Digital Commons Network^™

Javatutor: An Integrated Llm Framework For Structured Programming Tutoring And Problem-Solving In Java, Amey Makarand Dhongade

Master's Projects

Large Language Models (LLMs) are being adopted more actively to assist in pro- gramming tasks, but much of the available AI code assistants devices are encouraging the rapid generation of solutions, as opposed to assisting students in developing an understanding. As a result, they can give the students correct code without teaching on how to judge a problem and how to build solutions or how to debug their programs themselves. This study describes JavaTutor, an LLM-based tutoring system that is used to assist learners in the learning process in a three-step process of understand- ing, generating a solution, and refining …

Towards Secure Program Partitioning For Smart Contracts With Llm’S In-Context Learning, Ye Liu, Yuqing Niu, Chengyan Ma, Ruidong Han, Wei Ma, Yi Li, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Smart contracts are highly susceptible to manipulation attacks due to the leakage of sensitive information. Addressing manipulation vulnerabilities is particularly challenging because they stem from inherent data confidentiality issues rather than straightforward implementation bugs. To tackle this by preventing sensitive information leakage, we present PARTITIONGPT, the first LLM-driven approach that combines static analysis with the in-context learning capabilities of large language models (LLMs) to partition smart contracts into critical (privileged) and normal codebases, guided by a few annotated sensitive data variables. We evaluated PARTITIONGPT on 18 annotated smart contracts containing 99 sensitive functions. The results demonstrate that PARTITIONGPT successfully generates …

Guidelines For Standard Basic Notations In Applied Statistics, Abhaya Indrayan, Shivani Saini Ms

COBRA Preprint Series

Whereas some statistical notations are standard and uniformly used by different workers, many are not. Varying notations lead to confusion among the readers, particularly those engaged with applied statistics material, such as medical professionals. This communication proposes that all basic notations be standardized so that the same notations are consistently used by different authors, in different books, journals, and articles for the benefit of those who are not rigorously trained statisticians. Guidelines for such standard notations are also provided. The lead must be taken by statisticians.

A Novel Lightweight Framework For Low-Light Image Enhancement Via Gaussian Denoising And Clahe, Daniel Oluwaseun Adesoji

Master's Theses or Doctor of Nursing Practice

Low-light image enhancement is a major challenge in digital imaging, especially in medical imaging, surveillance, and autonomous vision systems. Images captured under poor illumination often appear dark, noisy, and low in contrast, which makes it hard to observe important details. Traditional enhancement methods can improve brightness but usually introduce artifacts or increase noise. Although deep learning methods have shown strong performance, they usually require large datasets, and high computational resources. This creates a need for simpler and more efficient enhancement techniques. This study proposes a lightweight framework that incorporates Gaussian denoising with Contrast Limited Adaptive Histogram Equalization (CLAHE) to enhance …

Algorithmic Trading In Idiosyncratic-Payoff Markets: A Multi-Agent System For On-Chain Prediction Contracts, Saif Aldeen A.K. Agha

CMC Senior Theses

This thesis documents the design, deployment, and forward-test evaluation of an evolutionary multi-agent algorithmic trading system on Polymarket, the largest decentralized prediction market. The system pairs a locally-hosted 72-billion-parameter language model with a gradient-boosted statistical filter and an evolutionary selection mechanism that maintains a population of approximately 500 autonomous trading agents. Each agent generates a probability estimate for an event, compares it to the prevailing market price, and trades the resulting disagreement.

The central empirical exercise estimates a panel regression of trade-level profit on the absolute disagreement between the agent's probability estimate and the market price, controlling for agent identity, …

Interpretable Sample Uncertainty Measures For Ranked-Choice Election Polls, Jason Liang

CMC Senior Theses

Polling results from traditional single-choice plurality elections are readily interpretable. Simple frequentist population parameters are estimated, including each candidate’s total support and the size of the front runner's lead. If the point estimate for the size of the front runner's lead exceeds the margin of error of the lead, we can conclude that the poll shows a statistically significant front runner. However, the interpretability of these population statistics disappears when applied to ranked-choice voting elections. Because ballots rank multiple candidates and candidates are eliminated in rounds, simple population-wide parameters are not well-defined. In RCV elections, a candidate’s ability to win …

Bridging The Knowledge-Practice Gap In Breast Cancer Awareness: A Nationwide Online Cross-Sectional Kap Study Among Adult Females In Nigeria, Madinat Hassan, Taofeek Tope Adegboyega, Bilkisu Usman Farouk, Sunday Zeal Bala, Rachael Olufunmilayo Oduyemi, Kazeem Owolabi, Munir Sani, Miracle Uwa Livinus, Hannatu Usman Ayuba, Sadiq Hassan, Ifeyinwa Maureen Okeke, Abednego Shekari, Murtala Jibril

Chemistry & Biochemistry Faculty Publications

Background and Aims

Breast cancer (BCa) is a major cause of cancer morbidity and mortality among women in Nigeria, with late presentation contributing to poor outcomes. This study assessed knowledge, attitudes, and willingness to perform breast self-examination (BSE) among adult females in Nigeria and examined associated factors.

Methods

We conducted a descriptive cross-sectional online survey between February 16 and April 30, 2024. A structured, pretested questionnaire was disseminated through digital platforms, yielding 711 consenting adult female respondents from all six geopolitical zones. Knowledge, attitude, and willingness-to-perform-BSE measures were analyzed using descriptive statistics, linear regression, and binary logistic regression. Associations were …

Training Set Augmentation And Biology-Aware Harmonization Improve Radiomic Models For Lung Cancer Prediction In Indeterminate Nodules, Claire Huchthausen, Menglin Shi, Gabriel De Sousa, James Larner, Einsley Janowski, Jonathan Colen, Krishni Wijesooriya

Data Science Faculty Publications

CT radiomics-based machine learning has potential to predict lung cancer in pulmonary nodules (PNs) earlier than standard-of-care methods. Low malignancy rates in early-development PNs and variable image acquisition hinder development of radiomic models for diagnosing these PNs. To address these challenges, we augmented training using later-development PNs and harmonized for acquisition effects. We examine early-development benign and malignant PNs (n = 106) below the sensitivity of standard-of-care diagnosis. Classifiers predicting malignancy performed near chance when trained on ComBat-harmonized radiomic features from only early-development PNs. We then augmented training with later-development benign and malignant PNs (n = 225). We evaluated whether …

Exploring Causes Of Beam Loss At Cebaf, C. Matthews, J. Benesch, R. M. Bodenstein, B. Freeman, D. Moser, D. Turner, K. Price, J. Samari, B. Terzić

Physics Faculty Publications

At Jefferson Lab, the Continuous Electron Beam Accelerator (CEBAF) features a unique design with two linear accelerators and two arc sections allowing for multiple turns of the electron beam, as well as four experimental end stations. This topology leads to increased beam losses, especially in the spreader and recombiner regions connecting the arcs to the LINACs and in the extraction regions connecting the experimental end stations to the accelerator. These losses result in equipment activation and operational interruptions. Recent upgrades to the facility’s diagnostic systems, including the addition of xenon ion chambers, have provided higher-resolution data regarding these loss events. …

Real-Space Imaging Of The Electron-Pair Density Hole In Molecular Auger-Meitner Decay, Mats Simmermacher, Nathan Goff, Andres Moreno Carrascosa, Elke Fasshauer, Thomas Northey, Lingyu Ma, Haiwang Yong, Brian Stankus, Asami Odate, Xuan Xu, Wenping Du, Kyle Acheson, Joseph C. Cooper, Daniel Ratner, Mengning Liang, Ruaridh Forbes, Michael P. Minitti, Adam Kirrander, Peter M. Weber

Physics Faculty Publications

Electrons in matter can rearrange extremely quickly under external perturbations, underpinning subsequent structural and chemical transformations. Coulomb interactions between neighbouring electrons often shape this response, giving rise to correlated motion and strongly affecting the distribution of electrons in the system. Here we show that non-resonant hard X-ray scattering can directly access changes in the radial electron-pair density during the rapid rearrangement of core and valence electrons. We do this by studying sulfur hexafluoride molecules undergoing Auger–Meitner decay. We exploit a second-order interaction between the X-ray photons and the molecules to trigger and probe the decay dynamics with a single pulse, …

A Chandra View Of Spt-Cl J0217–5014: A Massive Galaxy Cluster At A Cosmic Intersection At Z = 0.53, Dan Hu, Shida Fan, Zhongsheng Yuan, Junjie Mao, Norbert Werner, Yuanyuan Su, François Mernier, Yuanyuan Zhao, Liyi Gu, Haiguang Xu

Physics and Astronomy Faculty Publications

Context. Galaxy clusters trace the densest regions of the cosmic web and are crucial laboratories for studying the thermodynamic and chemical evolution of the intracluster medium (ICM). The massive galaxy cluster SPT-CL J0217−5014 (z ∼ 0.53; M₅₀₀ ∼ 3 × 10¹⁴ M_⊙) is one of the Swift X-Ray Telescope serendipitous galaxy clusters with the highest reported Fe abundance (∼1.3 ± 0.4 Z_⊙ within ∼ 1_.^′7) and a potentially disturbed morphology.

Aims. SPT-CL J0217−5014 presents an intriguing opportunity to investigate ICM chemical enrichment and cool-core survival. With this study, we aim to …

Energy Levels Of Multiscale Bound States From Qed Energy-Momentum Trace, Michael I. Eides, Vladimir A. Yerokhin

Physics and Astronomy Faculty Publications

Energy levels of quantum electrodynamics (QED) bound states, which depend on a number of independent mass parameters, can be calculated as matrix elements of the QED energy-momentum tensor trace. As an example of such system we consider muonic hydrogen. The leading one-loop corrections to its energy levels depend on the electron and muon masses. These corrections are calculated as matrix elements of the energy-momentum tensor trace. Respective one-loop trace diagrams are different from the standard Lamb shift diagrams. We explain analytically and diagrammatically why two different sets of diagrams lead to the same results. Similar relationships should also hold beyond …

Fe Xviii–Xxiv Kβ Inner-Shell Absorption Lines In The X-Ray Spectra Of Neutron Star And Black Hole Binaries With Xrism, Masahiro Tsujimoto, Daiki Miura, Hiroya Yamaguchi, Ehud Behar, Chris Done, María Díaz Trigo, Chamani M. Gunasekera, Peter A. M. Van Hoof, Stefano Bianchi, Maryam Dehghanian, Gary J. Ferland

Physics and Astronomy Faculty Publications

The advent of the X-ray microcalorimeter spectrometer Resolve onboard the XRISM space telescope opened a new era for high-resolution X-ray spectroscopy of astrophysical plasmas. Many spectral features were newly detected, including the Kα and Kβ inner-shell transition lines of mildly ionized (F- to Li-like) Fe at 6–8 keV in the spectra of X-ray binaries and active galactic nuclei. The widely used atomic databases contain information on the Kα but not Kβ lines of these ions. We conducted the atomic structure calculation using FAC to derive the Fe Kα and Kβ lines and verified the …

Development Of Thermal Joints For Conduction-Cooling Applications, J. Lewis, G. Ciovati

Mechanical & Aerospace Engineering Faculty Publications

In support of the development of conduction-cooled superconducting radiofrequency (SRF) niobium cavities for use in continuous-wave linear accelerators, an experimental study of thermal contact resistance was performed on bolted joints using high-purity niobium, aluminium, and copper along with Apiezon N grease and indium foil as interfacial materials. The geometry of each joint investigated aims at replicating the design adopted in conduction-cooled SRF cavities currently under development at Jefferson Lab. The materials' thermal conductivity and the joints' thermal resistance were measured in the temperature range of 3.5 - 10 K. The results showed that the low thermal contact resistance of 2-4 …

Handwriting Recognition In Vr, Dominique Mosley

EWU Masters Thesis Collection

Virtual Reality (VR) is slowly becoming more popular for more than just entertainment. VR can be found in educational, office, and even healthcare settings to help discover more intuitive ways to teach, collaborate, and treat patients. Outside of the virtual world, these environments typically rely on writing for communicating or note-taking. Currently, VR input forces users to rely on clunky on-screen keyboards which disrupts the user’s immersion and breaks the flow of natural interaction. This thesis explores the potential of VR as a learning platform by combining it with artificial intelligence (AI). It aims to develop a VR-enhanced handwriting practicing …

Assessing Forest Health And Small Mammals After A Limited Suppression Wildfire In Colville National Forest, Samantha J. Kennel

EWU Masters Thesis Collection

In the face of a wildfire crisis, there is a growing need to expand the pace and scale of forest treatments, including the strategic use of wildfire as a management tool. However, ecological outcomes remain uncertain in forests shaped by more than a century of fire suppression. The 2022 Thor Fire, a managed wildfire in the Colville National Forest, Washington, provides an opportunity to evaluate forest health in a relatively understudied system. Using a control–impact design, I established 100 monitoring plots in burned and adjacent unburned forests to assess how wildfire and fire severity influence forest structure, fuels, and tree …

Relationships Between Benthic Macroinvertebrate Communities And Environmental Conditions In Headwater Tributaries Of The Pend Oreille Lake Watershed, Idaho, Devlin Mee

EWU Masters Thesis Collection

Benthic macroinvertebrates are widely used indicators of stream condition, and their communities respond to thermal and land-use conditions in headwater streams. This study characterized macroinvertebrate biomass, community composition, and diversity across forested headwater tributaries of the Pend Oreille lake watershed in northern Idaho, and examined their relationships with summer temperature, land development, and road proximity. Samples from thirteen streams collected in 2024 were identified to genus, measured, and converted to estimated biomass using published length–mass regressions; ten streams had recovered temperature loggers. Because environmental variables were characterized once per stream, all analyses were conducted at the stream level.

Estimated total …

Analyzing Sleep Architecture And Brain State Transitions Via Hidden Markov Models On Fmri Data, Brileigh Jay Cates

Masters Theses

Sleep is associated with systematic changes in brain activity and functional connectivity observable in functional magnetic resonance imagining (fMRI) signals. Because subjects often fall asleep during resting-state experiments, the absence of vigilance monitoring can confound the interpretation of resting-state dynamics. Although electroencephalography (EEG) is the gold standard for sleep staging, simultaneous EEG-fMRI acquisition is not always feasible.

This study investigates whether sleep stages can be inferred directly from fMRI using a probabilistic latent-state framework. Hidden Markov Models (HMMs) are applied to blood-oxygen-level-dependent (BOLD) time series to identify latent brain states and their temporal transitions. Inferred states are aligned with EEG-derived …

Investigating The Effects Of Atg3 On Autophagosome Size And Number, Keeran R. Senthil Kumar

Senior Honors Theses and Projects

Macroautophagy, or autophagy, is a highly conserved catabolic process in all eukaryotes which allows for the degradation of large cytosolic contents. It occurs in two forms: bulk autophagy, which is induced by nutrient deprivation and targets nonspecific cargo, and selective autophagy, which is induced by cellular stress and sequesters specific substrates. The process of autophagosome formation is carried out by a group of Atg (autophagy-related) proteins, one of which is Atg3. Atg3 functions as an E2-like enzyme by conjugating Atg8 — a ubiquitin-like protein — to phosphatidylethanolamine (PE), a step required for autophagosome membrane formation. This lipidation process is catalyzed …

Investigating The Impact Of Climate Change On Physical And Chemical Hydrology Of A Michigan Wetland, Emmalynn Boulton

Senior Honors Theses and Projects

Wetlands support biodiversity, regulate water cycles, and sustain ecological health. Understanding their functions and the relative contributions of groundwater and precipitation are key to conserving these ecosystems effectively, especially under changing climate conditions. Fish Lake Environmental Education Center (FLEEC) is 240 acres of diverse, glacially-influenced wetlands located near Lapeer, Michigan. This site encompasses a bog consisting of sphagnum moss and peat underlain by clay, as well as many glacial kettles that form ephemeral vernal pools during periods of frequent precipitation. Previous studies have shown that groundwater flows from the north to the southeast, from the bog towards Fish Lake. The …

Applied Machine Learning In Mineral Prospectivity Mapping In The South Pass-Granite Mountains Of Wyoming, Carl D. York

Graduate Theses/Dissertations

The South Pass-Granite Mountains, comprised of Archean to Tertiary rocks embedded with an Archean greenstone belt in Central Wyoming, have historically been mined for gold, iron, steel, and silver. Rare earth elements have been of increasing interest in the region and thus, several datasets have become available. Knowledge driven and data driven models are used in mineral prospectivity mapping with input data including geological mapping, geochemical data, geophysical (USGS Critical Mineral magnetic and gravity data), radiometric (U, Th, K) data and multispectral remote sensing data. Mineral prospectivity has seen a rapid improvement in recent years using advancements in machine learning …

Incremental Cluster Validity Indices And Their Role In Interpreting Lifelong Learning Systems, Niklas Max Melton

Doctoral Dissertations

Clustering and supervised learning are often treated as distinct paradigms, yet both rely on structure in feature space. This dissertation investigates the relationship between cluster validity indices (CVIs) and supervised learning in real-time and lifelong learning settings where data arrive incrementally and cannot be revisited. Across four studies, it develops methods for online cluster validation, uses supervised learning to improve their interpretability, and applies these ideas to evaluating performance degradation in continual learning.

The first study extends incremental cluster validity indices (iCVIs), enabling widely used validation metrics to operate in streaming environments. Experiments on synthetic and real-world datasets show systematic …

The Occurence Of Expansive Clay Soils In Illinois And Their Effects On Shallow Lightly Loaded Foundations, Greg James Gollaher

Masters Theses

"The damage caused to shallow foundations and slabs on grade by the shrink-swell activity of clay soils is well documented across the United States. There are local and national resources available that delineate areas that are problematic and areas that are not. These resources paint Illinois as an undemanding foundation environment. However, our experience differs from this. Our experience tells us that damage related to the shrink-swell activity of clay soils is widespread, and commonly severe causing not only cosmetic damage to structures and hard improvements but also affecting the serviceability and longevity of structures. My goal is to accurately …

Advancing Hate Speech Detection: Binary And Multiclass Approaches From Traditional Methods To Parameter-Efficient And Ontology-Guided Language Models, Mahmoud Abusaqer

Graduate Theses/Dissertations

The widespread proliferation of hate speech on social media platforms poses significant challenges for content moderation and user safety, requiring automated systems that are simultaneously accurate, efficient, and capable of fine-grained distinctions. This thesis investigates hate speech detection through five published manuscripts organized into two complementary threads: binary detection (hateful vs. non-hateful) and multiclass detection across demographic targeting categories. The binary thread progresses from a broad 38-model baseline spanning traditional machine learning, deep learning, and transformer architectures (where RoBERTa reaches 91.48% accuracy and CatBoost remains competitive at 88.60%) to parameter-efficient adaptation, in which Low-Rank Adaptation (LoRA) of large language models …

Remediation Impacts Metal Concentrations And Metal Tolerant Bacteria In Soils Of The Missouri Tri-State Mining District, Ophelia R. Pettington

Graduate Theses/Dissertations

After over 100 years of Zn and Pb mining in the Tri-State mining district (TSMD), former mines continue to be sources of metals. Metal contaminated soils can be remediated using plant-microbe interactions. Plants manipulate their microbiome and recruit microbes to increase metal tolerance. Remediating bacteria are site-specific and identifying native microbes can accelerate remediation efforts. Studies relating microbes and metal concentrations in remediated areas in the TSMD are scarce. I collected root and bulk zone soils associated with Andropogon virginicus from remediated and non-remediated sites in Webb City, MO. I used 16S rRNA gene amplicon sequencing to evaluate the bacterial …

Synthesis And Characterization Of The New G3 Family Of Organoantimony(V) Cyanoximates, Thao Trang Phan

Graduate Theses/Dissertations

Bacterial infections pose a serious threat to humans by developing resistance, rendering antibiotics ineffective. Of the 12 antibiotics recently approved since 2017, 10 belong to an already existing class. Various resistance mechanisms, such as reduced drug uptake, active efflux, drug inactivation, and target modification, can significantly reduce the efficacy of entire classes of antibiotics. Discovering novel strategies to overcome diverse mechanisms of resistance and improve therapeutic efficacy is in high demand. Inorganic compounds with organic ligands (both complexes and organometallics) represent a new class of compounds against which antimicrobial resistance has not yet been established. Recently, we discovered two series …

Investigation Of Mercury Bioaccessibility In Subsistence Fishes From The Canadian Subarctic, Kiran Mateo Sharma Mr

Theses and Dissertations (Comprehensive)

Fish consumption is the primary pathway for human exposure to methylmercury (MeHg), a global contaminant of concern known to cause adverse health effects. Fort Albany First Nation, a remote Indigenous community in northern Ontario that relies on fish for both subsistence and cultural practices, has expressed concern regarding the safety of local fish consumption. Community members and leaders have communicated several priorities for scientific research that are the foundation of this thesis. Specifically, consumers of wild-caught fish have asked how traditional cooking methods may affect mercury concentrations in fish, and how mercury concentrations in little-studied organs, such as liver and …

Theoretical Study Of Long-Range Molecular Interactions, Adrian Luis Batista-Planas

Doctoral Dissertations

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions—with electrostatic, induction, and dispersion as main components—play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well-established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed Long-Range-Fit (LRF), an interactive and user-friendly software package designed to automate …

Security And Energy-Efficiency In Federated Learning, Priyesh Ranjan

Doctoral Dissertations

Federated Learning (FL), which facilitates collaborative model training and protects users' privacy, has drawn great interest from the research community. With FL, the participants train their models on local data and submit the corresponding updates for aggregation to a server. While concealing the participants' identities, FL may attract adversaries aiming to hamper the underlying model. These adversaries aim to submit malicious weight updates that corrupt the performance of the server model. Further, these models when communicated to the participating clients extend the behavior which is undesirable. Additionally, FL suffers from increased energy consumption at the edge device level due to …

Essays On Accelerated Failure Time Models For Recurrent Event Data, Emmanuel Masavo Djegou

Doctoral Dissertations

Recurrent event data arise in many fields such as medicine, reliability, insurance, and economics, where the same event may occur repeatedly for a subject. Accelerated Failure Time (AFT) models provide an intuitive framework for relating covariates to event times and offer a useful alternative to proportional hazards models, allowing direct prediction of event timing under right censoring. However, existing AFT extensions for recurrent events, such as accelerated gap time (AGT) models, often fail to account for interventions between events and may not capture complex temporal patterns.

In this work, we first propose a class of semiparametric AGT models incorporating an …