The interest in art for young ages is seen as an obvious breakthrough and as revealing of psychological and health feelings in addition to emotions, and it is a treatment for those who suffer from behavioral disorders. The problem arose with the following question: What is the role of artistic expression in diagnosing behavioral disorders for primary school pupils? The aim of the research is to detect the behavioral disorders in the artistic expression of the female students' paintings from the teachers' point of view. The descriptive analytical approach was adopted as it is the appropriate method for identifying and estimating the characteristics and features related to people, places and things, and analyzing situations or phenomena as a

The current search aims to identify First: To measure the level of authoritarian personality among the students of the sample as a whole. Second: Measurement of differences in the level of authoritarian personality among students in the middle school according to the following variables 0.Science (literary, scientific) 8. Sex (male - female) Third: the level of control site level among the students of the sample as a whole. Ra'aa: Measurement of differences in the level of the control site among junior students according to the following variables 0.Science (literary, scientific) 8. Sex (male - female) Fifth: Explain the relationship between the authoritarian personality and the locus of control among the students of the research sample.

The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati

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

Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

The tensions and crises and the psychological pressure as well as the rapid changes and great development which is taking place in the present time. And  witnessing community of wars and conflicts that give rise to future concern among members of the community in general and students in particular, as it included the current research a number of chapters, the First chapter contains the research problem, the important goal, then set researcher terminology that has defined and contained in the title of research in the form (concern the future, artistic expression, middle school). The Second chapter included three sections, the first included the nature of adolescence and traits, characteristics and pr