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Full-Text Articles in Entire DC Network
Distributed Software Build Assurance For Software Supply Chain Integrity, Ken Lew, Arijet Sarker, Simeon Wuthier, Jinoh Kim
Distributed Software Build Assurance For Software Supply Chain Integrity, Ken Lew, Arijet Sarker, Simeon Wuthier, Jinoh Kim
Faculty Publications
Computing and networking are increasingly implemented in software. We design and build a software build assurance scheme detecting if there have been injections or modifications in the various steps in the software supply chain, including the source code, compiling, and distribution. Building on the reproducible build and software bill of materials (SBOM), our work is distinguished from previous research in assuring multiple software artifacts across the software supply chain. Reproducible build, in particular, enables our scheme, as our scheme requires the software materials/artifacts to be consistent across machines with the same operating system/specifications. Furthermore, we use blockchain to deliver the …
Diverse Disconnectedness: Homophily, Social Capital Inequality, And Student Experiences In Law School, Anthony Paik, Swethaa Ballakrishnen, Carole Silver, Steven Boutcher, Tanya Rouleau Whitworth
Diverse Disconnectedness: Homophily, Social Capital Inequality, And Student Experiences In Law School, Anthony Paik, Swethaa Ballakrishnen, Carole Silver, Steven Boutcher, Tanya Rouleau Whitworth
Faculty Publications
Law school students are encouraged frequently to “network.” However, depending on demographic categories, they may have access to differently resourced social networks in law school. In this article, we draw from our mixed-methods research to explore this diversity of experience, its limitations of access, and the possible network inequalities that may limit the value of legal education to diverse students across different institutional contexts. Using survey and network data (N = 744), collected during the fall of 2019 from three law schools, as well as supplementary interview data (N = 55), we examined students’ social networks, the structures of these …
Diverse Disconnectedness: Homophily, Social Capital Inequality, And Student Experiences In Law School, Anthony Paik, Swethaa Ballakrishnen, Carole Silver, Steven Boutcher, Tanya Rouleau Whitworth
Diverse Disconnectedness: Homophily, Social Capital Inequality, And Student Experiences In Law School, Anthony Paik, Swethaa Ballakrishnen, Carole Silver, Steven Boutcher, Tanya Rouleau Whitworth
Faculty Publications
Law school students are encouraged frequently to “network.” However, depending on demographic categories, they may have access to differently resourced social networks in law school. In this article, we draw from our mixed-methods research to explore this diversity of experience, its limitations of access, and the possible network inequalities that may limit the value of legal education to diverse students across different institutional contexts. Using survey and network data (N = 744), collected during the fall of 2019 from three law schools, as well as supplementary interview data (N = 55), we examined students’ social networks, the structures of these …
Adding The Third Dimension: 3d Convolutional Neural Network Diagnosis Of Temporal Lobe Epilepsy, Erik Kaestner, Reihaneh Hassanzadeh, Ezequiel Gleichgerrcht, Kyle Hasenstab, Rebecca W. Roth, Allen Chang, Theodor Rüber, Kathryn A. Davis, Patricia Dugan, Ruben Kuzniecky, Julius Fridriksson Ph.D., Alexandra Parashos, Anto I. Bagić, Daniel L. Drane, Simon S. Keller, Vince D. Calhoun, Anees Abrol, Leonardo Bonilha, Carrie R. Mcdonald
Adding The Third Dimension: 3d Convolutional Neural Network Diagnosis Of Temporal Lobe Epilepsy, Erik Kaestner, Reihaneh Hassanzadeh, Ezequiel Gleichgerrcht, Kyle Hasenstab, Rebecca W. Roth, Allen Chang, Theodor Rüber, Kathryn A. Davis, Patricia Dugan, Ruben Kuzniecky, Julius Fridriksson Ph.D., Alexandra Parashos, Anto I. Bagić, Daniel L. Drane, Simon S. Keller, Vince D. Calhoun, Anees Abrol, Leonardo Bonilha, Carrie R. Mcdonald
Faculty Publications
Convolutional neural networks (CNN) show great promise for translating decades of research on structural abnormalities in temporal lobe epilepsy into clinical practice. Three-dimensional CNNs typically outperform two-dimensional CNNs in medical imaging. Here we explore for the first time whether a three-dimensional CNN outperforms a two-dimensional CNN for identifying temporal lobe epilepsy-specific features on MRI. Using 1178 T1-weighted images (589 temporal lobe epilepsy, 589 healthy controls) from 12 surgical centres, we trained 3D and 2D CNNs for temporal lobe epilepsy versus healthy control classification, using feature visualization to identify important regions. The 3D CNN was compared to the 2D model and …
A Comparison Of Gaussian Processes And Polynomial Chaos Emulators In The Context Of Haemodynamic Pulse–Wave Propagation Modelling, L. Mihaela Paun, Mitchel J. Colebank, Dirk Husmeier
A Comparison Of Gaussian Processes And Polynomial Chaos Emulators In The Context Of Haemodynamic Pulse–Wave Propagation Modelling, L. Mihaela Paun, Mitchel J. Colebank, Dirk Husmeier
Faculty Publications
Computational modelling of the cardiovascular system is a promising future direction for patient-specific healthcare. However, the computational cost of these simulators is a bottleneck for their practical use in clinic for real-time digital twins. Emulation can overcome this, yet an extensive investigation into cardiovascular emulators is warranted. In this study, we emulate two one-dimensional haemodynamics models of the pulmonary circulation and compare two common emulation strategies: Gaussian processes (GPs) and polynomial chaos expansions (PCEs). We start by reducing the parameter space of the models through global sensitivity analysis, and then compare both emulation strategies using a multivariate, time-series output …
Aspect-Ratio-Dependent Heat Transport By Baroclinic Acoustic Streaming, Jacques Abdul Massih, Remil Mushthaq, Guillaume Michel, Gregory P. Chini
Aspect-Ratio-Dependent Heat Transport By Baroclinic Acoustic Streaming, Jacques Abdul Massih, Remil Mushthaq, Guillaume Michel, Gregory P. Chini
Faculty Publications
Standing acoustic waves have been known to generate Eulerian time-mean ‘streaming’ flows at least since the seminal investigation of Lord Rayleigh in the 1880s. Nevertheless, a recent body of numerical and experimental evidence has shown that inhomogeneities in the ambient density distribution lead to much faster flows than arise in classical Rayleigh streaming. The emergence of these unusually strong flows creates new opportunities to enhance heat transfer in systems in which convective cooling cannot otherwise be easily achieved. To assess this possibility, a theoretical study of acoustic streaming in an ideal gas confined in a rectangular channel with top and …
Aspect-Ratio-Dependent Heat Transport By Baroclinic Acoustic Streaming, Jacques Abdul Massih, Remil Mushthaq, Guillaume Michel, Gregory P. Chini
Aspect-Ratio-Dependent Heat Transport By Baroclinic Acoustic Streaming, Jacques Abdul Massih, Remil Mushthaq, Guillaume Michel, Gregory P. Chini
Faculty Publications
Standing acoustic waves have been known to generate Eulerian time-mean ‘streaming’ flows at least since the seminal investigation of Lord Rayleigh in the 1880s. Nevertheless, a recent body of numerical and experimental evidence has shown that inhomogeneities in the ambient density distribution lead to much faster flows than arise in classical Rayleigh streaming. The emergence of these unusually strong flows creates new opportunities to enhance heat transfer in systems in which convective cooling cannot otherwise be easily achieved. To assess this possibility, a theoretical study of acoustic streaming in an ideal gas confined in a rectangular channel with top and …
Closed-Loop Adaptive Optics In The Presence Of Speckle And Weak Scintillation, Derek J. Burrell, Mark F. Spencer, Ronald G. Driggers
Closed-Loop Adaptive Optics In The Presence Of Speckle And Weak Scintillation, Derek J. Burrell, Mark F. Spencer, Ronald G. Driggers
Faculty Publications
In this paper, we show that speckle averaging helps to improve adaptive-optics (AO) performance in closed loop as a result of reduced measurement error associated with a Shack–Hartmann wavefront sensor (SHWFS); however, this reduction is rendered ineffective with increasing beacon anisoplanatism. We do so operating in a weak-scintillation regime, where the SHWFS offers robust performance, and using in-plane translation of the illuminated rough surface to accomplish frame-to-frame speckle diversity. Understanding these trade-space limitations is critical when performing AO with non-cooperative, extended-source beacons.
Examination Of Photoinduced Radicals In Two Crystal Forms Of Triphenylamine Bis-Urea Macrocycles, Md Faizul Islam, Gamage Isuri P. Wijesekera, Anmon J. Sindt, Mark D. Smith, Linda S. Shimizu
Examination Of Photoinduced Radicals In Two Crystal Forms Of Triphenylamine Bis-Urea Macrocycles, Md Faizul Islam, Gamage Isuri P. Wijesekera, Anmon J. Sindt, Mark D. Smith, Linda S. Shimizu
Faculty Publications
This study probes two solvates of triphenylamine (TPA) bis-urea macrocycle 1 and their activated structures to evaluate their maximum photoinduced radicals (PIRs), the subsequent decay of the radicals, and their regeneration. The hierarchical assembly of TPAs shows promise in stabilizing less substituted derivatives, potentially expanding the utility of TPAs that lack stabilizing para-substituents. Single crystal structure analysis reveals that host 1 adopts a planar conformation with the two ureas pointing in opposite directions when dimethoxyethane (DME) is encapsulated within the channel. Whereas previously, 1 adopted a bowl-shaped conformation with the two ureas pointing in the same direction (syn …
Examination Of Photoinduced Radicals In Two Crystal Forms Of Triphenylamine Bis-Urea Macrocycles, Md Faizul Islam, Gamage Isuri P. Wijesekera, Ammon J. Sindt, Mark D. Smith, Linda S. Shimizu
Examination Of Photoinduced Radicals In Two Crystal Forms Of Triphenylamine Bis-Urea Macrocycles, Md Faizul Islam, Gamage Isuri P. Wijesekera, Ammon J. Sindt, Mark D. Smith, Linda S. Shimizu
Faculty Publications
This study probes two solvates of triphenylamine (TPA) bis-urea macrocycle 1 and their activated structures to evaluate their maximum photoinduced radicals (PIRs), the subsequent decay of the radicals, and their regeneration. The hierarchical assembly of TPAs shows promise in stabilizing less substituted derivatives, potentially expanding the utility of TPAs that lack stabilizing para-substituents. Single crystal structure analysis reveals that host 1 adopts a planar conformation with the two ureas pointing in opposite directions when dimethoxyethane (DME) is encapsulated within the channel. Whereas previously, 1 adopted a bowl-shaped conformation with the two ureas pointing in the same direction (syn …
A Quantitative Adverse Outcome Pathway For Embryonic Activation Of The Aryl Hydrocarbon Receptor Of Fishes By Polycyclic Aromatic Hydrocarbons Leading To Decreased Fecundity At Adulthood, Jon A. Doering, Justin Dubiel, Eric Stock, Cameron H. Collins, Ian Frick, Hunter M. Johnson, Christopher M. Lowrey-Dufour, Justin G.P. Miller, Zhe Xia, Gregg T. Tomy, Steve Wiseman
A Quantitative Adverse Outcome Pathway For Embryonic Activation Of The Aryl Hydrocarbon Receptor Of Fishes By Polycyclic Aromatic Hydrocarbons Leading To Decreased Fecundity At Adulthood, Jon A. Doering, Justin Dubiel, Eric Stock, Cameron H. Collins, Ian Frick, Hunter M. Johnson, Christopher M. Lowrey-Dufour, Justin G.P. Miller, Zhe Xia, Gregg T. Tomy, Steve Wiseman
Faculty Publications
Quantitative adverse outcome pathways (qAOPs) describe the response–response relationships that link the magnitude and/or duration of chemical interaction with a specific molecular target to the probability and/or severity of the resulting apical-level toxicity of regulatory relevance. The present study developed the first qAOP for latent toxicities showing that early life exposure adversely affects health at adulthood. Specifically, a qAOP for embryonic activation of the aryl hydrocarbon receptor 2 (AHR2) of fishes by polycyclic aromatic hydrocarbons (PAHs) leading to decreased fecundity of females at adulthood was developed by building on existing qAOPs for (1) activation of the AHR leading to early …
Prescribed Fire Regimes Influence Responses Of Fungal And Bacterial Communities On New Litter Substrates In A Brackish Tidal Marsh, Viet Q. Dao, Crystal N. Johnson, William J. Platt
Prescribed Fire Regimes Influence Responses Of Fungal And Bacterial Communities On New Litter Substrates In A Brackish Tidal Marsh, Viet Q. Dao, Crystal N. Johnson, William J. Platt
Faculty Publications
Processes modifying newly deposited litter substrates should affect fine fuels in fire-managed tidal marsh ecosystems. Differences in chemical composition and dynamics of litter should arise from fire histories that generate pyrodiverse plant communities, tropical cyclones that deposit wrack as litter, tidal inundation that introduces and alters sediments and microbes, and interactions among these different processes. The resulting diversity and dynamics of available litter compounds should affect microbial (fungal and bacterial) communities and their roles in litter substrate dynamics and ecosystem responses over time. We experimentally examined effects of differences in litter types produced by different fire regimes and litter loads …
Conducting Structure-From-Motion (Sfm) Modeling Of Freshwater Environments Using Unpiloted Aerial Systems (Uas): Challenges And Lessons Learned, Benjamin T. Fraser, Christine L. Bunyon, Russell G. Congalton
Conducting Structure-From-Motion (Sfm) Modeling Of Freshwater Environments Using Unpiloted Aerial Systems (Uas): Challenges And Lessons Learned, Benjamin T. Fraser, Christine L. Bunyon, Russell G. Congalton
Faculty Publications
The pairing of Unpiloted Aerial Systems (UAS) and Structure from Motion (SfM) has provided new capabilities for modeling freshwater environments. Applications of UAS-SfM range from water quality monitoring to the mapping of aquatic vegetation. The models produced provide users with the ability to analyze features at ultra-high-resolutions and across scales not easily achieved through in situ sampling. Despite the demonstrated benefits of UAS-SfM in freshwater and other natural resource disciplines, there remain fundamental technical challenges in the modeling of environments with homogenous surfaces (e.g., water). In this research, the effectiveness of several image collection and processing approaches for the modelling …
Technician Assignment In Multi-Shift Maintenance Schedules In An Offshore Wind Farm, Md Imran Hasan Tusar, Bhaba R. Sarker
Technician Assignment In Multi-Shift Maintenance Schedules In An Offshore Wind Farm, Md Imran Hasan Tusar, Bhaba R. Sarker
Faculty Publications
Offshore wind farms are becoming more and more important to sustainable energy strategies, yet their maintenance presents unique logistical challenges. The focus of this research is the Technician Assignment Problem (TAP) which involves a complicated and fluctuating scheduling problem. The key objective is to determine the most effective assignment of technicians to maintenance tasks to maximize operational efficiency and ensure reliable service. This study introduces a mathematical optimization model that processes numerous variables—technician availability, skill sets, and temporal constraints—to minimize unmet maintenance needs and ensure equitable workload distribution. The model is based on assumptions derived from actual operational conditions and …
Reframing And Advancing Academic Mentorship To Support New And Early Career Faculty Members, Juanita-Dawne R. Bacsu, Patricia C. Heyn, Steffi Kim, Zahra Rahemi, Monique J. Brown, Darina V. Petrovsky, Justine S. Sefcik, Jodi L. Southerland, Jeremy Holloway, Elyse Couch, Ayse Malatyali, Matthew L. Smith
Reframing And Advancing Academic Mentorship To Support New And Early Career Faculty Members, Juanita-Dawne R. Bacsu, Patricia C. Heyn, Steffi Kim, Zahra Rahemi, Monique J. Brown, Darina V. Petrovsky, Justine S. Sefcik, Jodi L. Southerland, Jeremy Holloway, Elyse Couch, Ayse Malatyali, Matthew L. Smith
Faculty Publications
Mentorship is critical to fostering professional growth and career development in academia. However, academic mentorship is often an informal activity that is overlooked and under researched. There is much ambiguity and uncertainty surrounding mentorship roles and strategies in academia. This paper provides recommendations and strategies to reframe and advance academic mentorship to support new and early career faculty.
Allura Red Ac Is A Xenobiotic. Is It Also A Carcinogen?, Lorne J. Hofseth Ph.D., James Hébert Scd, Elizabeth Angela Murphy, Erica Trauner, Athul Vikas, Quinn Harris, Alexander A. Chumanevich
Allura Red Ac Is A Xenobiotic. Is It Also A Carcinogen?, Lorne J. Hofseth Ph.D., James Hébert Scd, Elizabeth Angela Murphy, Erica Trauner, Athul Vikas, Quinn Harris, Alexander A. Chumanevich
Faculty Publications
Merriam-Webster and Oxford define a xenobiotic as any substance foreign to living systems. Allura Red AC (a.k.a., E129; FD&C Red No. 40), a synthetic food dye extensively used in manufacturing ultra-processed foods and therefore highly prevalent in our food supply, falls under this category. The surge in synthetic food dye consumption during the 70s and 80s was followed by an epidemic of metabolic diseases and the emergence of early-onset colorectal cancer in the 1990s. This temporal association raises significant concerns, particularly given the widespread inclusion of synthetic food dyes in ultra-processed products, notably those marketed toward children. Given its interactions …
Allura Red Ac Is A Xenobiotic. Is It Also A Carcinogen?, Lorne J. Hofseth, James R. Hébert Scd, Elizabeth Angela Murphy, Erica Trauner, Athul Vikas, Quinn Harris, Alexander A. Chumanevich
Allura Red Ac Is A Xenobiotic. Is It Also A Carcinogen?, Lorne J. Hofseth, James R. Hébert Scd, Elizabeth Angela Murphy, Erica Trauner, Athul Vikas, Quinn Harris, Alexander A. Chumanevich
Faculty Publications
Merriam-Webster and Oxford define a xenobiotic as any substance foreign to living systems. Allura Red AC (a.k.a., E129; FD&C Red No. 40), a synthetic food dye extensively used in manufacturing ultra-processed foods and therefore highly prevalent in our food supply, falls under this category. The surge in synthetic food dye consumption during the 70s and 80s was followed by an epidemic of metabolic diseases and the emergence of early-onset colorectal cancer in the 1990s. This temporal association raises significant concerns, particularly given the widespread inclusion of synthetic food dyes in ultra-processed products, notably those marketed toward children. Given its interactions …
Regulating Crypto Intermediaries, Eric D. Chason
Regulating Crypto Intermediaries, Eric D. Chason
Faculty Publications
Early 2024 produced a dramatic rebound in cryptocurrency markets as Bitcoin hit an all-time high price in March 2024. This surge was fueled in large part by judicial and regulatory action. After years of denials and a high-profile defeat in court, the U.S. Securities and Exchange Commission (SEC) finally approved the first exchange-traded funds (ETFs) for Bitcoin in January 2024. Many believe that these approvals will lead to a greater shift of investment funds into crypto. Crypto regulation is not, however, ready for this shift. While ETFs have clear treatment under current law, other institutions lack the same clarity or …
Innovation Challenges In The Air Force Sbir Program: From The Small Businesses' Perspective, Hart J. Holt, Amy M. Cox, Scott Drylie, David S. Long, Alfred E. Thal Jr., Robert D. Fass
Innovation Challenges In The Air Force Sbir Program: From The Small Businesses' Perspective, Hart J. Holt, Amy M. Cox, Scott Drylie, David S. Long, Alfred E. Thal Jr., Robert D. Fass
Faculty Publications
Every year the United States invests $3.2 billion in the Small Business Innovation Research (SBIR) program to promote innovation among the nation’s small businesses. Half of this investment is from the DoD. This research considers the challenges faced by small businesses innovating with the DoD, particularly those awarded SBIR contracts with the United States Air Force. The authors surveyed 286 unique small businesses that were previously awarded an Air Force SBIR contract. By asking the survey respondents open-ended questions and categorizing their responses, they pinpoint unaddressed challenges from the small business perspective. By categorizing survey responses through Qualitative Content Analysis, …
Production Box Cost Estimating Relationships For Dod Avionics, Carla J. Cisneros, Edward D. White, Brandon M. Lucas, Jonathan D. Ritschel, Robert D. Fass, Shawn M. Valentine
Production Box Cost Estimating Relationships For Dod Avionics, Carla J. Cisneros, Edward D. White, Brandon M. Lucas, Jonathan D. Ritschel, Robert D. Fass, Shawn M. Valentine
Faculty Publications
The authors use historical information obtained from the Cost Assessment Data Enterprise to estimate recurring production unit cost for DoD avionics via cost estimating relationships (CERs). The specific modeled responses include mean unit cost, median unit cost, and the 100th production unit cost (T100) utilizing learning curve theory. For T100, the authors adopt both a multiplicative and an additive error for CER comparison. Recommended CERs consist of the mean unit cost and the T100 utilizing a multiplicative error. Moreover, results reveal that weight has a significant effect on cost as well as a potential underaccounting of real price change or …
Real-Time Synthesis Of A Nonuniformly Correlated, Partially Coherent Beam Using An Optical Coordinate Tansformation, Milo W. Hyde Iv
Real-Time Synthesis Of A Nonuniformly Correlated, Partially Coherent Beam Using An Optical Coordinate Tansformation, Milo W. Hyde Iv
Faculty Publications
We design, build, and validate an optical system for generating light beams with complex spatial coherence properties in real time. Beams of this type self-focus and are resistant to turbulence degradation, making them potentially useful in applications such as optical communications. We begin with a general theoretical analysis of our proposed design. Our approach starts by generating a Schell-model (uniformly correlated or shift-invariant) source by spatially filtering incoherent light. We then pass this light through an optical coordinate transformer, which converts the Schell-model source into a nonuniformly correlated field. After the general analysis, we discuss system engineering, including trade-offs among …
Equipping Future Physicians With Artificial Intelligence Competencies Through Student Associations, Spencer Hopson, Carson Mildon, Kyle Hassard, Paul Urie, Dennis Della Corte
Equipping Future Physicians With Artificial Intelligence Competencies Through Student Associations, Spencer Hopson, Carson Mildon, Kyle Hassard, Paul Urie, Dennis Della Corte
Faculty Publications
Advances in artificial intelligence (AI) in the medical sector necessitate the development of AI literacy among future physicians. This article explores the pioneering efforts of the AI in Medicine Association (AIM) at Brigham Young University, which offers a framework for undergraduate pre-medical students to gain hands-on experience, receive principled education, explore ethical considerations, and learn appraisal of AI models. By supplementing formal, university-organized pre-medical education with a student-led, faculty-supported introduction to AI through an extracurricular academic association, AIM alleviates apprehensions regarding AI in medicine early and empowers students preparing for medical school to navigate the evolving landscape of AI in …
Accurate Crystal Structure Prediction Of New 2d Hybrid Organic–Inorganic Perovskites, Nima Karimitari, William J. Baldwin, Evan W. Muller, Zachary J.L. Bare, W. Joshua Kennedy, Gábor Csányi, Christopher Sutton
Accurate Crystal Structure Prediction Of New 2d Hybrid Organic–Inorganic Perovskites, Nima Karimitari, William J. Baldwin, Evan W. Muller, Zachary J.L. Bare, W. Joshua Kennedy, Gábor Csányi, Christopher Sutton
Faculty Publications
Low-dimensional hybrid organic–inorganic perovskites (HOIPs) are promising electronically active materials for light absorption and emission. The design space of HOIPs is extremely large, as a variety of organic cations can be combined with different inorganic frameworks. This not only allows for tunable electronic and mechanical properties but also necessitates the development of new tools for in silico high throughput analysis of candidate materials. In this work, we present an accurate, efficient, and widely applicable machine learning interatomic potential (MLIP) trained on 86 diverse experimentally reported HOIP materials. This MLIP was tested on 73 experimentally reported perovskite compositions and achieves a …
Flexible Operation Of Nuclear Hybrid Energy Systems For Load Following And Water Desalination, An Ho, Blake W. Billings, John Hedengren, Kody M. Powell
Flexible Operation Of Nuclear Hybrid Energy Systems For Load Following And Water Desalination, An Ho, Blake W. Billings, John Hedengren, Kody M. Powell
Faculty Publications
Nuclear hybrid energy systems (NHES) have the potential to provide dependable and emission-free electricity to the grid while also increasing the flexibility and reliability of the electrical grid. Molten salt reactor (MSR) technology can provide consistent, carbon-free electricity while also increasing efficiency, security, and sustainability and reducing nuclear waste. This study investigates the integration of Molten Salt Reactors (MSR) and conventional Pressurized Water Reactors (PWR) with desalination technologies: Direct Contact Membrane Distillation (DCMD), Multi-Stage Flash Distillation (MSFD), and Reverse Osmosis (RO). Dynamic first-principles models were developed and tested using real grid data from the New York Independent System Operator. The …
High-Fidelity Machine Learning Techniques For Driver Drowsiness Detection, Yasser Ismail, Ebenezer Essel, Abeer Abdelhamid, Mahmoud Darwich, Fahmi Khalifa, Fred Lacy
High-Fidelity Machine Learning Techniques For Driver Drowsiness Detection, Yasser Ismail, Ebenezer Essel, Abeer Abdelhamid, Mahmoud Darwich, Fahmi Khalifa, Fred Lacy
Faculty Publications
It is devastating that daily, there is an ample number of car crashes that cause damage to automobiles, onboard passengers get injured, and others tend to lose their lives. Road crashes are fast rising across the globe and have drawn many road safety commissions and concerned individuals to discuss ways to reduce this menacing situation drastically. With the introduction of artificial intelligence and technological advancement, the government and state commissions have beckoned on the various universities and research institutions to develop methods to curb the rise of automobile crashes. Some causes of these crashes include drunk driving and drowsiness, the …
The Evaluation Of Machine Learning Techniques For Isotope Identification Contextualized By Training And Testing Spectral Similarity, Aaron P. Fjelsted, Tyler J. Morrow, Clayton D. Scott, Yilun Zhu, Darren E. Holland, Azaree T. Lintereur, Douglas E. Wolfe
The Evaluation Of Machine Learning Techniques For Isotope Identification Contextualized By Training And Testing Spectral Similarity, Aaron P. Fjelsted, Tyler J. Morrow, Clayton D. Scott, Yilun Zhu, Darren E. Holland, Azaree T. Lintereur, Douglas E. Wolfe
Faculty Publications
Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset …
Neurosymbolic Cognitive Methods For Enhancing Foundation Model-Based Reasoning, Kaushik Roy, Siyu Wu, Alessandro Oltramari
Neurosymbolic Cognitive Methods For Enhancing Foundation Model-Based Reasoning, Kaushik Roy, Siyu Wu, Alessandro Oltramari
Faculty Publications
Foundation models have emerged as powerful tools, exhibiting extraordinary performance across various tasks, such as language processing, visual recognition, code generation, and human-centered engagement. However, recent studies have highlighted their limitations when grounded, abstract, and generalized reasoning capabilities are required. Complex tasks often involve multiple hierarchical reasoning steps, which are typical features of human thinking processes. In fact, in this chapter we claim that cognitively-inspired computational models, such as the so-called Common Model of Cognition, are key to enable complex reasoning within foundation model-based artificial intelligence (AI) systems. We investigate neurosymbolic approaches for mapping AI system components to those of …
Malware Classification Through Abstract Syntax Trees And L-Moments, Anthony J. Rose, Christine M. Schubert Kabban, Scott R. Graham, Wayne C. Henry, Christopher M. Rondeau
Malware Classification Through Abstract Syntax Trees And L-Moments, Anthony J. Rose, Christine M. Schubert Kabban, Scott R. Graham, Wayne C. Henry, Christopher M. Rondeau
Faculty Publications
The ongoing evolution of malware presents a formidable challenge to cybersecurity: identifying unknown threats. Traditional detection methods, such as signatures and various forms of static analysis, inherently lag behind these evolving threats. This research introduces a novel approach to malware detection by leveraging the robust statistical capabilities of L-moments and the structural insights provided by Abstract Syntax Trees (ASTs) and applying them to PowerShell. L-moments, recognized for their resilience to outliers and adaptability to diverse distributional shapes, are extracted from network analysis measures like degree centrality, betweenness centrality, and closeness centrality of ASTs. These measures provide a detailed structural representation …
Model Predictive Control Of A Grid-Scale Thermal Energy Storage System In Relap5-3d, Jaron Wallace, John Hedengren, Kody Powell, Matthew Memmott
Model Predictive Control Of A Grid-Scale Thermal Energy Storage System In Relap5-3d, Jaron Wallace, John Hedengren, Kody Powell, Matthew Memmott
Faculty Publications
This research delves into the integration and control of a Thermal Energy Storage (TES) system with a Small Modular Reactor (SMR), specifically the NuScale VOYGR SMR module in RELAP5-3D. The research methodology centered on modeling the NuScale VOYGR SMR, a light water pressurized water reactor (LWR) with a power output capacity of 77 MWe per module. The reactor and plant details were sourced from NuScale's final safety analysis report and supplemented by information from the NuScale website. The SMR plays a crucial role in energy generation, and to manage and dispatch the produced energy effectively, a robust storage system …
Coarse-Gridded Simulation Of The Nonlinear Schrödinger Equation With Machine Learning, Benjamin F. Akers, Kristina O. F. Williams
Coarse-Gridded Simulation Of The Nonlinear Schrödinger Equation With Machine Learning, Benjamin F. Akers, Kristina O. F. Williams
Faculty Publications
A numerical method for evolving the nonlinear Schrödinger equation on a coarse spatial grid is developed. This trains a neural network to generate the optimal stencil weights to discretize the second derivative of solutions to the nonlinear Schrödinger equation. The neural network is embedded in a symmetric matrix to control the scheme’s eigenvalues, ensuring stability. The machine-learned method can outperform both its parent finite difference method and a Fourier spectral method. The trained scheme has the same asymptotic operation cost as its parent finite difference method after training. Unlike traditional methods, the performance depends on how close the initial data …