Merle Haggard

Merle Haggardhttps://commons.und.edu/performing-arts-photos/1098/thumbnail.jp

Chicago The Musical

Cast of Chicago The Musicalhttps://commons.und.edu/performing-arts-photos/1136/thumbnail.jp

Louise Mandrell

Louise Mandrellhttps://commons.und.edu/performing-arts-photos/1095/thumbnail.jp

Maynard Ferguson

Maynard Ferguson at the Chester Fritz Performing Arts Centerhttps://commons.und.edu/performing-arts-photos/1064/thumbnail.jp

Jay Leno

Jay Leno at the Chester Fritz Performing Arts Centerhttps://commons.und.edu/performing-arts-photos/1061/thumbnail.jp

Mickey Gilley

Mickey Gilleyhttps://commons.und.edu/performing-arts-photos/1100/thumbnail.jp

Buffalo Hide Drum

Featured in the exhibition, Plain of Stars: An exhibition to uplift, acknowledge, and celebrate Indigenous students.https://commons.und.edu/native-art/1099/thumbnail.jp

Advancing Human-Computer Interaction Systems Through Explainable And Secure AI Integration

As artificial intelligence (AI) systems increasingly shape how humans interact with digital environments, the need for transparency, security, and robustness in intelligent decision making has become critical. This thesis explores how explainable and secure AI techniques can be integrated into modern human-computer interaction (HCI) systems to enhance trust, resilience, and alignment with human operators. We present three related studies, each addressing a distinct challenge in the design of human-centered AI. First, we apply XAI methods, specifically Local Interpretable Model-Agnostic Explanations (LIME), to deep learning (DL) based CAPTCHA solvers. By interpreting model attention patterns, we uncover exploitable weaknesses in text CAPTCHA designs and propose improvements aimed at making human verification systems more transparent. Second, we introduce a unified framework for evaluating machine learning (ML) robustness under structured data poisoning attacks. We assess model degradation across traditional classifiers, deep neural networks, Bayesian hybrids, and LLMs, using attacks such as label flipping, data corruption, and adversarial insertion. By incorporating LIME into our evaluation process, we move beyond accuracy scores to uncover attribution drift and internal failure patterns that are vital for building resilient AI systems. Third, we propose a justification generation system powered by LLMs for real time automation. Using the Tennessee Eastman Process (TEP) dataset, we fine-tune a compact instruction-tuned model (FLAN-T5) to produce natural language explanations from structured sensor data. The results show that lightweight LLMs can be embedded into operator dashboards to deliver interpretable reasoning, enhance traceability, and support oversight in safety-sensitive settings. Together, these studies outline a framework for building AI systems that are not only capable, but also transparent, secure, and human aligned. This work advances the field of human-centered AI by emphasizing interpretability and robustness as foundational elements in the future of interactive intelligent systems

Rethinking Pilot Retention In The United States: An Analysis Of Key Factors

This thesis examined pilot retention challenges in U.S. regional and low-cost carriers (LCCs), focusing on nonfinancial incentives such as quality of life, career stability, and work-life balance, which may have a greater influence on retention than traditional financial incentives. This quantitative, survey-based approach assesses how pilots rank the factors that influence their retention. Using a sample of U.S.-based pilots, the study examines six key areas adapted from a European pilot retention framework. Statistical analyses, including the Friedman test, the Mann-Whitney U test, and the Kruskal-Wallis test, identified correlations between demographic variables and retention priorities. The inherent financial constraints of regional airline business models often mean that offered salaries cannot compete with the compensation packages provided by mainline carriers. However, the findings suggest that nonfinancial quality of life factors, such as desirable pilot bases, work-life balance, and predictable schedules, may counterbalance the financial incentives offered by mainline carriers, especially for the younger generation of pilots entering the workforce. Addressing the methodological limitations identified within the study and conducting comprehensive mixed-methods research in the future, will further clarify pilot retention dynamics, offering practical guidance to airline management, policymakers, and labor organizations

Ecological Dynamics In Beaver-Engineered Boreal Wetlands: Amphibian Phenology, Occupancy, And Aquatic Macroinvertebrate Communities

Boreal wetlands are ecologically rich yet vulnerable ecosystems shaped by hydrological dynamics, cold climate regimes, and landscape-scale disturbances. Among the most influential agents of change in these systems are beavers (Castor canadensis), whose engineering activities create a mosaic of lentic habitats at varying stages of ecological succession. This dissertation investigates the structure and dynamics of amphibian and aquatic macroinvertebrate communities across a beaver-influenced wetland landscape in Voyageurs National Park, Minnesota, USA.The first study (Chapter II) examines breeding phenology and detection patterns of boreal anurans using a combination of passive acoustic monitoring and visual encounter surveys at 25 wetlands over four years (2019–2022). Distinct seasonal calling patterns and developmental phenology were documented for seven species, revealing interspecific differences in timing and detectability. These patterns underscore the importance of time-sensitive monitoring protocols in temperate amphibian research and conservation. The second study (Chapter III) models amphibian occupancy as a function of wetland successional stage, pond size, and spatial location using site-level ecological predictors across 55 wetlands (35 sites in multi-year analyses) over four years. Species-specific logistic regression models revealed that habitat suitability was high across successional stages and wetland perimeter was among the most influential factors structuring occupancy, though spatial patterns were limited at the scale of the study. The presence of metamorphs and juveniles confirmed successful breeding at many sites and provided supporting evidence for site-level habitat suitability. The third study (Chapter IV) evaluates aquatic macroinvertebrate diversity and community composition in relation to successional stage, wetland type, and year across the same sites and time period as the amphibian component. Mid-season dip net sampling and laboratory identification to family level revealed high invertebrate richness across sites, with richness patterns corresponding to habitat structure and successional stage. Ordination analyses highlighted variation in assemblage structure associated with beaver-driven environmental heterogeneity and wetland classification. Together, these studies offer a comprehensive ecological portrait of boreal wetland communities and their response to a natural gradient of habitat succession shaped by beaver activity. The work integrates species phenology, spatial habitat modeling, and community ecology within a landscape framework. It contributes critical baseline knowledge of amphibian and invertebrate biodiversity in a northern protected area, informs wetland management strategies, and illustrates the ecological value of long-term, multi-taxa monitoring in dynamic ecosystems