The modern science of networks has made significant advancement in the modeling of
complex real-world systems. One of the most important features in these networks is the …

In recent years significant breakthroughs in exploring big data, recognition of complex
patterns, and predicting intricate variables have been made. One efficient way of analyzing …

The growing capability and accessibility of machine learning has led to its application to
many real-world domains and data about people. Despite the benefits algorithmic systems …

Student performance prediction (SPP) aims to evaluate the grade that a student will reach
before enrolling in a course or taking an exam. This prediction problem is a kernel task …

Clustering techniques are used to group the data based on the structure or through
classification to reduce the mathematical complexity of large datasets. The hierarchical and …

The convolutional neural networks (CNN) have shown promising results for various
classification problems over the past years. However, selecting various CNN architectures is …

E-learning is considered a leading application of digital technologies in educational
systems. The aim of the paper is to explore the utilization and impact of digital technologies …

Disaster caused by both nature and human factors has resulted in the occurrence of human
casualties, environmental damage, property loss, and psychological impact. The study aims …

One of the main challenges for online learners is knowing how to effectively manage their
time. Highly autonomous settings, such as Massive Open Online Courses (MOOCs), put …

Data is useless if information or knowledge that can be used for further reasoning cannot be
inferred from it. Cluster analysis, based on some criteria, shares data into important, practical …