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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 Sep 06 2015
Journal Name
Baghdad Science Journal
Disorder Activity of Some Enzymes Plays an Important Role in Pathological Mechanism of Rheumatoid Arthritis Disease
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The aim of this research to show the role of some enzymes in pathological mechanism of rheumatoid arthritis (RA) disease. Sixty patients with RA and matched number of apparently healthy volunteers were included in the study. Spectrophotometric methods were used to determine Peroxy nitrite (ONOO), Nitric oxide (NO), Nitric oxide synthase activity (NOS) cycloxygenase-2 activity (COX-2), glutathione peroxidase (GPX) activity and superoxide dismutase (SOD) activity in serum of both groups. Colorimetric assay kits were used to determine Iron. Rheumatoid factor (RF) was determined using Imuno-Latex kit. ONOO, NO levels, and NOS activity were significantly higher in the patients compared to the control group. Conversely, Iron level, SOD

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Publication Date
Thu Jun 30 2022
Journal Name
International Journal Of Drug Delivery Technology
Expression of Vascular Endothelial Growth Factor in the Placenta of Iraqi Women Complicated with Hypertensive Disorder
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During pregnancy, high blood pressure disorder is the most common medical complication in pregnancy. It is the foremost cause of maternal mortality and perinatal diseases. Vascular endothelial growth factor (VEGF) affects the growth of vascular endothelial cells, existence, and multiplying, which are known to be expressed in the human placenta. This study aimed to identify the expression VEGF in the placenta of hypertension and normotensive women. In this study, a cross-sectional study from november 2019 to February 2020. A total of 100 placentae involved 50 hypertensive cases and 50 normotensive groups were assessed. VEGF-A expression in two placentas groups was evaluated by immunohistochemistry techniques. Strong and moderate VEGF

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Community Detection in Modular Complex Networks Using an Improved Particle Swarm Optimization Algorithm
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     Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem.  In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Mechanical Science And Technology
Damage detection in glass/epoxy composite structure using 8–12 GHz X-band
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Publication Date
Sat Sep 01 2018
Journal Name
2018 15th European Radar Conference (eurad)
Delamination Detection in Glass-Fibre Reinforced Polymer (GFRP) Using Microwave Time Domain Reflectometry
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Publication Date
Sat Jun 04 2022
Journal Name
Al–bahith Al–a'alami
Iraq's Image in the British Press An analytical study of the Guardian and The Daily Telegraph for 1 / 1- 31/3/2019: Research extracted from a master's thesis
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The topic of the research dealt with the image of Iraq in the British press based on a sample of the newspapers (The Guardian and the Daily Telegraph), which are among the most important and largest newspapers in the United Kingdom and the world, because of its active role in guiding local and international public opinion towards important issues and events, Since these two newspapers are interested in the accuracy of sensitive political topics, the message aimed at knowing the media image that these two newspapers painted about Iraq in the period that was limited to the first quarter of 2019, and also to know the nature of the contents promoted by these newspapers about the Iraqi reality, The method of content analysis was used as an ap

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Publication Date
Sat Sep 21 2019
Journal Name
Journal Of The College Of Education For Women
Zanjan , Name and Origin: A Glimpse of Its History
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The aim of study is to shed light on an Islamic city which is unknown for a lot of people, it can have an old history in Parisian country and many events happen with it , This city is characterized with political, military, economic scientific ,and social features, This city is called Zanjan and it is one of the most important cities because it dates back to the period of post history and it has a good geographic location whereas it was, passage for trade caravans to pass through as well its land which was specialized in agriculture and industry. the study follows chronological order of historical events for the city, one of the most significant conclusions is to think that this city does belong to artifacts and it is an old city and it

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Publication Date
Tue Sep 15 2020
Journal Name
مجلة الاستاذ للعلوم الانسانية والاجتماعية
التدخل المبكر لنموذج مجموعة المهارات الاجتماعية الفورد بيكر لخفض التوحد الافتراضي لدى الاطفال
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المستخلص : هدفت البحث الحالي إلى بناء برنامج التدخل المبكر نموذج مجموعة المهارات الاجتماعية الفورد بيكر على وفق أساليب معرفية سلوكية، والتعرف على اثر البرنامج في خفض التوحد الافتراضي لدى الأطفال والتحقق من هذا الهدف وضعت الباحثة الفرضية الآتية لا توجد فروق ذو دلالة إحصائية بين متوسط رتب درجات أفراد المجموعة التجريبية في التطبيقين القبلي والبعدي على المقياس (CARS2-QPC). وقد اقتصر البحث الحالي على الأطفال من ذوي

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Publication Date
Sat Jan 01 2022
Journal Name
The International Journal Of Nonlinear Analysis And Applications
Developing Bulk Arrival Queuing Models with Constant Batch Policy Under Uncertainty Data Using (0-1) Variables
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This paper delves into some significant performance measures (PMs) of a bulk arrival queueing system with constant batch size b, according to arrival rates and service rates being fuzzy parameters. The bulk arrival queuing system deals with observation arrival into the queuing system as a constant group size before allowing individual customers entering to the service. This leads to obtaining a new tool with the aid of generating function methods. The corresponding traditional bulk queueing system model is more convenient under an uncertain environment. The α-cut approach is applied with the conventional Zadeh's extension principle (ZEP) to transform the triangular membership functions (Mem. Fs) fuzzy queues into a family of conventional b

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