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bsj-2869
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
Thu Jan 01 2015
Journal Name
The 2d International Conference Of Buildings, Construction And Environmental Engineering (bcee2-2015)
Terrestrial Laser Scanning to Preserve Cultural Heritage in Iraq Using Monitoring Techniques
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Publication Date
Tue Jun 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Furfural Degradation in Waste Water by Advanced Oxidation Process Using UV/H2O2
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Furfural is one of the one of pollutants in refinery industrial wastewaters. In this study advanced oxidation process using UV/H2O2 was investigated for furfural degradation in synthetic wastewater. The results from the experimental work showed that the degradation of furfural decreases as its concentration increases, reaching 100% at 50mg/l furfural concentration and increasing the concentration of H2O2 from 250 to 500 mg/l increased furfural removal from 40 to 60%.The degradation of furfural reached 100% after 90 min exposure time using two UV lamps, where it reached 60% using one lamp after 240 min exposure time. The rate of furfural degradation k increased at the pH and initial concentratio

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Publication Date
Sat Jul 01 2017
Journal Name
2017 Computing Conference
Protecting a sensitive dataset using a time based password in big data
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Publication Date
Sun Jan 01 2017
Journal Name
Spe
SPE-188966-MS: Drilling problems detection in Basrah oil fields using smartphones
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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
Optimizing Task Scheduling and Resource Allocation in Computing Environments using Metaheuristic Methods
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Optimizing system performance in dynamic and heterogeneous environments and the efficient management of computational tasks are crucial. This paper therefore looks at task scheduling and resource allocation algorithms in some depth. The work evaluates five algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly Algorithm (FA) and Simulated Annealing (SA) across various workloads achieved by varying the task-to-node ratio. The paper identifies Finish Time and Deadline as two key performance metrics for gauging the efficacy of an algorithm, and a comprehensive investigation of the behaviors of these algorithms across different workloads was carried out. Results from the experiment

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t

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Publication Date
Thu Sep 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
USING ALUMINUM REFUSE AS A COAGULANT IN THE COAGULATION AND FLIOCCULATION PROCESSES
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The present work aims to study the efficiency of using aluminum refuse, which is available locally (after dissolving it in sodium hydroxide), with different coagulants like alum [Al2 (SO4)3.18H2O], Ferric chloride FeCl3 and polyaluminum chloride (PACl) to improve the quality of water. The results showed that using this coagulant in the flocculation process gave high results in the removal of turbidity as well as improving the quality of water by precipitating a great deal of ions causing hardness. From the experimental results of the Jar test, the optimum alum dosages are (25, 50 and 70 ppm), ferric chloride dosages are (15, 40 and 60 ppm) and polyaluminum chloride dosages were (10, 35 and 55 ppm) for initial water turbidity (100, 500 an

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Using Graph Mining Method in Analyzing Turkish Loanwords Derived from Arabic Language
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Loanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing lette

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Publication Date
Tue Oct 12 2021
Journal Name
Innovative Infrastructure Solutions
Facilitating claims settlement using building information modeling in the school building projects
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