his research aims to identify fear of missing out on opportunities among university students in terms of gender and specialization (scientific and humanities). To achieve this objective, the researchers adopted the fear of missing out on opportunities scale developed by Subhi Hamid and Issa Al-Daghistani(2023). The scale, in its final form, consisted of 10 items. The researchers confirmed the psychometric properties of the scale. Then, it was administered to 140 male and female students selected using stratified random sampling from four colleges at the University of Baghdad (College of Arts, College of Education, College of Engineering, and College of Science) during the 2024-2025 academic year

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

Early diagnosis and clinical decision-making depend on accurate brain tumor classification using magnetic resonance imaging (MRI). However, traditional deep learning methods usually rely on centralized medical data, which raises privacy concerns and limits the use of distributed clinical data. This research proposes a privacy-preserving federated learning framework for MRI image-based binary brain tumor classification using a decentralized ResNet-18 architecture that enables collaborative training without sharing raw patient data. To reflect realistic clinical conditions, the framework integrates heterogeneous multi-source datasets in different image formats (PNG and JPG) and evaluates performance under both IID and non-IID settings

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

This research aims to identify the level of Voluntary work among university students, and explore the statistical differences of voluntary work among students due the gender and major. A total of (400) male and female student from morning study were selected as a sample to achieve the research's objectives. Al-Malaki (2010) scale was adopted to collect the required data. The results revealed that men take massive part in voluntary work than women, and students of human sciences showed significant differences than those of other majors.   

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 research aims at constructing a Scale of Kindness phenomenon among university female students and elicit criteria to it, It also recognizes the differences in kindness levels among female students according to variables (specialization, academic grade, social status, and the age). The sample consists of 534 female students who were selected randomly. The two researchers rely on experience and the results of questionnaire, The questionnaire is given to 130 female university students from different colleges as well as their acquaintance with literary works witch dealt with kindness , The scale consists of 39 items , It has psychometric characteristics (Validity and Reliability) . The criterion (Z) is extracted from it and throu