Digital Commons Network^™

Evaluating Feasibility Of Incorporating Fuel Cell Drive Trains Into Existing Haul Trucks, Ayorinde Akinrinlola, Kwame Awuah-Offei, Abdullah Al Moinee

Mining Engineering Faculty Research & Creative Works

Hydrogen, as a fuel source in material handling, has become a viable option for achieving carbon reduction targets. The objective of this work was to apply vehicle drive train and energy simulation in MATLAB/Simulink to guide a discussion of the challenges and opportunities of incorporating hydrogen fuel cell drive trains into the current form factors of mine haul trucks. We built and validated a model based on the Komatsu 830-E truck and used it to estimate the hydrogen requirements for typical short-haul, medium-haul, and long-haul cycles; in the short-haul case (cycle time = 852 s) the truck consumed 23.6 L …

Cracking The Code: Harnessing Serpentinization-Driven Micro-Crack Networks For Hydrogen Generation And Subsurface Resource Recovery, U. Mutlu, G. Boitnott, A. Lisjak, J. Ha, O. Mahabadi, P. Connolly, B. N. Tunnell, T. Sherizadeh, S. Nowak, J. E. Olson

Mining Engineering Faculty Research & Creative Works

This study focuses on simulating volume-increasing processes caused by natural hydrogen-generating serpentinization, a reaction in which olivine and pyroxene typically transform into serpentine minerals. The volume increase leads to crack propagation along grain interfaces and new crack generation within unreacted crystals (aka grains). The interplay between thermo-hydro-mechanicalchemical (THMC) conditions plays a critical role in the initiation, propagation, and coalescence of various fracture surfaces, which enhances permeability and can accelerate serpentinization and hydrogen production rates. In the scenarios considered, chemical reactions between formation brine and reactive minerals result in volumetric expansion, generating stress and promoting the propagation of micro-cracks. Our results …

Aperiodically Intermittent Dynamic Event-Triggered Control For Predefined-Time Synchronization Of Stochastic Complex Networks, Lei Xue, Haoyu Zhou, Yongbao Wu, Jian Liu, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, the problem of practical predefined-time synchronization in mean square (PTSMS) of stochastic complex networks (SCNs) is investigated through dynamic event-triggered control (E-TC). Different from the existing literature, this paper considers the dynamic E-TC in an a periodically intermittent control framework and employs the average control rate, which makes it easier to satisfy the conditions of the theorem. In comparison to existing finite-time and fixed-time synchronization, by introducing the time-varying function, it can be guaranteed that all states of SCNs achieve the practical PTSMS within a preset time without calculating the convergence time. Combined with stochastic analysis theory, …

Reflections On Linear B: An Egyptian Hieroglyphic Component, (Draft #2), Gerald Leonard Cohen

Arts, Languages and Philosophy Faculty Research & Creative Works

Most Linear B signs are presently regarded as being of unknown origin, with a general consensus that Egyptian hieroglyphs are at best of minimal help in solving the mysteries. But the present article revisits this subject and suggests that the Egyptian hieroglyphic component goes beyond a borrowing or two. Along the way I noticed that for some Linear B signs a familiarity with Egyptian religious mythology is essential in this effort.

For example, the mysterious Linear B sign 75 is pronounced /we/ and looks like a backwards letter S. I suggest it can be explained as the cobra goddess Wadjet …

Existential Resilience In The City, Shane Ray Epting

Arts, Languages and Philosophy Faculty Research & Creative Works

Severe weather continues to challenge cities worldwide. Typhoons, wildfires, floods, and extreme temperatures test urban systems, communities, and governments at all scales. To combat such effects, resilience has emerged as a term geared towards increasing their ability to address impacts, strengthen infrastructure, and deal with cleanup measures. Although this business sounds straightforward to non-philosophers, ethical and existential elements remain out of view for the sciences and require investigation. This article fleshes them out. The first step is to identify relevant stakeholder groups and competing interests. The second is discovering equitable ways to bring professionals and city dwellers together to develop …

A New Formulation Of Hardy-Type Dynamic Inequalities On Time Scales, Martin Bohner, Irena Jadlovská, Ahmed I. Saied

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we introduce a novel formulation of dynamic Hardy-type inequalities on a time scale, motivated by a recently established convexity approach in the Haar measure. The classical Hardy inequality is refined so that the classical Lebesgue-measure constant is replaced by the sharp constant 1. We obtain time-scale analogues on finite intervals with best constants, and, for nonincreasing and nondecreasing functions, reversed inequalities with explicit weights described by incomplete β-functions. To establish our results, we employ two distinct time scales and apply the chain rule, together with the substitution rule, the derivative of inverse functions, and Fubini's theorem for …

Transfection Of Ionizable Lipid Nanoparticles On Raw 264.7 And Mda-Mb-231, Lavanya Bhargava

Masters Theses

"This thesis investigates the preparation, characterization, and transfection efficiency of various ionizable lipid nanoparticles (LNPs) formulated for the delivery of mRNA encoding enhanced green fluorescent protein (EGFP) in RAW 264.7 macrophages and MDA-MB-231 breast cancer cell lines. The ionizable cationic lipid studied are ALC-035, C12-200, C14-4, PPZ-A10, DLin-MC3-DMA. The study addresses the need for effective gene delivery systems to provide a safe and versatile platform that protects and transports nucleic acids into target cells. LNPs were synthesized using microfluidic mixing methods, incorporating lipid components such as the cationic lipids, DSPE, DOPE, cholesterol and PEG lipids to achieve controlled particle sizes, …

Flexural Post-Cracking Performance Of Macro Synthetic Fiber Reinforced Super Workable Concrete Influenced By Shrinkage-Reducing Admixture, Jingjie Wei, Nima Farzadnia, Kamal H. Khayat

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Most literature has focused on the effect of shrinkage-reducing admixture (SRA) in shrinkage mitigation resistance of concrete. This study aims to examine the impact of SRA on the efficiency of macro synthetic fibers (MSF) in enhancing the flexural post-cracking behavior of fiber-reinforced super workable concrete (FR-SWC). A comparative analysis of the influence of fiber combinations on the flexural post-cracking behavior of beams is also included. Results showed that a higher dosage of SRA, particularly at 5 % by mass of binder, had a noticeable negative impact on flexural post-cracking performance of beams while exhibiting positive effect on workability and shrinkage …

Active Phytoextraction Of Toluene Shifts The Microbiome And Enhances Degradation Capacity In Hybrid Poplar, Michael Benisrael, Dasiel Obregon, Philipp Wanner, Jeremy Fernandes, Joel G. Burken, Ramon Aravena, Beth L. Parker, Elizabeth A. Haack, David T. Tsao, Kari E. Dunfield

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Hybrid poplars are widely recognized for their effectiveness in remediating subsurface aromatic hydrocarbon contaminants, including benzene, toluene, ethylbenzene, and xylene isomers (BTEX). While BTEX compounds are frequently found in the transpiration streams of poplars at contaminated sites, the microbial dynamics within these trees, particularly in response to hydrocarbon exposure, remain underexplored. This study utilized high-throughput amplicon sequencing to investigate the trunk microbiome in hybrid poplars at a field-scale toluene phytoremediation site. Across the plant growth season (spring to late summer), we observed a significant seasonal increase in bacterial diversity and richness, particularly in trees located in areas with the highest …

Innovative Air Convection Embankment For Cold/Arctic Region Low-Volume Roads, Hanli Wu, Jenny Liu, Xiong Zhang, Steve Saboundjian

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Roadbed thaw settlement is a unique challenge for the durability of low-volume roads (LVRs) in permafrost regions. Air convection embankment (ACE) is an effective technique that acts as a semi-heat-transfer system to control temperature variation and reduce the thaw depth of subsoil. However, limited by the shortage of the necessary crushed rocks within a short distance, building an ACE in Alaska, U.S., is prohibitively expensive. Previous studies identified the feasibility of using cellular concrete for ACE and determined the optimized thickness of the cellular concrete aggregate interlayer for ACE. However, the economic efficiency and thermal and mechanical performance of the …

Correction: Yolo-Based Miner Detection Using Thermal Images In Underground Mines (Mining, Metallurgy & Exploration, (2025), 10.1007/S42461-025-01249-6), Cyrus Addy, Venkata Sriram Siddhardh Nadendla, Kwame Awuah-Offei

Computer Science Faculty Research & Creative Works

In the original published article, Figure 3 appears with the Fig. 1 caption, Figure 1 appears with the Fig. 2 caption, and Figure 2 appears with the Fig. 3 caption. The article has been updated to correct this error.

Remenet: A Memory-Enhanced Gan Model For Intrusion Detection In Transportation Cyber-Physical Systems, Xin Wang, Lianbo Ma, Sajal K. Das, Zhonghua Liu

Computer Science Faculty Research & Creative Works

Ensuring the safety and reliability of Transportation Cyber-Physical Systems (T-CPS) is critical. However, the increasing interconnectedness of T-CPS exposes them to sophisticated cyberattacks, necessitating robust intrusion detection systems (IDS) to safeguard against evolving threats. This paper aims to enhance the security of T-CPS by addressing two key challenges: effective anomaly detection and handling imbalanced datasets in intrusion detection tasks. In this paper, we propose ReMeNet (Reconstruction Memory Network), a novel intrusion detection model that combines a memory module with a GAN-based architecture to enhance anomaly detection and data reconstruction. To address the challenge of imbalanced datasets, we incorporate a Vector …

V-Usdt: Vision-Based Uav Swarm Detection And Tracking By Leveraging Swarm Formation Constraints, Md Hasibur Rahman, Sanjay Madria

Computer Science Faculty Research & Creative Works

The rapid proliferation of Unmanned Aerial Vehicles (UAVs) and UAV swarm technologies has raised critical concerns about security and safety in low-altitude airspace. In response, we propose a vision-based system for detecting and tracking UAV swarms, which combines a novel UAV detection mechanism with a swarm tracking strategy. Our UAV detector incorporates parallel receptive field blocks alongside an attention mechanism to enhance detection performance. This design effectively captures multiscale features of UAVs while prioritizing salient features, ensuring robust detection under diverse conditions. For swarm tracking, we leverage the inherent formation constraints typically maintained by UAV swarms. These constraints allow us …

Securing Federated Learning From Distributed Backdoor Attacks Via Maximal Clique And Dynamic Reputation System, Priyesh Ranjan, Ashish Gupta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) is a distributed learning paradigm that leverages the computational strength of local devices to collaboratively train a model. The clients train the local model on their respective devices and submit the weight updates to the server for aggregation. This paradigm allows the clients to experience diverse data without sharing their local data with other participants or the server. However, FL is susceptible to backdoor attackers that deliberately train the model on altered data, essentially trying to get favor on a specific subtask separated from the main task. In this work, we focus on powerful backdoor attackers who …

Rush: Rule-Based Scheduling For Low-Latency Serverless Computing, Priyanka Ashok Birajdar, Kush Anchalia, Anurag Satpathy, Sourav Kanti Addya

Computer Science Faculty Research & Creative Works

Serverless computing abstracts server management, enabling developers to focus on application logic while benefiting from automatic scaling and pay-per-use pricing. However, dynamic workloads pose challenges in resource allocation and response time optimization. Response time is a critical performance metric in serverless environments, especially for latency-sensitive applications, where inefficient scheduling can degrade user experience and system efficiency. This paper proposes RUSH (Rule-based Scheduling for Low-Latency Serverless Computing), a lightweight and adaptive scheduling framework designed to reduce cold starts and execution delays. RUSH employs a set of predefined rules that consider system state, resource availability, and timeout thresholds to make proactive, latency-Aware …

Improving The Operator-Swarm Dynamic Under Mental Fatigue Constraints In Search And Rescue Operations, Jordan Morrow

Masters Theses

"Human-robot applications that allow for work to be done remotely are largely dependent on the lassitude of the operators. The exhaustion of these operators is a result of work completion and duration. Previous research attempts to evaluate the impact on reaction by quantiying human weariness. This paper examines how human weariness affects the human-robot dynamic in UAV-assisted search and rescue missions. An explanation of the connection between mental exhaustion and operator responsiveness over prolonged durations is provided by the search and rescue operations using UAV swarms (SAROUS) model. Through the use of artificial intelligence, SAROUS is modernized. This allows the …

Computation Of Natural Relative Trajectories In The Elliptic Restricted Three-Body Problem, Dane Huck

Masters Theses

"Humankind’s presence in deep space is certain to increase throughout future decades. Future missions will continue to exploit the complex dynamics making use of liberation point orbits. Along with this trend is the rise of small satellites ("small sats") and fractionated spacecraft in general. Compared to traditional monolithic spacecraft, small sats can often have higher maneuverability, be a fraction of the cost, and be more expendable in nature. The growing interest in these two areas drives the need for improvements in the area of relative motion in deep space. One obvious use of small sats in deep space is for …

Advanced 3d Lidar-Based Systems For Urban Traffic And Pedestrian Monitoring: Integrating Elevated Lidar, Data Collection, And Deep Learning For Precise Detection And Activity Classification, Nawfal Guefrachi

Masters Theses

"Accurate and real-time monitoring of urban traffic and pedestrian activities is crucial for intelligent transportation systems (ITS) and smart cities. Traditional camera-based methods struggle with issues like lighting and privacy. This research leverages advanced three-dimension light detection and ranging (3D LiDAR) technology and computational frameworks to address these challenges, providing transformative solutions for urban traffic management and pedestrian safety. By strategically deploying elevated LiDAR sensors, detailed 3D point cloud data is captured, enabling precise monitoring of urban environments. Enhancements to LiDAR-based frameworks, such as fine-tuning the Point Voxel Region-Based Convolutional Neural Network (PV-RCNN), improve the detection of vehicles and pedestrians …

Bond Behavior Of Magnesium Potassium Phosphate Cement (Mkpc) Coating For Steel Reinforcement, Eric Williams

Masters Theses

"This research investigates the bond behavior of magnesium potassium phosphate cement (MKPC) coated mild steel deformed bars in conventional concrete and concrete repair materials. For typical steel reinforcement in concrete, a thin “passive layer” develops around the reinforcement, which protects the reinforcement from corrosion. The concrete carbonates over time, reducing the protection of the passive layer and allowing chlorides, which corrode the reinforcement, to penetrate at an increasing rate. In some cases, to combat this corrosion, a protective layer is added to the reinforcement prior to installation. Common protective layers include epoxy coatings or zinc galvanization. MKPC is a novel …

Effects Of Climate Change On Fungal Diversity And Function In Streams, Syeda Tasfia Imam

Masters Theses

"This study investigated the impact of climate change, particularly drought, on leaf decomposition and associated fungal and macroinvertebrate communities in freshwater ecosystems. With climate change, streams may experience altered hydrology, leading to shifts in community composition and biogeochemical processes. Fungi decompose organic matter, facilitate nutrient cycling, and support food webs. However, drought can disrupt these processes by reducing water availability, causing declines in fungal diversity and activity. I examined leaf breakdown and associated biota in 13 stream sites across varying hydrologic conditions, from perennial to ephemeral flow patterns. Flow duration varied during the 8-week study. Leaf breakdown was significantly related …

Lidar From The Skies: A Uav-Based Approach For Efficient Object Detection And Tracking, Baya Cherif

Masters Theses

"Recently, there has been a growing interest in deploying the Light Detection and Ranging (LiDAR) technology to gain traction in the autonomous vehicle industry, its applications are expanding into areas like smart cities, agriculture, and renewable energy. This work proposes an advanced approach to enhance aerial traffic monitoring using Li- DAR. We aim to provide accurate, real-time object detection and tracking from an aerial perspective by integrating Unmanned Aerial Vehicle (UAV) with LiDAR, culminating in a smart UAV-integrated LiDAR (A-LiD) sensor for traffic surveillance. We introduce an adapted version of one of the newest methods of the cutting-edge 3D object …

Automated Generation Of Malware Metadata Signatures, Joel Schott

Masters Theses

In advanced, targeted malware attacks, the custom software tools used to package and send malicious files and messages can lead to distinctive metadata values that facilitate creation of a malware metadata signature. Manual creation of these signatures requires expert domain knowledge and is time-consuming and error-prone. Our goal is to automate this process. We created several methods of automatically generating malware metadata signatures for ZIP files and emails. We evaluated these methods by comparing signatures generated with these methods to existing expert-created signatures. We found automated methods for ZIP files and emails that are capable of generating metadata signatures that …

Hyper B-Ary Representations Of A Number, Mingway Wang

Masters Theses

In this work, we summarize combinatorial, analytical, and computational properties of Stern's diatomic sequence, and do the same for a generalization of a combinatorial property of this sequence to higher bases. We then construct special ``bit conversion'' functions $g_{b}$ that allows us to find a semi-explicit formula for the generalized sequences. Lastly, we analyze some of the properties of these $g_{b}$ functions.

Fetal Acidosis Prediction Using Attention Enhanced Convolutional Neural Networks, Anusha Adhikari

Masters Theses

This study explores the integration of spectral mixtures of fetal heart rate (FHR) and uterine contraction (UC) signals to enhance the prediction of fetal acidosis, utilizing the CTU-CHB dataset. Several classification models were trained using two distinct oversampling techniques and inputs, demonstrating that models incorporating spectral mixtures significantly outperform those using raw signals. These models, particularly when combined with convolutional neural networks (CNNs) and attention mechanisms, achieved a notable F1-score of 0.98, with the highest model achieving an area under the Receiver Operating Characteristic (ROC) curve of 0.95. The research employs a variety of techniques including short-time Fourier transform and …

Modeling Of Slot-Backed Microstrip Line For Emi Applications, Jongsuk Hyun

Masters Theses

Radiated emissions from printed circuit boards (PCBs) are a significant concern in electromagnetic interference (EMI) and radio frequency interference (RFI). Shielding cans are widely used to mitigate these emissions but evaluating requires accurate characterization of equivalent noise sources. Slot-backed microstrip antennas are employed for this purpose due to their near-zero height, low parasitic radiation, and PCB-compatible structure, offering a practical alternative to conventional loop antennas. This paper presents a physics-based analytical model that integrates both the discontinuity effects and radiated characteristics of slot-backed microstrip structures within a unified circuit framework. An analytical expression for the dipole moment is proposed based …

Long Short-Term Memory (Lstm) -Based Neural Network Model For Optimizing Composite Manufacturing Process Using Autoclave, Sourav P. Bolar

Masters Theses

The combination of high pressure and controlled heat plays a critical role in ensuring the uniform curing of composite materials, leading to parts with superior mechanical properties. In this study, three composite samples of IM7/CYCOM 5320-1, each cut into 12x12-inch squares, were placed in an autoclave at three different locations, spaced 6 inches apart. Sixteen thermocouples were randomly distributed across the setup to monitor the curing process as the autoclave temperature was systematically ramped up and down while maintaining constant pressure, creating a fully controlled curing environment. The primary objective was to optimize the curing locations to reduce machine runtime …

Characterization Of The Microstructural Changes Of Zrb2 Under Heavy Ion Irradiation For Molten Salt Reactor Applications, Narrie Loftus

Masters Theses

A primary challenge in finding suitable materials for Molten Salt Reactors (MSRs) lies in identifying those that concurrently exhibit high corrosion resistance, stability at elevated temperatures, resistance to radiation, and chemical compatibility with molten salts. 11B-enriched zirconium diboride (ZrB₂) is a potential candidate for applications in MSRs due to its unique combination of properties, including high melting point, high thermal conductivity, and resistance to corrosion in harsh environments. This ultra-high temperature ceramic (UHTC) has exhibited stability under extreme conditions, making it an attractive material for components within MSRs.

The microstructural response of ZrB₂ under heavy ion irradiation …

On Optimizing Sensor Data Collection, Processing, And Storage For Industrial Additive Manufacturing, Steven Thompson

Masters Theses

The widespread adoption of digital data management methods for transformative technologies, such as additive manufacturing (AM), within the aerospace industry is impeded by poor interoperability between AM component manufacturing processes. Moreover, data quality may be compromised due to sensor failures or other corruptions. Additionally, massive amounts of data are collected during these processes, often needing to remain accessible for decades. These storage costs can place a significant financial burden on smaller suppliers. This work aims to make digital data management methods more affordable and, therefore, approachable for smaller suppliers.

First, the design and initial implementation of an affordable and adaptable …

Emi Mitigation, Material Characterization, Transformer Equivalent Circuit Modeling, Reza Vahdani

Masters Theses

Modern high-frequency electronic systems demand precise characterization and modeling techniques to ensure signal integrity and electromagnetic compatibility. This thesis presents three core studies focused on real-world challenges in high-speed and power electronics: EMI mitigation using 3D printed absorbers, wideband liquid dielectric characterization, and accurate transformer modeling.

The first study demonstrates a targeted approach to mitigating electromagnetic interference (EMI) in a commercial router. By using holography imaging to identify radiation hotspots, custom absorber structures were designed with commercially available materials, fabricated via 3D printing, and applied directly to emission sources. Radiated emission tests in a reverberation chamber showed up to 9 …

Augmentation Of Quality Of Service, Security, And Trust In Edge-Enhanced Iot Networks Leveraging Blockchain, Kyle Matthew Whitlatch

Masters Theses

The meteoric rise of the Internet of Things (IoT) has led to multiple architectural schemas to handle the data these devices create. Edge-enhancement is a technique where groups of IoT report to a median layer to aggregate the data before relaying to the endpoint. These edges also open opportunities to perform more operations to ensure devices are behaving properly before committing the data to long term storage. By interconnecting these edges with a technology like blockchain, it is possible to have an interconnected and responsive system to ensure the Quality of Service (QoS) of the IoT devices within the architecture …