Digital Commons Network^™

A Ux Approach To Improving Patient Experience In Healthcare, Lingxin Sun

Theses

Doc Ease is a UX research and design project that addresses the emotional and functional difficulties patients experience before visiting a doctor. Through user interviews, competitive analysis, and design iteration, this project identified key user pain points such as unclear appointment processes, lack of trust, and pre-visit anxiety. The resulting mobile app offers clear booking tools, visual doctor information, medication reminders, and an emotional wellness module to help patients prepare with confidence. The project contributes to the field of healthcare UX by integrating functional usability with emotional care, proposing a design framework that centers patient experience in both logic and …

Assessing The Impact Of Codec-Induced Audio Degradation On Voice Biometric Systems, Suhil Ali Almuhaisni

Theses

This study examines the robustness of voice biometrics when speech signals undergo audio codec transformations and sampling rate variations, conditions common in telecommunication networks. Speaker verification systems such as ECAPA-TDNN perform well on clean datasets, but their accuracy declines when low-bitrate codecs compress speech or when signals are resampled at reduced frequencies. In real-world deployments, systems adapt audio to bandwidth and storage limitations, often removing subtle acoustic details that support consistent speaker recognition. The research will analyse how codec settings and sampling rates, particularly those optimized for efficiency in bandwidth-limited systems, influence the stability of speaker embeddings. Instead of ranking …

Beyond Detection: A Batch-Based Ai Framework For Temporal And Event-Correlated Trend Analysis Of Misinformation On Social Media, Vishnu Tejas Vijayaraghavan

Theses

The rapid spread of misleading information on social media influences public behaviour and complicates crisis communication. Although transformer models such as BERT accurately detect misinformation at the post level, most studies analyse posts in isolation and overlook howmisinformation fluctuates over time or responds to major events. This study addresses that gap by developing an end-to-end analytical workflow that integrates BERT-based classification with temporal aggregation, topic clustering, anomaly detection, and event alignment. The analysis uses 10,700 COVID-19–related tweets (6,420 training, 2,140 validation, and 2,140 testing). Because timestamps were unavailable, synthetic timestamps were assigned using an evenly spaced date range between 1 …

An Examination Of High-Entropy Alternatives Of Connectionist Temporal Classification Loss For Optical Music Recognition Using Convolutional Recurrent Neural Networks, Hritik Saynganthone

Theses

The Connectionist Temporal Classification (CTC) loss function is the most commonly used loss function in the field of Optical Music Recognition (OMR). However, OMR suffers from a massive class imbalance problem, exacerbated by the fact that CTC loss is subject to the spiky distribution problem, wherein the blank token introduced by CTC is vastly overpredicted and appears in timesteps where it would make more sense to predict a non-blank token, since CTC will collapse repeated tokens into a single token. This work posits that alternative loss functions to CTC that optimize for an increase in entropy of the prior probability …

Assessing Large Language Models As An Interpretive Layer In Marketing Mix Modeling: Implications For Marketing Analytics, Mohammad Bin Haider

Theses

Marketing mix modelling (MMM) remains a core technique for guiding budget allocation, yet its outputs are often difficult for non-technical planners to interpret and govern. At the same time, large language models (LLMs) offer new possibilities for translating complex model artefacts into narrative guidance, but raise concerns about hallucination, reproducibility, and alignment with model-risk governance. This thesis examines whether an open-source MMM framework can be engineered as a repro- ducible, governance-ready pipeline and then augmented with a tightly constrained LLM interpretive layer. The empirical setting is a multi-brand, multi-country retail portfolio with several years of digital marketing and outcome data …

Desiccation Tolerance In Tetradesmus Green Algae, Kristen Patten

Theses

In the face of the global climate change threat, understanding the adaptations that organisms have evolved to handle environmental variation is of particular interest to scientists. With climate change impacting global water availability and increasing the risk of drought for many traditional agricultural areas in the United States (IPCC, 2014, IPCC, 2021, and Kuwayama et al., 2019), desiccation tolerance in vegetative states is one adaptation that is currently receiving a lot of attention. Green algae are particularly useful organisms for understanding this adaptation due to their ubiquity across environments, which has given rise to independently evolved organisms displaying different levels …

Accelerating The Degradation Of Biodegradable Mulch Films In Soil And Compost Environments, Harshal Jayesh Kansara

Theses

The incomplete degradation of biodegradable mulch films (BMFs) in agricultural soils poses environmental challenges, with persistent plastic residues impacting soil health. This dissertation investigates the use of bioaugmentation with P. guariconensis to enhance BMF degradation under laboratory, raised bed, and field conditions. The research focuses on optimizing microbial delivery methods, evaluating the efficacy of drip and spray bioaugmentation techniques, and assessing mass loss as a primary metric for degradation. Laboratory experiments established proof-of-concept by demonstrating enhanced carbon mineralization, weight loss, and fragmentation of BMFs under bioaugmented conditions. These findings were translated to field-scale trials, where bioaugmentation treatments consistently outperformed untreated …

Meshed Trees: A Framework For Resilient Network Algorithms And Protocols, Peter Willis

Theses

The continued growth of computer networks in both size and complexity presents challenges for the control protocols that are tasked with maintaining optimal data-forwarding paths. These protocols commonly rely on shortest-path algorithms to determine where network data should be propagated and how it should be analyzed for inclusion in forwarding tables. However, problems arise during reconvergence, the process in which devices rediscover optimal paths following a network failure. Because control protocols were built decades ago for the networks of that era, the existing shortest-path algorithms utilized were designed for problems before the advent of modern computer networks. This resulted in …

Infinite Screen-A Spatial Interface For Multi-Device Collaboration, Yichen Hou

Theses

Infinite Screen is a speculative design project that explores how mixed reality can transform a room full of personal devices into a shared spatial workspace for small-team collaboration. In studios, classrooms, and meeting rooms, people routinely work with multiple laptops, tablets, phones, and large displays, yet most existing tools still treat collaboration as a single-person screen-sharing activity. As a result, teams struggle to maintain a coherent shared view of their work, spending significant time negotiating who presents, which device is connected, and where key information resides. This thesis investigates how a room-scale interface might orchestrate these scattered screens through an …

Timeless Poetry, Xuning Li

Theses

Timeless Poetry reimagines classical Chinese poetry through contemporary digital tools, transforming ancient verse into immersive visual experiences. Using Cinema 4D and Blender for 3D modeling and ink-wash–inspired rendering, the project reconstructs poetic landscapes as cinematic-style environments that invite viewers to encounter traditional imagery through modern visual language. Postcards—chosen for their nostalgic and emotional resonance—serve as both a physical anchor and an interactive trigger: when scanned, each card reveals an AR visuals that reveal the scene in motion. This hybrid design bridges past and present, showing how technology can enhance, rather than replace, cultural heritage by offering new entry points for …

Into The Arms Of Earth, Alex Paat

Theses

This thesis investigates the construction of a visual language illuminating the Biblical theme of duality-union. Section 1 provides an overview of duality-union across Scripture, investigates the portrayal of duality-union in the Biblical theme of Heaven and Earth, and summarizes criteria for a successful visual language surrounding this concept. Section 2 outlines and justifies the building blocks of this visual language, which include clay, neon, a gestural building process, arboreal imagery, references to the mandorla shape, an optimistic aesthetic influenced by midcentury children's book illustration, and found objects. Section 3 provides a description and assessment of the seven pieces that make …

Ecoviz: Experience The Future Of Environmental Insight Through Motion And Visuals, Ronger Xu

Theses

The project titled ‘ECOVIZ’ investigates the potential of motion-based visualization to transform the way environmental data is understood and emotionally experienced. Through an interactive visual system that merges 3D motion design with environmental datasets, the project explores how abstract ecological information can be translated into intuitive and immersive experiences. ECOVIZ examines the ways in which data visualization, when paired with motion, depth, and spatial interaction, can foster a deeper and more meaningful engagement with climate-related information, bridging the gap between scientific data and public comprehension. ‘ECOVIZ’ transforms environmental statistics into dynamic, visually expressive forms that mirror the rhythms, fluctuations, and …

Exploring Human Perception And Cognition In Expressing And Understanding Mechanical Designs, Yan-Ting Chen

Theses

Effective communication of mechanical designs through technical drawings requires geometric accuracy, efficiency, and an understanding of human perception and cognition. Although advances in computer-aided design (CAD) software have improved drawing precision and automation, current tools often overlook the spatial reasoning processes that users employ to interpret these representations. This study seeks to improve the accuracy and efficiency of human-computer interaction in CAD environments by examining how individuals perceive and interpret three-dimensional mechanical components within the context of technical drawings. A key focus is the identification of canonical and optimal views that align with intuitive human understanding. Through a series of …

Playa Sediment Bioaccessibility Presents Previously Unknown Risks To Population Health In A Water-Stressed Region Undergoing Lake Desiccation: Salton Sea, Usa, Jordan Jaeger

Theses

Globally, drylands are expanding, and endorheic basins are in rapid decline. Saline lake desiccation exposes lakebed playa likely to become dust, posing potential health risks to surrounding communities. Studies investigating health risks from playa dust exposure often focus on health effects associated with the presence of airborne particulates, but fewer studies investigate health risks associated with dust source chemistry. This study examines dust source particle composition in a desiccating inland sea in a water-stressed agricultural region of California. Specifically, chemical bioaccessibility of bound trace elements uncovers risks to children, adults, and agricultural worker health. Arsenic exposure via sediment ingestion poses …

The World Is Beautiful, Chelsea Demott Wildey

Theses

My thesis, The World is Beautiful is a short, digitally animated film that follows the journey of a jaded employee working at a dystopian fishery. The intention of this piece was to tell a well-paced, coherent story that also served as an allegory to spark verbal discourse in an audience. As a surface level story, the film portrays a working protagonist who has been forced to remain seated at her desk by a mechanical chair. She, presumably, has been monotonously pressing icons on a screen for her entire life until something catches her eye and prompts her to break free …

Advancing Applications Of Deep Learning On Network Traffic Analysis And Fingerprinting, Nate Mathews

Theses

The growing reliance on encrypted communication networks and privacy-preserving technologies, such as Tor, has intensified the demand for advanced defenses against traffic analysis attacks. Although encryption conceals content, the exposure of metadata—such as timing, packet size, and traffic volume—remains a significant vulnerability, allowing adversaries to infer private user behavior and visited websites. This dissertation addresses the limitations of existing analysis by advancing the application of deep learning techniques across multiple domains of traffic analysis and fingerprinting. The first major contribution is a comprehensive evaluation of current website fingerprinting defenses, revealing critical weaknesses against sophisticated modern attacks. Building on this foundation, …

Graphic Design For Visual Narratives: The Semiotics Of Diegetic Retrofuturism, Brooke Luke Ballard

Theses

While semiotics, diegesis, and retrofuturism have all been discussed at length in academia, it is uncommon to find the synthesis of all three. When these concepts are combined, it forms what I argue is a new genre of graphic design now prevalent enough in contemporary media to warrant definition and analysis. This thesis first explores the theories of visual semiotics, narrative diegesis, and retrofuturistic aesthetics individually before uniting them as a new design genre. Several candidates for this design classification will then be examined in case studies that meet the criteria of 1) containing a visual language that a modern …

Enhancing It Security Management With An Advanced Intrusion Detection System Based On Machine Learning And Explainable Ai, Hanan Aslam Al Zubaidi

Theses

The fast changing landscape of cyber threats continues to challenge the development of strong and reliable security frameworks for IT management systems. Traditional defense tools, such as Intrusion Detection Systems (IDS), often struggle to keep up with today's advanced and constantly evolving attack methods. This thesis explores these ongoing challenges and looks into how machine learning (ML) and explainable artificial intelligence (XAI) can be used to boost IDS performance.

The research outlines a smart, adaptive system that combines supervised learning for real-time threat detection, unsupervised models for anomaly analysis, and proactive defense strategies. The goal is to improve detection accuracy, …

Enhancing The Acceptability Of Decision-Making System Using Xai Case: Crime Profiling System, Mohamed Saeed Al Shamsi

Theses

In the current world, we need to place more emphasis on how easily interpretable, accurate, and acceptable data analysis results are, given that essential operations in law enforcement, among other sectors, are backed up by the use of complex computing systems. Crime profiling systems that use crime data for profiling encounter major problems because they depend on algorithm-based methods. These methods can be ambiguous and inaccurate, leading to low public acceptability. The study investigates major problems with Complex Crime profiling systems (CPS) because their unexplained algorithms result in system performance issues and public scepticism. XAI provides a solution to handle …

باستخدام مجموعة بيانات متعددة من الطائرات بدون طيار Yolo البحث والإنقاذ البحري القائم على في ظروف الطقس الصعبة, Aysha Ali Alshebli

Theses

Object detection models, powered by deep learning and computer vision, are revolutionizing marine search and rescue (SAR). By analyzing aerial imagery and live drone footage, these systems automatically identify critical targets like survivors, life rafts, and debris across vast and treacherous ocean areas. This capability enhances operational efficiency by reducing human workload and accelerating response times, even in challenging conditions such as poor light, high seas, or cluttered backgrounds. The result is continuous monitoring, faster decision-making, and a significantly improved probability of successful rescue.

Departing from prior methodologies, YOLO introduced a paradigm shift through its single-shot architecture, which concurrently predicts …

Enhanced Privacy Preserving Healthcare Data Management With Federated Learning Using Homomorphic Encryption, Omar Abdulla Ali

Theses

Federated Learning (FL) is a decentralized approach of machine learning on multiple clients jointly training models without sharing their raw data, which drastically improves privacy and enhance protection against security breach. This is particularly critical in the healthcare sector, where hospitals and medical institutions are often unable to exchange patient records due to strict privacy regulations and data-management policies. However, there is still a risk of privacy breach when clients send their model updates to the central server, because if a model update is intercepted or analyzed by a malicious entity, it could be used to recover sensitive data using …

Enhanced Air Hockey Robot Performance Through Adaptive Control Algorithim Using Ai-Based Hierarechal Decicion Archeticture, Ayham Majed Salim

Theses

This thesis presents the development of an intelligent air hockey robot that combines precise mechanical design, computer vision, and adaptive control within an AI-based hierarchical decision architecture. The system integrates synchronized stepper motors, high-speed image processing, and a real-time decision framework to achieve competitive gameplay performance. The robot detects the puck using adaptive HSV color segmentation, supported by dynamic calibration that maintains accuracy under different lighting conditions. A two-stage trajectory prediction model, based on exponential decay velocity estimation, enables anticipation of puck motion and improves response time during fast gameplay.

At the decision level, a fuzzy-logic supervisor governs the robot’s …

It Hurts To Become, Ana Maria Joyce

Theses

Using the medium of oil painting, this thesis will investigate the ways that memories of my past inform and distort my perception of reality. Using domestic spaces as a framework in combination with my own body as the subject matter, I am creating compositions that redefine the meaning of home as a concept. Rather than a physical place of comfort, home is a cemetery for past selves that I revisit in my mind and grieve, no matter the time that has passed. By expressing this internal decay through physically scraping and sludging paint onto large scale surfaces, I aim to …

Isolation And Characterization Of Plant Growth Promoting Rhizobacteria From Soils In The Uae And Their Effect On Plant Salt Tolerance, Layla Zayed Almazrouei

Theses

Plants are constantly challenged by environmental stresses that restrict their growth and productivity. In the United Arab Emirates (UAE), soil salinity is a critical barrier to agriculture, particularly for tomato (Solanum lycopersicum), which is highly sensitive to moderate salinity levels (>2.5 dS m⁻¹). This study explored the potential of plant growth–promoting rhizobacteria (PGPR), especially actinobacteria, to enhance salt tolerance in tomato. The objective was to evaluate the effects of rhizosphere-competent (RC) and non-rhizosphere-competent (NRC) PGPR on plant physiology and yield in saline sandy soils. Actinobacterial strains were isolated from the tomato rhizosphere and screened to produce 1-aminocyclopropane-1-carboxylic …

Advancing Security Safeguards In Large Language Models Through Multi-Agent Systems, Mohammed Rashed Alnuaimi

Theses

This thesis focused on enhancing the safe use of Large Language Model (LLM) through the innovative use of a Multi-Agent System (MAS). As LLMs like ChatGPT became essential to our everyday interactions, the need to maintain the safe use of these systems increased. This research thoroughly assessed the current security measures in place for LLM, pointed out their limitations and developed new and more effective security strategies. The core of the proposed solution was a MAS designed to ensure that all data processed by LLM met guidelines including Privacy, Confidentiality, and Ethical standards before reaching the user. The system involved …

Exploring Family-Friendly Policies In The Uae, Mariam Sultan Al Kaabi

Theses

Background: Family-friendly policies (FFPs) have become a critical element in global debates surrounding work–family balance (WFB), organizational performance, and gender equity. In the United Arab Emirates (UAE), rapid legal reforms, including Federal Decree–Law No. 33 of 2021, the introduction of paid parental leave, expanded maternity protections, and increased recognition of flexible and remote work, reflect a national commitment to strengthening family well-being.Yet, despite these advancements, many working parents continue to experience tensions between regulatory intentions and workplace realities.

Purpose: This study examines the lived experiences of fourteen working parents in the UAE to understand how current FFPs and workplace arrangements …

Determination Of Variations In Orbital Parameters Of Sample Of Satellites Through Spacecraft Tracking, Asma Ali Alasmari

Theses

The continues increasing density of Resident Space Objects (RSOs) in Earth’s orbit highlights the crucial need for Space Situational Awareness (SSA). This thesis studies the orbital changes in two regions, active low Earth orbit (LEO) satellites and inactive geostationary Earth orbit (GEO) satellites. For LEO satellites we used publicly available data (two line element TLE from Space-Track) and ASTRIAGraph. We verified the orbital elements series and time ordered them, applied a Hampel (median+MAD) mask to semi-major axis, eccentricity vector and inclination to find outliers and exclude them from event detection. The events are then detected using time normalized slopes and …

Understanding Behavioral Patterns: A Case Study Of Emirati Ex-Offenders In United Arab Emirates, Salim Ali Al Naqbi

Theses

Research on desistance has helped criminologists to better understand how people change their criminal identity and exercise personal choice. Yet in the UAE, these ideas has not often been applied to prisoners serving one or multiple offenses, even though incarceration and reoffending remain important social concerns. Because of this, desistance theory has not been fully used to study how rehabilitation is managed in UAE prisons, which means that some useful lessons may be missed. This study begins to close that gap by looking at the personal stories of 15 Emirati participants that were formerly incarcerated by adapting a qualitative and …

Microstrip Antenna Design Based On Ai And Machine Learning, Waleed Mohamed Sha Moulavi

Theses

Microstrip patch antennas (MPAs) rely on precise impedance matching for efficient power transfer between the antenna and feed line. This is often achieved using a number of different techniques, one of which is the quarter-wavelength transformer (QWT). While commercial electromagnetic (EM) solvers offer robust optimization capabilities, they often operate as "black boxes" without providing physical insights into parameter interdependencies. Furthermore, this thesis focuses on the specific scenario where the antenna input impedance is purely real. To address the lack of explicit design relationships for these specific conditions, this thesis develops and comparatively evaluates artificial intelligence (AI) models for QWT width …

Examining Children’S Intuitive Understanding Of Mechanical Systems With A Gears Assembly Task, Nicole Taboada

Theses

Children’s causal reasoning about machines and their components is crucial for acquiring knowledge about science and math. Mechanistic understanding involves knowing how parts can be effectively connected to work together as a functional mechanical system. Little is known about how children’s understanding of mechanical systems develops across the lifespan. Legare and Lombrozo (2014) developed a gears assembly task to assess children’s understanding and learning of mechanics but did not track this skill across ages. The present study adapted the gears assembly task to measure mechanistic understanding in children between the ages of 4 to 11 years and adults. The goal …