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Improving the BURT’s Sensitivity using Noise Calibration Unit via Crab Nebula Observations
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Radio observations from astronomical sources like supernovae became one the most important sources of information about the physical properties of those objects. However, such radio observations are affected by various types of noise such as those from sky, background, receiver, and the system itself. Therefore, it is essential to eliminate or reduce these undesired noise from the signals in order to ensure accurate measurements and analysis of radio observations. One of the most commonly used methods for reducing the noise is to use a noise calibrator. In this study, the 3-m Baghdad University Radio Telescope (BURT) has been used to observe crab nebula with and without using a calibration unit in order to investigate its impact on the signal. Radio observations of crab nebula have been carried out for different periods in 2022. Several parameters of the telescope have been calculated and analyzed using statistical measurements with and without using the noise calibration unit. Those parameters are receiver gain, system temperature, antenna temperature, and degree per flux unit. The results of this research revealed that the fluctuation sensitivity of BURT improved by about an order of magnitude, when the noise calibration unit is used. The root mean square error and the radiometer equation of the antenna temperature decreased to less than 33% and 10%, respectively in comparison to their initial values. In conclusion, the noise calibration unit plays a crucial role to improve the sensitivity of a radio telescope drastically.

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Publication Date
Thu Dec 06 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Enhancement of the Solubility and Dissolution Rate of Rebamipide by Using Solid Dispersion Technique (Part I)
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Solid dispersion is an attractive tool of pharmaceutical technology used to improve the physical properties of drugs. Among these properties is to enhance the solubility of the drugs.
Rebamipide is a poorly soluble drug of class IV of biopharmaceutical classification system (BCS).
Rebamipide is used as potent antiulcer, mucoprotective drug, by stimulating the generation of prostoglandine enhanced mucosal protection.
Rebamipide was formulated as a solid dispersion using different polymers such as pluronic F-127, PEG6000, PVP K30, and TPGS by using different preparation methods solvent evaporation, fusion, and kneading methods.
It was seen that rebamipide was successfully dispersed in a homogenous solid dispersion matrix by sol

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Tue Mar 26 2024
Journal Name
Scientific Reports
An in vitro assessment of the residual dentin after using three minimally invasive caries removal techniques
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Abstract<p>To evaluate the efficiency and effectiveness of three minimally invasive (MI) techniques in removing deep dentin carious lesions. Forty extracted carious molars were treated by conventional rotary excavation (control), chemomechanical caries removal agent (Brix 3000), ultrasonic abrasion (WOODPECKER, GUILIN, China); and Er, Cr: YSGG laser ablation (BIOLASE San Clemente, CA, USA). The assessments include; the excavation time, DIAGNOdent pen, Raman spectroscopy, Vickers microhardness, and scanning electron microscope combined with energy dispersive X-ray spectroscopy (SEM–EDX). The rotary method recorded the shortest excavation time (p < 0.001), Brix 3000 gel was the slowest. DIAGNOdent pen va</p> ... Show More
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Publication Date
Fri Jan 01 2021
Journal Name
Environmental Pollution
Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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Publication Date
Fri Apr 23 2021
Journal Name
International Journal Of Environmental Analytical Chemistry
Removal of levofloxacin and ciprofloxacin from aqueous solutions and an economic evaluation using the electrocoagulation process‏
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For this research, the utilisation of electrocoagulation (EC) toremove theciprofloxacin (CIP) and levofloxacin (LVX) from aqueous solutions was examined. The effective removal efficiencies are 93.47% for CIP and 88.00% for LVX, under optimum conditions. The adsorption isotherm models with suitable mechanisms were applied to determine the elimination of CIP and LVX utilizingtheEC method. Thefindingsshowed the adsorption of CIP and LVX on iron hydroxide flocs followed the Sips isotherm, with correlation coefficient values (R2) of 0.939 and 0.937. Threekinetic models were reviewed to determine the accurate CIP and LVX elimination methods using the EC method. The results showed that itfittedfor the second-order model, which indicated that the c

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Publication Date
Fri Apr 23 2021
Journal Name
International Journal Of Environmental Analytical Chemistry
Removal of levofloxacin and ciprofloxacin from aqueous solutions and an economic evaluation using the electrocoagulation process‏
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For this research, the utilisation of electrocoagulation (EC) toremove theciprofloxacin (CIP) and levofloxacin (LVX) from aqueous solutions was examined. The effective removal efficiencies are 93.47% for CIP and 88.00% for LVX, under optimum conditions. The adsorption isotherm models with suitable mechanisms were applied to determine the elimination of CIP and LVX utilizingtheEC method. Thefindingsshowed the adsorption of CIP and LVX on iron hydroxide flocs followed the Sips isotherm, with correlation coefficient values (R2) of 0.939 and 0.937. Threekinetic models were reviewed to determine the accurate CIP and LVX elimination methods using the EC method. The results showed that itfittedfor the second-order model, which indicated that the c

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Publication Date
Sat Oct 18 2025
Journal Name
مجلة العصر للعلوم الانسانية والاجتماع
Estimation of Flow Volume in Wadi Harran Basin in Eastern Iraq Using the SCS-CN Method
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Surface runoff is considered one of the most significant water resources in arid and semi-arid environments. Estimating the volume of surface runoff through the application of Geographic Information Systems (GIS), along with maps detailing the geomorphological and geological characteristics of the Wadi Haran basin, is an essential process. This estimation is supported by mathematical equations based on the Soil Conservation Service Curve Number method (SCS-CN), which is among the most widely used approaches for calculating runoff volume. The study area, Wadi Haran basin, covers approximately 1,895 km². The Curve Number (CN) was found to be 92, with runoff volume (QV) values ranging between 582.71 m³ and 12.85 m³. The total surfa

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Using the international standard for Training (ISO-10015) to Improve the Quality of the Control Activity – A Survey Study at the Federal Board of Supreme Audit.
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The great  importance of training made it as an investment for the organization, and assert the Quality of performance which support it by prepare the employee to the Current and future Jobs . The Research problem a rounded about How to measure the impact of training based on (ISO 10015) and its effect on the Quality of performance , How to evaluation the results of training to attained the training goals . The Research aims to find out the effects of application of international standard guidelines (ISO 10015) to attained the quality of audit work achieved in the Federal Board of Supreme Audit. The Research sought to achieve a number of objectives cognitive and applied on the basis of four key assumptions, and other su

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Publication Date
Mon Jan 02 2023
Journal Name
Pakistan Heart Jornal
The Effect of the Strategy of Differentiated Education According to the Auditory Learning Style by Using Assistance in Learning the Back Kick (T-Chagi) for the Young Players of …
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Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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