Digital Commons Network^™

Defect Detection And Closed-Loop Feedback Using Machine Learning For Fused Filament Fabrication, Amaris De La Rosa, Amir Armani, Marcia Golmohamadi

Faculty Research, Scholarly, and Creative Activity

The objective of this study was to develop a closed-loop system for a commercial fused filament fabrication printer based on visual machine learning inspection of common defects. Convolutional neural network was used to identify levels of common defects: stringing, over/under-extrusion, and weak infill. Transfer learning was used to adapt a pre-trained model to fit this problem, as it involves incrementally fine-tuning the model parameters to new data. The observation model achieved an accuracy of 92.86% on validation data set and 90.0% on the testing data set. By modifying the input G-code, the custom program could adjust the feed-rate, nozzle temperature, …

Eyes On Higher Education: Evaluating Web Usability In Kuwaiti Private Universities Using Eye-Tracking And Supr-Q Metrics, Reem Albaghli, Ayah Beidas, Nada Attar

Faculty Research, Scholarly, and Creative Activity

Website design and usability are critical factors that impact the effectiveness of a website, influencing both user attraction and retention. Understanding user preferences is essential for designers and researchers when optimizing user interfaces (UI) and user experiences (UX). This study addressed key research questions about usability by examining which design heuristics have the most impact on students’ interactions with private university websites in Kuwait. By assessing web design and usability across three private universities in Kuwait through specific tasks, we analyzed user experiences using eye-tracking data, task completion times, user inputs, and qualitative feedback from the Standardized User Experience Percentile …

Marine Protection And Environmental Forcing Influence Fish-Derived Nutrient Cycling In Kelp Forests, June Shrestha, Joseph R. Peters, Jennifer E. Caselle, Scott L. Hamilton

Faculty Research, Scholarly, and Creative Activity

Animal consumers excrete dissolved inorganic nitrogen, an essential nutrient for regulating primary production and macroalgal growth in the ocean. Often overlooked in attempts to explain kelp forest productivity, relatively little is known about the role of consumers in nutrient cycling in temperate systems, such as the magnitude of nutrients excreted and the factors that influence spatial and temporal variability in consumer-derived nutrients. To investigate the supply of ammonium (NH4+) excreted by the dominant members of the nearshore rocky reef fish community, we combined empirically-measured relationships between excretion rate and body mass with data on fish density and size structure from …

Mitigating Risk: Predicting H5n1 Avian Influenza Spread With An Empirical Model Of Bird Movement, Fiona Mcduie, Cory T. Overton, Austen A. Lorenz, Elliott L. Matchett, Andrea L. Mott, Desmond A. Mackell, Joshua T. Ackerman, Susan E.W. De La Cruz, Vijay P. Patil, Diann J. Prosser, John Y. Takekawa, Dennis L. Orthmeyer, Maurice E. Pitesky, Samuel L. Díaz-Muñoz, Brock M. Riggs, Joseph Gendreau, Eric T. Reed, Mark J. Petrie, Chris K. Williams

Faculty Research, Scholarly, and Creative Activity

Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting 600 bird and mammal species globally and over 83 million birds across North America (December 2023), poses a serious global threat to animals and public health. We combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was …

Next Steps For Assessing Ocean Iron Fertilization For Marine Carbon Dioxide Removal, Ken O. Buesseler, Daniele Bianchi, Fei Chai, Jay T. Cullen, Margaret Estapa, Nicholas Hawco, Seth John, Dennis J. Mcgillicuddy, Paul J. Morris, Sara Nawaz, Nishioka, Anh Pham, Kilaparti Ramakrishna, David A. Siegel, Sarah R. Smith, Deborah Steinberg, Kendra A. Turk-Kubo, Benjamin S. Twining, Romany M. Webb

Faculty Research, Scholarly, and Creative Activity

There are many potential approaches to marine carbon dioxide removal (mCDR), of which ocean iron fertilization (OIF) has the longest history of study. However, OIF studies to date were not primarily designed to quantify the durability of carbon (C) storage, nor how wise OIF might be as an mCDR approach. To quantify C sequestration, we introduce a metric called the “centennial tonne,” defined as 1,000 kg of C isolated from atmospheric contact for on average at least 100 years. We present the activities needed to assess OIF from a scientific and technological perspective, and additionally, how it might be responsibly …

Resume Content Generation Using Llama 2 With Adapters, Navaneeth Sai Nidadavolu, William B. Andreopoulos

Faculty Research, Scholarly, and Creative Activity

This paper presents a novel approach to enhancing the Llama language model for generating customized resumes tailored to domain-specific job descriptions. Unlike traditional methods that rely heavily on extensive fine-tuning, we implement scalable adapter modules to minimize parameter adjustments. This approach preserves the model's inherent ability to generate coherent and contextually appropriate language across diverse tasks, ensuring that its general linguistic capabilities remain intact. Additionally, we employ a prompting strategy to dynamically create a diverse and comprehensive dataset, ensuring high relevance to various job roles. Using a dataset of 10,000 job descriptions and resumes, our approach resulted in a 20% …

Selective Laser Melting And Mechanical Characterization Of Superalloys Made From Recycled Parts, Hugo Tupac-Yupanqui, Amir Armani

Faculty Research, Scholarly, and Creative Activity

Geometrically complex functional parts from recycled Inconel 718 were additively manufactured and characterized. Scrap parts were melted, recycled, and used in a new gas atomization process to produce the feedstock for a selective laser melting printer. Optimal print parameters were determined using finite element simulations. Standard test methods were employed to experimentally examine the properties of parts, including their density, anisotropic tensile behavior, chemical composition, and fracture surface. The results indicated that scrap Inconel 718 parts can be used to additively manufacture high-quality functional parts. As a case-study, an automotive turbocharger was resigned and additively manufactured based on the findings …

Student Understanding Of Divergence And Curl In Upper-Division Electromagnetism, J. Toby Stuckey, Gina M. Quan

Faculty Research, Scholarly, and Creative Activity

The purpose of this paper is to understand and characterize student thinking about the physics concepts of divergence and curl in the context of upper-division electromagnetism for physics majors. We interviewed five students at a west coast university who had taken at least one semester of upper-division electricity and magnetism. The interview prompted students to describe divergence and curl in multiple representations (visually, mathematically, qualitatively). Our analysis identified that students can notice but struggle to resolve discrepancies between the mathematical calculations and the graphical representations of vector fields. We illustrate examples of when students appear to have a disconnect between …

Study Of Using Variational Quantum Linear Solver For Solving Poisson Equation, Nithin Reddy Govindugari, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

Quantum computing is promising in speeding up the system of linear equations (SLE) solving process. However, its performance is limited by noise. The variational quantum linear solver (VQLS) algorithm is expected to be more resilient to noise than gate-based quantum computing algorithms. This is because error correction is not available yet and VQLS is based on cost function minimization. In this paper, the gate insulator Poisson equation is solved using VQLS. The results are compared to technology computer-aided design (TCAD) results and gate-based quantum algorithm results. We show that, even without error-free qubits, the IBM-Q quantum computer hardware can solve …

Tcad Structure Input File Generation Using Large Language Model, Le Minh Long Nguyen, Albert Lu, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

In this paper, we study the possibility of using Large Language Models (LLMs) to create Technology Computer-Aided-Design (TCAD) structure generation input files. LLMs are machine learning models trained on vast amounts of text data from the Web and are designed to understand, generate, and interact with humans through natural languages such as English. However, unlike programming languages with abundant training examples on the Web, TCAD examples are scarce. In this work, by using TCAD Sentaurus Structure Editor (SSE) as an example, 7000 nanowire data are generated to fine-tune open-source models (Llama 2 and 3) to obtain chatbots that can generate …

Financial Literacy In The Era Of Artificial Intelligence. Towards Financial Inclusion. Opening Remarks, Łukasz Kurowski, Anna Szelągowska

Journal of Banking and Financial Economics

Financial Literacy in the Era of Artificial Intelligence. Towards Financial Inclusion. Opening Remarks

Euro-Denominated Credit Liquidity: Tracing Cyclical Phases In Global Finance, Mateusz Mariusz Mierzejewski

Journal of Banking and Financial Economics

In the past few years, set against the backdrop of pandemic mitigation efforts and the resultant inflationary spike, the macrofinancial landscape has undergone significant transformation. The tightening of monetary policy by global central banks in response to these phenomena has notably affected global financial liquidity, particularly within the realm of foreign currency lending. This article delves into the shifts in credit liquidity, centering on the Global Liquidity Index for euro-denominated loans across European Union nations over the last two decades. Through the application of the Fourier Transform, we analyse the cyclical patterns within the index and delineate the primary phases …

Betting On The Market: The Influence Of Match-Day Odds On Price Reactions Of European Football Clubs, Pascal Alterauge, Marc Mehlhorn

Journal of Banking and Financial Economics

This research investigates the relationship between football match outcomes, betting odds and the stock prices of publicly traded European football clubs, spanning from 11 February 2004 to 7 April 2022. Drawing data from 12 major European and publicly traded clubs, the study utilised betting odds as a key metric. These odds, aggregated from the Odds Portal, serve as a gauge for expected versus unexpected match outcomes. Preliminary findings showed a market value increase of 0.44% after a win and a decrease of 1.08% post-defeat. Moreover, deviations from betting odds predictions significantly influenced stock prices, with unexpected wins and losses resulting …

Optimal Empirical Strategy For Deriving The Spot Curve: The Case Of Poland, Piotr Bartkiewicz

Journal of Banking and Financial Economics

We use a proprietary dataset of daily quotations of individual bonds from the period 2005–2018 to assess the appropriateness of three common yield curve intrapolation methods: Nelson-Siegel (NS), Diebold-Li (DL) and cubic splines. Spot (zero-coupon) yield curves derived from the methods are used to price all securities in the sample in both in-sample and out-of-sample settings. The results highlight trade-offs inherent in any empirical strategy: between flexibility and in-sample fit, between overall fit and fit in particular segments of the curve. We look at both in-sample and out-of-sample. Cubic splines offer the best in-sample fit, but out-of-sample results indicate that …

Indirect Measure Of Financial Constraints: Evidence From Unquoted Innovative Smes, Katarzyna Prędkiewicz

Journal of Banking and Financial Economics

This paper examines whether companies’ innovativeness affects the availability of capital and, therefore, whether this group is financially constrained. It uses an objective, indirect way of measuring financial constraints based on the assumption that financially restricted firms only invest when internal cash flow allows them to do so. Therefore, the research was based on the investment-cash flow equation, more precisely the adjusted ECM model adapted to the SME sector. The companies’ innovativeness was measured based on a proprietary synthetic indicator covering a broad range of information on innovation activity. The research was conducted on a sample of 403 firms, including …

Impact Of Environmental, Social, And Governance Disclosure On Firm Performance: A Case Of Listed Manufacturing Firms In Nigeria, Abdulbaki Ubandawaki

Theses and Dissertations

The traditional goal of companies is to maximize shareholders’ wealth. However, to achieve this objective, many complementary goals must be pursued alongside the traditional ones. To achieve corporate goals, businesses need to interact with the environment. The continual interaction of the corporation with the environment has definitely come with its costs and benefits, and the global interest in promoting sustainable development has made corporate ESG reporting a crucial issue. The aim of the study is to investigate the relationship between ESG reporting and firm performance among listed manufacturing firms in Nigeria. The data was collected from annual and standalone sustainability …

A Structure From Motion Photogrammetric Method For Continuously Measuring And Tracking The Deformations Of Soils During Triaxial Testing, Xiaolong Xia

Doctoral Dissertations

"Measuring soil deformation characteristics during triaxial testing is an important part of characterizing the stress-strain behavior of both saturated and unsaturated soils. The total and local deformations and volume changes of a soil specimen are indispensable parameters that need to be measured and are of great significance for understanding volume change and shear strength characteristics of the soil. Over the past several decades, numerous efforts have been made to measure the soil deformations during triaxial testing. However, it remains a great challenge for researchers to measure the volume-changes of unsaturated soils due to the existence of the air phase.

This …

Synthesis And Characterization Of Quantum Materials, Yunsheng Qiu

Doctoral Dissertations

"In this study, attempts were made to grow quantum materials that have recently undergone a profound change of perspective. These materials are involved in intricate macroscopic properties rooted in the subtle nature of quantum physics. To explore our understanding of quantum materials, this study includes three projects: Magnetic Topological Insulators, Topological Superconductors, and high-temperature superconductors.

A Cr-doped Sb₂Te₃ is added to the category for the magnetic topological insulators project. Their transport properties are studied, and the origin of ferromagnetism is studied. Anomalous Hall effect is observed in the Hall measurements, and serval factors (cooling rate, dopant deficiency) …

Re-Evaluating Missouri’S Strategic Element Potential: A Geochemical Study Of The Mesoproterozoic Fe-Cu-Co-Ree Deposits In Southeast Missouri, Usa, Brandon James Sullivan

Doctoral Dissertations

"Iron-oxide-copper-gold (IOCG) deposits are poorly understood mineral systems. For example, we do not know why Cu- and Co-rich IOCG deposits typically occur proximal to Fe ore deposits that are notably Cu and Co-poor, such as Iron Oxide Apatite (IOA) deposits. To better understand the formation of IOA and IOCG deposits in Missouri, USA, this PhD thesis examines the genesis of the Kratz Spring IOA and the Boss Central Dome IOCG deposits. This study presents the first constraints on formation conditions and fluid sources in the studied deposits using integrated petrographic, mineral composition, and Fe isotope analyses of oxide minerals. Observations …

Characterization Of The Acquisition Parameters Of A Submersible Gamma-Ray Computed Tomography System, Zhongmin Jin

Doctoral Dissertations

"The purpose of this work is to study a component of a submersible gamma-ray computed tomography (CT) system used in the non-destructive testing of irradiated nuclear fuels. The first section of this study proposes two acceleration approaches for rapidly modeling a transmission-type gamma-ray tomography system. The first relies on Monte Carlo simulations with a monodirectionally biased source sampled from a sub-volume of the whole source volume. This method estimates the real count rate using analytical correction factors. The second way of acceleration is based on deterministic calculations that use the Beer-Lambert law and detector response characteristics. It shows that both …

Novel Uses Of Distributed Optical Fiber Sensing For Geo-Mechanical Monitoring, Samuel Vincent Nowak

Doctoral Dissertations

"Rock mass monitoring in underground excavations is crucial for ensuring workplace safety and efficiency. As mines become deeper and more complex, the need to monitor larger volumes of rock during mining becomes impractical with existing instruments due to high costs. Distributed Optical Fiber Sensing (DOFS) is a powerful technology with advantages like long sensor length, real-time measurement capabilities, ease of installation, low cost, and distributed measurement. However, its application in rock mass monitoring is limited, especially in the mining industry. This study addresses a major gap in DOFS technology, specifically the inability of long-range distributed optical fiber strain sensors to …

Modeling And Analysis Methods For Esd And Emi Problems, Xin Yan

Doctoral Dissertations

"Electrostatic discharge (ESD) failures and Electromagnetic interference (EMI) problems are becoming more critical in electronic devices and large systems. In this work, four studies are presented to model and analyze ESD and EMI problems.

First, a simplified physical-based model for deep-snapback transient voltage suppressors (TVS) is developed. While based on physics, the number of parameters and components is minimized. Results show that the proposed model captures the most important behaviors of the TVS response using a limited number of parameters, allowing the model to be tuned relatively easily using data obtained only from package-level transient and quasi-static measurements. Second, a …

Melt Pool Feature Extraction, A State-Space Model And Spatial Layer-To-Layer Control For Powder Bed Fusion, Xin Wang

Doctoral Dissertations

"Powder Bed Fusion (PBF) is an Additive Manufacturing (AM) technique which can reduce material waste and is a fast-prototyping technique for complex geometries. However, the lack of consistent quality is a major problem in industrial applications. An InfraRed (IR) camera is a common tool to monitor a surface temperature field and melt pool morphology in PBF. With melt pool features from camera videos, manufacturing researchers use spatial feature maps to visualize defect locations and control researchers use layer-to-layer control to achieve more uniform melt pools and less defects.

Paper I presents a simulation method to characterize the effect of down-sampling …

The Science Of Gravitational-Wave Sources And Beyond Compact Binary Coalescences, Yanyan Zheng

Doctoral Dissertations

"This work focuses on the field of gravitational-wave astronomy by extending the scope of detectable sources beyond compact binary coalescences, All the gravitational-wave detections so far come from compact binary coalescences. Focusing on core-collapse supernovae as promising sources for short gravitational-wave transients, this work reports optically targeted searches for gravitational-wave emitted by core-collapse supernovae during the third observing run of the LIGO and Virgo detectors. It also predicts the search sensitivity for the ongoing fourth and forthcoming fifth observing runs. Moreover, the work introduces a novel computational framework for testing the spatial distribution of binary black hole sources, allowing for …

Material Models For Simulation Of Steel Hot Rolling Process Using Experimentally Determined Properties At Elevated Temperatures And Strain Rates, Siva Sai Krishna Dasari

Doctoral Dissertations

"Hot rolling is one of the most important and complex process that includes large material deformation, different contact conditions, complex geometries and different temperature gradients along with micro structural changes such as viscoplasticity, dynamic recrystallization, and static softening. In the present work, the viscoplasticity, damage evolution, static softening and void closure of alloyed metal during hot rolling process was numerically investigated. Gleeble^TM hot compression and double hit tests were performed to provide experimental stress-strain curves at recrystallization temperatures and at different strain rates. Johnson-Cook viscoplastic model was calibrated using experimental stress-strain curves. Static softening model was developed at varying …

Advanced Mass Spectrometry Method Development And Applications For Assessment Of Traumatic Brain Injury And Legionella Pneumophila Dissinfection With Copper, Austin Chase Sigler

Doctoral Dissertations

"Pathological processes often involve complex biochemical changes which can be assessed using advanced mass spectrometry. In this present dissertation, two fields were studied: traumatic brain injury (TBI), and water contamination by L. pneumophilia. TBI is a pressing public health concern for which current clinical tools remain inadequate. We present newly developed mass spectrometric methods to access metabolites associated with blast induced TBI. We applied these methods to the biofluids of soldiers conducting explosives training. Significant changes in several metabolites were observed between pre- and post-blast specimens, including changes that increased with repeated exposure. These changes point to the possibility of …

Deep Learning Techniques For Image Segmentation In Dermoscopic Skin Cancer Images, Norsang Lama

Doctoral Dissertations

"Melanoma is recognized as the most lethal type of skin cancer, responsible for a significant proportion of skin cancer-related deaths. However, early detection of melanoma is essential for successful treatment outcomes. Computer-aided skin cancer diagnosis tools can save lives by enabling earlier detection of skin cancer. Image segmentation is a crucial step in computer-aided diagnosis as it allows the detection of critical features or regions in an image. Thus, an accurate image segmentation method is necessary to create a more precise computer-aided diagnostic tool for skin cancer diagnosis. This dissertation includes investigating and developing deep learning techniques to improve image …

Improving Decision-Making Processes In Construction And Infrastructure Bidding: Qualitative And Quantitative Approaches Including Graph Theory, Game Theory, And Machine Learning, Muaz Osman Elzubeir Ahmed

Doctoral Dissertations

"Construction and infrastructure bidding is a highly competitive process that entails various uncertainties faced by contractors. Contractors weigh various factors to determine the expected benefits of a construction project and decide their bid value. However, the situation is more complex in multi-stage bidding (MSG), where general contractors must account for the bids of their subcontractors and face a greater threat of the winner’s curse (i.e., situation where the winning contractor underestimates the actual cost of the project). As such, bidding-related complexities, risks, and uncertainties, if uncontrolled, can lead to the rise of claims and disputes between stakeholders. Existing research falls …

Semiconductor Physics Based Signal Integrity Analysis For 3d Ic, Ze Sun

Doctoral Dissertations

"Three-dimensional integrated circuits (3DICs) are becoming increasingly popular in high-speed electrical systems. 3DICs are made by stacking multiple dies vertically and connecting them with through-silicon vias (TSVs). In this dissertation, three studies were carried out to model the performance of 3DICs in extreme working conditions and the signal integrity (SI) performance of 3DICs.

First, an in-house Monte Carlo particle simulator was developed to characterize extreme working conditions (ESD/EMP) for ICs at the microscopic level instead of the macroscopic level. The ability of the simulator was demonstrated by modeling a voltage regulator diode under forward and reverse bias. The diode simulation …

Non-Linearity Modeling And Quantifications For Practical Rf Interference Control, Shengxuan Xia

Doctoral Dissertations

"Radio frequency (RF) interference can degrade the receiving sensitivity of antennas (desense problem). It is essential to model the nonlinearity as it is the root-cause of the unwanted frequency components. Understanding the electromagnetic (EM) coupling or radiated emissions is also important.

Nonlinearity causes modulation-involved desense problems, and it consists of two categories: upconvertion of the baseband noise by the transmitting (TX) signal, and the passive intermodulation (PIM) of the transmitting signal itself. The upconvertion caused desense can be modeled and analyzed with the dipole-moment based coupling framework. PIM has been identified as another nonlinear distortion mechanism, specifically in the metallic …