Engineering Commons^™

Matrix Stiffness Sensing By Nascent Adhesions And The Role Of Riam In Adhesion Assembly, Nikhil Mittal

Dissertations, Master's Theses and Master's Reports

Mechanical stiffness of the extracellular matrix (ECM) impacts many cellular functions such as proliferation, migration, and differentiation. ECM stiffness is sensed by a cell via integrin-based focal adhesions (FAs) by changing conformation and biochemical activities of molecules within FAs by the exchange of the force between the ECM and filamentous actin (F-actin). Cells in turn respond to this stiffness by generating traction force that plays an important role in many biological events such as tissue morphogenesis, stem cell differentiation, wound healing, and cancer cell metastasis. The stiffness of the extracellular matrix induces differential tension within integrin-based adhesions. Understanding stiffness sensing …

Developing Robust Autonomous Vehicles With Ros, Dylan J. Kangas

Dissertations, Master's Theses and Master's Reports

The demand for autonomous vehicles (AVs) is rising across both military and civilian sectors. These unmanned systems offer numerous advantages, such as improved efficiency, safety, and adaptability. Addressing this demand requires the development of resilient and versatile autonomous vehicles crucial for the transport and reconnaissance markets.

The sensory perception of autonomous vehicles of any kind is paramount to their ability to navigate and localize in their environment. Factors such as sensor noise, erroneous readings, and deliberate attacks should all be considered when developing a robust autonomous system. This work aims to quantify the degradation of sensor data which causes mapping …

Anaerobic Reductive Bioleaching Of Manganese Ores, Neha Sharma

Dissertations, Master's Theses and Master's Reports

Manganese extraction by biological methods is a green and economical way to produce manganese from low as well as high grade manganese ores. This is especially important for US ores, which are primarily either small in extent, low-grade with a high iron content, or both. They are therefore not suitable for conventional mining, which is very capital-intensive and requires a large up-front investment and are therefore imported at high costs. The goal is therefore to develop a process that can be applied at small scales, with minimal startup costs, and low equipment and labor requirements. It is also critical to …

Wave Energy Converter Wave Force Prediction Using A Neural Network, Morgan Kline

Dissertations, Master's Theses and Master's Reports

Due to the unpredictable nature of large bodies of water, wave energy can be a difficult renewable resource to rely on. One way to make Wave Energy Converters (WECs) more efficient is to apply a control strategy. In many control solutions, it is assumed that the wave excitation force is known into the future. In many instances, especially with complex waveforms, this is simply not the case. Simulation studies have shown the promise of wave force prediction using neural networks. This study demonstrates this experimentally and aims to characterize the important factors when designing such a network. Several wave elevation …

Modeling Of Inverter-Based Resources For Hardware In The Loop Testing Of Protection And Control Schemes, Md Aamir Rahmani

Dissertations, Master's Theses and Master's Reports

High penetration of inverter-based resources (IBR) may cause the misoperation of protective relays due to the dynamic nature of fault currents fed by the IBR during short-circuit faults. Misoperation may cause damage to power system equipment and affect the reliability of the power system. This dissertation presents an in-depth investigation into the modeling of IBR in the context of transmission line fault scenarios to understand and analyze the characteristics of fault currents fed by the IBR. The research objectives encompass the development of reliable IBR models capable of accurately replicating fault current behaviors, designing IBR operation control schemes, and implementing …

Halide-Assisted Growth Of Transition Metal Dichalcogenides, Vinaayak Sivam Balasubramaniam

Dissertations, Master's Theses and Master's Reports

Monolayers of transition metal dichalcogenides (TMDCs) have attracted significant attention as the rare two-dimensional (2D) semiconducting materials with a direct energy band gap. Chemical vapour deposition (CVD) is one of the scalable techniques to grow atomically thin TMDC monolayers in high quality, but it requires high growth temperature. Herein we report the growth of MoS2, WS2 and MoSe2 by a one-step halide-assisted CVD method using NaCl and KCl as the catalysts. These halides could reduce the growth temperature of TMDCS by reacting with the precursors (TMDC powders) to form volatile intermediate compounds as the growth species. We use optical microscopy, …

Continuous, Platform Purification Of Viral Products Using Aqueous Two-Phase Extraction, Natalie M. Nold

Dissertations, Master's Theses and Master's Reports

Cell and gene therapies, a ground-breaking class of drugs that can heal genetic diseases and cure cancer, often have treatment costs over $1 million. Most cell and gene therapies are delivered using virus-based delivery vectors, which are incredibly expensive to manufacture. Liquid chromatography is the favored method of viral vector purification since it is easily scalable and can be functionalized to purify by biospecificity, charge, hydrophobicity, or size. However, chromatography-based purification processes are highly expensive and usually only recover 20-50% of the viral vectors. There is currently no platform purification strategy for viral vectors due to differences in their surface …

Optimizing Diabetes Diagnostics: Electrophoretic Separation And Detection Of Hemoglobin A1c With Boronate, Rixlie Fozilova

Dissertations, Master's Theses and Master's Reports

Diabetes affects 537 million people worldwide, while 136 million Americans have diabetes or prediabetes; roughly 22.6% of individuals are undiagnosed. Diabetes is the inability to regulate blood sugar levels. Hemoglobin A1c (HbA1c) is glycosylated hemoglobin and indicates average blood sugar levels over the past three months.

We adapted the selective boronic acid binding to the HbA1c sugar moieties from boronate affinity chromatography and translated it into a portable microchip paper-based electrophoresis platform. We explored a range of boronate concentrations at a steady voltage and sample volume to determine the optimal HbA1c binding and subsequent electrophoretic separation. A pH above 11 …

Multi-Functional Gelatin-Dithiolane Hydrogels For Tissue Engineering, Saad Asim

Dissertations, Master's Theses and Master's Reports

Biomaterials that integrate multiple functionalities, mimic the extracellular matrix (ECM) microenvironment to support cellular growth, and adhere robustly to damaged tissues are highly needed to advance tissue engineering. Protein-based biomaterials are promising due to their inherent biocompatibility, biomimicry, biodegradation, and cell-supportive properties. Herein, by leveraging the unique ability of dithiolanes to generate on-demand in-situ thiols, we developed a new class of dithiolane-modified, protein-based biomaterial that combines unique, seemingly opposing functions for tissue engineering. Dithiolane-modified gelatin, a model protein used herein, enabled photoinitiator-free photo-crosslinking to form multi-functional gelatin-dithiolane (GelDT) hydrogels, which displayed exceptional long-term stability in cell culture media (>28 …

Initial Solution Improvements To A Tethered Robotic Path Planner Using Random Geometric Graph Configurations And Biased Sampling, Austen J. Goddu

Dissertations, Master's Theses and Master's Reports

With NASA's ongoing efforts to establish a presence on the lunar surface to eventually move on to exploring mars, the development of intelligent robotic systems is more important than ever. The ability of robotics to explore hazardous and extreme terrain, coupled with long communication times from earth places an ever increasing need on more robust and efficient autonomy. Tethered robotics offer unique advantages to explore scientific targets both on the lunar and martian surfaces, capable of using their tether as a physical or metaphorical lifeline to allow the exploration of slopes, extreme dark regions, or areas in which wireless communication …

Exploring The Diffusion Potential Of A Collaborative Mobile Platform For Disaster Management And Relief, Joao De Mendonca Salim

Honors Undergraduate Theses

This thesis describes the creation of a collaborative digital platform for disaster management and relief, focusing on the case study of the city of Petrópolis natural disaster in February 2022. The frequency and intensity of natural disasters are rising, necessitating efficient and timely disaster response efforts. This thesis details the development of a software application that fosters collaboration among governmental agencies, emergency services, non-governmental organizations (NGOs), and civil society to enhance logistical planning and situational awareness during disasters. The proposed platform harnesses the power of social networking and leverages the ubiquitous presence of smartphones equipped with cameras, GPS, and sensors …

Functional Verification Of Additively Manufactured Metallopolymer Structures For Structural Electronics Design, Nathan D. Singhal

Honors Undergraduate Theses

As an attempt to improve the overall cost-effectiveness and ease of structural electronics manufacturing, this study characterizes the mechanical and electrical responses of structures which are fabricated from a novel metallopolymer composite material by fused deposition modeling as they are subjected to quasi-static, uniaxial mechanical tension. Baseline values of tensile properties and electrical resistivity were first obtained via ASTM D638-22 standard testing procedures and linear sweep voltammetry (LSV), respectively. A hybrid procedure to measure in-situ mechanically dependent electrical behavior was subsequently developed and implemented. The mechanical and electromechanical testing was followed by the derivation of stochastic values for several mechanical …

Adaptation Of A Commercially Available Galvanic Skin Response Sensor To Measure Respiration Across The Chest For Heart Rate Variability Monitoring, Breno C. Dobal

Honors Undergraduate Theses

Heart rate variability (HRV) is a naturally occurring cardiovascular phenomenon referring to the changing timing between consecutive heartbeats. The connection between HRV and overall cardiovascular health and autonomic nervous system function has been well established through prior research and well documented in existing literature. The existing studies, however, included shorter HRV subject recording session, using traditional HRV monitoring methods that do not typically combine electrocardiogram (ECG), seismocardiogram (SCG) and galvanic skin response (GSR) respiration monitoring. The inclusion of longer HRV subject recording may allow for further insight on the possible effects of given observable biological phenomenon on HRV.

The current …

Analysis Of Variations In Flow-Independent Liquid Jet-In-Crossflow Injections, Michael Scott

Honors Undergraduate Theses

Liquid fuel injection is a critical mechanism for the deliverance of liquid fuel in contemporary aircraft propulsion combustion systems due to its outsized influence in providing optimal combustion conditions and improving overall aircraft efficiency and performance. Despite this, these liquid jet in crossflow (LJIC) systems are highly variable due to conditions in the jet and the surrounding airflow, leading to variability in performance behavior and inconsistency in fuel mixing and combustion efficiency. This has prompted the introduction of solid pintile obstructions of novel designs to provide a more flow-independent fuel injection scheme and decrease variability of the jet properties against …

Reinforcement Learning From Human Feedback For Ethically Robust Ai Decision-Making, Marco M. Plasencia

Honors Undergraduate Theses

The emergence of reinforcement learning from human feedback (RLHF) has made great strides toward giving AI decision-making the ability to learn from external human advice. In general, this machine learning technique is concerned with producing agents that learn to work toward optimizing and achieving some goal, advanced by interactions with the environment and feedback given in terms of a quantifiable reward. In the scope of this project, we seek to merge the intricate realms of AI robustness, ethical decision-making, and RLHF. With no way to truly quantify human values, human feedback is an essential bridge in the learning process, allowing …

Guarding The Grid: Exploring Iot And Iiot Security Vulnerabilities In Smart Power Systems, Nicole G. Parker

Honors Undergraduate Theses

The Internet of Things (IoT) encompasses the collective network of electrical devices and the technology that enables them to send and receive data. The use of IoT technologies in industrial settings, such as transportation, manufacturing, and energy is referred to as the Industrial Internet of Things (IIoT). With the expansion of IoT in homes and IIoT in the energy sector has come an increase in the number of devices connected with each other. Engineers have utilized this network to develop sophisticated smart systems that combine sensing, processing, actuation, and control to produce smart environments. Along with the benefits of IoT …

Enhancing Medical Chatbots With Image Diagnosis, Swatisri Chavali

Master's Projects

Medical chatbots, at the conjunction of artificial intelligence and healthcare, are the very cornerstone of a transformative force in diagnostic capabilities and communication channels for healthcare professionals. The history of this journey, from early chatbot models to sophisticated systems, is born out of a relentless pursuit of accuracy and contextual understanding. This proposal acknowledges the critical role played by NLTK in raising the interpretability and communicative capabilities of intelligent systems, meeting challenges that arise from varying writing styles and accommodating the standards of the medical field. The integration of NLTK is a linchpin, bridging the gap between sophisticated technological architectures …

Multimodal Emotion Detection In Conversations And Dialogues: A Fusion Model Approach, Abhinay Jatoth

Master's Projects

Emotion recognition is gaining traction due to its wide range of potential applications across different fields. With the rise of social media, chat platforms, and voice assistants, there is a vast increase in data through which humans implicitly and explicitly carry emotional cues. With new algorithms being developed for understanding the nuances of human language and emotion, businesses can tailor more personalized and empathetic service. Sentiment analysis, expresses a positive, negative, or neutral viewpoint laid the foundation of Emotion classification. Emotion classification in conversations represents the most advanced stage of classification. It is also challenging due to the existence and …

Transitioning To A Lower Global Warming Refrigerant, A Performance Study Of R-513a And Hfc-134a In Commercial Chillers, Hossein Abedsoltan, Mark B. Shiflett

Chemical and Biochemical Engineering Faculty Research & Creative Works

The performance of R-513A and HFC-134a refrigerants is compared in two identical chillers operating at the University of Kansas. R-513A is a more environmentally friendly refrigerant due to its lower global warming potential that can be used as a retrofit replacement for HFC-134a in chillers. This study investigates the performance comparison of transitioning from HFC-134a to R-513A. The chillers have been in operation for two years, and cooling capacity, coefficient of performance, and other operating parameters are compared under similar cooling conditions. Cooling capacities ranged from 100 to 500 kW for both chillers. Overall, the energy consumption and coefficient of …

Root Water Uptake Patterns Are Controlled By Tree Species Interactions And Soil Water Variability, Gökben Demir, Andrew J. Guswa, Janett Filipzik, Johanna Clara Metzger, Christine Römermann, Anke Hildebrandt

Engineering: Faculty Publications

Root water uptake depends on soil moisture which is primarily fed by throughfall in forests. Several biotic and abiotic elements shape the spatial distribution of throughfall. It is well documented that throughfall patterns result in reoccurring higher and lower water inputs at certain locations. However, how the spatial distribution of throughfall affects root water uptake patterns remains unresolved. Therefore, we investigate root water uptake patterns by considering spatial patterns of throughfall and soil water in addition to soil and neighboring tree characteristics. In a beech-dominated mixed deciduous forest in a temperate climate, we conducted intensive throughfall sampling at locations paired …

Economic Profitability Of Sustainable Buildings Industry, Mohanad Ibrahim Altuma, Hanadi Abdulridha Lateef, Ayad Abdulkhaleq Al-Yousuf

Al-Esraa University College Journal for Engineering Sciences

The increasing global awareness of the Earth's deteriorating condition and the unpredictable effects of climate change has given rise to worldwide phenomena that impact several elements like the economy, agricultural security, water availability, and energy supplies. Buildings contribute significantly to the generation of greenhouse gases, as well as the disposal of pollutants and energy consumption. Therefore, they play a crucial role in addressing environmental issues.

Although sustainable buildings are widely acknowledged as a potential advancement, professionals in the property market still believe that the upfront costs of creating sustainable buildings are significantly higher than those of conventional buildings. This view …

Designing A Visual Control Framework Based On Feature Point Analysis To Guide Robots In Uncharted Areas, Isam Sadiq Rasham Al-Ghadhbawi

Al-Esraa University College Journal for Engineering Sciences

Image processing may be made more accurate and efficient with the use of optical processing technologies. In order to make better design judgments early in the package design process, visual packaging art simulation aims to swiftly develop realistic packaging effects. Conventional simulation techniques frequently yield findings that are neither realistic or detailed, and they also take a lot of time and human resources. Optical processing-based machine vision technology can fully utilize computer vision and image processing techniques to simulate package designs accurately and efficiently. This research proposes a foundation for machine vision technologies based on image optical processing. Real package …

Machine-Learning-Assisted Design Of Deep Eutectic Solvents Based On Uncovered Hydrogen Bond Patterns, Usman Lame Abbas, Yuxuan Zhang, Joseph Tapia, Md Selim, Jin Chen, Jian Shi, Qing Shao

Markey Cancer Center Faculty Publications

Non-ionic deep eutectic solvents (DESs) are non-ionic designer solvents with various applications in catalysis, extraction, carbon capture, and pharmaceuticals. However, discovering new DES candidates is challenging due to a lack of efficient tools that accurately predict DES formation. The search for DES relies heavily on intuition or trial-and-error processes, leading to low success rates or missed opportuni- ties. Recognizing that hydrogen bonds (HBs) play a central role in DES formation, we aim to identify HB features that distinguish DES from non-DES systems and use them to develop machine learning (ML) models to discover new DES systems. We first analyze the …

Perfluorooctanesulfonic Acid Exposure Leads To Downregulation Of 3-Hydroxy-3-Methylglutaryl-Coa Synthase 2 Expression And Upregulation Of Markers Associated With Intestinal Carcinogenesis In Mouse Intestinal Tissues, Josiane Weber Tessmann, Pan Deng, Jerika Durham, Chang Li, Moumita Banerjee, Qingding Wang, Ryan A. Goettl, Daheng He, Chi Wang, Eun Y. Lee, B. Mark Evers, Bernhard Hennig, Yekaterina Y. Zaytseva

Markey Cancer Center Faculty Publications

Perfluorooctanesulfonic acid (PFOS) is a widely recognized environment pollutant known for its high bio- accumulation potential and a long elimination half-life. Several studies have shown that PFOS can alter multiple biological pathways and negatively affect human health. Considering the direct exposure to the gastrointestinal (GI) tract to environmental pollutants, PFOS can potentially disrupt intestinal homeostasis. However, there is limited knowledge about the effect of PFOS exposure on normal intestinal tissues, and its contribution to GI- associated diseases remains to be determined. In this study, we examined the effect of PFOS exposure on the gene expression profile of intestinal tissues of …

Investigation Of Delta-Focused Ictal Electrical Source Imaging In Refractory Focal Epilepsy, Jared A. Rybarczyk

Theses and Dissertations--Electrical and Computer Engineering

Refractory focal epilepsy is characterized by the presence of seizures that cannot be controlled via anti-seizure medications. For patients suffering from this form of epilepsy, accurate identification of the seizure onset zone is a crucial step for many modalities of treatment. Electrical source imaging (ESI) allows for estimation of the seizure onset zone from electroencephalography. EEG feature extraction is an important step that can impact the final accuracy of source estimates. This work provides a review of 23 ictal ESI studies and proposes a delta-focused ictal ESI methodology. Our proposed delta-focused ictal ESI is implemented across 33 refractory focal epilepsy …

Electronics Design For Krepe Atmospheric Entry Capsule Avionics, Matt Ruffner

Theses and Dissertations--Electrical and Computer Engineering

This research documents the design, testing, and implementation of sensing, control, and communications subsystems for small atmospheric entry capsules. Atmospheric entry capsules pose a unique electronics design challenge given mission requirements, environmental constraints, and inherent risk involved in space based missions. Previous work on small satellites developed the CubeSat platform as a means of ensuring reliability after university-led small satellite missions experienced failures. The publication of the CubeSat platform allowed researchers to focus on the payload science utilizing a standardized form-factor and reusable electronics. Environmental and operational constraints of CubeSats and atmospheric entry capsules overlap and best-practices associated with building …

Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai

Theses and Dissertations--Electrical and Computer Engineering

Artificial Intelligence (AI) has experienced remarkable success in recent years, solving complex computational problems across various domains, including computer vision, natural language processing, and pattern recognition. Much of this success can be attributed to the advancements in deep learning algorithms and models, particularly Artificial Neural Networks (ANNs). In recent times, deep ANNs have achieved unprecedented levels of accuracy, surpassing human capabilities in some cases. However, these deep ANN models come at a significant computational cost, with billions to trillions of parameters. Recent trends indicate that the number of parameters per ANN model will continue to grow exponentially in the foreseeable …

Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso

Theses and Dissertations--Electrical and Computer Engineering

The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …

Mitigation Of Reflected Overvoltage In Wind-Turbine Generator-Converter Systems With A Smart Coil Concept, Lulu Wei

Theses and Dissertations--Electrical and Computer Engineering

In the recent decade, ultra-fast wide bandgap switching devices such as Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) have been increasingly utilized in power electronic converters for renewable energy power generation systems due to their advantages of enabling high energy efficiency and high power density. However, the much higher voltage slew rate (i.e., dv/dt) with SiC power converters may induce voltage reflection and reliability concerns in machine-converter systems, especially for medium-voltage systems with long cable connections. In wind-turbine power generation systems, generators are typically located in the nacelles, and medium-voltage power converters are mostly placed at the bottom of the …

Multi-Physics Modeling Of Immersion Cooled Electric Power Apparatuses, Reza Ilka

Theses and Dissertations--Electrical and Computer Engineering

Electric power conversion apparatuses such as electromagnetic transformers and power electronic converters play a backbone role in the global power and energy industries, such as power transmission and distribution, electrified transportation vehicle systems, industry automation, and the like. To investigate the performance (efficiency, reliability, etc.) of such critical power conversion apparatuses, high-fidelity multi-physics modeling becomes critical which involves dedicated coupling among multiple physical domains, including electrical, magnetic, thermal, mechanical, and material engineering. Nevertheless, the majority of the existing models for these power conversion apparatuses focus only on one or two physical domains, and the modeling fidelity needs to be further …