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.

Key words: Quran translation, religious texts, ambiguity

With the growing demand for fast and reliable telecommunications infrastructure, deploying a Long-Term Evolution (LTE) network has become a necessity to support both economic and social development. This paper presents three proposed layouts for designing an LTE network in the downtown area of Gharyan, which represents the city’s central and most densely populated zone. The project was motivated by the uneven distribution of coverage across the area, whereseveral locations experience either a complete lack of service or very weak signal reception. The aim is to support the city’s digital transformation by improving access to mobile internet and data services, which in turn enhances business performance, emergency response, public service efficiency, education, remote learning, telemedicine, and remote work opportunities. To implement this plan, the design process relied on Mentum Planet software, a tool specialized in mobile network planning, using real-world terrain and signal data provided by Almadar Company. Three different network layout designs were simulated using two built-in propagation models: the Planet General Model (PGM) and the Q9 model. These simulations were conducted to assess signal strength and coverage across the study area. The analysis showed that one of the layouts provided significantly better signal quality and broader coverage compared to the others. Moreover, the Q9 model proved more reliable in predicting signal behavior in densely built urban settings. Based on these findings, a set of technical recommendations has been developed to guide the future implementation of LTE networks in similar environments, while also addressing challenges such as terrain variations, signal interference, and infrastructurelimitations. In conclusion, this work contributes to enhancing telecommunications services in Gharyan and supports broader efforts toward innovation and digital inclusion across key sectors in the region.

1. Abstract: Albumin is the main protein found in the blood, and is the most abundant protein. It is manufactured in the liver and is a major factor in preventing blood fluids from leaking from the blood vessels to the body's tissues, as well as a link to vital compounds in the bloodstream and transporting them to the body's organs. However, a deficiency in the level of albumin in the bloodstream leads to increased permeability of the blood vessels, which leads to inflammation in the body and chronic liver disease or chronic kidney failure and some other diseases, and results in symptoms, the most important of which are swelling in the feet and face. This study was conducted to compare the deficiency of protein albumin in the blood by conducting a serum albumin analysis at Gharyan Central Hospital. This study included 90 cases divided into 30 cases with kidney failure, 30 cases with diabetes, and 30 healthy cases (control group), with ages ranging from 18 years to 80 years in the period from 3/2/2020 to 12/1/2021. The results obtained were compared using statistical methods, which showed through P-values that there is a weak direct relationship between age and albumin levels in people with kidney failure and healthy people (albumin levels increase with age), and also a weak inverse relationship between age and albumin levels in diabetes (albumin levels decrease with age). The results also showed significant differences, meaning that there is a difference between the average albumin levels in the three groups (kidney failure, diabetes, healthy people) by comparing the results obtained with the reference values, as it was found that the albumin levels in kidney failure were all at the reference value, while in diabetic patients and the healthy group, most of the readings were at the reference value for albumin.

الملخص

يواجه استقرار الجهد تحديات كبيرة بسبب الطلب المتزايد على الكهرباء والاعتماد على خطوط النقل الطويلة، خاصة في شبكات الجهد المتوسط بجنوب ليبيا. تركز هذه الدراسة على شبكة سبها بجهد 66 كيلو فولت، التي تعاني من عدم استقرار الجهد نتيجة الاعتماد على مصادر توليد الطاقة الشمالية وخسائر الطاقة التفاعلية العالية. باستخدام برنامج، NEPLAN تم تقييم فعالية جهازين من تقنيات، FACTS وهما المعوض المتزامن الثابت (SVC) والمعوض المتزامن الديناميكي، (STATCOM) في تحسين استقرار الجهد.

تناولت الدراسة ثلاثة سيناريوهات: بدون تعويض، باستخدام، SVC وباستخدام. STATCOM أظهرت النتائج أن كلا الجهازين يحسنان استقرار الجهد بشكل ملحوظ ويقللان من خسائر الطاقة، مع تفوق STATCOM في الاستجابة الديناميكية والكفاءة الإجمالية. تؤكد هذه النتائج أهمية تقنيات التعويض المتقدمة في ضمان استقرار وموثوقية توصيل الطاقة في الظروف التشغيلية الصعبة.

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