and the best inhibition zone obtained was against Candida albicans (32mm), S.aureus (15mm), and to E.coli (9mm). While it showed no effect against both S.epidermidis and Klebsiella spp. Biofilm was formed by all tested isolates with differences in its strength formation. The C. reinhardtii

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Antibiotic Resistance of Staphylococcus Sp. Isolated from Air, Surface, Food and Clinical samples Collected from Baghdad Hospital
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Staphylococcus Sp.is the most common type of bacteria found in contamination place, we design this
study to compare the contamination accident between two hospitals in Baghdad.One of them isthe Burns
Specialist Hospital in the Medical CityinRusafa and another one is Al-Karama Hospital in Karkh. The
samples were collected fromOperativeWard No1 (OW1), Operative Ward No2 (OW2), Consulting Pharmacy
(CP), Emergency Room (ER), Reception Room (RR), Women's Ward (WW) and Men's Ward (MW).The
samples were taken from inside each clinical unit, surfaces, food, and air. The results showed that the
number of samples containing Staphylococcus sp. bacteria is 81, including 45 belonging to Al-Karama Burns
Ward Ho

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Thu Jun 13 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Association of the MDR1 Variants (rs2032582 and rs2032583) with Steroid Response in Iraqi Children with Idiopathic Nephrotic Syndrome
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Background: Several studies linked the development of steroid-resistant nephrotic syndrome (SRNS) to genetic variations in the multidrug resistance 1 (MDR1) gene, though a disparity in findings was underlined among children with different ethnic origins. Objective: This study examined the relationship between MDR1 variants (rs2032582 and rs2032583) and the risk of developing SRNS in Iraqi patients with idiopathic nephrotic syndrome (INS). Methods: This case-control study included children with steroid-sensitive INS (SSNS; n=30) and SRNS (n=30) from the Babylon Hospital for Maternity and Pediatrics. Sanger sequencing was used to determine the participants’ genotypes. Results: The rs2032582 genotypes and alleles were not associated

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