Physical Sciences and Mathematics Commons^™

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 …

Diagenesis Of The Lower Permian Wolfcamp Formation, West Texas: Implications For Reservoir Quality In The Midland Basin, Kory John Talcott

Graduate Student Theses, Dissertations, & Professional Papers

This study focuses on documenting the diagenesis and pore evolution within the lower Permian Wolfcamp B Formation in two producing wells from the Midland Basin of west Texas. Both wells are located near the northeastern margin of the Midland basin, with well A located proximal to the basin margin and well B located about 20km down depositional dip. The entire Wolfcamp B interval has been cored from both wells.

In both wells, the Wolfcamp B consists of calcareous and siliceous mudstone, skeletal wackestone, packstone, grainstone, rudstone, and floatstone facies that were deposited below wave base by a combination of suspension …

Super-Resolution Imaging Of Remote Sensed Brightness Temperature Using A Convolutional Neural Network, Kellen A. Donahue

Graduate Student Theses, Dissertations, & Professional Papers

Steady improvements to the instruments used in remote sensing has led to much higher resolution data, often contemporaneous with lower resolution instruments that continue to collect data. There is a clear opportunity to reconcile recent high resolution satellite data with the lower resolution data of the past. Super-resolution (SR) imaging is a technique that increases the spatial resolution of image data by training statistical methods on simultaneously occurring lower and higher resolution data sets. The special sensor microwave/imager (SSMI) and advanced microwave scanning radiometer (AMSR2) brightness temperature data products are well suited to super-resolution imaging, and SR can be used …

Building Bridges: How Collaboration Is Addressing Wildlife-Vehicle Conflicts In Montana's Upper Yellowstone Watershed, Daniel Phelps Anderson

Graduate Student Theses, Dissertations, & Professional Papers

In my first semester of graduate studies at the University of Montana – Fall, 2019 – I was given an assignment from one of my professors to research a “landscape-scale” conflict of my choosing and compose a professional memo that could be sent to key influencers or stakeholders tied to the issue. Naturally, I directed my attention to a community I know and love, the Upper Yellowstone, and a conflict that is ubiquitous across the West: Wildlife-Vehicle Conflicts (WVCs).

In the pages that follow I describe how Yellowstone Safe Passages came to be, who is involved, and the steps we …

Relating Streamflow Discharge To Surface Elastic Response Under Hydrologic Loading Using Single Gps Vertical Displacement And The Storage-Discharge Relationship At Local Watershed Scales, Noah B. Clayton

Graduate Student Theses, Dissertations, & Professional Papers

Uncertainties associated with climate change and increasing demands for water resources require better methods for estimating water availability at small to intermediate watershed scales (<1500 km²). Temporal changes in watershed storage and transport across various watersheds in the western U.S. were investigated using the hydrologic loading signal from GPS vertical displacements as a proxy for changes in watershed total terrestrial storage. GPS vertical displacement and streamflow discharge relationships were analyzed at daily to monthly temporal resolution. Stream connected storage changes were inferred using discharge using a first-order dynamical system model. Storage inferred from discharge, GPS vertical displacement and storage …

A Monte-Carlo Analysis Of Monetary Impact Of Mega Data Breaches, Mustafa Canan, Omer Ilker Poyraz, Anthony Akil

Engineering Management & Systems Engineering Faculty Publications

The monetary impact of mega data breaches has been a significant concern for enterprises. The study of data breach risk assessment is a necessity for organizations to have effective cybersecurity risk management. Due to the lack of available data, it is not easy to obtain a comprehensive understanding of the interactions among factors that affect the cost of mega data breaches. The Monte Carlo analysis results were used to explicate the interactions among independent variables and emerging patterns in the variation of the total data breach cost. The findings of this study are as follows: The total data breach cost …

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 …

A Review And Evaluation Of Techniques For Improved Feature Detection In Mass Spectrometry Data, Annika R. Tostengard, Rob Smith

Graduate Student Theses, Dissertations, & Professional Papers

Mass spectrometry (MS) is used in analysis of chemical samples to identify the molecules present and their quantities. This analytical technique has applications in many fields, from pharmacology to space exploration. Its impacts on medicine are particularly significant, since MS aids in the identification of molecules associated with disease; for instance, in proteomics, MS allows researchers to identify proteins that are associated with autoimmune disorders, cancers, and other conditions. Since the applications are so wide-ranging and the tool is ubiquitous across so many fields, it is critical that the analytical methods used to collect data are sound.

Data analysis in …

Human Characteristics Impact On Strategic Decisions In A Human-In-The-Loop Simulation, Andrew J. Collins, Shieda Etemadidavan

Engineering Management & Systems Engineering Faculty Publications

In this paper, a hybrid simulation model of the agent-based model and cooperative game theory is used in a human-in-the-loop experiment to study the effect of human demographic characteristics in situations where they make strategic coalition decisions. Agent-based modeling (ABM) is a computational method that can reveal emergent phenomenon from interactions between agents in an environment. It has been suggested in organizational psychology that ABM could model human behavior more holistically than other modeling methods. Cooperative game theory is a method that models strategic coalitions formation. Three characteristics (age, education, and gender) were considered in the experiment to see if …

Blockchain For A Resilient, Efficient, And Effective Supply Chain, Evidence From Cases, Adrian Gheorghe, Farinaz Sabz Ali Pour, Unal Tatar, Omer Faruk Keskin

Engineering Management & Systems Engineering Faculty Publications

In the modern acquisition, it is unrealistic to consider single entities as producing and delivering a product independently. Acquisitions usually take place through supply networks. Resiliency, efficiency, and effectiveness of supply networks directly contribute to the acquisition system's resiliency, efficiency, and effectiveness. All the involved firms form a part of a supply network essential to producing the product or service. The decision-makers have to look for new methodologies for supply chain management. Blockchain technology introduces new methods of decentralization and delegation of services, which can transform supply chains and result in a more resilient, efficient, and effective supply chain. This …

A Blockchain-Enabled Model To Enhance Disaster Aids Network Resilience, Farinaz Sabz Ali Pour, Paul Niculescu-Mizil Gheorghe

Engineering Management & Systems Engineering Faculty Publications

The disaster area is a true dynamic environment. Lack of accurate information from the affected area create several challenges in distributing the supplies. The success of a disaster response network is based on collaboration, coordination, sovereignty, and equality in relief distribution. Therefore, a trust-based dynamic communication system is required to facilitate the interactions, enhance the knowledge for the relief operation, prioritize, and coordinate the goods distribution. One of the promising innovative technologies is blockchain technology which enables transparent, secure, and real-time information exchange and automation through smart contracts in a distributed technological ecosystem. This study aims to analyze the application …

Enhancing Cyberweapon Effectiveness Methodology With Se Modeling Techniques: Both For Offense And Defense, C. Ariel Pinto, Matthew Zurasky, Fatine Elakramine, Safae El Amrani, Raed M. Jaradat, Chad Kerr, Vidanelage L. Dayarathna

Engineering Management & Systems Engineering Faculty Publications

A recent cyberweapons effectiveness methodology clearly provides a parallel but distinct process from that of kinetic weapons – both for defense and offense purposes. This methodology promotes consistency and improves cyberweapon system evaluation accuracy – for both offensive and defensive postures. However, integrating this cyberweapons effectiveness methodology into the design phase and operations phase of weapons systems development is still a challenge. The paper explores several systems engineering modeling techniques (e.g., SysML) and how they can be leveraged towards an enhanced effectiveness methodology. It highlights how failure mode analyses (e.g., FMEA) can facilitate cyber damage determination and target assessment, how …

Interactive Agent-Based Simulation For Experimentation: A Case Study With Cooperatve Game Theory, Andrew J. Collins, Sheida Etemadidavan

Engineering Management & Systems Engineering Faculty Publications

Incorporating human behavior is a current challenge for agent-based modeling and simulation (ABMS). Human behavior includes many different aspects depending on the scenario considered. The scenario context of this paper is strategic coalition formation, which is traditionally modeled using cooperative game theory, but we use ABMS instead; as such, it needs to be validated. One approach to validation is to compare the recorded behavior of humans to what was observed in our simulation. We suggest that using an interactive simulation is a good approach to collecting the necessary human behavior data because the humans would be playing in precisely the …

Ship Deck Segmentation In Engineering Document Using Generative Adversarial Networks, Mohammad Shahab Uddin, Raphael Pamie-George, Daron Wilkins, Andres Sousa Poza, Mustafa Canan, Samuel Kovacic, Jiang Li

Engineering Management & Systems Engineering Faculty Publications

Generative adversarial networks (GANs) have become very popular in recent years. GANs have proved to be successful in different computer vision tasks including image-translation, image super-resolution etc. In this paper, we have used GAN models for ship deck segmentation. We have used 2D scanned raster images of ship decks provided by US Navy Military Sealift Command (MSC) to extract necessary information including ship walls, objects etc. Our segmentation results will be helpful to get vector and 3D image of a ship that can be later used for maintenance of the ship. We applied the trained models to engineering documents provided …

Novel Statistical Analysis In The Context Of A Comprehensive Needs Assessment For Secondary Stem Recruitment, Norou Diawara, Sarah Ferguson, Melva Grant, Kumer Das

Mathematics & Statistics Faculty Publications

There is a myriad of career opportunities stemming from science, technology, engineering, and mathematics (STEM) disciplines. In addition to careers in corporate settings, teaching is a viable career option for individuals pursuing degrees in STEM disciplines. With national shortages of secondary STEM teachers, efforts to recruit, train, and retain quality STEM teachers is greatly important. Prior to exploring ways to attract potential STEM teacher candidates to pursue teacher training programs, it is important to understand the perceived value that potential recruits place on STEM careers, disciplines, and the teaching profession. The purpose of this study was to explore students’ perceptions …

Forest Policies And Adaptation To Climate Change In Maine: Stakeholder Perceptions And Recommendations, Alyssa R. Soucy, Sandra De Urioste-Stone, Ivan J. Fernandez, Aaron Weiskittel, Parinaz Rahimzadeh-Bajgiran, Tom Doak

Maine Policy Review

Socioeconomic pressures require forest management to address the impacts of climate change. However, we must ask, Are current forest policies sufficient to deal with the impacts of climate change? Here, we report on two surveys of forest stakeholders in Maine including woodlot owners and forestry professionals and discuss their perceptions of the barriers to climate change adaptation. We conclude with several policy directions including reevaluating existing policies, expanding incentivebased policies, integrating adaptation efforts into mitigation efforts, and increasing communication and outreach.

Open Data From The First And Second Observing Runs Of Advanced Ligo And Advanced Virgo, R. Abbott, T. D. Abbott, S. Abraham, Fausto Acernese, Teviet Creighton, Mario C. Diaz, Volker Quetschke, Malik Rakhmanov, Karla E. Ramirez, Palash K. Roy, Wenhui Wang, Adam Zadrozny

Physics and Astronomy Faculty Publications and Presentations

Advanced LIGO and Advanced Virgo are monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are gravitational-wave strain time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software.

Ligo Detector Characterization In The Second And Third Observing Runs, D. Davis, J. S. Areeda, B. K. Berger, R. Bruntz, A. Effler, R. C. Essick, R. P. Fisher, B. Martinez, Karla E. Ramirez, P. Godwin

Physics and Astronomy Faculty Publications and Presentations

The characterization of the Advanced LIGO detectors in the second and third observing runs has increased the sensitivity of the instruments, allowing for a higher number of detectable gravitational-wave signals, and provided confirmation of all observed gravitational-wave events. In this work, we present the methods used to characterize the LIGO detectors and curate the publicly available datasets, including the LIGO strain data and data quality products. We describe the essential role of these datasets in LIGO–Virgo Collaboration analyses of gravitational-waves from both transient and persistent sources and include details on the provenance of these datasets in order to support analyses …

An Algorithm To Compute Cvts For Finitely Generated Cantor Distributions, Carl P. Dettmann, Mrinal Kanti Roychowdhury

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Centroidal Voronoi tessellations (CVTs) are Voronoi tessellations of a region such that the generating points of the tessellations are also the centroids of the corresponding Voronoi regions with respect to a given probability measure. CVT is a fundamental notion that has a wide spectrum of applications in computational science and engineering. In this paper, an algorithm is given to obtain the CVTs with n-generators to level m, for any positive integers m and n, of any Cantor set generated by a pair of self-similar mappings given by S1(x)=r1x and S2(x)=r2x+(1−r2) for x∈R, where r1,r2>0 and r1+r20 and p1+p2=1.

Analysis Of Intervention Effectiveness Using Early Outbreak Transmission Dynamics To Guide Future Pandemic Management And Decision-Making In Kuwait, Michael G. Tyshenko, Tamer Oraby, Joseph C. Longenecker, Harri Vainio, Janvier Gasana, Walid Q. Alali, Mohammad Alseaidan, Susie Elsaadany, Mustafa Al-Zoughool

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a World Health Organization designated pandemic that can result in severe symptoms and death that disproportionately affects older patients or those with comorbidities. Kuwait reported its first imported cases of COVID-19 on February 24, 2020. Analysis of data from the first three months of community transmission of the COVID-19 outbreak in Kuwait can provide important guidance for decision-making when dealing with future SARS-CoV-2 epidemic wave management. The analysis of intervention scenarios can help to evaluate the possible impacts of various outbreak control measures going forward which aim to reduce the effective reproduction …

Internet-Based Cognitive–Behavioural Therapy For Tinnitus: Secondary Analysis To Examine Predictors Of Outcomes, Hansapani Rodrigo, Eldré W. Beukes, Gerhard Andersson, Vinaya Manchaiah

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

Objectives The current study examined predictors of outcomes of internet-based cognitive–behavioural therapy (ICBT) for individuals with tinnitus.

Design Secondary analysis of intervention studies.

Setting Internet-based guided tinnitus intervention provided in the UK.

Participants 228 individuals who underwent ICBT.

Interventions ICBT.

Primary and secondary outcome measures The key predictor variables included demographic, tinnitus, hearing-related and treatment-related variables as well as clinical factors (eg, anxiety, depression, insomnia), which can have an impact on the treatment outcome. A 13-point reduction in Tinnitus Functional Index (TFI) scores has been defined as a successful outcome.

Results Of the 228 subjects who were included in the …

Identifying The Microphysical Sensitivities Of Mesoscale And Synoptic Precipitation Using An Ensemble Framework, Lauriana Gaudet

Legacy Theses & Dissertations (2009 - 2024)

Through ensemble sensitivity analysis, this dissertation aims to identify the amount of forecast uncertainty that stems from the representation of mixed-phase cloud microphysics within the Weather Research and Forecasting Model (WRF). The first research thrust focuses on how the evolution of ice crystal shape and choice of ice nucleation parameterization in the Adaptive Habit Microphysics Model (AHM) influences the lake-effect storm that occurred during Intensive Operating Period 4 (IOP4) of the Ontario Winter Lake Effect Systems (OWLeS) Field Campaign. This localized snowstorm produced total liquid-equivalent precipitation amounts up to 17.92 mm during a 16-hour time period, providing a natural laboratory …

"Prophet", Terry A. Messmer

Human–Wildlife Interactions

This is the letter from the editor-in-chief.

Energy And Greenhouse Gas Savings For Leed-Certified U.S. Office Buildings Using Weighted Regression, Tian Liang

Honors Papers

In this study, we studied the energy consumption and greenhouse gas emission performance of LEED-certified office buildings. We obtained the 2016 energy consumption and greenhouse gas emission data for 4002 office buildings from nine major US cities, including 522 buildings that we identified as LEED-certified. We discovered that LEED buildings used significantly more electricity percentagewise as their energy source. We also discovered that the locations and ages of buildings have significant effect on their performance. We removed the effect of locations and building ages using weighted regression. Our result showed that LEED office buildings used 11% less site energy, 9% …

Towards Formally Verified Compilation Of Tag-Based Policy Enforcement, Chr Chhak, Andrew Tolmach, Sean Anderson

Computer Science Faculty Publications and Presentations

Hardware-assisted reference monitoring is receiving increasing attention as a way to improve the security of existing software. One example is the PIPE architecture extension, which attaches metadata tags to register and memory values and executes tag-based rules at each machine instruction to enforce a software-defined security policy. To use PIPE effectively, engineers should be able to write security policies in terms of source-level concepts like functions, local variables, and structured control operators, which are not visible at machine level. It is the job of the compiler to generate PIPE-aware machine code that enforces these source-level policies. The compiler thus becomes …

View Synthesis Of Dynamic Scenes Based On Deep 3d Mask Volume, Kai-En Lin, Guowei Yang, Lei Xiao, Feng Liu, Ravi Ramamoorthi

Computer Science Faculty Publications and Presentations

Image view synthesis has seen great success in reconstructing photorealistic visuals, thanks to deep learning and various novel representations. The next key step in immersive virtual experiences is view synthesis of dynamic scenes. However, several challenges exist due to the lack of high-quality training datasets, and the additional time dimension for videos of dynamic scenes. To address this issue, we introduce a multi-view video dataset, captured with a custom 10-camera rig in 120FPS. The dataset contains 96 high-quality scenes showing various visual effects and human interactions in outdoor scenes. We develop a new algorithm, Deep 3D Mask Volume, which enables …

Sequential Monte Carlo Methods In The Nimble And Nimblesmc R Packages, Nicholas Michaud, Perry De Valpine, Daniel Turek, Dao Nguyen

Faculty and Student Publications

nimble is an R package for constructing algorithms and conducting inference on hierarchical models. The nimble package provides a unique combination of flexible model specification and the ability to program model-generic algorithms. Specifically, the package allows users to code models in the BUGS language, and it allows users to write algorithms that can be applied to any appropriate model. In this paper, we introduce the nimbleSMC R package. nimbleSMC contains algorithms for state-space model analysis using sequential Monte Carlo (SMC) techniques that are built using nimble. We first provide an overview of state-space models and commonly-used SMC algorithms. We then …

An International Pilot Study Of Volunteer Stream Monitoring Groups: The Role Of Place Attachment In Volunteer Motivations, Rachel Pierson

Graduate College Dissertations and Theses

Engaging the public in scientific research through volunteer monitoring (a form of community science) has potential to expand knowledge of conditions and to improve collaborative decision-making. Many studies have sought to understand motivations for participation and potential resulting actions or behaviors that benefit the environment. Place-based connections have been demonstrated to lead people to adopt environmentally responsible behaviors. However, few studies have considered possible differences in motivations across countries or the role place attachment may play as a driver of initial or sustained participation.

The aim of this research was to determine the extent to which place attachment influences people’s …

Estimating Floodplain Storage And Prioritizing Floodplain Reconnection In The Northern Lake Champlain Basin In Vermont, Stephanie Drago

Graduate College Dissertations and Theses

Floodplains play a major role in maintaining the health and sustainability of riverine systems, but human interventions have reduced the connectivity between stream channels and floodplains. Geomorphic assessments of streams and rivers in Vermont (USA) show they have been significantly altered within the past two centuries due to straightening, berming, and armoring channels to accommodate development, agriculture, roads, and rail lines. These alterations in river-floodplain connectivity have decreased floodplain functioning, specifically their capacity to store water during flood events. Currently, there is a lack of knowledge concerning the amount of floodwater, sediment, and nutrient retention provided by Vermont’s floodplains. This …

Evaluating The Distributional Equity Of Ecosystem Services Under Land Use And Climate Change Scenarios, Jesse David Gourevitch

Graduate College Dissertations and Theses

Nature supports human well-being and sustainable development through the provision of ecosystem services (ES). While ES have been mapped, modeled, and valued with multiple methods by a wide range of disciplines, understanding the distribution of ES benefits among individuals and groups within society remains a critical gap. Addressing this gap is essential for making conservation and environmental policy-making more equitable. In this dissertation, I present four studies that evaluate the distribution of ES among demographic and socioeconomic groups under a range of land use and climate change scenarios.

In my first chapter, I project changes in the supply, demand, and …