University of Central Florida
University of Central Florida (UCF): STARS (Showcase of Text, Archives, Research & Scholarship)Not a member yet
166656 research outputs found
Sort by
The Intersection of AI & Instruction: Navigating our New Information Landscape
No full textThis poster will explore our current understanding of AI and dive into a broad view of where libraries are at with AI technology. We will provide a framework to get library instructors prepared to engage with questions and projects on the topic of AI within their classrooms, research appointments, liaisons, partnerships, and university at large
Sliding Through The Cracks: An Evaluation of The FBA System and An Exploration of Traditional Trombone Training Practices
No full textMy experience as a low brass player trained in an FBA (Florida Bandmasters Association) program was well rounded. I attended a school with a rich history of continued excellence, taking part in various honor bands and preparing standard trombone repertoire for the Solo and Ensemble evaluations. Despite all of this, fundamental aspects of my trombone playing were lacking when I arrived at college, remaining unrectified until I started my master’s degree at UCF. I was a committed trombone player, regularly practicing multiple hours every day during my formative years. In retrospect, I realize that my performances suffered in fundamental areas. This was due to a lack of guidance in efficient tone production practices, correct slide technique; and a tradition of sound associated with classical trombone repertoire. I am not alone in this experience. As part of this document, I circulated a survey to various professional trombonists who came from Florida band programs. The survey results proved how multiple professional trombone players that emerged from FBA programs shared similar accounts.
It is my goal with this thesis to highlight and analyze the disparities in trombone training seen in the FBA band system through the experiences of myself and others. I will also provide implementable solutions that create an equitable and realistic opportunity for all trombonists to receive information that has been kept behind paywalls of private instruction and conservatory training.
It is also my goal to offer specific orchestral teaching strategies and pedagogical methods that can be easily implemented into the average middle or high school band curriculum. These strategies take the methods traditionally used to individually train professional trombonists and apply them to the band room warmup, and solo repertoire in a way that fosters self-assessment through well informed goal-oriented practice
Characterizing Muscle Control as an EMG Visual Matrix
No full textEvaluating electrical muscle activity patterns using surface electromyography (EMG) is a widely used technique to assess movement in research settings, but its use has not been translated to clinical settings. This study aims to investigate the potential of evaluating muscle activity control through a visual matrix display. EMG data from older and younger adults collected in a previous seated locomotor perturbation study was used to generate visual matrices representing their lower-limb ankle muscle activity. Visual matrices from each condition consist of 20x20 grids, where each axis represents activity from an individual muscle of muscle pairs, such as the tibialis anterior and soleus. The color gradient in each square in the matrix represents the time the EMG was in that box such that darker colors indicate more time spent. We anticipated that older adults’ data will generate EMG visual matrices where the center is more filled during the perturbed stepping stage of the conditions compared to the unperturbed stepping stages, indicating higher simultaneous muscle activation strategies (i.e. co-contraction) in response to these perturbations. We also predicted that EMG visual matrices generated from younger adults’ data would be more filled along the axes instead compared to the older adults’ matrices. Our results, however, have been unable to capture a change in muscle activation behavior between unperturbed stepping and perturbed stepping stages, and a difference between young and older adult muscle activity has not yet been observed in these matrices. This may be due to the methods used during EMG processing or unknown variables in the tested dataset, which requires further investigation. Regardless, these EMG visual matrices could provide a more detailed and easily understandable assessment of muscle co-contraction compared to previous measures, allowing clinicians to develop more personalized rehabilitative training options for patients if applied in clinical settings
Evaluating Robustness of Methods for Comparing Two Means Using Paired Data With Few Incomplete Pairs
No full textPractitioners often resort to the paired t test to test equality of two means when data is complete. When small amounts of data are missing, is this method still as robust? Are there alternative methods which can perform the job better on the missing data? In this thesis, we measured the robustness of the paired t-test, two sample t-test, corrected z-test, modified corrected z-test, weighted t-test, pooled t-test, optimal pooled t-test, unequal variance test, correlation focused t-test, multiple imputation method, mixed model method, modified maximum likelihood estimate method, and Uddin’s modified maximum likelihood estimate method. This is simulated in an environment which considers all possible combinations of specified missing values. The results suggest that when the paired t test hovers above the significance level of 0.05 on complete data, some alternative methods perform just as well if not better depending on case-by-case scenarios. For smaller sample sizes, the mixed model method performs the best under a series of strict significance levels. As sample size increases, all methods perform similarly well
Least Squares Support Vector Data Description with Adaptive Optimizers
No full textOne-class classification has emerged as a powerful technique for data description, enabling a model to learn exclusively from data belonging to a single (target) class. By focusing solely on patterns within this class, this classification procedure is implemented in order to successfully assess whether incoming input deviates or is part of the target group. This approach develops a sophisticated understanding of the defining characteristics of the target data in relation to other groups. Consequently, any data point that deviates from the target group is flagged as an anomaly because it diverges from the learned distribution. One way to explore the implementation of one-class classification is through the use of Least Squares Support Vector Data Description (LS-SVDD).
In this study, we apply the Least Squares Support Vector Data Description (LS-SVDD) framework by leveraging gradient descent methods with adaptive learning rates to solve the associated optimization problem. We investigate a range of adaptive optimization strategies to simultaneously estimate the center and radius of the hypersphere that encloses the target data. Our approach utilizes a closed-form solution for the radius, which is iteratively updated in tandem with the center. Emphasis is placed on the final cost function value, the optimized center and radius, and the execution times as key performance metrics. The results demonstrate that adaptive learning rate methods not only yield competitive accuracy but also achieve significantly faster convergence compared to traditional gradient descent, highlighting their critical role in modern machine learning applications
Multiscale Modeling And Experimental Evaluation Of Droplet Evaporation In High-Pressure Pulsed Spray Cooling For Thermal Management Applications
No full textDroplet evaporation plays a vital role in spray cooling applications, helping to maintain safe operating temperatures for high-powered devices such as lasers and supercomputers. There exists an ongoing debate regarding the appropriateness of diffusion-limited versus kinetically limited models for describing this complex process. This work seeks to bridge the macro-scale evaporation, governed primarily by capillary forces, with the nano-scale interactions among the vapor, liquid, and solid phases through a comprehensive description of disjoining pressure.
By integrating principles from lubrication theory, heat conduction, diffusion, and statistical methods, a detailed model for evaporative mass flux is developed. This model incorporates various interactions, including capillary, Van der Waals, structural, and electrostatic forces, while also illustrating how the thickness and thermal properties of thin films impact evaporation on low thermal conductivity substrates. Single droplet evaporation experiments conducted on pure copper and composite substrates, composed of metal thin films (copper, aluminum, and titanium) layered over fused silica, yield results that align closely with the proposed model, particularly for temperatures below saturation, where bubble formation is not considered.
Moreover, the investigation into single droplet evaporation is extended by applying statistical methods, specifically the gamma distribution, to analyze a wide array of non-interacting droplets evaporating on a heated substrate. This analysis leverages high-speed video recordings, infrared temperature measurements, and contour tracking. The findings exhibit strong agreement with the predictions from the single droplet evaporation model at temperatures below saturation, confirming the validity of the approach
Enhancing the Hardness of the Multispectral ZnS Transparent Ceramics Through Ga2S3 Incorporation: A Comparative Study of Vapor Transport Deposition and Solid-Solid Reaction Methods
No full textMultispectral zinc sulfide (MS-ZnS) is an important optical ceramic widely used in broadband imaging systems due to its wide transmission range and relatively low cost. However, its modest mechanical properties limit its durability in harsh environments. This dissertation investigates two solute strengthening methods, vapor transport deposition (VTD) and diffusion coupling (DC), to enhance the hardness of MS-ZnS windows through Ga2S3 incorporation while maintaining optical transparency. The VTD process successfully incorporated gallium in the subsurface, resulting in up to 120 % increase in microhardness compared to untreated samples, but with slight discrepancies in lateral gallium distribution. The DC technique demonstrated superior control and uniformity of gallium incorporation, achieving a 100% increase in average microhardness while preserving optical transmission. However, both methods initially resulted in subsurface cracking due to high gallium concentrations. To address this issue, modifications were implanted into both strategies to mitigate cracking: sulfurization during VTD and gradual diffusion for the DC technique. These modifications enabled crack-free gallium incorporation while maintaining hardness improvements. To better understand the effect of Ga on MS-ZnS, a series of characterization techniques were employed to provide insights into the gallium incorporation mechanisms and resulting material properties. This research demonstrates for the first time the feasibility of enhancing MS-ZnS hardness through controlled gallium doping, while maintaining good transparency. VTD and DC strategies could be combined with other established hardening techniques such as advanced coating technologies to create highly resilient MS-ZnS windows suitable for extreme environments or high-stress applications
Liquid Fuel Cloud Detonation Propagation and Dynamics
No full textDetonations are a form of combustion that produce significantly higher work per specific volume than traditional deflagration combustion, thus are an active area of interest for increased combustion efficiency and power generation. However, the highly unsteady nature of detonations complicates the ability to harness their energy in a fieldable technology, prompting the need for a more fundamental understanding of the detonation phenomena. Fundamental detonation research has overwhelmingly focused on gaseous reactants due to ease of experimentation, though liquid fuels are increasingly relevant as their high energy density makes them more suitable for real-world engine applications, and much of the research on detonation-based propulsion devices have operated with multiphase reactions. This research presents a liquid-fuel detonation experiment using aerosolized Jet-A droplets as the sole fuel in a detonation reaction. The oxidizer is modulated from pure oxygen to near-air though nitrogen dilution, and both equivalence ratio and droplet size are varied. Highly resolved diagnostics are used to image the reaction, including CH* chemiluminescence, shadowgraph, Mie scattering, and pressure measurements. Results show increasing nitrogen leads to more irregular detonations and the mass loading ratio scales with detonability limits. A characteristic liquid detonation length scale is shown through Mie scattering images and discussed in terms of mass stripping liquid droplet breakup models and heat transfer calculations
Bridging Physiology, Data Science, And Genomics To Illuminate Photosynthetic Variation In Sunflower
No full textPhotosynthesis is a critical metabolic process in plants involving ‘light reactions’ that capture solar energy to produce ATP and NADPH, and ‘dark reactions’ where these molecules power the enzyme Rubisco to synthesize sugars in the Calvin-Benson cycle. These processes serve as the primary energy source for plant growth and reproduction, displaying significant variation across species and environments. In Helianthus, distinct differences in photosynthetic traits are observed between annual and perennial species. Notably, carboxylation rates, photon capture, and maximum photosynthetic rates show strong phylogenetic signal (Pagel’s λ = 0.99) and are significantly higher in annuals. Photosynthesis is modeled here as a multivariate function-valued trait using the non-rectangular hyperbola model, and methods to test and compare different photosynthetic models are made accessible for researchers to implement in the R package photosynthesisLRC.
Genetic diversity in chloroplast genes related to photosynthesis reveal signs of positive selection on a suite of genes involved in the light reactions, and distinct genotypes are identified between annual and perennial species. Phylogenetic generalized least squares analysis indicate selective pressures from dry, arid environments as primary drivers of evolution in photosynthetic genes. These pressures promote increased CO2 specificity and catalytic activity in Rubisco, enhance the operations of light-harvesting complexes under high light intensities, and improve molecules responsible for energy production and chloroplast repair. The photosynthetic adaptations identified here have broad implications for evolutionary ecology and could be used to inform crop sunflower breeding programs aimed at improving photosynthetic efficiency and resilience to environmental stressors
Inter-Basin Groundwater Flow In West-Central Florida
Get PDFThe mean annual values of inter-basin groundwater flow (IGF) and its inter-annual and seasonal variability across 172 watersheds in west-central Florida were estimated using the Integrated Northern Tampa Bay (INTB) model, which is an application of the Integrated Hydrologic Model dynamically coupling HSPF and MODFLOW. The estimated IGF for the scenario without human fluxes shows spatial heterogeneity in the model domain ranging from -1291mm/year to 4808 mm/year, and the variability of IGF decreases with spatial scales. A region with gaining IGF is defined as groundwater importer and a region with losing IGF is defined as a groundwater exporter. The characteristics of IGF are dominated by hydrogeology: 1) The subregion with unconfined Upper Floridan Aquifer (UFA), where runoff essentially occurs through the groundwater system by point discharge through springs and by diffuse discharge, serves as a groundwater importer; 2) The subregions with confined UFA are dominated by IGF exporters, particularly the subregion with large local recharge; and 3) Both IGF importers and exporters exist in the subregion with semi-confined UFA, but the watersheds near the Hillsborough River tend to be IGF importers. IGF plays a key role in the mean annual water balance at the watershed scale by modulating the available water for partitioning. The mean annual precipitation in the study watersheds varies from 1180 to 1495 mm/year, while the available water has a wider range from 80 to 6198 mm/year. Moreover, the climate aridity index ranges from 0.94 to 1.18, but the watershed aridity index exhibits enhanced variability, ranging from 0.23 to 2.07, due to existence of IGF. Human activities are also found to affect available water directly since human flux is a component of available water and indirectly since IGF is affected by human flux, which counteracts the impact of groundwater pumping on available water in watersheds