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ijcpe-337
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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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%.

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Publication Date
Mon Jan 01 2018
Journal Name
Al–bahith Al–a'alami
News website Analytical: study of news sites (Iraqi Media network, The Seventh Day,Huffington Post Arabic
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This research focuses on the services provided by news websites (IMN, Youm7, Huffington Post Arabic) to its audience of Internet users, as well as materials posted through its pages, trying to monitor and explain them to identify their types & features, and it›s functions, whether informational or non-informational, to know the technical potential of each of the news sites, with the entry of the latest technology information. The research used the analysis method to achieve the research objectives within the period from 1/1 to 31/1/2017. The researchers used the content analysis tool as a research tool to analyze the news sites and to know the services they provide through their pages. The research was divided into three parts, the

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Publication Date
Fri Jan 01 2021
Journal Name
Environmental Pollution
Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Upgrading Sharky Baghdad Heavy Crude Oil
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Shaky Baghdad heavy crude oil 22 API is processed by distillation and solvent extraction. The purpose of distillation is to separate the light distillates    (light fractions) which represent 35% of heavy crude oil, and to obtain the reduced crude oil. The heavy residue (9 API) is  extracted with Iraqi light naphtha to get the deasphaltened oil (DAO), the extraction carried out with temperature range of 20-75 oC, solvent to oil ratio 5-15:1(ml:g) and a mixing time of 15 minutes. In general, results show that API of DAO increased twice the API of reduced crude oil while sulfur and metals content decreased 20% and 50% respectively. Deasphaltened oil produced from various operating conditions blended with the

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Publication Date
Thu May 10 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Securing Data in Wireless Body Area Network Using Hyper-Chaotic Zhou System
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  E-Health care system is one of the great technology enhancements via using medical devices through sensors worn or implanted in the patient's body. Wireless Body Area Network (WBAN) offers astonishing help through wireless transmission of patient's data using agreed distance in which it keeps patient's status always controlled by regular transmitting of vital data indications to the receiver. Security and privacy is a major concern in terms of data sent from WBAN and biological sensors. Several algorithms have been proposed through many hypotheses in order to find optimum solutions. In this paper, an encrypting algorithm has been proposed via using hyper-chaotic Zhou system where it provides high security, privacy, efficiency and

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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Biometric Identification System Based on Contactless Palm-Vein Using Residual Attention Network
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Palm vein recognition technology is a one of the most effective biometric technologies for personal identification. Palm acquisition techniques are either contact-based or contactless-based. The contactless-based palm vein system is considered more accurate and efficient when used in modern applications, but it may suffer from problems like pose variations and the delay in the matching process. This paper proposes a contactless-based identification system for palm vein that involves two main steps; First, the central region of the palm is cropped using fast extract region of interest algorithm, then the features are extracted and classified using altered structure of Residual Attention Network, which is a developed version of convolution

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Publication Date
Sat Nov 28 2020
Journal Name
Iraqi Journal Of Science
Activation and Enhancement of the Performance of Iraqi Ca-Bentonite for Using as Drilling Fluid in Iraqi Oil Fields
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In this study, Iraqi bentonite taken from Trefawi area/ Al-Anbar region province/ Iraq, was activated to enhance its rheological and filtration properties and increase its quality by decreasing the non-clay minerals (impurities), in order to be used in Iraqi oil companies instead of commercial bentonite. Bentonite was characterized by X-ray diffraction (XRD), X-ray fluorescence (XRF) and particle size distribution (PSD) before and after activation to show the effects on its mineral and chemical properties. The rheological properties of bentonite were enhanced by using different weights (0.4, 0.5, 0.6, 0.7 and 0.8 gm) of sodium carbonate (Na₂CO₃), whereas the filtration properties were enhanced by using different weights (0.5

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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks
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This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

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Publication Date
Wed Feb 01 2017
Journal Name
Iosr Journal Of Pharmacy And Biological Sciences
Role of Diffusion Weighted MRI in Evaluation of Urinary Bladder Cancer in Iraqi Patient in Correlation with Histopathological Grade.
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Publication Date
Fri Apr 22 2022
Journal Name
Neuroquantology
Effect of Some Essential Oils on American Cockroach Periplaneta Americana L
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Essential oils were extracted from Syzqiumoramac clove, Nigella sativa and eucalyptus oil for purpose of studying effect of these oils on adult cockroaches as repellents and extent of their attraction to them by treating biscuits with three concentrations (0.5, 0.25,1%). The results showed that clove oil was significantly more repellent than black seed oil at a concentration (1%), as average for five days was (0.32) compared to black seed oil (1.36). Insects attracted towards lunch averaged 7.58, 14 and this indicates fading of repellent effect due to penetration of the aroma of volatile clove oil. Results also showed that clove oil has a more lethal effect by direct spraying on nymphs and adults than black seed oil, as mortality in

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