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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
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Determination of Sulfacetamide Sodium in Pure and Their Pharmaceutical Formulations by Using Cloud Point Extraction Method
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      In this study, simple, low cost, precise and speed spectrophotometric methods development for evaluation of sulfacetamide sodium are described. The primary approach contains conversion of sulfacetamide sodium to diazonium salt followed by a reaction with p-cresol as a reagent in the alkaline media.  The colored product has an orange colour with absorbance at λmax 450 nm. At the concentration range of (5.0-100 µg.mL-1), the Beer̆ s Low is obeyed with correlation coefficient (R2= 0.9996), limit of detection as 0.2142 µg.mL-1, limit of quantification as 0.707 µg.mL-1 and molar absorptivity as 1488.249 L.mol-1.cm-1. The other approach, cloud point extraction w

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Decolorization of Phenol Red Dye by Immobilized Laccase in Chitosan Beads Using Laccase - Mediator - System Model
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This work describes the enhancement of phenol red decolorization through immobilizing of laccase in chitosan and enzyme recycling. Commercial laccase from white rot fungus, Trametesversicolor (Tvlac), was immobilizedin to freshly prepared chitosan beads by using glutaraldehyde as a cross linker. Characterization of prepared chitosan was confirmed by FTIR and scanning electron microscope (SEM). Tvlac (46.2 U/mL) immobilized into chitosan beads at 0.8 % glutaraldehyde (v/v) within 24 hrs. Synthetic (HBT) and natural (vanillin) mediators were used to enhance dye decolorizoation. It was found that 89 % of phenol red was decolorized by chitosan beads within 180 min. in the absence of enzyme and mediator, while decolorization percenta

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Measuring the impact of internal control on tax performance using balanced score card indicators: An applied research in a sample of the branches of the General Tax Authority in Iraq
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This research dealt with the impact of internal control on tax performance using balanced scorecard indicators because of its special importance in improving tax performance and reform. The internal control system is a safety valve for senior management in all organizations, it plays an important role in the regularity and development of work and the fight against corruption To provide reliable and accurate data and information, follow up on compliance with laws, regulations and instructions. The aim of this research is to demonstrate how control affects tax performance and how to adapt internal control components to improve tax performance. In the General Authority for taxes and its branches,. The research resulted in a number of conclu

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Publication Date
Thu Oct 03 2024
Journal Name
Retos
The effect of purposeful three-dimensional training on developing some motor abilities and skill performance among female fencing players
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O estudo destaca a necessidade crítica de se focar nas capacidades físicas, motoras e técnicas das jogadoras de esgrima, desenvolvendo e testando metodologias de treino modernas, baseadas na ciência, adaptadas às exigências específicas do desporto. O objetivo do estudo foi avaliar a eficácia do treino tridimensional visando melhorar as capacidades motoras e o desempenho técnico dos participantes. Recorrendo a um desenho experimental, o estudo envolveu a formação de grupos experimentais e de controlo. A amostra incluiu 16 esgrimistas da Faculdade Feminina de Educação Física e Ciências do Desporto. Após a exclusão de dois jogadores durante a fase exploratória, os restantes 14 foram divididos igualmente em grupos experimental

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Publication Date
Thu Oct 03 2024
Journal Name
Retos
The effect of purposeful three-dimensional training on developing some motor abilities and skill performance among female fencing players
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The study highlights the critical need to focus on the physical, motor, and technical abilities of female fencing players by developing and testing modern, scientifically-based training methodologies tailored to the specific demands of the sport. The study's objective was to assess the effectiveness of targeted three-dimensional training in enhancing the participants' motor skills and technical performance. Utilizing an experimental design, the study involved forming both experimental and control groups. The sample comprised 16 female fencers from the College of Physical Education and Sports Sciences for Girls. After excluding two players during the exploratory phase, the remaining 14 were evenly divided into experimental and contro

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Engineering
Development and Verification of the Capacity Curve for Two Dimensional Reinforced Concrete Moment-Resisting Frames System under Earthquake Loading
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Pushover analysis is an efficient method for the seismic evaluation of buildings under severe earthquakes. This paper aims to develop and verify the pushover analysis methodology for reinforced concrete frames. This technique depends on a nonlinear representation of the structure by using SAP2000 software. The properties of plastic hinges will be defined by generating the moment-curvature analysis for all the frame sections (beams and columns). The verification of the technique above was compared with the previous study for two-dimensional frames (4-and 7-story frames). The former study leaned on automatic identification of positive and negative moments, where the concrete sections and steel reinforcement quantities the

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Publication Date
Thu Sep 01 2016
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Performance evaluation of heterogeneous network based on RED and WRED
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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Water Quality Assessment of Al-Najaf City Potable Water Network
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 Water is an essential aspect of life and important in evolution. Recently the potable water quality topic has received much attention. The study aims to determine drinking water quality in Al-Najaf City by collecting samples throughout Al-Najaf city and comparing the results with the Iraqi guidelines (IQS 417) and World Health Organization (WHO) guidelines, as well as to calculate the WQI. Samples were tested in the laboratory between December 2021 and June 2022. The results showed that multiple parameters exceeded the allowable limits during both testing periods; during winter months, the results of TDS and turbidity exceeded the upper limits in multiple locations. Total hardness values also

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Publication Date
Fri Jun 01 2007
Journal Name
Journal Of Al-nahrain University Science
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
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The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

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Publication Date
Sun Jan 01 2023
Journal Name
Advances In Animal And Veterinary Sciences
Deleterious Effects of Mercuric Chloride Toxicity Initiated Partially from Physiological Disorder of Kidney, Immunocytes and Redox System, can be Reversed by Resveratrol Administration
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This study is designed to highlight some of the physiological disorders taken place in the renal function, immunological response as well as the ability of the redox system represented by total antioxidant capacity and malondialdehyde levels to combat the toxic exposure of mercuric chloride (HgCl2) with or without collaboration of resveratrol (RES) supplement. Forty-five adult Sprague Dawley, 8-10 weeks old female rats weighing 170-220 g were randomly grouped as following; control group (C) kept without any medication. Dimethyl sulfoxide (DMSO) used as vehicle to prepare RES treatment was given to D-group. RES administered to R-group. Challenge group of rats (HD) was administered HgCl2. The last group of rats (HR) was given HgCl2 with RES i

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