The present study deals with the story of Epidemic in two literary works issued in the same year (1947). One of them is a novel titled "Plague" written by the French writer Alber Kamo, the second is a poem of the Iraqi poetess Nazik Al-Malaekah. The research reflects a contrastive study of the war vision in the two works as both writers used science to serve literature by using Epidemic as a metaphor to refer to the dangers that the societies faced.

The problem of the present research lies in answering the question about the reason that makes the two writers use metaphor while narrating the issues of the society instead of mentioning them directly and illuminate what implications do the narrative style of Epidemic story have and

Le présent travail aborde la question de l’enseignement de traduction en tant que matière faisant partie du programme élaboré dans des Départements de Français au sein de certaines universités irakiennes, en particulier celle de Bagdad. La méthode d’enseigner suivie constitue une véritable problématique qu’on a bien diagnostiquée à partir de quelques années d’expériences, à la lumière des observations faites dans des cours de traduction professionnelle, et dans la perspective des citations et témoignages établies par des traductologues et pédagogues et principalement par Marianne LEDERER qui a établi la Théorie Interprétative de la traduction. Mais pourquoi l’enseignement lui-même poserait une telle probl

The ability of insurance companies to achieve goals depends on their ability to meet customers' requirements, and this requires them to identify target markets and respond to needs and wishes of the markets, the skill is to convince the company to operate what is in the interest of the customer if he is convinced the customer service provided to him, he would repeat to deal with, and where the cost of maintaining existing customers is less than the cost of attracting new customers, the insurance companies that is working hard to maintain their customers, the more customer satisfaction with the services provided has increased loyalty and weakened the ability of competitors lured.

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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

The paired sample t-test for testing the difference between two means in paired data is not robust against the violation of the normality assumption. In this paper, some alternative robust tests have been suggested by using the bootstrap method in addition to combining the bootstrap method with the W.M test. Monte Carlo simulation experiments were employed to study the performance of the test statistics of each of these three tests depending on type one error rates and the power rates of the test statistics. The three tests have been applied on different sample sizes generated from three distributions represented by Bivariate normal distribution, Bivariate contaminated normal distribution, and the Bivariate Exponential distribution.

This paper consist some new generalizations of some definitions such: j-ω-closure converge to a point,  j-ω-closure directed toward a set, almost  j-ω-converges to a set, almost  j-ω-cluster point, a set  j-ω-H-closed relative, j-ω-closure continuous mappings, j-ω-weakly continuous mappings, j-ω-compact mappings, j-ω-rigid a set, almost j-ω-closed mappings and  j-ω-perfect mappings. Also, we prove several results concerning it, where j ÃŽ{q, δ,a, pre, b, b}.

  In this paper, we introduce and discuss an algorithm for the numerical solution of two- dimensional fractional dispersion equation.  The algorithm for the numerical solution of this equation is based on explicit finite difference approximation. Consistency, conditional stability, and convergence of this numerical method are described. Finally, numerical example is presented to show the dispersion behavior according to the order of the fractional derivative and we demonstrate that our explicit finite difference approximation is a computationally efficient method for solving two-dimensional fractional dispersion equation

In order to reduce hydrostatic pressure in oil wells and produce oil from dead oil wells, laboratory rig was constructed, by injecting LPG through pipe containing mixture of two to one part of East Baghdad crude oil and water. The used pressure of injection was 2.0 bar, which results the hydrostatic pressure reduction around 246 to 222 mbar and flow rate of 34.5 liter/hr fluid (oil-water), at 220 cm injection depth. Effects of other operating parameters were also studied on the behavior of two phase flow and on the production of oil from dead oil wells.

The Effect of the Addie and Shayer Model on the Achievement of Fifth Grade Students and their Attitudes towards History

1. Ahmed Hashim Mohammed and Hadil Jassas Ali

University of Baghdad - College of Education for Women

[email protected]

Abstract

The current research aims to examine the effect of the Adi and Shayer model on the achievement of fifth-grade students and their attitudes toward history. To achieve the research objective, the researcher has adopted two null hypotheses. 1) there is no statistically significant difference at the level o

This study aims to analyze the flow migration of individuals between Iraqi governorates using real anonymized data from Korek Telecom company in Iraq. The purpose of this analysis is to understand the connection structure and the attractiveness of these governorates through examining the flow migration and population densities. Hence, they are classified based on the human migration at a particular period. The mobile phone data of type Call Detailed Records (CDRs) have been observed, which fall in a 6-month period during COVID-19 in the year 2020-2021. So, according to the CDRs nature, the well-known spatiotemporal algorithms: the radiation model and the gravity model were applied to analyze these data, and they are turned out to be comp