Engineering Commons^™

Capstone Review: Warn Winch Proximity Sensor, Leana Girton

University Honors Theses

This thesis reviews the mechanical engineering capstone project that designed a winch proximity sensor for WARN Industries. WARN is very interested in developing this product for market as a safety and ease-of-use accessory, and working with Portland State University was the first step in this process. A group of four mechanical engineering and four electrical engineering capstone students collaborated to research sensor types, test the selected methods, and design and build a prototype. The final design implements an inductive ring, a mechanical button, and bluetooth signaling. The project succeeded in prototyping a proximity sensor for WARN, who will have access …

Gps Tracking Smart Dash Cam Capstone Review, Simrah Saleem

University Honors Theses

This thesis details our design, implementation, and collaborative development of an intelligent vehicle logging system built on a Raspberry Pi 5. Unlike standard consumer dash cams that act as closed "black boxes," our system uses a dual-camera stereo vision setup integrated with centimeter-level accuracy. While we successfully built a functional Proof of Concept capable of event-triggered recording, dual-monitor visualization, and smart detection and recognition, this paper focuses on our engineering journey and the real-world challenges we faced. Using an Agile framework, we split into three specialized sub-teams to handle hardware, database, and interface design in parallel. This structure created unique …

Strategies For Extending The Service Life Of Prestressed Concrete I-Shaped Beams, Sanjoy Kumar Bhowmik

Dissertations

Prestressed concrete (PSC) I-shaped beams are widely used in bridge construction because of their structural efficiency and durability. The service life of these beams is reduced and the maintenance frequency is increased due to the distress during fabrication and subsequent deterioration. Although several mitigation strategies have been proposed and implemented, beam end cracking during fabrication remains a major concern. The causes and mitigation strategies for beam end cracking have been studied for decades, but there have been no comprehensive studies utilizing beam end strains during fabrication and lifting at prefabrication plants under normal operational conditions. Moreover, existing maintenance and repair …

Design Of Advanced Water Purification System For The City Of Palo Alto, Kailee Oyama, Alex Marquez

Civil, Environmental and Sustainable Engineering Senior Theses

The Advanced Water Purification System (AWPS) is designed with multiple treatment units to facilitate potable water reuse of the effluent from the Wastewater Treatment Plant (WWTP) in Palo Alto. The membrane filtration process as well as post treatment conditioning results in a high quality recycled water that has a lower salinity concentration. The membrane filtration process separates the suspended particles such as bacteria, protozoa, and viruses from the WWTP effluent as well as reducing the dissolved solids, salts, smaller organic molecules, and trace contaminants by 90-99%. Then, the air stripping tower removes the excess carbon dioxide increasing the pH from …

Nanosilica-Enhanced Concrete For Commercial Construction, Pavlik Gribanovsky, Angel Lozano, Sebastian Rico

Civil, Environmental and Sustainable Engineering Senior Theses

Concrete is the most widely used construction material in the world. In consequence, the production of Portland cement contributes significantly to global carbon dioxide emissions. As the construction industry seeks more sustainable materials, nanosilica emerges as a promising material capable of enhancing the performance of concrete which would in turn reduce the demand of cement. This project investigated the feasibility of using laboratory-synthesized nanosilica as a concrete admixture to improve the mechanical performance of self-consolidating concrete. Concrete specimens were prepared in accordance with applicable ACI and ASTM procedures, cast into cylindrical molds, cured, and tested for compressive strength at seven …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Membrane-Engineered Nanotherapeutic Platforms For Drug Delivery: Hollow Fiber Membrane Synthesis Of Lipid Nanoparticles, Biomimetic Nanocarriers, And Nanobubbles, Zhixiang Liu

Dissertations

Lipid-based nanocarriers have emerged as a cornerstone technology for RNA therapeutics, enabling effective intracellular delivery for applications ranging from vaccination to gene regulation. However, current manufacturing approaches, particularly microfluidic-based platforms, face inherent limitations in scalability, throughput, and structural tunability due to their reliance on confined channel geometries and restricted mixing architectures. Addressing these challenges requires fundamentally new strategies that decouple nanoparticle formation from traditional microscale flow constraints while maintaining precise control over physicochemical properties.

This dissertation presents a comprehensive framework for the design, engineering, and application of advanced lipid-based nanocarriers, centered on a hollow fiber membrane (HFM)—assisted nanopore-mediated assembly platform. …

Transcranial Ac Modulation Of Cerebellar Nuclear Activity In Awake Animals, Nuran Kavakli

Dissertations

Entrainment of cerebellar nuclear (CN) cells via cerebellar transcranial alternating current stimulation (ctACS) has been reported in animals under ketamine/xylazine anesthesia. Our main objective was to demonstrate modulation of CN activity in unanesthetized, freely moving animals using ctACS. Multi-channel carbon-fiber electrodes were implanted into the interpositus nucleus for recording multi-unit (MU) activity, and thin-film electrodes were implanted subcutaneously over the posterior cerebellum for stimulation. A frequency-domain-based metric was developed to quantify modulation from MU signals. The results demonstrated modulation in a wide range of frequencies (4 Hz-300 Hz) as in anesthetized animals. In contrast, the amplitude of the peak in …

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 …

Autonomous Exploration Of An Environment With Static Obstacles Using A Ppo Agent, Brandon Knight

Theses

Research in autonomous exploration has created many effective algorithms that have been tested and proven to work in many different virtual and physical environments. Many optimizations have also been developed to reduce computational effort and increase exploration speed.

However, despite optimizations, these algorithms can still require considerable computational effort and time to explore even small environments. To obtain further improvements in computation and exploration speed, a reinforcement learning agent using actor-critic style proximal policy optimization (PPO) is trained to explore various environments efficiently, then compared to an algorithm using contemporary exploration methods.

Testing is performed in virtual environments with ideal …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …