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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 …

Greenhouse Gas Flux Response In Biochar- And Compost-Amended Lawn Soils Under Simulated Water Saturation Conditions, Angel Salinas, Chu-Lin Cheng, Engil Pereira, Rafael M. Almeida, James Jihoon Kang

School of Earth, Environmental, & Marine Sciences Faculty Publications

Understanding greenhouse gas emission dynamics in lawn soils is important for improving climate change mitigation strategies in urban and suburban landscapes. In this greenhouse mesocosm study, carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes were measured from 12 turfgrass soil columns arranged in an unreplicated, completely randomized 4 × 3 factorial design. Four amendment treatments (biochar, compost, bio-com [1:1 volume ratio of biochar and compost], and unamended control) were combined with three water-table conditions (full saturation, half saturation, and unsaturated), with a single column representing each treatment combination. Columns were irrigated at 1 cm day−1 for 24 days, …

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 …

Imaging Oxygen Near Implanted Medical Devices Through Tissue With X-Ray And Ultrasound Modulated Luminescence Chemical Imaging, Vigjna Abbaraju

All Dissertations

Oxygen plays a crucial role in stem cell maintenance, tissue regeneration, disease progression, and treatment efficacy. For example, understanding oxygen dynamics within implanted medical devices, such as bone scaffolds, is essential for successful tissue regeneration and can serve as an early indicator of infection. The existing oxygen sensing and imaging techniques are often limited by narrow imaging depth, low spatial resolution in vivo resulting in poor understanding of oxygen dynamics in tissue microenvironments. This dissertation describes the development of implantable sensors using X-ray scintillators and thermochromic leuco dye paired with phosphorescent oxygen dye (PtTFPP) to image oxygen using X-ray luminescent …

Structure And Dynamics Of Associative Polymers Under Quiescent State And Flow, Rosita Sivaraj

All Dissertations

Associative polymers, including ionizable polymers, are widely used in membranes, coatings, fuel cells, energy storage, and other advanced soft materials. Their properties are governed by ionic aggregation and associative interactions, which influence chain mobility, phase behavior, self-assembly, interdiffusion, and flow response. This dissertation employs large-scale molecular dynamics (MD) simulations to investigate the structure, dynamics, phase behavior, interdiffusion, and extensional flow response of ion-containing and associative polymer systems under quiescent and nonequilibrium conditions.

The influence of molecular architecture is first examined by comparing ring and linear associative polymers using the Kremer–Grest bead-spring model. In linear chains, their closed-loop architecture reduces interchain …

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 …

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 …

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, …

Optimizing Urban Forestry Through Green Infrastructure: Tree Health And Water Retention In Ciudad Juarez Rain Gardens, Tomas Rogelio Lizarraga Ruiz

Open Access Theses & Dissertations

Urban green spaces (UGS) in arid regions face significant challenges due to water scarcity and extreme thermal demand. This study evaluates the efficacy of Nature Based Solutions (NBS), rain gardens and median strips, in enhancing the physiological resilience of urban trees in Ciudad Juárez, Mexico. Using a comparative framework, the research monitored a native evergreen (Dermatophyllum secundiflorum) and an introduced deciduous species (Morus sp.) across six planting treatments. Statistical analysis reveals that green infrastructure (GI) acts as a critical physiological accelerant. Trees situated within rain gardens and medians significantly outperformed those in restricted pot and sidewalk settings, maintaining higher stomatal …

Non-Uniform Mixing Of Quantum Walks On The Symmetric Group, Avah Banerjee

Computer Science Faculty Research & Creative Works

It is well-known that classical random walks on regular graphs converge to the uniform distribution. Quantum walks, in their various forms, are quantization's of their corresponding classical random walk processes. Gerhardt and Watrous (2003) demonstrated that continuous-time quantum walks do not converge to the uniform distribution on certain Cayley graphs of the Symmetric group, which by definition are all regular. In this paper, we demonstrate that discrete-time quantum walks, in the sense of quantized Markov chains as introduced by Szegedy (2004), also do not converge to the uniform distribution. We analyze the spectra of the Szegedy walk operators using the …

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 …

A Longitudinal Analysis Of Hospital Consumer Evaluation In Virginia, Tulay Akmandor Inac

Health Services Research Dissertations

Suboptimal patient experience signals a need to improve clinical efficacy, patient safety, and healthcare quality. The COVID-19 pandemic intensified hospital resource and staffing demands, reducing hospitals’ capacity to invest in patient experience improvement. Prior studies remain limited because many lack longitudinal structure and organized theoretical models, making temporal inference difficult and weakening analyses of patient experience disparities. To address these limitations, this dissertation incorporates three studies examining patient experience and pandemic-related effects.

In state-level markets comparable to Virginia, limited research has examined longitudinal patient experience trends across regional hospital systems using HCAHPS scores. The first study uses descriptive trend analysis …

Modeling The Psychological And Technical Factors Influencing The Use Of Artificial Intelligence Tools Among Non-Native Arabic Learners: A Comparative Study In Egypt, Saudi Arabia, And Jordan., Mohammad Odeh, Alaa Al Din Musa, Ahmed Ragab Ali Ghalish, Montaser Adel Sayed Ahmed

All Works

This study aimed to develop a predictive longitudinal model of the psychological and technical factors influencing the use of artificial intelligence tools among non-native Arabic learners (international students) in three Arab countries: Egypt, the Kingdom of Saudi Arabia, and Jordan. The study adopted an extended Technology Acceptance Model (TAM) incorporating two psychological variables: trust in artificial intelligence and artificial intelligence anxiety. A quantitative longitudinal design with two time waves (T1 and T2) over a full academic semester was employed using Hierarchical Multiple Regression Analysis and PROCESS Macro for mediation. The sample consisted of 812 international students from public universities in …

Practical On-Device Intelligence For Resource-Constrained Embedded And Wearable Devices, Xiao Ma

Dissertations and Theses Collection (Open Access)

Embedded and wearable devices increasingly rely on deep neural networks to support intelligent sensing applications directly on the device. However, building practical on-device intelligence remains challenging throughout the deployment lifecycle. Before deployment, models must remain accurate despite severe memory, computation, and energy budgets, and a single device often needs to support multiple sensing applications without deploying a separate model for each application. After deployment, the device continues to operate in changing real-world environments, where shifts in data distribution can degrade the model’s performance over time, so the model must be able to adapt to such shifts efficiently.

The first challenge …

A Comparison Of Ahdrift And Pitfall Traps For Surveying Small Vertebrates, Gabrielle Risko

All-Inclusive List of Electronic Theses and Dissertations

Understanding species occupancy is necessary to inform wildlife management and conservation decisions. To minimize the invasiveness of occupancy studies, some wildlife researchers have deployed game cameras to detect the presence of small vertebrates instead of utilizing stressful traditional live-capture methods. The Adapted Hunt Drift Fence Technique (AHDriFT) is an increasingly popular method for modifying and deploying camera traps to detect small vertebrates; however, no studies have directly compared AHDriFT to traditional pitfall traps operating at the exact same time, even though both are deployed along drift fences to capture small vertebrates. I compared these two methods (pitfall trapping and AHDriFT …

Performance Of The Denitrification-Decomposition Model In Simulating Agronomic Properties And N2o Emissions Under Smallholder Climate-Smart Farming Systems, Esphorn Kibet, Collins M. Musafiri, Milka Kiboi, Onesmus K. Ng'etich, David K. Kosgei, Abdirahman Zeila, Franklin Mairura, Felix K. Ngetich

All Peer-Reviewed Publications

The DeNitrification-DeComposition (DNDC) model is a crucial tool for estimating soil greenhouse gas fluxes and understanding soil-plant interactions. This study evaluates the performance of the DNDC model in simulating soil temperature, moisture, crop yield, and nitrous oxide (N2O) fluxes across different land utilization types in Western Kenya. The land utilization types included: i) agroforestry M (agroforestry with Markhamia lutea, ii) sole sorghum, iii) agroforestry L (agroforestry with Leucaena leucocephala), iv) sole maize, and v) grazing Land, each replicated thrice. Fertilizer and manure were applied as part of the management practices, with manure applied at 2t ha⁻¹. Soil greenhouse …

Magnetic Properties And Ultrafast Spin Dynamics In Quantum Materials, Trung Kien Mac

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern electronics mostly work by moving electric charge, which generates heat and hence wastes energy, especially as devices become smaller and faster. An alternative is to use the spin of electrons (a tiny magnetic property) and related “valley” states in certain atomically thin materials to store and process information more efficiently. This thesis explores how magnetism and spin behavior can be created and measured in a family of ultra-thin materials known as van der Waals quantum materials. Three kinds of materials are studied. First, atomically thin semiconductors are shaped into narrow nanoribbons. Because of their narrow size, their edges can …

Too Hot To Work? Exploring The Average And Seasonal Effects Of Temperature Variability In The Philippine Labour Market, Paolo R. Magnata, Maire Carroline Magante

Economics Department Faculty Publications

Using temperature and employment data covering 16 regions from Q3 2003 to Q1 2022, this study examined the average and seasonal effects of temperature on year-on-year employment growth in the Philippines. Average effects are insignificant while seasonal effects are heterogeneous. During the dry and cool season (Q1), higher temperatures are associated with a temporary 0.0397% increase in employment growth. In contrast, higher temperatures in the dry and hot season (Q2) are associated with a persistent decrease of 0.1361% while higher temperatures during the wet and hot season (Q3) are associated with a persistent increase of 0.1450%, which is primarily driven …

Examples And Evaluation Of Sustainability Research With Tribes, Aaron M. Canter, 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 …

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 …

Hvi-Cidnet+: Beyond Extreme Darkness For Low-Light Image Enhancement, Kangbiao Shi, Xiaowen Ma, Yixu Feng, Tao Hu, Peng Wu, Guansong Pang, Qingsen Yan

Research Collection School Of Computing and Information Systems

Low-Light Image Enhancement (LLIE) aims to recover visually pleasing content and details from degraded low-light images. However, existing RGB-based methods often suffer from color bias and brightness artifacts due to inherent high color sensitivity. Although the HSV color space can decouple brightness and color, it introduces noticeable red and black noise artifacts. To address these challenges, we adopt the Horizontal/Vertical-Intensity (HVI) color space for LLIE, which is defined by the HV color map and learnable intensity. The former enforces small distances for red coordinates to alleviate red noise artifacts, while the latter adaptively compresses low-light regions to suppress black noise …

Task-Aligned Haze Removal With Semantic-Aware Fusion And Contrast Self-Correction, Jinbin Wang, Aiping Yang, Guosong Jiang, Wenlong Yu, Dongwei Ren, Qinghua Hu

Research Collection School Of Computing and Information Systems

Adverse haze conditions introduce complex degradations that obscure scene details and distort structural cues critical for object detection, posing persistent challenges for vision‐based sensing systems. Although existing haze removal methods have achieved notable improvements in visual clarity, their optimisation objectives are often misaligned with downstream detection requirements, leading to limited detection performance in real‐world scenarios. To address this issue, this work proposes a task‐aligned weakly supervised haze removal framework, termed Dehaze4Detection, which explicitly aligns low‐level restoration with high‐level detection objectives. The framework incorporates a Semantic‐Aware Multi‐Scale Fusion Module (SMFM) that embeds pixel‐level semantic knowledge into the dehazing process, enabling selective …

Parameterized Approximation Schemes For Fair Clustering In Doubling Metrics, Xiaoliang Wu, Ting Liang, Zhize Li, Qilong Feng

Research Collection School Of Computing and Information Systems

Fair clustering has garnered considerable attention, with various fairness notions proposed to ensure equitable representation across demographic groups. In this paper, we focus on the k-center problem in bounded doubling metrics under two popular fairness requirements: group fairness and data summarization fairness, referred to Group Fair k-Center (Gf-k-Cen) and Data Summarization Fair k-Center (Dsf-k-Cen), respectively. Both fairness notions extend classical clustering formulation by associating each data point with a demographic label. Motivated by recent advances in parameterized approximation results for fair clustering, we investigate whether these problems admit Fixed-Parameter Tractable (FPT) approximation schemes in bounded doubling metrics. The previous algorithms …

Corruption Is Futile: Hardware-Assisted Multi-User Searchable Encryption, Feng Li, Chengyan Ma, Xiaoguo Li, Pengfei Wu, Lisha Yao, Jianting Ning, Guomin Yang, Jianfeng Ma, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Searchable encryption enables writers to upload encrypted data to an untrusted cloud server, while allowing authorized readers to perform keyword searches over the encrypted content without compromising data privacy. The multi writer/multi-reader (M/M) setting better reflects real-world de ployment requirements because it aligns with the collaborative nature of many modern applications, but introduces substantial challenges in both efficiency and security. The state-of-the art scheme, delegatable searchable encryption (DSE), achieves optimal search time and forward privacy in the M/M setting. Nevertheless, DSE provides only limited security guarantees: search tokens generated by readers reveal the update count of queried keywords, and the …

Medical Firms’ Online Q&A Interactions: Effect Of Language Style On Investor Engagement, Runyu Wang, Keng Siau, Zili Zhang

Research Collection School Of Computing and Information Systems

PurposeThis study aims to investigate how language styles used by medical firms on digital question and answer (Q&A) platforms influence investor engagement. It examines the linguistic characteristics of managerial responses and compares their effects across industries, with a focus on the distinctive demands of medical communication.Design/methodology/approachWe analyze a panel dataset of 1,223 firm-month observations, constructed from 13,549 individual responses provided by 70 medical firms on a major Chinese web-based firm-investor Q&A platform over a 24-month period (2020–2021). Content analysis is used to assess linguistic features, such as first-person usage, uncertainty, understandability and concreteness. A two-way fixed effects model with clustered …

Nanostructured Negative Electron Affinity Gallium Arsenide Photocathodes With Enhanced Quantum Efficiency And Extended Charge Lifetime For Advanced Photoinjectors, Md Aziz Ar Rahman

Physics Theses & Dissertations

This dissertation presents a comprehensive experimental and computational investigation of nanostructured negative electron affinity (NEA) gallium arsenide (GaAs) photocathodes. This work was undertaken to achieve higher quantum efficiency (QE) and longer charge lifetime than conventional flat NEA GaAs electron sources commonly used in photoinjectors. Finite-Difference Time-Domain and charge-transport simulations of three types of nanostructure geometries reveal substantial QE enhancement over flat GaAs via Mie resonance mode excitation. Consequently, the truncated nanocone array (TNCA) photocathodes with heights of 400, 700, and 1000 nm were fabricated and NEA activated via Cs-NF₃ deposition. In a low-voltage ultra-high vacuum chamber with a base pressure …

Sem-Pdpl: Semantic Exposure Graphs For Privacy-Law-Informed Risk Assessment Of Public Social-Media Data, Heba Ismail

All Works

Public social-media content often contains self-disclosed personal attributes that appear low-risk in isolation but become privacy-relevant when linked across posts, platform accounts, or user-level traces. Existing research has advanced privacy-sensitive content detection, de-anonymization analysis, social-media research ethics, and privacy-compliance workflows; however, limited work operationalizes how personal-data disclosures combine structurally and how these structures can be translated into auditable governance actions. This paper proposes SEM-PDPL, a computational, privacy-law-informed risk-assessment framework for modeling public social-media exposure as semantic exposure graphs and mapping graph patterns to controls aligned with the United Arab Emirates Personal Data Protection Law (PDPL) and compatible with GDPR principles. …

Transnational Indigenous Environmental Justice: A Distant Comparative Study Of Nepali And U.S. Environmental Policies And Counter-Archives In Technical Communication, Shankar Paudel

Open Access Theses & Dissertations

This dissertation investigates how institutional communication, state bureaucracy, and Indigenous sovereignty intersect within Rhetoric and Writing Studies (RWS) and Technical and Professional Communication (TPC). Current TPC research increasingly focuses on social justice; however, the field still lacks ethical frameworks to deal with the complicated dynamics of transnational Indigenous Environmental Justice Communication (IEJC). This study addresses this gap by examining how two distinct Indigenous communities - the Tharus of Chitwan, Nepal, and the Ysleta del Sur Pueblo Tigua Indians of El Paso, Texas - communicatively navigate, contest, and resist state environmental policies.

Grounded in decolonial Distant Comparativism, Mestiza Consciousness, Rhetoric of …

From Screening To Risk: Assessment Of Potentially Toxic Elements In Children's Toys Along The El Paso, Tx, U.S.A.-Ciudad Juarez, Chih, Mex Border Region, Jesus Rodriguez-Loya

Open Access Theses & Dissertations

Children are uniquely vulnerable to potentially toxic elements (PTEs), absorbing them more readily than adults and encountering them through the hand-to-mouth behaviors of early childhood. Exposure carries element-specific consequences: lead (Pb) impairs cognitive development with no established safe threshold; cadmium (Cd) damages the kidneys and reduces bone mineralization; arsenic (As) is a recognized carcinogen and developmental neurotoxicant; hexavalent chromium (Cr) is carcinogenic and induces allergic dermatitis; nickel (Ni) is the leading cause of allergic contact dermatitis in children; and excess zinc (Zn) disrupts copper absorption and causes gastrointestinal distress. Toys are a distinctive source of such exposure, yet none had …