Physical Sciences and Mathematics Commons^™

Advancing Depth-Storage-Discharge Modeling In Regional Hydrology, Fahad Alshehri

USF Tampa Graduate Theses and Dissertations

This dissertation presents the development of an innovative approach to populating rating characteristics and supporting hydrologic modeling, designed to simplify complex real-world hydrological systems and accurately estimate their responses to rainfall, runoff, baseflow and evaporation stresses. The core of this research addresses the challenges inherent in characterizing hydrography elements in hydrologic modeling, particularly in regions lacking comprehensive stream reach survey data, flow and stage. This issue is pronounced in areas with extensive wetland hydrography, where traditional modeling requires intensive manual calibration, and course rating data that are often unavailable. To overcome these challenges, this study introduces a novel procedure that …

Interfacial Magnetism And Anisotropy In Dirac And Weyl Semimetals, Noah Schulz

USF Tampa Graduate Theses and Dissertations

Semimetals have gained intense interest recently due to their exotic magnetic and electronic properties. One of the most widely studied semimetals is graphene, a Dirac semimetal. The utilization of graphene in devices and sensors requires interfacing it with other materials, which may induce potentially strong interfacial effects. Furthermore, graphene alone does not possess magnetic order. Studying the interfacial effects between graphene and magnetic materials is therefore of great importance in the application of graphene to meet modern technological needs. Furthermore, by understanding the fundamental interfacial physics between graphene and magnetic materials, new properties can be unlocked, broadening the possible applications …

Dissolved Nitrogen Removal In Biochar Amended, High Permeability Media For Urban Stormwater Treatment, Mark Vicciardo

USF Tampa Graduate Theses and Dissertations

Nutrient pollution in stormwater drives the eutrophication of inland and costal waterbodies which leads to sea grass retreat and the proliferation of harmful algal blooms (HAB). These anthropogenic effects destabilize ecosystems, and some HABs can pose direct human health risk. Bioretention, or the storage and controlled discharge of stormwater run-off in an ecologically engineered setting, is a potential solution to this problem. However, it relies heavily on the settling of particles as a nutrient removal mechanism, and thus struggles with pollutants, such as dissolved nitrogen, which is a particular problem in Florida where the geological prominence of phosphorus leaves nitrogen …

Brain-Inspired Spatio-Temporal Learning With Application To Robotics, Thiago André Ferreira Medeiros

USF Tampa Graduate Theses and Dissertations

The human brain still has many mysteries and one of them is how it encodes information. The following study intends to unravel at least one such mechanism. For this it will be demonstrated how a set of specialized neurons may use spatial and temporal information to encode information. These neurons, called Place Cells, become active when the animal enters a place in the environment, allowing it to build a cognitive map of the environment. In a recent paper by Scleidorovich et al. in 2022, it was demonstrated that it was possible to differentiate between two sequences of activations of a …

Integration Of Algae And Biomass Processes To Synthesize Renewable Bioproducts For The Circular Economy, Jessica Martin

USF Tampa Graduate Theses and Dissertations

Rapid population growth and global industrialization have substantially heightened the demand for fossil-based fuels and products in various sectors of the global economy, including energy production, transportation fuels, and as raw materials for petrochemicals. The intense consumption of fossil fuels has caused immense environmental impacts, especially pertaining to carbon dioxide emissions. Shifting to renewable feedstocks (raw materials) is expected to reduce these emissions by lowering the carbon footprint of fuels and products compared to traditional fossil-derived alternatives. This transition aligns with the goal of creating a sustainable and circular economy, emphasizing efficient resource use, and reducing waste generation through recycling …

Syntheses, Photophysics, & Application Of Porphyrinic Metal-Organic Frameworks, Zachary L. Magnuson

USF Tampa Graduate Theses and Dissertations

Porphyrins are a group of heterocyclic macrocycles that play crucial roles in various biological processes such as electron transfer, catalysis, and sensing. Hemoglobin, which carries oxygen in the blood of mammals, and chlorophyll, which drives photosynthesis in plants and algae, are both porphyrins. The ability of porphyrins to bind metal ions and their unique electronic and photophysical properties make them an excellent platform for designing functional materials for various applications, often drawing inspiration from their function in nature. Metal-organic frameworks (MOFs) are a class of porous materials that have been extensively studied in recent years due to their high surface …

Deep Learning-Based Automatic Stereology For High- And Low-Magnification Images, Hunter Morera

USF Tampa Graduate Theses and Dissertations

Quantification of the true number of stained cells in specific brain regions is an important metric in many fields of biomedical research involving cell degeneration, cytotoxicology, cellular inflammation, and drug development for a wide range of neurological disorders and mental illnesses. Unbiased stereology is the current state-of-the-art method for collecting the cell count data from tissue sections. These studies require trained experts to manually focus through a z-stack of microscopy images and count (click) on a hundred or more cells per case, making this approach time consuming (~1 hour per case) and prone to human error (i.e., inter-rater variability). Thus, …

Exploratory Data-Driven Models For Water Quality: A Case Study For Tampa Bay Water, Sandra Sekyere

USF Tampa Graduate Theses and Dissertations

Water, a crucial resource for sustaining life, covers approximately 70% of the earth's surface. Nonetheless, the quality of water is deteriorating rapidly due to the rapid growth of urban areas and industries, which is a worrying trend causing harm to human health and the ecosystem. Water quality forecasting has a key role in water resources management by enabling effective pollution control, ecosystem monitoring, and decision-making.

Previously, traditional statistical models were used to forecast water quality, but they were unable to examine the non-linear relationships between water quality parameters, and they assumed that all datasets were distributed normally. This study uses …

Deep Learning Enhancement And Privacy-Preserving Deep Learning: A Data-Centric Approach, Hung S. Nguyen

USF Tampa Graduate Theses and Dissertations

Deep Learning and its applications have become attractive to a lot of research recentlybecause of its capability to capture important information from large amounts of data. While most of the work focuses on finding the best model parameters, improving machine learning performance from data perspective still needs more attention. In this work, we propose techniques to enhance the robustness of deep learning classification by tackling data issue. Specifically, our data processing proposals aim to alleviate the impacts of class-imbalanced data and non- IID data in deep learning classification and federated learning scenarios. In addition, data pre-processing strategies such that dimensionality …

Characteristics And Hydraulic Behavior Of Adsorptive Media For Use In Permeable Reactive Barriers, Shelby Rocha

USF Tampa Graduate Theses and Dissertations

The Cargill ditch is located on the property of Se7en Wetlands, a 1600-ac treatment wetland system in Lakeland, Polk County, Florida. The Se7en Wetlands property was previously utilized for phosphate mining prior to the construction of the system. Nonpoint nutrient sources derived from remnants of abandoned phosphate mines – known as “legacy phosphorus” – become mobilized by stormwater runoff and impair surface water bodies by promoting harmful algal blooms (HABs). Thus, the Cargill ditch likely conveys nutrient rich flow resulting from legacy phosphorus and is thought to be one contributing factor in the occurrence of HABs within the treatment wetland …

Insect Classification And Explainability From Image Data Via Deep Learning Techniques, Tanvir Hossain Bhuiyan

USF Tampa Graduate Theses and Dissertations

Since the dawn of the Industrial Revolution, humanity has always tried to make labor more efficient and automated, and this trend is only continuing in the modern digital age. With the advent of artificial intelligence (AI) techniques in the latter part of the 20th century, the speed and scale with which AI has been leveraged to automate tasks defy human imagination. Many people deeply entrenched in the technology field are genuinely intrigued and concerned about how AI may change many of the ways in which humans have been living for millennia. Only time will provide the answers. This dissertation is …

Remote Medical Diagnosis Via Infrared Thermography And Augmented Reality, Frederick M. Selkey

USF Tampa Graduate Theses and Dissertations

Fast, accurate, and non-invasive diagnostic techniques are required by the medical industry to increase the success of medical treatments and enhance the quality of patient care. Medical IRT has been demonstrated reasonably effective at diagnosing and monitoring several physiological conditions. Diversities in the human body, physical and psychological condition, measurement equipment, and environment all influence the sensitive readings obtained by passive IR measurement devices. New standards for medical IRT and fever screening have been demonstrated effective, but there is limited adherence to the guidelines [36]. Absolute temperature readings require regular calibration checks and can easily be thrown off by noise. …

Deep Reinforcement Learning Based Optimization Techniques For Energy And Socioeconomic Systems, Salman Sadiq Shuvo

USF Tampa Graduate Theses and Dissertations

Optimization, which refers to making the best or most out of a system, is critical for an organization's strategic planning. Optimization theories and techniques aim to find the optimal solution that maximizes/minimizes the values of an objective function within a set of constraints. Deep Reinforcement Learning (DRL) is a popular Machine Learning technique for optimization and resource allocation tasks. Unlike the supervised ML that trains on labeled data, DRL techniques require a simulated environment to capture the stochasticity of real-world complex systems. This uncertainty in future transitions makes the planning authorities doubt real-world implementation success. Furthermore, the DRL methods have …

Reducing Instrumentation Barriers Of Diffuse Correlation Spectroscopy For Low-Cost Deep Tissue Blood Flow Monitoring, Arindam Biswas

USF Tampa Graduate Theses and Dissertations

Cerebral blood flow (CBF) is a good indicator of brain health as blood carries necessary nutrients, oxygen, and metabolic byproducts. Quantitative blood flow information can be used in several clinical and therapeutic applications such as stroke detection, measuring autoregulation, evaluating brain injury, or determining neuronal activity. Over the past few decades, light-based deep tissue hemodynamic detection modalities have become popular for non-invasive CBF measurements. In particular, noninvasive Diffuse Correlation Spectroscopy (DCS), has become a tool of choice for research and clinical applications due to its depth sensitivity (>1 cm), portability, validity against other technologies such as Magnetic Resonance Imaging …

Frequency Domain Diffuse Optics Spectroscopies For Quantitative Measurement Of Tissue Optical Properties, Sadhu Moka

USF Tampa Graduate Theses and Dissertations

Tissue oxygen saturation, blood flow and blood volume are physiological bio-markers of tissue health. Diffuse Optical Spectroscopy(DOS) and Diffuse Correlation Spectroscopy (DCS) are two complementary approaches to measure tissue oxygen saturation and blood flow respectively. Quantitative Diffuse Optical Spectroscopy (DOS) uses multi-spectral intensities of near-infrared light that have been modulated at RF frequencies to estimate static tissue optical properties and hence concentrations of oxygenated and de-oxygenated hemoglobin. Diffuse Correlation Spectroscopy estimates tissue dynamics - i.e., blood flow, by measuring temporal intensity auto-correlation function of backscattered light diffusing through the tissue. Conventionally, DCS instruments use coherent light sources with constant intensity. …

Data-Driven State Estimation For Improved Wide Area Situational Awareness In Smart Grids, Md Jakir Hossain

USF Tampa Graduate Theses and Dissertations

Wide area situational awareness (WASA) in smart grids includes automatic monitoring, perception and detection of anomalies in these systems. The goal of WASA is to make smart grids aware of their physical and operational state for more effective operational decisions and control. As such, tracking the system's state or state estimation is one of the key objectives of WASA. The extensive integration of cyber elements into smart grids, such as large deployment of various monitoring and measurement devices, provides new opportunities to improve WASA. However, the tight coupling of power grids with cyber components introduces vulnerabilities to cyber and physical …

Quantifying A 21-Year Surface Water And Groundwater Interaction In A Ridge And Valley Lake Environment Using A Highly Constrained Modeling Approach, Richard T. Bowers Jr.

USF Tampa Graduate Theses and Dissertations

Karst lakes are ubiquitous in ridge terrain settings in limestone aquifer coastal plain environments. In west-central Florida, these lakes are frequently connected to the Upper Floridan aquifer and have unique aquifer recharge characteristics. They have been selectively studied because they commonly have no or very limited surface water discharge and limited drainage areas, have appreciable surface water and groundwater interaction and leak to the deep aquifer. An innovative modeling approach was developed to collectively understand and more precisely quantify this vertical leakage, both from a lake-specific and regional water budget standpoint, for a 21-year study period (2000-2020). A unique, calibrated …

Optimizing Lake Okeechobee Watershed Management And Reservoir Operations For Water Quality Improvement, Osama Mahrous Mossad Tarabih

USF Tampa Graduate Theses and Dissertations

Rivers around the globe have been altered as people have constructed water resources infrastructure to store water for different human needs, causing negative impacts on ecosystem processes and functions. Environmental flows have been introduced to restore deteriorated riverine ecosystems; however, environmental flows have not always been practical or adequate to restore environment conditions in rivers globally. Lake Okeechobee is a large subtropical lake that plays a pivotal role in South Florida water system providing various water demands for the surrounding communities as well as providing crucial services to the ecosystem of South Florida. However, hydrologic alterations and nutrient (phosphorus and …

Development Of An Automated Platform For Sensing And Differentiating Vapor-Phase Btex Constituents, Jonathan Samuelson

USF Tampa Graduate Theses and Dissertations

Light aromatic hydrocarbons are an inevitable byproduct of fossil fuel extraction, refinement, distribution, and use. The four lightest and most prevalent of these are benzene, toluene, ethylbenzene, and xylene, which are known collectively as BTEX. In spite of their chemical similarity these species have markedly different effects on human health and substantially different concentrations are permitted by OSHA in workplaces and by the EPA in ambient air and groundwater. Real-time detection, identification, and quantification of these species is therefore of great importance wherever they see industrial use.This work represents the continuation and advancement of a line of research in which …

Generative Spatio-Temporal And Multimodal Analysis Of Neonatal Pain, Md Sirajus Salekin

USF Tampa Graduate Theses and Dissertations

Neonates can not express their pain like an adult person. Due to the lacking of proper muscle growth and inability to express non-verbally, it is difficult to understand their emotional status. In addition, if the neonates are under any treatment or left monitored after any major surgeries (post-operative), it is more difficult to understand their pain due to the side effect of medications and the caring system (i.e. intubated, masked face, covered body with blanket, etc.). In a clinical environment, usually, bedside nurses routinely observe the neonate and measure the pain status following any standard clinical pain scale. But current …

Magnetism In Doped And Hybrid Two – Dimensional Transition Metal Dichalcogenides, Nalaka Kapuruge

USF Tampa Graduate Theses and Dissertations

In recent years, spintronics has gained increasing interest due to the possibility of storing and processing information through the manipulation of both the charge and spin of an electron. Dilute magnetic semiconductors are ideal for the fabrication of such devices as they display carrier-mediated ferromagnetism which allows the electronic control of magnetism. Transferring these properties into the two-dimensional (2D) realm is very attractive for both fundamental research and novel applications. The recent discovery of long-range magnetic order in 2D materials has attracted a growing effort in the search for new functional 2D materials that can display ferromagnetic properties at room-temperature. …

Preventing Variadic Function Attacks Through Argument Width Counting, Brennan Ward

USF Tampa Graduate Theses and Dissertations

Format String attacks, first noted in June 2000 [1], are a type of attack in which anadversary has control of the string argument (the format string) passed to a string format function (such as printf). Such control allows the attacker to read and write arbitrary program memory. To prevent these attacks, various methodologies have been proposed, each with their own costs and benefits. I present a novel solution to this problem through argument width counting, ensuring that such format functions cannot access stack memory beyond the space where arguments were placed. Additionally, I show how this approach can be expanded …

Accelerating Multiparametric Mri For Adaptive Radiotherapy, Shraddha Pandey

USF Tampa Graduate Theses and Dissertations

MR guided Radiotherapy (MRgRT) marks an important paradigm shift in the field of radiotherapy. Superior tissue contrast of MRI offers better visualization of the abnormal lesions, as a result precise radiation dose delivery is possible. In case of online treatment planning, MRgRT offers better control of intratumoral motion and quick adaptation to changes in the gross tumor volume. Nonetheless, the MRgRT process flow does suffer from some challenges that limit its clinical usability. The primary aspects of MRgRT workflow are MRI acquisition, tumor delineation, dose map prediction and administering treatment. It is estimated that the acquisition of MRI takes around …

Adaptive Multi-Scale Place Cell Representations And Replay For Spatial Navigation And Learning In Autonomous Robots, Pablo Scleidorovich

USF Tampa Graduate Theses and Dissertations

Place cells are one of the most widely studied neurons thought to play a vital role in spatial cognition. Extensive studies show that their activity in the rodent hippocampus is highly correlated with the animal’s spatial location, forming “place fields” of smaller sizes near the dorsal pole and larger sizes near the ventral pole. Despite advances, it is yet unclear how this multi-scale representation enables navigation in complex environments.

In this dissertation, we analyze the place cell representation from a computational point of view, evaluating how multi-scale place fields impact navigation in large and cluttered environments. The objectives are to …

A Protein-Based Therapeutic Combination For The Treatment Of Hard-To-Heal Wounds, Graham L. Strauss

USF Tampa Graduate Theses and Dissertations

Chronic wounds present many clinical challenges in relation to the successful treatment and closure of the damaged tissue. Most current treatment methods focused on one or two aspects to drive wound closure, while most chronic wounds are multifactorial environments with many of those dependencies relying on the termination of one another to effectively gain tissue construction, closure, and full skin thickness and composition. Natural wound healing processes allude to potential biologics that can impede the chronic breakdown of tissue, while restoring deposition of new tissue, and effectively leading to a healed wound. Proteases secreted by the body’s immune system lay …

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 …

An Integrated Approach For Dynamic Process Modeling And Optimization Of Wastewater Treatment Facilities, Komal Rathore

USF Tampa Graduate Theses and Dissertations

The subareas of process systems engineering including process modeling, simulation, and optimization are becoming progressively substantial for understanding processes, making decisions, improving efficiency, and complying with stricter environmental and safety legislation. Additionally, the availability of user-friendly flowsheet simulators and computational resources with the current trend of data collection and analysis has allowed for a more accurate representation of complex processes such as wastewater treatment systems. Despite all the progress in the areas of process modeling and simulation, the first-principle mechanistic models for wastewater treatment processes are at best employed during the design stage, and therefore, not used optimally for day-to-day …

Explainable And Cooperative Autonomy Across Networks Of Distributed Systems, Peter Joseph Jorgensen

USF Tampa Graduate Theses and Dissertations

Large networks of complex systems-of-systems are commonplace and evermore present in both mundane and extraordinary facets of human existence. From the exponential growth of connectivity via the internet and other information networks, to the miniaturization of computers and sensors, to cross-domain sensor and communication networks, these networks of distributed systems-of-systems (NDSS) present incredible benefits and challenges. Autonomy is perhaps the most important and most difficult to achieve enabling technology for efficient performance of the NDSS. Giving each individual agent in a network the ability to manage its internal state in dynamic operating environments and in pursuit of multiple complex and …

Improved Performance Of Silica-Supported La0.5Ba0.5Feo3 In The Reverse Water Gas Shift - Chemical Looping Process For Carbon Dioxide Reduction – A Density Functional Theory Study, Jiawei Guo

USF Tampa Graduate Theses and Dissertations

Global warming is increasingly obvious, and the reduction of greenhouse gases is an effective way to heal. Increasing the efficiency of catalysts that is applied in the industry can significantly reduce the emission of greenhouse gases. Reverse water gas shift chemical looping (RWGS-CL) is a promising reaction to convert CO2 to CO. La0.5Ba0.5FeO3 (LBF) is a good candidate for RWGS-CL, which shows increased conversion yield when supported on silica. This research focuses on identifying the mechanism of RWGS-CL via silica-supported LBF by exploring the oxygen vacancy formation energy (EO-vac). Density Functional Theory (DFT) is a powerful computational method to solve …

Data-Driven Design And Analysis Of Next Generation Mobile Networks For Anomaly Detection And Signal Classification With Fast, Robust And Light Machine Learning, Muhammed Furkan Küçük

USF Tampa Graduate Theses and Dissertations

This research focuses on machine (and deep) learning applications (including clustering,anomaly detection and signal classification) for self-organizing and next generation mobile networks in wireless communications. Specifically, this dissertation document will address the three different topics.

First, in the study titled “Performance analysis of neural network topologies and hyperparameters for deep clustering”, we explore the relationship between the clustering performance and network complexity. Deep learning found its initial footing in supervised applications such as image and voice recognition successes of which were followed by deep generative models across similar domains. In recent years, researchers have proposed creative learning representations to utilize …