Digital Commons Network^™

Surviving And Thriving In The Hybrid Cloud: A Review Of The Current Cloud Computing Landscape, Peter Munsch, Alison Munsch

Journal of International Technology and Information Management

Background and Purpose

Both academic and industry institutions have increasingly migrated essential services to public cloud providers (e.g., Microsoft, AWS, Google) with mixed outcomes. Some industry leaders attempted to fully replace their on-premises data centers with public cloud services, a move not advised without thorough performance and cost analyses (Potel, 2023). Despite some organizations pulling back from the “Cloud First” strategy, the public cloud services market continued to grow, with revenue increasing by approximately 20% year-over-year since 2020 and surpassing half a trillion dollars in 2022 (IDC Worldwide Semiannual Public Cloud Services Tracker, 2H 2022). Cloud technologists suggested that hybrid …

Predicting Global Healthcare Supply Chain Delays: A Machine Learning Approach Leveraging Country-Level Logistics Metrics, Jeevan Sai Gali, Nima Molavi, Sepideh Alavi

Journal of International Technology and Information Management

In global healthcare logistics, ensuring the timely delivery of medical commodities is critical, particularly in low- and middle-income countries characterized by infrastructural limitations and operational uncertainties. This research introduces an advanced, data-driven predictive framework designed to forecast delivery delays by synthesizing granular, internal shipment-level data from the USAID Global Health Supply Chain Program (GHSC-PSM) with external country-level logistics capabilities indicators derived from the World Bank’s Logistics Performance Index (LPI). Rather than relying on retrospective trend analyses, this study employs machine learning algorithms such as Random Forest, XGBoost, Support Vector Machines (SVM), and Multi-Layer Perceptron (MLP) to detect …

Microscopic Analysis Of Temperature Effects On Surface Colonization And Biofilm Morphology Of Salmonella Enterica, Zachariah Vice, You Zhou, Sapna Chitlapilly Dass, Rong Wang

Nebraska Center for Biotechnology: Faculty and Staff Publications

Salmonella enterica represents a diverse group of pathogens commonly associated with food contamination including red meat. Even though pre- and post-harvest cleaning and sanitization procedures are widely implemented at meat processing plants to mitigate the hazard, S. enterica cells may escape the process by colonizing, on contact, surfaces in the form of a biofilm that functions as an aggregated microbial community to facilitate mutual protection, antimicrobial resistance, proliferation and dissemination. Biofilm development is a complex process that can be affected by a variety of factors including environmental temperature. We developed methods using scanning electron microscopy and confocal microscopy with a …

Detecting Ai-Generated News Articles Using Unsupervised Machine Learning Algorithms, Lilou Sicard-Noel

Master's Projects

The widespread adoption of Large Language Models (LLMs) has revolutionized text generation and heightened concerns over misinformation and the erosion of journalistic integrity. Detecting AI-generated text is critical to addressing these challenges, yet current detection methods face adaptability, scalability, and accuracy limitations. This research paper uses machine-learning techniques to explore the classification of human and AI-generated articles, including a mix of human and AI-written content. The primary focus is on evaluating the effectiveness of clustering algorithms (K-Means and Agglomerative Clustering), auto-encoders, and Part-Of- Speech Tag Transition Matrix Log-Likelihood for distinguishing between AI-generated and human-written texts. Our findings reveal that while …

Image-To-Text Transcription: Analyzing And Describing Visual Content, Zixiao Fan

Master's Projects

Image captioning, which provides a textual understanding of visual content, is the fundamental support for the advancement of Human-A.I. Interaction technology. In the hope of exploring the application of such technology, this project focuses on two specific goals. One is to directly explore the application of the image informationretrieving abilities, and the other is to dive into the specifics of the pipeline and components of image captioning models. As a result, this project presents a working app that exploits the text retrieval functionalities to enable image storage with functions like tagging and transcription. It also supports search functionality with a …

Extraction Of A Knowledge Graph Of Biomedical Relationships, Brian Tran

Master's Projects

Rapid release in biomedical literature poses a challenge in linking information. This thesis aims to extract data from expanding datasets to identify and form meaningful relationships between biomedical entities. Large language models (LLMs) enable us to learn at a rapid pace. Creation of LLms from scratch are impractical. This thesis aims to collect a small dataset, containing biomedical papers, and use it to train large language models (LLMs) to extract entities from the text and learn the relationships between these entities. The experiment will be divided into two stages and utilize EU-ADR and ChemProt dataset. Starting with named entity recognition …

Galora: A Lightweight Graph-Aware Llm Framework For Node Classification On Text-Attributed Graphs, Mayur Choudhary

Master's Projects

With the exponential rise of language models (LMs) and their potential to understand semantic relationships, large LMs are being used across a wide range of applications. Text-attributed graphs (TAGs) are one notable example where LLMs can be combined with Graph Neural Networks (GNNs) to enhance node classification results. TAGs associate textual content with each node and are commonly seen in various domains such as social networks, citation graphs, recommendation systems, etc. Effectively modeling TAGs would enable deeper insights into different aspects of the graph and improve decision-making in relevant domains. We present GaLoRA, a parameter-efficient framework to integrate structural information …

Optimizing Integrated Access And Backhaul Topology Using Monte Carlo Tree Search, Srimanth Reddy Ummenthala

Master's Projects

Integrated Access and Backhaul (IAB) plays a central role in enabling scalability and high-throughput in wireless networks, especially in areas where wired backhaul is not feasible. Optimizing the topology of IAB networks is a complex task, involving trade-offs between path loss, node capacity, and link quality. To address this, this project investigates a Monte Carlo Tree Search (MCTS)-based approach to improve overall network performance by maximizing the capacity of network, considering Signal-to-Noise Ratio (SNR) on wireless links. MCTS provides a guided search mechanism to construct topologies efficiently under the constraints and is evaluated against baseline topologies. Experimental results show that …

Synthetic Malware Generation Using Generative Ai, Phanidhar Sai Sravan Chandana

Master's Projects

Malware grows in numbers and complexity, evading conventional signature-and anomaly-based defenses and worsening extreme data sparsity and class imbalance problems for machine learning based detection. Generative models, specifically GANs conditioned on contextual embeddings like BERT have proved effective augmenting training corpora to improve classifier accuracy, but these approaches have largely produced family-specific samples In this paper, we propose a generalized augmentation scheme for generating robust malware embeddings for various families. We begin by extracting opcode sequences from 13 malware families and encoding them into three embedding methods: CountVectorizer, TF-IDF, and BERT’s ‘[CLS]‘ vectors. We therefore train standard GANs and Wasserstein …

Bot Detection In Social Media Using Graphsage And Bert, Abhishek Deshmukh

Master's Projects

This project details a novel bot detection system developed to battle the ever- changing challenge of disinformation, misinformation, and other bot-generated content.

The methodology employed in this project combines the text-based analytical strength of BERT (Bidirectional Encoder Representations from Transformers) with the strength of GraphSage (Graph Sample and Aggregation) for analyzing network structures. The project concatenates BERT and GraphSage vectors to create an 896-size feature embedding with a rich blend of network and text features. This project employs a Support Vector Machine to process the concatenated embeddings, as SVM works well with high-dimensional data. This project was evaluated on two …

Social Engineering Scenario Generation For Awareness-Based Attack Resilience, Jade Webb

Master's Projects

Social engineering is found in a strong majority of cyberattacks today, as it is a powerful manipulation tactic that does not require the technical skills of hacking. Calculated social engineers utilize simple communication to deceive and exploit their victims, all by capitalizing on the vulnerabilities of human nature: trust and fear. When successful, this inconspicuous technique can lead to millions of dollars in losses. Social engineering is not a one-dimensional technique; criminals often leverage a combination of strategies to craft a robust yet subtle attack. In addition, offenders are continually evolving their methods in efforts to surpass preventive measures. A …

Cca Analysis Using Computer Vision Techniques, Rahul Thakur

Master's Projects

Coral reefs are an essential part of the marine ecosystem. They perform a wide variety of tasks, some directly and others indirectly. They can produce oxygen, absorb carbon dioxide, along with supporting ocean habitat. Crustose Coralline Algae (“CCA”) plays an important role in helping provide structural support to Coral Reef ecosystems. However, global warming is causing ocean water to become more acidic resulting in coral bleaching. This is leading to changes in coral environments and causing coral deaths at alarming rates. Object detection using computer vision techniques, specifically deep learning, can help to monitor coral reef health and identify CCA …

Machine Learning Based Network Traffic Classification With Cosine-Similarity Based Out-Of-Distribution Detection, Prabhat Edupuganti

Master's Projects

The changes occurring in the amount of encrypted network traffic is growing at an alarming rate. This development has created intricate problems in traffic classification which is vital for effective cybersecurity. Moreover, most frameworks seem to ignore OOD detection, model calibration and novel pattern detection as cornerstone problem areas. The due analysis is presented as a machine learning approach aimed at resolving encrypted traffic classification issues and focuses on novel OOD detection and calibration issues. Primary contributions comprise detection of out-of-distribution states using softmax scaled cosine similarity, advanced variance-based feature elimination, and lowering ECE using stringent NNs. This work demonstrates …

Real-Time Adaptive Framework For Topic Modeling In Social Engineering Attacks, Manav Bhasin

Master's Projects

Detecting social engineering attempts is crucial for security, as these threats are becoming more frequent and increasingly exploit human vulnerabilities. This research focuses on topic modeling using conversational data from Kevin Mitnick’s ”The Art of Deception” with dialogues that illustrate various social engineering strategies. The dataset comprises manually extracted and synthetically augmented conversations to ensure natural dialogue flow. Two methodologies are presented for utterance-level and global topic extraction: prompt engineering leveraging OpenAI’s GPT-4o-mini, characterized by few-shot learning and chain-of-thought prompting, and Quantized Low Rank Adaptation (QLoRA) utilizing Mistral’s 7B instruct model for efficient fine-tuning. Through experimentation and evaluation, this study …

Key Steering Characteristics For Training Remote Operators Of Maritime Autonomous Surface Ships In Collision Avoidance, Soyeong Lee, Ik-Hyun Youn

Journal of Marine Science and Technology–Taiwan

Maritime Autonomous Surface Ships (MASS) require remote operators (ROs) who need to be trained in collision avoidance (CA) maneuvers. In order to develop a training system, this study investigated differences in the steering characteristics of expert and novice navigators such as the timing of the initial rudder operation, rudder angle at a relative bearing 0°, heading at the maximum rate of turn to starboard, and, heading at the closest point of approach. The experts exhibited relatively consistent and controlled steering patterns characterized by earlier rudder adjustments and smoother heading transitions while novices demonstrated delayed reactions and greater variability in heading …

In-Situ And Laboratory Sound Velocities Of Unconsolidated Sediments In The Western South Korea Plateau Of The East Sea, Kiju Park, Gil Young Kim, Yuri Kim, Bo Yeon Yi, Nyeon Keon Kang, Gwang Soo Lee

Journal of Marine Science and Technology–Taiwan

The in-situ velocity of unconsolidated shelf sediments in the western South Korea Plateau of the East Sea was directly measured using the Korea Institute of Geoscience and Mineral Resources (KIGAM) Seafloor Acoustic Probe. Physical properties, including laboratory velocity, were also measured for core samples collected from the same location. The laboratory measurements were conducted at a temperature of 23℃ and under atmospheric pressure. Owing to the in-situ temperature and pressure (0.5–1.5℃ and 100–180 atm, respectively) at the sampling site, the laboratory velocity was adjusted to the in-situ conditions. In addition, a comparison with a theoretical prediction model (Biot-Stoll model) was …

Apply Cluster Analysis To Improve Interpretation Of Ert Images, Yin-Chun Hung, Yu-Xiang Zhao

Journal of Marine Science and Technology–Taiwan

The completeness and accuracy of collecting and investigating geotechnical and marine engineering geological conditions are key to the success or failure of engineering development. Traditional marine engineering and geotechnical surveys often require the assistance of geophysical methods to fully present the geological conditions. Electrical Resistivity Tomography (ERT) is an advanced geophysical method that produces accurate cross-sections of underground resistivity. Although 2D ERT has been widely used in geotechnical engineering and marine engineering, many uncertainties remain hidden behind the vivid and colorful resistivity profiles. To apply 2D ERT profiles effectively in geotechnical and marine geological surveys and monitoring, it is essential …

Empowering Shipping Management Competence With Artificial Intelligence: A Strategic Approach To External Environmental Volatility, Yu-Kai Huang, Cheng-Hsien Hsieh, Chi-Chang Lin, Yu-Tzu Chang, Yu-Chao Cheng

Journal of Marine Science and Technology–Taiwan

The shipping industry is undergoing significant transformation with advancements in artificial intelligence (AI), yet challenges remain in effectively adopting AI technologies. This study addresses the key concerns influencing AI adoption in shipping management. Using the Analytic Hierarchy Process (AHP) integrated with the PEST model, an evaluation framework was developed to assess AI applications in shipping companies. Based on expert input collected through the Delphi method, four constructs and twelve criteria were identified, with the 'Technological' dimension being the most critical. 'Robustness,' 'Costs,' and 'Data quality' emerged as the top factors affecting AI implementation. The framework offers practical insights for shipping …

Explorations Of Dna-Single-Walled Carbon Nanotube Interactions To Develop Multiplexed Molecularly Specific Biosensors For Inflammation, Amelia K. Ryan

Dissertations and Theses

Inflammatory cytokines such as interleukin-6 (IL-6) and interleukin-12 (IL-12) are central regulators of immune signaling and key biomarkers of disease, yet existing assays for their detection remain slow, invasive, and lack multiplexing ability. This dissertation advances the development of single-walled carbon nanotube (SWCNT) optical nanosensors capable of real-time, multiplexed, and molecularly specific cytokine detection through innovative use of single-stranded DNA (ssDNA) interfaces.

First, an IL-6-specific DNA aptamer was employed as both a dispersing agent and recognition probe for SWCNT fluorescence sensing. Sequence modifications, including anchor domains, truncations, and thermally induced refolding, were systematically tested to optimize sensitivity and selectivity. The …

Wearable Disposable Elecetrotherapy, Mohamad Fallahrad

Dissertations and Theses

Non-invasive electrotherapies offer promising treatments for a wide range of conditions such as pain, headaches, depression, addiction, cognitive decline, wound healing, and drug delivery. However, patient compliance remains low due to the high initial cost, cumbersomeness and inconvenience of existing technology compared to pharmaceuticals. Current electrotherapy devices are often bulky and require users to connect disposable electrodes, initiate programs, and manage charging cycles, which hinders widespread adoption.

We address these challenges by designing and validating a novel electrotherapy platform that is single-use, disposable, low-cost, and wearable. Activated automatically upon skin contact, the device delivers a preset dose of controlled electrical …

Design And Lab Implementation Of An Air Source Transcritical Co2 Heat Pump, Geoffrey Turbeville

Dissertations and Theses

A laboratory-scale air-source transcritical CO2 heat pump (TCHP) was developed to evaluate the performance of low-global-warming-potential (GWP) refrigerants for cold climate applications. A custom climate chamber was also constructed to simulate winter weather conditions typical of the northeastern United States. Both the TCHP and the chamber were fully instrumented to collect temperature, pressure, and mass flow data, which were used to calculate the co- efficient of performance (COP) in accordance with ASHRAE standard refrigerant enthalpy methods. Prior to testing the CO2 system, the experimental setup was benchmarked using a commercially available R410A heat pump manufactured by LG.

The climate chamber …

A Novel Dual-Imaging Approach For Visualizing Multiphase And Droplet Interactions Including Shock-Driven Flows, Tad Jerzy Misztal

Dissertations and Theses

Shock-droplet/particle interactions have garnered substantial interest in recent years, fueled by advancements in aerospace and defense technologies, including supersonic and hypersonic systems in highly humid conditions, as well as the ongoing space exploration efforts from global space centers as well as private space companies. Understanding the interactions between shockwaves and droplets that impact on solid surfaces is critical due to the potential to cause significant damage to materials and structures in high-speed flow environments. Studies like these have applications in areas ranging from aerospace engineering to blast mitigation systems, where these interactions play a pivotal role in designing the relevant …

Metasurfaces And Their Applications In Photonic Devices, Shuwei Guo

Dissertations and Theses

Metasurfaces are flat artificial optical elements composed of dielectric and/or metallic nanostructures. They can manipulate light in unprecedented ways by altering amplitude, phase, and polarization at subwavelength scales. The ability of these two-dimensional elements to perform multiple optical functions within compact optical systems—while offering high functionality, small form factors, and easy integration into optoelectronic devices—has sparked significant interest across various fields and industries. These applications span imaging, sensing, nonlinear and quantum optics, optical computing, automotive technology, augmented and virtual reality, and more.

In this dissertation, we explore and design new multifunctional metasurfaces with a focus on manipulating spectral responses. First, …

High-Performance Small Satellites For Demanding Missions, Lance Fife

Space Dynamics Laboratory Publications

SDL Presentation on High Performance Small Satellites

Principles Of Modular Open Architectures For Enabling Future Capabilities, Jacob Christensen

Space Dynamics Laboratory Publications

What is Modular Open Architecture?

Vision

• Modular Open Architectures enable affordable and evolutionary capabilities

Principles

• Employ Modular Design
• Designate Key Interfaces
• Select Open Standards

Benefits

• Reduce schedule
• Reduce cost
• Faster upgrades
• Enhanced interoperability
• Increased competition
• Increased innovation

Assessment Of Surface Area Application Ratios For Beach Sand Treated Via Surface Percolated Micp-Bioslurry For Erosion Mitigation, Connor J. Marlin

UNF Graduate Theses and Dissertations

Rapid shoreline erosion associated with sea-level rise is an ongoing threat to coastal infrastructure. Traditional stabilization techniques, such as revetments, seawalls, and periodic nourishment, often prove costly, ecologically disruptive, or provide only temporary protection. Microbially Induced Calcite Precipitation (MICP) and its operational variant, bioslurry, present a biologically inspired alternative capable of forming a cemented surface crust that reduces soil erodibility. Previous laboratory studies typically prescribed a solution dosage as a percentage of pore volume (%PV). While geotechnically sound, this metric is poorly suited to field deployment across a large area. This thesis evaluates surface-area-based dosing (L/m²) as the primary dosage …

Characterization Of The Solid-State Bonding For Simulated Charge And Seam Welds In The Porthole Die Extrusion Process, Randall L. Bowers

Theses and Dissertations--Chemical and Materials Engineering

The isothermal (ISO-T) compression configuration is ideal for utilizing as a material input of flow stress at temperature and strain rate in models of the porthole die extrusion process due to the isothermal nature of the test. Micro-tensile testing was conducted to validate the solid-state welding integrity of the ISO-T samples at various temperatures and strain rates. Results of the mechanical testing were correlated with fractography and microstructural evaluations of the welds to confirm bonding behavior. Both clean interface conditions and oxidation and lubrication layers were evaluated to simulate the difference of seam and charge welds in the process. Results …

Computational Modeling Of The Heat Treatment Of White Oak Bound For Spirit Maturation, Kate E. Mclarney-Popham

Theses and Dissertations--Chemical and Materials Engineering

Maturation of distilled spirits in white oak barrels is a long standing practice known to have great impact on spirit character. Much of this impact can be controlled by the thermal modification of the barrel, since thermal degradation of the wood determines what wood compounds are available to interact with the spirit during maturation. In this work, a computational model for the thermal degradation of wood was developed and, with flavor compound data from literature, was used to investigate the effect of heat treatment on lignin-derived flavor compounds. The computational model in this work accounted for three solid species, three …

The Optimization And Manufacturing Scale-Up Of Polymeric Membranes Using Eco-Friendly Solvents, David Lu

Theses and Dissertations--Chemical and Materials Engineering

Polymeric membranes have become a prominent technology applied in water filtration due to the lower cost, energy input, and simpler manufacturing process relative to other separation technologies. However, the environmental impact of polymeric membrane fabrication remains a hindrance due to the use of hazardous solvents derived from fossil fuels (e.g., DMAc, NMP, DMF) that pose a risk to the environment and human health. Whereas recent studies have demonstrated the proof-of-concept of polymeric membrane derived from eco-friendly solvents, the next steps of optimizing and upscaling the production of these membranes remains understudied and a gap between lab-scale studies and the path …

Development And Verification Of Testing Platform For Torque Vectoring Controller, Nicholas Petersen

Dissertations, Master's Theses and Master's Reports

A foremost concept in the automotive industry in recent years has been that of a vehicle “digital twin”. A digital twin is an accurate simulation of a dynamic system for the use of rapid development. These digital twins have a critical advantage over physical testing, which have dominated vehicle development up to now. As the cost of physical testing continues to rise, simulation can deliver rapid system development in a low-cost format. No simulation environment is a perfect representation of reality, however, and physical testing is still necessary to validate systems for use in the real world. This is especially …