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

The current research aims to identify the achievement of goals and the significance of the differences in achieving goals according to the variable of gender (male-female), specialization (scientific-human), and the stage (Master-PhD) for postgraduate students. To achieve the goals of the current research, the researcher developed a scale of achieving goals that was built according to the theory of (Lock & Latham 1990), which was applied to a sample of (257) male and female students who were selected randomly with a proportional distribution for the academic year (2021-2022). The scale of achieving goals consists of (30) items. The current research found that the research sample of postgraduate students has achieved their goals in ge

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

The current research aims to identify the self-regulation of university students, as well as to identify the significance of the difference in self-regulation according to the variable of sex (male-female), specialization (scientific-human), and grade (first-fourth). To achieve the research objectives, the two researchers developed a scale of (28) items about self-regulation According to the theory of (Pandora, 1991). The scale was administered to (500) students from the first and fourth stages of Al -Mustansiriyah University who were selected based on the random stratification method for the 2020/2021 academic year. The results showed that university students have a good level of self-regulation. There are no significant differences in

The study explored applications of artificial intelligence and its dialectical relationship with international human rights law of individuals, which requires assessing the effects of this technology on human rights and freedoms. The problem of privacy of humanity, as AI technologies can control human rights and freedoms, while monitoring potential violations in this context. The study use of documentary research and qualitative lens to analyze the data. In conclusion, unawareness of the use of AI may impose significant hurdles on future generations and may infringe on human rights across all sectors of society. The government should mandate obligations for artificial intelligence businesses concerning education, health, human right

The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

The sale of facial features is a new modern contractual development that resulted from the fast transformations in technology, leading to legal, and ethical obligations. As the need rises for human faces to be used in robots, especially in relation to industries that necessitate direct human interaction, like hospitality and retail, the potential of Artificial Intelligence (AI) generated hyper realistic facial images poses legal and cybersecurity challenges. This paper examines the legal terrain that has developed in the sale of real and AI generated human facial features, and specifically the risks of identity fraud, data misuse and privacy violations. Deep learning (DL) algorithms are analyzed for their ability to detect AI genera