Abstract :

This paper generally investigates religious texts in many aspects, definition,

ways of translation, and difficulties in translation that may face both translators

and MA students. Yet it particularly focuses on The Holy Quran, its distinction

over other kinds of texts and difficulties translators and/or MA students face

when translating its verses and passages. Translating religious passages literally

(like The Holy Quran) will not give the real meaning , but it depends on the

interpreting ( tafseer ) to make the readers of the translation get the real and

intended meaning. The participants of this study were ten MA students of both

genders.

The results of this study show that translation is not always an easy task,

especially translating religious texts. This type of text is different from all

other types of literature, scientific, technical … etc. Translators have to follow

special translation techniques to produce an accurate translation and be faith to

the original text, never omit words or replace them with words may change

the intended meaning. That is a big challenge faces translators of religious

texts.

This research deals with estimating the likely switch of car ownership drivers and private transport vehicles modes

users to public transportation system (PT) modes in the main cities as Tripoli Capital city of Libya due to reduced

shopping travel time of all trips influenced by age, household size. Car ownership and shopping distance through

the introducing the public transport modes such as public buses. The data on other factors (variables) that could

potentially reason a model switch of from car ownership drivers and private transport vehicles modes users to

public transport were collected through a survey (questionnaire) with a specified predilection method. Modeswitch models to describe the switch of conduct of own car operators to PT system are developed. A binary

logistic regression model was used to assessment the transport displacement model for shopping trips. Probability

curves have been developed to change the position so that it is a user-friendly tool for analysing the potential

transformation Model of a variety of variables. One way to achieve this objective is by establishing reserved

public transportation lanes on main urban Tripoli city roads. The providing of private road lanes will increase of

service road level and reduce the level of road traffic congestion and this may effect in a switch of all or some

private transport mode users to public transport modes.

Key words: Own car, Public transport modes, logit model, shopping Travel time, shopping distance, age, car

ownership and switch probabilities, likelihood..

Abstract: This paper presents simulation technique for life assessment of the insulation of the power transformer. Load and ambient temperatures are two important factors that influence the hot spot of transformers. The transformer hot spot temperature is one of the most critical parameter in determining the life of transformer paper insulation. The simulation (Matlab Software Package) is based on related international standards as the IEC 60076-7:2005 loading guide method. Load and ambient temperatures of the transformer obtain from General Electrical Company and meteorology office of Libya are used as the input for the simulation together with transformer parameters from heat run test. Hottest spot temperature and loss-of-life are calculated. Lifetime of transformer is predicted. Keywords: Hot-spot temperature, power transformer, top-oil temperature, loss of life

Abstract

William Shakespeare’s "Hamlet," written around 1600, is one of the most famous tragedies in the English language. The play is rich in themes such as revenge, madness, mortality, and the complexity of the human condition.                   

This paper analyzes the dramatic structure using Freytag’s pyramid and Aristotle tragedy theory as a framework. They examine the play’s exposition, inciting incident, rising action, climax, falling action, resolution, and conflict combining with Aristotle theory to understand how Shakespeare constructs a powerful tragedy. The method used in this study is a descriptive qualitative, which aims to analyzing and collecting data from the play and some referential books, library ,websites and other data sources that were useful for the analysis.The study also explores the significance of Hamlet in literary studies. The results of the study have pedagogical implications for teaching English literature for students and language learners. 

Key words: Hamlet ,Aristotle theory, Freytag pyramid, tragedy drama. 

Abstract: In light of the aspiration to achieve sustainability in the field of education, especially after the development of artificial intelligence technologies in general and artificial neural network technologies in particular, the process of improving e-learning has become one of the most important strategies for achieving sustainability. This study aims to evaluate the impact of using artificial intelligence techniques and artificial neural networks on improving cloud e-learning by extracting and mining data from the electronic cloud and analyzing it to provide a more efficient and effective educational experience. Through several methodologies, including descriptive methodology to describe the factors influencing the improvement of machine learning through the use of artificial intelligence techniques and the mechanism for using these techniques, quantitative methodology was used in collecting data and analytical scientific methodology to analyze the results of the proposed model, which is a hybrid of convolutional artificial neural networks (CNN) and recursive neural networks (RNN). Through the model, it is possible to extract and analyze user data such as interaction with content and duration of study to extract patterns and behaviors that support improving the learning experience, and personalizing individual learning paths. Predicting the academic performance of students using machine learning techniques. The results showed an improvement in the learning experience of 86% and an improvement in platform performance of 85%. Machine learning indicators, such as accuracy (94%), recall (93%) and f1 score (91%), also indicated the success of the model used in