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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 Jan 05 2014
Journal Name
Journal Of Educational And Psychological Researches
Attention Deficit Hyperactivity Disorders ADHD
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زاد الاهتمام بالأطفال ذوي اضطراب الانتباه المصحوب بالنشاط الزائد نظراً لانتشاره بين الأطفال في عمر المرحلة الابتدائية حيث تراوحت نسبته ما بين  3% إلى 20%  ومعظمهم من الذكور ، وأن انتشاره يقع في مختلف الطبقات الاجتماعية بالنسبة لعوائل هؤلاء الأطفال كما أن المشكلات المتعلقة به لا تنتهي بانتهاء مرحلة الطفولة ، وغالباً ما تمتد إلى مرحلة المراهقة حيث توصل ويز و هتكمانWeiss&Hechtman,1989  إلى أن هناك علامات م

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Publication Date
Thu Dec 31 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Measurement and accounting disclosure of intellectual capital using accounting models in the Iraqi insurance company
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The research aims to shed light on the possibility of measuring the intellectual capital in the Iraqi insurance company using accounting models, as well as disclosing it in the financial statements of the company, where human capital was measured using the present value factor model for discounted future revenues and the intellectual value-added factor model for measuring structural capital It was also disclosed in the financial statements based on the theory of stakeholders. The research problem lies in the fact that the Iraqi insurance company does not carry out the process of measuring and disclosing the intellectual capital while it is considered an important source for the company’s progress in the labor market recently. T

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Total Global Dominator Coloring of Trees and Unicyclic Graphs
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          A total global dominator coloring of a graph  is a proper vertex coloring of  with respect to which every vertex  in  dominates a color class, not containing  and does not dominate another color class. The minimum number of colors required in such a coloring of  is called the total global dominator chromatic number, denoted by . In this paper, the total global dominator chromatic number of trees and unicyclic graphs are explored.

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Publication Date
Sat Jan 25 2020
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Determination of the Dissociation Constants of Metformin from a Second Derivative UV Spectrum
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An environmentally begnin second derivative spectrometric approach was developed for the estimation of the dissociation constants pKa(s) of metformin, a common anti-diabetic drug.  The ultraviolet spectra of the aqueous solution of metformin were measured at different acidities, then the second derivative of each spectrum was graphed. The overlaid second derivative graphs exhibited two isobestic points at 225.5 nm and 244 nm pointing out to the presence of two dissociation constants for metformin pKa1 and pKa2, respectively. The method was validated by evaluating the reproducibility of the acquired results by comparing the estimated values of the dissociation constants of two different strategies that show excellent matching. As we

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Publication Date
Fri Feb 28 2025
Journal Name
International Journal Of Intelligent Engineering And Systems
MCNet: Mask Cell of Multi Class Deep Network for Blood Cells Detection and Classification
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Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

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Publication Date
Wed Jan 01 2020
Journal Name
Desalination And Water Treatment
Combination of the artificial neural network and advection-dispersion equation for modeling of methylene blue dye removal from aqueous solution using olive stones as reactive bed
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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
The Mental Disorder of mothers as a Mediating Variable Between Marital adjustment and Kindergarteners Development
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This current study aimed to explore the mediation effects of mother's mental health symptoms between marital adjustment and child development aspects. (666) participants of mothers and their children were the sample of the study. The researchers used the marital adjustment scale prepared by Manson, Morse, Lerner, Arthur, as well as, a package of tests for some aspects of growth Kindergarten children prepared by Kenawi and Mohamed (1999). In addition, theyemployed a list of modified symptoms (Symptom Checklist-90- Revised (SCL) -90-, prepared by Derogatis, Lipman and Lipogun & Cov (1976), The results of the current study showed there is a statistically significant relationship between marital adjustment and the symptoms of mental diso

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Publication Date
Sat Dec 17 2022
Journal Name
Iraqi Journal Of Laser
PDF Biosensing technique for detection of H.pylori bacteria: Israa M.L. SaQari*, Layla M.H. Al-ameri
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Abstract :H.pylori is an important cause of gastric duodenal disease, including gastric ulcers, Mucosa-associated lymphoid tissue (MALT), and gastric carcinoma. biosensors are becoming the most extensively studied discipline because the easy, rapid, low-cost, highly sensitive, and highly selective biosensors contribute to advances in next-generation medicines such as individualized medicine and ultrasensitive point-of-care detection of markers for diseases.  Five of ten patients diagnosed with H.pylori ranging in age from 15–85 participated in this research. who [gastritis, duodenitis, duodenal ulcer (DU), and peptic ulcer (PU)] Suspected H.pylori colonies w

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Publication Date
Mon Dec 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
Neural Networks as a Discriminant Purposes
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Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.  

 

 

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Detection of Leishmania tropica Using Nested-PCR and Some of Their Virulence Factors in Thi-Qar Province, Iraq
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Cutaneous leishmaniasis is one of endemic diseases in Iraq. It is considered as widely health problem and is an uncontrolled disease. The aim of the study is to identify of Leishmania species that cause skin lesions among patients in Thi-Qar Province, South of Iraq, also to detect some virulence factors of L. tropica. This study includes three local locations, Al-Hussein Teaching, Suq Al-Shyokh General and Al-Shatrah General Hospitals in Province for the period from the beginning of December 2018 to the end of September 2019. The samples were collected from 80 patients suffering from cutaneous leishmaniasis, both genders, different ages, various residence places and single and multiple lesions. Nested-PCR technique was

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