The dramatic series on television have a great impact on people’sattitudes towards dialects of language varieties, by relating theconceptual pictures or prototypes presented by series’ characters tothose dialects. This study aims to show the influence of TV series onIraqi university learners’ gender and age in relating positive ornegative semantic qualities to their dialects. To this end, 150 Iraqi EFLlearners have participated in this study to examine their attitudestowards Baghdadi, Mousli and Nasiriya dialects. The data arecollected by Lambert, Hodgson, Gardner, Fillenbaum's (1960)matched guise technique and then labeled by Willmorth’s (1988)subjective reaction test. A structured interview is conducted to supportthe data

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

Background:This is a prospective study of three children presented to us in the Orbital clinic in AL ShahidGazi Al Hariri Hospital with painless proptosiswith suspension of Hydatid disease.Objectives: : Orbital hydatid disease is a rare lesion accounting for less than 1% of the total lesions of the body (1, 2). Orbital cysts presented as a primary lesion in our study which is rare to have such lesion without involvement of other organs (3). Humans represent the intermediate host where the commonly affected organ are liver and the lung (10-15%) (4). Methods:This is a prospective study of three Children presented to us in the Orbital clinic in Al Shahid Ghazi Alhariri Hospital with painless proptosis with suspension of Hydatid disease, dep

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

This study revolves around the rapid changes of science and a comparison of the formal and practical aspects and the reason behind summoning the changes and their types, which are subject to the influence of the recipient. This transformation represents formal and intellectual production cycles and formal functional generation that is subject to the goals of the system of multiple differences at the level of time and place. It meets the needs and the request for change, but access to it comes through multiple systems and portals that are different from the normal and the usual, so this study was called (meta and its dimensions in the designed biological formation (virtual reality environment - a model). The research seeks to find solutio

Many literary research papers have dealt with the work of Margaret Atwood's The Handmaid's Tale (1985) as a feminist work. However, nearly few studies combine social oppression with religious extremism. To bridge this gap, the present study aims at exploring the use of totalitarian theocracy of terror to oppress its citizens in the name of religion. In other words, it explicates the way religion is used to brutally suppress and exploit people in general and vulnerable women in particular. To meet this objective, the study adopted the qualitative descriptive method to describe how religion is used as a contradictory controlling means in Gilead discourse. It also adopted the Foucault theory in analyzing the data of the study, illu

Because of its importance in the world, Middle East area is one of the competition areas between the major and great powers. Among those powers are Russia and United states of America. The competition between these two powers to control Syria is greatly clear since 2011. It is also one of the most important subject in the international politics. This importance comes from the importance of Russia and the United States of America besides importance of the Middle East. At the end of the cold war, United States of America maintained its role in the international system and became the only pole that dominated the international affairs while Russia tried to overcome the challenges inherited from the former Soviet Union, and it succeeded in th

  In this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the  and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.