Open Access Theses

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Open Access
Machine Learning Assisted Signal Enhancement
(2025) Yan, Longfei Felix
In an era of abundant signals, the ability to obtain desired signals while rejecting undesired ones has become increasingly crucial. Often, the desired signals are mixed with interference or contaminated by noise. Signal enhancement techniques play a vital role in performing tasks such as signal separation, extraction, and suppression. This thesis addresses critical challenges in signal enhancement tasks by harnessing the power of machine learning techniques. Firstly, we propose a novel independence criterion called the Finite Basis Independence Criterion (FBIC). This criterion estimates the Hirschfeld-Gebelein-Rényi maximum correlation coefficient between tested variables and is based on mapping functions from a subspace of finite basis. FBIC detects dependence between variables in linear time and outperforms more computationally expensive kernel-based counterparts. Extensive testing in Independent Component Analysis benchmarks demonstrates its potential for various signal separation applications. Secondly, we conduct a comprehensive robustness analysis of a popular signal enhancement approach: fixed beamforming based on first-order linear Differential Microphone Arrays (DMAs). We demonstrate that both bounded and unbounded phase errors of microphones can affect the mainlobe orientation of the beamformer. Analytically derived white noise gain thresholds indicate when mainlobe misorientation occurs. Through rigorous mathematical derivations, we prove that a higher number of microphones and increased spacing between microphones contribute to the robustness of the beamformer. This work provides practical guidelines for designing robust first-order linear DMAs. Thirdly, we propose a neural network model to optimize both the geometry and spatial filter of linear DMAs. The model consists of two feed forward neural networks and is trained end-to-end. The signals enhanced by this model exhibit superior quality compared to those obtained from conventional DMA approaches. Furthermore, the model offers flexibility in controlling the tradeoff between different performance metrics, allowing for customized optimization. Lastly, we extend the neural network model to a general framework that allows optimization of microphone arrays of any geometry, along with their spatial filters. This model employs ResNets and augmented Lagrangian techniques to achieve state-of-the-art frequency-invariant fixed beamforming performance. We showcase our performance in linear, circular, and concentric circular microphone arrays. Moreover, our findings challenge the conventional belief that concentric circular arrays require multiple rings, as we demonstrate that good performance can be achieved with only one ring. Overall, this thesis contributes novel techniques and insights to the field of signal enhancement, leveraging machine learning approaches to address key challenges. The proposed criteria, guidelines and models have the potential to advance various signal separation applications and enhance the overall quality of processed signals.
Open Access
Theorising the Dingo Howl: Jazz in Australian Film in the 1990s and Early 2000s
(2025) Tsuei, Jeremy
In discussing the films Dingo (1991), The Boys (1998), Come in Spinner (1990), and The Tracker (2002), I examine the meeting of jazz music as a “sonic indicator of authenticity” with the critical notion of settler-colonial Australia as an unreconciled, uncanny, and inauthentic space. These films tell uniquely Australian stories and diegetically or non-diegetically feature improvised music practices that fall under the category of jazz as a broad “coverall” term. In these films, the music unsettles us and portray an uneasy relationship between their Australian subjects and the Australian landscape. They are also unique films in how their music and musicians were respected and prioritised, sometimes with significant implications for how scenes were filmed and composed. I argue that these films are significant in reflecting the cultural tensions at the time they emerged, many which can still be felt today. These films connect with contemporary developments in jazz practice in Australia and offer a template for future practice-based research and cultural collaborations.
Open Access
Characterising two P. falciparum transporters essential for life cycle progression
(2025) Huppertz, Frederik
During life cycle progression, Plasmodium parasites rely on a complex repertoire of transporter proteins to supply them with nutrients obtained from their host. Of the 144 transporter proteins annotated in Plasmodium falciparum, the majority has already been deemed likely essential for asexual blood growth. In this thesis, I hypothesized that a part of the unassigned parasitic transportome will be specifically essential to the sexual gametocyte stages and thus could contain transmission blocking targets for future application. The transportome of P. falciparum was screened in silico for potential candidates and the most promising genes were then targeted via a Crispr-Cas9-based disruption approach. Through this, I was able to confirm a defect in gametogenesis caused by disruption of PfGEP1 previously observed in P. yoelii. Both male and female gametocytes lacking GEP1 were unable to produce gametes. Overall, my data indicates that GEP1 plays a central role in the activation process, making it a promising transmission blocking target. Disruption of a second candidate gene called MCP2 did not affect P. falciparum asexual and sexual blood stages. Deletion of its P. berghei ortholog instead resulted in impaired sporozoite formation in the mosquito vector. While parasites lacking PbMCP2 were able to infect mosquito midguts and form oocysts, only few of them appeared to produce midgut sporozoites. Consequently, very few sporozoites colonized mosquito salivary glands. While lack of MCP2 does not seem to affect vertebrate-to-mosquito transmission as anticipated, it appears necessary for life cycle progression. Together, the findings presented here underline the importance of transporter proteins for Plasmodium parasites throughout their life cycle and contribute to our understanding of their roles in the different life cycle stages of malarial parasites.
Open Access
Implicit Mixtures of Experts for Rigorous Interpretable Machine Learning
(2025) Elazar, Nathan
This work aims to provide a rigorous framework for practical Interpretable Machine Learning (IML). While IML research has exploded in popularity in recent years, the vast majority of works in the field propose no definition of what interpretability actually means, and even fewer propose practical objective metrics which can quantify the interpretability of models. In this work I define interpretability to be inversely proportional to complexity. While it is difficult to compare the complexities of two arbitrary functions, there are certain model classes which do permit easy measurement of complexity, most notably: the complexity of a decision tree can be measured by the number of nodes it contains. Therefore, as long we restrict ourselves to only considering models from a complexity-measurable class, interpretability is well defined and objectively quantifiable. Unfortunately, for many tasks decision trees perform sub-optimally even when they are allowed to be arbitrarily large. For these tasks, we would like to be able to use more powerful models, such as neural networks. The major technical contribution of this work is the development of the Implicit Mixtures of Experts via Neural Networks (IMoENN) methodology. IMoENN uses neural networks to implicitly generate Mixture of Experts (MoE) models. While explicitly training a MoE directly is only feasible for small mixtures, IMoENN can produce implicit mixtures with arbitrarily many experts. In addition, IMoENN's prediction performance generalizes as well as the neural network architectures that it employs, whereas explicit MoE are prone to overfit to the training dataset. Even when using extremely simple experts, such as linear functions, IMoENN can match deep neural network classification accuracy on image benchmark datasets MNIST10, Fashion-MNIST10 and CIFAR10, provided that there are sufficiently many experts in the mixture. If the experts that make up a mixture are simple models, such as linear functions or decision trees of fixed size, then the complexity of a MoE is readily given by the number of experts in the mixture. In addition, when using IMoENN, the accuracy of these mixtures increases up to that of a black-box classifier as the number of experts is increased. With these facts in mind, I argue that MoE are the ideal model class on which to base complexity-grounded IML. In this work I will demonstrate how IMoENN can be used to create mixtures of linear experts which match black-box accuracy on MNIST10, Fashion-MNIST10, and CIFAR10. These mixtures provide local interpretability by showing the expert responsible for classifying a particular data point. The quality of that local interpretation can be measured by the number of experts in the mixture. IMoENN can also be used for global interpretability, so long as the mixture is small enough that every expert can be inspected. When using such small mixtures IMoENN is unable to match black-box accuracy, so I propose two variants of IMoENN which exploit properties of natural images to improve performance. These variants can match black-box accuracy on MNIST10, but are still worse on Fashion-MNIST10 and CIFAR10. Finally, I show how IMoENN can be used to both learn semantically meaningful features from data and assign feature importances to those features at the same time. This method can provide a degree of global interpretability in the form of global feature importances, and can match black-box accuracy on MNIST10 and Fashion-MNIST10. While I have focused on image classification benchmarks in this work, IMoENN is a very general methodology and can potentially be applied to any task. Therefore, IMoENN is a promising approach to making complexity-grounded IML practically viable on complex datasets, thereby providing a much needed objective metric of interpretability.
Open Access
2003: A Spatial Odyssey: Referring to Space in Makasai
(2003) Brotherson, Anna
This thesis provides an overview of how speakers of the East Timorese language Makasai (also known as Makasae) refer to space and spatial relationships. A summary of basic Makasai grammar is provided, followed by discussion and semantic analysis of space-denoting verbs, postpositions, directionals and demonstratives. The study is based on data collected by the author and other researchers at the Australian National University between July 2002 and November 2003.
Open Access
Spectral Properties of Non-local Schr\"{o}dinger Operators: Techniques and a Counterexample
(2025) Chen, Sophie
This thesis aims to expand our understanding of the spectral properties of non-local Schr\"{o}dinger operators on an open set in Euclidean space. The first part concerns extending the method of modulus of continuity for solutions of parabolic equations---as used, for instance, to prove the Fundamental Gap Conjecture---to solutions of non-local heat equations on $\R^n$ and in dimension one with a non-local Neumann boundary condition. Specifically, we show that if a solution of a non-local heat equation has an initial modulus of continuity satisfying simple criteria, then this modulus of continuity is preserved at all subsequent times. In the process of trying to generalise our result in one dimension, we found a counterexample suggesting that a non-local analogue of the Payne-Weinberger inequality would depend on more than the diameter of a bounded (convex) domain. In the second part, we construct a counterexample demonstrating that the second eigenfunction of a perturbed fractional Laplace operator on a bounded interval, with Dirichlet `boundary' data off the interval, can exhibit more than one sign change. This stands in stark contrast to the classical expectation that it should have exactly one zero. Our construction employs the Kato-Rellich regular perturbation theory to analyse an infinite potential well eigenvalue problem, and then uses an energy-minimisation argument to extend this counterexample to finite potential wells. Although our detailed analysis focuses on the case $s=1/2$ (the Cauchy process), our approach strongly suggests that similar phenomena occur for other rational values of $s$ in $(0,1)$. At the time of writing, this result provides one of the first rigorous insights into the qualitative behaviour of eigenfunctions for perturbed non-local Schr\"{o}dinger operators.
Open Access
Sovereignty and land tenure in the British Colonial Asia and Australia
(2025) Knapman, Gareth
This thesis examines the question: How did British colonial agents in Asia and Australia interpret the relationship between sovereignty and land ownership? The question of this thesis reflects the real dilemma that British colonial agents faced in colonial territories in Asia. In the mid-18th century, the British legal theorist William Blackstone had defined sovereignty 's 'supreme, irresistible, absolute, uncontrolled authority', but in many colonial territories, British sovereignty was not a clear fact. For example, British East India Company's authority in Bengal relied on the right to collect tax (Diwan) for the Mughal Emperor. Under British feudal law, all land was owned by the sovereign; subjects possessed only tenure over the land, not the land itself. In Bengal (acquired after 1757), Penang (acquired in 1786), and Singapore (acquired in 1819), British colonial agents applied their feudal understanding of sovereignty and land tenure to determine the various pre-existing rights of local people over land, and to determine to what extent these rights constituted sovereignty or shared sovereignty over the land. The answers to these questions then indicated how these rights related to colonial rule. This thesis argues that British approaches to Asian systems of political rule were framed by ideas of feudalism. The thesis concludes by examining how these ideas of feudalism were applied to the colonies of New South Wales, Port Phillip and Sarawak .
Open Access
Advancing Aluminyl Anions: Synthesis of Acyclic and Four-Membered Metallocyclic Aluminium Nucleophiles
(2025) Matthews, Aidan
Chapter 1 presents a general introduction to modern organometallic chemistry and its subsequent paradigm shift encompassing the developing roles of the main group elements, their fundamental considerations and challenges in low oxidation state element synthesis. It includes an overview of the frontiers of research interests and the pursuit of transition-metal metallomimetic species for small molecule activation. Finally, the focus of the chapter shifts to group 13, highlighting its elemental members, and a chronological summary of research discoveries in developing a new class of group 13 anionic nucleophiles. Chapter 2 focuses on the preparation of bulky silylamido aluminium(III) halide complexes incorporating both monodentate and bidentate chelating ligand scaffolds. The rationalisation and role of ligand design in modern organometallic chemistry, and previous applications of the utilised ligand scaffolds are discussed. The necessitated synthetic routes, isolation and structure of prepared species are explored and compared with related aluminium(III) halide complexes. The complexes reported in the chapter will serve as precursors for the novel aluminyl anions presented in Chapters 3 and 4. Chapter 3 discusses the preparation and isolation of low oxidation state, aluminium(I) nucleophiles. These include the isolation and characterisation of the first acyclic aluminyl anion [K2(Al{N(Dipp)SiMe3}2)2], synthesised by the reduction of [AlI{N(Dipp)SiMe3}2] with potassium graphite. The reduction of the bulkier analogue, [AlI{N(Dipp)Si(iPr)3}2], yielded intramolecular activation products consistent with the transient generation of an aluminyl anion. The reactivity of the resulting acyclic aluminyl anion was explored briefly towards a range a small molecules, and applied in the preparation of the magnesium aluminyl complexes [(ArNanac)Mg-Al{N(Dipp)SiMe3}2] ([ArNacnac]- = [(ArNCMe)2CH]-, Ar = mesityl, 2,6-diisopropylphenyl). Structural classifications of related aluminyl anions are explored from the conversion of the parent acyclic aluminyl anion contact dimeric pair toward both monomeric and charge-separated ion pairs. Chapter 4 further expands on the isolated examples of low oxidation state aluminium(I) nucleophiles. This includes the isolation and characterisation of the first aluminyl anion contained within a four-membered metallocycle. This anion was synthesised by the reduction of the aluminium(III) iodide precursor [AlI(DAS)] ([DAS]2- = [Ph2Si(NDipp)2]2-) with potassium graphite under short timeframes, [K{Al(DAS)}] was isolated as a 1-dimensional coordination polymer in the solid state. Synthesis and characterisation of the corresponding iron aluminyl coordination complex [(CO)2CpFe-Al(DAS)] (Cp = cyclopentadienyl) is also discussed. The reactivity of [K{Al(DAS)}] was briefly explored and utilised in the preparation of complexes featuring unsupported bonds of Mg-Al [(ArNanac)Mg-Al(DAS)] and Al-Al [{Al(DAS)}2]. The published library and presented aluminyl anions [K2(Al{N(Dipp)SiMe3}2)2] and [K{Al(DAS)}] are compared, concerning their ligand scaffolds and the imparted electronic and nucleophilic effects present in reactivity is reported. Chapter 5 concentrates on research investigations undertaken on exchange at the University of Stuttgart. Huckel antiaromatic group 13 metalloles incorporating boron and aluminium, and their reduction to give aromatic and radical species are discussed. The redox applications of the acyclic aluminyl anion [K2(Al{N(Dipp)SiMe3}2)2] with 2,5-disilyl-3,4-diaryl boroles is presented through reductions to analogous boroldiide and borole radical anions, and coinciding oxidation yielding an acyclic dialane [(Al{N(Dipp)SiMe3}2)2]. A catalogue of new 2,5-disilyl-3,4-diaryl alumole complexes are reported, their synthesis, structure and reactivity are explored, and investigations undertaken toward new NHC-stabilised alumole cations are discussed.
Open Access
V3O5 as a Functional Material for a Solid-State Neuron
(2025) Das, Sujan Kumar
Artificial intelligence (AI) is evident in every facet of our lives but traditional computing, based on CMOS technology and von Neumann architecture, is very inefficient for such tasks. Neuromorphic computing aims to address this shortcoming by emulating the computational architecture of the brain. This typically takes the form of a spiking neural network (SNN) comprising a highly interconnected network of solid-state synapses and neurons, where the synapses serve as distributed memory (synaptic weights) and the neurons function as simple processing units. This thesis is focused on the development of a suitable solid-state neuron based on threshold switching in V3O5. In the first part of this thesis, the structural, electrical, and thermal properties of V3O5 thin films are investigated. X-ray diffraction (XRD), Raman spectroscopy, and electron diffraction techniques show that the as-deposited V3O5 films are polycrystalline with a monoclinic structure. Electrical characterisation shows that the films undergo an insulator-metal transition (IMT) at 420 K. The IMT occurs over a broad temperature range due to the inhomogeneous nature of the V3O5 phase transition, as indicated by temperature-dependent C-AFM maps of through-film current distributions. The thermal conductivity of the V3O5 films was shown to increase slightly with temperature below the IMT temperature and significantly during the IMT due to the increasing electronic contribution. These properties show that V3O5 holds promise as a functional oxide for threshold switching applications. The second part of this thesis focuses on the threshold switching characteristics of Pt/V3O5/Pt memristors. These devices exhibit volatile threshold switching and negative differential resistance (NDR) from the first voltage-sweep and stable cycle-to-cycle operation, with a variation in switching parameters of less than 3 percent during 10000 cycles. The threshold and hold voltages decrease with increasing substrate temperature while still maintaining an NDR window up to the V3O5 IMT temperature. The physical mechanisms underpinning these characteristics are investigated using a combination of electrical measurements, in situ thermal imaging, and device modelling. This shows that conduction is confined to a narrow filamentary path due to the self-confinement of the current distribution. Additionally, it shows that the threshold switching and NDR response are initiated at temperatures well below the IMT temperature due to the temperature-dependent conductivity of the insulating phase. Variations and discontinuities in the NDR slope are further shown to be consistent with the averaging of the electrical oscillations. In the final part, the application of V3O5 memristors as solid-state neurons is investigated. This focuses on the dynamics of individual and coupled relaxation oscillators and leaky integrate-and-fire (LIF) neurons. It is observed that individual oscillators exhibit a fast-spiking pattern and maintain stable relaxation oscillation even at operating temperatures exceeding 400 K. Capacitively coupled oscillators are then shown to exhibit rich non-linear dynamics, including frequency and phase synchronisation, which is a key feature for oscillator-based computing. Effective LIF neuron's behaviour can be tuned through relative timing and amplitude of the external stimulus, and resistively coupled LIF neurons exhibit various neural functionalities (i.e. phasic, regular and adaptation, etc.) depending on the input voltage and circuit parameters. The behaviours of both individual and coupled neurons are shown to be well described by a physics-based lumped element circuit model, which, therefore, provides a solid foundation for exploring more complex systems. These results establish V3O5 as a potential functional material for volatile threshold switching and advance the development of robust solid-state neurons with low power consumption for neuromorphic computing.
Open Access
Navigating the Embodied Agent: Design and Optimisation of Object-Goal Visual Navigation System
(2025) Du, Heming
Embodied Artificial Intelligence (Embodied AI) represents a significant shift from traditional static computations to dynamic interactions with the environment, interactions that not only respond to but also actively shape the physical world. Within this paradigm, Object-Goal Visual Navigation (ObjNav) is pivotal, as it equips robots with the capability to navigate and pinpoint specific target objects, an essential function that underpins the operational framework of Embodied AI systems. A typical reinforcement learning based ObjNav system comprises two primary components:(i) a visual perception module that interprets the scene by extracting navigation cues, such as the target's location and its spatial relationships with surrounding elements; and (ii) a navigation policy module that processes both the current visual inputs and historical navigation data to determine the optimal action. This ensures that the ObjNav system not only recognises its targets but also formulates effective navigation strategies, thereby enabling robust and adaptable performance in dynamic real-world environments. This thesis investigates Object-goal Visual Navigation systems, focusing on both visual perception and navigation policy. We enhance visual perception by leveraging object relationships within scenes. Meanwhile, we first concentrate on preventing the navigation policy from predicting actions that often lead to failure. Then, we shift our focus to prioritising information most relevant to the current navigational step. We achieve this through three key contributions: In Chapter 3, we enhance object-driven visual navigation using object relation graphs (ORG), trial-driven imitation learning (IL), and a memory-augmented tentative policy network (TPN). ORG improves visual understanding by modelling object relationships. IL and TPN help create robust navigation policies, guiding the agent away from unproductive actions and promoting efficient navigation. In Chapter 4, we introduce VTNet, a Visual Transformer Network for learning informative visual representations. VTNet emphasises spatial locations and object relationships, using attention mechanisms to create informative visual information for navigation decisions. A pre-training scheme aligns these representations with navigation signals for effective policy learning. In Chapter 5, we address the impact of navigation states on effectiveness and efficiency by introducing the History-inspired Navigation Policy Learning (HiNL) framework. HiNL uses historical navigation data to improve current decision-making. It incorporates a History-aware State Estimation (HaSE) module to reduce the influence of past states and a History-based State Regularisation (HbSR) technique to minimise correlations among states during training. This enables the agent to adapt to changing environments and make informed decisions. In Chapter 6, we introduce the Experience-aware Action Cogitator (ExAC), a framework that utilises the power of Large Language Models (LLMs) to elevate decision-making in ObjNav. By integrating insights derived from both expert-informed and trial-and-error experiences, ExAC refines the LLM's decision framework. Consequently, the model not only predicts effective navigation actions with remarkable intuition but also articulates the reasoning behind its choices, thereby enhancing the transparency and reliability of navigation in complex indoor settings. In conclusion, this thesis has tackled multiple open challenges in Embodied AI, especially in the area of Object-goal Navigation, showing improvements in both navigation effectiveness and efficiency in unseen environments. Through this work, we aim to foster conversations among academics in the Embodied AI space while also motivating future efforts and collaborations that would push the field toward more challenging real-world problems.
Open Access
Essays on Fertility Related Issues in East Asia
(2025) Li, Ji
This dissertation is divided into three interconnected chapters, each addressing a specific aspect of how institutional and cultural factors shape demographic and socioeconomic outcomes, focusing primarily on China and the broader East Asian region. Chapter 1, titled "Born with Burden? The Effect of Family-Planning Above-quota Sanctions on Children's Education in Rural China," investigates how the above-quota sanctions imposed by China's coercive family planning policies affect the educational outcomes of children in rural areas. It highlights the severe financial and non-financial penalties faced by families who exceeded their birth quotas, particularly low-income households, and examines the trade-off between human capital investment and the burden of sanctions. This chapter contributes to the literature by demonstrating that while family planning policies may have promoted human capital accumulation through reduced family sizes, they also disadvantaged over-quota households, especially in terms of children's education. Chapter 2, "Beyond Policy: Parental Preference and Fertility Behavior under China's Coercive Family Planning Regime," shifts focus to the deeply rooted cultural phenomenon of son preference in China. It examines how this preference interacts with family planning policies to influence fertility behaviors and the intra-household allocation of resources. This chapter builds on the finding that son-biased fertility-stopping behavior is prevalent, with parents continuing to have children until their desired gender composition, especially sons, is achieved. This chapter reveals that son preference, combined with the coercive family planning policies, reinforces gender disparities in educational outcomes, particularly in households that violate policy mandates. Chapter 3, "Education Competition and Ultra-Low Fertility in East Asia," extends the analysis beyond China to explore the broader context of East Asia, where countries such as South Korea, Japan, and Taiwan also face persistently low fertility rates. The chapter focuses on the role of education competition and its influence on family formation behaviors. It argues that the intense competition for educational success, driven by Confucian values, high-stakes entrance exams, and rising income inequality, has significantly contributed to the region's ultra-low fertility rates. The high financial burden of education, particularly shadow education and private schooling, discourages parents from having more children. This chapter integrates Becker's Quantity-Quality (Q-Q) trade-off model with a competitive education framework to explain how the educational competition reduces fertility in East Asian societies. It also discusses potential policy interventions to alleviate the competitive pressures on families and promote higher fertility rates.
Open Access
Towards Immersive Environments: Ambisonics-driven Room Acoustic Modeling and Spatial Audio Capture
(2025) Bastine, Amy
Spatial audio technology has gained significant importance across various fields, including extended reality, gaming, telecommunications, and immersive media, where delivering realistic auditory experiences is crucial. These applications require extensive and resource-intensive microphone measurements to accurately capture and reproduce authentic acoustic environments. This thesis addresses the need for more efficient and scalable methods by developing solutions that balance precision with practicality, thereby making high-quality spatial audio more accessible for a wide range of applications. Aligning with the evolving spatial audio technologies, we focused the research on three core challenges: (i) achieving comprehensive room acoustic characterization with minimal measurements, (ii) enabling versatile auditory experiences beyond measurement locations via Room Impulse Response (RIR) extrapolation, and (iii) facilitating spatial audio capture using Head-Worn Devices (HwDs). All our methods are fundamentally grounded in the solution of the acoustic wave equation, employing spherical harmonic basis functions. A key contribution of this thesis is the development of a room acoustic analyzer based on higher-order eigenbeams/ambisonics. This tool provides detailed insights into the directional characteristics of early reflections and late reverberation, with an emphasis on their frequency-dependent behavior. We can adapt this tool to various microphone arrays and measurement setups capable of ambisonic capture. For high-precision 3D analysis, the use of a Spherical Microphone Array (SMA) is demonstrated through comprehensive studies conducted in a small lab room and an empty classroom. The analyzer's scalability is further showcased through a comparative study involving a first-order ambisonic array and a higher-order SMA in a recording studio with variable acoustic settings. Additionally, a novel metric, termed the ``directivity time-span'', is introduced as a more accurate alternative to traditional estimates of mixing or transition times, enhancing the precision of room acoustic analysis. Utilizing reflection characteristics learned by the proposed analyzer, we present a method for extrapolating RIRs from a single SMA measurement. Our reconstruction approach ensures the coherence of early reflections and late reverberations, preserving perceptually critical objective parameters, even as the extrapolation extends farther from the original measurement location. To further advance spatial audio capture, we propose a method for estimating perceptually accurate higher-order ambisonics using HwDs. This method overcomes the challenges posed by the arbitrary geometry and complex scattering effects of HwDs by leveraging the inherent diversity of wearable-device-related transfer functions, optimized using a magnitude least-squares approach. Validation through simulation results and listening tests confirms that the binaural audio produced by this method is on par with that generated by traditional SMAs, establishing HwDs as a viable solution for seamless spatial audio capture and reproduction in extended reality applications. The contributions in this thesis collectively pave the way for more sophisticated and adaptive acoustic modeling, supporting the development of highly immersive, personalized, and real-time spatial audio solutions.
Open Access
Optimal Planning of Community Energy Storage Systems In Low-Voltage Distribution Networks
(2025) Kariyawasam Bovithanthri, Jayaminda Anuradha
The increased adoption of renewable energy sources in modern power systems is mainly driven by their sustainable solutions for clean energy and potential to reduce energy costs. However, the intermittent and non-dispatchable nature of common renewable energy sources, such as photovoltaic energy systems, may restrict the ability to fully exploit their benefits. Energy storage systems are used to overcome these challenges efficiently. Community energy storage systems (CESSs) are an emerging type of energy storage system that can trade energy with multiple stakeholders, including prosumers, consumers, and the grid, thereby generating techno-economic benefits. The benefits of a CESS can be further enhanced by optimising its planning aspects, namely its location, size, and rated power. In this thesis, we propose novel optimal CESS planning frameworks to benefit multiple stakeholders in low-voltage distribution networks. First, we develop a multi-objective CESS planning framework to deliver technical benefits to the network, and economic benefits to the CESS provider and prosumers. The results demonstrated that our model generates enhanced techno-economic benefits compared to models that do not utilise a CESS, and models that optimise only the CESS operation. Then, we present a multi-objective stochastic optimisation framework to optimally plan CESSs under different energy pricing schemes (EPSs) of the CESS provider, thereby producing economic benefits for a community of prosumers and the CESS provider equitably. The optimisation framework minimises the investment and expected operating cost of the CESS provider, and the expected operating costs of prosumers. Our experiments show that under the EPS where the CESS provider trades energy with prosumers at the average grid energy price, and the objective of the CESS provider is traded-off moderately to improve the objective of prosumers, spreads the economic benefits for both beneficiaries most equitably. Next, we propose a multi-objective stochastic optimisation framework that can be used by governments to run auctions and select the best CESS project to financially support. So, CESS providers and energy community members can equitably benefit from the economic value generated by CESSs. Our experiments demonstrate that government financial support can accelerate the installation of CESSs and enhance their business viability. This can be achieved by boosting the economic benefits shared between CESS providers and communities, and ensuring these benefits are distributed equitably. Finally, we evaluate how the economic benefits for prosumers can be improved through optimal CESS planning under different energy trading schemes (ETSs). The results demonstrate that the ETS enabling prosumers to trade energy with both the grid and the CESS maximises their economic benefits.
Open Access
Hole-selective passivating contacts: from process development to application
(2025) Bartholazzi Lugao De Carvalho, Gabriel
Increasing energy demand and need to reduce greenhouse gas emissions are major concerns for this century. In this context, photovoltaic (PV) technology has risen as one of the primary solutions to overcome these challenges. Therefore, it is important to seek ways to further reduce costs and improve performance of c-Si solar panels. Current state-of-the-art solar panels utilize so-called passivating contacts, a key technology to enable high-efficiency solar cells. Passivating contacts comprise a single layer or stack of materials designed to induce carrier-selectivity and passivation between the c-Si and metal electrodes, minimizing recombination losses. Despite enabling high performances, current passivating contact technologies, based on amorphous or polycrystalline silicon, suffer from one or a combination of drawbacks, such as high parasitic absorption, high-thermal budget or thermal instability, and process complexity. In this context, transition metal oxides (TMOs) have emerged as alternative passivating contact materials mainly due to their improved transparency. In this thesis, the development and application of hole-selective passivating contacts based on TMOs is explored. The thesis can be divided into two sections. In the first part, the development of novel atomic layer deposition (ALD) processes for potential hole-selective contact materials based on copper oxide is reported. In the second, a novel ALD interlayer is employed together with existing hole-selective materials and the resulting structures are investigated as hole-selective contacts in c-Si solar cells. Novel ALD processes are developed for the binary oxides Cu2O and CuO using thermal and plasma processes, respectively. The complete process development is reported, including saturation curves and growth behaviour. Self-limiting reactions are achieved for both processes, producing uniform thin films with low roughness. In a third ALD work, a ternary oxide deposition process to form CuxCryOz is investigated using the super-cycle approach. A wide range of compositions is explored, ranging from pure CuOx to CrOx. An unexpected dependency of growth rate as a function of the CuOx/CrOx sub-cycle ratios is found. Through modelling, it is shown that CuOx enhances the growth of CrOx by a factor of 9, working as a catalyst to the reaction. The properties of the various CuxCryOz compositions are investigated both as-deposited and after annealing, and some tested as potential hole-selective contacts. As-deposited Cr-rich CuxCryOz thin films appear to be strong hole-selective candidates as they present a wide band gap and the lowest contact resistivity among different compositions. In separate works, Cu2O and MoOx hole-selective materials are investigated in novel stack structures containing an ALD-deposited AlyTiOx/TiO2 stack as a passivating interlayer. Both stacks are optimised to achieve the best trade-off between passivation and contact resistivity. Record-low recombination is achieved for both materials while maintaining low contact resistivity and high optical transparency. Additionally, the AlyTiOx/TiO2/MoOx stack demonstrates self-healing behaviour after sputtering of a transparent conductive oxide layer, without requiring an additional annealing step. The optimized stacks of AlyTiOx/TiO2/Cu2O and AlyTiOx/TiO2/MoOx are implemented as full-area contacts at the rear side of proof-of-concept c-Si homojunction solar cells. A significant improvement in open-circuit voltage confirms the boost in surface passivation provided by the interlayer. A record efficiency for devices incorporating full-area TMO-based contacts (including electron-selective materials) without an a-Si:H interlayer is achieved for the stack containing MoOx, providing an important stepping stone towards the development of high-efficiency cells employing TMO-based contacts fabricated using simple, low-temperature processes.
Open Access
Dynamics of grassroots collectivism: natural resource conflicts and social movements in Thailand's Special Economic Zones
(2025) Arpornsilp, Ratchada
Open Access
Encouraging the regulatory evaluation of off-patent repositioned medicines in Australia
(2025) Perkin, Katrina
Australia's National Medicines Policy (NMP) aims to ensure medicines meet agreed standards of quality, safety and efficacy. This is achieved when a prescription medicine is evaluated by the Therapeutic Goods Administration (TGA) to ensure benefits outweigh risks prior to approval. The use of a prescription medicine beyond approved limits is known as off-label use. Medicines prescribed off-label for different health conditions, usually due to a lack of effective approved treatments, are known as repositioned medicines. Without regulatory approval, prescription medicines are not eligible for Commonwealth Government cost subsidisation, making access unaffordable for some patients. There is limited understanding of how repositioned medicines are used across the Australian health system and what changes might be made to improve regulation and access. Informed policy responses rely on an assessment of the best available evidence and the production of intentional strategies for reform. This thesis reviewed and synthesised multiple sources of secondary data to explore ways to encourage the regulatory evaluation of off-patent repositioned medicines in order to create a novel policy model to improve regulation and access. An initial scoping review found that the extent of off-patent repositioned medicine use across Australia is greater than previously thought. In addition, state and territory funded patient access varies because safety, efficacy and cost effectiveness are evaluated at the local level rather than nationally. Analysis of regulatory processes and policies found that while regulatory pathways in Australia and comparable international jurisdictions permit the evaluation of off-patent repositioned medicines, complexity and cost limit use of these systems. In particular, the presence or absence of three key drivers (evidence generation, application submission and revenue generation) either facilitate or impede the regulatory evaluation of repositioned medicines. This means that in practice, when patent protection expires, a medicine sponsor is unlikely to seek regulatory approval for repositioned medicines due to effort and unrecoverable costs. Evidence shows that stakeholders in Australia are advocating for better access to repositioned medicines for patients and changes to the regulatory system to promote medicine repurposing. However, without the potential for revenue generation, sponsors of off-patent repositioned medicines are unlikely to invest in evidence generation and application submission to enable regulatory evaluation. The findings of the studies conducted enabled the development of a draft policy framework which aims to facilitate affordable patient access to safe and effective medicines. Through generation of the clinical evidence necessary to enable the regulatory evaluation of off-patent repositioned medicines, the policy framework removes barriers to the submission of clinical evidence in a regulatory evaluation application and creates avenues for revenue generation post approval. The utility of the draft policy framework was tested with experts via a modified Delphi consultation. Consensus was reached on characteristics of a policy model specifically designed to facilitate evidence generation, application submission and revenue generation for off-patent repositioned medicines. The novel policy framework translates key drivers of regulatory evaluation into practice in the Australian context. This thesis highlights the drivers of regulatory evaluation in order to identify the barriers specific to off-patient repositioned medicines. Strategic reforms that concurrently incentivise evidence generation, application submission and revenue generation could potentially improve affordable patient access to safe and effective off-patent repositioned medicines in Australia. The novel policy framework presented should help to improve the quality use of medicines and alignment with broader NMP objectives.
Open Access
Developing a Guitar Solo Idiolect in Hard Rock and Metal Music Performance
(2025) Buchli, James
This PhD thesis examines how a guitar solo idiolect in hard rock and metal music performance may be developed in creative practice. Crucial to my thesis is understanding and demonstrating how consciously drawing upon ideas from aggregate influences, as well as documented analysis and reflections on practice, informs this transformative guitar solo idiolect development process. Existing studies have explored the historical origins and stylistic attributes of hard rock and metal lead guitar performance, as well as themes of innovation, technology, and social issues in these genres. However, there has been little research that examines the development of a solo idiolect in hard rock and metal guitar performance from a practitioner's perspective. This is a significant gap in my field, as hard rock and metal are widely learned and performed popular styles by guitarists. My research addresses this gap through the application of blended creative practice, reflective, analysis, and autoethnographic methodologies, and by recounting and demonstrating findings through a folio of recorded performances and this accompanying exegesis. In this exegesis, I discuss how my conception and application of a novel methodology enabled me to consciously innovate existing ideas from my collective influences to create original guitar solos. I also provide a contextual critique of the concept of virtuosity as applied to hard rock and metal guitar performance and a case studies discussion of my primary guitar influences. Additionally, I recount my various creative processes when developing and documenting my emerging solo idiolect. I conclude by discussing my folio of recordings and findings, as well as identifying avenues for potential further research. The main findings from this PhD project are that a guitarist's solo idiolect is comprised of technique, tone and phasing; my methodology permanently changed my practice as it enabled me to create my own guitar solos more effectively; and modifying and combining existing ideas from other practitioners amounts to innovation and novelty.
Open Access
Topics in Tax and Child Benefit Design
(2025) Tin, Darapheak
This thesis examines the interaction between means-tested child benefits and the progressive tax system in Australia, focusing on efficiency, welfare, and equity. It consists of three chapters. Chapter 2 provides the empirical foundation by documenting income dynamics and the role of government transfers in insuring parents against earnings shocks. The findings also reveal that public transfer responses to primary earners' shocks correlate with weak labour supply responses from secondary earners, suggesting potential work disincentives. Chapter 3 develops a dynamic general equilibrium overlapping-generations model with heterogeneous households, incorporating family structure, education, female human capital formation, uninsurable earnings shocks, child-related costs, and the exact structure of child benefit programs in Australia. The model is used to assess the current child benefit design and potential reforms. The results support universal child benefits for enhancing female labour supply, output, and overall welfare. However, they also underscore the importance of means-testing by demonstrating that while the universal scheme improves aggregate outcomes, it imposes a heavier tax burden that disproportionately harms single mothers, the intended beneficiaries. Chapter 4 extends the analysis by examining the broader tax-benefit interplay. It argues that optimizing the tax system alone can undermine child benefit objectives and proposes an optimal joint policy design featuring a less progressive tax schedule and a universal lump-sum child benefit set at 30% of the average income per child. While this system improves overall and parental welfare by enhancing consumption allocative efficiency, particularly for vulnerable groups such as single mothers, it comes at the expense of non-parents, who face higher tax burdens, raising important equity considerations. This thesis makes three key contributions: (i) From a policy-making perspective, it demonstrates that overall welfare (under the veil of ignorance) improves significantly when policies target vulnerable demographics, such as young single mothers. However, the distributional consequences for non-parent households must be carefully considered; (ii) In line with recent literature, it highlights the importance of modelling family structure in policy analysis, as different demographic groups face distinct economic constraints, including household size, earnings capacity, access to family insurance, and child-related costs; (iii) It underscores the critical role of policy interactions, particularly the trade-off between means-testing and tax distortions, in shaping welfare outcomes, providing a foundation for future research. Lastly, the findings suggest multiple policy options to improve both overall and parental welfare. If both tax and child benefit policies can be adjusted flexibly, an optimal policy mix can be designed to maximize welfare. Otherwise, relaxing the phase-out rates of the Child Care Subsidy emerges as a well-rounded reform that effectively balances improvements in female labour supply, output, overall welfare, and equity.
Open Access
Theoretical calculation and machine learning aided design of functional materials for energy conversion
(2025) Sun, Zhehao
This thesis investigates the integration of machine learning (ML) and theoretical calculations to design and optimize functional materials for photocatalytic applications. By combining experimental techniques with theoretical calculations, that is, finite-difference time-domain (FDTD) simulations, and density functional theory (DFT) calculations, this work aims to accelerate the discovery of efficient, selective, and scalable photocatalytic systems for CO2 reduction and seawater splitting. The central focus is on leveraging ML and advanced simulations into experiments to provide new insights into plasmonic photocatalysts and microenvironmental perturbations in photoreaction. The first study explores the development of Ag-TiO2 core-shell photocatalysts for the selective reduction of CO2 to methane (CH4). A significant contribution of this work is the use of FDTD simulations to model and optimize microenvironmental perturbations, thereby enhancing the catalytic activity of the plasmonic core-shell nanoparticles. Additionally, DFT simulations demonstrate that localized surface plasmon resonance (LSPR)-induced electric field enhancements lower the energy barriers for CO2 activation and methanation. Experimentally, this system achieves 100% selectivity for CH4 with a production rate of 75 umol/g/h. This study emphasizes the advantages of microenvironmental engineering in optimizing photocatalytic activity and selectivity, with FDTD and DFT simulations further elucidating the mechanisms of microenvironmental perturbations. The second study focuses on the design of Co-NC@Cu core-shell photocatalysts for solar-driven hydrogen production from seawater. By dispersing single Co atoms on a nitrogen-doped carbon (NC) shell surrounding a Cu core, this novel catalyst achieves a hydrogen production rate of 9080 umol/g/h and a solar-to-hydrogen (STH) conversion efficiency of 4.78%. A key highlight of this work is the detailed investigation of the local coordination environment of the single Co atoms, as well as the thermodynamic and kinetic effects of electric field perturbations on the catalytic process. DFT calculations reveal that the single Co atoms act as highly active sites for hydrogen evolution, exhibiting low energy barriers for the reaction. Furthermore, the electric field's role in enhancing the reaction thermodynamics and kinetics was elucidated, providing insights for further optimization of catalytic performance. Integrating single atoms, photothermal effects, and localized surface plasmon resonance (LSPR) demonstrates a robust and efficient design for seawater splitting. The third study showcases a comprehensive workflow combining ML and DFT calculations to accelerate the discovery and optimization of single-atom-based (SA) 2D photocatalysts. Using a dataset of Janus-TMD materials as a case study, ML models were trained to identify high-activity catalytic sites and screen potential substrates for photocatalytic CO2 reduction. The ML-driven predictions successfully prioritized optimal single-atom catalysts, with experimental validation confirming the activity and selectivity of two synthesized Janus substrates MoOSe with single-atom Pt. Photocatalytic experiments demonstrated the potential of the ML-guided design in delivering efficient and selective catalysts, underscoring the synergy between computational and experimental approaches. The growing dataset of atomic structures, intermediates, Janus configurations, and adsorption models provides a robust foundation for refining ML models and driving innovations in SA-based 2D materials discovery. In conclusion, this thesis demonstrates the successful integration of ML, FDTD, and DFT techniques with experimental approaches for the design of advanced functional materials, which contribute to the development of sustainable energy solutions through CO2 reduction and hydrogen production.
Open Access
The impact of undernutrition on tuberculosis prevalence and treatment outcomes in Ethiopia
(2025) Shiferaw, Fasil
Introduction: Tuberculosis (TB) is a leading infectious cause of death globally, with an estimated 10.6 million new cases and 1.3 million deaths annually. The emergence of multidrug-resistant tuberculosis (MDR-TB), characterized by resistance to isoniazid and rifampicin, further complicates the global TB control efforts. The progression from latent to active TB is influenced by various factors including undernutrition. While the individual-level association between TB and undernutrition has been documented, there has been a lack of studies exploring their geospatial co-distribution, particularly in high TB-burden countries like Ethiopia. There was also limited evidence on the impacts of undernutrition or failure to gain weight during follow-up on treatment outcomes among patients with TB and MDR-TB in Ethiopia. Furthermore, there was insufficient conclusive evidence to measure the effects of nutritional intervention on improving adherence to TB treatment and outcomes. This PhD thesis aimed to address these knowledge gaps by investigating the geospatial overlap of undernutrition and TB (objective 1), quantifying the effect of undernutrition and weight change on TB and MDR-TB treatment outcomes (objectives 2 and 3), and assessing the impact of nutritional intervention on TB treatment adherence, prognostic markers, and treatment outcomes (objective 4). Various study designs and statistical analyses were used to address the thesis objectives. A Bayesian model-based geostatistics was used to investigate the geospatial overlap of undernutrition and TB prevalence in Ethiopia (objective 1), using data from national prevalence surveys. A Cox proportional hazard model was performed to assess the effect of undernutrition on TB treatment outcomes using data from a retrospective cohort study in northwest Ethiopia (objective 2). Longitudinal data analysis using a joint model was applied to determine the effect of weight variation over time on MDR-TB treatment outcomes in patients with MDR-TB (objective 3). Systematic reviews and meta-analyses were performed to synthesize evidence on the impact of nutritional intervention on improving TB treatment adherence, prognostic markers, and treatment outcomes (objective 4). Results: The results of this thesis showed that spatial co-distribution of undernutrition and TB prevalence was found in some parts of Ethiopia. Population density was positively associated with TB and negatively associated with all forms of undernutrition. The distance to a health facility was positively associated with stunting and adult undernutrition. The overall successful treatment outcomes for patients with TB and MDR-TB in northwest Ethiopia were 89% and 67%, respectively. Undernutrition was positively associated with unsuccessful treatment outcomes, higher mortality, and a longer time to sputum culture conversion in patients with TB and MDR-TB. This thesis also indicated a significant relationship between weight variation over time and early unsuccessful MDR-TB treatment outcomes, suggesting that a one-unit increase in weight corresponds to a nearly 5% reduction in the risk of an unsuccessful outcome. Systematic reviews and meta-analyses demonstrated that the provision of nutritional support, as well as zinc and vitamin A supplementation, can improve adherence to TB treatment, increase early sputum smear conversion, and higher levels of serum zinc, retinol, and hemoglobin among people with TB. Conclusion: This thesis provides evidence that could guide decision-making and shape service delivery strategies for supporting nutritional aspects in the prevention and management of TB. The co-distribution of TB and undernutrition provides important evidence for targeted intervention strategies. This thesis has also made policy suggestions that could contribute to achieving the End-TB targets, emphasizing the relevance of strengthening the integration of nutritional interventions as an integral part of TB care.