Physical Sciences and Mathematics Commons^™

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 …

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 …

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 …

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 …

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 …

Stability Analysis Of Delay-Driven Coupled Cantilevers Using The Lambert W-Function, Daniel Siebel-Cortopassi

USF Tampa Graduate Theses and Dissertations

A coupled delay-feedback system of two cantilevers can yield greater sensitivity than that of asingle cantilever system, with potential applications in atomic force microscopy. The Lambert W-function analysis concept for delay differential equations is used to more accurately model the behavior of specific configurations of these cantilever systems. We also use this analysis concept to find parameters which yield stability for greater parameter ranges, of the delay differential equations. The Q factor, or quality factor, is the ratio of energy stored in the system, to the energy lost per fixed oscillation/movement cycle. Having stability of the cantilevers corresponds to the …

Block Copolymer Directed Self-Assembly: Exploring The Efficacy Of Applications In Semiconductor Fabrication, Jakin Bryce Delony

USF Tampa Graduate Theses and Dissertations

Over the course of the past 80 years, semiconductor devices have become increasingly ubiquitous in everyday life.From constructing mainframes that encompassed entire rooms during the 1940s, to inventing personal computers in the 1980s, to developing progressively faster smartphones and wearable technology in the 2010s, the primary driving force behind the Digital Revolution has been increasing transistor counts, and thus computing power, via incremental improvements in optical lithography. In 1965, Intel co-founder Gordon Moore boldly predicted that the transistor density of semiconductor devices would double approximately every 18-24 months. While this prediction -- now colloquially referred to as Moore's Law -- …

On The Reliability Of Wearable Sensors For Assessing Movement Disorder-Related Gait Quality And Imbalance: A Case Study Of Multiple Sclerosis, Steven Díaz Hernández

USF Tampa Graduate Theses and Dissertations

Approximately 33 million American adults had a movement disorder associated with medication use, ear infections, injury, or neurological disorders in 2008, with over 18 million people affected by neurological disorders worldwide. Physical therapists assist people with movement disorders by providing interventions to reduce pain, improve mobility, avoid surgeries, and prevent falls and secondary complications of neurodegenerative disorders. Current gait assessments used by physical therapists, such as the Multiple Sclerosis Walking Scale, provide only semi-quantitative data, and cannot assess walking quality in detail or describe how one’s walking quality changes over time. As a result, quantitative systems have grownas useful tools …

Exploring Magneto-Excitons In Bulk And Mono-Layer Semiconductors Using Non-Linear Spectroscopy Techniques, Varun Mapara

USF Tampa Graduate Theses and Dissertations

The research in two-dimensional (2D) materials has evolved from ``traditional" quantum wells based on group III-V and II-VI semiconductors to atomically thin sheets of van der Waals materials such as 2D semiconducting Transition Metal Dichalcogenides (TMDs). These 2D materials remain a stimulating field that continues to introduce new challenges. From both a fundamental physics and technological perspective, magneto-optical spectroscopy has been an essential tool in this research field. TMDs, for example, pose the challenge of characterizing their spin-valley-resolved physics and deriving implications in quantum computation and information research. With the discovery of valley Zeeman effects, the spin-valley physics of TMDs …

Analyzing Decision-Making In Robot Soccer For Attacking Behaviors, Justin Rodney

USF Tampa Graduate Theses and Dissertations

In robotics soccer, decision-making is critical to the performance of a team’s SoftwareSystem. The University of South Florida’s (USF) RoboBulls team implements behavior for the robots by using traditional methods such as analytical geometry to path plan and determine whether an action should be taken. In recent works, Machine Learning (ML) and Reinforcement Learning (RL) techniques have been used to calculate the probability of success for a pass or goal, and even train models for performing low-level skills such as traveling towards a ball and shooting it towards the goal[1, 2]. Open-source frameworks have been created for training Reinforcement Learning …

Novel Approach To Integrate Can Based Vehicle Sensors With Gps Using Adaptive Filters To Improve Localization Precision In Connected Vehicles From A Systems Engineering Perspective, Abhijit Vasili

USF Tampa Graduate Theses and Dissertations

Research and development in Connected Vehicles (CV) Technologies has increased exponentially, with the allocation of 75 MHz radio spectrum in the 5.9 GHz band by the Federal Communication Commission (FCC) dedicated to Intelligent Transportation Systems (ITS) in 1999 and 30 MHz in the 5.9 GHz by the European Telecommunication Standards Institution (ETSI). Many applications have been tested and deployed in pilot programs across many cities all over the world.

CV pilot programs have played a vital role in evaluating the effectiveness and impact of the technology and understanding the effects of the applications over the safety of road users. The …

Efficient Management Of Nitrogen And Phosphorus At Centralized Water Reclamation Facilities, Helene Kassouf

USF Tampa Graduate Theses and Dissertations

A variety of process configurations are employed at municipal water reclamation facilities (WRFs), such as 5-stage Bardenpho, oxidation ditch, modified Ludzack-Ettinger (MLE) process, and sidestream recycle. However, all of these configurations face certain challenges in achieving optimum treatment of nitrogen and phosphorus. In this dissertation, the driving objectives were to: (1) quantitatively assess the fate of nitrogen and phosphorus (mass fluxes) at a treatment facility that employs biological nutrient removal, aerobic digestion, and sidestream recycle, (2) evaluate the performance of a microbial fuel cell (MFC) as a technology to remove nitrogen from sidestreams at a treatment plant that employs that …

Pressure Retarded Osmosis: A Potential Technology For Seawater Desalination Energy Recovery And Concentrate Management, Joshua Benjamin

USF Tampa Graduate Theses and Dissertations

Currently, a significant challenge with reverse osmosis-based desalination is reducing the energy consumption and environmental impacts of the process. This project analyzed the viability of using pressure-retarded osmosis (PRO) for energy recovery in seawater desalination facilities using brine concentrate (the draw solution) and other water sources (the feed solution) such as wastewater effluent. The primary goal of this project is to decrease the cost and overall energy consumption of seawater desalination through PRO-based energy recovery. Process modeling, statistical and sensitivity analysis, energy and cost analysis, geospatial and GIS analysis, laboratory-scale testing, water quality analysis, SEM-EDS microscopy, computational fluid dynamics (CFD), …

Crystal Structure Prediction Of Materials At Extreme Conditions, Ashley S. Williams

USF Tampa Graduate Theses and Dissertations

The prediction of the structure of a crystal given only the constituent elements is one of the greatest challenges in both materials science and computational science alike. If one were to try to predict a novel crystal by brute force, meaning by arranging the atoms in every possible position of the unit cell and optimizing the geometry to find the energy minima of the potential energy surface, the amount of computer resources required to complete the calculation on the timescale of a few years would vastly exceed the currently installed computational capacity of the entire world. Fortunately, several methods have …

The Photophysical Studies Of Transition Metal Polyimines Encapsulated In Metal Organic Frameworks (Mof’S), Jacob M. Mayers

USF Tampa Graduate Theses and Dissertations

Light harvesting systems provide a platform that converts solar energy into other forms of energy. One of the most common examples of photon capturing and conversion into chemical energy is observed in photosynthetic organisms in both Eurkaroyic and Prokaryotic domains. Nature provides a model for successful light harvesting platforms which includes the compartmentalization of antenna complexes that contain separated donor and acceptor pairs that participate in efficient electron transfer processes. In order to mimic such systems, crystalline porous materials that exhibits regular cavities and pore dimensions provides an excellent starting place. Metal organic frameworks (MOFs) are a class of porous …

A System Architecture For Water Distribution Networks, Noha Abdel-Mottaleb

USF Tampa Graduate Theses and Dissertations

This dissertation examines structure-function relationships of water distribution networks (WDNs), with focus on improving the decision-making process for water utilities. WDNs are lifeline infrastructure systems, necessary for the functioning of cities. Yet water utilities around the world struggle with emerging challenges that include but are not limited to aging infrastructure components, limited budgets, increased interdependencies between infrastructure systems, increased rates of urbanization, and increasing extreme weather conditions. This is why enhancing the performance of WDNs is a priority for water utilities around the world. This research begins to delineate a system architecture for WDNs and evaluates the use of various …

Investigation Of Immobilized Enzymes In Confined Environment Of Mesoporous Host Matrices, Xiaoliang Wang

USF Tampa Graduate Theses and Dissertations

Enzyme immobilization in metal-organic frameworks (MOFs) as a promising strategy, is attracting the interest of scientists from different disciplines with the expansion of MOF’s development. Different from other traditional host materials, their unique strengths of high surface areas, large yet adjustable pore sizes, functionalizable pore walls, and diverse architectures make MOFs an ideal platform to investigate hosted enzymes, which is critical to the industrial and commercial process. In addition to the protective function of MOFs, the extensive roles of MOFs in the enzyme immobilization are being well-explored by making full use of their remarkable properties like well-defined structure, high porosity, …

Modeling The Ambient Conditions Of A Manufacturing Environment Using Computational Fluid Dynamics (Cfd), Yang Liu

USF Tampa Graduate Theses and Dissertations

As manufacturing equipment evolve to higher speed and require high precision operations, the impact of environmental changes on machine accuracy becomes critical. Due to thermal expansion, the structure of the machine can change when ambient temperature varies. When the airflow in the laboratory changes, this also alters the operator's thermal comfort. Either the change in machine structure or operator comfort can ultimately affect machine accuracy. The manufacturing industry is currently using heating, ventilation, and air-conditioning (HVAC) systems to regulate the temperature of the working environment. However, since conventional HVAC systems determine whether to activate the HVAC system by collecting the …