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The Manufacture of Lead Acid Battery Separators using Locally Produced Polyethylene
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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Protection of Galvanized steel from corrosion in salt media using sulfur nanoparticles
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                The characteristics of sulfur nanoparticles were studied by using atomic force microscope (AFM) analysis. The atomic force microscope (AFM) measurements showed that the average size of sulfur nanoparticles synthesized using thiosulfate sodium solution through the extract of cucurbita pepo extra was 93.62 nm. Protecting galvanized steel from corrosion in salt media was achieved by using sulfur nanoparticles in different temperatures. The obtained data of thermodynamic in the presence of sulfur nanoparticles referred to high value as compares to counterpart in the absence of sulfur nanoparticles, the high inhibition efficiency (%IE) and corrosion resistance were at high temperature, the corrosion rate or weig

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Determination of essential and trace elements in various vegetables using ICP-MS
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Metal contents in vegetables are interesting because of issues related to food safety and ‎potential health risks. The availability of these metals in the human body ‎may perform many biochemical functions and some of them linked with various diseases at ‎high levels. The current study aimed to evaluate the concentration of various metals in ‎common local consumed vegetables using ICP-MS. The concentrations of metals in vegetables ‎of tarragon, Bay laurel, dill, Syrian mesquite, vine leaves, thymes, arugula, basil, common ‎purslane and parsley of this study were found to be in the range of, 76-778 for Al, 10-333 for B, 4-119 for ‎Ba, ‎2812‎-24645 for Ca, 0.1-0.32 for Co, 201-464 for Fe, 3661-46400 for K, 0.31–‎‎1.

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Publication Date
Thu Nov 18 2021
Journal Name
Frontiers In Public Health
Dentists' Practices and Attitudes Toward Using Personal Protection Equipment and Associated Drawbacks and Cost Implications During the COVID-19 Pandemic
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Objectives: During the COVID-19 pandemic, dentists have had to work under stressful conditions due to the nature of their work. Personal protection equipment (PPE) has become mandatory for work in the dentistry field. This study aimed to examine dentists' practices and attitudes regarding the use of PPE and the associated drawbacks and cost implications during the pandemic.

Methods: A questionnaire-based survey was used and was divided into five sections dedicated to collect demographic variables and to examine the dentists' practices, attitudes toward PPE, drawbacks, and cost of using PPE. Mann-Whitney U and Kruskal-Wallis tests were used to compare different sections of

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Determining and Predicting the Water Demand Dynamic System Model Mapping Urban Crawling and Monitoring Using Remote Sensing Techniques and GIS
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The problem of rapid population growth is one of the main problems effecting countries of the world the reason for this the growth in different environment areas of life commercial, industrial, social, food and educational. Therefore, this study was conducted on the amount of potable water consumed using two models of the two satellite and aerial images of the Kadhimiya District-block 427 and Al-Shu,laa district-block 450 in Baghdad city for available years in the Secretariat of Baghdad (2005, 2011,2013,2015). Through the characteristics of geographic information systems, which revealed the spatial patterns of urban creep by determining the role and buildings to be created, which appear in the picture for the

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Geological Journal
A Predictive Model for Estimating Unconfined Compressive Strength from Petrophysical Properties in the Buzurgan Oilfield, Khasib Formation, Using Log Data
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Unconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute

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Publication Date
Sat Apr 01 2023
Journal Name
Heliyon
A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
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Publication Date
Fri Feb 28 2025
Journal Name
Bmc Psychology
Delving into the Elements Impacting Treatment Acceptance among patients with Substance Use Disorder using Health Belief Model: a qualitative study
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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Determining and Predicting the Water Demand Dynamic System Model Mapping Urban Crawling and Monitoring Using Remote Sensing Techniques and GIS
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