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Using ANN for well type identifying and increasing production from Sa’di formation of Halfaya oil field – Iraq
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Abstract<p>The current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. For layer SB1, the average daily production is 291.544 STB/D with the horizontal well, 441.82 STB/D with the multilateral well, and 1298.461 STB/D with the fishbone well type. Also, for the SB2 layer: 197.966, 336.9834, and 924.554 STB/D, and for the SB3 layer: 333.641, 546.6364, and 1187.159 STB/D for the same well type sequence. The cumulative production for each formation layer is 22.440 MMSTB from the horizontal well, 59.05 MMSTB from the multilateral well, and 84.895 MMSTB from the fishbone well types for the SB1 layer; 48.06, 70.1094, and 160.254 MMSTB for SB2; and 75.2764, 111.7325, and 213.1291 MMSTB for SB3 for the same well types.</p>
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Publication Date
Sun Mar 01 2009
Journal Name
Al-khwarizmi Engineering Journal
The Optimum Conditions for Production of Soya Peptone by Acidic Hydrolysis of Soya Proteins
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     This study was carried out to obtain the optimum conditions necessary for the process of soya protein hydrolysis by using hydrochloric acid (as a chemical catalyst) instead of the papain enzyme (as a biological catalyst), for the production of soya peptone. These conditions are implemented to test the effect of the variables of the process of hydrolysis on the nature and quality of the product.

        The production of soya peptone was studied for their importance in the process of preparing and producing the culture media used in medical and microbiological laboratories.

      The process of production of soya peptone includes four main

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Publication Date
Thu May 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Modified Thompson –Type Testimators for the Parameters of Simple Linear Regression Model
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Publication Date
Mon May 14 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Urinary Vitamin-D Binding Protein as an Early Predictor of Diabetic Nephropathyin Type 1 and Type 2 Diabetes
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    Diabetic nephropathy (DN) is the most common microvascular complication that may lead to chronic renal failure in diabetic patients. Till now microalbuminuria, with its restrictions, is the early marker of DN, appeared after the disease exacerbation. Thus, new biomarkers are required to predict the early onset of DN before the appearance of microalbuminuria. The aim of this study is to investigate the possible use of uVDBP in the early prediction of DN. Fifty diabetic patients with DN and 40 diabetic patients without DN for both types of diabetes were enrolled in this study. All patients were tested for uACR, uVDBP (measured by ELISA), and blood HbA1c. The results demonstrated a highly significant elevation of uAC

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Publication Date
Wed Oct 09 2019
Journal Name
International Journal Of Drug Delivery Technology
The comparative study among the MRSAcin, Nisin A and vancomycin, on biofilm formation by Methicillin resistance Staphylococcus aureus isolated from food sources.
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Biofilms formation by pathogens microbial Control considered important in medical research because it is the hazarded virulence factor leading to becoming difficult to treat because of its high resistance to antimicrobials. Glycopeptide antibiotic a (Vancomycin) and the commercial bacteriocin (Nisin A) were used to comparative with purification bacteriocin (MRSAcin) against MRSA biofilm. One hundred food samples were collected from Baghdad markets from July 2016 to September 2016, including (cheese, yogurt, raw milk, fried meat, grilled meat, and beef burger). All samples were cultures; S. aureus was confirmation by macroscopic culture and microscopic examination, in addition to biochemical tests. Methicillin resistance S. asureus (

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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Ecological Engineering
Optimization of Response Surface Methodology for Removal of Cadmium Ions from Wastewater using Low Cost Materials
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Publication Date
Thu Oct 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Novel Method of Oil/Water Separation Using Composite of Polymethylacrylamide Hydrogel-Coated Metal Mesh
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Different compositions of hydrogels composed of mathacrylamide homopolymer (60 and 90% of PMAM) were prepared using the free radical polymerization technique, with and without methylene bisacrylamide as crosslinker (0 and 3%). Several parameters and properties were studied to evaluate their performance as oil/water separators. Many parameters are used, such as residual oil in water, water recovery, separation time, hydrogels coated percentages, swelling parameters, mechanical properties, microscopic and photographic images, and scanning electron microscopy. The results showed that water recovery (87-97), Separation efficiency (96.2-99.6 %), separation time (6-9.5 min.), hydrogels coated percentages (18-23 %), water content (70-97 %), and

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Scopus (4)
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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
((The Impact of Organizational Values on achieve Strategic Success Analytical Research in the Iraq Ministry of Oil ))
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This study aims to determine the impact of organization values as an independent variable across its dimensions (organization management values, organization mission values, relations management values, and environment management values) on achieve the strategic success which is the dependent variable and include its dimensions  (environmental analysis, creative thinking, strategic decision, effective implementation, and leadership capacities). The study is conducted in the Iraq Oil Ministry. It deployed the analytical descriptive approach. It focuses on the study problem enquiries throughout addressing several principal and sub-hypothesizes in regards to cause and effect relationship. To achieve this result

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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Composition and Temperature Dependence of Excess Volume of Heavy Oil-Stocks Mixtures + (Gas oil or Toluene or Reformate)
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Binary mixtures of three, heavy oil-stocks was subjected to density measurements at temperatures of 30, 35 and 40 °C. and precise data was acquired on the volumetric behavior of these systems. The results are reported in terms of equations for excess specific volumes of mixtures. The heavy oil-stocks used were of good varity, namely 40 stock, 60 stock, and 150 stock. The lightest one is 40 stock with °API gravity 33.69 while 60 stock is a middle type and 150 stock is a heavy one, with °API gravity 27.74 and 23.79 respectively. Temperatures in the range of 30-40 °C have a minor effect on excess volume of heavy oil-stock binary mixture thus, insignificant expansion or shrinkage is observed by increasing the temperature this effect beco

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