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Investigation of the State Vectors and Prediction of the Orbital Elements for Spot-6 Satellite during 1300 periods with Perturbations
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Abstract<p>Computer simulations were carried out to investigate the dependence of the main perturbation parameters (Sun and Moon attractions, solar radiation pressure, atmosphere drag, and geopotential of Earth) on the orbital behavior of satellite. In this simulation, the Cowell method for accelerations technique was adopted, the equation of motion with perturbation was solved by 4<sup>th</sup> order Runge-Kutta method with step (1/50000) of period to obtain the state vectors for position and velocity. The results of this simulation have been compared with data that available on TLEs (NORD data in two line elements). The results of state vectors for satellites (Cartosat-2B, Gsat-14 and Spot-6) shows excellent correlation and this is leading us to extend our study for (spot-6) satellite to include the orbital behavior during 13000 periods under the effect of one type of perturbation or all types. The results indicate that all perturbation have clear effect on spot-6 orbit, reduced the perigee and apogee about 3 Km. during 89 days, also the time of period reduced 4.7 sec. Other conclusions present that the perigee angle increases 28.01 degree with any perturbation accept SRP. Furthermore, the geopotential have a big periodic effect but the atmospheric drag have accumulated effect on most orbital elements.</p>
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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

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Publication Date
Tue Dec 03 2013
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Multiphase Flow Behavior Prediction and Optimal Correlation Selection for Vertical Lift Performance in Faihaa Oil Field, Iraq
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In the petroleum industry, multiphase flow dynamics within the tubing string have gained significant attention due to associated challenges. Accurately predicting pressure drops and wellbore pressures is crucial for the effective modeling of vertical lift performance (VLP). This study focuses on predicting the multiphase flow behavior in four wells located in the Faihaa oil field in southern Iraq, utilizing PIPESIM software. The process of selecting the most appropriate multiphase correlation was performed by utilizing production test data to construct a comprehensive survey data catalog. Subsequently, the results were compared with the correlations available within the PIPESIM software. The outcomes reveal that the Hagedorn and Brown (H

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment And Total Dissolved Solids Prediction For Tigris River In Baghdad City Using Mathematical Models
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Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

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Publication Date
Thu Nov 18 2021
Journal Name
Frontiers In Public Health
Dentists' Practices and Attitudes Toward Using Personal Protection Equipment and Associated Drawbacks and Cost Implications During the COVID-19 Pandemic
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Objectives: During the COVID-19 pandemic, dentists have had to work under stressful conditions due to the nature of their work. Personal protection equipment (PPE) has become mandatory for work in the dentistry field. This study aimed to examine dentists' practices and attitudes regarding the use of PPE and the associated drawbacks and cost implications during the pandemic.

Methods: A questionnaire-based survey was used and was divided into five sections dedicated to collect demographic variables and to examine the dentists' practices, attitudes toward PPE, drawbacks, and cost of using PPE. Mann-Whitney U and Kruskal-Wallis tests were used to compare different sections of

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Publication Date
Tue Mar 03 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Administrative performance and its relationship with the cognitive style (rigidity - flexibility) for management body members of the sport clubs
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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

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Publication Date
Thu Feb 29 2024
Journal Name
Iraqi Journal Of Science
Examining the Seasonal Correlations Among Different Ionospheric Indices During Solar Cycle Twenty-Four
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     The present work aimed to examine the nature and degree of the cross-correlations among three different ionospheric indices: these are Optimum Working Frequency (OWF), Highest Probable Frequency (HPF), and Best Usable Frequency (BUF). VOCAP and ASASPS models were adopted to determine the datasets of the selected ionospheric indices. The determination was made for different transceiver stations that provide certain HF connection links during the minimum and maximum years of solar cycle 24, 2009 and 2014, respectively. Matlab program was implemented to produce the geodesic parameters for the selected transceiver stations. The determination was made for different path lengths (500, 1000, 1500, and 2000) Km and bearings (0o, 45

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Publication Date
Mon Feb 24 2025
Journal Name
Advances In Structural Engineering
Experimental and numerical investigation on the behavior of composite reinforced concrete columns encased by steel section and hybrid GFRP section
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GFRP was employed in constructions as an alternative to steel, which has many advantages like lightweight, large tensile strength and resist corrosion. Existing researches are insufficient in studying the influence of hybrid reinforced concrete composite columns encased by GFRP I-section (RCCCEG) and I-section steel (RCCCES). In this study twenty one (RC) specimens of a cross-section of 130 mm × 160 mm, with different length (long 1600 mm and short 750 mm) were encased by using I-section (steel and GFRP) and tested under various loading (concentric, eccentric and flexural loads). The test was focused on the influence of many parameters; load-carrying capacity, mode of failure, deformation and drawing an interaction diagram (N-

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Publication Date
Sat Jun 19 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Development, Characterization and Pharmacological Investigation of Umbelliferone Conjugates of NSAIDs
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The present investigation developed the ester prodrugs of Non-steroidal anti inflammatory drugs (NSAIDs), Mefenamic acid and Flurbiprofen by conjugating with the natural antioxidant, 4-methyl umbelliferone that resulted the formation of Mefenamic acid-umbelliferone ester prodrug and Flurbiprofen-umbelliferone ester prodrug .The principal objective this study is the synthesis of the ester prodrugs of NSAIDs with the enhanced therapeutic activity and minimized side effects. Prodrugs were synthesized by coupling method using N,N- dicyclohexylcarbodiimide/4-dimethylaminopyrimidine, subjected to  physical, chemical characterization, spectral characterization (IR, 1H NMR, 13C NMR and Mass spectra),hydro

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