The transformer-based machine learning technique is a deep learning model that processes the sequential input data using an encoder-decoder process. Transformers process the input data simultaneously using a parallelism ...

The waist circumference cut-off point for diagnosing metabolic syndrome in Sub-Saharan Africa is based on standards established for European populations. The purpose of this study was to determine the prevalence of ...

Mobile Edge Computing (MEC) enhances networking technology by bringing computing and storage close to end users. However, this advancement introduces security challenges, particularly its susceptibility to Distributed ...

Understanding factors influencing the age at first marriage is crucial for addressing social issues, promoting gender equality, and ensuring women’s wellbeing. This research aims to identify key determinants of age at ...

The research inspects the application of machine learning approaches to forecasting customer attrition in telecommunication companies. Machine learning models such as extreme gradient boosting, random forest, k-nearest ...

Business owners play a vital role in the social and economic development of South Africa by providing employment and services to the country’s citizens. South African infrastructure and community services are maintained ...

In this dissertation, we use modular representation theory to find error-correcting codes admitting finite simple group as a primitive permutation group and show that every binary linear code admitting group G as a primitive ...

Cybersecurity has become an ever-pressing concern in the modern digital landscape, demanding robust and efficient intrusion detection systems. In this research, we conducted a comparative analysis of tree-based intrusion ...

This study investigates the properties of strongly paracompact and uniformly paracompact spaces into locales. The research builds on the work of Rice [31], Frolik [15], and Borubaev [3], who expanded the concept of ...

Malicious software (malware) poses a significant threat to the security and integrity of computer systems. Traditional malware detection approaches often encounter challenges due to small-scale and imbalanced datasets, ...