Digital Commons Network^™

Public Understanding Of Ai-Enabled Cyber Threats And Its Impact On Cybersecurity Governance In The United States, Charlotte M. Barbrick

LSU Master's Theses

Artificial intelligence is spreading quickly in workplaces and everyday life, and that fast growth is creating cybersecurity and privacy risks that current laws and organizational practices do not fully address. This thesis asks whether AI-specific knowledge shapes public support for cybersecurity governance of AI-enabled systems in the United States. Using nationally representative survey data from the Pew Research Center’s American Trends Panel (ATP) Wave 119, fielded December 12--18, 2022, I estimate weighted regression models to test how objective AI knowledge shapes support for cybersecurity governance. I also test whether concern about data misuse helps explain that relationship and whether AI …

Evaluation Of Remote Sensing Soil Moisture Datasets In Arid Regions And Their Prospect For Leak Detection In Water Distribution Systems, Alaa Shakfeh

Thesis/ Dissertation Defenses

This thesis is concerned with the evaluation of satellite-based soil moisture (SSM) datasets in arid regions and their potential application to leak detection in water distribution systems. The work focuses on the SMAP Level-4 soil moisture product and a Sentinel-1 SAR-based (SAR4SM) retrieval framework, used in conjunction with in-situ observations from the International Soil Moisture Network (ISMN) and historical leak records from the Al Ain Distribution Network (AADC), currently part of TAQA Distribution. The main objectives are (i) to quantify the performance of SMAP and SAR4SM surface soil moisture estimates over arid environments against ground-based measurements, and (ii) to develop …

Hypertext Transfer Protocol Fingerprinting: Techniques For Attacker-In-The-Middle Proxy Detection, Evasion, And Counter-Evasion, Jensen George Wood

Theses and Dissertations

Attacker-in-the-middle (AitM) phishing toolkits have emerged as a critical threat to enterprise and individual security by enabling adversaries to bypass multi-factor authentication (MFA) and compromise cloud-based accounts at scale. Traditional detection techniques--such as IP blocklists or content-based detection methods--are often ineffective against these increasingly sophisticated attacks. We propose a novel method that detects malicious proxies by identifying artifacts they introduce into HTTP request headers. To evaluate our approach, we systematically analyze traffic passed through several open-source AitM toolkits and proxies, identifying distinct modifications to header structures and content, then formalize these features as YARA rules for automated use. To validate …

Predictive Analytics In Oncology And Ophthalmology: Machine Learning Applications For Diabetic Retinopathy And Breast Cancer, Ali Abidalkareem

Electronic Theses and Dissertations 2020 - Present

The convergence of artificial intelligence and healthcare represents one of the most transformative developments in modern medicine, with deep learning technologies emerging as powerful tools for addressing complex diagnostic challenges. This dissertation develops and validates machine learning frameworks that address critical challenges in medical diagnosis through innovative approaches to data augmentation, feature learning, and classification, focusing on two fundamental problems: Diabetic Retinopathy (DR) severity classification using multi-model convolutional neural networks (CNNs), and breast cancer stage identification using microRNA (miRNA) gene expression biomarkers. For diabetic retinopathy classification, this work proposes an ensemble deep learning framework that integrates Diffusion-based data augmentation for …

Real-Time Data Collection System For Low-Cost Diesel Emissions Monitoring, Zachary Driskill

Theses and Dissertations

Diesel trucks are a major source of pollutants, including particulate matter (PM) and NO$_x$. Roadside emissions monitoring can identify high-emitting diesel vehicles, but conventional sensing systems rely on expensive, complex sensing instruments that limit widespread deployment. Low-cost sensors offer increased scalability due to their small size, low cost, and low power consumption, but they have lower accuracy and slower response time. This thesis presents the design and evaluation of a low-cost roadside emissions monitoring system, establishing the foundation for a scalable and widely deployable alternative. We apply machine learning calibration to roadside emission monitoring to improve the usability of low-cost …

Implementation And Evaluation Of Alternative Methods For Simulation Of Sidescan Sonar, Blake Paul Romrell

Theses and Dissertations

The original sonar implementation for the HoloOcean simulator was built upon a cached octree representation of the world. On first runs, building the cache was prohibitively slow, and the cache had a major memory footprint. This work presents alternative implementations for the sidescan sonar using direct raytracing on the CPU and rendering on the GPU. To evaluate and compare the implementations, timing tests on comparable parameters, as well as sweeps on resolution and range parameters, were performed. The render-based GPU implementation outperformed the others in the timing tests.

Engineering Problem Solving In First Robotics Competition, Jingyuan Fu

SACAD: Scholarly Activities

FIRST Robotics Competition is a program in which high school students design, build, and program robots for a new engineering challenge each year. Within that environment, robot development requires more than mechanical construction alone, since successful performance depends on strategy, subsystem integration, software development, and continuous iteration. This poster examines how game analysis shaped the robot’s overall development, including design priorities, system layout, material choices, and coding decisions. It also highlights how programming and tuning were used to improve subsystem performance and increase effectiveness in competition. This project demonstrates how the FIRST Robotics Competition can serve as a practical setting …

Application Of Fidic Epc/Turnkey Contract Under The Egyptian Public Works Contracts Law, Ahmed Alhady Dr., Mahmoud Mahmoud Ahmed Eng., Ahmed Elhakeem Prof., Mohamed Ibrahim Dr.

Civil Engineering

This study focuses on the application of FIDIC Conditions of Contract for EPC Turnkey Projects—Silver Book 1999, (FIDIC (EPC&T)), when governed by the Egyptian Law of Contracts concluded by public bodies No. 182 of 2018 (ELC) due to the conflicts that may arise from such application. Hence, this study identifies specific FIDIC (EPC&T) 1999 clauses that have the potential for conflicts with ELC, shows the similarities and disparities between these clauses and the relevant ELC articles, and provides recommendations to ensure the successful application of FIDIC (EPC&T) 1999 under ELC. This was achieved through a multistep research methodology in which …

Leveraging River Forecast Center Knowledge To Improve Large-Scale Hydrologic Model Performance Through Bias Correction, Ian Mathews

Theses and Dissertations

The National Water Model (NWM) provides continental-scale streamflow predictions but exhibits bias and reduced skill in highly regulated and snow-driven basins. In contrast, River Forecast Center (RFC) models incorporate decades of local calibration and regulatory knowledge but are limited in spatial coverage to specific points of interest. This study evaluates whether hydrologic knowledge embedded in RFC-calibrated simulations can be transferred to improve NWM performance at unmonitored locations using the Streamflow Analysis for Bias Estimation and Reduction (SABER) framework. Using Colorado Basin River Forecast Center (CBRFC) simulations as surrogate reference data, we applied SABER to the NWM 44-year retrospective model simulation …

Development Of New Methods For Calculating Pressure And Energy Losses For Pumping Station Water Intakes, Faxriddin Jaylovovich Nosirov, Oleg Yakovlevich Glovatsky, Jurabek Abdyrahmon O'G'Li Urolov, Abduqodirkhon Samatkhonovich Abdullakhaev, Anvar Mamur Ugli Uzokov

Technical science and innovation

The aim of this study is to improve the efficiency of water resource management methods. Improvements to the water intake of the Karshi Main Canal are considered using calculations of pressure losses at the entry and exit of liquid into the flow, which differ from pressure losses in a stationary medium. The article considers some of the methods for using renewable energy sources, where the change in gravitational potential energy does not depend on the way of using energy and the operating scheme is a gravitational energy pump. The implementation of control and monitoring systems is necessary to ensure optimal …

Impact Of Compositing Method Choice On Spectral Fidelity In Semi-Arid Mining Landscapes, Ruslan Nailevich Khadzhaev, Dilbarkhon Shamuradovna Fazilova

Technical science and innovation

This study examines the choice of satellite image compositing method for Landsat 8/9 (Collection 2 Level-2) imagery to calculate the Normalised Difference Vegetation Index (NDVI). This paper compares the methods used to create median and medoid composites for the Angren open pit coal mine. The 'synthetic' nature of the composites is quantified based on a spectral consistency metric. This involves assessing the equivalence of median and medoid values, and analysing the sensitivity of NDVI to the compositing method across varying surface types. A strongly right-skewed distribution of surface reflectance values was found, covering 82.8% of the pixels, mostly in areas …

Studying The Performance Of Photovoltaic Installations In The Pvsyst Software Package, Zukha Islamovna Juraeva, Isroil Abriyevich Yuldoshev I.A.Y., Islom Rakhmatovich Juraev

Technical science and innovation

This article simulates the operation of photovoltaic installations consisting of photovoltaic panels of crystalline and thin-film technologies. The calculations were performed in the PVSyst software package 7.4.8 version. In the calculations, the input parameters were environmental factors, the angle of inclination of the panels to the horizon. In calculating the values of the solar radiation flux density, the program selects the METEONORM climate database in accordance with the geographical area of the Tashkent city. The tilt angles of the photovoltaic panels of the installation were set manually by selecting specific values of the characteristic tilt angles in the range from …

Analysis Of Automatic Regulation Based On The Dynamic Indicators Of The Working Body For Cleaning Channels And Ditches, Nasiba Siraj Amirbayova

Technical science and innovation

Today, the comprehensive development of road infrastructure and agriculture directly requires the reconstruction and effective use of systems intended for irrigation and protection of road surfaces. The goal of agricultural development has made it necessary to increase attention to this area. This also reveals the correct use and operation of existing melioration irrigation systems as an important problem. This is mainly one of the issues of correct operation of road infrastructure. It is known that the majority of agricultural products are produced in areas where irrigation systems are widely developed. On the other hand, the use of collector-drainage networks, cleaning …

Analysis And Study Of Telemetry Systems For Directional And Horizontal Well Drilling, Jahongir Abdiganiyev Erkin Ugli, Sherali Halloqovich Umedov

Technical science and innovation

The article discusses the issues of reducing non-productive drilling time during the construction of directional and horizontal wells. The main focus is on the analysis of drilling conditions in complex geological and high-temperature environments. Particular attention is paid to drilling conditions in the territory of the Republic of Uzbekistan, with a specific study of data from the Boysun and Ustyurt regions. An analysis and study of the performance of telemetry systems available on the market, as well as their main technical characteristics, have been conducted. Key factors affecting the accuracy of wellbore trajectory measurements under various geological and technical conditions …

Refinement Of Wind Speed Estimation At Turbine Hub Height Using Satellite Data And Regression Analysis Under Complex Terrain Conditions, Isroil Abriyevich Yuldoshev, Tulqin Rustamovich Jamolov, Sa'dullo Sayfiddin Ugli Fazliddinov, Jumanazar Farhodjon OʻGʻL Abdurashidov

Technical science and innovation

Reliable assessment of wind energy potential in regions characterized by complex terrain is often constrained by the limited availability of ground-based meteorological measurements. This study proposes an improved regression-based approach for refining wind speed estimates at the wind turbine hub height of 65 m using satellite-derived data from the NASA POWER database combined with a logarithmic vertical wind profile. The proposed methodology is validated using real operational data from a 750 kW wind power plant located in the mountainous Bostanlyk district of Uzbekistan for the period 2018–2021. The regression analysis demonstrates a strong linear relationship between the extrapolated wind speed …

Design Of Virtual Impedance Controller For Parallel-Connected Converters In A Microgrid, Manyanda Makoye, Francis Mwasilu, Peter M. Makolo, Jackson Justo

Tanzania Journal of Science

This paper addresses the significant challenge of inaccurate power sharing among Distributed Generators (DGs) in islanded microgrids, which is primarily caused by mismatched feeder and line impedances. Conventional decentralized control solutions often fail to ensure accurate power sharing, especially when line impedances are resistive. To overcome this, the paper proposes a robust, coordinated Virtual Impedance Control (VIC) strategy for DGs. This method implements fixed virtual resistance and virtual inductance to standardize the output impedance characteristics of parallel-connected inverters, thereby minimizing impedance discrepancies and enhancing system stability through increased damping. The theoretical analysis and design of the VIC were validated through …

Sub-Nanometer Nanoclusters Of Copper Atop Single-Atom Copper Moieties Toward Electrochemical Co2 Hydrogenation To Methane, Ahmed Badreldin, Mohammad Bilal Minhas, Shengyao Wang, Gabriella Smith, Shaoqin Chen, Shiwen Wu, Carter Racine, Jin Feng, Yun Hang Hu, Tao Li, Ying Li

Michigan Tech Publications

The electrochemical CO2 reduction (eCO2R) offers a compelling route for converting CO2 into value-added fuels and chemicals. Among CO2-derived products, methane (CH4) occupies a distinct position, serving both as a key intermediate for emerging cascade electro-oxidation to oxygenates and as a strategically important extraterrestrial fuel that can be generated in situ from off-planet CO2 resources. Although Cu-based catalysts capable of selectively producing CH4 have been reported, they seldom sustain high selectivity at practically relevant current densities. Here, we created a single-step co-pyrolysis strategy toward generating and anchoring Cu sub-nanometer clusters (CuSNC) atop Cu-Nx single-atom (SA) motifs embedded within N-doped carbon …

Evaluating Fine-Scale Air-Quality Heterogeneity Using A Low-Cost Multipollutant Sensor Network In Twin Cities, Minnesota, Varuni Abhayaratne, Weixing Hao, Chen Ye, Anjana Yatawara, Philip K. Hopke, Jiayu Li, Yang Wang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

There is growing interest and effort in deploying low-cost sensors (LCSs) to understand fine-scale spatiotemporal heterogeneity of ambient air pollutants in urban areas. The Assessing Urban Air Quality project conducted by the Minnesota Pollution Control Agency deployed 45 low-cost air-quality monitors (AQMesh, Environmental Instruments Ltd.) in the Minneapolis/St. Paul metropolitan area network. Hourly averaged pollutant concentrations or mixing ratios for carbon monoxide (CO), ozone (O₃), nitrogen dioxide (NO₂), nitric oxide (NO), and sulfur dioxide (SO2), as well as particulate matter (PM), including PM1, PM2.5, and PM10, were obtained. The network data from June 2019 to June …

Escaping Isolation: An Analysis Of Virtual Machine And Container Breakout Vulnerabilities, Felix Iov

Cybersecurity Undergraduate Research Showcase

Cloud computing providers rely on multi-tenant architectures to maximize resource efficiency. This infrastructure depends on virtualization, which provides isolation between clients. This comes primarily in the form of Virtual Machines (VMs) and Containers. However, “breakout attacks” or “escapes” are a critical threat where attackers bypass these isolation layers to gain unauthorized access to the host system and neighboring environments. This paper surveys virtualization escape threats and analyzes three case studies: a runc container escape (Leaky Vessels), a VMware ESXi VM escape (VSOCKPuppet), and an NVIDIA GPU container escape (NVIDIAScape). Each demonstrates different attack surfaces, including file descriptor misuse, kernel driver …

Security Risks Of Ai-Generated Code In Software Development, Maame Agyekum

Cybersecurity Undergraduate Research Showcase

Artificial Intelligence(AI) has recently forced change globally, public Institutions and as well as national security. Advancement in machine learning, mixed datasets have enabled significantly powerful systems while being capable of operating at a large scale. As innovation and technological advancement increases at rapid pace, issues like a regulation gap where scientific development far exceeds the government’s ability to regulate and establish an effective oversight. As a result, Artificial Intelligence has been controlled by private companies, leading to an industry where speed and profit often outweigh safety and ethical responsibility.

Proxyconnec: A Lora-Based Proactive Safety Communication System For Off-Grid Environments, Shruti Bhandari, Roza Shaimurat

ATU Scholars Symposium

Remote environments lacking cellular or satellite coverage present significant safety challenges. ProxyConnec was developed as a point-to-point communication system using ESP32 microcontrollers and REYAX RYLR998 LoRa modules to provide off-grid monitoring.

The system implements a proactive heartbeat model in which a beacon device transmits a signal every 1,000 milliseconds. A base station monitors this connection using a 5,000 millisecond watchdog timer. If communication is interrupted, the system immediately triggers audible and visual alerts. Unlike conventional tracking devices that depend on manual SOS activation, this design treats unexpected signal loss as a potential safety event.

The manufacturer rates the selected LoRa …

Automatic Three Phase Balancing In Utility Applications, Ryan Morris

ATU Scholars Symposium

Balancing three-phase power has become more important as modern loads like EVs and large agricultural fans create fast and uneven changes in distribution systems. Manual balancing is slow, inconsistent, and often only done during certain “seasons,” which leaves long periods of imbalance. This paper reviews existing automatic methods such as the Fast-Switching Relay method, the Practical Balancing Algorithm, and the Phase-EQ system and highlights their benefits and limitations. Based on this analysis, a new method called the Predicted Practical Balancing Algorithm (PPBA) is proposed. The PPBA combines the stability of threshold-based switching with historical data to predict when imbalances are …

Comparison Of Anomaly Detection Methods On Event-Based Vision Sensor Data In A High Noise Environment, Will Johnston, Anthony L. Franz, Shannon R. Young, Rachel Oliver, Zachary Theis, Brian Mcreynolds, Michael L. Dexter

Faculty Publications

Event-based vision sensors (EVSs) provide unique frequency analysis opportunities due to their event data output and high temporal resolution. Anomaly detection methods used in hyperspectral analysis can be used on the event frequency spectra to detect targets. However, the introduction of a strong, flickering interfering source can reduce the EVS sensitivity and obscure targets of interest. Previous work presented a method showing that targets could still be detected through an overwhelming source using frequency analysis, background suppression, and statistical filtering. This paper extends that research and compares the ability of five different eigenanalysis anomaly detection methods (principal component background suppression …

Approach To Physics Education Using Local Ai With Rag For Open Educational Materials Generation, Dmitriy Beznosko

All Things Open

The new tool that starts to enter all parts of our life is AI – and it enters education as well. There are two standing large concerns with using AI for education – the safety of students’ data and the AI missing specific knowledge about the given class. The approach of using the Retrieval Augmented Generation (RAG) provides the user data to the locally run LLM model (using Ollama framework, a free and open-source tool that allows you to run large language models locally on your system) as a context for the generation of the OER materials. As this AI …

Digital Transformation And Market Microstructure: Analyzing The Impact Of Algorithmic Trading On National Stock Exchange Of India Price Discovery Mechanisms Through Complex Systems Theory., Mukesh Bhaskar Ahirrao, Harshal Anil Salunkhe, Vishal Sunil Rana

Northeast Journal of Complex Systems (NEJCS)

Abstract

This research examines the evolution of market microstructure at the National Stock Exchange of India (NSE) from 2020 to 2024, a period characterized by substantial growth in algorithmic trading from 35% to 44% of total trading volume. Using market microstructure data and analytical techniques grounded in complex systems perspectives, the study documents temporal patterns in price discovery, liquidity, volatility, and market efficiency associated with this digital transformation.

The analysis reveals several notable changes in market characteristics. Transaction costs improved significantly, with bid-ask spreads declining by 23.4% and market depth increasing by 18.1%. Price adjustment half-life decreased by 50%, indicating …

Arum–D Nexus: Adaptive Reflexive Urban Metabolism For Complex Construction And Demolition Waste Governance In Bengaluru, Talat Naaz, Rosewine Joy

Northeast Journal of Complex Systems (NEJCS)

Urban material systems exhibit nonlinear dynamics governed by feedback, adaptation, and emergent coupling among institutions, markets, and behaviors. Construction and demolition (C&D) waste in Bengaluru is a great example of such complexity, where fragmented regulation, informal actors, and digital asymmetries coalesce into unstable waste flows and resource leakages. This study conceptualizes Bengaluru’s C&D waste system as a Complex Adaptive System (CAS), where institutional, market, behavioral, and metabolic subsystems co-evolve through nonlinear feedback interactions. A meta-analysis of secondary literature combined with benchmarking of government datasets is used to evaluate two key complexity indicators, i.e., response speed and feedback density. The advancement …

Gas Lift Valve Operation Under Elevated Pressure And Temperature Conditions, Pedro O. De Melo Flores

LSU Master's Theses

Gas lift valves are critical components in artificial lift systems, and their performance directly influences well unloading efficiency and long-term production. Current industry models used to correct valve opening and closing pressure for temperature rely on assumptions that have not been extensively validated against experimental data. This study experimentally investigates the opening and closing behavior of injection pressure-operated (IPO) gas lift valves under controlled elevated-temperature conditions. A load rate test bench was modified to include a heating system capable of maintaining valve temperatures up to 220°F. Five gas lift valve designs from multiple manufacturers were tested over a range of …

Multiple-Valued Quantum Automata For Robotics, Yuchen Huang

Dissertations and Theses

This dissertation introduces a new type of quantum automata, their encoding and circuit realization. I concentrate on possible applications in robotics. Several methods and application of quantum automata and quantum circuit-based controllers for elementary robotic systems, with a focus on humanoid robot motion, emotion, and behavior generation are illustrated in detail. The research introduces several novel methodologies that bridge quantum computing principles with robotic control, aiming to overcome the limitations of classical deterministic and probabilistic approaches.

The dissertation first presents a quantum-circuit-based framework for generating non-repetitive and expressive (e)motions in a humanoid robot actor, using superposition and entanglement to produce …

Ai Method For Classification Of Diagnosis Of Near-Infrared Breast Lesion Images, Kaiquan Chen, Fangyang Shen, Honggang Wang, Zhengchao Dong, Jizhong Xiao, Ming Ma, Afroza Aktar, Christopher Chow, Wenxiong Zhang

Publications and Research

In near-infrared optical breast lesion screening and diagnosis systems, high-speed four-dimensional scanners can dynamically acquire tens of thousands of lesion images within a five-minute period. Currently, manual computer annotation is required to generate standard samples from these scanned breast lesion images, a process that depends heavily on physicians with clinical expertise. On average, a single physician can annotate only approximately ten samples per working day. As a result, this process is time-consuming and labor-intensive, and the collected samples often suffer from low accuracy, large variability, and limited diagnostic reliability. Several AI-based annotation tools, such as QuPath, HALO AI™, and X-AnyLabeling, …

Solving Wordle Using Information Theory, Talal Aladaileh, Donald Stephens, Mallak Alqaisi, Congyu Wu

Northeast Journal of Complex Systems (NEJCS)

Wordle, a popular word-guessing game, challenges players to identify a five-letter secret word through iterative guesses and feedback on letter placement. The players must figure out the secret word within six guesses. After each guess, the letters will be color-coded based on different criteria. Optimizing the choice of guesses is critical for maximizing success within the limited attempts allowed. In this study, the application of Shannon entropy is explored as a strategy for selecting words that maximize information gain at each step of the game. By quantifying the uncertainty reduction achieved by potential guesses, this method prioritizes words that are …