Preferred Language
Articles
/
joe-1076
Artificial Neural Network (ANN) for Prediction of Viscosity Reduction of Heavy Crude Oil using Different Organic Solvents
...Show More Authors

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.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed Aug 09 2023
Journal Name
Applied Sciences
Effect of Crude Oil on the Geotechnical Properties of Various Soils and the Developed Remediation Methods
...Show More Authors

Crude oil still affects many countries because it is one of the essential fuel sources. It makes life more manageable in modern communities and cannot be overstated because it is easy to use and find. However, the pollution caused by its use in industries such as mining, transportation, and the oil and gas business, especially soil pollution, cannot be ignored. Soil pollution is an issue in most communities because it influences people and ecology. Accidental infusions and spills of ore oils are prevalent occurrences leading to the entire or fractional exchange of the soil pore fluid by oil-contaminated soils that have affected the geotechnical engineering properties. The liquid limitations for polluted soil grades silty loam and sa

... Show More
Scopus (10)
Crossref (12)
Scopus Clarivate Crossref
Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of Different Soil Organic Carbon Content in Different Soils on Water Holding Capacity and Soil Health
...Show More Authors
Abstract<p>An experiment was carried out to study the effect of soil organic carbon (SOC) and soil texture on the distance of the wetting front, cumulative water infiltration (I), infiltration rate (IR), saturated water conductivity (Ks), and water holding capacity (WHC). Three levels ( 0, 10, 20, and 30 g OC kg-1 ) from organic carbon (OC) were mixed with different soil materials sandy, loam, and clay texture soils. Field capacity (FC) and permanent wilting point (PWP) were estimated. Soil materials were placed in transparent plastic columns(12 cm soil column ), and water infiltration(I) was measured as a function of time, the distance of the wetting front and Ks. Results showed that advance we</p> ... Show More
View Publication
Scopus (7)
Crossref (4)
Scopus Crossref
Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
...Show More Authors

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

View Publication Preview PDF
Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
...Show More Authors

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

... Show More
View Publication Preview PDF
Scopus (18)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Mon Feb 20 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Text Encryption Algorithm Based on Chaotic Neural Network and Random Key Generator
...Show More Authors

This work presents a symmetric cryptography coupled with Chaotic NN , the encryption algorithm process the data as a blocks and it consists of multilevel( coding of character, generates array of keys (weights),coding of text and chaotic NN ) , also the decryption process consists of multilevel (generates array of keys (weights),chaotic NN, decoding of text and decoding of character).Chaotic neural network is used as a part of the proposed system with modifying on it ,the keys that are used in chaotic sequence are formed by proposed key generation algorithm .The proposed algorithm appears efficiency during the execution time where it can encryption and decryption long messages by short time and small memory (chaotic NN offer capacity of m

... Show More
View Publication Preview PDF
Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
...Show More Authors

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
...Show More Authors

In this paper, an enhanced artificial potential field (EAPF) planner is introduced. This planner is proposed to rapidly find online solutions for the mobile robot path planning problems, when the underlying environment contains obstacles with unknown locations and sizes. The classical artificial potential field represents both the repulsive force due to the detected obstacle and the attractive force due to the target. These forces can be considered as the primary directional indicator for the mobile robot. However, the classical artificial potential field has many drawbacks. So, we suggest two secondary forces which are called the midpoint

... Show More
View Publication Preview PDF
Publication Date
Thu Nov 29 2018
Journal Name
Al-khwarizmi Engineering Journal
Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
...Show More Authors

Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

... Show More
View Publication
Crossref (1)
Crossref
Publication Date
Sun Mar 01 2020
Journal Name
Iraqi Journal Of Physics
Study the performance of pentacene based organic field effect transistor by using monolayer, bilayer and trilayer with different gate insulators
...Show More Authors

In this paper, Pentacene based-organic field effect transistors (OFETs) by using different layers (monolayer, bilayer and trilayer) for three different gate insulators (ZrO2, PVA and CYEPL) were studied its current–voltage (I-V) characteristics by using the gradual-channel approximation model. The device exhibits a typical output curve of a field-effect transistor (FET). Source-drain voltage (Vds) was also investigated to study the effects of gate dielectric on electrical performance for OFET. The effect of capacitancesemiconductor in performance OFETs was considered. The values of current and transconductance which calculated using MATLAB simulation. It exhibited a value of current increase with increasing source-drain voltage.

View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sun Mar 01 2020
Journal Name
Iraqi Journal Of Physics
Study the performance of pentacene based organic field effect transistor by using monolayer, bilayer and trilayer with different gate insulators
...Show More Authors

In this paper, Pentacene based-organic field effect transistors (OFETs) by using different layers (monolayer, bilayer and trilayer) for three different gate insulators (ZrO2, PVA and CYEPL) were studied its current–voltage (I-V) characteristics by using the gradual-channel approximation model. The device exhibits a typical output curve of a field-effect transistor (FET). Source-drain voltage (Vds) was also investigated to study the effects of gate dielectric on electrical performance for OFET. The effect of capacitance semiconductor in performance OFETs was considered. The values of current and transconductance which calculated using MATLAB simulation. It exhibited a value of current increase with increasing source-drain voltage.

Preview PDF