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Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
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The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio toluene / n-Heptane)  at constant temperature. Experimentally the higher viscosity reduction was about from 135.6 to 26.33 cP when the mixture of toluene/heptane (75/25 vol. %) was added. The input parameters for the model were solvent type, wt. % of solvent, RPM and shear rate, the results have been demonstrated that the proposed model has superior performance, where the obtained value of R was greater than 0.99 which confirms a good agreement between the correlation and experimental data, the predicate for reduced viscosity and DVR was with accuracy 98.7%, on the other hand, the μ and DVR% factors were closer to unity for the ANN model.

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Publication Date
Sun Dec 06 2009
Journal Name
Baghdad Science Journal
Antimicrobial activity of grape fruit seed crude extract on microbial growth
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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.

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Publication Date
Fri May 01 2020
Journal Name
Iraqi Geological Journal
DETERMINATION OF PORE TYPES AND POROSITY TRENDS USING OF VELOCITY-DEVIATION LOG FOR THE CARBONATE MISHRIF RESERVOIR IN HALFAYA OIL FIELD, SOUTHEAST IRAQ
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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Modeling The Power Grid Network Of Iraq
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Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Engineering
A Prediction Formula for The Estimation of Sediment Load in The Upper Reach of Al-Gharraf River
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The presence of deposition in the river decreases the river flow capability's efficiency due to the absence of maintenance along the river. In This research, a new formula to evaluate the sediment capacity in the upstream part of Al-Gharraf River will be developed. The current study reach lies in Wasit province with a distance equal to 58 km. The selected reach of the river was divided into thirteen stations. At each station, the suspended load and the bedload were collected from the river during a sampling period extended from February 2019 till July 2019. The samples were examined in the laboratory with a different set of sample tests. The formula was developed using data of ten stations, and the other three s

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Publication Date
Tue Sep 30 2025
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Oxidation desulfurization of model oil using carbon composite derived from peach stone waste
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     In this study, oxidative desulfurization of dibenzothiophene (DBT) with H2O2 as an oxidant was studied, whereas the catalyst used was zirconium oxide supported on Activated carbon (AC). Zirconium oxide (ZrO2) was impregnated over prepared activated carbon (AC) and characterized by various techniques such as XRD, FTIR, BET, SEM, and EDX. This composite was used as a heterogeneous catalyst for oxidation desulfurization of simulated oil. The results of this study showed that ZrO2/AC composite exhibited significant catalytic activity and stability, effectively lowering sulfur content under mild conditions. Factors such as reaction temperature (30, 40, 50, 60°C), time (5, 10, 15,20,30,60, 80 100 min), catalyst dose (0.3, 0.5,

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Publication Date
Mon Dec 03 2018
Journal Name
Journal Of Engineering
Performance of Different Concatenated Coding Schemes for CDMA System
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In this paper different channel coding and interleaving schemes in DS/CDMA system over multipath fading channel were used. Two types of serially concatenated coding were presented. The first one composed of Reed-Solomon as outer code, convolutional code as inner code and the interleaver between the outer and inner codes and the second consist of convolutional code as outer code, interleaved in the middle and differential code as an inner code. Bit error rate performance of different schemes in multipath fading channel was analyzed and compared. Rack receiver was used in DS/CDMA receiver to combine multipath components in order to enhance the signal to noise ratio at the receiver.

 

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
The Adsorption of Some Trace Heavy Metals from Aqueous Solution Using Non Living Biomass of Sub Merged Aquatic Plant Ceratophyllum demersum
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Heavy metals contamination in aquatic ecosystems is considered one of the most important threats of aquatic life. Submerge aquatic plants Ceratophyllum demersum in its non living form used for the removal of trace elements. This article studied the ability of the fine powder of C.demersum for the removal of some heavy metals (HM) like copper, cadmium, lead and chrome from aqueous solution with in variable experimental factors. The study occupy two treatments the first included different hydrogen ions pH within a range of 4, 5,6and 8 with a constant HM concentration (1000 ppm).While the second treatment represented by using variable HM concentrations within a range of (250,500,750and 1000 ppm) with a constant pH=7.In both treatments the a

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Publication Date
Sat Jan 26 2019
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Secure Mobile Sink Node location in Wireless Sensor Network using Dynamic Routing Protocol
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The important device in the Wireless Sensor Network (WSN) is the Sink Node (SN). That is used to store, collect and analyze data from every sensor node in the network. Thus the main role of SN in WSN makes it a big target for traffic analysis attack. Therefore, securing the SN position is a substantial issue. This study presents Security for Mobile Sink Node location using Dynamic Routing Protocol called (SMSNDRP), in order to increase complexity for adversary trying to discover mobile SN location. In addition to that, it minimizes network energy consumption. The proposed protocol which is applied on WSN framework consists of 50 nodes with static and mobile SN. The results havw shown in each round a dynamic change in the route to reach mobi

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