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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 CNNs have shown improved accuracy in the classification of ASD compared to traditional machine learning algorithms, on all these datasets with higher accuracy of 99.45%, 98.66%, and 90% for Autistic Spectrum Disorder Screening in Data for Adults, Children, and Adolescents respectively as they are better suited for the analysis of time series data commonly used in the diagnosis of this disorder

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Publication Date
Mon May 31 2021
Journal Name
Iraqi Geological Journal
Mechanical Rock Properties Estimation for Carbonate Reservoir Using Laboratory Measurement: A Case Study from Jeribe, Khasib and Mishrif Formations in Fauqi Oil Field
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Estimation of mechanical and physical rock properties is an essential issue in applications related to reservoir geomechanics. Carbonate rocks have complex depositional environments and digenetic processes which alter the rock mechanical properties to varying degrees even at a small distance. This study has been conducted on seventeen core plug samples that have been taken from different formations of carbonate reservoirs in the Fauqi oil field (Jeribe, Khasib, and Mishrif formations). While the rock mechanical and petrophysical properties have been measured in the laboratory including the unconfined compressive strength, Young's modulus, bulk density, porosity, compressional and shear -waves, well logs have been used to do a compar

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Publication Date
Thu Apr 11 2024
Journal Name
Hemodialysis International
Using cryotherapy, <scp>EMLA</scp> (eutectic lidocaine/prilocaine) cream, or lidocaine spray to reduce pain during arteriovenous fistula puncture: A randomized controlled trial
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Abstract<sec><title>Introduction

In hemodialysis patients, pain associated with needle insertion into an arteriovenous fistula is a physical and psychological problem. The aim of this study was to assess the effectiveness of pre‐puncture application of an ice pack, EMLA cream, or lidocaine spray to reduce pain associated with access puncture.

Methods

This was a multicenter study done in nine hemodialysis centers in Iraq. The study utilized a randomized, parallel‐group design, in which patients being dialyzed using an arteriovenous access were allocated into one of four groups. Access puncture was preceded by nothing (contr

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Oral Medicine And Oral Surgery
Evaluating dental implant stability using three devices Osstell<sup>®</sup>, Periotest<sup>®</sup>, and AnyCheck<sup>®</sup>: a clinical study
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Introduction: Implant stability is usually measured with resonance frequency analysis (RFA) and damping capacity assessment (DCA). This study aimed to measure primary and secondary stabilities using 3 devices that are based on these methods, namely; RFA (Osstell®) and DCA (Periotest® and AnyCheck®) to assess the correlations of the measurements obtained by these devices and the correlations between implant stability and insertion torque. Material and Methods: This observational prospective study included 35 dental implants. The implant stability was measured using the 3 devices. Mann–Whitney U

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Classical and Statistical Optimization of Medium Composition for Promoting Prodigiosin Produced by Local Isolate of Serratia Marcescens
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Prodigiosin is a ‘natural red pigment produced by Serratia marcescens which exhibits immunosuppressive and anticancer properties in addition to antimicrobial activities. This work presents an attempt to maximize the production of prodigiosin by two different strategies: one factor at time (OFAT) and statistical optimization. The result of OFAT revealed that sucrose and peptone were the best carbon and nitrogen sources for pigment production with concentration of prodigiosin of about 135 mg/ L. This value was increased to 331.6mg/ L with an optimized ratio of C/N (60:40) and reached 356.8 with pH 6 and 2% inoculum size at end of classical optimization. Statistical experimental design based on Response surface methodology was co

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Modeling and Simulation of Solar Module performance using Five Parameters Model by using Matlab in Baghdad City
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This work presents the modeling of the electrical response of monocrystalline photovoltaic module by using five parameters model based on manufacture data-sheet of a solar module that measured in stander test conditions (STC) at radiation 1000W/m² and cell temperature 25 . The model takes into account the series and parallel (shunt) resistance of the module. This paper considers the details of Matlab modeling of the solar module by a developed Simulink model using the basic equations, the first approach was to estimate the parameters: photocurrent Iph, saturation current Is, shunt resistance Rsh, series resistance Rs, ideality factor A at stander test condition (STC) by an ite

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Publication Date
Tue Jul 01 2025
Journal Name
المجلة العراقية للعلوم الاقتصادية
Using the Hybrid ARDL–GRU Model in Investigating the Dynamic Relationship between Dinar Deposits and US Dollar Payments at the Central Bank of Iraq
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This research examines the relationship between dinar deposits and U.S. dollar payments at the Central Bank of Iraq using monthly data for the period 2016–2025. The ARDL model, the GRU neural network, and a hybrid ARDL–GRU model are applied. The results show that dollar payments are stationary at level, while dinar deposits become stationary after first differencing, with a significant positive long-run cointegrating relationship. The linear ARDL model has limited ability to capture sudden shocks, whereas the hybrid ARDL–GRU model achieves superior forecasting performance both in-sample and out-of-sample. The findings confirm the Central Bank of Iraq’s efficiency in managing domestic and foreign liquidity and maintaining market stab

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Tue Feb 21 2017
Journal Name
Biomechanics And Modeling In Mechanobiology
A novel method for non-invasively detecting the severity and location of aortic aneurysms
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The influence of an aortic aneurysm on blood flow waveforms is well established, but how to exploit this link for diagnostic purposes still remains challenging. This work uses a combination of experimental and computational modelling to study how aneurysms of various size affect the waveforms. Experimental studies are carried out on fusiform-type aneurysm models, and a comparison of results with those from a one-dimensional fluid–structure interaction model shows close agreement. Further mathematical analysis of these results allows the definition of several indicators that characterize the impact of an aneurysm on waveforms. These indicators are then further studied in a computational model of a systemic blood flow network. This demonstr

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Corrosion And Scale Inhibition
Enhancing of corrosion protection properties of stainless steel 316L using chemically synthesized thin film poly(pyrrole-co-p-toluidine) coating on SS316L surface in a 3.5 wt.% NaCl medium
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Publication Date
Thu Mar 21 2024
Journal Name
International Development Planning Review
THE EFFECT OF USING A DISABLING FORCE TRAINING TOOL ON WALKING PERFORMANCE: AN ANALYTICAL STUDY OF TIME AND STEP LENGTH IN THE 20 KM WALKING RACE EVENT FOR APPLICANTS
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