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Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological properties of water-based drilling fluid using other simple measurable properties. While mud density, marsh funnel, and solid% are key input parameters in this study, the output models are plastic viscosity, yield point, apparent viscosity and gel strength. The prediction methods have been applied on datasets taken from the final reports of two wells drilled in the Ahdeb oil field, eastern Iraq. To test the performance ability of the developed models, two error-based metrics (determination coefficient R2 and root mean square error have been used in this study. The current results support the evidence that MW, MF, and solid% are consistent indexes for the prediction of rheological mud properties. Both mud density and solid content have a relative-significant effect on increasing PV, YP, AV, and gel strength. The results also reveal that both MRA and ANN are conservative in estimating the fluid rheological properties, but ANN is more precise than MRA. Eight empirical mathematical models with high performance capacity have been developed in this study to determine the rheological fluid properties using simple and quick equipment such as mud balance and marsh funnel. This study presents cost-effective models to determine the rheological fluid properties for future well planning in Iraqi oil fields.

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Publication Date
Sun Sep 03 2023
Journal Name
Iraqi Journal Of Computers, Communications, Control & Systems Engineering (ijccce)
Efficient Iris Image Recognition System Based on Machine Learning Approach
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HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Chemical Sensor Based on a Hollow-Core Photonic Crystal Fiber
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In this work a chemical sensor was built by using Plane Wave Expansion (PWE) modeling technique by filling the core of 1550 hollow core photonic crystal fiber with chloroform that has different concentrations after being diluted with distilled water. The minimum photonic bandgap width is.0003 and .0005 rad/sec with 19 and 7 cells respectively and a concentration of chloroform that filled these two fibers is 75%.

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Publication Date
Sat Dec 01 2018
Journal Name
2018 Third Scientific Conference Of Electrical Engineering (scee)
A UWB Monopole Antenna Design based RF Energy Harvesting Technology
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Recently, wireless charging based RF harvesting has interfered our lives [1] significantly through the different applications including biomedical, military, IoT, RF energy harvesting, IT-care, and RFID technologies. Wirelessly powered low energy devices become significantly essential for a wide spectrum of sensing applications [1]. Such devices require for low energy resources from sunlight, mechanical vibration, thermal gradients, convection flows or other forms of harvestable energy [2]. One of the emerging power extraction resources based on passive devices is harvesting radio frequency (RF) signals powers [3]–[5]. Such applications need devices that can be organized in very large numbers, so, making separate node battery impractical.

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Scopus (14)
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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
Satellite Images Classification in Rural Areas Based on Fractal Dimension
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Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Iraqi stock market structure analysis based on minimum spanning tree
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tock markets changed up and down during time. Some companies’ affect others due to dependency on each other . In this work, the network model of the stock market is discribed as a complete weighted graph. This paper aims to investigate the Iraqi stock markets using graph theory tools. The vertices of this graph correspond to the Iraqi markets companies, and the weights of the edges are set ulrametric distance of minimum spanning tree.

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Publication Date
Sat Dec 30 2023
Journal Name
Wasit Journal For Pure Sciences
Honeywords Generation Technique based on Meerkat Clan Algorithm and WordNet
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The efficiency of the Honeywords approach has been proven to be a significant tool for boosting password security. The suggested system utilizes the Meerkat Clan Algorithm (MCA) in conjunction with WordNet to produce honeywords, thereby enhancing the level of password security. The technique of generating honeywords involves data sources from WordNet, which contributes to the improvement of authenticity and diversity in the honeywords. The method encompasses a series of consecutive stages, which include the tokenization of passwords, the formation of alphabet tokens using the Meerkat Clan Algorithm (MCA), the handling of digit tokens, the creation of unique character tokens, and the consolidation of honeywords. The optimization of t

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation
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The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order t

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Scopus (11)
Crossref (3)
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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Programming a Pneumatic Processes Sequence based on PLC by Demonstration
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Abstract

Pneumatic processes sequence (PPS) is used widely in industrial applications. It is common to do a predetermined PPS to achieve a specific larger task within the industrial application like the PPS achieved by the pick and place industrial robot arm. This sequence may require change depending on changing the required task and usually this requires the programmer intervention to change the sequence’ sprogram, which is costly and may take long time. In this research a PLC-based PPS control system is designed and implemented, in which the PPS is programmed by demonstration. The PPS could be changed by demonstrating the new required sequence via the user by following simple series of manual steps without h

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Publication Date
Mon Mar 01 2021
Journal Name
Iop Conference Series: Materials Science And Engineering
An efficient multistage CBIR based on Squared Krawtchouk-Tchebichef polynomials
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Abstract<p>Image databases are increasing exponentially because of rapid developments in social networking and digital technologies. To search these databases, an efficient search technique is required. CBIR is considered one of these techniques. This paper presents a multistage CBIR to address the computational cost issues while reasonably preserving accuracy. In the presented work, the first stage acts as a filter that passes images to the next stage based on SKTP, which is the first time used in the CBIR domain. While in the second stage, LBP and Canny edge detectors are employed for extracting texture and shape features from the query image and images in the newly constructed database. The p</p> ... Show More
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Publication Date
Wed Apr 20 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Text image secret sharing with hiding based on color feature
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Scopus (1)
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