Digital Commons Network^™

Sticks, Naomi Karen Miller

Theses

Sticks is a thesis consisting of allegorical sculptural objects informed by chairs and inspired by a transgender woman’s personal narrative. Derived from personal anecdotes and feelings, the objects form a constellation of moments in time. The body of work primarily consists of burned wooden chairs. The chairs are analogous to the self. Fire is applied to the chair to document change. My work is about the ways an individual is changed by small moments of interaction. It explores the relationship between identity, observation, perception, and time.

Relative Effectiveness Of A Radionuclide (210pb), Surface Elevation Table (Set), And Lidar At Monitoring Mangrove Forest Surface Elevation Change, Richard Mackenzie, Ken Krauss, Nicole Cormier, Eugene Eperiam, Jan Van Aardt, Ali Rouzbeh-Kargar, Jessica Grow, Val Klump

Articles

Sea-level rise (SLR) is one of the greatest future threats to mangrove forests. Mangroves have kept up with or paced past SLR by maintaining their forest floor elevation relative to sea level through root growth, sedimentation, and peat development. Monitoring surface elevation change (SEC) or accretion rates allows us to understand mangrove response to SLR and prioritizes resilient ecosystems for conservation or vulnerable ecosystems for restoration. We compared three methods to measure SEC and accretion in mangrove forests: 210Pb, surface elevation tables (SETs), and a terrestrial light detection and ranging system (compact biomass LiDAR—CBL). Lead-210 accretion rates were not significantly …

Enhancing Efficiency And Sustainability: Retrofitting Fluorescent Lights To Leds, Khalifa Alshaiba

Theses

This research work emphasizes the urgent need to implement energy-efficient lighting technologies, particularly the retrofit of fluorescent lights with LED alternatives, in order to reduce energy consumption and greenhouse gas emissions. In addition to that maintaining operational safety and sustainability, improving energy efficiency is essential in Dubai's industries, which are major consumers of electricity and economic drivers. The project's goal is to retrofit energy-efficient LED lighting into a well-known packaging company's current fluorescent lighting systems. In doing so, the project hopes to improve illumination quality and minimize maintenance needs while lowering energy consumption, operating expenses, and environmental impact. The goals …

Partake: A Product Design Aimed At Helping Individuals Master The Art Of Cooking, Zikai Meng

Theses

Many individuals aspire to become skilled cooks and create delectable dishes on their own. However, following recipes or tutorials can be challenging for many. This is why I developed Partake - an interactive cooking learning platform designed to provide a solution. With this app, users can learn the art of cooking in a personalized and engaging way by adjusting ingredient quantities and receiving clear instruction on culinary techniques. Partake aims to enhance the likelihood of success for those embarking on their journey to master cooking skills.

Hybrid Test-Smell Based Approach For Prediction Of Flaky Tests, Saurabh Bodke

Theses

Regression testing is an essential component in software development, aimed at verifying that recent code changes do not negatively impact existing functionalities. A prevalent challenge in this area is the occurrence of flaky tests, which exhibit inconsistent outcomes—passing or failing without any code alterations. Such tests erode the reliability of automated testing frameworks, leading to increased debugging efforts and diminished confidence in software stability. This research addresses the challenge of flaky tests by exploring machine learning and prediction models, specifically focusing on test smells and four principal root causes of flakiness: Async Wait, Concurrency, Test Order Dependency, and Resource Leak. …

Improving The Test Smell-Based Detection Of Flaky Tests, Shubham Kumar Karum

Theses

Regression testing, a critical process in software development, ensures that the recent code changes have not adversely affected existing functionality. A significant challenge in this domain is the existence of flaky tests—tests that inconsistently pass or fail without any changes to the code. These flaky tests undermine the reliability of automated testing and can lead to increased debugging and decreased confidence in software stability. To tackle the issue of flaky tests, there exists approaches that make use of machine learning and prediction models. However, approaches that rely on analyzing test case vocabulary typically face challenges like higher costs to run …

Florist: (Ar System), Yanran Ding

Theses

The "Florist (AR system)" envisions a novel application of Augmented Reality (AR) in floral design, aimed at harmonizing traditional floristry with the digital age. While the full system is not yet realized, the conceptual design presents a compelling visual and interactive blueprint. It anticipates a platform that educates and assists users in crafting personalized floral arrangements through a rich database, AR tutorials, and customization features. This conceptual framework promises to address common barriers in flower arrangement by fostering an accessible, usercentered experience that could transform the floristry landscape.

Cookool: A Futuristic Cooking Innovation, Guannan Ling

Theses

Cookool is a futuristic innovation project that utilizes real-time interactive design and technology to display cooking information seamlessly, aiming to create a cool, friendly, and relaxed cooking experience for everyone to try, learn, and fall in love with. In traditional kitchens, people often face various challenges such as choosing dishes and controlling temperatures. However, in the future, our kitchen will leverage AI technology to precisely recommend dishes based on personal preferences, utilize thermal detection to monitor utensil temperatures, and leverage hologram and AR technology to showcase recipes and cooking processes, making cooking simpler. Yet, technology alone cannot create an inclusive …

Predicting Cost Contingency In Retrofit Projects Using Machine Learning Techniques, Dana Amin

Theses

Project contingency is one of the most important preliminary processes in any project estimation as it ensures the project risk for cost over-run due to uncertainties , in light of that, it is also important to make sure that the project contingency is not overestimated to maintain competitiveness in the market. This project aims to develop contingency decision support tool using ML techniques in order to predict the optimum contingency cost that balances between maintaining business competitiveness in the market and achieving project objectives. Different ML ways were evaluated and based on accuracy level ; Random Forest was found to …

Functional Role Of Toll-Like Receptor Associated Micrornas In Intervertebral Disc Pathophysiology, Petra Cazzanelli

Theses

Intervertebral disc (IVD) degeneration is one of the main contributing factors to low back pain (LBP), the leading cause of years lived in disability worldwide. The degenerative processes in the IVD tissue are characterized by the metabolic dysregulation of IVD cells and aberrant mechanical loading. The major hallmarks of this multifactorial pathology are the degradation of the extracellular matrix (ECM), inflammation, and cell loss. Inflammation has been specifically linked to the development of discogenic LBP, as increased secretion of pro-inflammatory cytokines can cause the infiltration of immune cells and nerve fibers. Toll-like receptors (TLR) are key regulators of inflammation, amongst …

Towards Bias-Resilient Deep Neural Networks, Robik Shrestha

Theses

Deep learning systems have brought about a paradigm shift in the field of artificial intelligence, often surpassing human performance across a wide range of tasks. Nonetheless, there are numerous apprehensions regarding their robustness when deployed in the real world. Multiple studies have demonstrated that deep learning models tend to latch onto biases present in their training data instead of truly solving the tasks. Given the pervasive nature of this issue across various datasets and tasks, researchers have proposed a variety of techniques to improve bias resilience. However, the evaluation protocols used in prior works leave many open questions regarding their …

Demonstration Of A Hybrid Electroabsorption Modulator/Photovoltaic Device For Space-Based Free Space Optical Communication And Power Generation, Emily Kessler-Lewis

Theses

The emergence of proliferated low-Earth orbit (pLEO) constellations using small satellites has resulted in significant interest in lowering the size, weight, and power (SWaP) of mission critical subsystems. III-V semiconductors are the class of materials typically used for photovoltaic (PV) arrays for satellites due to their exceptional efficiencies of upwards of 35 % and ability to be made thin, flexible, and lightweight. This is contrasted with the high SWaP communication system, which utilizes a radio frequency (RF) transceiver in order to communicate with a ground station. A lower SWaP alternative to the RF transceiver is to transmit data using free …

Effect Of Fabrication Pressure And Nmc Cathode Composition On Lpscl Electrolyte For Solid-State Battery Performance Improvement, Winervil James

Theses

Batteries are a key energy storage solution for a sustainable energy future. They provide carbon free power to portable devices such as mobile phones, laptops, and even electric vehicles. With further improvements to battery performance¸ the diversity of machines that can be electrified will increase. Solid state batteries (SSBs) have the potential to provide much greater energy density compared to conventional batteries. Greater energy density will help address the power to size ratio limitation of conventional batteries. Despite improvements in these major areas, SSBs still face some significant operational challenges. The study herein focuses on improving the performance of a …

A Prototype Of Simple Implantable Optofluidic Device Enabled By 3d Printing Technology, Yu Chang

Theses

Superhydrophobic surface-based optofluidics have been introduced to biosensors and unconventional optics recently with unique advantages such as dynamic adjustable optical properties, low light loss, and high versatility. Most of these platforms were manufactured by Microelectromechanical systems (MEMS) manufacturing technology and usually need to be further packaged or sealed. Although the MEMS-based technology is prone to make an integrated device containing sensing and electronic components, the technology may constrain the design of the morphology of the featured structures. For example, it was hard to manufacture a three-dimensional, fully enclosed round channel with complex structures along the inner surface. The limitations could …

A Comprehensive Machine Learning Approach To Assess Fall Risk In Stroke Survivors: Integrating Common Clinical Tests, Motor-Cognitive Dual-Tasks, Wearable Motion Sensors, And Detailed Motion Analysis, Masoud Abdollahi

Theses

This PhD dissertation focuses on developing improved methods for assessing and reducing fall risk in stroke survivors. Falls are a major concern in this population as they occur more frequently and can lead to catastrophic injuries due to factors like hemiparesis, spasticity, impaired balance and cognitive deficits. The dissertation reviews fall risk factors (FRFs) identified in prior studies and finds balance, gait and mobility metrics to be most significant. It notes current assessment methods rely on subjective scales and lack detailed motion analysis. Dual-task testing is also overlooked despite revealing subtle deficits. To address these gaps, wearable sensors and machine …

Non-Invasive Glucose Detection Using A Triple Pole Csrr Sensor, Chibuike Nnabuife Okika

Theses

A compact, low-cost, portable, non-invasive blood glucose sensor has been designed and presented in this paper. The proposed sensor is a triple-pole square Complementary Split Ring Resonator (CSRR) sensor that is etched on an FR4 substrate. At the bottom of the sensor is coupled an etched Microstrip Transmission Line (MTL) with an impedance matching of 50 Ω, which excites the sensor elements. Utilizing the CSRR-based sensor overcomes the disadvantages of pain and discomfort that the traditional method of pricking the skin to measure blood glucose levels could pose. The sensors work in such a way that as the glucose concentration …

The Effect Of Tensile Reloading On The Lüder Phenomena In Aisi 1524 Steel Alloy, Mohamed Rashid Almatroushi

Theses

Some low-carbon steels, magnesium-aluminum alloys, and nickel-based alloys exhibit plastic flow instability at their respective yield points in the form of a drop and plateau of stress in the stress-strain curve. This phenomenon is often referred to as the Lüder phenomenon in the yield point elongation region of the stress-strain curve. The Lüder phenomenon is characterized by the formation of regions, or bands, of high strain intensity at certain locations on the material. This behavior has been shown to be affected by several parameters such as material composition, grain size, temperature, strain rate, and microstructure to name a few. This …

The Role Of Large Language Models (Llms) Driven Chatbots In Shaping The Future Of Government Services And Communication With Citizens In Uae, Dina Fares

Theses

As technological advancements continue to redefine the landscape of Government Services and Communication with Citizens in the UAE, and in line with the UAE government's efforts towards achieving the UAE charter for future services, the integration of Large Language Models (LLMs) driven chatbots emerges as a pivotal factor in shaping the future of government services and communication with citizens in the United Arab Emirates (UAE). Through a comprehensive review of literature and collaboration with industry experts, this thesis explores the development of AI-based chatbots and the introduction of the breakthrough in the field of Deep Learning Language models (Transformers, and …

Tapered-Precision Numerical Formats For Deep Learning Inference And Training, Seyed Hamed Fatemi Langroudi

Theses

The demand to deploy deep learning models on edge devices has recently increased due to their pervasiveness, in applications ranging from healthcare to precision agriculture. However, a major challenge with current deep learning models, is their computational complexity. One approach to address this limitation is to compress the deep learning models by employing low-precision numerical formats. Such low-precision models often suffer from degraded inference or training accuracy. This lends itself to the question, which low-precision numerical format can meet the objective of high training accuracy with minimal resources? This research introduces tapered-precision numerical formats for deep learning inference and training. …

Shift Variant Image Deconvolution Using Deep Learning, Arnab Ghosh

Theses

Image Deconvolution is a well-studied problem that seeks to restore the original sharp image from a blurry image formed in the imaging system. The Point Spread function(PSF) of a particular system can be used to infer the original sharp image given the blurred image. However, such a problem is usually simplified by making the shift-invariant assumption over the Field of View (FOV). Realistic systems are shift-variant; the optical system’s point spread function depends on the position of the object point from the principal axis. For example, asymmetrical lenses can cause space variant aberration. In this paper, we first simulate our …

Software-Based Property Enforcement For Detecting Hardware Anomalies, Jacob Thomas

Theses

As the world grows more and more reliant on microcomputing systems, security becomes a greater and greater concern. Malicious code is an ever-present issue in the field of computing and hardware vulnerabilities pose a rising threat to an increasingly connected landscape. This variety in threats can be mitigated through invariant rules for device operation, which form a policy for acceptable device behavior such that policy violations can be interpreted as either erroneous or malicious. This defense architecture disregards threat source and identifies issues based on their symptoms. Such systems are usually enforced through hardware implementations, which can become expensive in …

Investigation On Sputter Ambient Oxygen Partial Pressure And Anneal Conditions On The Operation Of Indium-Tungsten-Oxide Thin-Film Transistors, Meghana Nagesha

Theses

Amorphous oxide semiconductors (AOS) have emerged as compelling candidates for thin film transistors due to their remarkable attributes, including high mobility(>20cm2/Vs), low-temperature deposition, optical transparency, and electrical uniformity. However, current solutions, such as amorphous indium gallium zinc oxide (a-IGZO), exhibit sensitivity to moisture and wet etch processes, leading to suboptimal device performance and stability issues. To address these challenges, this study explores Indium Tungsten Oxide (IWO), an AOS devoid of Ga or Zn, as a potential material for fabricating high-performance and stable flexible enhancement mode thin-film transistors (TFTs). The experiment investigates the impact of oxygen partial pressure during the …

Application Of Ai In Financial Sector: Earnings Call Dataset Analysis, Kesa M. Abbas

Theses

Deep learning has emerged as a cornerstone in diverse scientific domains, demonstrating profound implications both in academic research and conventional applications. The utilization of deep learning has branched to the financial sector for stock prediction, management of assets, credit score analysis, etc. During the end of the financial fiscal year, top executives present their companies’ growth and losses in earnings calls. These earnings calls invariably webcasted, furnish stakeholders with insights into a firm’s fiscal performance during a given period. These audios along with transcripts are published on the company website for the general public. If these audio and transcripts are …

Lifelong Learning In Spiking Neural Networks Through Neural Plasticity, Nicholas Soures

Theses

Lifelong learning, the ability to learn from continually changing data distributions in real-time, is a significant challenge in artificial intelligence. The central issue is that new learning tends to interfere with previously acquired memories, a phenomenon known as catastrophic forgetting. Surrounding this are several other challenges associated with this, such as knowledge transfer and adaptation, few-shot learning, and processing of noisy data. Since humans do not seem to suffer from this problem, researchers have applied biologically inspired techniques to address it, including metaplasticity, synaptic consolidation and memory replay. Although these approaches have seen some success in traditional neural networks, there …

Prediction Of Unplanned 30-Day Readmission Of Heart Failure Patients Using Lstm, Jesdin Raphael

Theses

In the context of heart failure, a leading cause of hospitalization in the United States, approximately 15\% of patients discharged within 30 days face readmission, contributing to escalated healthcare costs and compromised clinical outcomes. This study leverages a wealth of personal information extracted from Emergency Health Records (EHRs) spanning two decades. This research aims to enhance the predictive capabilities of re-hospitalization for cardiac patients by creating a two-stage LSTM model while incorporating features into regression and time series datasets. A critical aspect of this study involves ensuring the integration of all relevant features across both datasets. Including constant data elements, …

Renewable Energy Integration Strategy Development For Dubai South, Oshba Almheiri

Theses

Dubai South is an aerotropolis city, a global aviation and logistics hub, home to the world’s largest airport, Al Maktoum International Airport (DWC). Along with such growth, a high demand of energy is expected therefore in response to address such need for the implementation of sustainable energy practices in Dubai South’s aviation, logistics, and residential districts. The development of an integrated renewable energy strategy for the region is the subject of this capstone project. The project relies on three pillars; first environmental impact to battle climate change, secondly alignment with local and international standards like as the UN Sustainable Development …

Viability Of Rental Chillers For The Gcc Region By Using Uae As A Baseline, Kenaz Thomas George

Theses

The HVAC industry in the UAE is a lucrative business, with five companies operating in the UAE, two of which are major players in the market. COMPANY-X, is one of two and it is a multi-million-dollar company headquartered in the USA. The company has franchises in Dubai and Abu Dhabi, along with several dealerships across the country. Despite considering entering the rental market for the past six years, however, it remained just an idea until the outbreak of the COVID-19 pandemic in 2022. The pandemic resulted in a surge in demand for rental services, specifically in the testing and vaccination …

Enhancing Human-Robot Collaboration Through Intuitive Augmented Reality Interface And Precise Visualization, Wenhao Yang

Theses

In terms of changing production in the transformation to the Industry 4.0 landscape and increasing demand for customized products, small and medium enterprises (SMEs) utilizing industrial robots encounter a shortage of skilled labor. Open questions in human-robot interaction encompass the need for natural and effective interfaces, path planning within intricate environments, and the design and execution of human-robot collaborations. This dissertation aims to tackle these challenges by leveraging Augmented Reality (AR) to enhance robot operations in manufacturing scenarios, with a focus on optimizing the efficiency of the Human-Robot Interaction (HRI) system, improving the bidirectional trust between humans and robots, and …

Security Datasets For Network Research, Bruce Hartpence, Bill Stackpole, Daryl Johnson

Data

This document describes the content of the security traffic datasets included in this collection and the conditions under which the packets were collected. These datasets were assembled from 2023 onward. There will be periodic updates or additions to the dataset collection. The current collection includes a variety of nmap intense scans, an Address Resolution Protocol Man in the Middle (ARP MITM) attack, an Internet Control Message Protocol (ICMP) Redirect MITM and an active directory enumeration attack.

New additions include two DNS Covert channel projects. The first builds the covert channel and exploits the DNS TXT resource records. The second includes …

Probability Distributions Arising In Connection With The Inspection Paradox For Bernoulli Trials., James E. Marengo, Anne Marino Himes, W. Cade Reinberger, David L. Farnsworth

Articles

In renewal theory, the Inspection Paradox refers to the fact that an interarrival period in a renewal process which contains a fixed inspection time tends to be longer than one for the corresponding uninspected process. We focus on the paradox for Bernoulli trials. Probability distributions and moments for the lengths of the interarrival periods are derived for the inspected process, and we compare them to those for the uninspected case.