Digital Commons Network^™

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, …

Thermo-Kinetic Parameters Governing Decomposition Of Amino Acids: A Computational Study, Mubarak Taleb Alkwradi

Theses

Amino acid model compounds are important nitrogenated species that in various categories of biomass. These compounds exhibit unique fragmentation pathways because of their adjacent amino and hydroxyl groups. Comprehending the decomposition chemistry of amino acids is essential to reduce harmful nitrogen emissions during biomass thermal treatment. This research reports the kinetic and thermodynamic properties of amino acids, and sulfur-containing amino acid, based on accurate density functional theory calculations coupled with kinetic modelling. The first part of the thesis provides comprehensive thermochemical parameters for the complete set of amino acids in the gas phase. The optimized geometries of amino acid compounds …

Selective Production Of Levoglucosan (Lg) From Pyrolysis Of Date Pits And Its Catalytic Transformation Into Transportation Fuels, Ala Hamid Higazi

Theses

Levoglucosan (LG) or (1,6-anhydro-β-D-glucopyranose) signifies important sugar derivatives produces in appreciable quantities from thermochemical and biochemical degradation of biomass. It is often regarded as an important platform chemical for the synthesis of value-added products, most notably styrene and furans. The work in this thesis entails two broad aims; to produce LG from pyrolysis of date pits; and then convert the LG into transportation fuels through a hydrodeoxygenation (HDO) reaction. The particular choice of date pits stems from its local relative abundance as a waste biomass. Aiming to further improve the yield of levoglucosan yields from pyrolysis of date pits, pre-treatment …

Assessing Open Source Tools For Enhanced Forensic Analysis Of Unmanned Aerial Vehicles (Uavs), Nura Shifa Hamed

Theses

The widespread applications of Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, has given rise to significant national security threats due to their illicit activities. Consequently, the domain of UAV forensics is rapidly evolving, presenting a substantial knowledge deficit among forensic experts. Open source tools provide accessible and affordable resources, making it easier for investigators to bridge this gap by gaining expertise in the use of these tools. This helps ensure that forensic professionals can keep up with the ever-changing UAV technology landscape. This thesis undertakes the mission of navigate the complex field of drone forensics and conducting a …

Construing Children’S Perceptions Of Ideal Learning Spaces Based On Personal Construct Theory, Rawan Natheer Abdel Rahman

Theses

Learning is an intrinsic aspect of human experience, predominantly shaped by interactions within the socio-physical environment, including engagements with educators, peers, and the built surroundings. The design and character of these learning spaces influence children's cognitive, perceptual, and motor development while also embodying different pedagogical philosophies. Therefore, designing these spaces to align with educational shifts and enhance learning experiences requires a deep understanding of learner’s needs and perceptions. With the COVID-19 pandemic necessitating a shift to home-learning, there arose a unique opportunity to explore children’s perception of ideal learning spaces as they experienced both home and school settings. This research …

Impactful Interactivity Within Video Games, Luke Robert Maeser

Theses

Despite half a century of existence and dedicated academic programs educating next generations of game developers, conclusive evidence does not exist as to if video games are beneficial to learning or costly. Examining the notion of benefit versus cost, it is important to assess the value of video games when leveraged as tools for learning as traditional educational methodologies are not infallible. This paper explores how video games can generate psychological responses; and therefore, one must conclude learning has occurred. The following is encompassed: meaningful interactivity within video games (regarding narrative and gameplay), video games as educational tools, video game …

The Importance Of Female Bass Players: How They Have Influenced And Shaped Our Conception Of Music, Jessica Sacks

Theses

Music allows us to think creatively, dream, and create a soundtrack for our lives. When we think of female artists, most people recognize singers, but I want to describe how women have shaped music for over sixty years with their fantastic playing abilities. This project will analyze how female bass players have contributed to American music and society.

Post-War Restitution In The Republic Of Croatia: Awareness Of The Komza And Reconciliation Of Moveable Property Through Public Sculpture, Anita Govic

Theses

This project is a public sculpture prototype focused on the need for post-war art restitution in the Republic of Croatia: it will have an impact by enhancing public knowledge of the KOMZA list, which offers legal proof for families to retrieve heirlooms taken during WWII and the wars of secession from Yugoslavia.

The sculpture design includes three pillars, two etched with the 1529 names from the KOMZA list and a third that will be progressively built, brick-by-brick, as artworks are restituted. The nature of viewers’ interaction includes access to QR codes that offer links to the KOMZA list, information about …

Drone Swarms In Adversarial Environment, Bhavana Sai Yadav Akula

Theses

Drones are unmanned aerial vehicles (UAVs) operated remotely with the help of cameras, GPS, and on-device SD cards. These are used for many applications including civilian as well as military. On the other hand, drone swarms are a fleet of drones that work together to achieve a special goal through swarm intelligence approaches. These provide a lot of advantages such as better coverage, accuracy, increased safety, and improved flexibility when compared to a single drone. However, the deployment of such swarms in an adversarial environment poses significant challenges. This work provides an overview of the current state of research on …

A Socio-Hydrological Assessment Of Illinois Levee Systems, Nicholas Keller

Theses

Recent inspections conducted on levee safety in the U.S. that participate in the United States Army Corps of Engineers (USACE) Levee Safety Program under Public-Law 84-99 have shown that the overwhelming majority (>95%) of these levees have at least some deficiency associated with them, and many being identified as having an unacceptable safety rating (≈30%). In the U.S., many levees were constructed using funding from the federal government, but the responsibility of operation and maintenance of the levees were turned over to local government bodies. Given the local funding of levee maintenance, the socioeconomic characteristics of these levee-protected communities …

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 …

Biodov: A Tool Used To Encourage Discovery In Bioinformatics Through Gamification, Gregory D. Johnson Jr.

Theses

Expressing big data in a meaningful manner is exceptionally difficult. Scientists often struggle with the visualization of data due to several limitations. Currently, many scientists use two-dimensional figures to display and analyze meaningful data. However, I believe using game design theory and game technologies, we can create more robust visualizations. These visualizations will allow scientists to easily communicate science to the masses and make better discoveries. Therefore, we introduce BioDOV (Biological Data Oriented Visualization). This tool will utilize game design principles to expand upon current visualization methods in the scientific community. Through this proof of concept, we will create the …

Application Of Icp Rie Techniques To Produce Cnt Arrays, Mujtaba Yar Khan Siddiqui

Theses

Introducing biomolecules into cells is an important process in the field of gene therapy and in developing cures for debilitating illnesses such as HIV and cancer. However, the currently used methods for cellular transfection are slow, inefficient and expensive, causing them to be restrictive. A solution to this problem would be the carbon nanotube (CNT) array devices developed by our research group, which have been shown to be highly efficient at transporting biomolecules into cells. In the current manufacturing process, a sacrificial template with vertically aligned nanopores is used to deposit carbon in, the template then is etched away to …

Optimal Entanglement And Spin Squeezing In Collections Of Two-Level Atoms, Emily Finson

Theses

Spin squeezing is a bulk, non-classical effect that can occur in spin systems and occurs when fluctuations between two observables are redistributed while still maintaining the minimum uncertainty product. Planar-quantum squeezing is a similar phenomenon where there are decreased spin variances in two orthogonal spin components. In the work that follows, we consider specifically the realization of a spin-j system, a collection of N = 2j two-level atoms, in accordance with the famous Dicke model for such a system. Both spin and planar-quantum squeezing act as entanglement witnesses. This means that where we observe spin squeezing we should also observe …

Bearings Fault Classification Using Machine Learning And Dashboard For Bearing Signals Vibration, Ameirah Mohamed

Theses

Bearings are crucial components for the mechanical system that allows relative motion between two parts. Bearings primarily used to reduce the friction on the component. However, Bearings can fail for several reasons such corrosions, fatigue and electrical damage ..etc .This research aims to develop an accurate prediction model and visualization dashboard to avoid the costly downtimes, high repair cost and enhance the maintenance experience for workers and engineers. The data used in this research is CASE WESTERN RESRVE UNIVERSITY (CWRU) bearing data set. The data set contains signals vibration readings of bearings that can used for bearings fault detection. The …

Real-Time Object Tracking With Yolov5 And Recurrent Network On A Hardware Platform, Mohammed Abdulhakeem Alameri

Theses

The advancement of computer vision, particularly in the domain of object tracking, involves the integration of conventional feature-based approaches with contemporary deep learning methodologies. The initial phase of object detection plays a fundamental role in generating prospective objects for further tracking, and its level of success has a direct influence on the overall effectiveness of the tracking process. Many of the methods used to generate candidate objects start with object detection, and then object tracking algorithms are developed to link the object instances together to create the trajectories.
The primary difficulties in object tracking pertain to the establishment of reliable …

Fabrication Of Diffraction Grating Prototype Solar Sails For In-Space Propulsion, Qing Xian Wang

Theses

Solar sails offer advantages over rockets for heliocentric navigation by utilizing sunlight as an unlimited source of radiation pressure for propulsion. This eliminates the need to carry fuel and allows the sail craft to reach destinations that are difficult or impossible for rockets to reach. Solar sails provide a small but continuous acceleration that produces large changes in the sail craft velocity over time. A conventional solar sail makes use of the law of reflection to achieve in-space propulsion. By tilting the reflective sail away from the sunline, an optimal angle of reflection is achieved, generating a transverse force for …