Digital Commons Network^™

Meridian, Rachel Seaton

Theses

Meridian is an ambient tabletop object that translates physiological data into a continuously evolving visual landscape. Rather than presenting emotional information through charts or notifications, it exists as a quiet environmental presence that can be understood through peripheral awareness. A simulated biometric system drives a particle field whose movement reflects physiological variation, producing eight distinct visual signatures. The visual system is governed by four parameters: field density, field disturbance, signal trace, and signal duration, which together shape the behavior and persistence of the particle field. The teardrop form was selected for its ability to convey both the passage of time …

Spikerff: Learning Forward With Layer-Local Plasticity And Semi-Hard Negatives, Karthik Tumkur Kumar

Theses

Effective contrastive learning relies on choosing useful, informative "hard" negative samples. Current hard negative sampling methods designed for traditional artificial neural networks (ANNs) are, in general, computationally costly and are ill-suited to account for the temporal structure relevant to neuromorphic data. To tackle these issues, in this work, we formulate a similarity-guided semi-hard negative sampling strategy for neuromorphic computing based on spiking neural networks (SNNs). We propose SpikeRFF (Spiking Recurrent Forward-Forward), a gradient-free and unsupervised recurrent spiking framework that combines layer-local Forward-Forward learning with semi-hard negative selection and temporally structured negative construction. Positive samples are encouraged to produce high goodness, …

Comparing Deposition-Dependent Variations In Tungsten Oxide Thin-Film Composition Using X-Ray Photoelectron Spectroscopy, Tevfik Ozkaynak

Theses

In this work, tungsten oxide thin films were fabricated using magnetron sputter deposition and electron beam evaporation under varying oxygen conditions to produce a range of stoichiometries, including substoichiometric compositions near WO₂.₇. The primary goal was to evaluate how reliably X-ray photoelectron spectroscopy (XPS) can quantify the stoichiometry of WOₓ thin films, determine how deposition conditions influence measured composition and oxidation states, and assess how argon ion sputtering, used for surface cleaning, alters tungsten oxidation states and affects XPS based stoichiometry. The films were analyzed using XPS under ultra-high vacuum conditions. Survey spectra were used to identify elemental composition, while …

What’S Kept, Caitlin Smith

Theses

This thesis examines the collective psychological aftermath of de-industrialization in a rust belt city, processed through perspectives of nostalgia and betrayal. By reframing childhood memories of instability and inherited narratives, a framework is established for investigating the modalities through which love and attachment may obscure entangled harm, and how grief operates across both collective and personal registers. Found objects are situated as sites of projection where memories are abstracted and reconstituted. The processes of decay and weathering serve as analogues for psychological trauma, reframing deterioration as an inevitable and generative condition. Natural elements act as metaphors for neutrality, challenging imposed …

Large Language Model-Driven Agents In Virtual Reality For Inclusive Communication Training, Ziming Li

Theses

Vocational training programs aimed at improving the employability and autonomy of autistic individuals primarily focus on enhancing social communication skills. However, developing and implementing such training activities often demands significant time and effort from job coaches, who must adapt to various interview and workplace scenarios while customizing the training to meet the specific needs of autistic trainees. These challenges create barriers for job coaches to efficiently train autistic individuals and objectively evaluate their performance. To address these challenges, this dissertation explores the use of virtual reality (VR) and large language model (LLM)-driven agents to create customizable and interactive training platforms …

Evaluation Of Laser Power, Heat Treatment, And Wall Configuration Of Ss316l And Er70s-6 Structures Fabricated By Wire Laser Metal Deposition, Ayman Abdelgwwad

Theses

Wire-Laser Metal Deposition (W-LMD) is a transformative direct energy deposition additive manufacturing technology that utilizes a laser heat source to melt metallic wire feedstock for the high-efficiency fabrication of large-scale, near-net-shape components. The technology is distinguished by its high material utilization efficiency and superior safety compared to metal powder-based systems. W-LMD systems are composed of a focused laser, a wire feeder mechanism, a multi-degree of freedom motion system, cooling system, and a shielding gas supply to prevent oxidation. Deviation in process parameters can lead to external defects such as stubbing (insufficient melting) and dripping (melting above the melt pool), as …

Decision Model For The Application Of Circular Economy In The End-Of-Life Management Of Power Transformers, Maha Mansour Nadhari

Theses

Power transformers are critical assets within utilities characterized by high capital and material intensity and long operational lifetimes. Traditionally, end-of-life management strategies for these transformers are very linear, limited to recovery or basic recycling and disposal. Although circular strategies can be integrated into the end-of-life management of these transformers, a key challenge to implementation is the absence of a structured, multi-criteria framework that can support decision-making in this context. This study addresses this gap by developing a decision model using a hybrid Multi Criteria Decision Analysis (MCDA) approach combining the Analytic Hierarchy Process (AHP) and the Technique for Order Preference …

Understanding The Lubrication Mechanisms Of Environmentally Compatible Protic Ionic Liquids, Davis Kipkania Kiboi

Theses

The development of environmentally sustainable lubricants is increasingly important as industries seek to reduce friction, wear, energy losses, and environmental impact. Choline amino acid protic ionic liquids (PILs) have emerged as promising candidates due to their bio-based constituents, tunable molecular structures, and favorable lubrication properties. However, the influence of amino acid structure on their lubrication mechanisms and tribological performance remains poorly understood. This dissertation investigates the physicochemical properties, tribological behavior, and tribofilm formation mechanisms of choline amino acid PILs to establish structure–property–performance relationships for sustainable lubricant design. Ten choline amino acid PILs containing glycine, alanine, lysine, leucine, isoleucine, aspartic acid, …

Exergy Analyses Of Potential Clean Hydrogen Technologies In The Uae, Gaurav Cjk Kewalramani

Theses

This thesis evaluates clean hydrogen production pathways suitable for the United Arab Emirates by  integrating nuclear, solar, and wind energy with proton exchange membrane electrolysis (PEM), anion  exchange membrane electrolysis with a liquid alkaline separator (AEM), and alkaline water electrolysis  (AWE). A literature review was first conducted to compare hydrogen production technologies based on  efficiency, cost, scalability, environmental performance, and compatibility with UAE energy resources.  Energy and exergy models were then developed for the APR1400 steam Rankine cycle, the Mohammed bin  Rashid Al Maktoum Solar Park, the Sir Bani Yas wind farm, and the three electrolysis technologies.  The APR1400 Rankine-cycle …

Modernizing Civic Building Design For Emergency Shelter Operations: An Architectural Framework With Proposed Design Guidelines For 21st-Century Shelter Readiness, Enrique M. Peralta

Theses

The frequency and severity of climate-related disasters are rising globally, resulting in the displacement of millions of individuals each year. Although this is a worldwide issue, the present research concentrates on the New York, New Jersey, and Connecticut tri-state region, where severe storms, flooding, prolonged power outages, and other natural hazards frequently necessitate the activation of emergency shelters. While schools, community centers, and other civic buildings are commonly designated for emergency shelter operations, these facilities were not originally designed to accommodate displaced groups during such events. This study focuses on the immediate sheltering period following a disaster, defined as the …

Towards Reliable Large Language Models For Cyber Threat Intelligence, Md Tanvirul Alam

Theses

Cyber Threat Intelligence (CTI) helps security analysts respond to evolving threats, but the evidence it draws on is often scattered across noisy reports, advisories, and threat descriptions. Large language models (LLMs) provide a flexible interface for security analysis, yet reliable use requires grounding their outputs in source evidence, domain schemas, and CTI standards. We address this problem through structured threat representation, task-specific evaluation, and verifier-guided post-training. First, we study how unstructured CTI reports can be converted into structured threat knowledge. We develop an ontology-guided extraction framework that normalizes attack patterns, extracts typed entities and relations, and constructs a threat intelligence …

Assessing The Imprint Of Eccentricity In Gravitational-Wave Signatures, Natalie Malagon

Theses

The gravitational wave signal from merging compact binaries encodes information about their orbital and intrinsic properties. Over the last few years, state-of-the-art waveform models have begun to incorporate the effects of orbital eccentricity into their estimated signal. Over a similar period, many groups have applied these waveforms to characterize whether the imprint of eccentricity is present and, if so, measure this time-evolving property (at a suitably-defined reference point). In this work, we present a comprehensive analysis of 173 confident sources identified in the O1 through O4a observing runs of the International Gravitational Wave Network (LIGO-Virgo-KAGRA). Using the RIFT parameter inference …

Learning-Based Multi-Objective Operation Of Microgrid With Renewable Uncertainty And Demand-Side Management, Zeina Bahij

Theses

A microgrid is a small-scale power grid that can operate in either the grid-connected mode or the islanded mode. It consists of energy generation and storage devices for both power and thermal demands, where the thermal energy from the exhaust heat that cannot be transmitted over long distances can be utilized locally. The supply side may include dispatchable generation units with adjustable outputs and energy storage, alongside non-dispatchable renewables that depend entirely on resource availability. On the demand side, thermal loads are satisfied through waste heat recovery from exhaust gas (to maximize overall system efficiency) and direct fuel combustion. Electrical …

Rooted Worlds, Eli Groborchik

Theses

Plant Awareness Disparity (PAD) describes a widespread cognitive bias where plant life is systematically overlooked in favor of its animal counterparts. This disconnect is acutely visible in natural history museums where plant life is notoriously difficult to display. Rooted Worlds is an interactive, physical-digital installation designed to combat this bias by bridging the emotional and educational gap between audiences and Earth’s diverse ecosystems. Rejecting traditional flat screens and passive dioramas, the exhibit utilizes a fourteen-foot, 270-degree cylindrical projection screen to immerse visitors in six distinct, digitally rendered global biomes, creating a restorative and engaging space that leverages Attention Restoration Theory …

Analysis Of The Formation And Structure Of Protective Films In Sustainable Ionic Liquid Lubricants, Brendan Mahoney

Theses

Friction losses and wear of sliding components account for nearly one quarter of global energy consumption. Developing new lubricants to reduce these losses is essential for a more cost-effective and sustainable future. The automotive industry offers the greatest economic potential for new tribological discoveries, as it affects billions of people around the world. A significant portion of the friction losses in automobiles are due to the reciprocating motion in the engine, which leads to metal-on-metal contact. Ionic liquids have emerged as novel lubricants and additives due to their ability to form protective surface layers on metals, reducing friction and wear. …

Integrated Sources Of Photon-Pairs For Quantum Networking, Vijay Soorya Shunmuga Sundaram

Theses

Quantum networking enables the distribution of quantum information across distant nodes, unlocking capabilities such as secure communication, distributed quantum computing, enhanced metrology, and tests of fundamental physics. Photons serve as the natural carriers of quantum information over long distances due to their low loss in optical fibers and robustness to environmental decoherence. However, the practical realization of quantum networks remains limited by the lack of photon sources that are simultaneously compatible with diverse quantum systems, stable over long timescales, and suitable for deployment in real-world fiber infrastructure.  This dissertation addresses these challenges through the co-development of photon-pair sources and a …

Development Of Blue And Near-Uv Iii-Nitride Laser Diodes, Matthew Seitz

Theses

III-Nitrides show tremendous promise for a wide range of laser diodes and other optoelectronics devices. The wide range of emission wavelengths possible makes these devices ideal candidates for a wide range of applications. Despite this, several challenges remain unsolved, limiting the efficiency and output power from III-Nitride optoelectronics. Three of the most significant remaining challenges surround the formation of low resistance ohmic electrical contacts, poor p-type doping of III-Nitride crystals as well, and the fabrication of the smooth, mirror facets needed for optical feedback and laser operation. Inefficient dopant activation leads to poor conductivity and increased electrical resistance due to …

Lubricating Abilities Of Choline Amino Acid Protic Ionic Liquids Under High Temperature And Electrified Conditions, Esmond Lau

Theses

This work explores the tribological properties of choline amino acid protic ionic liquids (PILs) as environmentally friendly lubricants under high temperatures and electrified conditions. These conditions are found in the automotive sector, notably in internal combustion engine vehicles (ICEVs) and electric vehicles (EVs). Lubrication technologies are vital to improving the efficiency and operating lifetime of moving components in automotive drivetrains. The use of ionic liquids (ILs) is actively being researched, with ongoing exploration of their lubricating potential and unique physicochemical characteristics. Compared to traditional petroleum-based lubricants, ILs’ ability to thrive in these conditions will offer substantial benefits, immediately extend operational …

Towards Efficient Continual Deep Learning, Md Yousuf Harun

Theses

Modern AI systems can achieve remarkable performance on tasks such as image recognition, object detection, and language understanding, but they often struggle with a basic ability that humans rely on every day: learning continuously. When deep neural networks (DNNs) are updated with new information, they can unexpectedly forget what they previously learned, making them difficult to deploy in changing real-world environments. This dissertation explores how to build AI systems that can learn more like humans: adapting to new data, preserving past knowledge, and using prior experience to learn future tasks more efficiently. Rather than focusing only on preventing forgetting, this …

Reinforcement Learning-Enabled Resource Allocation For Distributed And Uncoordinated Cognitive Radio Networks, Ankita Vijay Tondwalkar

Theses

To keep up with the ever-increasing performance demand from wireless applications, wireless networks necessitate to operate following an efficient use of the available radio spectrum. Since the radio spectrum is a limited resource, the increasing demand for wireless services and applications to support a wide spectrum of users is a challenge in itself and therefore requires advanced techniques to manage and utilize radio resources efficiently. Dynamic spectrum access (DSA) and sharing play a crucial role in improving the utilization of the radio spectrum, as it departs from the traditional approach of static radio spectrum band allocation which usually leads to …

Assistive Active Safety, Long Nguyen

Theses

As electric bicycles become faster and more prevalent in urban environments, the safety systems designed to protect riders face significant challenges. The current industry standard relies heavily on auditory warnings—which can exclude Deaf and Hard of Hearing (HOH) cyclists—and digital dashboards that often demand intense visual focus. Forcing a rider to process cluttered screen data while navigating high-speed traffic can contribute to cognitive overload and physical danger. This thesis explores how micro-mobility safety might be improved by shifting away from auditory-dependent alerts toward intuitive, multi-sensory communication. To address this safety gap, this project introduces the Assistive Active Safety (AAS) framework. …

Fractional Bernstein Polynomial Approximations For Nonlinear Timefractional Partial Differential Equations, Reem Abdul Quzli

Theses

This thesis studies the numerical approximation of nonlinear time-fractional partial differential equations using fractional Bernstein polynomials. The main model considered is the nonlinear time-fractional foam drainage equation, in which the classical time derivative is replaced by the Caputo fractional derivative. This formulation introduces memory effects into the model and allows the present drainage behavior to depend on the previous evolution of the liquid fraction.

The proposed method approximates the solution by a finite expansion of fractional Bernstein basis functions. After substituting this approximation into the governing equation, the residual is expanded in powers of t^�� . The unknown coefficient …

Analytical And Numerical Methods For Solving Fractional Integro-Differential Equations Using The Modified Operational Matrix Method, Nour Alzoubi

Theses

Fractional calculus has attracted considerable attention in recent years because of its wide applicability to model a variety of linear and nonlinear physical phenomena across different scientific disciplines. In particular, fractional diferential equation systems have proven to be effective in describing processes with memory and hereditary properties. However, the solvability and analysis of such systems strongly depend on the type of fractional operator employed, especially in the presence of nonlocal fractional derivatives with singular kernels, which remain an open and challenging area of research.

The main objective of this thesis is to develop efficient analytical and numerical techniques for solving …

Sea-Ice Observation In The Arctic By The Arab Satellite 813, Simulated By The Radiative Transfer Model ‘Sciatran’, Tuqa Mohsin Al Hajri

Theses

The purpose of this research is to explore the spectral behavior of sea ice and to understand how Arctic sea ice surfaces appear when they are observed with a hyperspectral sensor. This is crucial because sea ice changes a lot during the melt season, and different surface types can sometimes look similar to a human eye, but physically they are different. It is thus essential to identify the spectral differences between these surfaces. The main objective of this study is to examine how the spectra of white ice and melt ponds change when their physical and optical properties are varied, …

A Hybrid Approach To Phishing Email Detection: Leveraging Machine Learning And Large Language Models, Hessa Shamal Biri

Theses

Phishing attacks have reached a new level of sophistication through the deployment of large language models by attackers. The current AI-generated threats defeat existing detection systems which base their operation on past data. The thesis presents a hybrid system for phishing email detection which combines real email data with synthetic LLM-created samples to enhance traditional machine learning classifiers performance. The study created a hybrid dataset of 20,627 emails by combining 18,631 real messages from the Kaggle Email Classification Dataset with 1,996 synthetic emails. The synthetic emails were generated using four large language models LLaMA-3, Falcon, LLaVA, and Mistral to capture …

Heat Transfer And Micropolar Characteristic Analysis For Fluid Flow Over A Contracting Permeable Infinite-Length Cylinder: A Fractional Derivative Study, Khalid Al Homran

Theses

This study presents a comprehensive analysis of heat transfer and micropolar fluid characteristics for flow over a contracting permeable infinite-length cylinder using fractional derivative modeling. The micropolar fluid model accounts for microstructure effects that are prevalent in many practical applications, such as polymeric fluids, colloidal suspensions, and biological fluids. The inclusion of fractional derivatives allows the analysis to incorporate memory effects, which provide a more accurate depiction of the physical phenomena compared to classical integer-order models. The governing partial differential equations, representing the momentum, micropolar momentum and energy transport processes, are transformed into a set of nonlinear ordinary differential equations …

Ai-Powered Student Support And Development Platform, Wadha Rashed Alyammahi

Theses

Over the past few years, academic stress and student mental well-being have become critical concerns in educational settings, significantly affecting academic performance and overall quality of life. Students increasingly rely on digital platforms for academic support; however, many existing solutions lack the ability to adapt to users’ emotional states or provide personalized, context-aware assistance. In response to this challenge, this study presents the design and development of an intelligent, stress-aware conversational support system for students based on advanced natural language processing techniques and large language models.

The main goal of this study is to explore the effectiveness of an LLM-based …

A Reproducible Hdr-Native Psychophysics Infrastructure For Color Science Research, Fernando Voltolini De Azambuja

Theses

Color science psychophysics measures the human visual system by relating controlled visual stimuli to observer responses, often through forced-choice paradigms such as two-alternative forced choice (2AFC) (Kingdom and Prins 2016). These studies require stimuli specified in physically meaningful units, technically correct display emission, and reproducible execution (Fairchild 2013; Lin et al. 2023). In practice, graduate-level experiments often rely on bespoke MATLAB or Python scripts, standard dynamic range (SDR)-first toolchains such as Psychtoolbox and PsychoPy, manual stimulus duplication, and incomplete capture of calibration, colorimetric state, and display capability (Brainard 1997; Peirce et al. 2019). These limitations increase experimental friction and create …

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 …