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THE STYLE, ANALYSIS, AND PERFORMANCE PRACTICES OF LAS CUATRO ESTACIONES PORTEÑAS BY ASTOR PIAZZOLLA, ARRANGED BY LEONID DESYATNIKOV
Get PDFThis research study mainly focuses on Leonid Desyatnikov’s version of Four Seasons for solo violin and string orchestra, an arrangement of Astor Piazzolla’s renowned tango-style chamber music. Desyatnikov’s music retains the classical music structure while incorporating tango elements inspired by Piazzolla, and this piece enriches the repertoire of modern violin music and makes an outstanding contribution to the development of violin music. This document includes an analysis of the work’s musical structures, stylistic elements, and different classical and modern violin techniques. Besides, it combines a comparative evaluation of performances by five renowned violinists to offer musical ideas and practical guidance for interpreting and mastering this significant violin piece
COLLABORATING WITH THE SAC AND FOX COMMUNITY TO DOCUMENT THE PAST AND CHART A FUTURE FOR THE SAC AND FOX MISSION BOARDING SCHOOL
Get PDFThis thesis explores the history and legacy of the Sac and Fox Mission School (1872-1917) through community-engaged research grounded in oral histories, archival investigation, and site-based collaboration. By centering the voices of Sac and Fox community members, this project surfaces stories of silence, loss, and rediscovery that have long been obscured in official records. Many community members and interviewees were unaware of their relatives' attendance at the school until shown archival materials, revealing the profound emotional weight of reconnecting with fragmented family histories. Themes such as language loss, cultural disruption, and intergenerational disconnection emerged alongside expressions of strength and curiosity. The project also highlights the importance of material culture, the landscape as a living archive, and the need for respectful stewardship of school records. Guided by the principles of community-based archaeology and the “archaeology of the heart”, this work underscores the value of collaboration, care, and continued dialogue in addressing the histories of boarding schools. Ultimately, it seeks to contribute to community healing while offering a model for ethical, relational research within and beyond the academy
Healthcare innovations empowered by discriminative and generative artificial intelligence
Get PDFArtificial Intelligence (AI) is reshaping healthcare through discriminative and generative models, among other paradigms. Discriminative models classify data by learning boundaries, while generative models capture underlying distributions to produce new data. This dissertation advances both directions with novel computational frameworks. For discriminative models, I developed NACHOS (Nested and Automated Cross-validation with Hyperparameter Optimization on Supercomputers), an algorithm that integrates nested cross-validation, automated hyperparameter optimization, and high-performance computing (HPC) to more reliably estimate test performance and quantify uncertainty at scale. A companion algorithm, DACHOS (Deployment with Automated Cross-validation and Hyperparameter Optimization using Supercomputing) supports reproducible deployment by retraining the best-selected configuration on full datasets. To validate the NACHOS framework, I applied it to real-time medical imaging with optical coherence tomography (OCT). In the percutaneous nephrostomy study, ResNet50 achieved a mean accuracy of 82.6% ± 3.0% under NACHOS evaluation, highlighting that deeper architectures more effectively capture fine-grained tissue differences. In the epidural anesthesia study, a biologically informed sequential binary pipeline outperformed a conventional multi-class approach, reaching 96.7% ± 1.3% overall accuracy and >99% precision for detecting the epidural space—a clinically critical milestone. Together, these case studies demonstrate that rigorous evaluation strategies and thoughtful task reformulation can substantially improve robustness and safety in time-critical decision support. For generative models, I applied large language models (LLMs) to enhance a smoking cessation app whose limited corpus of ~900 messages risked repetitiveness. I systematically compared five open-source LLMs and ChatGPT, optimizing prompts and decoding strategies using perplexity and LIWC analysis, and validated outcomes through expert counselor evaluations. The results indicated that ChatGPT and the larger language models consistently generated the most credible and persuasive content. Overall, this dissertation contributes computational frameworks that advance discriminative and generative AI in healthcare, demonstrating novel pipelines for performance estimation with uncertainty quantification on HPC systems in medical imaging and message generation for patient support systems
Neuromorphic Digital-Twin-Based Controller for Indoor Multi-UAV Systems Deployment
Get PDFFinancial support was provided by the University of Oklahoma Libraries' Open Access Fund.This study introduces a novel distributed cloud-edge framework for autonomous multi-unmanned aerial vehicle (UAV) systems that combines the computational efficiency of neuromorphic computing with nature-inspired control strategies. The proposed architecture equips each UAV with an individual spiking neural network (SNN) that learns to reproduce optimal control signals generated by a cloud-based controller, enabling robust operation even during communication interruptions. By integrating spike coding with nature-inspired control principles inspired by tilapia fish territorial behavior, our system achieves sophisticated formation control and obstacle avoidance in complex urban environments. The distributed architecture leverages cloud computing for complex calculations while maintaining local autonomy through edge-based SNNs, significantly reducing energy consumption and computational overhead compared to traditional centralized approaches. Our framework addresses critical limitations of conventional methods, including the dependence on premodeled environments, computational intensity of traditional methods, and local minima issues in potential field approaches. Simulation results demonstrate the system's effectiveness across two different scenarios: first, the indoor deployment of a multi-UAV system made up of 15 UAVs, and second, the collision-free formation control of a moving UAV flock, including six UAVs considering the obstacle avoidance. Due to the sparsity of spiking patterns, and the event-based nature of SNNs on average for the whole group of UAVs, the framework achieves almost 90% reduction in computational burden compared to traditional von Neumann architectures implementing traditional artificial neural networks.Ye
Critical Considerations for Intercultural Sensitivity Development: Transnational Perspectives
Get PDFFinancial support was provided by the University of Oklahoma Libraries' Open Access Fund.Intercultural sensitivity is crucial in today’s diverse society, and accurate assessment is key to developing effective intercultural programs in educational institutions and beyond. The Intercultural Development Inventory (IDI) is widely used for this purpose, yet its applicability to transnational individuals—those navigating multiple cultural and social systems—remains underexplored. This gap is important to address given the interconnected nature of our global society, where individuals frequently move across borders. To address this issue, this conceptual paper critically examines the underlying assumptions of the IDI regarding culture and identity through three interrelated frameworks: transnationalism, relational ontology, and intersectionality. Drawing on existing literature on these frameworks and the IDI, our analysis highlights how integrating these perspectives into the IDI and, by extension, other intercultural assessment tools can more accurately capture the complex, fluid, and dynamic nature of transnational experiences. This integration also shifts the discourse on intercultural assessment from a focus on individual competence to an emphasis on shared responsibility in fostering equitable, relationally grounded intercultural spaces. Implications for future research and practice are also discussed.Ye
Daughter of another
Get PDFThe fantasy genre has always been a way to explore and express the imagination and worlds only dreamt of. This project examines methods of writing fantasy from a decolonized perspective and what that looks like, comparing existing fantasy anthologies and novels to those that are currently in the mainstream but still perpetuates the colonial and white-supremacist mindset i.e. "A Court of Thorns and Roses" by Sara J Maas. This novel, Daughter of Another, uses the mythos and tales from marginalized communities across the United States, similar to "Fire Keeper’s Daughter" by Angeline Bouley. This project navigates the best way to approach such writing style within the fantasy genre and how an outsider can speak on subjects, communities, and cultures in a way that is objective and amplifies these marginalized voices rather than drowning them out. Through the lenses of decolonization and intersectionality, Daughter of Another follows Hiraya’s odyssey in a parallel realm to Earth where colonization never occurred and magic and myth still persist. She travels across Keya Island in search of her long-lost half-sister, hoping to save her city from the next heir: her immature younger half-brother. In doing so, she is drawn into a journey interwoven with myths and stories not of her own. The importance of this project is to understand there are worlds beyond those approved by a colonized lens when creating a fantastical world, and that it is crucial to involve a diverse array of groups—especially marginalized communities—that do not support colonial powers, but instead dismantle them and amplify these subjugated voices
Climate-induced losses of surface water and total water storage in Northeast Asia
Get PDFFinancial support was provided by the University of Oklahoma Libraries' Open Access Fund.Water shortages are intensifying globally due to climate change and human activities. Northeast Asia, with diverse ecosystems and transboundary water systems, is particularly sensitive to these pressures. Yet, the region’s water resource changes and drivers remain largely unknown. Here, we integrate Landsat and Sentinel-2 images, Gravity Recovery and Climate Experiment and its Follow-On observations, climate and anthropogenic data, finding a net surface water area loss of 16 × 103 km2 in Far East Russia over 2000−2023, primarily driven by rising temperature and evaporative demand, and a net surface water area gain of 3 × 103 km2 in Northeast China, primarily driven by increasing precipitation and irrigation infrastructure. Approximately 1004 0.5° gridcells (1.4 × 106 km2) have concurrent losses of surface water area and total water storage. Approximately 185 million people reside in watersheds with surface water area or total water storage loss, underscoring the need for sustainable water management under intensifying climate change and human activities.Ye
GLOBAL OPTIMIZATION STRATEGIES FOR EFFICIENT ENERGY LANDSCAPE EXPLORATION IN ATOMISTIC SIMULATIONS
No full textGenetic algorithms (GAs) are widely used in materials science to explore complex potential energysurfaces and identify optimal atomic configurations. This study develops a comprehensive GAbased workflow to optimize nanoparticle structures, incorporating both traditional and machine learning-accelerated approaches. The process begins with the generation of candidate structures, followed by structural relaxation using the Vienna Ab initio Simulation Package (VASP). We evaluate and compare five selection strategies: tournament, elitism, ranking, elitism with ranking, and elitism with tournament. These strategies are compared using hypothesis testing to assess statistically significant differences in optimization performance. This analysis is conducted on two systems: • An FCC(111) 3×3×4 Ag slab with a single atom of (Pd, Pt, Ru, or Rh), • A Ni₆Pd₄ cluster, where the goal is to discover the atomic arrangement that minimizes total energy. Various crossovers are benchmarked following the selection strategy comparison to further refine the evolutionary process. The best-performing GA configuration is then coupled with a Gaussian Process (GP) surrogate model, enabling accelerated prediction of structural stability and significantly reducing the number of expensive DFT evaluations. Key findings from this study include: vii • Ranking and tournament selection strategies effectively balance exploration and exploitation, yielding consistently low-energy configurations. • Integrating a Gaussian Process model reduces the number of VASP evaluations needed while achieving similar or better minima with minimal loss in accuracy for the cluster system. • Simple Cut Splice and Half Uniform crossovers produced the most favorable distributions among the crossover operators tested. These results highlight the critical importance of selecting appropriate evolutionary strategies and operators and demonstrate the potential of surrogate modeling to improve computational efficiency significantly in nanoparticle structure optimization. The combined GA-GP framework developed here offers a promising path forward for accelerating the discovery and design of advanced materials. The custom genetic algorithm operators (selection, crossover, mutation) and Gaussian Process surrogate modeling scripts developed as part of this work are available at: https://github.com/gunasooriya-lab/cluste
EXPANDING BEYOND BIOMEDICINE: HOW HOSPICE PROVIDES WHOLE PERSON CARE
No full textThis work is an exploration of how patient-family units navigate and experience hospice care. Since its introduction to the US, hospice care has been transformed from a social movement to a Medicare benefit. Through the Medicare Hospice Benefit hospice organizations now can be finically viable businesses. As hospice care has evolved it has become a form of care that is rooted in biomedicine but extends beyond the confines of biomedicine to provide better care to dying patients. Through affective care and a holistic approach, hospice care provides patient-family units with personhood care and opportunities for whole person healing. Hospice care is medical care that prioritizes relationships and the patient-family unit’s needs. While hospice care is imperfect, it can be used as a model for how to improve biomedical health care systems