Digital Commons Network^™

Stomp (The Student Organization Management Portal), Lindsey Leong, Madeline Follosco, Noelle Evanich, Irene Chang

Computer Science and Engineering Senior Theses

At Santa Clara University, the Center for Student Involvement (CSI) leads to support hundreds of student-led organizations with different audiences and ambitions, but all aim to bring students together nonetheless. However, such development regarding student organization management proves to be much harder when administrative processes are decentralized and cumbersome, often involving numerous layers of manual work and departmental bottlenecks. Restructuring and optimizing administrative workflows would entail more energy towards the growth of student life at Santa Clara University.

The Student Organization Management Portal, or StOMP, is a web application that aims to centralize and optimize student organization-related processes, as well …

Real-Time Corridor Counting, Erick Sun, Jacob Lin, Jayden Malhotra, Joseph Hissen

Computer Science and Engineering Senior Theses

Identifying traffic trends is a critical step in urban planning and design for the purpose of creating safer and more efficient roads. One such problem in the field of traffic data is corridor counting, which is the process of counting the unique number of vehicles that pass through a set of predefined intersections in a given time. In this paper, we develop an automated solution to perform corridor counting in real-time using camera footage and computer vision. We build upon the architecture of a previous Senior Design project, replacing and refining key components and architectural choices to improve accuracy and …

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 …

Investigations Of Carbon Dioxide Storage In Low-Temperature Reservoirs For Non-Leaking Storage, Md Nahin Mahmood

Doctoral Dissertations

Carbon dioxide (CO₂) injection into subsea or low-temperature water zones has emerged as a promising strategy for long-term, non-leaking CO₂ storage through the formation of solid hydrates. This research investigates CO₂ injection into Berea sandstone cores saturated with water under simulated subsea conditions, focusing on hydrate formation behavior across varying temperatures, pressures, and injection flow rates. Experimental results demonstrate that CO₂ hydrate formation under dynamic (flowing) conditions occurs at significantly higher pressure compared to static conditions reported previously. At temperatures ranging from 0 °C to 5 °C, dynamic hydrate formation pressures were observed to be approximately double. This can be …

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 …

Large-Scale Synthesis (75 G/Batch) Of Single-Atom Catalysts For Selective Electrochemical Co2 Reduction To Co And Commercialization Potential Analysis, Carter Racine, Ahmed Badreldin, John Pellessier, Yayun Chen, Shaoqin Chen, Shengyao Wang, Jin Feng, Chengcheng Fei, Yun Hang Hu, Ying Li

Michigan Tech Publications

A promising approach to mitigate climate change is to use renewable electricity to convert carbon dioxide (CO2) emissions into useful products like carbon monoxide (CO) and hydrocarbons. While research has largely focused on developing high-performance catalysts for electrochemical CO2 reduction (eCO2R), scalability of catalyst synthesis remains underexplored. Metal–nitrogen–carbon (M–N–C) catalysts with dominant single-atom sites are among the most effective materials for CO production, but conventional synthesis methods rely on energy-intensive steps and complex pre- and post-treatment processes, hindering scalability and adding negative environmental impacts. This work demonstrates a scalable, single-step synthesis of M–N–C (M = Ni/Fe) catalysts using commercially available …

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- …

A Simulation-Based Lean Six Sigma Framework For Process Optimization In Textile Manufacturing Toward Industry 4.0, Md Shafiqul Islam Chowdhury

Masters Theses

This study focuses on integrating simulation modeling with Lean Six Sigma (LSS) within the DMAIC (Define, Measure, Analyze, Improve, Control) framework for process optimization in textile manufacturing industry. Although traditional LSS framework such as Value Stream Mapping (VSM) and Root Cause Analysis are effective in identifying waste, they mainly rely on static and historical data which make their capability limited for real analysis or predictive decision making. As a result, many textile manufacturing processes still face challenges such as production delays, excessive work-in-process (WIP), high cycle time, and inefficient resource utilization. To address this issue, this research proposes a simulation-based …

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 …

Mitigating Surfactant-Gas Interactions In Associated Gas Reservoirs: A Simulation And Machine Learning Guided Approach, Francis Dela Nuetor

Masters Theses

Surfactant flooding is a promising chemical enhanced oil recovery (EOR) method for mobilizing residual oil through interfacial tension reduction and wettability alteration. However, its performance in associated-gas reservoirs can be limited by salinity, gas composition, surfactant adsorption, and possible chemical instability. This study investigates the effect of salinity on surfactant flooding efficiency using an integrated reservoir simulation and machine learning workflow. A synthetic three-dimensional reservoir model was developed in ECLIPSE using a 10 × 10 × 3 Cartesian grid to simulate surfactant flooding over a 300-day production period under salinity conditions ranging from 100 to 50,000 ppm. Key outputs, including …

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 …

Competitions Among Stations In Ieee 802.11be Networks, Jun Peng

Electrical and Computer Engineering Faculty Publications

The IEEE 802.11be standard aims for the next-generation applications that demand connections of extremely high bandwidth and low latency. It is the basis for Wi-Fi 7. An IEEE 802.11be device can operate in the 2.4, 5, and 6 GHz frequency bands simultaneously under the multi-link operation (MLO) mode. In the 6 GHz band, it can use a channel width up to 320 MHz. Its QAM-constellation can have up to 4096 states. Some of its other features include multiple resource units (MRU), preamble puncturing, and enhanced security. This paper shows the competitions among the stations in an IEEE 802.11be network with …

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 …

6tisch Based Sensing Network For Smart Agriculture, Riley Heike, Griffin Jones, Justin Odo, Jalen Paige, Rosalie Wessels

Computer Science and Engineering Senior Theses

This project investigates 6TiSCH (IPv6 over Time-Slotted Channel Hopping), a relatively recent IETF networking standard introduced in 2013 that combines deterministic TSCH scheduling, 6LoWPAN header compression, and RPL mesh routing to enable low-power, reliable, multi-hop wireless communication for IoT deployments. Despite its strong theoretical properties, 6TiSCH remains underexplored in practice, and real-world questions around configuration, scalability, power behavior, and end-to-end integration are not well documented. Our primary goal was to build and operate a working 6TiSCH network, characterize its performance through iterative testing, and understand what it takes to go from raw packet delivery to a complete data pipeline.

To …

Mimica, Sean Lai, Gurprasaad Hora, Stephanie Campos

Computer Science and Engineering Senior Theses

Language barriers remain a significant obstacle to natural human communication, limiting access to healthcare, business, travel, and daily social interaction for billions of people worldwide. Existing translation solutions such as smartphone applications and earpiece devices address the functional problem of converting words between languages but fail to preserve the speaker’s voice identity, require hands-on interaction, or depend on proprietary device ecosystems. These limitations disrupt the natural flow of conversation and reduce the human quality of cross-lingual communication.

Mimica is a real-time wearable translation necklace designed to address these shortcomings. Built around an ESP32-S3 microcontroller with an integrated microphone and speaker, …

Enhancing Occupational Comfort And Energy Performance In Administrative Buildings Through Thermochromic Glazing And Upvc Curtain Wall Systems, Sherihan Adel, Esraa E. Abu-Elenain

HBRC Journal

This study investigates the influence of curtain wall façade systems—defined as non-structural glazed enclosures—on workplace comfort and energy performance in administrative buildings in Cairo, Egypt. The research addresses the limited understanding of how façade orientation and the integration of sustainable materials affect building performance in hot-arid climates. The focus is on the role of Unplasticized Polyvinyl Chloride (UPVC) frames and thermochromic glazing in enhancing thermal, visual, and acoustic comfort. A mixed-methods approach was applied, combining 600 occupant questionnaires from six office buildings with performance simulations using DesignBuilder (v6.1.0.006). The findings showed that west- and southwest-facing façades provided poor daylighting and …

``Urban Expansion And Its Relationship To The Development Of New Cities (Applied Study On The New Egyptian Cities)'', Tarek Abdel Latif Abou El Atta, Aliaa Mamdouh Mahmoud

HBRC Journal

The Egyptian government adopted a policy of establishing new cities to address urban challenges such as rapid population growth and unbalanced population distribution, with the aim of redistributing residents and achieving more balanced urban development. However, many of these cities have not achieved their planned population growth, despite the continued issuance of urban expansion decisions, raising questions about the alignment of these decisions with demographic and developmental realities. This study aims to evaluate urban expansion decisions in Egypt's new cities by analyzing their relationship with urban development factors and the city's capacity to attract residents, as well as examining their …

Public Preferences For Critical Mineral Mining In The U.S.: Evidence From A Discrete Choice Experiment, Bamidele Ajiga, Kwame Awuah-Offei, Mahelet G. Fikru

Mining Engineering Faculty Research & Creative Works

Even though there is widespread recognition that we need to mine more critical minerals for national security and energy needs, concerns about environmental impacts often lead to public opposition to proposed new mining projects. The literature lacks sufficient data from communities with proposed mineral projects to assess drivers of differences in support. This study investigates public preferences for mining projects in three states in the United States with proposed critical minerals projects, using a discrete choice experiment. Respondents evaluated projects that vary in job creation, state tax revenue, tailings reprocessing content, groundwater impacts, and surface water impacts. We also randomly …

Recent Advances In The Rheological Properties Of Ultra-High-Performance Concrete: A Critical Review, Le Teng, Kamal H. Khayat, Jiaping Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Ultra-high-performance concrete (UHPC) with adapted rheology continues to attract interest considering the requirement for novel processing techniques such as self-consolidating, pumping, spraying, and three-dimensional (3D) printing. The rheology of UHPC is complex due to its high solid volume fraction, low water content, and wide range of constituent materials that affect its flow properties. This work provides guidance for tailoring the mixture proportioning of UHPC to secure proper rheological properties and performance of UHPC for various applications. In the first part of this work, key physical, physicochemical, and chemical factors that can affect the rheological properties of UHPC are discussed. Rheological …

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 Near-Field Communication (Nfc) Multi-Sensor Node With Optimized Read Range And Adaptive Power Management For Remote Monitoring, Rishin Patra, Hilary Scott Nkimbeng Cho, Jin W. Choi

Michigan Tech Publications

This paper presents the design of a batteryless near-field communication (NFC) multi-sensor node with an integrated adaptive power-management system for sensing applications. The work focuses on harvesting energy from a 13.56 MHz NFC field to power an ultra-low power sensing platform. The design consists of the TI RF430FRL152H, an integrated NFC transponder with an embedded MSP430 microcontroller core and ferroelectric random-access memory (FRAM) non-volatile memory. The system combines an ISO/IEC 15693 NFC front end, a tuned loop antenna for optimized power harvesting, and multiple analog and digital sensor interfaces, and a firmware architecture for intermittent harvested energy operation. The aforementioned …

Operation Bite Block, Jennifer Aline Robles, Laura Marie Strobbe, William Pearce Graham, Annabelle Katherine Thalken

Mechanical Engineering

Current dental bite blocks, or mouth props, are typically manufactured in fixed sizes, and often result in patient discomfort, reduced procedural efficiency, and the need for dental offices to maintain multiple product sizes. This project sought to design, prototype, and validate an adjustable dental bite block capable of accommodating a wide range of patient mouth openings while maintaining comfort, structural integrity, sterilizability, and operator usability. Working in collaboration with Dr. Alan Latta, a practicing dentist in San Luis Obispo, the design process incorporated stakeholder feedback, patent and market research, engineering analysis, and iterative prototyping to develop a solution that addresses …

Mars Rover Wheels And Drive, Presley S. Sacavitch, Ryan W. Trevena, Dylan A. Mack, Daniel Hudak

Mechanical Engineering

Cal Poly’s Poly1Rover team, advised by Professor Rich Murray, aims to deploy four student-designed mini-Mars rovers, each equipped with a sample-tube retrieval claw, before 2030. However, the wheels of Poly1Rover’s current 6th generation rover are not ready for deployment to Mars, as they do not utilize space-grade materials, are not optimized for manufacturability, and lack sufficient spoke compliance to absorb landing and high-impact loads. This project will be developed by a team of Mechanical Engineering students at California Polytechnic State University, San Luis Obispo (Cal Poly): Daniel Hudak, Dylan Mack, Presley Sacavitch, and Ryan Trevena. Next Intent is providing funding …

Formula Sae Planetary Gearbox Characterization Dynamometer, Trevor Marco Toma, Thomas Welden Pierce, Ethan Liu

Mechanical Engineering

This report outlines a custom hub motor dynamometer requested by the Cal Poly Racing FSAE team. The need for this testing platform is to characterize an existing Formula SAE planetary gearbox for a proposed 4WD powertrain. Hub motors, compact electric machines integrated directly into each outboard wheel, offer significant advantages in efficiency, traction, and chassis packaging compared to conventional RWD drivetrains. By mapping torque capacity, efficiency, lubrication method effectiveness, and fatigue life, the team can validate gearbox design and performance.

This senior project group designed and built a dynamometer according to these specifications which will allow for successful testing to …

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 …

An Exploratory Latent Segmentation Approach To Account For Temporally Shifting Parameters In Driver Injury-Severity Models, Tanmoy Bhowmik, Shahrior Pervaz, Fred Mannering, Naveen Eluru

Civil and Environmental Engineering Faculty Publications and Presentations

Temporally shifting parameters in crash severity modeling is a well-documented phenomenon, with growing evidence suggesting that the influence of explanatory variables changes over time due to shifts in driver behavior, vehicle technology, and roadway conditions. Many studies have examined this issue by comparing the temporal stability of adjacent-year data using a variety of modeling frameworks that have often assumed a homogenous effect of explanatory variables across the entire crash population. The current research effort departs from past work in two ways. First, it compares data separated by multiple years (instead of comparing adjacent years), and second, it tests the homogeneous …