Researcher: Netshamutshedzi Ndivhuwo, University of Venda
Supervisor: Dr Ibidun Obagbuwa, University of the Witwatersrand, Johannesburg

This study investigates email monitoring systems using machine learning. In this study, we contribute to previous studies on spam problems to improve accuracy by utilising a variety of methods.

Researcher: Moris Madike, University of Limpopo
Supervisor: Prof Justine Nasejje, University of the Witwatersrand, Johannesburg

Researcher: Fhulufhelo Mugware, University of Venda
Supervisor: Prof C. Sigauke, University of the Witwatersrand, Johannesburg

Researcher: Dimpho Mosaka, University of the Witwatersrand, Johannesburg
Supervisor: Dr Martins Arasomwan, University of the Witwatersrand, Johannesburg

More studies have demonstrated that the DeepNeural Networks(DNN)techniques can be used to forecast the stock market price. This research project aims to investigate the effectiveness of deep neural network techniques in the SouthAfrican stock market price forecastinhusing Long-Short TermMemory(LSTM) and Convolutional Neural Network( CNN) technique, including the challenges and opportunities of this approach

Researcher: Mufunwa Nemushungwa, University of the Witwatersrand, Johannesburg
Supervisor: Dr Martins Arasomwan, University of the Witwatersrand, Johannesburg

This research compares three variations of SOM: standard SOM, SOM combined with K-means, and SOM paired with the social spider optimization (SSO) algorithm in performing customer segmentation. The results show that combined SOM with SSO algorithm outperforms the the paired SOM and K-means in
enhancing the SOM clustering performance.dress road damage problems.

Researcher: Vhahangwele Netshilonwe, Sol Plaatje University
Supervisor: Dr. Michael Olusanya , Sol Plaatje University

This study investigates how machine learning can be used to detect road damage, specifically potholes, in images of roads. The study tests a particular machine learning model called the “one-class support vector
machine (OCSVM)” to determine if it can effectively identify road damage better than random chance. The objective is to enhance our capability to detect and address road damage problems.

Researcher: Mafanedza Nephawe, University of the Witwatersrand, Johannesburg
Supervisor: Prof Prince Ntimeni

The Higgs boson, a fundamental particle, gives mass to others and was confirmed in 2012 at
CERN[1, 5]. The associated Higgs field explains mass differences and supports the Standard
Model. [2]Large Hadron Collider channels target specific particles, ZH (associated production of
top quarks with Higgs and Z bosons). This project introduces CEPC, a circular electron-positron
collider in China, aiming to study particle properties[5, 3]. AI and machine learning analyze detector
data to understand the Higgs boson and explore beyond the standard model. The research
aims to employ a deep neural network for model-independent analysis of the Standard Model
Higgs, focusing on signal-background separation in ZH channels at CEPC with a 40% branching
ratio at 95 GeV.

Researcher: Mafanedza Nephawe, University of the Witwatersrand, Johannesburg
Supervisor: Dr. M. Arasomwan

Researcher: Dzhivhuho Asakundwi Praisethelord, University of Venda
Supervisor: Dr. M. Arasomwan

Researcher: Vincent Mohale, Sol Plaatjie University
Supervisor: Dr Ibidun Obagbuwa

Bloemfontein, a city, where wheat has long been a culinary cornerstone, faces a silent transformation which is underway. Wheat, the bedrock of staples like bread, cereals, and the essence of beverages such as beer and whiskey, now faces a challenging foe: climatechange.
In this study, we delve into the heart of this global staple, unravelling the complex web of connections that link climate change to wheat yield in Bloemfontein.