Digital Commons Network^™

Deciphering Ultrafast Photoinduced And Photocatalytic Reaction Dynamics On Oxide Surfaces: Direct Detection Of Radical Intermediates, Fragment Trapping, And Carbon–Carbon, Carbon–Oxygen, And Carbon–Hydrogen Bond Formation Pathways, Aakash Gupta

Graduate Studies Theses and Dissertations 2026

Understanding photoinduced reactions at solid interfaces is essential for advancing heterogeneous photocatalysis, surface photochemistry, and energy conversion technologies. This dissertation investigates the ultrafast dynamics of reactive intermediates, fragment trapping, and radical-mediated bond formation on oxide surfaces using time-of-flight mass spectrometry in conjunction with femtosecond pump-probe spectroscopy. Various experimental findings are validated through collaborations via density functional theory (DFT). By combining temporal, mass, and energy-resolved measurements, this work provides molecular-level insight into the elementary processes governing light-driven surface reactions. The photodissociation dynamics of CH₃I adsorbed on TiO₂(110), TiO₂(100), and amorphous silicon oxide surfaces are examined …

Policy Into Practice: Exploring School Counselors' And School Psychologists' Knowledge And Sensemaking Towards The Application Of Alternative Gifted Identification Criteria For Lower Socioeconomic Students, Brittany E. Hague

Graduate Studies Theses and Dissertations 2026

Persistent underrepresentation of students from lower socioeconomic status (SES) backgrounds in Gifted education reflects long-standing structural inequities embedded in identification policies and practices. In response, many Florida school districts have adopted equity-oriented identification reforms, including universal screening, local norms, and multiple-measure approaches. However, policy equity does not automatically translate into equitable outcomes; rather, it is mediated through the interpretive work of school-based practitioners. Guided by Sensemaking Theory, this convergent mixed-methods study examines how school counselors and school psychologists construct meaning around alternative Gifted identification criteria and how their beliefs, professional judgment, and organizational contexts shape implementation. The study explores how …

Examining Teachers’ Data Usage Using The Teacher Data Use Survey, Natasha L. Hawkins

Graduate Studies Theses and Dissertations 2026

The United States spends approximately 2.7 billion dollars on classroom assessments and local exams for K-12 students (SIMBA, 2019).  However, despite this financial investment and the adoption of data-driven frameworks such as Multi-Tiered System of Support, the U.S. Department of Education found that only 55% of teachers used student data to make instructional decisions (U.S. Department of Education, 2007).  This study aims to explore the psychological and organizational factors that influence teachers’ data use when making instructional decisions.

This study used the Teacher Data Use Survey (TDUS) to investigate the extent that teachers’ use of data could be predicted by …

Integrated Optical Probes For Confocal Scanning Imaging And Adjustable Coherent-Gated Dynamic Sensing, Yonglin Huang

Graduate Studies Theses and Dissertations 2026

Optics and photonics have been one of the most important sciences and technologies that impact modern human life in a big way. For example, fiber-optics for communications and artificial intelligence. Optical probes are critical components for optical imaging and optical sensing technologies that have been actively researched and developed in the past decades. Advanced fiber-optic sensor probes with smaller size, better performance, lower noise, higher photon efficiency, rapid sensing time, and lower cost are needed in many applications, such as nanoscale material science, chemistry, and biomedical fields, etc.  In this project, new fiber-optic sensor probe technologies and integrated micro-optic devices …

Modeling And Mitigating Atmospheric Degradation In Computer Vision With Application In Renewable Energy Prediction, Sumit Laha

Graduate Studies Theses and Dissertations 2026

Weather-induced variability poses significant challenges to the reliability and performance of modern computational systems, particularly those relying on visual perception and environmental prediction. This dissertation focuses on enhancing computer vision and machine learning based predictive models that operate under varying atmospheric conditions. Two representative weather-impacted applications are investigated: image dehazing and solar photovoltaic (PV) power output forecasting. Image dehazing focuses on the restoration of clear, unobstructed visuals from hazy or foggy images, a task that is vital for various applications. On the other hand, photovoltaic (PV) power forecasting aims to predict future solar energy generation based on historical sky images …

Emergent Spin Fluctuation And Structural Metastability In Self-Intercalated Cr1+Xte2 Compounds, Clayton Conner, Ali Sarikhani, Theo Volz, Mathew Pollard, Mitchel Vaninger, Xiaoqing He, Steven Kelley, Jacob Cook, Avinash Sah, John Clark, Hunter Lucker, Cheng Zhang, Paul Miceli, Yew San Hor

Physics Faculty Research & Creative Works

Intercalated van der Waals (vdW) magnetic materials host unique magnetic properties due to the interplay of competing interlayer and intralayer exchange couplings, which depend on the intercalant concentration within the van der Waals gaps. Magnetic vdW compound chromium telluride, (Formula presented.), has demonstrated rich magnetic phases at various Cr concentrations, such as the coexistence of ferromagnetic and antiferromagnetic phases in (Formula presented.) (equivalently, (Formula presented.)). The compound is created by intercalating 0.25 Cr atom per unit cell within the van der Waals gaps of (Formula presented.). In this work, we report a notably increased Curie Temperature and an emergent in-plane …

Contextual Influences On Algebra 1 Achievement In Florida: A Multilevel Analysis Of Fsa Data And Policy Implications For B.E.S.T., Alberto Leiro Jr

Graduate Studies Theses and Dissertations 2026

This study examined how school-level and district-level contextual factors are associated with Algebra 1 achievement in Florida using a multilevel modeling framework. Drawing on statewide publicly available data from the Florida Standards Assessments (FSA), the analysis included schools nested within districts to account for the hierarchical structure of educational data. School-level predictors included absenteeism, economic disadvantage, English language learner status, student mobility, and the proportion of students with disabilities, while district-level variables included poverty and crime rates. Results from the null model indicated that a meaningful proportion of variance in Algebra 1 achievement was attributable to differences among districts, supporting …

Generation Of Wave Turbulence In Dipolar Gases Driven Across Their Phase Transitions, Georgios A. Bougas, Koushik Mukherjee, Simeon Mistakidis

Physics Faculty Research & Creative Works

Ultracold quantum gases with long-range anisotropic interactions host novel exotic phases of matter, such as super solids, exhibiting both rigid and superfluid characteristics. The impact of this interplay on the out-of-equilibrium dynamics of dipolar gases, and in particular its connection with universal turbulent behavior, remains highly unexplored. Here, upon considering a dipolar Bose-Einstein condensate of dysprosium atoms being dynamically driven across the super solid-superfluid phase transition and vice versa, we unveil the emergence of a robust nonequilibrium quasi-steady state. This state displays self-similar momentum distributions exhibiting algebraic decay at large momenta, with scaling exponents supporting the existence of wave turbulence. …

The Perceptions Of Instructional Coaching On Teacher Efficacy And Retention In Elementary Schools, Stephanie Lucas

Graduate Studies Theses and Dissertations 2026

Administrators in a large school district in Central Florida encountered challenges regarding teacher retention and sustainability. Flite STEM coaching, a new instructional coaching model, was developed to support teachers in hopes of reducing those challenges. This model includes coaching cycles that encouraged collaboration and reflective thinking aligned with professional learning. This qualitative study focused on implementing the Flite STEM coaching model with teachers and instructional coaches. The coaching cycle consisted of the following: 1) a pre-observation conference, 2) video observation, 3) post-observation conference with feedback, and 4) a professional learning opportunity. It included DebriefScape Observation Dashboard resources to collect and …

Genuine And Meaningful Black Character Narratives In Video Games, Derek L. Manns

Graduate Studies Theses and Dissertations 2026

The lack of Black representation in video games reflects stereotypes and hollow narratives. Authentic and meaningful design of Black characters allows Black players a reflection of emotional attachments everyone wants when playing a game. Examining racial identities through avatars, critiquing the notion that customization equates to racial inclusivity, limited options and predominant, white-coded protagonists reinforce systemic biases in games (Dietrich, 2013). My Afrofuturistic content analysis framework explores Black culture with a future of speculative fiction. Reimagining the past, present, and future through Black narratives for alternate futures (Womack). Integrating these ideas enhance culture and aesthetics in this dissertation to highlight …

Discrete Element Modeling Of Granular Soils: Critical State Behavior Applied To Impact Pile Driving, Esteban Patino Marin

Graduate Studies Theses and Dissertations 2026

This thesis investigates the use of the Discrete Element Method (DEM) to study two complementary aspects of granular soil mechanics: critical state behavior of granular materials and dynamic response of driven piles in sand, both of which are governed by the same particle-scale mechanisms of dilation, contraction, and fabric evolution.

The first examines the critical state behavior and fabric anisotropy of granular soils through DEM simulations of direct shear, direct simple shear, and true triaxial tests. Sphere-cluster particles representative of a uniform sand are used in two assemblages of approximately twenty-five thousand and one hundred twenty-five thousand spheres to evaluate …

Securing The Energy Transition: Cyber-Physical Security And Resilience In Next-Generation Power Systems, Airin Rahman

Graduate Studies Theses and Dissertations 2026

Modern power systems are rapidly evolving into renewable-dominated and digitally interconnected cyber-physical infrastructures due to the increasing deployment of distributed energy resources (DERs), inverter-based technologies, and advanced control platforms. Maintaining reliability under high renewable penetration requires flexible resources capable of shifting energy across extended time horizons. Long-duration energy storage (LDES), particularly hydrogen-based energy systems, has therefore emerged as an important enabler of renewable integration, grid flexibility, and resilience. However, the growing dependence on communication, sensing, and distributed control also expands the cyber-physical attack surface of modern power systems, creating security and resilience challenges that conventional operational paradigms were not designed …

Advancing Cyber-Physical Security And Resilience Of Modern Power Systems: Intelligent Monitoring, Secure Operation, And Resilient Recovery, Md Moshiur Rahman

Graduate Studies Theses and Dissertations 2026

Modern power distribution systems are rapidly evolving into cyber-physical, DER-rich, and data-driven networks that rely on extensive sensing, communication, automation, grid-edge intelligence, and operator decision support. While this transformation improves flexibility, observability and controllability, it also expands the cyber-attack surface and increases the risk that cyber intrusions can propagate into physical disturbances, compromised DER operation, degraded situational awareness, and interrupted service continuity. This dissertation advances the cyber-physical security and resilience of modern distribution systems by developing a high-fidelity real-time cyber-physical hardware-in-the-loop testbed using OPAL-RT, EXata CPS, industrial relays, SCADA/RTAC, HMI, and grid-edge devices to emulate realistic DER-integrated distribution grid operation. …

Mathematical Modeling And Characterization Of A Variable Stiffness Ankle-Foot-Orthosis, David E.L. Richards

Graduate Studies Theses and Dissertations 2026

Conventional ankle–foot orthoses (AFOs) typically employ static stiffness profiles that do not replicate the dynamic quasi-stiffness of the human ankle during gait. Variable stiffness mechanisms (VSMs) offer a promising alternative solution for gait pathologies, such as foot drop and post-stroke hemiparesis; however, their implementation is limited by the lack of accurate mathematical models capable of predicting force and stiffness characteristics. The objective of this thesis is to develop and validate comprehensive mathematical models describing the kinematics and kinetics of a novel variable stiffness ankle–foot orthosis (VS-AFO). This study derives governing equations to characterize how mechanical adjustments influence the force transmission …

Examining Principals' Perceptions Of Their Preparedness To Lead In Title I Schools, Tiffany Roebuck

Graduate Studies Theses and Dissertations 2026

Principals serving in Title I schools face complex instructional, organizational, cultural, and community related demands that require specialized leadership preparation and support.  The purpose of this qualitative phenomenological study was to explore the lived experience of principals serving in urban Title I schools regarding their preparedness, supports, challenges, and successes as instructional leaders. The study also examined principals' perceptions of culturally proficient leadership and principal preparation program attributes considered essential for leadership readiness in high-needs school settings. Guided by the Culturally Responsive School Leadership (CRSL) framework, data were collected through semi-structured interviews with 10 principals serving in urban Title I …

Visual Cues Of Human-Likeness, Not Salience, Impact Trust-Related Human-Computer Interaction, Jordan Schotz

Graduate Studies Theses and Dissertations 2026

As interactions with digital agents become increasingly integrated into daily life, understanding how visual representations influence social decision-making is critical. Previous research in human-computer interaction has frequently confounded the psychological effects of an agent's perceived human-likeness with the underlying visual salience of the stimuli. To address these persistent gaps, the present study systematically isolated the effects of human-likeness and visual cue trustworthiness on trust behavior while controlling for objective image properties. The present study expanded on and normed the Virtual Avatar Facial Stimuli Set (VAFSS), a comprehensive database comprising hundreds of identity-matched photographs and computer-generated avatars varying across a spectrum …

Concept Drift Detection For Streaming Data Using One-Class Classification, Poorna Sandamini Senaratne

Graduate Studies Theses and Dissertations 2026

Modern machine learning systems are increasingly deployed in streaming environments where data arrive sequentially and the underlying data-generating process may evolve over time. This phenomenon, known as concept drift, can significantly degrade model performance if not detected and addressed in a timely manner. This dissertation proposes a principled framework for concept drift detection based on one-class classification, integrating neural network embeddings with Support Vector methodologies.

The proposed approach leverages neural networks to learn compact and informative embeddings of input data, capturing complex nonlinear structures in a lower-dimensional latent space. These embeddings are then used to construct a statistical description of …

Study On Fracture Toughness Under Different Modes Through Continuum Damage Mechanics Based Fracture Locus, Yeting Sun

Graduate Studies Theses and Dissertations 2026

Traditional elastic-plastic fracture mechanics (EPFM) relies on crack-tip analysis, whereas continuum damage mechanics (CDM) is typically calibrated from uncracked bodies. This dissertation aims to bridge the gap between these two fundamental branches by explicitly linking fracture toughness with ductile damage models. Based on the assumptions regarding Mode I crack deformation, analytical solutions are derived to establish a novel relationship among Mode I fracture toughness, CDM-based ductile fracture strain, and material strain hardening capability. This theoretical framework is subsequently extended to encompass Mode II and Mode III loading conditions. To validate the proposed relationships, finite element (FE) models are developed in …

Volumetric Fluorescence Microscopy For High-Throughput And High-Sensitivity Imaging: From Single Molecules To Tissues, Le-Mei Wang

Graduate Studies Theses and Dissertations 2026

Fluorescence microscopy is an indispensable tool in the biological sciences, enabling researchers to investigate intricate subcellular structures, particularly for volumetric studies. However, conventional optical microscopy for volumetric imaging remains fundamentally constrained by imaging speed and throughput. To bypass traditional serial z-scanning, we introduce an axially scan-free method using a phase layer cake to modulate the system's point spread function. This approach projects volumetric information onto a 2D plane in a single shot, offering high flexibility in tuning axial depth alongside simultaneous multicolor imaging with high spatial resolution and sensitivity. This dissertation divides these technical advancements into cellular and tissue imaging …

Human And Ai Support In Business Simulations: A Quasi-Experimental Mixed Methods Study Of Performance At Scale, Sara Willox

Graduate Studies Theses and Dissertations 2026

Large classes change what instruction looks like. In hybrid business courses with high enrollment, it becomes harder to respond to individual students, and performance can suffer as a result. This study looked at what happens when that gap is addressed in different ways during an eight-week business simulation at the University of Central Florida. Six course sections were divided into three study groups. One group worked without support, one received instructor guidance, and one used AI tools that included a course search system and generative responses. Student outcomes were based on weekly profit and loss recorded in Sim Companies. The …

Careless Responding: Testing The Theory Of Vigilance, Rusty Wilson

Graduate Studies Theses and Dissertations 2026

Careless responding (CR) has been identified as a threat to the psychometric integrity of cognitive and non-cognitive tests, with much of the current research focusing on the identification and removal of carelessness from dataset. While this research has proved fruitful in improving data quality, there has been a recent push to move towards preventing carelessness as opposed to post-hoc removal, which harms statistical power. However, the most common prevention strategy to prevent carelessness (pre-survey warnings) has shown equivocal effects. Additionally, the literature lacks an agreed upon theory to explain why carelessness occurs. To address these gaps I introduce theory from …

Michigan Academician Volume 50, Issue 2

Michigan Academician

Volume 50, Issue 2 - Abstract Issue

Optimal Takeoff Trajectory Prediction Of Electric Drones Based On A Fully Automated Optimal Experimental Design Method, Jiachen Wang, Dheeraj Paramkusham, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft is attracting great interest as a viable solution to promote urban aerial mobility with promising flexibility as well as emission reductions. However, the low specific energy of the current battery is still a strong constraint on the range and endurance of eVTOL flights, especially considering the significant power demands during the takeoff process. Engineering design optimization permits promising solutions for the minimum takeoff energy consumption but can be computationally intensive due to iteratively evaluating simulation models. Surrogate-based design optimization is efficient but still relies on optimization iterations which prohibit real-time decision-making. To fill …

Insights Into The Petrogenesis Of Alkalic, Shonkinitic Magmas From The Adel Hill Volcanic Field, Montana, Kenneth L. Brown, C. L. Mcleod, M. L. Lytle, T. J. Cracas, B. J. Shaulis, M. Loocke

Geology and Environmental Geoscience Faculty Publications

Shonkinites are rare alkali-rich igneous rocks found in the geological record from the Precambrian to the Eocene. This study investigates the Upper Cretaceous shonkinites from the Adel Hills Volcanic Field (AHVF), central Montana. The AHVF shonkinites are porphyritic with large, euhedral to subhedral phenocrysts of diopside that exhibit sector zoning. Other major mineral phases include plagioclase, sanidine, and secondary zeolites. Minor and accessory phases identified with SEM-EDS include magnetite, apatite, rare ilmenite and pyrite, and secondary calcite. Bulk rock SiO2 ranges from 47 to 49 wt% with Na2O + K2O varying from 5.50 to 7.34 wt% within that silica range. …

Large Language Models For Neurology: A Mini Review, Donald C. Wunsch, Daniel B. Hier

Electrical and Computer Engineering Faculty Research & Creative Works

Large language models have the potential to transform neurology by augmenting diagnostic reasoning, streamlining documentation, and improving workflow efficiency. This Mini Review surveys emerging applications of large language models in Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy, with emphasis on ambient documentation, multimodal data integration, and clinical decision support. Key barriers to adoption include bias, privacy, reliability, and regulatory alignment. Looking ahead, neurology-focused language models may develop greater fluency in biomedical ontologies and FHIR standards, improving data interoperability and supporting more seamless collaboration between clinicians and AI systems. Two future developments have the potential to be particularly impactful: (1) …

Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

An output feedback (OF)-based control scheme utilizing both a scalable multilayer neural network (MNN) observer and actor–critic MNN via integral reinforcement learning (IRL)/adaptive dynamics programming (ADP) approach for a class of nonlinear systems with output constraints is introduced. The proposed observer, critic, and actor MNN weight updates are derived using a singular value decomposition (SVD) of MNN activation function gradient along with output error, Bellman and control input errors, respectively. Next, the approach incorporates continual learning (CL), utilizing a penalty function in the weight update laws for both actor–critic MNNs to consolidate knowledge from previous tasks and enhance learning in …

Safe Optimal Control Framework For Cooperative Manipulation Of Objects In Human–Robot Teams, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article introduces a distributed deep neural network (NN)-based adaptive control framework for cooperative object manipulation in human–robot teams with unknown agent dynamics by using three distinct multilayer NN observers (MNNOs). The first observer, termed the reference point estimator, enables each robotic agent to estimate the object's reference center using consensus-based learning, even without direct access to global reference trajectories. The second observer, referred to as the human force-to-trajectory estimator, uses human-applied forces to infer the intended position, velocity, and acceleration of the object, enabling real-time estimation of human intent. Together, these two observers allow distributed estimation of human-intended motion. …

Self-Calibrating Uav Navigation: Reinforcement Learning Approaches For Horizontal Trajectory Estimation, Shirin Nasr-Esfahani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate unmanned aerial vehicle (UAV) trajectory estimation is essential for autonomous navigation, particularly in GPS-denied environments. Visualodometry and simultaneous localization and mapping (SLAM) approaches require precise camera intrinsic parameters, which are typically obtained through predefined or offline calibration. Instead, in this work, we propose a reinforcement learning (RL)-based self-calibration framework that estimates camera intrinsic parameters directly from monocular video sequences, without requiring prior knowledge of the camera, environment, or calibration targets. This intrinsic parameter estimation is then leveraged to achieve robust UAV trajectory estimation using only video data. We formulate the problem as a sequential decision-making task, where an RL …

Online Lifelong Optimal Adaptive Control Of Partially Uncertain Strict Feedback Discrete-Time Systems With Application To Quadrotor Uavs, Maxwell Geiger, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article considers the infinite time horizon optimal adaptive tracking control of partially uncertain strict feedback discrete-time (DT) systems with application to quadrotor uncrewed aerial vehicles (UAVs). First, the strict feedback DT system is transformed into an equivalent affine nonlinear DT system in terms of the tracking error dynamics. The optimal adaptive tracking control problem is solved using an augmented system approach, where a horizon of future bounded reference trajectory points is used in the augmented state, when compared to using a single point. It is assumed that the internal dynamics of the strict feedback system are unknown, but the …

New Metrics For Disambiguating Feature Overlap And Catastrophic Forgetting In Incremental Learning Contexts, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Catastrophic forgetting remains a central challenge in lifelong learning, where newly acquired knowledge interferes with previously learned tasks, degrading performance over time. Mitigation strategies such as rehearsal and regularization have been proposed, but both introduce limitations, either by retaining old data or by constraining model updates in ways that may impair learning. Complicating matters, recent findings show that feature-space overlap between tasks can produce similar performance drops even in models that memorize data, making it difficult to distinguish true forgetting from representational interference. Current accuracy-based metrics fail to disentangle these effects, undermining diagnostic clarity. In this work, we introduce the …