Tshwane University of Technology
  • Pretoria, Gauteng, South Africa
Recent publications
Photovoltaic (PV) plants utilization for green solar energy is growing exponentially in demand as industries committed to move away from carbon energy sources such as coals, oil, or gas. However, for efficient green solar energy utilization, a precise prediction method is required to minimize design composition wastage. The measured output current determined by empirical method will be compared with the predicted current obtained from the proposed neural network (ANN) and random forest (RF) methods. The comparative analysis of the measured and the proposed models is evaluated by using the minimum root means square error (RMSE), mean absolute percentage error (MAPE), and mean bias error (MBE). The obtained results suggest the superiority of RF over the ANN with improvement performance metrics values of 173% for RMSE, 39% for MAPE, and 188% for MBE.
Banking credit risk analysis is a form of evaluation conducted by financial institutions to determine applicants’ ability to repay their debt obligation. Financial institutions, such as banks, set objectives to offer credit to creditworthy customers, after spending time trying to evaluate their repaying capacity. In this paper, we propose a credit risk analysis system based on an artificial neural network (ANN) to identify customers who will default. A feedforward propagation algorithm is used to train the model consisting of three layers. Data pre-processing is performed to clean the datasets and check for missing variables. The datasets were normalized using min–max normalization to get the correlation among the variables. The datasets are applied to the proposed model and logistic regression models, and the comparison shows the proposed model which has a better performance.
A thorough understanding of an industrial robot’s dynamic model is critical for practical robotic applications. An effective dynamic model is required for optimal controller design and trajectory planning. Robot manufacturers only provide kinematic data, which can only guarantee a certain level of positioner accuracy. The design of the trajectory-planning scheme, on the other hand, necessitates a thorough understanding of its dynamic features. The identification of dynamic parameters involves several procedures. This study used the Euler-Lagrangian equation to derive the robot dynamic model in its canonical form. To excite each link of the irb1600 robot industrial robot while avoiding displacement, velocity, and acceleration discontinuities at the start and endpoints, a Freudenstein 1-3-5 trajectory based on Fourier series expansion was used. The dynamic parameters were determined using the nonlinear least-squares approach based on the Levenberg-Marquart equation. The Savitzky-Golay smoothing filters improved the identification method by decreasing system noise. © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
There is a growing need to understand the role of non-cognitive factors in relation to university students’ academic performance and successful adaptation to university life. This study investigated the relationship between the non-cognitive factor “resilience” and student success (academic performance, turnover intentions, brain-body optimisation) among South African university students. This cross-sectional correlational study analysed data from 360 first-year students. Self-report data were collected using the Neurozone Assessment, comprising two subscales: the Brain Performance Diagnostic and the Resilience Index. Turnover intentions were assessed using the Neurozone Assessment, and students’ academic marks were obtained via the university’s management information system. Correlational analyses revealed significant positive relationships between the Stress Mastery and Positive Affect components of resilience and academic performance, a significant negative relationship between the Positive Affect component of resilience and turnover intentions, as well as significant positive relationships between brain-body optimisation and all three components of resilience (Stress Mastery, Positive Affect, and Early-Life Stability). Through regression analyses, we identified the behavioural predictors that underlie resilience and outline a framework for implementing behavioural interventions to enhance resilience and increase student success. Resilience is an important non-cognitive determinant of student success in first-year students.
Abstract: The objective of this paper was to establish challenges and benefits on formalization in South Africa using a qualitative approach. To meet the objective, 15 interviews were carried out with owners of small businesses that had just formalized in Johannesburg and Pretoria. This study contributes to the existing knowledge on small business formalization by bringing evidence from formalized businesses. The research does so through asking unique questions that cannot be answered quantitatively. Using themes for analysis, the study found conditional formalization, high levels of bureaucracy, unsustainable fees, information asymmetry, credit or capital unavailability and corruption as key challenges being faced by emerging entrepreneurs. In addition, the study also identified increased chances to benefit from BEE, improved access to information to supply the public sector, improved chances of securing credit, increased credibility of the business and better access to markets as the benefits that entrepreneurs derive from formalization. This study recommends that informal businesses be supported through skills training initiatives and expanded credit opportunities so that they can be of better size and capacity to formalize. Subjects: Economics; Political Economy; Business, Management and Accounting Keywords: formalization; tax evasion; survivalists; informal; Small businesses JEL: E24; J81; L26
Background Substandard and Falsified (SF) medical products are a growing global concern. They harm the individual patient, the healthcare system and the economy. The World Health Organisation (WHO) has highlighted contributing factors globally: insufficient national medicine regulation, poor enforcement of existing legislation, weak stakeholder collaboration and the rise of novel viruses, such as the COVID-19. The study aimed to assess the legislative and policy framework and institutional relationships governing pharmaceuticals and anti-counterfeiting strategies. Methods The study was explorative and consisted of two phases. The first phase was between 2016 and 2017. It looked at document analysis (annual reports and press releases from 2011 to 2016) from government institutions involved in medicines regulation and law enforcement for SF seizure reports between 2004 and 2017. The second phase was between 2016 and 2018 through in-depth semi-structured interviews (seven in total) with selected stakeholders. Results First Phase—the data collected and reported by various departments was sporadic and did not always correlate for the same periods indicating, a lack of a central reporting system and stakeholder collaboration. In South Africa, counterfeiting of medicines mainly involves the smuggling of non-registered goods. The most common counterfeit items were painkillers, herbal teas, herbal ointments, while some were medical devices. Furthermore, Customs identified South Africa as a transhipment point for SF infiltration to neighbouring countries with less robust regulatory systems. Second phase—interview transcripts were analysed by thematic coding. These were identified as the adequacy of legislation, institutional capacity, enforcement and post-market surveillance, stakeholder collaboration and information sharing, and public education and awareness. Conclusion Document analysis and interviews indicate that South Africa already has a national drug policy and legislative framework consistent with international law. However, there is no specific pharmaceutical legislation addressing the counterfeiting of medicines. Law enforcement has also been complicated by poor stakeholder engagement and information sharing.
Background: Campylobacter spp. are one of the most frequent causes of diarrhoeal disease in humans throughout the world. This study aimed at determining the prevalence and the genotypic distribution of Campylobacter spp. and their association with diarrhoea and child growth in children of less than the age of two in the Limpopo Province of South Africa. Methods: A total of 4280 diarrheal and non-diarrheal stool samples were collected on a monthly basis from children recruited at birth and followed up to 24 months. All stool samples were screened for the presence Campylobacter antigen using ELISA technique after which CAH 16S primer was used on the positive samples to confirm the presence of Campylobacter. Subsequently, the PCR positive samples were further characterised using species specific primers for Campylobacter jejuni and Campylobacter coli. Results: Campylobacter antigen was detected in 564/4280 (13.2%). Campylobacter was more commonly found in diarrheal stools (20.4%) compared to non-diarrheal stools (12.4%) with a statistically significant difference (χ2 = 7.345; p = 0.006). Throughout the year there were two main peaks of Campylobacter infection one in December- January and the second peak in June. The prevalence of Campylobacter increased with the age of the children up to 11 months after which the prevalence decreased. Out of 564 positive ELISA samples, 257 (45.6%) were confirmed to have 16S rRNA gene for Campylobacter spp. Furthermore, C. jejuni was found to be more prevalent (232/257) than C. coli (25/257) with a prevalence of 90.3% and 9.7%, respectively. Both C. jejuni and C. coli were significantly associated with diarrhea with statistical values of (χ2 = 22.224; p < 0.001) and (χ2 = 81.682; p < 0.001) respectively. Sequences generated from the analysis of hip gene confirmed the PCR positives samples were C. jejuni positive. Conclusions: This study has delineated a high prevalence of Campylobacter spp. in the study cohort. Moreover, C. jejuni was found to be more prevalent than C. coli both of which were associated with diarrhea. These findings are of clinical and epidemiological significance.
Carbon sequestration in unmineable coal seams has been proposed as one of the most attractive technologies to mitigate carbon dioxide (CO 2 ) emissions in which CO 2 is stored in the microporous structure of the coal matrix in an adsorbed state. The CO 2 adsorption process is hence considered one of the more effective methodologies in environmental sciences. Thus, adsorption isotherm measurements and modelling are key important scientific measures required in understanding the adsorption system, mechanism, and process optimization in coalbeds. In this paper, three renowned and reliable adsorption isotherm models were employed including Langmuir, Freundlich, and Temkin for pure CO 2 adsorption data, and the extended-Langmuir model for multicomponent, such as flue gas mixture-adsorption data as investigated in this research work. Also, significant thermodynamics properties including the standard enthalpy change ( $$\Delta H^\circ$$ Δ H ∘ ), entropy change ( $$\Delta S^\circ$$ Δ S ∘ ), and Gibbs free energy ( $$\Delta G^\circ$$ Δ G ∘ ) were assessed using the van’t Hoff equation. The statistical evaluation of the goodness-of-fit was done using three (3) statistical data analysis methods including correlation coefficient ( R ² ), standard deviation ( σ ), and standard error (SE). The Langmuir isotherm model accurately represent the pure CO 2 adsorption on the coals than Freundlich and Temkin. The extended Langmuir gives best experimental data fit for the flue gas. The thermodynamic evaluations revealed that CO 2 adsorption on the South African coals is feasible, spontaneous, and exothermic; and the adsorption mechanism is a combined physical and chemical interaction between the adsorbate and the adsorbent.
The reliance on energy to power vehicles in the transport sector is solely fossil-based fuels. These are the dominant source of greenhouse gas emissions (GHGs) posing huge threats to climate change and increasing global warming. To detect the driving forces responsible for GHG emissions in realising its intensity target, the paper examines the national population, economic growth, energy intensity, urbanisation, infrastructural investments, fuel consumption, freight turnover and passenger vehicles on energy related GHGs emissions in the South Africa’s transport sector from 2011 to 2020 by applying an extended Stochastic Impact by Regression on Population, Affluence and Technology (STIRPAT) and nonparametric additive regression to assess the main driving forces. The empirical results revealed that increase in population, economic growth, energy intensity, passenger vehicles and freight transport are more liable to cause an increase in GHG emissions. From the estimated elastic coefficient, the study shows that population and economic growth are the most influencing factors to GHGs emitted. Others are also significant but more often dependent on the increasing population and the nation’s economic growth. Hence, for policy recommendations in mitigating GHG emissions the dynamic effects of the influencing factors at varying provinces and periods should be of consideration in mitigating GHG emissions in the transportation sector of South Africa.
Deterioration of materials when in contact with their environment is a global challenge. Developing an environmentally friendly process for protecting metallic substrates is a field of growing research due to the ban against toxic materials already in use. Among the various means employed in combating corrosion, one of the most accessible and practical methods is using a corrosion inhibitor. The corrosion inhibitor forms a film on the surface of the metal, creating a thin layer adsorbed on the metal surface that blocks the metal and its environment, thus preventing corrosion. Natural compounds have been tested to replace toxic organic and inorganic corrosion inhibitor. Interests in them stem from their eco-friendliness, accessibility, and cost-efficiency. In recent years, Nanoparticles as corrosion inhibitors have attracted much attention considering their various range of industrial applications and economic benefits. The control of the metallic rate of corrosion via nanomaterials emphasizes discoveries in the nanotechnology field. Different researchers have effectively assessed nanomaterials’ application as inhibitors of corrosion. In the present review, the application of Nanoparticles for different industrial metal corrosion protection is investigated according to the experimental data reported and their inhibition technique. More also, various drawbacks, further trends and improvements in this area were also highlighted.
Biocomposite films (derived from polysaccharides, proteins, gums and microbial origin) have poor physical and mechanical properties. The nonbiodegradable synthetic polymers have good film characteristics, but it has unavoidable environmental concerns. In order to meet the food packaging demand and the environmental concerns associated with commercial packaging, biopolymer matrix with nanoclay reinforcements could be used as an alternative solution. Nanoclays, as filler materials in biopolymer matrix, helps to improve functional characteristics, such as: mechanical strength, optical, thermal, rheological, gas and water vapor barrier properties of biocomposite films. Nanoclays are administered as filler materials because of their high aspect ratio in the individual layers and specific chemical properties. However, uniform and complete dispersion of filler materials in the biopolymer matrix is necessary for a well-ordered morphology and structure of films. Nanoclays are capable of creating better reinforcement with greater impact on the tensile strength and gas barrier properties of food packaging films. This review aims to focus on the importance of nanoclay fillers in influencing the characteristic parameters of biocomposite materials. Although nanoclays are conveniently used, the toxicity profiles of nanoclays are least known. We have also discussed the toxicity and migration of nanoclays in food stimulants thereby, resolving the utility and safety of nanoclays on food packaging materials.
Polycyclic aromatic hydrocarbons (PAHs) are a known class of persistent and ubiquitous contaminants not only found in sediments but also associated with coastal areas and waters of urbanized estuaries. Due to their hydrophobic nature, PAHs tend to accumulate in the aquatic sediments, leading to bioaccumulation and elevated concentrations over time which is of global concern owing to the serious health risks that they pose to both humans and aquatic life. However, this review highlights various polymeric nanocomposite materials (PNMs) used for the photocatalytic degradation and mechanism of PAHs in aquatic sediments and associated water bodies. It presents the current progress made in the understanding of the toxicological effects of PAHs and mechanisms of their detoxification using photocatalytic processes as an alternative green method for environmental pollution, remediation and control. The paper also provides a brief account of the chemistry, origin and photocatalytic transformation of PAHs, highlighting their bioaccumulation in aquatic sediments and marine environments. It finally accentuates the significance of PNMs as a plausible candidate for the effective treatment of PAHs-contaminated aquatic environments. The available literature reveals that a small number of PNMs has been used to photodegrade PAHs in industrial effluents, seawater, aqueous solution and synthetic wastewater samples. Anthracene, phenanthrene, 2-naphthol and naphthalene as low molecular weight -PAHs were photodegraded using these PNMs under natural light. The findings also show that only chitosan- and graphene oxide-based PNMs have been employed to photodegrade these kinds of PAHs in water matrices. Most of the PNMs found in the literature were based on the iron oxide or magnetite incorporation which generates reactive oxygen species via AOPs. Another finding was no study was conducted on the photodegradation of PAHs in soil and sediments which are their main sink in the environment.
Ni-Cr-ZrO 2 composites with varying amounts of ZrO 2 additive (5 wt%, 7.5 wt%, 10 wt% and 12.5 wt%) were fabricated using spark plasma sintering method at a sintering temperature of 1000°C, heating rate of 100°C/min, holding time of 5 min, and a pressure of 50 MPa. The effect of ZrO 2 addition on the microstructure, tribological and mechanical properties of the developed composites were studied. The results showed that maximum densification was attained at 10 wt% ZrO 2 . Further increase in the fractions of ZrO 2 within the composites results in a decrease in the relative density of the sintered composite. A significant increase in hardness from 433.24 HV to 510.11 HV and elastic modulus from 252.67 GPa to 294.6 GPa was observed in the fabricated samples as the ZrO 2 content increase from 5 to 12.5 wt%. An appreciable improvement in the wear performance of the sintered samples was obtained with increasing ZrO 2 content. The observed improvement in the properties of the sintered composites was attributed to the presence of the hard dispersoids of ZrO 2 and formation of solid solution strengthening and hard Cr 3 Ni 2 phases within the matrix of the sintered composites.
Pollution has continued to be the source of elevated nutrient levels in catchment areas, causing eutrophic conditions that threaten human health. Adsorption has been seen as a cost-effective and simple process of removing and recovering nutrients from wastewater. Biomass feedstocks have received significant research interest in recent years on the production of biochar and its magnetized variants for wastewater treatment. However, there have been minimal studies on the use of paper waste sludge obtained from the recycling industry as a feedstock for biochar production used in wastewater treatment. Hence this study focused on the production of magnetic biochar composites as an adsorbent for nutrient removal and recovery from wastewater. Neat non-demineralized biochar and its magnetized variant were produced using paper waste sludge through co-pyrolysis at 450 °C and for the magnetized variant, the feedstock was synthesized using Fe3+ and Fe2+ salts. The biochar produced exhibited good structural and chemical properties suitable for adsorption. Hence further analysis was performed using MBC-SPS-450 for the removal of phosphorus (P), selenate (Se), and methylene blue (MB) from wastewater. The observed efficiencies for P, Se, and MB were 48.83, 58.43, and 5.92 mg g−1 respectively. From the results obtained, the magnetized variant (MBC-SPS-450) displayed excellent adsorption efficiencies, lower loading requirements with an optimum loading of 5g L−1, easy removal from solution by magnets, and was regenerated with excellent adsorption efficiencies. These excellent results position paper waste sludge-derived biochar as a good and low-cost adsorbent for the removal and recovery of nutrients from wastewater with the added benefit that it is part of the recycling process.
Active power and frequency control reflecting the stability of network operation is referred to as load frequency control (LFC). The area control error (ACE) is a combinatorial model between the tie-line in the interconnected system and its frequency deviations. The ACE is forced to be close to zero to achieve generation and load balance in network control and network balancing. The present research proposes introducing an energy storage system (ESS) in the control loop to regulate the frequency when the network is under an unstable condition or where the average frequency between the different areas connected is different to zero. The proposed method is developed to coordinate the different modes (charging and discharging) of the storage system. The storage parameters are unknown constants and are calculated online with a modified heuristic and directional derivative objective. The system consists of two tie-lines connected between the two areas, and each one is made up of a synchronous generator, renewable energy sources, ESS and load. The optimal frequency deviation in the areas and tie problem was modelled into a control problem and solved using the MPC. The dynamic model of ESS was modelled as a control bahaviour to inject energy at any time of the control horizon to balance the electrical network. Modified control of the ESS by a new approach used to estimate uncertainties parameters of the interconnected system. The effectiveness of the frequency control strategies is measured through simulation assessment.
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Mulatu Fekadu Zerihun
  • Department of Economics
Rasigan Maharajh
  • Institute for Economic Research on Innovation (IERI)
Mario Scerri
  • Institute for Economic Research on Innovation (IERI)
Yskandar Hamam
  • Department of Electrical Engineering
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