• Performance evaluation of machine learning algorithms for intrusion detection 

  Ndleve, Nsovo Mildred (2024)

  In the cyber security domain, the increasing sophistication of attacks requires the development of improved detection techniques. This research looked at the usefulness of machine learning methods, especially Decision Tree, ...
• Statistical modelling and analysis of business ownership in South Africa 

  Sebola, Lepulana Sylvester (2024)

  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 ...
• New estimators for cure rate models 

  Ramalata, Aluwani (2024)

  If study subjects are tracked long enough, it is a typical assumption in survival analysis that they will eventually experience the event of interest. However, that is not always the case. In reality, it is not uncommon ...
• Error-correcting codes from 2-representations of the unitary group U(3,3) 

  Nyikadzino, Tapiwanashe Gift (2024)

  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 ...
• Statistical modelling and analysis of business ownership in South Africa 

  Sebola, Lepulana Sylvester (2023)

  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 ...
• Comparative analysis of tree-based intrusion detection modelling and machine learning classification models using cyber-security dataset 

  Mokoele, Motlatso Sarel (2024)

  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 ...
• Throughput maximization and latency optimization in fifth-generation networks using a multistage machine learning for early hybrid automatic repeat request 

  Hlewane, Nhlanhla Patrick (2024)

  The physical layer Hybrid Automatic Repeat Request (HARQ) protocol efficiently achieves low error-rate transmission and high network reliability in the fifth generation (5G) Ultra Reliable Low Latency Communication ...
• On strongly paracompact and uniformly paracompact locales 

  Gwizo, Gorden (2024)

  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 ...
• Review of extreme value theory with application to the Johannesburg Stock Exchange financial market data 

  Metwane, Maashele Kholofelo (2023)

  The financial sector is vital to the economy as it encourages economic growth. Therefore, modelling the extremes and risk management of financial stock returns and losses is vital to economic survival. However, with ...
• Malware detection using random forest method trained on a balanced synthetic dataset 

  Matsobane, Neo Onica (2024)

  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, ...
• A Bayesian statistical evaluation of the competition indices used in eucalyptus tree growth modelling 

  Mnisi, Samuel (2024)

  Eucalyptus is the most frequently planted genus tree in the world which is grown in more than 100 different countries. It is a subfamily of the Myrtaceae family with approximately 800 species of flowering evergreen trees ...
• Short and long-term forecasting of wind speed in Limpopo Province using machine learning algorithm and extreme value theory 

  Makubyane, Kgothatso (2024)

  Numerous studies have applied Extreme Value Theory (EVT) to model environmental variables like wind speed, rainfall and temperature. Recently, academic focus has shifted to machine learning algorithms for the same variables. ...
• Statistical modelling of injury mortality in Gauteng and Mpumalanga Provinces of South Africa 

  Lebogo, Ramookana Johannes (2023)

  Injury is a truly global health issue with massive societal and economic consequences. In this study, Negative-Binomial integer-valued generalised autoregressive conditional heteroscedasticity (NB-INGARCH) and autoregressive ...
• Mitigation of denial of service attacks in software-defined-cognitive radio network using software-defined-cognitive radio shield 

  Lebepe, Mampuele (2023)

  A ground-breaking approach to managing network resources is provided by softwaredefined networks that solve a number of management-related concerns. A novel paradigm called Cognitive Radio Networks (CRN) was developed to ...
• Constructing designs and codes from fixed points of alternating groups 

  Kekana, Madimetja Jan (2024)

  The study of finite structures in discrete mathematics is a broad area which has many in influential results not only in mathematics but also in practice. It is well known that 1􀀀designs have many applications in coding ...
• On P- frames and their generalisations 

  Ngoako, Thabo David (2024)

  In this dissertation, we study P -frames and their generalisations. On the generalisations of P - frames we consider, in particular essential P -frames, CP -frames, almost P -frames, F -frames, F ′-frames and PF -frames. ...
• Prediction of South African crime rate using supervised machine learning techniques 

  Mutobvu, Ronewa (2023)

  Kaggle crime statistics for South Africa were used to create machine learning categorization models. Although the techniques used in the experiments that came before this one differed, the dataset that was used was. The ...
• Integrated and automated demographic surveillance data quality systems for rural areas 

  Tlouyamma, Joseph (2024)

  The Health and Demographic Surveillance System (HDSS) is a data collection system that can track crucial events such as births, deaths, and migrations in well-defined geographic areas, particularly in low- and middle-income ...
• Detection cerebrovascular disease in brain images using convolutional neural network 

  Sethibela, Lehlohonolo Bridget (2023)

  Cerebrovascular disease is the world's second major cause of mortality and disability, and the fourth major cause of mortality and disability in South Africa. Cerebrovascular disease occurs due to issues of the brain's ...
• Sarcasm detection in political speeches using recurrent neural networks 

  Mulaudzi, Thikho (2024)

  Sarcasm detection is a challenging task in natural language processing (NLP) that has received significant attention in recent years. Sarcasm is a form of indirect speech in which the speaker says the opposite of what ...

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