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Measurement of Alpha Emitters Concentration in Tomato Fruits Using CR – 39 Plastic Track Detector
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Our country suffered from pollution translation as a result to the wars events, so, it is necessary to measure the amount of radiation in the fields that are of indirect contact with human life and health. The main aim of the present work is to measure the concentration of alpha emitters in tomato fruits collected from different farms in Al – Basra governorate in the south of Iraq. Nuclear track detectors of type CR – 39 are used as a detection device and Can technique as a detection technique. Results show that the maximum concentration recorded is sample no.7 of site Al – Rafidhya which was equal to (6.9621 ± 0.111) ppm and sample no.1 of site Lothan with concentration equals to (4.9236 ± 0.117) ppm. The minimum concentrations were in sample 6 of site Al – Lehaiss (1.5360 ± 0.084) ppm followed by sample 9 of site Malhan which recorded (1.6840 ± 0.111) ppm (20.208 ± 1.332 Bq/m3).

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Publication Date
Mon Mar 23 2020
Journal Name
Journal Of Engineering
Diagnosing Water Problem for Asmari Reservoir in Abu Ghirab Oilfield Using Analytical and Numerical Approaches
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Asmari is the main productive reservoir in Abu Ghirab oilfield in the south-east part of Iraq. It has history production extends from 1976 up to now with several close periods. Recently, the reservoir suffers some problems in production, which are abstracted as water production rising with oil production declining in most wells. The water problem type of the field and wells is identified by using Chan's diagnostic plots (water oil ratio (WOR) and derivative water oil ratio (WOR') against time). The analytical results show that water problem is caused by the channeling due to high permeability zones, high water saturation zones, and faults or fracturing. The numerical approach is also used to study the water movement insi

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Publication Date
Thu Apr 03 2025
Journal Name
Aip Conference Proceedings
Determining the Optimum Reference Orbits Using Lagrange’s Series for Geocentric Satellite in Low Earth Orbit
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The Taylor series is defined by the f and g series. The solution to the satellite's equation of motion is expanding to generate Taylor series through the coefficients f and g. In this study, the orbit equation in a perifocal system is solved using the Taylor series, which is based on time changing. A program in matlab is designed to apply the results for a geocentric satellite in low orbit (height from perigee, hp= 622 km). The input parameters were the initial distance from perigee, the initial time, eccentricity, true anomaly, position, and finally the velocity. The output parameters were the final distance from perigee and the final time values. The results of radial distance as opposed to time were plotted for dissimilar times in

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Publication Date
Sat Dec 21 2024
Journal Name
Edelweiss Applied Science And Technology
Using count regression models to investigate the most important economic factors affecting divorce in Iraq
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The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo

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Publication Date
Fri Sep 30 2022
Journal Name
Industrial Engineering & Management Systems
Optimizing the Complex Systems Reliability Using Mixed Strategy in Ultra-fast Gas Turbine Protection System
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Publication Date
Mon Sep 01 2008
Journal Name
Al-khwarizmi Engineering Journal
Correcting Working Postures in Water Pump Assembly Tasks using the OVAKO Work Analysis System (OWAS)
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Ovako Working Postures Analyzing System (OWAS) is a widely used method for studying awkward working postures in workplaces. This study with OWAS, analyzed working postures for manual material handling of laminations at stacking workstation for water pump assembly line in Electrical Industrial Company (EICO) / Baghdad. A computer program, WinOWAS, was used for the study. In real life workstation was found that more than 26% of the working postures observed were classified as either AC2 (slightly harmful), AC3 (distinctly harmful). Postures that needed to be corrected soon (AC3) and corresponding tasks, were identified. The most stressful tasks observed were grasping, handling, and positioning of the laminations from workers. The construct

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Publication Date
Tue Jun 14 2016
Journal Name
Transactions Of The Asabe
Using Terahertz Time-Domain Spectroscopy to Discriminate among Water Contamination Levels in Diesel Engine Oil
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Publication Date
Fri Mar 27 2020
Journal Name
Solid State Technology
Seepage and Slope Stability Analysis for Hemrin Earth Dam in Iraq Using Geo-Studio Software
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Publication Date
Fri Feb 28 2020
Journal Name
Neuroquantology
Studying the Swarm Parameters and Electron Transport Coefficients in N2– CH4 Mixtures Using BOLSIG+ Program
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Publication Date
Sun Jun 12 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Using Phone Calls to Promote Community Pharmacist Counselling during COVID-19 Pandemic in Baghdad, Iraq
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Drug consultation is an important part of pharmaceutical care. mobile phone call or text message can serve as an easy, effective, and implementable alternative to improving medication adherence and clinical outcomes by providing the information needed significantly for people with chronic illnesses like diabetes and hypertension particularly during pandemics like COVID-19 pandemic.

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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