Digital Commons Network^™

Computer Vision Methods For Detecting Counterfeit Usd Bills, Tyler W. Jones

Master's Theses

This thesis addresses the global challenge of counterfeit paper currency by proposing a classical computer vision framework for distinguishing genuine United States Dollar (USD) bills from counterfeit ones using image data. In contrast to existing approaches that rely on a large number of easily reproducible visual features, this work prioritizes the detection of a single, robust security feature: the ultraviolet (UV) reactive security strip embedded in genuine USD bills of denominations $5 and above. By focusing on a feature that is inherently difficult to replicate, the proposed method reduces the likelihood of counterfeit bills being misclassified as genuine.

The system …

Development Of A Free-Floating Space Robotic Simulator, Truman: Terrestrial Robotic Unit For Multibody Analysis And Navigation, Jackson W. Cordova

Master's Theses

This work describes the development of a 3 Degree-of-Freedom (DOF) robotic manipulator for use on a free-floating planar air-bearing vehicle. The system developed aims to serve as a foundation for future space robotics research at the California Polytechnic State University (Cal Poly)’s Space Robotics Laboratory. Systems doc- umentation describes conceptual operation and architecture of the proposed system: Terrestrial Robotic Unit for Multibody Analysis and Navigation (TRUMAN). The key operation of TRUMAN is to study a self launch maneuver of a free-floating ve- hicle including 4 distinct phases: launch off a fixed rail, coast, reorientation using manipulator motion, and capture of …

Spaceotter: A Floating Spacecraft Simulator Air Bearing Vehicle For Hardware-In-The-Loop Experiments And Research, Alexander Debartolo

Master's Theses

Growing interest in nanosatellites has increased demand for accessible ground-testing methods, which have historically been expensive and restricted. Floating Spacecraft Simulators (FSS), built around Air Bearing Vehicles (ABVs), address this gap by approximating a zero-gravity, friction-minimized environment suitable for testing spacecraft control systems, robotics, and propulsion on the ground.

This thesis presents the design, realization, and initial performance characterization of the Space Optically Tracked Testbed for Experiments and Research (SpaceOTTER) ABV, developed for the Cal Poly Space Robotics Lab. SpaceOTTER is the first step toward emulating the 3 degree of freedom (3-DOF) planar dynamics of a simulated spacecraft and is …

Efficient Mathematical Modeling And Synthesis Of Realistic Musical Instrument Sounds, Andrew Chookaszian

Master's Theses

This thesis develops and evaluates a compact parametric additive synthesis model for isolated musical instrument tones. The method analyzes a single-note recording, estimates its fundamental frequency, extracts harmonic amplitude and frequency behavior, and stores the sound as a reduced set of interpretable parameters. These parameters include the note duration, pitch, per-harmonic amplitude envelopes, phase information, and amplitude- and frequency-modulation vibrato parameters. The stored model is then used to resynthesize the tone without directly using the original audio waveform.

The model was evaluated using synthetic signals, real instrument samples, objective error metrics, storage comparisons, pitch and duration modification tests, and listening …

Design And Implementation Of An Embedded Control System For The Cal Poly Spacecraft Attitude Dynamics Simulator, Neil Mahesh Bedagkar

Master's Theses

This thesis presents the development of a cascaded reaction wheel control system for Cal Poly's Spacecraft Attitude Dynamics Simulator. This work considers system architecture, empirical modeling, high-fidelity simulation, embedded firmware, hardware integration, and experimental characterization. In discrete-time simulation, it is shown that nonlinear direct model reference adaptive control (NDMRAC) enables a nonlinear, partially known plant with realistic actuator dynamics to track the response of a canonical second-order transfer function, with settling time within 4.67% and percent overshoot within order of magnitude of the second-order response. In hardware, the feasibility of a cascaded reaction wheel control architecture is experimentally demonstrated, achieving …

Characterization Of The Thermally Driven Red Hue Effect In Coated And Uncoated Concrete Systems: Implications For Post-Fire Assessment In Wildland Urban Interface Communities, Juan C. Palominos Jr

Master's Theses

The increasing frequency and intensity of Wildland-Urban Interface (WUI) wildfires, such as the destructive 2025 Pacific Palisades Fire that destroyed over 6,000 structures, have underscored the urgent need for rapid post-fire safety assessment methodologies. This study sought to quantitatively characterize the Thermally Driven Red Hue Effect (TRHE), a unique, irreversible color shift observed in architectural coatings and concrete substrates, to determine its reliability as a permanent visual record of thermal exposure. Concrete substrates were formulated with three distinct coarse aggregates: gold granite (14.7% Fe), red cinder (22.4% Fe), and green rock (33.6% Fe) and coated with a 20 PVC waterborne …

A2s Uplink Latency Minimization For Wildfire Monitoring Systems Using Mbse And Stochastic Modeling, Luis Giovanni Wang

Master's Theses

Wildfire response depends on how quickly a detection reaches the people who act on it, and the slowest remaining step is often the link that carries an alert from a remote sensing platform to a satellite. This thesis models the latency of that link, the Air-to-Space uplink, for a wildfire-monitoring UAV that carries a Starlink terminal and sends an ALERT packet to a serving Low Earth Orbit satellite. The uplink is difficult to predict because both the UAV and the satellite move, and because the wildfire environment degrades the channel at the moment the data matters most.

The thesis uses …

Thermally Induced Color Changes In Iron Oxide Pigments Used In Architectural Coatings, Han Diep

Master's Theses

The 2025 Palisades Fire was one of the most destructive wildfires in the history of Los Angeles, destroying thousands of structures and severely impacting the communities after. This widespread destruction demonstrated an urgent need for more effective wildfire prevention strategies. Architectural coatings do not only provide aesthetics and protection against environmental conditions but can also function as a thermal indicator when a fire breaks out. This study examines the thermally induced color transformation of iron oxide pigments, commonly used in earthtone paint, to provide information relevant to CAL FIRE for improved analysis of wildland-urban interface (WUI) fire behavior and mitigation …

To Wait Or To Transfer? A Three-Level Optimization Framework For Intermodal Transfer Coordination In First Train Timetabling And Bus Bridging Services Management, Hao Li, Liujiang Kang, Norman Weik, Huijun Sun, Qingying Lai, Zhiguang Cao

Research Collection School Of Computing and Information Systems

This study addresses the integrated optimization of the first train timetabling and bus bridging service design (FTT-BBSD) for morning transfer challenges, two critical but interdependent passenger services in the public transit system. In contrast to most existing studies and conventional approaches, this study explicitly models the influence of passenger path choices and transfer mode selections on FTT-BBSD. Through a novel dual-level network representation that integrates subway and bus systems, we formulate the FTT-BBSD problem as a mixed-integer nonlinear programming model. The model simultaneously determines subway and bus timetables and bridging line deployment to minimize total travel time for all first …

Pso-Style Social Influence In An Ant Colony Algorithm For Continuous-Domain Optimization, Ashraf M. Abdelbar, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

ACOR is a well-established Ant Colony Optimization (ACO) algorithm for continuous-domain optimization. In this paper, we propose an extension (which we call ACOR∗) in which several fundamental modifications are made to ACOR's solution construction process, including the incorporation of a social influence mechanism borrowed from Particle Swarm Optimization (PSO). Our modifications to the ACOR algorithm are intended to promote search diversity and combat premature convergence. We experimentally evaluate our proposal in the context of training feedforward neural networks for classification using 65 widely used datasets from the University of California Irvine (UCI) repository, as well as the optimization of several …

Numerical Evaluation Of A Zero Poisson’S Ratio Structure In Μ-3d-Printed Self-Expanding Nitinol Stents, Farhana Yasmin, Ana Vafadar, Majid Tolouei-Rad

Research outputs 2022 to 2026

Stenting is a minimally invasive treatment used in managing peripheral artery disease (PAD). However, clinical challenges persist, including in-stent thrombosis and restenosis, primarily driven by axial foreshortening or elongation and suboptimal balance between radial stiffness and flexibility inherent to conventional stent designs. This study proposes an innovative arrow-shaped geometry exhibiting zero Poisson’s ratio (ZPR) behaviour for 3D-printed self-expanding Nitinol stents. The complete stent deployment process was modelled using finite element analysis (FEA), including radial crimping and subsequent expansion to enable systematic parametric investigation while accounting for µ-3D printing constraints. Response surface methodology (RSM) rigorously evaluated mechanical performance, defining peak stress, …

Exploiting Underground Mine Topology For Resilient Concurrent Lora Mesh Emergency Communications: Architecture, Protocol Design, And Performance Analysis, Hilary Kelechi Anabi, Samuel Frimpong, Muhammad Azeem Raza

Mining Engineering Faculty Research & Creative Works

Underground mine emergencies compromise fixed communication infrastructure exactly when situational awareness is most critical for effective rescue operations. Existing LoRa mesh protocols fail in underground mines because they ignore the structured topology of tunnel networks, specifically the waveguide effect along straight galleries, severe signal discontinuity at junctions, and the dead-end geometry of working faces. This paper presents the Topology-Aware Concurrent LoRa (TACL) mesh protocol, in which each node autonomously infers its structural role from local RF observations and packet header information, without GPS, pre-loaded mine maps, or central coordination. Role classification resolves the contender estimation problem (Formula presented.) left open …

Multiplexed Fabry-Pérot High-Temperature Sensing Based On Dispersive Microwave-Photonic Frequency-Time Domain Analysis, Ruimin Jie, Chen Zhu, Bohong Zhang, Koustav Dey, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We propose and experimentally demonstrate a multiplexed high-temperature Fabry-Pérot (FP) fiber sensing system interrogated by dispersive microwave-photonic frequency-time domain analysis (DM-FTDA). In the proposed architecture, incoherent broadband probing light is modulated by radio-frequency (RF) signals and then reflected by a parallel network of hollow-core photonic crystal fiber FP (HCPCF-FP) sensors. A chirped fiber Bragg grating provides strong dispersion to map the composite FP spectral response into a well-defined microwave transfer function. Unlike conventional optical Fourier-domain multiplexing that requires deliberate cavity-length allocation, the proposed approach achieves multiplexing via delay-dominated discrimination. Distinct delay fibers are assigned to each sensor branch, and an …

Rc-Nf: Robot-Conditioned Normalizing Flow For Real-Time Anomaly Detection In Robotic Manipulation, Shijie Zhou, Bin Zhu, Jiarui Yang, Xiangyu Zhao, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Recent advances in Vision-Language-Action (VLA) models have enabled robots to execute increasingly complex tasks. However, VLA models trained through imitation learning struggle to operate reliably in dynamic environments and often fail under Out-of-Distribution (OOD) conditions. To address this issue, we propose Robot-Conditioned Normalizing Flow(RC-NF), a real-time monitoring model for robotic anomaly detection and intervention that ensures the robot's state and the object's motion trajectory align with the task. RC-NF decouples the processing of task-aware robot and object states within the normalizing flow. It requires only positive samples for unsupervised training and calculates accurate robotic anomaly scores during inference through the …

The Sleep Effects Of Construction Management Students At Cal Poly Slo, Riley James Coalwell

Construction Management

Sleep deprivation and poor sleep quality have become increasingly common among college students, particularly in demanding studies such as construction management. This study examined sleep patterns, sleep duration, and perceptions related to sleep deprivation among construction management students at California Polytechnic State University, San Luis Obispo. The study replicated prior research conducted at Mississippi State University while focusing exclusively on one academic program and institution. A quantitative research method was used through an anonymous Microsoft Forms survey distributed to construction management students over a ten-week period. The survey collected demographic information, sleep behaviors, academic workload, and perceptions regarding sleep within …

Computational Insights Into Nucleosome Dynamics In Epigenetics Using Molecular Dynamics Simulations, Rutika Patel

Dissertations, Theses, and Capstone Projects

Nucleosome core particles (NCP) are the building blocks that form a highly organized and compact chromatin structure. Nucleosomes package DNA in the nucleus of eukaryotic cells. The NCP consists of about 147 base pairs of DNA wrapped around the histone octamer, with 1.65 superhelical turns in a left-handed manner. The histone octamer is composed of two copies of H3, H4, H2A, and H2B. Together with histone H1 and linker DNA, they further assemble into a higher-order chromatin structure. The nucleosome complex is stabilized by electrostatic interactions between positively charged histone residues and the negatively charged DNA backbone. To effectively access …

Toward Data-Centric Ai: A Comprehensive Survey Of Traditional, Reinforcement, And Generative Approaches For Tabular Data Transformation, Dongjie Wang, Yanyong Huang, Wangyang Ying, Haoyue Bai, Nanxu Gong, Xinyuan Wang, Sixun Dong, Tao Zhe, Kunpeng Liu, Meng Xiao, Multiple Additional Authors

Computer Science Faculty Publications and Presentations

Tabular data is one of the most widely used formats across industries, driving critical applications in areas such as finance, healthcare, and marketing. In the era of data-centric AI, improving data quality and representation has become essential for enhancing model performance, particularly in applications centered around tabular data. This survey examines the key aspects of tabular data-centric AI, emphasizing feature selection and feature generation as essential techniques for data space refinement. We provide a systematic review of feature selection methods, which identify and retain the most relevant data attributes, and feature generation approaches, which create new features to simplify the …

A Review On Credit Card Electronic Fraud Detection Methodologies, Titilayo Mary Sayikanmi, Ibrahim Adepoju Adeyanju, Bolaji Abigail Omodunbi

Mansoura Engineering Journal

Credit card fraud remains a critical and escalating challenge within the global financial ecosystem, driving substantial annual losses and necessitating the continuous evolution of detection methodologies. This paper presents a systematic literature review, conducted via the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework, which comprehensively analyzes the state-of-the-art in electronic credit card fraud detection. Through a rigorous examination of 49 high-quality studies, this review maps the methodological evolution from traditional rulebased systems and statistical models to advanced artificial intelligence techniques, including machine learning, deep learning, and graph-based approaches. The analysis reveals that while individual methods possess distinct advantages …

Polarimetric Terahertz Imaging For The Measurement Of Birefringence In Plastic, Rachel Cohen

Theses

Birefringence offers a promising way to observe stress concentration in materials such as glass and plastic, and thereby to identify weaknesses. Polarimetric imaging can be used to measure the birefringence of material, so long as the material is transparent to the light being used for the imaging. In this research, 2D Terahertz imaging was investigated as a means of measuring the birefringence of plastics that are opaque to visible light but transparent to THz radiation, for the eventual purpose of analyzing the residual stress present. In order to do so, two separate terahertz cameras were characterized for potential use in …

Adaptive Multimodal Smart Home Control On A Raspberry Pi 5 Using Hand Gestures, Voice Cues, And User Feedback, Vaibhav Bora

Theses

A real time multimodal smart home control system deployed on a Raspberry Pi 5 is presented. The system combines hand gestures, short voice cues, and proximity aware interaction to execute household commands such as light brightness control, fan speed adjustment, and stop or kill switch actions. Lightweight gesture and keyword spotting voice classifiers were trained offline and exported to TensorFlow Lite for efficient on device inference. For more natural spoken phrases, the system additionally integrates a locally deployed pretrained offline ASR component rather than a speech recognizer trained from scratch. Using a USB camera and microphone, the system operates fully …

Robustness Of Ai-Driven Histopathology Under Real-World Adversarial Examples, Ruchik N. Yajnik

Theses

This robustness of histopathology classification models under adversarial and real-world perturbations resembling clinical artifacts is being investigated.

Using whole-slide images from the CAMELYON17 cohort, four representative architectures—ResNet-18, ResNet-50, HIPT-2MLP, and ViT-B/16 —are benchmarked across controlled pixel-level distortions and artifact-like transformations. Adversarial methods include iterative Fast Gradient Sign, Projected Gradient Descent, Salt-and-Pepper noise, and the Adversarial Watermark—Stain Shift (AWSS). Three defense strategies—Randomized Smoothing, Adversarial Training, and an Artifact Detector—are evaluated for their ability to preserve diagnostic accuracy and model reliability. Structured perturbations consistently degrade performance, with transformer-based models showing the greatest sensitivity. The benchmark developed here offers a reproducible framework for …

Mechanics And Physical Attributes Of Nature-Based Alterations: Rock Reinforcement And Urban Heat Island Assessment, Mary Chikondi Ngoma

Dissertations

Ground improvement is critical to geotechnical and geo-engineering systems, where modification of the properties of geomaterials (rocks and soils) is required to maintain stability and prevent failure of infrastructure installed within and around them. This need has become increasingly important with rapid urbanization and population growth, which intensify demands on surface and subsurface systems and further challenge the performance of supporting geomaterials. As a result, there is growing interest in nature-based solutions, particularly biologically mediated processes such as biocementation, which can enhance the physical, hydraulic, and mechanical properties of geomaterials while offering environmentally sustainable alternatives to conventional ground improvement techniques. …

Enabling Ml/Ai In 6g And Future Wireless Communication With Privacy Preservation, Mec Offloading And Quantum Computing, Changshi Zhou

Dissertations

The forthcoming sixth-generation (6G) and future wireless networks are envisioned to support an unprecedented range of services, delivering ultra-low latency, massive connectivity, and intelligent real-time responsiveness. These capabilities will enable emerging applications such as extended reality (XR), autonomous vehicles (AVs), industrial robotics, and the Internet of Things (IoT) to reach their full potential. Achieving this vision requires the integration of enabling technologies such as artificial intelligence and machine learning (AI/ML) and quantum computing, which are poised to play central roles in shaping the landscape of wireless communication systems.

In AI-native, data-driven, and computing-centric 6G networks, ML models will be deeply …

Holistic Dram Enhancements: From Intrinsic In-Memory Operations To Robust Security Mechanisms, Ranyang Zhou

Dissertations

Dynamic Random-Access Memory (DRAM) is both the performance bottleneck and a critical security boundary of modern computing systems. Its physical properties make it an attractive substrate for near-data computation—yet those same properties expose it to disturbance-based hardware attacks. This dissertation argues that these two dimensions are not independent: the architectural choices that make DRAM efficient also reshape its threat landscape. Addressing both requires a unified approach to memory architecture and security co-design.

The first part of this dissertation attacks the memory wall through four processing-in-DRAM (PIM) frameworks. ReD-LUT and LT-PIM unify lookup-table arithmetic with charge-sharing logic, achieving up to 37.8x …

A Generative Ai-Driven Computational Framework For Industry-Scale Discovery Of Novel Battery Materials, Joy Datta

Dissertations

The growing demand for sustainable, high-energy-density electrochemical storage has motivated the exploration of multivalent-ion batteries based on earth-abundant elements such as aluminum, calcium, magnesium, and zinc. While multivalent charge carriers offer higher theoretical energy density than lithium, their practical deployment is hindered by sluggish ion transport, strong ion-host interactions, and structural degradation of electrode materials. Identifying host materials that can reversibly accommodate multivalent ions while maintaining structural integrity remains a fundamental challenge. The dissertation develops a scalable, end-to-end computational framework that integrates density functional theory (DFT), machine learning (ML), and generative artificial intelligence (GenAI) to accelerate the discovery of next-generation …

Toward Learning-Based Reconstruction And Part Decomposition Of Man-Made 3d Geometry: Neural Implicit Representations And Scalable Supervision, Shen Fan

Dissertations

Digital three-dimensional (3D) models are central to engineering design, analysis, and manufacturing, but learning pipelines for man-made geometry often operate on sampled carriers that do not preserve all of the structure present in exact CAD representations. This dissertation studies learning-based reconstruction and part decomposition for structured man-made 3D geometry, from general object benchmarks to CAD-derived datasets, with a focus on neural implicit representations trained from signed-distance samples, point clouds, and tessellated meshes. The goal is to make these models more accurate, more part-aware, and more consistently supervised.

First, signed distance function (SDF) reconstruction with implicit neural representations is improved through …

Glass Transition Temperature Of Plga Nanoparticles And The Application In Drug Delivery, Guangliang Liu

Dissertations

The glass transition temperature (T_g) of poly(D,L-lactic-co-glycolic acid) (PLGA) nanoparticles plays a crucial role in governing molecular mobility, diffusion, and consequently, drug release kinetics. However, the interaction among residual surfactant, drug effect, nanoscale confinement, and release medium on T_g remains insufficiently characterized. This study aims to bridge this gap by correlating the thermal behavior of PLGA nanoparticles with their drug release behavior under physiologically relevant conditions.

In the present study, PLGA nanoparticles were synthesized using both nano-emulsion and surfactant-free nano-precipitation approaches. The influence of residual surfactants - poly(vinyl alcohol) (PVA) and didodecyldimethylammonium bromide (DMAB) - was systematically …

Machine Learning-Driven Prediction And Mechanistic Insight Into Co2 Adsorption On Biomass-Derived Activated Carbons Using Explainable Ai (Xai), Dalia A. Ali Dr.

Chemical Engineering

To improve CO2 uptake in Biomass-Derived Activated Carbon (BDAC), this study develops a multiscale hybrid digital twin framework. By integrating microscopic descriptors from Density Functional Theory and Molecular Dynamics (DFT/MD) with experimental data from 63 chemically diverse biomass precursors, a Gaussian Process Regression (GPR) model was developed using the Materń 5/2 Automatic Relevance Determination (ARD) kernel. The framework achieved high internal training accuracy (R2 = 0.968) and Root Mean Square Error (RMSE = 0.2552), while providing a realistic generalization baseline across heterogeneous precursors with a 5-fold Cross Validated (CV) R2 of 0.1567 and CV RMSE of 0.283. Explainable Artificial Intelligence …

Electrospun Nanofiber Scaffolds For In Vitro 3d Tissue Engineering, Victoria E. Santillan, Samerender Nagam Hanumantharao, Stephanie Bule, Ronish M. Shrestha, Carter Rodzik, Alan Mendoza Estrada, Stephen L. Farias, Marina Tanasova, Smitha Rao

Michigan Tech Publications

Tissue engineering is widely used in research for investigating cellular proliferation, behavior, and responses to various stimuli. However, the predictive value of preclinical studies using cell culture plates is limited by the inability to recapitulate the complexity of the physiological microenvironment. Synthetic three-dimensional (3D) scaffolds can be engineered to mimic the complex morphology of the extracellular matrix of native tissues and can serve as physiologically relevant platforms for preclinical studies. In this study, 3D electrospun scaffolds were characterized to aid in breast cancer research. Unlike previous studies that focused primarily on scaffold fabrication or cell viability, this work systematically evaluates …

Hydrodynamic Analysis And Cfd Modeling Of Pawec Interacted With Regularwaves Using Cfx, Ahmed Elbaz

Mechanical Engineering

The multiplicity of renewable energy sources represents the biggest challenge for environmental scientists and engineers. This research presents a mathematical model and a numerical study using the high-performance ANSYS-CFX software to analyze the dynamic behavior of the point absorberwave energy converter (PAWEC). Two different models were constructed to predict the hydrodynamic response of the wave energy converter in both free and forced oscillations under the action of incident regular waves and external mechanical damping. The differential equations are solved analytically using RKFOM. CFX multiphase model is constructed to solve the 3D Unsteady Reynolds Averaged Navier–Stokes Equation (URANS) using the two-way …