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Integration Of Blockchain Technology In Industrial Applications, Sanjana Sakinala
Integration Of Blockchain Technology In Industrial Applications, Sanjana Sakinala
Theses
This research explores the integration of Hyperledger Fabric., a framework of blockchain in industrial applications, particularly focusing on supply chain management. By addressing the limitations of traditional blockchains - such as high transaction latency, scalability challenges, and privacy concerns - this research demonstrates how Hyperledger fabrics overcomes them. Through simulation, we show significant enhancements in transaction speed, data privacy and scalability, making the Fabric a viable solution for industrial systems.
Using Stimulus Equivalence Procedures To Increase Police Officers' Identification Of Behavioral Functions, Caitlin Sturges
Using Stimulus Equivalence Procedures To Increase Police Officers' Identification Of Behavioral Functions, Caitlin Sturges
Theses
Mentalistic constructs and theories have been spouted since the dawn of mankind to explain the many behaviors of humans. These philosophies, however, leave many unanswered questions in society’s understanding of why complex behaviors (e.g., the multifaceted behaviors between police officers and citizens) occur. Society has entered an era of policing reform. Moreover, society is in search of answers as to why violent and seemingly complex behaviors are on the rise between law enforcement officials and citizens. The purpose of this study was to teach police officers the four functions of behavior utilizing equivalence-based instruction (EBI). Three active-duty law enforcement officials …
Investigating The Effect Of Metal Site Of The Leaf And Branch Compost Cutinase Through Molecular Dynamics Simulations, Ryan James Molitor
Investigating The Effect Of Metal Site Of The Leaf And Branch Compost Cutinase Through Molecular Dynamics Simulations, Ryan James Molitor
Theses
The petroleum-based polyethylene terephthalate (PET) is a versatile and synthetic polymer that plays a pivotal role in the economy, including packaging, textiles, 3D printers, and even medical-related applications. There is a need for plastic waste management. Biological up-cycling of PET is a promising method for a clean and sustainable future. In 2012, a group of researchers, Tournier et. al., performed experiments and molecular dynamics simulations on the Leaf-branch Compost Cutinase, LCC (PDB Code: 4EB0), which outperformed the PET hydrolysis activity compared to three other PET hydrolyzing enzymes. The LCC and PET depolymerization rate of wildtype LCC was reported to be …
Rainfall Prediction Using Machine Learning Methods, Ibrahim Abdulla Obaidalla
Rainfall Prediction Using Machine Learning Methods, Ibrahim Abdulla Obaidalla
Theses
The capability to predict rainfall effectively is crucial for both economic planning and safety measures. This project examined the performance of three well-known forecasting models: Long Short-Term Memory (LSTM), Autoregressive Integrated Moving Average (ARIMA), and Seasonal Autoregressive Integrated Moving-Average (SARIMA) to determine their accuracy in predicting rainfall patterns. Extensive analysis of data was conducted to identify which model was the most reliable and accurate, considering varying climatic conditions and time scales. The LSTM model, a type of network designed for sequential data, was expected to excel due to its ability to understand long-term dependencies in data series. This is vital …
Smart Credit Card Fraud Detection Using Machine Learning, Aisha Bin Sulaiman, Rowdha Masood Falaknaz
Smart Credit Card Fraud Detection Using Machine Learning, Aisha Bin Sulaiman, Rowdha Masood Falaknaz
Theses
This thesis addresses the increasing issue of fraud resulting from technological advancements affecting both customers and fraudsters, while law enforcement agencies face challenges of inadequate case prioritization; data overload and slow investigative analysis. The central objective of this thesis revolves around strategies to counter these challenges, emphasizing the urgency of rapid response to major alert cases that can lead to widespread impacts. The authors' experience in financial fraud detection and credit card crime investigation within the police department has inspired this research, guiding the approach toward practical solutions for everyday operational challenges. The significance of this thesis lies in its …
Modeling Impact Of Simulated Myocardial Perfusion On Cardiac Ablation For Arrhythmia, Brendan Cappon
Modeling Impact Of Simulated Myocardial Perfusion On Cardiac Ablation For Arrhythmia, Brendan Cappon
Theses
Bioheat transfer is the study of heat transfer applied in anatomy and physiology, which is relevant to maintaining homeostatic conditions from metabolic activity, thermal exposures, and various treatments and diagnostic methods. Blood flow significantly impacts heat transfer throughout the body, facilitating the diffusion of heat. Models have been developed to quantify bioheat transfer and the effect of blood flow through tissue for many biological functions and medical procedures, one of which is radiofrequency ablation for cardiac arrhythmia. Significant improvements to models and assumptions are still required as success rates for this procedure remain low for various arrhythmia types. The research …
Application Programming Interface For Embedded Protocol Management System, Mathew David Barrera
Application Programming Interface For Embedded Protocol Management System, Mathew David Barrera
Theses
This paper defines an architecture and software structure which implements a polymorphic system to manage hardware devices. The architecture implements a system to manage integration of hardware devices by providing the constructs required to implement communication and data transport protocols with a method that manages system state independence of each hardware component integrated. The architecture components provide a system which maintains the independence of each device by defining abstractions between each component of the system providing the software constructs required to integrate hardware components which implement differing connections methods and communication protocols. The software architecture provides the means of Integration …
Development And Optimization Of Electric-Double-Layer Gated Transistors Based On Low-Dimensional Materials: Gate-All-Around Inas Nanowire Arrays And Graphene Channels, John Wyatt Morrell
Development And Optimization Of Electric-Double-Layer Gated Transistors Based On Low-Dimensional Materials: Gate-All-Around Inas Nanowire Arrays And Graphene Channels, John Wyatt Morrell
Theses
Electric-double-layer (EDL) gating is a promising alternative to conventional gating methods for field-effect transistors (FETs), with potential applications spanning current logic, future logic, and neuromorphic computing architectures. This technique employs mobile ions in an electrically insulating but ionically conductive medium to generate strong local electric fields at the gate-to-channel interface, achieving field magnitudes on the order of 1 V/nm. These intense local fields enable significant charge carrier accumulation in the semiconducting channel, positioning EDL gating as a strong candidate for device applications. In this study, we investigate the use of low-dimensional channel materials, including two-dimensional graphene and one-dimensional InAs nanowires, …
Artificial Neurovascular Networks To Simulate Energy Distribution To Spiking Neural Networks, William Bottom
Artificial Neurovascular Networks To Simulate Energy Distribution To Spiking Neural Networks, William Bottom
Theses
Biological neurons are known to be much more energy efficient than modern computers, with the human brain only consuming about 20 Watts. An Artificial Neural Network can take hours or days to train on high-performance and energy-consuming GPUs, so networks that can achieve similar performance at a fraction of the energy cost are very sought after. Spiking Neural Networks, which mimic biological neurons more closely than Artificial Neural Networks (ANNs), are a potential option for the energy problem in Neural Networks. By converting an ANN to an SNN and applying energy-saving methods/architectures, the equivalent SNN network can achieve similar performance …
Applying Machine Learning For Crime Trend Analysis, Dana Alsoori
Applying Machine Learning For Crime Trend Analysis, Dana Alsoori
Theses
The analysis of crime rates has always been a critical component in shaping law enforcement strategies and public policy. This study focuses on the U.S. crime rates from 1975 to 2015, as reported by the FBI’s Uniform Crime Reporting (UCR) Program, to explore patterns and trends over four decades. By analyzing this extensive dataset, the project aims to provide insights into the dynamics of criminal activity across different regions and crime categories. The goal is to uncover both visible and hidden trends that can inform better decision-making in crime prevention and resource allocation. With the rise of data-driven methods, this …
Leveraging Ai To Improve Service Quality For Better Passenger Satisfaction At Airport, Abdulrhman Alsaleh
Leveraging Ai To Improve Service Quality For Better Passenger Satisfaction At Airport, Abdulrhman Alsaleh
Theses
The aim of this research is to explore the impact of airport service quality on passenger satisfaction level in Dubai International Airport (DXB) and the study employed machine learning approach to establish the services quality dimensions relationship with passenger satisfaction. However, the initial objective is to analyze patterns and make future forecasts that DXB could use to enhance service delivery. The research focuses on key service quality dimensions: The study investigates the causal relationship between five constructs: reliability, service quality tangibility, assurance, responsiveness, and empathy using machine learning models such as regression and classification. The information data applies to the …
Analyzing The Effects Of Economic Factors On Residential Real Estate Market Dynamics Of Dubai: Using Machine Learning Methods, Zarrina Shokirova
Analyzing The Effects Of Economic Factors On Residential Real Estate Market Dynamics Of Dubai: Using Machine Learning Methods, Zarrina Shokirova
Theses
Dubai’s residential real estate market is known for its rapid growth and dynamic nature, making it an intriguing subject for analyzing the impact of various economic factors. This thesis examines how key economic elements such as GDP growth, inflation rates, and foreign investment influence property dynamics in Dubai. By synthesizing current research, this study aims to understand how these economic conditions affect real estate values, demand, and supply. Additionally, modern analytical methods, including decision trees, logistic regression, and random forest models, are employed to predict market trends and uncover significant patterns. This research contributes to both academic understanding and practical …
Robust And Efficient Active Inference For Perception, Action, And Learning, Zhizhuo Yang
Robust And Efficient Active Inference For Perception, Action, And Learning, Zhizhuo Yang
Theses
Active Inference (AIF) is an emerging framework rooted in neuroscience aimed at elucidating human perception, action, and cognitive processes. Recent advances in machine learning have facilitated the non-invasive study of human cognition through the lens of this framework. This dissertation expands upon this theoretical foundation to address practical challenges in robotic control and human cognitive behavior analysis. We initiate our exploration with a review of the eye-tracking studies that underpin the motivation for AIF research. This provides a background for understanding how AIF can model cognitive processes. First, we present a minimal AIF model within a discrete state space, framed …
The Tale Of Mari, Anya Vaughn
The Tale Of Mari, Anya Vaughn
Theses
The Tale of Mari is a mixed media animated documentary which follows the life of Mari Arakaki Gaskins. Shortly after moving to America in the 1970s, Mari began illustrating comic strips about a Japanese family, emulating the cartoons she saw in newspapers. She sent a letter to the creator of Garfield, Jim Davis, and included her comics. Davis sent her a response, and told her that her artwork was good. However, he believed that the strips were unlikely to be published, because comics about a young Japanese girl would not be relatable to American audiences. Mari grew up during a …
Design Of A Custom Embedded Replay Control Board For A Vintage Porsche, Christopher Heltz
Design Of A Custom Embedded Replay Control Board For A Vintage Porsche, Christopher Heltz
Theses
Many industries rely on decades old software and electronics to run machines that are essential for America’s industry. These companies operate on the sentiment of “if it’s broke, don’t fix it”. This works great until something breaks, then these same companies are faced with a tough decision. Either replace the old software and electronics with modern solutions or fix the original electronics. Both options have their challenges, the first costs much more in the short term and will require many man hours to design a new solution however the latter will require finding the original documentation or having trained individuals …
Tehran Is Ours, Hamideh Azimi
Tehran Is Ours, Hamideh Azimi
Theses
Tehran is Ours is a thesis film, mainly 2D animation, with some experimental and 3D parts. This film dramatizing the movement that is happening in Iran which is about women’s rights. 2D fluid animation represents the movement that never stops.
Utilizing Machine Learning For Categorizing Disaster-Related Tweets, Ahmad Alfalasi
Utilizing Machine Learning For Categorizing Disaster-Related Tweets, Ahmad Alfalasi
Theses
This study presents the development of a machine-learning model that recognizes tweets about disasters in real-time. The fast-paced development of social media, especially Twitter, has drastically changed the field of news transmission during crises. This change creates new challenges for the management of the volume, velocity, and veracity of data that are generated in such situations. The present tools do not have the capabilities of real-time processing of the huge volume of data; hence, new solutions are required. The model we are proposing addresses this problem by using advanced machine learning methods, such as natural language processing, to filter and …
Heat Transfer During Air-Water Two Phase Flow, Saumitra K. Deshpande
Heat Transfer During Air-Water Two Phase Flow, Saumitra K. Deshpande
Theses
The effects of air injection on the heat transfer coefficient for the liquid flow in two-phase in microchannels are studied. Different manifolds and microchannel configurations are used for studying the effects of air injection. The manifold has a uniform gap of 400μm between the heater chip and the cover. A manifold is designed and manufactured to provide different air water flow patterns for different combinations of liquid and air flow rates. The effect of these flow rates on the heat transfer coefficient are studied. The flow rate for air injected is kept very small with respect to the flow rate …
Enhancing Healthcare Services Through Machine Learning-Driven Anomaly Detection, Mohammad Ayoub Nather Hussain Natheruddin
Enhancing Healthcare Services Through Machine Learning-Driven Anomaly Detection, Mohammad Ayoub Nather Hussain Natheruddin
Theses
The healthcare industry’s expanding data presents opportunities for artificial intelligence (AI) and machine learning (ML). Despite advancements in medical technology, medical errors remain a significant issue. Anomaly detection, identifying data points that deviate from normal patterns, is crucial for addressing these errors and detecting healthcare fraud. This study uses the “Healthcare Providers Data for Anomaly Detection” dataset to identify fraudulent activities. Clustering and two-step clustering, two unsupervised anomaly detection methods, are employed to uncover anomalies without prior knowledge. These techniques are applied to detect unusual events, such as anomalous patient health states and time-series data deviations. The study focuses on …
Holistic Correlation Measure For Enhanced Encapsulation Of Trait Heterogeneity And Discovery Of Co-Expression, Zachary Valleroy
Holistic Correlation Measure For Enhanced Encapsulation Of Trait Heterogeneity And Discovery Of Co-Expression, Zachary Valleroy
Theses
Large-scale, high-dimensional data analyses can be computationally prohibitive due to combinatorial explosion of the search space for finding complex patterns; a viable alternative is network modeling for abstraction and quantifying intrinsic data associations. Prominent network analysis methods furnish frameworks for model synthesis and validation but rely on standard correlation measures impaired by semi-supervised biases, latent heterogeneity, and uneven discretization techniques. Here we investigate a holistic measure for encapsulating data heterogeneity for enhanced efficacy of revealing complex patterns through network analysis. Our unique correlation metric, K-medoids Utility for Duo Original Similarities (Kudos), exhaustively factors real-valued analyte data to compute …
Resolution Enhancement For High Numerical Aperture Extreme Ultraviolet Lithography Using Aperiodic Multilayer Masks, W Ethan Maguire
Resolution Enhancement For High Numerical Aperture Extreme Ultraviolet Lithography Using Aperiodic Multilayer Masks, W Ethan Maguire
Theses
As extreme ultraviolet lithography tools with higher image numerical apertures are introduced, the range of angles at the mask multilayer are increased. This represents a challenge for maintaining through-angle mask reflection using the current periodic mask multilayer structures. In addition to reflectance amplitude, the phase of reflected light, which plays an important role in imaging, is also strongly influenced by increasing angles. The propagation of light through each bilayer in the stack imparts a phase shift based on incidence angle. This accumulates over many layers, inducing phase effects which are unique to each illumination point. While adjustments to multilayer period …
Vitamin D Clinical Relevance In The Recovery From Traumatic Brain Injury Among The Military Population, Yuisa Mariceli Colón
Vitamin D Clinical Relevance In The Recovery From Traumatic Brain Injury Among The Military Population, Yuisa Mariceli Colón
Theses
Traumatic brain injury (TBI) still remains a difficult disorder to treat. TBI has been associated to chronic neuroinflammation and a high risk for neurodegenerative disorders. Since 2001 between ten to twenty percent of all deployed military members have suffered a combat-related TBI. Nearly twenty to thirty percent of those will experience chronic cognitive, behavioral and somatic symptoms after suffering a TBI. This review found compelling evidence to support that the pathology of TBI is closely associated with neuroprotective mechanisms of vitamin D.
Headspace, Katrina E. Kauffman
Headspace, Katrina E. Kauffman
Theses
Headspace is a contemplation of the dynamics and labor of thought. As someone with ADHD, dysgraphia, and dyslexia, my thought process is often circuitous yet cyclical. This thesis will explore the overlap between ritual and hyperfocus as a facet of artistic practice as well as their impact on physical and emotional equilibrium. By personifying the three proposed stages of memory by the Cognitive Load theory through the performance of repetitive tasks like making chewing gum, paper, and ink by hand, I both exemplify my neurodivergent brain structure and the reformatting my neural pathways undergo to conform to neurotypically inclined society. …
Hope Vs. Hate: Understanding User Interactions With Lgbtq+ News Content In Mainstream Us News Media Through The Lens Of Hope Speech, Jonathan Pofcher
Hope Vs. Hate: Understanding User Interactions With Lgbtq+ News Content In Mainstream Us News Media Through The Lens Of Hope Speech, Jonathan Pofcher
Theses
This thesis makes three contributions. First, via a substantial corpus of 1,419,047 comments posted on 3,161 YouTube news videos of major US cable news outlets, we analyze how users engage with LGBTQ+ news content. Our analyses focus both on positive and negative content. In particular, we construct a fine-grained hope speech classifier that detects positive hope speech, negative, neutral, and irrelevant content. Second, in consultation with a public health expert specializing on LGBTQ+ health, we conduct an annotation study with a balanced and diverse political representation and release a dataset of 3,750 instances with fine-grained labels and detailed annotator demographic …
Digital Microfluidic Oligonucleotide Synthesis: Automated Assembly Of Dna Products In Air And Oil With Integrated On-Chip Incubation, Sari Houchaimi
Digital Microfluidic Oligonucleotide Synthesis: Automated Assembly Of Dna Products In Air And Oil With Integrated On-Chip Incubation, Sari Houchaimi
Theses
Production of accurate DNA products is essential for many biological applications including drug development and delivery, synthetic biology, molecular engineering and epigenetics. It is difficult to build long DNA chains accurately and repeatably with conventional methods such as phosphoramidite method and polymerase chain assembly. DNA aqueous enzymatic assembly is a promising alternative. Multiple DNA fragments can be reliably and consistently assembled into one product using engineering enzymes in an aqueous medium. Digital Microfluidics uses asymmetric electric fields to simultaneously manipulate multiple reagent droplets on an array of electrodes. This platform is biocompatible and easily controllable. It has been used for …
Design And Implementation Of Attitude Control System For Gnssas 6u Cubesat, Anoud Nasser Alkatheeri
Design And Implementation Of Attitude Control System For Gnssas 6u Cubesat, Anoud Nasser Alkatheeri
Theses
This thesis presents the design and simulation of the Attitude Control System (ACS) for the GNSSaS 6U CubeSat, developed by the National Space Science and Technology Center (NSSTC) at UAE University. The CubeSat's mission is to enhance GNSS signal accuracy, which requires precise attitude control to achieve this objective. The ACS utilizes magnetorquers and reaction wheels for actuation. The primary objective of this thesis is to design an ACS that fulfills the mission’s performance requirements, including maintaining pointing accuracy in both fine and medium pointing modes. To achieve this, a comprehensive disturbance analysis was conducted, leading to the selection of …
Assessing The Spatiotemporal Variability Of Aerosol Optical Depth And Particle Sizes In The Uae Atmosphere Using Remotely Sensed Data, Bashayer Ali Alzahmi
Assessing The Spatiotemporal Variability Of Aerosol Optical Depth And Particle Sizes In The Uae Atmosphere Using Remotely Sensed Data, Bashayer Ali Alzahmi
Theses
This thesis investigates atmospheric aerosol concentrations, with a particular focus on the United Arab Emirates (UAE). The study maps the spatial and temporal variations in Aerosol Optical Depth (AOD) and characterizes aerosols using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) products. The primary objective of this research is to enhance the understanding of aerosol dynamics in the UAE by distinguishing between natural and anthropogenic aerosols through the Angström Exponent (AE) and assessing their impacts on local climate, air quality, and public health. The study employs Remote Sensing (RS) techniques to conduct detailed environmental assessments, analyzing AOD variability across daily, monthly, seasonal, …
Effect Of Virtual Reality Technology On Computer Science/Engineering Based Laboratories Education – A Case Study, Mariam A. Al Nuaimi
Effect Of Virtual Reality Technology On Computer Science/Engineering Based Laboratories Education – A Case Study, Mariam A. Al Nuaimi
Theses
Virtual reality (VR) is becoming increasingly popular and essential in education as institutions strive to incorporate technology in education. In Engineering and Computer Science, students face difficulties in comprehending many abstract complex concepts that are typically studied in Labs. This situation worsens with hardware failure and the lack of pedagogical tools. The main goal of this paper is to investigate the impact of VR environments on learning advanced and complex STEM concepts. We also explore the impact of different human-computer interaction (HCI) techniques including gamification on the learning experience of STEM students. To measure such impact, we developed a VR …
Utility Of New Remote Sensing Data In Evaluating The Hydrological Response To Land Use And Land Cover Changes, Chithrika Jayamini Alawathugoda
Utility Of New Remote Sensing Data In Evaluating The Hydrological Response To Land Use And Land Cover Changes, Chithrika Jayamini Alawathugoda
Theses
Land use and land-cover (LULC) changes have profound impacts on hydrological responses, influencing runoff dynamics and flood risks. This study focused on two contrasting watersheds undergoing rapid LULC transformations: the arid Wadi Ham watershed in the UAE and the tropical Imphal watershed in India. The research emphasized the critical role of accurate LULC data for hydrological modeling in climate-sensitive regions, where land-use changes are accelerating. Using high-resolution PlanetScope and Sentinel-2 satellite imagery, LULC maps were developed and classified using Maximum Likelihood (ML) and Random Forest (RF) algorithms. PlanetScope imagery paired with the RF classifier achieved the highest overall accuracy, with …
Effect Of Virtual Reality Technology On Computer Science/Engineering Based Laboratories Education – A Case Study, Saeed Salem Al Shebli
Effect Of Virtual Reality Technology On Computer Science/Engineering Based Laboratories Education – A Case Study, Saeed Salem Al Shebli
Theses
The rapid growth in mobile applications raises critical concerns about the security of apps and users' privacy, especially in permission control. Mobile apps access sensitive information of users, and the current cybersecurity landscape faces a huge challenge in ensuring the least required permissions are granted. This research focuses on designing an advanced permission recommendation system that couples the strengths of Natural Language Processing (NLP) and Machine Learning (ML) in solving most of the existing gaps in permission management, thus guiding which permissions are mostly needed by Android applications.
The research thus follows a multi-classification approach, integrating state-of-the-art ML techniques with …