Publications

Academic Journals

  1. Bonnet, W., & Celik, T. (2021). Random Sampling-Based Relative. IEEE Geoscience and Remote Sensing Letters, 9321136, 1–4. https://doi.org/10.1109/LGRS.2020.3047344
  2. Byamugisha, J., Saib, W., Gaelejwe, T., Jeewa, A., & Molapo, M. (2020a). Abstract PR-12: Towards verifying results from biomedical deep learning models using the UMLS: Cases of primary tumor site classification and cancer Named Entity Recognition. Association for the Advancement of Artificial Intelligence, PR-12-PR-12. https://doi.org/10.1158/1557-3265.adi21-pr-12
  3. Byamugisha, J., Saib, W., Gaelejwe, T., Jeewa, A., & Molapo, M. (2020b). Towards Verifying Results from Biomedical NLP Machine Learning Models Using the UMLS: Cases of Classification and Named Entity Recognition. www.aaai.org
  4. Choma, J., Correa, F., Dahbi, S.-E., Dwolatzky, B., Dwolatzky, L., Hayasi, K., Lieberman, B., Maslo, C., Mellado, B., Monnakgotla, K., Naudé, J., Ruan, X., & Stevenson, F. (2020). Worldwide Effectiveness of Various Non-Pharmaceutical Intervention Control Strategies on the Global COVID-19 Pandemic: A Linearised Control Model. MedRxiv, 2020.04.30.20085316. https://doi.org/10.1101/2020.04.30.20085316
  5. Daniel, L. O., Sigauke, C., Chibaya, C., & Mbuvha, R. (2020). Short-term wind speed forecasting using statistical and machine learning methods. Algorithms, 13(6). https://doi.org/10.3390/A13060132
  6. Freeborough, W., Gentle, N., & Rey, M. E. C. (2021). WRKY Transcription Factors in Cassava Contribute to Regulation of Tolerance and Susceptibility to Cassava Mosaic Disease through Stress Responses. Viruses, 13(1820).
  7. Harling, G., Gómez-Olivé, F. X., Tlouyamma, J., Mutevedzi, T., Kabudula, C. W., Mahlako, R., Singh, U., Ohene-Kwofie, D., Buckland, R., Ndagurwa, P., Gareta, D., Gunda, R., Mngomezulu, T., Nxumalo, S., Wong, E. B., Kahn, K., Siedner, M. J., Maimela, E., Tollman, S., … Herbst, K. (2021). Protective behaviors and secondary harms resulting from nonpharmaceutical interventions during the COVID-19 epidemic in South Africa: Multisite, prospective longitudinal study. JMIR Public Health and Surveillance, 7(5), 1–17. https://doi.org/10.2196/26073
  8. Masangu, L., Jadhav, A., & Ajoodha, R. (2021). Predicting student academic performance using data mining techniques. Advances in Science, Technology and Engineering Systems, 6(1), 153–163. https://doi.org/10.25046/AJ060117
  9. Netshandama, V. O., Directorate, C. E., Africa, S., Iwara, I. O., Africa, S., Nelwamondo, N. I., & Africa, S. (2021). Social entrepreneurship knowledge promotion amongst students in a Historically Disadvantaged Institution of Higher Learning. Journal of Entrepreneurship Education, 24(1), 1–13.
  10. Ngwenduna, K. S., & Mbuvha, R. (2021). Alleviating class imbalance in actuarial applications using generative adversarial networks. Risks, 9(3), 1–33. https://doi.org/10.3390/risks9030049
  11. Nkolele, R. (2020). Mapping of Narrative Text Fields To {ICD}-10 Codes Using Natural Language Processing and Machine Learning. Proceedings of the The Fourth Widening Natural Language Processing Workshop, 131–135. https://doi.org/10.18653/v1/2020.winlp-1.35
  12. Orievulu, K. S. (2020). (Re-engaging) the “tyranny” of process in participatory development programming in Africa: Fadama in Nigeria as a case study. South African Journal of International Affairs, 27(2), 243–264. https://doi.org/10.1080/10220461.2020.1785930
  13. Ratshilengo, M., Sigauke, C., & Bere, A. (2021). Short-term Solar Power Forecasting using Genetic Algorithms: An Application using South African Data. Applied Sciences (Switzerland), 11(9). https://doi.org/10.3390/app11094214

Conference Proceedings

  1. Baloyi, N., Mellado, B., & Ruan, X. (2021). Discrimination of Signal-Background Events with Supervised and Semi-Supervised Learning in the Search for New Bosons Decaying to the Z + γ Final State. SAIP Conference. https://events.saip.org.za/event/144/contributions/1492/attachments/284/388/NBaloyi_SAIP_Proceedings.pdf
  2. Chabumba, R., Ajoodha, R., & Jadhav, A. (2021). Predicting Telecommunication Customer Churn using Machine Learning Techniques. International Conference on Interdisciplinary Research in Technology and Management in Association. www.kaggle.com
  3. Essa, Y., Ajoodha, R., & Hunt, H. G. P. (2020, December 16). A LSTM Recurrent Neural Network for Lightning Flash Prediction within Southern Africa using Historical Time-series Data. 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2020. https://doi.org/10.1109/CSDE50874.2020.9411544
  4. Essa, Y., Hunt, H. G. P., & Ajoodha, R. (2021). Short-term prediction of lightning in southern africa using autoregressive machine learning techniques. 2021 IEEE International IOT, Electronics and Mechatronics Conference, IEMTRONICS 2021 – Proceedings. https://doi.org/10.1109/IEMTRONICS52119.2021.9422493
  5. K. Mabunda, Ajoodha, R. (2021). A review: Predicting student success at various levels of their learning journey in a science programme. 2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), 1–5. https://doi.org/10.1109/IEMTRONICS52119.2021.9422519
  6. Lange, R., Lange, T., & van Zyl, T. L. (2020). Predicting particle fineness in a cement mill. Proceedings of 2020 23rd International Conference on Information Fusion, FUSION 2020. https://doi.org/10.23919/FUSION45008.2020.9190236
  7. Matsane, L., Jadhav, A., & Ajoodha, R. (2020). The use of Automatic Speech Recognition in Education for Identifying Attitudes of the Speakers. 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2020. https://doi.org/10.1109/CSDE50874.2020.9411528
  8. Mngadi, N., Ajoodha, R., & Jadhav, A. (2020). A Conceptual Model to Identify Vulnerable Undergraduate Learners at Higher-Education Institutions. 2020 2nd International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2020, 1–8. https://doi.org/10.1109/IMITEC50163.2020.9334103
  9. Oni, O. O., & Zyl, T. L. van. (2020). A Comparative Study of Ensemble Approaches to Fact-Checking for the FEVER Shared Task. 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), 1–8. https://doi.org/10.1109/CSDE50874.2020.9411564
  10. Thulare, E., Ajoodha, R., & Jadhav, A. (2021, January 27). An Empirical Analysis and Application of the Expectation-Maximization and Matrix Completion Algorithms for Varying Degrees of Missing Data. 2021 Southern African Universities Power Engineering Conference/Robotics and Mechatronics/Pattern Recognition Association of South Africa, SAUPEC/RobMech/PRASA 2021. https://doi.org/10.1109/SAUPEC/ROBMECH/PRASA52254.2021.9377210