Digital Commons Network^™

Deep Learning For Uav Classification: Impact Of Noise And Multipath Fading In Rf Signals, Prajoy Podder, Maciej Jan Zawodniok, Sanjay Kumar Madria

Electrical and Computer Engineering Faculty Research & Creative Works

The increasing presence of unmanned aerial vehicles (UAVs) raises serious security concerns, particularly regarding unauthorized drone operations. Recent U.S. security statistics report a sharp rise in unauthorized UAV activities, with the Federal Aviation Administration (FAA) receiving over 100 monthly reports of illegal drone operations near airports. In 2024 alone, Dedrone records 1.19 million unauthorized drone flights across major U.S. cities, highlighting the need for robust UAV detection and classification systems. In this work, a lightweight Convolutional Neural Network (CNN) model is proposed for RF-based UAV classification under noisy and multipath fading conditions. The proposed CNN consists of multiple convolutional blocks, …

A Dynamically Adapting Forecast Cone Based On Ensemble Spread, Michael N. Barletta

Electronic Theses & Dissertations (2024 - present)

Dynamically based ensemble prediction systems have gained considerable attention because they can provide a greater range of possible forecast outcomes and quantify the uncertainty in forecasts. In turn, forecasters can convey clearer messages to the public on the range of forecast scenarios and display inherent uncertainty in weather forecasts, which can be difficult to do with deterministic forecasts. Although global ensemble prediction systems have demonstrated skill in their probabilistic track predictions, the information contained within them is not always fully utilized beyond the mean forecast and standard deviation (i.e., spread). One way that these ensembles could be better employed is …

Automated Methods For Estimating Blood Alcohol Concentration Level From Facial Cues, Ensiyeh Keshtkaran

Theses: Doctorates and Masters

This thesis investigates different approaches for detecting alcohol intoxication in drivers by analysing facial video data. Tackling this issue necessitates the creation of a novel dataset to overcome the limitations of existing datasets. The dataset constructed in this study is the first to include RGB video recordings of individual faces at varying levels of alcohol intoxication during simulated driving, featuring 60 participants with BAC levels ranging from 0 to 0.165 g/100ml. The constructed dataset not only supports this thesis, but also offers the broader scientific community a valuable resource for further study and development.

Building on this, this thesis presents …

An Exploratory Attempt To Incorporate Social Criteria Into Spent Nuclear Fuel Site Screening And Relocation, Julie M. Sorfleet

Cal Poly Humboldt theses and projects

Spent nuclear fuel, also known as nuclear waste, is the byproduct of nuclear power generation. The need for safe and responsible long-term storage and disposal of radioactive fuel presents significant technical and social challenges. These challenges are compounded by several factors, including the emerging nuclear renaissance in the United States, climate and coastal hazards, and the lack of consolidated interim or permanent storage. This research explores perceptions of risk, relocation, and siting spent nuclear fuel, predominantly focusing on Humboldt County, California. I used online surveys, the Analytic Hierarchy Process, and geographic information systems (GIS) analysis to inform how social and …

Snag Failure And Fuel Recovery Following Stand-Replacing Fire In The Klamath Mountains, Joseph R. Nicholas

Cal Poly Humboldt theses and projects

High-severity wildfires can produce extensive patches of standing dead trees (snags), which later contribute to surface fuel loading and present a hazard as they decay and fall. In the Klamath Mountains of northwestern California and southwestern Oregon, recent increases in the occurrence of large stand-replacing wildfires have raised concerns about fuel and vegetation recovery trajectories, the likelihood of future fires, and resulting impacts to local communities. Nevertheless, the post-fire environment may offer opportunities to enhance ecological and community resilience. Estimates of snag failure and fuel loading can support land management planning and risk assessment following wildfire, though such work is …

Identifying The Lithologies And Thicknesses Of Coal Seam Roofs And Floors Based On Multiparameter Logging Of Boreholes, Li Zhe, Gao Baobin, Lei Wenjie, Li Donghui, Li Zixin

Coal Geology & Exploration

Background In the process of coal mining, effective exploration methods for stratigraphic characteristics are crucial to underground operations. The reason is that the accurate stratigraphic characteristics of coal seams, along with the surrounding rocks of coal seam roofs and floors, facilitate the treatment of gas in coal seams, thereby ensuring safe and efficient coal mining. Methods Based on the multiparameter logging of boreholes crossing strata in a bottom drainage roadway, this study highlighted the lowstand, upgoing borehole trajectories, as well as the variations in parameters including natural gamma rays, spontaneous potential, and resistivity. By comprehensive comparison of the trajectories, video-derived …

Analysis Of Dense Metals Accumulation In Shikaripara Stone Mines, Gopinath Gorai, Nirajan Kumar Mandal

Makara Journal of Science

This study aimed to measure the amount of dangerous substances in the cultivated area of the Shikaripara stone mines in Jharkhand, India, which are well known for their stone quarrying. Sixteen soil samples were collected at varying dis-tances from the Shikaripara stone mines in the Dumka District of Jharkhand. The metals found in these samples in-clude Pb, As, Zn, Mn, Cd, Cu, Fg, and Fe. The combined amount of the elements was calculated by inductively coupled plasma mass spectrometry. Enrichment factor, accumulation index, contamination factor, pollution load index (PLI), Nemerow index, and ecological risk index (RI) were employed to assess …

Zoning Regulations Are Harming Nebraska’S Wind Energy Future, Carter Probst

Op-Eds from ENSC230 Energy and the Environment: Economics and Policies

Nebraska is a prime location for renewable energy sources, such as wind. According to Climate Central, a policy-neutral non-profit, “While Nebraska ranks fourth among U.S States for potential wind energy generation, it ranks 15th in installed capacity.” What is the number one reason Nebraska has not fully tapped into its potential, which would have numerous economic and climate benefits? Harsh zoning regulations at the county level, fueled by misinformation, have made installation of wind turbines nearly impossible across multiple counties in Nebraska.

Enhancing Smart Grid Security And Resilience Using Programmable Networks, Zheng Hu

Graduate Theses and Dissertations

The security and resilience of smart grids are essential to ensuring reliable and efficient energy distribution, especially as these cyber-physical systems grow more interconnected and complex. Supervisory Control and Data Acquisition (SCADA) systems play a critical role in smart grid operations by enabling essential infrastructure control and real-time monitoring. However, SCADA systems are highly vulnerable to modern cyber threats, which target weaknesses in industrial protocols and real-time data requirements.

This dissertation investigates the potential of programmable network technologies, with a focus on P4 (Programming Protocol-independent Packet Processors) switch, to deliver adaptable, in-network security solutions tailored to the needs of smart …

Domain-Specific Machine Learning Approaches For Geospatial Problems, Shine Bedi

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation explores novel algorithms for complex geospatial problems at the intersection of environmental, social, and computational sciences. Emphasizing the unique challenges of the geospatial domain, particularly the deviation from the independent and identical distribution (IID) assumption, the research spans various methodologies across different domains, demonstrating the benefits of specialized approaches in spatial analysis.

First, we show that machine learning techniques can be effectively used in environmental modeling, which often has severe class imbalance challenges. Using artificial neural networks (ANN), support vector machines (SVM), and extreme gradient boosting (XGB) and techniques to address class imbalance provides insights into groundwater quality …

Detecting Anomalies In Dynamic Attributed Graphs: An Unsupervised Learning Approach, Austin Hamilton

Electronic Theses and Dissertations

Dynamic attributed graphs, which evolve over time and hold node-specific attributes, are essential in fields like social network analysis, where anomalous node detection is a growing area. Vehicular social networks (VSNs), a subset of these graphs, are ad hoc networks in which vehicles exchange data with one another and with infrastructure. In this dynamic context, identifying anomalous nodes is challenging but crucial for maintaining trust within the network. This work presents an unsupervised deep learning approach for anomalous node detection in VSNs. This model achieved an accuracy of 71% while detecting synthetic anomalies in a simulated network based on real-world …

Landslide Inventory And Unstable Slope Monitoring Along Highways In Eastern Tennessee, Robert Mcsweeney

Electronic Theses and Dissertations

This research introduces an unstable slope management program (USMP) for Tennessee based on federal slope management standards, along with improved methods for landslide monitoring with unmanned aerial systems (UAS) lidar and photogrammetry. In mountainous regions, monitoring slope hazards is a critical function of transportation management. A mobile field assessment form created with Survey123 was used to collect 22 unstable slope ratings in eastern Tennessee. Location points were appended with photographs, notes, and site information. Landslide scores ranged from 325 (Fair) to 1005 (Poor). UAS monitoring of a slow-moving soil landslide along I-40 near Rockwood, TN, produced high-resolution lidar and photogrammetry …

Shield-U: Safeguarding Traffic Sign Recognition Against Perturbation Attacks, Shengmin Xu, Jianfei Sun, Hangcheng Cao, Yulan Gao, Ziyang He, Cong Wu

Research Collection School Of Computing and Information Systems

Traffic sign recognition systems are crucial for the navigation and situation awareness of autonomous vehicles. They leverage deep learning technologies to swiftly and accurately identify traffic signs, even in the most challenging traffic environments. However, security researchers have uncovered a critical vulnerability in these systems: learning-based TSRs are particularly susceptible to physical-world perturbation attacks. Through subtle modifications (i.e., attaching well-designed patches on traffic signs), attackers can deceive the recognition system into making erroneous judgments, which can further lead to serious traffic accidents. Although several defense mechanisms have been proposed to enhance the security of sign recognition systems, these solutions generally …

Recovery Resiliency Of Interdependent Power Systems Infrastructure Subject To Extreme Events, Partha P. Sarker

Graduate Theses and Dissertations (2019 - present)

When Hurricane Maria struck the island of Puerto Rico on September 20, 2017, it devastated the island’s aging power systems infrastructure and inflicted an island-wide power outage that left Puerto Rico in total darkness for an entire week before the system slowly started to recover. This unprecedented failure of the critical power systems infrastructure exacerbated the failure of other critical infrastructures or lifeline systems of the island. This research explores and quantifies the relationships or interdependencies that exist between the power systems and other critical infrastructure systems by investigating the post-hurricane recovery data of these lifeline systems. Subsequently, the research …

Understanding And Influencing Public Concerns About Prescribed Fire Use In Utah, Brooke Richards

All Graduate Theses and Dissertations, Fall 2023 to Present

Prescribed fire is beneficial for improving forest health and reducing wildfire risk, which is especially important for residents who live near forested areas. To expand the use of prescribed fire, Utah land managers must first ensure there is public support. Therefore, better understanding public concerns and what shapes their beliefs about prescribed fire can help managers improve outreach and education methods. Through interviews with south-central Utah land managers, private landowners, and Health departments employees, a focus group discussion with Park City natural resource managers, and observation of Summit County public commentary, two outreach messages were suggested to address the five …

Dynamic Key-Based Privacy-Preserving Authentication Scheme For Internet Of Drones, Zain Chaudhary

Honors Theses

The Internet of Drones (IoD) proliferation has catalyzed transformative changes across various industries, from agriculture to urban management. However, expanding drone networks also presents significant security challenges concerning secure communication and authentication. This paper introduces a robust privacy-preserving key-based authentication scheme tailored explicitly for the IoD, utilizing a matrix key generated by Hierarchical Message Authentication Codes (HMAC) and the SHA-256 algorithm to address these vulnerabilities. Our system enhances security by ensuring each drone in the network can authenticate securely and reliably with a central unit, preventing unauthorized access and securing communications against common threats like eavesdropping and impersonation attacks. Our …

Automating Maritime Risk Data Collection And Identification Leveraging Large Language Models, Donghao Huang, Xiuju Fu, Xiaofeng Yin, Haibo Pen, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Maritime risk research is crucial yet challenging for improving safety, efficiency, and sustainability in maritime operations. This paper presents an innovative method for automating the collection and identification of risk data related to global maritime risks from news sources, addressing the limitations of traditional manual methods. To evaluate the proposed method, different learning-based models, including conventional machine learning approaches and advanced Large Language Models (LLMs) such as GPT-4 and LLaMA-3.1, are comprehensively studied for comparison. In addition, not only do we use popular evaluation metrics to assess the proposed method, but we also introduce a new evaluation metric, called the …

Hurricane Evacuation: Navigating Uncertainty During Covid 19 And With Existing Communication Scales, And Considering Public And Expert Perception Of Alternative Scales, Leilani D. Paxton

USF Tampa Graduate Theses and Dissertations

This dissertation investigates the effectiveness of current hurricane warning products and communication strategies, exploring factors influencing public perception of risk and decision-making during evacuations. The study employs a mixed-methods approach, combining survey data, focus group discussions, and interviews with meteorologists and emergency managers. The first paper examines the impact of the COVID-19 pandemic on hurricane risk perception and evacuation decisions. Findings indicate that while COVID-19 concerns played a role in some individuals' decisions, particularly those with pets or concerns about shelter conditions, the majority of participants evacuated for Hurricane Ian. The study highlights the importance of providing clear, consistent, and …

Drone Vs. Drone, Mariah Smith

Cybersecurity Undergraduate Research Showcase

This paper focuses on the problems that drones pose to digital and physical infrastructure, as well as potential solutions to combat these issues. One solution is incorporating drone usage into ethical hacking. These drone-based attacks are affecting not only economic spaces but also seemingly high-security areas such as prison systems. It is only a matter of time before critical infrastructure is targeted. Conversely, by simulating drone attacks, drones equipped with complex hacking tools and sensors can detect unauthorized pathways and infiltrate networks for the greater good. Incorporating these new practices would enhance digital and physical protection. "Drone vs. Drone" highlights …

Examining Wildfire Dynamics Using Ecostress Data With Machine Learning Approaches: The Case Of South-Eastern Australia's Black Summer, Yuanhui Zhu, Shakthi B. Murugesan, Ivone K. Masara, Soe W. Myint, Joshua B. Fisher

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Wildfires are increasing in risk and prevalence. The most destructive wildfires in decades in Australia occurred in 2019–2020. However, there is still a challenge in developing effective models to understand the likelihood of wildfire spread (susceptibility) and pre-fire vegetation conditions. The recent launch of NASA's ECOSTRESS presents an opportunity to monitor fire dynamics with a high resolution of 70 m by measuring ecosystem stress and drought conditions preceding wildfires. We incorporated ECOSTRESS data, vegetation indices, rainfall, and topographic data as independent variables and fire events as dependent variables into machine learning algorithms applied to the historic Australian wildfires of 2019–2020. …

Unlocking Potential: Analyzing The Content, Style, Structure, And Interactivity Of Mesonets As Operational Dashboards, Savannah Olivas, Jeannette Sutton, Michele K. Olson

Emergency Preparedness, Homeland Security, and Cybersecurity Faculty Scholarship

Emergency managers need data and information to make life-saving decisions on behalf of the public. Operational dashboards, if designed appropriately, can provide this information in a central location and reduce cognitive demands during decision-making. Mesonet websites can serve as a type of operational dashboard that has the potential to provide the meteorological data necessary for emergency managers to make decisions. In this study, we use quantitative content analysis to examine the content, style, structure, and interactivity of 18 Mesonet websites from across the contiguous United States. We find that Mesonet websites vary in the type and amount of content they …

Assessing The Spatiotemporal Variability Of Aerosol Optical Depth And Particle Sizes In The Uae Atmosphere Using Remotely Sensed Data, Bashayer Ali Alzahmi

Theses

This thesis investigates atmospheric aerosol concentrations, with a particular focus on the United Arab Emirates (UAE). The study maps the spatial and temporal variations in Aerosol Optical Depth (AOD) and characterizes aerosols using high-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) products. The primary objective of this research is to enhance the understanding of aerosol dynamics in the UAE by distinguishing between natural and anthropogenic aerosols through the Angström Exponent (AE) and assessing their impacts on local climate, air quality, and public health. The study employs Remote Sensing (RS) techniques to conduct detailed environmental assessments, analyzing AOD variability across daily, monthly, seasonal, …

A Decentralized Digital Watermarking Framework For Secure And Auditable Video Data In Smart Vehicular Networks, Xinyun Liu, Ronghua Xu, Yu Chen

Michigan Tech Publications

Thanks to the rapid advancements in Connected and Automated Vehicles (CAVs) and vehicular communication technologies, the concept of the Internet of Vehicles (IoVs) combined with Artificial Intelligence (AI) and big data promotes the vision of an Intelligent Transportation System (ITS). An ITS is critical in enhancing road safety, traffic efficiency, and the overall driving experience by enabling a comprehensive data exchange platform. However, the open and dynamic nature of IoV networks brings significant performance and security challenges to IoV data acquisition, storage, and usage. To comprehensively tackle these challenges, this paper proposes a Decentralized Digital Watermarking framework for smart Vehicular …

San Diego Collaboration For Conservation: Sustaining The Region's Legacy Of Biodiversity Conservation, Tessa Tinkler, Darbi Berry, A-Bel Gong, Bryan Cardenas, Daniela Olguin, Connelly Meschen, Eo Hanabusa

Environment

We are living through significant environmental, social, political, and economic challenges. These challenges have strained our communities and humanbuilt systems, as well as our interconnected habitats, wildlife, and natural systems. Lack of adequate infrastructure to withstand natural disasters and climate change, as well as historical and presentday inequities in resources across neighborhoods, are examples of the multifaceted and interconnected threats contributing to the accelerated loss of our rich biodiversity. This natural abundance is integral to our region’s health, history, and continued prosperity.

Empowering Modernization Of National Emergency Management With New Generation Of Information Technology: Technology Foresight And Policy Recommendations Based On Typical Scenarios, Haibo Zhang, Xinyu Dai, Yi Peng, Yi Liu, Xue Lin, Yongjian Zhu, Wu Chen, Zhen Wu, Xinyue Qin, Depei Qian, Jian Lv

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the context of the new round of scientific and technological revolution, how to grasp the historical opportunity of supporting the development of the “overall safety and emergency response framework” with the NGIT, and promoting the transformation of the public safety governance to emphasis on prevention, is a pressing issue to be studied. This study focuses on five typical scenarios in emergency management, drawing on multiple rounds of expert interviews and questionnaire surveys to identify a list of critical technologies, analyze future development trends and constraints, and provide references for advancing relevant technological research and development. The study further emphasizes …

Typology Of Atmospheric Conditions Leading To Dam Overtopping In The Eastern Us, Hodo I. Orok, Deanna Hence

I-GUIDE Forum

Statistical characterization of reanalysis datasets during over 300 hydrologic dam incidents between 2003 and 2022 will create a detailed typology of weather systems associated with dam overtopping in the eastern United States. Dam overtopping poses significant risks to infrastructure and public safety, necessitating a comprehensive understanding of the multi-scale atmospheric conditions that lead to such events. To better account for the natural flow of water to the affected dams, we will adopt a watershed-focused Principal Component Analysis (PCA) on regional atmospheric data collected from ERA5 alongside USGS streamflow and Stage IV precipitation observations to enhance understanding of high-risk weather conditions. …

Operation And Management Of A Modern Park And Recreation System, Christopher Sullivan

Sustainability Seminar Series

The talk will focus on the various operational divisions which comprise most park and recreation agencies and how they work together to provide a modern park and recreation system to visitors, along with the common management challenges which face park and recreation agencies. On average, the Passaic County Department of Parks and Recreation employs 75 permanent employees and 113 seasonal. The department provides various recreation and environmental education activities throughout the year for all age levels, including a comprehensive K-5 elementary school based environmental education program which educates approximately 1,200 children per year and is available to all public and …

How Did The Deer Cross The Road? Reducing Habitat Fragmentation And Wildlife-Vehicle Collision Deaths Through Connective Conservation In The South Mountain Region, Pennsylvania, Jack B. Joiner, Emily R. Kreider, Thomas H. Manning, Madison E. Rowell

Student Publications

While some deleterious effects of road networks and the vehicles that travel them– such as pollution, fossil fuel extraction, and carbon emissions– are widely recognized, their significant role in causing an estimated one million wildlife deaths per day (Shilling et al., 2021) and contributing to habitat loss and degradation, the leading causes of global biodiversity decline (Pinto et al., 2023), has garnered less attention. Connective conservation policies, such as designating wildlife corridors and constructing wildlife crossings on roadways, have been proposed as a means of mitigating these repercussions. This study proposes a connective conservation plan addressing the logistics of a …

Zero-Shot Object Counting With Good Exemplars, Huilin Zhu, Jingling Yuan, Zhengwei Yang, Yu Guo, Zheng Wang, Xian Zhong, Shengfeng He

Research Collection School Of Computing and Information Systems

Zero-shot object counting (ZOC) aims to enumerate objects in images using only the names of object classes during testing, without the need for manual annotations. However, a critical challenge in current ZOC methods lies in their inability to identify high-quality exemplars effectively. This deficiency hampers scalability across diverse classes and undermines the development of strong visual associations between the identified classes and image content. To this end, we propose the Visual Association-based Zero-shot Object Counting (VA-Count) framework. VACount consists of an Exemplar Enhancement Module (EEM) and a Noise Suppression Module (NSM) that synergistically refine the process of class exemplar identification …

Measurement And Prediction Of Transit System Performance Using Probe Data Generated Through Dsrc And Non-Dsrc Technologies, Gregory L. Newmark

Mineta Transportation Institute

This research explores the application of two different probe data standards to transit performance measurement. The first section chronicles the proposed and implemented transit uses of dedicated short-range communication (DSRC) technologies during the two decades between the standard’s emergence and its announced sunset. The research finds that, despite proposed applications across safety, operation, and information domains, DSRC never became embedded in transit operations. By contrast, the general transit feed specification (GTFS) standard with its real-time (RT) extension has been widely embraced and offers the potential to use the associated VehiclePosition messages as probe data to generate detailed transit performance metrics. …