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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
Thu Jun 10 2021
Journal Name
مجلة حقائق للدراسات النفسية والاجتماعية
الضغوط الفسية والخوف من المستقبل لدى امهات اطفال طيف التوحدفي مدينة بغداد
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هدفت الدراسة التعرف على الضغوط النفسية والخوف من المستقبل لدى أمهات أطفال طيف التوحد، بلغت عينة الدراسة )60( ام لديهن طفل توحدي، تم استخدام المنهج الوصفي التحليلي وبعد تطبيق مقياسي الدراسة ومعالجة البيانات احصائيا توصلت الدراسة ان األمهات لديهن درجة عالية من الضغوط النفسية ودرجة عالية من الخوف حول مستقبل اطفالهن، وفي ضوء نتائج الدراسة خرجت الباحثة ببعض التوصيات والمقترحات.

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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
A Digital-Based Optimal AVR Design of Synchronous Generator Exciter Using LQR Technique
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In this paper a new structure for the AVR of the power system exciter is proposed and designed using digital-based LQR. With two weighting matrices R and Q,  this method produces an optimal regulator that is used to generate the feedback control law. These matrices are called state and control weighting matrices and are used to balance between the relative importance of the input and the states in the cost function that is being optimized. A sample power system composed of single machine connected to an infinite- bus bar (SMIB) with both a conventional and a proposed Digital AVR (DAVR) is simulated. Evaluation results show that the DAVR damps well the oscillations of the terminal voltage and presents a faster respo

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that

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Publication Date
Fri Aug 28 2015
Journal Name
Al-khwarizmi Engineering Journal
wavelength division multiplexing passive optical network modelling using optical system simulator
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Due to the continuing demand for larger bandwidth, the optical transport becoming general in the access network. Using optical fiber technologies, the communications infrastructure becomes powerful, providing very high speeds to transfer a high capacity of data. Existing telecommunications infrastructures is currently widely used Passive Optical Network that apply Wavelength Division Multiplexing (WDM) and is awaited to play an important role in the future Internet supporting a large diversity of services and next generation networks. This paper presents a design of WDM-PON network, the simulation and analysis of transmission parameters in the Optisystem 7.0 environment for bidirectional traffic. The simulation shows the behavior of optical

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Publication Date
Sun Jan 01 2012
Journal Name
Journal Of Educational And Psychological Researches
اضطراب ما بعد الضغوط الصدمية والعنف لدى طلبة الإعدادية
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Human beings are under the threat of the environment they are living in. With the course of time, they seriousness of this threat and its effect in changing their life . The most common threat that human beings might pass through is the trauma which is commonly bound with wars. The greater trauma that human beings might have is the threatening sudden facing or death facing. Consequently there would be disorder especially War disorder. This Phenomenon is clearly observed in Iraqi society as Iraq has been passing through continuous wars and disasters namely during and after the American Invasion. These events might lead to changes in Peoples  behavior and to Social Violence. Thus, the Study aims at:

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Publication Date
Thu Sep 01 2016
Journal Name
Physica Medica
Quantitative analysis of sentinel lymph node detection using a novel small field of view hybrid gamma camera (HGC)
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Introduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm

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Publication Date
Wed Aug 06 2025
Journal Name
مجلة الباحث
الاعراض الشائعة لدى اطفال التوحد وفقاً للدليل الاحصائي الخامس للاضطرابات النفسية والعقلية (DSM-5)
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   يُعد اضطراب طيف التوحد من الاضطرابات النمائية الأكثر انتشاراً، ويشكل تحدي للأُسرة والمجتمع بأكمله، وتنوعت أساليب تشخيصه حسب الأعراض الظاهرة، وينبغي ان يتم التفريق بين هذا الإضطراب والاضطرابات النمائية الاخرى، كذلك هدف البحث إلى إعداد أداة لقياس هذا الإضطراب وفقا للدليل الإحصائي الخامس للإضطرابات النفسية والعقلية (DSM-5 ، وكذلك تعرف أكثر الأعراض شيوعاً لدى عينة من اطفال اضطراب طيف التوحد بلغت (60)

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Publication Date
Fri Jan 01 2016
Journal Name
International Journal Of Wireless And Mobile Computing
A comprehensive simulation study of a network-based distributed mobility management framework
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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Assessing the Potentiality of Using CXCL9 as A Predictive Biomarker for Acute and Chronic Toxoplasmosis, and Study the Correlation Between CXCL9, Toxoplasmosis and Thyroid Disorder in These Cases
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     Background:  Chemokine (C-X-C motif) ligand (CXCL9) has an important role recruiting the T-lymphocytes and immune response after infection by inducing T-cells accumulation around the areas associated with infections. However, this role is poorly known in relation with Toxoplasma gondii infection and also in association with thyroid hormones, which the present study is focused on. Methods: Eighty-seven women were included in this study for the period between September 2021 and February 2022. Blood samples of uninfected healthy pregnant, in addition to aborted and pregnant women infected with toxoplasmosis, were collected. Sera were then obtained and stored at -10°C. Toxo-latex agglutination test was done, followed by detec

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