Digital Commons Network^™

Mbse For Process Analytical Technology- Bwon Analysis Case Study, Arnaldo Garcia Cervantes

Open Access Theses & Dissertations

Volatile Organic Compound (VOC) emissions from industrial sources, particularly Benzene, present significant environmental and public health challenges. Regulatory frameworks, such as the U.S. Environmental Protection Agency’s Benzene Waste Operations NESHAP (BWON), mandate strict monitoring of control devices, specifically carbon adsorption canisters, to prevent emission breakthrough. However, current industry practices rely heavily on manual Method 21 testing, a labor-intensive process that creates lagging indicators and increases the risk of non-compliance events. This thesis proposes the design and development of an on-line, automated fugitive emissions monitoring system tailored for carbon canisters using Model-Based Systems Engineering (MBSE). Utilizing the Object-Oriented System Engineering Method …

Impacts Of Nutrient Addition And Disturbance On Coastal Dune Arthropod Communities And Trophic Interactions, Kayla Beitzel

Graduate Theses and Dissertations (2019 - present)

Coastal dune ecosystems face ongoing threats from human-mediated disturbance and altered resource availability. Because these dunes provide critical habitat for many organisms, including shorebirds, beach mice, and arthropods, changes in disturbance regimes or resource availability can impact plant communities and higher trophic levels by altering plant richness and productivity, which in turn influence arthropod abundance and diversity. To examine how disturbance and nutrient addition affect arthropod communities, we established twenty 5×5 m plots on Dauphin Island, crossing mechanical disturbance with a 10 g m⁻² addition of nitrogen, phosphorus, and potassium, replicated across five experimental blocks. Arthropods were sampled using three …

Performance Enhancement For Rufa: Rapid Urban Forest Assessment, Nicholas Tan

Master's Theses

Urban forests are crucial to the livability and resilience of cities, offering critical ecosystem benefits such as air quality enhancement, temperature regulation, and biodiversity. Managing said urban forests is essential to ensure their sustainability and adaptability to rapidly changing environmental and climate conditions. The Rapid Urban Forest Assessment (RUFA) tool was developed to address the need for a standardized approach to evaluating and comparing urban and community forestry programs. By analyzing and aggregating tree-specific data across California, such as canopy cover, tree counts, and diversity scores, RUFA assigns a comprehensive urban forestry score for each city. This score allows for …

Peptoid-Based Molecular Analysis Utilizing High-Speed Molecular Dynamics Methods, In Chul Hwang

LSU New Orleans Theses and Dissertations

Polypeptoids are N-substituted glycine polymers, which differ from peptides in the placement of the side chain being present on the amide nitrogen rather than the backbone C_α. While both peptoids and peptides are composed of linked amino acids, the structural changes resulting from the differing origin of the side chain leads to distinct backbone structure, as well as remove the chirality found in the peptide structure. These differences lead peptoids to have different physiochemical and biological properties, such as being resistant to proteolysis and diverse three-dimensional structures that are not observed in peptides. With the shifting of the …

Evaluating Utilidor Performance And Ground Temperature Variability In UtqiaġVik, Tate Rachow

Geosciences

Permafrost degradation in Arctic regions poses increasing risks to infrastructure as climate warming accelerates thaw processes, alters hydrology, and deepens the active layer. In Utqiaġvik, Alaska, utilidors— utility conduits—play a vital role in protecting water and wastewater services, yet their thermal performance under changing conditions remains poorly constrained. This thesis evaluates the thermal behavior of the Site U-1 direct buried pipes on Stevenson Street using historical thermistor resistance data converted to temperature, combined with calibrated two- dimensional TEMP/W numerical models. The models incorporate layered backfill materials and polyurethane insulation, while also simulating operational influences of water and wastewater temperatures. Calibration …

Engineering Risk And Indigenous Resilience Toward Intelligent Decision Support For Mining In Ancestral Lands, Izech Brian O. Edwin, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

Mining within ancestral territories reveals an ongoing conflict between technical viability and Indigenous consent. This collaborative study, conducted by an engineering scholar and a policy researcher of Indigenous heritage in Benguet among the Ibaloi and Kankanaey peoples, investigates how risk transparency and policy alignment can bridge existing divides, while formulating principles applicable to other Indigenous mining contexts. The study provides an initial evaluation of the feasibility of a proposed large-scale mining operation within a risk-informed, data-driven governance framework. Three elements of engineering risk were assessed utilizing literature-derived and proxy parameters: (1) Land degradation is indicated by a Soil Productivity Index …

Proverag: Provenance-Driven Vulnerability Analysis With Automated Retrieval-Augmented Llms, Reza Fayyazi, Stella Hoyos Trueba, Michael Zuzak, Jay Yang

Institute for Informatics and Applied Technology Scholarship

In cybersecurity, security analysts constantly face the challenge of mitigating newly discovered vulnerabilities in real-time, with over 300,000 vulnerabilities identified since 1999. The sheer volume of known vulnerabilities complicates the detection of patterns for unknown threats. While LLMs can assist, they often hallucinate and lack alignment with recent threats. Over 40,000 vulnerabilities have been identified in 2024 alone, which are introduced after most popular LLMs’ (e.g., GPT-5) training data cutoff. This raises a major challenge of leveraging LLMs in cybersecurity, where accuracy and up-to-date information are paramount. Therefore, we aim to improve the adaptation of LLMs in vulnerability analysis by …

Water Circulation Beneath A Hovering Suas For Water Quality Monitoring Applications, Erin E. Hackett, Boone Fleenor, Jensine C. Coggin, Duvall Dickerson-Evans, Nikolaos Vitzilaios, Whitney E. Schuler, Paige K. Williams, Michael L. Myrick

Faculty Publications

Water quality has traditionally been measured via in situ sensors and satellites. The latter has limited applicability for smaller inland water bodies, while the former requires significant logistics, labor, and expense for routine sampling, and reactive/spurious sampling is often not feasible as a result (e.g., sampling pre-/post-storm). Consequently, small uncrewed aircraft system-based (sUAS-based) sampling has emerged as a potential solution to bridge these sampling gaps and challenges. But sampling from an sUAS is complicated by the need to pump water from depth, rather than suspending a sensor from the sUAS, due to concern over sampling sUAS-impacted waters. Here, we measure …

The Impact Of Screentime In Childhood, Kyla P. Shirley

Informatics

The increased dependency on technological devices as a result of the digital age being upon us impacts a multitude of individuals from all age groups. For older groups, they might find an easier time navigating the world wide web due to their awareness of the potential dangers these digital spaces may bring. On the other hand, younger age groups are more susceptible to the dangers posed due to their lack of maturity which in turn makes them extremely vulnerable to being negatively impacted when using these electronic devices. The goal of this project was to generate awareness concerning screen time …

Soil Organic Carbon Depth Profiles And Centennial And Millennial Decay Rates In Tidal Marsh, Mangrove And Seagrass Blue Carbon Ecosystems, Nerea Piñeiro-Juncal, Miguel Ángel Mateo, Carmen Leiva-Dueñas, Eduard Serrano, Karina Inostroza, Montserrat Soler, Eugenia T. Apostolaki, Paul Lavery, Carlos M. Duarte, Anna Lafratta, Oscar Serrano

Research outputs 2022 to 2026

The management of coastal blue carbon ecosystems can contribute to mitigate anthropogenic greenhouse gas emissions. However, limited information on soil organic carbon (OC) decay rates in tidal marsh, mangrove, and seagrass soils hinders their inclusion in climate strategies and carbon-crediting schemes. Here, we analyzed downcore OC trends in 3761 soil cores from blue carbon ecosystems worldwide. A decrease in OC content with soil depth was measured in 63% of the cores, whereas stable and increasing trends were observed in 22% and 15% of the cores, respectively. Based on 85 profiles where OC decay could be modelled, the OC decay rate …

Social Media Mining For Extracting The Experience Of Neurodivergent Individuals On Twitter (X) And Reddit, Kartik Thakkar

All Graduate Theses and Dissertations, Fall 2023 to Present

Neurodiversity refers to the natural neurological variations in the human brain such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), dyslexia, dyspraxia, Tourette syndrome and other neurological disorders. it’s estimated that around 15% to 20% of the world’s population is neurodivergent. This means a significant portion of people experience neurological differences in how they think, learn, and interact with the world.

Social Media has become an important space for neurodivergent individuals to share their experiences, build communities, and seek support. This thesis explores how the online venues like X (Twitter) and Reddit offer themselves as digital spaces where …

Agentguard: An Active Threat Discovery System For Package Confusion Using Multi-Agent Collaboration, Wei Ma, Yu Li, Zhi Chen, Ye Liu, Lingxiao Jiang, Qiang Hu, Junyi Tao

Research Collection School Of Computing and Information Systems

The proliferation of open-source software (OSS) has made software supply chains prime targets for attacks like Package Confusion, where adversaries publish malicious packages with names deceptively similar to legitimate ones. Existing detection methods often rely on simple lexical similarity or passive analysis of known package pairs, struggle with high false positive rates (FPR), fail to proactively identify emerging threats, and are vulnerable to adversarial evasion. To overcome these limitations, we introduce AgentGuard, a novel framework for proactive, single-input package confusion detection. AgentGuard employs a multi-agent architecture that autonomously discovers potential confusion targets using fine-tuned word embedding model to hybird semantic …

Registration Is A Powerful Rotation-Invariance Learner For 3d Anomaly Detection, Yuyang Yu, Zhengwei Chen, Xuemiao Xu, Lei Zhang, Haoxin Yang, Yongwei Nie, Shengfeng He

Research Collection School Of Computing and Information Systems

3D anomaly detection in point-cloud data is critical for industrial quality control, aiming to identify structural defects with high reliability. However, current memory bank-based methods often suffer from inconsistent feature transformations and limited discriminative capacity, particularly in capturing local geometric details and achieving rotation invariance. These limitations become more pronounced when registration fails, leading to unreliable detection results. We argue that point-cloud registration plays an essential role not only in aligning geometric structures but also in guiding feature extraction toward rotation-invariant and locally discriminative representations. To this end, we propose a registration-induced, rotation-invariant feature extraction framework that integrates the objectives …

Rising From Ashes: Generalized Federated Learning Via Dynamic Parameter Reset, Jiahao Wu, Ming Hu, Yanxin Yang, Xiaofei Xie, Zekai Chen, Chenyu Song, Mingsong Chen

Research Collection School Of Computing and Information Systems

Although Federated Learning (FL) is promising for privacy-preserving collaborative model training, it suffers from low inference performance due to heterogeneous client data. Due to heterogeneous data across clients, FL training easily learns client-specific overfitting features. Existing FL methods adopt coarsegrained averaging, which can easily cause the global model to get stuck in local optima, leading to poor generalization. Specifically, this paper presents a novel FL framework, FedPhoenix, to address this issue. It stochastically resets partial parameters in each round to destroy some features of the global model, guiding FL training to learn multiple generalized features for inference rather than specific …

Efskip: A New Error Feedback With Linear Speedup For Compressed Federated Learning With Arbitrary Data Heterogeneity, Hongyan Bao, Pengwen Chen, Ying Sun, Zhize Li

Research Collection School Of Computing and Information Systems

Due to the communication bottleneck in distributed and decentralized federated learning applications, algorithms using compressed communication have attracted significant attention. The Error Feedback (EF) is a widely-studied compression framework for convergence with biased compressors such as top-k sparsification. Although various improvements have been obtained in recent years, the theoretical guarantee for EF-type framework is still limited. Previous works either 1) rely on strong assumptions such as bounded gradient/dissimilarity assumptions, thus can not deal with arbitrary data heterogeneity and also slow the convergence speed, or 2) can not enjoy linear speedup in the number of clients. In this work, we propose …

Scalable Graph Indexing Using Gpus For Approximate Nearest Neighbor Search, Zhonggen Li, Xiangyu Ke, Yifan Zhu, Bocheng Yu, Baihua Zheng, Yunjun Gao

Research Collection School Of Computing and Information Systems

Approximate nearest neighbor search (ANNS) in high-dimensional vector spaces has a wide range of real-world applications. Numerous methods have been proposed to handle ANNS efficiently, while graph-based indexes have gained prominence due to their high accuracy and efficiency. However, the indexing overhead of graph-based indexes remains substantial. With exponential growth in data volume and increasing demands for dynamic index adjustments, this overhead continues to escalate, posing a critical challenge.In this paper, we introduce Tagore, a fasT library accelerated by GPUs for graph indexing, which has powerful capabilities of constructing refinement-based graph indexes such as NSG and Vamana. We first introduce …

Llm-Assisted Cwe Identification, Severity Assessment, And Vulnerability Description Generation, Mohammad Jalili Torkamani

School of Computing: Dissertations, Theses, and Student Research

Identifying the underlying weakness types and assessing their severity using CWE and CVSS standards are critical steps in software vulnerability management. While timely assessment of vulnerabilities mitigates the impact of severe security incidents, automating joint CWE identification and severity assessment remains challenging due to the heterogeneity of vulnerabilities across different code granularities and programming languages. In addition, generating vulnerability descriptions is often time-consuming, as it requires extensive manual review, validation, and writing by security experts.

In this thesis, we leverage the capabilities of Large Language Models (LLMs) to automate the identification of CWE identifiers and the assessment of their severity …

Evaluating The Preparedness Of Local Zoning Regulations For Flood Risk Reduction In The Most Affected Local Jurisdictions In Nebraska, Md Asaduzzaman Noor

Community and Regional Planning Program: Theses

Flooding has profound social, economic, and environmental impacts on local communities, and zoning plays a critical role in mitigating these risks. The 2019 Nebraska floods, among the most severe in the state’s history, highlighted the urgent need to strengthen local preparedness and mitigation strategies. This study assesses the extent to which local zoning regulations in Nebraska’s most affected jurisdiction, including rural areas, address flood risk reduction. A systematic review of 117 zoning ordinances from counties, cities, towns, and villages, we applied a structured analytical framework encompassing regulatory and permitting policies, voluntary and incentive-based measures, and nature-based solutions. The results show …

Bridging Conservation And Disaster Recovery: A Dual Study On Wetland Program Plans Evaluation And Midwest Post Disaster Recovery Assessment, Rao Nargis Jahan

Community and Regional Planning Program: Theses

Wetlands provide essential ecological, social, and economic benefits for our society. In the United States, states and tribes play crucial roles in wetland protection, restoration, and management. However, no research has systematically measured state-level wetland planning efforts towards national conservation goals. This study is the first to comprehensively evaluate how state-level Wetland Program Plans (WPPs) align with national missions, particularly the "no-net-loss" of wetlands goal. Our research assesses the EPA-approved state-level WPPs from 42 out of 50 states in the United States during the period from 2015 to 2024. Using a protocol of 30 indicators across five categories, this study …

Final Quarterly Operations And Maintenance Report Butte Treatment Lagoon System – First Quarter 2024, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Synthetic Dataset For Understanding Negation In Text-Guided Image Editing, Nhat-Tan Bui

Graduate Theses and Dissertations

Negation is a fundamental linguistic concept used by humans to convey information that they do not desire. Despite this, minimal research has focused on negation within text-guided image editing. This lack of research means that vision-language models (VLMs) for image editing may struggle to understand negation, implying that they struggle to provide accurate results. One barrier to achieving human-level intelligence is the lack of a standard collection by which research into negation can be evaluated. This thesis presents the first large-scale dataset, Negative Instruction (NeIn), for studying negation within instruction-based image editing. Our dataset comprises 366,957 quintuplets, i.e., source image, …

Programmable Network Approaches To Resilience And Security In Phasor Measurement Unit Networks, Zhiyao He

Graduate Theses and Dissertations

The security and resilience of smart grids are critical for ensuring reliable and stable power delivery. As modern power systems evolve to incorporate more advanced sensing and control capabilities, Phasor Measurement Units (PMUs) have become an important source of high-frequency, time-synchronized measurements that support wide-area monitoring, control, and protection. However, the growing complexity of smart grids and their reliance on real-time communication expose them to a range of cyber threats, including data loss, tampering, and coordinated attacks. This dissertation explores the use of programmable network technologies, particularly P4-based programmable switches, to provide in-network solutions that enhance the reliability and security …

Privacy Protection In Cloud-Based Biometric Systems, Yatish Reddy Dubasi

Graduate Theses and Dissertations

The widespread adoption of server-based biometric authentication systems, often hosted in the cloud, has introduced significant privacy risks. While these systems offer convenience, they require storing sensitive biometric templates on remote servers, creating a high-value target for adversaries. Unlike passwords, compromised biometric data is immutable and cannot be reissued, leading to an irreversible loss of privacy. This threat is exacerbated by template inversion attacks, which can reconstruct a user's original biometric trait (e.g., a face image) from its stored feature vector. This dissertation addresses these critical privacy challenges by designing, implementing, and evaluating a suite of novel frameworks for privacy-preserving …

When The Grid Goes Dark: A Digital Forensics Study Of Industrial Control System Cyberattacks, Katie Kettler

Graduate Theses and Dissertations

Industrial Control Systems (ICS) and Operational Technology (OT) maintain the grid, ensure water safety, and keep transportation running. Because they influence nearly every aspect of daily life, these systems have become prime targets for cyberattacks. The need for this research arises from the fact that when ICS and OT systems are compromised, the consequences go beyond data loss, and they can directly disrupt communities and endanger public safety. This thesis introduces digital forensics fundamentals and explains how investigations in ICS environments differ from those in traditional IT environments. This work then examines major attacks, including Stuxnet, the Ukrainian Grid Attacks …

Soil Characterization With Proximal Geophysics, Sophia M. Becker

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

High quality soil data is crucial for addressing numerous threats to human well-being such as water scarcity, food insecurity, and intensified natural disasters. True soil property values are determined by analyzing soil samples in a laboratory, but soil sampling is often expensive and time-consuming. Some in-field point sensors and remote sensing products are available to measure soil properties, but they have inherent limitations in measurement extent and resolution. Geophysical methods can fill the measurement scale gap between point measurements and remote sensing products, but various research questions remain open. This dissertation aims to advance understanding of geophysics-derived soil property measurements …

Investigating Molecular Rotation And Vibration With Ultrafast Electron Diffraction, Haoran Zhao

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

Ultrafast electron diffraction (UED) has emerged since the late 20th century as a powerful technique for resolving molecular dynamics. With its high spatial and temporal resolution, UED can now measure rotational motion induced by linearly polarized, nonresonant, nonadiabatic laser pulses—one of the fundamental molecular degrees of freedom with broad applications. By combining laser-induced alignment with UED, new capabilities such as three-dimensional structural retrieval and isotope detection have been demonstrated, as discussed in Chapter 2.

In Chapter 3, three symmetry relations in the coefficients of rotational wave packets are identified and derived, reducing the computational cost of simulating asymmetric-top molecular alignment …

Electrical And Magnetic Properties Of Ferroic Oxide Thin Films And Free-Standing Membranes, Qiuchen Wu

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

This dissertation presents a comprehensive study of the electrical, magnetic, and transport properties of epitaxial ferroic oxide thin films and free-standing membranes, including ferroelectric PbZr_0.2Ti_0.8O₃ (PZT) and ferrimagnetic NiCo₂O₄ (NCO).

We evaluate the effects of electrostatic and mechanical boundary conditions on the ferroelectric properties of free-standing PZT membranes by transferring them on three types of base layers: the metallic Au, strongly correlated oxide La_0.67Sr_0.33MnO₃ (LSMO), and 2D semiconductor MoS₂. The coercive field and domain wall roughness depend sensitively on the metallicity and surface roughness of …

N-Aryl Phenoxazines As Polymer Supported Photocatalysts, Mary Kathryn Hall

Master's Theses

In photosynthesis, the energy of sunlight is perfectly harnessed to facilitate the production of small molecules that are essential for plant life on earth. Inspired by this model of energy efficiency and simplicity, this work seeks to mimic that ability to use the energy in visible light to perform new and more efficient chemistries. Just like in photosynthesis, photocatalysts can act as chromophores absorbing light to excite electrons opening new pathways for previously untapped reactivity. Recent research has provided a wide range of small molecule reactions that are made possible or easier by the use of a photocatalyst. However, these …

Definition Of The 3d Position And Motion Status Of The Moving Heart Based On 2d Projections, Lawrence D. Orijuela

Electronic Theses, Projects, and Dissertations

This thesis presents a novel application of deep learning to the estimation of pulmonary vein coordinates using X-ray image pairs from a FORBILD Thorax phantom derived motion dataset. A Siamese neural network was developed to predict the 3D coordinates of one pulmonary vein at a time, specifically the Right Superior Pulmonary Vein (RSPV), Left Superior Pulmonary Vein (LSPV), Left Inferior Pulmonary Vein (LIPV), or Right Inferior Pulmonary Vein (RIPV), based on two-dimensional projection images.

The input data consisted of over 1.6 million grayscale X-ray image pairs across 1331 virtual patients, each annotated with ground truth 3D coordinates. To manage memory …

Marsanywhere: Dataset And Cross-View Diffusion Model For Satellite-To-Ground View Synthesis With Mars Data, Benjamin T. Hinchliff

Master's Theses

Satellite-to-ground view synthesis aims to create a realistic ground view image from a corresponding satellite view image. This is a well-studied problem for street level imagery, with good results being achieved by using modern image synthesis techniques such as diffusion models. However, despite the public availability of satellite and ground level imagery on Mars, these techniques have yet to be applied to the domain due to difficulties in collating and processing the data into a usable form. We address this deficiency by creating a dataset consisting of ground view panorama imagery from the Perseverance rover, along with associated satellite view …