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Some Indicators of Learning Difficulties and their Relationship to the Self-Concept of Elementary School Students (Case Study)
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The aim of the research is to identify learning difficulties and their role in children's perception of self-concept. The researcher adopted the descriptive and analytical approach method in this study. A questionnaire was designed by the researcher to collect some related information such as biodata, family, health, diagnostic and behavioral patterns of the case. In addition, the researcher adopted the scale of learning difficulties for elementary school students prepared by Zaidan Ahmed Al-Sartawi (1995), the scale of student appreciation for the survey of learning difficulties for primary school students by Michael Best, which was translated to the Arabic language by (Saeed Abdullah Debis). The researcher adopted also the Self-Concept Scale prepared by (Ahmed Abdul Rahman and Mr. Abu Hashim (2002). The study was conducted in the Emirate of Ajman for the academic year (2017-2016). The results of the study according to the questionnaire showed that the sample suffers from difficulties in the subjects (reading, expression, calligraphy, mathematics, and geography). However, the number and type of errors are normal compared to their colleagues and on the scale of learning difficulties. The results showed that the first dimension is (academic difficulties) and in the second dimension is (behavioral characteristics) they occurred within the area of (potential learning difficulties). On the scale of the pupil’s appreciation for surveying learning difficulties, the case resulted in the presence of learning difficulties in the aspects (verbal comprehension, spoken language, and orientation). It can conclude that there are learning difficulties in the academic aspect related to (comprehension, spoken language, and knowledge). The absence of learning difficulties in terms of cognitive-motor related to (personal, social behavior, and movement coordination). As for the degree obtained by the case on the Self-Concept Scale, it was within the medium range, meaning that the case suffers from an average concept. As the student's self-understanding helps to perceive, know the strengths, and weaknesses of his personality, which supports the student's chances of success in academic achievement, academic achievement, and professional. The study recommended the activation of treatment programs designed for learning difficulties among elementary school students, by following training related to the curriculum, due to its association with active life success at the cognitive, psychological, and social levels.

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Sun Sep 03 2023
Journal Name
Iraqi Journal Of Computers, Communications, Control & Systems Engineering (ijccce)
Efficient Iris Image Recognition System Based on Machine Learning Approach
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HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Sat Jan 19 2019
Journal Name
Artificial Intelligence Review
Survey on supervised machine learning techniques for automatic text classification
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Publication Date
Tue Feb 05 2019
Journal Name
Journal Of The College Of Education For Women
Attitudes of Mass Media Students in Baghdad University toward Marriage
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This Study aims at identifying the attitudes of Masses Media students in Baghdad university toward marriage and the differences of this variable according to sex and the grade. The sample consists of (160) male and Females students, where the questionnaire consists of (40) items’ after achieving their reliability and constancy.
The results show that the attitudes of the students are Positive, there are no differences in the attitudes toward marriage according to sex variable (males and females) and there are differences in the variable of grade toward marriage for the First Class. In the lights of these results the researcher suggests making improvements in the attitudes toward marriage suiting the social value and customs of Iraqi

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Publication Date
Wed Jul 01 2015
Journal Name
Al–bahith Al–a'alami
Dependence on Media and the Formation of the Level of the Academic Elite's Knowledge concerning United Nations' Affairs (A research based on a doctoral thesis)
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The UN organization is considered one of the most important organizations at the international level. It has accomplished multiple tasks and roles of many different issues and events that hit the developing and advanced world countries. It has performed a series of procedures and laws that have had an impact on ending the wars and conflicts that plagued some countries and continued for a period of time in the past. Moreover, it has improved the level of the international relations between a number of countries due to the problems and incidents took place between them. It has relied on finding solutions and treatments for humanitarian problems such as the preservation of the environment, preventing the spread of epidemics and diseases Thi

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Publication Date
Mon Oct 15 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY OF THE EFFECT OF MAGNETIC FIELD POLES ON THE GROWTH OF Staphylococcus AND Streptococcus ISOLATED FROM TOOTH DECAY: STUDY OF THE EFFECT OF MAGNETIC FIELD POLES ON THE GROWTH OF Staphylococcus AND Streptococcus ISOLATED FROM TOOTH DECAY
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The study aimed to determine the impact of energy for the north and south magnetic poles on the the growth of bacteria isolated from cases of tooth decay, 68 swabs were collected from surfaces of faulty tooth, the detected of Staphylococcus aureus

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