Digital Commons Network^™

Enhancing Risk And Crisis Communication With Computational Methods: A Systematic Literature Review, Madison H. Munro, Ross J. Gore, Christopher J. Lynch, Yvette D. Hastings, Ann Marie Reinhold

VMASC Publications

Recent developments in risk and crisis communication (RCC) research combine social science theory and data science tools to construct effective risk messages efficiently. However, current systematic literature reviews (SLRs) on RCC primarily focus on computationally assessing message efficacy as opposed to message efficiency. We conduct an SLR to highlight any current computational methods that improve message construction efficacy and efficiency. We found that most RCC research focuses on using theoretical frameworks and computational methods to analyze or classify message elements that improve efficacy. For improving message efficiency, computational and manual methods are only used in message classification. Specifying the computational …

From Cyclones To Cybersecurity: A Call For Convergence In Risk And Crisis Communications Research, Ann Marie Reinhold, Ross J. Gore, Barry Ezell, Clemente I. Izurieta, Elizabeth A. Shanahan

VMASC Publications

Effective risk and crisis communication can improve health and safety and reduce harmful effects of hazards and disasters. A robust body of literature investigates mechanisms for improving risk and crisis communication. While effective risk and crisis communication strategies are equally desired across different hazard types (e.g., natural hazards, cyber security), the extent to which risk and crisis communication experts utilize the “lessons learned” from scientific domains outside their own is suspect. Therefore, we hypothesized that risk and crisis communication research is siloed according to academic disciplines at the detriment to the advancement of the field of risk communications research writ …

Age Of Information-Based Optimal Scheduling With Energy Cost Trade-Off For Smart Warehouse: A Deep Reinforcement Learning-Based Approach, Sandip Roy, Abhishek Bisht, Ashok Kumar Das, Sachin Shetty

VMASC Publications

Recent advances in the integration of high-speed mobile networks and real-time IoT devices have facilitated in building of smart warehouses, where a set of beacons and Internet of Things (IoT) devices (or source nodes) can monitor the status of various physical processes in a time-critical way. In real-time status monitoring systems, like smart warehouses, quantifying the freshness of the Internet of Things (IoT) data based on the age of information (AoI) metrics becomes quite crucial. As source nodes are battery-constrained, a balanced trade-off between AoI minimization and preservation of source node battery energy is essential. In this paper, in a …

Quantum-Augmented Ai/Ml For O-Ran: Hierarchical Threat Detection For Synergistic Intelligence And Interpretability, Tan Le, Vanessa Le, Sachin Shetty

VMASC Publications

Open Radio Access Networks (O-RAN) enhance modularity and telemetry granularity but also widen the cybersecurity attack surface across disaggregated control, user and management planes. We propose a hierarchical defense framework with three coordinated layers—anomaly detection, intrusion confirmation, and multiattack classification—each aligned with O-RAN’s telemetry stack. Our approach integrates hybrid quantum computing and machine learning, leveraging amplitude- and entanglement-based feature encodings with deep and ensemble classifiers. We conduct extensive benchmarking across synthetic and real-world telemetry, evaluating encoding depth, architectural variants, and diagnostic fidelity. The framework consistently achieves near-perfect accuracy, high recall, and strong class separability. Multi-faceted evaluation across decision boundaries, probabilistic …

Master Of Social Work Portfolio: Rooted In Community, Whitney Wb Pratt

Graduate Student Portfolios, Professional Papers, and Capstone Projects

No abstract provided.

Cultivating A Community-Based Food System In Western Montana, Elaina Lamphere

Graduate Student Portfolios, Professional Papers, and Capstone Projects

No abstract provided.

A Critical Juncture: The Convergence Of Natural Resource Management And Tribal Sovereignty, Anna Aleta Butterfield

Graduate Student Portfolios, Professional Papers, and Capstone Projects

This portfolio reflects the work I’ve done in my four years as a dual degree student, pursuing a Master of Science in Environmental Studies and a juris doctorate degree, and focuses on policies and laws surrounding natural resource management. It touches on how those policies relate to and expand or constrict the exercise of sovereignty by indigenous populations.

This piece first considers the effects of plastic on salmon populations and those indigenous groups that rely on salmon for subsistence and cultural purposes. The remaining three pieces focus on various aspects of the Confederated Salish and Kootenai Tribes - Montana Water …

Daughter Of A Lost Bird, Susan J. Schwidde

Graduate Student Portfolios, Professional Papers, and Capstone Projects

No abstract provided.

An Adaptive Sampling Strategy On Optimal Takeoff Trajectory Prediction Of Electric Drones, Dheeraj Paramkusham, Samuel Sisk, Jiachen Wang, Shuan Tai Yeh, Xiaosong Du, Nathan Roberts

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft transforms future transportation systems by alleviating transportation congestion on the ground. This eVTOL technique possesses unique features, including reduced noise, low pollutant emissions, efficient operating costs, and flexible maneuverability. Meanwhile, battery consumption poses critical challenges to flight task duration. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimization, however, iteratively evaluates high fidelity simulation models, making the design process computationally intensive. In this work, we implement a machine learning-enabled inverse mapping optimization concept, i .e., directly predicting optimal design based on design requirements (including …

Phase-Variation Microwave Resonator For Highly Sensitive Dynamic Sensing, Chen Zhu, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

High-precision dynamic sensing is critical in fields, such as industrial automation, structural health monitoring, and environmental sensing, where real-time responses to minuscule changes can prevent system failures or optimize performance. In this work, we introduce and demonstrate a phase-variation coaxial cable resonator (CCR) as a highly sensitive sensor for dynamic sensing applications. As a proof of concept, a prototype device based on a custom-designed CCR is thoroughly investigated for dynamic displacement measurements, as displacement is a fundamental quantity essential to numerous applications. The sensor consists of two components: a static CCR device and a movable conducting plate. As the conducting …

Adaptive Nussbaum Design For Nonholonomic Systems With Asymptotic Stabilization Against False Data Injection, Guilong Liu, Yongliang Yang, Weinan Gao, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This article addresses the stabilization challenges of nonholonomic systems under the threat of false data injection (FDI) attacks, which compromise the integrity of state information. A novel adaptive control strategy using Nussbaum-type gains is proposed to ensure the asymptotic stability of the closed-loop system while maintaining signal boundedness. The approach extends conventional Nussbaum designs to handle multiple unknown control directions. It integrates online learning mechanisms to mitigate the impact of FDI attacks. Additionally, adaptive backstepping and fuzzy-logic systems are utilized to approximate and compensate for unknown nonlinear dynamics. The methodology transforms nonholonomic systems into equivalent cascade structures to address inherent …

An Extensive Analysis Of Match-Tracking Methods For Artmap, Niklas M. Melton, Leonardo Enzo Brito Da Silva, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper identifies and studies five match-tracking (MT) methods in the adaptive resonance theory (ART) literature and conducts a detailed comparative analysis of these in ARTMAP applications. We focus on model performance for each MT method with respect to time and space efficiency as well as classification accuracy. Experimental results indicate that one MT variant, used in ARTMAP applications for the first time in this work, provides significant improvements in computational efficiency: depending on the ARTMAP variant, it was able to achieve up to one order of magnitude reduction in both time and space requirements, albeit with a compromise in …

A Data-Driven Adaptive Control Approach For Enhancing The Dynamic Response Ff Vsgs In Varying Grid Conditions, Shah Fahad, Buxin She, Junjie Yin, Fangxing Li, Hantao Cui, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Conventionally, a virtual synchronous generator (VSG) is designed for islanded mode (IM) operation to meet specific operational requirements such as the rate of change of frequency (RoCoF). However, the operation of VSG designed for IM may not meet the operational and control criteria in grid connected mode (GCM) when the grid conditions vary. In addition, conventional VSG control technology does not consider the influence of the presynchronization scheme when connected to a weak grid, which degrades the RoCoF in IM. To overcome the aforementioned challenges, the proposed study presents a twin-delayed deep deterministic policy gradient (TD3) algorithm to improve the …

Understanding Students' Decision To Proceed With Hybrid Education: Examining The Post-Covid-19 Scenario, Heng Zhang

Master's Theses and Doctoral Dissertations

Hybrid education—integrating online and in-person instruction—has become a prominent educational model in the post-COVID-19 educational landscape. While prior research has examined the benefits and challenges of hybrid learning, as well as general acceptance patterns through frameworks such as the technology acceptance model and the theory of planned behavior, critical gaps remain in identifying the factors shaping students’ behavioral intentions toward this educational model. This study addresses these gaps by analyzing the interplay of external variables (such as prior hybrid learning experience, employment status, course type, commute time, and work-family balance) and socio-demographic attributes (such as age, gender, academic program and …

Autoregressive Neural Quantum States Of Fermi Hubbard Models, Eduardo Ibarra-García-Padilla, Hannah Lange, Roger G. Melko, Richard T. Scalettar, Juan Carrasquilla, Annabelle Bohrdt, Ehsan Khatami

Faculty Research, Scholarly, and Creative Activity

Neural quantum states (NQSs) have emerged as a powerful ansatz for variational quantum Monte Carlo studies of strongly correlated systems. Here, we apply recurrent neural networks (RNNs) and autoregressive transformer neural networks to the Fermi-Hubbard and the (non-Hermitian) Hatano-Nelson-Hubbard models in one and two dimensions. In both cases, we observe that the convergence of the RNN ansatz is challenged when increasing the interaction strength. We present a physically motivated and easy-to-implement strategy for improving the optimization, namely, by ramping of the model parameters. Furthermore, we investigate the advantages and disadvantages of the autoregressive sampling property of both network architectures. For …

A Self-Sustaining Autonomous System For Long-Term Arctic Monitoring, Wenqiang Xu

Electronic Theses and Dissertations 2020 - Present

The accelerated melting of Arctic sea ice poses critical challenges to global climate stability, marine ecosystems, and navigation safety. To address the need for continuous, high-resolution monitoring of the Arctic environment, this dissertation explores the development and feasibility of a Self-sustaining Autonomous System (SAS) for long-term Arctic observation. The proposed system is designed to overcome the limitations of traditional fixed or drifting buoys, as well as the range and endurance constraints of drones and Autonomous Underwater Vehicle (AUV)s, by utilizing a Small Waterplane Area Twin Hull (SWATH) Unmanned Surface Vehicle (USV) as a core observation platform. The wind-powered SWATH harnesses …

Meta’S Ai Bias To What Extent Do Meta's Algorithmic Processes For Classifying And Processing Information Related To Acts Of Racism Impact Fairness, Bias, And Social Justice Across Its Platforms?, Shanique Foster

Electronic Theses and Dissertations 2020 - Present

Algorithmic processing and classification of racism-related content have become increasingly prevalent across Meta's platforms. While these algorithms aim to create safer online environments, their effectiveness and impact on fairness remain understudied. This research examines how Meta's algorithmic processes for classifying racist content affect fairness, bias, and social justice across Facebook, Instagram, and WhatsApp.

Using qualitative research methodology, the study conducted focus groups with diverse platform users to understand their experiences with content moderation. The research also analyzed theoretical frameworks related to algorithmic bias, fairness metrics, and social justice in digital spaces.

Key findings revealed significant variations in algorithmic effectiveness across …

Phenotype Specific Nuclear Lamina Remodeling In Hipsc Derived Cardiomyocytes Bearing Tnnt2 Sarcomeric Variants, Isabella Leite Coscarella, Olalekan H. Usman, Lili Wang, Maicon Landim-Vieira, Lillian Wirstiuk, Amber N. Brown, Diego A. R. Zorio, Brian K. Washburn, Cynthia Vied, Bjorn C. Knollmann, Christopher Solís, Vitold E. Galkin, P. Bryant Chase, J. Travis Hinson, Jerome Irianto, Jose Renato Pinto

Department of Biomedical and Translational Sciences Faculty Publications

[Summary] Cardiomyocytes endure physical stress from the myocardium environment while generating their own mechanical strains. The force generated by sarcomeres is transmitted both longitudinally to adjacent sarcomeres and laterally to the cytoskeleton via intermediate filaments. This mechanical stimulus impacts other organelles, including the nucleus, thus playing a vital role in sensing and signaling nuclear adaptations. However, there is limited understanding of how changes in cardiac contractility affect nuclear mechanics. Here, we sought to investigate the effects of hyper- and hypo-contractility in nuclei of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) bearing TNNT2 pathogenic variants associated with hypertrophic (HCM) or dilated …

Saferespirator: Comprehensive Database For N95 Filtering Facepiece Respirator Leak Detection Including Infrared, Rgb Videos, And Quantitative Fit Testing, Geoffrey Marchais, Mohamed Arbane, Barthelemy Topilko, Jean Brousseau, Clothilde Brochot, Yacine Yaddaden, Ali Bahloul, Xavier Maldague

Études primaires

The COVID-19 pandemic underscored the challenges of performing mandatory Quantitative Fit Tests (QNFT) for healthcare professionals and the limitations of self-administered fit checks. To address this, it is crucial to develop faster and more efficient methods for detecting, locating, and quantifying leaks in Filtering Facepiece Respirators (FFRs), providing wearers with immediate feedback on their safety. Infrared (IR) technology, which relies on temperature variation analysis around the face seal, has proven effective for locating leaks but has not yet achieved automated quantification. This paper introduces a validated protocol for creating a comprehensive database to advance automatic leak detection. The database includes …

Effect Of A Back-Support Exoskeleton On Internal Forces And Lumbar Spine Stability During Low Load Lifting Task, Amir Hossein Eskandari, Farshid Ghezelbash, Aboulfazl Shirazi-Adl, Navid Arjmand, Christian Larivière

Études primaires

This study assessed the effect of a small-torque generating passive back-support exoskeleton during a low demanding occupational task, namely a repetitive lifting/lowering of an empty crate between the knee and shoulder heights. A comprehensive set of outcomes was considered, ranging from the measured trunk muscle activation and trunk movement to the estimated muscle group forces/coordination, spine loading and spine stability, using a dynamic subject-specific EMG-assisted musculoskeletal model. The exoskeleton decreased back muscle activation and corresponding muscle forces in the lowering phase and reduced spinal loading at larger trunk flexion angles (decreased peak compression and shear forces by ∼ 15%). However, …

Performance-Based Approach To Characterize External Sulfate Attack For Reactive Powder Concrete, Umut Bakhbergen, Chang Seon Shon, Dichuan Zhang, Jong Ryeol Kim, Jenny Liu

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Reactive powder concrete (RPC) is a relatively new type of high-performance concrete, offering enhanced load-bearing capacity, mechanical strength, and durability. The enhanced microstructural density of RPC with the incorporation of reinforcing fibers significantly increases its resistance to durability challenges, particularly against external sulfate attack (ESA). However, conventional laboratory testing methods for evaluating the resistance of RPC to ESA are limited. Hence, a new performance-based approach was developed to evaluate the durability of RPC exposed to ESA. Expansion of nine RPC mixtures designed by Taguchi L9 orthogonal array method with four factors (steel fiber content, water-to-binder ratio (w/b), silica fume content, …

Machine Learning And Artificial Intelligence Models And Techniques In Modern Power Grid Communication Architecture, Majid Jamal Majid Salim Almheiri

Theses

Smart grid is evolving in different phases and artificial intelligence (AI) models are also the part of it. In the recent developments of Smart grid system there are research areas which are left unaddressed specifically in privacy techniques, scalability, more efficient data processing techniques. This Thesis highlights the research gaps on smart grid development across various integration phases. In the initial phase of Smart grid development, challenges included scalability issues in Machine-to-Machine (M2M) communication, communication delays affecting voltage stabilization and high computational costs in implementing Genetic Algorithm (GA)-based grid state estimation are covered in this review report. Review is further …

Detecting Wireless Security Threats Through Ieee 802.11 Frame Field Anomalies, Aria Young

Williams Honors College, Honors Research Projects

It is not uncommon for most public spaces to offer Wi-Fi, while it is convenient and affordable, there are significant security risks due to its open nature. Rogue access points pose a security threat to many networks because they have the potential to bypass security measures and intercept traffic containing sensitive information. The attempt to formulate a method that one hundred percent guarantees the detection of a rogue access point has proven to be an intricate and complex problem for many to tackle, as there are numerous ways a rogue access point can be configured. This project aims to demonstrate …

Design And Development Of A Rapid Tensile Quench Rig, Tyler Jewell, Justin Naylor

Williams Honors College, Honors Research Projects

This report outlines the design process and implantation of a tensile quenching rig that incorporated forced convection and a frequency generator. When any metal is quenched, a vapor barrier forms around it. When this happens, it limits the heat flux that may occur until the barrier turns into just nucleate boiling. The vapor barrier acts as an insulator and causes the heat flux to fluctuate, causing uneven hardening which would limit the use of some materials. To combat this effect, we are trying to use forced convection, and something new, which is adding high frequency waves into the quenching process. …

Cognitive Fatigue Detection Using Photoplethysmography (Ppg) And Reaction Time Data, Anhar Sami Mohammed, Prajoy Podder, Maciej Jan Zawodniok, Cihan Dagli

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a framework for real-time cognitive fatigue detection among shift workers using an integrated approach that combines photoplethysmography (PPG) data and reaction time analysis with advanced deep learning models, including Long Short-Term Memory (LSTM) networks and Feedforward Neural Networks (FNNs). The system leverages heart rate variability (HRV) and reaction time data to identify fatigue indicators. The results demonstrate significant performance, with the first FNN model achieving a test accuracy of 98.94% and a loss of 0.2928, while the second FNN model achieved the same accuracy with a slightly higher loss of 0.3089. The LSTM model, designed for sequential …

Guest Editorial, Li Ai, Xiao Tan, Arslan Akbar, Guirong Yan

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Impacts Of Tick Parasitism On The Rodent Gut Microbiome, Robert J. Brinkerhoff, Joshua Pandian, Meghan Leber, Isabella D. Hauser, Holly D. Gaff

Biological Sciences Faculty Publications

Host microbiota may impact disease vector behavior and pathogen transmission, but little is known about associations between ectoparasites and microbial communities in wildlife reservoir species. We used Illumina metagenomic sequencing to explore the impacts of tick parasitism on the rodent fecal microbiome in both a field and laboratory setting. We found that tick parasitism on wild hosts was associated with variation in the fecal microbiota of both the white-footed deermouse, Peromyscus leucopus, and the southern cotton rat, Sigmodon hispidus. In a lab experiment, we detected significant changes to the fecal microbiome after experimental exposure to immature ticks in …

The Role Of Tgf-Beta Superfamily Members In Immune Homeostasis And Disease, Natalie Eva Nieuwenhuizen, Ioannis Eleftherianos, Piotr Jan Kraj, Maria Semitekolou

Biological Sciences Faculty Publications

[Introduction] The Transforming Growth Factor beta (TGF-beta) superfamily, encompassing molecules such as TGFs, activins, Bone Morphogenetic Proteins (BMPs), Growth/Differentiation Factor (GDFs) and Nodals, represents the largest family of growth and differentiation factors, playing crucial roles in developmental and physiological processes across animal species (1). These molecules are integral to tissue homeostasis and cell fate determination. Among them, TGF-beta is particularly noted for its regulatory influence on immune responses and tissue fibrosis (2, 3). Recent research has expanded our understanding of the immune functions of other superfamily members, including activin A and BMPs (4). These molecules signal through receptor complexes composed …

Squid Paralarvae Turn With High Agility Using Jets Near The Reynolds Number Threshold For Viscous Domination, Ian K. Bartol, Alissa M. Ganley, Paul S. Krueger, Joseph T. Thompson

Biological Sciences Faculty Publications

Turning is critical for survival in the ocean, as marine animals need to maneuver to capture prey, elude predators, and navigate complex environments. While prior research has focused on turning performance of adult swimmers, less is known about early ontogenetic stages that locomote within lower Reynolds number (Re) regimes, especially young jetters. To evaluate squid paralarval turning proficiency and the role of the pulsed jet in maneuvers, recently hatched longfin squid Doryteuthis pealeii swimming in a viewing chamber were studied using digital particle image velocimetry and kinematic motion analyses. Paralarvae exhibited a wide repertoire of turning behaviors, including those performed …

Assemblage Structure Of Large Carnivorous Coral Reef Fishes At Shallow And Mesophotic Depths In Two Of The Largest And Most Isolated Marine Protected Areas In The Philippines, Rene A. Abesamis, Mikaela L. Salvador, Ryan Murray, Kymry Delijero, Segundo F. Conales, Jean T. Utzurrum, Christopher E. Bird, David T. Gauthier

Biological Sciences Faculty Publications

Overfishing remains a threat to coral reef fishes globally, with large carnivores often the most vulnerable. Marine protected areas (MPAs) can restore fish populations and biodiversity, but their impact has been understudied in mesophotic coral ecosystems (MCEs – extensions of shallow reefs from 30 to 150 m). We analyzed baited remote underwater videos recorded in 2016 to investigate the assemblage structure of large carnivorous fishes at shallow (4–12 m) and mesophotic (45–96 m) depths in two of the largest and most isolated MPAs in the Philippines: Tubbataha Reefs Natural Park (TRNP), a fully no-take MPA enacted in 1988; and Cagayancillo, …