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

War as a human phenomenon, has its own literature. Poetry is a major genre in this literature. This paper is an attempt to investigate and analyse some stylistic features in two selected, English and Arabic, war poems. These poems share the same theme.Both promote the principle of sacrificing one’s own life for the sake of homeland.  This paper limits itself to analyse, thecontent words, tenses, semantic grouping of vocabulary and foregrounding in the two poems. The areas of analysis show great similarities in distributing the general content words (nouns, verbs, adjectives, and adverbs). In the analysis of the semantic areas of each content word, these poems reveal some similarities and some differences in their frequency rates.

This research provides a new method to study praise poetry that can be used as a course to teach English and Arabic to students in the College of Education. This research answers two questions: Is it possible to examine praise poetry as a tagmeme? Is this analysis of great help in teaching English and Arabic to students in the College of Education? The data that will be chosen for the purpose of analysis are two of Shakespeare's sonnets and two of AL Mulik's poems. The sonnets selected for this purpose are 17 and 18. AL Mulik's poems selected for the same purpose are 8 and 9. Each line in both English and Arabic data is numbered by the researcher herself. Then, those lines are grouped into sentences to facilitat

DBN Rashid, 2012 - Cited by 2

osion and deposition are natural phenomena in rivers that can be identified by using velocity profiles and shear stress as indicators. The Shatt Al-Arab River located south of Iraq suffers from these phenomena. Based upon the basic principles of hydraulics, it is reasonably easy to identify shear stress distributions within the river reach of the Shatt Al-Arab; and that will allow us to know the locations of the erosion and deposition. For this purpose, a 2D model using HEC-RAS software was developed to simulate the flow within the lower reach of Shatt Al-Arab. The results showed that the maximum shear stress at the right bank of Shatt Al- Arab reached 0.1N/m2 at 12 km upstream of Ras- Al-Bisha. This value of shear stress was recorded durin

Teachers' self-efficacy plays a very important role in the process of teaching English language, and teachers have primary role in determining what is needed or what would work best with their students. The sample consists of eighty-seven English language teachers in secondary schools in Baghdad/Kaarkh2. Self-efficacy questionnaire of fifteen items was constructed. Face, content validity and reliability were verified. Then, pupils' marks for the first semester were taken as their achievement.The main finding of the study indicates that:
English language teachers' self-efficacy has effect on their pupils' achievement.
In the light of the findings of the present study, several conclusions, recommendations and suggestions for further

.