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Articles 1141 - 1170 of 21692
Full-Text Articles in Entire DC Network
The Role Of Ai In Digital Propaganda And Its Influence On Public Political Perception. A Case Study Of The Uae Citizen, Maitha Salem Mohamed Alshamsi
The Role Of Ai In Digital Propaganda And Its Influence On Public Political Perception. A Case Study Of The Uae Citizen, Maitha Salem Mohamed Alshamsi
Theses
The study investigates the role of artificial intelligence (AI) in digital propaganda and its influence on public political perception, using the United Arab Emirates as a case study. It aims to understand how AI-generated content shapes political opinions by analyzing the relationships between digital propaganda exposure, AI content interaction, social media engagement and media literacy. In addition, the study uses the Framing Theory (1974) by Erving Goffman. It posits that individuals interpret information and events through cognitive frameworks or "frames" that organize and influence their understanding. It implies that AI amplifies specific frames by customizing content and targeting audiences, which …
User Perceptions Of Ai Services In Abu Dhabi Government: An Empirical Study Of Satisfaction And Acceptance Factors On The Tamm Platform, Muneera Ali Zaher Alsulaimani
User Perceptions Of Ai Services In Abu Dhabi Government: An Empirical Study Of Satisfaction And Acceptance Factors On The Tamm Platform, Muneera Ali Zaher Alsulaimani
Theses
Artificial Intelligence (AI) is transforming how governments deliver services by enabling automation, personalization, and data-driven decisionmaking. In the United Arab Emirates, particularly in Abu Dhabi Emirate, the TAMM platform exemplifies this transformation, integrating AI to streamline citizen-government interaction. Understanding the factors that influence the user’s satisfaction of Powered AI services in the public sector is crucial for effective policy implementation and user engagement. This study employs a sequential explanatory mixed-methods approach, grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), extended with User Satisfaction as a fifth construct. Quantitative data were collected from 137 TAMM platform users …
The Role And The Limitation Of Ai Implementations In Pcb Defect Detection, Hamad Saeed Mohammed Alyammahi
The Role And The Limitation Of Ai Implementations In Pcb Defect Detection, Hamad Saeed Mohammed Alyammahi
Theses
This research explores the transformative impact of Artificial Intelligence (AI) on quality control in Printed Circuit Board (PCB) fabrication, explicitly focusing on enhancing defect detection processes. As PCB designs become increasingly complex and dense, traditional inspection methods, such as manual inspection and Automated Optical Inspection (AOI), need to be revised to meet the precision and efficiency demands of modern electronics manufacturing. Manual inspection is often slow and labor-intensive, while AOI needs help with accuracy in detecting subtle defects in intricate designs, leading to potential errors in quality assurance. This study investigates AI-driven techniques to overcome these challenges, leveraging deep learning …
A Comparative Analysis Of Machine Learning Models For Predictive Process Monitoring Using Objectcentric Event Logs, Buthaina Hasan Aidaros Alhebshi
A Comparative Analysis Of Machine Learning Models For Predictive Process Monitoring Using Objectcentric Event Logs, Buthaina Hasan Aidaros Alhebshi
Theses
The increasing complexity of business processes drives the need for advanced predictive monitoring solutions capable of handling multi-entity interactions. Traditional case-centric event logs fall short of capturing these complexities, leading to the emergence of Object-Centric Event Logs (OCEL). Despite the growing interest in OCELs, their structural complexity and impact on predictive performance remain unexplored. This thesis investigates how process complexity influences the performance of machine learning models in predictive process monitoring using OCEL. A framework combining Graph Neural Networks and graph embedding-based models is applied across three predictive tasks: next activity, next timestamp, and remaining time prediction. The evaluation covers …
An Inclusive Learning Metaverse: A Virtual Reality Approach To Supporting Dyslexic Children, Reem Salem Mohammed Salem
An Inclusive Learning Metaverse: A Virtual Reality Approach To Supporting Dyslexic Children, Reem Salem Mohammed Salem
Theses
Dyslexia is one of the most common learning difficulties worldwide, often requiring tailored interventions targeting phonological awareness, reading comprehension, and cognitive support. This study explores the design and evaluation of a metaverse-based virtual reality (VR) application to support dyslexic children in the UAE. Using a usercentered, explanatory sequential mixed-methods approach, the research involved three phases: a stakeholder survey with therapists, educators, and parents (N = 151), development of a multi-featured VR prototype, and evaluation by six dyslexia experts. The survey identified key priorities such as progress tracking, adaptive learning, accessibility, working memory, and attention, along with concerns about VR unfamiliarity, …
Sustainable Hydrogels: Advancing Soil And Water Retention In The Uae, Mariam Abdulla Alhosani
Sustainable Hydrogels: Advancing Soil And Water Retention In The Uae, Mariam Abdulla Alhosani
Theses
Long-term climatic issues like soil erosion and water scarcity affect arid regions, making sustainable agricultural systems more challenging to put into practice. By creating different hydrogels from local agricultural biomass (cellulose extracted from date palm tree waste).This will assist in overcoming the limitations of synthetic water- retentive materials. Several hydrogel samples were created using physical and chemical crosslinking techniques, forming several hydrogel variants samples that were labelled as (T1 to T4). TGA, SEM, FTIR and swelling tests were used. TGA results revealed improved thermal stability in T2 (physically crosslinked), and T3 (dual cross-linking citric acid with gelatin), with degradation temperatures …
Burnout Among Social Care Providers In The Uae: The Role Of Coping Strategies And Institutional Support, Faiza Saleh Alothali
Burnout Among Social Care Providers In The Uae: The Role Of Coping Strategies And Institutional Support, Faiza Saleh Alothali
Theses
This study focuses on the self-reported levels of burnout, the coping strategies employed, and the perceived institutional support of a sample of social care workers in the UAE. The research also explores how coping strategies and institutional support influence burnout levels and the role of demographic factors such as gender, age, and years of experience. A total of 204 social care providers participated in the study, which used a survey to gather data on burnout, coping strategies, and institutional support. The Maslach Burnout Inventory (MBI) was used to measure burnout, the Brief COPE Inventory was used to assess coping strategies, …
Remember The Ladies: A Consideration Of The Subtle Contributions Of Women To The Patriot Cause, Davon Howard
Remember The Ladies: A Consideration Of The Subtle Contributions Of Women To The Patriot Cause, Davon Howard
Theses
Before the American Revolution, colonial women lived in a hierarchical society. When the fighting began, the constructs of that hierarchy were challenged and, in some cases, broken down, with only few remaining while the fight for freedom was in full effect. The battle for independence was not fought only on the battlefield. Women were left at home to survive in a harsh wartime world and desperately doing what they could to make sure there was a home to come back to. Even with such tremendous responsibility on their shoulders, and in addition to their struggles to secure the home front, …
Evaluation Of Strain-Rate Sensitivity Of 3k70pw/Inf114 Woven Fiber-Reinforced Composite Material, Elias James Gerstein
Evaluation Of Strain-Rate Sensitivity Of 3k70pw/Inf114 Woven Fiber-Reinforced Composite Material, Elias James Gerstein
Theses
Fiber reinforced composites have seen continued use in aerospace and automotive industries due to their inherent high strength-to-weight ratios, which makes them ideal choices for vehicles where fuel economy is an important design factor. However, it is necessary for structures in these industries to preserve the life and safety of passengers in the event of a crash; thus, crashworthiness of these vehicles must be tested. Many finite element material models for simulating composite materials exist, but few take strain rate effects into account, which is important for accurate modeling of dynamic crash scenarios. LS DYNA MAT_213 is a material model …
Subconscious Warnings As A Safety Mechanism Against Phishing Attacks, Henry Schulz
Subconscious Warnings As A Safety Mechanism Against Phishing Attacks, Henry Schulz
Theses
Phishing attacks are very common and considerably successful in stealing people’s information, but unfortunately normal security procedures fail to warn the user of their possible dangers. By considering how subliminal messages are very effective in informing people without actively disrupting their attention, a prototype of a browser extension was made by implementing subconscious messages and the elements of an effective warning, in an attempt to subconsciously warn users of possible phishing attempts, with minimal impact on browser performance.
Attention Deficit Hyperactivity Disorder And Metacognitive Awareness Of Learning, Kara R. Muscha
Attention Deficit Hyperactivity Disorder And Metacognitive Awareness Of Learning, Kara R. Muscha
Theses
The present study examined knowledge updating abilities in individuals with and without ADHD when forced to metacognitively evaluate the effectiveness of different study strategies. Participants with and without ADHD were randomly assigned to either a spontaneous or a forced knowledge updating condition, with those in the latter condition being asked to keep track of encoding strategy-recall outcome results, but no additional instructions for those in the spontaneous condition. I expected that healthy control participants would show greater knowledge updating abilities than those with ADHD, the participants in the forced knowledge updating condition would show greater knowledge updating abilities than participants …
Neural Acceleration Of Graph Partitioning, Vishvam Patel
Neural Acceleration Of Graph Partitioning, Vishvam Patel
Theses
Graph Partitioning is a critical problem in numerous scientific and engineering domains including social network analysis, VLSI design, and many more. Spectral methods are known to produce quality partitions while minimizing edge cuts for a wide range of problems. However, the computational cost associated with the calculation of the Fiedler vector, an eigenvector associated with the second smallest eigenvalue of the graph Laplacian, remains a significant bottleneck. In this paper, we present an neural acceleration approach to spectral bisection partitioning by replacing the traditional eigenvalue calculation with a simple artificial neural network model to approximate the fiedler vector. We demonstrate …
Evaluating Bias In Facial Recognition Datasets : A Study On Representation And Classification Fairness, Milyonta Williams
Evaluating Bias In Facial Recognition Datasets : A Study On Representation And Classification Fairness, Milyonta Williams
Theses
Facial recognition technology is widely used in security and identity verification but exhibits biases that disproportionately impact certain demographic groups. This thesis examines racial and skin tone biases in commonly used facial recognition datasets, assessing their influence on classification models. Using manual classification via the Fitzpatrick scale and numerical skin tone representations from LAB color values, we identified significant dataset imbalances, with lighter skin tones (Fitzpatrick Types 1 and 2) overrepresented and darker tones (Types 4-6) underrepresented. Model evaluation using Random Forest, SVM, and XGBoost showed an overall accuracy of 72\%, but classification for Asian individuals was notably weaker (0.45 …
Modifying The L-Tryptophan Affinity Of The Ribosomal Arrest Peptide Tnac, Alexis Orlando Delgado Castillo
Modifying The L-Tryptophan Affinity Of The Ribosomal Arrest Peptide Tnac, Alexis Orlando Delgado Castillo
Theses
Since creating biosensors from zero has proven a more challenging enterprise than expected, resorting into naturally occurring regulatory systems already characterized represents a more accurate, rapid, and attractive option. Various previous strategies have sought to exploit and modify regulatory elements that sense for different molecules, including monosaccharides (Tang et al., 2008), secondary metabolites (Flachbart et al., 2021), and other amino acids (Della Corte et al., 2020). This study aims to leverage current scientific knowledge and advances concerning the structure and function of the ribosomal arrest peptide TnaC. With this research I integrated the TnaC ribosome-arresting peptide into a new biosensor …
Aviation Weather Forecasting Utilizing An Artificial Neural Network, Joshua Mote
Aviation Weather Forecasting Utilizing An Artificial Neural Network, Joshua Mote
Theses
Weather forecasting is critical to minimize risk and maximize efficiency for flying operations and is challenging due to the uncertainty involved in atmospheric changes. Operational area weather is becoming more critical with the growing reliance on air domain for transportation. This study investigates whether the forecasting accuracy using a Hybrid Long-Short Term Memory (LSTM) Artificial Neural Network (ANN) outperforms the San Antonio International Airport (KSAT) Terminal Aerodrome Forecast (TAF) by integrating diverse data sources – regional Meteorological Aerodrome Report (METAR), TAF, Avian Advisory System (AHAS) Data and geomagnetic activity K Index Data. When tested on one year of historical data, …
Improving Satellite Needs Working Group Assessment Process Through Automation And Process Consolidation, Raj Dangol
Improving Satellite Needs Working Group Assessment Process Through Automation And Process Consolidation, Raj Dangol
Theses
The increasing complexity of modern software ecosystems, presents significant challenges to system resilience, maintainability and automation. This work presents a proof-of-concept implementation of an automation system to address these challenges for a large scale fragmented software systems. Succinctly we address these challenges in the context of Satellite Needs Working Group (SNWG), which is responsible for collecting and communicating federal agencies' Earth observation needs to National Aeronautics and Space Administration (NASA). Multiple automation scripts and applications exist to support the SNWG's assessment cycle, encompassing the areas of data validation, visualization, report generation, and user management. However, the dispersion of these tools …
Sliding Mode Control Design Using Generalized Relative Degree Approach : Aerospace Application, Robert J. Jesionowski
Sliding Mode Control Design Using Generalized Relative Degree Approach : Aerospace Application, Robert J. Jesionowski
Theses
The relative degree (RD) approach is a powerful tool, for obtaining a system’s input-output dynamics of an output tracking controller design with minimum phase dynamics. Designs using RD alone can fail due to insufficient control authority in minimum phase systems, and instability of internal/zero dynamics attributed to non-minimum phase systems. Generalized RD (GRD) in minimum phase systems can identify parasitic control terms (PCTs). An Alternate GRD (AGRD) is investigated, to determine the impact of discarding these PCTs. A novel definition for Practical GRD (PGRD) is proposed and used in concert with Sliding Mode Control (SMC) compensating system perturbations in minimum …
Surveying Subterranean Biodiversity Of The Tongass National Forest Using Traditional Survey Approaches And Environmental Dna (Edna) Metabarcoding, Jared P. Higgs
Theses
The Tongass National Forest (TNF) is a large temperate rainforest in southeastern Alaska, much of which is underlain by karst. Timber harvest, among other threats, can have detrimental effects on karst habitats; however, the subterranean fauna of this region is understudied and lacks a baseline for monitoring. I spent three field seasons conducting biological assessments of caves in the TNF using two approaches: traditional specimen-based sampling and eDNA metabarcoding. To improve the reference sequence database, I generated 213 novel sequences from invertebrate specimens collected from 35 caves. I also collected 125 water samples from 39 sites for environmental DNA (eDNA) …
Performance Comparison Of Variable Center Body Configurations For A 25 Mm Rotating Detonation Rocket Engine, Kaito Jonathan Durkee
Performance Comparison Of Variable Center Body Configurations For A 25 Mm Rotating Detonation Rocket Engine, Kaito Jonathan Durkee
Theses
Rotating detonation rocket engines (RDREs) are propulsion devices that harness circumferentially traveling detonation waves, providing theoretical benefits compared to classical, deflagration-based combustors. Because of the integration challenges posed by typical annular (Center Body, CB) RDREs, a cylindrical (Center Bodiless, CBL) chamber geometry is attractive. To understand the corresponding trade-offs for small-scale devices, the performance and operational characteristics for a 25 mm with removable 15 mm center body are compared using gaseous methane and hydrogen with oxygen, operating at varying equivalence ratios and at a total mass flow rate of 0.076 kg/s and varying mass flow rates at an equivalence ratio …
Experimental Evaluation Of Recent Theoretical Real-Time Signal Higher-Order Sliding Mode Differentiators On Noisy Sensors, Jessica Hamer
Experimental Evaluation Of Recent Theoretical Real-Time Signal Higher-Order Sliding Mode Differentiators On Noisy Sensors, Jessica Hamer
Theses
This thesis explores the performance of higher-order sliding mode differentiators applied to sensor signals under varying sampling rates and switching functions. Two differentiator designs are evaluated: a hybrid algorithm that combines a super-twisting algorithm with a linear observer, and a fixed-time higher-order sliding mode differentiator. Each was tested on a physical sensor testbed using position data from a servomotor and electronic compass. The differentiators were implemented in a ROS2 environment, and their estimates were evaluated by obtaining the minimum and maximum position and velocity values, as well as analyzing graphs to capture the nature of the algorithms' noise reduction. The …
170 Years Of San Francisco Sea Level Pressure, Brendan Heaven
170 Years Of San Francisco Sea Level Pressure, Brendan Heaven
Theses
This data-recovery project and subsequent data analyses address the construction of a continuous, long instrumental record of sea level pressure for San Francisco, California, USA and examines what the time series may reveal about atmospheric patterns through time. Atmospheric pressure is a physical component which is associated with both daily and seasonal weather phenomena and is one of the most robust of the meteorological variables. Observational data of surface pressure (SFP) and later sea level pressure (SLP) were accessed from digital archives, with a large part of these being manually keyed from original observations on paper. San Francisco, being near …
Analyzing Code Generation By Ai Models: An Anova-Based Study Of Quality, Consistency, And Composite Ranking, Rajavi Gontiya
Analyzing Code Generation By Ai Models: An Anova-Based Study Of Quality, Consistency, And Composite Ranking, Rajavi Gontiya
Theses
As generative Artificial Intelligence(AI) tools become increasingly common in software development, there is a growing need to understand how well these tools perform beyond just producing code that runs. This thesis examines the performance of four popular generative AI models, ChatGPT (GPT-4 mini), GitHub Copilot, Code LLaMA 3.3, and DeepSeek Web, in generating code that is not only functionally correct but also efficient and maintainable. To do this, we tested each model on six real-world-style coding problems sourced from LeetCode, covering a range of algorithmic challenges like dynamic programming, graph traversal, and array manipulation. Using a consistent prompting strategy, we …
Utilization Of Artificial Intelligence To Predict Surface Energy Budget, Joseph Bonucchi
Utilization Of Artificial Intelligence To Predict Surface Energy Budget, Joseph Bonucchi
Theses
Estimating heat and moisture exchange between the land and atmosphere has several important practical applications, including water resource management, air pollution forecasting, and atmospheric propagation modeling. Turnkey systems for measuring the surface energy budget typically cost between $5,000 and over $50,000. This study explores the use of artificial intelligence (AI) to predict sensible heat flux (SHF) and latent heat flux (LHF) using inexpensive surface meteorology data and downwelling solar radiation measurements as inputs. Observations from Amer- iFlux sites were used to train several AI models—Convolutional Neural Networks (CNNs), One Dimensional Transformers (1D Transformers), Artificial Neural Net- works (ANNs), and Long …
Particle Image Velocimetry (Piv) Measurements Of Flow Characteristics Of An Unsteady Oblique Shock Wave Train, Andrew Girgis
Particle Image Velocimetry (Piv) Measurements Of Flow Characteristics Of An Unsteady Oblique Shock Wave Train, Andrew Girgis
Theses
Presented is the development of a Particle Image Velocimetry (PIV) apparatus to quantify the velocity field produced by an oblique shock wave and its reflections in a supersonic/transonic wind tunnel. A flow seeding system is developed using mesquite wood smoke generated in a metal vessel heated with a Vevor TDGC-2KVA variable autotransformer. A pressurized K-bottle drives the smoke through a cooled copper coil and moisture trap to remove contaminants before injection. A dual-pulsed class IV Nd:YAG Big Sky laser with Thorlabs optomechanical components, including two cylindrical lenses, is used to create a pulsed light sheet to illuminate tracer particles. Image …
Safe Reinforcement Learning For Trajectory Tracking Of Mobile Robots With Minimal Intermittent Observations, Mahtab Noor Shaan
Safe Reinforcement Learning For Trajectory Tracking Of Mobile Robots With Minimal Intermittent Observations, Mahtab Noor Shaan
Theses
Autonomous wheeled mobile robots (WMRs) are widely used for safe operation in safety-critical systems, such as robotic visual inspection of confined spaces in energy infrastructure, warehouse automation, delivery robots, and autonomous vehicles. The operating environments for these safety-critical systems are often uncertain. Therefore, in such environments, it is essential for WMRs to reliably follow predetermined paths while effectively maintaining lane position and avoiding collisions. However, frequent observations required for control execution to account for environmental uncertainty result in increased sensing, computation, and energy costs. This necessity drives the research for safe and resource-aware trajectory-tracking control methods. Although several state-of-the-art trajectory …
Information Capacity For Time-Varying Adversarial Networks, Raphael Thorp
Information Capacity For Time-Varying Adversarial Networks, Raphael Thorp
Theses
This thesis investigates the capacity of time-varying adversarial networks where intelligent adversaries can corrupt transmissions on restricted subsets of network edges that change availability over time. Building upon the work of Beemer et al. on adversarial network coding with restricted adversaries, we analyze networks whose topology evolves temporally, motivated by applications in space networking and delay-tolerant systems. We introduce different adversarial modes that capture different temporal aspects of corruption behavior and establish their hierarchical relationship with respect to network capacity. The analysis employs time-expanded graph representations and develops recursive counting methods for computing expected network capacity under random time assignments, …
Unbound Subgenres : Overlapping Age Categories In Contemporary Romance And Their Implications, London Stevenson
Unbound Subgenres : Overlapping Age Categories In Contemporary Romance And Their Implications, London Stevenson
Theses
This thesis aims to highlight the importance of genre labelling in contemporary romance fiction and the larger implications that come from the misuse of labels. Considerations of the genre based on narrative elements (Regis, 2003; Michelson, 2022), age categorization (Cart, 2011; Tribunella, 2007), and emerging market conditions (McAlister, 2018; Stewart, 2013) have generated considerable discussion over the last twenty-five years. While each of these scholars draws important conclusions about romance and its subgenres, none of them consider the significance of reader opinion, which is now enhanced due to literary digital spaces. In this paper, I examine nine romance novels for …
Sidelobe Reductions In Linear And Circular Phased Array Antennas Based On Hybrid Synthesis Techniques, Eli C. Brothers
Sidelobe Reductions In Linear And Circular Phased Array Antennas Based On Hybrid Synthesis Techniques, Eli C. Brothers
Theses
The concentration of electromagnetic waves within an angular space is made possible by radiating devices, typically realized in the form of an antenna. Hence, energy emitted or received outside of the intended field of view is manifested in the sidelobes and minor lobes of a radiation pattern, of which sidelobes are commonly responsible for unwanted interference and signal spread. To mitigate these issues, this study seeks to investigate the efficacy of a hybrid synthesis technique based on electrically displaced phase center antenna (E-DPCA) and partially-tapered methods in reducing the sidelobes of linear and planar arrays by optimizing the excitations of …
Evaluating Sequential Inference Via Poisson And Change-Point Frameworks, Samuel Johnson
Evaluating Sequential Inference Via Poisson And Change-Point Frameworks, Samuel Johnson
Theses
Sequential testing reduces sample size and costs compared to fixed-sample approaches by allowing decision making during data collection. This thesis investigates sequential methods for Poisson processes and change-point detection. Wald’s sequential probability ratio test (SPRT) and efficiency measures are developed. Practical applications of the SPRT are studied, from detecting noisy sources to classification algorithms. The MaxSPRT is derived, and its critical value algorithm is optimized. The MaxSPRT, a Bayesian SPRT, Wilk’s generalized likelihood ratio test, and the Cash statistic are examined. Various change-point algorithms are surveyed, including Shewhart control charts, cumulative sum methods, homogeneity tests, and multiple change-point approaches. These …
Blockchain Poisoning Attacks In Federated Learning, Mohammad Raihan Uddin
Blockchain Poisoning Attacks In Federated Learning, Mohammad Raihan Uddin
Theses
Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, thereby preserving privacy. However, conventional FL depends on a centralized aggregator, exposing it to poisoning and backdoor attacks that threaten model integrity. This thesis introduces B-ZkFed, a blockchain-based and zero-knowledge proof (ZKP)-enhanced FL framework designed to ensure verifiable trust, transparency, and robustness. The blockchain layer decentralizes aggregation through smart contracts, while the ZKP module allows clients to cryptographically prove the correctness of updates without revealing private data. A multi-layer adaptive defense combining gradient-norm filtering, model-similarity analysis, and robust aggregation mitigates poisoning threats under both IID and …