Digital Commons Network^™

Efficient Compression Framework For Time Series Self-Supervised Learning, Brooklyn Berry

Theses and Dissertations

Time series data is perhaps one of the most broad data types that exist and is studied by diverse research fields. Recently, Self-Supervised Learning (SSL) training frameworks, the training frameworks to pre-train deep learning models without human annotations, have been proposed. Because human annotation for time series is typically associated with being costly, there is a growing interest in developing effective SSL for time series data. In SSL, the pre-trained model will often produce a time series embedding series summarized from the original time series to ensure temporal information is preserved. Although such representation can effectively capture the semantic information, …

Empowering Latinas In Computer Science: Success Stories And Challenges, Martin Jalomo

Theses and Dissertations

Latina women remain significantly underrepresented in computer science, and limited research centers their lived experiences within the field. This qualitative narrative inquiry examined how Latina women who completed computer science degrees and secured employment persisted in predominantly male and non-Latina environments. Guided by Yosso’s (2005) Community Cultural Wealth framework, the study explored how participants leveraged forms of capital to navigate structural, relational, and psychological barriers. Data were collected through narrative interviews with five Latina graduates and analyzed using thematic and cross-case analysis. Findings indicate that underrepresentation shaped participants’ sense of belonging while persistence was supported through aspirational, familial, social, navigational, …

Data Driven Monitoring And Control Of Laser Powder Bed Fusion Process, Jose De Jesus Galarza

Theses and Dissertations

The Laser Powder Bed Fusion Process (LPBF) has been one of the main processes of additive manufacturing, enabling the manufacturing of complex geometries, customization, and lightweight parts. Modern LPBF processes have integrated monitoring systems that capture the light emissions per layer for quality assurance. However, standard defect detection algorithms have not yet achieved the high precision required due to the inherently variable nature of the signal, insufficient data for model training, and the confounding effects of the print.

The processes still have some challenges, such as characterizing the roughness from the build parameters alone, improving the pore detection using the …

Advances In Computational Methods For Sparsity-Promoting Linear Inverse Problems, Jonathan Lindbloom

Dartmouth College Ph.D Dissertations

Inverse problems arise throughout science and engineering, where indirect, incomplete, and noisy observations are used to recover unknown parameters of interest. In these applications, the corresponding forward or measurement models are often ill-conditioned or underdetermined, so direct inversion is unstable and regularization is required. This thesis develops computational methods for linear inverse problems in which the unknown is assumed to be approximately sparse in a transformed domain defined by a linear, possibly rank-deficient operator, such as a finite-difference matrix, with particular emphasis on large-scale problems.

The thesis makes three main contributions. First, it generalizes hierarchical Bayesian maximum a posteriori estimation …

My Journey As A Migrant Bilingual Learner From Student To Teacher: Lessons Learned, Sylvia Lopez

Theses and Dissertations

These reflections in this thesis are an analysis of narratives based on my lived experiences as an immigrant, migrant student who is now a certified Bilingual & Special Education teacher servicing students, many of whom are bilingual, in public school classrooms. My goal is to connect my life experiences to teaching practices and thus embrace and celebrate my linguistic identity. Bilingual educators have a language learning journey that drives their classroom practices. When bilingual teachers reflect on their bilingual trajectory and connect their life experiences to research, they may provide spaces for stronger positive impacts on bilingual students, and their …

Insights Into Androgen Receptor Allosteric Modulation By P,P'-Dichlorodiphenyldichloroethylene Binding At The Binding Function-3 Site And Site-Specific Binding Function-3 Mutations, Emanuel Aggeo Flores

Theses and Dissertations

One of DDT’s metabolites, p,p’-dichlorodiphenyldichloroethylene (DDE), has been classified as an endocrine disrupting chemical (EDC) due to its ability to interfere with hormone signaling by binding to nuclear receptors (NR) such as the androgen receptor (AR).

Structurally, the AR contains a ligand-binding domain (LBD) where endogenous steroids bind. Furthermore, the LBD contains a surface binding site known as binding function-3 (BF-3), which studies suggest exerts an allosteric effect on bound DHT when small, hydrophobic molecules bind.

Here, we present a study that examines how specific BF-3 site mutations and DDE binding affect steroid stability within the LBP utilizing computational methods. …

Exploring The Role Of Video Games In Civil Engineering Education And K-12 Stem Engagement, Jillian S. Codron

Architectural Engineering

Civil engineering education has traditionally emphasized a linear progression from theory to application, with foundational concepts introduced in lecture before being reinforced through laboratory or design experiences. While effective for advanced learners, this approach can limit early engagement for K–12 students who may struggle to connect abstract principles to realworld engineering practice. This project examines the use of video games as interactive, feedback-driven environments for introducing civil engineering concepts and practices to younger learners in more exploratory and accessible ways.

The study pursues four primary objectives: evaluating the educational affordances of selected video games; examining how gaming experiences have influenced …

I Am Still Learning, Too!: Pre-Service Teachers' Experiences Of Mathematics Anxiety In An Inquiry-Based Mathematics Education Course At Utrgv, Jeremiah James Adriano Dela Rosa

Theses and Dissertations

Mathematics anxiety is a prevalent issue in mathematics education that negatively impacts students’ learning, performance, and engagement in mathematics. Prior research suggests that mathematics anxiety is often shaped by students’ experiences and emotional responses within the classroom environment.

The purpose of this study is to explore how Pre-Service Teachers experience mathematics anxiety in an Inquiry-Based Mathematics Education (IBME) classroom. This study employed a qualitative research design supported by descriptive survey data collected through the Abbreviated Mathematics Anxiety Scale (AMAS), selected components of the Fennema-Sherman Mathematics Anxiety Scale (FSMAS), and semi-structured interviews. The survey instruments were used to provide descriptive background …

Do I Have To Know Someone? The Impact Of Factors Beyond The Playing Field That Affect Mlb Hall Of Fame Voting., Jackson Wollscheid

Economics Undergraduate Honors Theses

With the creation of WAR (Wins above Replacement), it has created an index to measure the player’s value using a variety of statistics relevant to that player’s position. The higher a player’s career WAR then the greater the impact that player had on the game during his career. However, players are not simply inducted into the Hall of Fame on this measure of value but on voting from members of the BBWAA (Baseball Writers’ Association of America). This research investigates external factors outside of standard playing statistics’ influence on Hall of Fame voting, including team affiliation, career length, and other …

F.L.A.I.R. -- A Flow-Level Autoencoder For Intrusion Recognition, Joseph P. Dumond

Electrical Engineering and Computer Science Undergraduate Honors Theses

Industrial Internet of Things (IIoT) networks underpin critical infrastructure worldwide, yet securing them remains an open challenge. Traditional intrusion detection systems require labeled attack data for training, a resource that is rarely available in real industrial deployments. They also fail against novel threats, a model trained on known attacks has no basis for detecting anything outside its training set. This thesis presents a Flow-Level Autoencoder for Intrusion Recognition, or FLAIR, a fully unsupervised deep learning system for network intrusion detection in IIoT environments. FLAIR is built on a Gated Recurrent Unit (GRU) autoencoder trained exclusively on normal network traffic. Rather …

From Mobilenet To Repvit: A Survey Of Edge-Optimized Computer Vision Architectures, Eli A. Bosch

Electrical Engineering and Computer Science Undergraduate Honors Theses

Edge-optimized computer vision is a constantly evolving field where the definition of efficiency has changed repeatedly. This thesis presents a literature survey of four recent Convolutional Neural Network (CNN) families, all analyzed through a consistent framework of accuracy, parameter count, and Multiply-Accumulate Operations (MACs), alongside a survey of five CNN and Vision Transformer (ViT) hybrid models to examine the direction of the field. It was found that accuracy follows a logarithmic curve with respect to parameter count, exhibiting diminishing returns as models scale. This suggests that architectural design contributes more to performance gains than parameter count alone. Theoretical efficiency metrics …

A Case Study On Using Large Language Models To Drive Convergence-Oriented Literature Discovery In Critical Infrastructure Security, Caden J. Williamson

Electrical Engineering and Computer Science Undergraduate Honors Theses

In the world of cybersecurity, the rapid development of artificial intelligence proposes a constant challenge for researchers to defend critical infrastructure. Attacks on critical infrastructure can be catastrophic, and emerging strategies of cyber-adversaries that implement leading AI models can expose vulnerabilities in critical infrastructure much faster than previous tools. To defend against this emerging threat, the Cybersecurity Research Working Group at the University of Arkansas is aiming to develop a cross-domain and cross-discipline center of excellence. To support this effort, the group is writing a literature review on the topics of AI and critical systems security. Literature review is an …

Multi-Task Growing Interpretable Neural Network For Multi-Target Symbolic Regression, Hussein Rajabu

All Theses

Over the past decade, deep learning has achieved remarkable success across domains such as computer vision and natural language processing. Despite their strong predictive capabilities, these models often function as black boxes, limiting transparency and making them difficult to trust in high-stakes applications such as healthcare and business decision-making. While explainable artificial intelligence (XAI) methods improve interpretability, most approaches remain post-hoc, focusing on statistical associations rather than uncovering the underlying functional mechanisms governing predictions.

Symbolic regression (SR) has emerged as a promising direction within XAI by directly discovering explicit mathematical expressions that describe relationships between inputs and outputs. Unlike traditional …

Prism: Priming Relationships In Syntax And Mathematics, Michelle J. Zhu

Honors Scholar Theses

The implementation of sheltered education programs has become increasingly prevalent in schools as new research in second language acquisition emerges. Yet despite this growing attention to ESL instructional practice, far less is known about the cognitive processes that underlie how bilingual students engage with academic content. This study investigates cross-domain structural priming between mathematical and linguistic processing in monolingual and bilingual individuals, focusing on how bilingual experience influences syntactic attachment preferences. Prior research suggests that mathematical and linguistic structures share underlying cognitive representations, and that exposure to structures in one domain can influence processing in another. Additionally, bilingualism has been …

Csbsju Ash Tree Maps, Trevor Barton

Celebrating Scholarship and Creativity Day (2018-)

Ash trees in MN are recently susceptible to the invasive species of Emerald Ash Borer. These insects burrow into native MN ash trees, lay their larvae, and significantly harm or kill the trees. MN native ash trees are not equipped to deal with this invasive species and rather need to be chemically treated to save the trees. These maps depict the GPS locations of the ash trees on CSBSJU campus proper. Trees were mapped by hand with a Garmin GPS device while size, health, and value to campus assessments were recorded to pair along with the maps in a separate …

The Implications Of Music Therapy On The Human Mind, Mckayla Martin

Senior Honors Theses

Music therapy harnesses the power of music in clinical settings. It is primarily used to support mental health. Music affects areas such as anxiety, memory, and brain plasticity. Therapeutic music practices can reduce stress and anxiety, enhance specific types of long-term memory, and encourage neuroplasticity. It is an effective, non-invasive treatment for those experiencing mental distress. Ongoing research on the effectiveness of music therapy in clinical settings has the potential to significantly improve the treatment of mental illness, disorders, and disabilities.

Know Thy Enemy: Building A Command-And-Control Solution For Adversarial Emulation, Caleb J. Chen

Senior Honors Theses

Command and Control (C2) is a critical part of any cyberattack. It serves many purposes, including Distributed Denial of Service (DDoS) attacks, data exfiltration, and malware deployment. Consequently, C2 frameworks play an important part in red team engagements and adversary emulation. However, many adversary emulation solutions focus on comprehensive testing through sequential technique execution instead of realistic chained and automated attacks. The proposed solution is Centurion, an open-source C2 framework that integrates MITRE's ATT&CK framework and several cybersecurity tools into modular playbooks for effective threat emulation. This paper provides background by defining key terms and concepts before delving into a …

You Can’T Spell Audit Without Ai: The Current Uses Of Artificial Intelligence In Audit, Jena Perkins

Senior Honors Theses

The accounting profession continuously adapts to the innovations provided by the broader context in which it exists. Artificial intelligence (AI) is a forerunner among tools used to enhance and optimize auditing services within the accounting profession. The realm of AI offers advancements to procedures used within an audit to detect misstatements. Based on the proprietary platforms developed by Big 4 accounting firms, AI is a key component in maintaining an advanced approach towards auditing.

Rhodium On Alumina Catalyzed Hydrodechlorination Of Trichlorethylene, Amber Krueger, Gage Mueller

Celebrating Scholarship and Creativity Day (2018-)

Chlorinated ethylenes are common groundwater contaminants that persist in the environment and pose significant risks to human health such as damage to the nervous system, liver, kidneys, and even increased risk of cancer. Catalytic dehydrochlorination has emerged as a promising strategy for detoxifying compounds such as trichloroethylene (TCE). This study investigates whether rhodium on alumina (Rh/Al₂O₃) in the presence of hydrogen gas can completely degrade TCE to non-toxic products without the accumulation of harmful chlorinated intermediates. While palladium catalysts have been widely studied for dehydrochlorination, the activity and mechanism of rhodium supported on alumina in aqueous systems remains less characterized. …

Keeping Track Of Time: Does Formal Education Of Temporal Symbols Refine People's Ability To Perceive Time?, Alyssa Gabrielle Smith

Undergraduate Honors Thesis Collection

While many studies find a relation between symbolic and nonsymbolic numerical abilities (e.g., Chen & Li, 2014), whether this relation is causal has been questioned. For example, does learning symbols refine nonsymbolic abilities (i.e., Refinement Hypothesis)? One study found that as children gained proficiency in their verbal counting abilities, their nonsymbolic numerical acuity increased (Shusterman et al., 2016), thus supporting the Refinement Hypothesis. As studies have found similar processing for numerical and temporal abilities (e.g., Walsh, 2003) and a similar relation between symbolic and nonsymbolic timing abilities has been found (e.g., Hamamouche & Cordes, 2020), it begs the question of …

Deep Learning For Predicting Impact Energy And Compression After Impact Strength Of Composite Materials Using C-Scan Images, K. T. Tan, Jason P. Mack, Faizan Mirza, Zhong-Hui Duan

University Research

Traditional assessment of post-impact performance in carbon fiber reinforced polymer (CFRP) composites often relies on simplified scalar metrics that fail to capture the complex spatial interactions driving failure. This study addresses this limitation by developing an automated, end-to-end deep learning framework that shifts from manual feature extraction to the direct interpretation of raw damage morphology from ultrasonic C-scans. Using a ResNet18-based convolutional neural network (CNN) trained on 1,428 augmented images, the model achieved coefficients of determination (R2) of 0.7948 ± 0.0847 for compression after impact (CAI) strength and 0.9436 ± 0.0098 for impact energy. Beyond prediction, this dual-purpose methodology serves …

An Analysis Of The Rapid Intensification Of Hurricane Milton, Ayden Rodriguez, Mark Sinclair

Publications

Hurricane Milton (October 2024) provides a compelling case study of a multiscale pathway to rapid intensification (RI), highlighting the alignment of synoptic preconditioning, favorable environmental conditions, and rapid inner-core structural evolution. The storm originated from the interaction of multiple tropical waves embedded within a low-level trough associated with the Central American Gyre, which enhanced low-level vorticity and moisture convergence prior to development. Upon entering the Gulf of Mexico, Milton encountered an environment characterized by anomalously warm sea surface temperatures, high ocean heat content, and weak vertical wind shear, enabling steady intensification and the onset of explosive RI that exceeded conventional …

Preclinical Animal Modeling To Investigate Redox-Mediated Molecular Dysfunction In Traumatic Brain Injury, Brandon Z. Mcdonald

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Impacts associated with traumatic brain injury (TBI) induce a multitude of neurological morbidities mediated by a spread of biochemical dysfunction. Redox stress is a significant contributor to TBI pathophysiology and several redox stress markers have substantial evidence to support their role in diagnosing preclinical and clinical TBI. However, there is a critical need to verify their translational utility through correlations with behavioral, imaging, and molecular modalities. In chapter two, we examined the therapeutic efficacy of an antioxidant treatment (NPC3) using a controlled cortical impact (CCI) mouse model of TBI. NPC3 alleviated glial expression and reactivity while influencing the expression of …

Fisheries Management Paper No. 313: Western Australian Statewide Small Pelagic Scalefish Resource Harvest Strategy, Department Of Primary Industries And Regional Development, Western Australia

Fisheries Management Papers

Harvest strategies for Western Australia’s (WA) aquatic resources are formal documents developed by the Department of Primary Industries and Regional Development (DPIRD, the Department) to support decision-making processes that ensure the outcomes are consistent with the principles of Ecologically Sustainable Development (ESD; Fletcher 2002a) and Ecosystem Based Fisheries Management (EBFM; Fletcher et al. 2012).

Harvest strategies are a key component of all contemporary fishery management systems and a requirement for certification under the Marine Stewardship Council (MSC; Marine Stewardship Council 2018). The objectives of ESD are reflected in the objects of the Fish Resources Management Act 1994 (FRMA).

This Statewide …

Engineering Silicone Magnetic Fluids For Localized Radiation Attenuation During Ocular Melanoma Brachytherapy, Zachary L. Caprow

All Dissertations

Ocular melanoma is commonly treated using plaque brachytherapy; however, radiation-induced damage to healthy ocular tissues frequently results in partial or complete vision loss. This work investigates the development of an injectable, magnetically responsive silicone magnetic fluid designed to localize adjacent to the tumor and attenuate low-energy gamma radiation during treatment.

The material system consists of iron oxide nanoparticles surface-functionalized with a siloxane polymer, in which the nanoparticles provide magnetic responsiveness and radiation attenuation, while the polymer coating ensures colloidal stability, injectability, and biocompatibility. A one-pot synthetic approach was developed wherein a functionalized siloxane polymer containing iron-affinitive groups was reacted with …

Stability Of Paraffin-Insulated Nitrogen-Doped Carbon Fiber Ultramicroelectrodes, Maxwell H. Kwakwah

Electronic Theses and Dissertations

Nitrogen-doped carbon materials can facilitate the reduction oxygen-oxygen bonds, a key step in electroreduction of both O₂ (an important reaction in energy applications) and H₂O₂ (an important reaction in sensing and biosensing). Our lab previously demonstrated that thermal decomposition of urea in the presence of carbon fiber (CF) results in an N-doped carbon material that exhibits good electrocatalytic properties for H₂O₂ reduction. However, previous methods of insulating single N-doped CF via laser heating of borosilicate capillaries and epoxy to prepare ultramicroelectrodes (UMEs) seemed to adversely affect surface nitrogen contents and electrocatalytic properties. More recent work that utilized paraffin to …

Using Online And Traditional Tools To Assess K-5 Homework Assignments, Annika M. Altman

Capstone Projects and Master's Theses

Online school work is becoming more common with every passing academic year. Since the pandemic, there has been a major shift to online homework for elementary school students that has yet to go back to traditional paper and pen homework. The purpose of this capstone paper is to examine the ways that online homework has shifted since the schools returned from lockdown to face-to-face classroom. Through the use of literature review, interviews with 3 teachers, anonymous surveys for parents, teachers, and  students, the results indicated both parents and teachers share the responsibility to ensure that students complete homework, whether online …

Effects Of Chronic Absenteeism On The Academic Achievement And Learning Behaviors Of Elementary School Students, Arianna M. Sanchez

Capstone Projects and Master's Theses

Chronic absenteeism has become a growing concern in elementary schools today affecting their academic achievement and behaviors. This senior capstone research project examines the effects of chronic absenteeism on elementary school students, as well as the factors that contribute to frequent absences. Through the use of literature review and anonymous surveys on 7 elementary school teachers and their school students, the findings indicate that chronic absenteeism is associated with lower academic performance, decreased classroom participation, and created gaps in learning. In addition, factors, such as family responsibilities, health issues, and a lack of engagement between teachers and students also contribute …

Course Insight Portfolio: Math 1020 Business Calculus I, Ibrahim Khalilullah, M.G.M. Al Faruque, Jessica Ratovondranto, Leslie Spahr

Publications

This portfolio presents an overview of the student educational context, key course concepts, and some approaches to clarify student misconceptions associated with MATH 1020 (Business Calculus I). The portfolio includes a concept map illustrating the major topics of the course and an overview of common student misconceptions, and lesson plans designed to address those misconceptions through research informed instructional practices.

The concept map highlights the interconnected nature of topics such as functions, limits, continuity, differentiability, derivatives, optimization, graph interpretation, and applications of calculus. Particular attention is given to areas where students commonly experience difficulty, including distinguishing domain, codomain, and range; …

Course Insight Portfolio: Math 2070 Business Calculus Ii, Samuel Ajibola, Zachariah Baer, Kensey Doughtie, Abby Hyatt

Publications

MATH 2070 - Business Calculus II, is a course that most students in the Wilbur O. and Ann Powers College of Business will likely take, but can also meet the mathematics requirement for many majors outside of the College of Science and the College of Engineering, Computing, and Applied Sciences. Like most second semester calculus courses, it requires decent foundations in both algebraic manipulation and derivation to succeed, skills that students will prove through pre-college examination and by passing a first calculus course. Where it differs from a STEM-oriented calculus II course is that it goes beyond integration, touching on …