Digital Commons Network^™

Global Sporadic-E Prediction And Climatology Using Deep Learning, J. A. Ellis, Daniel J. Emmons, M. B. Cohen

Faculty Publications

Sporadic-E (E_s) is an ionospheric phenomenon defined by strong layers of plasma which may interfere with radio wave propagation. In this work, we develop deep learning models to improve the understanding of E_s, including the presence, intensity and height of the layers. We developed three separate models. The first, building off earlier work in (J. A. Ellis et al., 2024, link in AFIT Scholar, 10.1029/2023sw003669), includes only the main features from radio occultation (RO) measurements. The second adds to that time, date, location, geomagnetic and solar indices, solar winds, x-ray flux, weather and lightning. A …

A Risk Evaluation Framework And Comprehensive Security Compliance Assessment Solution For Space Information Networks (Sin), Bernard Afaare Dawaare

Masters Theses & Doctoral Dissertations

The integration of Internet of Things (IoT) devices into space information networks introduces unprecedented security challenges, necessitating advanced methods for information systems risk assessments. Some proposed approaches in terrestrial networks, predominantly based on Euclidean distance metrics, often fall short of capturing the nuanced and multidimensional nature of risks and vulnerabilities in the unique context of space environments. This paper proposes a novel risk management methodology that leverages both Euclidean distance metrics and probabilistic Monte Carlo-based models for evaluating the likelihood/frequency and impact/severity of vulnerabilities within space IoT systems. Leveraging vulnerability data from established sources such as the NIST and VARIoT …

Predicting Cardiac Resynchronization Therapy Response: Development And Validation Of A Single Photon Emission Computed Tomography-Based Nomogram, Zhongwei Jiang, Zhongqiang Zhao, Zhuo He, Qiushi Chen, Ju Bu, Chunxiang Li, Dianfu Li, Chang Cui, Weihua Zhou, Huiyuan Qin, Cheng Wang

Michigan Tech Publications

Background: Cardiac resynchronization therapy (CRT) is an effective treatment for patients with drug-refractory heart failure. However, more than thirty percent of patients do not benefit from CRT. This study aimed to develop and validate a novel model based on single photon emission computed tomography (SPECT) phase analysis features to predict CRT response. Methods: We identified 163 CRT patients who received gated resting SPECT myocardial perfusion imaging (MPI) between 2010 and 2020 at The First Affiliated Hospital of Nanjing Medical University. All variables were first processed by univariate logistic regression, and those with a P value < 0.05 were retained. The selected variables were subsequently used in the least absolute shrinkage and selection operator (LASSO) regression to construct a predictive model, which was then represented as a nomogram. Nomogram performance was assessed via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analyses (DCAs). Internal validation was performed by bootstrapping with 1,000 replicates. Results: Of the 163 patients, 93 (57.1%) responded to CRT during follow-up. Responders had a wider QRS complex duration (QRSd) (164.80 vs. 154.51 ms, P=0.003), fewer premature ventricular contractions (PVCs) (1,392.98 vs. 2,283.60, P=0.003), lower prevalence of non-sustained ventricular tachycardia (NS-VT) (45.2% vs. 77.1%, P< 0.001), and better cardiac function [based on N-terminal pro-B-type natriuretic peptide (NT-proBNP), New York Heart Association (NYHA), and left ventricle (LV) parameters] compared to non-responders. Univariate logistic regression revealed 14 variables significantly associated with CRT response (all P< 0.05). The area under the ROC curve (AUC) value for the nomogram was 0.845 [95% confidence interval (CI): 0.785–0.906; sensitivity: 0.771; specificity: 0.849]. Internal validation yielded a mean AUC of 0.814 (95% CI: 0.777–0.836). The calibration curve demonstrated strong consistency between the predicted and observed outcomes. DCA revealed that the nomogram consistently provides a net benefit over the baseline, demonstrating its high practical value in clinical decision-making. A web-based dynamic nomogram (https:// jzw20000624.shinyapps.io/CRTpredictionmodel/) was developed for clinical application. Conclusions: We developed and validated a SPECT-based prediction model for predicting CRT response, which can assist clinicians in optimizing CRT candidacy preoperatively. Pacing at the latest contraction and relaxation segments, while avoiding scarred regions and optimizing preoperative status, is anticipated to improve CRT response.

Trust And Success: Franchisee Perspective On Relational Trust With The Franchisor And Impact On Unit Growth, Giovannie M. Hoff

Electronic Theses and Dissertations

Abstract

The problem addressed in this study was that it is unknown how franchisees perceive trust and its influence on unit growth and contractual control within the franchisor and franchisee relationship. The purpose of this case study was to explore the franchisee’s perspective of trust within the franchisor and franchisee relationship and its impact on growth and contractual control. A qualitative case study approach was used, with data collected from 13 participants from one franchise organization in the United States through semistructured interviews and questionnaire. Data were transcribed, coded, and analyzed thematically, with triangulation and member-checking ensuring credibility. Two key …

Melanaphis Sacchari/Sorghi Complex: Current Status, Challenges And Integrated Strategies For Managing The Invasive Sap-Feeding Insect Pest Of Sorghum, Alejandro Vasquez, Joseph Belsky, Neetu Khanal, Heena Puri, Devi Balakrishnan, Neelendra K. Joshi, Joe Louis, Glenn Studebaker, Rupesh Kariyat

School of Integrative Biological & Chemical Sciences (Formerly Dept. of Biology)

Melanaphis sacchari (Zehntner;Hemiptera: Aphididae), sugarcane aphid (SCA), is an invasive phloem-feeder found worldwide with a wide host range of economically important plants including sorghum and sugarcane. Given its high reproductive capacity and ability to rapidly spread over long distances, SCA presents challenges for effective control, leading to substantial economic losses. Recent studies have identified two multiloci SCA genotypes specialized in feeding on sugarcane (MLL-D) and sorghum (MLL-F) in the USA, which raises concerns as the USA is the second largest sorghum-producing country. This has encouraged research towards identifying these two biotypes where some research has stated them as two species; …

Exploring The Biasing Effects Of Gender On Personality Disorder Diagnoses Formulated By Artificial Intelligence, Zoe Colclough

Student Theses

Gender bias is prevalent in personality disorder assessments, and while artificial intelligence has been posited as a solution to improve diagnostic objectivity and accuracy, the potential for such technologies to propagate human gender bias in mental health contexts remains underexplored. This study investigated the influences of gender bias on the diagnostic performance of ChatGPT-4o for personality disorders using three factorial research designs, which involved experimentally manipulating patient gender in a combined sample of 360 vignettes and case studies. Vignettes were synthesized through a novel artificial intelligence-assisted methodology established for this research, and case studies were identified from the literature. Significant …

Relationship Between Local Fiscal Effort And High School Graduation Rate, Zachary Michael Haney

Educational Leadership & Workforce Development Theses & Dissertations

Education is an investment in human capital, but the cost to provide this public service is significant. Understanding the return on this investment is essential for informed and effective financial decision-making. While previous school finance studies have examined the relationship between funding and various indicators of student achievement and student attainment, most have focused on spending practices rather than the level of investment itself. Although the literature affirms the need for educational resources, further research is required to determine which types of investment most positively affect student outcomes. Therefore, funding must be analyzed prior to budgetary allocation to evaluate its …

Shades Of Families: Exploring Intersectionalities Of Cross-Cultural Parenting Experiences In The U.S., Shu-Han Huang

Dissertations

As multiracial and multicultural families continue to grow across the United States, parents must navigate evolving cultural identities, systemic inequities, and increasing social and emotional pressures. These realities underscore the need for parenting resources that are both culturally responsive and emotionally supportive. This transcendental phenomenological study explored the lived experiences of 11 cross-cultural parents raising children in the U.S., with a focus on how intersecting identities and systemic forces shape parenting practices.

Guided by Critical Multiracial Theory and Intersectionality Theory, this study investigated parenting at the personal, familial, societal, and structural levels. Data were collected through semi-structured interviews and analyzed …

Improving Home Security Through User Centered Device Positioning, Lalith Nadipalli

Theses and Dissertations

In today’s world, where technology is advancing rapidly and security threats are becoming more complex, the need for effective home safety measures is more critical than ever. Homeowners are increasingly turning to a variety of smart devices, such as smoke detectors, carbon monoxide detectors, and security cameras, to protect their living spaces against potential dangers like burglary, fire, and environmental hazards. These devices offer essential protection, acting as both early warning systems and visual surveillance tools. However, their effectiveness largely hinges on how well they are placed within the home. Proper placement of these safety devices ensures that they provide …

C-Band Air To Ground Communication System For Uav, Mubark Alghamdi

Theses and Dissertations

C band spectrum 5030-5091 MHz is allocated for command-and-control communication services with unmanned aircraft systems. This document evaluates the possibility of using 3GPP 5G standards for provisioning of such services. Channelization of the spectrum and major system parameters are proposed. The performance of the proposed system in channel fading environment is evaluated using MATLAB based simulations. The evaluations examine SINR, and average throughput of the proposed system at different altitudes of the unmanned aircraft system. MATLAB simulations are used to evaluate system performance in free-space environments. Signal-to-Interference-plus-Noise Ratio (SINR) and Reference Signal Received Power (RSRP) are predicted at different UAS …

Developing End-To-End Imitation Learning For Asteroid Proximity Operations, Patrick David Quinn

Theses and Dissertations

Asteroid exploration remains a popular topic in the scientific community, however hurdles still exist for controlling spacecraft within the asteroid environment. Communication delays often require the usage of limited onboard computing hardware for navigation. Additionally, long mission timelines must be accommodated with highly efficient fuel use. Considering these issues, it is apparent that any guidance, navigation, and control (GNC) system in these spacecraft should emphasize both computational and fuel efficiency in its design. Furthermore, the integration of a robust state estimation system is necessary for the successful deployment of such systems. The development of a controller aiming to address these …

Advancing Precision And Autonomy In Agriculture And Medical Imaging Through Ai And Computer Visions, Tan-Hanh Pham

Theses and Dissertations

Deep learning has revolutionized numerous fields by enhancing precision, automation, and decision-making capabilities. This dissertation explores its applications in agriculture and medical image processing, introducing novel methodologies to improve accuracy and efficiency in these domains. These fields hold critical societal importance -- agriculture underpins global food security and sustainability, while medical imaging drives advancements in diagnostics and personalized healthcare, both benefiting significantly from data-driven innovations. In agriculture, deep learning is applied to precision spray systems through droplet analysis. Specifically, a generative model is designed to create synthetic droplet images, addressing the challenge of limited training samples, which are expensive …

Cross-Dataset Fairness Evaluation Of Transformer-Based Sentiment Models, Sara Zuiran

Theses and Dissertations

With the growing exploration of Natural Language Processing (NLP) systems in decision-making environments, it is essential to evaluate technical and ethical aspects of the dataset and the NLP model to improve fairness. To assess fairness, the thesis examines demographic imbalances in sentiment classification models by evaluating transformer-based models fine-tuned on the Stanford Sentiment Treebank version 2 dataset (SST-2) against the demographically annotated Comprehensive Assessment of Language Model dataset (CALM). This work identifies performance disparities in sentiment prediction across demographic groups by examining sensitive attributes such as gender and race. The study evaluates both the RoBERTa and MentalBERT transformer models using …

Bridging The Gap: Enhancing Devops Security Through Comprehensive Threat Modeling, Ashutosh Jagdish Sonar

Theses and Dissertations

Today, security is an essential component of software development, especially in DevOps environments where rapid and continuous product release cycles are common. Systems are vulnerable to new attacks because traditional security approaches often cannot keep up with the pace of change. The threat modeling approaches used in DevOps are examined in this thesis, along with their advantages, disadvantages, and suitability for use in current software development processes. Well-known frameworks including STRIDE (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service (DoS), and Elevation of Privilege), Attack Trees, LINDDUN (Linking, Identifying, Non-Repudiation, Detecting, Data Disclosure, Unawareness, and Non-Compliance.), Practical Threat Analysis (PTA), …

Stochastic Analysis With Operational Calculus In Reliability, Hend Hamdan Al-Jahani

Theses and Dissertations

Our dissertation models several reliability systems subject to occasional random shocks of random magnitudes W1,W2,..occurring at times tau0, tau2,..In Model 1, the underlying system becomes inoperational if it wears out due to aging specified by a monotone increasing continuous function Delta identifying system's wear at any time t>=0 . The system is deemed inoperational if delta crosses a sustainability threshold at some moment T=(delta )^-1(D). The precise time T is difficult to identify making the realistic failure time randomly delayed and thus identified at some opportune observation epoch. The system can also fail due to damages by external shocks, …

The Prototype Of A Fully Automated Pressuremeter For Various Geotechnical Applications, Anuar Akchurin

Theses and Dissertations

The geotechnical engineering field requires high-quality in-situ testing equipment that ensures consistency in the test execution. This research focuses on developing and testing a prototype of a fully automated pressuremeter control unit to allow the industry to obtain reliable and controlled stress-strain data, thereby improving efficiency and reducing testing time.

The objectives of this work are to design and develop a system with the necessary components to perform the pressuremeter test, integrate the testing procedure into the state machine design, enable automated testing, and validate the results by comparing the stress-strain data with that obtained from the existing hand-operated pressuremeter …

Alternative Robust Design Formulation And Exploration Strategies For Managing Uncertainties In The Realization Of Complex Engineering Systems, Pooja Mukundan

Theses and Dissertations

The design of complex engineered systems often relies on simulation-based models, which inherently introduce uncertainties. Managing these uncertainties is critical to ensure robust system performance. From a decision-based design (DBD) perspective, robust design metrics such as the Design Capability Index (DCI) and Error Margin Index (EMI) are employed to formulate and solve problems under uncertainty. However, existing formulations of these metrics rely on first-order Taylor series approximations for variance estimation, which are often inadequate in the presence of highly nonlinear or multimodal performance functions.

This thesis proposes alternate formulations of DCI and EMI, which use the multiple-point method of variance …

Trends In And Factors Associated With Science Achievement Among Fourth Graders In Saudi Arabia: A Secondary Analysis Of Timss Data, Reda Massawe

Theses and Dissertations

This secondary analysis examined trends and factors associated with science achievement among fourth-grade students in Saudi Arabia using data from the Trends in International Mathematics and Science Study (TIMSS). Between 2007 and 2019, Saudi students consistently scored below the international average in science, with female students outperforming males by more than 30 points. The study addressed two issues: (1) reasons behind Saudi students’ underperformance and (2) limited research on contributing factors. TIMSS data from 2011, 2015, and 2019 were analyzed using descriptive, correlational, and regression methods. While trends across the years were explored, only 2019 data were used for detailed …

Trends In And Factors Associated With Science Achievement Among Eighth Graders In Saudi Arabia: A Secondary Analysis Of Timss Data, Roba Alzahrani

Theses and Dissertations

This secondary analysis examined trends in and factors influencing science achievement among eighth-grade students in Saudi Arabia, using data from the Trends in International Mathematics and Science Study (TIMSS). However, Saudi Arabia's performance on the TIMSS science assessments fell below the international average, from 2003 through 2019. In addition, gender differences in science achievement have been observed, with female students outperforming male students by 30 or more points. This study addresses two problems: factors associated with the lower performance of Saudi students on TIMSS science assessments compared to global standards, and the small number of studies which explored factors which …

Co-Designing Manufacturing Systems For Robustness And Resilience: A Decision-Based Design Perspective, Mathew Baby

Theses and Dissertations

Manufacturing systems (MSs) comprise various stakeholders associated with the manufacture and supply of products required by customers and are interrelated by the flow of materials and information. The interrelated stakeholders make system-specific decisions and stakeholder-specific decisions across multiple levels of a decision hierarchy to satisfy many conflicting system-specific and stakeholder-specific requirements that define system and stakeholder performances. Given the stakeholder interrelations and conflicting nature of system-specific and stakeholder-specific requirements, system and stakeholder performances are correlated and conflicting.

In the Industry 5.0 era, there is an increased emphasis on the creation and equitable distribution of value among all the stakeholders in …

Autonomous Defect Detection In Additive Manufacturing, John Samuel Poindexter Iv

Theses and Dissertations

Additive manufacturing (AM) is the process of creating a product by applying layers of material to build up to the final product. AM has revolutionized the field of manufacturing and has allowed more complex products to be manufactured at reasonable cost, quicker manufacturing time, and optimized material usage. Traditional forms of manufacturing were based on subtractive manufacturing, where by a product would be created by removing material from its source. AM is a new manufacturing process and faces significant challenges when it comes to manufacturing due to defects. Defects can vary from type and severity and can overall weaken or …

Does The Transit Industry Understand The Risks Of Cybersecurity And Are The Risks Being Appropriately Prioritized?, Scott F. Belcher, Terri Belcher, James Grimes, Lusa Holmstrom, Andy Souders

Mineta Transportation Institute

The intent of this study is to assess the readiness, resourcing, and capabilities of public transit agencies to detect, identify, be protected from, respond to, and recover from cybersecurity vulnerabilities and threats. This study is an update of the 2020 Mineta Transportation Institute (MTI) study, “Is the Transit Industry Prepared for the Cyber Revolution? Policy Recommendations to Enhance Surface Transit Cyber Preparedness.” In the previous study, the authors found that the transit industry was ill-prepared for cybersecurity attacks. Unfortunately, after four years and the development of new, and often free, resources, the situation has not markedly improved. In fact, this …

Brain Morphometry In Infants Later Diagnosed With Autism Is Related To Later Language Skills, Luke E Moraglia, Kelly N Botteron, Natasha Marrus, Et Al.

2020-Current year OA Pubs

Autism spectrum disorder (ASD) presents early in life with distinct social and language differences. This study explores the association between infant brain morphometry and language abilities using an infant-sibling design. Participants included infants who had an older sibling with autism (high likelihood, HL) who were later diagnosed with autism (HL-ASD; n = 31) and two non-autistic control groups: HL-Neg (HL infants not diagnosed with autism; n = 126) and LL-Neg (typically developing infants who did not have an older sibling with autism; n = 77). Using a whole-brain approach, we measured cortical thickness and surface area at 6 and 12 …

Political Threads In Legal Tapestry: A Computational Analysis Of Executive Branch Legal Interpretation, 1934–2022, Reilly S. Steel

Faculty Scholarship

How does the push and pull between law and politics shape the work of executive branch lawyers charged with providing “neutral” interpretations of the law? To shed light on this longstanding question, this Article undertakes the first large-scale computational analysis of legal interpretation in the executive branch of the United States federal government. Using a new dataset comprised of the texts of 12,879 pages of opinions issued by the Office of Legal Counsel (OLC) in the Department of Justice (DOJ), I use machine learning methods to explore markers of partisanship and ideology in these high-profile executive branch decisions.

Several important …

A Pure Rotational Spectroscopic Study Of Two Nearly-Equivalent Structures Of Hexafluoroacetone Imine, (Cf3)C=Nh, Daniel A. Obenchain, Beppo Hartwig, Daniel J. Frohman, Garry S. Grubbs, B. E. Long, Wallace C. Pringle, Stewart E. Novick, S. A. Cooke

Chemistry Faculty Research & Creative Works

Rotational spectra for hexafluoroacetone imine, the singly substituted 13C isotopologues, and the 15N isotopologue, have been recorded using both cavity and chirped pulse Fourier transform microwave spectrometers. The spectra observed present as being doubled with separations between each pair of transitions being on the order of a few tens of kilohertz which is consistent with a large amplitude motion producing two torsional substates. The observed splitting is most likely due to the combined motions of the CF₃ groups, for which the calculated barrier is small. However, no transitions between states could be observed and, similarly, no Coriolis coupling parameters …

Aircraft Routing And Crew Pairing Solutions: Robust Integrated Model Based On Multi-Agent Reinforcement Learning, Chengjin Ding, Yuzhen Guo, Jianlin Jiang, Wenbin Wei, Weiwei Wu

Faculty Research, Scholarly, and Creative Activity

Every year, airlines invest considerable resources in recovering from irregular operations caused by delays and disruptions to aircraft and crew. Consequently, the need to reschedule aircraft and crew to better address these problems has become pressing. The airline scheduling problem comprises two stages—that is, the Aircraft-Routing Problem (ARP) and the Crew-Pairing Problem (CPP). While the ARP and CPP have traditionally been solved sequentially, such an approach fails to capture their interdependencies, often compromising the robustness of aircraft and crew schedules in the face of disruptions. However, existing integrated ARP and CPP models often apply static rules for buffer time allocation, …

Temporal Reversibility Of Reactive Systems Out Of Equilibrium: Molecular Dynamics Simulation, O. Politano, Alejandro L. Garcia, F. Baras, M. Malek Mansour

Faculty Research, Scholarly, and Creative Activity

The second law of thermodynamics states that entropy production in macroscopic systems is non-negative, reaching zero only at thermodynamic equilibrium. As a corollary, this implies that the state trajectory of macroscopic systems is inherently time-irreversible under out-of-equilibrium conditions. However, over the past half-century, various studies have shown that this principle does not universally apply to the composition sample paths of certain isothermal reactive systems. Theoretical frameworks leading to this surprising observation primarily focus on perfectly homogeneous systems (often referred to as zero-dimensional systems), which inherently exclude the effects of local fluctuations. This oversimplification may account for the paradoxical theoretical predictions. …

Efficient Fully Bayesian Approach To Brain Activity Mapping With Complex-Valued Fmri Data, Zhengxin Wang, Daniel B. Rowe, Xinyi Li, D. Andrew Brown

Mathematical and Statistical Science Faculty Research and Publications

Functional magnetic resonance imaging (fMRI) enables indirect detection of brain activity changes via the blood-oxygen-level-dependent (BOLD) signal. Conventional analysis methods mainly rely on the real-valued magnitude of these signals. In contrast, research suggests that analyzing both real and imaginary components of the complex-valued fMRI (cv-fMRI) signal provides a more holistic approach that can increase power to detect neuronal activation. We propose a fully Bayesian model for brain activity mapping with cv-fMRI data. Our model accommodates temporal and spatial dynamics. Additionally, we propose a computationally efficient sampling algorithm, which enhances processing speed through image partitioning. Our approach is shown to be …

Development Of Saddlepoint Methodologies For Sparse Sample Multiple Parameter Generalized Linear Models And Correlated Data Scenarios, Christopher Johnson

All Graduate Theses and Dissertations, Fall 2023 to Present

Parameter estimation using maximum likelihood techniques may be biased when sample sizes are small, event rates are low, or otherwise sparse counts exist in a parametric model. This in turn may lead researchers to draw invalid statistical conclusions when conventional methods are utilized. The saddlepoint approximation has potential to lessen the degree of bias in sparse data conditions through its use of moments beyond the mean and variance, which allows for more accurate approximations using a smaller number of observations. We propose two novel saddlepoint methods for use in practical analysis scenarios, as an alternative to maximum likelihood estimation. First, …

Learning Intentions, Success Criteria, And Metacognition: The Influence Of A Professional Development For Grades Three To Five Teachers, Jason Hart

All Graduate Theses and Dissertations, Fall 2023 to Present

Formative assessment is a strategy that teachers use to improve student learning. This study explored how professional development focused on assessment for learning practices (AFL), with the main emphasis on learning intentions and success criteria, influences teacher use of those strategies and changes in teacher and student metacognition. The overarching research question was: How does professional development on AFL practices influence teachers' reported use of AFL practices and teacher and student metacognition? This study utilized a mixes-methods research design and provided professional development on AFL practices to 16 in-service elementary mathematics teachers and measured changes to their AFL practices and …