Engineering Commons^™

Analysis Of Leak Testing Planning For Carbon Dioxide Piping Systems In The Development Of Carbon Capture, Utilization, And Storage Facilities In The Bintuni Basin, Devi Sentiani, Akhmad Herman Yuwono Professor

Journal of Materials Exploration and Findings

Carbon Capture, Utilization, and Storage (CCUS) technologies have become a key strategic response to global efforts to reduce CO₂ emissions. This study presents a leak testing strategy designed for a carbon dioxide (CO₂) piping system as part of a Carbon Capture, Utilization, and Storage (CCUS) project in the Bintuni Basin, West Papua, Indonesia. This study aims to ensure the system is properly prepared before commissioning by designing a leak test plan that is both practical and technical, based on ASME B31.3, ASME PCC-2, and API STD 520 Part 1. We conducted the process, which involves identifying the system boundaries, …

Investigating Information Extraction And Language Models In Medical Domain Text Processing, Pouyan Nahed

UNLV Theses, Dissertations, Professional Papers, and Capstones

This dissertation demonstrates that carefully adapted language-model pipelines can transform unstructured clinical-trial and pharmacological prose into reliable, low-latency structured data. Four interconnected studies support this claim.Tri-AL platform. An open-source dashboard ingests all 440 k+ ClinicalTrials.gov records—including every historical revision—into a normalized schema and parses the 20 GB XML archive over 10x faster than a BeautifulSoup baseline, while exposing hooks for demographic analytics and supporting integration of user-defined modules. Clinical trial summarization. An encoder–decoder model is trained on 57k description–summary pairs to condense clinical trials into a few sentences. ROUGE evaluation shows a 20% improvement over the baseline, while graph-based evaluation …

Autonomous Uav Swarm Formation Utilizing Gradient-Driven Contour Mapping For Radiation Source Localization, Edgar Amalyan

UNLV Theses, Dissertations, Professional Papers, and Capstones

This thesis presents a drone swarm for radiation mapping to aid source localization. The Department of Energy advocates employing UAVs for this task, but existing approaches remain inefficient and impractical in real-world scenarios. Three custom drones are built and flight-tested. A control algorithm to follow a contour, a constant-intensity path, is designed using a gradient fit. By knowing the source’s direction, the drone swarm can fly in the optimal trajectory at every step, leaving nothing to assumption. A program is created that implements formation flight and autonomous navigation. It is tested via a software-in-the-loop simulation utilizing radiation sources and detectors …

Note For Quadripartitioned Neutrosophic Offset, Pentapartitioned Neutrosophic Offset, And Heptapartitioned Neutrosophic Offset, Takaaki Fujita

Neutrosophic Systems with Applications

Neutrosophic sets assign each element three independent membership values—truth, indeterminacy, and falsity—and their partitioned extensions introduce additional components subject to sum-bounded constraints. Notable examples include quadripartitioned, pentapartitioned, and heptapartitioned neutrosophic sets. The O set concept further extends this framework by allowing membership values outside the standard [0, 1] interval, including negative values and values exceeding one. In this paper, we introduce and analyze the Quadripartitioned Neutrosophic O set, Pentapartitioned Neutrosophic O set, and Heptapartitioned Neutrosophic O set. These extensions are intended to enhance the expressiveness of neutrosophic theory and to stimulate further research in neutrosophic and fuzzy uncertainty.

Integrated Algorithm And Hardware Design For Hybrid Neuromorphic Systems, James Seekings, Mahsa Ardakani, Peyton Chandarana, Arshia Eslami, Mohammadreza Mohammadi, Ramtin Zand

Faculty Publications

This paper investigates the combined potential of neuromorphic and edge computing to develop a flexible machine learning (ML) system designed for processing data from dynamic vision sensors. We build and train hybrid models that integrate spiking neural networks (SNNs) and artificial neural networks (ANNs) using the PyTorch and Lava frameworks. We explore the effects of quantization on ANN models to assess its impact on both accuracy and energy efficiency. Additionally, we address the challenges of deploying hybrid models on hardware by implementing individual components on specific edge platforms. We also propose an accumulator circuit to bridge the spiking and non-spiking …

Digital Trading Platform Selection Under Neutrosophic Numbers And Multi-Criteria Decision-Making Methodology: An Illustrative Example, Eman Sayed, Karam M. Sallam, Ibrahim Alrashdi

Neutrosophic Systems with Applications

Uncertainty, vagueness, and incomplete information are pervasive in real-world decision-making scenarios, particularly in multi-criteria decision-making (MCDM) contexts involving expert judgments. To address these challenges, this study introduces a comprehensive decision-making framework that integrates Triangular Neutrosophic Numbers (TNNs) with the Weighted Aggregated Sum Product Assessment (WASPAS) method. The framework begins by capturing expert evaluations using TNNs, which effectively represent the degrees of truth, indeterminacy, and falsity inherent in subjective assessments. These evaluations are then transformed into crisp values using a novel score function that preserves the embedded uncertainty. The resulting decision matrices are aggregated into a unified structure to ensure consistency …

Quantified Possibility Neutrosophic Soft Set Based Decision Support System For Enhanced Accuracy In Sustainable Supplier Selection Decision Analysis, Neha Andaleeb Khalid, Muhammad Saeed

Neutrosophic Systems with Applications

To deal with the concepts of vulnerability, ambiguity, and indeterminacy that are typical in complex decision analysis contexts, neutrosophic set-like structures are frequently used. Although neutrosophic sets are particularly good at handling indeterminate circumstances, indeterminacy plays a part in making the decision making process imprecise and ambiguous. This paper develops a more advanced technique to improve the accuracy of decision analysis problems: the Quantified Possibility Neutrosophic Soft Set Decision Support System (Q^t PNSSDSS). In order to reduce the element of indeterminacy present in conventional neutrosophic sets, the proposed DSS is based on the Quantified Neutrosophic Set, which employs a …

Some Properties Of Neutrosophic Cubic Hypersoft Sets, Lubna Nayab, Muhammad Gulistan, Fawad Hussain

Neutrosophic Systems with Applications

This study addresses the limitations of NCS in managing uncertainties associated with multiple attributes and their further bifurcation. To address this challenge, we propose a generalization of the neutrosophic cubic soft set, introducing the concept of "neutrosophic cubic hyper soft set." Within this framework, we define internal and external neutrosophic cubic hypersoft sets, along with operations such as P-intersection, P-union, P-restricted union, P-extended intersection, P-OR operator, P-AND operator, R-intersection, R-union, R-restricted union, R-extended intersection, R-OR operator, R-AND operator, complement, and relative complement of neutrosophic cubic hyper soft sets. The study explores and presents relevant results, demonstrating the enhanced capability of …

Application Of Multi-Criteria Decision Analysis For Quantifying Responsibility In Ml-Based Intrusion Detection System, Mona Mohamed, Zekra Sakr

Neutrosophic Systems with Applications

With the swift growth in Internet of Things (IoT), certifying secure and trustworthy networks has turned to be a critical challenge, particularly as IoT devices are increasingly vulnerable to sophisticated cyberattacks. As a remedy, intelligent intrusion detection systems (IDS) evolved as promising solutions in recent years, but deciding on the appropriate model remains difficult because of competing performance and trustworthiness criteria. To this end, this paper explores a novel application of an ML-augmented decision-making framework to enhance security-related decision-making in IoT environments. The framework systematically evaluates and ranks ML-based IDS systems according to different evaluation criteria with distinct trade-offs, including …

Land8fire: A Complete Study On Wildfire Segmentation Through Comprehensive Review, Human-Annotated Multispectral Dataset, And Extensive Benchmarking, Anh Tran, Minh Tran, Esteban Marti, Jackson Cothren, Chase Rainwater, Sandra Eksioglu, Ngan Le

Electrical Engineering and Computer Science Faculty Publications and Presentations

Early and accurate wildfire detection is critical for minimizing environmental damage and ensuring a timely response. However, existing satellite-based wildfire datasets suffer from limitations such as coarse ground truth, poor spectral coverage, and class imbalance, which hinder progress in developing robust segmentation models. In this paper, we introduce Land8Fire, a new large-scale wildfire segmentation dataset composed of over 20,000 multispectral image patches derived from Landsat 8 and manually annotated for high-quality fire masks. Building on the ActiveFire dataset, Land8Fire improves ground truth reliability and offers predefined splits for consistent benchmarking. We evaluate a range of state-of-the-art convolutional and transformer-based models, …

Wear Of High Entropy Alloys: Understanding Effects Of Cryogenic Temperatures And Surface Nitriding On Wear Behavior, Aubrey Yu Tang

Dartmouth College Ph.D Dissertations

Cryogenic tribological applications have become increasingly important with the development and innovation of advanced equipment in aerospace, polar regions, superconductivity, and more. Traditional lubrication methods are not viable under these harsh environments, so metallic materials must be able to maintain excellent mechanical properties and withstand the constant impact and wear alone. High entropy alloys (HEAs) have emerged as potential candidates for these applications because of their wide variety of excellent room temperature properties and apparent improvement of mechanical properties of some HEAs at extremely low temperatures. Despite their promising nature, very limited work has been done on understanding the wear …

64th Annual Rocky Mountain Conference On Magnetic Resonance

Rocky Mountain Conference on Magnetic Resonance

Final program, abstracts, and information about the 64th annual meeting of the Rocky Mountain Conference on Magnetic Resonance. Held in the Snowbird Resort and Conference Center, Snowbird, Utah, August 3-7, 2025.

Assembly Of Non-Close-Packed Poly(N-Isopropylacrylamide) Microgels On Metal Halide Perovskite Films, Amal Alruwaili, Osama M. Alkhudhari, Ran Wang, Zhenyu Jia, Jennifer M. Saunders, Eugenio Picheo, Daniel T.W. Toolan, L. Andrew Lyon, Brian R. Saunders

Engineering Faculty Articles and Research

Hypothesis

Experiments

Method For Target Detection In A High Noise Environment Through Frequency Analysis Using An Event-Based Vision Sensor, Will Johnston, Shannon Young, David Howe, Rachel Oliver, Zachary Theis, Brian Mcreynolds, Michael L. Dexter

Faculty Publications

Event-based vision sensors (EVSs), often referred to as neuromorphic cameras, operate by responding to changes in brightness on a pixel-by-pixel basis. In contrast, traditional framing cameras employ some fixed sampling interval where integrated intensity is read off the entire focal plane at once. Similar to traditional cameras, EVSs can suffer loss of sensitivity through scenes with high intensity and dynamic clutter, reducing the ability to see points of interest through traditional event processing means. This paper describes a method to reduce the negative impacts of these types of EVS clutter and enable more robust target detection through the use of …

08.04.2025 Ored Connect, Liz Williamson

ORED Newsletter

NIH limits AI use and annual proposals accepted per PI

Volumetric Imaging Of Cellular Dynamics Using Light-Sheet Microscopy: From Subcellular Structures To Whole Organisms, Md Nasful Huda Prince

Optical Science and Engineering ETDs

Advancing biomedical imaging requires platforms that combine high-resolution, speed, and stability across biological scales. This dissertation presents three innovations designed to address limitations of conventional light-sheet and oblique plane imaging. First, we introduce Reflected Inline Detection in Epi-Oblique Plane Microscopy (RIDE-OPM), a compact and drift-resistant system that eliminates a tertiary detection path while maintaining alignment flexibility, enabling robust long-term live imaging. Second, we present a high-speed Axially Swept Light-Sheet Microscopy (ASLM) platform for cleared tissues, using dual foci and synchronized sweeping to achieve isotropic sub-micron resolution at up to 40 frames-per-second, a fourfold improvement over standard ASLM. Integrated with a …

Understanding Structure-Property Relationships Within Polyolefin-Derived Vitrimer Systems, Mikaela Sadri

Dissertations

Polyolefins are extremely ubiquitous materials due to their satisfactory material properties, ease of synthesis, and low cost. Unfortunately, their extensive use has led to a global plastic waste mismanagement problem. As such, notable efforts have recently focused on converting these commodity polymers into vitrimers, or dynamic networks, to extend their use-life and tailor their properties. However, the fundamental polymer physics of these emerging materials, remain largely underexplored, hindering their widespread implementation. To address this challenge and enable a more sustainable future, the overarching goal of my dissertation research is to understand the fundamental structure-property relationships within complex polyolefin-derived vitrimer systems. …

Mantle Flow And Crustal Deformation Revealed By Seismic Anisotropy In The Subduction Zone Beneath Myanmar, Enbo Fan, Mingming Jiang, Yinshuang Ai, Stephen S. Gao, Kelly H. Liu, Yumei He, Yiming Bai, Guangbing Hou, Yuan Ling, Chit Thet Mon, Myo Thant, Kyaing Sein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

The oblique convergence of the Indian and Eurasian plates drives significant deformation in the crust and mantle beneath Myanmar. However, the crustal deformation in the Indo-Burman Ranges (IBR) and mantle flow beneath Myanmar and adjacent areas remain unclear due to limited studies. We utilized data from the newly deployed second phase of the China-Myanmar Geophysical Survey of the Myanmar Orogen array to perform shear wave splitting analysis of PKS, SKKS, and SKS (XKS) phases. Our results, together with previous findings, provide new insights into mantle flow and crustal deformation across central Myanmar. In the IBR, we observed a transition from …

Ev Charging Management In A Real-Time Optimization Framework Considering Operational Constraints, Hilmi Cihan Güldorum, Ayşe Kübra Erenoğlu, İbrahim Şengör, Barry P. Hayes, Ozan Erdinç

Department of Computer Science Publications

The electrification of transportation plays a central role in the decarbonization of energy systems. Although electric vehicles (EVs) are expected to reduce energy related emissions, the increasing demand imposed by large scale EV adoption presents serious challenges for distribution systems (DSs), which were not originally designed to accommodate such loads. This study proposes a mixed integer quadratically constrained programming (MIQCP) framework to optimize the operation of an EV parking lot (EVPL) under DS constraints. The model compares three widely adopted objective functions: minimization of active power loss, charging cost, and uncontrolled charging impact, which is represented by minimizing the total …

Life Cycle Assessment Of The Cultivation Of Lettuce In A Hydroponic System Using The Nutrient Film Technique, Raquel Jordan

All Theses

Hydroponic systems are an emerging method of soilless crop cultivation typically done inside a greenhouse where nutrients are delivered dissolved in water rather than being supplied from the soil. Potential benefits of hydroponic systems include reduced irrigation requirements, higher crop yield per area, and the ability to grow crops year-round in nontraditional areas such as urban settings, cold climates, and sites with contaminated soil. However, hydroponic systems tend to have high energy requirements for lighting and climate control, which can yield significant environmental impacts. To explore the environmental impacts of cultivating lettuce in a nutrient film technique (NFT) hydroponic system, …

Complex System Governance And Cyber Operations, Willie Gernard Mccallister

Engineering Management & Systems Engineering Theses & Dissertations

This dissertation examines the potential integration of Complex System Governance (CSG) within cybersecurity, emphasizing the development of a reference model for Cybersecurity Infrastructures. Traditional strategies for securing digital environments have struggled to address the intricate and dynamic layers inherent in modern cybersecurity systems. The purpose of this research is to explore the applicability of CSG as a framework to assess cybersecurity infrastructure using a case study research design. The research addresses two key questions: (1) How can the CSG reference model be adapted to explore cybersecurity infrastructure? (2) What results from CSG based exploration of cybersecurity infrastructure through a case …

Input Structure Based Optimization For Privacy Preserving Ai Systems, Feng Yizhou

Electrical & Computer Engineering Theses & Dissertations

As Artificial Intelligence (AI) systems become increasingly integrated into critical domains, ensuring privacy-preserving model design and system deployment has become a pressing priority. Safeguarding both sensitive user data and proprietary model parameters is critical throughout the AI model and system, from data acquisition and pre-processing to model inference and deployment. However, existing privacy-preserving frameworks face several limitations, including fragmented data ownership, incomplete protection across system stages, substantial computational overhead, and poor scalability to modern architectures such as large language models. This dissertation explores a unifying optimization strategy centered on input structure design to address these challenges. The core idea is …

Traffic Prediction For Research And Education Networks: Anomaly-Aware Deep Learning And Benchmarking, Mohammad Arafath Uddin Shariff

School of Computing: Dissertations, Theses, and Student Research

Research and Education Networks (RENs) and High-Performance Computing (HPC) environments are critical infrastructures for modern scientific discovery, demanding sustained high-throughput and low-latency data transfers. Unlike commercial networks, RENs exhibit unique traffic characteristics, including predominant “elephant flows,” inherent burstiness, and complex temporal-spatial dynamics often decoupled from human-driven cycles. Traditional traffic forecasting methods, tailored for commercial Wide Area Networks (WANs), consistently fail to capture these distinct REN dynamics, leading to inefficient resource management and potential impediments to scientific progress.

This thesis addresses this critical gap by developing and validating a robust, scalable, and anomaly-aware traffic forecasting framework specifically tailored for REN/HPC networks. …

Simulation Of Photochemical Effects On Air Quality, Grace Li

Chemical Engineering Undergraduate Honors Theses

Nitrogen dioxide (NO₂) and ozone (O₃) are both EPA criteria air pollutants in the troposphere, largely generated by combustion and therefore present in significant concentrations in urban areas. Sunlight facilitates chemical reactions between pollutants and ambient air. Aerosols modulate the amount of available energy required to drive such photochemical reactions, ultimately impacting air quality. Simulating photolysis rates with FastJX software is a resource-efficient strategy to study how these aerosols can affect air quality.

Effective Transformer Networks For Undersampled Magnetic Resonance Image Reconstruction, Tahsin Rahman

Open Access Theses & Dissertations

The proliferation of data-driven tools for solving problems in every possible domain, coupled with rapid advances in computing technology, has led to an arms race of AI development and application research in industry and academia. One field of research that stands to gain immeasurably from this revolution is medical imaging. It is a critical part of modern diagnostics, and advancements in this area can directly benefit the average person by making healthcare more accessible, accurate, and affordable. Breakthroughs in mainstream image processing and computer vision have long fueled development in medical imaging, and it is now common to see cutting …

Visceral, Neural, And Immunotoxicity Of Per- And Polyfluoroalkyl Substances: A Mini Review, Pietro Martano, Samira Mahdi, Tong Zhou, Yasmin Barazandegan, Rebecca Iha, Hannah Do, Joel Burken, Paul Ki-Souk Nam, Qingbo Yang, Ruipu Mu

Chemistry Faculty Research & Creative Works

Per- and polyfluoroalkyl substances (PFASs) have gained significant attention due to their widespread distribution in the environment and potential adverse health effects. While ingestion, especially through contaminated drinking water, is considered the primary route of human exposure, recent research suggests that other pathways, such as inhalation and dermal absorption, also play a significant role. This review provides a concise overview of the toxicological impacts of both legacy and emerging PFASs, such as GenX and perfluoro butane sulfonic acid (PFBS), with a particular focus on their effects on the liver, kidneys, and immune and nervous systems, based on findings from recent …

Low Energy Ion Irradiation Effects In Electronic Devices And Materials, David C. Mccall

All Dissertations

The physics and engineering of ion-solid interactions are governed by the ion beam characteristics (flux, charge, energy) and target(s) in question. Here I present work on two projects related to the extraction of a high flux of low charge state Argon ions from a commercial plasma source and the irradiation of an engineered target, a transistor, with high charge state Argon ions.

An end-Hall ion source that produces a a high current plasma of ions and electrons in a rough vacuum environment is characterized. Using a Langmuir probe and multiple pressure measurements, the ion and electron content of the source …

Robustness Investigation, Detection, And Defense Of Deep Learning Models Against False Data Injection, Amirhossein Nazeri

All Dissertations

This dissertation addresses the critical challenge of adversarial robustness in deep learning systems, focusing on two fundamental domains: time-series prediction and object detection. As these AI systems become increasingly deployed in safety-critical applications from power grid management to autonomous vehicles their vulnerability to adversarial attacks poses significant risks to infrastructure and human safety.

The first contribution introduces a novel stealthy black-box False Data Injection (FDI) attack specifically designed for quasi-periodic time-series data. Unlike existing attacks that produce easily detectable anomalies, our method generates adversarial perturbations that preserve the underlying periodicity and statistical properties of the data, effectively bypassing traditional anomaly …

Advancing Lithium-Ion Batteries Through Exploration Of Novel Physico-Chemical Phenomena, Peshal Karki

All Dissertations

Lithium-ion batteries (LIBs) power a wide range of modern devices, from smartphones to electric vehicles. This dissertation integrates materials characterization and electrochemical testing to develop novel Si-based electrode materials, investigate separator effects, and improve electrochemical impedance spectroscopy (EIS) modeling. First, I synthesized Si@CC composites using bio-based carbon sources and discovered a novel in situ disorder reduction in the amorphous carbon cloud during cycling, attributed to Si volume fluctuations and mesoporous carbon structure, which enhanced capacity retention. A binder-free electrode (Si@CC@BP) using bucky paper further improved gravimetric and areal capacities while reducing weight and manufacturing complexity.

Next, I investigated how separator …

Enhanced Point Cloud Generation From A Novel 360° Underwater Lidar, Olagoke E. Daramola

Dissertations

This dissertation presents novel algorithms to improve the mapping capabilities of a 360-degree underwater Pulsed Laser Line Scanner LiDAR (PLLS-360°). Due to its 360° field-of-view (FOV), the PLLS-360° is a compact full-waveform omnidirectional imager suitable for seafloor mapping, underwater asset inspection, object detection, ice-sheet mapping, and construction progress monitoring. The proposed methodology includes an improved waveform fitting technique for saturated waveform recovery, detection array response correction, radiometric corrections, and fusion of LiDAR and sonar bathymetric datasets. The first part of this dissertation assesses the LiDAR’s performance and describes how the data for this unique 360° FOV architecture is processed. The …