Digital Commons Network^™

Soc-Based Control System Performance Analysis For Trapped-Ion Quantum Computing, Tiamike Dudley

Electrical and Computer Engineering ETDs

Scatter-gather dynamic-memory-access (SG-DMA) is utilized in applications that require high bandwidth and low latency data transfers between memory and peripherals, where data blocks, described using buffer descriptors (BDs), are distributed throughout the memory system. The data transfer organization and requirements of a Trapped-Ion Quantum Computer (TIQC) possess characteristics similar to those targeted by SG-DMA. In particular, the ion qubits in a TIQC are manipulated by applying control sequences consisting primarily of modulated laser pulses. These optical pulses are defined by parameters that are (re)configured by the electrical control system. Variations in the operating environment and equipment make it necessary to …

Improving The Performance Of The Modal Holographic Wavefront Sensor By Adapting To Prevailing Turbulence Conditions: Experimental Verification, Andreas Zepp, Emma Branigan, Kevin Murphy, Szymon Gladysz

Conference Papers

The modal holographic wavefront sensor offers a promising alternative to established wavefront sensing techniques. Since the strengths of individual aberration modes are directly measured, there is no need for time-consuming signal processing and wavefront reconstruction. Bandwidths up to three orders of magnitude higher than those of commercial wavefront sensors can in principle be achieved. However, in practice the accuracy of measurements is compromised by intermodal crosstalk, which arises when the wavefront exhibits additional aberrations to those encoded in the modal wavefront sensor. This issue is particularly prominent when measuring wavefronts disturbed by atmospheric turbulence. To mitigate the effects of intermodal …

Integrating Humanities Into Cybersecurity Education: Enhancing Ethical, Historical, And Sociopolitical Understanding In Technical Training, Joseph Frusci

Journal of Cybersecurity Education, Research and Practice

The increasing complexity of cybersecurity challenges necessitates a holistic educational approach that integrates both technical skills and humanistic perspectives. This article examines the importance of infusing humanities disciplines such as history, ethics, political science, sociology, law, and anthropology—into cybersecurity education. Through a pilot course developed for Staten Island Technical High School, aligned with the New York State K-12 Computer Science and Digital Fluency Standards, students were introduced to an interdisciplinary curriculum that combined technical cybersecurity training with historical analysis, ethical reasoning, and sociopolitical context. The results of pre- and post-course assessments demonstrated significant improvements in critical thinking, ethical decision-making, and …

Beyond Human-Centric Models In Cybersecurity Education: A Pilot Posthuman Analysis Of The Nice Workforce Framework For Cybersecurity, Ryan Straight

Journal of Cybersecurity Education, Research and Practice

This study applies a posthuman lens to the National Initiative for Cybersecurity Education (NICE) Workforce Framework, examining two key Work Roles in cybersecurity education. Employing a novel posthuman coding scheme, the associated Tasks, Knowledge, and Skills (TKS) statements were analyzed. Findings reveal significant posthuman elements within the framework while identifying opportunities for further integration. The analysis demonstrates a strong presence of human-technology entanglement and adaptive learning concepts, yet highlights areas where the framework could emphasize system complexity and interconnectedness. This research contributes to ongoing discussions on cybersecurity education in complex technological landscapes, proposing a theoretical framework for integrating posthuman concepts …

From Classroom To Cloud: Why Cybersecurity Education Is Crucial For Tomorrow's Learners, Kiori Edwards

Cybersecurity Undergraduate Research Showcase

This paper examines the transformative impact of cloud computing on education, highlighting how cloud technologies are reshaping teaching and learning environments, making education more accessible, flexible, and collaborative. It also explores the critical importance of incorporating cybersecurity education into school curricula. As digital devices and cloud-based platforms become integral to students' daily lives, they are increasingly vulnerable to cyber threats. This paper argues that early cybersecurity education, starting at the elementary level, is essential for equipping future generations with the knowledge and skills needed to navigate the digital world safely, protect their personal information, and avoid cybercrime.

Between Copyright And Computer Science: The Law And Ethics Of Generative Ai, Devin R. Desai, Mark Riedl

Northwestern Journal of Technology and Intellectual Property

Copyright and computer science continue to intersect and clash, but they can coexist. The advent of new technologies such as digitization of visual and aural creations, sharing technologies, search engines, social media offerings, and more, challenge copyright-based industries and reopen questions about the reach of copyright law. Breakthroughs in artificial intelligence research, especially Large Language Models that leverage copyrighted material as part of training, are the latest examples of the ongoing tension between copyright and computer science. The exuberance, rush-to-market, and edge problem cases created by a few misguided companies now raises challenges to core legal doctrines and may shift …

Preparing Children For Kindergarten Readiness: Early Childhood Teachers’ Goals And Practices, Julie Chappell

USF Tampa Graduate Theses and Dissertations

Literature in the field of early childhood education suggests that standardization and the accountability movement in the United States has changed the way that teachers approach kindergarten, resulting in less play and more teacher-directed activities. This pedagogical shift causes challenges for early childhood educators striving to promote developmentally appropriate, play-based and child-centered approaches to learning for young children while preparing children for the expectations of kindergarten. The purpose of this qualitative study was to gain an understanding of prekindergarten teachers’ views about their role in preparing children for kindergarten. The study was guided by two research questions: How do prekindergarten …

Disparities In The Prevalence Of Hospitalizations And In-Hospital Mortality Due To Acute Myocardial Infarction Among Patients With Non-Alcoholic Fatty Liver Disease: A Nationwide Retrospective Study, Umar Hayat, Faisal Kamal, Muhammad Kamal, Wasique Mirza, Tariq Ahmad, Manesh Gangwani, Dushyant Dahiya, Hassam Ali, Shiva Naidoo, Sara Humayun, Hayrettin Okut, Muhammad Aziz

Division of Gastroenterology and Hepatology Faculty Papers

Background: Non-alcoholic liver disease (NAFLD) may be associated with cardiovascular diseases; however, only a few studies have analyzed this relationship. We aimed to assess the epidemiologic data and the association between NAFLD and acute myocardial infarction (AMI) in the United States. Methods: The National Inpatient Sample (NIS) database 2016-2019 was queried using ICD10-CM diagnostic codes to identify hospitalizations of AMI + NAFLD. Essential demographic variables were analyzed to determine the disparities in the prevalence of AMI hospitalizations and deaths among NAFLD patients. Univariate and multivariate logistic regression models determined the association between NAFLD and AMI hospitalizations and death. …

Disentangling Genotype And Environment Specific Latent Features For Improved Trait Prediction Using A Compositional Autoencoder, Anirudha Powadi, Talukder Zaki Jubery, Michael C. Tross, James C. Schnable, Baskar Ganapathysubramanian

Department of Agronomy and Horticulture: Faculty Publications

In plant breeding and genetics, predictive models traditionally rely on compact representations of high-dimensional data, often using methods like Principal Component Analysis (PCA) and, more recently, Autoencoders (AE). However, these methods do not separate genotype-specific and environment-specific features, limiting their ability to accurately predict traits influenced by both genetic and environmental factors. We hypothesize that disentangling these representations into genotype-specific and environment-specific components can enhance predictive models. To test this, we developed a compositional autoencoder (CAE) that decomposes high-dimensional data into distinct genotype-specific and environment-specific latent features. Our CAE framework employed a hierarchical architecture within an autoencoder to effectively separate …

A New Proof Of An Inequality Of Bourgain, Polona Durcik, Joris Roos

Mathematics, Physics, and Computer Science Faculty Articles and Research

The purpose of this short note is to demonstrate how some techniques from additive combinatorics recently developed by Peluse and Peluse-Prendiville can be applied to give an alternative proof for a trilinear smoothing inequality originally due to Bourgain.

Time Domain Spectral Lidar Enabled By Cascaded Raman In A Hydrogen-Filled Transmitter, Richard K. Martin, Trevor L. Courtney, Arielle M. Adams, Daniel E. Leaird, Luke Ausley, Christian K. Keyser

Faculty Publications

We introduce what we believe to be novel spectral light detection and ranging (LiDAR) architectures that enable ultra-compact systems by a transition from spectral signal processing in space (gratings) to processing in time. The architectures leverage temporal dispersion and the unique spectro-temporal waveforms produced from the cascaded Raman scattering generated in the (H₂) filled hollow core fiber. The characterized Raman source yields as many as six Raman orders from 1.06-1.70 μm; their unique spectro-temporal waveforms are measured. System performance simulations based on measured Raman waveforms show that high accuracy measurement of range and reflectivity are possible with proper …

Limitations Of Beam-Control Compensation, Matthew Kalensky, Darren Getts, Matthias T. Banet, Derek J. Burrell, Milo W. Hyde, Mark F. Spencer

Faculty Publications

In this paper, we use wave-optics simulations to explore the limitations of beam-control compensation. We evaluate performance in terms of the normalized power in a diffraction-limited bucket for the cases of no beam-control compensation, perfect phase compensation, and perfect full-field compensation. From these results, we are able to arrive at the following conclusions: (1) without any form of beam-control compensation, performance begins to degrade when D/r₀ > 1; (2) with perfect phase compensation, performance begins to degrade when D/r₀ > 1 and (λ/r₀)/θ₀ > 1; and (3) with perfect full-field compensation, performance begins to degrade when D/r_{0 …}

11.18.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Director of Research Lab Safety

GIS Day

Tech Startup Weekend

NSF Virtual Grants Conference

Six-Year College Graduation Status For High School Students Participating In An Upward Bound Program, Raymond Upward Cabrera

USF Tampa Graduate Theses and Dissertations

This study examines the impact of high school academic indicators and participation in the federally funded Upward Bound program on college graduation rates for first-generation, low-income students. Specifically the extent to which participation in the federally funded TRIO Upward Bound program and related factors—high school GPA, course rigor, program involvement, gender, race, and college type—predict 6-year college graduation rates for first-generation, low-income students. Using stepwise logistic regression analysis on data of 163 students in an Upward Bound program in the Southeast, the results show that students with higher GPAs, active engagement in the program, and females were significantly more likely …

Performance And Trihalomethane Formation Potential Of Alternative Electron Donors For Wastewater Denitrification, Bruno Fulco Mancini

USF Tampa Graduate Theses and Dissertations

Nitrogen removal from wastewater is critical to preserve ecosystems, as well as human health and welfare. Excess nutrients in receiving waters can cause many problems to the environment, such as algal blooms, drinking water contamination, and economic losses. Nitrogen removal in wastewater occurs mainly through the oxidation and reduction processes of nitrification and denitrification, which occur in engineered systems at wastewater treatment plants or water reclamation facilities.

The site for this research was the South Cross Bayou (SCB) Water Reclamation Facility, located in Pinellas County, FL, USA. At SCB, nitrogen is removed through a Modified Ludzak-Ettinger (MLE) process with the …

Seasonal And Interannual Abundance, Distribution, And Carbon Production Estimates In The Northeastern Gulf Of Mexico Using The Sipper Camera Imaging System, Carlyn Scott

USF Tampa Graduate Theses and Dissertations

Larvaceans are filter-feeding gelatinous zooplankton whose contributions to marine biogeochemical processes are poorly constrained. By frequently shedding their particle-rich houses and producing dense fecal pellets, larvaceans contribute large amounts of particulate organic matter to deeper waters and to the sea floor. Despite their importance, little is known about larvacean abundance, distribution, and carbon production in the highly productive northeastern Gulf of Mexico (NEGOM). To address this gap in knowledge, we collected images of larvaceans at discrete depths in the upper 300 m of the water column between August 2010 –2014 using the Shadowed Image Particle Profiling and Evaluation Recorder (SIPPER) …

Uab Mathematics Sophomore Is On The Fast Track To Success, Staff

Browse All News

No abstract provided.

Changing Characteristics Of Land Cover, Landscape Pattern And Ecosystem Services In The Bohai Rim Region Of China, Jiaqi Liu, Wei Chen, Hu Ding, Zhanhang Liu, Min Xu, Ramesh P. Singh, Congqiang Liu

Mathematics, Physics, and Computer Science Faculty Articles and Research

Since the Anthropocene, ecosystems have been continuously deteriorating due to global climate change and human intervention. Exploring the changing characteristics of land use/land cover (LULC), landscape pattern and ecosystem service (ES) and their drivers is crucial for regional ecosystem management and sustainable development. Taking the Bohai Rim region of China as an example, we used the land use transfer matrix, landscape pattern index and InVEST model to analyze the changing characteristics of LULC, landscape pattern and six key ESs [crop production (CP), water yield (WY), carbon storage (CS), soil conservation (SC), habitat quality (HQ), landscape aesthetics (LA)] during 2000–2020. Detailed …

The Rider (2024-11-18), Natalie Lapsley

The Rider Archives

Vol.10 No.13

The Sonata For B-Flat Trumpet And Piano By Burnet Corwin Tuthill: A Guide To Performance Practice, Joseph Moore

Electronic Theses and Dissertations Archive

Moore Joseph M., The Sonata for B-flat Trumpet and Piano by Burnet Corwin Tuthill: A Guide to Performance Practice. Doctor of Musical Arts (Performance). The focus of this dissertation is the Sonata for B-flat Trumpet and Piano, op. 29 by Burnet Corwin Tuthill (1888-1982). This work explores the life of Burnet Tuthill, with principal focus on the aforementioned work. Burnet Tuthill was an influential composer in the United States during the early part of the twentieth century, composing in a variety of mediums and expanding the brass repertoire through his work with the National Association of Schools of Music. This …

Statistical Methods For Interpreting Spatial And Temporal Heterogeneity Of Martian Tropical Water Ice Informed By Properties Of Crater Ejecta Types, Jamie D. Riggs, Michelle R. Kirchoff

College of Population Health Faculty Papers

The martian tropical water ice spatial and temporal distribution was characterized using impact crater ejecta type, location, size, and age in one of two epochs, (Formula presented.) Ga and (Formula presented.) Ga, using statistical models designed for spatial and temporal correlation structures. The indicator thought to identify the presence of ice is craters with layered ejecta, while the indicator thought to identify no ice is craters with radial ejecta. These indicators imply the location (longitude and latitude) and, potentially, depth (crater diameter as a proxy) of ice, and when the ice was present. The spatial and temporal distribution of layered …

Dualrep: Knowledge Graph Completion By Utilizing Dual Representation Of Relational Paths And Tail Node Density Insights, Haji Gul, Feras Al-Obeidat, Adnan Amin, Muhammad Wasim, Fernando Moreira

All Works

Knowledge graphs (KGs) possess a vital role in enhancing the semantic comprehension of extensive datasets across many fields. It facilitate activities like recommendation systems, semantic searching, and intelligent data mining. However, lacking information can sometimes limit the usefulness of knowledge graphs (KGs), as the lack of relationships between entities could severely limit their practical application. Most existing approaches for KG completion primarily concentrate on embedding-based methods or just use relational paths, neglecting the valuable structural information offered by node density. This research presents an approach that effectively combines relational paths and the density features of tail nodes to enhance the …

Implementing Bernstein Operational Matrices To Solve A Fractional‐Order Smoking Epidemic Model, Jalal Al Hallak, Mohammed Alshbool, Ishak Hashim

All Works

This paper leverages the Bernstein operational matrices method for the first time in order to resolve the nonlinear fractional smoking epidemic model presented in terms of Caputo’s fractional derivative. An approximate solution is derived using Bernstein’s operational matrices and strategically chosen collocation points. This is followed by the validation of the proposed method’s accuracy and reliability against the established Runge–Kutta fourth‐order method. Furthermore, a comprehensive comparative analysis is conducted against two prominent techniques: the fractional differential transform method (FDTM) and the q‐homotopy analysis transform method (q‐HATM). The results show a superior and significant performance regarding accuracy as well as approximation. …

Principles Of Glacial Geomorphology And Geology By I. Peter Martini, Michael E. Brookfield, And Steven Sadura., C. Nicholas Raphael

The Geographical Bulletin

"Principles of Glacial Geomorphology and Geology" is different from most glacier-related textbooks. The principal difference between this text and most others is the wider range of topics covered. As in most glacial texts, the book covers glaciology and glacial sediments and landforms. Close to half of this text, however, covers permafrost and periglacial processes, dating techniques, isostasy/eustasy, migration of biota dur - ing glacial cycles, and an extensive global history of glaciation. As a result, the most positive aspect of the book is that one can design a class, using one book, that covers almost any glacier-related topic. The negative …

Phishing Emails: An Evolving Cyberattack, Brooke Waltz

Cybersecurity Undergraduate Research Showcase

This paper describes the history of phishing attacks and how they turned into cyberattacks, focusing on companies. Over the course of 34 years, phishing has been evolving at an alarming rate, especially with AI now coming into play. As phishing attacks have become more prominent towards companies, there has been an increase in financial loss and data breaches, resulting in a loss of trust in companies. With this loss, companies are trying to find solutions to this problem. Some notable attacks were the RSA breach in 2011, the Texas Energy Company in 2014, and the ILOVEYOU virus in 2000. They …

A Contexted Learning Experience: Instructional Strategies For Effective Teaching For Primary And Intermediate Students From Diverse Ses Environments, R. Suzanne Legg

USF Tampa Graduate Theses and Dissertations

The aim of my three-article dissertation was to investigate the methods employed by effective teachers to promote academic progress among all students, regardless of their socioeconomic status. Each article addressed perspectives on effective teaching strategies aimed at closing the opportunity gap from three different contexts. These contexts were 1) a focus group consisting of primary teachers, 2) a focus group consisting of intermediate teachers, and 3) personal reflections from observations of both focus groups pertaining to COVID-19. Recent scores from the Programme for International Student Assessment (OECD, 2023) revealed a growing disparity in academic achievement between students from higher socioeconomic …

Safe Reinforcement Learning For Intersection Management In Riti Communities Under Rare Extreme Events, Yuanzhang Xiao

CSET Project Reports

The rapid advancement of artificial intelligence (AI) is reshaping the transportation sector, with applications spanning autonomous vehicles, driver injury prevention, and traffic management. Efficient traffic management, particularly through adaptive intersection control, holds significant potential for reducing congestion. This study explores the application of reinforcement learning (RL) to adaptive traffic signal control in rural, isolated, tribal, and indigenous (RITI) communities, which face unique challenges such as rare extreme weather events. Standard RL approaches struggle in these contexts due to limited exposure to these rare events. In our study, we first evaluate several mainstream RL algorithms and identified two most promising approaches. …

Adaptive Mesh Refinement For Variational Inequalities, Stefano Fochesatto

Mathematics and Statistics

Variational inequalities play a pivotal role in a wide array of scientific and engineering applications. This project presents two techniques for adaptive mesh refinement (AMR) in the context of variational inequalities, with a specific focus on the classical obstacle problem. We propose two distinct AMR strategies: Variable Coefficient Elliptic Smoothing (VCES) and Unstructured Dilation Operator (UDO). VCES uses a nodal active set indicator function as the initial iterate to a time-dependent heat equation problem. Solving a single step of this problem has the effect of smoothing the indicator about the free boundary. We threshold this smoothed indicator function to identify …

Emerging Consensus On Net Energy Paves The Way For Improved Integrated Assessment Modeling, Louis Delannoy, Matthieu Auzanneau, Baptiste Andrieu, Olivier Vidal, Pierre -Yves Longaretti, Emmanuel Prados, David J. Murphy, Roger W. Bentley, Michael Carbajales- Dale, Marco Raugei, Mikael Ho¨O¨K, Victor Court, Carey W. King, Florian Fizaine, Pierre Jacques, Matthew Kuperus Heun, Andrew Jackson, Charles Guay- Boutet, Emmanuel Aramendia, Jianliang Wang, Hugo Le Boulzec, Charles A.S. Hal

University Faculty Publications and Creative Works

Extracting, processing, and delivering energy requires energy itself, which reduces the net energy available to society and yields considerable socioeconomic implications. Yet, most mitigation pathways and transition models overlook net energy feedbacks, specifically related to the decline in the quality of fossil fuel deposits, as well as energy requirements of the energy transition. Here, we summarize our position across 8 key points that converge to form a prevailing understanding regarding EROI (Energy Return on Investment), identify areas of investigation for the Net Energy Analysis community, discuss the consequences of net energy in the context of the energy transition, and underline …

Stochastic Predictive Modeling Of Social Media Stocks And Reliability Of Hard Disk Drives, Sameer Anand

USF Tampa Graduate Theses and Dissertations

In recent years, social media has emerged as a highly appealing investment sector due to its substantial returns. Our research focuses on creating a predictive model for the financial performance of social media companies. We gathered data from five companies in the S&P 500: Meta, Etsy, Match, Pinterest, and Alphabet. We developed a non-linear, data-driven stochastic analytical model that employs real data, incorporating six financial indicators and four economic indicators, to forecast the weekly closing prices of these social media companies with an accuracy of 94.7%. Additionally, we ranked the statistically significant indicators and their interactions based on their percentage …