Digital Commons Network^™

Fault Tolerant Dynamic Task Allocation For Heterogeneous Multi-Robot Systems, Jack R. Cline

Master's Theses

This research presents a novel approach to dynamic task allocation in heterogeneous multi-robot systems with integrated fault detection capabilities. As multiple industries are becoming more reliant on multi-robot systems for tasks, maintaining operational efficiency despite robot failures becomes critical. We propose a framework that combines optimization-based task allocation with a Kalman filter that estimates task progress for anomaly detection to identify unreliable agents and dynamically redistribute tasks. Observing values such as the normalized innovation squared (NIS), covariance, and progress rate, the algorithm can designate a robot as faulty. Embedding information about which robots are faulty in the task algorithm allows …

Identification And Functional Assessment Of Candidate Causal Cis-Regulatory Variants Underlying Electrocardiographic Qt Interval Gwas Loci, Supraja Kadagandla, Lavanya Gunamalai, Dongwon Lee, Ashish Kapoor

The Brown Foundation: Institute of Molecular Medicine

Background: Identifying causal variants among tens or hundreds of associated variants at each locus in genome-wide association studies is challenging. As the vast majority of genome-wide association studies variants are noncoding, sequence variation at cis-regulatory elements (CREs) affecting transcriptional expression of specific genes is a widely accepted molecular hypothesis. Following this hypothesis, combined with the observation that open chromatin is a universal hallmark of all types of CREs, we aimed to identify candidate causal cis-regulatory variants underlying QT interval genome-wide association studies loci.

Methods: Common variants in high linkage disequilibrium with genome-wide significant variants were identified using variant …

All Things Pass Away, John Stuart Wilson

Dartmouth College Master’s Theses

“All Things Pass Away” is a work of crime fiction. Set amidst the downfall of local print journalism, laid off sportswriter Mark McGinnis travels from Rochester, New York to the oil boomtown of Fort McMurray, Alberta to pursue a freelancing project on troubled NHL draft prospect Noah Jeannot. Once there, McGinnis’s profile on the player is thrown into question when Jeannot disappears after an apparent violent altercation near his billet family’s home. Exploring themes of nostalgia, ambition, and obsession, the novella traces McGinnis’s attempts to understand not only the culture of the twin gods – oil and hockey – which …

Early Life Exposure To Fine Particulate Matter And Fine Motor Function, Attentional Function, And Working Memory Among Spanish School-Aged Children, Kristina W Whitworth, Aitana Lertxundi, Mingze Yuan, Alison Rector-Houze, Wei-Jen Chen, Mònica Guxens, Jordi Julvez, Michael Swartz, Elaine Symanski, Antonia Valentin, Carmen Iniguez, Llúcia L González-Safont, Jesús Ibarluzea

Faculty, Staff and Student Publications

Background: Evidence of the association between fine particulate matter (PM2.5) exposure and child neuropsychological function is equivocal. We examined early life PM2.5 exposure in relation to fine motor function, attention, and working memory in early childhood.

Methods: We used data from the Spanish INfancia y Medio Ambiente Project, 2003-2008. Exposure to PM2.5 (μg/m3) was assessed using spatiotemporal land-use random forest models and assigned based on residential address histories. Around age six, children completed the finger tapping test, attentional network test (ANT), and n-back task to evaluate fine motor speed, attention, and working memory, respectively. A total of 1,310 children had …

Optical Character Recognition For Early Handwriting Legibility Assessment, Franceli L. Cibrian, Kayla Anderson, Yingying 'Yuki' Chen, Lauren Min, Lizbeth Escobedo

Engineering Faculty Articles and Research

Monitoring children’s handwriting, such as avoiding writing assignments, displaying uneven letter formation, or showing slow writing speed, can help identify developmental and academic issues early. Poor handwriting affects up to 34% of children, leading to academic and self-esteem challenges. Handwriting assessments, typically conducted by teachers, are often delayed due to workload and could be subjective and inconsistent. This paper explores the potential of Optical Character Recognition (OCR) technology to augment and ease handwriting assessments. Based on an evaluation of 10 OCR algorithms using 33 handwriting samples assessed by two experts, the research indicates that Pen to Print and Google are …

The Effects Of Sirulina And Nannochloropsis Supplementation On Broiler Performance, Intestinal Morphology, And Gut Microbiology, Emily Beckerman

Master's Theses

The poultry industry is constantly searching for new nutritional strategies and better feed conversion ratio to enhance broiler growth and productivity. Microalgae have been shown to improve broiler performance and health depending on species and supplementation levels. The objective of this study was to determine the effects of Spirulina supplementation (Experiment I) and Nannochloropsis supplementation (Experiment II) on broiler production performance, intestinal morphology, and gut microbiology. In Experiment I, a total of 270 broiler chicks (one-day-old Ross 708) were obtained from a local hatchery after vaccinating against Newcastle, Marek’s disease, and Infectious Bronchitis. They were weighed and sorted into 18 …

Understanding Utilization And Prevention Measures Associated With A Caries Risk Assessment In Oral Health Transformation, Melody Mcgee, Ryan Brandon, Muhammad Walji, Joel White, Kristen Moses, Eric P Tranby, Lisa J Heaton, Kristen Simmons

Faculty, Staff and Student Publications

Objectives: Dental decay is endemic in the United States, underscoring the need to measure the utilization of caries risk management tools to elucidate the effect of prevention interventions in reducing the dental decay rates of individuals. An academic institution partnered with a third-party institute to call attention to the utilization and prevention measures associated with caries risk assessment (CRA) used with children 0-18 years. This environmental scan examined claims across the United States to evaluate the proportion of dental examinations, CRAs, and caries prevention procedures within a calendar year.

Methods: A 12-month deidentified participant list categorized by age, race, sex, …

Europe–Africa Collaboration: Working Together To Strengthen Health Research, Implementation, And Equitable Systems, Lara Pandya, Irene Norstedt, Martin Seychell, Emer Cooke, Isabel De La Mata Barranco, Niklas Blomberg, Marleen Temmerman, Michael Makanga

Centre of Excellence in Women and Child Health

In September 2024, key representatives from European Union (EU) directorates and agencies convened to enhance collaboration with Africa in strengthening health research, innovation, and implementation. The meeting focused on bolstering joint efforts to improve health outcomes and support wellbeing across all ages in Africa. Despite progress in addressing infectious diseases, the continent faces a dual burden with the rise of non-communicable diseases and emerging threats such as antimicrobial resistance, climate change, falsified medicines, and pandemic risks. These challenges are exacerbated by fragile health systems, rapid population growth, urbanisation, and limited access to affordable medical interventions.

To address these issues, the …

A Bayesian Approach To Grappa Parallel Fmri Image Reconstruction Increases Snr And Power Of Task Detection, Chase J. Sakitis, Daniel B. Rowe

Mathematical and Statistical Science Faculty Research and Publications

In fMRI, capturing brain activation during a task is dependent on how quickly k-space arrays are obtained. Acquiring full k-space arrays, which are reconstructed into images using the inverse Fourier transform (IFT), that make up volume images can take a considerable amount of scan time. Undersampling k-space reduces the acquisition time but results in aliased, or “folded,” images. GeneRalized Autocalibrating Partial Parallel Acquisition (GRAPPA) is a parallel imaging technique that yields full images from subsampled arrays of k-space. GRAPPA uses localized interpolation weights, which are estimated prescan and fixed over time, to fill in the missing …

Marching To College: Exploring Military-Connected Students’ Access Experiences Navigating College Choice, Latosha R. Henderson, Jennifer Johnson, Shannon Martin

Journal of College Access

This study analyzed how pre-college advising and transition experiences impact the postsecondary success of military-connected students (MCS). Each year, approximately 200,000 military veterans transition to civilian life, with around 40% seeking higher education. Despite the financial support of the Post-9/11 GI Bill, MCS face unique challenges in accessing and succeeding in higher education, including restrictive admissions policies, unclear credit transfer processes, and insufficient pre-college advising.

Through a case study approach, this study explores the college transition experiences of MCS and the role of pre-college advising in supporting these transitions. Data were collected via surveys and interviews, focusing on the participants' …

Kin 460.01: Electrocardiogram Assessment, Ronald Michalak

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Csd 261.51: Introduction To Speech-Language Pathology Assistant, Collie A. Putman

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Intraoperative Dynamic Contrast-Enhanced Fluorescence Imaging For Navigating Open Orthopedic Surgeries, Yue Tang

Dartmouth College Ph.D Dissertations

Infection following trauma is one of the most prevalent and challenging complications faced by orthopedic surgeons. Inadequate tissue perfusion plays a critical role in this complication, as poorly perfused bone can be a nidus for bacterial biofilm formation and promote resistance to antibiotic treatments. Consequently, the management of open fractures and fracture-related infections relies on aggressive and thorough debridement to remove all poorly perfused bone. This thesis focuses on developing an indocyanine green (ICG)-based dynamic contrast-enhanced fluorescence imaging (DCE-FI) to objectively measure bone perfusion during open orthopedic surgeries and guide surgical debridement of devitalized bone.

Novel methodologies were developed to …

Understanding The Habitat Associations Of Nearshore Rockfishes Inside And Outside Of Marine Protected Areas Using Hook-And-Line Data, Kaila Raeanne Fritch

Master's Theses

Habitat is an important driver in shaping the distribution of a range of species. For demersal fish species, benthic habitat characteristics can drive distribution and community structure. Understanding the relationship between habitat and species distribution in important, especially for exploited species such as rockfishes (Sebastes spp.). Increased data on the relationship between rockfish and benthic habitat characteristics could enhance marine protected areas (MPAs) and management practices which are used to protect rockfishes along the U.S. West Coast. To address this, we used hook-and-line, catch-and-release data that were collected inside two MPAs on the central coast of California, and …

Compact, Low-Power Underwater Acoustic Modem Characterization And Sensing Network Node Implementation, Lucas W. Lucia

Master's Theses

There is a growing market for compact, power-efficient underwater communication technology. Due to the limited propagation of electromagnetic waves through water, modulated acoustic waves have emerged as an effective means of wireless communication underwater. In decades past, many acoustic modems had been developed primarily for defense customers in larger systems functioning at high power. In recent years, smaller, relatively inexpensive acoustic modems have become available on the market—but data on their performance in a real-world environment is scarce. Companies such as OWL Integrations are interested in employing such acoustic modems as part of sensing networks across multiple mediums. For such …

Deeppanorf: Deep Prior For Neural 3d Reconstruction From Sparse Panoramas, Edward Du

Master's Theses

Advances in neural field representations have led to a significant improvement in view synthesis quality. However, many current novel view synthesis methods rely on a dense set of input views, which can be impractical and inefficient in real-world applications. We propose DeepPanoRF, a novel method for 360◦ scene reconstruction from a sparse set of input equirectangular panoramas. Built upon K-Planes, a radiance field representation that encodes explicit features on orthogonal feature planes, our method does not directly learn feature grids. Instead, we parameterize the feature grids to enable sparse view reconstruction without pretraining or additional regularization. We implement a custom …

Spos: An Attestation Solution For The Detection And Mitigation Of Point Of Sale Malware, Damian Singh Dhesi

Master's Theses

Securing 95% of card present transactions, accounting for billions of transactions a year, has made EMV the premier protocol for card-based payment. Created by and named after Europay, Mastercard, and Visa, the EMV protocol provides multiple solutions to resolve security concerns with the outdated, swipe-based, magnetic stripe payment. Such solutions are Chip and PIN which provides a more secure transaction at a significant time cost and EMV contactless which provides improved security to Chip and PIN at greater ease of use with its quick, tap-to-pay based payment. However, regardless of how secure the EMV protocol makes the card side of …

Investigating Social Presence In Collaborative Keys For Asynchronous Courses, Lily P. Cook

Master's Theses

Asynchronous virtual courses have become increasingly popular in the years following the global Covid-19 pandemic. These courses, with no set meeting schedule, offer flexibility to both students and instructors, but pose challenges for developing a collaborative learning environment. The Community of Inquiry framework (Rourke et al., 1999) identifies three essential components in an online course necessary to foster a collaborative environment- teaching presence, cognitive presence, and social presence. Social presence is especially impacted in asynchronous learning settings, which presents challenges for the students to display their personalities and connect with the community. This study investigates Collaborative Keys (CKs), structured collaborative …

Analog Hardware Implementation Of A Linearly Constrained Quadratic Program Real-Time Solver, Claire E. Tylutki, Claire Tylutki

Master's Theses

This thesis presents the design, implementation, and analysis of a hardware system for solving Linearly Constrained Quadratic Programs (LCQPs) in real time. The architecture follows a generalized feedback structure composed of three key elements: gradient descent on the quadratic cost function, saturation-based nonlinearity to enforce inequality constraints, and an integral controller with an anti-windup mechanism to regulate dynamic behavior and determine steady-state error. This majority analog system converges with equilibria that satisfy the Karush-Kuhn-Tucker (KKT) optimality conditions. Using a representative LCQP, this work presents simulation of the circuit in PLECS and LT Spice to confirm the feasibility of the novel …

Adversarial Deep Reinforcement Learning For Tank Duel Simulation Using Lidar-Based Observations, Braedan Kennedy

Master's Theses

Previous research has demonstrated that reinforcement learning agents can learn to steer differential-drive robots around obstacles using 2D lidar scans as observations. However, these studies typically treat all range returns as undifferentiated obstacles—objects to avoid—without distinguishing between different object types. This thesis builds upon previous research by introducing an adversarial task in which an agent must interpret raw range readings to both avoid static obstacles and identify, pursue, and engage a hostile target.

To investigate this problem, this thesis introduces TankGame, a novel, lightweight 2D tank duel simulator. Each agent receives a 360° lidar scan, controls its motion via tread …

Distributed Formation Control Of Nonholonomic Mobile Robots: Safety-Critical Leader-Follower Approach With Obstacle Avoidance And Dynamic Reconfiguration, Kelvin C. Villago

Master's Theses

Networked control systems for multi-agent robotics have emerged as a critical paradigm for executing complex coordinated tasks in diverse environments. While formation control serves as the backbone of such systems, real-world deployment introduces significant challenges including communication constraints, environmental obstacles, and the need for adaptive reconfiguration. This research addresses these challenges by developing a novel unified framework that seamlessly integrates obstacle avoidance algorithms with dynamic formation reconfiguration capabilities, specifically designed for communication-limited networked control architectures. The proposed framework represents a significant advancement over existing approaches by simultaneously handling both static and dynamic obstacles while maintaining system cohesion under communication constraints. …

Opening The Black Box With Regal: A Novel Explainable Ai Approach To Uncover Key Predictors In Search And Rescue Success, Brandon Hyunjun Kim

Master's Theses

The outcome of a search and rescue (SAR) operation is influenced by a complex, non-linear interplay among numerous factors, including geographic context, subject-specific characteristics, and environmental conditions. The high dimensionality and intricate dependencies among these variables pose significant challenges to traditional exploratory modeling approaches, limiting their ability to uncover meaningful patterns and relationships associated with mission success. This study introduces Rules Based Explanations for Generated neighborhoods Around Localized cases (REGAL), a novel adaptation of the Local Interpretable Model-agnostic Explanations (LIME) framework to explain deep multimodal neural networks and what key features it assesses to determine search and rescue success. REGAL …

Sentry V3: Extending Context Switches On A Trusted Secure Coprocessor, Mark Kong

Master's Theses

Software correctness and integrity is only ensured through trust in the un- derlying hardware. However, modern computer systems are complex to design and secure. Thus, given the choice between performance and security, companies will often prioritize performance, resulting in vulnerable systems. This creates exploitable systems that must be patched retroactively because business value performance over security. One approach to this issue is to separate the root of security from the rest of the system to create a minimal trusted computing base. Trustguard is one instance of this. Trustguard implements a Containment Architecture with Ver- ified Output (CAVO) model which shows …

Optimizing Web Servers With Io_Uring, Mihika Nigam

Master's Theses

Modern web servers face unprecedented demands for high throughput and low latency [10] [11]. Yet, even the state-of-the-art optimizations often fail under heavy workloads on existing infrastructure. Despite advancements in hardware, communication between applications and the kernel remains a critical bottleneck.

Industry surveys reveal that over 50% of production servers still rely on traditional epoll-based architectures [5]. This research aims to investigate and characterize Linux’s new io_uring subsystem, which has the potential to overcome these challenges. Through controlled load testing of various existing architectures like event-driven, multi-process, and multi-threaded architectures (including other commercial servers), we demonstrate how io_uring can help …

Enhancement Of A Python Integral Boundary Layer Method, Jeffrey T. Azuma

Master's Theses

This thesis presents a series of additions to a Python based integral boundary layer software library known as PyBL. This library provides the user the means to calculate boundary layer properties using different models for boundary layer behavior. The additions feature the integration of a set of new laminar and turbulent integral boundary layer models originally developed for and currently found in the program XFOIL. These models were modified to fit the ODE solver method at the foundation of PyBL. A new method for PyBL that stitches a laminar and turbulent solution together has been developed to improve the ability …

Efficient Gan-Based Adversarial Example Generation Against Ml-Based Network Intrusion Detection Systems, Darren D. Hartono

Master's Theses

In the realm of network security, Network Intrusion Detection Systems (NIDS) are essential for identifying and mitigating malicious activities targeting networked devices. Traditionally, these systems have relied on signature-based and anomaly-based detection techniques. However, the increasing complexity and adapt- ability of cyber threats have driven the adoption of Machine Learning (ML) ap- proaches in modern NIDS, significantly improving their ability to detect a wider range of attack vectors. Despite these advancements, ML-based NIDS remain vulnerable to adversarial examples—deliberately crafted inputs designed to mislead models and trigger incorrect classifications. Originally identified in the field of computer vision, adversarial examples now pose …

Design And Development Of A Laboratory Star Tracker System, Kevin D. Iverson

Master's Theses

This thesis presents the design, calibration, and validation of a low-cost star tracker system and hardware-in-the-loop testbed intended for small satellite applications. The system is composed entirely of commercial off-the-shelf components and integrates both a custom star tracker and a screen-based star field simulator for controlled, repeatable testing. An analytical modeling approach was used in the early design phase to predict system accuracy based on key optical and geometric parameters, informing the selection and configuration of components and guiding the development of calibration routines.

A simulation environment was developed to validate the star tracker software and assess the impact of …

Hardware-In-The-Loop Testing For The Polysim Adcs Lab, Shealyn P. Miller

Master's Theses

Hardware-in-the-loop, HIL, testing is an important tool for the validation and verification of systems in the aerospace industry. A common subsystem to be tested using HIL testing is the attitude, dynamics, and controls subsystem, ADCS. This is due to HIL tests using realistic simulations of the space environment to control physical hardware. To create a HIL test, a simulation and HIL interface are needed to test and communicate with hardware. Using a Speedgoat Performance Real-Time Target Machine to communicate with a Raspberry Pi and a Simulink model, three tests were conducted to ensure communication was functioning properly. A simulation, in …

Identifying Interchromosomal Interactions Using A Graph-Based Computational Pipeline, Ethan Outangoun

Master's Theses

Current computational tools for analyzing chromatin organization are mainly focused on intrachromosomal interactions, despite growing evidence that suggests long-range interactions across chromosomes contribute to transcriptional regulation and disease development. This thesis aims to address this gap in interchromosomal genome analysis, presenting a robust computational pipeline that identifies a clique (i.e., a subgraph) of highly interacting trans-chromosomal regions anchored at a user-specified seed genomic locus. A weighted interaction network is constructed from an input Hi-C contact matrix, a widely used experimental assay for measuring genome-wide chromatin interactions. We model this input contact matrix as a graph and devise three different strategies …

Investigating And Evaluating Poison Unlearning Under Imperfect Detection, Mitashi D. Parikh

Master's Theses

Machine unlearning is an emerging field focused on removing the influence of specific data points from trained machine learning models. Early work in this field has primarily focused on privacy-oriented unlearning, often motivated by data protection regulations such as the GDPR. More recently, security-oriented unlearning has emerged as a response to data poisoning attacks, where malicious inputs are injected into training data to manipulate model behavior. In these security-oriented settings, unlearning methods aim to reverse the influence of malicious training data after a model has already been deployed. However, existing methods assume access to an accurately identified portion of poisoned …