Physical Sciences and Mathematics Commons^™

Hyper Face-Magic Graphs, Ross Belgram, Donald Mcginn

Theory & Applications of Graphs

For a planar graph G of order n, let F(G) be the set of all faces of G embedded into R 2 , including the exterior face. A bijective vertex labeling f : V (G) → {1, 2, ..., n} induces a face labeling f ∗ : F(G) → N defined by setting f ∗ (F) equal to the sum of all labels of the boundary vertices of F. The graph G is said to be hyper face-magic if there exists a vertex labeling whose induced face labeling is constant. In this paper, we state properties of hyper face-magic graphs …

Flip It And Reverse It: Probing Consistency Of Llm World Knowledge Under Logical Transformations, Rhianna Smith

Computer Science Senior Theses

When assessing the extent to which someone truly understands the topics they discuss, you might ask them a series of questions that examine their knowledge from different angles. As Large Language Models (LLMs) are increasingly integrated into real-world tasks, they are often required to reason through ambiguous and uncertain scenarios that rarely have a single correct answer. In these settings, their usefulness is contingent on more than accuracy alone. Rather, it depends on the strength of the reasoning that underlies their responses. This begs the question: how might we extend these types of tests to LLMs? We formalize this informal …

Fabrication Of Two-Dimensional Optoelectrical Devices, Holly Walworth

Honors Projects

Optoelectrical devices enable the exploration of interesting quantum states observed in two-dimensional (2D) condensed material systems. 2D materials, such as graphene and transition metal dichalcogenides, exhibit unique electronic properties, including the Fractional Quantum Anomalous Hall effect (FQAHE). The realization of the FQAHE offers a pathway toward topological quantum computing via non-Abelian anyons. Still, fabricating high-quality 2D optoelectrical devices remains a significant experimental challenge. Using mechanical exfoliation and stacking techniques within an inert argon environment, we attempted to fabricate optoelectrical devices using twisted molybdenum ditelluride (tMoTe2) and gallium telluride (GaTe). Three devices were successfully assembled; however, structural defects including hexagonal boron …

Investigating How Llm Trading Agents Integrate External Signals, Rohan Ray

Computer Science Senior Theses

Large Language Models are increasingly deployed in systems that assume more information leads to better decisions: RAG pipelines inject retrieved documents, tool-augmented agents call external APIs, and multi-model architectures route signals between specialized components. Whether this holds when both the information and the outcomes are noisy, and decisions compound over time, has received limited empirical attention. This thesis tests that assumption on LLM-based trading agents. Using StockBench (Chen et al., 2025) as our benchmark, we ran 150 backtests across 2 frontier LLMs (Kimi K2 and Qwen3-235B-Instruct), 12 augmentation strategies, and 5 random seeds, over 82 trading days — a period …

Comparison Of Fish Biomass And Fish Carbon Content Associated With Reef Sites At The Rio Grande Valley Artificial Reef In The Gulf Of Mexico, Allison K. White, Md Saydur Rahman, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

As global fisheries stocks have decreased due to overfishing and climate change, artificial reefs have gained significant attention. In addition to providing or restoring habitat, artificial reefs may serve as carbon capture sinks and potential climate mitigation strategies. The Rio Grande Valley (RGV) Reef is an artificial reef located in the northwestern Gulf of Mexico off the coast of Texas. The RGV Reef area spans 1,650 acres and is comprised of hundreds of groupings of recycled and pre-formed materials ranging from low relief (1–2 ft) to high relief (8–30 ft) reef structures. This reef provides a variety of novel habitat …

The Malaugh Operations And The Quadratic Invariant Gaps Of $\Si_4^C$, Forrest M. Hilton

ETDs from 2020-2029

Connected Julia sets of polynomials generally correspond to laminations, sets of chords of the unit disc that reflect the dynamics of the Julia set. If the circle is measured in revolutions and the polynomials studied are of degree $d$, then the dynamics on the lamination is given by the covering map $\sigma_d(t) := td \pmod 1$ where chords are mapped by their end points. Every lamination has at least one laminational invariant set, which is loosely an invariant complementary component of the lamination. That set has a significant impact on the shape of the Julia set. James Malaugh showed how …

2026 June 04- Tennessee Weekly Drought Summary, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Recognizing And Rewarding Peer Review: Rethinking Research Assessment For Openness, Fairness, And Global Equity, Tung Tung Chan, Bernd Pulverer, Johan Rooryck

FORCE 2026

The Coalition for Advancing Research Assessment (CoARA) Working Group on Recognizing and Rewarding Peer Review has developed a comprehensive framework for reforming how scholarly review is valued within research careers. Our recommendations address a fundamental question: how can peer review, a critical yet often invisible scholarly contribution, be made visible, credited, and meaningfully integrated into research assessment?

Developed through a collaborative effort across 16 European organisations, the Working Group’s outputs offer targeted recommendations for four key stakeholder groups: research performing organizations, research funding bodies, publishers and editors, and individual researchers. These recommendations are structured across five key dimensions:
(1) Openness: …

Open Research Information - How To Support Publishers To Make Metadata Openly Availble, Bianca Kramer

FORCE 2026

Research information, or scholarly metadata, is important for decision making around strategic priorities, distribution of resources, and evaluation of researchers and institutions. It is also used to assess the effect of policies, and to find and assess research results. Open research information (free to access and free to (re)use) is increasingly valued for fair assessment and equitable decision making, and is also important in digital sovereignty.


The Barcelona Declaration on Open Research Information calls on organizations performing, funding and evaluating research to make openness of research information the default, work with services and systems that support and enable open research …

Biologically Informed Negative Samplingfor Antibody Chain Pairing Classification, Ishita Singh

Computer Science Senior Theses

Antibody heavy and light chain (H/L) pairing is fundamental to antigen recognition and stability. While single-cell sequencing preserves native pairing information, widely used bulk repertoire and spatial transcriptomics platforms do not, motivating the need for efficient ML methods to infer H/L pairing. Training a binary classifier for this task faces the methodological challenge of a lack of true biological negatives, since natural selection eliminates B cells with incompatible H/L pairs.

In this thesis, I introduce a biologically informed negative sampling strategy for H/L pairing classification, drawing on known V-gene biases in heavy and light chain pairing. Pseudo-negatives are constructed by …

Mimic: A Multimodal Dataset For Affective Incongruity In Video, Ethan M. Baird

Computer Science Senior Theses

This thesis investigates the computational challenges of constructing a database for affective incongruity, exploring the difficulties in automating the collection of contradictory affective states. Capturing these incongruities is essential for advancing Vision-Language Models (VLMs) and sentiment analysis, which struggle to interpret signals deviating from basic emotional archetypes. Curating non-congruent affect provides the data necessary for models to navigate complex social contexts, which is critical for applications like automated Audio Description (AD) for the visually impaired and nuanced Human-Computer Interaction (HCI). To capture these signals, two distinct methodologies were employed. The first utilized a tripartite decomposition of video data, isolating textual, …

Representing Lean Proofs: Tactics, Trajectories, Search, Elisaveta Samoylov

Computer Science Senior Theses

In neural theorem proving for interactive proof assistants such as Lean, tactic prediction models score proof steps by surface likelihood, missing whether a move actually advances the proof. This thesis proposes representing each step by the symbolic edit it induces on the proof state rather than by its token-level surface form, and shows that this effect-grounded view yields better tactic embeddings, reveals structured geometry in complete proofs, and enables a practical proof search prior.

We introduce Delta Tokens — token-level state edits augmented with structural indicators — and show they outperform surface-only representations on tactic retrieval and operator-analogy benchmarks. Embedding …

A Global Internal Tide Modeling Framework For Improving Satellite Observations Of Fine-Scale Ocean Circulation, Badarvada Yadidya, Brian K. Arbic, Edward D. Zaron, Jay F. Shriver, Maarten C. Buijsman, Eric P. Chassignet, Loren Carrère, Michel Tchilibou

Faculty Publications

Small-scale oceanic eddies and filaments mediate the vertical exchange of heat and carbon within the global ocean. The Surface Water and Ocean Topography (SWOT) mission resolves these features through wide-swath interferometry, but internal tides often mask these observations. Non–phase-locked internal tides present special difficulty because they vary with the evolving ocean background. We show that this chaotic variability can be predicted. We use a data-assimilative ocean forecast model to resolve the mesoscale environment and separate tidal signals from the broader circulation. The model captures the organized structure of these incoherent waves in the independent SWOT measurements. Correcting for the total …

Residential Ai Data Centers: Security, Privacy, And Governance Concerns, Alan Saquella

Publications

The concept of placing mini data centers and distributed AI computer nodes inside residential homes may appear innovative from an energy efficiency perspective, but it introduces significant security, privacy, governance, and liability concerns. What is effectively occurring is the expansion of commercial and potentially critical infrastructure into lightly protected residential environments.

Once a residence becomes part of a distributed computer grid supporting hyper-scalers, AI providers, or enterprise workloads, the home is no longer simply a private residence. It becomes a commercial technology asset, a potential cyber target, and even a physical target. A distributed network of thousands of residential nodes …

Llzk-Symex: Building A Circuit Verification Framework For The Llzk Zero-Knowledge Intermediate Language, Nicolás Iair Schaievitch

Computer Science Senior Theses

The rising adoption of ZK (Zero-Knowledge) technology has led to a plethora of DSLs (Domain Specific Languages) for facilitating the development of ZK circuits. At the same time, there has also been an increase in the number of compilation targets for these languages, with different cryptographic foundations and performance optimizations. LLZK, by Veridise, aims to unify the ecosystem by providing a single IR (Intermediate Representation) for the different frontend DSLs, that would then also allow choosing between different backends. Given the high stakes (particularly financial) that a lot of ZK circuits are under, together with their high level of complexity, …

Capturing Large Language Model Similarity Through Spectral Analysis, Ishan Verma Prasad

Computer Science Senior Theses

With the rapid development of open-sourced models on Huggingface, there is a strong need for a way to systematically determine the similarity between models. More strongly, for intellectual property and organization, we need a way to determine the "lineage" of models. We borrow principles from Heavy-Tailed Self-Regularization and Random Matrix Theory to provide an inference-free method to accomplish this. We cluster a corpus of several model families by their spectral fingerprints and demonstrate that each model family occupies a distinct region in weight space. This confirms prior ideas of training setups leaving artifacts on model weights and allows us to …

Knockout Tournaments: An Investigation Of Stability, Isabelle Han

Computer Science Senior Theses

Knockout (or single game elimination) tournaments are a competition format widely used to determine a single winner from a pool of participants. However, the seeding, or the initial pairings set by the organizers of the tournament, can dramatically change each participant's probability of winning. This paper introduces stability as a property of tournaments. More specifically, a tournament is stable if no pair of players can be found such that they both wish to swap initial positions. This property is adapted from prior work on stable matchings and is therefore a well-defined structural property.

We investigate three theoretical questions on the …

Reliability-Aware Mixture-Of-Agents For Robust Ai-Generated Image Detection, Jake Jump, Yu-Wing Tai

Computer Science Senior Theses

Detecting AI-generated images requires reasoning across multiple levels of evidence, ranging from low-level statistical artifacts to high-level semantic inconsistencies. Existing approaches typically rely on a single class of signals or emphasize complex multi-agent coordination, which limits robustness under distribution shifts and common image degradations. We propose a reliability-aware Mixture-of-Agents (MoA) framework that treats Vision-Language Model (VLM) agents and computational features as complementary experts and aggregates their predictions based on empirically calibrated reliability. Rather than relying on intricate inter-agent reasoning, our approach centers on structured aggregation: high-precision “anchor” agents drive predictions, while weaker but complementary signals are adaptively incorporated to resolve …

Dancing For The People: A Culturally Grounded Learning-To-Rank Framework For Powwow Dance Evaluation, Avery C. Sutherland

Computer Science Senior Theses

Powwow dance is a form of Indigenous expression that combines movement, storytelling, regalia, and community values. Within competition powwows, dancers are evaluated through a highly subjective judging process that often lacks standardized criteria, creating challenges for consistency, transparency, and fairness. This work investigates whether a learning-to-rank framework can model subjective powwow dance preferences while remaining grounded in the cultural context of the practice. To support this research, a new dataset was constructed consisting of 19 Women's Fancy Shawl dancer profiles and 236 pairwise preference labels collected from experienced members of the powwow community. Each dancer profile combines textual descriptions, images, …

Rscore - A Tool For Learning And Quantifying Software Infrastructure Resiliency, Selena Yujia Zhou

Computer Science Senior Theses

As LLMs take over writing code, infrastructure resilience has become the central challenge of software development, especially for gaming applications, where latency, availability, and scale demands are extreme. However, holistic software infrastructure is difficult to understand for casual developers because of the multiple layers of abstraction that make up an application, and the lack of structured information from proprietary companies. This thesis explores the creation of rscore, a tool that quantifies software infrastructure resiliency and subsequently educates developers about the architecture of any existing gaming application. The tool generates two graphical models of a game’s early versus current infrastructure and …

Holistic Strategies For Optimizing Municipal It Operations And Cost Efficiency, Joseph Yazdanpanahi

Certified Public Manager® Applied Research

Municipalities work to deliver secure and impactful IT (information technology) services while often working within tight budget constraints. To address this problem, this article offers an experience-based and comprehensive framework to optimize municipal IT operations. It emphasizes leveraging automation, streamlining hardware and software management, and forging strategic partnerships to drive cost savings and efficiency gains. Designed to equip municipal IT leaders with practical tools and insights, this article aims to help modernize IT processes.

Winddensity-Mbir: Model-Based Iterative Reconstruction For Wind Tunnel 3d Density Estimation, Karl J. Weisenburger, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Faculty Publications

Experimentalists often use wind tunnels to study aerodynamic turbulence, but most wind tunnel imaging techniques are limited in their ability to take non-invasive three-dimensional (3D) density measurements of turbulence. Wavefront tomography is a technique that uses multiple wavefront measurements from various viewing angles to non-invasively measure the 3D density field of a turbulent medium. Existing methods make strong assumptions, such as a spline basis representation, to address the ill-conditioned nature of this problem. We formulate this problem as a Bayesian, sparse-view tomographic reconstruction problem and develop a model-based iterative reconstruction algorithm for measuring the volumetric 3D density field inside a …

Ai, Translation, And Telling The Truth, David I. Smith

University Faculty Publications and Creative Works

I am working on a large translation project this year. I have been surprised to find several conversation partners voicing the assumption that I am getting AI to do the translating for me. I’ve been wondering how to respond.

A short, but in the end inadequate answer is that, impressive as the current variations on machine translation are, they still get things wrong. Neural machine translation services such as Google Translate and DeepL still produce oddities fairly regularly. I have been working lately with seventeenth-century Czech texts, an area in which I would expect machine translation to struggle a little …

A Comprehensive Survey Of Artificial Intelligence Applications In Predicting Mining-Induced Subsidence, Deformation, And Landslides: Strengths, Limitations, And Future Trends, Long Quoc Nguyen, Dung Ba Nguyen, Minh Tuyet Dang

Journal of Sustainable Mining

Mining activities often cause mining-induced ground deformation, including subsidence and landslides, and related geo-environmental impacts, posing significant risks to infrastructure and safety. This study conducts a systematic assessment to identify, categorize, and evaluate AI-based methods (machine learning, deep learning, and hybrid models) for predicting and monitoring mining-induced ground deformation. The literature search was performed across major scientific databases, using predefined keywords and selection criteria, resulting in a final dataset of relevant peer-reviewed studies. The reviewed works were classified into three methodological groups: traditional machine learning, deep learning-based approaches, and hybrid methods. The results show that ML still dominates in terms …

On The Fractional Laplacian Type Operator, Maysam Abdulnaser Zain

Thesis/ Dissertation Defenses

In this thesis, we study analytical structures arising from Dunkl theory and their applications to harmonic analysis and fractional Laplacian operators. Dunkl operators are differential-difference operators associated with finite reflection groups, providing a natural generalization of the classical Fourier analysis through the introduction of root systems and multiplicity functions. Within this framework, several classical transforms appear as special cases of the (k,a)-generalized Fourier transform. We study the generalized Fourier transform, its kernel, and the associated translation operator and convolution structures. Using these tools, we construct the corresponding heat kernel and analyze the associated heat semigroup. Our main contribution concerns the …

Structure-Property Relationship In Low-Dimensional Cesium Metal Halides: Coordination Chemistry, Luminescent Mechanism And Optoelectronics Applications, Sheikh Jobe

Thesis/ Dissertation Defenses

Low-dimensional metal halides are gaining popularity in optoelectronic applications owing to their interesting optical properties and structural diversity. In general, low-dimensional metal halides refer to one-dimensional and zero-dimensional structures. The main difference between the two is that one-dimensional structures have chain-like connectivity, whereas zero-dimensional structures consist of isolated units. Their optical properties are mainly determined by the B-site metal ion, which is coordinated to halide ions in trigonal, tetrahedral, or octahedral geometry. In particular, copper (I) and manganese (II) metal halides are emerging as novel materials for solid-state lighting, and anti-counterfeiting applications. The two well-known phases of cesium copper (I) …

Decoding Stock Market Movements: The Role Of Unemployment And Volatility, Bipllab Roy, Suparna Bhattacharjee

Northeast Journal of Complex Systems (NEJCS)

This study investigates how unemployment and market volatility interact with stock prices in the Indian context, framing the stock–labour–volatility nexus as a complex adaptive system (CAS) rather than a set of linear, time-invariant relationships. Using verified secondary data on unemployment, India VIX, and NSE stock indices for 2013–2023, we first apply simple and multiple regression as a descriptive baseline. Results show a strong negative association between unemployment and stock prices (R ≈ 0.824, R² ≈ 0.68, p < 0.05), consistent with Keynesian demand-side channels, while the linear VIX–stock relationship is weak and statistically insignificant (R² ≈ 0.07, p > 0.05), consistent with the expectation that volatility operates through non-linear, regime-dependent mechanisms not captured by OLS.

Importantly, we document and transparently disclose critical …

Olaf: Towards Robust Llm-Based Annotation Framework In Empirical Software Engineering, Mia Mohammad Imran, Tarannum Shaila Zaman

Computer Science Faculty Research & Creative Works

Large Language Models (LLMs) are increasingly used in empirical software engineering (ESE) to automate or assist annotation tasks such as labeling commits, issues, and qualitative artifacts. Yet the reliability and reproducibility of such annotations remain underexplored. Existing studies often lack standardized measures for reliability, calibration, and drift, and frequently omit essential configuration details. We argue that LLM-based annotation should be treated as a measurement process rather than a purely automated activity. In this position paper, we outline the Operationalization for LLM-based Annotation Framework (OLAF), a conceptual framework that organizes key constructs: reliability, calibration, drift, consensus, aggregation, and transparency. The paper …

Mathematical Analysis Of Within-Host Models: Viral–Immune Dynamics, Bifurcations, And Disease Severity, Nazia Afrin

Doctoral Dissertations

My research develops and analyzes ODE-based within-host models at multiple scales. Using dynamical systems theory and numerical methods, I study host–pathogen interactions and immune responses, providing insights into disease dynamics and control. The first model describes the complex dynamics of Hepatitis B virus (HBV) infection and addresses the question: what mechanisms determine whether the infection is cleared during the acute phase or progresses to a chronic state? A key feature of this model is the assumption that all classes of liver cells (uninfected, infected, and protected from reinfection) proliferate at different rates. The findings provide insight into two important aspects …

The Impact Of Evolution And Strong Allee Effects On The Dynamics Of A Discrete-Time Predator-Prey System, Neerob Basak

Doctoral Dissertations

This dissertation investigates the dynamics of discrete-time predator-prey systems, focusing on both evolutionary responses and ecological interactions. The first part of this dissertation, in Chapters 2 and 3, explores how evolutionary processes, particularly the development of resistance to toxicants in predators, influence the persistence and stability of predator-prey populations. In this part, we extend the predator-prey model developed in Ackleh et al., 2019 to incorporate the evolution of a predator's resistance to toxicant effects. We consider three cases: (1) lethal effects, where the toxicant directly influences the predator's survival; (2) sublethal effects, where the toxicant impacts the predator's fecundity, and …