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Full-Text Articles in Entire DC Network
Effects Of Goal Setting, Self-Monitoring And Feedback On Physical Activity In Older Adults, Sofia O'Leary
Effects Of Goal Setting, Self-Monitoring And Feedback On Physical Activity In Older Adults, Sofia O'Leary
USF Tampa Graduate Theses and Dissertations
Healthy aging can be defined as maintaining functional ability that promotes overall wellbeing as one ages. Adequate levels of physical activity in older adulthood are associated with many positive health outcomes which support healthy aging; however, most older adults do not meet the current physical activity recommendations associated with healthy aging. Generally, inadequate physical activity is associated with a variety of health risk factors including overweight and obesity, cardiovascular disease, Type 2 diabetes, and certain types of cancer. Although older adults share these same risk factors for inadequate levels of physical activity as adults, there are additional risk factors that …
An Analysis Of The Learning Activity System Of An Elementary Education Program For The Development Of Social And Emotional Competence In Preservice Teachers, Lisa Sheldon Brown
An Analysis Of The Learning Activity System Of An Elementary Education Program For The Development Of Social And Emotional Competence In Preservice Teachers, Lisa Sheldon Brown
USF Tampa Graduate Theses and Dissertations
This mixed-methods descriptive case study examined how a public research university's elementary education teacher preparation program develops social and emotional competence (SEC) in preservice teachers. Using Engeström's Expansive Learning Theory framework, the study analyzed the tools and mediating artifacts within the program's learning activity system, specifically focusing on activities known to develop SEC. Through semi-structured interviews with 18 instructors and comprehensive document analysis, the study found that SEC development is extensively integrated throughout the program's coursework and field experiences. Three primary types of SEC development activities were identified: self-reflection/self-awareness, active listening, and collaboration. The study revealed a significant correlation between …
Electrochemical Copper Printing For Wearable Electronics, Nirmita Roy
Electrochemical Copper Printing For Wearable Electronics, Nirmita Roy
USF Tampa Graduate Theses and Dissertations
Wearable electronics have become a transformative force across industries like healthcare, aerospace, and military applications. However, a significant challenge persists in directly integrating electronic circuits onto fabrics. Addressing this challenge, the aim of this research is to introduce a novel sequential manufacturing process. Initially, a fabric is coated with a customized ink containing lignin, establishing a conductive template through laser burning. Subsequently, a localized Hydrogen Evolution Assisted (HEA) copper electroplating method is applied, resulting in a low-resistive circuit layout. Our investigations encompassed nanostructure analyses using Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), Raman Spectroscopy, and Fourier Transform Infrared …
Coding Connections: Exploring Relationships Between Computer Science Learning And Mathematics Achievement In Secondary Education, Bradley Hayes
Coding Connections: Exploring Relationships Between Computer Science Learning And Mathematics Achievement In Secondary Education, Bradley Hayes
USF Tampa Graduate Theses and Dissertations
This dissertation in practice explores the intersection of computer science education, specifically computational thinking and programming, with mathematics achievement among 15-year-old students in selected English-speaking countries. The research addresses a gap in understanding whether skills developed through computer science can positively influence mathematics performance by assessing the extent to which learning in computer science transfers to mathematics.
To achieve this, a quantitative methodology was employed, incorporating pilot study data from a single school and large-scale survey data from the Programme for International Student Assessment (PISA) 2022. The analysis assessed the correlation between regular participation in programming activities and mathematics attainment, …
Cactus Infused Beads For Off-Flavor Mitigation In Aquaculture Systems, Rama Mahita Kambhampati
Cactus Infused Beads For Off-Flavor Mitigation In Aquaculture Systems, Rama Mahita Kambhampati
USF Tampa Graduate Theses and Dissertations
Aquaculture has become a vital component of global food production, now providing 50% of the world's fish supply. However, the industry encounters major challenges due to off-flavor compounds like Geosmin and 2-Methylisoborneol (MIB), which give fish an unpleasant earthy or musty smell. These compounds are detectable by humans at extremely low levels 0.7 parts per billion (ppb) for MIB and ten parts per trillion (ppt) for Geosmin—making them a persistent problem. Their presence not only reduces the sensory quality of aquaculture products but also results in significant economic losses, with U.S. catfish production incurring an additional $15–$23 million annually due …
Balancing Context And Clarity Through Visualizations For Better Decision-Making, Bhavana Doppalapudi
Balancing Context And Clarity Through Visualizations For Better Decision-Making, Bhavana Doppalapudi
USF Tampa Graduate Theses and Dissertations
In this era of a data driven world, the effective communication of data through visualizations is pivotal for converting complex information into accurate insights. Effective visualizations not only enhance users' comprehension of complex data but also induce trust, leading to better decision-making. This dissertation explores methods to improve trust in visualizations by providing additional context and enhancing their clarity, ensuring appropriate data interpretations and better decisions from users.
The work in the dissertation begins by examining the impact of scatterplots combined with statistical metrics such as accuracy on users' trust and decision-making focused on recommender systems. In addition, we show …
Efficient Smartphone Sensor Analysis For Behavioral Profiling In Transportation Research: A Case Study Of Driver And Passenger Classification, Wilson Lozano, Tempestt Neal
Efficient Smartphone Sensor Analysis For Behavioral Profiling In Transportation Research: A Case Study Of Driver And Passenger Classification, Wilson Lozano, Tempestt Neal
Research Reports
Our study investigates smartphone sensor data for classifying drivers and passengers, aligning with our original proposal to enhance multimodal transportation data collection via the OneBusAway app. We address challenges in balancing data quality with smartphone resource constraints and find that shorter data collection windows significantly improve classification performance. Additionally, feature standardization and selection enhance accuracy, particularly during extended data periods, supporting our goal of refining data quality from open-source platforms. These insights advance our objectives by optimizing data efficiency and supporting the real-world applicability of intelligent models in transportation safety and efficiency.
Advanced Strategies For Improving The Robustness Of Deep Learning, Keyu Chen
Advanced Strategies For Improving The Robustness Of Deep Learning, Keyu Chen
USF Tampa Graduate Theses and Dissertations
Machine Learning (ML) and Deep Learning (DL) have achieved great success across diverse fields in the last decades, such as facial recognition, medical diagnosis, and language translation. The success, however, largely hinges on the assumption that the training and testing data share the same distribution or domain. In practice, real-world data often exhibits domain shifts, leading to notable degradation in model performance. Hence, the generalization capability of machine lea=rning models is of great importance, which refers to the domain generalization problem. In this dissertation, we present DADG, an effective algorithm for domain generalization, aiming to learn domain-invariant features from seen …
Implementing Acceptance And Commitment Therapy To Reduce Caregiver Stress And Enhance Procedural Fidelity For Families Affected By Autism Spectrum Disorder, Casey K. Marsh
USF Tampa Graduate Theses and Dissertations
The rate of children diagnosed with autism spectrum disorder (ASD) is increasing each year (CDC, 2022). Although the severity of symptoms is specific to individuals, the families of those diagnosed are often also affected in a variety of ways. Caregivers of children with ASD experience higher rates of depression, anxiety, and stress. The purpose of this paper is to examine the effects of Acceptance and Commitment Therapy (ACT) on caregiver stress and procedural fidelity. Three caregivers of children with ASD were trained using an ACT curriculum and caregiver stress was measured using two self-report scales, before and after six ACT …
Phosphoglycerate Dehydrogenase Regulated By The Mitogen-Activated Protein Kinase Pathway Is An Actionable Vulnerability In Cutaneous Melanoma, Neel Jasani
USF Tampa Graduate Theses and Dissertations
Metabolic alterations play a critical role in shaping tumor growth and development. Many metabolic enzymes are shown to play an important role in different aspects of tumor development, growth, and metastasis. One such enzyme that we are investigating in this project is the Phosphoglycerate Dehydrogenase (PHGDH). The PHGDH gene, encoding the rate-limiting enzyme of the serine synthesis pathway, is located at chromosome locus 1p12 and frequently amplified in melanoma. PHGDH is required for the proliferation of melanoma cells with chromosome 1p12 amplification. However, the role of PHGDH in chromosome 1p12 non-amplified melanoma is poorly understood. In this project, we sought …
Analyzing And Extending Machine Learning Frameworks On High Risk Domains, Chengbin Hu
Analyzing And Extending Machine Learning Frameworks On High Risk Domains, Chengbin Hu
USF Tampa Graduate Theses and Dissertations
Machine learning (ML) has become a transformative force in high-risk domains such as genomics and cybersecurity, where accurate predictions and robust defenses are essential. This dissertation advances ML frameworks in these areas by developing methods to enhance predictive power in health applications and assess vulnerabilities in machine learning systems.
In the genomics field, the work addresses challenges in Non-Invasive Prenatal Testing (NIPT) of monogenic disorders by proposing a deep learning model that reconstructs the fetal genome using maternal plasma cell-free DNA (cfDNA) and parental whole-genome sequencing (WGS) data. This model achieves high accuracy in single nucleotide variation (SNV) prediction, surpassing …
Methods And Compositions For Oxygen Electrocatalysis, John N. Kuhn, Swetha Ramani, Sadik Cogal, Jeffrey Lowe, Venkat R. Bhethanabotla
Methods And Compositions For Oxygen Electrocatalysis, John N. Kuhn, Swetha Ramani, Sadik Cogal, Jeffrey Lowe, Venkat R. Bhethanabotla
USF Patents
In one aspect, the disclosure relates to catalysts for electrochemical water splitting, in particular catalysts useful for oxygen evolution at an anode in electrochemical water splitting. The disclosed catalysts compositions comprise a catalyst core component, a shell component, and optionally a catalyst outer component; wherein the catalyst core component comprises a composition having the chemical formula MxPy; where M is a transition metal; wherein x is a number from about 1 to about 20; wherein y is a number from about 1 to about 20; wherein the shell component comprises a conducting polymer; and wherein the catalyst outer component is …
Control Of Multiagent Networks With Misbehaving Nodes, Emre Yildirim
Control Of Multiagent Networks With Misbehaving Nodes, Emre Yildirim
USF Tampa Graduate Theses and Dissertations
The overarching objective of this dissertation is to introduce system theoretical frameworks in control of misbehaving multiagent networks subject to limited resources (i.e., limited number of driver nodes), and the presence of disturbances and/or uncertainties (i.e., misbehaving nodes). Below, we briefly summarize each problem studied in this dissertation with their proposed solutions.
Specifically, we first consider multiagent networks subject to misbehaving nodes over fixed undirected graph topologies. To address this problem, we apply proportional-integral control signals to a subset of nodes (i.e., driver nodes) in the network to address the undesired effects arising from misbehaving nodes. Since multiagent networks with …
Precursors To Student Burnout Through A Person-Environment Fit Lens, Kenny Le
Precursors To Student Burnout Through A Person-Environment Fit Lens, Kenny Le
USF Tampa Graduate Theses and Dissertations
Burnout has been shown to be a pressing mental health outcome across populations, and this phenomenon has received more recent attention in young adult and student populations with increasing evidence mirroring what has previously been found in workplace research. However, the current research has not yet developed a theoretical model towards student burnout specifically, and the existing multidimensional theory of burnout does not capture precursors towards the first stages of the syndrome. The current study uses the person-environment (P-E) fit as a framework to identify relevant environmental and individual factors, as research has suggested perceived environmental fit is associated with …
Examining Emergency Remote Teaching And Undergraduate Academic Outcomes During The Pandemic, Melissa S. Ramge
Examining Emergency Remote Teaching And Undergraduate Academic Outcomes During The Pandemic, Melissa S. Ramge
USF Tampa Graduate Theses and Dissertations
The COVID-19 pandemic represented an extraordinary public health emergency, leading to the most profound disruption to education systems in modern history. As higher education institutions expand their post-pandemic online course catalogs, it is necessary first to explore the student outcomes and student perceptions of learning related to the pandemic. This study used an explanatory sequential mixed methods research design to assess the relationship between the COVID-19 pandemic and students’ perceptions of online learning. The purpose of the study was to examine what, if any, trends in undergraduate student course grades and student perceptions of the instruction occurred coincident with the …
Telu Activation Function For Fast And Stable Deep Learning, Alfredo Fernandez
Telu Activation Function For Fast And Stable Deep Learning, Alfredo Fernandez
USF Tampa Graduate Theses and Dissertations
We propose the Hyperbolic Tangent Exponential Linear Unit (TeLU), a neural network hidden activation function defined as $TeLU(x)=x \cdot tanh(e^x)$. TeLU’s design is grounded in the core principles of key activation functions, achieving strong convergence by closely approximating the identity function in its active region while effectively mitigating the vanishing gradient problem in its saturating region. Its simple formulation enhances computational efficiency, leading to improvements in scalability and convergence speed. Unlike many modern activation functions, TeLU seamlessly combines the simplicity and effectiveness of ReLU with the smoothness and analytic properties essential for learning stability in deep neural networks. TeLU’s ability …
Links, Fit, And Sacrifice: How Job Embeddedness Impacts Work Modality And Intention To Stay In Public Accounting, Maryalice C. Trussell
Links, Fit, And Sacrifice: How Job Embeddedness Impacts Work Modality And Intention To Stay In Public Accounting, Maryalice C. Trussell
USF Tampa Graduate Theses and Dissertations
Historically, the public accounting profession has applied an in-person apprenticeship model to assimilate new professionals into the culture of the firm and client service profession. The COVID-19 pandemic quickly challenged this in-person apprenticeship model in early 2020 by forcing most professionals to work remotely. Initial post-pandemic research with public accountants highlighted issues related to remote work, including a lack of social bonds with coworkers, reduced organizational socialization as well as less commitment to the firm and profession. Notwithstanding the new obstacles with COVID-induced remote work, turnover and talent shortages have been persistent challenges in public accounting.
This study is the …
Exploring Llm Integration And Its Influence On Agent Behavior And Productivity In Insurance Call Centers, Gerardo L. Wibmer Gonzalez
Exploring Llm Integration And Its Influence On Agent Behavior And Productivity In Insurance Call Centers, Gerardo L. Wibmer Gonzalez
USF Tampa Graduate Theses and Dissertations
This study investigates the theoretical impacts of supportive AI tools, specifically Large Language Models (LLMs), on agent behavior and communication dynamics in call centers. While technological advancements have streamlined operations, limited research addresses the indirect ways these tools influence agent behavior. Using frameworks like context switching—the cognitive shift required when external stimuli prompt attention shifts—and the Hawthorne effect, where perceived observation modifies behavior, we examine how LLMs shape communication patterns. In call centers, this context switching occurs indirectly as agents adapt to AI note-taking features, whereas in industries like Architecture, Engineering, and Construction (AEC), automation tools prompt more immediate changes …
The Impact Of Hearing Aid User Speech On Environment Classification And Own Voice Listener Preferences, Robert Andrew Budinsky Iii
The Impact Of Hearing Aid User Speech On Environment Classification And Own Voice Listener Preferences, Robert Andrew Budinsky Iii
USF Tampa Graduate Theses and Dissertations
Hearing aids (HA) have improved over the past few decades with advanced signal processing, such as environment classification and background noise reduction, but are still limited by challenges related to when the user is speaking. These challenges include the potential interference a HA user’s voice has on device environment classification and the potential influence a HA has on own voice (OV) sound quality. However, the effects of OV on HA environment classification and signal processing are not well established, nor are the desired HA program settings regarding OV listening preferences. In this study, a combination of electroacoustic and behavioral methods …
The Monsters In Twentieth And Twenty-First Century Illustrated Adaptation Of Beowulf For Children And Young Adults, Johanna Katharine Burton
The Monsters In Twentieth And Twenty-First Century Illustrated Adaptation Of Beowulf For Children And Young Adults, Johanna Katharine Burton
USF Tampa Graduate Theses and Dissertations
I examine how some authors and illustrators of children’s and young adult literature adapt the old English Beowulf, how critics receive their works, and the functions these adaptations serve. My focus is on how the interplay between the visual and verbal text modifies or amplifies the overall story as well as how theories of translation/adaptation, monster, gender, and post-colonialism provide insight and aid in analysis. My ultimate objective is to demonstrate the significance of children’s and young adult adaptations of Beowulf and how these texts contribute to a rich and varied corpus. I argue that the adapter’s social/cultural context affected …
Sea Surface Temperatures, The Gulf Of Mexico Loop Current, Hurricane Ian, And Their Junction, Alexander K. Nickerson
Sea Surface Temperatures, The Gulf Of Mexico Loop Current, Hurricane Ian, And Their Junction, Alexander K. Nickerson
USF Tampa Graduate Theses and Dissertations
In the first chapter, a climatology was created for the deep Gulf of Mexico, West Florida Shelf, and Tampa Bay. These climatologies were compared to each other and to global temperatures. Seasonal variability is shown to be a product of bathymetry as well as latitude. In Chapter Two, using the self-organizing map neural network, patterns of the Gulf of Mexico Loop Current were analyzed to establish phases with necessary and sufficient conditions for translation from one phase to the next. Two separate patterns of evolution were established from these analyses, and empirical arguments are used to confirm the findings from …
Gnsi Decision Brief: Did We Miss The Golden Hour? Foreign Assistance And The Collapse Of Afghanistan, Alexious Butler, Guido Rossi
Gnsi Decision Brief: Did We Miss The Golden Hour? Foreign Assistance And The Collapse Of Afghanistan, Alexious Butler, Guido Rossi
GNSI Decision Briefs
James Stephenson former country director for Iraq for the U.S. Agency for International Development (USAID), explains in his book Losing the Golden Hour that there is a short window of time – usually a year or so – immediately following the cessation of hostilities in a country during which any assistance efforts will prove successful, or not, in the long term. This time frame is known as “the golden hour,” a lease from the medical field referring to the few precious minutes after a traumatic injury when proper first aid can make the difference between life or death.
An argument …
Is It Really An Affect Gap? Outcome Type Vs. Intensity In Risky Decision-Making, Jordan E. Martin
Is It Really An Affect Gap? Outcome Type Vs. Intensity In Risky Decision-Making, Jordan E. Martin
USF Tampa Graduate Theses and Dissertations
People respond to decisions differently when emotion is involved. The affect gap hypothesissuggests that people are more likely to focus on the outcome and ignore probabilities of outcomes when emotions are strong, and people are likely to include consideration of probabilities with outcomes when emotions are weak. However, typical methodologies have a confound in the manipulation of affect, with affect-poor outcomes that are quantitative in nature (e.g., money) and affect-rich outcomes that are typically qualitative (e.g., experiences). To address this confound, I created a mixed factorial design to examine choices made in lottery pairs manipulated by intensity (low, high), outcome …
Deep Reinforcement Learning For Adaptive Network Slicing In 5g For Intelligent Vehicular Systems And Smart Cities, Almuthanna Nassar, Yasin Yilmaz
Deep Reinforcement Learning For Adaptive Network Slicing In 5g For Intelligent Vehicular Systems And Smart Cities, Almuthanna Nassar, Yasin Yilmaz
USF Patents
Systems and methods for processing a service request within a network environment can include a first cluster of fog nodes that execute service tasks. The cluster can include a primary fog node and nearest neighbor fog nodes. The primary fog node can receive, from the network, a service request, determine service request resource data that includes a first time, quantity of resource blocks required to serve the request, and a hold time required to serve the request locally. An edge controller, connected to the network and the first cluster, can receive, from the primary fog node, the service request resource …
Characterizing The Temporal And Nearshore To Offshore Spatial Scale Of Phytoplankton Assemblages Within The Florida Keys National Marine Sanctuary, Sebastian P. Di Geronimo
Characterizing The Temporal And Nearshore To Offshore Spatial Scale Of Phytoplankton Assemblages Within The Florida Keys National Marine Sanctuary, Sebastian P. Di Geronimo
USF Tampa Graduate Theses and Dissertations
This study investigates the spatial and temporal dynamics of phytoplankton communities within the Florida Keys National Marine Sanctuary (FKNMS) from 2016 to 2021. Phytoplankton biomass and community composition were analyzed across four seasons and from both Nearshore (within 2 km of shore) and Offshore (8 to 10 km from shore) locations along the Florida Keys from Miami to the Western Sambo Ecological Reserve. High-performance liquid chromatography (HPLC) quantified chlorophyll-a (tchla) as a proxy for bulk biomass, and other pigments. CHEMTAX, a chemotaxonomic identification method, was employed to estimate phytoplankton community composition. Our results revealed significant seasonal variability in bulk biomass, …
Satellite-Based Mapping Of Seagrass Habitats And Coastal Wetlands In The Us Gulf Of Mexico And Florida: A Remote Sensing Approach For Environmental Conservation And Management, Luis Lizcano-Sandoval
Satellite-Based Mapping Of Seagrass Habitats And Coastal Wetlands In The Us Gulf Of Mexico And Florida: A Remote Sensing Approach For Environmental Conservation And Management, Luis Lizcano-Sandoval
USF Tampa Graduate Theses and Dissertations
Coastal wetlands and seagrass meadows provide multiple services to nature and human society, but their spatial and temporal changes are often not well characterized. They are habitats that are threatened by natural and human causes such as changes in water quality, urban development, pollution, and climate change, among others. Coastal ecosystems rely on water quality and sea level variability for survival, and changes in those variables and their potential effects are of concern to many coastal communities. Satellite remote sensing is a powerful tool that has been used for mapping ecosystem distribution on land and in the ocean. Satellite sensors …
A Case Study Of A Large School District’S High School Principals’ Instructional Decision-Making For Students With Disabilities, Laura Meehan
A Case Study Of A Large School District’S High School Principals’ Instructional Decision-Making For Students With Disabilities, Laura Meehan
USF Tampa Graduate Theses and Dissertations
This dissertation is a case study of a large school district and it’s high school principals’ approach to instructional decision making for students with disabilities. This study explores how principals utilize teaching resources and make instructional decisions for students receiving special education services on their campus. Using district-wide quantitative data on special education students in high school, this study offers a comprehensive view of how these students are served. Additionally, five in-depth interviews with high school principals currently serving in the district provide qualitative insights into leadership practices. Findings from this study reveal variation in how students with disabilities are …
Forgotten Partners: Mothers’ Perceptions Of Early Literacy Instruction For Students With Intellectual And Developmental Disabilities, Andrew Payne
USF Tampa Graduate Theses and Dissertations
Families are often the forgotten partners in education and in educational research. It is important to consider input from families regarding their children’s education. Their voices are crucial ones that should be heard more often. The research is currently lacking information about families’ perceptions about the education of their children with significant disabilities. This qualitative study explored mothers’ perspectives on the literacy education of their children and the role they play in the process. Stories of five participants and their lived experiences of supporting their children with intellectual and development disabilities in acquiring early literacy skills are shared. Themes relating …
Self-Doubt: Impostor Phenomenon And The Doctoral Seeking School-Based Leader, Rose Apollon-Simon
Self-Doubt: Impostor Phenomenon And The Doctoral Seeking School-Based Leader, Rose Apollon-Simon
USF Tampa Graduate Theses and Dissertations
This qualitative narrative inquiry explores the experiences of school-based administrators in K-12 public school settings within the state of Florida who navigate the challenges of Impostor Phenomenon while concurrently pursuing a doctoral degree. The research draws on the personal stories of four participants—three women and one man—who are currently or previously employed as principals or assistant principals. The study focused on how participants manage the psychological tensions coming from their experiences with Impostor Phenomenon or the persistent self-doubt and the fear of being exposed as a fraud. While most Impostor Phenomenon research has concentrated on fields like business, medicine, and …
On The Role Of Prediction In Streaming Hierarchical Learning, Ramy Mounir
On The Role Of Prediction In Streaming Hierarchical Learning, Ramy Mounir
USF Tampa Graduate Theses and Dissertations
In today's world, AI systems need to make sense of large amounts of data as it unfolds in real-time, whether it's a video from surveillance and monitoring cameras, streams of egocentric footage, or sequences in other domains such as text or audio. The ability to break these continuous data streams into meaningful events, discover nested structures, and predict what might happen next at different levels of abstraction is crucial for applications ranging from passive surveillance systems to sensory-motor autonomous learning. However, most existing models rely heavily on large, annotated datasets with fixed data distributions and offline epoch-based training, which makes …