Digital Commons Network^™

Comparative Analysis Of Leaflet Materials, Stent Materials, And Stent Cell Density For Bileaflet Transcatheter Mitral Valve Design, Joseph Chibuike Nwokeafor, Joshua D. Hofmeister, Breandan B. Yeats, Lakshmi Prasad Dasi, Charanjit S. Rihal, Juan A. Crestanello, Leigh Griffiths, Mohamad A. Alkhouli, Hoda Hatoum

Michigan Tech Publications

Background: The biomechanical performance of bileaflet transcatheter mitral valves (TMVs) depends on complex interactions between leaflet material behavior and stent design. However, the contributions of leaflet materials and constitutive models, stent materials, and stent geometry to valve function and durability remain poorly understood. Methods: A parametric finite element study was conducted using a CAD model of a bileaflet TMV subjected to physiological pressure loading. Five leaflet material models were evaluated: 3 glutaraldehyde-fixed tissues—bovine pericardium (BP; FBP1, FBP2) and porcine pericardium (PP; FPP)—and 2 unfixed tissues—bovine (UBP) and porcine pericardium (UPP). BP was modeled as a linear elastic (FBP1) and Ogden …

Design Of Precise Hinges For Optical Space Arrays, Jacob Sutton

Theses and Dissertations

Deployable origami-based arrays offer significant advantages for space optical systems due to their ability to stow compactly and deploy to a large surface area. However, achieving the panel alignment precision required for optical applications remains an open challenge, particularly for non-rigid-foldable patterns such as the flasher, where large relative motion during deployment and geometric constraints at panel interfaces limit the effectiveness of traditional hinge designs. This thesis addresses the precision alignment challenge through the design, prototyping, and experimental testing of novel passive precision hinges for rigid-panel origami-based deployable space arrays. A compact kinematic coupling hinge incorporating Lamina Emergent Torsional (LET) …

Optimization Of Cyanide Leaching Process Based On Grain Size And Slurry Density In Artisanal Small-Scale Gold Mining In Tatelu Area, North Sulawesi, Indonesia, Dadan Mohamad Nurjaman, Harmin Sulistiyaning Titah, Adji Kawigraha, Ipung Fitri Purwanti, Wahyu Hidayat

Journal of Sustainable Mining

Artisanal and small-scale gold mining (ASGM) in Tatelu Village, North Sulawesi, has shifted from mercury amalgamation to cyanide leaching. However, gold recovery remains inefficient, requiring process optimization. This study uses multiple linear regression analysis to evaluate the influence of grain size and slurry density on gold dissolution. The results indicate that grain size plays a dominant role in leaching efficiency, while slurry density, pH, temperature, dissolved oxygen (DO), and cyanide concentration have statistically insignificant effects (p > 0.05). Laboratory tests show that finer grain sizes enhance dissolution, with the highest recovery rate of 89.08% achieved at 75% passing through 44 …

Rape Pregnancies And Consequent Ptsd Resulting From The Overturn Of Roe V. Wade, Emma Lindenfelser, Yulia Garaeva, Nenette Nti-Agyemang, Ellen Davis, Anna Kabwa, Alexandra M Calaman

Binghamton University Undergraduate Journal

Prior to the 1973 Roe v. Wade ruling, access to safe legal abortions was limited and often restricted along racial, economic, and geographic lines. Nearly fifty years later, women’s health policy evolved again following the 2022 Dobbs v. Jackson Women’s Health Organization decision overturning Roe v. Wade. This court ruling decimated federal protections of abortion. This paper presents the research that the 2022 Dobbs judicial decision may contribute to and exacerbate rape-related PTSD on 1 out of 20 American who are unable to access a safe abortion after a rape-related pregnancy. Pregnant women living in conservative states that have outlawed …

Investigation Of Portland Limestone Cement Blended With Biochar From Downdraft Gasification: Hydration Kinetics, Microstructure, Rheology, And Performance Mechanisms, Ugochukwu Ewuzie, Paul C. Ani, Abdulkareem O. Yusuf, Joseph D. Smith, Monday Uchenna Okoronkwo

Chemical and Biochemical Engineering Faculty Research & Creative Works

The widespread adoption of Portland Limestone Cement (PLC) in U.S. concrete production has necessitated research into commercially available supplementary cementitious materials (SCMs) for formulating high-performance, low-carbon blended binders with PLC. This study investigated the influence of biochar (BC) in biochar-PLC composites (CBCs), focusing on hydration kinetics, microstructure, rheology, pore-solution chemistry, compressive strength, and the underlying mechanisms. Biochar was produced via downdraft gasification at 850 °C and incorporated into PLC at 5, 7, and 10% substitution by mass. Isothermal calorimetry and hydration data modeled using the Knudsen equation revealed that BC retarded early hydration but improved hydration degree and later-age heat …

Implementation Of A Mixed Precision Iterative Solver On An Amd Apu, Saeyeon Kim, Henrik Evers

Computer Science and Engineering Senior Theses

Solving systems of linear equations is a core operation in high-performance computing and many scientific and engineering applications. One of the most widely used direct methods for solving such systems is LU factorization. Mixed-precision methods accelerate these solvers by using low-precision LU factorization with iterative refinement, improving performance and energy efficiency while preserving high numerical accuracy. AMD Accelerated Processing Units (APUs), which integrate CPU and NPU resources, provide an opportunity to explore this approach on emerging heterogeneous architectures. However, effective NPU utilization remains challenging due to workload partitioning, buffer management, data-movement overhead, and software tooling limitations.

This project implements a …

Matching Two Long Interferometric Pathlengths Using Low Temporal Coherence Light For Finding Hong–Ou–Mandel Dip, Keith A. Wyman, Noah S. Everett, Anil K. Patnaik

Faculty Publications

Hong–Ou–Mandel (HOM) dip from a biphoton source in a two-photon interferometer provides a myriad of quantum tools for quantum communication and sensing. But the stringent requirements for spatial coherence between the photon pair makes it prohibitively difficult to observe high-fidelity HOM dip in long-distance free-space implementations, e.g., for the photon pairs involved in quantum communication need to match the two path lengths within a few 10 s of micron because of the short coherence width of the two-photon wave-packet. While many techniques for the pathlength balancing of two interferometric arms have been studied and applied extensively, such balancing is further …

Declination Of Groundwater Potential Zones Of Nashik, Maharashtra Using Geographic Information System With Analytic Hierarchy Process-Fuzzy Techniques, Madhusudhan M. Reddy, Bhogayya G. Naidu, Bharat N. Mulay, Ramanjaneyulu B, Ravi K. Kumar, Mirzi L. Betasolo, Praveen U. Goud, Snehal N. Chaudhari

Mansoura Engineering Journal

Groundwater is a critical resource for agriculture and domestic use in the semi-arid region of Nashik District, Maharashtra, where overexploitation and erratic climatic conditions have led to declining groundwater availability. This study integrates Geographic Information System (GIS) with Analytic Hierarchy Process (AHP) and Fuzzy-AHP techniques to delineate groundwater potential zones (GWPZs) and identify suitable sites for artificial recharge. A total of ten thematic layers drainage density, rainfall, geomorphology, elevation, distance from river, geology, slope, land use/land cover, topographic wetness index (TWI), and curvature were derived from SRTM DEM, Landsat-8, and IMD datasets, representing key controls on groundwater recharge, infiltration, and …

Fatigue Behavior Characterization Of Magnesium And Aluminum Alloys In Military Trainer Aircraft, Alysson Sousa Rabelo, José Aécio Gomes De Sousa, Feliciano José Ricardo Cangue, Luiz Leroy Thomé Vaughan

Journal of Aviation Technology and Engineering

The increasing demand for lightweight and durable materials in aviation industry necessitates continuous improvements in research into fatigue-resistant alloys to improve operational efficiency, safety, and cost-effectiveness. The estimation of the operational life of aeronautical structures is directly related to the study of their mechanical properties, particularly concerning fatigue behavior due to the constant exposure to cyclic loads. For this reason, the aeronautical sector often invests significant capital in research for the development of new alloys that enable high structural performance, lightness, low cost, high durability, and tolerance to environmental damage. Despite the advancements in composite materials, aluminum and magnesium alloys …

A Provable Semi-Infinite Programming Approach For Solving Constrained Dynamic Games, Tyler C. Gardner, Matthew W. Harris, Logan Lancaster

Mechanical and Aerospace Engineering Student Publications and Presentations

Many engineering problems must account for the non-cooperative decisions and actions of multiple players. These problems can be modeled within a game-theoretic framework. The approach herein is to model such problems as mathematical games, convert them to semi-infinite programs, and utilize a semi-infinite program solver whose output is provably an ϵ-optimal Nash equilibrium. The approach is successfully benchmarked on two low-dimensional problems. Two types of higher-dimensional linear quadratic dynamic games are then investigated: ones where each player’s problem is convex and ones where at least one player’s problem is nonconvex. Within each type, variations based on information structure, control …

Bilingual Math For Kindergartners (Biki), Anna Aldrin, Caroline Tapia, Lillian Le

Computer Science and Engineering Senior Theses

For many children from bilingual households, kindergarten represents a critical, learning benchmark where the introduction of fundamental math concepts coincides with their first significant exposure to the English language. Traditional educational methods often fail to support English language learners, leading to a disconnect between their understanding of math in the home and its application in the classroom. This linguistic barrier frequently results in reduced engagement, diminished confidence, and an unstable educational foundation that can discourage students from pursuing STEM careers later in life. While existing platforms like Khan Academy and Duolingo address either language acquisition or mathematical proficiency independently, they …

Winddensity-Mbir: Model-Based Iterative Reconstruction For Wind Tunnel 3d Density Estimation, Karl J. Weisenburger, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Faculty Publications

Experimentalists often use wind tunnels to study aerodynamic turbulence, but most wind tunnel imaging techniques are limited in their ability to take non-invasive three-dimensional (3D) density measurements of turbulence. Wavefront tomography is a technique that uses multiple wavefront measurements from various viewing angles to non-invasively measure the 3D density field of a turbulent medium. Existing methods make strong assumptions, such as a spline basis representation, to address the ill-conditioned nature of this problem. We formulate this problem as a Bayesian, sparse-view tomographic reconstruction problem and develop a model-based iterative reconstruction algorithm for measuring the volumetric 3D density field inside a …

A Comprehensive Survey Of Artificial Intelligence Applications In Predicting Mining-Induced Subsidence, Deformation, And Landslides: Strengths, Limitations, And Future Trends, Long Quoc Nguyen, Dung Ba Nguyen, Minh Tuyet Dang

Journal of Sustainable Mining

Mining activities often cause mining-induced ground deformation, including subsidence and landslides, and related geo-environmental impacts, posing significant risks to infrastructure and safety. This study conducts a systematic assessment to identify, categorize, and evaluate AI-based methods (machine learning, deep learning, and hybrid models) for predicting and monitoring mining-induced ground deformation. The literature search was performed across major scientific databases, using predefined keywords and selection criteria, resulting in a final dataset of relevant peer-reviewed studies. The reviewed works were classified into three methodological groups: traditional machine learning, deep learning-based approaches, and hybrid methods. The results show that ML still dominates in terms …

Decoding Stock Market Movements: The Role Of Unemployment And Volatility, Bipllab Roy, Suparna Bhattacharjee

Northeast Journal of Complex Systems (NEJCS)

This study investigates how unemployment and market volatility interact with stock prices in the Indian context, framing the stock–labour–volatility nexus as a complex adaptive system (CAS) rather than a set of linear, time-invariant relationships. Using verified secondary data on unemployment, India VIX, and NSE stock indices for 2013–2023, we first apply simple and multiple regression as a descriptive baseline. Results show a strong negative association between unemployment and stock prices (R ≈ 0.824, R² ≈ 0.68, p < 0.05), consistent with Keynesian demand-side channels, while the linear VIX–stock relationship is weak and statistically insignificant (R² ≈ 0.07, p > 0.05), consistent with the expectation that volatility operates through non-linear, regime-dependent mechanisms not captured by OLS.

Importantly, we document and transparently disclose critical …

Multidomain Modeling And Ramp-Aware Forecasting Of Floating Photovoltaic Systems For Water-Energy Nexus Applications, Md Atiqur Rahaman

Doctoral Dissertations

Floating photovoltaic (FPV) systems have become a transformative renewable energy technology because of their cooling effects on PV performance and ability to prevent water evaporation in land-constrained areas. Although FPV systems have the potential to become a commercially viable technology, their large-scale deployment remains constrained by uncertainties in thermal behavior, sustainability, and grid-operational variability. This dissertation identifies and characterizes these three key issues and presents an integrated, measurement-based evaluation of a 130 kW FPV installation located at the Passaúna reservoir in Brazil. In the first contribution, four temperature models, including physical and empirical models, were developed and comparatively evaluated to …

Automating Distillation Column Internals Design Via Reinforcement Learning: A Hybrid Action Space Approach, Holden B. Broussard

Masters Theses

Distillation columns are the most used separation technique in all chemical fields. The design of column internals presents a hybrid action space problem, where trayed internal parameters are continuous and packed parameters are discrete; Hybrid meaning the action space consists of both discrete and continuous design parameters. Hybrid action spaces have presented a challenge in the reinforcement learning space, since the most robust algorithms are designed to handle specific action types. This research develops and validates a hierarchical multi-agent reinforcement learning framework that divides the action spaces into different agents. The Controller agent selects between internal types, the Soft Actor- …

Hyperdimensional Computing For Edge And Mobile Devices, Colin Eddy Dupuis

Masters Theses

This thesis presents a set of four Hyperdimensional Computing (HDC) frameworks and their Android application implementations to evaluate efficiency and feasibility on resource-constrained devices. These proposed methods target a range of application domains, including wearable health monitoring, mobile malware detection, and activity recognition utilizing both computer vision and multiple sensor streams as input. The proposed frameworks utilize HDC’s simple, lightweight arithmetic operations to convert raw data into high-dimensional representations for use in both binary and multi-class classification schemes. Each method utilizes unique encoding techniques tailored for each use case, demonstrating the flexible nature and specialization HDC offers as an emerging …

Geological Carbon Storage In Deep, Low Permeable Shale Reservoirs: Insights From The Haynesville Formation, Louisiana, Himakshi Goswami

Masters Theses

As global initiatives to mitigate greenhouse gas emissions intensify, depleted unconventional shale gas formations have emerged as critical candidates for large-scale geological carbon storage (GCS). This study investigates the feasibility, dynamic trapping mechanisms, and operational optimization of CO₂ sequestration in deep, low-permeability shale reservoirs, using the Upper Jurassic Haynesville Shale in northwest Louisiana as a comprehensive case study. Compositional reservoir simulation (CMG GEM 2021.10) was performed using the SPE Haynesville dataset, with CO₂ injected at a rate of 10,000 ft³/day across single and multiple depth intervals spanning 11,290–11,314 feet. Results demonstrate that multi-depth injection significantly improves residual trapping, reduces buoyancy-driven …

Optimizing Co₂ Wag Flooding Parameters For Enhanced Oil Recovery And Formation Damage Control In Asphaltene Reservoirs Using Soft Experimentation, Derrick Amoah Oladele

Masters Theses

CO₂ Water Alternating Gas flooding has become an important enhanced oil recovery process in increasing oil production in medium to heavy oil reservoirs. However, CO₂ injections have the potential to cause asphaltene destabilization, leading to precipitation, deposition, and pore plugging. This study evaluated and optimized the effect of CO₂ flooding parameters to maximize oil recovery and minimized formation damage. Eclipse 300 compositional reservoir simulator was used to assess the effect of CO₂ Water Alternating Gas (WAG) Injection Rate, WAG Ratio, and CO₂ Water Alternating Gas (WAG) Injection Pressure on the reservoir. Predictive models for Cumulative Oil Production (FOPT) and Asphaltene …

Jsd: Novel Methodology For Synthetic Data Evaluation, Jeffrey Lane, Scott Wang, Vincent Chang, Bojun Zhang

Computer Science and Engineering Senior Theses

The proliferation of sensitive Personally Identifiable Information (PII) on dark web marketplaces has created an urgent need for robust data protection systems, especially for vulnerable populations such as minors. Traditional PII redaction often fails to identify implicit privacy risks—such as author gender indicators or non-fictional child-related context—hidden within large-scale e-commerce datasets. This paper presents JSD, a dual-stage framework for the detection and protection of sensitive text data. The Detection phase utilizes Transformer and CNN-based architectures and Human-in-the-Loop AI to surpass the "semantic ceiling" of traditional NER approaches, enabling context-aware identification of implicit PII. The Protection phase introduces GASE (Genetic Algorithm …

Hemlock, Ephraim Esson, Ambrose Vellequette, Geno Meschi

Computer Science and Engineering Senior Theses

Hemlock is a tool designed to protect musicians from having their work used to train generative AI models without their consent. It works by adding carefully crafted inaudible noise to audio files that disrupts the ability of AI models to learn from them — a technique known as adversarial perturbation. Our system targets three different types of AI model simultaneously: a Music Information Retrieval (MIR) classifier, a sequential audio generation model (Mel-LSTM), and Meta’s AudioCraft, a transformer-based music generator. Testing in twenty songs showed an average 15% reduction in the MIR model’s classification confidence, a 59% increase in Mel- LSTM …

A Broadband, Dual Polarized Antenna For The Radio Neutrino Observatory In Greenland, Laken Baker

Electrical Engineering

Neutrinos contain information necessary to determine the origins of the universe and cosmic events because they can travel long distances with minimal interaction, preserving information about their cosmic origins. Since neutrinos interact with ice sheets resulting in RF radiation, antennas have been developed to detect RF transmissions.

A compact 'vane structure' (see Fig. 1a) dual-polarized broadband antenna model has been developed, constructed, and characterized according to input reflection coefficient, and co and cross-pol E and H plane radiation patterns using HFSS and Cal Poly San Luis Obispo’s anechoic chamber for the Radio Neutrino Observatory in Greenland (RNO-G) [1]. Its design …

A Workflow For Automating Geospatial And Data Visualizations For Post-Earthquake Building Damage Data, Alejandra Bravo

Architectural Engineering: Graduate Reports

After major seismic events, reconnaissance efforts of various types are made to gather data. Coarse data can be collected with satellite imagery, mid-scale data can be recorded by capturing thousands of images, and granular data is typically documented manually by humans. Post-earthquake reconnaissance teams can be deployed by universities, research organizations, professional associations, and private firms. Academics, engineers, and students with varying degrees of expertise are tasked with collecting building metadata and damage data, typically in a short period of time. This data can be of various types including numerical (i.e. number of stories, height, etc.), categorical (i.e. damage level, …

A Machine Learning Framework For Residential District Cooling: Forecasting Consumption, Explaining Drivers, And Evaluating Decarbonization Pathways, Kadhim Hayawi, Husna Maliakkal, Neethu Venugopal, Thanveer Musthafa Hussain, Gomathi Bhavani Rajagopalan

All Works

District Cooling Systems (DCS) in the Middle East, while energy-efficient, are significant contributors to carbon emissions. This study introduces a novel framework to decarbonize DCS operations by integrating predictive machine learning, explainable AI (XAI), and renewable energy planning, all grounded in extensive real-world data. Leveraging a unique dataset from 59 residential buildings in the UAE—including energy consumption, climate variables, and building features—we developed a high-fidelity cooling load forecasting model. Following a rigorous chronological validation methodology, the Random Forest model was identified as the most robust, achieving a strong performance (R² = 0.8256, RMSE = 11,668.31). Outdoor temperature was confirmed …

A Comparative Study Of Model Predictive Control And The Stanley Method For Vehicle Path Tracking Applications, Noah S. Fitzgerald

Master's Theses

This thesis compares a model predictive controller (MPC) and a lateral Stanley controller for vehicle path-tracking applications under simulation-based and perception-driven operating conditions. Both controllers were evaluated in simulation using a nonlinear dynamic bicycle model executing single and double lane change maneuvers. Following simulation-based evaluation, both controllers were implemented on hardware within a perception-driven steering-control pipeline. This pipeline utilized recorded sensor data from the MXcarkit 1/8^th-scale autonomous vehicle platform, incorporating lane instance segmentation and homography-based roadway estimation.

Under idealized simulation conditions, the MPC demonstrated improved trajectory-tracking performance during aggressive maneuvers while requiring greater steering activity and computational effort …

Constructing Orthonormal Bases With The Residuals Of Successive Approximations, An Introduction To Multiresolution Analysis, Elijah J. Guptill

Master's Theses

Wavelets and wavelet analysis are used in the study of signal processing, quantum field theory, functional analysis, multifractal analysis, and various other areas of mathematics. Multiresolution analysis provides a framework for building a wavelet basis of $\mathcal{L}^{2}(\mathbb{R})$ from a scaling function $\phi$, whose dyadic dilations and translations, $\{2^{j /2}\phi(2^{j}x-k):j,k\in \mathbb{Z}\}$, approximate $\mathcal{L}^{2}(\mathbb{R})$. One of the key properties of  $\phi$ is that it must satisfy $\phi(x)=\sum_{k\in \mathbb{Z}}{p_{k}2^{j /2}\phi(2^{j}x-k)}$ with respect to the norm on $\mathcal{L}^{2}(\mathbb{R})$. This equation is called a two-scale difference equation. Such equations enforce a regularity on the ordinary generating function $2^{-1 /2}\sum_{k\in \mathbb{Z}}{p_{k}z^{k}}$, known as the quadrature condition. …

Deep Learning For Affect Recognition: A Comparative Study Of Physiological Sensor-Based And Facial Image-Based Approaches, Ravi Panchal, Ravi Panchal

Master's Theses

This thesis investigates deep learning approaches for affect recognition using wearable physiological signals and facial image data. The sensor-based component evaluates stress and affect recognition on the WESAD dataset using wrist-based physiological windows and examines multiple temporal modeling strategies, including convolutional, recurrent, hybrid CNN-LSTM, attention-based, ensemble, and time-frequency approaches.

The image-based component evaluates hard-label facial expression recognition on AffectNet+ using pre-trained ResNet-50, EfficientNet-B3, and ConvNeXt-Tiny architectures across Easy, Challenging, and Difficult subsets representing different levels of expression ambiguity.

Experimental results show that the proposed Multi-Branch Attention CNN-BiLSTM (MBA-CNN-BiLSTM) model achieves the strongest wearable stress- and affect-recognition performance among the evaluated …

Reproducing And Evaluating Charger Surfing: Robustness Of Smartphone Charging-Line Side-Channels, Colby M. Watts

Master's Theses

Smartphones are frequently connected to external, untrusted charging hardware, creating opportunities for side-channel attacks that do not require malware or direct access to device data. Charger Surfing, a recently proposed charging-line power analysis side-channel attack, reported high accuracy in inferring touchscreen input from voltage measurements collected from a smartphone’s charging cable; however, the reproducibility and robustness of these results under different conditions remain unclear. This thesis presents an independent replication and evaluation of Charger Surfing, including the development of an end-to-end data collection pipeline consisting of a modified charging cable, oscilloscope-based recordings, custom Android app, automated trace processing, and convolutional …

Improving The Reliability And Performance Of A Supersonic Indraft Tube Wind Tunnel, Christian J. Kaml

Master's Theses

Access to supersonic testing is increasing in demand, and wind tunnels remain one of the safest and most cost-effective methods for gathering high-speed flow data. Despite being more economical than alternative options, supersonic wind tunnel facilities often require substantial investment to construct, operate, and maintain.

The novel indraft tube tunnel architecture was conceived as a high-speed flow testbed that incorporates features of both Ludwieg tubes and indraft wind tunnels to maintain costs low enough to be accessible even to small universities. This design was first developed and tested in 2018 at California Polytechnic State University, featuring a cost per test …

Design And Analysis Of A Customizable 6-Dof Force/Torque Sensor, Pyeongkang Kim

Master's Theses

This thesis presents the design, development, calibration, and testing of a novel customizable six-degree-of-freedom force/torque sensor, called the Kustom Force/Torque Sensor (KFTS), for use in the Cal Poly Low Speed Wind Tunnel (LSWT). The KFTS was developed as an alternative to commercial multi-axis force/torque sensors that feature fixed specifications. The swappable components and configurable structure of the KFTS enables changes to the sensor sensitivity, sensing range, and frequency response. Experimental testing verified that the sensor behaved as a linear time-invariant system, enabling calibration through the method of least squares and allowing the applied forces and moments to be reconstructed as …