Physical Sciences and Mathematics Commons^™

Assessing The Impact Of Parallel Burnout Fires On Flank Rate Of Spread, Erik Borke

Graduate Student Theses, Dissertations, & Professional Papers

The effects of flank-parallel suppression fires on the local rate of spread (ROS) of freely burning headfires through fully cured homogeneous grass fuels are assessed. Data sets include: one thermal image stack of a prescribed burn recorded by drone, and a suite of simulation experiments carried out in Wildland Urban Interface Fire Dynamics Simulator (WFDS). A new approach to computing ROS, curvature proxy driven normals to convex polylines, was developed to carry out this analysis. ROS time series depicting flank acceleration of the prescribed burn and simulation experiments, observable under coarse and fine directional classification schemes respectively, are the primary …

Evaluating The Use Of Environmental Tracers To Reduce Conceptual Model Uncertainty Of Hydrogeologic Models, Andrew Nordberg, Jon Graham, W. Payton Gardner

Graduate Student Theses, Dissertations, & Professional Papers

Environmental tracer concentrations for CFC12, SF6, and tritium are used in groundwater simulations to assess the ability of these tracers to reduce conceptual model uncertainty due to uncertainty of a site’s geologic and recharge characterization. The resulting groundwater simulations are characterized by site-specific hydrologic and geologic data, and with coordination from a field team with years of knowledge about the site. First-order (conceptual) uncertainty is directly addressed by using a stochastic modeling approach for spatial variability of the proposed subsurface configurations. Simulations of environmental tracer concentrations and water levels are used to assess six alternate conceptual models that are based …

Lasso: Listing All Subset Sums Obediently For Evaluating Unbounded Subset Sums, Christopher N. Burgoyne, Travis J. Wheeler

Graduate Student Theses, Dissertations, & Professional Papers

In this study we present a novel algorithm, LASSO, for solving the unbounded and bounded subset sum problem. The LASSO algorithm was designed to solve the unbounded SSP quickly and to return all subsets summing to a target sum. As speed was the highest priority, we benchmarked the run time performance of LASSO against implementations of some common approaches to the bounded SSP, as well as the only comparable implementation for solving the unbounded SSP that we could find. In solving the bounded SSP, our algorithm had a significantly faster run time than the competing algorithms when the target sum …

Sensitivity Of Lidar Derived Fuel Cells To Fire Modeling At Laboratory Scale, Anthony Albert Marcozzi

Graduate Student Theses, Dissertations, & Professional Papers

Computational models of wildfires are an important tool for fire managers and scientists. However, fuel inputs to wildfire models can be difficult to represent with sufficient detail to be both computationally efficient and representative of observations. Recent advances in fuel mapping with airborne and terrestrial laser scanning (LIDAR) techniques present new opportunities to capture variation in fuels within a tree canopy and on a landscape. In this paper, we develop a technique for building 3D representations of vegetation from point clouds created by Terrestrial Laser Scans (TLS). Our voxel based approach can be extended to represent heterogeneous crown fuels as …

A Non-Deterministic Deep Learning Based Surrogate For Ice Sheet Modeling, Hannah Jordan

Graduate Student Theses, Dissertations, & Professional Papers

Surrogate modeling is a new and expanding field in the world of deep learning, providing a computationally inexpensive way to approximate results from computationally demanding high-fidelity simulations. Ice sheet modeling is one of these computationally expensive models, the model used in this study currently requires between 10 and 20 minutes to complete one simulation. While this process is adequate for certain applications, the ability to use sampling approaches to perform statistical inference becomes infeasible. This issue can be overcome by using a surrogate model to approximate the ice sheet model, bringing the time to produce output down to a tenth …

Optimal Construction Of A Layer-Ordered Heap And Its Applications, Jake Pennington

Graduate Student Theses, Dissertations, & Professional Papers

The layer-ordered heap (LOH) is a simple data structure used in algorithms that perform optimal top-$k$ on $X+Y$, algorithms with the best known runtime for top-$k$ on $X_1+X_2+\cdots+X_m$, and the fastest method in practice for computing the most abundant isotopologue peaks in a chemical compound. In the analysis of these algorithms, the rank, $\alpha$, has been treated as a constant and $n$, the size of the array, has been treated as the sole parameter. Here, we explore the algorithmic complexity of LOH construction with $\alpha$ as a parameter, introduce a few algorithms for constructing LOHs, analyze their complexity in both …

Ensemble Protein Inference Evaluation, Kyle Lee Lucke

Graduate Student Theses, Dissertations, & Professional Papers

The Protein inference problem is becoming an increasingly important tool that aids in the characterization of complex proteomes and analysis of complex protein samples. In bottom-up shotgun proteomics experiments the metrics for evaluation (like AUC and calibration error) are based on an often imperfect target-decoy database. These metrics make the inherent assumption that all of the proteins in the target set are present in the sample being analyzed. In general, this is not the case, they are typically a mix of present and absent proteins. To objectively evaluate inference methods, protein standard datasets are used. These datasets are special in …

Soda: An Open-Source Library For Visualizing Biological Sequence Annotation, Jack W. Roddy, Travis J. Wheeler

Graduate Student Theses, Dissertations, & Professional Papers

Genome annotation is the process of identifying and labeling known genetic sequences or features within a genome. Across the various subfields within modern molecular biology, there is a common need for the visualization of such annotations. Genomic data is often visualized on web browser platforms, providing users with easy access to visualization tools without the need for installing any software or, in many cases, underlying datasets. While there exists a broad range of web-based visualization tools, there is, to my knowledge, no lightweight, modern library tailored towards the visualization of genomic data. Instead, developers charged with the task of producing …

Inference Of Surface Velocities From Oblique Time Lapse Photos And Terrestrial Based Lidar At The Helheim Glacier, Franklyn T. Dunbar Ii

Graduate Student Theses, Dissertations, & Professional Papers

Using time dependent observations derived from terrestrial LiDAR and oblique
time-lapse imagery, we demonstrate that a Bayesian approach to glacial motion es-
timation provides a concise way to incorporate multiple data products into a single
motion estimation procedure effectively producing surface velocity estimates with
an associated uncertainty. This approach brings both improved computational effi-
ciency, and greater scalability across observational time-frames when compared to
existing methods. To gauge efficacy, we apply these methods to a set of observa-
tions from the Helheim Glacier, a critical actor in contemporary mass loss trends
observed in the Greenland Ice Sheet. We find that …

Modeling Hydrologic Impacts Of Tribal Water Rights Quantification And Settlement On The Flathead Indian Irrigation Project, Jordan Andrew Jimmie

Graduate Student Theses, Dissertations, & Professional Papers

The Confederated Salish and Kootenai Tribes (CSKT) of the Flathead Reservation are a federally-recognized group of tribes (Kootenai, Salish, and Pend d’Oreille) located in western Montana. On the reservation lies the expansive Flathead Indian Irrigation Project (FIIP), which supplies irrigation water to approximately 127,000 acres of tribal and non-tribal agricultural land. The 1904 Flathead Allotment Act opened “surplus” land to non-native homesteaders without tribal consent, initiating the land ownership fragmentation observed on the reservation today. This legacy, combined with historically unquantified tribal reserved water rights and the antiquated state of the FIIP infrastructure, including water losses from unlined earthen canals, …

A Deep Learning Approach To Mapping Irrigation: U-Net Irrmapper, Thomas Henry Colligan Iv

Graduate Student Theses, Dissertations, & Professional Papers

Accurate maps of irrigation are essential for understanding and managing water resources in light of a warming climate. We present a new method for mapping irrigation and apply it to the state of Montana over the years 2000-2019. The method is based on an ensemble of convolutional neural networks that only rely on raw Landsat surface reflectance data. The ensemble of networks method learns to mask clouds and ignore Landsat 7 scan-line failures without supervision, reducing the need for preprocessing data or feature engineering. Unlike other approaches to mapping irrigation, the method doesn't use other mapping products like the Cropland …

Generating Peptide Mass Spectrometry Ground Truth Data, Jessica L. Henning, Rob Smith

Graduate Student Theses, Dissertations, & Professional Papers

Very few quantitative evaluations exist for precursor mass spectrometry data due to the lack of tools for enabling the manual feature finding necessary to generate this data. Other lacks the ability to capture, edit, save, and view precursor mass spectrometry data. We present JS-MS 2.0, a software suite that provides a dependency-free, browser-based, one click, cross-platform solution for creating precursor ground truth. The software retains the first version’s capacity for loading, viewing, and navigating MS1 data in 2- and 3-D, and adds tools for capturing, editing, saving and viewing isotopic envelope and extracted isotopic chromatogram features. The software can also …

Zero-Knowledge De Novo Algorithms For Analyzing Small Molecules Using Mass Spectrometry, Patrick Anthony Kreitzberg

Graduate Student Theses, Dissertations, & Professional Papers

In the analysis of mass spectra, if a superset of the molecules thought to be in a sample is known a priori, then there are well established techniques for the identification of the molecules such as database search and spectral libraries. Linear molecules are chains of subunits. For example, a peptide is a linear molecule with an “alphabet” of 20 possible amino acid subunits. A peptide of length six will have 20⁶ = 64, 000, 000 different possible outcomes. Small molecules, such as sugars and metabolites, are not constrained to linear structures and may branch. These molecules are …

Utilization Of Various Methods And A Landsat Ndvi/Google Earth Engine Product For Classifying Irrigated Land Cover, Andrew Nemecek

Graduate Student Theses, Dissertations, & Professional Papers

Methods for classifying irrigated land cover are often complex and not quickly reproducible. Further, moderate resolution time-series datasets have been consistently utilized to produce irrigated land cover products over the past decade, and the body of irrigation classification literature contains no examples of subclassification of irrigated land cover by irrigation method. Creation of geospatial irrigated land cover products with higher resolution datasets could improve reliability, and subclassification of irrigation by method could provide better information for hydrologists and climatologists attempting to model the role of irrigation in the surface-ground water cycle and the water-energy balance. This study summarizes a simple, …

Development Of An Open-Source, Custom Environmental Data Logger For Spatially Scalable Data Collection, Tim Anderson

Graduate Student Theses, Dissertations, & Professional Papers

Characterizing the processes that lead to differences in ecosystem productivity and watershed hydrology across complex terrain remains a challenge. This difficulty can be partially attributed to the cost of installing networks of proprietary data loggers that monitor differences in the biophysical factors contributing to vegetation growth or hydrological processes. Studies that aim to compare concurrent time-series data sets across multiple locations must therefore balance the high cost of these data logger systems with the need for spatial resolution in their data. Here, we present the design, implementation, and case study for an open-source “Pinecone” data logger system, released under the …

A Dual State Hierarchical Ensemble Kalman Filter Algorithm, William J. Cook, Jesse Johnson, Marko Maneta, Doug Brinkerhoff

Graduate Student Theses, Dissertations, & Professional Papers

Dynamic models that simulate processes across large geographic locations, such as hydrologic models, are often informed by empirical parameters that are distributed across a geographical area and segmented by geological features such as watersheds. These parameters may be referred to as spatially distributed parameters. Spatially distributed parameters are frequently spatially correlated and any techniques utilized in their calibration ideally incorporate existing spatial hierarchical relationships into their structure. In this paper, a parameter estimation method based on the Dual State Ensemble Kalman Filter called the Dual State Hierarchical Ensemble Kalman Filter (DSHEnKF) is presented. This modified filter is innovative in that …

Optimization Of Simulations In Opensimpplle, Robin Lockwood

Graduate Student Theses, Dissertations, & Professional Papers

Computer software has become an integral tool in exploring scientific concepts and computational models. Models, such as OpenSIMPPLLE, use a complex set of rules developed by experts to predict the impact of fires, disease, and wildlife on large scale landscapes.

OpenSIMPPLLE’s simulations are time-consuming when projecting far into the future. OpenSIMPPLLE needs to execute more efficiently to allow for faster completion of simulations. The increase in speed will also enable users to run simulations with more timesteps in shorter periods. There are plenty of ways to accomplish this.

The work described here identifies three different methods for increasing efficiency. The …

High Dimensional Outlier Detection, Omid Khormali

Graduate Student Theses, Dissertations, & Professional Papers

In statistics and data science, outliers are data points that differ greatly from other observations in a data set. They are important attributes of the data because they can dramatically influence patterns and relationships manifested by non-outliers. It is therefore very important to detect and adequately deal with outliers. Recently, a novel algorithm, the ROMA algorithm, has been proposed [11]. In this paper, we propose a modification of the ROMA algorithm that reduces its computational complexity from $O(n^2 m)$ to $O((n/(2^m-o(1)))^2 m)$ where $n$ is the number of data points and $m$ is the dimension of the space. And as …

Quantifying Effects Of Using Thermally Thin Fuel Approximations On Modelling Fire Propagation In Woody Fuels, David Blasen, Jesse Johnson, William Jolly, Russell Parsons

Graduate Student Theses, Dissertations, & Professional Papers

In this paper, we quantify the effects of the thermally thin fuel approximations commonly made in numerical models that eliminate temperature gradients within a heated object. This assumption is known to affect the modeled ignition and burn behavior, but there is little research on its impact, particularly in larger fuels or in numerical models including moisture and chemical decomposition of fuels.

We begin by comparing modeled to observed ignition times and burn rates. To constrain variability in the material properties of wood and focus on variability caused by fuels assumed to be thermally thin, we conduct experiments using thermogravimetric analysis …

Exploring Population Change Detection By Monitoring Effective Number Of Breeders, Brian Trethewey

Graduate Student Theses, Dissertations, & Professional Papers

Detecting if a population is in decline is an important objective for biologists and conservationists who are monitoring threatened populations. As genetic methods improve effective population size (N_e) and effective number of breeders (N_b) continue to gain popularity as a way to monitor species. Using simulated populations and linkage disequilibrium, we explored detecting population decline through N_b in age structured populations. Through comparisons of sensitivity (1 – false negatives) and specificity (1- false positives) over 1000 replicates, we explored how factors such as starting N_b, number of SNPs, number of individuals …

K-Mer Analysis Pipeline For Classification Of Dna Sequences From Metagenomic Samples, Russell Kaehler

Graduate Student Theses, Dissertations, & Professional Papers

Biological sequence datasets are increasing at a prodigious rate. The volume of data in these datasets surpasses what is observed in many other fields of science. New developments wherein metagenomic DNA from complex bacterial communities is recovered and sequenced are producing a new kind of data known as metagenomic data, which is comprised of DNA fragments from many genomes. Developing a utility to analyze such metagenomic data and predict the sample class from which it originated has many possible implications for ecological and medical applications. Within this document is a description of a series of analytical techniques used to process …

Mirage: A Novel Multiple Protein Sequence Alignment Tool, Alex Nord

Graduate Student Theses, Dissertations, & Professional Papers

A fundamental problem in computational biology is the organization of many related sequences into a multiple sequence alignment (MSA) [2]. MSAs have a range of research applications, such as inferring phylogeny [22] and identifying regions of conserved sequence that indicate functional similarity [18]. In the case of protein isoforms, MSAs are valuable tools for transitively annotating post-translational modifications (PTMs) by enabling information transfer between known PTM sites and the sites that they align to [11].

For protein MSA tools, one challenging biological phenomenon is alternative splicing, wherein identical genomic sequence will differentially select from a subset of available coding regions …

Xic Clustering By Baseyian Network, Kyle J. Handy

Graduate Student Theses, Dissertations, & Professional Papers

No abstract provided.

Modeling The Cryosphere With Fenics, Evan M. Cummings

Graduate Student Theses, Dissertations, & Professional Papers

This manuscript is a collection of problems and solutions related to modeling the cryosphere using the finite element software FEniCS. Included is an introduction to the finite element method; solutions to a variety of problems in one, two, and three dimensions; an overview of popular stabilization techniques for numerically-unstable problems; and an introduction to the governing equations of ice-sheet dynamics with associated FEniCS implementations. The software developed for this project, Cryospheric Problem Solver (CSLVR), is fully open-source and has been designed with the goal of simplifying many common tasks associated with modeling the cryosphere. CSLVR possesses the ability to download …

Chillisource Game Engine Particle System Study, Angela Gross

Graduate Student Theses, Dissertations, & Professional Papers

The majority of modern game engines utilize intricate objects called particle systems which are a collection of many particles that together represent an object without well-defined surfaces. This thesis discusses the results of studying and stressing particle systems within ChilliSource, an open-source game engine written in C++, with the goal of understanding a complex system and exploring possible optimizations that could be made to it. The studies performed were driven by metrics generated with custom profiling classes that kept track of things like the number of particles rendered, how long the engine spent rendering particles, or even how long a …

Synthesis Of Satellite Microwave Observations For Monitoring Global Land-Atmosphere Co2 Exchange, Lucas Alan Jones

Graduate Student Theses, Dissertations, & Professional Papers

This dissertation describes the estimation, error quantification, and incorporation of land surface information from microwave satellite remote sensing for modeling global ecosystem land-atmosphere net CO₂ exchange. Retrieval algorithms were developed for estimating soil moisture, surface water, surface temperature, and vegetation phenology from microwave imagery timeseries. Soil moisture retrievals were merged with model-based soil moisture estimates and incorporated into a light-use efficiency model for vegetation productivity coupled to a soil decomposition model. Results, including state and uncertainty estimates, were evaluated with a global eddy covariance flux tower network and other independent global model- and remote-sensing based products.

Hydraulic Conductivity As A Proxy For Drainage System Connectivity In A Subglacial Hydrology Model, Jacob Z. Downs

Graduate Student Theses, Dissertations, & Professional Papers

The link between subglacial hydrology and basal sliding has prompted work on basal hydrology models with water pressure and storage as prognostic variables. We find that a commonly used model of distributed drainage through linked cavities underpredicts winter water pressure when compared to borehole observations from Issunguata Sermia in Western Central Greenland. Possible causes for this discrepancy including unrealistic model inputs or unconstrained parameters are investigated through a series of modeling experiments on both synthetic and realistic ice sheet geometries. We find that conductivity acts as a proxy for the connectivity of the linked cavity system and should therefore change …

Introduction To Parallel Computation, Clinton Mckay

Graduate Student Theses, Dissertations, & Professional Papers

Introduction to Parallel Computing is a course designed to educate students on how to use the parallel libraries and tools provided by modern operating systems and massively parallel computer graphics hardware.

Using a series of lectures and hands-on exercises. Students will learn about parallel algorithms and concepts that will aid them in analyzing a problem and constructing a parallel solution, if possible, using the tools available to their disposal.

The course consists of lectures, projects, quizzes, and homework. The combination of these components will deliver the necessary domain knowledge to students, test them, and in the process train them to …

An Adaptive Hybrid Method For Link Prediction In Multi-Modal Directed Complex Networks Using The Graph Traversal Pattern, William Lyon

Graduate Student Theses, Dissertations, & Professional Papers

The paper examines the link prediction problem for directed multi-modal complex networks. Specically, a hybrid method combining collaborative filtering and Triadic Closeness methods is developed. The methods are applied to a sample of the GitHub network. Implementation details are discussed, with a focus on design of a scalable system for handilng large data sets. Finally, results of this new method are discussed with no significant improvement over current methods.