Cognitive Absorption and E-learning Readiness in Learning Digitization among Preparatory Stage in Qatar

Abdulnaser A. Fakhrou; Sara  A. Ghareeb; عبد الناصر عبد الرحيم فخرو; سارة عبد الرحيم غريب

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Publication Date

Sun Mar 19 2023

Journal Name

Journal Of Educational And Psychological Researches

Volume

20

Issue Number

76

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Cognitive Absorption and E-learning Readiness in Learning Digitization among Preparatory Stage in Qatar

cognitive absorption

E-learning readiness cyber-learning

E-learning

Abdulnaser A. Fakhrou

Sara A. Ghareeb

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Abstract

The study aims to examine the relationships between cognitive absorption and E-Learning readiness in the preparatory stage. The study sample consisted of (190) students who were chosen randomly. The Researcher has developed the cognitive absorption and E-Learning readiness scales. A correlational descriptive approach was adopted. The research revealed that there is a positive statistical relationship between cognitive absorption and eLearning readiness.

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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

Hind Moutaz

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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

Mon Jan 01 2024

Journal Name

Aip Conference Proceedings

Comparative analysis of deep learning techniques for lung cancer identification

Yasir Salam

Auns Qusai

Ahmed Faeq

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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

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(1)

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

Salih S.Q.

NUHA SAMI

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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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(2)

Publication Date

Sat Nov 02 2019

Journal Name

Advances In Intelligent Systems And Computing

Modified Opposition Based Learning to Improve Harmony Search Variants Exploration

Alaa A.

AbdulRahman A.

Hammoudeh S.

Kamal Z.

Waleed

Mohammed I.

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Publication Date

Sun Jan 01 2023

Journal Name

Computers, Materials & Continua

Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems

Mohammed

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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

Kadhim A.I.

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Publication Date

Sun Jan 01 2017

Journal Name

البحوث التربوية والنفسية

the effect of an educational -learning programe according to the concepts of renewable energy and nanotechnology on technological enlightenment among students of the che chemistry department

Basama

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Publication Date

Tue Aug 10 2021

Journal Name

Design Engineering

Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri

Image compression

Convolutional Autoencoder (CAE)

k-mean algorithm

PSNR

Compression Rate (CR)

MSE

Clustering

CLIC

Kodak

deep learning

lossy

Mohammed

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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Publication Date

Fri Dec 14 2018

Journal Name

Iraqi National Journal Of Nursing Specialties

Evaluation of Personal Digital Assistant Acceptance in Nursing Education

PDA --- Nursing --- Education Students --- Technology Acceptance Model

Shatha

Basema

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Objective:To measure the acceptance level of the Personal Digital Assistance (PDA)’suse among nursing students as a tool of education in the Kingdom of Saudi Arabia. Methodology: Eighty-nine nursing students participated in this cross-sectional descriptive study by completing a questionnaire based on the Technology Acceptance Model (TAM) by Davis. Two dimensions were explored and evaluated; (1) the applicability of the TAM model in assessing this technology; and (2) the overall percentage of students’ agreement on the different TAM variables. Results: This study presented significant positive influence bet

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Publication Date

Wed Oct 11 2023

Journal Name

Journal Of Educational And Psychological Researches

The Degree to which Arabic Language Teachers at the Secondary Stage Possess the Teaching Competencies Necessary to Develop the Literary Appreciation Skills of Their Students from the Point of View of Educational Leaders in Bisha Governorate

competencies

teaching

savour

literary

education

Ali

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This study aims to identify the degree of Arabic language teachers at the secondary stage possessing the teaching competencies necessary to develop the skills of literary savor among their students from the perception of educational leaders in Bisha Province. To achieve the objectives of the study, the descriptive approach was used by adopting a comprehensive survey method. The study sample consisted of (48) school principals and Arabic language supervisors in Bisha Province who supervise the teaching of Arabic language at the secondary level in Bisha Province. The necessary data was collected using a questionnaire. The results of the study revealed that the evaluation of the study sample for the degree to which Arabic language teachers

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