The present study intends to trace The friendship in puple and the differences in this according to the variables of age and sex .
The study sample includes (200) puple in intermediate, and secondary schools in Baghdad in AL- Karkh .The sample is the age of whom is ranging from (13) to (15) years .
Maghly scale for measuring the development of friendship is adopted in this study after adjusting it to the Iraqi environment . The Scale consists of (40) items .
The face and construct validity of the Scale is checked as well as its reliability which is checked by test- retest
The study reveals the following :
1 – There is positive effect of the interaction between the of middle scale friendship .
2 – There is No differe

Abstract

The current research aims to identify the communicative competence of university students, to identify the levels of communicative competence among university students and which of these levels are more common, and to identify the significance of differences in communicative competence among university students according to the variables of gender and specialization. The study population consisted of (782) male and female students, as the statistical analysis sample was limited to (400) male and female students to extract the psychometric properties of the current research tool. The study sample included (382) male and female students at the University of Baghdad who were chosen by the stratified random

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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