It's challenging to help EFL students in Iraq learn and use synonyms. This study investigates the challenges faced by Iraqi English as a Foreign Language (EFL) students in understanding and employing synonyms. By employing Langacker's cognitive linguistic theory of domains, the research aims to enhance EFL Iraqi students' synonym knowledge and vocabulary acquisition. The study utilizes a descriptive analysis technique, with a pre-test and post-test design, involving fifty first-year students at the University of Baghdad's College of Languages, Department of English. The findings reveal that the domain theory significantly improved students' comprehension and application of English word semantics. Prior to the intervention, students

This research aims to examine the effectiveness of a teaching strategy based on the cognitive model of Daniel in the development of achievement and the motivation of learning the school mathematics among the third intermediate grade students in the light of their study of "Systems of Linear Equations”. The research was conducted in the first semester (1439/1440AH), at Saeed Ibn Almosaieb Intermediate School, in Arar, Saudi Arabia. A quasi-experimental design has been used. In addition, a (pre & post) achievement test (20 Questions) and a (pre & post) scale of learning motivation to the school mathematics (25 Items) have been applied on two groups: a control group (31Students), and an experimental group (29 Students). The resear

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

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

The current paper examines the Arab EFL teacher view on the application of AI-based chatbots as a method of aiding writing instruction. It explores pedagogy, didactic difficulties and ethics. The overall aim is to clarify the perception that teachers have of AI chatbots as a useful tool in the writing process and to find out to what degree these perceptions are reflected in instructional decision-making and classroom behaviors. A quantitative study was conducted using a structured questionnaire that was given to forty Arab EFL teachers, using a sequential explanatory mixed-method design. To elaborate and contextualize the survey results, qualitative enquiry was implemented through semi-structured interviews with twelve teachers. Fin

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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

Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

Peer support is an effective strategy to promote self-management behaviors and improve well-being in those with cardiometabolic disease, including type 2 diabetes mellitus (T2DM). There is limited knowledge about stakeholder perceptions regarding peer support programs in low- and middle-income countries (LMICs). The study assessed stakeholders’ awareness and understanding of peer support initiatives for T2DM, and explored their perceived barriers and readiness for implementation. A cross-sectional, self-administered online survey with branching logic was distributed to stakeholders across macro- (health policy), meso (tertiary hospital), and micro (community) levels of LMIC healthcare systems from June 1 to December 15, 2023. Quan