Engineering Commons^™

Cellular Air Quality Sensors With Lora Backchannel A Robust Sensor Suited For Remote Deployment In Harsh Environments, Joseph R. Miera

Theses and Dissertations

Air quality significantly impacts health and overall quality of life, making its measurement essential. However, most affordable air quality devices are designed only for use within WiFi range and cannot handle extreme temperatures, limiting their usefulness for people in remote or extreme environments, such as regions with harsh winter climates. This limitation is concerning, as winter often brings worse air quality due to temperature inversions that trap pollutants and increase fuel burning for heating. Inversion is a problem as close to home as Utah Valley, and as far away as Ulaanbaatar, Mongolia. Most low-cost air quality sensors are not built …

Physics-Informed Transfer Learning For Process Control, Samuel Arce Munoz

Theses and Dissertations

In the realm of process control, managing complex systems with limited prior knowledge presents significant challenges, particularly in environments where traditional mechanistic models are either unavailable or computationally prohibitive. This work explores the integration of deep transfer learning with system identification and Model Predictive Control (MPC) to develop control strategies that are both data-efficient and computationally streamlined. Initially, Long Short-Term Memory (LSTM) networks are employed to create approximate MPC controllers by leveraging transfer learning from a source system to a target system, demonstrating that transfer learning can achieve comparable performance to traditional MPC methods with reduced training data. Building upon …

Securing Legacy Multivalue Pick Systems Modernized By Restful Web Service Apis, Jacob S. Lee

Theses and Dissertations

With more applications accessible on the Web, organizations with mission-critical legacy systems have had to find a way to stay relevant and competitive by modernizing with RESTful APIs. REST architecture, serving as a guideline rather than a strict protocol, offers significant advantages in terms of scalability, flexibility, and independence; however, its widespread adoption has also led to notable security vulnerabilities and weaknesses. Additionally, there is not one all-encompassing security testing methodology to follow when testing RESTful APIs. For this reason, a new security testing methodology was developed for legacy MultiValue Pick systems that implement the REST API component, MVConnect. The …

The Assessment Of Liquefaction Surface Ejecta Predictions On A New Large Dataset From The 2012 Emilia Romagna, Italy Earthquakes, Holten T. Flinders

Theses and Dissertations

The presence of a non-liquefied crust overlying a liquefied layer has been found to have a significant effect on sand ejecta and surficial liquefaction damage, as observed by Ishihara (1985). Following the 2010-2011 Canterbury seismic sequence in New Zealand, almost no foundation deformation occurred in areas with liquefaction susceptible soils overlain by at least a 3 m-thick crust [3]. In contrast, the 2012 Emilia-Romagna earthquake in Italy provided surface evidence of liquefaction despite 6- to 10 m-thick crusts. Several researchers have proposed liquefaction prediction models [e.g. LPI [6], Ishihara Curves [8], LSN [9], LPIISH [10] and the methods proposed by …

Enhancement Of Ambient Air Quality Index Forecasting Using Optimized Ensemble Model, Vanitha M

Theses and Dissertations

Forecasting ambient air quality is essential for environmental sustainability and public health, especially in heavily populated regions such as China, India, and the United States where air pollution remains a serious concern. Traditional forecasting models often struggle to accurately represent air quality data because of its complex patterns and nonlinear interactions. To address these challenges and improve forecast performance, this research proposes a comprehensive strategy that integrates parallel heterogeneous ensemble modeling with Bayesian optimization.

The study begins with a seasonal machine learning–based imputation technique (SeasonalMLImpute) designed to handle missing data in meteorological and air quality parameters. This method is evaluated …

Effect Of Laser Textured Surface With Different Patterns On Tribological Characteristics Of Bearing Material, Paul Joshua S

Theses and Dissertations

This research work determines the wear rate and friction characteristics of bearing material under different laser textured surface conditions. Chrome steels are used in bearings since they possess high strength and wear resistance. However, when those parts are in service, failure happens due to sliding friction before the lifetime. To improve the durability of the American Iron and Steel Institute (AISI) 52100 chromium steel, in this work, the effect of laser surface texturing (LST) was analysed.

With the different pattern of circle, ellipse, groove and grid were produced on the sample surface, the wear behavior was investigated using the pin …

Generative Ai-Based Optimized Recommender System For Debt Collection Using Large Language Models, Keerthana S

Theses and Dissertations

Reducing the percentage of defaulters who often skip payments throughout the debt collection process might help minimize losses in the banking industry. The debt collection process should be optimized to reduce the rate of defaulters and improve collection rates. Traditional Machine Learning algorithms focused on credit risk analysis, defaulter prediction, and forecasting the recovery rate of debt collection. Researchers are not currently prioritizing the analysis of debt collectors’ performance. The debt collector’s primary responsibility is to retrieve outstanding debts from consumers on behalf of the debt collection firm.

Examining debt collectors’ performance is essential to enhance collection efficiency in the …

Understanding The Role Of The Heat Transfer Coefficient Between Tool/Workpiece Interface During Friction Stir Welding, Matthew Goodson

Theses and Dissertations

The heat transfer coefficient is a key parameter in modeling friction stir welding and has yet to be measured experimentally. The importance of this parameter was shown through validating friction stir models on both sides of the tool/workpiece interface. Both a transient plunge and a steady state model were validated by matching experimental temperatures. The steady state tool temperatures were matched (with in 2.5%), but the steady state workpiece temperatures were off by around 20%. The transient model of the FSW plunge showed the effect of varying the ℎ𝑊/𝑇 on workpiece temperatures and tool temperatures. Two methods were looked at …

Extracting Permittivity And Permeability Using The Position-Insensitive And Calibration-Independent Method On A Rectangular Waveguide, James Conrad Denemark

Theses and Dissertations

Classic methods for extracting material characteristics require known measurements to accurately calibrate the network analyzer. Previous work demonstrated a position-insensitive and calibration-independent (PiCi) transmission/reflection method to extract a material’s permittivity. This thesis proposes a method with the same function, manipulated to use one empty measurement and then two samples of different thicknesses. The PiCi method is first adopted for rectangular waveguide which resulted in inaccurate permittivity data when compared to the calibrated solution. Once detector mismatch corrections were applied, the PiCi method produced accurate results. Using a 2-D numerical root search, permittivity and permeability material characteristics are now successfully extracted …

Patterns Of Interactions In Human-Machine Teams, Kazuhiko Momose

Theses and Dissertations

Increasingly capable machines, including Artificial Intelligence (AI) agents are playing a more important role in a wide range of applications, including human daily activities and safety-critical systems. They can benefit even more when humans and such machines agents work together as a team by leveraging each other's strengths and complementing each other to enhance overall performance. To design high-performing teams, it is critical to analyze the team dynamics and understand how humans and machines interact with each other. Collaboration, Coordination, and Cooperation (3Cs) are terms typically used to describe the behavior of teams. However, these terms tend to be used …

Breaking The Procrastination Barrier, Bianca Ebanks

Theses and Dissertations

Procrastination is a common barrier to productivity, impacting individuals' ability to achieve goals, especially in academic and professional settings. This study investigates a mixed-methods online intervention combining Behavioral Analysis (BA) principles with mindfulness exercises to reduce procrastination. The aim was to develop a human-centered, personalized intervention that utilizes behavioral reminders and mindfulness techniques to address procrastination in 43 participants. Participants' procrastination levels were assessed using the Irrational Procrastination Scale (IPS), and interventions were tailored based on individual procrastination tendencies. Reminders were sent via email or text, with timing adjusted to participants’ specific needs. The intervention also included mindfulness exercises designed …

Theoretical Advancements In Hawkes Processes And Their Practical Applications, Xi Zhang

Theses and Dissertations

Hawkes self-exciting point processes have been widely used in fields such as seismology, finance and social media analysis. Despite decades of research focusing on these processes, several key aspects remain under-explored. These include broadly applicable methods for model evaluation and selection, intuitive nonparametric inference approaches akin to kernel density estimation for probability density functions, and strategies to enhance the performance of generative point process models in predictive tasks. In this dissertation, first, we extend the time-rescaling theorem, which is traditionally limited to non-terminating processes with complete observations, to accommodate terminating processes and incomplete observations as well. This extension allows for …

Feasibility Study On Microwave Glucose Level Monitoring, Ricardo Cepeda

Theses and Dissertations

Diabetes management heavily relies on regular blood glucose monitoring, which traditionally involves invasive techniques. In recent years, significant research has been directed towards developing non-invasive glucose monitoring methods, particularly using electromagnetic waves. This study explores the feasibility of detecting blood glucose levels non-invasively by measuring the resonant frequency shifts of an antenna, influenced by the dielectric properties of blood. Microwave measurement techniques have garnered attention due to their ability to safely penetrate human tissue and detect biochemical markers like glucose. While previous studies have established a link between glucose concentration and dielectric properties, many techniques suffer from poor sensitivity or …

Fabrication And Performance Of Scalable Bio-Engineered Porous Layers For Efficient Co2 Capture, Mary Sharon Rose Bondugula

Theses and Dissertations

This dissertation addresses the critical challenge of mitigating climate change by advancing CO2 capture technologies. As global CO2 emissions continue to rise, effective methods for capturing and separating CO2 from industrial processes are essential to combat climate change. Existing CO2 capture systems, such as Pressure Swing Adsorption (PSA) and Temperature Swing Adsorption (TSA), often rely on packed bed designs that face limitations, including poor heat and mass transfer, slow gas diffusion, and low thermal conductivity, reducing their efficiency. To overcome these challenges, this dissertation explores innovative solutions by developing advanced adsorbent coatings and scalable bed configurations.

This research begins by …

Heterogeneous Collaborative Robotics: Multi-Robot Navigation In Dynamic Environments, Tyler Nicholas Raettig

Theses and Dissertations

Abstract: The challenges of multi-robot navigation in dynamic environments, focusing on uncertainties in obstacle complexities, partial observation, and the transition of policies from simulations to the real world. The proposed approach utilizes a deep reinforcement learning (DRL) framework enabling a Light Detection and Ranging (LiDAR)-equipped robot to communicate with a camera-equipped robot to achieve optimal paths despite their different sensors. The key contributions include the development of a cooperative architecture for information exchange between robots, a DRL-based framework for learning navigation policies, and a training mechanism based on dynamic randomization for enhanced real-world adaptability. Experimental validation using Gazebo simulations demonstrates …

Primary And Secondary Resonances Of Fringe Effect Electrostatically Actuated Mems Cantilever Resonators, Miguel Armando Martinez

Theses and Dissertations

The nonlinear dynamics of micro-electromechanical system (MEMS) cantilever resonators actuated by the fringe field at parametric and primary resonances are studied. Three models are used based on different descriptions of the system capacitance. In the fringe and capacitance models, the electrostatic force due to the parallel-plate capacitance is neglected due to a hole in the ground plate (removes overlapping area). The SolidWorks model is based on numerical capacitance simulations performed on SolidWorks using EMS. All three models that approximate the fringe field capacitance are compared with one another. The Method of Multiple Scales (MMS) and Reduced Order Model (ROM) up …

Study Of Temperature Effects Of Glucose And Microwave Dielectric Dispersion Model, Ethan Grant Boone

Theses and Dissertations

In this study, the temperature effect of dielectric properties in various aqueous solutions containing glucose are examined. A design for a new testing chamber is introduced to provide improved conditions for testing to ensure accurate and precise measurements. A N-SMA Adaptor is used when obtaining dielectric characteristics of glucose solutions ranging 100-300mg/dl. Dielectric parameters are obtained adopting a modified Debye dispersion model. MATLAB is used to confirm coaxial dimensions are suitable fabrication designs using fixed dielectric parameters of air and water. Simulations and design models were implemented utilizing ANSYS High Frequency Structure Simulator and 3-D Modeler software to develop the …

3d Bioprinted Coaxial Tubule Optimization For Human Aortic Endothelial Cell Growth, Ilse Gabriela Perez Garcia

Theses and Dissertations

This paper introduces a research study of printing parameter optimization of extruded, cell-laden, 3D bioprinted coaxial tubules, as well as cell interaction observations. Optimization of printing parameters seeks to reduce variability of the tubules’ inner and outer diameters. The tubules were manufactured from a 0.4% Collagen I - 1.6% NaC6H7O6 (Sodium Alginate) bioink, that reaches gelation through interaction with a 3.2% CaCl2 (Calcium Chloride) solution. The bioinks were extruded through a dual syringe pump mechanism connected to a coaxial nozzle, which is mounted on an adapted 3D FDM (Fused Deposition …

Resonances Of Electrostatically Actuated Non-Uniform Mems Cantilever Resonator Of Constant Width And Linearly Varying Thickness, Rigoberto Flores

Theses and Dissertations

In this investigation the behavior of an electrostatically actuated non-uniform microelectromechanical (MEMS) cantilever resonator of constant width and linearly varying thickness is investigated. The cantilever resonator vibrates using soft AC voltage at near half the first natural frequency of the cantilever and near the first natural frequency of the cantilever, known as primary and parametric resonances, respectively. Bifurcation diagrams for the amplitude-frequency and amplitude-voltage response are obtained for both resonances. Two methods are used in this investigation, namely the Method of Multiple Scales (MMS) and Reduced Order Model (ROM) using up to 6 modes of vibration.

These methods are used …

Identifying Challenges Faced By Small And Medium Enterprises (Smes) In The Middle East And North Africa (Mena) Region Through Total Quality Management, Mohamad Atef

Theses and Dissertations

Recently, Small and Medium Enterprises (SMEs) have become recognized as an important driver of global economic growth and innovation. This phenomenon is particularly evident in the MENA region, where small and medium-sized enterprises (SMEs) make a significant contribution to the businesses. SMEs offer significant benefits in terms of job creation, revenue generation, and fostering economic diversity. Although SMEs have a vital contribution in the economy of the MENA region, SMEs face many challenges that hinder their development and long-term viability. Focusing on these challenges is very important for fostering a vibrant and resilient economic environment. The objective of this thesis …

The Design And Implementation Of A Modular Tissue Engineering Test Bed To Pursue An Alternate Pathway Of Cell Culture Based Research, Ryley Patrick Griffin

Theses and Dissertations

The development of a Modular Automated Tissue Engineering Test Bed (MATETB) is the next step in the development of cheap and easily available in vitro cell regulatory systems for both academic and industrial purposes. This project outlined the framework and requirements for a device that could automatically regulate and collect data on a cell culture through the manipulation of its liquid environment. From this framework, a prototype was built. The device would fulfill cell culture needs while collecting data automatically and allowing for live viewing and imaging of cells. The device was comprised of a mechanical skeleton (MS), an environmental …

End-To-End Learning For A Low-Cost Robotics Arm, Abhishek Chothani

Theses and Dissertations

Robotic manipulation is a cornerstone of automation, with the ultimate goal of developing versatile systems capable of executing a wide range of real-world tasks autonomously. Traditional robotics approaches, while reliable and widely adopted in industrial settings, often struggle with adaptability, perception, and dynamic task execution. This thesis explores the evolution from classical robotics techniques to modern learning-based approaches, leveraging advancements in artificial intelligence to overcome these limitations.

Initially, the thesis presents a pick-and-place pipeline built using the Drake robotics framework and the KUKA iiwa robotic arm. This system employs a pseudoinverse controller for inverse kinematics to perform structured tasks like …

Learning-Based Feature Identification For Rendezvous And Capture Of Non-Cooperative Space Objects, Trupti Mahendrakar

Theses and Dissertations

In recent years, On-Orbit Servicing (OOS) and Active Debris Removal (ADR) have attracted increasing interest due to growing concerns about space debris. This debris poses a significant risk to spacecraft, as collisions can catastrophically end missions and potentially trigger a cascading chain reaction of more debris. Space debris ranges from tiny paint chips to large non-functional spacecraft and even launch vehicle components. One way to mitigate the formation of additional space debris is to reduce the total number of large non-cooperative resident space objects present in operational orbits. This can be achieved through two approaches: de-orbiting these objects as part …

Demonstrating Feasibility Of Ultrasound-Sensitive Microbubbles Delivery To Treat Disruptions In The Blood Brain Barrier Endothelium, Rubens Jourdain

Theses and Dissertations

Vascular cognitive impairment and dementia (VCID) is one of the main causes of dementia. VCID is caused by age and other genetic factors that lead to disruptions in the blood brain barrier (BBB) and allow blood components to enter the brain. The currently available treatments of VCID include opening the BBB with high-frequency-ultrasound to deliver drugs to the brain. However, this only treats the already developed disease. Consequently, we developed a new drug delivery system whose goal is to restore the brain capillary endothelial cells (BCEC) lining the blood vessel. The objective of this study was to demonstrate the feasibility …

Advancing Biofabrication Methodologies To Develop Biomimetic Tissue Scaffolds For Musculoskeletal Applications, Nashaita Yezdi Patrawalla

Theses and Dissertations

Musculoskeletal injuries impose a significant global burden, affecting millions and generating an economic toll exceeding $14 billion. Tissue engineering has gained traction as a promising strategy offering potential for functional restoration of damaged musculoskeletal tissues. This research aims to advance biofabrication techniques for generation of biomimetic tissue scaffolds, by optimizing scaffold design and modulating fabrication process parameters to generate scaffolds for musculoskeletal regeneration with application-specific tailored properties. In this realm, collagen-based biomaterials have been extensively investigated for tendon and ligamentous applications, and in combination with bioceramics incorporated into the collagen framework to produce composite scaffolds that better recapitulate the native …

Mathematical Model For Helically Propagating Spatially Multiplexed Mimo Channels Inside Single Core Optical Fibers, Ibrahim Barka

Theses and Dissertations

It all started when our curiosity was sparked by observing light beams from a Multi-Channel Laser Source precisely coupled into a single-core optical fiber positioned on an optical bench in the lab. The multiplexed light beams, characterized by different spatial azimuthal angles, were guided by the fiber, tracing helical paths and producing a bright central spot with concentric rings depending on the launched angles, a phenomenon we came to call Spatial Domain Multiplexing (SDM). Conventional concepts of hybrid and LP modes couldn’t fully explain the behavior of SDM modes, leading us to the question of the types of field configurations …

Loss Of Control In General Aviation: An Investigation Into The Mooney M20 And The Full Trimming Tail Design, Trenton Neil Wright

Theses and Dissertations

Loss of Control (LOC) in General Aviation (GA) remains one of the leading causes of aviation accidents, with 94% of all accidents in 2022 occurring in this sector, and 42% attributed directly to LOC [2][3]. This thesis focuses on the Full Trimming Tail (FTT) in Mooney aircraft, hypothesizing that the FTT design significantly increases the likelihood of LOC, particularly during go-arounds and touch-and-go landings. Prior studies have shown that certain trim systems can amplify pitch-up moments following rapid configuration changes, leading to stalls or LOC if not adequately managed by the pilot [23][24][25].

This research utilized a combination of logistic …

Fabrication And Charcaterization Of Pullulan-Collagen Nanofibers Via Forcespinning, Valeria Leon Leal

Theses and Dissertations

Extensive research on collagen has spurred advancements in tissue engineering and biomaterial development, given collagen´s pivotal role in regulating various tissue structures across diverse organisms. This study delves into fabricating nanocomposites utilizing collagen, along with silver nanoparticles, chondroitin sulfate and pullulan, for potential applications in antibacterial medical devices, and cell regeneration. Collagen, abundant in the extracellular matrix, provides essential structural support, while silver nanoparticles and chondroitin confer antimicrobial properties, crucial for combating infections. Pullulan, a polysaccharide polymer, serves as a biocompatible carrier for silver nanoparticles whilst being the starting nanofiber forming material. Utilizing Forcespinning® technology, composite nanofibers were successfully synthesized. …

Tac-It An Affective Computing User Interface Design, Andrew Biron

Theses and Dissertations

TAC-IT affective computing user-interface design is an independent computer peripheral that is a tool to be utilized to obtain a user’s self-reported emotional state in real-time. Doctor Rosalind Picard first coined and used the term affective computing in her paper Affective Computing [Picard, R. (1995)]. Affective Computing is defined as the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. Since that time, areas of research have expanded exponentially, and areas of interest include how to trigger emotions in a test …

Dual-Channel Side Channel Attack: Improved Aes Key Decryption By Combining Power And Electromagnetic Side Channels With Convolutional Neural Networks, Sean P. O'Neill

Theses and Dissertations

This research introduces a novel DL approach for SCA that combines power consumption and EM signals to enhance encryption key deduction by leveraging a dual-channel CNN architecture. A new dataset, consisting of simultaneous power and EM signal collections during 128-bitAES encryption, was developed to train and evaluate the model’s effectiveness. The combined approach achieved an 88% reduction in traces needed, from 50 traces to 6, for encryption key classification, outperforming traditional methods such as random forest, DPA, DEMA,and individual side channel CNN models. These findings highlight the potential of integrating multiple side channels in SCA to improve performance without the …