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A Comparative Investigation of Different Ionospheric Models to Predict the MUF Parameter During Severe Geomagnetic Storm on 17th March 2015.
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The present work aimed to make a comparative investigation between three different ionospheric models: IRI-2020, ASAPS and VOACAP. The purpose of the comparative study is to investigate the compatibility of predicting the Maximum Usable Frequency parameter (MUF) over mid-latitude region during the severe geomagnetic storm on 17 March 2015. Three stations distributed in the mid-latitudes were selected for study; these are (Athens (23.50o E, 38.00o N), Jeju (124.53o E, 33.6o N) and Pt. Arguello (239.50o W, 34.80o N). The daily MUF outcomes were calculated using the tested models for the three adopted sites, for a span of five-day (the day of the event and two days preceding and following the event day). The calculated datasets were compared for each location with the observed daily MUF values. In general, the findings show that the three investigated models gave good outcomes compared to the observed values for all selected stations. The comparative investigation results of the three tested models corresponding to the observed MUF values during the storm event revealed that the IRI -2020 Model indicate a clear impact of the geomagnetic storm on the predicted MUF values during the day of event. Similarly, for ASAPS Model, the storm's impact is clear on both the day of the event and the subsequent day, in contrast, the VOACAP model showed almost no impact of the geomagnetic storm on the observed MUF values throughout the entire study period for event 17 March 2015.

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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Investigation of Electromagnetically Induced Transparency in the Rubidium Vapor
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We have studied theoretically the response of atomic three- level cascade scheme
of rubidium vapor to a strong laser under conditions in which electromagnetically
induced transparency would be induced on a weak probe beam. We show that the
medium that is an opaque to a probe laser can, by applying both lasers
simultaneously, be made transparent.

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Publication Date
Tue Mar 14 2023
Journal Name
Iraqi Journal Of Science
Analytical Study for the Annual TEC Parameter Variations for the Solar Cycle 24 over Iraqi Zone
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In this research, the TEC parameter has been determined for the ionosphere layer over the Iraqi zone. The calculations of this parameter have been conducted using the IRI model that considered as one of the recommended international models which used to calculate the ionosphere parameter (TEC). The determinations have been made for several sites or sites that located within the Iraqi territory. The years (2011-2013) of the solar cycle 24 have been adopted to make the determinations for the TEC parameter.The capital Baghdad has been selected to represent the transmitter station and many different communication points which are located in different directions around the transmitter station have been represented as receiving stations.

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Publication Date
Fri May 01 2015
Journal Name
2015 Ieee Congress On Evolutionary Computation (cec)
Differential evolution with adaptive repository of strategies and parameter control schemes
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A new Differential Evolution (ARDE) algorithm is introduced that automatically adapt a repository of DE strategies and parameters adaptation schemes of the mutation factor and the crossover rate to avoid the problems of stagnation and make DE responds to a wide range of function characteristics at different stages of the evolution. ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. Then a new adaptive procedure called adaptive repository (AR) has been developed to select the appropriate combinations of the JADE strategies and the parameter control schemes of the MDE_pBX to generate the next population based on their fitness values. Experimental results have been presented to confirm the reli

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
Intelligent Bat Algorithm for Finding Eps Parameter of DbScan Clustering Algorithm
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    Clustering is an unsupervised learning method that classified data according to similarity probabilities. DBScan as a high-quality algorithm has been introduced for clustering spatial data due to its ability to remove noise (outlier) and constructing arbitrarily shapes. However, it has a problem in determining a suitable value of Eps parameter. This paper proposes a new clustering method, termed as DBScanBAT, that it optimizes DBScan algorithm by BAT algorithm. The proposed method automatically sets the DBScan parameters (Eps) and finds the optimal value for it. The results of the proposed DBScanBAT automatically generates near original number of clusters better than DBScanPSO and original DBScan. Furthermore, the proposed method

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Publication Date
Sun Mar 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Simulation of five methods for parameter estimation and functionExponential distribution reliability
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The estimation process is one of the pillars of the statistical inference process as well as the hypothesis test, and the assessment is based on the collection of information and conclusions about the teacher or the community's teachers on the basis of the result
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Publication Date
Fri Jul 07 2023
Journal Name
Journal Of Obstetrics, Gynecology And Cancer Research
Evaluation of Maternal and Fetal Complications in Pregnant Women with Polycystic Ovary Syndrome (PCOS) with Severe and Mild Phenotype
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An essential issue in obstetrics is the prevalence of maternal and fetal complications in pregnant women with polycystic ovary syndrome (PCOS). The purpose of the present study was to investigate the prevalence of pregnancy complications among various phenotypes of pregnant women with PCOS.

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
A Molecular Investigation of Phytoplasma (Candidatus Phytoplasma) Infecting Arabic Jasmine (Jasminum sambac) in Iraq
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This study was conducted to investigate phytoplasma causing a virescence disease on Arabic jasmine Jasminum sambac based on microscopy and molecular approaches. Samples were collected from symptomatic Arabic jasmine plants grown in nurseries in Baghdad-Iraq. Specimens from infected plants were prepared and Dienes stained for light microscopy examination. Phytoplasma were detected in infected plants by polymerase chain reaction (PCR) using P1/P7 and SecAfor1/SecArev3 Candidatus Phytoplasma specific primer sets. Light microscopy test showed symptomatic Arabic jasmine plants were phytoplasms infected when phloem tissues were stained with a dark blue color. PCR test confirmed the symptomatic plants were phytoplasms infected when SecAfor1/Sec

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Engineering
Experimental Investigation of Natural Convection into a Horizontal Annular Tube with Porous Medium Effects
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In this work, an experimental investigation has been done for heat transfer by natural-convection through a horizontal concentric annulus with porous media effects. The porous structure in gap spacing consists of a glass balls and replaced by plastic (PVC) balls with different sizes. The outer surface of outer tube is isothermally cooled while the outer surface of inner tube is heated with constant heat flux condition. The inner tube is heated with different supplied electrical power levels. Four different radius ratios of annulus are used. The effects of porous media material, particles size and annulus radius ratio on heat dissipation in terms of average Nusselt number have been analyzed.

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Publication Date
Wed May 01 2019
Journal Name
Ieee International Electric Machines & Drives Conference (iemdc)
An Investigation of Short Translator Linear Machines for Use in a Free Piston Engine
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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
An Empirical Investigation on Snort NIDS versus Supervised Machine Learning Classifiers
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With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

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