Faculty of Science (ETDs)

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    Digital toolbox for the generation and detection of vectorial structured light
    (University of the Witwatersrand, Johannesburg, 2023-06) Singh, Keshaan; Dudley, Angela; Forbes, Andrew
    Light has been an invaluable tool in the development of the modern world, with the myriad of applications increasing along with our degree of control over it. From the development of coherent light sources, to the shaping of amplitude and phase, this development has not ceased for the past half century. The field of structured light, borne out of the necessity and desire for control over light, has been growing steadily in recent years. In the spatial domain, the control over light’s polarization (i.e., the local planes in which the electric and magnetic fields oscillate) has been the most recent avenue of improvement, providing enhancements to a variety of applications ranging form microscopy and communication to materials processing and metrology. This class of light, commonly referred to as vectorial light, often requires specialised equipment in order for its its creation before its numerous benefits can be exploited. These tools often incur high costs and suffer from limitations relating to the diversity of vectorial light they can create, wavelength dependence and slow refresh rates. This thesis follows the development of a series of digital tools for the versatile generation and analysis of vectorial light using low-cost core technologies which can operate at high rates over a broad wavelength range. We follow the development of the generation tool in the context of its application in generating novel accelerating polarization structures, emulating vectorially apertured optics, generating probes to measure birefringence and chirality and creating synthetic spin dynamics. The development of the analysis tool is explored by investigating its application in performing automated digital Stokes polarimetry measurements, completely characterizing the internal degrees of freedom of arbitrary vectorial light and acting as a polarization and wavelength independent wavefront sensor. We then demonstrate how these tools can be used, in conjunction, to investigate the fundamental invariance of vectorial light to perturbing channels and how this invariance can be exploited in a highly robust novel communication scheme. In addition to demonstrating the applicability and versatility of these vectorial light tools, the applications offered a means to highlight areas for the optimization for the design. This culminated in the ongoing prototyping of versatile, fast, broadband devices which operate stably and have a small physical footprint.
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    3D Human pose estimation using geometric self-supervision with temporal methods
    (University of the Witwatersrand, Johannesburg, 2024-09) Bau, Nandi; Klein, Richard
    This dissertation explores the enhancement of 3D human pose estimation (HPE) through self-supervised learning methods that reduce reliance on heavily annotated datasets. Recognising the limitations of data acquired in controlled lab settings, the research investigates the potential of geometric self-supervision combined with temporal information to improve model performance in real-world scenarios. A Temporal Dilated Convolutional Network (TDCN) model, employing Kalman filter post-processing, is proposed and evaluated on both ground-truth and in-the-wild data from the Human3.6M dataset. The results demonstrate a competitive Mean Per Joint Position Error (MPJPE) of 62.09mm on unseen data, indicating a promising direction for self-supervised learning in 3D HPE and suggesting a viable pathway towards reducing the gap with fully supervised methods. This study underscores the value of self-supervised temporal dynamics in advancing pose estimation techniques, potentially making them more accessible and broadly applicable in real-world applications.
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    Creating an adaptive collaborative playstyle-aware companion agent
    (University of the Witwatersrand, Johannesburg, 2023-09) Arendse, Lindsay John; Rosman, Benjamin
    Companion characters in video games play a unique part in enriching player experience. Companion agents support the player as an ally or sidekick and would typically help the player by providing hints, resources, or even fight along-side the human player. Players often adopt a certain approach or strategy, referred to as a playstyle, whilst playing video games. Players do not only approach challenges in games differently, but also play games differently based on what they find rewarding. Companion agent characters thus have an important role to play by assisting the player in a way which aligns with their playstyle. Existing companion agent approaches fall short and adversely affect the collaborative experience when the companion agent is not able to assist the human player in a manner consistent with their playstyle. Furthermore, if the companion agent cannot assist in real time, player engagement levels are lowered since the player will need to wait for the agent to compute its action - leading to a frustrating player experience. We therefore present a framework for creating companion agents that are adaptive such that they respond in real time with actions that align with the player’s playstyle. Companion agents able to do so are what we refer to as playstyle-aware. Creating a playstyle-aware adaptive agent firstly requires a mechanism for correctly classifying or identifying the player style, before attempting to assist the player with a given task. We present a method which can enable the real time in-game playstyle classification of players. We contribute a hybrid probabilistic supervised learning framework, using Bayesian Inference informed by a K-Nearest Neighbours based likelihood, that is able to classify players in real time at every step within a given game level using only the latest player action or state observation. We empirically evaluate our hybrid classifier against existing work using MiniDungeons, a common benchmark game domain. We further evaluate our approach using real player data from the game Super Mario Bros. We out perform our comparative study and our results highlight the success of our framework in identifying playstyles in a complex human player setting. The second problem we explore is the problem of assisting the identified playstyle with a suitable action. We formally define this as the ‘Learning to Assist’ problem, where given a set of companion agent policies, we aim to determine the policy which best complements the observed playstyle. An action is complementary such that it aligns with the goal of the playstyle. We extend MiniDungeons into a two-player game called Collaborative MiniDungeons which we use to evaluate our companion agent against several comparative baselines. The results from this experiment highlights that companion agents which are able to adapt and assist different playstyles on average bring about a greater player experience when using a playstyle specific reward function as a proxy for what the players find rewarding. In this way we present an approach for creating adaptive companion agents which are playstyle-aware and able to collaborate with players in real time.
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    Procedural Content Generation for video game levels with human advice
    (University of the Witwatersrand, Johannesburg, 2023-07) Raal, Nicholas Oliver; James, Steven
    Video gaming is an extremely popular form of entertainment around the world and new video game releases are constantly being showcased. One issue with the video gaming industry is that game developers require a large amount of time to develop new content. A research field that can help with this is procedural content generation (PCG) which allows for an infinite number of video game levels to be generated based on the parameters provided. Many of the methods found in literature can generate content reliably that adhere to quantifiable characteristics such as playability, solvability and difficulty. These methods do not however, take into account the aesthetics of the level which is the parameter that makes them more reasonable levels for human players. In order to address this issue, we propose a method of incorporating high level human advice into the PCG loop. The method uses pairwise comparisons as a way in which a score can be assigned to a level based on its aesthetics. Using the score along with a feature vector describing each level, an SVR model is trained that will allow for a score to be assigned to unseen video game levels. This predicted score is used as an additional fitness function of a multi objective genetic algorithm (GA) and can be optimised as a standard fitness function would. We test the proposed method on two 2D platformer video games, Maze and Super Mario Bros (SMB), and our results show that the proposed method can successfully be used to generate levels with a bias towards the human preferred aesthetical features, whilst still adhering to standard video game characteristics such as solvability. We further investigate incorporating multiple inputs from a human at different stages of the PCG life cycle and find that it does improve the proposed method, but further testing is still required. The findings of this research is hopefully going to assist in using PCG in the video game space to create levels that are more aesthetically pleasing to a human player.
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    Play-style Identification and Player Modelling for Generating Tailored Advice in Video Games
    (University of the Witwatersrand, Johannesburg, 2023-09) Ingram, Branden Corwin; Rosman, Benjamin; Van Alten, Clint; Klein, Richard
    Recent advances in fields such as machine learning have enabled the development of systems that are able to achieve super-human performance on a number of domains, specifically in complex games such as Go and StarCraft. Based on these successes, it is reasonable to ask if these learned behaviours could be utilised to improve the performance of humans on the same tasks. However, the types of models used in these systems are typically not easily interpretable, and can not be directly used to improve the performance of a human. Additionally, humans tend to develop stylistic traits based on preference which aid in solving problems or competing at high levels. This thesis looks to address these difficulties by developing an end-to-end pipeline that can provide beneficial advice tailored to a player’s style in a video game setting. Towards this end, we demonstrate the ability to firstly cluster variable length multi-dimensional gameplay trajectories with respect to play-style in an unsupervised fashion. Secondly, we demonstrate the ability to learn to model an individual player’s actions during gameplay. Thirdly we demonstrate the ability to learn policies representative of all the play-styles identified with an environment. Finally, we demonstrate how the utilisation of these components can generate advice which is tailored to the individual’s style. This system would be particularly useful for improving tutorial systems that quickly become redundant lacking any personalisation. Additionally, this pipeline serves as a way for developers to garner insights on their player base which can be utilised for more informed decision-making on future feature releases and updates. For players, they gain a useful tool which can be utilised to learn how to play better as well identify as the characteristics of their gameplay as well as opponents. Furthermore, we contend that our approach has the potential to be employed in a broad range of learning domains.
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    Hunting dark matter with faint radio halos
    (University of the Witwatersrand, Johannesburg, 2023-10) Sarkis, Michael David; Beck, Geoff
    The nature of Dark Matter (DM), the elusive substance that constitutes a significant amount of the total matter in the universe, remains an unsolved problem in modern physics despite a decades-long search effort. One approach to this problem has been to search for faint emission signatures that are produced indirectly from the DM present in large astrophysical structures, and thus infer properties about theoretical DM models from observational data. In recent years, the results from studies that use this type of indirect search have produced stringent constraints on the most popular DM particle candidate parameter spaces, ruling out swathes of viable DM models. These compelling results have been enabled by the arrival of sophisticated interferometric radio telescopes, which are excellent DM hunters due to their high sensitivity and resolution. In this thesis, we focus on the use of the latest data from the MeerKAT radio interferometry telescope, through the first public release of the MeerKAT Galaxy Cluster Legacy Survey, to search for DM emissions in a set of nearby galaxy clusters. Each step of this process, from the creation of theoretical DM emission models to the statistical analysis of the observational data, has been described in detail in this thesis. With this data, we find an almost universal improvement to results found with corresponding modelling scenarios in the literature. Since this work is among the first to use MeerKAT data in astrophysical DM searches, these results present a strong argument for continued work in this field. Another central focus of this thesis is the accurate modelling of the physical processes involved in the production of the DM-induced radio emissions, as the quality of current radio data requires theoretical models that are sufficiently accurate to describe the emission at such high resolutions. One aspect of the modelling that has lacked this accuracy has been the solution to the diffusion-loss equation, which is a crucial factor in determining indirect DM emissions. A new algorithm for solving this equation, which provides higher accuracy and computational efficiency than previous public methods, has thus been developed and presented in this thesis. These aspects of DM indirect detection study will become ever more important as we approach the inauguration of the Square Kilometre Array (SKA), which will provide data with unprecedented potential with which to continue the hunt for DM.
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    Implementation of the DAQ software for the ALTI module in the ATLAS TileCal and the search for new physics in the four lepton final state
    (University of the Witwatersrand, Johannesburg, 2023-06) Tlou, Humphry Sijiye; Wilkens, Henric; Ruan, Xifeng; Mellado, Bruce
    The discovery of the Standard Model (SM) Higgs boson in 2012 presents new challenges and opportunities for the Large Hadron Collider (LHC) experiments. After a long period of operation, the LHC experiments needed to maintain and upgrade their detectors in order to continue and conduct research beyond the SM. As part of the upgrades, the Tile Calorimeter (TileCal) participated in Phase-I of the upgrades (December 2018 - March 2022). TileCal, the central hadronic calorimeter (|η| < 1.7) of the ATLAS experiment uses a set of Trigger and Data Acquisition (TDAQ) software to readout, transport and store physics data resulting from collisions at the LHC. In preparation for the Phase-I upgrades, the ATLAS Local Trigger Interface (ALTI) module was designed for the ATLAS experiment at CERN for TDAQ purposes. It is a 6U VME electronics board, which is a part of the Timing, Trigger and Control (TTC) system. It integrates the functionalities of four legacy modules, currently used in the experiment: Local Trigger Processor, Local Trigger Processor interface, TTC VME bus interface and the TTC emitter. The ALTI module provides the interface between the Level-1 Central Trigger Processor and the TTC optical broadcasting network to the front-end electronics of each of the ATLAS sub-detectors. This thesis discusses the development, validation and integration of the TileCal specific ALTI software in the TileCal online software by the author. A set of ALTI boards were installed in the back-end electronics of the sub-detector and fully validated for the ATLAS detector at CERN. Performance testing and maintenance of the ALTI modules and software were performed during the second half of the upgrade period, in preparation for Run 3 (2022–2025) data-taking period. The thesis also discusses the search for the presence of a new heavy resonance produced via gluon-gluon fusion and decaying to the four-lepton (4ℓ) final state, in association with missing transverse energy (EmissT), with ℓ = e, µ (where ℓ is the lepton, e is the electron and µ is the muon). The search uses 2015–2018 proton-proton collision data at √s = 13 TeV, corresponding to an integrated luminosity of 139 fb−1, collected by the ATLAS detector. The data are interpreted in terms of two models, firstly the R → SH → 4ℓ + EmissT , where R is a scalar boson, which decays to two lighter scalar bosons (S and H). The S decays to a pair of neutrinos and the H decays into 4ℓ, through ZZ bosons. The second model is the A → Z(νν)H(ZZ) → 4ℓ + X, where A is considered to be a CP-odd scalar which decays to a CP-even scalar H and the Z boson. The Z boson decays to X, which can be a pair of neutrinos or jets, and the H decays to the 4ℓ final state.
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    Dissolution of non-functionalized and functionalized nanomaterials in simulated biological and environmental fluids
    (University of the Witwatersrand, Johannesburg, 2023-06) Mbanga, Odwa; Gulumian, Mary; Cukrowska, Ewa
    The incorporation of nanoparticles in consumer products is exponentially high, however, research into their behaviour in biological and environmental surroundings is still very limited. In the present study, the static system and the continuous flow-through dissolution protocols were utilized to evaluate and elucidate the dissolution behaviour of gold, silver, and titanium dioxide nanoparticles. The behaviour of these particles was studied in a range of artificial physiological fluids and environmental media, to obtain a more precise comprehension of how they would react in the human body and the environment. The biodurability and persistence were estimated by calculating the dissolution kinetics of the nanoparticles in artificial physiological fluids and environmental media. The details of the current research are described as follows: An investigation into the dissolution of non-functionalized and functionalized gold nanoparticles was conducted as the first component of the research, examining the effect of surface functionalization on dissolution. The study determined the dissolution rates of functionalized and non-functionalized gold nanoparticles. Dissolution was observed to be significantly higher in acidic media than in alkaline media. The nanoparticle surface modification, particle aggregation, and chemical composition of the simulated fluid significantly affected the dissolution rate. It was concluded that gold nanoparticles are biodurable and have the potential to cause long-term health effect as well as high environmental persistency. This work has been published in the Journal of Nanoparticle Research and is presented in this thesis as Paper 1. Silver nanoparticles were also included in this study because they have many applications and industrial purposes. Therefore, their risk assessment was also of utmost importance. The results indicated that silver nanoparticle solubility was influenced by the alkalinity and acidity of artificial media. Low pH values and high ionic strength encouraged silver nanoparticle dissolution and accelerated the dissolution rate. The agglomeration state and reactivity of the particles changed upon exposure to simulated fluids, though their shape remained the same. The fast dissolution rates in most fluids indicated that the release of silver ions would cause short-term effects. This work has been published in Toxicology Reports and has been presented in this thesis as Paper 2. Although titanium dioxide nanoparticles are insoluble and undergo negligible dissolution, it was of utmost importance to investigate their behaviour in biological and environmental surroundings. This is as a result of the incorporation of these particles in everyday consumer products, in the nanosized range which raises concerns about their safety. Therefore, in Paper 3 presented in this thesis the dissolution kinetics of titanium dioxide nanoparticles in simulated body fluids representative of the lungs, stomach, blood plasma and media representing the aquatic ecosystem were investigated to anticipate how they behave in vivo. This work has been published in Toxicology In Vitro and presented in this thesis as Paper 3. The results indicated that titanium dioxide nanoparticles were very insoluble, and their dissolution was limited in all simulated fluids. Acidic media such as the synthetic stomach fluids were most successful in dissolving the particles, while alkaline media had lower dissolution. High ionic strength seawater also had a higher dissolution rate than freshwater. The dissolution rates of the particles were low, and their half-times were long. The results indicated that these particles could potentially cause health issues in the long term, as well as remain unchanged in the environment. This work has been published in Toxicology In Vitro and presented in this thesis as Paper 3. The last component of the research compared the dissolution kinetics of gold, silver and titanium dioxide nanoparticles through the use of the continuous flow-through system. The findings indicated that titanium dioxide nanoparticles were the most biodurable and persistent, followed by gold and silver nanoparticles. Therefore, it was suggested that product developers should use the OECD's guidelines for testing before releasing their product to the market to ensure its safety. This work has been published in Nanomaterials MDPI and presented in this thesis as Paper 4.
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    Study on the influence of Nuclear Deformation on the Pygmy Dipole Resonance in Samarium isotopes
    (University of the Witwatersrand, Johannesburg, 2023) Jivan, Harshna; Sideras-Haddad, Elias; Pellegri, Luna
    The past decade has seen an increase in studies dedicated to understanding the low-lying electric dipole (E1) response, commonly referred to as the Pygmy Dipole Resonance (PDR). These studies revealed that the PDR has a mixed isospin nature, and that the use of complimentary probes is needed to fully understand this response. Since majority of studies on the PDR focused on spherical nuclei, the influence that deformation has on the PDR response is yet to be understood. Preliminary relativistic proton scattering studies on 154Sm performed at RCNP (Japan), showed potential evidence for a splitting in the PDR responses similar to that of the Giant Dipole Resonance with deformation. A tentative interpretation suggested that this splitting could be connected to the splitting of the resonance structure with respect to the K quantum number. Theoretical studies considering the deformed HFB+QRPA model however, suggest that this splitting is connected to the isospin mixed character of these states as observed in spherical nuclei. The isoscalar responses of the spherical 144Sm and axially deformed 154Sm isotopes were investigated for the first time using the inelastic scattering of alpha particles at 120 MeV. The comparative experiments were performed at iThemba LABS in South Africa, coupling together for the first time, the K600 magnetic spectrometer in zero-degree mode with the BaGeL (Ball of Germanium and LaBr3:Ce detectors) array. The particle-gamma coincidence measurement was used to obtain the cross section for the population of the pygmy states. In both nuclei, the region of the PDR was excited and the E1 multipolarity of the transitions was supported by the angular correlation between the α-particles and the co-incident γ-rays measured. The total exclusive cross section measured for 144Sm amounted to 24.3 ± 3.8 mb/sr while for 154Sm to 18.8 ± 2mb/sr. The experimental results were compared with the prediction of the RQTBA and the deformed HFB+QRPA theories, respectively. The theoretical cross sections were extracted within a semiclassical coupled-channel approach. The fragmentation observed in the experiment for the 144Sm was underestimated by the calculations, although good agreement with the total cross section measured was found. In the case of the deformed 154Sm however, the experimental cross section accounted for only 52% of the predicted cross section in the same excitation region. The isoscalar response extracted in this thesis was compared with the isovector strength obtain from an experiment performed at RCNP using the relativistic proton scattering at forward angles. The double hump observed in the isovector channel was not found in the case of the isoscalar strength. This implies that the difference obtained between these two experiments is related to the “isospin splitting” of the PDR rather than a splitting of thestrength connected with the K quantum number.
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    Properties of composite nanomaterials for gas sensor applications
    (University of the Witwatersrand, Johannesburg, 2023-09) Diantantu, Aime Diakanwa; Usman, Ibrahim
    Sensors are- important devices nowadays that have been instrumental towards the development of the Internet of Things (IoT) amongst other recent technological innovations. They are used to detect and respond to some form of input or stimulus from the environment we are living in. There are different types of sensors in the market nowadays, depending on the materials used for their manufacture and their applications, namely position sensors, pressure sensors, gas sensors, etc. Gas sensors use semiconductors as materials. Metal oxides, conducting polymers, carbon nanotubes, graphene, and transition metal chalcogenides are some semiconductors materials used in gas sensors. Metal oxides are very good gas sensors materials due to their low cost, high stability, and sensitivity but their high operating temperature disqualify them. Conducting polymers are also good sensors materials due to their flexibility and low operating temperature but they are altered by humidity. To counteract humidity problem, conducting polymers need to be modified or doped with selected elements or molecules. In this project, cellulose was drugged with carbon nanotube (CNT) to create a mechanically and chemically stable structure, which can interact and sense many gases. The chemical and physical properties of cellulose make it a potential material for the development of conductive and potential sensing stuff. This led to the focus of this investigation, which is the development of mixed cellulose nanocrystal (CNC) – CNT materials for sensor application. The CNC was synthesized through the Tempo oxidation method, and various amounts of CNT were added into the CNC below the aggregation threshold of 2.5% using ultrasonication to form a CNC – CNT rectangular sheet. The developed mixed materials were characterized using Scanning Electron Microscopes (SEM) and Transmission Electron Microscope (TEM) to determine the morphology. Fourier Transform Infrared (FTIR), Raman Spectroscopy and X-ray Diffraction (XRD) were employed to investigate the structure of the final material, while TGA has shown similar degradation temperatures of CNC and CNC – CNT. SEM images showed an interconnected network-like structure with a porous architecture assembled by curved thin sheets, and the increase in CNT resulted in aggregate formation within the CNC. TEM micrographs confirmed the structure of CNC, which was rod-like and artefactual dendrites particles, and the presence of CNT in the matrix, while FTIR confirmed the main functional groups of the mixed matrix sheet. The degree of graphitization and presence of disordered cellulose in the mixed materials were determined by Raman spectroscopy to vary between 0.98 and 1.2. The XRD pattern has shown that the crystallinity index of the CNC – CNT composite is correlated to the increase in the concentration of CNT. However, the TGA data has shown that the CNC – CNT materials exhibited similar thermal behaviour, this is expected, since the concentrations of the composites have similar bonding structure and configuration compared to the pristine CNC. It is also evident that the increase in CNT content reduces the thermal degradation (reduced slope) of the CNC. The research work has developed CNC – CNT materials for sensor applications. The composite has exhibited sensor response and thereby detected H2, CO2, NO2 and Ar gases at room temperature through the changes in their electrical conductivities. The ability of CNC-CNT to respond to these gases at room temperature opens-up the possibility for its easy use in indoor and outdoor monitoring.