Background Epilepsy is one of the most widespread neurological illnesses in the world with a prevalence rate of 2.8–19.5 per 1000 of the general population, and it is more prevalent in childhood. The understanding of the teachers about epilepsy has a significant impact on the academic performance and social skills of schoolchildren with epilepsy. Aim of Study This study aimed to assess teachers’ knowledge, attitude, and practice regarding epilepsy in schoolchildren and the association of certain studied variables with the level of schoolteachers’ knowledge, attitude, and practice. Subjects and Methods This was a cross-sectional study that included 402 participants and was conducted in Al-Rusafa/Baghdad during the period from November

The organization of sporting activities at the local and international levels requires a lot of money, which has increased interest in marketing in the sports field, as it is one of the modern topics that represent the basic knowledge needed by the sports marketer and which represents one of the basic concepts to enhance the benefits and returns of sports clubs. The research problem was the weak awareness of the members of the administrative body of Iraqi sports clubs of the role of sports marketing in the dimensions of competitive superiority and not exploiting them in the optimal way that enables clubs to achieve competitive superiority. The research aims to know the role of sports marketing in competitive superi

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

Background: The efficacy of educational strategies is crucial for nursing students to competently perform pediatric procedures like nasogastric tube insertion. Specific Background: This study evaluates the effectiveness of simulation, blended, and self-directed learning strategies in enhancing these skills among nursing students. Knowledge Gap: Previous research lacks a comprehensive comparison of these strategies' impacts on skill development in pediatric nursing contexts. Aims: The study aims to assess the effectiveness of different educational strategies on nursing students' ability to perform pediatric nasogastric tube insertions. Methods: A pre-experimental design was employed at the College of Nursing, University of Baghdad, i

HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue