Engineering Commons^™

Task Management Application, Dhaval Chaturbhai Hirpara

Electronic Theses, Projects, and Dissertations

The Task Management Application is a web-based platform designed to facilitate efficient task and project management, similar to other Project Management Tools like Jira, Trello, ClickUp, Wrike, Zoho Projects, and Asana. The application features three distinct roles: Administrator, Project Manager, and Employee, each with specific functionalities and permissions to streamline workflow.

Administrator: This role encompasses comprehensive project oversight, including adding, viewing, and managing project managers, supervising ongoing projects, and viewing employee details.

Project Manager: Project Managers can manage employees, assign tasks, and oversee project progress effortlessly.

Employee: Employees have dedicated functionalities to view and manage tasks assigned …

Understanding The Challenges To Robotic-Assisted Surgery Adoption From The Perspectives Of The Human-Robot Interaction, Built Environment, And Training, Patrick A. Fuller

All Theses

Introduction: Robotic-assisted surgery (RAS) is a form of minimally invasive surgery that is increasing in both its adoption and development due to many perceived advantages such as tremor reduction and motion scaling. However, RAS is still relatively new and there are a variety of novel barriers and challenges to the adoption of these platforms. Objectives: This study aims to understand how the integration of RAS platforms impacts the interactions and outcomes of interactions between surgical team members to explore the barriers from three aspects critical to facilitating Robotic-assisted-surgery (RAS) adoption: the human-robotic interaction, built environment, and RAS training. Future …

Degradation Products And Microbial Communities Associated With The Conversion Of Five Long-Chain Fatty Acids Relevant For Anaerobic Co-Digestion Of Fog With Sludge, Claire Funk

All Theses

Anaerobic digestion is a technology that allows wastewater treatment plants to convert sludge to energy by recovering the biogas produced during the breakdown of proteins, carbohydrates, and lipids. Furthermore, adding fats, oils, and greases (FOG) through co-digestion with wastewater sludge can increase energy production as lipids have a higher methane yield than proteins and carbohydrates. However, adding FOG can also lead to operational problems in the digester due to the potential accumulation of certain long-chain fatty acids (LCFAs). Current research is limiting in the degradation pathways of prominent LCFAs in FOG and the microbial communities responsible for their degradation

The …

Hyperspectral Image Classification Of Bacteria Using A Deep Convolutional Neural Network, Bruce S. Vogelsberg Jr

All Theses

Hyperspectral imaging is a non-invasive imaging method capable of collecting both spatial and spectral information. However, because of the large volume of data collected, much of it is redundant or not useful for classification. Deep learning is a subset of machine learning that uses artificial neurons in a multilayered structure to learn representations from data. One of the main advantages of deep learning is the powerful feature extraction capabilities, which allow the model to learn both high- and low-level features. Convolutional neural networks are a type of deep learning model that have alternating convolutional and pooling layers capable of extracting …

Training Uav Teams With Multi-Agent Reinforcement Learning Towards Fully 3d Autonomous Wildfire Response, Bryce Hopkins

All Theses

As climate-exacerbated wildfires increasingly threaten landscapes and communities, there is an urgent and pressing need for sophisticated fire management technologies. Coordinated teams of Unmanned Aerial Vehicles (UAVs) present a promising solution for detection, assessment, and even incipient-stage suppression – especially when integrated into a multi-layered approach with other recent wildfire management technologies such as geostationary/polar-orbiting satellites and CCTV detection networks. However, there remains significant challenges in developing the necessary sensing, navigation, coordination, and communication subsystems that enable intelligent UAV teams. Further, federal regulations governing UAV deployment and autonomy pose constraints on real-world aerial testing, creating a disconnect between theoretical research …

Proportioning And Performance Of Ultra-High Performance Concrete (Uhpc) For High Friction Surface Treatment (Hfst) On Pavement And Bridge Decks, Adam R. Biehl

All Theses

High Friction Surface Treatment (HFST) is a roadway remediation technique used to improve pavement’s coefficient of friction, to enhance roadway safety. The application of HFSTs has repeatedly demonstrated the ability to significantly reduce crashes in both wet and dry conditions. Typically, epoxy-resins and calcined bauxite aggregate are used in HFST treatment. However, the high material costs and scarcity of calcined bauxite render this form of HFST an expensive and limited option for roadway rehabilitation. Therefore, the identification of alternative binders and HFST aggregates is needed for broad scale implementation. One potential alternative binder is Ultra-High-Performance Concrete (UHPC), a specialty cementitious …

Impact Of Nitrogen Species On Algal Carbon Capture, Lauren J. Todd

All Theses

Increasing global carbon emissions from fossil fuel combustion and the resulting detrimental effects of climate change have created a need for atmospheric carbon drawdown. Biological-based carbon capture not only sequesters carbon dioxide (CO₂) but also provides a sustainable source of biomass for biofuels and biomaterials. Thus, the aim of this research was to examine freshwater green algal growth with total ammoniacal nitrogen (TAN) and nitrate nitrogen (NO₃-N) sources at high pH for improving carbon capture potential. The following objectives were accomplished: nitrogen uptake was identified as simultaneous or sequential, the effect of TAN and NO_{3 …}

Advancing Unmanned Ground Vehicle Path Planning With Quantified Map Uncertainty, Israel Afriyie

All Theses

This thesis addresses the complex challenge of path planning for Unmanned Ground Vehicles (UGVs) in areas where traditional navigation systems are inadequate, such as unstructured or off-road military zones. Recognizing the limitations of current path planning algorithms, which primarily focus on optimizing for the shortest path and often fail to account for variability and risks, this research proposes an enhanced Hyperstar algorithm. This approach not only considers the fastest route but also integrates maximum delays and visibility risks into its computation, ensuring a balance between swift mission completion and concealment from adversaries.

Utilizing terrain maps and incorporating uncertainties in map …

Smart Zoning Control For Air Conditioning Systems, Octavio Gomes Diaz

Mechanical Engineering Theses

Nearly 45% of the energy consumed in residential buildings goes for Heating, Ventilation, and Air Conditioning (HVAC). Typical HVAC systems are mostly controlled by one thermostat that is usually located in the living room. This means that the HVAC system is running without consideration of the thermal conditions in the other rooms (zones), which might be colder (or warmer). Colder zones in the summer indicate that a lot of energy is wasted, and warmer zones mean that the HVAC system can’t produce a good comfort level. Therefore, zoning was introduced into relatively recent HVAC systems. Zoning in HVAC systems uses …

Exploiting Physical Side-Channel Information For Offensive And Defensive Ends, Sisheng Liang

All Dissertations

Side-channel information consists of side effects of computation that range from microarchitectural to physical phenomena. Empirical studies have demonstrated the practical exploitability of these side effects in real-world systems for malicious attacks and effective defenses. In this dissertation, we discover, analyze, and exploit certain physical side-channel information for end-to-end attacks and defense across three studies.

In the first study, we demonstrate a new DNN model extraction attack named Clairvoyance that exploits certain far-field electromagnetic signals emitted from a GPU to steal DNN models several meters away from the victim machine, even with some physical obstacles in between. Using Clairvoyance, an …

Frameworks For The Techno-Economic Assessment Of Membrane-Based Bioprocessing Platforms, Juan Jose Romero Conde

All Dissertations

This dissertation describes developing and implementing computational frameworks for simulating and optimizing purification processes in the biopharmaceutical industry. The framework performs techno-economic analyses to establish value propositions for new process alternatives, especially membrane technologies. Initially, the focus is developing a framework capable of simulating monoclonal antibody (mAb) capture using membrane and resin media in multi-column chromatography (MCC) platforms for continuous manufacturing. Subsequently, the impact of capture MCC is compared against other intensification strategies in established mAb manufacturing facilities. Finally, the framework application expands to simulate the purification of adeno-associated virus (AAV) vectors for gene therapy.

Chapter 2 details the framework …

Large-Scale Hpc-Empowered Power Electronics Modeling And Simulation In Photovoltaic Applications, Liwei Wang

All Dissertations

The rising popularity of renewable energy sources requires advanced, efficient power electronic systems for energy conversion, grid integration, and system management, thereby raising expectations for power electronics in the energy industry. The complexity of modern power electronic systems requires comprehensive simulations and in-depth analysis to predict performance accurately, but this process is impeded by prolonged simulation times. The primary objective of this dissertation is to develop a high-fidelity, high-speed event-driven simulator to tackle challenges related to mass data processing, uncertainty evaluation, as well as modeling and simulation issues in assessing the reliability of power electronics in large-scale Photovoltaic (PV) systems. …

Investigating Institutional Support For A Minority Engineering Program At A Historically White Institution, Stephanie Damas

All Dissertations

Engineering programs at historically White institutions (HWIs) often perpetuate stereotypes and racism against Black students, impacting their experiences and opportunities in the field. Minority engineering programs (MEPs) provide support and resources to minority students in engineering, challenging stereotypes and fostering positive identity development. MEPs push back on cultural norms by rejecting the stereotypical narrative of what it means to be Black in engineering. Despite their significance, MEPs face challenges in garnering institutional support and recognition within engineering departments. It is imperative to understand what institutional support for MEPs looks like to mitigate barriers identified in the literature. To address these …

Ultra High-Performance Concrete As A High Friction Surface Treatment For Pavements And Bridges, Kyle Maeger

All Dissertations

High Friction Surface Treatment (HFST) is a proven technology to reduce crashes on roadways by increasing the coefficient of friction between vehicle tires and the pavement. However, it is an expensive solution due to the high cost of the two commonly used constituent materials, calcined bauxite aggregate and epoxy resin binders.

This study evaluated the abrasion resistance performance of four alternative HFST aggregates to calcined bauxite using Los Angeles Abrasion and Micro-Deval Abrasion tests, and studied the surface texture utilizing a high-resolution laser scanner and friction utilizing the British Pendulum Test.

This study also assessed the performance of non-proprietary Ultra …

Time-Domain Line Protection In Presence Of Renewables, Prabin Adhikari

All Dissertations

Inverter based resources (IBRs) are crucial in integrating renewable energy sources into the power grid. However, their unique fault characteristics, significantly different from synchronous generators (SGs), present several challenges for existing line protection schemes at both transmission and distribution levels. These schemes, reliant on distance and directional relays designed in phasor domain, are not well-suited for IBRs. Most published literature addressing this problem concentrates on altering the control design of inverters. However, this approach faces practical limitations. Inverter controls, often proprietary, are not readily accessible to utilities, rendering the control-based solutions impractical for widespread implementation.

To address this challenge, this …

Fluid-Solid Coupled Analysis Of Biological Samples In A Flow Chamber Using Optical Coherence Tomography, Reece W. Fratus

All Dissertations

Forces from fluid flow on a tissue or cellular boundary can drive remodeling processes through mechanotransduction pathways. In most cases, the exact mechanisms are not understood, such as in marine biofilm development or vascular remodeling. To gain a better understanding of these interactions, the flow profile at a solid boundary and the mechanical changes of that solid can be coupled together to determine the impact of fluid flow on mechanical remodeling. To achieve this, optical coherence tomography (OCT) is used to image the fluid and solid simultaneously. Fluid seeded with particles can be imaged and run through a particle image …

Fundamental Study Of Nonlinear Electrophoresis, Joseph Armakan Bentor

All Dissertations

Classical electrophoretic theory describes the linear response of particles suspended in Newtonian fluids under weak electric fields. When the electric field exceeds this weak limit, a nonlinear response arises due to non-uniform surface conduction over the curved particles. This nonlinear behavior introduces dependencies on fluid and particle properties not considered in the classical theory, offering potential advantages for microfluidic particle manipulation. While this phenomenon has been extensively studied theoretically and numerically in Newtonian fluids, experimental investigations have been relatively limited.

Fluid rheology can significantly alter particle dynamics under applied electric fields. Rheological properties like shear-thinning and elasticity which are not …

Contribution Of Collagen Type I To The Mechanical Properties Of Myocardial Tissues At The Micron Level, Adam Baker

All Dissertations

Collagen is a critical component of the organization and one of the key factors contributing to the mechanical stability of the myocardium. Where cardiomyocytes actuate to contract the heart and deliver blood to the lungs and the entire body, the local collagen network must be able to support the mechanical needs of the heart by enhancing rigidity, reducing the mechanical responsibility of cells, and increasing compliance to add loading capacity during diastole. At an organ-wide level, this has been measured and modeled in many ways. At the tissue level, the mechanical properties have been evaluated using techniques such as bi-axial …

Lab To Leadership: How Do Women College Stem Students’ Classroom Experiences Inform Their Leader Identity Development?, Meredith Mcdevitt

All Dissertations

This dissertation is an exploration of leader identity development and women in science, technology, engineering, and mathematics (STEM) college academic classrooms. While there continues to be research promoting diversity in STEM professions, women remain underrepresented in STEM disciplines, leadership positions, and for this specific study, the college academic classroom. This dissertation represents an opportunity for women in STEM college students to reflect on their experiences in STEM academic spaces and communities, while self-exploring factors that shape their leader identity development. The research utilized a basic qualitative research design to understand the participant’s authentic experiences within the academic environment. Conducting semi-structured …

Base Case Shear-Wave Velocity Profiles And Non-Linear Material Property Models Of Local Site Conditions In South Carolina For Seismic Site Response Analyses, Ali Sedaghat Shirehjini

All Dissertations

This dissertation presents the development of base case small-strain shear-wave velocity ( ) profiles and non-linear materials property models of local site conditions in South Carolina for seismic site response analyses. The need to address South Carolina's seismic hazards is partly motivated by the 1886 Charleston earthquake (moment magnitude, M_w= 6.7 to 7.5). Required inputs for seismic site response analysis include profile down to a specified reference outcrop condition and non-linear material properties for each layer in the profile. Although firm rock (i.e., ≥ 2,500 ft/s) or hard rock (i.e., ≥ 9,850 ft/s) is commonly assumed for the …

Exploring The Synthesis Of Biobased And Chemically Recyclable Polysulfone Using Imine Chemistry, Vitasta Jain

All Dissertations

Plastic waste poses a major problem because of the chemical stability of these materials, leading to their accumulation in the environment and the leaching of toxic chemicals during their slow decomposition. Additionally, the use of depleting petroleum reserves for synthesis has made for an unsustainable production and risks due to use of chemicals hazardous to the environment and the individuals exposed to it.

To address these concerns, researchers have explored biobased feedstock and incorporating chemical recycling capabilities for a closed loop, sustainable process. One promising feedstock is lignin with its abundant functional groups that can be modified and utilized to …

Linear And Nonlinear Topology Optimization With Morphing Beam Networks, Andrew S. Montalbano

All Dissertations

Topology optimization (TO) is an engineering design discipline dedicated to optimizing material distribution within a given domain. In traditional gradient-based topology optimization, the solid domain is discretized into small volumetric elements. Using finite element analysis (FEA) of the structure, the gradient of the objective function with respect to the design variables (the pseudo densities) is computed, and these design variables are updated iteratively until convergence is achieved. Although gradient-based TO methods are well-established, sensitivity analyses of objective functions and constraints can be both mathematically complex and computationally intensive. The nonconvex nature of most TO problems often complicates efficient convergence. Furthermore, …

Hybrid Physics-Infused Machine Learning Framework For Fault Diagnostics And Prognostics In Cyber-Physical System Of Diesel Engine, Shubhendu Kumar Singh

All Dissertations

Fault diagnosis is required to ensure the safe operation of various equipment and enables real-time monitoring of associated components. As a result, the demand for new cognitive fault diagnosis algorithms is the need of the hour. Existing deep learning algorithms can detect, classify, and isolate faults. Still, most depend solely on data availability and do not incorporate the system's underlying physics into their prediction. Therefore, the results generated by these fault-detecting algorithms sometimes need to make more sense and deliver when tested in actual operating conditions.

Similar to diagnosis, the fault prognosis of diesel engines is paramount in numerous industries. …

An Emergency Response System To Assist The Movement Of Vehicles During Emergency Operations In Urban Transportation Networks, Jamal Nahofti Kohneh

All Dissertations

Emergency responders need to arrive at the emergency scene as soon as possible, but operating vehicles under emergency conditions can pose a risk to both the responders and other road users, potentially resulting in crashes or delays in emergency operations. In this research, an emergency response system is proposed to assist emergency and non-emergency response vehicles (ERVs and non-ERVs) during emergency operations in a connected vehicle environment. This system collects the information from connected ERVs and non-ERVs, utilizes this information as inputs in the proposed models, and sends instruction messages back to vehicles. The proposed models provide the fastest ERV …

Feasibility Assessment And Container Traffic Forecasting Of Inland Waterway Container On Barge Transportation, Fan Bu

Graduate Theses and Dissertations

Container on Barge (COB) transportation is an intermodal freight transport mode that moves shipping containers via barges on navigable inland and intracoastal waterways. During the past twenty years, COB has been a growing mode of container shipping globally due to its low-cost, eco-friendly, and congestion-reducing characteristics. Europe and China are currently leading global COB transportation, and the United States (U.S.) may have the potential to achieve economic benefits through the implementation of COB within its intermodal transportation system. To explore this potential, this dissertation investigates the implementation feasibility of COB transportation within the U.S. intermodal freight transportation system. Three contributions …

A Broadband, Dual Polarized Antenna For The Radio Neutrino Observatory In Greenland, Danny Maas

Master's Theses

The Radio Neutrino Observatory in Greenland (RNO-G) is a multidisciplinary, multinational collaboration which uses antennas to detect neutrino interactions with arctic ice sheets. Neutrinos are formed from nuclear reactions; predominant sources include nuclear reactors, stars, supernovae, and the big bang. They rarely interact with normal matter and thus travel from origin to destination relatively unimpeded, with applications including tracking nuclear weapons tests and supernovae. Measurements of galactic neutrino flux can provide information about how the universe developed and its current evolution. Neutrino interactions produce signals from 100 to 1000MHz. Current RNO-G antennas operate over only a portion of this band; …

Real-Time Gun Detection In Video Streams Using Yolo V8, Harish Kumar Reddy Kunchala

Electronic Theses, Projects, and Dissertations

In this research, we advance the domain of public safety by developing a machine learning model that utilizes the YOLO v8 architecture for real-time detection of firearms in video streams. A diverse and extensive dataset, capturing a range of firearms in varying lighting and backgrounds, was meticulously assembled and preprocessed to enhance the model's adaptability to real-world scenarios. Leveraging the YOLO v8 framework, known for its real-time object detection accuracy, the model was fine-tuned to accurately identify firearms across different shapes and orientations.

The training phase capitalized on GPU computing and transfer learning to expedite the learning process while preserving …

Society Management App, Ruchit Rakholiya

Electronic Theses, Projects, and Dissertations

A comprehensive solution as native mobile application which is feasible economical and fast, which will establish the authenticity and reliability for society management overcoming the drawbacks of current system. In today's fast-paced technological ecosystem, the capacity to readily store and access information is becoming increasingly important. Residential societies, where individuals live together and manage collective resources, often require a large number of documents, registrations, vehicle parking records, and other forms of paperwork. The complexity and volume of these documents can lead to inefficiencies and frustrations among residents and management alike.

Service Connect, Namrata Bomble

Electronic Theses, Projects, and Dissertations

ServiceConnect is an innovative web-based marketplace platform designed to revolutionize how local services are accessed and managed in the US. By connecting service providers and customers directly, ServiceConnect provides a simple, secure, user-friendly platform for a range of services such as home repairs, tutoring, pet care and more. Featuring convenient booking tools that increase efficiency while simultaneously building trust among both parties involved. ServiceConnect stands out with its comprehensive service range, user-friendly interface, secure payment processing and rigorous verification process for service providers. Leveraging advanced technologies like ReactJS on the frontend, Node.js & Express on the backend and MongoDB for …

Crime Data Prediction Based On Geographical Location Using Machine Learning, Sai Bharath Yarlagadda

Electronic Theses, Projects, and Dissertations

This project employs machine learning methods like K Nearest Neighbors (KNN), Random Forest, Logistic Regression, and Decision Tree algorithms to monitor crime data based on location and pinpoint areas with risks. The project implements and tunes the four models to improve the precision of predicting crime levels. These models collaborate to offer a trustworthy evaluation of crime patterns. K Nearest Neighbors (KNN) categorizes locations by examining the proximity of data points considering coordinates and other factors to identify trends linked to increased crime data. Logistic Regression gauges the likelihood of crime incidents by studying the connection, between factors (like location …