LOUIS University of Alabama in Huntsville
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Subterranean drought classification and ecological risk in karst systems
No full textCave ecosystems depend on stable groundwater inputs, yet no standard method exists for detecting subterranean drought. This study develops a framework to define and monitor drought in karst cave systems by adapting surface-based hydrologic indicators. Using long-term water level data from Bobcat Cave in northern Alabama, we identified drought events through percentile-based thresholds and evaluated multiple surface metrics, including the Standardized Precipitation Index (SPI) and deep-layer soil moisture, as predictors of cave drought severity. Random Forest models supported the selection of key indicators and informed classification thresholds. These thresholds were then applied across the Middle Tennessee Elk watershed to map seasonal drought exposure and intersect with species-specific breeding periods. Vulnerability analyses highlighted potential ecological risks to taxa such as the Alabama Cave Shrimp and Southern Cavefish. This work establishes a transferable approach for identifying subterranean drought and supports conservation planning in sensitive karst environments
Information capacity for time-varying adversarial networks
No full textThis thesis investigates the capacity of time-varying adversarial networks where intelligent adversaries can corrupt transmissions on restricted subsets of network edges that change availability over time. Building upon the work of Beemer et al. on adversarial network coding with restricted adversaries, we analyze networks whose topology evolves temporally, motivated by applications in space networking and delay-tolerant systems. We introduce different adversarial modes that capture different temporal aspects of corruption behavior and establish their hierarchical relationship with respect to network capacity. The analysis employs time-expanded graph representations and develops recursive counting methods for computing expected network capacity under random time assignments, along with degradation matrix decompositions to enumerate network failure scenarios. We extend classical capacity bounds to time-varying settings where a network yields an expected capacity under uniform random edge- time assignment. The framework provides tools for analyzing communication systems where connectivity patterns evolve over time while operating under adversarial interference
Augmenting attention : an OODA-centric framework for explainable AI in AR human-AI teaming applications
No full textArtificial Intelligence (AI) is increasingly deployed in high-stakes environments where success depends on more than computational accuracy; it also requires alignment with human perception and attention. Traditional explainable AI (XAI) methods provide static, post-hoc justifications that are poorly suited to time-critical decision cycles. This thesis investigates whether perceptually aligned, real-time explanations in Augmented Reality (AR) can enhance performance, workload balance, and trust within the Observe–Orient–Decide–Act (OODA) loop. A custom AR search-and-rescue simulation tested three conditions: no assistance, static overlays, and perceptually aligned explanations using adaptive cues such as occlusion-aware tethers and urgency-based visuals. The results show that any explanation improved results compared to no support, with perceptually aligned explanations producing the strongest gains: accelerating rescue performance, improving attentional alignment, reducing cognitive inefficiencies and fostering calibrated trust without distraction. These findings advance an OODA-centric framework for XAI and demonstrate that explanations can serve as active perceptual supports rather than passive rationalizations. The work contributes design principles for AR-enabled XAI systems that integrate objective, subjective, and physiological evidence to improve human performance in mission-critical contexts
Patient violence in the emergency department : the potential role of endogenous and exogenous factors
No full textPatient Violence against nurses is a widespread problem resulting in both emotional and physical injury to the nurse. Emergency Department (ED) nurses are at an increased risk due to the volume and variety of the patients they serve, and the general chaotic environment of the ED; however, little research has been done examining the characteristics of patients who offend and the physical environment of the ED where the event happened. The aim of this three-article dissertation was to develop a more thorough understanding of the personal attributes (endogenous) of the individual patient and external (exogenous) factors of the emergency department (ED) setting and how they potentially influence violence against nurses in the ED. The first manuscript was a scoping literature review that aimed to gain a deeper understanding of potential precipitating factors for patient violence in the ED. The second manuscript applied Juarez’s Public Health Exposome Conceptual Model to the concept of patient violence against nurses, proposing the novel investigator developed Patient Violence Public Health Exposome (PVPHE) Conceptual Model. This model explained endogenous factors of individuals and how these factors affect the potential for violence. The third manuscript was a descriptive qualitative study guided by Florence Nightingale’s Environmental theory that sought to develop a deeper understanding of the lived experience of ED nurses in Alabama that had been the victim of or witness to patient violence against nurses and the role the physical environment potentially played in these acts. Findings showed that both endogenous and exogenous factors influence the potential for patient violence and that system and nursing interventions could potentially mitigate this risk
Frameworks for multi-source image search using latent space feature matching
No full textIn this dissertation we study frameworks for image matching for three distinct application scenarios: the first relates to positioning in GPS agnostic environments, the second relates to matching and retrieving similar images in an indoor environment sourced from multiple uncalibrated cameras and the third relates to matching and retrieving satellite images across multiple uncalibrated satellite cameras. We propose three different frameworks the first one based on the idea of transformers, the second one based on the idea of autoencoders and the third one based on the idea of Siamese networks. We report extensive experiments with novel datasets for each of these scenarios. For the first we use a novel high altitude aerial image dataset obtained from Leon county GIS in Florida and a publicly available dataset curated from Google Earth, for the second we curate our own dataset at UAH and use it for our experiments. Finally, for the third we use dataset from Maxar and Planet obtained at the courtesy of NASA
Liposomes as a platform for CD40 ligand presentation for the purpose of feeder-free B cell activation
Get PDFImprovement of in-vitro culture of immune cells is critical for expanding our understanding of the immune system and advancing the treatment of diseases, whether pathogenic, cancerous, or autoimmune, via cellular immunotherapies. This study aims to develop a feeder-free B cell culture system using biomaterials-based presentation of a critical signaling molecule, namely CD40 ligand (CD40L). Traditional B cell culture methods rely on allogenic feeder cells to present CD40L, but a culture of only autologous cells is preferable for cellular immunotherapies. Previous work of our lab established an effective feeder-free B cell culture system using magnetic microbeads as a synthetic platform for CD40L presentation, and this study tested liposomes as an alternative platform for CD40L presentation. When coupled with appropriate soluble signaling, the liposome effectively induced the hallmarks of B cell activation and subsequent germinal center (GC)-like reactions in vitro, namely a large proliferation (up to 27-fold expansion), antibody isotype class switch recombination, and differentiation into effector cells in a feeder-free, serum-free culture. More particularly, liposome-based CD40L presentation was more effective in the generation of antibody-secreting cells (ASCs) when compared to the microbead-based presentation. Up until now, liposomes have been mainly used for drug delivery, but the success of this study highlights their potential for use as a signal presentation platform in cell culture generally, and this research specifically is an important step on the path toward viable B cell-based immunotherapie
Dual-mode linear phased array antennas for monopulse radars
Get PDFPhased array antennas are widely used around the world. Much research is focused on extending capabilities of modern wireless systems and radars. Dual-mode elements are researched for use in beamforming, monopulse radar and multi-frequency applications. Beamforming in itself is an extensively researched topic, aimed at canceling interference and/or finding signal angle-of-arrivals. The goals of this thesis are two-fold. Firstly, to take the monopulse capabilities of a dual-mode antenna element to allow for a linear phased array antenna to generate the sum, delta-azimuth, and delta-elevation channels whereas normal linear phased array antennas can only generate a single difference channel. Secondly, to exploit the signal separating abilities of eigen-space methods to improve the performance of monopulse in a scenario where there is a closely correlated target corrupting the data. Future work should investigate array designs using multi-mode elements and further studies of any extra capabilities such an element brings to adaptive processing
Improving satellite needs working group assessment process through automation and process consolidation
Get PDFThe increasing complexity of modern software ecosystems, presents significant challenges to system resilience, maintainability and automation. This work presents a proof-of-concept implementation of an automation system to address these challenges for a large scale fragmented software systems. Succinctly we address these challenges in the context of Satellite Needs Working Group (SNWG), which is responsible for collecting and communicating federal agencies\u27 Earth observation needs to National Aeronautics and Space Administration (NASA). Multiple automation scripts and applications exist to support the SNWG\u27s assessment cycle, encompassing the areas of data validation, visualization, report generation, and user management. However, the dispersion of these tools into isolated, stand-alone components has led to operational inefficiencies, data inconsistency, and increased maintenance overhead. Through a comprehensive analysis of the SNWG assessment phases, this research identifies the specific challenges stemming from fragmentation and highlights the deficiencies in inter-system communication. To resolve these issues, our work proposes a unified software platform conceptualized using modern software engineering principles, such as micro-services architecture, RESTful API design, and cloud-based infrastructure. By consolidating the previously silo-ed software components into a centralized system, the proposed solution enhances inter-agency collaboration, reduces manual intervention, improves data consistency, and strengthens security. From a software engineering perspective, this work exemplifies a broader industry trend in software development: the transition from silo-ed, legacy automation scripts to integrated, scalable, and maintainable ecosystems. Similar challenges exist in other domains, for example, finance, healthcare, and government operations, where organizations struggle to unify disparate software components while ensuring operational continuity and resilience. By demonstrating best practices in systems architecture, software development, testing, and deployment, this thesis presents findings that can be extended beyond the realm of Earth observation applications, offering a generally applicable framework for designing resilient and unified software platforms
