The current research aims to identify the possible self of university students and the differences in the level of possible self of students in terms of gender, specialization (scientific-humanitarian), and the interaction between them. In order to achieve the objectives of the current research, the two researchers have prepared a scale of the possible self, based on the theory (Markus and Nurius, 1986). The research tool was applied to a sample of (400) male and female students who were selected through a random stratified method from Al-Mustansiriya University students/morning studies for the academic year (2019-2020). The researcher reached the following results: the research sample has a high level of possible self; there is a differ

The current study aims to find out:

1. The ingratiating behavior of university students.
2. The differences of statistical significance in The ingratiating behavior among university students according to the variables of sex and specialization

The current study is determined by University of Baghdad students of both genders (males and females) and for both majors (scientific and humanities) for the academic year (2019-2020).

In order to achieve the researcher's objectives:Ingratiating behavior scale has been constructed. It consists in its final form of (32) items divided into four behaviors. The researcher has extracted scale validity and reliability.

The researcher based the two scales

Research was: 1- known as self-efficacy when students perceived the university. 2- know the significance of statistical differences in perceived self-efficacy according to gender and specialty. Formed the research sample of (300) students were chosen from the original research community by way of random (150) male specialization and scientific and humanitarian (150) females specialized scientific and humanitarian. The search tool to prepare the yard tool to measure perceived self-efficacy based on measurements and previous literature on the subject of perceived self-efficacy. The researcher using a number of means, statistical, including test Altaúa and analysis of variance of bilateral and results showed the enjoyment of the research s

The study aims to identify the students’ attitudes toward recent techniques’ use in teaching; using power point software and data show to facilitate teaching approaches as well as following the approach of lecture in giving subjects, do these techniques facilitate, increase, and tackle the difficulties of subjects, do these attitudes positive or negative?, and to what extent these techniques raise up students’ motivation.   

The effects of Internet use on university’s students:The effects of Internet use on university’s students:“A Study on a Sample of Jordanian University’s students "This survey aims to identify the most important effects of Internet use on Jordanian public and private universities’ students by monitoring and analyzing a set of indicators that show the quality of the effects on specific fields such as  cultural, social, psychological, moral and political effects .To achieve these goals, the study attempts to answer the following questions:1.   What are the effects of Internet’s use on students?2. What is   the relationship between the effects and demographic variables such as  gender, age, family size an

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

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