Digital Commons Network^™

Clinical Value Of Chatgpt For Epilepsy Presurgical Decision-Making: Systematic Evaluation Of Seizure Semiology Interpretation, Yaxi Luo, Meng Jiao, Neel Fotedar, Jun-En Ding, Ioannis Karakis, Vikram R. Rao, Melissa Asmar, Xiaochen Xian, Orwa Aboud, Yuxin Wen, Jack J. Lin, Fang-Ming Hung, Hai Sun, Felix Rosenow, Feng Liu

Engineering Faculty Articles and Research

Background: For patients with drug-resistant focal epilepsy, surgical resection of the epileptogenic zone (EZ) is an effective treatment to control seizures. Accurate localization of the EZ is crucial and is typically achieved through comprehensive presurgical approaches such as seizure semiology interpretation, electroencephalography (EEG), magnetic resonance imaging (MRI), and intracranial EEG (iEEG). However, interpreting seizure semiology is challenging because it heavily relies on expert knowledge. The semiologies are often inconsistent and incoherent, leading to variability and potential limitations in presurgical evaluation. To overcome these challenges, advanced technologies like large language models (LLMs)—with ChatGPT being a notable example—offer valuable tools for …

Computational Modeling And Structural Generation Of Piano Music In The Classical Style, Yijing Feng

Dartmouth College Ph.D Dissertations

Listening to fast-tempo piano sonatas of the Classical period (circa 1750-1820) has been shown to have therapeutic effects for neurological disorders such as epilepsy. The limited existing repertoire of music in this style motivates the creation of more long-form, coherent compositions with clearly defined structure. Despite the long history of computer-based music generation and recent progress in deep learning, particularly transformer-based models, generating structurally coherent long-form music remains a major challenge. This difficulty stems from the scarcity of reliable structural annotation datasets, the computational demands of modeling very long musical sequences, and the lack of effective structural encoding in both …

On The H-Property For Step-Graphons: Residual Case, Wanting Gao

McKelvey School of Engineering Graduate Student Theses & Dissertations

We investigate the H-property for step-graphons. Specifically, we sample graphs Gn on n nodes from a step-graphon and evaluate the probability that Gn has a Hamiltonian decomposition in the asymptotic regime as n → ∞. It has been shown in Belabbas and Chen (2023); Belabbas et al. (2021) that for almost all step-graphons, this probability converges to either zero or one. We focus in this paper on the residual case where the zero-one law does not apply. We show that the limit of the probability still exists and provide an explicit expression of it. We present a complete proof of …

Interpreting Spatial And Temporal Variations In Global Air Quality Using A Chemical Transport Modeling Framework, Deepangsu Chatterjee

McKelvey School of Engineering Graduate Student Theses & Dissertations

Air quality is a major health concern. Exposure to fine particulate matter (PM2.5) and nitrogen oxides (NOx = NO + NO2) is a leading mortality risk factor across the world. Numerous cohort studies conducted over the past two decades have identified strong associations between ambient air pollution and human mortality, highlighting the adverse health effects of PM2.5 and NO2 exposure. My thesis includes three studies that contribute to a better understanding of air quality. In many regions, including South Asia, elevated emissions from various sectors and sparse ground monitoring are significant challenges. The concurrent development and use of the high-performance …

Computational Complexity Of Soundness Verification For Neural Networks, Scott Sirri

McKelvey School of Engineering Graduate Student Theses & Dissertations

Neural networks are an increasingly ubiquitous tool in systems of varying complexity across a range of domains. While these tools can be used to learn and predict complex functions, their opaque nature limits the scope of their acceptable applications. In particular, a lack of performance guarantees means that they are unsuitable for safety-critical applications such as self-driving cars and scheduling systems. Neural networks trained to solve NP-complete problems, in particular, are unlikely to be able to solve the problem exactly. However, a weaker soundness guarantee may be sufficient for some systems, e.g., that positive instances of the problem may be …

Transfer Learning For Temporal Logic Objectives, Lucas M. Santana Rovira

McKelvey School of Engineering Graduate Student Theses & Dissertations

Reinforcement learning algorithms can enable autonomous systems to learn the control skills needed to accomplish a task specified by a linear temporal logic formula. However, they cannot be transferred to a new task, even when the two are very similar. For each new task, the policy must be redesigned from scratch, which is a common limitation of existing reinforcement learning methods for temporal logic tasks. A proposed solution to this problem leverages the similarity between past and new tasks to reuse already learned control skills to accomplish the new task, with minimal or no retraining.

Rather than learning a single …

Cyber-Physical Security Through The Lens Of Ai-Enabled Systems, Zhiyuan Yu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Cyber-physical systems (CPS), powered by emerging artificial intelligence (AI) technologies, have become integral to various critical domains such as the Internet of Things (IoTs), medical devices, and autonomous vehicles. A unique aspect of these systems lies in their interactions with the physical world, by perceiving environments through heterogeneous modalities (perception), processing digital data with human-in-the-loop intelligence algorithms (computing), and autonomously actuating controls that affect physical processes (actuation). While this intricate fusion of cyber and physical components has unlocked unprecedented capabilities, it has also introduced new security challenges. However, traditional security measures often fall short in addressing these multifaceted threats. This …

Turn-On Fluorescent Glucose Transport Bioprobe Enables Wash-Free Real-Time Monitoring Of Glucose Uptake Activity In Live Cells And Small Organisms, Monica Soma Hensley, David Hutchings, Abdelrahman Ismail, Marina Tanasova

Michigan Tech Publications

The direct link between sugar uptake and metabolic diseases highlights the iminent need for molecular tools to detect and evaluate alterations in sugar uptake efficiency as approaches to identify disease-relevant metabolic alterations. However, the strict requirements of facilitative glucose transporters regarding substrate binding and translocation pose challenges for developing effective fluorescence molecular probes. Based on the state-of-the-art understanding of glucose recognition by facilitative transporters (GLUTs), we designed a glucopyranoside mimic - GluRho - that delivers the “turn-on” rhodamine B to live cells via glucose transport, including major transporters GLUTs 1-4. The high binding affinity achieved through the secondary interaction between …

Active Insight: Using Active Learning To Detect Students Who Need Help Asap, Eric Hicks

Electronic Theses and Dissertations Archive

CS Education has been plagued with high fail and dropout rates for some time. This has put a larger strain on traditional teaching practices and lead to many attempts to assist struggling students. To deal with these problems, many teachers started to incorporate software tools into their curriculum. By using platforms that came with copious examples and built in testing features, students were able to practice and learn on their own time with immediate feedback, although at a lesser quality. Researchers have often used student data to obtain a better understanding of how students will perform in the future with …

Hadronic Vacuum Polarization For The Muon G-2 From Lattice Qcd: Complete Short And Intermediate Windows, Alexei Bazavov, David Anthony Clarke, Christine Davies, Carleton Detar, Aida X. El-Khadra, María Elvira Gámiz Sánchez, Steven Gottlieb, Anthony Grebe, Leon Hostetler, William Jay, Hwancheol Jeong, Andreas Kronfeld, Shaun Lahert, Jack Laiho, Gerard Lepage, Michael Lynch, Andrew Lytle, Craig Mcneile, Ethan Neil, Curtis Peterson, James Simone, Jacob W Sitison, Ruth S. Van De Water, Alejandro Vaquero Avilés-Casco

School of Engineering, Computing and Mathematics

We present complete results for the hadronic vacuum polarization (HVP) contribution to the muon anomalous magnetic moment aμ in the short- and intermediate-distance window regions, which account for roughly 10% and 35% of the total HVP contribution to aμ, respectively. In particular, we perform lattice-QCD calculations for the isospin-symmetric connected and disconnected contributions, as well as corrections due to strong-isospin breaking. For the short-distance window observables, we investigate the so-called log-enhancement effects as well as the significant oscillations associated with staggered quarks in this region. For the dominant, isospin-symmetric light-quark-connected contribution, we obtain aμll,SD(conn)=48.139(11)stat(91)syst[92]total×10-10 and aμll,W(conn)=206.90(14)stat(61)syst[63]total×10-10. We use Bayesian model …

Beyond Boundaries: A Comprehensive Survey Of Transferable Attacks On Ai Systems, Guangjing Wang, Ce Zhou, Yuanda Wang, Bocheng Chen, Hanqing Guo, Qiben Yan

Computer Science Faculty Research & Creative Works

As Artificial Intelligence (AI) systems increasingly underpin critical applications, from autonomous vehicles to biometric authentication, their vulnerability to transferable attacks presents a growing concern. These attacks, designed to generalize across instances, domains, models, tasks, modalities, or even hardware platforms, pose severe risks to security, privacy, and system integrity. This survey delivers the first comprehensive review of transferable attacks across seven major categories, including evasion, backdoor, data poisoning, model stealing, model inversion, membership inference, and side-channel attacks. We introduce a unified six-dimensional taxonomy: cross-instance, cross-domain, cross-modality, cross-model, cross-task, and cross-hardware, which systematically captures the diverse transfer pathways of adversarial strategies. Through …

Should Physicians Take The Rap? Normative Analysis Of Clinician Perspectives On Responsible Use Of 'Black Box' Ai Tools, Ben H Lang, Kristin Kostick-Quenet, Jared N Smith, Meghan Hurley, Rita Dexter, Jennifer Blumenthal-Barby

Center for Medical Ethics and Health Policy Staff Publications

Background: Increasing interest in deploying artificial intelligence tools in clinical contexts has raised several ethical questions of both normative and empirical interest. One such question in the literature is whether "responsibility gaps" (r-gaps) are created when clinicians utilize or rely on such tools for providing care, and if so, what to do about them. These gaps are particularly likely to arise when using opaque, "black box" AI tools. Compared to normative and legal analysis of AI-generated responsibility gaps in health care, little is known, empirically, about health care providers views on this issue. The present study examines clinician perspectives on …

Deep Learning Classification Of Drainage Crossings Based On High-Resolution Dem-Derived Geomorphological Information, Michael Edidem, Bill Xu, Ruopu Li, Di Wu, Banafsheh Rekabdar, Guangxing Wang

Computer Science Faculty Publications and Presentations

High-resolution digital elevation models (HRDEMs) from LiDAR and InSAR technologies have significantly improved the accuracies of mapping hydrographic features such as river boundaries, streamlines, and waterbodies over large areas. However, drainage crossings that facilitate the passage of drainage flows beneath roads are not often represented in HRDEMs, resulting in erratic or distorted hydrographic features. At present, drainage crossing datasets are largely missing or available with variable quality. While previous studies have investigated basic convolutional neural network (CNN) models for drainage crossing characterization, it remains unclear if advanced deep learning models will improve the accuracy of drainage crossing classification. Although HRDEM-derived …

Enabling New Synthetic Platforms For Aryne Synthesis With Aryl Thianthrenium Reagents, Riley Augustus Roberts

Dissertations and Theses

The enormous importance of aromatic rings in organic molecules cannot be understated. Aromatic rings are present in the majority of pharmaceuticals, agrochemicals, and consumer products. The way in which these rings are arranged and substituted results in a molecule’s unique properties. Because of this, the current limitations of the chemical methods used to synthesize these molecules results in limited structural diversity and thus missed opportunities for the development of value-added products. To this end, this work demonstrates novel methods of aryne synthesis, aryl thianthrenium synthesis and a unique approach to structural scaffold hopping. The approaches presented herein allow for rapid …

Temperature-Driven Air Circulation In Caves With Blind Passages, Chris Hendy Dr, David J. Merritt, Shannon Corkill, Cross Cross

International Journal of Speleology

Two blind-passage show-caves in the Waitomo district of New Zealand, Ruakuri Cave and Aranui Cave, have been monitored for the impact of visitors on their environment, especially focusing on partial pressures of carbon dioxide because high levels cause speleothem degradation. In Ruakuri Cave, annual cycles of daily mean pCO₂ correspond with annual cycles of visitor numbers, both peaking in summer. The origin of the high pCO₂ had been assumed to be anthropogenic due to respiration from visitors. Prolonged intervals with no visitation during the Covid-19 pandemic saw the daily mean pCO₂ continuing to show the annual cycle, …

Development Of A Numerical Modeling Of The Flow In An Overtopping Device With Coupled Savonius Turbine, Vinicius Heitmann Avila, Rafael Gonçalves, Jaifer Martins, Emanuel Estrada, Liércio Isoldi, Luiz Rocha, Elizaldo Dos Santos

Seatific Journal

The study of wave energy conversion (WEC) technologies has been growing, with an emphasis on the overtopping device. Its operation is based on a ramp that directs wave water into an elevated reservoir. The accumulated water flows through a low-head tur-bine, generating electricity. This study proposes to develop a complete computational model to simulate a wave channel containing an overtopping device with a Savonius-type turbine inserted in the device's outlet duct. This study deals with the computa-tional modeling of a multiphase (air and water), turbulent, incompressible flow with constant thermo-physical properties, generated by the movement of numerical ocean waves. Verification/validation …

Southern Adventist University Commencement Program Spring 2025, Southern Adventist University

Commencement Programs

Program for Southern Adventist University Spring 2025 graduation. The commencement service took place on May 1, 2025 at 9 am and 1 pm in Iles Physical Education Center.

Evidence Of The Evolution Of Interdisciplinarity: A Study Of Boundary Objects In Information Science, Susan Berrigan Corieri

Dissertations - ALL

This research investigates interdisciplinarity within the field of information science through the lens of boundary objects, addressing the primary research question: How does an examination of academic boundary objects provide evidence of the evolution of interdisciplinarity? By analyzing four boundary objects, (1) a peer-reviewed journal, Journal of the Association for Information Science and Technology (JASIS&T) (2) an academic conference, the iConference, (3) university organizational structures of U.S. iSchools, and (4) the nomenclature used to refer to U.S. iSchool academic units, the study explores how these artifacts document the collaboration and evolution of academic communities in information science. Motivated by the …

Machine Learning Course: A 15-Week Interactive Curriculum With Code And Case Studies, Pegah Khosravi

Open Educational Resources

This open-access machine learning course is a comprehensive 15-week curriculum developed and published on GitHub with full Google Colab compatibility. It combines theoretical concepts with hands-on Python coding, real-world datasets, and structured projects covering regression, classification, clustering, deep learning, transformers, and multimodal AI. The course is designed for students, educators, and researchers interested in applied machine learning, including biomedical applications. It includes explainable AI components and ethical discussions to align with modern AI standards. The course is maintained by BioMind AI Lab at CUNY.

An Examination Of Writing Attitudes And Writing Proficiency Throughout A Performance Feedback Writing Intervention, Sophia Victoria Alderman

Theses - ALL

Writing attitudes, defined as self-assessments of liking or disliking writing (Ekholm et al., 2017), are important motivational factors that can impact writing development. A review of the literature on writing attitudes found that attitudes positively predicted writing achievement and that writing interventions can increase writing attitudes (Ekholm et al., 2017). Existing empirical literature has primarily focused on examining writing attitudes before and after implementing writing interventions, which vary in empirical support (Boscolo et al., 2012; ; Knudson, 1991b, 1992; Seban, 2012). However, no studies have dynamically assessed writing attitudes throughout the course of an evidence-based writing intervention with emerging writers. …

Authentically Assessing Student Learning In A Data Driven School System, Curtis Marolf

Art 895 Research Papers

As educators, we are often tasked with measuring student progress and understanding using standardized testing methods. As a visual arts instructor, I find these testing methods to be antiquated and inadequate for measuring students’ knowledge in the classroom, as they solely focus on an individual’s ability to recognize, recall or repeat factual data. If the goal of a quarterly assessment is to answer the question, “How do we know that the students know what we want them to know?” then standardized assessments are not the answer for the visual arts. The art classroom is a creative and expressive space, where …

Robotic Rhythm: A Contemporary Look At Ai-Driven Editing Tools’ Efficacy In Understanding And Replicating Creative Rhythm Editing Techniques., Alexander Selby-Lara, Charles Howard

Honors Thesis

It is undeniable that artificial intelligence (AI) has made its way into the film world. From AI-generated imagery and sound design in two 2025 Oscar nominees — The Brutalist and Emilia Pérez (Pulver) — to weekly updates and monthly beta releases of existing and new generative image and video models, AI-driven filmmaking tools are here to stay. But what does this mean for the post-production workflow? Much like camera development, editing technology has come a long way from flatbed film editors to Adobe Premiere Pro v. 25.0. Yet, despite each technological leap from system to system, the delicate task of …

Maximal Simple Regular Matroids, Elana Joy Israel

Dissertations - ALL

In 1980, Seymour completely classified regular matroids. In this thesis, we use this classification to provide a complete list of maximal simple regular matroids up through rank six. In each rank, exactly one of these is graphic. Additionally, there are one, two, and eight cographic, but not graphic, maximal simple regular matroids in ranks four, five, and six, respectively. In rank five, we also have the 10-element sporadic matroid, and in rank six we have a 12-element maximal simple regular matroid and 16-element maximal simple regular matroid, both of which are decomposable matroids that are not graphic, cographic, or sporadic. …

Towards The Next Generation Of Storage Stack For Nand Flash Memory-Based Systems, Ziyang Jiao

Dissertations - ALL

The explosive growth of data has led to increased attention on NAND flash-based solid-state drives (SSDs), which offer high performance, low power consumption, and significant capacity per unit volume when compared to traditional hard-disk drives (HDDs). However, as NAND flash memory density continues to scale, modern SSDs suffer from what is known as fail-slow symptoms, and their performance degrades over time as they wear out. In this dissertation, we focus on understanding and addressing the performance, reliability, and sustainability challenges of modern flash-based storage systems by modeling key metrics, analyzing the design tradeoffs between these metrics, and optimizing existing storage …

Asymptotics Of Fubini-Study Currents For Sequences Of Line Bundles, Melody Ann Wolff

Dissertations - ALL

Let $(X,\omega)$ be a Kähler manifold, and $L_p$ be a sequence of line bundles on $X$ equipped with continuous hermitian metrics $h_p$. Let $\gamma_p$ be the Fubini-Study current and $h_p^{eq}$ the equilibrium metric corresponding to the metric $h_p$. Our goal is to generalize a theorem of Tian in Complex Geometry to a setting using arbitrary line bundles equipped with metrics with non-positive curvature. This amounts to finding sufficient conditions for $\gamma_p-c_1(L_p,h_p^{eq})$, when appropriately scaled, to converge to $0$ in the sense of currents. To achieve this goal, we imply methods of Demailly and the Oshawa-Takegoshi Extension Theorem to bound a …

Quasiparticle Poisoning And Mitigation Strategies In Superconducting Qubits, Clayton Larson

Dissertations - ALL

Quantum computers promise to solve currently intractable problems of great interest for a diverse range of applications. For a quantum computer to solve these problems, it must handle occasional errors with quantum error correction, which distributes the quantum information across many physical qubits, increasing resilience. A promising technology for implementing such a system uses superconducting circuits as physical qubits. Standard quantum error correction schemes can accommodate random, local errors, but errors that are correlated across multiple qubits are fatal. Correlated errors can arise from ionizing radiation impacting the device substrate, which creates free charge that can be sensed by the …

Encircling Chains Around 4- And 6-Clusters In Fullerenes, Hannah Melissa Kimbrell

Dissertations - ALL

Fullerenes are purely carbon molecules which can be represented by a 3-regular planar graph consisting of only hexagonal and (exactly 12) pentagonal faces. Since carbon atoms have valence 4 but our graphs are trivalent we need to double the edges in a perfect matching to bring the valence up to 4. The edges in a perfect matching form a Kekulé structure and the hexagonal faces bound by three Kekulé edges are called benzene rings. A maximal independent set of benzene rings for a given Kekulé structure is called a Clar set, and the maximum possible size of a Clar set …

Development Of New Oxidative Methods And Synthesis Of Small Molecules For Modulation Of Biological Systems, Robert Eric Anderson

Dissertations - ALL

Oxoammonium salts have commonly been used to oxidize alcohols to aldehydes and ketones. More recently these reagents have been employed in several different oxidative transformations. Utilizing these reagents a new tandem elimination-oxidation process of tertiary alcohols has been developed. The new process yields an allylic ether which can be transformed to the alcohol easily through a reduction with zinc metal, removing the tetramethylpipyridyl protecting group derived form the oxoammonium salt. Mechanistically the reaction likely proceeds through oxoammonium salt mediated elimination followed by allylic oxidation through an ene-type mechanism. Due to the alcohol being protected by the easily removed oxoammonium salt, …

Automated Flaw Discovery In Decentralized Systems Via Semantic Fuzzing Tools, Yibo Wang

Dissertations - ALL

This dissertation studies the security challenges of blockchain transaction processing before consensus. While prior work has focused on consensus protocols and smart contract bugs, the pre-consensus infrastructure, such as the mempool and off-chain batching, remain underexplored. This dissertation aims to bridge that gap by systematically analyzing both transaction processing in the mempool and off-chain transaction batching for cost-optimization. This dissertation focuses on two core contributions. First, it presents MPFUZZ, an automated software fuzzing tool designed to uncover denial-of-service vulnerabilities in Ethereum mempools. This work is the first to formally define the mempool fuzzing problem and introduce bug oracles that detect …

What Is The Impact Of An Education Program Designed To Remove The Healthcare Professional As A Barrier To Care For The Transgender And Gender Diverse Community?, Richard D. Dansereau

Doctoral Projects

Healthcare disparities disproportionately affect transgender and gender-diverse (TGD) individuals, often due to implicit biases among healthcare providers. This study examines the impact of an educational intervention designed to address these biases and improve care for TGD patients. Using the Biased Care Model as a guiding framework, the intervention targeted three critical phases of bias: pre-visit assumptions, in-visit interactions, and post-visit decisions. Conducted in the intensive care unit of a mid-sized hospital in Northern California, the study employed a pretest-posttest quasi-experimental design involving multidisciplinary healthcare workers. Participants completed a modified Jefferson Scale of Empathy survey to assess changes in cognitive and …