Academic institutions operate in an extremely demanding and competitive environment. Some difficulties confronting most schools are delivering high-quality education to the students, developing systems for evaluating student performance, analyzing performance, and recognizing the future demands...

With recent increases in the use of social media in agricultural communities, many farmers are showing more and more interest in participating in social media and sharing different aspects of their profession with peers and policymakers. However, researchers have not explored this valuable data...

There has been a huge gap between male and female students in the field of science, technology, engineering, and mathematics. Women have always been inadequately represented in the field of information technology and engineering, both in universities and in the labor market. To understand the...

The valuation of house prices is drawing noteworthy attention due to worldwide financial and real estate crises in the last decade. Therefore, there is an immediate need to design more effective predictive systems of house prices. Indeed, investors, creditors, and governments are all interested...

The generation of huge data with high velocity creates alteration in the distribution of the stream data, which is defined as the concept of drifts. The concept drifts negatively influence the classification accuracy and the stability of the data streams. Numerous machine learning-based models...

Goods and services are sold through social media by individuals not authorized as legitimate dealers, resulting in lost taxes and customs duties to governments. This study proposes a model called SHIELD for detecting these violations through unstructured data in social media. The process...

Environmental pollution is generally a by-product of various human activities. Researchers have studied the dangers and harmful effects of pollutants and environmental pollution for centuries, and many necessary steps have been taken. Modern solutions are being constantly developed to tackle...

Artificial neural networks (ANNs) are commonly used to solve nonlinear problems. ANNs are composed of parallel interconnected layers that include processing elements called neurons. These neurons use mathematical functions to process the data, mimicking the human brain. In this study, we use...