2026 Graduate Research Achievement Day
University of North Dakota
Tuesday, March 3 | 9:00 to 11:00 a.m.
Session 1: 9:00 to 10:00 a.m.
Session 2: 10:00 to 11:00 a.m.
Graduate Research Achievement Day is an annual celebration is which graduate students from all disciplines present their work to faculty and community judges. Scholarship prizes are awarded to those students whose work and presentation are deemed best.
More info: https://und.edu/gradschool/grad
Show Posters:
▼ Award Ceremony Back to top
Awards Ceremony - Starts at 1:00 p.m. on March 3
Abstract
Come join us to celebrate the winners of the GRAD virtual program!
Please click "Chat with the presenter" to join the Zoom meeting at 1:00 p.m.
Please click "Chat with the presenter" to join the Zoom meeting at 1:00 p.m.
Presented by
UND Graduate School
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Available 1 p.m. (CST)
▼ Session 1: 9am-10am CST Back to top
V1-01 | Encouraging Isolated Community Connectiveness with Swing Dancing: An Research Study at McMurdo Station
Abstract
This study explores a Swing dance class at McMurdo Station, Antarctica, and the implications of non-formal dance education for community connectedness. McMurdo is the largest US station in Antarctica, maintaining a population from a few hundred in the austral winter to over a thousand during the austral summer. Stressors of those in Antarctica involve “isolation, confinement, and an extreme physical environment” (Palinkas, 2003, p. 354). Those working at McMurdo face significant challenges due to harsh environmental conditions, rigorous workloads, limited privacy and space, and limited access to the Internet. This qualitative study seeks to better understand whether a greater sense of connectedness can be fostered in students through swing dance. Connectiveness is being used to describe “a sense of belonging expressed through new types of interaction across space and time” (Twyford et al., 2009). Overall, classroom observation showed increased feelings of connectedness made in workplaces and the greater McMurdo Community.
Presented by
Rachel Jones
V1-02 | Introduction of Occupational Therapy in a Suburban Supportive Housing Program
Madeline Kuntz
Abstract
Unhoused individuals experience compounded barriers beyond housing access and are often underserved within occupational therapy practice. This doctoral capstone project partnered with a nonprofit residential program to develop a research-informed onboarding manual grounded in a holistic occupational therapy framework. The manual was designed to clarify expectations, address diverse resident needs, and promote independence as the organization expands. Development was informed by a comprehensive literature review identifying anticipatory barriers and supports commonly experienced prior to program entry. Key areas of need including physical, mental, and spiritual/social health were organized into a self-paced residential manual. Although direct intervention was not feasible due to site constraints, the occupational therapy lens was used to guide creation of a resource to enhance individualized support and promote independence along a pathway toward permanent housing. Survey measures were developed to support long-term evaluation and program sustainability, demonstrating the value of occupational therapy in an underserved practice area.
Presented by
Madeline Kuntz
V1-03 | A Point-of-Care Optical System for Quantifying Hemolysis and Detecting Clots in Whole Blood Samples
Megan Stubbs
Abstract
Hemolysis and clotting are the leading causes of clinical specimen rejection, resulting in significant diagnostic delays and an estimated $6 billion in annual losses in the U.S. Rejected samples often require redraws, adding hours to turnaround time (TAT) in emergency settings and days to weeks in rural or outsourced laboratories. Current detection methods rely on centrifugation, visual inspection, and centralized spectrophotometric analyzers, delaying time-critical tests and impacting regulatory compliance and patient outcomes. We developed a point-of-care (POC), consumable-free optical system for rapid assessment of hemolysis and clotting in whole blood. The platform applies Beer–Lambert–based absorbance measurements using a miniaturized spectrophotometer, alongside 90° side-scatter detection from LED illumination to correct turbidity and flag large clots. A binary pass/fail output is generated using user-defined hemolysis thresholds. Testing with de-identified clinical discard samples demonstrated correlation with a clinical reference standard. This CLIA-waivable, noncontact system enables bedside verification of specimen integrity… (abstract truncated)
Presented by
Megan Stubbs
V1-04 | A Survey on Concept and Data Drifting Behavior in Zero-Day Attack Detection Research
Mofe Jeje
Abstract
In zero-day attack detection research, A critical yet underexplored factor undermining the efficacy of machine learning-based zero-day detection is the dynamic and drifting nature of data, resulting not only from evolving attacker tactics, but also from system behaviors, software updates, and changes in user behavior or network topology. This drifting behavior in data streams created two related but distinct phenomena called concept drift and data drift where the underlying statistical properties of the target variable and the distribution of input features changes over time. Worse still, while these phenomena can potentially degrade the performance of static detection models, making effective real-time zero-day detection difficult; the absence of labelled data for novel attacks, further compounds the problem, placing detection systems in a continuous game of catch-up. This survey seeks to provide a comprehensive overview of concept and data drifting behavior in zero-day detection research… (abstract truncated)
Presented by
Mofe Jeje
V1-05 | AL3X: A High Altitude Platform for Comparative Analysis of Stratified Atmospheric Microbial Communities Across Earth’s Surface Ecosystems
Kim Berthet
Abstract
The atmosphere is a central connector in Earth system processes, yet its biological component remains largely unobserved. This study introduces AL3X (Aeromicrobiology Layered 3D Exploration), a modular, 3D printed, altitude resolved bioaerosol sampling platform conceived to generate vertically structured microbial data. Preliminary results from the first launch reveal clear stratification: surface associated taxa dominate at lower altitudes, peak diversity occurs in the troposphere consistent with long range transport, and the stratosphere contains a low diversity but distinct assemblage of stress tolerant organisms. These observations demonstrate that the atmosphere functions as a structured biological transport system rather than a well mixed reservoir. Designed as a reproducible and cost accessible platform, AL3X enables standardized, distributed observations across spatially separated sampling sites. This framework provides the data infrastructure required to investigate the atmosphere as a living biome and to quantify microbial connectivity among Earth’s surface ecosystems… (abstract truncated)
Presented by
Kim Berthet
V1-06 | Exploring Imagery Symptomology of Athletes with OCD to Inform Therapeutic and Performance-Enhancing Imagery Interventions
Sydney Raboin
Abstract
Mental imagery is known to be a potential symptom of Obsessive-Compulsive Disorder (OCD), but there needs to be more research on how exactly it appears and is experienced. Imagery in OCD can serve as both obsessions and compulsions and can arise out of the person’s control or be intentionally created (e.g., reassurance-seeking mental compulsion). There are also potential ways in which these individuals may have unique capabilities or struggles when it comes to supportive imagery usage due to their brain’s circuitry and the relevancy of imagery as a symptom of their disorder. Thus, gaining information on these topics will support understanding of the disorder and how to work most effectively with these individuals, and will guide supportive imagery interventions (i.e., psychotherapeutic and sports-psychology based). This poster explains the work of a qualitative three-article dissertation aimed at synthesizing analysis of OCD imagery symptomatology and procedures for connecting to supportive imagery concepts.
Presented by
Sydney Raboin
V1-07 | Victimization, Health, and Help Seeking in North Dakota: How Interpersonal Violence Shapes Physical and Mental Health
Tahmid Hassan Jeeshan
Abstract
Interpersonal violence extends beyond physical assault to include psychological and/or emotional abuse that can produce substantial physical and mental health consequences. This study examines how multiple forms of interpersonal violence relate to health outcomes among North Dakotan women, focusing on differences between rural and non rural residents. We compare victimization patterns, physical and mental health status, and treatment seeking behaviors. We anticipate that rural victims will report more severe or chronic victimization yet face reduced access to and use of healthcare and victim services. By jointly considering violence type, rural versus non-rural status, health outcomes, and treatment seeking, this project highlights differences between rural and non-rural residents, identifies the unique needs of rural North Dakotans.
Presented by
Tahmid Hassan Jeeshan
V1-08 | Fuzzy Logic-based PMDC Motor Speed Control
Yasha Pirani
Abstract
This paper investigates the performance of Fuzzy Logic-based controllers in regulating the speed of Permanent Magnet DC (PMDC) motors, comparing them against conventional Proportional and PI controllers. Four control strategies - Proportional, PI, P-FLC, and PI-FLC - are implemented and evaluated under varying speed references and load disturbances. Simulation results show that Fuzzy Logic-based controllers outperform their conventional counterparts, with P-FLC and PI-FLC achieving better rise times, settling times, and disturbance rejection. Notably, P-FLC yields the best overall performance in three out of five scenarios. These results support the integration of Fuzzy Logic into PMDC motor control systems to improve precision, adaptability, and robustness.
Presented by
Yasha Pirani
V1-09 | AI-Driven Handover Optimization and QoS-Aware Routing for 6G Non-Terrestrial Networks
Murat Parlakisik
Abstract
The research focuses on handover challenges in 6G networks integrating terrestrial and non-terrestrial networks (NTN), particularly Low Earth Orbit (LEO) satellite constellations. LEO satellites provide global coverage but introduce frequent handovers (5-10 minutes) and variable latency, which pose challenges for mission-critical applications. This study develops an AI-based handover mechanism using deep learning and reinforcement learning to manage seamless network transitions while monitoring signal quality, network load, and transmission delay. The research leverages BrightLight, a novel hybrid emulation-simulation framework that combines Linux network namespaces and NS-3 integration to enable realistic 6G-satellite network testing. BrightLight enables real-time protocol execution, supports constellations with more than 4,000 satellites, and provides comprehensive telemetry. Expected contributions include validated AI models for handover optimization, novel ML training datasets generated from BrightLight simulations, and demonstrated improvements in QoS maintenance during terrestrial-to-satellite transitions.
Presented by
Murat Parlakisik
V1-10 | Prevalence, Frequency, and Age of Tobacco Initiation Among American Indian/Alaska Native and Non-Hispanic White Youth - 2019 NYTS
Haily Augustine
Abstract
Using secondary data, National Youth Tobacco Survey, this study examines self-reported cigarette and e-cigarette use, frequency, and age at first-time usage among non-Hispanic American Indian/Alaska Native (AI/AN) youth compared with non-Hispanic White (NHW) youth. Statistical methods included chi-square tests, rank-sum tests, and proportions. A higher proportion of AI/AN youth who used cigarettes (9 vs 5%; P=0.002). E-cigarette usage was similar in both groups 23 vs 22%; P=0.7). Small proportions of AI/AN (8-39%) provided data on frequency of use and age at start. In exploratory analyses, cigarette and e-cigarette use frequencies were similar between AI/AN and NHW youth. National survey data on cigarette and e-cigarette usage in AI/AN youth is limited but suggests cause for concern. Exploratory findings suggest a need for prevention intervention at earlier stages of school level for AI/AN youth. Inclusion of culturally relevant questions in the NYTS may improve understanding of tobacco use in the AI/AN demographic.
Presented by
Haily Augustine
▼ Session 2: 10am-11am CST Back to top
V2-12 | Building and Analyzing the Factor Structure of a New Motion Sickness Susceptibility and Severity Questionnaire
Abstract
Motion sickness is a pervasive experience, depending on the intensity of motion or simulation of motion. Since the frequency and intensity of motion sickness varies across a population, validated questionnaires are necessary to measure this subjective experience. The current research attempts to develop a new motion sickness questionnaire based off the MSSQ-Short Form and the SSQ infused with visual motion stimulations and symptoms from a widely used anxiety symptom scale, the Beck Anxiety Inventory (BAI). The administration of this questionnaire and resulting factor analysis aims to assess how stimulations that provoke motion sickness are organized into factors in a questionnaire assessing real motion and VR stimulations. As part of the symptom factor analysis, with the inclusion of anxiety symptoms, this research also aims to determine if symptoms associated with anxiety fall into a factor unique from other symptoms. This research is foundational for creating a new motion sickness assessment.
Presented by
Sarah Kingsbury
V2-13 | Multi-Channel Detection of Antialiased Pixels in Rendered Content for Visual Regression Testing
Abstract
Visual Regression Testing (VRT) detects unintended graphical user interface(GUI) changes. However, rendering inconsistencies, specifically anti-aliasing(AA), often trigger “false positives.” This forces developers to manually inspect differences unrelated to their code changes, undermining automation. Vyšniauskas (2009) [1] proposed an algorithm to identify AA-affected pixels by measuring intensity gradients between immediate neighbors. Yet, this approach ignores color data and alpha blending, which are fundamental to modern GUIs. We present a method that integrates multi-channel color analysis and probabilistic alpha-blending reversal to more accurately estimate if a pixel value results from AA. By modeling the blending process, our approach provides a theoretically grounded framework for isolating rendering noise. We validate this method using images from a modern rendering engine, measuring performance against existing algorithms and “ground truth” (i.e. without AA) renderings. This research demonstrates a more precise path for reducing manual overhead in automated visual testing.
Presented by
Scott Johnson
V2-14 | Resilience and Adaptation in Southern Pine Forests: Investigating the Interactions between Climate Change, Forest Management, and Ecosystem Health
Abstract
Southern US pine forests, dominated by longleaf and shortleaf pine, face threats from climate change and forest management practices. This study investigates how different forest management strategies impact pine tree health and ecosystem resilience. Using the VIDA model, various management scenarios are simulated, including timber harvesting, prescribed burning, and restoration efforts, to examine their effects on pine growth, health, and ecosystem dynamics under climate change. The goal is to inform adaptive management strategies that balance timber production with ecosystem conservation, promoting the long-term integrity of these ecosystems.
Presented by
Morticia Moonchilde
V2-15 | Is Prenatal Exposure to Acetaminophen/Paracetamol Related to Autism/ADHD in Children?
Abstract
For pregnant females, would taking acetaminophen increase the rates of neurodevelopmental disorders (autism/ADHD) compared to pregnant women that do not take acetaminophen throughout the course of a pregnancy?
Presented by
Michael Eide
V2-16 | Investigating Decision-Making in the Consolidation of Norway's Rural Schools
Abstract
The purpose of this study is to explore the school consolidation process, with a focus on political and administrative decision-making, that is carried out in rural Norway. Four rural municipal sites were selected across three different counties in Norway, each of which had at least one school consolidated or closed since 2020. Qualitative data about these municipal sites were collected and integrated according to case study methodology. Research questions about stakeholder perspective and factors for decision-making yield an analysis leading to thematic findings about the institutional logics which are at play in the examined municipal sites within Norway. Findings and discussion of this analysis pose questions about the values and voices of rural community members, the ideas and choices that influence the administration of rural schools, and whether the growing trend of rural school consolidation serves the public interest in Norway, as well as internationally.
Presented by
Richard Hoberg
V2-17 | Bridging the Mentorship Gap: A Cognitive Load Theory Case for AI Decision Support
Abstract
Cognitive Load Theory (CLT) offers a framework for understanding how artificial intelligence (AI) may support novice nurse decision-making. Traditional clinical mentoring is highly effective for reducing information overload, building clinical reasoning, and supporting the transition to practice; however, mentorship is often unavailable in real-time clinical situations, particularly in rural settings. My poster proposes that AI chatbots can support novice nurses through cognitive scaffolding, much as a mentor would. My research adapts CLT, suggesting novice clinicians experience high extraneous cognitive load due to fragmented information, chaotic learning environment, and limited schemas. AI chatbots can reduce extraneous load by organizing information, prompting clinical considerations, and offering timely guidance, allowing learners to devote more cognitive resources to germane load and schema development. By aligning AI support with established learning theory, my research provides a theoretical rationale for integrating AI chatbots as a clinical decision-making support when residency programs or mentors are unavailable.
Presented by
Matt Weisgarber
V2-18 | Childhood Adversity and Mental Health in Early Adulthood: A Proposal to Explore the Role of Emotion Regulation, Cognitive Functioning, and Social Support
Abstract
This project proposal aims to explore how experiences of childhood adversity shape well-being and mental health in early adulthood. The proposed study builds on prior research by adopting the dimensional framework of adversity introduced by McLaughlin and Sheridan (2014), which conceptualizes adversity across distinct domains (e.g., threat and deprivation). Specifically, this proposal outlines a study which aims to examine the differential pathways through which these domains of childhood adversity influence mental health and overall well-being. Emotion regulation and cognitive functioning will be tested as a potential mediators of the relationship between adversity and mental health outcomes. Additionally, social functioning will be examined as a protective factor that may buffer the negative effects of adversity in childhood on mental health.
Presented by
Christina Burns
V2-19 | A non-thermal plasma system to generate aqueous fertilizer compounds for Indigenous and rural communities
Abstract
Nitrogen based fertilizers are required to sustain global food production and their typical manufacture by the Haber-Bosch process is energy intensive, centralized, and depends on fossil fuels. This project investigates a decentralized alternative process using non-thermal plasma technology to produce aqueous nitrogen fertilizer compounds for Indigenous or rural communities. The proposed system uses a nanosecond pulsed microbubble reactor to produce reactive nitrogen and oxygen species (RONS) from atmospheric nitrogen and oxygen at standard temperature and pressure. Experimental data from prior plasma-activated water (PAW) studies show the formation of RONS like nitrate, nitrite, hydrogen peroxide, and ozone in aqueous solutions at 10g per kWh. The proposed design utilizes continuous flow reactors. Ten 0.1 m3 plasma units powered by solar panels produce 4-5 kg of dissolved fertilizer per day for a 0.5 km2 farm. The aqueous nitrate solution may be applied directly to fields, or can be stored for later use… (abstract truncated)
Presented by
Carter Peek
V2-20 | Rethinking Stress and Recovery Prediction with Glucose and HRV
Abstract
Long duration spaceflight missions (LDSFMs) are strenuous undertakings, placing sustained physiological and psychological demands on individuals engaged in the endeavor. Accurate monitoring and recognition of psychological stress responses will therefore remain essential for mission planning and crew health management. Physiological stress is commonly measured through sampling of salivary cortisol secretion, which is not feasible for LDSFMs. However, delayed kinetics and lab dependence limit real-time use during LDSFMs. This proposal will evaluate the feasibility and scientific validity of continuous blood glucose measurement (CGM), both independently and in combination with heart rate variability (HRV). We hypothesize that CGM combined with HRV may detect acute physiological stress and may enable earlier prediction of 24-hour recovery than salivary cortisol sampling, whose delayed hormonal kinetics limit its real-time utility in analog mission environments. Such monitoring capabilities may improve the detection, interpretation, and prediction of stress and recovery states of measured stress in LDSFM crews.
Presented by
Joseph Matthew Clift
V2-21 | Methane Injection and Storage in Depleted SAGD Reservoirs Using Repurposed Observation Wells
Abstract
Depleted oil reservoirs are ideal locations for underground methane storage because they possess proven structural traps, scientists understand their geological makeup, and they already have established infrastructure (Bo Wei et al., 2023). The subsurface architecture provides efficient seasonal storage which supports national energy security and helps reduce environmental pollution (Buscheck et al., 2023). Research studies demonstrate that cyclic injection and withdrawal operations can succeed when the reservoir maintains its natural integrity (Zhao et al., 2024). The use of observation wells for injection purposes creates problems because cement loses its bond and casing materials fatigue, which current assessment methods detect during initial well-logging stages (Yousuf et al., 2021). The conversion of an observation well to an injector requires thorough integrity assessments to validate the system's long-term storage capabilities (Freifeld et al., 2016).
Presented by
Yomi Adesimi