Digital Commons Network^™

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. …

Perception Of Dynamic Lighting: Chromatic Adaptation And Augmented Reality, Abigayle Weymouth

Theses

Augmented reality (AR) is a rapidly developing technology with use cases ranging everywhere from medicine to entertainment. This research focuses on optical see-through (OST) AR, one of the common overarching types of available augmented reality devices. Color appearance in OST AR systems is affected by a mix of the viewing conditions and environment of the real world and the transparent virtual elements. Accurate control of the color of AR content in real-world use cases, which often includes changes in color over time in both parts of the environment, is important for many applications. This dissertation includes three studies of color …

استخدام تقنيات الذكاء الاصطناعي في إجراءات الاستدلال والتحقيق "دراسة مقارنة", حمد مصبح اليليلي

Theses

The Use of Artificial Intelligence Techniques in Reasoning and Investigation Procedures: Comparative Study

This research aims to analyze the role of artificial intelligence (AI) technologies in the stages of criminal investigation and inquiry through an applied analytical study. It focuses on the use of these technologies to support law enforcement and investigators with advanced scientific methods, particularly in analyzing digital evidence and accurately linking it to suspects. The study also explores the future development of these systems through their integration with AI technologies to enhance the efficiency of criminal investigation.

The United Arab Emirates has consistently been keen to develop …

On The Fractional Laplacian Type Operator, Maysam Abdulnaser Zain

Theses

In this thesis, we study analytical structures arising from Dunkl theory and their

applications to harmonic analysis and fractional Laplacian operators. Dunkl operators are differential–difference operators associated with finite reflection groups, providing a natural generalization of the classical Fourier analysis through the introduction of root systems and multiplicity functions. Within this framework, several classical transforms appear as special cases of the (k,a)-generalized Fourier transform. We study the generalized Fourier transform ��ₖ,ₐ, its kernel B_k,a (x,y), and the associated translation operator and convolution structures. Using these tools, we construct the corresponding heat …

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 …

Developing Sight-Reading Proficiency In Music Education: A Synthesis Of Instructional Strategies And Pedagogical Approaches, Charles Clements Ii

Theses

Sight-reading is a foundational skill in music education that enables students to perform unfamiliar musical material independently. Despite its importance, instruction is often inconsistent and driven by performance priorities rather than systematic skill development. This thesis synthesizes existing research on sight-reading pedagogy to identify effective instructional strategies and organize them into a cohesive framework for educators.

By connecting research to classroom application, this project provides a practical, research-informed model for sight-reading instruction. The findings suggest that effective instruction requires a structured and integrated approach that supports both cognitive processing and musical performance, ultimately promoting greater student independence and musical literacy.

The Impact Of Elevated Co2, Uv-B Irradiation, And Rising Temperature On Quinoa, Mohamed Yousif

Theses

Climate change is driving simultaneous increases in atmospheric CO₂, surface UV-B radiation, and temperature, yet most crop research has examined these stressors in isolation, leaving their combined effect on nutritional quality poorly understood. Quinoa (Chenopodium Quinoa Wild.), a stress-tolerant C3 pseudocereal, has been promoted as a climate-resilient forage and food crop for arid regions, but its performance under realistic multi-stress conditions remains uncertain. This study therefore asked whether quinoa can maintain biomass, yield, and mineral quality when exposed to elevated CO₂, enhanced UV-B, and rising temperature individually and in combination, and whether their interaction is additive or non-additive.

To …

Malicious Quic Traffic Detection Using Malicious Quic Traffic Detection Using Malicious Quic Traffic Detection Using Malicious Quic Traffic Detection Using, Choudhary Muhammad Zia

Theses

The enhanced QUIC protocol's encryption capabilities not only encrypt the traffic payload but also encrypt the packet headers that network security tools rely on for packet inspection. This enhanced encryption capability introduces challenges for network operators in monitoring and analyzing network traffic by creating blind spots in firewalls, intrusion detection systems, and deep packet inspection devices. Earlier research has demonstrated that training machine learning classifiers on individual QUIC packets across different classifiers has failed to detect any malicious traffic due to encrypted packet headers.

This thesis demonstrates that shifting to network flow analysis resolves this problem. Rather than analyzing individual …

Advanced Mathematical Modeling And Data-Driven Techniques For The Diagnosis Of Diabetes Using Continuous Glucose Monitoring (Cgm) Data, Farah Morsi

Theses

Diabetes mellitus is a major and growing health challenge, particularly in the Middle East and North Africa (MENA) region. Continuous Glucose Monitoring (CGM) provides high-resolution time-series data that capture detailed glucose fluctuations over time. However, conventional CGM summary measures, such as mean glucose, standard deviation, and time-in-range, may not fully describe the nonlinear temporal structure of glucose dynamics.

This thesis investigates nonlinear dynamical approaches for analyzing CGM time series, with a focus on recurrence-based analysis and ordinal-network analysis. Recurrence-based methods, including recurrence quantification analysis (RQA), are used to characterize geometric and temporal patterns in reconstructed phase space, while ordinal networks …

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 …

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, …

Control And Entrainment Of Oscillatory Dynamics In An Oncolytic Virus–Tumor Model Under Periodic Therapy Forcing, Aya Salaheddin Shujrawi

Theses

This thesis investigates the dynamics of a tumour–virus interaction model under sinusoidal periodic viral injection, using the three-compartment ordinary differential equation framework of Baabdulla and Hillen (2024). The aim is to characterise how the frequency and amplitude of periodic injection interact with the system's intrinsic oscillatory dynamics, and to identify conditions for stable frequency entrainment. Equilibrium and Hopf bifurcation analysis of the autonomous system yields a supercritical bifurcation at θ_H^auto ≈ 338.45 with intrinsic frequency Ω₀^auto ≈ 0.7552. Introducing a constant baseline injection u₀ = 0.05 raises the threshold to θ_H^forced ≈ 364.85 and shifts …

Effects Of Led Light Spectra And 1-Mcp On Postharvest Quality And Bioactive Compounds Of Cucumber (Cucumis Sativus L.) During Cold Storage, Imad Eldin Abbas Yousif

Theses

Extending postharvest quality and maintaining the nutritional value of cucumber fruit requires specific storage conditions to postpone senescence and enhance marketability. The postharvest lighting environment is a main factor that influences quality preservation for harvested biomass. The objective of this study was to investigate the effects of different light emitting diodes (LED) spectra (green, red, blue, and white LED) alone or in combination with 1-Methylcyclopropene (1-MCP) on postharvest quality and bioactive compounds of cucumber fruit during cold storage for 16 days at 5°C, the control fruit were left in the dark. For combined treatment, the fruits were exposed to 1-MCP …

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 …

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 …

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 …

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 …

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 …

Edge Co-Occurrence Regularization For Node Classification, Kadir Altunel

Theses

We propose a simple yet effective regularization technique for node classification on graphs that leverages edge-based label co-occurrence patterns. We first train an MLP on node features to produce class probability distributions, then compute a fixed penalty matrix from edge-based co-occurrence statistics of these predictions. This penalty matrix, which captures unlikely class combinations on connected nodes, is then used to regularize GNN training without further updates. We evaluate this approach across multiple homophilic datasets (Cora, CiteSeer, PubMed, ogbn-arxiv) and heterophilic benchmarks (Chameleon, Squirrel, Actor, Roman-Empire) using three GNN architectures: GCN, GraphSAGE, and H2GCN. Results show consistent improvements on homophilic graphs, …

Sound Detection Of Memory Leaks In Llvm Ir Programs Using Accumulation Analysis, Robert Blacha

Theses

Resource leaks occur when a limited resource such as memory is allocated by a program and needlessly held past the point of use. Leaks can lead to a degradation of services which can be specifically triggered with malicious behavior, for example abusing a memory leak in a program to cause a server to slow down and crash for a denial-of-service attack.

Prior work has demonstrated that accumulation analysis provides a sound detection of resource leaks with a working implementation for programs written in Java. While useful, current implementations are limited to programs written in Java, which has a garbage collector, …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …