Digital Commons Network^™

Leveraging Disparate Wildland Fire Datasets To Address Longstanding Fire Management Questions, Kendra Fallon

Boise State University Theses and Dissertations

While wildfire season is perceived as occurring in the warm months, and expanding, wildfire management is a year-long process. Juxtaposed to wildfire seasons are the reactive seasons of mitigating for post-fire effects, namely first-order effects of potential hydrological impacts in burn footprints, and the proactive implementation of fuels treatments to modify fire behavior to lessen the reactive workload. In this dissertation, I focus on answering lingering questions that are critical to the management of the shoulder seasons of wildfire season. To assist in resource allocation and identification of post-hydrological risks, I present a model identifying the major drivers of soil …

Evaluation Of Graphite And Activated Carbon As Suitable Water Purification Media For In-Situ Resource Utilisation (Isru) On Mars, Ciaran Archenoul

The Plymouth Student Scientist

Eventual human missions to the red planet will require large-scale in-situ resource utilisation to meet their objectives. Perhaps the most critical element for developing a sustainable architecture is propellant production from the products of water electrolysis and atmospheric carbon dioxide. The purpose of this study was to assess how graphitic materials may be used as porous filters to remove solvated ions from Martian water prior to electrolysis, reducing the overall complexity of ISRU systems. The two materials under study were PG25 graphite and activated carbon powder.

A comprehensive three-technique characterisation of both materials was performed, using helium pycnometry, N_{2 …}

Analysis Of Organic Compounds Extracted From Recycled Polypropylene Via Gc-Fid/Ms And Pyr-Gc-Ms For Future Pharmaceutical Applications, India E. Hateley

The Plymouth Student Scientist

A mandatory target for 30% of plastic packaging to be recycled has been proposed by 2030, in order to mitigate the problem of plastic waste being incinerated or deposited in landfills. However, during the recycling process additives are added and with polypropylene being used for plastic packaging and surgical masks, these additives need to be analysed for the presence of contaminants. Examples include VOCs, PAHs, phthalates, and brominated diphenyl’s, all of which have health issues. Two samples of recycled polypropylene pellets were obtained from a national recycling company, along with a reference pellet purchased through Sigma-Aldrich. All pellets underwent ultrasound-assisted …

Method Optimisation And Environmental Analysis Of Methanesulfonic Acid (Msa) In Rainwater By Ion Chromatography, Thomas Levett

The Plymouth Student Scientist

This research optimised a method of analysis for methanesulfonic acid (MSA) alongside common inorganic anions using ion chromatographic (IC) apparatus developed at the University of Plymouth. The aim was to assess whether MSA could be more easily and routinely monitored alongside common rainwater anions. The method’s analytical quality was evaluated through each development stage of the research and its limitations found. Historical rainwater samples collected at Penlee Point, Plymouth, UK (2015–2018) were also used for testing. The method successfully provided detectable ranges of MSA between 0.001 – 5 mg/L for F^-, Cl^-, NO_2-, Br …

Quantification Of Trace Metal(Loids) In The River Seaton, Cornwall, Uk And The Influence Of The South Caradon Mine On Ecological Risk, Bjorn Piñol

The Plymouth Student Scientist

Freshwater quality is critical to the health of aquatic ecosystems and human water security, yet anthropogenic activities, such as historic mining, continue to degrade aquatic systems. While extensive research has examined metal contamination in major rivers like the River Tamar, smaller tributaries affected by legacy mining remain understudied. This study investigates trace metal contamination and its controlling factors in the River Seaton, Cornwall, a small river influenced by historic mining from the South Caradon Mine. Water samples collected from four study sites along the river gradient and a reference site at Siblyback Lake were subjected to ICP-MS analysis and physico-chemical …

Scaling Wind Farm Layout Optimisation To Meet Uk Energy Demands, Grace Richardson

The Plymouth Student Scientist

This research aims to explore the Wind Farm Layout Optimisation Problem (WFLOP) through both single- and multi-objective optimisation, to show that it can be used to create farm layouts that provide enough power for all homes in the UK. We highlight the intricacies of the problem, including the application of different algorithms and models, and the challenges of scaling the models to achieve optimal results. We employ both a Hill Climbing Algorithm (HCA) and an evolutionary algorithm (NSGA-II) to obtain wind farm layouts, and compare these to the well-known results proposed by Mosetti et al. Moreover, we present a novel …

Interpretable Alignment Of Textual Weather Reports With Local Sensor Time Series For Extreme Weather Event Visualization, Juan Luis Garza

Theses and Dissertations

This thesis presents an automated and interpretable pipeline that links natural-language weather narratives with local meteorological sensor time series. Using large language models, NOAA-style event reports are transformed into structured records capturing event type, timing, descriptive context, and uncertainty. Each extracted event is aligned with harmonized temperature, precipitation, and wind measurements from nearby weather stations, enabling systematic comparisons between narrative evidence and observed atmospheric conditions.

Across roughly fifty stations and more than two thousand events, the analyses show that discrepancies between narrative descriptions and sensor behavior arise primarily from spatial separation rather than from temporal offsets, sensor preprocessing artifacts, or …

An Income Subsystem As A Discrete Stochastic Leslie System: A Simulation-Based Approach, Fahd Nii Okantah Cobblah

Electronic Theses and Dissertations

This thesis formulates the household-income engine of an integrated population sim- ulator as a Discrete Stochastic Leslie System (DSLS). The nonnegative state vector nt ∈ Rk + aggregates income, savings, debt, employment, and transfers. (Here, the subscript + denotes the positive cone, i.e., vectors with nonnegative components). Annual evolution is linear in state, stochastic in coefficients: nt+1 = Ttnt + εt, with Tt : Rk + → Rk + cone-preserving. Exogenous macro drivers (inflation, employment, tax, salary inflation, mortgage) are forecast via ARIMA; forecasts multiply entries of Tt, preserving linearity in expectation while introducing realistic temporal correlation. The discrete-event implemented …

Mountain Communities During A Time Of War: A Case Study Of The Hutsul Region In The Carpathian Mountains Of Ukraine, Pavlo Rybaruk

Electronic Theses and Dissertations

This thesis investigates the ethno-ecological technologies employed by the Hutsul people within the highland agrarian economy of the Carpathian Mountains. Over centuries, the Hutsuls have developed ethno-ecological technologies that maintain ecological integrity while supporting community livelihoods.

The study addresses three primary research questions: What are the most important ethno-ecological technologies of the Hutsul highland economy? How might these traditional ethno-ecological practices be applied to economic, agricultural, and tourism development in the Hutsul region? How might these traditional ethno-ecological practices be combined with contemporary approaches to encourage sustainable development in the region?

The research explores the devastating impact of the Russian …

Taxonomy Of Endophytic Fungi Associated With Vallisneria Neotropicalis, Md. Arafat Rashid

Graduate Theses and Dissertations (2019 - present)

This study presents the first comprehensive taxonomic and ecological investigation of endophytic fungi (EF) associated with the submerged aquatic macrophyte Vallisneria neotropicalis in the southern United States. Over a 12 month period, from April 2023 to March 2024, leaf samples were collected from two distinct sites in Mobile Bay, Alabama a disturbed, brackish Causeway location and a cleaner, less impacted site at Meaher State Park. Using culture dependent methods, a total of 257 fungal endophytes were isolated from 1,200 leaf segments. All isolates belonged to the phylum Ascomycota, distributed across 3 classes, 6 orders, 10 families, and 19 taxa. The …

Modeling Flood Risks For Small-Scale Coastal Watershed Across Shared Socioeconomic Pathway Scenarios, Sebastian Loschner

Graduate Theses and Dissertations (2019 - present)

Coastal flooding, driven by the mixture of natural processes and human activities such as precipitation, waves, sea level rise, and urbanization, remains a growing concern. While recent flood-risk studies use IPCC's Shared Socioeconomic Pathways with climate projections to assess future flood exposure, smaller coastal watersheds, < 120,000 acres, remain insufficiently studied. Projected sea level rise is expected to intensify these impacts in smaller systems, potentially causing more severe flooding than reported for larger watersheds. To address this gap, this study used the SRH-2D model integrated with Aquaveo's Surface-water Modeling System to simulate flooding in the lower Fish River basin, Alabama. A coastal watershed sensitive to both riverine and tidal influences. Simulations tested different sea levels based on SSP scenarios corresponding to low, moderate, and high emissions for the years 2050 and 2100. Results indicate that the midcentury scenarios remained even in inundation extent and volume, between 9.9-10.4% compared to the 2020 baseline, the latter scenarios had a wider range in results of between 25.9-50.3% compared to the same baseline. Across scenarios, the most vulnerable and inundated areas of the smaller coastal watershed were the narrow points where upstream flow convene with downstream backwater. These findings highlight the need for futuristic location-specific flood mitigation strategies.

Modeling Aerosol Transport During High Particulate Matter Episodes In El Paso-Juarez Region And Mitigating Mining-Related Emissions Of Rare Earth Elements (Rees) To The Air, Suzan Aranda Luna

Open Access Theses & Dissertations

This dissertation examines the use of the HYSPLIT model to develop a methodology for the transport and dispersion of air masses affecting particulate matter (PM) concentrations in the El Paso Region, and bioleaching experiments as an alternative to mitigating rare-earth concentrations in the air. Chapter 2 describes the study methodology, 3 and 4 cover the modeling methodology using two-representative high PM2.5 episodes, occurring on February 28, 2024, and June 19, 2024, respectively. These sections encompass the analysis of backward trajectories using four different meteorological datasets to build trajectory frequency maps, the exploratory model analysis of modeled outputs from lower to …

Summary Of Pine Valley Area Groundwater Studies, Melissa Stamp, Bethany Neilson, Anna Mcentire, Burdette Barker, Lisa Welsh, Joanna Endter-Wada, Brian Steed

Reports

The Utah Division of Water Resources contracted with Utah State University to document key scientific and policy information related to the current water conflict between Iron and Beaver Counties over the development of the Pine Valley Water Supply Project (PVWSP). The proposed PVWSP would pump groundwater from Pine Valley in Beaver County and pipe it southeast to the Cedar City region of Iron County served by the Central Iron County Water Conservancy District (CICWCD). Numerous concerns about the project have been raised by Beaver County and other interested parties. A number of these concerns are related to different understandings or …

Artificial Intelligence For Reliability: Predictive Health Maintenance And Geolocation In Gps-Denied Environments, Rafael Toche Pizano

Graduate Theses and Dissertations

In this dissertation, we explore the potential of machine learning and deep learning techniques to enhance the performance and robustness of applications across two major domains. By addressing the challenges within these fields, we demonstrate that we can leverage learning algorithms to obtain substantial improvements in accuracy and robustness. First, we tackle a problem in the field of predictive health maintenance. We propose a novel auto encoder and neural network based methodology to predict failure times in complex aviation systems to learn to distinguish between normal and abnormal operational behavior, and use this information to inform the neural network to …

Physics-Guided Strategies For Enhancing Neural Networks Trained With Limited Data, Jose Guadalupe Perez Zamora

Open Access Theses & Dissertations

Deep neural networks excel at a wide range of processing tasks across various disciplines. However, the quantity and quality of data significantly impact network performance. In specialized domains, high-quality datasets are often difficult to gather, interpret, and curate for effective learning. Few-shot learning techniques, including transfer learning, data augmentation, and meta-learning, have emerged to address these constraints.

We propose three physics-guided strategies for enhancing neural networks trained with limited data: (1) combining existing models like LSTMs with Physics-Informed Neural Networks through two-branch architectures that merge their outputs, (2) deriving custom physics-informed data augmentation algorithms to expand limited datasets, and (3) …

Detecting Prescribed Fire, Haying And Grazing Events Via Remote Sensing To Create Grassland Disturbance Landcovers For The Ring-Necked Pheasant (Phasianus Colchicus), Megan Amy Baldissara

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation developed disturbance detection models to fulfill the need for remote sensing landcover products describing grassland structure. The use of landcover products derived from remote sensing is increasing over time in pheasant (Phasianus colchicus) research. Such landcover, however, does not provide relevant pheasant structural habitat information (Chapter 1). Pheasants require tall, high-density grassland for nesting, tall grassland with medium density for brood rearing, and tall grassland for wintering. Time since disturbance can serve as a proxy for structure, as it shapes vegetation by removing biomass and resetting succession. Disturbance is easier to detect than structure with current …

Universal Systems Simulation Via Constraint Hypergraphs With Applications To Digital Twins, John Morris

All Dissertations

The characterization of systems encompasses a variety of modeling frameworks designed to capture specific behaviors and components of various system domains. Whatever the framework, the core elements of a system representation are the information of the system and a description of how that information is related. The relations in deterministic systems are functions, which, when composed to form executable processes, can be used to simulate system data. A declarative modeling framework is one that encodes mechanisms for preparing these simulations within the model structure, allowing an external agent to form the execution processes required for a given context. To date, …

Navigating Ai-Nature Frictions: Autonomous Vehicle Testing And Nature-Based Constraints, Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

In cities, the application of Artificial Intelligence (AI) is being directed towards transforming different aspects of urban life. These applications take material form in urban spaces, with autonomous vehicles (AVs) providing a prominent example. AI systems rely on large volumes of data on their surroundings to refine the algorithms and enhance the accuracy of prediction for operational efficiency and safety. However, such algorithmic learning and execution can present challenges when dealing with the unpredictable, complex, and dynamic aspects of urban spaces. Nature is a paradigmatic example of such unpredictability, because natural phenomena usually defy consistent patterns and precise data-based modelling. …

Pilot-C: Physics-Informed Low-Distortion Optimal Trajectory Compression, Kefei Wu, Baihua Zheng, Weiwei Sun

Research Collection School Of Computing and Information Systems

Location-aware devices continuously generate massive volumes of trajectory data, creating demand for efficient compression. Line simplification is a common solution but typically assumes 2D trajectories and ignores time synchronization and motion continuity. We propose PILOT-C, a novel trajectory compression framework that integrates frequency-domain physics modeling with error-bounded optimization. Unlike existing line simplification methods, PILOT-C supports trajectories in arbitrary dimensions, including 3D, by compressing each spatial axis independently. Evaluated on four real-world datasets, PILOT-C achieves superior performance across multiple dimensions. In terms of compression ratio, PILOT-C outperforms CISED-W, the current state-of-the-art SED-based line simplification algorithm, by an average of 19.2%. For …

Ice Surface Change And Flow Dynamics Analysis Of Sít’ Tlein (Malaspina Glacier) Through Remote Sensing, Victor Devaux-Chupin

Geosciences

Sít’ Tlein, located in southeast Alaska, is the largest piedmont glacier in the world. Periglacial lake expansion, low-lying bed, and proximity to the Pacific Ocean put its glacier lobe at risk of rapid retreat. Its disappearance would equate to removing an area of land about half the size of Rhode Island. Sít’ Tlein exhibits complex ice flow responsible for its iconic folded moraines, and for its heterogeneous ice resupply in its lobe, which occasionally surges. This lobe is gradually mantled by debris and vegetation as the ice flow fades towards its margins, protecting it from melting. This the­ sis is …

Ai-Based Mapping Of Offshore Wind Energy Around The Korean Peninsula Using Sentinel-1 Sar And Numerical Weather Prediction Data, Jason Sung-Uk Joh, Son V. Nghiem, Menas Kafatos, Jay Liu, Jinsoo Kim, Seung Hee Kim

Institute for ECHO Articles and Research

Offshore wind farm projects are being promoted in the seas surrounding the Korean Peninsula to secure renewable energy. To support site selection, offshore wind resource maps were generated using deep neural networks trained on Sentinel-1 SAR imagery, numerical weather prediction data, offshore wind observations, sea surface temperature, and bathymetry. The deep neural network (DNN) framework consisted of six sub-models targeting eastward and northward wind components across three regions—the Yellow Sea, Korea Strait, and East Sea—to account for spatial heterogeneity. The proposed models outperformed existing approaches, achieving mean absolute errors (MAE) ranging from 1.31 to 1.69 m/s and correlation coefficients (CC) …

Transdisciplinary Perspectives On Ai: The Fourth Annual Conference Of The European Culture And Technology Laboratory, Connell Vaughan, Ioana Madalina Moldovan, Silivan Moldovan, Noel Fitzpatrick

Books/Book Chapters

The fourth annual conference of the ECT Lab+ was hosted by Technical University of Cluj-Napoca over two days in October 2024 at the Cluj Innovation Park. The conference brought together experts from the Arts, Humanities, Social Sciences, Technology, and other fields to discuss and reflect on the advent of Artificial Intelligence and how the associated technologies are transforming how we live, work and study. Under the title Transdisciplinary perspectives on AI: Alternative Histories, Current Practices and Possible Futures the conference moved beyond simplistic technophila and technophobia to consider whether we can co-evolve with these new technologies which combine machine learning …

An Objective Method To Locate Shear Lines During The Northeast Monsoon Season In The Philippines, Lyndon Mark P. Olaguera, John A. Manalo, Jun Matsumoto, Faye Abigail T. Cruz, Jose Ramon T. Villarin

SOSE Affiliate: Manila Observatory

The shear line is a narrow zone of maximum horizontal wind shear, typically identified as a confluence zone of low-level wind streams. Previous studies showed that this system can trigger heavy to extreme rainfall events in the Philippines during the northeast monsoon season. However, a research gap remains in objectively identifying and locating this system. Thus, this study develops a detection method that may be used for monitoring and forecasting the location of shear lines. Results show that the gradient of meridional winds in the y-direction (∂V925hPa/∂y), the boundary layer moisture flux convergence, and the 925 hPa relative vorticity may …

Harnessing Hyperspectral Imaging And Deep Learning For Terrestrial Habitat Mapping In Arid Landscapes: A Case Study In Saudi Arabia, Ali Elgendy, Hesham Morgan, Brandon Tran, Rejoice Thomas, Tamer Ismail, Yehya Kh. Shehadeh, Ahmed Elgharib, Ahmed Abdullah Al-Dughairi, Ali El Muburak, Khaled Allam Harhash, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Arid ecosystems remain under-mapped at actionable scales despite their ecological importance. Decision makers lack reliable, high-resolution habitat maps in drylands to prioritize protection and target restoration. This research integrates spaceborne hyperspectral imaging from the Environmental Mapping and Analysis Program (EnMAP) with deep learning semantic segmentation models to produce an updated level of habitat classification based on the International Union for Conservation of Nature (IUCN) for part of the Imam Turki bin Abdullah Royal Reserve, Saudi Arabia. Using ground control points and the full EnMAP spectral cube without band selection, U-Net and DeepLabV3+ architectures were each implemented with VGG19 and ResNet-101 …

Doughnut Economics And Strong Sustainability: Rethinking The Role Of Financial Investment, Isabelle Pierotti

Electronic Theses and Dissertations

This thesis investigates how private investment could align doughnut economic framework. Doughnut economics is a strong sustainability economic framework where the economy operates within planetary boundaries while ensuring social equity. Theories of sustainable development, weak sustainability, and strong sustainability are discussed to provide theoretical context for doughnut economics and mainstream economics. The analysis concludes that conventional, profit maximizing private investment does not support a doughnut economics system by supporting the depletion of natural resources and exacerbating social issues. Sustainable mainstream investment also fails to support a doughnut framework. Lastly, while impact investment is theoretically committed to social and financial returns, …

Archaeological Predictive Meta-Modeling In Pre-Columbian Mexico, Peter Stamm

Electronic Theses and Dissertations

Archaeological Predictive Modeling stands firmly as an important tool for Archaeologists to predict undiscovered sites from civilizations all across the globe. While powerful, this methodology is not without its own set of qualms. Striking a balance between pure a data-driven approach while also observing leading expert theories can be a complicated task. Going further, deciding on the specific domain of features to emphasize or overlook can be a challenge within itself, as one misstep can drastically change the output of model, sometimes for the worst. In addition, creating models that can expose their reasoning process can be rather difficult to …

Future Vision And Action Recommendations, Sondoss Elsawah, Melissa Haeffner, Anthony Jakeman

Environmental Science and Management Faculty Publications and Presentations

Let us imagine a future world where water management is more fully integrated and supported by the science of sociohydrology and related metadisciplines. This is a vision for the future where the social, cultural, environmental, and economic values of water are explicitly considered through the lens of the science–water policy interface. The ultimate value of research will be measured by how much it supports improvements in water resources and hazards management and, in particular, completes and enriches the science–water policy interface.

Correcting Class Imbalance Through Synthetic Training Data And 3d Modeling For Carabid Pitfall Trap Sampling, Blair Mirka

Geography ETDs

Crowdsourced biodiversity data provide an accessible foundation for large-scale ecological monitoring, but class imbalance limits automated species identification, particularly for rare taxa. This research explores the use of synthetic training data generated from 3D models of carabid beetle museum specimens to improve detection and classification performance for underrepresented species in crowdsourced datasets. High-resolution 3D models were created to simulate variation in lighting, orientation, and background. These synthetic images were incorporated into convolutional neural network training datasets at varying synthetic-to-real ratios to assess their impact on classification accuracy. Models were evaluated using controlled pitfall-trap imagery to examine the influence of scene …

Shape: Spatial Health And Population Estimator, Emma M. Von Hoene, Aanya Gupta, Hamdi Kavak, Amira Roess, Taylor Anderson

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling Social Isolation: A Data-Driven Index Function Design And Implementation, Jeremis N. Morales Morales, Carmen Caiseda, Phyllis Muniu, Joshua Atsu, Folashade B. Agusto

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.