Engineering Commons^™

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 …

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 …

Water Quality Impacts Of Recycling Nutrients Using Organic Fertilizers In Circular Agricultural Scenarios, W. Lisenbee, A. Saha, P. Mohammadpour, R. Cibin, Jason Philip Kaye, C. Grady, Indrajeet Chaubey

Biological and Agricultural Engineering Faculty Publications and Presentations

CONTEXT

OBJECTIVE

METHODS

Exploring Differences In Perceived Learning For Students In Online Versus Face-To-Face Collegiate Pilot Ground Schools: A Quantitative Causal-Comparative Study, Christopher Komsa

Doctoral Dissertations and Projects

The purpose of this quantitative, causal-comparative study was to determine if there was a difference in the perceived learning of students completing online versus face-to-face collegiate pilot ground schools. Higher education institutions with pilot training programs are highly invested in student success and Federal Aviation Administration (FAA) compliance. A growing number of students are taking online courses in college, and this shift was accelerated by the COVID-19 pandemic. Perceived learning was quantified using a web-based survey that collected perceived learning data as measured by the Cognitive, Affective, and Psychomotor (CAP) Perceived Learning Scale. A sample of 86 students at University …

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, …

Stretching The Limits Of Mri—Stretchable And Modular Coil Array Using Conductive Thread Technology, Folk W. Narongrit, Thejas Vishnu Ramesh, Joseph V. Rispoli

Purdue University Libraries Open Access Publishing Fund

Objective: We propose a modular stretchable coil design using conductive threads and commercially available embroidery machines. The coil design increases customizability of coil arrays for individual patients and each body part. Methods: Eight rectangular coils were constructed with custom-fabricated stretchable tinsel copper threads incorporated onto textile. Tune, match, and detune circuits were incorporated on the coil. A hook-and-loop mechanism was used to attach and decouple the modular coils. Phantom and in vivo scans at various anatomical flexion angles were acquired to highlight performance, and a temperature test was performed to verify safety. Results: In vivo MRI experiments demonstrate high sensitivity …

Enhancing Contractor Selection Through Fuzzy Topsis And Fuzzy Saw Techniques, Mohammadsoroush Tafazzoli, Ayoub Hazrati, Kishor Shrestha, Krishna Kisi

Civil Engineering & Construction: Faculty Publications

Contractors play an integral role in construction projects, and their qualifications directly impact various aspects of a project’s success. The unbiased selection of contractors is a challenge in the construction industry worldwide, particularly in public projects where impartiality in the final selection is essential. Numerous factors must be considered when evaluating contractors, making the selection process challenging for the human brain. This paper introduces and compares two methods for assessing contractor prequalification by applying the fuzzy theory. The idea is to facilitate using human judgments in a mathematical system for decision-making with regard to selecting contractors. The method is based …

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 …

California 4-H Computer Science Education Pathway, Steven M. Worker, Roshan Nayak, Fe Moncloa

Journal of Extension

Young people need digital competency and confidence to effectively harness computing power to solve problems and design solutions; a core component is improving young people’s computational thinking. Unfortunately, access to computer science education is lacking for all youth, and in particular for youth who live in lower-income households, who are Black or Latino, or live in rural areas. With funding from Google, through the National 4-H Council, California 4-H embarked on a three-year project to build the capacity of 4-H professionals, volunteers, and teenagers to facilitate computer science education with youth. Our programming was effective as assessed with survey methodology. …

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) …

Turbine Cooling System With Energy Separation, James L. Rutledge, Matthew N. Fuqua, Carol M. Bryant

AFIT Patents

A method and system for cooling an engine and/or vehicle using energy separation is disclosed herein. An energy separation device is operable for separating a compressed gaseous coolant stream into a first relatively cooler coolant flow stream and a second relatively hotter coolant flow stream. The relative cooler coolant flow stream is directed to a first region requiring increased cooling and the relative hotter coolant flow stream is directed to a second region requiring lower cooling than the first region in the engine or vehicle.

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 …

Extreme Value Statistics Analysis Of Process Defects In Additive Manufacturing Materials, Ayorinde E. Olatunde, Kristen Hernandez, Austin Ngo, Arafath Nihar, Thomas G. Ciardi, Rachel Yamamoto, Pawan K. Tripathi, Roger H. French, John J. Lewandowski, Anirban Mondal

Faculty Scholarship

Fatigue and fracture studies focused on process defects that occur in Additive Manufacturing (AM) materials have shown that defect populations possess features which are better measured with extreme value statistics (EVS). In AM alloys, defect occurrences increase with material volume. This situation facilitates the need to model process defects in the path of fatigue crack growth with suitable statistical tools, such as EVS, which is more cost-effective when compared to destructive experiments. The application of EVS on defect space features helps determine the difference in defects present on fracture surfaces. As the fatigue quality of any material depends on its …

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 …

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 …

Editorial: Mitral Valve Disease: Mechanisms To Therapies, Maria Carmo Nunes, Hoda Hatoum, Alison M. Pouch, Muralidhar Padala

Michigan Tech Publications

No abstract provided.

Detection Of Wintertime Green Vegetated Cover Using Object-Based Classification With Open-Source Remote Sensing And Geospatial Technologies, Jae Sung Kim, Sara P. Syswerda, Sigrid D. P. Smith

Michigan Tech Publications

It is important to detect wintertime green vegetated cover (WGVC), since it includes cover crop information, which is one of the most important agricultural best management practices used today. Related to this, cover crop area, which is part of WGVC, has been estimated using survey methods traditionally, but remote sensing can be used as a more time- and cost-effective assessment. Previously developed pixel-based methods to assess cover crops using remote sensing can have a salt-and-pepper effect, which lowers classification accuracy. Therefore, object-based classification was applied to estimate the spatial distribution of WGVC across the entire state of Delaware. To reduce …

Spectral Behavior Of Fiber Bragg Gratings During Embedding In 3d-Printed Metal Tensile Coupons And Cyclic Loading, Farid Ahmed, Md Shahriar Forhad, Mahmudul Hasan Porag

Manufacturing & Industrial Engineering Faculty Publications

Additive manufacturing (AM) enables the spatially configurable 3D integration of sensors in metal components to realize smart materials and structures. Outstanding sensing capabilities and size compatibility have made fiber optic sensors excellent candidates for integration in AM components. In this study, fiber Bragg grating (FBG) sensors were embedded in Inconel 718 tensile coupons printed using laser powder bed fusion AM. On-axis (fiber runs through the coupon’s center of axis) and off-axis (fiber is at 5° and 10° to the coupon’s center of axis) sensors were buried in epoxy resin inside narrow channels that run through the coupons. FBGs’ spectral evolutions …

New Generation Graphenes In Cement-Based Materials: Production, Property Enhancement, And Life Cycle Analysis, Sahil Surehali, Sayee Srikarah Volaity, Aswathy Simon, Ranjith Divigalpitiya, Aditya Kumar, Narayanan Neithalath

Materials Science and Engineering Faculty Research & Creative Works

Several studies have explored the use of graphene to improve the properties of cement-based materials. However, most commercially available graphenes are expensive, not amenable to mass production, and have high embodied energy and emissions, making their use in concrete less attractive, despite the beneficial mechanical property attributes. This paper discusses the use of two novel graphene types, fractal graphene (FG) and reactive graphene (RG), obtained through a cost-effective and scalable detonation synthesis, in cement-based materials. FG and RG are sheets containing 6-10 layers, with lateral dimensions of 20-50 nm and a z-axis thickness of RG, when added at very small …

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 …

A Country-Level Primary-Final-Useful (Cl-Pfu) Energy And Exergy Database: Overview Of Its Construction And 1971–2020 World-Level Efficiency Results, Paul E. Brockway, Matthew Kuperus Heun, Zeke Marshall, Emmanuel Aramendia, Paul Steenwyk, Thomas Relph, Michelle Widjanarko, Jeonghoo (James) Kim, Anjana Sainju, Julian Irtube

University Faculty Publications and Creative Works

Societal exergy analysis examines the flows of energy and exergy through societies, from primary (e.g. oil) to final (e.g. gasoline) to useful (e.g. propulsion) energy stages. By extending the study of energy to the useful stage, new insights into the under-represented role of energy in economic growth have been made. However, currently (a) country coverage is patchy and incomplete, (b) available data are based on varying methods and assumptions including efficiencies based on economic rather than engineering data, and (c) datasets are constructed using piecemeal computational approaches. To address these gaps, we construct a country-level primary-final-useful (CL-PFU) energy and exergy …

Enhancing Urban Parking Efficiency Through Machine Learning Model Integration, Sai Sneha Channamallu, Sharareh Kermanshachi, Jay Michael Rosenberger, Apurva Pamidimukkala

Open Initiatives Grant Funded Publications-Archive

An increase in vehicular traffic and a scarcity of parking spaces are creating significant challenges for urban parking management. This study aims to tackle these issues that escalate congestion and pollution and decrease urban productivity, by utilizing machine learning models to accurately predict parking space availability and categorize occupancy levels. It employs a dataset from a college campus garage collected from January 2022 to June 2023 and analyzes the performance of random forest, decision tree, linear regression, and support vector models by comparing them, using multiple evaluation metrics. The results revealed that the random forest model was the most reliable, …