Digital Commons Network^™

Microfluidic Paper-Based Device Coupled With 3d Printed Imaging Box For Colorimetric Detection In Resource-Limited Settings, Vijay Vaishampayan, Oinam Robita Chanu, Balasubramanian Sivasamy, Muthamilselvi Ponnuchamy, Varshini Karthik, Ambar Pendharkar, Lohith Srinivas Thotakura, Aryan Prabhu, Venkatesan Dhananjeyan, Ashish Kapoor

Faculty, Staff and Student Publications

Rapid and effective methods for the detection of analytes such as water contaminants, food adulterants and biomolecules are essential for the protection of public health and environmental protection. Most of the currently established analytical techniques need sophisticated equipment, centralized testing facilities, costly operations, and trained personnel. Such limitations make them inaccessible to the general populace, particularly in regions with limited resources. The emergence of microfluidic devices offers a promising alternative to overcome several such constraints. This work describes a protocol for fabricating a low-cost, open-source paper-based microfluidic device using easily available tools and materials for colorimetric detection of analytes. The …

Making Waves: Integrating Wastewater Surveillance With Dynamic Modeling To Track And Predict Viral Outbreaks, Tin Phan, Samantha Brozak, Bruce Pell, Jeremiah Oghuan, Anna Gitter, Tao Hu, Ruy M Ribeiro, Ruian Ke, Kristina D Mena, Alan S Perelson, Yang Kuang, Fuqing Wu

Faculty, Staff and Student Publications

Wastewater surveillance has proved to be a valuable tool to track the COVID-19 pandemic. However, most studies using wastewater surveillance data revolve around establishing correlations and lead time relative to reported case data. In this perspective, we advocate for the integration of wastewater surveillance data with dynamic within-host and between-host models to better understand, monitor, and predict viral disease outbreaks. Dynamic models overcome emblematic difficulties of using wastewater surveillance data such as establishing the temporal viral shedding profile. Complementarily, wastewater surveillance data bypasses the issues of time lag and underreporting in clinical case report data, thus enhancing the utility and …

Use Of Compartmental Modeling And Retinol Isotope Dilution To Determine Vitamin A Stores In Young People With Sickle Cell Disease Before And After Vitamin A Supplementation, Jennifer Lynn Ford, Michael H Green, Jefferson N Brownell, Joanne Balmer Green, Anthony Oxley, Georg Lietz, Joan I Schall, Virginia A Stallings

Faculty, Staff and Student Publications

BACKGROUND: Suboptimal plasma retinol concentrations have been documented in US children with sickle cell disease (SCD) hemoglobin SS type (SCD-HbSS), but little is known about vitamin A kinetics and stores in SCD.

OBJECTIVES: The objectives were to quantify vitamin A total body stores (TBS) and whole-body retinol kinetics in young people with SCD-HbSS and use retinol isotope dilution (RID) to predict TBS in SCD-HbSS and healthy peers as well as after vitamin A supplementation in SCD-HbSS subjects.

METHODS: Composite plasma [

RESULTS: Model-predicted group mean TBS for subjects with SCD-HbSS was 428 μmol, equivalent to ∼11 mo of stored vitamin …

Evaluation Of Novel Ai Architectures For Uncertainty Estimation, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja

Computer Science: Faculty Publications and Other Works

Deep learning (DL) has become a cornerstone for advancements in computer vision, yielding models capable of remarkable performance on complex visual tasks. Despite these achievements, there remains a critical need for accurate uncertainty estimations, especially when models encounter out-of-distribution (OOD) inputs. Addressing this, our research focuses on the implementation and evaluation of uncertainty techniques in two prominent DL architectures: Convolutional Neural Networks (CNN) and Vision Transformers (ViT). These architectures were applied specifically to computer vision tasks, utilizing the MNIST and ImageNet-1K datasets for our evaluations.

High-Performance Computing (HPC) platforms, pivotal to this research, were employed to assess these techniques. The …

Empowering Foot Health: Harnessing The Adaptive Weighted Sub-Gradient Convolutional Neural Network For Diabetic Foot Ulcer Classification, Abdullah Alqahtani, Shtwai Alsubai, Mohamudha Parveen Rahamathulla, Abdu Gumaei, Mohemmed Sha, Yu-Dong Zhang, Muhammad Attique Khan

School of Podiatric Medicine Publications

In recent times, DFU (diabetic foot ulcer) has become a universal health problem that affects many diabetes patients severely. DFU requires immediate proper treatment to avert amputation. Clinical examination of DFU is a tedious process and complex in nature. Concurrently, DL (deep learning) methodologies can show prominent outcomes in the classification of DFU because of their efficient learning capacity. Though traditional systems have tried using DL-based models to procure better performance, there is room for enhancement in accuracy. Therefore, the present study uses the AWSg-CNN (Adaptive Weighted Sub-gradient Convolutional Neural Network) method to classify DFU. A DFUC dataset is considered, …

Interpersonal Behavior In Assessment Center Role-Play Exercises: Investigating Structure, Consistency, And Effectiveness, Simon M. Breil, Filip Lievens, Boris Forthmann, Mitla D. Back

Research Collection Lee Kong Chian School Of Business

Although the behaviors displayed by assessees are the currency of assessment centers (ACs), they have remained largely unexplored. This is surprising because a better understanding of assessees' behaviors may provide the missing link between research on the determinants of assessee performance and research on the validity of performance ratings. Therefore, this study draws on behavioral personality science to scrutinize the behaviors that assessees express in interpersonal AC exercises. Our goals were to investigate (a) the structure of interpersonal behaviors, (b) the consistency of these behaviors across AC exercises, and (c) their effectiveness. We obtained videotaped performances of 203 assessees who …

A Review Of Smart Structures Vibration Control Strategies, Imad Z. Gheni, Hm Alwan2, Hussein M. Khafaji

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The expert system and artificial intelligence are still important modern technologies. A structure can modify its behavior under dynamic stresses by using active controls. The term "intelligent" or "smart" structures refers to these self-modifying structures. The structural engineering discipline may experience a reVolution thanks to smart structure technologies. Particularly for huge structures, It is anticipated to have major effects. Effects with regard to the avoidance of fatalities and damage to the structure and its contents, particularly with regard to huge buildings that have thousands of elements. An efficient control algorithm to establish the magnitude of the actual forces to be …

A Comparative Study Between The Fragile And Robust Watermarking Techniques And Proposing New Fragile Watermarking With Embedded Value Technique, Yasmin A. Hassan, Abdul Monem

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Since the Internet has been more widely used and more people have access to multimedia content, copyright hacking, and piracy have risen. By the use of watermarking techniques, security, asset protection, and authentication have all been made possible. In this paper, a comparison between fragile and robust watermarking techniques has been presented to benefit them in recent studies to increase the level of security of critical media. A new technique has been suggested when adding an embedded value (129) to each pixel of the cover image and representing it as a key to thwart the attacker, increase security, rise imperceptibility, …

Police Officers’ Perspectives On The Death Of George Floyd By Minneapolis Police Officers: A Descriptive Study, Janet Henderson

Electronic Theses and Dissertations

On May 25, 2020, four Minneapolis police officers reported to the location where an African American man had been accused of trying to use a counterfeit $20 bill in a convenience store. After being taken outside of the store, the man, George Floyd, was eventually placed in the back of a police patrol car, after he was handcuffed. Saying he was claustrophobic and resisting arrest, Mr. Floyd was removed from the patrol car, and placed on the ground on his stomach. One of the patrol officers, the most senior officer present, and a field training officer, placed his knee on …

0883: John O'Brien Collection, 1547-2017, Marshall University Special Collections

Guides to Manuscript Collections

This collection of O’Brien materials includes a large number of CDV, stereo card, and photograph images of prominent individuals from the nineteenth century, various locations in the United States and Europe, and Confederate military and political leaders. Other items include wartime and postwar broadsides, election tickets, pamphlets, and newspapers. There are two photographs signed by Jefferson Davis and letters from Shelby Foote and Douglas Southall Freeman. In addition to the manuscript and photograph materials, the collection includes a number of rare books, with the earliest published in 1546.

Leveraging Galois Theory And Computational Results In The Search For Legendre Pairs, David M. Arquette

Theses and Dissertations

With applications spanning myriad disciplines, Hadamard matrices have tremendous utility. Infinitely many have been discovered, but there is no general proof of their existence. Proving the Hadamard conjecture would provide a significant technological edge. Hadamard matrices are difficult to construct in general; however, they can be created directly from Legendre pairs (LPs). While LPs are not trivial to find, a breakthrough in this area would be pivotal in the quest to prove the Hadamard conjecture. Most recent efforts rely upon refined search algorithms, and we seek to either develop a better such algorithm or discover an altogether new theoretical construction. …

Steady State Thermal Blooming With Convection: Modeling, Simulation And Analysis, Jeremiah S. Lane

Theses and Dissertations

The modeling, simulation, and analysis of high energy laser propagation is a research topic of significant interest to the defense community. A detailed understanding of the phenomenon of thermal blooming is crucial as it is detrimental to the propagation of lasers over long distances and in the presence of aerosols. The simulation of thermal blooming has historically relied on wave optics models and scaling laws for the fluid response to the laser. Since thermal blooming occurs in the presence of natural convection, however, there is a need for simulating this coupled fluid-beam effect using a first principles approach. In this …

Advanced Statistical Methodology For The Modern Probability Of Detection, Christine E. Knott

Theses and Dissertations

Probability of detection (POD) is an invaluable part of the calculations used by the USAF to validate the capabilities of nondestructive inspection systems for detecting defects in critical structural components on aircraft. A POD study consists of a designed experiment, linear modeling, and a probability of detection verses defect size curve. This curve is useful for determining how often an aircraft should be re-inspected. Some POD studies are unsuccessful in creating realistic POD curves because the statistical modeling used has two common limitations: (1) a lack of convergence leading to no solution and, (2) violated assumptions leading to incorrect solutions. …

Numerical Simulation Of Nonlinear Wave Equations With Machine Learning, Kristina O. F. Williams

Theses and Dissertations

A machine learning procedure is proposed to create numerical schemes for solutions of certain types of nonlinear wave equations on coarse grids. This method trains stencil weights of a discretization of the equation, with the truncation error of the scheme as the objective function for training. A neural network is used as a model for the stencil weights. The method uses centered finite differences to initialize the optimization routine and a second-order implicit-explicit time solver as a framework. Symmetry conditions are enforced on the learned operator to ensure a stable method. The procedure is applied to the Korteweg - de …

Methods Of Evaluating Quantum Phase Estimation Circuit Output, Charles A. Woodrum

Theses and Dissertations

The quantum phase estimation (QPE) algorithm is one of the most important quantum computing algorithms that has been developed. The QPE algorithm estimates the phase or phases of the eigenvalue or eigenvalues of a unitary operator. It is a critical step for applications like Shor’s algorithm for factoring and the HHL algorithm for solving linear systems of equations, but it remains difficult to implement on current quantum computers due to small numbers of logical qubits and high error rates. This investigation derives a more accurate estimation of the phase of a unitary operator than would otherwise be attained with the …

Analysis Of Multi-Agent Routing Solution Methodologies Exploring A Mosaic Warfare Strategy, Stephen D. Donnel

Theses and Dissertations

Recognizing that communication between assets may be possible locally but not globally (e.g., due to disruptions to a communication network), Mosaic Warfare requires the movement and operation of multiple, dispersed assets in smaller groups (i.e., tiles), within which exist hierarchical, functional relationships between assets. This research first evaluates a heuristic for an enterprise of aerial assets comprised of airborne sensors, command and control, and strike aircraft seeking to move towards and destroy stationary targets. Next, we examine routing multiple assets of different types over a network to service demands in a collaborative manner, in that, when servicing a demand, …

Advances In Quaternion-Valued Neural Networks, Jeremiah P. Bill

Theses and Dissertations

This dissertation investigates the construction, optimization, and application of quaternion neural networks (QNNs) to Department of Defense (DoD) related problem sets. QNNs are a type of neural network wherein the weights, biases, and input values are all represented as quaternion numbers. This work provides a critical evaluation of the myriad different quaternion backpropagation derivations that exist in the literature, testing the performance of each on a range of regression problem sets. The optimization dynamics of QNNs are explored, presenting visualizations of QNN loss surfaces and a novel method for assessing the “smoothness” of these loss surfaces. Finally, this dissertation presents …

Refining Contract Management: Essays On Relational Contracting, Transaction Costs, And Text Analysis, Timothy E. Landucci

Theses and Dissertations

This dissertation refines defense contracting by addressing aspects of managing contractual relationships. While the setting and data relate to defense contracts, the lessons can be expanded to nonprofit contracting beyond defense and even to contract management in general. First it presents a game theoretic model of a relational contract between a for-profit supplier and a non-profit buyer and explores how the model could be used to promote stability, manage costs, enhance cooperation, and encourage long-term capacity. The dissertation then explores governance alignment using transaction cost economics (TCE) and Department of the Air Force contracting data. One analysis uses data from …

Improving Deep Reinforcement Learning Methodology For Autonomous Defense And Escort Of Military High-Value Assets, Joseph Liles Iv

Theses and Dissertations

This dissertation explores the application of machine learning to the control of autonomous unmanned combat aerial vehicles (AUCAVs). In particular, this research applies deep reinforcement learning methodologies to a defensive air combat scenario wherein a fleet of AUCAVs protects a military high-value asset (HVA). A collection of air battle management scenarios along with an original simulation environment and a set of designed computational experiments support the approximation of high-quality decision policies by employing Markov decision processes, approximate dynamic programming algorithms, and deep neural networks for value function approximation.

Network Vulnerability Identification For The Material Routing Problem, Carson G. Long

Theses and Dissertations

This dissertation considers the importance of identifying spatiotemporal vulnerabilities in ground distribution networks and uses operations research methods to formulate models that allow military logistic planners to implement prevention and mitigation measures regarding the routing of personnel, equipment, and supplies in contested Areas of Responsibility (AOR). For optimization models relating to identifying spatiotemporal network vulnerabilities in distribution networks, this work leverages game theory, mixed-integer programming, multi-objective optimization, and metaheuristics to inform mitigation measures for shipment routing. This research has three related components: the first component develops a multi-objective mathematical program to identify spatiotemporal vulnerabilities via myopic heuristic identification, in combination …

Test Problem Generation And Metaheuristic Selection For The Multidemand Multidimensional Knapsack Problem, Matthew E. Scherer

Theses and Dissertations

This work focuses on instance generation methods for the multi-demand multidimensional knapsack problem (MDMKP). Specifically, instance space analysis (ISA) is used to characterize the landscape of existing instances and validate the novelty of new instances generated with a novel problem generation method, the primal problem instance generator (PPIG). The instance generator is capable of producing feasible, diverse, and challenging instances by directly controlling the problem features. PPIG contributes to the previous collections of instances and is validated through instance space analysis. The research presents an in-depth empirical evaluation of existing solution procedures for the MDMKP. The portfolio of metaheuristics examined …

Analysis Of Coronal Magnetic Field Parameters During X- And M-Class Solar Flares, Seth H. Garland

Theses and Dissertations

Using Non-Linear Force Free Field (NLFFF) extrapolation, 3D magnetic fields were modeled from the 12-minute cadence Helioseismic and Magnetic Imager (HMI) photospheric vector magnetograms, spanning a time period of one hour before through one hour after the start of 18 X-class flares and 12 M-class flares. Several magnetic field parameters were calculated from the modeled fields directly – as well as from the power spectrum of surface maps generated by summing the fields along the vertical axis – for two different regions: areas with photospheric Bz ≥ 300 G (Active Region – AR) and areas above the photosphere with the …

Brdf Measurements And Physical Optics Modeling Applied To Anisotropic Satellite Solar Cells, Madilynn E. Compean

Theses and Dissertations

Light curve analysis is often used to discern information about satellites in geosynchronous orbits, and since solar panels comprise relatively large surface areas, their reflected energy can contribute greatly to observed light curves. Data was collected using a space qualified solar cell interrogated by a green HeNe laser. The data validated certain aspects from previous work, but also identified multi-slit behavior, showed that the specular term was a second diffraction pattern, and diagnosed the out-of-plane diffraction curvature as the conical diffraction phenomenon. Two physical-optics-based models were developed to incorporate these new features and better predict solar cell BRDF solely from …

Improving And Evaluating Performance Of The Proton Prediction System Through An Expanded Solar Proton Event Catalog, Samantha R. Howard

Theses and Dissertations

Solar energetic particles (SEPs) are especially high energy protons (≥ 5 or 10MeV kinetic energies) originating from the Sun that are known to have significant effects on space-based military operations. The Air Force’s current forecast model, the Proton Prediction System (PPS), forecasts less than half of SEP events that are observed, motivating the need for an update to the operational model. To develop the updated PPS model, PPS2.0, an expanded SEP catalog was produced, which includes 103 previously unidentified events and specification of the proton flux response above background levels or prior events. Event detection and source association were initially …

Quantifying Atmospheric Turbulence Effects On Image Quality Using A Deconvolution Algorithm, Ahmad M. Almalki

Theses and Dissertations

Imaging through turbulence is affected by several factors including imaging system specifications, imaging system setup and more importantly the atmospheric turbulence as it is uncontrollable. One important parameter which is used to quantify the atmospheric turbulence severity is the atmospheric coherence diameter (��₀ ), known as Fried's parameter. This thesis explores ways to characterize the atmospheric turbulence effects on image quality using simulated and laboratory generated turbulence where ��₀ is estimated using a maximum a posteriori (MAP) estimator and frequency domain analysis algorithms. Furthermore, image quality metrics such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM) …

An Analytical Framework For Photonic Storage And Retrieval: Implications For Quantum Optical Networks, Billie V. Deluca

Theses and Dissertations

Quantum information and communication is the next revolution in information technology. However, communication through quantum networks will require the ability to transmit, store, and interact with photonic quantum bits (qubits). The focus of this dissertation is a theoretical description of a promising technology for storage of photonic states employing electromagnetically induced transparency (EIT). A general semiclassical model for EIT photonic storage will be developed, a key capability required for understanding the effect of storage that is independent of the photonic state being stored. This dissertation demonstrates the capability of this model to predict light pulses retrieved from EIT storage as …

Pattern-Of-Life Modeling With Automatic Dependent Surveillance-Broadcast (Ads-B), Sarah J. Bolton

Theses and Dissertations

This dissertation and research were sponsored by the Air Force Research Laboratory Layered Sensing Exploitation Branch (AFRL/RYA) to investigate the utility of using the data found within aircraft secondary radar to make predictions about aircraft characteristics and intent. The research focuses on making predictions on aircraft characteristics using only the kinetic data within one type of secondary radar, Automatic Dependent Surveillance-Broadcast (ADS-B), as a surrogate for primary radar. The results from this research provide a means to reduce the reliance on a type of aircraft tracking that is vulnerable to cyber attack and other integrity concerns.

Atmospheric Propagation Of Qubits: Laboratory Experiments To Field Demonstrations, Keith A. Wyman

Theses and Dissertations

Free-space quantum networks can enable global-scale quantum communication via satellite-based nodes and quantum ground transceivers. To enable building of robust global quantum networks, it is critical to learn how the state of the qubit is transformed while propagating through the atmosphere. With such an overarching goal, we built a laboratory based atmospheric turbulence simulator (ATS) to characterize the effects of atmospheric turbulence on an entangled pair of photons as a function of statistical quantities such as the Fried parameter or scintillation index for long-distance communication. Specifically, the changes in the statistical properties associated with a quantum source was investigated using …

Quiet, But Not Silent: Uncovering Quiescent State Properties Of Two Transient High-Mass X-Ray Binaries, Gayathri Raman, Pragati Pradhan, Jamie Kennea

Publications

We present the first set of broad-band spectral and timing studies of two transient X-ray pulsars, MXB 0656 −072 and MAXI J1409 −619 using NuSTAR observations conducted during quiescence. Despite being captured at one of their lowest luminosity states, both these targets show signs of ongoing low-level accretion. Results from the time-averaged spectral analysis indicate for the first time, the presence of a strong soft power-law component along with thermal emission from the neutron star hotspots. For both targets, the quiescent thermal X-ray emission is consistent with the deep crustal heating model. In MXB 0656 −072, we do not detect …

What Is The Best Way To Develop A Website?, Nahomy Julieta Calderon Lopez

Theses

This project is centered around empowering individuals with the knowledge and resources necessary for effective website development. The culmination of Thesis/Directed Project II is a user-friendly website designed to distill and present the insights gathered during Thesis/Directed Project I. This website features an engaging interactive quiz, aimed to help the users identify what is the best way, for them, to develop a website. The quiz has multiple questions, each with three distinct response options, the quiz guides users towards one of three key approaches for website development: Website Builders, Content Management System platforms, or Coding. Upon receiving their quiz results, …