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Directive and Steerable Radiation Pattern using SASPA Array
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This work examines the ability of a special type of smart antenna array known as Switched Active Switched Parasitic Antenna (SASPA) to produce a directive and electronically steerable radiation pattern. The SASPA array consists of antenna elements that are switchable between active and parasitic states by using P-Intrinsic-N (PIN) diodes. The active element is the element that is supplied by the radio frequency while short-circuiting the terminals of an element in the array results in a parasitic element. Due to the strong mutual coupling between the elements, a directional radiation pattern with high gain and a small beamwidth can be produced with only one active element operating at a time. By changing the parasitic state to the active state sequentially for all elements, the directed radiation pattern can be easily rotated. The antenna array structure used in this work is the uniform circular array (UCA) to achieve symmetrical radiation patterns and full coverage of the entire azimuth plane. Also, a novel method for reducing the mutual coupling effect in SASPA arrays is proposed in this work. By using this method, some parameters of the generated SASPA’s radiation pattern can be controlled. The simulated results obtained from this work depict that an N-element SASPA-UCA produces N-symmetrical, switchable, and steerable radiation patterns with high gain, small beamwidth, and a high Front-to-Back (F/B) ratio. Also, the results show that further improvements in these parameters can be achieved by increasing the number of elements in the array. Additional simulations demonstrate that by including decaying function weight in each element's circuitry, the mutual coupling between the components of the SASPA-UCA array can be minimized. The aforementioned parameters can then be efficiently modified using this mutual coupling reduction.

 

 

 

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Publication Date
Sun Sep 03 2023
Journal Name
Wireless Personal Communications
Application of Healthcare Management Technologies for COVID-19 Pandemic Using Internet of Things and Machine Learning Algorithms
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Publication Date
Tue Mar 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
An Experimental Assessment of Iraqi Local Cement and Cement Slurry Design for Iraqi Oil Wells Using Cemcade
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This effort is related to describe and assess the performance of the Iraqi cement sample planned for oil well-cementing jobs in Iraq. In this paper, major cementing properties which are thickening time, compressive strength, and free water in addition to the rheological properties and filtration of cement slurry underneath definite circumstances are experimentally tested. The consequences point to that the Iraqi cement after special additives encounter the requests of the API standards and can consequently is used in cementing jobs for oil wells. At this research, there is a comparative investigation established on experimental work on the effectiveness of some additives that considered as waste materials which are silica fume, baux

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Study electron transport coefficients for Ar, O<sub>2</sub> and their mixtures by using EEDF program
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Publication Date
Sun Jan 01 2017
Journal Name
Proceeding Of Second Thermal And Fluids Engineering Conference
Solidification Enhancement in Triplex-Tube Latent Thermal Energy Storage System Using a Combination of Nanoparticles and Fins
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Publication Date
Sat Apr 01 2017
Journal Name
2017 International Conference On Environmental Impacts Of The Oil And Gas Industries: Kurdistan Region Of Iraq As A Case Study (eiogi)
Inverse fluidized bed for chromium ions removal from wastewater and produced water using peanut shells as adsorbent
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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Tue Sep 07 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Wellbore instability management using geomechanical modeling and wellbore stability analysis for Zubair shale formation in Southern Iraq
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Abstract<p>Wellbore instability problems cause nonproductive time, especially during drilling operations in the shale formations. These problems include stuck pipe, caving, lost circulation, and the tight hole, requiring more time to treat and therefore additional costs. The extensive hole collapse problem is considered one of the main challenges experienced when drilling in the Zubair shale formation. In turn, it is caused by nonproductive time and increasing well drilling expenditure. In this study, geomechanical modeling was used to determine a suitable mud weight window to overpass these problems and improve drilling performance for well development. Three failure criteria, including Mohr–Coulomb, modifie</p> ... Show More
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Publication Date
Mon Jan 01 2024
Journal Name
Open Engineering
Using ANN for well type identifying and increasing production from Sa’di formation of Halfaya oil field – Iraq
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Abstract<p>The current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo</p> ... Show More
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Publication Date
Wed Jan 01 2020
Journal Name
Petroleum And Coal
Evaluation of geomechanical properties for tight reservoir using uniaxial compressive test, ultrasonic test, and well logs data
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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Genetic diversity of Capsicum annuum L. in local and imported samples in Iraq by using RAPD-PCR
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Genetic variation was studied in 22 local and imported samples collected from local Iraqi market by using random amplified polymorphic DNA (RAPD-PCR). Five randomly primers set were used in this study. These primers produced 292 bands. Molecular weights of these bands ranged between 1.8 Kb (1800 bp) to 150 bp. The percentage of polymorphic bands is 100%, with one distinguished band which is produced by using C52 primer. The other primers did not produce any distinguished band. The results of Dendrogram of the studied samples depended on RAPD-PCR results by using Jaccard coefficient for genetic similarity was distributed the samples into 8 groups. This Dendrogram revealed a higher similarity between Iraqi/Yousifia green bell pepper and Jo

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