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Prediction of consolidation due to dewatering by using MATLAB software
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Publication Date
Tue Jun 27 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluating the Benefits of Using Mobile Application (diarrhea management step by step) in the Management of Diarrhea by Community Pharmacists
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Diarrhea is one of the most commonly encountered minor ailments in the community pharmacies. It is associated with significant morbidity and mortality. However, the majority of pharmacists in Iraq did not manage diarrheal cases in a proper way. Therefore, the current study aimed to evaluate the benefit of a new mobile application (diarrhea management step by step) to improve the pharmacist's role in the management of diarrhea. The study was conducted from 21th September to 21th October 2021 using a pre-post design via a simulated patient (SP) technique. A validated diarrhea scenario was presented to each pharmacist by the SP twice, once before and the other after giving the mobile application to the pharmacist. Furthermore, pharmaci

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Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
Biodegradation of Naphthalene by Aspergillus flavus Before and After Exposing to UV Light
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Aspergillus flavus was tested for its ability to degrade naphthalene by using solid mineral salts medium (SMS) with different concentrations 100, 300, 500 ppm of naphthalene. Results showed that 100ppm was the best concentration consumed by the fungal test then 300ppm and 500ppm the results for secondary test by using Liquid Mineral Salts Medium (LMSM) 95% of degradation for 100ppm then75% for 300ppm and 30% of degradation for 500ppm then the fungal test was tested for its ability to produce lignolytic enzymes results revealed that lignin peroxidase enzyme was only produced .then fungal test exposed to U.V light and the result showed after 10 minutes of U.V light exposure the degradation ratio were 91% for 100ppm then 79% for 300ppm and

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Engineering
Reinforcement of Asphalt Concrete by Polyester Fibers to Improve Flexural Bending Fatigue Resistance
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Reinforcing asphalt concrete with polyester fibers considered as an active remedy to alleviate the harmful impact of fatigue deterioration. This study covers the investigation of utilizing two shapes of fibers size, 6.35 mm by 3.00 mm and 12.70 mm by 3.00 mm with mutual concentrations equal to 0.25 %, 0.50 % and 0.75 % by weight of mixture. Composition of asphalt mixture consists of different optimum (40-50) asphalt cement content, 12.50 mm nominal aggregate maximum size with limestone dust as a filler. Following the traditional asphalt cement and aggregate tests, three essential test were carried out on mixtures, namely: Marshall test (105 cylindrical specimens), indirect tensile strength test (21 cylindrical specimens)

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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
Enhancement Solution to Improve Remediation of Soil Contaminated with Lead by Electrical Field
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A laboratory investigation of six different tests were conducted on silty clay soil spiked with lead in concentrations of 1500 mg/kg. A constant DC voltage gradient of 1 V/cm was applied for all these tests with duration of 7 days remediation process for each test. Different purging solutions and addition configurations, i.e. injection wells, were investigated experimentally to enhance the removal of lead from Iraqi soil during electro-kinetic remediation process. The experimental results showed that the overall removal efficiency of lead for tests conducted with distilled water, 0.1 M acetic acid, 0.2 M EDTA and 1 M  ammonium citrate as the purging solutions were equal to 18 %, 37 %, 42 %, and 29 %, respectively. H

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Publication Date
Sun Apr 16 2023
Journal Name
Iraqi Journal For Computer Science And Mathematics
Some Methods to Estimate the Parameters of Generalized Exponential Rayleigh Model by Simulation
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This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
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Publication Date
Thu Apr 04 2024
Journal Name
Journal Of Electrical Systems
AI-Driven Prediction of Average Per Capita GDP: Exploring Linear and Nonlinear Statistical Techniques
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Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

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Publication Date
Fri Aug 28 2020
Journal Name
Iraqi Journal Of Science
An application of Barnacle Mating Optimizer in Infectious Disease Prediction: A Dengue Outbreak Cases
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Meta-heuristic algorithms have been significantly applied in addressing various real-world prediction problem, including in disease prediction. Having a reliable disease prediction model benefits many parties in providing proper preparation for prevention purposes. Hence, the number of cases can be reduced. In this study, a relatively new meta-heuristic algorithm namely Barnacle Mating Optimizer (BMO) is proposed for short term dengue outbreak prediction. The BMO prediction model is realized over real dengue cases data recorded in weekly frequency from Malaysia. In addition, meteorological data sets were also been employed as input. For evaluation purposes, error analysis relative to Mean Absolute Percentage Error (MAPE), Mean Square Err

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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