Engineering Commons^™

Investigation Of The Use Of Recycled Concrete Aggregates In Porous Asphalt Mixture, Asad Elmagarhe

USF Tampa Graduate Theses and Dissertations

This study aims to address the national need for using recycled concrete in road pavements. This is especially important in the governmental and corporate sectors, where reducing the cost and carbon footprint of construction projects is a priority. The long-term goal is to meet the public demand for environmentally friendly infrastructure and minimize the harmful effects of waste disposal on humans and the environment.

The project focuses on using recycled concrete aggregate (RCA) in porous asphalt pavement to reduce stormwater runoff, a popular environmentally friendly road design. However, compared to regular dense asphalt mixtures, porous asphalt mixtures (PAM) are more …

Sliding Mode Control With Chattering Reduction, Suryamshu Ramesh

Doctoral Dissertations and Master's Theses

Sliding Mode Control is a powerful nonlinear control methodology that can handle parametric uncertainties and external disturbances. However, the discontinuous and high-frequency switching nature of the control law introduces the chattering phenomenon, which leads to potential actuator degradation, alterations to the desired response characteristics and, sometimes, instability during control implementation. The main objective of this thesis is to study Sliding Mode Control with chattering reduction. The Sliding Mode Control law involves an equivalent control component and a discontinuous control component. A disturbance estimation is performed based on Lyapunov analysis and adaptive control techniques and then included in the control law …

Study Of Polymer-On-Polymer Cold Spray Deposition Windows Under Apparently Similar Conditions, Ülar Tiitma

Theses and Dissertations

The purpose of this thesis is to explore and expand the capabilities of polymer-on-polymer cold spray demonstrated herein using polyamide 6 (PA6)-based powder and substrates. Experiments were conducted using three different cold spray systems described in this work, permitting more in-depth examination of process response to different cold spray process control parameters, such as nominal system pressure and temperature. Two specific responses of interest were the deposition window (DW) and deposition efficiency (DE) of PA6. The DW was determined by performing several sprays at different calculated particle impact velocities and temperatures. The composite result from these experiments was identification of …

Economic Planning And Operation Of Ev Charging Infrastructure Participating In Electric Power Markets, Diwas Paudel

USF Tampa Graduate Theses and Dissertations

As electric vehicles (EVs) are becoming more common, there are not enough charging infrastructures to keep up with the projected EV charging demands. This necessitates investment from private enterprises in the charging infrastructure, along with additional government investments, to support the expected EV growth. The profit potential of the EV charging business will be crucial in attracting private enterprises to invest in the infrastructure. The profitability of these infrastructures depends on their location and effective operation. The charging infrastructure needs to be strategically placed and sized in the service area of interest. Once built, they need a robust strategy to …

Deep Learning Framework For Graph-Based Molecular Drug Discovery, Daniel Manu

Electrical and Computer Engineering ETDs

This dissertation proposes the GraphGANFed framework, which combines Graph Convolutional Networks (GCN), Generative Adversarial Networks (GAN), and Federated Learning (FL) to generate novel molecules while preserving data privacy. FL allows learning from distributed clients without sharing local datasets, GCN extracts molecular structural properties, and GAN generates new molecules retaining the learned properties. Extensive simulations on three benchmark datasets show GraphGANFed's effectiveness, producing molecules with high novelty (≈ 100) and diversity (> 0.9). Results indicate a trade-off among evaluation metrics, and the right dropout ratio avoids mode collapse. Additionally, Conditional GraphGANFed (cGraphGANFed) incorporates a critic network from Reinforcement Learning (RL) to …

Transforming Organizational Cyber Security With Artificial Intelligence And Data-Driven Optimization, Soumyadeep Hore

USF Tampa Graduate Theses and Dissertations

This dissertation presents a comprehensive framework for enhancing organizational cybersecurity through data-driven intelligence. The research integrates multiple methodologies to tackle challenges in network intrusion detection and vulnerability management within cybersecurity operations centers (CSOCs). First, the research investigates vulnerability prioritization and mitigation techniques currently employed by CSOCs. To further streamline the vulnerability prioritization and mitigation process a machine learning (ML)-based Vulnerability Priority Scoring System (VPSS) is introduced, significantly improving the prioritization and mitigation of context-sensitive vulnerabilities. The VPSS outperforms traditional methods, reducing the cumulative vulnerability exposure score by up to 30% by considering both organizational context and vulnerability severity. Next, the …

A Robust Data-Driven Framework For Artificial Intelligent Systems, Quoc H. Nguyen

USF Tampa Graduate Theses and Dissertations

Artificial Intelligence (AI) systems have demonstrated remarkable performance across various domains. However, their robustness remains a critical concern, particularly in terms of data and model reliability. This dissertation aims to address the challenges associated with building robust AI systems by focusing on two key aspects: data robustness and model robustness. Data robustness poses significant challenges, including data shift, concept shifting, limited and imbalanced datasets, and interoperability issues in IoT systems for data collection. Existing methods fall short in handling dynamic business objectives and evolving data landscapes effectively. To bridge these gaps, we propose an IoT framework that ensures interoperability, seamless …

Model-Based Systems Engineering For Engineering Education Systems Simulation, Pallavi Singh

USF Tampa Graduate Theses and Dissertations

As the engineering education system continuously evolves to meet the demands of modern industry and society, there is a need for a methodology that would manage and resolve the complexities inherent in engineering educational systems. Model-based Systems Engineering (MBSE) is a structured approach to system design that utilizes models across all stages of the system's life cycle and supports requirements management, design, analysis, verification, and validation processes. While MBSE has been applied successfully in industries like defense, aerospace, and automotive, its application in engineering educational systems remains unexplored. This dissertation develops a dynamic model of the university-level engineering education system …

Anonymized Identity Recognition And Classification Using Privacy Preserving Facial Encoding, Manas Sanjay Pakalapati

USF Tampa Graduate Theses and Dissertations

The need for sharing large-scale datasets to train deep neural network models, particularly in healthcare, raises significant data security and privacy concerns. To address these issues, methods such as data encryption or encoding are utilized. These techniques can encrypt the data and make it unreadable to humans, while still retaining its usefulness for training models.

In this study, we investigate various image encoding techniques designed to protect privacy by making images unrecognizable while still retaining their usefulness for model training. Our investigation utilized publicly available facial databases and focused on evaluating the trade-offs inherent in image encoding techniques, with a …

Continuum Mechanics Modeling Of High Strain Rate Impact Of Thermoplastic Polymer Particles, Jeeva Muthulingam

Theses and Dissertations

The study of particle impact at high strain rates is crucial in fields ranging from materials science and engineering to space exploration and environmental science. In the particular case of cold spray, a particle undergoes intense plastic deformation upon impact, causing it to adhere to the target substrate. While metallic particles impacting on metallic substrates have been extensively studied, understanding the mechanical characteristics of polymeric particles on polymer and metal substrates requires further research. This study focuses on single particle impact modeling, analyzing impact parameters such as particle size, velocity, and angle of incidence using continuum mechanics finite element modeling …

Understanding The Mechanical And Electrochemical Impacts Of Binder Systems On Silicon Anodes In Lithium-Ion Batteries, Fei Sun

Theses and Dissertations

Silicon has emerged as a promising alternative to traditional graphite as an anode material in battery technology, primarily due to its high theoretical capacity and abundance. However, its application is hindered by significant challenges, including severe volume expansion in the active material (~275%) during cycling, which can lead to a series of electrode failure issues. Polymer binder plays an essential role in addressing these challenges as it accommodates silicon's volume expansion and the rearrangement of particles. This work conducted an analysis of how different binders influence mechanical and electrochemical properties of silicon electrodes. Our findings are supported by a series …

Integration Of Machine Learning In Structural Health Monitoring For Damage Identification And Response Prediction In Bridges, Naga Lakshmi Chittitalli Ravuri

Theses and Dissertations

Machine learning-based structural health monitoring (ML-SHM) plays a pivotal role in enhancing structural resilience. By recognizing potential hazards, implementing resistance measures, facilitating swift recovery, and continuously monitoring structural health, ML-SHM ensures proactive maintenance and minimizes recovery delays post-events. Leveraging machine learning algorithms and sensor data, ML-SHM enables early detection of anomalies, prediction of failures, and adaptive responses, enhancing the structure's ability to withstand and recover from adverse conditions. This integrated approach not only improves the structure's performance and adaptability but also contributes to overall safety and longevity. This thesis presents a comprehensive exploration of structural health monitoring (SHM) techniques for …

Understanding Social Impacts Of Major Disruptions From The Perspective Of Destination Access, Manika Rana Bhat

LSU Master's Theses

Major disruptions (like public health crises and extreme weather events) significantly impact human mobility and travel patterns. This study investigates the social impacts of major disruptions on human mobility from the perspective of accessing destinations. This study used a large-scale dataset from SafeGraph and focused on analyzing the impacts of COVID-19 and Hurricane Ida on destination access in Louisiana. The findings of the temporal plots indicated that the impact magnitude of Hurricane Ida was much smaller than that of the COVID-19 pandemic but still resulted in hardship on destination access. During COVID-19, it was found that parishes with limited active …

Tool Life Characterization In Refill Friction Stir Spot Welding, Ruth Guadalupe Belnap

Theses and Dissertations

As light-weighting becomes a priority for the automotive industry, refill friction stir spot welding emerges with enormous potential to supplement or replace conventional spot joining processes. This thesis addresses the limitations of current tooling options by examining materials beyond steel for use in RFSSW. Contained herein is an analysis of weld quality as a function of tool material, a production evaluation of RFSSW using various tool materials, and an assessment of long-term performance of a tungsten carbide tool. Over the course of this research, tungsten carbide emerged as a viable candidate for long-lasting RFSSW tooling.

Digimindready: Enhancing Military Readiness Through Edge Ai-Driven Wellness, Education, And Digital Discipline Via Privacy-First Mhealth Innovation, Md Mehedi Hasan

Master's Theses

Military personnel often find themselves in intense situations that require high focus. Successfully engaging in these dangerous missions means they must efficiently control cognitive load, manage overwhelming stress, and stay focused through distractions to perform at their best. Military training significantly focuses on human performance, which benefits military readiness. The 21st century has introduced unanticipated challenges to all, such as the adverse effects of excessive screen time, external distractions, and over-reliance on technology without being aware of digital discipline. Militaries are no exception. These challenges have become an emerging threat to military personnel's cognitive, emotional, and physical well-being. On top …

Aligning Clinical Productivity Of Cancer Care Providers: A Simulation-Based Approach, Maile Sinclair-Baxter

USF Tampa Graduate Theses and Dissertations

The growing number of cancer patients over the years has presented many challenges and opportunities for improvement in the healthcare system. These challenges and opportunities have demonstrated the need for a tool that can enhance the clinical productivity of healthcare providers, ultimately impacting patients’ overall experience. We studied the clinical Full Time Equivalency (cFTE) for providers at a cancer research center. cFTE is the percentage of time allocated for clinical work. In this cancer research center, the clinical work of each provider is supposed to match a targeted cFTE. The cancer research center’s concern was that the provider’s clinical productivity …

Advancing Adversarial Audio: Human-In-The-Loop Black-Box Attacks, Rui Duan

USF Tampa Graduate Theses and Dissertations

Adversarial audio attacks pose significant security challenges to real-world audio applications. Attackers may manipulate speech to impersonate a speaker, gaining access to smart devices like Amazon Echo. In audio applications, there are two key areas: music and speech. In music, most attackers create a small noise-like perturbation on the original signal to evade copyright detection. However, this method degrades music's perceived quality for human listeners. In the speech, creating an adversarial example often requires many queries to the target model, a process too cumbersome for practical use in real-world scenarios, like interacting with smart devices numerous times.

In this dissertation, …

Copper-Based Electrocatalysts For Electrochemical Reduction Of Co2 To C2 Products, Monsuru Olatunji Dauda

LSU Master's Theses

The electrochemical reduction of CO₂ using copper-based electrocatalysts has emerged as a promising approach for sustainable chemical production, offering a pathway to mitigate the rising atmospheric CO₂ levels while generating valuable fuels and chemicals. However, the selectivity and efficiency of copper-based catalysts towards specific C₂ products remain a major challenge, hindering their commercial viability. This thesis focuses on the development, characterization, and mechanistic understanding of three promising electrocatalyst systems for multi-carbon product generation from CO₂ reduction: copper-phosphide (Cu-P), copper-tin (Cu-Sn), and copper selenide (Cu₂Se). A comprehensive investigation of the electrocatalysts was conducted using advanced …

Corridor Counting, Anthony Bryson, Vincent Zhou, Amy Ha

Computer Science and Engineering Senior Theses

Information on traffic patterns is essential for identifying and addressing sources of traffic congestion and informing future road layouts to create safer and more efficient roads. To this end, we develop a Corridor Counting, or Multi- Camera Vehicle Counting, algorithm that quantifies the number of vehicles traveling along a specific stretch of road. Our work builds upon the related problem of Multi-Camera Vehicle Tracking and draws inspiration from methods used for Single-Camera Counting. We propose a six-step solution comprising Vehicle Detection, Feature Extraction, Single- Camera Vehicle Tracking, Re-Identification, Movement Matching, and Multi-Camera Vehicle Counting. Finally, we adapt an evaluation metric …

Two-Step Hierarchical Multi-Camera People Tracking, Eerina Haque, Eric Huang, Sihang Li

Computer Science and Engineering Senior Theses

The possibility of an efficient and accurate solution for multi-camera people tracking (MCPT) is enabled by the improvement of computing power and the advancement of machine learning technologies. The problem of multi-camera people tracking serves as a cornerstone of real-world applications such as video surveillance or warehouse automation. The current solutions for MCPT suffer from problems such as appearance inconsistency, object occlusion, etc. Our work targets tackling the challenges faced by modern MCPT algorithms to bring a more robust, efficient, and accurate solution.

The Impact Of Emojis On User Engagement With Trolling Content In Online Platforms, Diya Saraf

Computer Science and Engineering Senior Theses

This thesis examines the impact of emojis on user engagement within online discussions, particularly focusing on the trolling behavior on social media platforms such as Reddit. The central problem addressed is understanding how different types of emojis—in emotional, informational, and popularity-based categories—affect user interactions and engagement in online communications. Through a robust methodological approach, combining quantitative data analysis and Random Forest regression modeling, this research meticulously analyzes emoji usage patterns and their correlations with engagement metrics like upvotes and comments.

The results highlight that emotional and popular emojis significantly enhance engagement by facilitating emotional expression and connection among users. In …

Ragu Conversational Menu Assistant: An Llm Retrieval Augmented Generation Approach, Sam Abdel, Seth Mak, Aaron Pham, Christopher Michael

Computer Science and Engineering Senior Theses

This project introduces a novel Conversational Menu Assistant leveraging Retrieval Augmented Generation (RAG) techniques within a modified Large Language Model (LLM) framework to enhance dining experiences by providing personalized menu assistance. The main innovation lies in the system’s ability to integrate up-to-date menu information from various sources, including web scraping, into its responses, thereby circumventing the limitations commonly associated with LLMs, such as the need for frequent retraining and the challenge of handling dynamic information. Our solution addresses the pressing issue of reducing the workload on restaurant servers and streamlining the ordering process by offering precise menu details, personalized recommendations …

Investigation Of Process-Structure-Property Relationships In Additively Manufactured Chopped Fiber-Reinforced Polymer Composites, Indu Modala

Theses and Dissertations

Fiber-reinforced polymer (FRP) composites are widely used in various industries because of their high stiffness-to-weight ratio. However, traditional manufacturing processes restrict the application of FRP composites to the production of parts with simple geometries. With the advent of additive manufacturing (AM), it is possible to produce topologically optimized parts with complex geometries using chopped FRPs. Fully leveraging the advantages of AM in the fabrication of chopped FRP parts requires a thorough understanding of the effect of the process parameters on the microstructure, and subsequently on the mechanical properties of the manufactured part. This research focuses on studying the process-structure-property (P-S-P) …

Characterizing The Potential For Failure In Environment Testing Due To Bolted-Joint Friction Nonlinearity And Bilinearity, Brennen Clark

Theses and Dissertations

Nonlinear behavior in systems complicates the analysis and design of many systems in engineering. In vibration engineering, typical methods such as modal analysis fail or require significant adjustment in the presence of nonlinearity. Understanding and modeling nonlinear behavior is becoming more important in many modern engineering applications. One area that is relatively unexplored is how nonlinearity affects environment testing. This can cover a wide variety of subtopics, but this thesis focuses on failures that can occur in a system which are not predicted by corresponding linearized systems. To further limit the scope of this work, and to provide a context …

Evaluating Computational Predictions Of Magnetic Resonance Acoustic Radiation Force Imaging For Breast Cancer Focused Ultrasound Surgery, Chloe K. Nelson

Theses and Dissertations

Purpose: In magnetic resonance-guided focused ultrasound (MRgFUS) therapies performed in highly heterogeneous tissues such as the breast, the focal location must be located and characterized to guide successful treatments of tumors. Treatment time can be minimized by a priori prediction of the focal location through computational models. The purpose of this work is to evaluate numerical simulations of focused ultrasound (FUS) on their predictions of the focal location. Those simulations are compared to clinical magnetic resonance acoustic radiation force imaging (MR-ARFI) data collected during in vivo treatment of breast tumors. Methods: The focal location was evaluated prior to MRgFUS treatment …

Specification, Enforcement, And Measurement Of Integrity Policies, Kevin Dennis

USF Tampa Graduate Theses and Dissertations

The first step to improving an organization's security posture is to define the organization's security goals. At a technical level, these goals are expressed as security policies. Security policies are predicates over programs, that return true or false if the program adheres to the policy. Defining these policies correctly is thus essential to ensuring the overarching security goals are met, but it is often quite difficult to translate human-oriented goals into their technical policy counterparts. In addition, these policies must be specified so that they are enforceable while minimizing false positives and false negatives. Integrity policies, which specify how data …

Ocean Rain Detection And Wind Retrieval Through Deep Learning Architectures On Advanced Scatterometer Data, Matthew Yoshinori Otani Mckinney

Theses and Dissertations

The Advanced Scatterometer (ASCAT) is a satellite-based remote sensing instrument designed for measuring wind speed and direction over the Earth's oceans. This thesis aims to expand and improve the capabilities of ASCAT by adding rain detection and advancing wind retrieval. Additionally, this expansion to ASCAT serves as evidence of Artificial Intelligence (AI) techniques learning both novel and traditional methods in remote sensing. I apply semantic segmentation to ASCAT measurements to detect rain over the oceans, enhancing capabilities to monitor global precipitation. I use two common neural network architectures and train them on measurements from the Tropical Rainfall Measuring Mission (TRMM) …

Hardware Acceleration Of Numerical Methods For Solving Ordinary Differential Equations, Soham Bhattacharya

Theses and Dissertations

Along with the advancement in technology, the role of hardware accelerators is increasing consistently, delivering advancements in scientific simulations and data analysis in scientific computing, signal processing tasks in communication systems, matrix operations, and neural network computations in artificial intelligence and machine learning models. On the other hand, several high-speed computer applications in this era of high-performance computing often depend on ordinary differential equations (ODEs); however, their nonlinear nature can present a challenge to obtaining analytic solutions. Consequently, numerical approaches prove effective in delivering only approximate solutions to these equations. This research discusses the implementation of a customized hardware accelerator …

Investigating The Impact Of Inverter-Based Resources On Power Grid Dynamics, Ratik Mittal

USF Tampa Graduate Theses and Dissertations

This dissertation explores the stability challenges posed by integrating Inverter-Based Resources (IBR) into power grids, particularly focusing on two major scenarios: IBRs connected to weak grid interconnections and their performance in series-compensated networks. With the increasing dependency on renewable energy sources, ensuring the stability of these grids is crucial. A multilayered investigative approach is employed, utilizing Electromagnetic Transient Simulations that model grid systems interfaced with IBRs. These simulations are pivotal as they emulate real-world stability issues and provide a foundational understanding of grid interactions. In this dissertation two major types of IBR control are modeled and analyzed: Grid Following Control …

Design And Characterization Of 3d-Printed Hydrogel Lattices With Consistent Structural And Mechanical Anisotropy, Daniel Yoon

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis explores the use of 3D printing to fabricate soft hydrogel lattice structures with consistent properties, including varying levels of mechanical anisotropy. Magnetic resonance elastography (MRE) is a non-invasive imaging tool to estimate and characterize the mechanical properties of tissue. MRE “phantoms” (physical surrogate models) have been used to assess how well MRE can measure and estimate mechanical properties. While gel phantoms generally simulate brain tissue, almost all have been isotropic. Prior studies have shown that white matter brain tissue is structurally and mechanically anisotropic. To validate anisotropic MRE, phantoms with controllable, reproducible anisotropic material properties are needed. This …