Digital Commons Network^™

Applied Forest Restoration And Conservation In Michigan: Advancing American Beech Restoration And Documenting A Historical Insect Collection, Thomas E. Panella

Dissertations, Master's Theses and Master's Reports

Forest restoration and conservation require both practical management approaches and the preservation of biological resources that support future research. This dissertation presents applied research conducted in Michigan that advances American beech (Fagus grandifolia) restoration in response to beech bark disease (BBD) while documenting an important historical entomological resource. Chapters 1–3 focus on overcoming practical barriers to American beech restoration. Restoration protocols were developed and refined for identifying BBD-resistant trees, graft propagation, rootstock collection, container production, and the field establishment of grafted BBD-resistant trees. A greenhouse experiment evaluated the influence of growing media and fertilization on container stock quality, …

Using Automotive Lidar To Reduce The Energy Consumption Of An Ego Autonomous Vehicle, Logan P. Schexnaydre

Dissertations, Master's Theses and Master's Reports

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model …

Predictive Maintenance For Manufacturing Equipment, Paloma De Andrade Batista

ICT

Unplanned equipment downtime is a significant challenge in manufacturing, resulting in substantial productivity losses and operational costs. Predictive maintenance, enabled by machine learning and big data analytics, offers an opportunity to identify potential equipment failures before they occur and improve maintenance efficiency. This report extends a previous capstone project that applied Random Forest and Logistic Regression to the AI4I 2020 Predictive Maintenance Dataset. The current study expands the analysis by incorporating XGBoost, systematic hyperparameter optimisation, cross-validation, and SHAP-based model interpretability. In addition, SWOT and PESTLE analyses, alongside a legal and ethical assessment, examine the broader strategic and responsible implementation of …

Designing Narrative-Based Ai Assistance For Sensemaking In Collaborative Environments: Case Studies In Education And Dementia Care, Dylan Edward Moore

Dartmouth College Ph.D Dissertations

This thesis addresses a gap in the human-computer interaction literature regarding the design, development, and evaluation of narrative-based AI assistance for collaborative, complex problem solving. I explore this design space through three case studies across the domains of education and dementia care. This work encompasses multi-year industry partnerships and longitudinal fieldwork, user-centered design, dataset curation, model training, and system evaluation.

Specifically, the first case study considers a story-based web platform for teaching AI literacy through peer-generated, personalized narrative scaffolding. Learners on the platform showed significant knowledge gains and other learning-related outcomes. To describe the novel design of this system, I …

Doikayt And The Ethics Of Belonging: Lessons In Place-Making From The Jewish Labor Bund, Zoë L. Jacobs

Scripps Senior Theses

This thesis traces the evolution of doikayt—the Bundist principle of hereness—from its origins in the Jewish Labor Bund to contemporary applications in North America. Rooted in a refusal of both assimilation and nationalist escape, doikayt emphasizes cultivating safety, solidarity, and belonging through collective responsibility rather than territorial claims.

Building on this foundation, the exploration situates hereness within a settler-colonial context, where ethical dwelling is complicated by Indigenous dispossession. Drawing on Alexis Shotwell alongside Indigenous thinkers Vanessa Watts and Kyle Whyte, I examine how inhabiting place requires confronting historical injustices and ongoing relational responsibilities. Chapter 3 analyzes Linke Fligl (2016–2022) as …

Feasibility Of Upcycling Spent Lithium-Ion Battery To Carbon Dioxide Capture Adsorbent, Chimezie Frank Onwudinjo

Master’s Theses

This study investigates the feasibility of repurposing spent lithium-ion battery (SLIB) to lithium orthosilicate (Li₄SiO₄), a high temperature carbon dioxide sorbent. Two synthesis pathways including conventional acid-leaching method (Scenario 1) and a pyrolysis-based route (Scenario 2) were explored. Additionally, techno-economic analysis (TEA) and lifecycle assessment (LCA) of the two processes were also performed. Different analytical characterization techniques were performed to understand the material properties of Li₄SiO₄ including surface area, crystallinity, morphology and thermal stability. CO₂ capture performance of the synthesized Li₄SiO₄ was tested in a thermogravimetric analyzer (TGA) using …

Overview And Methods Of Molecular Paleontology: A Review, Shelby Touchstone

Williams Honors College, Honors Research Projects

Molecular paleontology—the study of ancient biomolecules preserved in fossils and sediments, including ancient DNA, lipids, and proteins—has motivated researchers since the 1950s, inspiring both scientific inquiry and broader cultural imagination. Think Jurassic Park. This honors thesis presents a comprehensive review of the history, current state, and methods of the field of molecular paleontology. Drawing on peer-reviewed literature and scholarly resources accessed through databases such as EBSCO and Bierce library, this review examines key techniques such as Next Generation Sequencing and amino acid racemization and will go over limitations and controversies in the field. It will also explore potential new …

Towards Breach Hypothesis Based Predictive Autonomous Cyber Defense Ecosystem: Proactive Prevention Of Imminent Threats And Productivity Losses, Yogesh Chavarkar

Master's Theses and Doctoral Dissertations

As cyberattack tools and techniques get sophisticated and persistent, reactive cybersecurity has been unable to effectively prevent breaches and compromises. Organizations and institutions with large complex environments have wide vulnerable exposure with higher chances of a cyberattack. This also increases overall security and financial risk. Possibility of repetitive attacks from cyber threats increases, too, despite the use of standard defense measures. Security tools and system vulnerabilities often need manual patching and updates to keep the environment secure and functioning effectively. Productivity suffers from manual trade-offs in keeping the systems secure from adverse impact. Persistent high-severity cyberattacks, despite continued reactive defensive …

Novel Methods For Environmental Fluoride Measurement, Cable Warren

Chemistry & Biochemistry Dissertations

Fluoride analysis has been an important focus of analytical analysis for many years and will continue to be so going forward. Today, fluorinated compounds, specifically per/polyfluoroalkyl substances (PFAS), better known as “forever chemicals” have captured the moment and are the subject of vast research and regulation. Under this context, I have researched new methods of fluoride separation and concentration in complex media as well as a novel method of PFAS destruction and total organic fluorine analysis for screening of PFAS in aqueous samples. Through research and work on micro-scale detection methods, an understanding of the state of the art and …

Emotional Patterns In Conversational Social Media Using Graph-Based Context, Sai Sanjay Yerunkar

Master's Projects

Most social media datasets for emotion detection have not been constructed to account for conversational structure‚ so we investigate whether it carries signal for emotion prediction. Using Sentiment140 and GoEmotions Reddit threads‚ we construct their thread-based conversation graphs and compute the aggregated features of neighbors as well as the transformer and TF-IDF representations of comments. Connected comments are 4.5× more similar in emotions than expected by chance. Pairwise emotional similarity decays exponentially with geodesic distance (e.g.‚ after 2 hops). Pairs separated by a 30s timestamp difference have the highest emotional similarity. These results suggest that emotion is structured locally and …

A Simple Statistical Tool To Correct The Daily Temperature Effect On Dielectric Soil Matric Potential Sensor Readings, Sebastián Bravo Peña, Meindert Commelin, Ole O. Wendroth

Plant and Soil Sciences Faculty Publications

High-resolution time series recorded by soil water dielectric sensors are often affected by other processes. Dielectric soil matric potential sensors, such as the TEROS 21, exhibit temperature sensitivity, resulting in deviations of readings from the true value due to soil temperature fluctuations. However, methods for correcting this effect remain limited. The objective of this study was to create a straightforward, scale-based statistical approach to mitigate the influence of daily temperature oscillations on matric potential dielectric readings. The temperature sensitivity correction function (TSCF) identifies, quantifies, and smooths diurnal fluctuations caused by soil temperature dynamics. We provide a detailed description of the …

Accounting For Spatial Effects And Social Norms In Making Algorithmic Law: Insights From And Applications In Urban Mobility, Jingkang Gao

Journal of Law and Mobility

This Article examines a prominent idea in the law and technology literature: that algorithms and big data can be used to make law dynamic and personalized. As currently envisioned by legal scholars, “algorithmic law” entails laws that adjust in real time to changing conditions and vary across individuals, improving welfare by tailoring legal rules and standards to personal characteristics.

This Article argues that this vision of algorithmic law is incomplete—and often counterproductive. Existing proposals treat personalization as a function of individual attributes alone, overlooking the fact that effects of individual behavior are fundamentally interactive. Individual behavior is shaped by spatial …

Celebrating Faculty Scholarship 2026, Smith College Libraries

Celebrating Faculty Scholarship: Bibliographies

Bibliography of selected scholarly and creative work produced by Smith College faculty and submitted by faculty for the 2026 celebration in the Neilson Library Skyline Reading Room, Smith College on September 14, 2026.

Qubit Lattice Algorithm Simulations Of The Scattering Of A Bounded Two Dimensional Electromagnetic Pulse From The Infinite Planar Dielectric Interface, Min Soe, George Vahala, Linda Vahala, Efstratios Koukoutsis, Abhay K. Ram, Kyriakos Hizanidis

Electrical & Computer Engineering Faculty Publications

Qubit lattice algorithm (QLA) simulations are performed for a two-dimensional spatially bounded pulse propagating onto a plane interface between two dielectric slabs. QLA is an initial value scheme that consists of a sequence of unitary collision and streaming operators, with appropriate potential operators, that recover Maxwell equations in inhomogeneous dielectric media to the second order in the lattice discreteness. For the case of total internal reflection, there is transient energy transfer into the second medium due to the evanescent fields as the Poynting unit vector of the pulse is rotated from its incident to reflected direction. Because of the finite …

From Reviews To Value: Harnessing Crowdsourced Data To Capture Visitor Perceptions And Economic Benefits Of Recreation, Laura Costadone, Shan Zhang

ODU Articles

Quantifying the recreational value of protected natural areas is essential for sustainable management, conservation financing, and informed decision-making. Traditional approaches, such as on-site surveys, are often costly, spatially limited, and constrained by regulatory barriers. This study evaluates the potential of crowdsourced user-generated data to jointly assess visitor perceptions and the economic value of nature-based recreation, using Back Bay National Wildlife Refuge (Virginia, USA) as a case study. We integrated georeferenced photographs and textual content from four platforms (Flickr, TripAdvisor, Yelp, and AllTrails) with supplementary survey data to analyze visitation patterns, visitor sentiment, cultural ecosystem services, and recreational value using the …

Electronic Bills Of Lading And Blockchain Technology: A Regulatory Perspective, Hsin-Hua Tsai

Journal of Marine Science and Technology–Taiwan

Information and communications technology (ICT) systems are increasingly relevant to the maritime sector. Regarding the revolution of the bill of lading, many shipping lines and other technology startups have been looking into developing viable electronic transport documents that have the same functions as paper bills of lading to reduce supply chain risks. The limitations of the paper-based process have become increasingly visible in the COVID-19 crisis. The main purpose of the article is to analyze the application of blockchain bills of lading, which utilizes computational logic to create the digital ledger, and users can set up algorithms and rules to …

Visually Guided Landing System On Ship Deck For Multicopter, Dong-Lin Li, Shih-Kai Lee, Tzu-Hsiang Chou

Journal of Marine Science and Technology–Taiwan

Traditionally, high-value fish have been located at sea using helicopters. However, with advancements in technology, maritime drones have become increasingly important in recent years. Compared to traditional helicopter-based methods, drones offer significantly lower operational costs, making them cost-effective. However, the challenging sea conditions, including strong winds and the swaying motion of vessels, pose significant challenges for drone landings.

This paper proposes a stable approach for multicopter landing on ships at sea, incorporating improved marker detection, enhanced wind resistance control, and more accurate deck motion prediction. In the marker detection phase, we introduce a method to improve the accuracy of ArUco …

Paleo-Environmental Change In Deer Lagoon, Whidbey Island Interpreted From Diatoms And Lithology, Lourdes Garcia

All Master's Theses

Puget Sound is a densely populated, tectonically active area that can be affected by earthquakes from local crustal faults and the Cascadia subduction zone capable of producing abrupt coseismic subsidence. Tidal wetlands are particularly sensitive to abrupt changes because they are depositional environments that reside at sea-level and their lithology and ecological communities are strongly controlled by elevation within the tidal frame. As a result, coseismic subsidence can disrupt established environmental gradients and leave distinguishable signatures preserved within the stratigraphy, like tidal mud directly over peat deposits. These preserved records provide an opportunity to reconstruct past earthquakes and associated relative …

A Web-Based Wizard-Of-Oz Platform For Collaborative And Reproducible Human-Robot Interaction Research, Sean O'Connor

Honors Theses

The Wizard-of-Oz (WoZ) technique is widely used in Human-Robot Interaction (HRI) research, but two persistent problems limit its effectiveness: existing tools impose technical barriers that exclude non-engineering domain experts (the Accessibility Problem), and the fragmented landscape of robot-specific implementations makes interaction scripts difficult to port across platforms (the Reproducibility Problem- concerning execution consistency and portability, not third-party replication). Through a literature review, I identified three design principles to address both: a hierarchical specification model, an event-driven execution model, and a plugin architecture that decouples experiment logic from robot-specific implementations. I realized these principles in HRIStudio, an open-source, web-based platform providing …

Barriers To Immunity: Understanding Covid-19 Vaccine Uptake In Africa, Emilia Blechschmidt

Honors Theses

This thesis examines the factors influencing COVID-19 vaccine uptake across African countries, with a focus on structural, informational, and behavioral barriers to immunization. Drawing on cross-country data, the study analyzes how access to transportation, reliable information, and healthcare resources shape vaccination rates, alongside the effect of demographics and institutional factors in shaping individual perceptions of risk and vaccine safety.

The findings emphasize that the broader strength and preparedness of national health systems strongly influence vaccine uptake. Countries that demonstrated higher coverage of routine childhood immunizations, such as polio and hepatitis B, also tended to perform better in COVID-19 uptake efficiency …

Law Librarianship And Legal Information Science In The Age Of Genai, Paul D. Callister

Faculty Works

This article examines the relationship between law librarianship and legal information science in the age of generative AI (GenAI), arguing that closer integration between the two is essential to navigating a rapidly evolving legal information landscape. It contends that law librarianship—long grounded in stable classification systems and cognitive authority—must adopt the analytical methods of legal information science to remain effective in the digital era. Together, these fields can reinforce the rule of law by improving the organization, retrieval, and stability of legal information. The article identifies emerging subfields of legal information science that support this integration and develops several concepts …

Indigenous Land Seizure & Environmental Injustice: Impacts Of Settler Colonialism, Lydia Moorman

Journal of Earth and Life Science

The fields of conservation and environmentalism prioritize ecosystem health, yet both emerged from western frameworks that displaced and criminalized Indigenous land stewardship. The idealization of “pristine wilderness” narratives served to justify the removal of Indigenous peoples from their homelands and erased millennia of sustainable land stewardship that had maintained ecological balance long before western conservation existed. These narratives not only misrepresented Indigenous relationship with land but also constructed a false dichotomy between humans and nature that positioned Indigenous presence as a threat rather than a source of ecological knowledge. Simultaneously, anthropogenic expansion; such as pipelines, mining, railroads, and other extractive …

Powering The Machine, Draining The Planet: Whether U.S. Environmental Law Is Equipped To Regulate The Energy And Water Demands Of Ai Data Centers, Michael Marcu

Journal of Earth and Life Science

Artificial intelligence (AI) data centers have become one of the United States' fastest-growing and least-regulated sources of environmental stress. In 2024 alone, U.S. data centers consumed 183 terawatt-hours (TWh) of electricity more than the entire nation of Pakistan and consumed an estimated 17 billion gallons of water (IEA, 2025; Berkeley Lab, 2024). By 2030, electricity demand from these facilities is projected to reach 426 TWh, a 133% increase in six years (Pew Research Center, 2025). This paper examines whether the existing U.S. environmental regulatory framework put by the National Environmental Policy Act (NEPA), the Clean Water Act (CWA), and the …

Spatiotemporal Dynamics Of Mountain Front Recharge Flow Paths And Their Contribution To Alluvial Aquifer Water Supply, Mikaela Bollag-Miller

Graduate Student Theses, Dissertations, & Professional Papers

Mountain Front Recharge (MFR) is a critical recharge source for alluvial basin aquifers throughout the Intermountain West, yet the spatial and temporal dynamics of distinct recharge pathways remain poorly constrained. This study investigates the seasonal and spatial dynamics of MFR pathways and evaluates their impact on the Missoula Aquifer, a sole-source alluvial aquifer in western Montana, USA. MFR includes both surface-water inflows from mountain areas and Mountain Block Recharge (MBR), the groundwater contribution to the basin aquifer. A valley-scale water balance was employed to estimate first-order contributions and temporal fluctuations of MBR flow paths. A three-layer steady-state MODFLOW groundwater model …

Understanding Motivations And Health Outcomes Of College-Aged Triathletes During Covid-19: A Mixed-Methods Study, Patrick Wilson, Eddie Hill, Justin Haegele, Xihe Zhu

Human Movement Studies & Special Education Faculty Publications

A triathlon is a multi-sport event that consists of three simultaneous events: swimming, biking, and running. This sport has experienced significant growth in the past few decades, with colleges and universities now participating. This exploratory mixed-methods study examined the motivations and perceived health benefits of college triathletes during the COVID-19 pandemic, using the Means-Ends of Recreation Scale and the Perceived Health Outcomes of Recreation Scale (N = 29), as well as semi-structured interviews (N = 4). Results indicate no difference in motives or health outcomes between male and female survey respondents. The thematic analysis of open-ended interview questions highlighted lived …

Inside Out: Improving Large Model Safety, Wei Zhao

Dissertations and Theses Collection (Open Access)

While Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) are at the frontier of current advancements in artificial intelligence, demonstrating remarkable capabilities across diverse applications, there are growing concerns about their reliability and security. LLMs remain vulnerable to adversarial attacks through carefully crafted prompts that circumvent safety mechanisms, while MLLMs face additional security challenges stemming from their multimodal nature. Despite considerable efforts in reinforcement learning from human feedback (RLHF) and supervised fine-tuning, existing safeguards have proven inadequate in addressing these critical vulnerabilities. This inadequacy stems from the fact that these models are inherently blackboxes that do not provide …

Eeg And Imu Gait Signal Processing: A Comparative Assessment Of The "Reza" Exponential Filter And Classic Filters, Reza Pousti, Daniel M. Russell, Derek C. Monroe, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

Noise degrades both EEG and gait signals, and classical IIR filters (Butterworth, Chebyshev, elliptic) involve trade-offs between passband flatness, ripple, and roll-off. This study compared a novel exponential "Reza" filter with these designs for neural and locomotor data. We analyzed an open-source mobile brain-body imaging dataset with EEG and gait data from 49 healthy adults (EEG: 256-channel, 512 Hz; IMUs: six APDM Opals, 128 Hz). EEG channels were grand-averaged and band-pass filtered at 0.5-50 Hz, while IMU axes were averaged and band-pass filtered at 0.5-5 Hz. The outcomes were signal-to-noise ratio SNR (dB) and band-integrated Welch PSD (EEG:0.5-50 Hz; IMU:0.5-5 …

Exploring The Synergy Between Very Large Transformer And Lstm Models For Effective Medical Captioning From Videos To Text: The Impact Of Captioning In Healthcare, R. V. Aswiga, Moin Ahmed Zahir

Data Science Faculty Publications

In today’s rapidly evolving digital landscape, the demand for accurate and contextually relevant subtitles for image and video content, particularly in the medical domain, is increasingly critical. Despite the proliferation of visual data across various platforms, existing captioning systems often struggle due to variations in visual settings, complex temporal relationships, and nuanced semantics. Additionally, challenges such as limited datasets, privacy issues, and specialized annotation requirements make medical image captioning particularly difficult. To tackle these challenges, we investigate cutting-edge deep learning methodologies, specifically Transfer Learning and Transformer models, through a comparative analysis. Specifically, we focus on Transfer Learning through the MedVisionCapturer …

A Decade Of Programming Languages: Trends In Popularity And Influence, Jonathan C. Erb

Williams Honors College, Honors Research Projects

Programming languages play a central role in open-source software ecosystems, yet their adoption, visibility, and influence shift over time as technologies, developer communities, and industry practices evolve. The study aims to investigate long-term trends in programming-language usage on GitHub from 2014 through 2024, focusing on ten major languages that represent diverse domains and ecosystems. Using repository metadata, engagement metrics such as stars and forks, and language-level code statistics measured with cloc, the analysis will examine changes in repository creation, code contribution volume, and popularity. Since popularity remains an unsettled and multidimensional concept, part of this research involves determining how it …

Reconstructing Lost Voices, Lana Tamim

Williams Honors College, Honors Research Projects

This project uses digital text mining tools (OCR, NLP, sentiment analysis, and topic modeling) to analyze 19th–20th-century newspaper archives, focusing on how marginalized groups (women, immigrants, or labor workers) were historically portrayed. Many historical newspapers were dominated by elite voices, so this project aims to recover silenced or misrepresented perspectives by identifying hidden patterns in language, frequency of coverage, sentiment, and shifts in public perception over time. Using machine learning and visualization tools, the project will create interactive maps and timelines showing how representation evolved across regions.