• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.7-14
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• 2022

This study aimed to test the factor structure of the measure of student participation in distance education. The study population consisted of all teachers in public education and faculty members in higher education in the Kingdom of Saudi Arabia by applying it to a sample of bachelor's and graduate students at the college of Education at umm al-Qura University. The (ESE) was applied to a random sample representing the study population consisting of (216) respondents. The results of the study showed that the scale consists of three main factors, with showed a high degree of construct validity through fit indices of the confirmatory factor analysis. The results have shown a gradual consistency of the measure's invariance that reaches the high level of the Measurement Invariance across the gender and study groups variables.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.115-122
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• 2023

Makkah Al-Mukarramah is the capital of Islamic world. It receives special attention from the Saudi government's rulers to transform it into a smart city for the benefit of millions of pilgrims. One of the 2030 vision objectives is to transform specific cities to smart ones with advanced technological facilitation, Makkah is one of these cities. The history of Makkah is not well known for some Muslims. As a result, we built the concepts of our application "Ain Makkah" to enable visitors of Makkah to know the history of Makkah by using technology. In particular "Ain Makkah" uses Augmented Reality to view the history of Al-Kaaba. A 3D model will overlay Al-Kaaba to show it in the last years. Our project will use Augmented Reality to build a 3D model to overlay Al-Kaaba. Future work will expand the number of historical landmarks of Makkah.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.275-280
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• 2021

With the development of communication networks, the processes of exchanging and transmitting information rapidly developed. As millions of images are sent via social media every day, also wireless sensor networks are now used in all applications to capture images such as those used in traffic lights, roads and malls. Therefore, there is a need to reduce the size of these images while maintaining an acceptable degree of quality. In this paper, we use Python software to apply K-mean Clustering algorithm to compress RGB images. The PSNR, MSE, and SSIM are utilized to measure the image quality after image compression. The results of compression reduced the image size to nearly half the size of the original images using k = 64. In the SSIM measure, the higher the K, the greater the similarity between the two images which is a good indicator to a significant reduction in image size. Our proposed compression technique powered by the K-Mean clustering algorithm is useful for compressing images and reducing the size of images.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.17-34
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• 2021

This study aimed to examine the Factor Structure of the teacher satisfaction scale (TSS) with distance education during the Covid-19 pandemic, as well as affirming the (Factorial Invariance) according to gender variable. It also aimed at identifying the degree of satisfaction according to some demographic variables of the sample. The study population consisted of all teachers in public education and faculty members in higher education in the Kingdom of Saudi Arabia. The (TSS) was applied to a random sample representing the study population consisting of (2399) respondents. The results of the study showed that the scale consists of five main factors, with a reliability value of (0.94). The scale also showed a high degree of construct validity through fit indices of the confirmatory factor analysis. The results have shown a gradual consistency of the measure's invariance that reaches the third level (Scalar-invariance) of the Measurement Invariance across the gender variable. The results also showed that the average response of the study sample on the scale reached (3.74) with a degree of satisfaction, as there are no statistically significant differences between the averages of the study sample responses with respect to the gender variable. While there were statistically significant differences in the averages with respect to the variable of the educational level in favor of the middle school and statistically significant differences in the averages attributed to the years of experience variable in favor of those whose experience is less than (5) years.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.191-202
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• 2021

This research was conducted with the aim to appraise the level of satisfaction of students and faculty members with the services of the Deanship of e-Learning and Distance Education at Umm Al-Qura University. In addition, it investigated any differences arising between the evaluation of students and faculty members for these services owing to their gender..To achieve these goals, a descriptive analysis methodology was used in this research. The sample comprised 1357 students (704 male and 653 female) and 372 faculty members (208 male and 164 female) from Umm Al-Qura University in the academic year 2020-2021. To collect the requisite data, the study participants were asked to complete a 5-point Likert scale questionnaire, and the validity and reliability of the data were then assessed. The findings revealed the existence of a high level of satisfaction of students and faculty members with the services of Deanship of e-Learning and Distance Education at Umm Al-Qura University. There are no statistically significant differences between the mean scores of students (male/female) at Umm Al-Qura University in evaluating the said services. Furthermore, there are no statistically significant differences between the mean scores of faculty members (male/female) at Umm Al-Qura University in evaluating these. There exist statistically significant differences between the mean scores of faculty members and students in the evaluation of the services of the Deanship for the benefit of faculty members.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.132-138
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• 2022

Due to the impacts of the current pandemic COVID-19 and the continuation of studying online. There is an urgent need for an effective and efficient education platform to help with the continuity of studying online. Therefore, the question bank system (QB) is introduced. The QB system is designed as a website to create a single platform used by faculty members in universities to generate questions and store them in a bank of questions. In addition to allowing them to add two types of questions, to help the lecturer create exams and present the results of the students to them. For the implementation, two languages were combined which are PHP and Python to generate questions by using Artificial Intelligence (AI). These questions are stored in a single database, and then these questions could be viewed and included in exams smoothly and without complexity. This paper aims to help the faculty members to reduce time and efforts by using the Question Bank System by using AI and Natural Language Processing (NLP) to extract and generate questions from given text. In addition to the tools used to create this function such as NLTK and TextBlob.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.199-208
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• 2022

The world health organization classified the emerging coronavirus (known as Covid-19) as a pandemic after confirming the extent of spread and scale. As a matter of fact, outbreaks of similar scale or even worse have been witnessed throughout history. Thus, the development of prevention strategies exists to protect against such calamaties. One of the widely proven measures that controls the spread of any contagious diseases is social distancing. As a result, this paper will demonstrate the concept of an application "Be Aware" on enabling the implementation of this preventive measure. In particular "Be aware" evaluates the extent of congestion in public places using current time data. The proposed project will use Global Positioning System (GPS), and Application Programming Interface (API), to ensure information accuracy, and the API use Crowdsourcing to collect Real-Time Data (RTD) from the selected places. One line

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.23-30
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• 2022

Glaucoma is a chronic neuropathy that affects the optic nerve which can lead to blindness. The detection and prediction of glaucoma become possible using deep neural networks. However, the detection performance relies on the availability of a large number of data. Therefore, we propose different frameworks, including a hybrid of a generative adversarial network and a convolutional neural network to automate and increase the performance of glaucoma detection. The proposed frameworks are evaluated using five public glaucoma datasets. The framework which uses a Deconvolutional Generative Adversarial Network (DCGAN) and a DenseNet pre-trained model achieves 99.6%, 99.08%, 99.4%, 98.69%, and 92.95% of classification accuracy on RIMONE, Drishti-GS, ACRIMA, ORIGA-light, and HRF datasets respectively. Based on the experimental results and evaluation, the proposed framework closely competes with the state-of-the-art methods using the five public glaucoma datasets without requiring any manually preprocessing step.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.319-323
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• 2022

Handwritten text recognition is one of the active research areas nowadays. The progress in this field differs in every language. For example, the progress in Arabic handwritten text recognition is still insignificant and needs more attentions and efforts. One of the most important fields in this is Arabic handwritten manuscript text recognition which focuses in extracting text from historical manuscripts. For eons, ancients used manuscripts to write everything. Nowadays, there are millions of manuscripts all around the world. There are two main challenges in dealing with these manuscripts. The first one is that they are at the risk of damage since they are written in primitive materials, the second challenge is due to the difference in writing styles, hence most people are unable to read these manuscripts easily. Therefore, we discuss in this study different papers that are related to this important research field.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.84-92
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• 2021

Care services are a significant asset in human life. Care in its overall nature focuses on human needs and covers several aspects such as health care, homes, personal care, and education. In fact, care deals with many dimensions: physical, psychological, and social interconnections. Very little information is available on estimating the cost of care services that provided to orphans and abandoned children. Prediction of the cost of the care system delivered by governmental or non-governmental organizations to support orphans and abandoned children is increasingly needed. The purpose of this study is to analyze the care cost for orphanage organizations in Saudi Arabia to forecast the cost as well as explore the most influence factor on the cost. By using business analytic process that applied statistical and machine learning techniques, we proposed a model includes simple linear regression, Naive Bayes classifier, and Random Forest algorithms. The finding of our predictive model shows that Naive Bayes has addressed the highest accuracy equals to 87% in predicting the total care cost. Our model offers predictive approach in the perspective of business analytics.