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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
Sun Mar 01 2015
Journal Name
Current Research In Microbiology And Biotechnology
Evaluation for the Cytotoxic Effect of Exotoxin A Produced by Pseudomonas aeruginosa on Mice by using Cytogenetic Parameters
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This research was conduct to evaluate the cytotoxic effect of exotoxin A (ETA) produced by Pseudomonas aeruginosa on mice in comparison with (phosphate buffer saline (PBS) as a negative control. The effect of the toxin was measured by employing the cytogenetic analysis which included (the mitotic index (MI), chromosomal aberrations (CAs), micronucleus (MN) and sperm abnormalities) parameters. In order to specify the cytotoxic effect of the toxin, three doses of ETA (125, 250 and 500 ng/ml) were used. Results showed that ETA was found to cause a significant decrease in mitotic index (MI) percentage, while significant increase in micronucleus (MN), chromosomal aberrations (CAs) and sperm abnormalities parameters in compression with control wa

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Publication Date
Tue Jan 01 2019
Journal Name
Chemical Industry And Chemical Engineering Quarterly
Optimization of dye adsorption process for Albizia lebbeck pods as a biomass using central composite rotatable design model
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Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison of Parameters Estimation Methods for the Negative Binomial Regression Model under Multicollinearity Problem by Using Simulation
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This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

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Publication Date
Tue Jan 01 2019
Journal Name
Chemical Industry And Chemical Engineering Quarterly
Optimization of dye adsorption process for Albizia lebbeck pods as a biomass using central composite rotatable design model
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Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi

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Publication Date
Tue Jan 12 2021
Journal Name
Pollution Research
DETERMINATION OF ANILINE IN WASTEWATER BY CLOUDPOINT EXTRACTION FOLLOWED BY HPLC USING 8-HYDROXYQUINOLINE AS A DERIVATIZATION AGENT
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A procedure, depending on the derivatization and determination of aniline was depicted andvalidated in this study. 8-hydroxyquinoline (8-HQ) was used as the derivatizing agent for thedetermination of aniline. An optimization study was performed for the derivatization reaction, i.e.,the diazonium coupling reaction, the optimum parameters were as follows: 22 mM of hydrochloricacid, 54mM of sodium hydroxide, and 1.8mM of sodium nitrate. The optimization study of themethod of cloud point extraction (CPE) revealed that the extraction solvent was 0.5 ml of Triton X-100, the optimum temperature was 90 °C, and the incubation time was 25 min. The linearity,correlation coefficients, molar absorptivities, and limits of detection were improved using t

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Publication Date
Mon May 04 2020
Journal Name
Environmental Engineering Research
Experimental and modeling study of water defluoridation using waste granular brick in a continuous up-flow fixed bed
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Contamination of surface and groundwater with excessive concentrations of fluoride is of significant health hazard. Adsorption of fluoride onto waste materials of no economic value could be a potential approach for the treatment of fluoride-bearing water. This experimental and modeling study was devoted to investigate for the first the fluoride removal using unmodified waste granular brick (WGB) in a fixed bed running in continuous mode. Characterization of WGB was carried out by FT-IR, SEM, and EDX analysis. The batch mode experiments showed that they were affected by several parameters including contact time, initial pH, and sorbent dosage. The best values of these parameters that provided maximum removal percent (82%) with the in

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Publication Date
Fri May 01 2015
Journal Name
Ieee Transactions On Microwave Theory And Techniques
On the Design of Gyroelectric Resonators and Circulators Using a Magnetically Biased 2-D Electron Gas (2-DEG)
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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and characterization of Posaconazole as a Nano-micelles using d-α-Tocopheryl polyethylene glycol 1000 succinate (TPGS)
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It is important to note that Posaconazole (POCZ) is a newly developed extended-spectrum triazole that belongs to BCS class II and has a solubility of less than 1µg/ml. In patients with a weakened immune system, POCZ has been shown to be effective as an antifungal treatment for invasive infections caused by candida and aspergillus species. The nano-micelles technique can be used to increase POCZ solubility. In order to increase their apparent solubility in water, nano-micelles are made by combining macromolecules that self-assemble into ordered structures capable of entrapping hydrophobic drug molecules in the interior domain. Dispersed colloidal systems, of which nano-micelles are a subset, are a large and diverse group. Composed of a p

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Publication Date
Wed Oct 01 2025
Journal Name
Chinese Journal Of Analytical Chemistry
Synthesis, characterization, antioxidant and bioactivity assessment, and thermodynamic analysis of metal ion complexes using a novel azo dye
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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Developing A Mathematical Model for Planning Repetitive Construction Projects By Using Support Vector Machine Technique
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Abstract<p>Each project management system aims to complete the project within its identified objectives: budget, time, and quality. It is achieving the project within the defined deadline that required careful scheduling, that be attained early. Due to the nature of unique repetitive construction projects, time contingency and project uncertainty are necessary for accurate scheduling. It should be integrated and flexible to accommodate the changes without adversely affecting the construction project’s total completion time. Repetitive planning and scheduling methods are more effective and essential. However, they need continuous development because of the evolution of execution methods, essent</p> ... Show More
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