Digital Commons Network^™

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 …

The Effects Of Osha State Plans And State Gdp On Occupational Injuries And Illnesses In The United States, Ahmad Abdel Rahman Mohammad Amoorah

Theses

Workplace safety in the United States is governed by a system in which some states operate under federal OSHA oversight, while others administer their own OSHA-approved safety and health plans. This duality raises questions about whether state-level control leads to variation in safety and health outcomes. Economic conditions have also been shown to influence workplace injury rates, yet the interaction between safety and health regulations and local economies remains underexplored. Understanding these relationships is critical to protecting workers in occupational settings. The effects of OSHA state-plan status and state-level economic activity on occupational injury and illness rates across the United …

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 …

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 …

Pypitfall: Dependency Chaos And Supply Chain Vulnerabilities In Python, Jacob Mahon

Theses

Python software development heavily relies on third-party packages. Direct and transitive dependencies create a labyrinth of software supply chains. While it is convenient to reuse code, vulnerabilities within these dependency chains can propagate through dependencies, potentially affecting downstream packages and applications. PyPI, the official Python package repository, hosts many packages and lacks a comprehensive analysis of the prevalence of vulnerable dependencies. PyPitfall, a quantitative analysis of vulnerable dependencies across the PyPI ecosystem, is introduced. The dependency metadata of 378,573 PyPI packages is analyzed. 4,655 packages that explicitly require a known vulnerable package version and 141,044 packages that permit a vulnerable …

Context-Aware Vulnerability Scoring For Dubai Immigration Systems: Enhancing Cvss With Exposure And Asset Risk Factors, Saeed Adnan Saeed Alkhatibi Alsuwaidi

Theses

This paper explores the drawbacks of Common Vulnerability Scoring System (CVSS) usage in case of mission critical government infrastructures with special attention to Dubai Immigration systems. Even though the widely used tool against evaluating the severity of technical vulnerability is the CVSS, it fails to consider the organisational factors like the exposure of the asset, the criticality of the system, the number of users and the sensitivity of data. Such contextual blindness may contribute to prioritisation being off-kilter and ineffective resource assignment in high-risk and highly sensitive settings. The researchers systematically analyse the potential to incorporate contextual features in CVSS …

Machine Learning–Based Spatio-Temporal Analysis And Prediction Of Urban Air Quality Using Global Aqi And Geolocation Data, Rashed Ibrahim Almheiri

Theses

The research problem addressed in this study involves the use of machine learning approach in the spatio-temporal analysis and prediction of urban air quality by relating Air Quality Index (AQI) and geolocation data on Air Quality across a global dataset. The study is informed by the increased concern on the effects of air pollution both on human health and the environment, whereby specific attention is given to comprehending the determinants of AQI in various regions. In the study, four main research questions guide the research: what key factors play an effective role on AQI, the efficiency of machine learning models …

Social, Economic, And Environmental Sustainability Of Small-Scale Hydroponic Farms, Alexa Genevieve Kaminski

Theses

Controlled environmental agriculture (CEA) is well-positioned to contribute to a more sustainable food system. It has the potential to offset some of the negative impacts of conventional agriculture through its ability to optimize the crop growing environment, locate production closer to population centers, and take advantage of non-arable land. The focus of this dissertation is one type of CEA: the hydroponic container farm (HCF). The HCF grows crops using only water and fertilizer inside a 40-foot shipping container that can be located anywhere in the world. Manufacturers are optimistic about this farm’s abilities, but little research exists that investigates the …

Smartdesk: Automatic Ticket Classification And Resolution Prediction Using Data Analytics, Danarir Almuhairi

Theses

Public and service-oriented organizations increasingly rely on digital ticketing systems to manage large volumes of citizen and customer requests. Despite this, many ticket management processes remain partially manual, leading to delays in case routing, inefficient resource allocation, and inconsistent resolution times. These challenges can negatively impact service quality, operational efficiency, and user satisfaction, particularly in large-scale public sector environments. This study proposes SmartDesk, a data-driven framework for automatic ticket classification and resolution time prediction using data analytics and natural language processing (NLP) techniques. The research leverages publicly available helpdesk and service ticket datasets to simulate real-world service environments where incoming …

Comparative Analysis Of Standard Building Materials In Earth-Sheltered Architecture, Austin Greifenkamp

Theses

In an industry that significantly contributes to the ever-increasing environmental destruction witnessed globally, architects are responsible for ensuring human comfort without sacrificing environmental health. Earth-sheltering, an architectural design technique that uses earth to partially or fully cover a building, results in reduced operational energy consumption but introduces structural components to increased loads and higher levels of humidity. Using the material properties and life cycle data of wood, concrete, and steel, this study analyzes the viability of each material in a below-grade environment and the resulting embodied impact of a typical earth-sheltered structure. To align the results of this research with …

Automated Contact Pattern Extraction And Evaluation For Gears, Tom Abraham

Theses

The tooth contact pattern is a crucial indicator of overall performance for many gear geometries, especially spiral bevel and hypoid gears. It is directly associated to the loaded function of transmission errors, a primary contributor to gear noise and vibration. This is especially relevant in electric vehicles, where gear noise is more pronounced due to the absence of masking noise from internal combustion engines. Consequently, the inspection and control of the contact pattern are essential aspects of gear design and manufacturing. Traditionally, contact patterns are evaluated using a manual process known as the tooth contact roll test. This test is …

The Impact Of Employment On Sense Of Belonging And Metacognitive Awareness: A Mixed-Methods Study Of Undergraduate Students’ Mathematical Performance, Erin Ryan

Theses

This study investigated how employment intensity affects two critical factors for academic success: a student’s sense of belonging and their metacognitive awareness (the ability to monitor and manage their own learning). Using a mixed-methods approach at the Rochester Institute of Technology, we analyzed survey data through multi-level modeling and conducted qualitative interviews to capture the personal experiences of employed students. Results reveal that students working off-campus for more than eleven hours a week showed significantly lower sense of belonging and metacognitive awareness scores than unemployed students. However, on-campus employment did not show the same effect. Both quantitative and qualitative results …

Toward Autonomous Wireless Networks: Spatio-Temporal Prediction Via Physics-Aware Generative Ai Models, Rahul Gulia

Theses

The realization of fully autonomous Industry 4.0 environments depends on wireless networks that are not merely connected, but predictively aware—capable of anticipating channel degradation before it disrupts mission-critical operations. In dynamic industrial environments such as automated warehouses, radio frequency propagation is governed by dense metallic infrastructure, continuously moving obstacles, and frequent line-of-sight to non-line-of-sight transitions that render the channel non-stationary and spatiotemporally complex. Conventional approaches face a fundamental dichotomy: deterministic simulators such as ray-tracing and NS-3 achieve high physical fidelity but require up to 38 hours to generate a single high-resolution SINR heatmap, making real-time adaptation computationally infeasible; empirical and …

A Comparative Static Analysis Of Identifier Clones And Homonyms In Open Source Projects, Jose Palomino Lau

Theses

Identifier naming is a core element of software engineering and program comprehension. While existing literature suggests that naming consistency is ideal, there is limited empirical data on identifier homonyms, instances where the same name is used for different behaviors. This thesis investigates these naming patterns through a manual analysis inspired by grounded theory, supported by static analysis with srcML across three open source projects in Java, C and Python. By establishing a behavioral framework through axial coding, this research classifies 771 identifiers into functional categories to document their presence and role within the code. The results reveal that naming redundancy …

As I Live And Breathe, Jessica Fitzgerald

Theses

This thesis employs the unique materiality of glass as a means of investigating interconnection and worth. Through glass, I explore the value of attention, and how directing it informs a sense of what matters. By allowing the fundamental forces of heat and gravity to lead the work, I explore connection, and the hidden ways in which Process influences Piece. The particular malleability of warm glass enables me to capture moments of making. It is the lens through which I focus my investigations, highlighting phenomena in process as the evidence of its creation.

Uncovering Cytoskeletal Length Control From Growth Trajectories Using Sparse Dynamical Modeling, Carson Hearn

Theses

Understanding the governing equations of biological filament dynamics is essential for predicting cellular behavior, yet these equations are often difficult or impossible to derive directly from first principles. This thesis investigates the use of Sparse Identification of Nonlinear Dynamics (SINDy) as a unified, data-driven framework for discovering, validating, and refining governing equations from both simulated and experimental data. Focusing on biological filament processes, including growth, disassembly, and severing, this work is designed not only to apply SINDy, but to systematically demonstrate that it is a reliable and generalizable tool for modeling complex biophysical systems. To establish this, SINDy is first …

Understanding Communication In Green Infrastructure Project Teams In Rochester Ny Region: Coordination, Negotiation, And Constraints, Hayden Berner

Theses

This study explores how communication is perceived and used within multidisciplinary green infrastructure (GI) project teams. As GI continues to grow in the United States, projects increasingly rely on collaboration between professionals from different fields, making communication a critical factor in project success. Using a qualitative research approach, semi-structured interviews were conducted with professionals working on GI projects in the Greater Rochester, New York region. The data were analyzed using an inductive, grounded theory approach to identify key themes related to communication practices, challenges, and outcomes. Results show that communication is not just a tool for sharing information, but a …

Stance Detection On Social Media: The Impact Of Doping On Athlete Reputation, Connor O'Neill

Theses

Doping scandals can have a lasting effect on both athletes' and organizations' reputations, causing athletes to lose money and fans to lose trust in the organizations that govern their favorite sports. This paper investigates the impact a doping scandal can have on an athlete's reputation by  conducting a case study on Jannik Sinner, one of the top tennis players in the world, who ultimately accepted a suspension after testing positive for performance-enhancing drugs, despite being unintentionally exposed. Using data sourced from YouTube comments on tennis-related videos, a fine-tuned Mistral-7B-Instruct-v0.3 model with a classification head was used to carry out stance …

Complexity And Usability Of Digital Healthcare, Theresa Haas

Theses

Digital services, ranging from online shopping and banking to government services and healthcare, are rapidly taking over human-provided services. The accessibility and usability of such digital services may not allow older adults to make use of them, making automation a barrier to access societal services. This is especially critical with many healthcare-related services and apps. This research is framed around two interrelated constructs, task complexity and individual complexity, the latter influenced by cognitive decline in older users. The experiment has three representative tasks of different task complexity and the measure of individual complexity which is understood through previous knowledge of …

Support Systems, Capability Configurations, And Enabling Conditions For Circular Entrepreneurship, Israa Thiab

Theses

The transition to a circular economy requires entrepreneurs who can create value from waste, design regenerative business models, and navigate resource-constrained environments. Yet understanding what enables circular entrepreneurial success remains fragmented across the sustainability and entrepreneurship literatures. This dissertation examines how entrepreneurial support systems, capability configuration, and external enabling conditions shape circular venture development and performance through three complementary studies that together advance a unified framework of circular entrepreneurial effectiveness. Study 1 employs participatory action research with a donor-funded incubation program in Jordan, examining how stakeholder priorities reconfigure support systems for circular entrepreneurs. Analysis of two cohorts reveals that stakeholder-driven …

An Lstm-Based Framework For Predictive Power Quality Monitoring, Ian Aiken

Theses

Rapid integration of photovoltaic (PV) systems introduces significant power quality challenges, including voltage sags and harmonic distortion, yet existing approaches either perform post-hoc classification or rely on computationally expensive meteorological forecasting unsuitable for real-time edge deployment. In this paper, a resource-efficient framework is developed for short-term power factor sag prediction using only on-line electrical measurements via a dual-track methodology. A regression model is first established to define the predictive limits of direct value estimation. The analysis of drop-event-specific metrics reveals that sensor features are lagging indicators incapable of regressing immediate drop magnitude, motivating a classification re- framing. A binary Long …

Traumatic Stress Recruits An Excitatory Orbitofrontal-Amygdala Pathway To Drive Maladaptive Aggression, Mikaela Aholt

Theses

Traumatic stress is a reliable predictor of heightened aggression, yet the mechanisms linking stress exposure to aggression remain poorly understood. The Nordman lab previously found that traumatic stress activates the posterior ventral segment of the medial amygdala (MeApv) to drive persistent increases in aggressive behavior. However, why traumatic stress would engage an aggression-promoting pathway is unclear. To address this, the inputs to the MeApv were mapped and a population of excitatory, but not inhibitory, neurons in layer 5 of the medial orbitofrontal cortex (mOFC) were identified. The OFC is classically viewed as an inhibitory brake on amygdala-driven impulses, yet emerging …

Avoiding White Elephants: An Empirical Assessment On The Failure Of Airport Capacity To Drive Tourism Receipts, Somanithel Kheang

Theses

This study investigates the relationship between airport infrastructure capacity and international tourism receipts across 12 major Asian and European economies from 2000 to 2019. Using a Panel Fixed Effects framework, the analysis tests the "Supply-Led Growth" hypothesis to determine if physical infrastructure expansion independently drives tourism revenue. To address potential endogeneity and reverse causality, the study employs specification where all independent variables are lagged by one year.The empirical results yield a robust null finding: airport capacity does not exhibit a statistically significant impact on tourism receipts. Conversely, government consumption is identified as a potent driver of tourism performance, with a …

Deep Reinforcement Learning-Based Equitable Post Disaster Resource Allocation Incorporating Social Vulnerability, Trevor John Mogaka

Theses

Prior Deep Reinforcement Learning (DRL) approaches frame post‑disaster recovery as a sequential decision-making problem over infrastructure elements, using graph-based system models and resilience-oriented rewards. This thesis builds on an existing DRL framework by introducing a modified CDC Social Vulnerability Index (mCDC-SVI), developed using Max-min scaling, to quantify social vulnerability.A synthetic interdependent infrastructure testbed is divided into four socio‑economic regions using federal poverty and SNAP eligibility guidelines. The DRL simulation and Deep Q‑Network architecture are retrained under a multi-objective reward function that is efficiency-equity weighted (α:β). Agents are evaluated across unconstrained and constrained budget scenarios to examine how varying α and …

Resurrecting The Lost City Of Kaskaskia: An Archival, Gis, And Archaeological Investigation Of Illinois’ First Capital, Rebecca Ramey

Theses

This thesis centers around the question of how much remains of historical Kaskaskia, Illinois in the archaeological context, and examines the common historical narrative and its lack of inclusion of non-white voices. Kaskaskia was a vibrant, diasporic community that shaped the founding of Illinois. Through archival research, ArcGIS, geophysical surveys, and an archaeological investigation, this thesis proves that it is possible to bring those voices back through the archaeological record. Kaskaskia has long been ignored by the broader research community, and this thesis aims to show just how much potential Kaskaskia has at contributing to our understanding of the founding …

Development Of Chemical Reaction Airbag Safety System For Multi-Rotor Uav To Mitigate Free-Fall Collision Impact, Brady Kent Villiger

Theses

With Unmanned Aerial Vehicles (UAVs) becoming more advanced, the demand of companies that plan to use them for commercial use has only increased. Amazon plans to use UAVs for shipping purposes, Esri uses UAVs for surveying purposes, and many government organizations use UAVs for search and rescue, infrastructure inspection, and power line inspection. With all these uses, UAV safety becomes a major concern. If a UAV were to fail mid-flight there would be an issue if it collided with a person or an expensive piece of equipment after a free-fall. In this paper, the proposed safety system would be a …

Prediction Of The Nga-West2 Average Vertical Peak Ground Acceleration Using Genetic Expression Programming, Dipankar Karki

Theses

Ground Motion Predicting Equation (GMPEs) has been proposed with the use of Genetic Expression Programming (GEP) tool using 10,080 ground motion records obtained from the NGA West2 database. For this research, moment magnitude, dip angle, rake angle, Joyner Boore Distance, depth to top of fault distance, closest distance to ruptured fault area and the shear wave velocity in top 30 m of the site have been selected as the predictor set. It was found that the results from the GEP model compared well with the existing GMPEs and validates the use of GEPs for creating GMPEs along with other regressions …

The Investigation Of The Digital Divide: Government Literacy With African American Seniors, Jenettie Pirtle

Theses

My thesis, The Great Divide: An Investigation of Digital Literacy with African American Seniors, explores how race, age, and income shape access to technology and digital learning. Many African American seniors continue to face barriers to digital literacy due to limited resources, lack of exposure, and social inequalities. Using a qualitative approach, I conducted a focus group to hear directly from seniors about their experiences with technology, what challenges they face, how they feel about using it, and what support they need. Guided by Critical Race Theory and the concept of digital inequality, my analysis highlights the gap between access …