This study investigates the phonotactics of English obstruent clusters in the word-final position from a markedness theory perspective among Iraqi EFL College Students whose native language, Arabic, prefers only two-member word-final obstruent cluster as a maximum. The markedness of clusters is measured depending on Iraqi EFL College Students’ utilization of the simplification strategies. This study tries to answer whether or not word-final obstruent clusters are marked or unmarked for Iraqi EFL College Students, and whether or not the markedness of the obstruent cluster increases as to its length. In order to answer these questions, a test has been distributed among 60 Iraqi EFL Fourth-Year College students, Department of English, Colleg

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Abstract: The research covered five chapters:       So, the first chapter definition of the research is from the introduction to the research and its importance, as the importance of the research lies in an expression of the reality of e-learning as it is one of the new patterns of the educational process and its role in enhancing communication and interconnectedness between the learners from the students ’point of view Physical Education and Sports Sciences for Girls, University of Baghdad, as for the problem The research was, and through the researcher’s acquaintance with many previous studies, references and sources, and being a student at the College of Physical Education and Sports Sciences - University of

MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022

This article proposes a new strategy based on a hybrid method that combines the gravitational search algorithm (GSA) with the bat algorithm (BAT) to solve a single-objective optimization problem. It first runs GSA, followed by BAT as the second step. The proposed approach relies on a parameter between 0 and 1 to address the problem of falling into local research because the lack of a local search mechanism increases intensity search, whereas diversity remains high and easily falls into the local optimum. The improvement is equivalent to the speed of the original BAT. Access speed is increased for the best solution. All solutions in the population are updated before the end of the operation of the proposed algorithm. The diversification f