Nonlinear adaptation of established linear and predictive control laws through safe reinforcement learning by Bras, Edward Hendrik

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A Machine Learning Framework for Predicting Fabrication Hours for Industrial Steel Structure Projects by Ibrahim, Dalia

“…The objectives were achieved by employing combinations of six machine learning models and various pre-processing techniques to find the model that best enhances the estimates of the fabrication hours of the collaborating company. …”
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Development of scalable hybrid switching-based software-defined networking using reinforcement learning by Blose, Max

“…To address the SDN scalability issues identified by creating a scalable hybrid switching solution using machine learning algorithms. We propose an SDN OpenFlow model switch which collaborate with the traditional switch to represent a scalable framework of Hybrid Routing with Reinforcement Learning (sHRRL). …”
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Development of scalable hybrid switching-based software-defined networking using reinforcement learning by Blose, Max

“…To address the SDN scalability issues identified by creating a scalable hybrid switching solution using machine learning algorithms. We propose an SDN OpenFlow model switch which collaborate with the traditional switch to represent a scalable framework of Hybrid Routing with Reinforcement Learning (sHRRL). …”
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Investigating the Relationship between Learning Styles and Delivery Methods in Information Security Awareness Programs by Ntwali, Blaise

“…Additionally, the aligned learning styles and delivery methods' construct was added to the KAB model to investigate the research questions. …”
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Machine Learning techniques to discover and understand the population of flare stars in MeerLICHT data by Bangiso, Aphiwe

“…In this work, we develop generic machine learning models that classify a given transient object from the observed light curve. …”
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Cape Town Airbnb price prediction: an exploration of spatial statistic and machine learning methods by Williams, Courtney

“…By accounting for spatial effects, model predictive performance does improve, but not so much as to outperform non-spatial, non-linear machine learning model predictions. …”
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Modelling uncertainty of cost and time in infrastructure projects by Moghayedi, Alireza

“…The developed hybrid tool models the main structures from the activity level to the entire highway project. …”
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Creating the conditions for entrepreneurial learning within an inclusive and scalable African business education ecosystem by Hosken, Christopher

“…Online and virtual education technologies, pedagogies and methodologies are explored as the core proponents of these learning experiences. Different models are explored and analysed in their distinct contexts to discover what it takes to create these learning experiences. …”
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Deep Reinforcement Learning-Based Approaches for the MPPT Control of Standalone Solar PV Systems by Nwachukwu, Sampson

“…Reinforcement learning (RL) is a model-free optimization approach that can learn solar PV behaviour and store and reuse optimization information for future optimization tasks. …”
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Initial attempt: classification of Simmental cattle based on body conformation using machine learning by Schulenburg, Suzette

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The lateral load carrying capacity of wall ties used in cavity wall construction in the Western Cape : a comparison between the Butterfly-type wire tie and the Crimped-type wire ti... by Ebrahim, I

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Evaluating the current copyright provisions for the reproduction and dissemination of electronic educational material in distance learning by Lamont, Kim Tracy

“…Some countries such as the Unites States have come to this realisation early and have started to accommodate digitisation of works and distance learning models through the Digital Millennium Copyright Act and the codification of the fair use model in section 107 of the United States Copyright Act.…”
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Reducing the Burden of Aerial Image Labelling Through Human-in-the-Loop Machine Learning Methods by Razzak, Muhammed T

“…We then investigate active learning in the context of remote sensing. Active learning looks at reducing the number of labelled samples required by a model to achieve an acceptable performance level. …”
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Exploring the relationship between the leadership role of the school principal and ICT integration in instruction and learning

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The architects Atelier : rethinking boukunde's interior spaces

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Discriminating between forest plantation genera using remote sensing and machine learning algorithms by Higgs, Caley

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How accurately do routinely reported HIV viral load suppression proportions reflect progress towards the 90-90-90 target in the population on ART in Khayelitsha, South Africa? by Euvrard, Jonathan George

“…Background: In 2016, Khayelitsha reported almost 89% viral load (VL) suppression but less than 56% completion on routine quarterly reports, casting doubt on the validity of reported suppression. …”
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