Digital Commons Network^™

Arson Event Detection Using Yolov9, Ali Abbas Abbod, Matheel E. Abdulmunimb, Ismail A. Mageed

Journal of Soft Computing and Computer Applications

Detecting event anomalies is crucial for surveillance systems, as it enables the identification of occurrences in videos, both temporally and spatially. It can identify deviations from patterns without requiring human oversight by learning from past information to distinguish normal behavior and pinpoint irregularities. Early detection of arson fires is critical to mitigating damage, public safety, property, and the environment, as well as saving lives and aiding in law enforcement investigations. The objective of this study is to evaluate a system for detecting events using the You Only Look Once version 9 (YOLOv9) model in surveillance videos with a focus on …

Elemental Analysis Of Sediments In Johnson County, Kansas: Applications In Fluvial Suspended Sediment Tracing, Kiena Campbell

Undergraduate Theses, Capstones, and Recitals

This exploratory study investigates whether bulk elemental analysis of sediment samples using inductively coupled mass spectrometry (ICP-MS) can reveal chemical signatures that identify anthropogenic contributions to sedimentation and increased fluvial suspended sediment loads, and whether these contribution sources can be identified. Human activity, urbanization, and changes in land use increase erosion, resulting in higher-than-natural suspended sediments (SS) in waterways and increasing sedimentation in reservoirs across the state of Kansas. These threats to freshwater storage capacity are especially urgent given the projected rise in freshwater demand in the Great Plains region driven by climate change. Understanding the origin of anthropogenic SS …

Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover

Theses and Dissertations

The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …

Integrating A Stakeholder-Centric Approach Into Dynamic Adaptation Policy Pathways For Equitable Coastal Flood Risk Management In East Boston, Shailee M. Desai

Graduate Doctoral Dissertations

This research aims to illustrate a methodology incorporating diverse stakeholder values in adaptation planning to promote equitable outcomes using a hypothetical case study of the Lower Border Street area in East Boston, using the Dynamic Adaptive Policy Pathways (DAPP) framework for managing coastal flood risk. It offers three significant contributions to the field of adaptation planning: (i) It demonstrates how to integrate a stakeholder-specific assessment within the DAPP framework and illustrates individual impacts to a variety of stakeholders, including high- and low-income residents, commercial actors, government actors, and coastal landowners hoping that the planning process remains transparent and motivates local …

Real-Time Enhanced Tornado Warning Product Guidance Based On Tornado Debris Signature Height And Population Density, Alexander Cooke

Theses and Dissertations

This research aims to develop an operational program for enhancing real-time tornado warning capabilities by integrating tornado debris signature (TDS) analysis with population impact assessment. The proposed Python-based tool will ingest Level II radar data to identify and analyze TDS, estimating tornado intensity based on maximum TDS height. For high-intensity tornadoes, the program will project the potential impact area using storm motion vectors and integrate this with population density data. The system will assess whether the situation meets National Weather Service criteria for enhanced warning products, providing forecasters with rapid, objective guidance for critical warning decisions. The program’s performance will …

Earth Analogue Analysis Of Volcanic/Tectonic Interactions With Applications To Venusian Stresses, Michael Ortigoza

Theses and Dissertations

Venus shares many geological similarities with Earth, yet its tectonic processes and magma injection mechanisms remain poorly understood. A key question in planetary geology is how effusive volcanism persists despite the intense horizontal compression terrestrial bodies experience over time. To explore these issues, we examine the Spanish Peaks dike swarm in Colorado which serves as an ideal site for investigating magma intrusion under compressive stress conditions. Through field mapping, orientation measurements, and structural analysis, we identify a strong relationship between pre-existing joints and dike orientations, suggesting that these fractures serve as critical magma pathways in compressive regimes. Additionally, evidence of …

Creating A Shade Tree Commission For Shamokin, Skye Sunderhauf, Beth Williams, Marques Owens, Olivia Follansbee

Final Reports in ENST 411: Environmental Community Projects

Final Project for ENST411 Environmental Community Projects

Harnessing Llms To Detect Hate Speech, Weibin Cai

Theses - ALL

Hate is a sentiment, while hate speech refers to the expression of hate in a form that targets and attacks specific groups, such as race, religion, or gender. With the rise of the internet and social media, hate speech has spread rapidly, gaining wide exposure and posing threats to individual well-being, the profits of major tech companies, and social stability. As a result, both industry and academia have turned their attention to the study of hate speech. One of the most active areas is hate speech detection, which involves training models to predict whether a given piece of content is …

Intrinsic And Extrinsic Drivers Of Bioaerosol Decay: Investigating Pathogen Stability Of Bacteriophage Ms2, Sin Nombre Virus, And Sars-Cov-2 In Simulated Environments, Elizabeth A. Klug

Theses & Dissertations

The threat posed by a virus as a bioaerosol depends largely on its stability under various environmental conditions (relative humidity (RH), sunlight, ozone, etc.). This stability is typically studied through aerosol decay—how the virus' viability changes over time when exposed environmental conditions. The Goldberg rotating drum, a widely used tool for studying bioaerosols, has been the basis of such research (Goldberg et al., 1958). However, it has significant limitations, including an inability to measure initial pathogen infectivity loss and the use of small sample volumes. Additionally, it does not answer the question of what intrinsic factors (lipids, proteins, nucleic acids) …

Community Stakeholders’ Perceptions On Growing A Nonprofit Donor Base Through In-Kind Donations, Brittany A. Heine

Walden Dissertations and Doctoral Studies

In Northern Virginia alone, over 90,000 people are food insecure. The USDA has reported strong correlations between food insecurity and negative health outcomes. The purpose of this qualitative case study was to determine community stakeholders’ perceptions on engaging in strategic partnerships with Organization X using in-kind donations as a strategy to decrease the organization’s expenditures and grow its donor base. 14 community stakeholders were chosen through purposive sampling and participated in semi structured interviews. Using the conceptual framework of the unified theory of revenue generation for nonprofits, interview questions were developed to determine the variables that impact a stakeholder’s decision …

Optimizing Fire Station Placement In Sugar Land, Tx: A Socioeconomic Risk-Based Approach, Alicia Gallemore

Data Science Undergraduate Honors Theses

Fire station placement has a critical role in emergency response efficiency and community safety. Traditional optimization models focus on mainly the minimization of response times and the maximization of coverage. However, this approach may overlook potential socioeconomic disparities that can influence emergency demand. This study seeks to expand upon the existing project of zoning a fire station in Sugar Land, TX, by integrating spatial road network analysis and publicly available census data—including population density, median household income, and age-based vulnerability—into a Maximal Coverage Location Problem (MCLP) framework. Using a road network-based travel time with realistic constraints, the goal is to …

A Machine Learning Framework For Packet Anomaly Detection In Smartgrid Substation Networks, Sowmya Bandari

School of Computing: Dissertations, Theses, and Student Research

The increasing reliance on Smart Grid Substation Networks for efficient electricity distribution has amplified cybersecurity vulnerabilities, particularly within Supervisory Control and Data Acquisition (SCADA) systems. The IEC 60870-5-104 (IEC-104) protocol, widely adopted for communication between Remote Terminal Units (RTUs) and Human-Machine Interfaces (HMIs), lacks inherent encryption and authentication mechanisms, rendering it susceptible to sophisticated cyberattacks. Threats such as False Data Injection Attacks (FDIAs), command injection, covert attacks and replay attacks pose significant risks by manipulating grid control signals, potentially leading to undetected operational disruptions, cascading failures, or system-wide instability. Conventional signature-based Intrusion Detection Systems (IDS) often fail to identify zero-day …

Community Voices, Climate Action Choices: Working Towards A Resilient Monterey County, Lesley A. Solano Alonso

Capstone Projects and Master's Theses

Vulnerable communities in Monterey County face disproportionate environmental and health impacts due to climate change, yet many residents remain unaware of the tools and resources available to support local action. This capstone project was implemented in partnership with Ecology Action (EA) and the Resilient Central Coast (RCC) campaign to increase awareness and engagement with the RCC platform. Serving diverse communities across Monterey County, the project included bilingual outreach efforts, community tabling, educational presentations, and a climate action survey. Over 650 residents were engaged directly, resulting in 99 new household sign-ups on the RCC website, a major milestone for the agency. …

A Comprehensive Review Of Carbon Sequestration And Its Assessment Techniques Using Remote Sensing And Geospatial Methods, Imen Ben Salem

All Works

Global warming has elevated carbon sequestration as a critical strategy for mitigating climate change, while enhancing sustainability in productivity. Agricultural land use systems contribute substantially to CO2 emissions due to crop residues, shifting cultivation practices, low-biomass crops, land degradation, and deforestation. The significant rise in CO2 emissions over the past thirty years is associated with burning fossil fuels, leading to substantial environmental changes, including global warming. Remote sensing (RS) and Geographic Information Systems (GIS) are advanced geospatial technologies that facilitate the rapid evaluation of terrestrial carbon stock over extensive regions. An integrated RS-GIS approach for carbon stock estimation and precision …

Key-Based Authentication Scheme For Evtol Drones Using Chebyshev Chaotic Maps, Eduardo A. Hernandez Escobar

Master's Theses

The development of electric Vertical Take-Off and Landing (eVTOL) drones signifies a substantial advancement in urban air mobility, ready to transform transportation models in densely populated regions. These advanced drones, distinguished by their capacity to function in limited spaces and their minimized environmental impact, are set to transform individual, shipping, emergency services, and public safety activities. Nonetheless, like any transformational technology, the implementation of eVTOL systems presents many challenges, especially in the realm of cybersecurity. Adding many devices and entities to an eVTOL network increases the risk of privacy and security attacks. This paper proposes a key-based authentication scheme that …

Understanding The Impact Of Ransomware On Biotechnology, Tswvyim Vang

Electronic Theses, Projects, and Dissertations

Biotechnology encompasses the use of research on both biology and technology to create products that can advance in areas such as healthcare and agriculture. Because of the technology and products that arise from the use of biotechnology, the industry is especially targeted by cyber-attacks. A prominent type of cyber-attack that is utilized by cyber criminals on biotechnology is ransomware. The goal of this project is to determine the impact of ransomware on biotechnology. The research questions posed are: Q1) What are real examples of ransomware attacks that have occurred on biotechnology companies and what patterns can be identified by these …

Qualitative And Quantitative Analysis Of New Psychoactive Substances And Related Metabolites Using Liquid Chromatography-Ion Mobility-Mass Spectrometry (Lc-Im-Ms), Ralph Aderorho

All Dissertations

The increasing prevalence of novel psychoactive substances (NPS) in illicit drug markets has posed significant challenges for forensic and clinical toxicology, primarily due to the structural similarity and diversity among these compounds. This dissertation investigates the application of advanced liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS/MS) techniques, using the high-resolution Structures for Lossless Ion Manipulations (SLIM) platform and the drift tube ion mobility spectrometry (DT-IMS), for the qualitative and quantitative analysis of various types of synthetic opioids, synthetic cannabinoids, psychedelics and xylazine. By combining IMS separations with mass spectrometry and targeted chemical derivatization, this work enhances the ability to distinguish and characterize …

Empirically Exploring The Physical Realizability Of Adversarial Examples, Ruoyao Wen

McKelvey School of Engineering Graduate Student Theses & Dissertations

The development of autonomous vehicles (AVs) has been accelerated by advancements in deep neural networks (DNNs), which power the complex perception systems necessary for safe and efficient real-world navigation. However, as AVs increasingly integrate into public transportation networks, the robustness of their perception systems against potential vulnerabilities is critical. Among these threats, adversarial attacks—particularly through the use of adversarial patches—pose significant risks. These patches are carefully crafted perturbations designed to mislead DNNs, potentially compromising AV safety by causing incorrect object recognition or misclassification.

While extensive research has demonstrated high attack success rates for adversarial patches in controlled digital environments, their …

Real-Time Active-Learning Method For Audio-Based Anomalous Event Identification And Rare Events Classification For Audio Events Detection, Farkhund Iqbal, Ahmed Abbasi, Ahmad Almadhor, Shtwai Alsubai, Michal Gregus

All Works

Introduction: Audio event detection, the application of scientific methods to analyze audio recordings, can be helpful in examining and analyzing audio recordings to preserve, analyze, and interpret sound evidence. Furthermore, it can be helpful in safety and compliance, security, surveillance, maintenance, and predictive analysis. Audio event detection aims to recover meaningful information from audio recordings, such as determining the authenticity of the recording, identifying the speakers, and reconstructing conversations. However, filtering out noise for better accuracy in audio event detection is a major challenge. A greater sense of public security can be achieved by developing automated event detection systems that …

Essential Pillars For The Post-2026 Colorado River Guidelines, Anne Castle, John Fleck, Eric Kuhn, Jack Schmidt, Kathryn Sorensen, Katherine Tara

The Traveling Wilburys of the Colorado River

The process for determining the operating rules for the Colorado River system that will take effect in 2027 is in full swing. While various alternative operating regimes have been proposed, no preferred or consensus alternative has yet emerged. As a group of experienced Colorado River colleagues without affiliation to any Basin State, Tribe, or interested stakeholder, we submit that there are fundamental principles that should form the basis of the ultimate Record of Decision defining management of the Colorado River for the future. We propose the following essential pillars for inclusion in the Post-2026 Guidelines.

Balancing Privacy And Security: A Comparative Analysis Of Ai-Driven Surveillance In The Uae And Usa, Belal Alghafri, Abdallah Tubaishat

All Works

AI-driven surveillance has emerged as a critical tool for enhancing public safety, enabling authorities to monitor and prevent crime and terrorism more effectively. In countries like the UAE and the USA, these systems are often implemented under the pretext of national security, offering advanced methods to track potential threats. However, the increasing reliance on AI for surveillance raises significant ethical concerns about privacy and individual freedoms. The boundary between protecting citizens and infringing on their privacy becomes increasingly blurred, potentially leading to abuses of power, diminished public trust, and a pervasive atmosphere of fear. This paper explores the complex relationship …

Enhancing Animal Shelter Operations With Time Series And Machine Learning, Sakava L. Kiv, Donald L. Anderson, Shivam Negi, Jacquelyn Cheun

SMU Data Science Review

Enhancing animal shelter operations through machine learning involves employing a variety of advanced techniques aimed at increasing efficiency, promoting animal welfare, and optimizing resource allocation. This paper explores predictive analytics for adoption rates using regression models to estimate the likelihood of adoption based on historical data, encompassing variables such as breed, health status, and previous adoption trends. Additionally, classification algorithms are utilized to categorize animals by adoption probability, facilitating better resources and marketing prioritization. Clustering algorithms are employed to group animals according to behavior patterns and/or physical health, enabling tailored medical care and enrichment activities that improve their mental and …

Living With Alzheimer’S: A Guide To How To Lower The Risk Of Memory Loss & Care For Those With Alzheimer’S, Mona Muzammil, Washain Muzammil

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

Despite the frequent characterization of Alzheimer's disease as a “loss of self,"" this enlightening book demonstrates unequivocally that a person's unique self persists throughout the course of the disease. The important message in Caring for People with Alzheimer’s is how much can be done in care settings to support a person's sense of identity and thereby enrich the lives of people experiencing the many losses associated with dementia. Drawing from a diverse body of research, this book brings together the recommendations of the best thinkers and practitioners in multiple disciplines to illustrate the meaning of self and the importance of …

Enhancing Smart City Management With Ai: Analyzing Key Criteria And Their Interrelationships Using Dematel Under Neutrosophic Numbers And Mabac For Optimal Development, Asmaa Elsayed, Mai Mohamed

Neutrosophic Systems with Applications

Purpose: This paper explores the transformative role of AI across various domains of smart cities, including urban mobility, energy management, public safety, healthcare, environmental monitoring, economic development, and data management. It aims to develop a novel decision-making framework that integrates AI technologies with a hybrid approach to analyze the interrelationships among smart city components.

Methodology: This paper employs a hybrid decision-making framework that combines the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with single-valued trapezoidal neutrosophic numbers (STrNN). This approach is used to analyze the complex relationships among criteria and sub-criteria in smart city contexts, addressing uncertainty and incomplete information …

Enhancing Smart City Management With Ai: Analyzing Key Criteria And Their Interrelationships Using Dematel Under Neutrosophic Numbers And Mabac For Optimal Development, Asmaa Elsayed, Mai Mohamed

Neutrosophic Systems with Applications

Purpose: This paper explores the transformative role of AI across various domains of smart cities, including urban mobility, energy management, public safety, healthcare, environmental monitoring, economic development, and data management. It aims to develop a novel decision-making framework that integrates AI technologies with a hybrid approach to analyze the interrelationships among smart city components.

Methodology: This paper employs a hybrid decision-making framework that combines the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with single-valued trapezoidal neutrosophic numbers (STrNN). This approach is used to analyze the complex relationships among criteria and sub-criteria in smart city contexts, addressing uncertainty and incomplete information …

Code Of Faith: Programming Spirituality In The Digital Age, Caleb Martin

Senior Honors Theses

With the increasing pervasiveness of technology in our daily lives, it is critical to consider the potential effects on an individual's religious practices and beliefs from software applications developed within a religious framework. This thesis delves into the relationship between software development and religious experiences, examining the manner in which the creation, operation, and application of religious technology can mold and impact an individual's spiritual development. This thesis aims to inform the implementation of technologies with a nonsecular application, ensuring that they are developed with a deep respect for the nuances of religious experience. The findings of this study will …

Exploring Corona Discharge In Electrostatic Printing For Electronics And In Other Application, Zijian Weng

USF Tampa Graduate Theses and Dissertations

The field of printed electronics (PEs) is expanding rapidly, driven by increasing market demand. According to reports, the global market for PEs is expected to reach $23 billion by 2026, with a compound annual growth rate of 18.3% from 2023 to 2028. This growth necessitates the development of innovative printing technologies that can meet these demands efficiently, delivering high-quality, high-resolution PEs suitable for applications in health, environmental monitoring, sports, aerospace, and more.

Currently, PEs manufacturing relies on two main groups of printing technologies. Contact printing methods offer high-speed production but struggle with precision, while non-contact methods provide high resolution but …

Utilizing Deep Learning And Object-Based Image Analysis To Search For Low-Head Dams In Indiana, Usa, Brian M. Crookston, Caitlin R. Arnold

Publications

Although low-head dams in the USA provide water supply, irrigation, and recreation opportunities, many are unknown by regulators. Unfortunately, hundreds of drownings occur each decade at these dams from an entrapment current that can form immediately downstream. To explore the ability of deep learning to scan large areas of terrain to identify the locations of low-head dams, ArcGIS Pro and embedded deep learning models for object-based image analysis were investigated. The State of Indiana low-head dam dataset was selected for model training and validation. Aerial imagery (leaf-off conditions) captured from 2016 to 2018 for the nearly 94,000 km² area …

Maine Career Exploration: Final Evaluation Report, Julia Bergeron-Smith Mppm, Msw, Sarah Goan, Madison Burke, Becky Wurwarg, Amy Geren, Shannon Saxby

Publications

The Maine Career Exploration (MCE) Program was a two-year, $25 million pilot initiative launched in 2022 by Governor Janet Mills as part of the Maine Jobs and Recovery Plan. The program aimed to connect young people aged 16 to 24 with Maine’s economy through paid, age-appropriate career experiences that matched their interests, while also expanding career exploration opportunities in schools and communities and building long-term infrastructure to sustain these efforts. Managed by the Maine Department of Economic and Community Development, MCE distributed funding across three main streams: the Maine Children’s Cabinet Career Exploration Pilot Project, the Maine Department of Education’s …

Abolition By Algorithm, Peter N. Salib

Michigan Law Review

In one sense, America’s newest abolitionist movement—advocating the elimination of policing and prison—has been a success. Following the 2020 Black Lives Matter protests, a small group of self-described radicals convinced a wide swath of ordinary liberals to accept a sweeping claim: Mere reforms cannot meaningfully reduce prison and policing’s serious harms. Only elimination can. On the other hand, abolitionists have failed to secure lasting policy change. The difficulty is crime. In 2021, following a nationwide uptick in homicides, liberal support for abolitionist proposals collapsed. Despite being newly “abolition curious,” left-leaning voters consistently rejected concrete abolitionist policies. Faced with the difficult …