Digital Commons Network^™

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 …

Property Testing Ai: An Efficient Frontier, Paul Sopher Lintilhac

Dartmouth College Ph.D Dissertations

In this dissertation, we take a step towards addressing the major problem of a lack of standardized and rigorous approaches to testing and evaluation of AI systems. Taking inspiration from both the fields of Property Testing and Property Based Testing (for programs), we develop a novel taxonomy of partially overlapping classes of properties of AI systems, including simple properties, compound properties, higher order properties, data relation properties, and architecture-utility properties. We argue that this taxonomy categorizes a diverse set of AI traits -- including accuracy, fairness, robustness, monotonicity, point-wise and global privacy properties, sensitivity, and more -- according to the …

Final Bpsou Unreclaimed Sites: Ur-05 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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 …

Banach Algebras And The Gelfand Theory Of Group Algebras On Locally Compact Abelian Groups, James Gabriel Bonvanie

Master's Theses

A Banach algebra is a complex algebra that is simultaneously a Banach space in which the norm is submultiplicative. Notably, $L^1(\mathbb{R})$ with the convolutional product is an Abelian, non-unital Banach algebra that admits an approximate identity. We rectify $L^1(\mathbb{R})$ lacking a unit via the unitization $L^1(\mathbb{R})\times\mathbb{C}$ with identity $(0,1)$. Unitization opens the discussion to the spectrum $\sigma(x)$ of a Banach algebra element, in which the spectrum is a nonempty, compact subset of the complex plane. The spectrum of an Abelian Banach algebra is fully characterized with multiplicative linear functionals, and we prove that the Fourier transform is the unique multiplicative …

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 …

On Diffeomorphism Groups Of Surfaces, Madeleine Goertz

Master's Theses

Let $M$ be a closed, connected, smooth manifold. What are the symmetries of $M$? From a geometric viewpoint, the symmetries of $M$ are precisely its isometries, the self maps which preserve lengths and angles. In the smooth category, the symmetries of $M$ are its diffeomorphisms, the self maps which are smooth and have a smooth inverse. Does expanding our notion of symmetries to include diffeomorphisms result in ``more'' symmetries in a meaningful sense? As a formal conjecture, the claim is that the isometry group of $M$ is a deformation retract of the diffeomorphism group of $M$. If $M$ is the …

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 …

Minifying Deep Denoising Networks With Knowledge Distillation, Antonio L. Rozzi

Master's Theses

Hearing loss is a prevalent condition, affecting hundreds of millions globally, with a higher incidence among older adults. While hearing aids are the standard treatment, the majority of those who could benefit from hearing aids choose not to wear them, attributing this decision in large part to their inability to perform well in conversations in large groups and in noisy situations. To date, no denoising systems on commercial hearing aids are able to improve speech intelligibility. Recent advances in artificial intelligence research have shown that large deep-learning models can in fact improve speech intelligibility by removing background noise from audio. …

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 …

Filling Gaps In Scientific Data Sets Using Physics Informed Neural Networks: A Case Study In Velocity Fields, Ellen Saunders

Master's Theses

Gaps in scientific data sets are a persistent issue for researchers in a variety of fields, and while nothing makes up for missing out on real data, well-simulated synthetic data can be a useful tool. In the world of image processing, machine learning techniques have become quite sophisticated at taking an image with a missing component and filling in that space with something believable. The aim of this thesis is to take machine learning techniques similar to what gets used in image processing and repurpose them to infill gaps in scientific data sets in a realistic manner. This thesis compares …

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 …

Flair: A Fog-Native Workload Placement Framework For Qos-Aware Scheduling In Smart Manufacturing, Daiwik N. Swaminathan

Master's Theses

Smart manufacturing environments utilize a variety of heterogeneous IoT sensors that continuously stream large volumes of data. To detect and mitigate critical events such as fires or accidents in real time, this data must be promptly analyzed by machine learning (ML) image classifiers. These classifiers are typically deployed on fog computing nodes located within the manufacturing warehouse facilities to ensure low-latency responses and to protect data privacy. Although fog nodes offer a better alternative to remote cloud data centers for such latency-sensitive tasks, they are often resource-constrained and highly sensitive to the composition of workloads, particularly in heterogeneous environments where …

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 …

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 …

Data-Driven Product Recommendations: A Decision Support Framework Utilizing Customer Reviews, Tyler A. Lopez

Master's Theses

With the considerable presence of e-commerce in society, vast number of purchasable goods, and increasing brand variety, consumers are faced with the challenge of buying products that they perceive to be of greatest value to them. To assist consumers with making better informed decisions, e-commerce websites allow individuals to post their own experiences and score the products that they purchase. Despite this information, the variety of experiences and feedback that consumers share do not always lead to clarity on whether a product is best suited for the purchaser. To help guide customers through a simplified purchasing process from the perspective …

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 …

Vertical And Latitudinal Variability Of Marine Heatwaves In The California Current, Gavin M. Plume

Master's Theses

Marine heatwaves (MHWs) are increasing in frequency and intensity globally, with grave effects on marine ecosystems and their dependent industries. There are significant gaps in knowledge of the subsurface behavior and geographic distribution of MHWs, especially in eastern boundary upwelling systems like the California Current. Here, two decades of full water-column temperature observations from a shallow autonomous profiler in San Luis Obispo Bay (~10m) revealed that while MHWs have similar average durations and intensities across all depths, one-third of bottom MHWs occur without a concurrent surface signal. MHWs across the water column initiated during anomalously weak upwelling or downwelling conditions …

The Northern Elephant Seals (Mirounga Angustirostris) Of The Piedras Blancas Colony: A Story Of Recolonization, Monitoring And Movement, Mackenzie Davidson

Master's Theses

Northern elephant seals (Mirounga angustirostris) are large, ocean migrating carnivores that have a wide distribution along the west coast of North America. Like other pinniped species, northern elephant seals spend considerable time out at sea foraging and return to land to molt and breed. Northern elephant seals were hunted to near extinction in the late 1800s. Due to conservation efforts they have since rebounded, and they currently occupy 27 known terrestrial breeding colonies. Much literature has documented the recolonization, population dynamics, and dispersion of this species. Currently, Piedras Blancas (San Simeon, California) is the largest mainland breeding colony of northern …

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 …

Clusters, Trends, And Choices: Feature Selection In Interactive Statistical Graphics, Dylan Le

Master's Theses

Exploratory data analysis (EDA) is a method for uncovering the structure and key characteristics of data, often through the use of statistical graphics. These visual tools can reveal patterns and trends, and their effectiveness can be enhanced through interactivity. By enabling users to filter data, zoom, and toggle visual features, interactive plots can accelerate and enrich the EDA process. This study extends a previous graphical study by incorporating an interactive framework. Using a statistical lineup protocol with two target patterns (a linear trend and a clustering trend) participants interacted with plots by toggling various aesthetic features, including cluster coloring, ellipses …

Myceli-Yum: Elucidating Structure-Property Relationships For Polymer Degradation By Mycelial Digestion, Jordan Scott Ford

Master's Theses

Since the industrial entrance of polymer plastic materials, plastic has become ubiquitous in both everyday use and waste. Due to inefficiencies and knowledge gaps, current recycling methods are not able to account for the high scale of plastic waste, resulting in the bulk of this waste being landfilled, mishandled, and deposited in the environment. Mycelium, the microorganism responsible for fruiting mushroom bodies and mold growth, holds potential to reduce plastic waste and can potentially be utilized as a method of industrial recycling. Following a drug-design approach, the active site of mycelial enzymes responsible for natural biopolymer degradation have been assessed …

Adaptive Volatility Forecasting Models, Jeffrey K. Tan

Master's Theses

In finance, risk is often quantified by volatility, and computing accurate volatility forecasts — while vital to financial decision making — remains one of the most challenging tasks in financial modeling. This thesis, motivated in part by the Black-Scholes-Merton Model and its limitations, adopts a statistical approach to volatility forecasting. The two main models of interest are the Exponential Weighted Moving Average (EWMA) model and the GARCH(1,1) model. Specifically, this work expands upon a potential adaptive lambda algorithm for EWMA models first proposed by Bernard Bollen (2014), and this work also utilizes the Momentum of Predictability (MoP) to generate adaptive …

The Degrees Of The Irreducible Representations Of The Symmetric Group With Respect To Primes, Vanessa F. Beeler

Master's Theses

In this thesis, we explore the relationship between the degrees of irreducible matrix representations of the symmetric group and prime numbers. We start by building up the required background necessary to construct our results. We dive into topics of discrete mathematics including matrix representations, characters of representations, integer partitions, conjugacy classes, class functions, and tableaux. Some other key ingredients in our work include using character tables to classify the irreducible rep- resentations of the symmetric group and the hook-length formula to easily compute the degrees of these representations. Once we have laid the groundwork for our in- vestigation, we begin …

Subalpine And Alpine Plant Community Turnover In Yosemite National Park Following 30 Years Of Climate Warming, Rachel Friesen

Master's Theses

Subalpine and alpine regions in California are warming more rapidly than lower elevations. In response, high-elevation plants may acclimate or adapt to the new climate, move to higher elevations or latitudes, persist in refugia, or go extinct. While models predict substantial declines in subalpine and alpine plant communities due to discontinuous population distributions and lack of upslope area, actual responses may vary due to lags in dispersal, establishment, and extinction. Although shifts in high-elevation plant communities have been documented in other regions of the world, such changes have not yet been studied in Yosemite National Park. To assess high-elevation plant …

Leveraging Machine-Learning Algorithms In Two Car Crash Detection Systems On A Custom Dataset, Addison Jacob Sandvik

Master's Theses

Traffic accidents pose a significant threat to public safety, causing millions of deaths and injuries worldwide each year. While efforts to reduce accidents have seen limited progress in recent years, improving emergency response times through automated detection systems is a promising avenue for saving lives. This thesis describes the development of machine learning-based traffic accident detection systems, exploring both video classification and image detection models. The models are trained on a new dataset deemed the Cal Poly Traffic Accident Dataset, an extension of the existing Car Accident Detection and Prediction (CADP) dataset with a precise collision annotations. Two systems were …

The Impact Of Accessibility Features On Player Experience In Video Games, Christine M. Widden

Master's Theses

While video game accessibility is a growing research topic, few studies investigate how players perceive the presence versus the absence of accessibility features, or how non-disabled players react to the option of accessibility features. This study explores these research gaps, investigating how access to accessibility features affects the experience of both disabled and non-disabled players. For the purposes of this study, a small platformer game was developed with as many accessibility features as feasible for the scope of the project. An A vs.\ B study was conducted in the game, with anonymous participants randomly assigned to version A, with all …