Digital Commons Network^™

Sexisms And Gender-Washing In Australian Academia: Public Front, Private Realities, Jacqueline Ullman, Emily Gray, Mindy Blaise, Lucy Hobby

Research outputs 2022 to 2026

This paper offers an analysis of selected survey findings from a mixed methods research project, entitled Understanding and Addressing Everyday Sexisms in Australian Universities. The project is situated within the context of the negative impact of gender-based discrimination upon the higher education sector in Australia and internationally. The findings discussed in this paper relate to quantitative analyses of selected items from a national survey of over 1200 Australian academics, recruited through 12 public universities. In this paper, the ways in which different participant groups responded to items designed to explore their attitudes towards sexism in the academic workplace, both broadly …

When Brian Acted His Way Out Of A Wet Paper Bag: The Transformational Qualities Of Drama Education, Christina Gray, Robin Pascoe

Research outputs 2022 to 2026

This study utilised Mezirow’s Transformative Learning framework to explore drama teachers’ and pre-service drama teachers’ perceptions of transformation in the drama space. The research specifically examined three core questions: 1. Who are transformed? 2. What is transformed? 3. How does transformation happen? Adopting a phenomenological qualitative approach, we analysed interview data from eight drama teachers and 22 pre-service drama teachers in Western Australia. Findings indicate that participation in school-based drama activities fosters transformations (and perceptions of transformation) in self-confidence, personal values, and willingness to take creative risks. Beyond teaching performance skills, drama cultivates deeper understandings of self and others, offering …

How I Cook With No Kitchen: An Investigation Of How #Microapartment Kitchens Are Depicted On Tiktok, Joelie Mandzufas, Karen Lombardi, Dorian Winter, Sarah Foster, Siobhan Hickling, Gina S.A. Trapp

Research outputs 2022 to 2026

Background: Physical constraints of small apartment kitchens and the influence of the surrounding community food environment may impact food practices of apartment residents. Social media portrayal of these features may influence public perception of apartment living. Aim: This project aimed to describe the public depiction of small apartment kitchen and cooking facilities. Methods: Content analysis of TikTok videos posted with small apartment-related hashtags was determined the portrayal of kitchen facilities, residents’ food practices, and hypothesised barriers to healthy cooking and eating practices. Current residents of small apartments compared these video depictions to their own experience. Results: We found TikTok videos …

Metaverse And Artificial Intelligence As Web 4.0: The Next Generation Of The Internet, Anton Klarin, Elena Gorenskaia, Qijie Xiao, Pi-Shen Seet

Research outputs 2022 to 2026

This study utilizes systems thinking to explore and entwine an evolving metaverse scholarship to a relatively underexplored phenomenon of Web 4.0. We adopt a soft systems thinking framework to guide the interpretation of complex and evolving metaverse scholarship, using bibliometric mapping of 5587 publications sourced from Scopus. Using systems thinking, we synthesize these clusters into the following four thematic areas: (i) business and society implications, (ii) optimization, (iii) integration with other technologies and (iv) metaverse education. Drawing on the largest-to-date review of the metaverse as well as a systematic review of Web 4.0 literature, we propose a novel conceptualization of …

Towards Carbon Geosequestration: Comparing The Wettability Performance Of Western Australian Altered Basaltic Rock/Co2/Water Systems, Seyi Philemon Akanji, Rossen Sedev, Lionel Esteban, Ausama Giwelli, Trevor Beardsmore, Heather Howard, Joel Sarout, Alireza Keshavarz, Stefan Iglauer

Research outputs 2022 to 2026

Geosequestration of carbon dioxide in basaltic rock formations is considered to have the potential to safely and permanently store significant quantities of this greenhouse gas and thereby mitigate its potential global warming effect. The success of this storage method is primarily dependent on the wettability behaviour of the rock-water-CO2 system, which significantly affects fluid distribution, fluid transport, storage capacity and containment security. This study investigates the wettability performance of several Western Australian altered basaltic rocks, of similar geochemistry, porosity and inter-connection. The wettability behaviour of the basaltic materials is assessed using water containing ions that have been leached from the …

Two Strategies To Improve Stability In A Precision-Based Task: Insights From The Badminton Short Serve, Yochi Iino, Jodie Cochrane Wilkie, Senshi Fukashiro, Shinsuke Yoshioka, Shayne Vial

Research outputs 2022 to 2026

The badminton short serve is a highly precise task requiring accurate control of racquet face orientation, which directly influences shuttlecock trajectory and limits an opponent's ability to attack. Previous studies on motor redundancy have emphasized covariation among elemental variables as the primary mechanism for stabilizing performance. However, when the sensitivities of elemental variables differ, performance can also be stabilized by unevenly distributing individual variances without altering correlation — an approach that has received limited attention. This study investigated whether elite players use both the correlation strategy and the uneven variance strategy to stabilize racquet face angles during the short serve. …

Optimizing Ev Battery Charging Using Fuzzy Logic In The Presence Of Uncertainties And Unknown Parameters, Minhaz Uddin Ahmed, Md Ohirul Qays, Stefan Lachowicz, Parvez Mahmud

Research outputs 2022 to 2026

The growing use of electric vehicles (EVs) creates challenges in designing charging systems that are smart, dependable, and efficient, especially when environmental conditions change. This research proposes a fuzzy-logic-based PID control strategy integrated into a photovoltaic (PV) powered EV charging system to address uncertainties such as fluctuating solar irradiance, grid instability, and dynamic load demands. A MATLAB-R2023a/Simulink-R2023a model was developed to simulate the charging process using real-time adaptive control. The fuzzy logic controller (FLC) automatically updates the PID gains by evaluating the error and how quickly the error is changing. This adaptive approach enables efficient voltage regulation and improved system …

Waterborne, Theresa Ann Wilks

Theses : Honours

Waterborne incorporates four eco-Gothic fiction narratives that, through a practice-led enquiry, examine how drawing upon the abject, by employing the Gothic tropes of violence and captivity within Australian settings, may be positioned to foreground environmental impacts from anthropocentrism, particularly upon bodies of water. Utilising eco-Gothic settings in water locations exhibiting ecological damage, from land clearing and water management practices, the fictional narratives may also highlight the physical, social and emotional impacts of adverse environmental change upon ourselves.

“High Tea and Acquisitions” followed time immersed at a freshwater lake that is choked with introduced weeds and becoming shallow with sediment. It …

The Travelling Dancer: The Exploration Of Strength And Conditioning And Lifestyle Strategies To Mitigate The Risk Of Posterior Ankle Impingement Whilst Dancing Abroad, Emma Tucker

Theses : Honours

Ballet dancers commonly experience posterior ankle impingement (PAI), and while there is research regarding the biomechanical risk factors for PAI in ballet dancers, and mitigation and rehabilitation strategies for this type of injury, there is little research conducted surrounding further barriers posed by international travel. This study investigated the implications of international travel on the risk mitigation and rehabilitation of posterior ankle impingement in ballet dancers, exploring barriers posed by international travel to regular strength and conditioning and lifestyle practices. Three ballet dancers and two physiotherapists were interviewed and shared their lived experience with, or treating, posterior ankle impingement in …

Puppet Lab: Investigating Digital Technologies In Creative Learning, Harrison Lorenz-Daniel

Theses : Honours

This study interrogates the impact that digital technologies and digital mediation have on creative learning workshops run by arts organisations and delivered by teaching artists. It responds to a wave of new creative learning initiatives supported by arts organisations, state governments, and schools following the COVID-19 pandemic. Situating the research primarily in the investigation of Puppet Lab, a new digital workshop developed by Spare Parts Puppet Theatre in Walyalup (Fremantle), qualitative data was collected over a series of 5 semi-structured interviews with Western Australian teaching artists. The study found that digital technologies did not meaningfully impact the standard delivery of …

Directing Young Actors, Mitchell Whelan

Theses : Honours

This reflective practice case study examines the studio environment of a small ensemble of female actors aged 16-19, in the rehearsal of a one-act play. Performing arts researchers working in youth spaces commonly adhere to conventions of ethnodrama and facilitate a process in which participants contribute personal stories as performance material. The present paper uses a published text (Slut by Patricia Cornelius) to position participants as actors, rather than devisors who must conjure original material. Through critical reflection, the project assesses the impact of developing performance material slowly while also making time for socialisation between castmates. Drawing on my repertoire …

Symbolism And Choreographic Practice: Exploring The Application Of Symbolism To Dance Through The Creation Of A Solo Choreographic Work, Ruby Brazzalotto

Theses : Honours

This research project explored the significance of symbolism as a communicative tool within dance theatre. The project drew upon Symbolist theory and Pina Bausch’s choreographic approaches, in an attempt to understand how the symbolic use of props and gestural movement can communicate and elevate meaning within dance performance. This project involved the creation of a new solo dance work, self-reflexivity, and analysis of how Bausch’s and Symbolists’ modes of presenting ideas overlap. The project sought to document how symbolic props can be chosen, developed and combined with theatrical choreography to convey meaning to audiences.

Care-Full Climate Justice Organising, Kylie Wrigley

Research outputs 2022 to 2026

Feminist, Indigenous, and disability theories and activisms have long called for more attention to care–both as an ethic and practice–in response to environmental and social issues. Although care work is vital for collective survival, it is relatively devalued and trivialised in society and under-examined in climate justice research. Emerging critical research suggests that care work is central to how climate justice communities understand and respond to climate change and interlocking structural violences. Yet, there is limited climate justice scholarship that attends to the intersections of care and climate movements. At this juncture, this article draws on empirical reflections from a …

Delirium In The Acute Care Setting From The Families Perspective: A Scoping Review, Amber Mclean, Beverley Ewens, Amanda Towell-Barnard

Research outputs 2022 to 2026

Aim: To explore the existing literature on delirium within the acute care setting from the family members' perspective and summarise key findings. Design: A scoping review guided by Arksey and O'Malley's methodological framework and refined by the Joanna Briggs Institute. Review Methods: The Population, Concept, and Context framework recommended by the Joanna Briggs Institute's scoping review protocol identified the main concepts in the primary review question. The inclusion criteria focused on primary research studies from any chronological date that explored the family members' experience of delirium within the acute care setting. Following screening by two independent reviewers, data extraction was …

Perceptions And Knowledge Of Machine Learning For Paediatric Related Decision Support In Emergency Care – A Uk And Ireland Network Survey Study Of Clinician Leaders, Behalf Of Peruki, Fiona Leonard, Mark D. Lyttle, Dympna O’Sullivan, John Gilligan, Damian Roland, Michael Barrett

Research Outputs: 2025-Present

This study explores clinician leaders understanding and perception at site level towards machine learning (ML) decision support tools for paediatric related emergency care across the UK and Ireland, essential in guiding safe and effective frontline implementation. A cross-sectional online survey was distributed via Paediatric Emergency Research United Kingdom and Ireland (PERUKI) to the lead for digital systems or PERUKI site lead, with one response sought per site. Survey development was in REDCap, and descriptive analysis (counts, percentages) was primarily performed. The response rate was 86.7% (65/75), mostly from England (83.1%). While 80.0% understood ‘Artificial Intelligence’, fewer understood advanced concepts such …

An Evaluation Of Modelling Of Propagation Using Comsol For A Singlemode-Multimode-Singlemode Structure, Thomas Freir, Arun Kumar Mallik, Yuliya Semenova, Gerald Farrell

Research Outputs: 2025-Present

This paper presents simulation models developed for investigating singlemode-multimode-singlemode (SMS) structures, with the intention of utilising precise nano-scale 3D printing to print the center-section of the structures modelled. The models allow the design of structures for use in SMS fiber sensors, replacing the silica fiber center-section structures commonly used, with 3D printed elements. The paper discusses the process of evaluating and validating COMSOL propagation models by comparison to existing reported results and proposes the use of SMS self-imaging length and the transmission spectra as useful metrics for model comparisons. Both 2D and 3D COMSOL models are developed, and both show …

Fuzzy Logic-Based Driving Style Classification For Lane-Change Prediction In Intelligent Transportation Systems, Muhammed Fatih Koc, Nouman Ashraf, Pramod Pathak, Sachin Sharma

Research Outputs: 2025-Present

In recent years, Intelligent Transportation Systems (ITSs) have emerged as a solution to mitigate the problem of traffic congestion. Understanding human driving styles such as aggressive, normal, and cautious is crucial for safe driving. In particular, predicting lane-change manoeuvres may be further supported by combining vehicle state information with driving style information. However, existing vehicle trajectory datasets lack driving style information, making classification challenging. To address this limitation, this paper proposes a fuzzy logic-based driving style classification framework in a Vehicle-to-Everything (V2X) environment. The model uses vehicle state information, including speed, longitudinal acceleration, lateral acceleration, and distance headway to classify …

From Clinic To Code: Using Clinician Insights To Develop A Framework For Fair And Representative Datasets In Women’S Health Ai, Andrea Heaney, Emma Murphy, Eugene Hickey

Research Outputs: 2025-Present

The development of Artificial Intelligence (AI) in healthcare is largely dependent on the quality of medical datasets. However, these datasets often fail to accurately represent women (and those seen as women) due to historic, implicit and biological biases. This under-representation can lead to biased, inequitable and even harmful models. Building upon the findings of previously conducted qualitative semi-structured semantic interviews with clinicians on their perceptions of women’s health, this paper presents a framework for translating qualitative findings to dataset characteristics via operationalisation. This framework outlines the key characteristics and considerations a dataset should include or consider to more accurately represent …

Academics’ Experiences Of Work-Life Balance And Work-Life Conflict In A Familialist State: The Case Of Bosnia And Herzegovina, Sara Clavero, Caitriona Delaney

Research Outputs: 2025-Present

Background: This paper explores how women academics in Bosnia and Herzegovina (BiH) navigate work-life conflict and the main strategies they deploy to balance their work and personal lives. It examines the range of institutional support available to them and assesses their effectiveness in facilitating work-life balance and reducing work-life conflict. Methods: Drawing on 12 semi-structured interviews with female academics at various career stages from public and private universities across BiH, this study captures personal narratives of managing work and caregiving responsibilities. Results: Thematic analysis revealed the respondents’ personal strategies to find work-life balance while trying to achieve their career goals, …

Optimisation Of Laminar Jet Flow Microencapsulation Variables To Enhance The Anthocyanin Retention And Antioxidant Function Of Sohiong, Roshiya Nongmaithem, Raju Sasikumar, Kaviarasu G., Selva Kumar T., Ravikumar Rajarathinam, Paras Sharma, Sheena Haorongbam, Kowsalya T., K. Senthilkumar, Amit K. Jaiswal

Research Outputs: 2025-Present

Anthocyanins are valuable dietary elements with biological functions and health-promoting effects. However, there are technological barriers to their use in the food industry, primarily due to their poor stability and susceptibility to environmental factors, such as oxygen, temperature, pH, and light, which can significantly affect the physicochemical characteristics of the final food products. In this study, the microencapsulation of an anthocyanin extract from sohiong fruits was performed using a laminar jet flow vibration nozzle, with calcium chloride as a hardening agent and sodium alginate as a polymer. To produce calcium-alginate microbeads with a high anthocyanin content and favourable morphological characteristics, …

Using Drawings To Understand Undergraduates’ Perceptions Of Politics—The Us And Ireland, John Hogan, Sharon Feeney, Paul Kosempel

Research Outputs: 2025-Present

Purpose: This article seeks to gain insights from the interpretations of freehand drawings produced by American and Irish students, young voters, in response to the question: “What is American/Irish politics?” Our goal in using freehand drawing is to foster a collaborative and critical learning environment where participants enhance their ability to interpret and engage in self-reflection. Design/methodology/approach: Freehand drawing is a visual representation method that can bypass cognitive verbal processing pathways as part of a critical pedagogy. This approach enables participants to create clear, more critical, and inclusive depictions of their understanding of a topic, regardless of their vocabulary. Over …

Synthesising Cross-Speaker Data For Low-Resource Pathological Speech Recognition With Peft, Kesego Mokgosi, Milad Dadgar, Cathy Ennis, Robert Ross

Research Outputs: 2025-Present

Dysarthric speech recognition is essential for enhancing communication and accessibility for individuals with speech impairments, yet its development is hindered by a scarcity of robust, speaker-specific datasets. This study explores low-resource dysarthric speech recognition through cross-speaker transfer using synthetic data and parameter-efficient fine-tuning (PEFT). We integrate SpeechT5 text-to-speech (TTS) synthesis with x-vector speaker embeddings to generate speaker-specific dysarthric speech, enabling model adaptation while preserving pathological speech characteristics such as prosodic irregularities. Experiments on the TORGO dataset show that mixed cross-synthetic data with LoRA fine-tuning achieves a WER of 0.17, representing a 71.7% improvement over the standard model (0.60 WER) without …

How Digital Learning Shapes Managerial Skills In Small And Medium-Sized Enterprises (Smes), Anna Zherdeva, Lucía Morales

Research Outputs: 2025-Present

Purpose – Small and medium-sized enterprises (SMEs) are a critical pillar of the European economy, contributing to employment, regional and global development. However, many SMEs face heightened failure risks linked to limited financial resources, labour market pressures and significant knowledge loss. Developing strong managerial competencies has emerged as a key strategy for improving organisational performance and long-term sustainability. The COVID-19 pandemic accelerated the shift from traditional training to online learning, yet research remains limited, this paper examines how digital learning environments can support the development of managerial capabilities within SMEs. Design/methodology/approach – To understand how online learning can enhance knowledge …

Modelling Probabilistic Digital Twins Of Complex Inland Waterway Transportation Systems Using Bayesian Networks, Alexandra Micu, Lorcan Connolly, Alan O’Connor, Eugene O’Brien, Caitriona De Paor

Research Outputs: 2025-Present

The Horizon Europe Project, ReNEW, uses the digital twin concept to simulate and model the complexity and interdependencies of the Inland Waterway Transport (IWT) system. This concept is used to design novel strategies to ensure network functionality despite climate change impacts on IWT. A digital twin is an accurate copy of a real object/item/system with associated characteristics in the digital world. Digital twin models can be developed using physics or statistics or combining the two. They can be used for simulation, classification, prediction, optimization, and more. This work proposes probabilistic digital twin modelling of complex IWT networks using Bayesian networks. …

External Financing For Cleantech Firms: What Attracts Investors?, Ziqi Liu, Seán O’Reilly, Jim Hanly

Research Outputs: 2025-Present

This study examines the external financing dynamics of early-stage Cleantech firms through the theoretical lens of signaling theory, focusing on identifying the internal characteristics that attract equity investors. Cleantech firms are a key element in the move towards sustainable energy and environmental practices. However, securing external financing remains a challenge for these innovators, highlighting the need to explore what factors influence investor decisions. Through a comprehensive analysis, this research compares Cleantech firms against a matched sample of non-Cleantech firms to discover unique investment preferences. We find that innovation, particularly as indicated by patents pending, plays a vital role in attracting …

Extended-Stability Runge–Kutta Solvers For Neural Ode: Faster, More Stable Training With Predictable Compute, Gavin Lee Goodship, Stephen O’Sullivan, Luis Miralles-Pechuán

Research Outputs: 2025-Present

Neural ordinary differential equations provide a principled continuous depth formulation, yet their practical use is often limited by slow, numerically fragile, and computationally expensive training caused by the weaknesses of standard ODEs solvers. We introduce extended stability Runge Kutta methods, which are explicit fixed step solvers designed to remain stable at much larger step sizes than classical schemes such as RK4 or adaptive methods such as Dormand Prince. By enlarging the stability region of the real axis, these solvers cross the integration horizon with far fewer steps, providing deterministic computation, greatly reduced function evaluation cost, and smoother optimization dynamics. Across …

Video-Dprp: A Differentially Private Approach For Visual Privacy-Preserving Video Human Activity Recognition, Allassan Tchangmena A. Nken, Susan Mckeever, Peter Corcoran, Ihsan Ullah

Research Outputs: 2025-Present

Considerable effort has been made in privacy-preserving video human activity recognition (HAR). Two primary approaches to ensure privacy preservation in Video HAR are differential privacy (DP) and visual privacy. Techniques enforcing DP during training provide strong theoretical privacy guarantees but offer limited capabilities for visual privacy assessment. Conversely, methods such as low-resolution transformations, data obfuscation and adversarial networks, emphasize visual privacy but lack clear theoretical privacy assurances. In this work, we focus on two main objectives: (1) leveraging DP properties to develop a model-free approach for visual privacy in videos and (2) evaluating our proposed technique using both differential privacy …

An Unsupervised Learning Approach To Optimising Tumour Therapy Through Clinical Data Mining, Eleni Rozaki, Christina Skourou, David Fitzpatrick, Michael Amoo, Eoin Minnock, Caroline Hayhurst, Nachi Palaniappan, Mohsen Javadpour

Research Outputs: 2025-Present

Clinical data mining and healthcare analytics enable systematic evaluation of treatment strategies in precision oncology. This study analysed a harmonised multi-centre dataset of 150 patients treated with linac-based stereotactic radiosurgery for vestibular schwannoma across three institutions in Ireland and the UK. A data-driven framework combining descriptive analytics, unsupervised clustering (K-means and Gaussian Mixture Models), and Random Forest modelling was used to assess treatment plan consistency, explore dose–response patterns, and estimate clinical outcomes. Clustering identified four treatment plan groups with distinct profiles of tumour reduction and organ-at-risk exposure. Random Forest models linked these clusters and dosimetric factors with tumour control and …

Application Of Healthcare Data Mining Techniques To Planning For Nursing Length Of Stay In Surgical Departments, Mahdi Yousefi Nejad Attari, Akbar Abbaspour Ghadim, Ali Ala, Vladimir Simic, Domonkos Tinka, Dragan Pamucar

Research Outputs: 2025-Present

Effective allocation of nurse resources in surgical departments is essential for improving patient care and controlling operating costs in a health society. Length of stay (LOS) is the metric that connects clinical workload to staffing decisions, yet ward-level forecasting and its translation into daily nursing schedules remain limited. This study presents a hybrid, data-driven decision-support system that combines machine-learning LOS prediction with Reinforcement Learning (RL) for the surgical ward. A dataset of 137,145 records is used to evaluate Random Forest, Gradient Boosting, Decision Tree, and a Multi-layer Perceptron. Random Forest achieved the most accurate and stable performance (R² = 0.84; …

Interrogating The Interregnum, Chris O'Ralaigh

Research Outputs: 2025-Present

Of the various theoretical concepts utilised to understand our current global conjuncture, one, Antonio Gramsci's interregnum, has increasingly breached both academic and popular consciousness. The evocative power of Gramsci's century-old analysis whereby the dying out of an existing order bears witness to a variety of morbid symptoms seems to speak to our own era in which systemic morbidities are overt and omnipotent. Yet despite a flourishing literature base, no systematic review of the interregnum as a concept has been undertaken. This paper acts to fill that lacuna, offering a review of the key themes which emerge from an interrogation of …