Digital Commons Network^™

Advancing Academic Advising With Knowledge Graphs: Integrating Machine Learning And Llms For Personalized Course Planning, Sara Alshamsi

Theses

Academic advising plays a critical role in helping students make informed decisions, improve academic performance, and successfully navigate their university journey. However, with increasing university enrollment, traditional advising methods often struggle to scale, leading to student frustration and overburdened advisors. Additionally, designing course offerings that match student demand is a complex and error-prone process involving multiple stakeholders. To address these challenges, this thesis proposes an automated, data-driven system for generating personalized academic plans for students. The primary aim of this thesis is to develop a system that reduces students’ dependency on advisors while simultaneously providing accurate estimates of course demand …

Numerical Methods For Approximating Line Integrals Over Implicitly Defined Curves, Raghd Alsaadawi

Theses

In this thesis, we develop and investigate a predictor-corrector method for the numerical tracing of implicitly defined curves. The study begins with the introduction of modified numerical integration techniques — specifically, the modified trapezoidal and modified midpoint rules — for evaluating the line integral of a vector field along an implicitly defined curve. Furthermore, we explore higher-order methods aimed at improving the accuracy of such integrals. Theoretical and numerical results, including asymptotic error expansions, are presented to support the analysis. In addition, several numerical experiments are carried out to illustrate the effectiveness and robustness of the proposed approaches.

Multi-Point And Multi-Station Orbit Propagation For Non-Functional Drifting Geo Satellites, Hritik Mitra

Theses

Currently, there are thousands of man-made space objects that are orbiting the Earth. These satellites serve a host of essential purposes (scientific research, technical applications, services) and they are all required to remain within their mission parameters. Most critical for them is to maintain the orbital parameters that are specified to achieve a particular mission’s objectives. If a satellite deviates beyond a certain limit, there is not only a risk of mission failure but there is a major hazard for possible collisions with other objects such as active satellites, space debris and even natural objects in some cases. There is …

Investigation And Prediction Of Excessive Water Production In Bottom Water-Drive Naturally Fractured Reservoirs Using Machine And Deep Learning, Sami Abderraouf Belkhir

Theses

Naturally Fractured Reservoirs (NFRs) are characterized by dual-porosity and dual-permeability systems, posing significant challenges in managing water production due to highly conductive fracture networks that facilitate rapid water migration from bottom aquifers, often bypassing oil stored in the matrix, thus resulting in early water breakthrough and water channeling phenomena. The main objective of this thesis is to develop and validate deep learning and machine learning models to predict water production, water breakthrough time (tbt), and ultimate water cut (WCult) in NFRs, thereby enabling more effective reservoir management strategies. This work also aims to evaluate the sensitivity of water behavior to …

Measurement And Improvement Of Photon Identification Efficiencies Using Machine Learning Techniques In The Atlas Detector At The Lhc, Abdulla Esam Mahboub

Theses

Photons play a crucial role in numerous analyses at the Large Hadron Collider (LHC), particularly in studies like the Higgs boson decay to two photons. Precise photon identification is essential for enhancing the sensitivity and accuracy of such measurements. This thesis focuses on the development of a machine learning (ML)-based photon identification algorithm to improve the photon identification efficiency within the ATLAS detector, using a Deep Neural Network (DNN) approach. The primary goal is to boost photon identification efficiency by using advanced neural network techniques. Traditional photon identification relies on cuts applied to shower shape variables, which can limit the …

Exploring The Quality Of Professional Development In Addressing Challenges With Behavior Management Of Special Needs Students In Inclusive Classrooms: An Instrumental Case Study, Reem Hussein Abuwatfa

Theses

Inclusive education has become a major educational priority globally and within the United Arab Emirates (UAE), driven by policies promoting the full participation of students with special educational needs (SEN) in inclusive classrooms. This study explores how elementary-level general education teachers perceive the quality of professional development (PD) in addressing their challenges with behavior management of students with SEN in inclusive classrooms. A qualitative case study approach was used, utilizing semi-structured interviews. The findings indicated that teachers face challenges from the behavioral issues of SEN students in inclusive classrooms, affecting both typical peers and teachers. Moreover, teachers had mixed perceptions …

Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofriendly Systems, Noora Saleh Al Mansoori

Theses

Traditional experimental approaches in industrial processes, such as Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, thermogravimetric analysis (TGA), and well-drilling operations, are often constrained by time, cost, and operational limitations. This research explores the application of data-driven Machine Learning (ML)-based predictive modeling to improve efficiency and reduce dependency on resource-intensive experimentation. The study develops ML models for three distinct processes: FTIR intensity prediction of bitumen thermal cracking products, thermal degradation of Medium-Density Fibreboard (MDF) using TGA data, and Rate of Penetration (ROP) prediction in petrochemical industry. Six algorithms: Linear Regression (LinReg), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Gradient …

Wavelet-Based Multi-Step Methods For Systems Of Differential Equations, Rashad Assad Hijji

Theses

Wavelets have been widely used in many areas of engineering and mathematics, including the development of multistep algorithms to solve initial value problems (IVPs) in the context of the Galerkin method using Daubechies' wavelets. The main scope of our work is to build a comprehensive framework for solving Systems of Differential equations using the compactly supported wavelets proposed by I. Daubechies. Wavelets are mathematical functions that decompose data into distinct frequency components, and each element is analyzed with a resolution that matches its scale. Compact support of Daubechies wavelets is key in allowing them to be computationally efficient for high-dimensional …

Electrospun Membranes From Bio-Renewable Poly (Ethylene Furanoate)/Poly (Ethylene Teraphthalate) (Pef/Pet) Blend For Emulsification Application, Aya Ismat Sayed

Theses

This thesis focuses on manufacturing electrospun fibrous membranes from a blend of poly (ethylene terephthalate) and poly (ethylene furanoate) and using in premix emulsification. Poly (ethylene furanoate), which is a 100% bio-renewable polymer being blended with synthetic poly (ethylene terephthalate) for membrane fabrication contributes towards sustainability in the production of food and pharmaceutical emulsions. The primary objective of this research is to optimize the fabrication conditions of poly (ethylene terephthalate)/poly (ethylene furanoate) porous membranes, characterize their properties, and evaluate their performance in emulsification. This study compares poly (ethylene terephthalate) / poly (ethylene furanoate) blend membranes with individual poly (ethylene terephthalate) …

Utilizing Date Fruit Pomace As A Corrosion Green Inhibitor For Non Ferrous Alloys, Sardor Rustam Odilov

Theses

This thesis explores a novel green corrosion inhibitor derived from date fruit pomace extract (DFPE) for the protection of aluminum alloy 3003 in highly corrosive environments, specifically hydrochloric acid (HCl) and natural seawater. The central aim is to promote the sustainable reuse of agro-waste as an effective and eco-friendly alternative to conventional toxic inhibitors, aligning with environmental and industrial safety goals.

A comprehensive methodology was employed, including Soxhlet extraction (using both non-polar n-hexane and polar methanol-water solvents), rotary evaporation, and FTIR analysis to identify the active functional groups responsible for inhibition. Corrosion behavior was systematically evaluated using both mechanical (weight …

Engineering Microphysiological Systems To Investigate Cellular Responses To Biophysical Cues In Human Tissue Microenvironments, Mehran Mansouri

Theses

Cells constantly sense and respond to biophysical cues in their microenvironment. Understanding how they interpret these mechanical signals is essential for advancing tissue modeling, studying disease mechanisms, and developing more predictive in vitro platforms. This dissertation presents a series of engineered microphysiological systems (MPS) designed to investigate how mechanical stimuli shape cellular behavior in distinct human tissue microenvironments. In Aim 1, I developed a reconfigurable microfluidic platform that mimics key features of human vascular barriers. This system supports the integration of porous membranes, 3D hydrogels, and flow channels, enabling precise control over both mechanical and biochemical cues. The modularity of …

Interaction Of Liquid Phase Diisopropyl Methyl Phosphonate (Dimp) With Material Surrogates For Components Of Soil And Combustion Products Of Metal Fuels, Khushi Sunil Patel

Theses

Combustion products of three different Al-based materials, Al-CaCO₃, Al-SiO₂, and Al-Fe₂O₃ , have been produced to understand their interaction with liquid diisopropyl methyl phosphonate (DIMP), a surrogate for chemical weapon agents. The purpose of this is to see which materials were more effective at DIMP adsorption and decomposition at different temperatures. Prepared materials were characterized using electron microscopy, x-ray powder diffraction, and nitrogen adsorption. Prepared powders were submerged in DIMP and heated in a thermal analyzer, tracking the mass changes as a function of temperature. Surfaces of the recovered materials were studied using …

Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh

Theses

Gait impairments arise from systemic diseases, age-related degeneration, musculoskeletal dysfunctions, or neurological conditions. While traditional rehabilitation can be effective, they often face challenges such as high costs, inaccessibility, and low patient engagement. To address these challenges, my work introduces a virtual reality-based rehabilitation (VRBR) system, integrating real-time motion and electromyographic (EMG) muscle activation feedback with a gamified virtual environment for enhanced adaptability and engagement. The system includes a custom-designed hip-exoskeleton that provides adaptive spring-like assistance or resistance, supporting both mobility-impaired users and strength training. Assistance levels can be tuned to match the user's progress. Additionally, a custom pressure insole was …

Hybrid Sentiment Analysis Of Police Social Media: Managing Big Data Impact On Youth, Alunood Yousuf Alamiri

Theses

The pervasive influence of social media has reshaped public communication, particularly for institutions like law enforcement agencies that rely on these platforms to engage with the community. As police departments increasingly utilize social media to disseminate information, interact with the public, and manage public relations, the need for effective sentiment analysis becomes crucial. Understanding how police messages are received by the public, especially by the youth, who are among the most active and impressionable users of social media, is essential for maintaining public trust and ensuring effective communication. This thesis, seeks to develop a comprehensive solution for this challenge. The …

Forecasting Cryptocurrency Price Movements With Tweet Volume And Sentiment Analysis, Ahmed Alblooshi

Theses

Cryptocurrency markets are highly volatile and driven by rapidly shifting public sentiment and attention. Traditional financial models, reliant on historical pricing data, often fall short in capturingthereal-time,sentiment-basedbehaviourofcryptoinvestors. Among social platforms, X(formerly Twitter) stands out as a key influencer in crypto discussions, offering a rich source of public sentiment. The thesis presents a machine learning-powered tool that leverages tweet volume and sentiment to analyse short-term cryptocurrency trends. The primary aim is to design a practical analysis system that detects and interprets social media ”hype” around specific cryptocurrencies. By allowing users to choose a cryptocurrency name from a list, the tool provides …

Predicting Patient No-Show Rate In Healthcare To Improve Operational Excellence, Saeed Ahmed Al Wari

Theses

The challenge of integrating no-show predictive models into healthcare environments is complex and multifaceted, extending far beyond the distinct technical challenge of building accurate models. This thesis will discuss more on the subject of incorporating machine learning into healthcare. While algorithmic accuracy and model validation are critical, they are a mere sub-system of a much larger operational, technological, ethical, legal and human ecosystem. Predictive models face mass deployment in healthcare systems which are complex networks of stakeholders across strict regulatory frameworks and deeply embedded workflows (AlMuhaideb et al., 2019). However, for these models to result in long term and real …

Predicting Customer Churn In E-Commerce, Hind Tawfiq Kazim

Theses

Customer retention has become a critical focus for businesses seeking to sustain growth and profitability in an increasingly competitive market. In this thesis, advanced machine learning techniques are used to develop a data-driven churn prediction model for Majid Al Futtaim's customer base. In an e-commerce environment, the research focuses on identifying the key transactional and behavioral factors that influence customer churn, based on customer relationship management theory. The study is contextualized in the context of increased digital consumer engagement and high customer acquisition costs, which make retaining existing customers more cost- effective than acquiring new ones. Our primary research questions …

Future Of Inclusive Education In The Uae: Supporting Learning Disabilities In Higher Education, Christina Ayub

Theses

Inclusive education is a critical component of higher education, ensuring that students with learning disabilities (LDs) receive equitable access to academic opportunities and institutional support. While global advancements in inclusive education have been significant, the UAE’s higher education sector faces unique challenges in accommodating students with LDs, particularly as technological disruptions, demographic shifts, and evolving policies reshape the broader educational landscape. This research investigates how a higher education institution in the UAE, such as RIT Dubai, might adapt its support systems for students with LDs, such as ADHD, dyslexia, dyscalculia, dysgraphia, and dyspraxia, under a range of plausible future conditions …

Transmit And Deceive: Addressing The Insider Threat To Beacon Security, Noah Troy

Theses

IEEE 802.11 Beacon frames exist at the forefront of modern Wi-Fi networks and facilitate a wide array of essential network functionality, from discovery to time synchronization and even transmit power control. However, the central role Beacon frames play in initial network advertisement comes at the price of incomplete security guarantees, leaving these frames historically vulnerable to forgery and granting significant leverage over proximal wireless devices to a malicious actor that can effectively spoof them. With the publication of IEEE Std 802.11-2020, beacon protection was introduced to enable the authentication of received Beacon frames, placating most concerns. However, beacon protection is …

On The Use Of Nonlinear Electrophoresis For Separating Particles And Cells In Insulator-Based Electrokinetic Systems, Alaleh Vaghef-Koodehi

Theses

The increasing demand for efficient separation processes of micron-sized particles, including microorganisms, highlights the importance of developing low-cost, non-labor-intensive, and time-efficient techniques. Insulator-based electrokinetic (iEK) systems have proven to be a practical alternative to bench-scale methodologies such as centrifugation and membrane filtration. Several studies have reported the separation of microparticles by employing direct current (DC) voltages. However, all of them have overlooked the phenomenon of nonlinear electrophoresis (EPNL) and its role in the electrokinetic migration of particles. This study combines mathematical modeling and experiments to extend the capabilities of iEK systems. This dissertation has four aims: (1) to separate microparticles …

Shopping Quest: Transforming The Shopping Experience By Creating A More Immersive And Enjoyable Experience, Nagasai Vardhan Rao Sarvepalli

Theses

In the post-pandemic era, this thesis looks into how gamification and augmented reality (AR) can get customers back into physical retail settings. Brick-and-mortar stores have found it difficult to stay relevant as consumer preferences have shifted toward online convenience. Shopping Quest attempts to make in-store grocery shopping an engaging experience. The project started with qualitative surveys using a human-centered design process to determine the main frustrations of shoppers, which were navigation and remembering what to buy. The final idea makes use of a wearable AR interface that directs users with a virtual rocket and promotes exploration with collectible digital petals. …

Peach Street, Anastasia Lawrence

Theses

Peach Street connects to the universal phenomenon of losing innocence of childhood and navigating the perils and disappointments of the adult world and visualizes my ongoing experience with anxiety and what psychiatrists call derealization, the feeling of being detached from reality. Set in the same location as where I first felt immense panic, my photos create a fictional narrative where a small town, its residents, and the environment are being controlled by a force emanating from the town’s lake. The lake’s aura blinds the residents to its control, forcing them to live in a set way without personal expression or …

Wooden Spatial Analogies: Playful, Transformative Design Process Kit With Inclusion In Mind, Sarah R. Baxter

Theses

This paper concerns solutions to insufficient support in educational inclusivity through the subject of the five design process steps. It leverages the insights of researchers, such as Linda Silverman, regarding ‘visual-spatial learners’, individuals who perceive the world through images rather than words and thrive in navigating complex tasks, yet often face challenges with linear, step-by-step processes. This work critiques the conventional educational methods that frequently overlook the profound potential of spatially adept students. A final prototyped solution was assembled. The outcome was shaped, sanded, and painted wooden spatial analogies of play, designed for rearrangement, and interactively representative of the design …

On-The-Go Handbag: Sustainable & Biodegradable Handbag Design, Sydney Neff

Theses

Handbags have been an ever-present accessory in society for centuries, coming to symbolize not only fashion trends but status and femininity. They have evolved to hold extreme significance, being able to show a snapshot of who a woman is by taking a simple look inside. Purses have become a companion for consumers in many ways, accompanying them throughout important days and events, providing talking points, and even compliments for the user. However, these constant companions come at a cost. The fashion industry and the accessories produced within are an immense cause of environmental pollution. This provides an ever-present internal fight …

The Intersection Of Spirituality, Commerce, And Art In The Work Of William Keith, Joan Gallagher

Theses

This thesis examines the nineteenth-century Tonalist artist William Keith, focusing on how he successfully integrated commerce, art, and spirituality to achieve financial success, artistic innovation, and spiritual depth. While scholars often emphasize the symbolism and religiosity in his work, they tend to overlook his financial accomplishments. This study explores Keith's background, religious influences, and artistic development within the cultural, economic, and social context of nineteenth-century America. As a Tonalist, Keith produced popular works for the art market; as a Swedenborgian, his art reflected the spiritual principles of that faith. Unlike his East Coast counterparts, Keith’s California-based landscapes captured the dramatic …

End-To-End Systems Limitations In Hyperspectral Target Detection Using Parametric Modeling And Subpixel Lattice Targets For Validation, Chase Canas

Theses

Hyperspectral target detection applies algorithms to high-dimensional images to identify rare targets, or objects of interest, within cluttered scenes of diverse backgrounds. Computational demands of processing hyperspectral datasets, along with their limited availability in both public and private sectors, imposes challenges in assessing system-level limitations of detection. This research presents a methodology to quantify end-to-end sensitivities and limitations through statistical modeling across thousands of target detection scenarios. The objective is to identify specific parametric thresholds where detection begins to degrade, based on “knees” in detection curves derived from model outputs of various scenarios. The model considers subpixel targets, where an …

Realmweaver: Designing A Sandbox Simulation Game With Ai-Driven Storytelling, Tianzhe Fan

Theses

This paper introduces Realmweaver, a sandbox simulation game concept that combines artificial intelligence (AI) and procedural generation to balance player creativity and system automation. Realmweaver empowers players to create dynamic characters, build expansive worlds, and co-author narratives through adaptive AI systems. By leveraging technologies such as natural language processing and layered procedural algorithms, the game addresses challenges in maintaining narrative coherence and balancing user agency with system autonomy. The design framework integrates intuitive interfaces, including highlighted narrative systems and interactive hover functionality, ensuring accessibility while enhancing engagement. These features enable players to navigate complex systems and shape immersive worlds with …

Beyond Barcodes, Ritul Chaudhary

Theses

Beyond Barcodes is a conceptual zine that investigates the narratives encoded within barcodes and reinterprets receipts as tools to examine the emotional layers of consumer behavior. Often dismissed as transactional byproducts, receipts in this project are reframed as carriers of memory, identity and self-worth—reflecting personal values shaped by frugality, guilt, and inherited beliefs about money. The zine unfolds through a series of illustrated vignettes, each centered around a category of spending: groceries, essentials, dining, vanity, and experiences. This arc traces a journey from survival to indulgence, ending on a bittersweet note—critiquing how consumer culture quietly shapes how we spend, what …

Access To Justice For Deaf Defendants, Anna Zieba

Theses

Deaf individuals face systemic accessibility within the criminal justice system, which emphasizes the importance of the gaps in accommodations by the Americans with Disabilities Act (ADA). Inconsistent legal protection, limited access to interpreters, inadequate training for legal professionals, and a lack of technology resources obstruct effective communication for Deaf individuals. As a result, it prohibits achieving an effective and equitable legal outcome. This research paper will examine case studies, legal frameworks, and academic literature to highlight the critical need for reform, including mandatory Deaf culture training, standardized interpreting qualifications, and more resources to enable equitable access to justice.

Development Of A Miniaturized Extracorporeal Membrane Oxygenation (Ecmo) Device On A Microfluidic Platform, Nayeem Imtiaz

Theses

This research investigates the design, performance, and optimization of blood-contacting microfluidic medical devices, with each aim contributing to a broader understanding of how engineering choices influence hemocompatibility and oxygen transfer. Collectively, the findings from Aims 1A–2B offer integrated strategies to develop safer, more effective microfluidic systems for ECMO and dialysis. Aim 1A assessed hemolysis across device geometries using computational and experimental methods. All designs showed low device-induced hemolysis (< 2 ppm), validating their hemocompatibility. However, Power-Law models frequently overpredicted hemolysis, indicating a need for refined parameters tailored to microfluidic flow conditions. Aim 1B demonstrated the effectiveness of thrombosis assay techniques in evaluating clot formation in microfluidic device geometries. Results showed that geometry and local shear patterns strongly influence thrombogenesis. While hemolysis remained minimal even in high-shear devices, thrombus formation was more geometry-sensitive—underscoring the need to account for both factors in design. Modifying surface properties and accounting for blood composition could further reduce thrombotic risk. In Aim 2A, we compared PDMS, polypropylene (PP), and nanoporous silicon nitride (NPSiN) membranes for oxygen transport. Findings showed that in ECMO devices, blood-side resistance, not membrane permeability, often dominates oxygen transfer. Thus, membrane choice must be paired with optimized blood-side flow for full performance gains. Aim 2B directly addressed these limitations by integrating staggered herringbone mixers (SHBs), which introduced secondary flows and enhanced mixing. The Single Channel Herringbone design yielded the highest oxygen transfer, confirming the synergy between flow geometry and oxygen transport performance. Altogether, Aims 1A and 1B establish a strong framework for hemocompatibility evaluation, while Aims 2A and 2B provide complementary insights into optimizing oxygen transfer. Their interconnections highlight the value of a systems-level approach to designing microfluidic blood-contacting devices.