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Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Pose Invariant Palm Vein Identification System using Convolutional Neural Network
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Palm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Improvement of Traffic Movement for Roads Network in Al-Kadhimiya City Center
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Numerous regions in the city of Baghdad experience the congestion and traffic problems. Due to the religious and economic significance, Al-Kadhimiya city (inside the metropolitan range of Baghdad) was chosen as study area. The data gathering stage was separated into two branches: the questionnaire method which is utilized to estimate the traffic volumes for the chosen roads and field data collection method which included video recording and manual counting for the volumes entering the selected signal intersections. The stage of analysis and evaluation for the seventeen urban roads, one highway, and three intersections was performed by HCS-2000 software.The presented work plots a system for assessing the level of service

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Publication Date
Thu Dec 20 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EVALUATION OF THE EFFICIENCY OF AL-WAHDA PLANT IN PURIFICATION OF POTABLE WATER: EVALUATION OF THE EFFICIENCY OF AL-WAHDA PLANT IN PURIFICATION OF POTABLE WATER
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Water samples were collected from output of water for Al-Wahda plant where located in al-karrada area in Baghdad city to study water contamination with bacteria, fungi and Algae. The study lasted one year started on August, 2016 to July,2017.Results were acquired according to two tests performed, the first is biological test included total coliform,E.coli, pseudomonas aeruginosa, total fungi, Diatom and non Diatom Algae and the second is physiochemical test included temperature, turbidity and residual chlorine. The results of bacteria were within the permitted specification in the Iraqi standards no. 14/2270 for the year 2015 except August was exceeded the permitted standard for total coliform, it was 1.1< cell/100 ml.Total Fungi, Dia

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Publication Date
Wed Oct 18 2023
Journal Name
Ieee Access
A New Imputation Technique Based a Multi-Spike Neural Network to Handle Missing Data in the Internet of Things Network (IoT)
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Publication Date
Sun Dec 01 2024
Journal Name
Nordic Concrete Research
Evaluating Concrete Strength Under Various Curing Conditions Using Artificial Neural Networks
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Abstract<p>This study examines the impact of different curing methods on the compressive strength of concrete. It investigates techniques such as air curing, periodic water spraying, full water submersion, and polyethylene encasement. Artificial neural network models were employed to evaluate the compressive strength under each curing condition. A model for calculating compressive strength that considers surrounding conditions was created using an artificial neural network. The current study’s figures were generated using this model. The research thoroughly examined the impact of curing environments and concrete mix components on strength properties, taking into account factors such as tempera</p> ... Show More
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Publication Date
Tue Nov 09 2021
Journal Name
Abu Dhabi International Petroleum Exhibition & Conference
Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field
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Abstract<p>Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit</p> ... Show More
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Publication Date
Thu Sep 19 2024
Journal Name
Baghdad Science Journal
Effects of Ultrasonic Treatment and Hydrogen Donor Addition on the Viscosity of Iraqi Heavy Crude Oil
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The current investigation examines the combined impacts of ultrasonic radiation and hydrogen donors on the viscosity of heavy crude oil. The impact of exposure time, power, duty cycle, and temperature on the viscosity of Iraqi heavy crude oil with 20.32 API was studied. Also, the viscosity of the oil samples, which were mixed with a hydrogen donor (decalin) and subjected to ultrasonic treatment under optimal conditions, was examined to evaluate the combined impact of ultrasonic radiation and hydrogen donor on the viscosity of crude oil. The viscosity experienced a decrease of 52.34% at 2 min of irradiation, 360 W ultrasonic power, 0.8 duty cycle, 35 ⁰C, and 8vol% decalin. To validate the outcomes of the experiments, asphaltene content, s

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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Publication Date
Sun Aug 30 2015
Journal Name
Statistical Analysis Of The Relations Between Api,specific Gravity And Sulfur Content In The Universal Crude Oil
Statistical Analysis of the Relations between API, Specific Gravity and Sulfur Content in the Universal Crude Oil
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

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