Digital Commons Network^™

Navigating Ai-Nature Frictions: Autonomous Vehicle Testing And Nature-Based Constraints, Prerona Das, Orlando Woods, Lily Kong

Research Collection College of Integrative Studies

In cities, the application of Artificial Intelligence (AI) is being directed towards transforming different aspects of urban life. These applications take material form in urban spaces, with autonomous vehicles (AVs) providing a prominent example. AI systems rely on large volumes of data on their surroundings to refine the algorithms and enhance the accuracy of prediction for operational efficiency and safety. However, such algorithmic learning and execution can present challenges when dealing with the unpredictable, complex, and dynamic aspects of urban spaces. Nature is a paradigmatic example of such unpredictability, because natural phenomena usually defy consistent patterns and precise data-based modelling. …

Piezoelectric Energy Harvesting From Roadways: Challenges, Advances, And Future Directions, Heba Gaber, Mohamed Abdelraheem

Faculty Publications

As the global demand for renewable energy intensifies, piezoelectric energy harvesting from roadways has emerged as a promising avenue for sustainable power generation. This systematic literature review analyzes 61 peer-reviewed studies to assess the feasibility, performance, and potential of integrating piezoelectric systems into roadway infrastructure. While technology faces challenges, such as high installation costs, limited energy output, and a scarcity of thorough economic evaluations, findings suggest it holds considerable promise as a supplementary renewable energy source. The review analyzes the operational characteristics and efficiencies of various piezoelectric transducers, identifies key factors influencing system performance, and evaluates recent technological advances. It …

Analyzing The Global Happiness Index, Victoria Hernandez, Christy W. Wachira

SMU Data Science Review

This study explores the Global Happiness Index using data compiled from the OECD and Our World in Data to identify key factors contributing to societal well-being. Six primary predictors were analyzed: GDP per capita, social support, healthy life expectancy, freedom to make life choices, generosity, and perceptions of corruption. Regression and clustering techniques were employed to uncover patterns among countries. By expanding the analytical scope beyond conventional economic and social indicators, this study helps identify new pathways for improving well-being across diverse cultural and economic landscapes. Additional variables such as perceived safety, political engagement, and values related to family and …

Climatology Of Northeast Winds In Northern And Central California: A New Characterization Of The Diablo Wind, Alana R. Macken

Master's Theses

Diablo winds in northern California are known for driving some of the most destructive wildfires in state history. The Camp Fire of 2018, which caused at least 85 civilian fatalities, is just one example of the devastating outcomes associated with these rapidly developing downslope windstorms. While they are known to occur most frequently from fall through spring, much about the structure, evolution, and full spatial extent of these events remains poorly understood. Most previous studies have focused on a limited number of high-impact cases or have defined events using humidity-based thresholds in isolated regions such as the North Bay. As …

Exploiting Chloride Conservative Tendencies As Contaminant Surrogates In Groundwater Transport Modeling In A Typical Hydrogeological Environment Of Northern New Jersey, Toritseju Oyen, Duke Ophori

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

This study investigates the transport of chloride, a conservative tracer and surrogate for contaminants, in the fractured Brunswick aquifer of northern New Jersey using a dual-porosity MODFLOW-MT3DMS model. Focusing on the First Watchung Mountain region—a microcosm of northern New Jersey’s hydrogeological environment encompassing Montclair State University and adjoining communities, the numerical model simulates groundwater flow and solute transport in a hydrogeologically complex, urbanized setting. Results indicate that chloride migrates through the fractured aquifer via both local flow systems (e.g., Third River) and regional flow systems (Passaic River) within decades. Chloride concentrations exceeded the EPA’s 250 mg/L threshold much faster in …

Building Resilience Against Coastal Climate Risks, San Diego Regional Climate Collaborative, Brenda Castruita, Marius Van Dongen, Brandi Upshaw

San Diego Regional Climate Collaborative

The South Carlsbad Climate Adaptation Project (Project) is an initiative led by the City of Carlsbad (City) designed to address the growing risks of coastal erosion and sea level rise within the city. The Project focuses on a one mile segment of South Carlsbad Boulevard that runs directly along the coast and has experienced decades of coastal erosion, shoreline retreat, and recurring flooding–all of which are expected to intensify due to climate change. In an effort to protect critical infrastructure, natural resources, and public safety, the City has been evaluating the long-term viability of the current roadway and exploring various …

Fisheries Science Update - Western Australian Shark Resource: 2024 Stock Assessment Outcomes, Department Of Primary Industries And Regional Development, Western Australia

Fisheries Science Updates

The Western Australian (WA) shark resource includes more than 100 species of sharks and rays.

Key shark species are sustainably harvested in two commercial shark fisheries that provide fresh, local, affordable seafood to the WA community.

The WA shark resource has been in recovery since the 1990s–2000s when stocks were found to be at risk.

The Department of Primary Industries and Regional Development (DPIRD) tracks stock status by undertaking periodic weight of evidence stock assessments of indicator species.

Gummy, whiskery, dusky whaler, and sandbar sharks, are the indicator species for the WA shark resource, and make up ~80% of the …

Global Cooling Watch 2025, Omar Abdelaziz, Ray Gluckman, Ian Hamilton, Radhika Khosla, Lily Riahi

Research Collection College of Integrative Studies

The second edition of UNEP’s Global Cooling Watch Report takes a deep dive into one of the decade’s most urgent challenges: surging heat, soaring cooling demand, and stark inequalities in access. Produced by the UNEP-led Cool Coalition, the report provides a comprehensive assessment of the rapidly growing global demand for cooling and the need for climate-friendly solutions to the issue. The 2025 report builds on the first Global Cooling Watch (2023), which established the Sustainable Cooling Pathway framework. The new edition deepens analysis of intensifying extreme heat and its effect on cooling demand, improved assessment of passive cooling, and coverage …

Security Modelling For Cyber-Physical Systems: A Systematic Literature Review, Shao Fei Huang, Christopher M. Poskitt, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Cyber-physical systems are at the intersection of digital technology and engineering domains, rendering them high-value targets of sophisticated and well-funded cybersecurity threat actors. Prominent cybersecurity attacks on CPS have brought attention to the vulnerability of these systems and the inherent weaknesses of critical infrastructure reliant on them. Security modelling for CPS is an important mechanism to systematically identify and assess vulnerabilities, threats, and risks throughout system life cycles, and to ultimately ensure system resilience, safety, and reliability. This survey delves into state-of-the-art research on CPS security modelling, encompassing both threat and attack modelling. While these terms are sometimes used interchangeably, …

Barriers To Machine Learning Adoption In Regulated Electric Utilities, Donald R. Shiflet Jr.

USF Tampa Graduate Theses and Dissertations

Machine learning (ML) technologies have the potential to revolutionize regulated electric utilities by improving operational efficiency, enabling predictive maintenance, and optimizing energy management. Despite these advantages, the adoption of ML in this sector lags other industries due to technical, organizational, and regulatory barriers. This research, grounded in the Technology-Organization-Environment (TOE) framework, explores these barriers to uncover actionable solutions for integration. The study identifies key challenges, including explainability, cybersecurity, workforce resistance, and regulatory ambiguity to ML adoption in electric utilities. Utilizing an exploratory qualitative methodology, this approach integrates insights from the literature and industry interviews to rank barriers by frequency, severity, …

Bifusenet: A Multimodal Network For Estimating Blood Alcohol Concentration Via Bidirectional Hierarchical Fusion, Abdullah Tariq, Arooba Maqsood, Martin Masek, Syed Zulqarnain Gilani

Research outputs 2022 to 2026

Drunk driving remains a significant public safety challenge, demanding innovative alternatives to conventional methods such as field sobriety tests and breathalysers. Estimating a driver's level of intoxication through facial cues is particularly challenging due to the subtle and person-specific nature of alcohol-induced behaviours. In this paper, we present BiFuseNet, a 3D spatio-temporal multi-modal network designed to classify alcohol impairment levels into three categories: sober, moderate, and severe. Unlike prior approaches that rely on either uni-modal RGB video or hand-crafted facial features, our method exploits complementary physiological cues from RGB and infrared (IR) facial videos. We introduce a Bi-directional Hierarchical Fusion …

Synthesis And Characterization Of Lanthanide Extended Structures And Their Novel Transuranic Analogues, Hunter Bernard Tisdale

Theses and Dissertations

The United States owns a substantial amount of radioactive waste as a result of decades of research, weapons manufacturing, and nuclear energy production. As nuclear energy and research continue to add to our stockpiles of waste, the issue of remediating this waste becomes more pressing. Many of the radioactive constituents of this waste, such as the transuranic (Z > 92) elements, will give off radioactivity at harmful levels for millennia. Thus, a robust method of storing this waste is paramount to ensuring public safety. Currently, nuclear waste is being processed by vitrifying it in borosilicate glass. However, this method has shortcomings …

The Gender Pay Gap: An Occupational Analysis (2012-2023), Curtis Long

Harriet L Wilkes Honors College Theses 2020 - Present

This thesis examines the gender wage gap across thirty major U.S. occupations from 2014 to 2023 using data from the Current Population Survey (CPS), more specifically, the U.S. Bureau of Labor Statistics (BLS). The analysis measures the difference in median weekly earnings between women and men in each occupation and applies two statistical tests: a yearly z-test to evaluate whether the average wage gap is significant, and a ten-year t-test to identify persistent occupational gaps. Results show significant wage differences in every year, with the largest disparities in finance, management, and law, and smaller gaps in education and healthcare. Consistent …

Creating Wildfire-Resilient Communities In Utah: Fuel Treatments In The Wildland-Urban Interface, Luke Dutson, Kendall Becker, Katlyn Stemmler, J. Bradley Washa, Larissa L. Yocom Kent, Aish Chandrasekaran, Joseph D. Birch, Scott Hotaling

All Current Publications

In the western United States, decades of wildfire suppression and grazing have led to changes in the amount and type of wildland fuels. In many lower montane forests, fuels such as logs, dead trees, and fallen leaves have accumulated. In many sagebrush-dominated rangelands, annual grasses have invaded, and pinyon pine and juniper woodlands have encroached. These areas now threaten to burn at uncharacteristically high fire severity, a metric based on how much vegetation is killed. Climate change and rapid population growth have exacerbated this issue in Utah, increasing the threat wildfire poses to the state’s communities, infrastructure, and ecosystems. Fuel …

Reinforcement Learning Based Resource Management In Edge Systems, Motahare Mounesan

Dissertations, Theses, and Capstone Projects

Modern end-user applications that are highly compute- and data-intensive, while being extremely latency- and accuracy-sensitive, are increasingly reliant on distributed computing. This paradigm spans a range of architectures, from cloud computing to in-device processing. Cloud computing, though scalable, often incurs high latency and cost, constraints that are particularly problematic for time-sensitive applications. In contrast, in-device computing on end or IoT devices is limited by resource constraints, making it inadequate for many complex workloads. Edge computing presents a compelling alternative by bringing computation closer to data sources, thereby reducing end-to-end latency and improving responsiveness. However, the inherent decentralized and dynamic nature …

Hurricane Katrina Archive: Faculty Publications Bibliography 2020-2025, Lsu Health Sciences Center - New Orleans Libraries, Sharon Duffy, Matthew Folse

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 10 articles about Hurricane Katrina written by authors affiliated with LSU Health – New Orleans between January 2020 and August 2025.

Machine Learning And Crime Prevention, Emily Lizewski

Student Theses

Predictive policing uses machine learning to analyze crime patterns and help law enforcement better efficient use their resources. These tools can improve accuracy by highlighting complex trends in large sets of data. While this technology has its advantages, it also raises important ethical and social questions. Within this paper we looks at how predictive policing works, focusing on the machine learning models often used such as decision trees, random forests, gradient boosting, and models that factor in both time and location. It also explores how these tools might unintentionally reinforce biases already present in historical crime data. In reviewing the …

Efficient Decontamination Of Organophosphate-Based Pesticides And Nerve Agent Simulants Mediated By N-Containing Nucleophiles, Emmanuel Kingsley Darkwah, Puspa Aryal, Saidulu Todeti, Jared Kenik, Samuel Insall, V. Prakash Reddy, Chariklia Sotiriou-Leventis

Chemistry Faculty Research & Creative Works

There is a growing interest in developing safer and more effective decontaminating agents for organophosphate-based pesticides and nerve agents. In this study, we present an effective method for the nonaqueous decontamination of these compounds using small-molecule-based decontaminating agents under ambient conditions. Our approach utilizes aryl and heteroaryl carboxaldehyde hydrazones and hydrazides to effectively hydrolyze nerve agent simulants into their nontoxic degradation products. The effectiveness of this method was evaluated using a range of nerve agent simulants, including dimethyl 4-nitrophenyl phosphate (DMNP), dimethyl methyl phosphonate (DMMP), and triphenyl phosphate (TPhP). In the presence of the heteroaryl hydrazone, the rate of hydrolysis …

Using Geomorphic Change And Sediment Modeling To Calculate Debris Flow Volumes From The 2020 El Dorado Wildfire In The Southern San Bernardino Mountains, California, Sevag Injean

Electronic Theses, Projects, and Dissertations

Four years after the occurrence of the 2020 El Dorado Fire, Yucaipa Ridge and the surrounding communities of Oak Glen and Forest Falls still experience the devastation caused by debris flows. Wildfires can instigate a series of events leading to hydrophobic soils, loss of vegetation, and increased sediment availability which amplify post-fire debris flow risks. This study tested the hypothesis that post-wildfire geomorphic changes can be accurately quantified and predicted using high-resolution LiDAR-derived digital elevation models. To investigate this hypothesis, multi-temporal LiDAR datasets were analyzed to quantify geomorphic changes, including erosion and deposition, within two severely burned basins in the …

Broadband Resilience By Zero Trust Community Network Policy Design, Lee W. Mcknight, Danielle Smith

The Lender Center for Social Justice

This paper proposes a Zero Trust framework for broadband policy design to enhance community network resilience. It provides a governance and policy perspective for ensuring secure, equitable broadband access.

Complex System Governance And Cyber Operations, Willie Gernard Mccallister

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation examines the potential integration of Complex System Governance (CSG) within cybersecurity, emphasizing the development of a reference model for Cybersecurity Infrastructures. Traditional strategies for securing digital environments have struggled to address the intricate and dynamic layers inherent in modern cybersecurity systems. The purpose of this research is to explore the applicability of CSG as a framework to assess cybersecurity infrastructure using a case study research design. The research addresses two key questions: (1) How can the CSG reference model be adapted to explore cybersecurity infrastructure? (2) What results from CSG based exploration of cybersecurity infrastructure through a case …

An Experimental Investigation Of Federal Messaging On Public Support For Enforcement- And Treatment-Based Approaches For Opioid Overdose Prevention In South Carolina, Lídia Gual-Gonzalez, Hunter M. Boehme, Peter Baker, Melissa Nolan Ph.D., Mph

Faculty Publications

Background

As the opioid overdose crisis continues to produce excessive morbidity and mortality in the United States, government agencies have applied various approaches to prevent overdoses, including law-enforcement efforts (e.g., arresting people who use drugs, interrupting drug traffickers, etc.) and treatment-based approaches (e.g., naloxone, medications for opioid use disorder, etc.). Public perception and support of these approaches are relevant for informing policy, allocating resources, and effectively implementing community interventions to prevent drug-related harms.

Methods

Using an embedded informational survey design, we experimentally assessed whether public support for strategies to prevent overdose in South Carolina is influenced by language from federal …

Interactions Between A High Intensity Wildfire And An Atmopsheric Hydraulic Jump In The Case Of The 2023 Lahaina Fire, Clifford Dw Ehrke

Master's Theses

On 8 August 2023, a grass fire that started in the city of Lahaina, Hawai’i, grew into the deadliest wildfire in the United States since 1918. This wildfire offers a unique opportunity to explore the impact of high heat output on an atmospheric hydraulic jump and a downslope wind event. We conducted two WRF-SFIRE simulations to investigate these effects: one incorporating fire–atmosphere feedback and the other without it. We compare these WRF-SFIRE simulations to all available data regarding the fire event, including high resolution satellite data, weather station data from other parts of Maui and the Hawaiian Archipelago, and official …

Zero Trust Architecture For Electric Transportation Systems: A Systematic Survey And Deep Learning Framework For Replay Attack Detection, Grace Muriithi, Behnaz Papari, Ali Arsalan, Laxman Timilsina, Alex Muriithi, Elutunji Buraimoh, Asif Khan, Gokhan Ozkan, Christopher Edrington, Akram Papari

Montclair State University Scholarship & Creative Works

Modern and autonomous hybrid electric vehicles (HEVs), as complex cyber-physical systems, represent a key innovation in the future of transportation. However, the increasing interconnectivity and reliance on digital components expose these vehicles to significant cybersecurity risks. To address these challenges, Zero Trust Architecture (ZTA) has emerged as a promising security framework. Operating on the principle of ‘never trust, always verify,’ ZTA offers a comprehensive approach to ensuring continuous trust verification in HEV systems. Despite its potential, the application of ZTA within cyber-physical vehicular systems remains underexplored, and its practical benefits and limitations are not yet fully understood by the engineering …

Reliability Simulation Testing And Verification Technologies For Intelligent Systems: Frontiers, Progress, And Challenges, Zili Wang, Yuntian Gao, Dezhen Yang, Yeyang Liu, Yi Ren

Journal of System Simulation

Abstract: Intelligent systems are extensively deployed in domains such as transportation, energy and water resources, smart healthcare, and aerospace, where their reliability is directly linked to public safety and social stability, thus requiring thorough and scientifically rigorous verification. This article conducted an in-depth exploration of the current state of reliability simulation and verification techniques for intelligent systems. It defined the concept of reliability specific to intelligent systems and identified key challenges they face in areas including mission scenario modeling, characteristic modeling and simulation, evaluation and verification, and simulation platforms. Future development requirements were proposed to guide research toward more trustworthy, …

Machine Learning Crime Prediction Models And The Gap Between Research And Implementation: A Systematic Review, Ricardo Huamantingo, Miguel Cano-Lengua, Ciro Rodriguez

Karbala International Journal of Modern Science

A crime is an illegal or violent act committed by one individual against another. The increasing crime rate has become a major concern as it negatively affects people's quality of life and generates significant social and economic costs. This study aims to identify the most widely used machine learning (ML) models for crime prediction, determine evaluation metrics for assessing model performance, and analyze key data characteristics to enhance real-world implementation. The study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. A search string was formulated using the population, intervention, comparison, and outcomes (PICO) framework and applied …

Mitigation Behaviors Of Homeowners And Renters In The Wildland Urban Interface, Aishwarya Borate, Omar Pérez Figueroa, Douglas Houston, Christopher Ihinegbu, Ariane Jong-Levinger, Jochen E. Schubert, Brett F. Sanders

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Residential development within the wildland-urban interface (WUI) has greatly expanded in the United States since the 1990s, amplifying wildfire risk by placing people and structures in greater proximity to flammable vegetation. Household wildfire mitigation actions can vary substantially by cost, knowledge required, and perceived effectiveness, but few studies have examined them separately and how their adoption varies by housing tenure in the context of wildfires. To address this gap, we surveyed residents living in WUI areas within Southern California near recent burn scars in the Santa Ana and San Bernardino Mountain ranges. Drawing on the Protection Motivation Theory and the …

Green Energy Production Using A Hydro-Generator In An Underground Mine Water Pumping Station – Case Study, Andrzej Chmiela, Beata Barszczowska, Eugeniusz Krause, Arkadiusz Kulawik, Adam Smolinski

Journal of Sustainable Mining

The paper analyses the experience of almost one year of production of “green” electricity by a hydro-generator using a constant water drop in the pits of mine water pumping stations. The main technical, economic and environmental parameters obtained by the applied technical and organisational system are presented. Equipping the mine water pumping station with a hydro-generator proved to be a good investment. The investment offers a relatively low risk with a relatively low initial outlay and a relatively short payback period of about 4 years. The innovative use of typical but modern elements in an atypical operating environment has not …

Analysis Of Vision Transformers And Domain Adaptation In Long-Range Facial Recognition, Zachary Michael Swanson

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Atmospheric turbulence presents a significant barrier to long-range facial recognition, introducing severe geometric distortions and blur that degrade image quality. This thesis investigates deep learning approaches for mitigating these effects, with a focus on transformer based architectures and domain adaptation strategies.

An in-depth benchmarking study was performed using convolutional neural networks (CNNs) and vision transformers (ViTs) on the Husker BRIAR Research Collection from up to 500m (HBRC-500) face dataset. The results demonstrated that vision transformers, particularly hierarchical vision transformers like the shifted-window (Swin) transformer, outperform CNN-based models at long distances due to their ability to model global spatial relationships and …

Power Optimized Co-Registration Of Multispectral And Thermal Cameras For Real-Time Urban Pluvial Flood Monitoring, Fatemeh Rezaei

Theses - ALL

Urban pluvial flooding occurs when local precipitation intensity exceeds the capacity of natural and engineered drainage systems, resulting in dangerous and highly localized inundation that is not captured by traditional stream gaging networks. While satellite imagery and flood maps support regional-scale flood management, a critical gap remains in the real-time, spatially continuous, in-situ monitoring of urban surface flooding. To address this monitoring gap, we develop a low-power, camera-based distributed sensor network flood mapping platform, Urban Flood Observation Network (UFO-Net), featuring two co-mounted sensors: a multispectral optical (capturing RGB and Near-Infrared) and a long-wave infrared (thermal) camera. A five-band image (RGB, …