Engineering Commons^™

Research On Robot Dynamic Obstacle Avoidance Method Based On Improved A* And Dynamic Window Algorithm, Yan Zhang, Binghua Li, Tao Huo, Rong Liu

Journal of System Simulation

Abstract: Aiming at the problems that the traditional A* algorithm has too many extension nodes and path turning points, and can't deal with dynamic obstacles in complex environment, a robot obstacle avoidance method combining improved A* algorithm and DWA algorithm is proposed. The A* algorithm improves the neighborhood expansion method and effectively avoids the problem of redundant nodes in the classical four-neighborhood expansion and the path through the obstacle in the eight-neighborhood expansion. A quadrant selection method is proposed, which can effectively reduce the number of extended nodes in the path search process. The redundant point elimination strategy is proposed …

A Drl⁃Based Approach For Distributed Equipment Nodes Selection, Ziyi Wang, Kai Zhang, Dianwei Qian, Yuzhen Liu

Journal of System Simulation

Abstract: Aiming at the problem of insufficient solution speed and poor generalization of traditional algorithms in large-scale scenarios, this paper intelligently solves the large-scale distributed equipment system preference problem based on deep reinforcement learning. According to the characteristics of distributed equipment system combat, using the complex network to its graph form modeling, and based on the attention mechanism to the equipment between the connecting edge relationship for the characterization, in order to build a distributed equipment system digital simulation environment. Simulation results show that compared with the genetic evolutionary algorithm, the obtained model has obvious advantages in terms of solution …

Effect Of Cage Eccentricity On Moment Capacity Of Drilled Shafts, Jason Schaefer Steinbach

USF Tampa Graduate Theses and Dissertations

During the construction of drilled shafts, reinforcement cages can be inadvertently placed eccentrically. Current codes, such as ACI 318 and AASHTO LRFD Bridge Specifications, assume there is little impact from such movements within the drilled shaft or that cage centering provisions are sufficiently robust. This thesis will explore the impact that reinforcement cage eccentricity has on the bending capacity of drilled shafts and propose new strength reduction and resistance factors for tension-controlled failure in drilled shafts.

A total of 208 drilled shafts across eleven counties within the state of Florida were tested using thermal integrity profiling to identify the worst …

Life Cycle Costs Of The Little Cottonwood Canyon Transportation Scenarios Under Varied Economic Conditions And Analysis Periods, Emma Reeves, Dane Richards, Darrell Sonntag

Faculty Publications

Abstract— This study revisits the life cycle cost analysis (LCCA) of the Utah Department of Transportation’s (UDOT) proposed gondola project, using recommended best practices for selecting the discount rate, life cycle periods, and conducting a sensitivity analysis on cost projections. We reanalyze the life cycle costs of the five alternatives in the Environmental Impact Statement (EIS) (Scenario 1) across different economic scenarios, and subsequently, we reanalyze the life cycle costs of the Scaled Enhanced Bus (Scenario 2) and Enhanced Bus to Gondola (Scenario 3) from UDOT’s Revised LCCA, using construction dates in the record of decision (ROD) and considering various …

Towards Sustainable Manufacturing: A Framework For Resource Conservation And Waste Mitigation, Mahmood Talal Sultan

Thesis/ Dissertation Defenses

The manufacturing industry drives economic expansion, but it also contributes significantly to environmental change and shortages of resources. Therefore, the transformation to sustainable manufacturing has become an urgent need, driven by worldwide efforts to address climate change, minimize waste, and protect valuable assets. This thesis develops a robust framework tailored to the manufacturing sector, focusing on resource conservation and waste reduction. The framework is built on the identification and categorization of Key Performance Indicators (KPIs) and assessment tools, which address five major implementation challenges: complex supply chains, regulatory barriers, economic challenges, technological limitations, and social and cultural challenges.

To build …

Artificial Intelligence In Surveillance And Privacy, Elizabeth D. Brasher

NEXUS: The Liberty Journal of Interdisciplinary Studies

This paper attempts to provide insight into the new and developing world of artificial intelligence and its integration into surveillance technologies. These technologies being implemented by the government, retail companies, healthcare organizations, and more, all raise ethical questions and implications addressed in this article; other topics, such as the integration of Christian ethics and responsibilities, are also explored.

Empowering Tanzanian Education: Personalized And Accessible Test Preparation, Brian Wiebe, Shiv Jhalani

Computer Science and Engineering Senior Theses

Only 20% of students performed well enough on their secondary exams to continue their A-level studies. This challenge exists due to a lack of resources, classroom overcrowding, and absenteeism of the instructors. The project focuses on improving the pass rate for these national exams; we have built an intelligent quiz generating platform that helps Tanzanian students prepare more effectively for exams by meeting user needs including active recall, answer explanations, increasing difficulty, and filtered studying. Students can select the subject, form level, topic, and the difficulty level, and the platform provides different types of questions, including true/false, multiple choice, and …

Bridging Virtual Robots And Physical Tasks Via Augmented Reality, Xiangfei Kong

USF Tampa Graduate Theses and Dissertations

Entry to human-robot interaction research, e.g., conducting empirical experiments, faces a significant economic barrier due to the high cost of physical robots, ranging from thousands to tens of thousands. This cost issue also severely limits the field’s ability to replicate user studies and reproduce the results to verify their reliability, thus offering more confidence to incorporate these findings. Although virtual reality (VR) user studies present a potential solution, it is unclear whether we can confidently transfer the findings to physical robots and physical environments because VR isolates both the physical robot and the physical world where robots operate. To address …

Embedding-Based Deep Learning Frameworks For Multimodal Oncology Data Integration, Aakash Gireesh Tripathi

USF Tampa Graduate Theses and Dissertations

This dissertation presents a cohesive set of novel frameworks developed to address critical challenges in oncology data integration, representation learning, and clinical information extraction. The work encompasses four interconnected projects: MINDS (Multimodal Integration of Oncology Data System), HoneyBee (Harmonized ONcologY Biomedical Embedding Encoder), LLM Extraction (Large Language Model-based Extraction from Pathology Reports), and EAGLE (Embedding Analysis for Generalized Learning in Oncology). Together, these systems enable the unification of diverse cancer data modalities—from genomics and clinical records to histopathology images and radiological scans—creating a robust foundation for advanced machine learning applications in precision oncology. By addressing key barriers in data accessibility, …

Examining Green And Chemical Methods For Zero-Valent Iron Nanoparticle Synthesis In Heavy Metal Adsorption, Juan Ferro-Falla, Lewis Stetson Rowles, Farith Diaz Arriaga, Jaime Plazas-Tuttle

Civil Engineering & Construction: Faculty Publications

The increasing concern over heavy metal contamination in water has necessitated the development of sustainable and efficient treatment methods. This study compares two synthesis approaches for zero-valent iron nanoparticles (nZVI) for cadmium, chromium, and arsenic removal: chemical reduction using sodium borohydride and green synthesis utilizing cocoa husk extracts combined with hydrothermal carbonization (HTC). Chemically synthesized nZVI exhibited high initial removal efficiencies (>98%), though desorption effects occurred over time due to particle aging. In contrast, green-synthesized nZVI, stabilized by a carbon matrix, maintained consistent removal efficiencies above 98% for 120 h under acidic conditions, showcasing superior stability and reactivity. Characterization …

Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofrendly Systems, Noora Al Mansoori

Thesis/ Dissertation Defenses

Traditional experimental approaches in industrial processes, such as Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, thermogravimetric analysis (TGA), and well-drilling operations, are often constrained by time, cost, and operational limitations. This research explores the application of data-driven Machine Learning (ML)-based predictive modeling to improve efficiency and reduce dependency on resource-intensive experimentation. The study develops ML models for three distinct processes: FTIR intensity prediction of bitumen thermal cracking products, thermal degradation of Medium-Density Fibreboard (MDF) using TGA data, and Rate of Penetration (ROP) prediction in petrochemical industry. Six algorithms: Linear Regression (LinReg), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Gradient …

Engineering Bio-Based Poly (Ethylene Furanoate) Blends And Nanocomposites, Safa Fadl Eldin Mohamed

Thesis/ Dissertation Defenses

The growing demand for sustainable materials has directed attention toward bio-based polymers such as poly(ethylene furanoate) (PEF), a 100% bio-derived alternative to PET. While PEF offers excellent gas barrier and thermal properties, its limited mechanical strength restricts its use. This study explores polymer blending and nanocomposite strategies to enhance PEF’s mechanical and electrical performance.
Blending PEF with linear low-density polyethylene (PE) using reactive compatibilizers (SEBS-g-MA, PE-g-MA) significantly improved ductility and tensile toughness. Interfacial reactions between PEF and compatibilizers transformed the blend morphology, resulting in improved flexibility suitable for packaging applications.
Electrically conductive composites were developed by localizing graphene nanoplatelets (GNP) …

Knee-Thigh-Hip Impact In Children: Effects Of Age And Impact Velocity, Mohammad Ziad Turki

Thesis/ Dissertation Defenses

Brief introduction: This thesis examined the crash impact injury outcomes of the knee-thigh-hip complex (KTH) in children based on age and impact velocity using computational modelling. Child occupant (3YO, 6YO, 10YO) Total Human Body Model for Safety (THUMS) models developed by Toyota were used to evaluate the effects of age and impact velocity on pediatric KTH crash impact response. Aims: The main objectives of this thesis are to analyze the effect of child age and impact velocity on KTH crash impact response. Methods: The knee impact simulations were performed based on different impact velocities (1.2, 3.5, 7.2, …

An Integrated Geophysical Approach For Estimating The Depth Of Mineral Potential In Some Part Of Basement Complex Terrain Southwestern Nigeria, Hamid Titilope Oladunjoye, Joseph Coker, Niyi-Ola Adebisi, Omolara Abosede Adenuga, Sofiat Adetomilola Adekoya, Aderemi Alabi, Abisola Akinmoladun

Al-Bahir

Effective mineral exploration in a basement complex necessitates precise delineation of overburden thickness and mineral potential within the Basement Complex terrain. This study examined the subsurface geology and assesses the abundance of prospective mineral deposits within the study area The objective of the study was to outline the overburden thickness and infer mineral potential using integrated ground magnetic and electrical resistivity geophysical methods. The electrical resistivity method unraveled the litho-stratigraphic sequence as surmised from geo-electric layers. Consequently, the mineralization of the basement delineated was characterized by the magnetic method. The acquired data were processed using WINRESIST and Oasis Montaj respectively. …

Cross-Cultural Inspiration Coach, Romeo Nickel, Veronica Flores, Rahul Rani, Andrew Yang

Computer Science and Engineering Senior Theses

Personal inspiration and motivation are fundamental drivers of well-being and growth, yet current digital wellness solutions predominantly reflect Western perspectives, failing to address the diverse cultural contexts through which inspiration manifests globally. This thesis presents the development of an Inspirational Coach platform that leverages artificial intelligence to deliver culturally-adaptive personal development content. The system employs a fine-tuned Llama 3.1 8B model using Low-Rank Adaptation (LoRA) techniques to generate personalized motivational content that incorporates users’ cultural backgrounds, personal themes, and individual preferences.

The platform integrates four core features within a comprehensive React-based web application: guided journaling with mood tracking, goal setting …

Teaching Computer Science Through An Educational Game, Aidan Walker, Matthew Leonard, Grant Goldman

Computer Science and Engineering Senior Theses

In our ever-evolving technological landscape, it is becoming more and more important for students of all ages to have at least a basic concept of coding fundamentals. It’s not just the basic knowledge of how to code; knowing important coding concepts is just as important. To help introduce these concepts to young students, we developed an educational game in the Roblox platform aimed at teaching foundational programming concepts—specifically recursion—to young learners through interactive and engaging gameplay. Leveraging Roblox’s accessibility and popularity among younger audiences, the game introduces players to recursive thinking in a visual and intuitive manner. Players control a …

Self Driving Robot Car, Eric Hicks, Ruby Huynh

Computer Science and Engineering Senior Theses

In the real world, vehicular crashes are the result of human error and inadequate reaction time and are often deadly. Due to the issue of accidents being frequent occurrences, using machine learning to drive vehicles has quickly become a relevant topic as it could potentially become a way to minimize fatalities and damages. Thus, the project aims to approach self-automation with the focus on maximizing the vehicle’s performance and the machine’s ability to make the best decisions within that time.

Today’s self-driving cars use radar or cameras as well as digital signal processing algorithms to sense the environment while using …

Tcras: Traffic Control Risk Analysis System, Owen Matejka

Computer Science and Engineering Senior Theses

Traffic intersections represent critical points of conflict in urban transportation networks, with over 40,000 traffic-related fatalities occurring annually in the United States alone. Traditional intersection monitoring systems, based on timer controls and inductive loop detectors, lack the sophisticated detection capabilities needed to address modern traffic safety challenges. This thesis presents the Traffic Control Risk Analysis System (TCRAS), a low-cost, computer vision-based solution that democratizes access to advanced intersection monitoring capabilities. TCRAS leverages edge AI processing through Hailo neural network accelerators combined with open-source computer vision algorithms to provide comprehensive intersection analysis. The system performs real-time multi-class object detection and tracking …

A Universal Lstm Stock Price Predictor Utilizing News Sentiment Analysis And Technical Indicators, Kelly Zhou, Zhirong Wang

Computer Science and Engineering Senior Theses

The stock market is influenced by a complex interplay of factors, including historical price trends, technical indicators, news sentiment, and macroeconomic conditions. Traditional stock prediction models typically focus on a single stock, limiting their ability to capture broader market relationships. Investors require a model that can accurately forecast price movements across multiple stocks to optimize trading decisions.

We propose a universal stock prediction model that leverages relationships across all S&P 500 stocks. Unlike traditional single-stock models, our approach utilizes a multi-stock LSTM architecture trained on a combination of historical stock prices, technical indicators, and news sentiment. The model is designed …

Preserving Yucatán’S Agricultural Heritage: A Mobile App For Agricultural Sustainability, Fernando Rojas, Jason Serrano, Kavya Sharma

Computer Science and Engineering Senior Theses

We developed a mobile application that preserves Yucatán’s agricultural heritage and supports local farmers, while addressing the urgent need for the technology-driven integration of Mayan agricultural knowledge, specifically the Milpa system, into an accessible mobile platform. Our objective was to create an intuitive, culturally appropriate, and low-technology resource to support farmers in making informed, sustainable agricultural decisions, regardless of their internet connection. We saw this as critical for enhancing agricultural practices in Yucatán and beyond. We accomplished this by creating a trilingual (Spanish, English, and Yucatec Maya) mobile app with features such as agrarian cycle information, mapping and location services, …

Adsorption And Electron Transfer Of Metal-Reducing Decaheme Cytochrome Protein Mtrf On Iron Oxide Nanoparticle Surfaces, Jiahuiyu Fang, Pranab Sarker, Xiaoxue Qin, Shuting Zhang, Size Zheng, Tao Wei

Faculty Publications

Dissimilatory metal-reducing bacteria (DMRB) transfer electrons to extracellular metal oxides via a multiheme cytochrome network. Coupling DMRB with iron oxide nanoparticles (NPs) enables continuous redox processes for various applications such as bioremediation and bioenergy. The conformation of the terminal decaheme cytochrome MtrF on the surface critically influences electron transfer (ET) efficiency. In this work, we used molecular dynamics simulations and master equations to study MtrF adsorption on 3.6 and 6.0 nm α-Fe2O3 NPs and its steady-state ET in water. Our study shows that the heme cofactors can have strong electrostatic interactions with iron oxide NP surfaces, promoting protein adsorption and …

Characterization Of Ultra-High-Speed Friction Stir Welds Made In Thin Sheet Aa6061-T4 Material, Todd Grant Lainhart

Theses and Dissertations

Friction stir lap welding (FSLW) of thin aluminum sheets in industry and in research has faced challenges in weld quality that limit welding speeds. Interfacial defects such as hooking and thinning are common defects that appear at the interface of FSLW, and researchers and process operators have traditionally reduced process parameters such as feed rate and spindle rotation to fully eliminate the defects. While such measures are successful in creating fully consolidated FSLW, feed rates for FSLW have stagnated around 1 mpm with the fastest feed rates recorded at 3 mpm, making it difficult for manufacturers to implement FSLW in …

Diversifying Cybersecurity: Evaluation Of An Internet Of Things (Iot)-Based Cybersecurity Training Course Designed To Bridge The Diversity Gap, Maureen Namukasa, Bhoomin B. Chauhan, Carlie Swords, Curtice Gough, Weronika Dymanus, Catherine Diresta, John Vitali, Vivek Sharma, T J. Oconnor, Meredith Carroll

Aeronautics Faculty Publications

This study aimed to evaluate the effectiveness of an eight-module Cybersecurity course at increasing the learning outcomes of middle and high school students with little to no experience, including underrepresented minorities (URMs) in Cybersecurity. Twice we administered and evaluated the Cybersecurity course, which included hands-on IoT-based activities, utilizing collaborative learning, scaffolding, and representation-based learning strategies. Using a quasi-experimental, within-subjects, repeated measures design, each participant experienced a pretest, the course, and a post-test to evaluate the impact on learners’ self-efficacy, interest, and knowledge. The results revealed that (1) at pre-test, female (p = .001) and in one course administration minority …

Practicality Of Implementing Sub-Clause 8.4 [Advance Warning] Of The Fidic 2017 Red Book In Egypt, Gehad Ibrahim

Theses and Dissertations

Disputes in construction projects can cause cost and time overruns that can be detrimental to the parties involved and to the project. Several measures have been advocated by the industry’s practitioners in an attempt to avoid disputes and their adverse impacts. One of these measures is the introduction of advance warning sub-clauses in construction contracts, where the contracting parties play a proactive and collaborative role in warning each other of potential adverse impacts to the project. Such clauses have been in the NEC suite of standard construction contracts for decades and have recently found their way to the 2017 edition …

Quantifying Wellbore Effects During Co2 Sequestration In A Saline Aquifer, Uzoma Johnpaul Ajugwe

USF Tampa Graduate Theses and Dissertations

Carbon capture and storage (CCS) is a strategy for mitigating climate change by reducing greenhouse gas emissions from large stationary sources like fossil-fuel-fired power stations. One method of CCS involves carbon dioxide (CO2) sequestration in deep saline aquifers, where supercritical CO2 is injected into an aquifer. The success of such projects depends on accurate predictions of CO2 behavior within the subsurface, which are obtained through numerical simulations.

TOUGHREACT, a renowned simulation tool, models subsurface fluid flow, geochemical interactions, and solute transport, providing insights into the feasibility of CO2 sequestration projects. A critical aspect of these simulations is the apportioning of …

Bilingual Buddy, Adian Alvarado, Farhaan Pishori, Luis Villalta, Andrea Yao, Ekam Singh

Computer Science and Engineering Senior Theses

Bilingual students often face challenges in mathematics not due to a lack of ability, but because of linguistic barriers that hinder their understanding of math-specific terminology and consequently their problem-solving language ability. This project addresses that issue through the development of a mobile application designed to support English language acquisition in the context of mathematics for Spanish-speaking students. Rather than teaching mathematical concepts directly, the app focuses on vocabulary, syntax, and contextual comprehension through scaffolded lessons, gamified elements, and an integrated AI chatbot.

Built using Flutter for cross-platform compatibility, the app prioritizes accessibility, simplicity, and engagement for young users. Ethical …

Getting An Airman Medical Certificate With Cerebral Palsy, Stefan Crisp

Honors Theses

This paper aims to document the personal experience of Stefan Crisp attempting to gain an airman medical certificate. It also aims to expose the airman medical certificate process for people with cerebral palsy in the United States. Stefan Crisp, who has cerebral palsy, attempted to gain an airman medical certificate through three attempts across multiple years. Research was done to compare the United States Federal Aviation Administration (FAA) with the United Kingdom's Civil Aviation Authority (CAA) to reveal similarities and differences between accessibility and requirements. Despite successfully navigating through Title 14 Code of Federal Regulations Part 67, Stefan was unable …

Networking For Power Grid And Smart Grid Communications: Structures, Security Issues, And Features, Biswash Basnet, Varsha Sen

Graduate Student Scholarship

The evolution from traditional to smart grid systems has radically changed communication architectures. It enables secure, efficient, and resilient energy infrastructures. Unlike the centralized, unidirectional communication practices typical of traditional grids with minimal automation, modern smart grids use tiered, bidirectional networks allowing real-time control, integration of distributed energy resources (DER), and active consumer participation. The drive for this development arises from the growing use of renewable energy resources, electric vehicles, and sophisticated digital metering technologies. End-to-end communication architectures now underpin grid reliability, interoperability, and cybersecurity. This research explores the end-to-end architecture of traditional and smart grids, including access technologies, protocol …

New Attack Surfaces Against Emerging Cloud And Web Based Infrastructures And Defenses, Junjie Xiong

USF Tampa Graduate Theses and Dissertations

Emerging network security threats, ranging from cloud-based infrastructure attacks to web-based content subversion, pose significant challenges to modern computing environments. In this dissertation, we explore two novel attack vectors that disrupt both cloud-based infrastructures and web-based content systems.

In this dissertation, we first introduce the Warmonger attack, a novel attack vector that can cause denial-of-service between a serverless computing platform and an external content server. The Warmonger attack exploits the fact that a serverless computing platform shares the same set of egress IPs among all serverless functions, which belong to different users, to access an external content server. As a …

Surface Acoustic Wave Energy Driven Degradation Of Aqueous-Based Methylene Blue, Xieqi Gu

USF Tampa Graduate Theses and Dissertations

This study investigates the degradation behavior of methylene blue (MB) under surface acoustic wave (SAW) excitation, focusing on the effects of power, frequency, hydrogen peroxide (H2O2) concentration, and the use of perovskite oxide catalysts (LFO and LSF). Initial experiments showed that MB concentrations remained stable under SAW at ~10 MHz and ~30 MHz with power levels of 1–3 W in the absence of H2O2, though solution temperatures increased. Upon introducing 1 M H2O2, MB degradation followed a second-order rate constant, with degradation rates increasing with power and significantly higher at ~30 MHz, suggesting that both frequency and power enhance free …