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Welcome to ResearchSpace, the institutional repository of the CSIR. ResearchSpace is an open access electronic archive collecting, preserving and distributing scholarly digital materials created by the CSIR.

Recent Submissions

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The value of demand response in South Africa's electric power system

(2025) Mdhluli, Sipho D; Makopo, Raisibe S; Mukoma, Peter; Madhoo, H; Figlan, T

The increasing adoption of grid-connected Distributed Energy Resources provided Distribution (and Transmission) Network Operators with the opportunity to procure a range of "flexibility services" from these third partyoperated assets in a way that is beneficial to the local or national electricity network—examples of flexibility services that can be procured include large-scale, grid-connected battery storage systems and demand response. This paper will explore different types of demand response interventions utilised globally, provide a South African context of the current demand response, and, lastly, use Plexos to quantify the system value that untapped demand response potential can provide to the South African electricity markets if pursued.

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Predictive analytics for proactive email security risk management: A systematic review

(2024-12) Singano, Zothile T; Mudau, Tshimangadzo C; Ngejane, Hombakazi C; Ndlovu, Lungisani; Mncwango, Lungisani S

In recent years, email has become an important communication tool for sharing private messages to crucial business message exchanges. However, its widespread use makes it a major target for cyber-attacks, including phishing, spam, and malware. These growing threats highlight the urgent need to investigate email security risk management to protect against attacks and maintain the integrity of communication systems. The study reviews the literature on the challenges of email security, risk management, and the role of predictive analysis in combating these threats. Using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), thirty-five (35) relevant peer-reviewed research articles were identified in various open research databases. This systematic literature review (SLR) also includes relevant case studies. The findings reveal that the integration of machine learning (ML), natural language processing (NLP), and real-time data analytics into email security frameworks improves threat detection and mitigation. Furthermore, these models often lack adaptability across languages and cultures. Additionally, they do not integrate well with human-centric security measures. Therefore, it is important to develop culturally adaptive predictive models, sector-specific solutions for industries such as finance and healthcare and incorporate behavioural analytics to enhance email threat detection and prevention. In other words, a comprehensive approach that combines technical advances with behavioural insights is crucial to strengthening email security and maintaining the integrity of global digital communications amid evolving cyber threats.

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Review of Machine Learning Techniques That Enable Network Slicing in Open RAN

(2025) Mthethwa, Nosipho BP; Mwangama, J; Masonta, Moshe T

The evolution of 5G networks and the anticipated capabilities of 6G have placed significant emphasis on intelligent Radio Access Network (RAN) slicing to meet the diverse and stringent requirements of services such as enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). This paper reviews state-of-the-art techniques, with a particular focus on the application of machine learning (ML) approaches in RAN slicing. The study categorises ML algorithms based on their primary functions: time series networks for traffic prediction, federated learning for security and privacy, supervised learning for slice admission control, and reinforcement learning for resource allocation and management. It also highlights the complementary nature of these techniques, as demonstrated by hybrid models such as federated deep RL and LSTM-integrated distributed deep RL.

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Feasibility of using metakaolinite for the treatment of coal-mining acid mine drainage: Insights into the interaction behaviour and partitioning of inorganic contaminants

(2025) Mothetha, M; Msagati, T; Masindi, Vhahangwele; Kebede, K

In this novel study, the efficacy of metakaolinite for the treatment of acid mine drainage (AMD) was evaluated. The optimized parameters included the feedstock dosage and contact time. Experimental results were further explored using inductively coupled plasma–mass spectrometry (ICP–MS), ICP–OES (inductively coupled plasma–optical emission spectroscopy), Fourier transform infrared spectroscopy (FTIR), high-resolutionfocused ion beam/scanning electron microscopy (HR–FIB/SEM), energy-dispersive x-ray spectroscopy (EDS), x-ray fluorescence (XRF) and x-ray diffraction (XRD). Optimum conditions were observed to be 45 min of mixing time, ≥10 g·L−1 of feedstock dosage, i.e., metakaolinite, and ambient temperature and pH. The metal content (Fe, Mn, Cr, Cu, Ni, Pb, Al, and Zn) embedded in AMD matrices were partially removed whilst the level of sulphate was significantly reduced. Chemical species removal efficacies were observed to occur in the following sequence; Cr ≥ Zn ≥ Cu ≥ Pb ≥ Mn ≥ Ni ≥ sulphate ≥ Mg ≥ Fe, with the following removal percentages: 100, 91.7, 74.6, 65, 38.8, 37.5, 32.3, 13.8, and 8.3%, respectively. Thus metakaolinite proved to be partially effective in the treatment of AMD emanating from coal-mining processes. Furthermore, to enhance the performance of this technology, a polishing technique needs to be coupled or integrated to further remove residual inorganic contaminants, as well as other forms of modification such as the addition of alkaline agents to synthesize the nanocomposite and increase its alkalinizing capabilities.

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Assessment of the water quality and microbial regrowth in drinking water treatment plants and the distribution network

(2025) Nduli, S; Tekere, M; Masindi, Vhahangwele; Foteinis, S

Recurring contamination of drinking water and microbial regrowth in distribution networks remains an issue of prime concern to water provision authorities. This is common in the developing world, where aging and under-developed infrastructure along with degraded freshwater resources exacerbate the problem. Here, the year-round measurements, on a weekly basis, of the quality of drinking water from a typical water treatment and distribution system in the South African setting are reported. Results confirmed that the drinking water treatment plants under study rely on heavily degraded freshwater, mainly affected by microbial contamination which could suggest the release of untreated or poorly treated wastewater in receiving water bodies, a common problem in low- and medium-income countries (LMICs). In most cases, freshwater was effectively treated (e.g., 100% removal for E. coli and over 99%, 92%, and 83% removal for total coliforms, turbidity, and colour, respectively) to meet the drinking water quality standards for South Africa and the world health organisation (WHO) guidelines. Yet, in some monthly measurements, certain contaminants such as ammonia were above the prescribed limits, suggesting the need to operationally improve water treatment and/or curbing the release of untreated or poorly treated wastewater in the catchment. Alarmingly, microbial regrowth was identified within the distribution networks, and this was significantly correlated (p < 0.01) with the distance (from 0 to 101 km) that the water travels within each distribution network and nodes. Also, large seasonal variations in the water quality were observed, with water quality being poorer during winter, likely tracing back to environmental factors in combination with parts of the distribution system being laid proximal to the surface or above ground. Overall, a clear correlation between the chlorine concentration and microbial failure was observed. This could be attributed to high chlorine demand, which devoids the system of residual chlorine, thus, to a larger extent, creating an environment that is conducive to microbial regrowth. Therefore, it can be concluded that high chlorine demand is the main contributor towards microbial regrowth within the water distribution networks, and, as such, comprehensive chlorine demand and decay studies are needed to identify whether chlorine booster stations are required, particularly at the distal ends of the network. This will inform the sustainable top-up of chlorine residual in the distributed water, hence effectively suppressing microbial regrowth. Albeit, high chlorine levels are not a panacea, since these can lead to the formation of toxic and carcinogenic disinfection by-products such as trihalomethanes (THMs). Therefore, first and foremost, focus should be placed on safeguarding the quality of freshwater resources.