The current study aims to examine the level of problems faced by university students in distance learning, in addition to identify the differences in these problems in terms of the availability of internet services, gender, college, GPA, interactions, academic cohort, and family economic status. The study sample consisted of (3172) students (57.3% females). The researchers developed a questionnaire with (32) items to measure distance learning problems in four areas: Psychological (9 items), academic (10 items), technological (7 items), and study environment (6 items). The responses are scored on a (5) point Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree). Means, standard deviations, and Multivariate Analysis of Variance (MANOVA) were used to analyze the data. The findings showed that students faced high levels of psychological and academic problems and medium levels of technological and study environmental problems. The findings also indicated statistically significant differences in the levels of all problems based on the availability of internet services. In addition, the sample in scientific colleges manifested higher levels of academic problems, and females showed higher levels of study environmental problems. Statistically significant differences also appeared in all types of problems based on study cohort and family economic status.
Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col
... Show MoreBackground: 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
... Show MoreMonaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi
... Show MoreHM 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
... Show MoreSocial networking sites represent one of the modern communication technologies that have contributed to the expression of public opinion trends towards various events and crises of which security crisis is most important being characterized by its ability to influence the community life of the public. In order to recognize its role in shaping opinions of the educated class of the public that is characterized by a high level of knowledge, culture and having experience in dealing with the media. Its advantage is that they have an active audience by expressing their views on the situations, events, and news published on them as well as expressing their attitudes and sympathy with the events. So a number of questions are included in the ques
... Show MoreTeaching through the system of personal learning, known as (Clare's plan) is amongst the most prominent plans which depend on self-education, as it received worldwide recognition. The plan lets the learner achieve learning by depending on himself after being familiar with the educational goals given to him, then he starts to solve the exercises and the drills accompanying the unit. After that, he checks his achievement by answering the self-evaluation tests. This method offers more opportunities for personal interaction than do the traditional systems, and individual leaning is a methodical expression aims at taking care of the learner and making him the locus of the processes of teaching and learning.
Aims of the study
... Show MoreAbstract The purpose of this study, teach the art of performing Olympic lifts (snatch and, clean and jerk) using the two methods are instructional (self-learning associated with the model) and (reverse style of partial way). Identify the effectiveness of these methods in learning the art of performance and style of the best Olympic lifting in the learning and retention of novice for Olympic lifts. The research sample consisted of 16 lifters were selected purposively representing specialist center for the care of athletic talent to weightlifting for ages 14 years. The sample was divided into two experimental, Each group (8) eight weightlifters. The experimental group used the style of the first self-learning associated with the m
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