Digital Commons Network^™

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 …

Evaluating The Cost-Benefit Tradeoffs Of Simt Control Mechanisms In Resource-Constrained Gpus, Nikolas Tambornini

Master's Theses

This thesis conducts a hardware-level analysis of the cost–benefit tradeoffs associated with increasingly complex SIMT control mechanisms in a resource-constrained GPU core. Four design implementations are evaluated: a Base Tiny GPU without warp scheduling capability; a Warp Scheduler using round-robin warp selection; a Branch Divergence implementation incorporating a dedicated divergence stack and post-dominator reconvergence mechanism; and a Dynamic Warp Allocation implementation that replaces the static warp structure with a runtime warp manager, regrouping threads by current program counter to recover SIMD lane utilization during active divergence. Each design is evaluated using two complementary measurements: functional simulation implemented using the CocoTB …

Neuron Notes, Araceli Franco, Ethan Diec, Max Blennemann, Shibo Cong

Computer Science and Engineering Senior Theses

Mainstream digital note-taking tools such as Notion, Microsoft OneNote, and Evernote organize knowledge around linear documents and rigid folder hierarchies, a structure that strays from the associative, graph-like nature of human semantic memory. Mind-mapping and linked-note systems such as XMind, Obsidian, Roam Research, and Logseq move closer to that associative model but still constrain users to short labels, automatic layouts, or page-centric workflows that underutilize spatial and visual recall. This thesis presents Neuron Notes, a spatial, graph-based note-taking system designed to align digital organization with how people actually form and retrieve ideas. The system is implemented as a three-tier web …

Restoreband: An Electromyography Band For Tracking Forearm Muscle Action And Activation In Post-Stroke Adults, Mairin T. Mullen, Melody Nwagwu, Kosuke Nishimura, Benjamin Miramon

Biomedical Engineering

This study involves the design of a non-invasive surface electromyography (EMG) band to estimate hand posture for individuals recovering from stroke and other neuromuscular disorders. The device is meant to measure forearm muscle activation to provide objective recovery data that can supplement traditional rehabilitation. Current EMG systems are often expensive, cumbersome, and difficult to use. The goal of this study is to develop an affordable, accurate, and easy to use solution that improves access to EMG motor monitoring.

The key stakeholders include stroke survivors, clinicians, and the project sponsor, Dr. Espinoza-Wade. This report includes project introduction, background, objectives, and project …

Nanofluid Flooding As A Sufficient Alternative To Waterflooding For Incremental Oil Recovery From Carbonate Reservoirs, Sarmad Al-Anssari, Dhifaf Sadeq, Hassanain A. Hassan, Ahmed Hamid Al-Taie, Hasan Ali Abood, Mohammed Mahdi, Zain Ul Abedin Arain

Research outputs 2022 to 2026

Oil recovery from carbonate reservoirs is one of the critical challenges in the oil industry due to the strongly oil-wet nature, natural fractures, and the heterogeneity of carbonate rocks. Subsequently, waterflooding can only displace oil from large fractures, leaving the majority of oil trapped in the rock matrix. This work suggests that nanofluid flooding, as a predesigned flooding method, is an alternative to conventional waterflooding. Various concentrations of silica nanofluid at different nanoparticle concentrations were formulated and systematically investigated for their characteristics, stability at reservoir conditions, and their influence on wettability and oil recovery. Silica nanoparticles were sustainably synthesized from …

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 …

Evaluation Of The Effect Of Vibration On Signal Reflection In Coaxial Cable Connectors For Vibration Sensing In Aircraft Structures And Systems, Saidanvar Esanjonovich Valiev, Anthony C. Okafor, Jeremiah J. Rittenhouse, Daniel S. Stutts, Jie Huang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper investigates the effects of vibration on signal reflection (S11) in aerospace data transmission line (ADTL) and commercial data transmission line (DTL) connectors for their alternative use as vibration sensors. The impact of vibration on the S11 signal was investigated on five ADTL and four DTL connectors at six vibration frequencies (20 Hz, 40 Hz, 80 Hz, 160 Hz, 320 Hz, and 640 Hz) and four vibration accelerations (0.5G, 1 G, 2 G, and 4G). The experiment was conducted using a split-plot design with a cable type assigned as the main-plot factor, with vibration frequency and acceleration as subplot …

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 …

2026 Annual V.E.S.T Hackathon: Improving Gender Inclusivity Of Glove Fitting, Makena E. Fix

Construction Management

Safety gloves are an essential part of field personnel's personal protective equipment (PPE). Gloves protect against cuts, burns, chemicals, and other hazards. Properly fitting gloves reduce the risk of injury by enabling the suitable use of task-specific protection. The 2026 Verifying Everyone’s Safety Together (V.E.S.T) Hackathon was hosted to identify ways in which gloves fit workers differently, and evaluated six different glove types, ranging from woven cut rated to firefighting gloves. To understand experiences faced by workers with their PPE, firefighters were interviewed and discussions were held at the Hackathon. The collaborative event brought industry members and students together to …

Ada Concrete Walkway Improvements At The Gala Pride And Diversity Center, Jonathan A. Mintz, Manuel Gonzalez

Construction Management

This paper presents the planning, design, and construction of an accessible concrete walkway completed for the GALA Pride and Diversity Center in San Luis Obispo, California. The project addressed an accessibility gap between the center's front entrance and rear parking lot through a combination of site preparation, concrete work, retaining wall construction, and supporting improvements. Construction was managed around the active events schedule while staying within the constraints of a nonprofit budget. Challenges encountered during the project included scope changes, material selection decisions, and client coordination. The completed walkway provides a safe and stable path for all visitors and directly …

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 …

S-[2-(Hydroxyamino)-2-Oxoethyl]-O-Octyl-Dithiocarbonate Ester (Ehaox): Performance And Adsorption Mechanism, Yue Zhou, Jiaxiang Li, Hongli Fan, Zhilong Li, Yuesheng Gao, Tian Lin, Haiyan Tang, Tingting Wang, Wei Sun

Michigan Tech Publications

This study explores the interfacial interactions between a novel collector, S-[2-(hydroxyamino)-2-oxoethyl]-O-octyl-dithiocarbonate ester (EHAOX), and bastnaesite mineral surfaces during selective flotation. Compared to conventional octylhydroxamic acid (OHA), EHAOX demonstrated superior recovery, achieving an over 40% absolute increase in recovery compared to octylhydroxamic acid (OHA) at the same collector concentration (1 × 10⁻⁵ mol/L) and pH 8.0, and selectivity for bastnaesite, attributed to its optimized hydrophobicity (supported by CLogP calculations). Mechanistic studies via zeta potential, UV/vis spectroscopy, and FTIR revealed the formation of a complex composite via chemisorption between EHAOX and Ce³⁺ sites on the bastnaesite surface, with coordination occurring …

A Data Analysis Study Of Temperature Based On California Cooperative Oceanic Fisheries Investigations (Calcofi) Data., Afsana Mimi

Dissertations, Theses, and Capstone Projects

This research presents an integrated analytical framework for predicting ocean temperatures using long-term observations from the California Cooperative Oceanic Fisheries Investigations (CalCOFI) data files. The study applies advanced data engineering and statistical modeling to assess how a variety of indicators, such as salinity, dissolved oxygen, key nutrients, and ocean depth shape oceanic temperature patterns along the California coastline. Using Microsoft SQL Server software for large-scale data integration and the R for statistical packages (R Core Team, 2025) for statistical computation, I developed and compared multiple regression models, including the ridge regression model, to evaluate the relative influence of physical and …

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 …

Deep Learning Approaches For Ctenophore Identification And Tracking, Anagha Bharadwaj

Theses

Ctenophores are translucent marine organisms with nearly invisible tentacles and pose significant challenges due to their transparent morphology and ambiguous structural features. This research addresses the classification and tracking of these organisms and evaluates the performance of current computer vision models under sparse-data environments.

A dataset from the NJIT Life History Lab consisting of microscopic laboratory videos and photographs of different growth stages is used to train and assess a number of convolutional neural network designs, including VGG16, ResNet, BioCLIP2, YOLO, and DeepLabCut. Additionally, a web-based interface is developed to evaluate expert-labeled ground truth with the model's performance.

The findings …

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 …

Retinomorphic Mid-Wave Infrared In-Sensor Processing Engine: Device-To-Architecture Co-Design, Hemalatha Nagaraju

Theses

Conventional frame-based CMOS image sensors acquire full-frame pixel data at discrete time intervals, resulting in substantial spatial redundancy and loss of temporal information between frames. The repeated conversion and transfer of redundant pixel data increases bandwidth and power consumption in machine vision systems. Retinomorphic sensing architectures address these limitations by enabling programmable, analog-domain processing directly at the sensor interface. A compact behavioral model of the PbSe device is developed in HSPICE based on calibrated TCAD simulation data to capture gate-controlled photocurrent modulation under varying illumination and gate bias conditions. Error analysis is performed to quantify the deviation between TCAD-generated photocurrent …

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 …

Evaluation Of Medical Instrument Reliability For The Heath And Maddox Components Of The Accommodative-Vergence System, Jacob Chabuel

Theses

Binocular vision relies on the coordination of near response triad composed in part by the vergence and accommodative systems. Binocular dysfunctions linked to these systems impact the quality of life of those affected by complicating day-to-day tasks and leading to further health concerns. Clinical evaluations that diagnose dysfunctions and tailor therapies rely on subjective methods, creating a need for a reliable, quantitative, measurement tool. This is achieved using a haploscope, a tool that quantitatively measures and observes binocular vision to identify deficiencies within the eye. Modernization of a haploscope system, measurement of the Heath and Maddox components of the visual …

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 …

Vergence Task-Based Neural Pathways With Binocularly Normal Vision And Comorbid Persistent Post-Concussive Symptoms -Convergence Insufficiency, Ayushi Sangoi

Dissertations

Binocular dysfunctions are more prevalent in the persistent post-concussive symptoms (PPCS) population than in the general population. The most prevalent binocular disorder is convergence insufficiency (CI), affecting 3-17% of the general population and up to 10 times as many people with PPCS. CI makes it difficult to fuse or maintain fusion on targets at near, and its symptoms include double or blurry vision and headaches when performing close-range tasks such as reading, which can exacerbate PPCS symptoms. Given controversy over the subjectivity and effectiveness of diagnostic tools and symptom surveys for both PPCS and CI, understanding why CI has high …

Significant Crash Characteristics Associated With E-Scooter And E-Bike Crashes, Aimee Jefferson

Dissertations

Micromobility devices—namely e-scooters and e-bikes—have rapidly gained popularity in the United Sates, rising from 35 million annual shared rides in 2017 to over 133 million in 2023 (NACTO 2024). But also increasing is the number of injuries associated with these devices; however, most research emphasizes injury and demographic patterns rather than crash characteristics that would inform prevention strategies. Most existing crash research also relies on small sample sizes, lacks nuance distinguishing between involved parties (motorists, pedestrians, single device), and fails to distinguish between bicycle and micromobility crash patterns despite micromobility devices often being instructed to use conventional bicycle facilities. These …

Omama-Db: The Oregon-Massachusetts Mammography Database, Avanih Kanamarlapudi

Graduate Masters Theses

Public datasets for training AI models in breast cancer screening are limited in size and quality, making it difficult to develop reliable systems. We introduce OMAMA-DB, an extensive publicly available collection of 2D mammograms and 3D tomosynthesis volumes. Starting from 967,991 images, we created a curated set of 231,080 images us ing a multi-stage filtering process that removes missing labels, uncommon dimensions, rare scanner types, duplicate studies, and invalid DICOM files. All 2D images then undergo additional outlier detection using histogram filtering and a variational autoen coder to remove low-quality outliers. OMAMA-DB includes pathology-based cancer labels and automated lesion annotations …

Reliable Offline Evaluation Under Exposure Bias: A Cross-Scale Study Of Counterfactual Estimators In Recommender Systems, Lakshmi Pranathi Vutla

Graduate Masters Theses

Offline evaluation underpins model selection in recommender systems, yet historical interaction logs are shaped by prior recommendation policies. Because users only provide feedback on exposed items, logged data entangles user preferences with exposure mechanisms, leading to exposure bias and potentially misleading model comparisons. Counterfactual estimators such as IPS, SNIPS, CRM, and DR offer principled corrections, but their empirical reliability across datasets and exposure regimes remains insufficiently under- stood. We present a systematic, cross-scale study of counterfactual evaluation in recommender systems. Comparing IPS, SNIPS, CRM, and DR on datasets with randomized exposure (Yahoo! R3, Coat, and KuaiRec), we analyze estimator behavior …

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 …

Towards Interpretable Transfer Learning With Limited Data, Youxiang Zhu

Graduate Doctoral Dissertations

Modern foundation models are typically trained with large-scale data to ensure good performance. However, certain tasks cannot scale with large amounts of data due to cost and practical constraints, resulting in limited performance. To address this, in this dissertation, I introduce model-task alignment, a general methodology for making a foundation model work well with tasks with limited data. The methodology comprises two parts: aligning downstream tasks with foundation models and aligning foundation models with downstream tasks. To study and validate this methodology, I first focus on speech-based dementia detection, a representative task with limited data, and then extend to general …

Ai-Augmented Financial Advisors: Comparing Ai And Human Analyst Investment Recommendations In Agreement, Performance, And Firm Size Effects, Crystal Chen

Honors College Theses

This study examines the level of agreement and performance between artificial intelligence (AI) generated investment recommendations and human analyst recommendations across U.S. publicly traded firms. Using a sample of twelve companies categorized by firm size (large, mid, and small), the study collects buy, hold, or sell recommendations from generative AI systems and human analysts. Agreement between AI-to-AI and AI-to-human recommendations is measured using Cohen’s Kappa agreement. Portfolio performance is evaluated by constructing equal-weighted portfolios for each recommendation source and size category. Risk-adjusted returns are measured using the Sharpe ratio over 1-, 2-, and 3-month periods. Furthermore, the study tests whether …

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 …

Drilling Fluid Enhancement Via Addition Of Sustainably Synthesized Nanoparticles, Hasan A. Abbood, Sarmad Al-Anssari

Research outputs 2022 to 2026

The addition of nanoparticles to the drilling fluids for geological projects is a promising application for enhancing the stability, rheological properties, and overall performance of the mud. This study aims to thoroughly analyze and compare the effects of silica and alumina nanoparticles on the properties and effectiveness of polymer drilling mud. Silica and alpha-alumina nanoparticles were synthesized using the sol-gel process and characterized through several techniques, including X-ray diffraction, Fourier-transform infrared spectroscopy, field-emission scanning electron microscopy, and atomic force microscopy. The effects of silica and alumina nanoparticles on various properties of drilling mud were then measured using a permeable plugging …

Software Engineering: Ai-Enhanced Full Stack Development, Huixin Wu, Haiying Xiao

Open Educational Resources

This course provides instruction in full‑stack web application development using modern JavaScript technologies. Students design, implement, and deploy web‑based solutions while applying AI‑assisted development tools in an ethical and effective manner. The curriculum emphasizes problem‑solving, system design, teamwork, and industry‑standard best practices, with dedicated focus on cloud‑native development—including containerization, distributed services, and modern deployment pipelines—as well as API‑first architecture, enabling students to build scalable, maintainable, and interoperable applications aligned with current industry expectations.