This research aimed at identifying the factors that affecting in the recruitment of a teaching staff for the Massive Open Online Courses (MOOCs) in university teaching at the University of Khartoum. The descriptive method was followed. The questionnaire was used as a tool for data collection,, which was distributed directly to a sample of (181) respondent of the teaching staff members of the senate at University of Khartoum from those who were attend at the senate meeting No. (409) which was held on 22 August 2016 Of (272). The researcher followed for the distribution the chance method, where each questionnaire was distributed to each of a teaching staff from different faculties at the University of Khartoum, according to his willingness

The article aims to consider the concept of language metaphor in Russian and Arabic languages and the problem of metaphor functioning in language, since it is one of the most important figurative components of the structural organization of the text and an important means of reflecting the national culture of each people. and often in revealing the image of a metaphor one can feel the full flexibility of the language and its beauty.

This paper describes a practical study on the impact of learning's partners, Bluetooth Broadcasting system, interactive board, Real – time response system, notepad, free internet access, computer based examination, and interaction classroom, etc, had on undergraduate student performance, achievement and involving with lectures. The goal of this study is to test the hypothesis that the use of such learning techniques, tools, and strategies to improve student learning especially among the poorest performing students. Also, it gives some kind of practical comparison between the traditional way and interactive way of learning in terms of lectures time, number of tests, types of tests, student's scores, and student's involving with lectures

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

فاعلية تطبيق اسلوب المهام الدراسية في اتقان اللغة الاسبانية للطلبة العراقيين.

The aim of this paper is to propose an efficient three steps iterative method for finding the zeros of the nonlinear equation f(x)=0 . Starting with a suitably chosen , the method generates a sequence of iterates converging to the root. The convergence analysis is proved to establish its five order of convergence. Several examples are given to illustrate the efficiency of the proposed new method and its comparison with other methods.