Digital Commons Network^™

Study Of Fire Regimes In Southwestern Australia Using Geospatial Techniques, Ana Do Carmo Carvalho

Theses: Doctorates and Masters

The Northern Jarrah Forest in Southwestern Australia (SWA), part of a global biodiversity hotspot, is home to fire-sensitive tree species such as marri (Corymbia calophylla) and jarrah (Eucalyptus marginata). As climate change intensifies drought and extreme fire events, understanding the drivers of fire severity is increasingly critical. This thesis analyses fire regimes within the Mundaring drinking water catchment to better understand the spatiotemporal complexity of fire severity in relation to fire history and environmental factors.

The thesis commences with a review of three Fire History Databases (FHDs) used in SWA, highlighting significant inconsistencies and data gaps across time and space. …

Development Of Virtual Reality Learning Environments In Science To Engage Secondary Students In Hazardous Activities, Luke Spartalis

Theses: Doctorates and Masters

This research examines the need for change in including hazardous activities in education. As different learning technologies develop, platforms that retain authentic outcomes via virtual reality are needed. The main objective of this research is to examine the inclusion of Virtual Reality Learning Environments (VRLEs) to determine their value in areas that include hazardous conditions. The research considered the ways that VR tools could be optimised to support these activities, as well as considering the challenges of VRLE implementation. The study examined whether VRLE’s allowed for authentic experiences to sufficiently drive an acceptance of VR to complement existing teaching and …

Enhancing Deep Reinforcement Learning With Expert Demonstrations For Mobile Robot Navigation In Unstructured Off-Road Environments, Dulitha Dabare

Theses: Doctorates and Masters

Advancements in the field of Deep Learning has ushered in a boom in autonomous navigation research. Most of the work being conducted in this space, however, has focused on on-road urban navigation scenarios, with unstructured outdoor terrain navigation receiving much more limited attention. Given the wide range of applications that exist for legged and wheeled ground robots in off-road environments in areas such as agriculture, mining and disaster recovery, there is a growing need for research work to improve the navigational capabilities of mobile robots deployed in these challenging environments.

A promising candidate for application to these navigation challenges in …

Patient Experiences Of Receiving Home-Based Immunotherapy Infusions - A Constructivist Grounded Theory Study, Patricia Ann Cook

Theses: Doctorates and Masters

Context: The treatment of cancer and chronic health conditions has been greatly revolutionised via intravenous immunotherapy infusions. Demand, both globally and in Australia, is increasing due to several factors including aging and increased populations, subsequent increases of cancer cases, new immunotherapy indications and increased survival rates.

In Perth, Western Australia, a private service provider commenced delivering a home based immunotherapy infusions model of care as a hospital substitution service provider in 2013 and the service has now been extended across Australia. The safety and efficacy of home-based infusions have been well documented in research, and an increasing number of patients …

Load-Settlement Behaviour Of Tailings Dam Foundation Strengthened Using The Wraparound Geosynthetic Reinforcement Technique, Francis Otieno, Sanjay Kumar Shukla

Research outputs 2022 to 2026

This paper presents a numerical investigation of the load–settlement behaviour of a geosynthetic-reinforced tailings foundation comprised of gold tailings, subjected to the weight of a tailings dam embankment. The study considered varying conditions, including the horizontal and vertical components of the wraparound reinforcement, reinforcement burial depth, and shear strength parameters of the foundation material. A particular focus of this study is to investigate the effect of reinforcement wraparound ends on the settlement behaviour of the foundation using commercially available finite element (FE) software. The reinforcement is a single-layer biaxial woven geotextile, with and without wraparound ends, at varying depths from …

Looking Forward, Reflecting Back: The Promise Of Dispute Resolution To Reform The Criminal Legal System, Cynthia Alkon

Faculty Scholarship

The criminal legal system in the United States is plagued by serious and systemic problems. There have been countless efforts at reform over the last many decades that have included changes in what is a crime, how crimes are punished, how prosecutors do their job, and changes in policing. Yet, despite these efforts, problems such as mass incarceration remain deeply embedded. It is easy to be swept up in pessimism when discussing the criminal legal system. Change is hard, at best incremental, and we seem to be in the beginning of an era of backlash against recent reforms. This is …

Equal Justice & Generative Ai, Milan R. Markovic

Faculty Scholarship

The United States has long suffered from unequal access to justice, with countless low-and middle-income Americans forced to navigate the legal system alone. Recently, prominent judges, lawyers, and scholars have seized on generative AI as a potential corrective. These techno-optimists maintain that ChatGPT and other large language models can demystify the law and address unmet legal needs. Chief Justice John Roberts has proclaimed that AI-based tools "have the welcome potential to smooth out any mismatch between available resources and urgent needs in our court system."

Although AI will be an increasingly important source of legal assistance for underserved populations, the …

Effect Of Traditional And Cluster Set Structures On Bar Path Kinematics During High-Volume Power Clean Training, Tsuyoshi Nagatani, Shayne Vial, Kristina L. Kendall, Paul Comfort, Jiahao Yang, G. Gregory Haff

Research outputs 2022 to 2026

The aim of this study was to examine the effects of traditional (TRAD) and cluster (CLU) set structures on bar path kinematics during a series of high-volume power clean sets, and compare insights gained from discrete versus waveform analysis. Twenty participants completed TRAD or CLU protocols in a randomised, crossover design. Each protocol involved three sets of nine repetitions at 70% of one-repetition maximum. In CLU sets, a 30-second inter-repetition rest was applied. During TRAD sets, peak velocity declined, and significant (p ≤ 0.05) changes were observed in both vertical and horizontal barbell displacement across repetitions, indicating fatigue-related technical alterations. …

Designing And Evaluating Quality Transdisciplinary Work-Integrated Learning: Insights Into Practice, Denise Jackson, Claire Lambert, Sonja Coetzee

Research outputs 2022 to 2026

Higher education’s role in fostering innovation and enacting social change is increasingly important. Transdisciplinary Work-Integrated Learning (TWIL) offers opportunities to prepare students to address societal issues by transcending disciplinary boundaries and collaboratively tackling real-world global challenges. While extensive literature exists on established WIL models, research on the critical aspects of designing, implementing and evaluating impactful TWIL activities remains scarce. This paper draws together insights from 15 TWIL academics across 14 Australian universities, highlighting important design elements such as training for small group collaboration, open-ended projects, design thinking, sustained mentorship and reciprocal partnerships. Emerging challenges related to online delivery, teamwork, scalability, …

Thorium Lung Burdens Of Norm Workers Revisited, Gregory S. Hewson, Martin I. Ralph, Marcus Cattani

Research outputs 2022 to 2026

Historical thorium bioassay data collected from Australian mine workers in the 1990s, including in vivo lung counting and thoron-in-breath (TIB) measurements, were re-evaluated using current dosimetric and biokinetic models. Revised daily thorium intakes from bioassay were compared with previous estimates to assess changes in the dose profile and potential implications for contemporary operations. Reanalysis revealed lower estimates of annual dose, including the number of workers assessed as exceeding 20 mSv. However, it was found that intakes derived from industry personal air sampling (PAS) underestimated intake by up to three-fold. This study determined that sensitive bioassay techniques, such as TIB using …

Harnessing Mono-2-(Methacryloyloxy) Ethyl Succinate Grafting For Robust Micro/Nanoplastic-Resistant Ultrafiltration Membranes, Mohadeseh Najafi, Javad Farahbakhsh, Mitra Golgoli, Michael Johns, Masoumeh Zargar

Research outputs 2022 to 2026

The growing presence of microplastics (MPs) and nanoplastics (NPs) in water systems poses a serious threat to conventional treatment processes, particularly membrane filtration. This study focuses on a surface modification strategy for commercial ultrafiltration (UF) membranes via plasma-induced grafting of mono-2-(methacryloyloxy) ethyl succinate (MMES) to enhance resistance against MP/NPs fouling. The membranes were characterised using advanced analytical techniques, including high-resolution scanning electron microscopy (HRSEM), X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM), confirming successful grafting, increased hydrophilicity, and a more negative surface charge. At optimal conditions of grafting (2 min pretreatment, 0.5 M monomer concentration, and 3 h grafting …

Sparse Gradient Training For Recommender Systems, Yunke Qu, Liang Qu, Tong Chen, Xiangyu Zhao, Jianxin Li, Hongzhi Yin

Research outputs 2022 to 2026

Recommender systems are widely applied in numerous online platforms such as shopping and social media platforms. They typically utilize large embedding tables that map users and items to dense vectors of uniform sizes. As the number of users and items continues to grow, this design leads to significant memory consumption and computational inefficiencies. This challenge is particularly pronounced in scenarios such as federated learning, where model parameters are updated locally on edge devices with limited computational resources before being transmitted to a central server for aggregation. Numerous approaches have been proposed to address this issue, among which embedding pruning methods …

Women In The Australian Mining Industry, Michelle Gander, Fleur Sharafizad, Aglae Hernandez Grande, Heidi Vivian, Mahan Poorhosseinzadeh, Kate Blackwood

Research outputs 2022 to 2026

This report synthesises existing research on women’s participation in the Australian mining industry to identify the structural and cultural factors shaping gender inequality across the sector.

Drawing on research conducted over the past four decades, the report brings together what is currently known about how mining workplaces operate and how organisational practices, work arrangements, and site cultures shape the experiences of women across the sector. While many companies have introduced diversity and inclusion initiatives aimed at improving gender balance, the evidence suggests that challenges persist in areas such as operational roles, leadership pathways, and workplace culture.

Specifically, the report examines …

Energy-Efficient Mixed-Criticality Multicore Systems, Fayyaz Ali, Saud Wasly, Amjad Ali, Shahid Iqbal, Asad Masood Khattak, Bashir Hayat, Shah Khalid

All Works

Balancing energy efficiency with stringent timing guarantees in real-time mixed-criticality systems (MCS) is a key challenge, especially in multicore architectures. This paper introduces a novel energy-aware scheduling framework that integrates dynamic voltage and frequency scaling (DVFS) with a Decreasing-Criticality-Decreasing-Utilization (DCDU) allocation approach. The optimal operating frequencies are obtained at each criticality level; high-criticality tasks are assigned to cores at full operating frequency to maintain timing guarantees, while low-criticality tasks are allocated using worst-case execution times scaled to their optimal frequency. A fixed-priority response-time analysis is used for schedulability in low mode, high mode, and during mode changes. The extensive simulations …

Edge-Aware Ris-Assisted Dynamic Channel Allocation With Lightweight Llm Decision Agent For Interference Mitigation In Low-Altitude Remote Sensing Networks, Safiya Nasser Al-Jaradi, Mohammad Kamrul Hasan, Nabeel Al-Qirim, Shayla Islam, Muhammad Attique Khan, Rashid A. Saeed, Hashim Elshafie, Bishwajeet Kumar Pandey, Khairul Akram Zainol Ariffin

All Works

Low-altitude remote sensing networks are increasingly important for applications, such as environmental monitoring, disaster response, infrastructure inspection, and real-time sensing services. However, when many sensing nodes share limited spectrum resources, severe cochannel interference can degrade communication reliability and delay sensing-data delivery. This challenge becomes more critical in edge-enabled deployments, where control decisions must be made under strict latency, memory, and computational constraints. To address this issue, this article proposes a large language model (LLM)-enhanced edge-aware lightweight reconfigurable intelligent surface (RIS)-assisted dynamic channel allocation (EL-RIS-DCA) framework for interference mitigation in dense low-altitude remote sensing networks. The novelty of the proposed framework …

Lightweight Tinyml-Enhanced Task Offloading In Vanets For Next-Generation Intelligent Transportation Systems, Muhammad Ali, Tariq Qayyum, Asadullah Tariq, Zouheir Trabelsi, Irfan Ud Din, Shabir Ahmed

All Works

Vehicular Ad Hoc Networks (VANETs) face resource constraints, high node mobility, and stringent latency requirements, especially in safety-critical applications such as collision avoidance, path planning, and emergency braking. Task offloading to nearby vehicles or Roadside Units (RSUs) mitigates local computational limits, but dynamic conditions, unreliable nodes, and rapid topology changes complicate dependable node selection. This paper proposes a Tiny Machine Learning (TinyML)-enhanced, credibility-based task offloading framework for real-time decision-making in vehicular networks. RSUs evaluate vehicle reliability through a three-component Credibility Assessment Module: a Task Assignment Component that distributes lightweight test tasks and filters unreliable nodes via TinyML inference; a Verification …

A Preliminary Exploratory Assessment Of Chatgpt To Generating Stride Data Flow Diagrams, Hassan Alsayegh, Mohamed El-Attar

All Works

Threat modeling is a core activity in security-by-design practices, enabling early identification of architectural weaknesses before system implementation. The drawings used during STRIDE analysis are typically Data Flow Diagrams (DFDs), referred to as “STRIDE diagrams” in this paper. STRIDE diagrams provide a visual approach for categorizing security threats; however, constructing accurate STRIDE diagrams require experience and is often time-consuming. Recent advances in Large Language Models (LLMs), such as ChatGPT, raise important questions about their suitability for supporting structured security modeling tasks. This study presents a preliminary exploratory assessment of ChatGPT’s ability to generate, analyse, and iteratively refine STRIDE diagrams from …

Sustainable Paper Production From Date Palm And Reed Leaves Through The Valorization Of Agricultural Waste Products, Imane Belyamani, Alreem Alameri, Jacqueline Soghman

All Works

The environmental consequences of wood-based paper production, including greenhouse gas emissions, have accelerated the search for sustainable alternatives. This study investigates the use of reed and date palm fibers as eco-friendly raw materials for paper production, focusing on starch's influence on their thermal, structural, and mechanical properties. Reed fibers exhibited a higher pulp yield (58.2 %) and lower lignin content (7.8 %) compared to date palm fibers (55.9 % yield, 14.1 % lignin), contributing to papers with smoother textures and greater flexibility. The incorporation of starch into both fiber types resulted in notable performance improvements, though the effects were more …

Conceptualizing A Model For Transforming Academic Search With Retrieval-Augmented Generation, Nikesh Narayanan

All Works

This study conceptualizes the transformative potential of RetrievalAugmented Generation (RAG) in academic research, addressing limitations of traditional search methods reliant on keyword matching, Boolean logic, and metadata analysis. RAG combines precise data retrieval with the generative capabilities of advanced AI models, synthesizing dispersed information into coherent outputs. By bridging retrieval accuracy and contextual generation, RAG offers a framework for providing researchers with comprehensive, nuanced, and up-todate insights tailored to their queries. This article explores the integration of tools like ChatGPT and LangChain to outline a RAGbased system, illustrating its potential to enhance academic discovery by harmonizing natural language processing, semantic …

Optimized Hybrid Beamforming For Ris-Assisted Multi-User Mimo In 6g Mmwave Networks: A Low-Complexity Approach To Spectral Efficiency And Interference Mitigation, Safiya Nasser Al-Jaradi, Mohammad Kamrul Hasan, Nabeel Al-Qirim, Shayla Islam, Thippa Reddy Gadekallu, Hana Mujlid, Hashim Elshafie, Rashid A. Saeed

All Works

The joint optimization of hybrid beamforming and reconfigurable intelligent surface (RIS) phase shifts in multi-user millimeter-wave (mmWave) MIMO systems is a challenging problem, mainly due to high computational complexity and the lack of adaptive interference management. Existing approaches typically rely on fixed Zero-Forcing (ZF) or Maximum-Ratio Transmission (MRT) designs or require iterative optimization with high overhead, limiting their practical use in dense 6G environments. To overcome these challenges, this research proposes a RIS-Aided Adaptive Zero-Forcing and Maximum-Ratio Transmission Hybrid Precoding (RA-ZMHP) framework for 6G mmWave multi-user MIMO systems. The main novelty of the method lies in an adaptive ZF–MRT mixing …

Integrative Machine Learning Of Genetic And Lifestyle Factors For Personalized Skin Health, Yassine Benachour, Lina Maloukh, Barbara Geusens

All Works

Objective: To develop an AI framework that combines genetic, phenotypic, and lifestyle data for profiling skin-health patterns and generating hypothesis-supporting summaries for potential decision support. Methods and procedures: A dataset of 5,254 individuals integrates six genes (FLG, AQP3, MMP-1, MMP-3, SOD2, GPX), six phenotype severities, and 20+ lifestyle factors. Mutation burden and interactions are tested by ANOVA. K-modes clustering identifies four interpretable dermatological profiles within the cohort and is embedded in leakage-free nested cross-validation (train-only selection; test labels from training centroids). Subtypes are predicted from genetics plus lifestyle using an XGBoost (XGB) classifier; explainability uses gain, permutation importance, and SHAP …

Empirically Evaluating The Accessibility Of A Pon-Enable Feature Diagrams Notation By The Red-Green Colorblind Community, Mohamed El-Attar, Sarah Kohail, Rima Grati

All Works

In 2016, an enhanced version of a feature diagram notation developed using the Physics of Notations (PoN) framework was introduced. Empirical evidence demonstrated that this revised notation was more cognitively effective than the original. However, the new notation relies on color, specifically red, which poses accessibility challenges for individuals with red–green color vision deficiency, as they cannot perceive the notation as originally intended. Consequently, the cognitive effectiveness of a red–green–deficient (RGD) version of the new notation relative to the original notation remained unknown. Although the PoN framework specifies several principles that may be satisfied with or without the use of …

Investigating The Impact Of Cyanobacterial Harmful Algal Blooms On Freshwater Bivalves, Destiny Devlin

Theses, Dissertations and Culminating Projects

Harmful algal blooms (HABs) threaten freshwater ecosystems by producing toxins that disrupt aquatic organism functions and pose risks to human health. This study investigated how exposure to toxin-producing cyanobacteria affects the behavior and toxin accumulation of Asian clams (Corbicula fluminea) under controlled laboratory conditions. Asian clams were collected from a freshwater site in New Jersey, maintained in greenhouse bins, and fed either Microcystis novacekii (non-toxin-forming, control N=3) or Microcystis aeruginosa (toxin-forming, experimental N=3) at 100,000 cells/mL for 28 days. Weekly behavioral assays were conducted to track shell opening, burying, clustering, valve closure, foot extension, and time to first opening. Toxin …

Holistic Stormwater Management In The Bound Brook River Basin, New Jersey, Sana Mirza

Theses, Dissertations and Culminating Projects

This dissertation presents a holistic framework for stormwater management in the Bound Brook River Basin, an urban watershed in central New Jersey that faces chronic nutrient enrichment and climate-driven hydrologic changes. The research integrates water-quality trend analysis, hydrologic modeling, and low-impact development (LID) optimization to assess current and projected watershed responses. By combining empirical monitoring data with downscaled climate simulations and spatial prioritization, the study utilizes a holistic approach for stormwater management planning. The first objective was to characterize nutrient dynamics and hydrologic transport pathways for nitrogen, phosphorus, and total suspended solids (TSS) from 2004 to 2019. Using bi-monthly monitoring …

Assessment Of Mechanical Performance And Quality Assurance In Fabricated Aa6061-T6, Anesti Nasi, Kledi Ushe, Klodian Dhoska, Anis Sulejmani, Odhisea Koça, Panagiotis Kyratsis, Aleksandra Petrovic

Babylonian Journal of Mechanical Engineering

This paper focuses on integrated methodology for the experimental mechanical properties of produced AA6061 aluminum alloy, coupled for a rigorous quality assurance framework to validate material reliability for structural applications. The approach combines microstructural analysis, tensile testing analysis, and systematic measurement uncertainty quantification, all performed through the relevant international standards. To ensure statistical reliability, the overall standard uncertainty was computed utilizing the propagation law of uncertainty for k = 2 with a confidence level of roughly 95%. The experimental results yielded a tensile strength of309.4±4.0N/mm2, showing excellent repeatability with a lower relative uncertainty that correspond to 1.3%. These values not …

Religious Riders And The Sherman Act, Bailey Sanders

Faculty Scholarship

Can corporations engage in anticompetitive behavior on the basis of religious belief? While the answer may seem like an obvious no, in fact this question has largely been overlooked. It has hovered at the margins of the debate over religious exemptions: Proponents of religious exemptions have essentially argued that there is no harm in providing such exemptions to businesses because a competitive market will ensure consumers who might be denied services or goods by a religious firm can still obtain those goods and services elsewhere. But what if religiously minded businesses act in ways that are specifically designed to limit …

Oompa 2025.08: A First Cut Of The Toolkit For Object-Oriented Modeling For Planning And Acting, Mark Roberts, David H. Chan, Dana S. Nau, Jamie C. Macbeth

Computer Science: Faculty Publications

OOMPA is a partially implemented Python 3.13+ toolkit for modeling hierarchical planning domains as annotated Python classes, without writing a separate PDDL or HDDL domain file. State properties, actions, and hierarchical methods attach to domain classes via decorator syntax; OOMPA projects the resulting model into a flat dictionary of dictionaries, like the Pyhop family of planners. We describe OOMPA’s motivation and architecture as we demonstrate its use in a restaurant planning domain. There are many unrealized features, so we end with a discussion of limitations and future work.

Rethinking Behavior - Winter 2026, Midwest Symposium For Leadership In Behavior Disorders

ReThinking Behavior Magazine

A magazine for professionals serving children and youth with behavioral needs.

Winter 2026, Volume 9, Issue 2

Formation-Based Ai Ethics: Ethical Formation, Responsibility, And Opportunity Cost In Ai Ecosystems, Maurice Emelu

2026 Faculty Bibliography

Recent efforts in AI ethics have been dominated by the proliferation of high-level principles intended to guide responsible development and deployment. Yet persistent implementation failures suggest that principlism and tool-based approaches alone do not cultivate the moral capacity required to govern sociotechnical systems. This article advances a formation based framework for AI ethics that situates moral agency throughout the developmental conditions of design, use, and the AI lifecycle. Drawing on Aristotelian-MacIntyrean virtue ethics applied to media ecology, and sociotechnical responsibility, the argument reframes AI as a formative environment that shapes patterns of attention, judgment, delegation, and accountability over time. Against …

Grading In The Digital Age: Ai Feedback Versus Professor Feedback, Latoya Russell, Andrew Zeisler, Ronald Mickler Jr.

2026 Faculty Bibliography

Feedback is a cornerstone of academic development, particularly in marketing education, where skill development often requires iteration and applied practice. While instructors spend considerable time providing effective feedback, artificial intelligence (AI) tools can significantly reduce this burden by generating timely, tailored responses. For example, AI-based chatbots can supplement instruction, providing students with timely feedback and reducing instructors’ workload. This study examines how marketing students perceive feedback quality based on its source, specifically whether it is delivered by an AI system or a human instructor. Through a scenario-based experiment, we investigate student perceptions of feedback quality and effectiveness based on the …