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Prediction Of Pasture Condition In The Kimberley Rangelands Of Western Australia Using Simple Classification Tree Models, Ben Nestor, Kath Ryan, Charles Martin, Philip Thomas, Chris Hetherington, Matthew Fletcher, Robert Sudmeyer, Karyn Reeves

Natural Resources Research Articles

Pasture condition assessments assist pastoralists, regulators, and policy makers in making informed decisions around livestock production and the preservation of natural resources in the Kimberley rangelands of Western Australia (WA). Reliable qualitative assessments of pasture condition require assessors with extensive expertise, which means frequent and reproducible assessments can be difficult to achieve. To develop a quantitative approach that can complement existing qualitative assessment approaches in the Kimberley, we investigated the use of simple classification tree models to predict pasture condition using assessment data from the Western Australian Rangeland Monitoring System (WARMS). Quantitative traits were derived from WARMS observation data for …

Mapler: An R Package For Estimating The Impact Of Climate Change On Maple Syrup Production, Matthew T. White

All Graduate Theses and Dissertations, Fall 2023 to Present

Successful maple sap tapping depends on the freeze/thaw cycle (i.e., temperatures fluctuating above/below freezing) during the winter and spring. Climate change threatens to alter the timing and duration of the tapping season. This necessitates research into how maple sap tapping will be impacted by climate change in order to help maple syrup producers prepare for the future. We define a sap day as a day where the freeze/thaw cycle occurred. Using information climate scientists use to predict future temperatures, we calculate how many sap days could occur each year. We develop software to analyze these sap day calculations to determine …

Advantages Of Dynamic Representation For Related Rates Problems In Calculus, Eri Osuna

Electronic Theses, Projects, and Dissertations

Related-rates problems are a standard yet persistently difficult topic in first-semester calculus. Research increasingly recommends dynamic visualization tools such as GeoGebra, but direct comparisons of static and dynamic representations in related-rates settings remain scarce. This qualitative study examines how representation type shapes the quality of students' reasoning and their perceived experience during related-rates problem solving. Six mathematics students who had completed Calculus —a group of four undergraduates and a pair of graduate students—completed a static sliding-ladder task and a dynamic airplane-and-camera task supported by an interactive GeoGebra applet, followed by an interview. Findings indicate that the two representations supported reasoning …

Geodesic Completeness And The Hopf-Rinow Theorem, Christopher Farias

Electronic Theses, Projects, and Dissertations

Differential geometry is concerned with the properties of calculus and geometry on curved n-dimensional manifolds. As a result, thinking about such a space often runs counter to the Euclidean geometer's intuition of distances, angles, and transformations. This thesis aims to build up to proving an important result in the study of Riemannian manifolds: the Hopf-Rinow theorem.

In Chapter 2, we begin by defining what a manifold is and showing that the collection of directional derivatives at a point on the manifold spans a tangent vector space. After defining a basis and a metric for this space, in Chapter 3, we …

Developing Solvent Tolerant Microbial Membranes: Lipid Extraction And Laurdan Fluorescence Approaches For Biofuel Optimization, Gladstone Anku

Electronic Theses and Dissertations

The high demand for sustainable energy has increased interest in advanced biofuels, though production is limited by solvent toxicity to microbial hosts. This study investigated the role of lipid composition in modulating membrane fluidity and solvent tolerance using Bacillus subtilis as a model organism. Five strains were cultured, and membrane lipids were extracted and analyzed using thin-layer chromatography and gas chromatography–mass spectrometry; however, inconsistent results limited compositional characterization. To address this problem, reconstituted vesicles composed of phosphatidylglycerol (PG) and phosphatidylethanolamine (PE) were used as model membranes. Membrane fluidity was assessed using Laurdan fluorescence spectroscopy by measuring generalized polarization (GP) values …

A Large And Robust Legless Lizard (Squamata, Anguinae) From The Gray Fossil Site Of Eastern Tennessee, Justice D. Lamer

Electronic Theses and Dissertations

The early Pliocene Gray Fossil Site in Tennessee preserved an abundance of microfossils, including numerous anguid lizard specimens. This includes the following elements: dentaries, a pterygoid fragment, a jugal, frontals, parietal fragments, dorsal and caudal vertebrae, and many osteoderms. Because these specimens had not been placed taxonomically beyond the subfamily level, comparative anatomy of similar elements from extant anguids and some quantitative data were used to provide more refined identifications. Using these methods, it was determined that a new, robust type of Ophisaurus is represented at the Gray Fossil Site. Important novel features include relatively robust dentaries, fewer but broader …

Efficient Test-Time Retrieval Augmented Generation, Hailong Yin, Bin Zhu, Jingjing Chen, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Although Large Language Models (LLMs) demonstrate significant capabilities, their reliance on parametric knowledge often leads to inaccuracies. Retrieval Augmented Generation (RAG) mitigates this by incorporating external knowledge, but these methods may introduce irrelevant retrieved documents, leading to inaccurate responses. While the integration methods filter out incorrect answers from multiple responses, but lack external knowledge like RAG methods, and their high costs require balancing overhead with performance gains. To address these issues, we propose an Efficient Test-Time Retrieval-Augmented Generation Framework named ET2RAG to improve the performance of LLMs while maintaining efficiency. Specifically, ET2RAG is a training-free method, that first retrieves the …

Student Attitudes And Perceptions Of Proof In Mathematics, Emelin G. Sibrian Marquez

Electronic Theses, Projects, and Dissertations

Traditionally, mathematical proof is viewed primarily as a tool for validation or verification. However, proof holds many other important roles such as discovery, reasoning, explanation, and justification. For many students, these other roles are not always obvious. Those encountering rigorous proof for the first time often find the process abstract, intimidating or disconnected from their previous learning. This disconnect can lead to negative attitudes as students transition from computational mathematics to advanced proof-based mathematics. Utilizing a mixed-methods approach, this study examined undergraduate and graduate mathematics students at a Hispanic-Serving Institution (HSI) in Southern California. We investigated what students perceive the …

Evolution Of Propagator Wakes On The Kolbeinsey Ridge From An Integrated Geophysical Perspective, Ethan Stowell

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Oceanic lithosphere is formed following the extension and rifting of a continent, with new material generated at mid-ocean ridges. While ridges generally spread in the direction of extension, individual spreading centers are offset by perpendicular transform faults that break the ridges into individual segments. Ridge propagation, in which one ridge segment grows at the expense of another’s shortening, has been identified in global investigations as a poorly understood component of axial reorganization. This process leaves propagator wake structures composed of faults and pseudofaults visible as lows in Earth’s gravitational field, and transferred lithosphere with a distorted magnetic signature. This study …

Draft Final Butte Priority Soils Operable Unit Insufficiently Reclaimed Sites Temporary Best Management Practices Work Plan: Bres No. 16 – Curry And Bres No. 50 – Zelia, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Bpsou Grove Gulch Sedimentation Bay Draft Remedial Action Construction Completion Report (Ccr), Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Quantifying Dust Structure In An Elliptical Galaxy Via Optical–Near-Infrared Color Mapping: A Detailed Study Of Ngc 6251, Luke Reed

Theses and Dissertations

The giant elliptical galaxy NGC 6251 is a well-studied active radio galaxy that hosts one of the largest known relativistic jet systems, with a projected size of approximately 3 Mpc. In addition to its large-scale radio structure, the galaxy hosts a prominent circumnuclear dust feature surrounding the active nucleus, previously interpreted as a warped dust disk. This thesis focuses on the inner morphology and dust structure of NGC 6251 using archival Hubble Space Telescope observations obtained with the WFPC2 and NICMOS instruments.

The central structure of the galaxy was investigated across multiple wavelengths through image calibration, PSF modeling and subtraction, …

Ai-Driven Segmentation And Volumetric Response Modeling Of Liver Regions To Radiotherapy, Aashish Chandra Gupta

Dissertations and Theses (Open Access)

In liver-directed radiotherapy (RT), liver regions receiving higher doses typically undergo atrophy while contralateral/adjacent lower-dose regions may exhibit compensatory hypertrophy through regeneration of healthy tissue. Optimizing the RT plan to promote regional hypertrophy while minimizing the risk of developing atrophy has the potential to enhance post-RT liver function and long-term survivorship. However, current clinical practice largely relies on global liver dose-volume metrics during RT-planning, which may obscure favorable dose-response correlation and limit actionable guidance for clinicians. Therefore, we hypothesized that post-RT regional liver response is governed by a combination of region-specific dose-volume and patient clinical features, and that these responses …

Dynamic Spectral Denoising With Global-Context Attention For Multi-Behavior Recommendation, Miaomiao Cai, Yunshan Ma, Fangqi Zhu, Junfeng Fang, Zhijie Zhang, Zhiyong Cheng, Xiang Wang, See-Kiong Ng

Research Collection School Of Computing and Information Systems

Multi-behavior recommendation improves target-behavior predic-tion by exploiting heterogeneous auxiliary feedback (e.g., view,collect, and cart), yet its robustness is often undermined by behavior-dependent noise and inconsistency. We argue that the key bottle-neck is not merely noisy behaviors, but a representation-level failurecaused by two coupled heterogeneities. First, intra-behavior rep-resentation entanglement arises when multi-hop propagationblends incidental signals with true preferences in the embeddingspace. This entanglement renders coarse spatial denoising inef-fective, since it cannot suppress noise without sacrificing weak-but-informative niche signals. Second, inter-behavior reliabilityheterogeneity complicates cross-behavior fusion, as the predic-tive value of auxiliary behaviors varies substantially across usersand contexts. Without reliability calibration, aggregation can …

Success Of New Ideas In Online Platforms: An Idea Network Perspective, Yimei Zhou, Qian Tang, Vincent Z.W. Mack Mack, Shao Yi Liaw

Research Collection School Of Computing and Information Systems

On online platforms, new ideas often emerge by recombining existing ones within idea networks. Unlike traditional knowledge networks, idea networks represent curated, meaning-based associations among ideas, offering a distinct lens on recombination. Drawing upon a hypergraph perspective, we investigate how new idea success depends on their structural and content attributes, and how collaborative participation shapes these attributes. Using data from an ideation platform, we find that both structural embeddedness and bridging benefit new idea success. Content diversity has no direct effect, but it amplifies the benefits of bridging while constraining those of embeddedness. Both crowd contributions and ideator expertise strengthen …

Llm-Based Early Rumor Detection With Imitation Agent, Fengzhu Zeng, Qian Shao, Ling Cheng, Wei Gao, Shih-Fen Cheng, Jing Ma, Cheng Niu

Research Collection School Of Computing and Information Systems

Early Rumor Detection (EARD) aims to identify the earliest point at which a claim can be accurately classified based on a sequence of social media posts. This is especially challenging in data-scarce settings. While Large Language Models (LLMs) perform well in few-shot NLP tasks, they are not well-suited for time-series data and are computationally expensive for both training and inference. In this work, we propose a novel EARD framework that combines an autonomous agent and an LLM-based detection model, where the agent acts as a reliable decision-maker for \textit{early time point determination}, while the LLM serves as a powerful \textit{rumor …

Efficient And Universal Watermarking For Llm-Generated Code Detection, Boquan Li, Zirui Fu, Mengdi Zhang, Peixin Zhang, Jun Sun, Xingmei Wang

Research Collection School Of Computing and Information Systems

Large language models (LLMs) have significantly enhanced the usability of AI-generated code, providing effective assistance to programmers. This advancement also raises ethical and legal concerns, such as academic dishonesty and the generation of malicious code. For accountability, it is imperative to detect whether a piece of code is AI-generated. Watermarking is broadly considered a promising solution and has been successfully applied to identify LLM-generated text. However, existing efforts on code are far from ideal, suffering from limited universality and excessive time and memory consumption. In this work, we propose a plugand- play watermarking approach for AI-generated code detection, named ACW …

When The Best-Fit Model Is Not Best: The Glass Slipper Fallacy And Latent Growth Mixture Modelling, Jonathan L. Chia, Markus Wettstein, Andree Hartanto

Research Collection School of Social Sciences

Despite the use of latent growth mixture modelling (LGMM) to study longitudinal changes, existing practices may inadvertently impede this very investigation. Although subgroup trajectories may theoretically differ in their structure (e.g., some subgroups being linear, some curvilinear), the current convention advocates overreliance on the baseline model to derive subsequent profile trajectories, which may obscure these structural differences. In this article, we provide a brief description of extant LGMM practices, after which we explicate the pitfalls of the current approach. Finally, we provide a principled approach for LGMM research moving forward. Specifically, we recommend specifying a set of theoretically plausible models …

Artificial Intelligence (Ai) In Forensic Psychology: An Umbrella Review Of Potentials And Pitfalls, Ysabel Thereze Ang Guevarra, Nur Eva Alisha Binte Mohamed Hisham, Andree Hartanto

Research Collection School of Social Sciences

Artificial intelligence (AI) is becoming increasingly embedded within forensic psychological practice, shaping how criminal risk, legal responsibility and public safety are assessed. AI tools are now used in recidivism prediction, behavioural analysis, deception detection and investigative support, high-stakes domains where errors can have profound consequences. Despite this rapid adoption, the existing literature remains fragmented, with most reviews confined to narrow subdomains and offering limited integrated synthesis of AI′s broader role in forensic psychology. Thus, this umbrella review addresses this gap by synthesising findings from 43 reviews obtained from five major databases, namely EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus and Web …

Caring With Ai: The Efficacy Of A Customised Chatgpt-Delivered Self-Compassion Intervention On College Students' Well-Being And Academic Functioning, Tracy Xi Chen, Chi-Ying Cheng, Andree Hartanto

Research Collection School of Social Sciences

College students face various challenges, including academic pressure, social stress, and the transition into adulthood, which can lead to increased anxiety and other mental health issues. By recognizing personal struggles as part of a shared human experience and responding with kindness, self-compassion serves as a powerful strategy for enhancing resilience, facilitating better well-being and performance outcomes. Although effective, Compassion-Focused Therapy often requires substantial resources and time, limiting its applicability to college students. To overcome these barriers, the current study designed and evaluated Your Self-Compassion Companion, a ChatGPT-powered AI chatbot intervention grounded in self-compassion theory and delivered over three weekly 20-min …

Technique-Level Normalization For Cybersecurity Intelligence: An Empirical Evaluation Of Att&Ck Attribution From Hids Alerts Using Fine-Tuned Transformers And Metadata Re-Ranking, Emad Sherif

International Journal of Cybersecurity Intelligence & Cybercrime

Cybercrime investigations increasingly depend on the ability to interpret large volumes of automated security events. For organizations without dedicated security operations centres, a situation common among small and medium enterprises, the manual translation of raw alerts into structured threat intelligence represents a critical bottleneck that slows investigative triage and limits cross-case comparability. This paper evaluates an automated enrichment pipeline designed to address this bottleneck by mapping security events to standardised adversary behaviour labels drawn from the MITRE ATT&CK framework, supporting both operational response and cybercrime investigation workflows. We compare three pipeline configurations, a general-purpose encoder model, a cybersecurity domain-adapted variant, …

Evaluation Of Dredged Sediments As A Partial Replacement For Fine Aggregate In Mortar And Concrete, Ashish Gautam

Graduate Theses and Dissertations (2019 - present)

The feasibility of using dredged sediment from the Mobile River as a partial replacement for fine aggregate in mortar and concrete was investigated through a series of laboratory characterization and performance evaluation. Three dredged sediment samples (A, B and C) were initially examined, and Sample A was selected for further evaluation due to its closer resemblance to natural fine aggregate. This sample exhibited lower moisture content, higher sand equivalent values, higher specific gravity, and lower absorption. Mortar mixtures with 0, 10, 20, 30, 50, 75 and 100% dredged sediment replacement showed decreasing workability as the replacement level increased. The 20% …

Alfred Russel Wallace Notes 42: How Accurate Are The Transcriptions Presented At The Alfred Russel Wallace Page Website?, Charles H. Smith

Faculty/Staff Personal Papers

A look is taken at the level of accuracy displayed by the transcriptions of Wallace writings offered at the Alfred Russel Wallace Page website, as determined by a ChatGPT analysis.

Lessons From The Club Homeschool Capstone: Testing, Data Discipline, And The Computer Science Curriculum, Shane Brown

University Honors Theses

This thesis looks at the CLUB Homeschool Capstone project to argue that Portland State University's Computer Science curriculum should introduce testing and data quality discipline earlier and more intentionally than it does now. As team lead of a seven-person team, I coordinated sprint planning, communicated with the sponsor, and developed custom Discourse plugins that enhanced an existing forum platform instead of creating a separate application database, as requested by the sponsor. The project's requirements document called for a formal testing plan, but our team lacked the practical experience to implement one. This gap became evident through my internships as a …

Indigenous Community Research Opportunities, Sharon Hausam, Aaron M. Canter

Faculty Publications

This is a working paper produced as part of National Science Foundation project #2115169, “Transforming Rural-Urban Systems: Trajectories for Sustainability in the Intermountain West,” known as the “Intermountain West Transformation Network” (TN), led by the University of New Mexico with institutional partners at three additional universities in New Mexico, two in Arizona, and one each in Utah, Colorado, and Washington. The TN’s Indigenous and Tribal engagement was supported through a contract with Dr. Sharon Hausam, additional work by Aaron M. Canter, coordination with Dr. Lani Tsinnajinnie, and an Advisory Committee on Indigenous Information Needs primarily comprised of Indigenous representatives in …

Opportunities For Leadership In Indigenous And Tribally Engaged Research At The University Of New Mexico, Sharon Hausam

Faculty Publications

This is a working paper produced as part of National Science Foundation project #2115169, “Transforming Rural-Urban Systems: Trajectories for Sustainability in the Intermountain West,” known as the “Intermountain West Transformation Network” (TN), led by the University of New Mexico with institutional partners at three additional universities in New Mexico, two in Arizona, and one each in Utah, Colorado, and Washington. The TN’s Indigenous and Tribal engagement was supported through a contract with Dr. Sharon Hausam, additional work by Aaron M. Canter, coordination with Dr. Lani Tsinnajinnie, and an Advisory Committee on Indigenous Information Needs primarily comprised of Indigenous representatives in …

Modeling Mean And Variability Of Anxiety In Ecological Momentary Assessment Data Using Mixed-Effects Location–Scale Models, Trenzy Odero

Electronic Theses and Dissertations

Ecological Momentary Assessment is a method of collecting repeated measures of people in real time within natural environments. This results in hierarchical data that has a significant amount of variation at the person level. The traditional linear mixedeffects models assume that the residual variance is constant, which might not be true when the residual variance varies among individuals as well as in time. This thesis uses mixed-effects location-scale (MELS) models to model the mean and variance of an EMA outcome together. By introducing the possibility of variability in residual variance within and across individuals and with covariates, the MELS framework …

Human-Centered Electric Vehicle Adoption Framework For Smart Mobility: Modeling Perceived Range And Charging Anxiety As A Psychological Barrier, Fatemeh Nazari, Abolfazl (Kouros) Mohammadian, Thomas Stephens

Civil Engineering Faculty Publications

Electric vehicles (EVs) offer a transformative pathway toward reducing the environmental, economic, and health-related externalities of internal combustion engine vehicles in urban settings. Despite substantial advances in battery technology, charging infrastructure expansion, and supportive policy incentives, EV penetration remains limited which poses challenges for smart and sustainable mobility planning. A critical yet insufficiently modeled barrier to adoption lies in the psychological perceptions surrounding electric driving range and charging reliability, which is commonly framed as “range anxiety,” but more broadly reflecting perceived range and charging anxiety. To address this gap, this study introduces a latent psychological construct capturing individuals’ perceived range …

Enabling Multi-Task Neural Network Inference On Heterogeneous Edge Devices, Redwanul Islam Arif

Master's Theses

Deep neural networks are increasingly required to run on the devices that generate the data. If such a device must perform more than one task, the standard practice is deploying one model per task, which makes memory grow linearly with task count, which is unacceptable when the entire budget is kilobytes. This thesis asks one question in three settings: how much capability can a network acquire without incurring deployment cost?

The first study takes an ImageNet-pretrained ResNet-18, sweeps the branch point across every residual stage and the classification-head depth across one, ten, and twenty layers, and deploys the resulting multi-head …

Federated Learning For Early Medical Diagnosis: Enhanced Diabetic Retinopathy Detection In Smart Healthcare, Mohammad Nasajpour Esfahani

Master's Theses

This thesis investigates the role of federated learning as a privacy-preserving solution for modern healthcare challenges. In traditional machine learning, sensitive medical data must be centralized for model training, raising concerns about privacy, security, and regulatory compliance. Federated learning offers an alternative by allowing hospitals, clinics, and personal health devices to collaboratively train shared models without exchanging raw patient data. The study first explores how federated learning is being used across various healthcare domains, including cancer detection, medical imaging, and disease prediction— highlighting its potential to support secure collaboration across institutions. It addresses key benefits such as data privacy, scalability, …