Research Articles (Electrical and Electronic Engineering)
Permanent URI for this collection
Browse
Recent Submissions
Now showing 1 - 5 of 79
- ItemTowards a cleaner production of an underutilised legume, bambara groundnut(IWACP, 2023-11) Mabitsela, Mosima Mamoyahabo; Hull, Keegan Jarryd; Mavengahama, Sydney; Phiri, Ethel E.; Booysen, M. J. (Thinus)ABSTRACT: Soilless cultivation systems such as aeroponics provide a more efficient, and clean food production of in areas where there is limited access to arable land for agricultural practices and drought-prone countries. The objective of this study was to evaluate the yield performance of seventy Bambara groundnut (BGN) landraces cultivated in aeroponics and compared with a traditional drip-irrigated hydroponic system with sawdust as a rowing medium. The result showed that BGN landraces cultivated in aeroponics accumulated a high number of seeds, as compared to those landraces cultivated in hydroponics. However, BGN landraces cultivated in hydroponics recorded a high shoot dry weight and one hundred seed weight. The root length that could only be measured in BGN landraces cultivated in the aeroponics systems, showed that BGN root length can extend beyond one meter. Soilless cultivation systems with their high-water use efficiency have the potential of reducing production costs, thus making them accessible to farmers in countries where drought is a reality.
- ItemSimulating the driving and charging of electric minibus taxis: a case study for Stellenbosch.(IWACP, 2023-11) Pretorius, Brendan; Strauss, Johannes M.; Booysen, M. J. (Thinus)ABSTRACT: The Global North is increasing the drive for the electrification of the mobility industry. In sub-Saharan Africa, however, the adoption is yet to pick up steam due to various other challenges in the region. The viability of converting the paratransit fleet (which consists mostly of minibus taxis) to electric vehicles (EVs) with current combustion-based operations is investigated by making use of simulation software, and EV-Fleet-Sim. This developed software simulates the driving and charging of operationally tracked taxis in the Stellenbosch area. A charging algorithm, as well as a simple battery model, was included in the simulation to provide a more accurate representation of the scenario. Most of the taxis were found to still complete their required trips with the specified battery size of 70 kWh. However, new methods would need to be found, such as including a mixed fleet with some petrol or diesel taxis, to assure a 100% trip completion rate. The grid impact per vehicle was found with an expected maximum load appearing between the hours of 08h00 and 10h00 of 22 kW per vehicle, which corresponds to the time after the morning peak traffic of getting people to work. Furthermore, a minimum number of chargers can be implemented which will not affect the trip completion rate of the taxis. This was found to be for 4 chargers per 17 taxis. Future work is left to the testing of various parameters to find optimal solutions as well as including home charging and failed trip classification.
- ItemMultilingual and Unsupervised Subword Modeling for Zero-Resource Languages(Elsevier Ltd, 2021-04) Hermann, Enno; Kamper, Herman; Goldwater, SharonSubword modeling for zero-resource languages aims to learn low-level representations of speech audio without using transcriptions or other resources from the target language (such as text corpora or pronunciation dictionaries). A good representation should capture phonetic content and abstract away from other types of variability, such as speaker differences and channel noise. Previous work in this area has primarily focused unsupervised learning from target language data only, and has been evaluated only intrinsically. Here we directly compare multiple methods, including some that use only target language speech data and some that use transcribed speech from other (non-target) languages, and we evaluate using two intrinsic measures as well as on a downstream unsupervised word segmentation and clustering task. We find that combining two existing target-language-only methods yields better features than either method alone. Nevertheless, even better results are obtained by extracting target language bottleneck features using a model trained on other languages. Cross-lingual training using just one other language is enough to provide this benefit, but multilingual training helps even more. In addition to these results, which hold across both intrinsic measures and the extrinsic task, we discuss the qualitative differences between the different types of learned features.
- ItemClassification learning of latent bruise damage to apples using shortwave infrared hyperspectral imaging(MDPI, 2021-07-22) Nturambirwe, Jean Frederic Isingizwe; Perold, Willem Jacobus; Opara, Umezuruike LinusBruise damage is a very commonly occurring defect in apple fruit which facilitates disease occurrence and spread, leads to fruit deterioration and can greatly contribute to postharvest loss. The detection of bruises at their earliest stage of development can be advantageous for screening purposes. An experiment to induce soft bruises in Golden Delicious apples was conducted by applying impact energy at different levels, which allowed to investigate the detectability of bruises at their latent stage. The existence of bruises that were rather invisible to the naked eye and to a digital camera was proven by reconstruction of hyperspectral images of bruised apples, based on effective wavelengths and data dimensionality reduced hyperspectrograms. Machine learning classifiers, namely ensemble subspace discriminant (ESD), k-nearest neighbors (KNN), support vector machine (SVM) and linear discriminant analysis (LDA) were used to build models for detecting bruises at their latent stage, to study the influence of time after bruise occurrence on detection performance and to model quantitative aspects of bruises (severity), spanning from latent to visible bruises. Over all classifiers, detection models had a higher performance than quantitative ones. Given its highest speed in prediction and high classification performance, SVM was rated most recommendable for detection tasks. However, ESD models had the highest classification accuracy in quantitative (>85%) models and were found to be relatively better suited for such a multiple category classification problem than the rest.
- ItemCanary in the coliform mine : exploring the industrial application limits of a microbial respiration alarm system(Public Library of Science, 2021-03-04) Stone, Wendy; Louw, Tobi M.; Booysen, Marthinus J.; Wolfaardt, Gideon M.; Zhang, DaweiFundamental ecological principles of ecosystem-level respiration are extensively applied in greenhouse gas and elemental cycle studies. A laboratory system termed CEMS (Carbon Dioxide Evolution Measurement System), developed to explore microbial biofilm growth and metabolic responses, was evaluated as an early-warning system for microbial disturbances in industrial settings: in (a) potable water system contamination, and (b) bioreactor inhibition. Respiration was detected as CO₂ production, rather than O₂ consumption, including aerobic and anaerobic metabolism. Design, thresholds, and benefits of the remote CO₂ monitoring technology were described. Headspace CO₂ correlated with contamination levels, as well as chemical (R² > 0.83–0.96) and microbiological water quality indicators (R² > 0.78–0.88). Detection thresholds were limiting factors in monitoring drinking water to national and inter- national standards (0 CFU/100 mL fecal coliforms) in both open- (>1500 CFU/mL) and closed-loop CO₂ measuring regimes (>100 CFU/100 mL). However, closed-loop detection thresholds allow for the detection of significant contamination events, and monitoring less stringent systems such as irrigation water (<100 CFU/mL). Whole-system respiration was effectively harnessed as an early-warning system in bioreactor performance monitoring. Models were used to deconvolute biological CO₂ fluctuations from chemical CO₂ dynamics, to optimize this real-time, sustainable, low-waste technology, facilitating timeous responses to biological disturbances in bioreactors.