Abstract

The scope of the humanitarian tragedies in the Arab region has widened after the conflicts that erupted over the past years, exacerbation to include educational, cultural, and social dimensions, economic and moral aspects of the displaced families, especially after the emergence of terrorist organizations and sectarian conflicts which overthrew human and led to various political and demographic changes, forcing citizens to leave their homes, fleeing with their families from the danger of murder, terrorism, and violation to other safer areas inside or outside their countries. Women and children were the vast majority of the displaced who were subjected to great pressures, The host communities bore the pro

The research is an attempt to investigate experimentally the influence of teacher’s errors correction and students’ errors correction on teaching English at the College of Physical Education for Women. Errors are seen as a natural way for developing any language but teachers are puzzled the way they can correct these errors. So, this research gives some idea of using two types of errors correction. The sample of the research is female students of the first year stage at the College of Physical Education for Women of the academic year 2009-2010. The whole population of the research is (94) students while the sample is (64). Thus, the sample represents 68% from the population of the research. The sample represents It is hypothesized th

The human gastrointestinal system is a complex ecosystem crucial for well-being. During sepsis-induced gut injury, the integrity of the intestinal barrier can be compromised. Lipopolysaccharide (LPS), an endotoxin from Gram-negative bacteria, disrupts the intestinal barrier, contributing to inflammation and various dysfunctions. The current study explores the protective effects of limonene, a natural compound with diverse biological properties, against LPS-induced jejunal injury in mice. Oral administration of limonene at dosages of 100 and 200 mg/kg was used in the LPS mouse model. The Murine Sepsis Score (MSS) was utilized to evaluate the severity of sepsis, while serum levels of urea and creatinine served as indicators of renal f

The exercise of activities and sports are of great importance to public health and to maintain the ideal health weight as well as the psychological and mental comfort of humans. The aim of this study is to determine the contribution and participation of educated females in physical activities at the University of Baghdad hall for the years 2011-2016, and to show the factors that influence women's contribution to physical activities at the university by selecting 100 students of males and 100 females' students randomly. During the questioning questions and statistical analysis of the questioning to find out the reasons for the discouraging contribution of the women to the various physical activities and try to find solutions and r

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff