University of Fort Hare Institutional Repository
Communities in DSpace
Select a community to browse its collections.
Recent Submissions
Benefits and challenges of AIOPS adoption and usage in HEIs in developing countries
(Stellenbosch University, 2024-11) Funda, Vusumzi; Francke, Errol
Adopting Artificial Intelligence for IT Operations (AIOps) holds transformative potential within Higher Education Institutions (HEIs) in developing countries. This systematic literature review delves into the benefits, challenges, and emerging trends associated with AIOps integration in this context. The review encompasses studies published between 2013 and 2023, focusing on the academic, administrative, and operational dimensions of AIOps adoption. The synthesis of 12 selected studies reveals a landscape where AIOps augments pedagogical strategies, automates administrative tasks, and enhances institutional decision-making. Academic benefits manifest through personalised learning experiences, innovative pedagogical approaches, and predictive analytics for student success. However, the integration of AIOps is full of challenges. Technical hurdles encompass data quality and availability, compatibility, and resource constraints, requiring comprehensive technological foundations. Organisational and cultural challenges necessitate strategies to mitigate change resistance, provide staff training, and address ethical considerations. The review identifies emerging patterns such as collaborative learning environments, data-driven institutional management, and the moral integration of AI in education. The interplay of benefits and challenges underscores the importance of a holistic approach involving educators, technologists, administrators, and policymakers. The findings illuminate the potential for HEIs to harness AIOps's capabilities while navigating intricacies to foster an AI-enhanced educational landscape. The implications for HEIs encompass strategic investment in infrastructure, comprehensive staff training, and ethical frameworks for AI use. The article concludes by advocating for an adaptive approach to AIOps adoption, informed by the synthesis of benefits, challenges, and emerging trends, to shape the future of education in developing countries.
Reservoir characterization and baseline rock physics investigation for CO2 storage in the Bredasdorp Basin, offshore South Africa
(University of Fort Hare, 2024) Vandala, Sandisile; Magoba, M.
Reservoir characterisation and baseline rock physics investigation for CO2 storage in the Bredasdorp Basin, offshore South Africa was extensively executed in 3 wells, namely E-E1, E S3, and E-W2. This study aimed to provide a qualitative and quantitative description of Lower Cretaceous clastic rocks (upper shallow marine sandstones) to explore their potential viability for CO2 sequestration in the Bredasdorp Basin based on their petrographic, petrophysical and rock physical characteristics. Geophysical wireline logs, conventional core analysis, core logging and petrographic studies, i.e., thin sections and Scanning Electron Microscopy/Energy Dispersive X-ray Spectroscopy (SEM/EDS), were utilized to determine lithology, fluid type, porosity, and permeability. The reservoirs were identified at ranging depths of 2336 m to 3528.5 m, with corresponding temperature and pressure ranging from 102.38 – 132.66°C and 26.95 – 36.29 MPa - meeting critical CO2 storage criteria. Clay volume, porosity, permeability, water saturation, and pore throat radius were quantitatively determined. Clay volumes ranged between 19.55 % and 27.19 %, confirming the shaly sandstone nature of the reservoirs. Water saturation varied from 51.78 % to 67.94 %, impacting the storage potential. Pore throat radius was examined using Winland’s technique and ranged from 1 – 2.4 µm, with the best reservoir quality found in lithofacies A and B (mesoporous). In contrast, microporous lithofacies E, F, and G were deemed non-reservoir zones due to their limited storage capacity. Reservoir quality across the wells was significantly impacted by diagenesis. In E-E1, porosity and permeability were reduced due to the presence of anhydrite or marialite and smectite. Concurrently, E-S3 experienced occlusion from illite and smectite while E-W2 exhibited concave-convex (long) contact diagenesis with the presence of kaolinite, further restricting reservoir potential. Average porosity ranged from 6.89 – 10.88 %, with permeability-range of 0.34 – 5.35 mD. The complementary acoustic properties of the reservoirs show a bulk density of 2.49 – 2.55 g/cc, with shear and compressional velocities between 3743.43 – 4792.12 m/s, respectively. Fluid substitution evaluation minimal changes in Vp when brine was replaced with oil and gas, however, significant decreases were observed when replaced by CO2. CO2 substitution notably reduced density in all wells except E-W2, which remained unaffected due to its micro- and nanopores. The results from the studied reservoir properties showed that the Upper Shallow Marine sandstones, E-S3 is the most prospective site for CO2 storage, even though its quality may be compromised by its significant water saturation and excess glauconite. E-E1 and E-W2 displayed some unfavourable properties such as high-velocity values, compaction (long contact) and smectite and kaolinite making them unsuitable for CO2 geological storage.
Education in Context: ECC 422, Degree Examinations October/November 2025
(University of Fort Hare, 2025-10) Nkohla, M.B.; Karima, R.; Kafu-Quvane, B.; Madiba, O.T.C.
Intermediate Language and African Literature: ECL 210E, Supplementary Examinations June 2025
(University of Fort Hare, 2025-06) Marawu, S.; Kirton-Els, T.; Mkhize, J.
Artificial intelligence-powered decision support system for operational decision-making in the ICT department of a selected African university
(Taylor and Francis Group, Routledge, 2024-09-16) Funda, Vusumzi; Francke, Errol
This paper aims to explore the effect of an artificial intelligence-enabled decision support system (AIDSS) on decisionmaking processes within a university setting, focusing on the ICT department of a selected South African university. The research objectives revolve around the effectiveness of AIDSS in enhancing decision-making in higher education institutions. Convenience sampling was employed in this study and a questionnaire administered to 28 participants. These methods were chosen to gather insights into the practical application of AI technology in the context of IT operational decision-making. The major findings of this research reveal that AIDSS has the potential to significantly improve decision-making processes in higher education. Despite these advancements, the research acknowledges the ethical and societal implications arising from AI integration, underscoring the importance of achieving a balance between technical advancement and the upholding of human values. As a major policy implication, this study underscores the importance of embracing AI technologies in higher education institutions to enhance decision-making processes, thus improving the efficiency and effectiveness of IT operations. The original contribution of this research lies in its exploration of the practical use of AIDSS in South African higher education, offering insights into how AI
can be harnessed to advance decision-making.