{"id":2998,"date":"2024-07-12T02:05:32","date_gmt":"2024-07-12T00:05:32","guid":{"rendered":"http:\/\/nepttp.avidakizomba.co.za\/?p=2998"},"modified":"2025-09-12T13:18:30","modified_gmt":"2025-09-12T11:18:30","slug":"academic-journals","status":"publish","type":"post","link":"https:\/\/www.escience.ac.za\/index.php\/2024\/07\/12\/academic-journals\/","title":{"rendered":"Academic Journals"},"content":{"rendered":"

Akinkaja, O.<\/strong> & Mosia, M., 2021. Using deep learning and sentiment analysis to identify mismatches between online courses\u2019 reviews and ratings. In:\u00a02021 3rd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>, Windhoek, Namibia, pp.1\u20136. doi:10.1109\/IMITEC52926.2021.9714655<\/a><\/p>

Antwi, A., Kammies, E.T<\/strong>., Chaka, L. & Arasomwan, M.A., 2025. Forecasting South African grain prices and assessing the non-linear impact of inflation and rainfall using a dynamic Bayesian generalized additive model.\u00a0Frontiers in Applied Mathematics and Statistics<\/em>, 11. doi:10.3389\/fams.2025.1582609.doi:10.1109\/IMITEC52926.2021.9714655<\/a><\/p>

Baloyi, N.<\/strong>, 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 + \u03b3 final state. In:\u00a0SAIP Conference<\/em>. [online] Available at:\u00a0https:\/\/events.saip.org.za\/event\/144\/contributions\/1492\/attachments\/284\/388\/NBaloyi_SAIP_Proceedings.pdf<\/a>\u00a0[Accessed 21 Sep. 2021].<\/p>

Bokgoshi, L., Sixhaxa, K., Jadhav, A., Nyamane, S<\/strong>. & Ajoodha, R., 2023. Enhancing timely graduations: An explainable AI approach to predict academic risks in South African students. In:\u00a02023 International Conference on Electrical, Computer and Energy Technolo<\/em>gies (<\/em>ICECET)<\/em>, Cape Town, South Africa, pp.1\u20137. doi:10.1109\/ICECET58911.2023.10389444<\/a>.<\/p>

Bonnet, W.<\/strong> & Celik, T., 2021. Random sampling-based relative. IEEE Geoscience and Remote Sensing Letters<\/em>, 9321136, pp.1\u20134.<\/p>

Byamugisha, J., Saib, W., Gaelejwe, T.<\/strong>, 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.\u00a0Association for the Advancement of Artificial Intelligence<\/em>, PR-12-PR-12. Available at:\u00a0https:\/\/doi.org\/10.1158\/1557-3265.adi21-pr-12<\/a>.<\/p>

Chabumba, D.R.<\/strong>, Jadhav, A. & Ajoodha, R., 2021. Predicting telecommunication customer churn using machine learning techniques. Interdisciplinary Research in Technology and Management<\/em>, 14 September, pp.625\u2013636.<\/p>

Chabumba, R.<\/strong>, Ajoodha, R. & Jadhav, A., 2021. Predicting telecommunication customer churn using machine learning techniques. In:\u00a0International Conference on Interdisciplinary Research in Technology and Management<\/em>. [online] Available at:\u00a0www.kaggle.com<\/a>.<\/p>

Daniel, L.O.<\/strong>, Mashao, D., Olukanmi, P. & Singh, G., 2025. Network slicing for mitigating interference in dense deployments. In:\u00a02025 IEEE 3rd Wireless Africa Conference (WAC)<\/em>, Pretoria, South Africa, pp.1\u20136. doi:10.1109\/WAC63911.2025.10992603<\/a>.<\/p>

Daniel, L.O<\/strong>., Sigauke, C., Chibaya, C. & Mbuvha, R., 2020. Short-term wind speed forecasting using statistical and machine learning methods. Algorithms<\/em>, 13(6).<\/p>

Daniel, L.O.<\/strong>, Singh, G., Mashao, D. & Olukanmi, P., 2024. Optimized coordinated resource allocation and power control for wireless communication networks. In:\u00a02024 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD)<\/em>, Port Louis, Mauritius, pp.1\u201310. doi:10.1109\/icABCD62167.2024.10645229<\/a>.<\/p>

Desai, P.<\/strong> & Harvey, R., 2023. Is the Southern African Development Community afflicted by premature deindustrialisation?\u00a0The Africa Governance Papers<\/em>, 1(4). Available at:\u00a0https:\/\/tagp.gga.org\/index.php\/system\/article\/view\/55<\/a>\u00a0[Accessed 12 Aug. 2025].<\/p>

Desai, P.<\/strong>, 2023. The link between population density, developmental outcomes and perceptions of governance in sub-Saharan Africa.\u00a0The Africa Governance Papers<\/em>, 1(3). Available at:\u00a0http:\/\/160.119.143.6\/index.php\/system\/article\/view\/42<\/a>.<\/p>

Essa, Y<\/strong>. et al., 2024. Classifying single versus multiple ground strike point lightning flashes from high-speed lightning videos using deep learning. In:\u00a037th International Conference on Lightning Protection (ICLP)<\/em>, Dresden, Germany, pp.297\u2013302.<\/p>

Essa, Y<\/strong>., Ajoodha, R. & Hunt, H.G.P., 2020. A LSTM recurrent neural network for lightning flash prediction within Southern Africa using historical time-series data. In: 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)<\/em>. IEEE.<\/p>

Essa, Y<\/strong>., Hunt, H.G.P. & Ajoodha, R., 2021. Short-term prediction of lightning in Southern Africa using autoregressive machine learning techniques. In:\u00a02021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)<\/em>, Toronto, ON, Canada, pp.1\u20135. doi:10.1109\/IEMTRONICS52119.2021.9422493<\/a>.<\/p>

Essa, Y.,<\/strong> Hunt, H.G.P., Gijben, M. & Ajoodha, R., 2022. Deep learning prediction of thunderstorm severity using remote sensing weather data.\u00a0IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing<\/em>, 15(June), pp.4004\u20134013. doi:10.1109\/JSTARS.2022.3172785<\/a>.<\/p>

Freeborough, W.<\/strong> & van Zyl, T., 2022. Investigating explainability methods in recurrent neural network architectures for financial time series data. Applied Sciences (Switzerland)<\/em>, 12(3), pp.1\u201315.<\/p>

Freeborough, W<\/strong>., 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.\u00a0Viruses<\/em>, 13(9), p.1820. Available at:\u00a0https:\/\/doi.org\/10.3390\/v13091820<\/a>.<\/p>

Harvey, R., Morrison, S.<\/strong> & Desai, P., 2025. Is South Africa afflicted by the resource curse?\u00a0The Extractive Industries and Society<\/em>, 23, p.101678. Available at:\u00a0https:\/\/doi.org\/10.1016\/j.exis.2025.10167<\/a>8.<\/p>

Hayes, B., Ashwal, L.D., Khumalo, K.B.<\/strong> & Iaccheri, L.M., 2024. Major, trace element and Sr-Nd isotope evidence for a sublithospheric mantle source for the Umkondo large igneous province.\u00a0Geoscience Frontiers<\/em>, 15(1), p.101719. doi:10.1016\/j.gsf.2023.101719<\/a>.<\/p>

Kgoale, T.<\/strong>, Whata, A., Nasejje, J.B., Rad, N.N. & Mulaudzi, T., 2024. Estimating average and individual treatment effects in the presence of time-dependent covariates. In: Chen, D.G. & Coelho, C.A. (eds.)\u00a0Biostatistics Modeling and Public Health Applications<\/em>. Emerging Topics in Statistics and Biostatistics. Springer, Cham. doi:10.1007\/978-3-031-69690-9_5<\/a>.<\/p>

Khumalo, K.B<\/strong>., Ashwal, L.D., Hayes, B., Iaccheri, L.M., Meintjes, P.G. & Webb, S.J., 2024. Neoarchean lavas of the Ventersdorp Large Igneous Province, South Africa: Sr-Nd-Hf isotopic and trace element evidence for a long-lived plume beneath a stationary African continent.\u00a0Earth-Science Reviews<\/em>, 252, p.104752. doi:10.1016\/j.earscirev.2024.104752<\/a>.<\/p>

Langa, K.<\/strong>, Wang, H. & Okuboyejo, O., 2025. Parameter-efficient fine-tuning of pre-trained large language models for financial text analysis. In: Gerber, A., Maritz, J. & Pillay, A.W. (eds.)\u00a0Artificial Intelligence Research. SACAIR 2024<\/em>. Communications in Computer and Information Science, vol. 2326. Springer, Cham. doi:10.1007\/978-3-031-78255-8_1<\/a>.<\/p>

Lange, R.<\/strong>, Lange, T. & Van Zyl, T.L., 2020. Predicting particle fineness in a cement mill. In: Proceedings of 2020 23rd International Conference on Information Fusion (FUSION)<\/em>.<\/p>

Mabunda, J.G.K.<\/strong>, Jadhav, A. & Ajoodha, R., 2021. A review: Predicting student success at various levels of their learning journey in a science programme. In:\u00a02021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)<\/em>, Toronto, ON, Canada, pp.1\u20135. doi:10.1109\/IEMTRONICS52119.2021.9422519<\/a>.<\/p>

Mabunda, J.G.K.<\/strong>, Jadhav, A. & Ajoodha, R., 2021. Sentiment analysis of student textual feedback to improve teaching. In: Interdisciplinary Research in Technology and Management<\/em>. CRC Press, pp.643\u2013651.<\/p>

Magoma, P.<\/strong> & Chibaya, C., 2021. Towards a CIA compliant RSA hybrid built on an artificial neural network. In:\u00a02021 3rd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>, Windhoek, Namibia, pp.1\u20139. doi:10.1109\/IMITEC52926.2021.9714634<\/a>.<\/p>

Magoma, P<\/strong>. & Chibaya, C., 2021. Towards a CIA compliant RSA hybrid built on an artificial neural network. In: 2021 3rd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>. IEEE.<\/p>

Makubyane, K<\/strong>. & Maposa, D., 2024. Forecasting short- and long-term wind speed in Limpopo Province using machine learning and extreme value theory.\u00a0Forecasting<\/em>, 6(4), pp.885\u2013907. doi:10.3390\/forecast6040044<\/a>.<\/p>

Malatsi, T.D<\/strong>. & Kara, A.H., 2022. Invariance, conservation laws and reductions of some classes of \u201chigh\u201d order partial differential equations.\u00a0Transactions of the Royal Society of South Africa<\/em>, 77(3), pp.255\u2013270. doi:10.1080\/0035919X.2022.2164629<\/a>.<\/p>

Masangu, L<\/strong>., Jadhav, A. & Ajoodha, R., 2021. Predicting student academic performance using data mining techniques. Advances in Science, Technology and Engineering Systems<\/em>, 6(1), pp.153\u2013163.<\/p>

Matsane, L.<\/strong>, Jadhav, A. & Ajoodha, R., 2020. The use of automatic speech recognition in education for identifying attitudes of the speakers. In: 2020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)<\/em>.<\/p>

Mawela, V<\/strong>. & Chibaya, C., 2020. Generation of virtual reality environments in which to evaluate swarm adherence to prescribed control rules. In: 2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>, pp.9\u201312.<\/p>

Michael, T.N<\/strong>., Obagbuwa, I.C., Whata, A. & Madzima, K., 2023. A comparative modeling and comprehensive binding site analysis of the South African Beta COVID-19 variant\u2019s spike protein structure. In: Lahby, M., Pilloni, V., Banerjee, J.S. & Mahmud, M. (eds.)\u00a0Advanced AI and Internet of Health Things for Combating Pandemics<\/em>. Springer, Cham. doi:10.1007\/978-3-031-28631-5_18<\/a>.<\/p>

Mngadi, N.<\/strong>, Ajoodha, R. & Jadhav, A., 2020. A conceptual model to identify vulnerable undergraduate learners at higher-education institutions. In: 2020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>. IEEE, pp.1\u20138.<\/p>

Mohale, V.Z<\/strong>. & Obagbuwa, I.C., 2024. Assessing the impact of climate variability on wheat yield in Bloemfontein wheat farms through time series analysis. Edelweiss Applied Science and Technology<\/em>, 8(5), pp.1213\u20131234.<\/p>

Mohale, V.Z<\/strong>. & Obagbuwa, I.C., 2024. Poverty analysis and prediction in South Africa using remotely sensed data.\u00a0Applied Computational Intelligence and Soft Computing<\/em>, 2024, p.5137110. doi:10.1155\/2024\/5137110<\/a>.<\/p>

Mohale, V.Z<\/strong>. & Obagbuwa, I.C., 2025. A systematic review on the integration of explainable artificial intelligence in intrusion detection systems to enhance transparency and interpretability in cybersecurity.\u00a0Frontiers in Artificial Intelligence<\/em>, 8, p.1526221. doi:10.3389\/frai.2025.1526221<\/a>.<\/p>

Mohale, V.Z<\/strong>. & Obagbuwa, I.C., 2025. Evaluating machine learning-based intrusion detection systems with explainable AI: Enhancing transparency and interpretability.\u00a0Frontiers in Computer Science<\/em>, 7, p.1520741. doi:10.3389\/fcomp.2025.1520741<\/a>.<\/p>

Mugware, F.W.<\/strong>, Ravele, T. & Sigauke, C., 2025. Short-term predictions of global horizontal irradiance using recurrent neural networks, support vector regression, gradient boosting random forest and advanced stacking ensemble approaches. Computation<\/em>, 13(3), p.72.<\/p>

Mugware, F.W<\/strong>., Sigauke, C. & Ravele, T., 2024. Assessing the predictive power of machine learning models for wind speed prediction under different weather conditions. [Details incomplete for full citation].<\/p>

Mugware, F.W.<\/strong>, Sigauke, C. & Ravele, T., 2024. Evaluating wind speed forecasting models: A comparative study of CNN, DAN2, Random Forest and XGBOOST in diverse South African weather conditions.\u00a0Forecasting<\/em>, 6(3), pp.672\u2013699. Available at:\u00a0https:\/\/doi.org\/10.3390\/forecast6030035<\/a>.<\/p>

Mulangaphuma, M.P.<\/strong>, Chibaya, C. & Madzima, K., 2021. A dynamic nDES model for hiding datasets for machine learning. In:\u00a02021 3rd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>, Windhoek, Namibia, pp.1\u20135. doi:10.1109\/IMITEC52926.2021.9714631<\/a>.<\/p>

Mutavhatsindi, T.<\/strong>, Sigauke, C. & Mbuvha, A.R., 2020. Forecasting hourly global horizontal solar irradiance in South Africa using machine learning models. IEEE Access<\/em>, 8, pp.198872\u2013198885.<\/p>

Nemavhola, A<\/strong>., Chibaya, C. & Ochara, N.M., 2021. Application of the LSTM – deep neural networks – in forecasting foreign currency exchange rates. In: 2021 3rd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>. IEEE.<\/p>

Nemavhola, A.<\/strong>, Chibaya, C. & Viriri, S., 2025. A systematic review of CNN architectures, databases, performance metrics, and applications in face recognition.\u00a0Information<\/em>, 16(2), p.107. doi:10.3390\/info16020107<\/a>.<\/p>

Nemavhola, A.<\/strong>, Viriri, S. & Chibaya, C., 2025. A scoping review of literature on deep learning techniques for face recognition.\u00a0Human Behavior and Emerging Technologies<\/em>, 5979728, pp.1\u201314. doi:10.1155\/hbe2\/5979728<\/a>.<\/p>

Nengwani, M.<\/strong>, Bhero, E. & Chibaya, C., 2024. Towards an aquatic school inspired swarm intelligence ontology. In:\u00a02024 4th International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>, Vanderbijlpark, South Africa, pp.147\u2013151. doi:10.1109\/IMITEC60221.2024.10851048<\/a>.<\/p>

Ngwenduna, K.S<\/strong>. & Mbuvha, R., 2021. Alleviating class imbalance in actuarial applications using generative adversarial networks. Risks<\/em>, 9(3), pp.1\u201333.<\/p>

Nhlapho, W.<\/strong>, Atemkeng, M., Brima, Y. & Ndogmo, J.-C., 2024. Bridging the gap: Exploring interpretability in deep learning models for brain tumor detection and diagnosis from MRI images.\u00a0Information<\/em>, 15(4), p.182. doi:10.3390\/info15040182<\/a>.<\/p>

Nkolele, R.<\/strong> & Wang, H., 2021. Explainable machine learning: A manuscript on the customer churn in the telecommunications industry. In:\u00a02021 Ethics and Explainability for Responsible Data Science (EE-RDS)<\/em>, Johannesburg, South Africa, pp.1\u20137. doi:10.1109\/EE-RDS53766.2021.9708561<\/a>.<\/p>

Nkolele, R.<\/strong>, 2020. Mapping of narrative text fields to ICD-10 codes using natural language processing and machine learning. In: Proceedings of the Fourth Widening Natural Language Processing Workshop<\/em>. Association for Computational Linguistics (ACL), pp.131\u2013135.<\/p>

Ntsenge, K.Y.<\/strong>, 2022. Indigenous women moving from physical to digital fires: the evolution of methods of transmission of indigenous knowledge. In:\u00a0Digital Humanities in Precarious Times<\/em>. [online] Available at:\u00a0https:\/\/humanities.nwu.ac.za\/humanities\/digital-humanities-precarious-times<\/a>\u00a0[Accessed 12 Aug. 2025].<\/p>

Nyamane, S<\/strong>., Abd Elbasit, M.A.M. & Obagbuwa, I.C., 2024. Harnessing deep learning for meteorological drought forecasts in the Northern Cape, South Africa.\u00a0International Journal of Intelligent Systems<\/em>, 7562587, pp.1\u201322. doi:10.1155\/2024\/7562587<\/a>.<\/p>

Nyamane, S.<\/strong>, Jadhav, A. & Ajoodha, R., 2023. Predicting academic success in blended learning environments: A probabilistic Bayesian approach leveraging student trajectory data. In:\u00a0P<\/em>roceedings of the International Conference on Information Systems and Emerging Technologies (ICISET)<\/em>. Available at:\u00a0https:\/\/ssrn.com\/abstract=4663410<\/a>.<\/p>

Obagbuwa, I.C., Mohale, V.Z<\/strong>. & Makade, M., 2023. Anti-lock braking system using Monte Carlo simulations. In: Das, A.K., Nayak, J., Naik, B., Vimal, S. & Pelusi, D. (eds.)\u00a0Computational Intelligence in Pattern Recognition<\/em>. CIPR 2022. Lecture Notes in Networks and Systems, vol. 725. Springer, Singapore. doi:10.1007\/978-981-99-3734-9_53<\/a>.<\/p>

Ohamadike, N<\/strong>. & Orakwe, E.C., n.d. The role of education in the public perception of corruption in Sudan and Zimbabwe.\u00a0Politeia<\/em>, pp.1\u201311. doi:10.25159\/2663-6689\/13663<\/a>.<\/p>

Ohamadike, N.,<\/strong> 2022. Measuring political accountability in Africa using a multi-item index. The Africa Governance Papers<\/em>, 1(2), pp.32\u201347. Available at: https:\/\/tagp.gga.org\/index.php\/system\/article\/view\/23.<\/p>

Oni, O.O.<\/strong> & van Zyl, T.L., 2020. A comparative study of ensemble approaches to fact-checking for the FEVER shared task. In:\u00a02020 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)<\/em>, Gold Coast, Australia, pp.1\u20138. doi:10.1109\/CSDE50874.2020.9411564<\/a>.<\/p>

Orievulu, K.S<\/strong>., 2020. (Re-engaging) the \u201ctyranny\u201d of process in participatory development programming in Africa: Fadama in Nigeria as a case study.\u00a0South African Journal of International Affairs<\/em>, 27(2), pp.243\u2013264. Available at:\u00a0https:\/\/doi.org\/10.1080\/10220461.2020.1785930<\/a>.<\/p>

Ramalivhana, D.D.<\/strong>, Chibaya, C. & Madzima, K., 2021. Trends matching as a dataset attack detection strategy during machine learning. In: 2021 3rd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>. IEEE.<\/p>

Ratshilengo, M<\/strong>., Sigauke, C. & Bere, A., 2021. Short-term solar power forecasting using genetic algorithms: An application using South African data. Applied Sciences (Switzerland)<\/em>, 11(9).<\/p>

Sibanda, K.<\/strong>, Gundu, T. & Whata, A., 2020. Assessing the credibility of South Africa’s anti-retroviral treatment (ART) eligibility guidelines using regression discontinuity designs. In:\u00a02020 2nd International Multidisciplinary Information Technology and Engineering Conference (IMITEC)<\/em>, Kimberley, South Africa, pp.1\u20135. doi:10.1109\/IMITEC50163.2020.9334077<\/a>.<\/p>

St\u00f6rbeck, C., Young, A., Moodley, S. & Ismail, S<\/strong>., 2022. Audiological profile of deaf and hard-of-hearing children under six years old in the \u201cHI HOPES cohort\u201d in South Africa (2006\u20132011).\u00a0International Journal of Audiology<\/em>, 62(9), pp.845\u2013852. Available at:\u00a0https:\/\/doi.org\/10.1080\/14992027.2022.2101551<\/a>.<\/p>

Thulare, E<\/strong>., Ajoodha, R. & Jadhav, A., 2021. An empirical analysis and application of the expectation-maximization and matrix completion algorithms for varying degrees of missing data. In: 2021 Southern African Universities Power Engineering Conference\/Robotics and Mechatronics\/Pattern Recognition Association of South Africa (SAUPEC\/RobMech\/PRASA)<\/em>. IEEE.<\/p>","protected":false},"excerpt":{"rendered":"

Akinkaja, O. & Mosia, M., 2021. Using deep learning and sentiment analysis to identify mismatches between online courses\u2019 reviews and ratings. In:\u00a02021 3rd International Multidisciplinary Information Technology and Engineering Conference (IMITEC), Windhoek, Namibia, pp.1\u20136. doi:10.1109\/IMITEC52926.2021.9714655 Antwi, A., Kammies, E.T., Chaka, L. & Arasomwan, M.A., 2025. Forecasting South<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[12],"tags":[],"class_list":["post-2998","post","type-post","status-publish","format-standard","hentry","category-publications"],"_links":{"self":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts\/2998","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/comments?post=2998"}],"version-history":[{"count":12,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts\/2998\/revisions"}],"predecessor-version":[{"id":4630,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/posts\/2998\/revisions\/4630"}],"wp:attachment":[{"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/media?parent=2998"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/categories?post=2998"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.escience.ac.za\/index.php\/wp-json\/wp\/v2\/tags?post=2998"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}