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Roadway Deterioration Prediction Using Markov Chain Modeling (Wasit Governorate/ Iraq as a Case Study)
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Publication Date
Sun Jun 25 2023
Journal Name
Tikrit Journal Of Pure Science
Chemical comparison and Trichomes types of Salvia species growing in Anbar Governorate – Iraq
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The trichomes and chemical composition of three species of the genus Salvia wild-grown (Salvia lanigera, Salvia spinosa) and cultured (Salvia officinalis) were studied in the Anbar governate, the chemical components of the stem and leaves were studied by Gas chromatography–mass spectrometry(GC-MS), in addition to studying the trichomes of the epidermis in the stem and leaves (upper and lower epidermis) by Light microscope. Important differences appeared to us in the chemical study, where it was found that some compounds were found in species without others, which gives them taxonomic importance, also, the trichomes were important in distinguishing the studied species, the species S. spinosa was distinguished by the presence of gla

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Publication Date
Wed Dec 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Dental Caries and Treatment Needs among Kindergarten Children in Al-Basrah Governorate/Iraq
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Background: Dental caries is a disease occurs in the world in both developed and developing countries, it is still widespread among children and it can be controlled but not eliminated , most of tooth loss occurs due to dental caries and its complications. The aim of this study was to estimate the occurrence, and severity of dental caries and treatment needs among kindergarten children in Al-Basrah governorate. Materials and methods: The sample consisted of 1000 kindergarten children at age of 4-5 years old (445 boys and 555 girls) from urban areas in Al-Basrah city. Diagnosis and recording of dental caries and treatment needs were done according to the criteria of WHO (1987). Results: The percentage of dental caries was (80.8%) of the tota

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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Prediction of consolidation due to dewatering by using MATLAB software
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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Wed Nov 06 2024
Journal Name
2024 17th International Conference On Development In Esystem Engineering (dese)
Improving Cardiovascular Prediction Performance Using Machine Learning Based Feature Selection
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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study Using the Passive Solar Chimney for Evaporative Cooling With PCM and CFM as a Thermal Energy Storage
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      In this work, a test room was built in Baghdad city, with (2*1.5*1.5) m3  in dimensions, while the solar chimneys (SC) were designed with aspect ratio (ar) bigger than 12. Test room was supplied by many solar collectors; vertical single side of air pass with ar equals 25, and tilted 45o double side of air passes with ar equals 50 for each pass, both collectors consist of flat thermal energy storage box collector (TESB) that covered by transparent clear acrylic sheet, third type of collector is array of evacuated tubular collectors with thermosyphon in 45o instelled  in the bottom of TESB of vertical SC. The TESB was

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
The study of some physical and chemical characteristics in drinking water treatment plant of Jurf Al- Sakar subdestric in Babylon governorate, Iraq
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Some physical and chemical characteristics of Jurf Al- Sakar drinking water plant in Babylon governorate have been studied. Seven locations for this plant were selected. These were the drinking water treatment plant source on Euphrates River before entering the plant, precipitation, filtration and collection tanks, and also after leaving the plant at distances of one meter, 4 and 8 km. The samples were collected bimonthly from October, 2002 to August, 2003. Some results match with the national and international standard characters while the other characters (Turbidity, total hardness, calcium, nitrate, phosphate and the biological oxygen demand values) were not match. The present study showed that drinking water treatment plant is undrinka

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Laboratory Study for Biodegradation of Oxymatrine Insecticide by Single and Mixed Cultures of Fungi Isolated from Agriculture Soils in Basrah Governorate, Iraq
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This study focuses on the biodegradation of oxymatrine insecticide by some soil fungi isolated from four agriculture stations. The results showed that the highest degradation rate 94.66% was recorded by Ulocladium sp. at 10 days and A. niger recorded the lowest degradation rate 45.86%, while at 20 days Ulocladium sp. also showed the highest degradation rate 94.98% and the lowest degradation rate reached to 82.49% with A.niger. The mix (Exerohilum sp.+Ulocladium sp.) recorded the highest degradation rate of oxymatrine insecticide 90.22%, 88.51%, 85.34%  at 4, 8 and 12 ppm.The use of mixed isolates enhanced the biodegradation process. There is no study of oxymatrine biodegradation

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