Digital Commons Network^™

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

Safety And Resilience In Disaster Debris Removal And Clean-Up Operations: A Field And Training Guide For Resilience Workers In Disaster Debris Removal And Cleanup, Mohsen Shahandashti, Ph.D, P.E., Abhijit Roy, Ph.D, Zhe Yin, Ph.D, P.E., Pmp, Leed Ap, Antonio Balderrama, Ph.D, P.E., Sandesh Adhikari, Santosh Acharya

Mavs Open Press Open Educational Resources

A practical safety guide for the people who clear debris after disasters, and for the trainers who prepare them. Built for crews of every experience level--from seasoned operators to first-time volunteers--it teaches how to read a damaged site, recognize hidden and shifting hazards, work safely around heavy equipment and hazardous materials, and make sound decisions under pressure. Every chapter pairs clear guidance with a one-page field job aid, facilitator notes for trainers, and a real-world scenario, all grounded in OSHA, FEMA, EPA, and NIOSH guidance.

Safety and Resilience in Disaster Debris Removal and Clean-Up Operations Copyright © 2026 by Mohsen …

Semantic Shields: Automating Critical Infrastructure Defense Via Nlp-Driven Ransomware Profiling, Henry Trowbridge, Ian Zalcberg, Ryan Schley, Carter Yagemann, Natasha Phan, Srikar Maduposu, Vimal Buck

Military Cyber Affairs

Ransomware poses a growing threat to critical infrastructure, where successful attacks can disrupt operational technology (OT) and industrial control systems (ICS) with significant public safety consequences. However, attributing ransomware incidents to specific threat actors remains challenging due to ransomware-as-a-service ecosystems, actor rebranding, and the obfuscation of traditional indicators of compromise. This paper presents Semantic Shields, an NLP-driven attribution framework that leverages BERT-generated semantic embeddings and DBSCAN clustering to profile ransomware actors through the linguistic characteristics of ransom notes. Using a dataset of 295 ransom notes from 189 distinct threat groups, the framework achieved an 87.2% true positive clustering rate and …

Identifying The Causality And Criticality Of Factors Influencing The Promotion Of Asian Island-Hopping Cruise Tourism In Taiwan, Hsiao-Chuan Liu, Gin-Shuh Liang, Feng-Ming Tsai, Yu-Ling Lien

Journal of Marine Science and Technology–Taiwan

Following the COVID-19 pandemic, the global tourism industry has steadily recovered since 2022. Island-hopping cruises have gained increasing attention for enhancing regional connectivity and diversifying marine travel experiences; however, their development in Asia remains limited compared with that in Europe and the Caribbean due to fragmented policy coordination, inadequate port infrastructure, and uneven technological readiness. Although Taiwan possesses a geographic advantage and can serve as a strategic hub linking Asian island destinations, systematic planning and stakeholder coordination remain insufficient, resulting in unclear mechanisms that drive or constrain island-hopping cruise tourism. Existing studies mainly focus on market demand or passenger behavior, …

The Global Chessboard: Strategic Deterrence In A New Era Of Great Power Competition, The 66th Annual Academy Assembly

Space and Defense

The 66th annual Academy Assembly brought together twenty-seven student delegates from civilian institutions and sister military service academies to discuss urgent issues in national affairs. This national student congress was held during March 3-5, 2026 and produced the following committee reports.

Metrological Characterization Of Pavement Friction Measurements For High-Friction Surface Treatments: Si Traceability, Uncertainty Evaluation, And Adhesion–Hysteresis Separation Via Water–Soap Bpt Protocol, Alireza Roshan, Magdy Abdelrahman

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Laboratory friction measurements are central to material screening for High-Friction Surface Treatments (HFST), yet metrological aspects including a proposed metrological traceability framework or uncertainty, and reproducibility are consistently underreported. This study applies a metrology-aligned framework to British Pendulum Tester (BPT) measurements performed in three states: dry, wet (water), and water–soap to assess operational adhesion and hysteresis components, document traceability to the International System of Units (SI), and report GUM-style uncertainty with covariance for the adhesion difference. Measurements were obtained for calcined bauxite (CB) and rhyolite (Rhy) in HFST and Coarse gradations across seven polishing protocols (baseline; LAA-1000/2000; MDA-105/180; PSV-10 h/20 …

Crowd Monitoring And Firearm Detection Uas, Arjun Nambiar, Sang-A Lee, Diego Espino, Will Obot Jr, Ethan Encarnacion, Jarrett Usui, Jacob D. Kline

Discovery Day - Daytona Beach

The increasing complexity of public safety operations in urban and high-density environments necessitates intelligent, mobile surveillance systems capable of real-time threat identification and situational awareness. Traditional monitoring approaches, such as fixed CCTV systems and manual observation, are often limited by coverage, scalability, and response latency in complex environments or large-scale events. This project addresses these challenges through the development of a computer vision-enabled Uncrewed Aerial System (UAS) designed for crowd monitoring and firearm detection. The primary objective is to design and validate a modular, Artificial Intelligence (AI)-Machine Learning (ML)-driven model capable of identifying firearms within dynamic environments while supporting real-time …

Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods

Discovery Day - Daytona Beach

Phaëthon System is the project name for the Search and Rescue Drone Initiative. This initiative will improve the current search and rescue drone industry by introducing new techniques to get through dense forest canopies and other places where an overhead view is not useful. The Phaëthon System uses a swarm of drones that can penetrate under the tree canopy to map and search with the utmost efficiency and safety for rescuers. A command drone is launched to survey the overall search area, and set up a communications and data link. The next component is then released, which is a swarm …

Fall Hazard Prevention: A Zero-Fatality Goal For Health, Safety, And Well-Being On Construction Sites, Alena Richardson, Chaidaliz Minguela Alicea, Nicola Kaehler, Charlene Weaver

Discovery Day - Daytona Beach

Jobsites face hazards like falls, which threaten the health, safety, and well-being of construction workers. Falls are the leading cause of all accidents and fatalities in construction, accounting for approximately 40% of all worker deaths in 2023. While achieving a zero-accident rate for falls is inherently challenging, prioritizing a zero-fatality objective represents a practical and impactful starting point. The Occupational Safety and Health Administration (OSHA) recommends a six-step action approach for the prevention and control of hazards like falls. Of particular interest, the State of Florida is consistently ranked among the highest for construction fall fatalities, often attributed to insufficient …

Chameleon Carriers In Trucking: Detection, Enforcement, And Financial And Safety Impacts, Brian Howell, Drew Law, Andrew Martin

Kentucky Transportation Center Research Report

Chameleon carriers are motor carriers that evade regulatory enforcement by dissolving and reregistering under new corporate identities. This study, commissioned by the Kentucky Transportation Cabinet (KYTC), examined how states characterize, detect, and respond to chameleon carrier activity and assessed its financial and safety impacts in Kentucky from 2020 through 2025. The research team conducted a literature review of existing agency practices and relevant stakeholder perspectives, reviewed administrative codes and statutes across 13 pilot states, and administered two structured surveys to state motor carrier credentialing officials examining carrier characterization and enforcement practices. An analysis of KYTC's carrier data flagged by CVIEW …

Evaluating Drug Concentration Profiles In Wastewater To Develop A Framework For Estimating Drug User Populations, Carl Michael E. Espinosa

All Theses

Chemical compounds, including licit and illicit drugs can be measured in wastewater and used to assess community drug consumption, providing valuable information for public health agencies, law enforcement, and local communities. While previous research primarily focused on estimating the per capita community drug consumption using back-calculation, this research focused on utilizing literature-derived parameters including drug dosage, renal excretion fraction, and sewer stability to develop a framework to estimate the user populations using Monte Carlo simulations. Samples were collected from two wastewater treatment facilities representing the Generostee Creek WWTP’s sewershed (GCS) and Mauldin Road WRRF’s sewershed (MRS). The target analytes included …

Leveraging Deep Learning Recurrence And Attention Mechanisms For Flood Forecasting And Assessment, Elnaz Heidari

All Dissertations

Predicting how much water will flow in rivers and streams is important for managing floods, water supply, and the environment. Traditionally, government agencies have used complex models, such as the National Water Model (NWM), which simulate how much water moves through landscapes using physical laws and real-world data. However, recent advances in Artificial Intelligence (AI) have enabled new ways to make these predictions. This research explored whether AI-based models could predict river discharge more accurately. These AI models learn patterns from past data instead of relying only on physical rules. To find out how well they work, the AI models …

Comparison Of Forces Generated By An Impinging Water Jet Using Numerical And Physical Experimentation, Spencer R. Young

All Graduate Theses and Dissertations, Fall 2023 to Present

When water is released from hydraulic structures such as dams water jets are formed and land on the downstream surfaces. When these jets land there is high potential for erosion or scour. Scour has the potential to compromise the structure and cause the uncontrolled release of water that can endanger downstream communities and infrastructure.

Engineers use tools including computational fluid dynamics (CFD) to inform their designs to mitigate the risk of scour. This study compares how well CFD is able to model the forces created by a water jet by comparing the results to laboratory collected physical data. To make …

Drones In Wildfire Airspace Management: Developing A Scalable Framework For Mid-Sized Cities, Victoria Denise Tanner Williamson

Engineering Management & Systems Engineering Theses & Dissertations

Wildfires are becoming increasingly frequent and severe, creating growing risks for mid-sized communities with limited emergency response resources. The January 2025 Los Angeles wildfires—which burned more than 57,000 acres and destroyed over 18,000 structures—underscore the urgent need to strengthen wildfire response strategies through the integration of unmanned aerial systems (UAS) (Hardy, 2025).

This study develops a scalable framework for drone-assisted wildfire response in resource-constrained environments. Using the city of Waynesboro, Virginia, as a case study, the research examines how mid-sized jurisdictions can integrate unmanned aerial vehicles (UAVs) to improve preparedness, response, and recovery. A three-round, mixed-methods Delphi study engages emergency …

The Effect Of Mobile Phone Use While Driving On Response Time: Driving Simulator Study, Hussein Mutar, Ahmed Abduljabbar, Ammar Mohammed

Engineering and Technology Journal

Mobile phone use is one of the most common daily tasks and this is normal, however, this task could be problematic while driving. The use of mobile phones while driving has become a major cause of road accidents and poses a threat to public health. This study investigated the effect of mobile phone usage while driving on response time, as it investigated four mobile phone tasks (hands-free calling, hand calls, reading text messages, and sending text messages) in addition to basic driving. A total of 42 participants, ranging in age from (19 to 55), with a mean age (mean = …

Case Study: Feasibility Of Creating A Simulated Mobile Data Center For Cross-Disciplinary Academic Programs, Stanley Mierzwa, Christoper J. Schultz, Iassen Christov, Michael Fagioli, Thomas Ikeda, Reinaldo Jaramillo, Giolian Sanagustin

Center for Cybersecurity

This case study examines the potential to envision, create, and deploy a simulated mobile micro data center solution that can be easily replicated and transported between locations and educational settings. The coined term for this solution is the Mobile AI-Centered Data Center (Mobile ACDC), which provides students with a platform to construct, in a hands-on fashion, such a solution and navigate the product to gain greater competencies and understanding of the components found in a data center. Instructor and student feedback assessments from the pilot classroom modules and laboratory experiential learning activities indicate that such a solution helps to improve …

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

Fuel Tank Seismic Stability Program-Informed Displacement Maps Of Portland's Critical Energy Infrastructure Hub, Ana Tijerina Esquino

Dissertations and Theses

Oregon's Critical Energy Infrastructure (CEI) Hub in northwest Portland contains a large portion of the state's liquid fuel storage and distribution capacity and is located in an area susceptible to liquefaction and earthquake-induced permanent ground deformation during a Cascadia Subduction Zone earthquake. Initial Seismic Vulnerability Assessments submitted under Oregon's Fuel Tank Seismic Stability program provide valuable facility-specific information, but the assessments vary in subsurface characterization, treatment of fine-grained soils, ground motion selection, and deformation estimation methods. This variability complicates interpretation of regional seismic risk and motivates a consistent corridor-scale analysis.

This thesis develops CPT-informed displacement estimates for representative cross sections …

Design And Implementation Of Cyber Risk Management In The Indonesian Aviation Sector Based On Nist Csf And Iso/Iec 27002:2022, Annisa Aulia Budianti Qurota'aini, Ira Rosianal Hikmah, Yulial Hikmah

Jurnal Vokasi Indonesia

As technology usage increases, cyberspace in Indonesia has developed significantly, including in Vital Information Infrastructure (VII) sectors such as aviation. However, this advancement introduces potential cyber threats that can disrupt operations. This research aims to design a systematic cyber risk management framework for a navigation authority within the Indonesian aviation sector using the National Institute of Standards and Technology Cybersecurity Framework (NIST CSF) as the primary standard. This research also utilizes national aviation regulations, Center for Internet Security Controls (CIS Controls) v8.0, and ISO/IEC 27002:2022 as supporting frameworks. The research employs a qualitative descriptive approach, gathering data through field observations, …

An Evaluation Of The “Police Response To Uncrewed Aircraft Systems Operations” Online Training Program, Anthony Galante, Leila Halawi

Publications

This study evaluates the impact of the “Police Response to Uncrewed Aircraft Systems Operations” online training program of officers from the Daytona Beach Police Department (DBPD). By measuring the effectiveness of the training through pretest and posttest assessments and considering variables such as educational background, length of service, and rank, this research underscores the training’s potential to enhance UAS response capabilities. Employing a self-selection sampling method, the study engaged 82 voluntary participants from the DBPD, revealing significant improvement across all groups in UAS knowledge and confidence levels. Despite limitations, these findings offer compelling evidence of the training’s efficacy and advocate …

Vision-Based Autonomous Tracking Rover, Alejandro Ahumada, Erick Ayala, Jonathan Chavez

Electrical Engineering

AAC Vision designed and constructed a vision-based autonomous tracking rover capable of exploring an indoor environment, avoiding obstacles, generating a two-dimensional LiDAR map, detecting a standard orange basketball, and approaching the target without manual steering. The rover uses a Raspberry Pi 4, an Intel RealSense D435 RGB-D camera, an RPLIDAR C1, four JGB37-520 Hall-encoder motors, dual H-bridge motor drivers, a 12 V battery, and a custom aluminum chassis measuring approximately 8 in by 12 in and weighing 6.7 lb. The final mission emphasized reliable target discovery rather than travel between predetermined points. The software integrates Python, OpenCV, Ultralytics YOLO, RealSense …

Managing Risks Under Nuclear Power Plant Projects: A Latent Similarity-Guided Contract Customization, Mariam Elazhary, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Global energy is transforming, with nuclear power emerging as a pivotal player in achieving sustainable and low-carbon energy goals. The nature of nuclear technology introduces unique challenges, such as stringent safety and environmental requirements. Existing studies focus on general risk identification, such as supply chain delays, cost overruns, and public perception issues. However, these studies fail to address integrating these risks into tailored contractual provisions, which are critical for navigating the unique challenges of nuclear projects. The goal of this paper is to examine how standard construction contracts can be tailored to better accommodate the risks inherent in nuclear power …

Explainable And Hybrid Machine Learning For Predicting Fatal Crash Risk, Hussein Khanjar, Abdolmajid Erfani

Michigan Tech Publications

Road traffic fatalities remain one of the most persistent public safety challenges, demanding predictive models that are not only accurate but also reliable and interpretable. While numerous machine-learning models have been developed for crash severity prediction, most remain limited in three critical dimensions: they simplify the unit of analysis by focusing only on the driver or the most severe occupant per crash, they emphasize predictive performance while neglecting model confidence and probability calibration, and they often function as black boxes lacking interpretability for real-world decision support. To address these gaps, this study proposes a calibrated hybrid machine-learning framework for nationwide, …

Improving Urban Search And Rescue Team Coordination Through Adaptive Context Awareness, Daniel Reyes Duran

Doctoral Dissertations and Master's Theses

Modern multi-agent Urban Search and Rescue (USAR) operations heavily rely on mobile geospatial Common Operating Pictures (COPs) to maintain team coordination and Situational Awareness (SA). However, the proliferation of high-frequency sensor telemetry at the tactical edge has introduced a data saturation paradox challenge: while information theoretically drives informed decision-making, unmanaged data surges induce increased operator cognitive overload and alert fatigue on mobile End-User Devices (EUDs), while downstream data-broadcasting models inherently strain edge processing and viewport environments.

To resolve these constraints, this dissertation presents a context-aware Value of Information (VoI) data-management framework integrated directly with a custom, event-driven Android Team Awareness …

Subspace Decomposition For Spatial Parameter Estimation, Arthur Grik

USF Tampa Graduate Theses and Dissertations

Passive emitter localization is an important capability for wireless sensing, interference detection, and spectrum awareness. Classical timing-based localization methods estimate emitter position from differences in signal arrival time across distributed sensor platforms, but their performance depends on precise receiver synchronization and favorable signal bandwidth characteristics. This thesis investigates subspace-decomposition-based spatial parameter estimation as an alternative approach in which directional information is extracted from coherent antenna-array measurements. This work develops the theoretical foundation and signal-processing framework for angle-of-arrival estimation. Various spatial parameter estimators are presented as supporting array-processing methods before focusing on a well-known subspace-decomposition-based approach called the Multiple SIgnal Classification …

An Intelligent System For Managing High-Priority Vehicle Routing In Smart Cities Using Artificial Intelligence And Spatial Data Analytics, Bahjat Abdulelah Madhloom

Al-Esraa University College Journal for Engineering Sciences

In developing metropolises, there is a risk to public safety in addition to the usual traffic jams. Traffic delays can have life-altering effects every second that fire trucks and ambulances are delayed. Large cities like Baghdad, which suffer from haphazard road sealing and incompetent traffic management, are especially affected, creating daily emergency crisis problems. We create a new intelligent routing system for these top priority vehicles in order to solve this life-or-death problem. Our method uses a trained model with real-time spatial information instead of outdated static maps. A Long Short-Term Memory (LSTM) neural network at its core constantly forecasts …

Hybrid Patrol–Staging Optimization For Freeway Service Patrols Under Cost Control: A Deterministic Milp With Dynamic Segment Adjustment & Environmental Co-Benefit, Mauricio Micolta

Electronic Theses and Dissertations 2020 - Present

Freeway Service Patrol (FSP) programs are central to Traffic Incident Management (TIM), delivering rapid response, clearance, and motorist assistance on high-volume corridors. The prevailing continuous roaming patrol model provides broad coverage but generates substantial non-productive vehicle-miles traveled (VMT), increases responders’ exposure to risk, and treats Service Level Agreement (SLA) compliance as a statistical outcome rather than a fixed operational constraint. Existing literature lacks a framework that simultaneously optimizes corridor segmentation, jointly deploys patrol and staged units across space, time, and direction, and enforces response-time SLA as a binding constraint.

This dissertation introduces the Segmental-Spatio-Temporal Hybrid Service Model (SSTHSM), a two-tier …

Enhanced Uav Surveillance With Rf-Based Drone Identification Using Transfer Learning, Prajoy Podder, Maciej Jan Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

With the development of technology and the decrease in costs, drones are now becoming easily accessible to the public. As the accessibility of this technology continues to grow, the concerns of security and surveillance increase, and to ensure a sense of security, the need to have reliable drone detection and identification systems is more urgent than ever. Besides, many civilian applications have been found for drones, which play a huge role in modern security and warfare. Unauthorized drones can be very dangerous regarding security issues, as they can be used for spying, smuggling, or even attacks against critical infrastructure. We …

Adopting Critical Power Grid Infrastructure Technologies: An Organizational Cybersecurity Assessment Against Ransomware, Fayez Alsoubaie

Dissertations and Theses

For many years, researchers and practitioners have studied emerging technologies in field of energy production and distribution. Power grid systems carry major weights in the energy branch of the economy. Researchers and scientists have been interested in finding ways to connect the power grid gap and improve protection for its technologies.

The research supports organizational adoption and prioritization of critical cybersecurity technologies for ransomware protection in power grid infrastructure. As utilities increasingly integrate digital technologies, they become more vulnerable to sophisticated cyberattacks that can disrupt services and put public safety at risk. The main focus of the study is to …

Bridgeide, Maya Srimal, Jeshwin Prince, Arnav Gupta, Will Zumbolo

Computer Science and Engineering Senior Theses

Anyone who has done a group project knows the pattern: the first meeting burns an hour on logistics—which document to use, who has access, why the formatting broke on one laptop—before real work begins. In computer science courses that gap is worse. Students must install the right compiler, runtime, and libraries on their own machines; a four-person team on four different laptops can lose the first week to setup alone. Instructors who want to review submissions often download every zip from the learning management system and run each one locally. Existing tools solve pieces of this puzzle—real-time document editing, browser-based …