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Evaluation of a fire safety risk prediction model for an existing building
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Abstract<p>Fire is one of the most critical risks devastating to human life and property. Therefore, humans make different efforts to deal with fire hazards. Many techniques have been developed to assess fire safety risks. One of these methods is to predict the outbreak of a fire in buildings, and although it is hard to predict when a fire will start, it is critical to do so to safeguard human life and property. This research deals with evaluating the safety risks of the existing building in the city of Samawah/Iraq and determining the appropriateness of these buildings in terms of safety from fire hazards. Twelve parameters are certified based on the National Fire Protection Association (NFPA2016) code. The concept of giving weight to each criterion was adopted to classify the criteria according to their importance and then conduct an on-site examination of these existing buildings to test the selected criteria. The result indicates a possible fire risk in these buildings due to the lack of compliance with fire safety instructions in the approved codes.</p>
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Medicinal And Chemical Sciences
An Evaluation of Activity of Prepared Zinc Nanoparticles with Extract Green Plant in Treatments of Diclofenac, Levofloxacin, and Tetracycline in Water
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Myrtle plant was washed, dried, and powdered after harvesting to produce a fine powder used in water treatment. An alcoholic extract was created from the myrtle plant using ethanol, which was then analyzed using GC-Mass, Fourier Transform Infrared spectroscopy, and ultraviolet-visible spectroscopy to identify the active components. Zinc nanoparticles were created using alcoholic extract. FT-IR, UV-Vis, SEM, EDX, and TEM were used to characterize zinc nanoparticles. Using a continuous processing procedure, zinc nanoparticles with myrtle extract and powder were employed to clean polluted water containing pesticides and antibiotic. First, 2 g of zinc nanoparticles was mixed with 20 ml of polluted water and the result was (Tetra 44%, Levo 32%),

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Publication Date
Thu Oct 15 2026
Journal Name
Journal Of Baghdad College Of Dentistry
An In Vitro Evaluation of the Effectiveness of Gotu Kola (Centella asiatica) on Inhibiting the Growth of Selected Microorganismsin Human Saliva
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Background: Gotu Kola (Centella asiatica) has been used as a traditional medicine for many years to cure different kinds of diseases. Studies have been reported that Gotu Kola extracts might be used as a cure for oral diseases such as periodontal disease. In the present study, Gotu Kola leaves extracted with water will be used to evaluate its effect on some microorganisms living in the human saliva using minimum inhibitory concentration (MIC) method. Material and Method:Gotu Kola fresh leaves extract have been used with water as a solvent, a rotary evaporator was used to separate the solvent from the extract. The following microorganisms: Streptococci, Lactobacilli, and Staphylococcus aureus have been isolated fromthe Saliva of ten voluntee

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Tue Jan 01 2013
Journal Name
Journal Of Engineering
Numerical Prediction of Bond-Slip Behavior in Simple Pull-out Concrete Specimen
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In this study the simple pullout concrete cylinder specimen reinforced by a single steel bar was analyzed for bond-slip behavior. Three-dimension nonlinear finite element model using ANSYS program was employed to study the behavior of bond between concrete and plain steel reinforcement. The ANSYS model includes eight-noded isoperimetric brick element (SOLID65) to model the concrete cylinder while the steel reinforcing bar was modeled as a truss member (LINK8). Interface element (CONTAC52) was used in this analysis to model the bond between concrete and steel bar. Material nonlinearity due to cracking and/or crushing of concrete, and yielding of the steel reinforcing bar were taken into consideration during the analysis. The accuracy of this

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Composites For Construction
Prediction of Concrete Cover Separation in Reinforced Concrete Beams Strengthened with FRP
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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Numerical Prediction of Bond-Slip Behavior in Simple Pull-Out Concrete Specimens
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In this study the simple pullout concrete cylinder specimen reinforced by a single steel bar was analyzed for bond-slip behavior. Three-dimension nonlinear finite element model using ANSYS program was employed to study the behavior of bond between concrete and plain steel reinforcement. The ANSYS model includes eight-noded isoperimetric brick element (SOLID65) to model the concrete cylinder while the steel reinforcing bar was modeled as a truss member (LINK8). Interface element (CONTAC52) was used in this analysis to model the bond between concrete and steel bar. Material nonlinearity due to cracking and/or crushing of concrete, and yielding of the steel reinforcing bar were taken into consideration during the analysis. The accuracy of t

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Rutting Prediction of Asphalt Mixtures Containing Treated and Untreated Recycled Concrete Aggregate
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Rutting is a crucial element of the mechanical performance characteristics of asphalt mixtures, which was the primary target of this study. The task involved substituting various portions of virgin coarse aggregate with recycled concrete aggregate materials that had been treated or left untreated at rates ranging from 25 to 100%, with a constant increase of 25%. The treatment process of recycled concrete aggregate involved soaking in acetic acid, followed by a mechanical process for a short time inside a Los Angeles machine without the balls. This research utilized two primary tests: the standard Marshall test to identify the optimal asphalt contents and the volumetric characteristics of asphalt mixtures. The other one w

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Composites For Construction
Prediction of Concrete Cover Separation in Reinforced Concrete Beams Strengthened with FRP
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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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