Damping Modulation Of Dampened Kapton Surfaces, Sebastian Esteban

Honors Undergraduate Theses

When droplets are vibrated or disturbed, they can exhibit a complex sloshing motion, an understudied behavior in drop physics. Droplet sloshing involves a complex combination of transverse and longitudinal motion that changes the droplet's effective weight on the surface the droplet is on. Our current understanding stems from preliminary work focusing on a cantilever beam of fixed thickness and variable viscosity of the liquid being sloshed. This investigation will focus on how variable cantilever thickness and constant viscosity for a liquid being sloshed affects the beam's deflection under consistent vibration. It will also investigate how the natural frequency of a …

Integrated Compliant Structure For A Hand Exoskeleton, Tristan R. Koopman

Honors Undergraduate Theses

This thesis presents the design and prototyping of a wearable hand exoskeleton that integrates a flexible structural framework to assist with hand movement while maintaining comfort and anatomical conformity. The goal was to create a device that supports tendon-driven actuation through a compliant structure, combining elements of rigidity and flexibility to match the natural geometry and motion of the human hand. Traditional hand exoskeletons often trade off motion for structure or vice versa. This project aims to bridge that gap with a hybrid compliant design that balances flexibility and support. The design process followed an iterative approach involving rapid prototyping …

Fabricating Silver-Ceria Polymer Nanocomposite Scaffolds For Biomedical Therapeutic Applications, Shreya S. Pawar

Honors Undergraduate Theses

Improper healing of bone fractures and limited regeneration of bone following bone tumor resection remain a prevalent complication worldwide. Long-term effects of this include joint instability, limited movement, and arthritis. Bone infections (osteomyelitis), reactive oxygen species (ROS) generation via excessive inflammation, and underlying conditions such as osteoporosis can contribute to suboptimal bone tissue regeneration. ROS accumulation stimulates osteoblast apoptosis, while promoting osteoclast differentiation. These processes inhibit mineralization and osteogenesis. Conventional therapeutics involve the utilization of drugs and bone grafts. However, these approaches pose limitations and can result in subsequent complications. Microbial infections, ROS accumulation, and excessive inflammations are factors that …

High-Performance Computational Kernels For Algorithm-System Co-Design In Machine Learning: Enabling Efficient Gcn Training And Llm Inference Serving., Shakya D. Jayakody Arachchige

Graduate Thesis and Dissertation post-2024

The rapid advancement of machine learning, from Graph Convolutional Networks (GCNs) to transformer-based Large Language Models (LLMs), continues to expose fundamental limitations in memory efficiency, scalability, and system reliability. GCNs are critical for domains such as biomedical modeling, social networks, and recommendation systems, yet their reliance on sparse general matrix–matrix multiplication (SpGEMM) makes them highly sensitive to GPU memory constraints and irregular access patterns. As graph data scales, out-of-core computation becomes inevitable, but existing systems are hindered by I/O bottlenecks and underutilized GPU resources. Our contribution with AIRES demonstrates how algorithm–system co-design can alleviate these challenges: by introducing block-wise data …

Development Of Generalizable Data-Driven Traffic State Prediction Solutions: A Comprehensive Approach, Md Mobasshir Rashid

Graduate Thesis and Dissertation post-2024

Increased urbanization and population growth lead to more traffic in the transportation system, causing severe congestion. Particularly during disruptive events such as hurricanes or traffic incidents, the traffic flow in the network worsens significantly. As a result, there is a need for data-driven traffic prediction models to reduce congestion in real-time, and the prediction model should be generalizable to be applicable across different dynamic scenarios. Additionally, a robust and adaptable traffic prediction model can help traffic managers to take proactive actions to optimize traffic flow. However, the majority of data-driven traffic prediction models suffer from limited applicability as they are …

Novel Nanomaterial-Based Platforms For Bio-Electrochemical Sensing And Photocatalytic Treatment Of Contaminants Of Emerging Concern In Water, Jonghyun Baik

Graduate Thesis and Dissertation post-2024

This dissertation presents the development of novel nanomaterial-based platforms for bio-electrochemical sensing and photocatalytic treatment of contaminants of emerging concern (CECs) in water, including heavy metals, polycyclic aromatic hydrocarbons (PAHs), per- and polyfluoroalkyl substances (PFAS), and microcystin toxins. Conventional detection and remediation methods are often costly, time-consuming, and impractical for field use. To overcome these limitations, in this dissertation, five distinct platforms were designed, developed, and evaluated under various water conditions.

First, a microbial fuel cell (MFC)-based biosensor was developed for detecting heavy metals (Cu²⁺ and Hg²⁺) and PAHs (benzene and xylene). The system exhibited rapid, linear …

Quantifying Surrogate Safety Measures And Traffic Delays At Mid-Block Pedestrian Crossings Using Video-Based Data Analytics, Md Jamil Ahsan

Graduate Thesis and Dissertation post-2024

This study presents a comprehensive evaluation of midblock pedestrian crossings in terms of safety and traffic efficiency, with a particular focus on the newly implemented Mid-Block Pedestrian Signal (MPS) systems. Extensive CCTV video data were collected across Florida and processed using advanced computer vision techniques, specifically the RT-DETR model for object detection and the ByteTrack algorithm for object tracking, to analyze vehicle-pedestrian interactions in detail. Since there is limited post-implementation crash data available for all locations, Surrogate Safety Measures (SSMs) were employed to assess safety outcomes. Conflict Modification Factors (CoMFs) were estimated using Cross-Sectional (CS), Comparison Group (CG), and Empirical …

Development Of A Data-Driven Decision Support System For Intelligent Traffic Management At Intersections, B M Tazbiul Hassan Anik

Graduate Thesis and Dissertation post-2024

Intersections are complex traffic environments where frequent vehicle and pedestrian interactions can lead to safety- and mobility-critical (SMC) conditions. Identifying these conditions promptly is crucial, as delays may result in missed interventions, thereby heightening crash risk, and diminishing operational efficiency. This dissertation introduces a data-driven, real-time decision support framework for the identification and mitigation of SMC conditions using High-Resolution Traffic Controller Data (HTCD) collected via Automated Traffic Signal Performance Measures (ATSPM) system and Connected Vehicle (CV) data from Signal Analytics. First, an end-to-end analytical pipeline was developed to transform HTCD into actionable safety and mobility measures. A Bayesian beta-binomial framework, …

Chondrogenic And Chondroprotective Response Of Composite Collagen I/Ii-Hyaluronic Acid Scaffolds Within An Inflammatory Osteoarthritic Environment, Carly M. Battistoni, Javier Munoz Briones, Douglas K. Brubaker, Alyssa Panitch, Julie C. Liu

School of Chemical Engineering Faculty Publications

Inflammation plays a key role in cartilage damage that occurs in osteoarthritis (OA). However, in vitro assessments of tissue-engineered constructs for cartilage regeneration generally do not consider their performance in the presence of inflammation. In this work, the chondrogenic differentiation potential of mesenchymal stromal cells (MSCs) was evaluated in the presence of both chondrogenic factors and inflammatory cytokines, and cartilage formation, degradative response, and inflammatory response were characterized. The addition of cytokines reduced cartilage production, increased cell proliferation, and resulted in an increase in inflammatory markers. Incorporation of hyaluronic acid (HA) had little impact on both collagen fibril microstructure and …

Considerations Of Undrained Behavior Of Compacted Clay Embankments Under Extreme Wetting-Drying Cycles, Ghada Ellithy, John F. Peters

Publications

Many geotechnical analyses, including slope stability, involve unsaturated soils or soils in thevadose zone. Undrained loading happens when the increase in driving forces occurs quicker thanthe ability of the soil to dissipate its pore-water pressure (PWP). During undrained loading forcompacted clay embankments, in which the material is typically unsaturated, it has beenestablished that the increase in shear strength caused by an increase in confining pressure is largerthan the reduction in shear strength due to a decrease in matric suction. This concept is not wellestablished in engineering practice because the conventional understanding is that the strength ofunsaturated soils is larger than …

Efficient And Test-Time Adaptive Visual Object Tracking In The Wild, Ram J. Zaveri

Graduate Theses, Dissertations, and Problem Reports (ETD)

Tracking a single object, given the location at the first frame, has been an ongoing challenge in the vision community for decades. Most recent approaches provide reasonably good performance, especially when benchmarked on in-distribution (ID) datasets, i.e., on the testing portion of the same datasets used for training. However, they incur high computational costs and hardware constraints, making their deployment in the wild for mobile, autonomous, and IoT applications still challenging. Efficient visual trackers address the efficiency aspect of such bottlenecks; however, they tend to overfit to their training distributions and lack generalization abilities, resulting in them performing well on …

Design And Simulation Of An Ai-Powered Autonomous Quadrotor Framework For Search And Rescue Operations, James J. Shope

Graduate Theses, Dissertations, and Problem Reports (ETD)

Unmanned aerial vehicles (UAVs), particularly quadrotor platforms, have proven to be indispensable tools for search and rescue (SAR) teams due to their maneuverability, rapid deployment, and affordable operation. The current SAR use cases of quadrotors span from aerial surveillance to mission planning and strategic deliveries. However, most SAR applications remain passive or semi-autonomous, such that they rely on human-operated control or data assessment. Advancements in autonomous control strategies bring about a future where a single SAR operator can program and deploy several UAVs. This thesis details the development and simulation of a fully autonomous, AI-powered quadrotor framework capable of detecting …

Microwave-Assisted Reduction Of Critical Metal Oxides From E-Waste Mixture, Kurundu Shavinka Jayasekera

Graduate Theses, Dissertations, and Problem Reports (ETD)

The efficient recovery of critical metals such as tantalum (Ta), manganese (Mn), gallium (Ga), and indium (In) from electronic waste (e-waste) is essential for resource sustainability and environmental protection. This research uses microwave-assisted treatment to investigate the carbothermal reduction of these four specific metals from their oxides in a simulated e-waste mixture, with carbon black serving as both a microwave coupling and reduction agent. Microwave processing is used specifically because it offers a rapid and energy-efficient alternative to conventional thermal methods, with the benefits of intrinsic heating and selective heating of materials. The first experiments centered on understanding the effects …

Estimation Of Energy Use Intensity By Space Usage At Minnesota State University, Mankato, Rocio Alvarado Ramirez

All Graduate Theses, Dissertations, and Other Capstone Projects

This thesis creates a model that serves as an evaluation tool for testing decarbonization strategies on energy-related projects at Minnesota State University, Mankato, by estimating Energy Use Intensity for different types of spaces across campus. These EUIs can be used to predict future energy consumption when space usage changes and also serve as a baseline for dynamic energy modeling. The methodology used was a regression-based spreadsheet model proposed by Dr. Shreshth N. and originally applied at the Massachusetts Institute of Technology. EUIs were estimated across five different scenarios, and for electricity, steam, and chilled water. Three criteria were used to …

Gfrp Reinforced Bridge Barriers: Experiment Testing, Manish Kumar Gadhe

Masters Theses

This study focused on evaluating the performance of concrete bridge barriers reinforced with Glass Fiber Reinforced Polymer (GFRP) compared to those reinforced with conventional mild steel. Four full-scale barriers were constructed, three using GFRP bars as the reinforcement and one with mild steel reinforcement. These were cast on two concrete slabs to ensure consistent support conditions. The use of GFRP aims to address durability concerns associated with steel reinforced concrete (RC), particularly corrosion of these bars in harsh environments.

To simulate real-world impact scenarios, a weighted cart was launched at each barrier using a guided sled system. Sensors, including load …

Polymeric Nanocomposites-Based Advanced Coatings For Antimicrobial And Antiviral Applications: A Comprehensive Overview, Rachid Amrhar, Jaspal Singh, Mostafa Eesaee, Pascal Carrière, Alireza Saidi, Phuong Nguyen-Tri

Revues de littérature, synthèses de connaissances

The rise in microbial infections and viral outbreaks has accelerated the development of advanced antibacterial and antiviral coating that effectively minimize infection risks. Amidst rising global health concerns due to infectious diseases, these coatings have emerged as vital solutions for surface protection across various settings. This review focuses on the recent development and in-depth analysis includes synthesis process, inactivation mechanism in photoreactive antimicrobial and antiviral bio-coatings. This review comprehensively explores the development of different nanocomposite materials, including polymers based on metal oxide nanoparticles, metal nanoparticles, graphene-based materials, and organic-inorganic composites. Their practicality and compatibility with diverse surfaces such as ceramics, …

How Do Human And Ai Gender Bias Interact In Hiring Decisions?, Eyuel Getahun, Daniel Burton Shank, Casey I. Canfield, Jessica L. Cundiff, Jenny L. Davis, Celia Freed

Psychological Science Faculty Research & Creative Works

The hiring process is crucial for organizational success but has long been troubled by human biases. Many organizations now include AI in their hiring protocols to mitigate these biases and increase efficiency. However, AI itself can have biases baked-in. Human biases and AI biases are distinct but related; here, we examine how human and AI biases interact to affect hiring outcomes. Through an online experiment, we examine this question in the context of gendered hiring for a male-dominated leadership position in electrical engineering. The study tests how elevated and depressed AI recommendations for male and female job candidates affect participant …

Comparison Of Cnn And Lstm Networks On Human Intention Prediction In Physical Human-Robot Interactions, Khosro Ghorbani Zadeh, Niloofar Zendehdel, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Ming-Chuan Leu, Yun Seong Song

Psychological Science Faculty Research & Creative Works

Advancements in robotics and AI have increased the demand for interactive robots in healthcare and assistive applications. However, ensuring safe and effective physical human-robot interactions (pHRIs) remains challenging due to the sophistication of human motor communication and intent recognition. Traditional physics-based models struggle to capture the dynamic nature of human force interactions, limiting robot adaptability. To address these limitations, neural networks (NNs) have been explored for force-movement intention prediction. While multi-layer perceptron (MLP) networks show potential, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks effectively model sequential dependencies, while Convolutional Neural Networks (CNNs) enhance spatial feature …

Integrating Sustainability Into Aviation Training: Perspectives From Industry Professionals, Eva Maleviti, Sarah Talley

Publications

This paper is part of a broader research project aimed at identifying the most appropriate training materials, formats, and delivery methods for aviation sustainability content for future aviation professionals, starting from the early stages of their training. The current paper presents the data analysis and results of a short online survey targeting aviation professionals. Specifically, it provides preliminary data on sustainability perspectives from global aviation professionals. Through qualitative analysis, the creation of a baseline from a random sample of aviation professionals offers insight into their perspectives and how they could be influenced toward a more sustainable pathway. Additionally, the paper …

Nebraska Test #2302: Claas Xerion 12.650 Terra Trac, Nebraska Tractor Test Lab

Nebraska Tractor Tests

ABOUT THE TEST REPORT AND USE OF THE DATA The test data contained in this report are a tabulation of the results of a series of tests. Due to the restricted format of these pages, only a limited amount of data and not all of the tractor specifications are included. The full OECD report contains usually about 30 pages of data and specifications. The test data were obtained for each tractor under similar conditions and therefore, provide a means of comparison of performance based on a limited set of reported data. EXPLANATION OF THE TEST PROCEDURES Purpose The purpose of …

Nebraska Test #2300: Claas Xerion 12.590 Terra Trac, Nebraska Tractor Test Lab

Nebraska Tractor Tests

ABOUT THE TEST REPORT AND USE OF THE DATA The test data contained in this report are a tabulation of the results of a series of tests. Due to the restricted format of these pages, only a limited amount of data and not all of the tractor specifications are included. The full OECD report contains usually about 30 pages of data and specifications. The test data were obtained for each tractor under similar conditions and therefore, provide a means of comparison of performance based on a limited set of reported data. EXPLANATION OF THE TEST PROCEDURES Purpose The purpose of …

Nebraska Test #2268: Case Ih Steiger 595, Nebraska Tractor Test Lab

Nebraska Tractor Tests

ABOUT THE TEST REPORT AND USE OF THE DATA The test data contained in this report are a tabulation of the results of a series of tests. Due to the restricted format of these pages, only a limited amount of data and not all of the tractor specifications are included. The full OECD report contains usually about 30 pages of data and specifications. The test data were obtained for each tractor under similar conditions and therefore, provide a means of comparison of performance based on a limited set of reported data. EXPLANATION OF THE TEST PROCEDURES Purpose The purpose of …

Fungal Recycling, Arden Yale, Alannah Ridgway

Student Research Design & Innovation Symposium

Fungal recycling is a developing technique that turns garbage into food. To do this, the presenters created a new method of growing fungi of all different types (e.g. white oyster, lion's mane, etc.) and inoculating them into bags. These bags are sterile and contain a few key ingredients: coco coir, grain pellets, and shredded cardboard boxes. These boxes are taken from anywhere, mostly from lab equipment. Using the coco coir and grain pellets as a "starter", the fungi used the cardboard as a growing medium, literally growing food from trash. The technique is currently being refined. This project could bring …

Wearable Lanyard Acc For On-Demand Communication, Valerie Rosario, Rileigh Kearney, Hailey Soares, Kristen Martinez, Hannah Pereira

Student Research Design & Innovation Symposium

Augmentative and Alternative Communication (AAC) devices help individuals experiencing challenges with verbal communication, including English language learners, individuals who are hard of hearing, on the autism spectrum, or those experiencing anxiety disorders. Current technologies include low-tech communication boards and complex mobile applications, but both of these offer little customization. Our prototypes integrate touch-sensing panels and small LCD screens into common wearables, like necklaces and lanyards, so that the ACC discretely blends in with everyday apparel and provides on-demand communication that is customizable to the individual user. The touch-sensing pads are sensory-friendly, and the LCD screens operate without sound to support …

Horizontal Infiltration Of Water Through Porous Snow As A Gravity Current, Anthony Cheng

Dartmouth College Master’s Theses

On the surface of the Greenland ice sheet or around the margins of the Antarctic ice shelf, water infiltrates porous ice. It is important to understand this infiltration process since water populating the pore space of ice directly impacts the density, porosity, and wetness of ice. These properties influence the mechanics and tensile strength of ice, as greater amounts of infiltration result in faster or more widespread deformation events, which may lead to adverse climatic effects such as sea level rise and ocean current disruption. While studies have considered the thermodynamics and fluid mechanics of water vertically percolating through snow …

The Implementation And Miniaturization Of A New Current Source Into The Consolidated Layout Of An Electrical Impedance Tomography Probe With A Novel Approach To Electrode Layout, Katherine M. Bullion

Dartmouth College Master’s Theses

Prostate cancer is the most highly diagnosed form of cancer in male subjects in the United States. As a result, over 100,000 radical prostatectomies are performed annually in the US [1]. However, it is currently very difficult for surgeons to confirm that all impacted tissues have been effectively removed from the patient. Positive surgical margins are an independent risk factor for the recurrence of cancer, yet currently there is no method to efficiently, intraoperatively assess the status of surgical margins during a radical prostatectomy. There is a need for a new tool that is small enough to fit into a …

Time Series Forecasting With Lstm: An Extensive Content Analysis, Andri Pranolo, Xiaofeng Zhou, Yingchi Mao

Knowledge Engineering and Data Science

This paper presents a comprehensive bibliometric and content review of the trend, architecture, and application of long short-term memory (LSTM) models for time series forecasting. The study aims to provide insights into the overall statistics and distribution of papers focused on LSTM for forecasting. Additionally, the research questions address the most highly cited papers based on LSTM approaches in forecasting, the most productive journals in this field, and identifying trends, gaps, summary tasks and their performance, datasets availability, and future research directions for LSTM in forecasting. This paper is a comprehensive review of LSTM for forecasting from 2017 to 2023 …

Prediction Of Audit Findings Using Deep Learning With Financial And Non-Financial Data: A Case Study In Province X, Fery Yohan Setiawan, Eko Mulyanto Yuniarno, Reza Fuad Rachmadi

Knowledge Engineering and Data Science

The implementation of the audit from the local government financial statements by The Audit Board of The Republic of Indonesia (BPK RI), especially for the Province X representative, are frequently faced by the various limitations, one of them being the required audit time. At this moment, the BPK RI representative of Province X doesn’t have the tools that are able to help the accurate of sample determination for the pick test, which resulted in this study proposing the application of multi-label classification to predict the findings of financial statement (Laporan Keuangan, LK) audits based on financial and non …

A Comparative Study Of Machine Learning Models For Javanese Wuku Classification: Exploring Svm, Naïve Bayes, And Cnn For Cultural Texts, Danang Arbian Sulistyo, Aji Prasetya Wibawa, Didik Dwi Prasetya, Fadhli Almu'iini Ahda, Agung Bella Putra Utama

Knowledge Engineering and Data Science

This study rigorously evaluates machine learning models for classifying culturally significant Javanese Wuku texts from the “Keagamaan atau Spiritual” category, a domain challenged by unique linguistic nuances and limited digitized resources. We compared Support Vector Machine (SVM), Naïve Bayes, and Convolutional Neural Network (CNN) on texts from five pivotal Wuku types (Sinta, Galungan, Kuningan, Sungsang, Warigalit) sourced from sastra.org, aiming to identify the most effective computational approach. The dataset comprises N = 1419 documents (T = 751.290 tokens), with per-class document counts reported for all five Wuku types. Our evaluation uses accuracy, precision, recall, F1-score, and …

Mapping Of Product Sales Potential Based On Brands In The East Kalimantan Region Using Hybrid Analytical Framework, Achmad F O Gaffar Mr, Mulyanto Mulyanto Mr, Arief Bw Putra Mr, Muhammad Taufiq Sumadi Mr, Emmilya Umma Aziza Gaffar

Knowledge Engineering and Data Science

In geographically dispersed markets, operational costs should be reflected in sales planning to support accurate performance evaluation. However, such considerations are often neglected in practice. This study proposes a hybrid analytical framework to map brand-based product sales potential, with and without operational cost consideration, using historical sales data from PT Karya Inti Total Anugerah (PT KITA) in East Kalimantan. The framework integrates spatial, statistical, and machine learning techniques. Principal Component Analysis (PCA) is used to reduce the dimensionality of variables related to travel distance, total sales, and units sold, where travel distance represents the primary contributor to operational costs. K-Means …