Digital Commons Network^™

Efficiency Of Enzyme Induced Carbonate Precipitation (Eicp) By Crude Extract Urease For Geotechnical And Geoenvironmental Applications, Kaniz Roksana

Theses and Dissertations

Geotechnical engineering is currently facing challenges, including accommodating rapid urbanization, adapting to climate change impacts, and prioritizing sustainability, all while ensuring the safety and stability of critical infrastructure. Biocementation is a recently developed new branch in geotechnical engineering that offers innovative and eco-friendly solutions by leveraging natural processes to enhance soil properties. This dissertation examines the potential of soybean extract urease as a cost-effective substitute for analytical-grade enzymes in Enzyme Induced Carbonate Precipitation (EICP) applications for biocementation. This research examines its effectiveness in various aspects, such as coastal erosion control, desiccation crack remediation, and the removal of heavy metals. Essential …

Free Space Optical Communications: Challenges, Mitigation Techniques, Classification Framework, And Standardization, Moataz Mohamed Roshdy, Ahmed Hosny Elghandour, Kamel Mohamed Hassan

Future Engineering Journal

Over the past several years, there has been a renewed interest in Free Space Optical (FSO) communication technology, commonly referred to as Optical Wireless Communications (OWC). FSO is sometimes viewed as a substitute for current technology, such radio frequency. In other situations, FSO is viewed as a potent contender to work in tandem and complement next-generation technology, such 5G wireless networks. FSO technology is therefore widely used in a variety of indoor (such as data centers), terrestrial (such as mobile networks), space (such as intersatellite and deep space communication), and underwater systems (such as underwater sensing). Nevertheless, despite the enormous …

Radiation Assessment And Distribution In Changing Atmospheric Structures And Turbulence (Radcast), Steven B. Hernandez

Theses and Dissertations

The accessibility of materials and online information has made radiological dispersal devices (RDDs) a more probable threat than conventional nuclear weapons. This study analyzed five datasets from three test periods, using a correlation analysis between optical turbulence, aerosol concentration, and environmental parameters, and geometric mean diameter (GMD) calculations. The correlation analysis failed to yield meaningful insights, prompted a transition to the GMD analysis, which produced clearer results. Findings show GMD ranged from 38–41 nm, increasing at night and during neutral events as reduced vertical motion and boundary layer contraction correlated with optical turbulence. An alternative GMD dataset, calculated by the …

Operational Energy Education: A Thematic Analysis Of Knowledge Area Needs And Educational Gaps, Nana Hene

Theses and Dissertations

Operational Energy (OE) education is vital for national security, military readiness, and fuel energy efficiency. This thesis analyzes the current landscape of OE education and identifies key gaps in awareness, energy knowledge, and curriculum structure. Through a reflexive thematic analysis of interviews with Subject Matter Experts (SMEs), the study underscores the necessity of integrating OE concepts into both educational and professional training programs. A framework is proposed to enhance OE education across various levels in the Air Force, aiming to cultivate a more energy-conscious and strategically prepared force. The findings highlight the critical need for targeted training, curriculum enhancements, and …

How Electricity Utility Practitioners In The United States Approach Power System Resilience, Shardul Tiwari, Aritra Chakrabarty, Chelsea Schelly, Mostafa Sahraei-Ardakani, Gaby Ou, Jianli Chen

Michigan Tech Publications

This study explores the understanding and practice of resilience among electrical utilities in the United States, focusing on how practitioners in the utility sector conceptualize and apply resilience in their work. As electricity becomes increasingly central to modern life, powering critical infrastructure and essential services, the resilience of power systems has gained prominence in energy policy and planning. However, there is a lack of standardized definitions and approaches to resilience in both academia and practice, particularly from an energy service perspective. The research employs a qualitative approach, utilizing semi-structured interviews with experts (practitioners) from transmission and distribution utilities in the …

Using Unmanned Aerial Vehicles To Facilitate Traffic Incident Management, Adam William Hill

Theses and Dissertations

Incident management teams (IMTs) minimize crash impacts and create a safer highway network for people and communities. Research has shown that optimizing the IMT fleet has strong benefits to the roadway network, but future models indicate that increasing IMT presence may have diminishing returns after excessive roadway saturation. The Utah Department of Transportation (UDOT) would like to improve situational awareness in areas of poor or limited camera coverage, where situational awareness is typically poor. UDOT is considering the use of unmanned aerial systems (UAS) to provide live camera coverage of traffic conditions in these instances. This thesis synthesizes practice from …

Generating Real-Time Synthetic Datasets To Improve Aerial Object Detection, Garrett Williams

Theses and Dissertations

The widespread use of unmanned aerial vehicles (UAVs) across civilian and military applications has necessitated the advancement of real-time drone detection and tracking capabilities. Machine Learning (ML) addresses these requirements, however, to train a robust and generalizable model requires large and diverse video datasets. Curating these real-world datasets is often time-consuming and cost-prohibitive. Here, we present DyViR, a real-time customizable rendering application capable of automatically generating highly realistic synthetic, multi-modal video of aerial objects, digital environments, and automatic generation and labeling of bounding boxes. Synthetic data, coupled with real-world training sets, augment the ML training process, leading to increased performance …

A Review On Exploring Artificial Intelligence Applications, Advancements, Issues, And Future Challenges, Sajid Naeem, Novman Nabeel, Waseem Beg, Shujaat Ali, Rajiv N. Kanojiya, Satish S. Mandawade, Chetan R. Yewale, Sc Kulkarni, Vt Salunke, Av Patil

Polytechnic Journal

Artificial intelligence (AI) is a transformative technology with diverse applications that is transforming several industries. AI is the use of systems and technology to replicate human intelligence and solve common real-world issues. Machine learning (ML) and deep learning are AI technologies that use algorithms to more accurately predict occurrences without the need for human intervention. Explainable Artificial Intelligence (XAI) refers to AI that can explain decisions or forecasts to human users. XAI seeks to improve AI systems' transparency, trustworthiness, and accountability, particularly when utilized in high-risk applications such as healthcare, finance, or security. This review article provides a thorough overview …

A Content-Based Recommender System For The Uav Caching In The Field Of Entertainment In Fog Computing, Elham Darbanian, Mohsen Nickray

Turkish Journal of Electrical Engineering and Computer Sciences

The Unmanned Aerial Vehicle (UAV) can be used as good flying base stations to cache popular content and follow a user mobility pattern, to help them in a suitable services. Conventional edge caching algorithms often prioritize cache contents with higher popularity. Nevertheless, the cache capacity of mobile devices is restricted, and diverse clients may have expansive varieties in content inclination designs. In this manner, the performance and effectiveness of the cache will be so constrained without great strategies. The composition of recommender system and edge caching is considered as a new research topic, which is used to reduce cost and …

Predicting Hazardous Near-Earth Objects Using Machine Learning For Planetary Defense, John Costa (Student), Lily Popova Zhuhadar (Mentor)

Posters-at-the-Capitol

Predicting Hazardous Near-Earth Objects Using Machine Learning for Planetary Defense

This research develops a machine learning model to classify Near-Earth Objects (NEOs) as hazardous or non-hazardous based on their physical and orbital characteristics, leveraging NASA's dataset of certified NEOs. NEOs, including asteroids and comets, often pass within close proximity to Earth, and while most pose no threat, some have the potential for catastrophic impacts. By using predictive models such as decision trees and random forests, this study aims to prioritize resources for monitoring and mitigation of high-risk objects. The model incorporates key features like velocity, diameter, and proximity to Earth …

Mitigating The Impacts Of Future Climate Change On Urban Infrastructure In Alabama Through Updating Precipitation Intensity-Duration-Frequency (Idf) Curves, Kofi Ntow Opare

All ETDs from UAB

Climate change is set to profoundly impact urban infrastructure, causing increased flooding and storm damage, necessitating the reevaluation and adaptation of design methodologies to account for increasing precipitation extremes. This dissertation aims to enhance the resilience of urban infrastructure in Alabama by updating Precipitation Intensity-Duration-Frequency (IDF) curves, which are crucial for designing stormwater management systems, drainage networks, and flood control structures. Traditional IDF curves, derived from historical rainfall data, operate under the assumption of stationarity, an assumption increasingly invalidated by climate change. This research employs the Generalized Extreme Value (GEV) distribution and compares the efficacy of L-moments and Generalized Maximum …

“Science Belongs Everywhere”: Outlooks On Post-Secondary Stem Education For Correctional Centers In Virginia, Shelita R. Augustus

Division of Strategic Enrollment Management and Student Success Publications

Virginia has an incarceration rate of 679 per 100,000 residents, the highest among independent democratic nations. This scoping review examines perspectives on post-secondary STEM education to promote STEM education within Virginia's correctional facilities, assesses programs to improve rehabilitation, reduce recidivism, and address systemic inequalities by developing the scientific potential of incarcerated individuals. The review finds that while STEM education in correctional facilities faces limitations, its potential benefits are being realized nationwide. Virginia has made strides through initiatives like House Bill 2158, which aims to expand higher education access for incarcerated individuals. Examples such as the programs at J. Sargeant Reynolds …

Developing A Guideline And Feasibility Tool For Highway Infrastructure Readiness For Autonomous Vehicles, Soujanya Pillala

Master's Theses and Doctoral Dissertations

Autonomous Vehicles (AVs) are one of the advanced technologies that is being developed, and infrastructure modifications supporting AVs will be the next major research that is needed. A systematic literature review methodology is used to explore key parameters needed for implementation of AVs. The key parameters are analyzed against economic implications, costs and projected benefits of the integration of Level 4 and Level 5 AVs into the highway system, offering a nuanced understanding of deployment of AV technologies. The research aims at developing a guideline and framework for highway infrastructure readiness for AVs, a toolbox for policy makers and government …

Crime Theory Informed Agent-Based Modeling For Crime Prediction And Patrolling Route Optimization, Shohreh Moradi

Industrial, Manufacturing, and Systems Engineering Dissertations - Archive

Crime reduction remains a global priority, demanding both accurate modeling of criminal dynamics and efficient allocation of scarce policing resources. To address these needs, this study presents a two‐fold framework that (1) simulates street‐level crime patterns using an agent‐based model (ABM) grounded in Routine Activity Theory (RAT), Rational Choice Theory (RCT), and Crime Pattern Theory (CPT), and (2) optimizes patrol routing through a time-dependent, multi‐visit mixed‐integer linear programming (MILP) formulation.

In the first component, we integrate real‐world crime, environmental, and census data to reproduce realistic offender, citizen, and Police behaviors, capturing where and when robbery, burglary, and larceny occur across …

Dc To Ac Voltage Source Converter Control System, Mohummad Tark Elgassier, Jordan M. Reichhardt, Brayden Richard Young

Electrical Engineering

The Voltage Source Converter Control System integrates a control system for a 2-phase half-bridge voltage source converter (VSC) utilizing a TMS320F2837xD Dual-Core Real-Time Microcontroller. VSCs are critical for the integration of power production into the power grid. They allow for accurate control over DC-AC energy conversion. Additionally with the improvement of renewable energies VSCs play a critical role in controlling the flow of these environmentally controlled and more unpredictable sources of energy. The control system regulates the output current and voltage, regulates switching patterns, and maintains power stability under varying loads. Within the control system Digital control systems, PWM generation, …

Detection Of Data Leakage And Disruption Of Covert Timing Channel In Secure Drone Communication Using Machine And Deep Learning, Jonathan Walatkiewicz

Master's Theses and Doctoral Dissertations

The utilization of recreational drones has experienced a substantial increase in both the United States and globally. However, it is noteworthy that most drones, classified as Internet of Things devices, are produced with a limited security lifecycle. This study's findings are of paramount importance, as traditional computing exploits can be applied to drones, designating them as high- value targets. This study examines the detectability and disruptability of covert timing channel traffic in secure drones. The investigation aims to ascertain the effects of multiple interarrival times, distances ranging from 1 to 330 feet, various detection algorithms, and stream sizes between 32-bit …

Landslide Susceptibility Mapping Via Dempster-Shafer, Statistical Index, And Certainty Factor Models In Gis And Their Comparison At Pidie Recency In Aceh, Indonesia, Septianto Aldiansyah, Amniar Ati, Fitriyani Saudi

Applied Environmental Research

Landslides are natural disasters that are active if there is an interaction of environmental factors that are considered to control them, especially in mountainous areas. This study developed a landslide susceptibility map in Pidie Regency via the Dempster-Shafer (DS), statistical index (SI), and certainty factor (CF) models. A total of 957 landslide events were mapped, 70% of which were used for modeling, whereas the remaining events were used to validate the model output. Fourteen layers of conditioning factors were used: elevation, slope, aspect, curvature, TWI, SPI, STI, NDVI, rainfall, distance from river, distance from road, distance from fault, LULC, and …

Enhancing Irs Localization Via Ml-Driven Aoa And Distance Estimation, Nikhila Kotlapara Surendran

Theses and Dissertations

Intelligent Reflecting Surfaces (IRSs) are transforming next-generation wireless networks by enabling dynamic control of the propagation environment for improved localization and security. This thesis advances Angle-of-Arrival (AoA) and distance estimation in IRS-assisted systems using a hybrid architecture with active sensing and passive reflecting elements. A modified MUSIC algorithm, optimized for near-field localization, decouples 2‑D AoA and 1‑D range estimation using a grid-and-peak pseudo-spectrum scan, achieving sub-degree AoA (0.003 rad) and sub-meter range (0.05 m) accuracy with over 100× lower complexity than classical 3D MUSIC.

The study further applies the algorithm to the DeepMIMO dataset (O1_28 scenario, 3.5 GHz) using …

Drone Medical Package Delivery For Improved Transportation And Better Patient Outcomes Final Implementation Report, Amro El-Adle, Madeline Alden, Yin-Hsuen Chen, Melissa Davidson

Information Technology & Decision Sciences Faculty Publications

The Drone Medical Package Delivery for Improved Transportation and Better Patient Outcomes planning and prototyping grant involves five partners, including Accomack-Northampton Planning District Commission (A-NPDC), Riverside Health System, Old Dominion University (ODU), Virginia Institute for Spaceflight & Autonomy (VISA), Virginia Innovation Partnership Corporation (VIPC), and DroneUp. The partners worked together to address access, safety, reliability and sustainability for medical and emergency response package delivery via drone, specifically, where the use of aerial drones could lead to better patient outcomes and improved safety and emergency response.

The goal of the project was to develop an operational prototype that woul evolve into …

A Framework For Fair And Trustworthy Multimodal Video Anomaly Detection: Fusion, Dataset Quality Auditing, Explainability, And Fairness, Omeshamisu Judith Anigala

Electronic Theses and Dissertations

No abstract provided.

Hydrogen Readiness In Aviation & Challenges- Technology Meets Regulation And Market Demand, Eva Maleviti

Publications

Where technology meets regulation and market demand.

Human Masters/Robot Servants: Highly Automated Vehicle Design, Intoxicated Drivers & Vicarious Liability, William H. Widen, Marilyn Wolf

Journal of Law and Mobility

A traditional engineering role is to design a safe product. Safety engineering is an exercise in harm avoidance ex ante. In contrast, liability attribution is an exercise to compensate for loss post hoc—traditionally viewed as a legal matter. We observe that, when a natural person incurs liability for a loss that exceeds insurance coverage, economic ruin can follow. Neither engineering nor law focus on the loss suffered by defendants considering law as a “safety risk.” The highly automated vehicle (HAV) design space, however, provides an opportunity to prevent this kind of economic harm from occurring ex ante just as attention …

Earthquake Wrangler: Leveraging Ios Technology For Earthquake Detection And Early Warning Application To Enhance Public Safety., Luis F. Salome

Theses and Dissertations--Civil Engineering

Earthquakes are devastating natural phenomena and generate secondary hazards such as tsunamis, landslides and fires. Their catastrophic impacts span both developed nations including the United States, Japan, Turkey, and Italy and developing countries such as El Salvador, Haiti, Nepal and the Philippines, where disparities in early warning infrastructure remain important. Seismic events start with stress waves generated by tectonic plate motion, with body waves (P- waves and S-waves) and surface Rayleigh and love waves that carry energy through the earth. While some regions have adopted advanced early warning systems based on seismic hazard models and strong ground motion analysis, others …

Acoustic Characterization Of A Quadcopter Using A Test Stand, Jared Schmal

Theses and Dissertations--Mechanical and Aerospace Engineering

Unmanned Aerial Vehicles (UAVs) with multirotor propulsion and control, commonly called drones or multicopters, generate a complex acoustic field that is not entirely understood. Many components and their interactions contribute to the overall noise level and behavior of the acoustic field. However, performing acoustic measurements on a multicopter in a confined space, such as a small anechoic chamber, can be an extremely difficult and time-consuming process. A test stand was developed to allow for rapid and safe acoustic measurements in a controlled environment. The design, development, and initial measurements are discussed. The performance and acoustic response are assessed to examine …

Development Of Generalizable Data-Driven Traffic State Prediction Solutions: A Comprehensive Approach, Md Mobasshir Rashid

Graduate Thesis and Dissertation post-2024

Increased urbanization and population growth lead to more traffic in the transportation system, causing severe congestion. Particularly during disruptive events such as hurricanes or traffic incidents, the traffic flow in the network worsens significantly. As a result, there is a need for data-driven traffic prediction models to reduce congestion in real-time, and the prediction model should be generalizable to be applicable across different dynamic scenarios. Additionally, a robust and adaptable traffic prediction model can help traffic managers to take proactive actions to optimize traffic flow. However, the majority of data-driven traffic prediction models suffer from limited applicability as they are …

Prioritizing Amd Impaired Watersheds For Watershed-Scale Restoration Using Multi-Criteria Decision Analysis, James Nicholas Marino

Graduate Theses, Dissertations, and Problem Reports (ETD)

Acid Mine Drainage (AMD) remains a significant environmental challenge in coal-mining and hard rock regions like West Virginia, degrading water quality and ecosystem health. Traditional site-specific remediation efforts often prove inefficient in addressing AMD at large scale. This study explores watershed-scale restoration as a more effective solution, leveraging centralized treatment facilities and multi-source pollution management. This study will follow Multi-criteria Decision Analysis (MCDA), specifically the Analytical Hierarchy Process (AHP), to develop a structured rubric for grading watersheds. The process involves identifying critical criteria, organizing them into a hierarchy, and generating weights for clusters of criteria through collaboration with decision makers. …

Updating Rainfall Zones And Intensities In Nebraska For Improved Design Of Non-Bridge-Sized Drainage Structures, Rezaul Mahmood, Tirthankar Roy, Chanchal Gupta, Kanak Kanti Kar, William Sorenson

Nebraska Department of Transportation: Research Reports

This study assesses the effectiveness of precipitation zones and Intensity-Duration-Frequency (IDF) curves used by the Nebraska Department of Transportation (NDOT) for designing drainage structures. Twenty stations were selected for the analysis of revised IDF curves out of forty-two stations. Datasets have been considered from the National Center for Environmental Information (NCEI). By Comparing the new curves with existing ones, the study efforts examine the frequency, duration and severe rainfall. The results show that the IDF curves for various zones and stations varied noticeably from one another. Also, noticed that Zone A and B shows lower rainfall intensities in short to …

Optimization, Machine Learning, And Networking Solutions For Cyber-Physical Systems, Xu Tao

Theses and Dissertations--Computer Science

Cyber-Physical Systems (CPS) represent a transformative paradigm that integrates sensing, computation, and actuation through networked systems to enable intelligent, context-aware applications across various domains. Despite their growing potential, CPS still face critical challenges, particularly in maintaining reliable, low-latency communication and efficient data processing in resource-constrained and dynamic environments. These challenges are further magnified in rural or remote deployments, where traditional network infrastructure is often unavailable or unreliable. This dissertation addresses these challenges through the development of optimization and inference algorithms that enhance network performance in Software-Defined Networks (SDN), using techniques such as reinforcement learning and network tomography for efficient routing. …

Upcycled Waste-Derived Triboelectric Nanogenerator For Sustainable Energy Harvesting, Archana Panda, Basanta Kumar Panigrahi, Subhendu Pati, Sunit Gourav Mohanty, Kushal Ruthvik Kaja

Journal of Metals, Materials and Minerals

The proliferation of disposable paper-based materials in laboratories has raised significant environmental concerns due to their rapid discard and accumulation. This study explores the upcycling of commonly discarded laboratory waste, specifically butter paper and polyurethane (PU) foam, into a single-electrode triboelectric nanogenerator (TENG) for mechanical energy harvesting. The fabricated device employs butter paper as the positive triboelectric layer and PU foam as the negative layer, with an aluminium tape electrode. Electrical tests reveal a peak voltage of 21 V and current of 47 nA, reaching a maximum power of 438 nW at 500 MΩ load. The TENG demonstrates stable performance …

The Impact Of 'Decent Life' Initiative On Sustainable Urban Development: Abu Galal Village In Egypt As A Case Study, Sally Hassan Abd-Elazim, Sherif Ahmed Sheta, Medhat Ahmed Shaban

Mansoura Engineering Journal

The “Decent Life” Initiative aims to enhance living conditions and support sustainable urban development in Abu Jalal village, Sherbin city, Dakahlia Governorate, Egypt. The research aims to assess the effectiveness of the 'Decent Life' initiative in promoting sustainable urban development in Egyptian villages, focusing on improving its mechanisms for future use and maximizing benefits in other villages facing similar challenges.. The research employs various methods, including surveys and questionnaires targeting local residents, evaluation based on SDG 11, and GIS software for spatial analysis. Research identifies key areas of improvement across housing, healthcare, transport, education, infrastructure, job opportunities, disaster resilience, waste …