Digital Commons Network^™

Design And Test Of Wpum Topography Monitor For Iqos, Rawah Azeez

Theses

With the emergence of diverse tobacco product forms, such as electronic cigarettes and heat-not-burn, the global user base has surged to an estimated 1.3 billion. In the United States, 28.3 million adults and 3.08 million middle and high school adolescents engage in tobacco product use. However, our understanding of the usage behaviors of these various products is lacking. Puff topography, which measures the inhalation patterns of tobacco products, provides a wealth of information, including puff flow rate, duration, volume, and more. This information is crucial in understanding the health effects of tobacco products and the influence of usage behavior on …

Supercook: Design Interactive Culinary Experiences With Ai Technology, Yize Peng

Theses

The project 'SuperCook' is a groundbreaking design project that explores the integration of AI with culinary apps. It aims to revolutionize the kitchen experience by connecting users to new and accessible culinary adventures through personalized recipe recommendations, real-time cooking guidance, and interactive meal planning. By leveraging AI technology, 'SuperCook' not only enhances user convenience and efficiency but also fosters a deeper engagement with cooking and promotes healthier eating habits. This thesis delves into the design process, user testing, and iterative improvements that culminated in a user-centered, intuitive, and visually appealing UI/UX solution for modern cooking enthusiasts. In designing 'SuperCook,' attention …

Using Data Analytics To Predict Government Employee Turnover, Aisha Alshamsi

Theses

Employee turnover is a significant problem in many organizations, resulting in increased costs, decreased productivity, and decreased morale. The aim of this research is to predict employee turnover using data analysis algorithms and develop a predictive model that can be used to identify employees who are at risk of leaving the organization. This study preprocesses data on employee turnover rates, employee demographics, employee satisfaction, and other relevant factors, and uses data analysis machine learning algorithms such as Logistic regression, Decision tree, and XGBoost to analyze the data and develop a predictive model. The result of the study helps impact on …

Exploring The Potential Pathogenicity Of A Type 2 Diabetes Mellitus Associated Insr Missense Variant Of Uncertain Significance Through Daf-2 In The Caenorhabditis Elegans Model, Brittany White

Theses

Type 2 diabetes mellitus (T2DM) is hallmarked by insulin resistance, with the INSR gene identified as a key player in this condition in humans. This gene is known to harbor genetic variants with a wide range of clinical significance from pathogenic to variants of uncertain significance (VUS) to benign. This project investigates a VUS associated with T2DM identified through ClinVar. A gene mutational analysis, predictive amino acid substitution analysis, and protein modeling predict INSR c.1628C>T (p. Thr543Met) to be likely pathogenic or damaging. PolyPhen-2 predicts this variant to be probably damaging (HumDiv score of 1.000).

Evolutionary conservation of the …

The Ghanaian War Against Malaria: A Geospatial Approach To Malaria And Healthcare Access In Ghana, Emmanuel Aklie

Theses

This geospatial research project aims to analyze the complex factors influencing malaria incidence in Ghana, including healthcare access, cultural beliefs, and preventive measures. Using GIS mapping and spatial analysis, the study examines malaria distribution and healthcare facility locations to identify hotspots and access inequalities. Combining quantitative data from sources like Demographic and Health Surveys with qualitative methods like surveys and interviews, the project analyzes the relationship between malaria prevalence and vaccination rates, bed net usage, and cultural views on treatment. By taking a comprehensive approach focused on evidence-based insights, the research seeks to inform targeted interventions by the Ghanaian government …

Improving Adaptation Of Deep Learning With Inductive Bias, Xiajun Jiang

Theses

Human intelligence is strong at adapting to a small number of observations, partially because of the human ability to 1) use given knowledge and 2) distill knowledge from related but different data to guide learning for future tasks, where such ability is the inductive bias during learning. Deep learning shows a promising solution to artificial intelligence. However, generalizing or adapting deep learning models to heterogeneous tasks remains an open question. Existing data-driven models often ignore prior knowledge about the underlying problems of interest, or have limitations in incorporating complex knowledge into neural networks. The one-size-fit-all formula assumes the training and …

An Intelligent Framework For Efficiently Utilizing Distributed Heterogeneous Resources To Improve Hpc Application Performance, Moiz Arif

Theses

High-Performance Computing (HPC) workloads are being widely used to solve complex problems in scientific applications from diverse domains, such as weather forecasting, medical diagnostics, and fluid dynamics simulation. HPC workloads are traditionally executed on baremetal HPC systems, containers, functions, or as workflows or ensembles. These workloads consume a large amount of data and have large memory and storage requirements that typically exceed the limited amount of main memory and storage available on an HPC system. HPC workloads such as deep learning (DL) are executed on platforms such as TensorFlow or PyTorch, are oblivious to the availability and performance profiles of …

Predictive Maintenance On Drone Batteries Failure Using Machine Learning, Khalifa Jamal Almannaei

Theses

Predictive maintenance, powered by machine learning models, presents an innovative solution to address the limitations of drone battery maintenance. The core aim of this study is to design and implement machine learning models suitable for drone batteries, predict battery health, and prescribe maintenance actions. The ultimate scope is to improve operational reliability, safety, and cost-efficiency for drone applications while advancing sustainability and efficiency within the drone industry. By integrating predictive maintenance, the management of drone batteries can be optimized, leading to more reliable, and cost-effective drone operations, the proposal will seek to identify different factors that impacts the health and …

Optimizing V2v Energy Exchange Using Ai, Marwa Alghawi

Theses

A key factor in promoting sustainable economies, industries, and society is the use of electric vehicles (EVs). They are an important step toward a greener future since they reduce greenhouse gas emissions, improve air quality, and encourage energy independence. The demand for charging stations (CSs) will undoubtedly rise as the global EV market continues to grow over the next few decades, requiring significant investments from both public and private players. By creating a cutting-edge AI model, this work tackles the crucial problems of EVs range prediction and charging optimization decisions. The contributions are summarized as the below: 1. Developed AI …

Predictive Analytics Of Road Traffic Incidents, A Machine Learning Approach, Maryam Essa Jaji

Theses

Traffic accidents rank among the world's most serious concerns due to the high number of deaths, injuries, and fatalities as well as the enormous financial losses they cause every year. Road travel is a necessary component of modern civilization, but because of the rise in traffic accidents, it costs the world economy billions of dollars and over a million deaths annually. Road accidents can be caused by a variety of elements. It can be possible to take action to lessen the severity and extent of the effects if these elements are better recognized and predicted. The goal of this project …

“Art For The Millions:” The Evolution Of Informal Learning From The Charleston Museum To The New Deal, Kristen Walker

Theses

The advent of the first museum in the United States in 1773, The Charleston Museum, sparked a shift in the way education is perceived and how it can be conducted. However, only recently has the intentional implementation of programs and exhibitions been created in a digestible way for the public. This thesis discusses how informal learning has evolved since the establishment of the Charleston Museum and the legacy of the Federal Art Project regarding informal learning and art education. Key research methods include the examination of primary and secondary resources, including oral histories held by the Smithsonian Archives of American …

Robust Machine Learning Under Vulnerable Cyberinfrastructure And Varying Data Quality, Sergei Chuprov

Theses

In our study, we investigate Machine Learning (ML) application robustness in ML Integrated with Network (MLIN) systems. We consider MLIN as an integration of three major components and interrelations between them: data sources, network facilities, and ML application. In contrast to the conventional approaches that focus on each separate component, we concentrate on their interrelationships, and consider them from the system integration perspective. We formulate our primary goal as to develop methods and tools aimed at assuring ML application performance towards Data Quality (DQ) variation in MLIN through improving ML application robustness. We examine the prior work on ML robustness …

Learning From Disagreement In Human-Annotated Datasets, Tharindu Cyril Weerasooriya

Theses

Artificial intelligence (AI) systems frequently need to learn from human decision makers, which aids in scaling systems for mass use. We see this in automated financial decisions, manufacturing processes, self- driving cars, and content moderation on social networks. These systems are built on human values and trained to mimic human decision-making through human annotation. However, different groups of human annotators, including domain experts, annotate content differently, leading to disagreements. Some practitioners treat dissenting opinions as “label noise”. A common approach to dealing with disagreement is to consider a majority vote, which effectively conceals the disagreements from the trained model. Although …

Transfer Learning Across Domains And Sensing Modalities, Chowdhury Sadman Jahan

Theses

Transfer learning facilitates the training of a deep learning (DL) model with limited or no labeled data, by initializing the network parameters using a similar model already trained on a different but related dataset or task. This dissertation examines two special cases of transfer learning for image classification tasks: cross-modal supervised learning, and cross-domain unsupervised adaptation. This dissertation proposes to apply cross-modal transfer learning to guide the training process of a DL model on Synthetic Aperture Radar (SAR) images via knowledge distillation from a DL model trained on corresponding electro-optical (EO) images. Furthermore, this approach explores class-balanced sampling strategies and …

Low Power Logic Locking Using Design Space Modeling To Achieve System-Wide Security, Long Lam

Theses

Rising design complexity and smaller technology nodes are escalating fabrication costs, prompting design houses to outsource to untrusted external facilities, which raises trust and privacy concerns. These concerns stem from the risk of security breaches like IP piracy, reverse engineering, and hardware trojans. The critical need to protect design intellectual property prompted the development of logic locking, a combinational hardware security technique that corrupts the functionality of a design without the correct secret key. However, the effectiveness of logic locking varies substantially based on how and where it is implemented within a system, including the specific technique families selected, the …

Adjoining Gates: Mitigating Optical Side-Channel Attacks On Integrated Circuits Through Security-Aware Placement, Thomas Wojtal

Theses

With the rise of outsourcing in Integrated Circuit (IC) fabrication processes, vulnerabilities in chip security have become a growing concern. These vulnerabilities can lead to attacks such as reverse-engineering, piracy, overproduction, and malicious modification of high-value intellectual property (IP) in a design. In light of this, a method called logic locking has been developed to protect chips prior to end-user shipment. Logic locking incorporates additional logic gates in a design to conceal a chip’s functionality during manufacture and test processes. However, recent developments have shown logic locking to be vulnerable to optical side-channel attacks. In this work, we explore these …

Novel Methods For Modeling And Treating Biofilm Infections, Emily Lazarus

Theses

Biofilms are responsible for the development of chronic infections, which are 10-1000 times more resistant to antimicrobial agents than two-dimensional (2D) planktonic culture. Traditionally, 2D planktonic cultures are used to study efficacy of antimicrobial treatments but 2D cultures have several shortcomings such as increased sensitivity to treatments, lack of complexity of the three-dimensional (3D) environment, limited host defense mechanisms, and lack the structural thickness of natural biofilms. Biofilm-related infections play a critical role in the delayed healing process of chronic skin wounds, and while treatments for chronic skin wounds exist, including negative pressure wound healing (NPWT), biofilm infections still prevail. …

Optimizing Supply Chain Dynamics Using Machine Learning, Mohammad Zubin Siddiqui

Theses

Supply chains face many challenges in today’s business environment. This paper examines how advanced analytics can be used to improve supply chain efficiency and resilience with a particular focus on demand forecasting and late delivery analysis. The thesis focuses on two areas, which are forecasting demand and analyzing late deliveries. With the help of data-driven models for forecasting demand and pinpointing reasons behind delayed shipments, establishments can take appropriate measures that will reduce risks and enhance operational efficiency. A complete analytic framework is suggested that integrates sophisticated analytics into supply chain management so that organizations can optimize all their operations …

Investigating Essential Oils, Natural Compounds, And Marine Based Rumen Buffers As Feed Additives For Enteric Methane Mitigation And Improved Ruminant Productivity, Ian Hodge

Theses

Ruminant dietary additives were investigated for enteric methane (CH4) mitigation and their effects on rumen fermentation characteristics during both in vitro and in vivo supplementation trials. A meta-analysis of the peer reviewed published literature was initially performed to establish the state of the art in the field and allowed benchmarking of the performance of the dietary additives screened during the project. Investigated feed additives included garlic oil (GO), nitrate, Ascophyllum nodosum (AN), Asparagopsis (ASP), Lactobacillus plantarum (LAB), calcareous marine algae (CMA), chitosan (CHI), essential oils (EO) and 3-nitrooxypropanol (3-NOP). The development of an in vitro screening method to evaluate the …

Intelligent Tutoring System Ontology, Wael Mohamed Hassan

Theses

The integration of pedagogical rules into Intelligent Tutoring Systems (ITS) using semantic web technologies, particularly the Web Ontology Language (OWL), holds great promise for enhancing the capabilities of these systems. However, a significant challenge arises from the labor-intensive process of manually constructing ontologies, which can consume valuable time and resources. While ontologies offer numerous advantages, including robust knowledge inference and scalability, the limitations of manual ontology creation are evident in terms of time and flexibility. Therefore, the primary objective of this research is to develop an efficient and automated solution that harnesses the benefits of ontologies while reducing the time …

Evaluating The Impact Of Hybrid Ventilation Strategies On Reducing The Cooling Load And Achieving Thermal Comfort Of Buildings: Regarding Arid Climate Of Uae, Sheikha A Hmed Al Niyadi

Theses

The hybrid ventilation system has shown considerable potential in managing indoor thermal comfort, preserving indoor air quality, and minimizing energy usage. This is achieved by integrating natural and mechanical ventilation. When natural ventilation is unfeasible, the system smoothly transitions to mechanical ventilation to uphold optimal indoor thermal comfort levels. However, the application of this system in extremely arid regions poses a challenge due to the high energy consumption linked to air conditioning and cooling during the summer. In these areas, air conditioning and cooling alone represent approximately 60% of urban energy consumption. This study aims to assess the viability of …

Disturbance Observer-Based Control For Pmsg-Based Wind Turbiner Considering Unbalanced Grid Conditions, Moayad Alanani Maher

Theses

A typical Permanent Magnet Synchronous Generator (PMSG)-based wind turbine system consists of an electrical generator, Machine-Side Converter (MSC), Grid-Side Converter (GSC), dc-link capacitor, and a passive filter such as L filter or LCL filter to connect the GSC to the host grid. When the wind turbine operates under unbalanced grid voltages, a negative sequence component is introduced to the system. This negative sequence voltage can pose challenges for classical controllers to ensure an efficient control of the PMSG-based wind turbine system. On one hand, when the control objective is to ensure injecting sinusoidal and balanced three-phase currents to the grid, …

Organic-Based Nutrient Solutions For Sustainable Vegetable Production In A Zero -Runoff Soilless Growing System, Maitha Salem Almheiri

Theses

As the adoption of soilless production systems escalates to meet the rising demand for safe and healthy fresh produce, the growing environmental awareness and consumer’s preference for sustainable production systems are stimulating the reduction of synthetic inputs. A greenhouse study using an auto-pot zero-runoff hydroponic system and lettuce (Lactuca sativa L.) as a model vegetable crop was conducted to evaluate the potential of substituting synthetic fertilizer Nutrient Solutions (NS) with organic-based NS. The use of organic NS resulted in lettuce plants with fewer leaves and a smaller leaf area, plant height, stem diameter, and fresh biomass compared to those …

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Theses

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Using Smart Contracts in Financial Stock Market: An Analytical Study

Smart contracts are considered one of the latest technologies that have obtained attention from many Legalists and Engineers. Smart contracts are a set of arrangements written via programming languages through computer programs or by programmers without the need for an intermediary. Smart contracts are self-executing. It executes once the terms and conditions agreed between the parties happen.

Perspectives differ among legalists about the legality of smart contracts. Some legalists consider these contracts as binding legal contracts, while others believe that a smart contract might be just a part of …

Design Analysis Of The Structural System Of Alainsat-1 Cubesat By Simulation And Experimental Validation, Abdalla Saad Elshaal

Theses

This thesis presents the process of conducting the structural analysis of AlAinSat-1 CubeSat through a numerical solution using Siemens NX. AlAinSat-1 is a 3U remote-sensing CubeSat carrying two earth observation payloads. The CubeSat is scheduled for launch on SpaceX's Falcon 9 rocket. To ensure the success of the mission and its ability to withstand the launch environment, several scenarios should be analyzed. For the AlAinSat-1 model, the Finite Element Analysis (FEA) method is used, and four types of structural analyses are considered: modal, quasi-static, buckling, and random vibration analyses. The steps followed include idealizing, meshing, assembling, applying connections and boundary …

Unveiling The Origins Of Source Code Through Authorship Attribution: A Comparative Study Of Ai And Human Coding Patterns, Shamma Humaid Alalawi

Theses

In recent years, Artificial Intelligence (AI) techniques have been used for source code authorship attribution, which is the process of identifying the original author of a given piece of code. With the advancement of AI technologies like ChatGPT, which can generate code, there is a need to accurately identify whether a piece of code is written by a human or generated by a machine. This is crucial for intellectual property protection, cybersecurity, and software forensics. The main objective of this thesis is to review existing research on source code authorship attribution and conduct several experiments to determine the best AI …

Enhancing Cybersecurity Awareness In The United Arab Emirates: An Assessment Of Current Practices And The Development Of An Ai-Enhanced Mobile Application, Meera Humaid Alalawi

Theses

In today's interconnected world, individuals, private corporations, public institutions, and governments face increasingly sophisticated cyber threats and attacks, highlighting the critical need for individuals and organizations to understand cybersecurity comprehensively. Cyberattacks have affected many countries and infrastructures in different sectors worldwide, including the United Arab Emirates (UAE), which has become a main target for cybercrime due to its booming economy and tourism. The UAE considers cybersecurity an increasingly critical issue in our digital world, and increasing cybersecurity awareness among residents is essential to protect themselves and their organizations from cyberattacks. The primary objectives of this study are to identify key …

Transformer-Based Deep Learning Model For Sign Language Recognition, Ganzorig Batnasan

Theses

Sign language recognition research aims to develop systems and tools that can interpret and translate sign language into text or spoken language. During the past two decades, the challenges faced in this domain are multifaceted. The first and foremost challenge is the complexity of sign language, which includes intricate hand gestures, facial expressions, and body movements. Recognizing and interpreting these components accurately is challenging. The second challenge is variability among different regions and communities, leading to variations in signs and gestures. This variability poses a challenge for developing universal recognition systems.
Limited data is another challenge which makes it difficult …

Improving Early Design Processes With The Use Of Bim And Vr Technologies In The Gcc Construction Industry, Mohamed Wahid Mohamed

Theses

The early stages of construction projects play a crucial role in determining the outcome of the entire project life cycle. However, conventional early design practices have been facing significant challenges and limitations in recent times. These challenges include a lack of coordination among various disciplines, communication gaps, and poor decision-making. Unfortunately, these challenges often lead to increased costs, project delays, and change orders. To tackle these challenges, it is essential to adopt the latest technological advancements in the construction industry. This is especially important given the complexity of modern construction projects and the rapid construction growth. One of the most …

Synthesis And Biological Assessment Of Safranal-Loaded Metal-Organic Framework Nanostructures, Alia Musabbeh Alkaabi

Theses

Liver cancer remains a primary worldwide health concern, necessitating the development of innovative and effective treatment options. In this study, we present a biocompatible iron-based metal-organic framework (Fe-MOF) consisting of iron ligands connected by terephthalate linkers loaded with safranal, a major biomolecule of saffron (the stigmas of Crocus sativus flower), as therapeutic intervention with dual efficiency. This compound not only meets the demand for improved liver cancer therapies but also exhibits antibacterial properties against Escherichia coli and Lactobacillus. The synthesis stage of the study focuses on preparing MIL-88B(Fe) and loading safranal into/onto its structure (SAF@MIL-88B(Fe)). The material's composition and …