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Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained were 96.5% and 93.47%, respectively, before applying balancing to the data. In addition, 98.59% and 97.18%, respectively, after applying the balancing technique The extreme gradient boosting (XGBoost) technique had been applied to selecting the important features and the Pearson correlation for finding the correlation between features.

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
The Musical Intelligence in kindergarten children
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The childhood of the important stages in which the adopted child's personality, mental and physical, motor and configure , as well as gain experience , it is the basis on which the future life of the child , studies have unanimously competent in the fields of childhood verily the first five years of a child of the most important stages of life and the most fertile life . Because the stage Childhood its an active role as the foundation upon which to build human personality , it was necessary to create all leads to raise the level of intelligence of children , because intelligence is the first element in the organization of thinking makes the child able to do the activities characterized by mental qualities .
Indicated most of the scien

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Publication Date
Sun Oct 10 2021
Journal Name
Journal Of Kirkuk University For Agricultural Sciences
Effect of Drought Stress (Water Deficit) and Plant Density on Productivity of Water and Zea mays (Baghdad Varieties) in Middle Region of Iraq
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The objective of this study was to investigate the drought stress and plant density possibility on water productivity and grain yield of maize (Zea mays L.) (Planting Baghdad 3 synthetic varieties), Field experiment was conducted at Abu Ghraib Research Station (Baghdad) during spring and Autumn seasons of 2016 using a randomized complete block design arranged in split plot with three replications. Three irrigation treatment included: irrigation after depletion 50% of available water (T1), irrigation after depletion 75% of available water (T2) and irrigation after depletion 90% of available water (T3) in the main plots and three plant density which were: 1 seeds hill-1 (D1) giving a uniform plant density of 66666 plants ha-1 , 2 seeds hill1

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of Applying Social Stories in Developing Social Interaction Skills among Children with Autism Spectrum Disorder
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Abstract

The current research aims to identify the effectiveness of social stories in increasing social interaction among children with an autism spectrum disorder. The researcher used the single-subject design methodology (Single Subject Designs, SSD) with

 (A-B) design to answer the research questions. The study sample consisted of (3) children with autism spectrum disorder enrolled in a transit daycare center in the Asir region, Saudi Arabia. The results of the study showed that there is a positive functional relationship between social stories and play to increase social interaction among children with autism spectrum disorder, which contributed to the acquisition and generalization of this behav

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Publication Date
Mon Feb 10 2025
Journal Name
Retos
The effect of the strategy to nominate ideas on divided and selective attention and perform some volleyball skills
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Introduction: Attention is a fundamental cognitive function in sports, particularly in volleyball, where players must process multiple stimuli and make rapid decisions. Effective attentional control can enhance an athlete’s ability to react to dynamic game situations. The nomination of ideas strategy. Objective: This study aims to examine the effectiveness of the nomination of ideas strategy in enhancing divided and selective attention and its subsequent impact on volleyball skill performance. Methodology: A controlled experimental design was employed, involving volleyball players divided into an experimental group and a control group. The experimental group integrated the nomination of ideas strategy into their training sessions,

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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
Fri Nov 01 2013
Journal Name
Journal Of Cosmetics, Dermatological Sciences And Applications
Treatment of gray hair in vitiligo patients by direct melanocytes transplant using needling micrografting and dermabrasion techniques
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KE Sharquie, AA Noaimi, HA Al-Mudaris, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 4

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Estimation the blast wave pressure effecters by apply Remote Sensing (RS) and Geographic Information System (GIS) techniques
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After the year 2003 terrorist attacks knock Baghdad city capital of Iraq using bomb explosion various, shook the nation, and made public resident of Baghdad aware of the need for better ways to protect occupants, assets, and buildings cause the terrorist gangs adopt style burst of blast to injury vulnerability a wider range form, and many structures will suffer damage from air blast when the overpressure concomitant the blast wave, (i.e., the excess over the atmospheric pressure 14.7 pounds per square inch at standard sea level conditions are about one-half pound per square inch or more(
to attainment injury. Then, the distance to which this overpressure level will extend depends primarily on the energy yield (§1.20) of the burst of

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Publication Date
Sun Dec 25 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Detection of Epicatechin in Camellia sinensis Leaves by Thin Layer Chromatography and High Performance Liquid Chromatography Techniques
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    The current study performed in order to detect and quantify epicatechin in two tea samples of Camellia sinensis (black and green tea) by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Extraction of epicatechin from black and green tea was done by using two different methods: maceration (cold extraction method) and decoction (hot extraction method) involved using three different solvents which are  absolute ethanol, 50% aqueous ethanol and water  for both extraction methods using room temperature and direct heat respectively. Crude extracts of two tea samples that obtained from two methods were fractionated by using two solvents with different polarity (chloroform and

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Publication Date
Sat Mar 10 2012
Journal Name
الدنانير
Cryptography Using Artificial Neural Network
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Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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