Physical Sciences and Mathematics Commons^™

The Role Of Self-Tutorial In Introductory Physics Student Performance On Test Of Understanding Of Vectors, Katherine Finegan

Master's Theses (2009 -)

A single-interaction self-guided lesson was designed to teach basic vector concepts to introductory physics students. The self-guided lesson was tested for efficacy by comparing pre-test and post-test subscores on a Test of Understanding of Vectors (TUV) and comparing subscore differences to students in the same physics courses who had not taken the self-guided lesson. Analysis showed no significant differences in subscore differences between students taking the self-guided lesson and those in comparable control groups, indicating that more robust interventions are needed and/or further work must be done on the self-guided lesson to improve student vector understanding.

Foldy-Wouthuysen Transformation In Strong Magnetic Fields And Relativistic Corrections For Quantum Cyclotron Energy Levels, Albert Wienczek, Christopher Moore, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We carry out a direct iterative Foldy-Wouthuysen transformation of a general Dirac Hamiltonian coupled to an electromagnetic field, including the anomalous magnetic moment. The transformation is carried out through an iterative disentangling of the particle and antiparticle Hamiltonians in the expansion for higher orders of the momenta. The time-derivative term from the unitary transformation is found to be crucial in supplementing the transverse component of the electric field in higher orders. Final expressions are obtained for general combined electric and magnetic fields, including strong magnetic fields. The time derivative of the electric field is shown to enter only in the …

Aligning The Transit Industry And Their Vendors In The Face Of Increasing Cyber Risk: Recommendations For Identifying And Addressing Cybersecurity Challenges, Scott Belcher, Terri Belcher, Kathryn Seckman, Brandon Thomas, Homayun Yaqub

Mineta Transportation Institute

Public transit agencies in the United States depend on external vendors to help deliver and maintain many essential services and to provide critical technologies, from ticket purchases to scheduling to email management. While the integration of new, advanced technologies into the public transit industry brings important advancements to U.S. critical transportation infrastructure, the application of digital technologies also brings with it a new assortment of digital risks. Transit agencies of all sizes are finding themselves subject to cyber incidents—most notably ransomware attacks—like those experienced by larger, more prominent companies and critical infrastructure providers. The findings in this report focus on …

Evaluation Of Silver Nanoparticles Attached To Methylene Blue As An Antimicrobial Agent And Its Cytotoxicity, Somon Hakimov

Masters Theses & Specialist Projects

Antibiotics resistance is considered as one of the greatest public health challenges of our time. In this work, we have synthesized silver nanoparticles (Ag NPs) using pulsed liquid ablation in different medium of growth and later combined with methylene blue (MB) to evaluate its potential as an effective photodynamic therapy agent. Ag NPs were synthesized by pulsed laser ablation technique in Polyvinylpyrrolidone (PVP), citrate, and Polyvinyl alcohol (PVA). The Ag NPs were characterized using transmission electron microscopy (TEM), UV-Visible (UV-Vis), and photoluminescence (PL) spectra. Next, Ag NPs were coupled with MB and used to deactivate the Gram-negative bacteria, Escherichia coli …

The Development Of A Monolithic Spatial Heterodyne Spectrometer For Extreme Environments, Arelis Michelle Colόn

Theses and Dissertations

This work describes improvements to a novel instrument, the monolithic spatial heterodyne Raman spectrometer (mSHRS), which has potential to be utilized in space exploration and deep-ocean marine sensing. In previous work, the spatial heterodyne Raman spectrometer (SHRS) was demonstrated, as a small, high resolution, wide field of view spectrometer, originally developed for space applications where small size and compactness is a key consideration or where a wide field of view is advantageous, such as in remote spectroscopy. The spatial heterodyne spectrometer (SHS) was then later utilized for remote Laser-Induced Breakdown Spectroscopy (LIBS). The high throughput, high spectral resolution, and large …

Learning Depth From Images, Zhenyao Wu

Theses and Dissertations

Estimating depth from images has become a very popular task in computer vision which aims to restore the 3D scene from 2D images and identify important geometric knowledge of the scene. Its performance has been significantly improved by convolutional neural networks in recent years, which surpass the traditional methods by a large margin. However, the natural scenes are usually complicated, and hard to build the correspondence between pixels across frames, such as the region containing moving objects, illumination changes, occlusions, and reflections. This research explores rich and comprehensive spatial correspondence across images and designs three new network architectures for depth …

Novel Synthetic Strategies Toward Polyolefin-Grafted Nanoparticles, Richard Tran Ly

Theses and Dissertations

Surface functionalization of nanoparticles has proven to be a powerful and versatile strategy in the development of various materials with advanced properties. Polymer brush composition can range from complex copolymers to more simplistic polyolefin, and by functionalizing nanoparticle surfaces, mobility of distinct particles can then be tuned and, therefore, control over dispersion in a polymer matrix can be achieved. Presented in this dissertation are new synthetic strategies for the preparation of polymer nanocomposites.

The first chapter covers a novel synthetic strategy for ethylene/propylene-like copolymers grafted to silica nanoparticles. This approach utilizes Reversible Addition-Fragmentation Chain Transfer (RAFT) polymerization to promote living …

Structure Preserving Reduced-Order Models Of Hamiltonian Systems, Megan Alice Mckay

Theses and Dissertations

Large-scale dynamical systems are expensive to simulate due to the computational cost accrued y the substantial number of degrees of freedom. To accelerate repeated numerical simulations of the systems, proper orthogonal decomposition reduced order models (POD-ROMs) have been developed. When applied to Hamiltonian systems, however, special care must be taken when performing the reduced order modeling to keep their energy-preserving nature. This work presents a survey of several structure-preserving reduced order models (SP-ROMs). In addition, this work employs the discrete empirical interpolation method (DEIM) and develops an SP-DEIM model for nonlinear Hamiltonian systems. The wave equation is considered as a …

Statistical Methods For Analyzing Multi-Omics Data: Dependence Structure And Missing Values, Wenda Zhang

Theses and Dissertations

The advancements in high-throughput technologies have made it possible to generate a huge number of "omics'' data, including genomics, proteomics, transcriptomics, epigenomics, metabolomics, and microbiomics. Combining multiple data sources and performing joint analyses with all available information and the phenotypic outcome can reflect various aspects in complex biological systems, such as revealing regulation processes, discovering novel associations between biological entities, and identifying relevant biomarkers for certain diseases or phenotypic outcomes. This dissertation focuses on developing statistical models for analyzing multi-omics data. It is comprised of three topics: (1) integrative analysis for multi-omics data with missing observations in intermediate variables; (2) …

Materials Discovery By Flux Crystal Growth: Synthesis, Structure Determination, Magnetic, And Optical Properties Of Complex Oxides, Oxychlorides, And Oxyfluorides, Darren Andrew Carone

Theses and Dissertations

Exploratory crystal growth has proven to be a successful technique in the synthesis of new compounds with desired properties. This method is very versatile and has various iterations, but results described herein were obtained through flux growth at high temperatures utilizing mixed alkali halide salts. The tunability of these reactions with respect to reactant ratios, reaction temperature, heating/cooling rates, metal precursors, and choice of flux allow for the exploration of phase spaces between a combination of elements and observation of significantly different products and/or structure types from minor tweaks.

Most of the research presented in this dissertation describes results that …

Taking Action: Managing Inclusive Excellence In Academia, Lesley Ann Giddings, Christine Salomon

Chemistry: Faculty Publications

No abstract provided.

Penguin: A Tool For Predicting Pseudouridine Sites In Direct Rna Nanopore Sequencing Data, Doaa Hassan, Daniel Acevedo, Swapna Vidhur Daulatabad, Quoseena Mir, Sarath Chandra Janga

Computer Science Faculty Publications and Presentations

Pseudouridine is one of the most abundant RNA modifications, occurring when uridines are catalyzed by Pseudouridine synthase proteins. It plays an important role in many biological processes and also has an importance in drug development. Recently, the single-molecule sequencing techniques such as the direct RNA sequencing platform offered by Oxford Nanopore technologies enable direct detection of RNA modifications on the molecule that is being sequenced, but to our knowledge this technology has not been used to identify RNA Pseudouridine sites. To this end, in this paper, we address this limitation by introducing a tool called Penguin that integrates several developed …

Challenging Predictions Of Inflationary Models With Cmb Data, Richik Bhattacharya, Atanu Debnath, Esha Sajjanhar, Shravani Sardeshpande, Pablo Tenorio Hernández, José Ricardo Torres Heredia

2022 REYES Proceedings

Cosmic inflation offers the best known explanations for many of the observed features of the Universe, such as its flatness. An imprint of the qualities of this mechanism is left in the cosmic microwave background (CMB), which can be instrumental to confirm inflation. Unfortunately, there is a plethora of inflationary models, which are a priori in the same footing. It is conceivable that contrasting the predictions of the various models with the measured values of the parameters of CMB data and other cosmological observables shall allow one to single out the successful theory of inflation. In this work we provide …

Contrasting Sea-Ice Algae Blooms In A Changing Arctic Documented By Autonomous Drifting Buoys, Victoria Hill, Bonnie Light, Michael Steele, Andrew Lowy Sybrandy

OES Faculty Publications

Novel observations of the seasonal evolution of an ice algal bloom on the Chukchi shelf were collected by two autonomous buoys deployed 180 km apart in first-year drifting sea ice. High attenuation of blue light in the bottom of the ice indicated considerable accumulation of ice algae biomass with derived Chlorophyll-a concentrations (Chl a) up to 184 mg m⁻². Differences in the magnitude and persistence of ice algae biomass under each buoy appear to have been driven by differences in snow thickness, as ice thickness was similar between the sites. Minimal snow cover (0.02 m) around …

Large Area Projection Sintering Of Semicrystalline Polymers And Part Analysis Of The Printed Specimens, Taranjot Kaur

USF Tampa Graduate Theses and Dissertations

As the requirements posed to products have increased in recent years. The trend towards individualized serial products steps up the need for respective manufacturing techniques to be more and more flexible. Conventional techniques of serial production, such as injection molding, are unable to fully meet the requirements of this trend. Additive manufacturing techniques generate components directly from a CAD data set while requiring no specific mold, producing minimal waste, and reaching satisfactory geometric accuracy. This is how, as opposed to conventional techniques, they comply with these increased demands to processing technology. Over the last two decades, the research community has …

Ocean Eddies And Frontal Zones In The Gulf Of Mexico And Straits Of Florida, Yingjun Zhang

USF Tampa Graduate Theses and Dissertations

Ocean eddies and fronts in the Gulf of Mexico (GoM) and the Straits of Florida (SoF) play important roles in ocean physics, biology, and ecology. These two ubiquitous physical features have been studied worldwide for decades, yet many questions remain unanswered or poorly studied for the GoM and SoF. This study aims to improve the understanding of ocean eddies and frontal zones in the GoM and SoF using satellite remote sensing, in situ observations and model outputs, as well as state-of-the-art algorithms, with the following objectives: 1) analyze the three-dimensional (3-D) statistical characteristics and thermohaline structure of mesoscale eddies in …

Elucidating The Sources Supplying Aerosol Iron, Zinc, And Cadmium To The Surface Of The North Pacific Ocean With Stable Isotopes, Zach B. Bunnell

USF Tampa Graduate Theses and Dissertations

Transition metals, such as iron (Fe), zinc (Zn) and cadmium (Cd), are found at just trace amounts within the global oceans yet are vital for many biological functions of phytoplankton. As a result, these metals influence the ocean’s efficacy for carbon sequestration. Atmospheric dust is the primary input of Fe to various surface waters and may also supply Zn and Cd to oligotrophic surface waters. Here, I present Fe, Zn, and Cd isotope data from the US North Pacific GEOTRACES Section GP15 (Alaska-Tahiti) from the low-dust season (Sept. – Nov. 2018). Using this data and aerosol enrichment factors, I show …

Multi-Level Cross-View Contrastive Learning For Knowledge-Aware Recommender System, Ding Zou, Wei Wei, Xian-Ling Mao, Ziyang Wang, Minghui Qiu, Feida Zhu, Xin Cao

Research Collection School Of Computing and Information Systems

Knowledge graph (KG) plays an increasingly important role in recommender systems. Recently, graph neural networks (GNNs) based model has gradually become the theme of knowledge-aware recommendation (KGR). However, there is a natural deficiency for GNN-based KGR models, that is, the sparse supervised signal problem, which may make their actual performance drop to some extent. Inspired by the recent success of contrastive learning in mining supervised signals from data itself, in this paper, we focus on exploring the contrastive learning in KG-aware recommendation and propose a novel multi-level cross-view contrastive learning mechanism, named MCCLK. Different from traditional contrastive learning methods which …

Comparative Study Of A Bidirectional Multi-Phase Multiinput Converter For Electric Vehicles, Furkan Akar, Murat Kale, Sebahatti̇n Yalçin, Gözde Taş

Turkish Journal of Electrical Engineering and Computer Sciences

Multiinput converters allow to create hybrid energy systems in electric vehicles with a reduced part count. In addition, interleaved structures help to build efficient converters with several possible benefits, such as low current ripple and high power density. This paper proposes utilizing a multiphase multiinput converter (MPMIC), which concentrates the aforementioned advantages and presents a comprehensive comparison with its single-phase version, called single phase multiinput converter (SPMIC). After analysing their steady-state characteristics, SPMIC and MPMIC are designed considering same conditions. Then, two laboratory prototypes rated at 2.5kW output power are implemented to validate the analysis. Finally, these prototypes are compared …

Breast Cancer-Caps: A Breast Cancer Screening System Based On Capsule Network Utilizing The Multiview Breast Thermal Infrared Images, Devanshu Tiwari, Manish Dixit, Kamlesh Gupta

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposed an accurate and fully automated breast cancer early screening system called the "Breast Cancer-Caps". The capsule network is used in this approach for the cancer detection in breast utilizing the thermal infrared images for the first time. This capsule network is trained with the help of Dynamic as well as Static breast thermal images dataset consisting of left, right, frontal views along with a new multiview thermal images. These multiview breast thermal images are fabricated by concatenating the conventional left, frontal and right view breast thermal images. The other current and popular deep transfer learning models such …

Interactions Between Tropical Cyclones And The Midlatitude Waveguide: Downstream Impacts And The Role Of Convective Processes, Kevin Prince

Theses and Dissertations

Significant amplification to the waveguide can occur when a recurving tropical cyclone (TC) interacts with the midlatitude flow, leading to significant downstream impacts. To this point in time, TC-midlatitude waveguide interactions have been conceptualized as primarily being driven by large-scale processes, with convective-scale contributions having been parameterized or neglected. This three-part study diagnoses the impact TC-midlatitude waveguide interactions have on the intensity evolution of downstream TCs and the role convective-scale processes play in TC-midlatitude waveguide interactions. Recurving TCs in both the North Atlantic and western North Pacific basins frequently interact favorably with upstream troughs, where a favorable interaction entails the …

Encoding Color Sequences In Active Tile Self-Assembly, Sonya Cirlos

Theses and Dissertations

Constructing patterns is a well-studied problem in both theoretical and experimental self-assembly with much of the work focused on multi-staged assembly. In this paper, we study building 1D patterns in a model of active self assembly: Tile Automata. This is a generalization of the 2-handed assembly model that borrows the concept of state changes from Cellular Automata. In this work we further develop the model by partitioning states as colors and show lower and upper bounds for building patterned assemblies based on an input pattern. Our first two sections utilize recent results to build binary strings along …

Analyzing The Impact Of Governance Strategies On Trust And Risk In The Salish Sea Transboundary Fishery Context, Evelyn Roozee

Theses and Dissertations

The Salish Sea is the site of a transboundary fishery whose coastal jurisdiction includes British Columbia, Washington State, the two federal governments, and many Indigenous tribes with sovereign rights. Fishery management becomes increasingly complex when transboundary cooperation is needed. Furthermore, while the Salish Sea region has attempted to facilitate better transboundary collaborative governance, these have generally failed to institutionalize the principles of adaptive management. This research seeks to assess current trust and risk perceptions and analyze the effects of control mechanisms used in the transboundary fishery management network. The data consists of a survey measuring collaborative precursors, barriers, and outcomes …

Advancing Human-Agent Teamwork, Vijayanth Tummala

Theses and Dissertations

Progress in the use of Artificial Intelligence (AI) has been made in many different fields. We are now reaching a point in AI development typical AI implementations are not enough: where we would need humans and AI systems to actively collaborate with each other, basing their actions on the actions and capabilities of each other. This collaboration could be in the form of agents assisting humans processing and analyzing information, assisting humans with smaller physical tasks or working with humans as an equal team member – having the same goals and performing the same tasks – to accomplish a goal. …

A Smartphone-Based Non-Invasive Measurement System For Blood Constituents From Photoplethysmography (Ppg) And Fingertip Videos Illuminated With The Near-Infrared Leds, Md Hasanul Aziz

Dissertations (1934 -)

At least two billion people are affected by hemoglobin (Hgb), diabetic-related, and other blood-related diseases. Regular clinical assessments of these problems are conducted by analyzing venipuncture-obtained blood samples in laboratories. A non-invasive, cheap, point-of-care, and accurate test is needed everywhere. We started with Hgb measurement, and after an extensive literature survey, we came up with a non-invasive solution with 10-second Smartphone videos of the index fingertips using custom hardware sets to illuminate the fingers. We tested four lighting conditions with wavelengths in the near-infrared spectrum suggested by the absorption properties of two primary components of blood- oxygenated Hgb and plasma. …

Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

We analyze a fully discrete finite element numerical scheme for the Cahn-Hilliard-Stokes-Darcy system that models two-phase flows in coupled free flow and porous media. To avoid a well-known difficulty associated with the coupling between the Cahn-Hilliard equation and the fluid motion, we make use of the operator-splitting in the numerical scheme, so that these two solvers are decoupled, which in turn would greatly improve the computational efficiency. The unique solvability and the energy stability have been proved in Chen et al. (2017, Uniquely solvable and energy stable decoupled numerical schemes for the Cahn-Hilliard-Stokes-Darcy system for two-phase flows in karstic geometry. …

Robust Sensor Design For The Novel Reduced Models Of The Mead-Marcus Sandwich Beam Equation, Ahmet Aydin

Masters Theses & Specialist Projects

Novel space-discretized Finite Differences-based model reductions are proposed for the partial differential equations (PDE) model of a multi-layer Mead-Marcus-type beam with (i) hinged-hinged and (ii) clamped-free boundary conditions. The PDE model describes transverse vibrations for a sandwich beam whose alternating outer elastic layers constrain viscoelastic core layers, which allow transverse shear. The major goal of this project is to design a single boundary sensor, placed at the tip of the beam, to control the overall dynamics on the beam.

For (i), it is first shown that the PDE model is exactly observable by the so-called nonharmonic Fourier series approach. However, …

Harnessing Confidence For Report Aggregation In Crowdsourcing Environments, Hadeel Alhosaini, Xianzhi Wang, Lina Yao, Zhong Yang, Farookh Hussain, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Crowdsourcing is an effective means of accomplishing human intelligence tasks by leveraging the collective wisdom of crowds. Given reports of various accuracy degrees from workers, it is important to make wise use of these reports to derive accurate task results. Intuitively, a task result derived from a sufficient number of reports bears lower uncertainty, and higher uncertainty otherwise. Existing report aggregation research, however, has largely neglected the above uncertainty issue. In this regard, we propose a novel report aggregation framework that defines and incorporates a new confidence measure to quantify the uncertainty associated with tasks and workers, thereby enhancing result …

End-To-End Open-Set Semi-Supervised Node Classification With Out-Of-Distribution Detection, Tiancheng Huang, Donglin Wang, Yuan Fang

Research Collection School Of Computing and Information Systems

Out-Of-Distribution (OOD) samples are prevalent in real-world applications. The OOD issue becomes even more severe on graph data, as the effect of OOD nodes can be potentially amplified by propagation through the graph topology. Recent works have considered the OOD detection problem, which is critical for reducing the uncertainty in learning and improving the robustness. However, no prior work considers simultaneously OOD detection and node classification on graphs in an end-to-end manner. In this paper, we study a novel problem of end-to-end open-set semisupervised node classification (OSSNC) on graphs, which deals with node classification in the presence of OOD nodes. …

Constraining Beam Backgrounds And Analyzing The Detector Response In A Test Beam With The Nova Experiment, Abhilash Yallappa Dombara

Dissertations - ALL

NOvA is a long-baseline neutrino oscillation experiment with two functionallyidentical detectors with the Near Detector at Fermilab, Illinois, and the Far Detector at Ash River, Minnesota. NOvA measures the rate of muon neutrino disappearance and electron neutrino appearance using muon neutrinos generated by the NuMI beam from the Accelerator Division(AD), thus NOvA measures neutrino oscillation parameters in the Pontecorvo-Maki- Nakagawa-Sakata matrix. The main experimental goal of NOvA is to determine the mass hierarchy, probe Charge-Parity violation and measure sin2 θ23 precisely. In this dissertation, the experimental setup, the latest analysis methods used in NOvA, and its results from analyzing 6 …