Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability. Trend test was performed to ensure that the developed model would follow the physical laws. Results show that the developed model outperforms the published correlations in term of absolute average percent relative error of 6.5%, and correlation coefficient of 96%.
It has become necessary to change from a traditional system to an automated system in production processes, because it has high advantages. The most important of them is improving and increasing production. But there is still a need to improve and develop the work of these systems.
The objective of this work is to study time reduction by combining multiple sequences of operations into one process. To carry out this work, the pneumatic system is designed to decrease\ increase the time of the sequence that performs a pick and place process through optimizing the sequences based on the obstacle dimensions. Three axes are represented using pneumatic cylinders that move according to the sequence used. The system is implemented and con
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Diabetes mellitus is a metabolic disorder categorized hyperglycemia resulting from defects in insulin secretion, insulin action or both. Protein tyrosine kinase (PTK) is an enzyme that catalyzes the transfer of phosphate groups from ATP to the tyrosine residues of many important proteins resulting in proteins phosphorylation. The aim of current study was to evaluate serum levels of protein tyrosine kinase enzyme and thyroid hormone (T3, T4and TSH) and to find the correlation between them in type 2 diabetes mellitus and diabetic nephropathy Iraqi patients. Methods: This study was conducted at The National Diabetes Center, Al-Mustansiriya University, Baghdad, Iraq and included 150 patients divided into three groups the first group included 50
... Show MoreKA Hadi, AH Asma’a, IJONS, 2018 - Cited by 1
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In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T
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The Growth Differentiation Factor -15 (GDF-15) is a member of the transforming growth factor β superfamily. İt represents an example of the stress response cytokines. It's mostly found in cardiac myocytes, adipocytes, macrophages, endothelial cells, and vascular endothelial cells, whether they're generated normally or not. GDF-15 levels have increased and are associated with cardiovascular risk. Aim of the study: To investigate the correlation between angiotensin-converting enzyme (ACE) inhibitors and angiotensin II receptor blockers (ARBs) with the level of plasma GDF-15 in a group of hypertensive patients. Materials and methods: A case-control study involved 90 individuals, 60 hypertensive patients (36 on ACE inhibitors and 24 on ARBs)
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Antimicrobial and antiyeast activity of ethanolic and aqueous extract of grape fruit seed (Citrus paradise ; Rutaceaa) was examined against 10 bacterial and 2 yeast strains. The level of the antimicrobial effects was established using an in vitro agar assay and minimum inhibitory concentration (MIC). In general ethanolic extract were more effective on gram positive bacteria than gram negative bacteria and strongest antimicrobial effect against Streptococcus pyogenes and Salmonella entritidis. Other tested bacteria and yeasts were sensitive to extract ranging from 4 to 16 mg/ml and more.
Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,
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