Engineering Commons^™

Magdm Model Using Single-Valued Neutrosophic Credibility Matrix Energy And Its Decision-Making Application, Jun Ye, Rui Yong, Wanlu Du

Neutrosophic Systems with Applications

This paper aims to develop a MAGDM model using single-valued neutrosophic credibility matrix (SVNCM) energy in a SVNCM scenario. To do it, first, SVNCM energy and its score function are presented as a conceptual extension of existing single-valued neutrosophic matrix (SVNM) energy. Then, a MAGDM model is developed in terms of SVNCM energy and its score function in a SVNCM scenario and also its decision algorithm is provided to solve MAGDM problems with SVNCMs. Finally, the developed MAGDM model is applied in the school site selection problem as an actual example, then the comparative investigation of the decision results in …

Experiment Development And Validation Of A Granular Jamming Robotic Gripper, Jacob R. Dowd

UNLV Theses, Dissertations, Professional Papers, and Capstones

A granular jamming gripper (GJG) is widely known as a Universal Gripper because of the wide range of objects that it can grasp and the simplicity of control, design, and manufacturing. Despite multitude of research improving the GJG, here, we focus on the base version of the GJG and attempt to glean the range of objects that it may reliably grasp. Despite the limited range of objects, which were a sphere, rectangular prism, and cylinder, we gleaned geometric properties as it relates to successful and unsuccessful grasping. This was based on the two types of testing: push and pull testing …

Performance Effects Of Dissociated Hydrogen In Nuclear Thermal Propulsion Engines, Richard Adam Gorrell

UNLV Theses, Dissertations, Professional Papers, and Capstones

Nuclear thermal propulsion (NTP) research considers hydrogen dissociation as negligible to design and analysis of propulsion engines. This study reintroduces chemically reacting flow to NTP engine analysis for investigation of the dissociation effect on engine performance. A first-principles approach observes the basic chemical mechanism and reaction within the high-speed, high-temperature NTP flow to baseline expected atomic hydrogen levels and validate equilibrium. A surface reaction study looks into hydrogen absorption through dissociation and its effect on the boundary layer, and bulk flow. For total performance, the resulting dissociated flow is analyzed through nozzle expansion and performance metrics calculated.

All historic reactor …

Redirection Of Current In A Dense Plasma Focus, Rocky Gonzalez

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Mission Support & Test Services (MSTS) reports that significant amounts of energy needed for generating high energy neutrons is lost within a Dense Plasma Focus between its pinch-end of the anode stalk and at its base near the insulating sleeve. It is their mission and the goal of this research effort to both experimentally and theoretically study current redirection in a DPF during and after pinch dynamics. It is hypothesized that current redirection, due to restrike, behind the dynamic sheath of a dense plasma focus will result in a measurable change in the magnetic field along the longitudinal axis …

Brain-Inspired Continual Learning: Rethinking The Role Of Features In The Stability-Plasticity Dilemma, Hikmat Khan

Theses and Dissertations

Continual learning (CL) enables deep learning models to learn new tasks sequentially while preserving performance on previously learned tasks, akin to the human's ability to accumulate knowledge over time. However, existing approaches to CL face the challenge of catastrophic forgetting, which occurs when a model's performance on previously learned tasks declines after learning the new task. In this dissertation, we focus on the crucial role of input data features in determining the robustness of CL models to mitigate catastrophic forgetting. We propose a framework to create CL-robustified versions of standard datasets using a pre-trained Oracle CL model. Our experiments show …

Examining The Relationship Between Manning's Roughness Coefficient And Stage, Henry Holtkamp

Biological and Agricultural Engineering Undergraduate Honors Theses

This paper uses LOESS regression to predict Manning's roughness coefficient to calculate flows in natural stream channels. Manning's roughness coefficient can introduce variability into Manning's equation, potentially destabilizing results. Utilizing LOESS to find n based on backcalculated n from collected discharge vs. stage information is the best way to acquire accurate Manning's roughness coefficient values at a variety of flows. Book values tend to drastically overestimate which can have wide-ranging implications for water allocation, flood management, maintaining environmental flows, and maintaining water quality.

The Importance Of Text Representation For Neural Networks Through Natural Language Processing Techniques, William Parsley

Data Science Undergraduate Honors Theses

Text representation is a fundamental aspect of natural language processing (NLP) when it comes to the performance of neural networks. Free-form text fields are being utilized in more and more industries. Anything from a description of an item on a web store to tracking service events to military-grade aircraft is being collected in free-form text. The goal of the thesis is to highlight best practices and discuss trends in data to prepare text for a neural network. It will demonstrate various techniques for representing free-form text in the context of neural networks, focusing on data preparation decisions, embedding techniques, and …

Examining The Impact Of Customer Rfp Characteristics On Award Compliance, Laasya Ravipati

Data Science Undergraduate Honors Theses

In the context of intermodal transportation, understanding the dynamics of award compliance holds significant importance for operational efficiency and strategic decision-making. Award compliance refers to the percentage of awarded freight volume that is realized, indicating the extent to which contractual agreements are fulfilled. This analysis delves into the intricate relationship between customer characteristics and award compliance, aiming to provide valuable insights into the variability and predictability of compliance rates. By analyzing Request for Pricing (RFP) data and primary awarded freight volumes, the study seeks to address the need for more accurate volume estimations, crucial for sales planning, revenue projections, and …

Examining Award Compliance To Inform Resource Allocation, Jacob Haarala

Data Science Undergraduate Honors Theses

This project focuses on JB Hunt Transport Inc's intermodal business unit (JBI) by focusing on the challenges associated with Published Pricing and Contractual Pricing. The primary issue revolves around the variance between the awarded freight volumes in Requests for Pricing (RFPs) and the actual volumes realized when the freight is shipped. This discrepancy poses challenges for effective sales planning, revenue goals, and optimal freight network management within JBI. Reporting tools, such as PowerBI, are currently used by JBI to provide insights into award compliance on a weekly basis. However, our goal with this project was to provide a deeper understanding …

Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark

Honors Theses

Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …

Numerical Simulation Of Laser Induced Elastic Waves In Response To Short And Ultrashort Laser Pulses., Alireza Zarei

All Dissertations

In an era of intensified market competition, the demand for cost-effective, high-quality, high-performance, and reliable products continues to rise. Meeting this demand necessitates the mass production of premium products through the integration of cutting-edge technologies and advanced materials while ensuring their integrity and safety. In this context, Nondestructive Testing (NDT) techniques emerge as indispensable tools for guaranteeing the integrity, reliability, and safety of products across diverse industries.

Various NDT techniques, including ultrasonic testing, computed tomography, thermography, and acoustic emissions, have long served as cornerstones for inspecting materials and structures. Among these, ultrasonic testing stands out as the most prevalent method, …

Vr Circuit Simulation With Advanced Visualization For Enhancing Comprehension In Electrical Engineering, Elliott Wolbach

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

As technology advances, the field of electrical and computer engineering continuously demands innovative tools and methodologies to facilitate effective learning and comprehension of fundamental concepts. Through a comprehensive literature review, it was discovered that there was a gap in the current research on using VR technology to effectively visualize and comprehend non-observable electrical characteristics of electronic circuits. This thesis explores the integration of Virtual Reality (VR) technology and real-time electronic circuit simulation with enhanced visualization of non-observable concepts such as voltage distribution and current flow within these circuits. The primary objective is to develop an immersive educational platform that makes …

From Bits To Beds: Design And Implementation Of A Hotel Booking System A Coding Project, Alexa Gilman

University Honors College

This thesis presents a comprehensive hotel booking system designed and implemented to showcase the transition "From Bits to Beds". There are two main motivations behind this project: firstly, to provide users with a user-friendly and efficient platform for booking accommodations. Secondly, it serves as a great learning opportunity, providing hands-on practice with coding, collaboration with teammates, and exposure to real-world challenges. The system utilizes technologies such as JavaScript, Express.js, and HTML/CSS to offer features like browsing hotels, filtering options, user authentication, and booking management. The implementation of this project demonstrates a successful integration of backend and frontend components, ensuring reliability …

Challenges For Room Temperature Operation Of Electrically Pumped Gesn Lasers, A. R. Ellis, D. A. Duffy, I. P. Marko, S. Acharya, W. Du, S. Q-. Yu, S. J. Sweeney

Electrical Engineering and Computer Science Faculty Publications and Presentations

Recent demonstrations of room-temperature lasing in optically pumped GeSn show promise for future CMOS compatible lasers for Si-photonics applications. However, challenges remain for electrically pumped devices. Investigation of the processes that limit device performance is therefore vital in aiding the production of future commercial devices. In this work, a combined experimental and modelling approach is utilised to explore the dominant loss processes in current devices. By manipulating the band structure of functioning devices using high hydrostatic pressure techniques at low temperature, the dominant carrier recombination pathways are identified. This reveals that 93 ± 5% of the threshold current is attributable …

Drag Reduction In Channel Flow Configurations For Laminar And Turbulent Flow Past Superhydrophobic Surfaces, Henry Louis Ems

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

In this work, we present friction drag reduction in minichannel laminar flow past superhydrophobic metallic surfaces. Femtosecond laser surface processing (FLSP), a one-step scalable method, was used to create permanent microscale and nanoscale structures on 316 stainless steel plates. The resulting superhydrophilic plates were covered by tall (215 μm) or short (27 μm) structures. The FLSP plates were then transitioned to superhydrophobic by evaporative deposition of a fluorinated silane, a low surface energy coating. Using purified water, the friction factor was obtained by measuring pressure drop along a minichannel with a rectangular cross section for flow rates corresponding …

The Analysis Of Mechanical Exfoliation Of Graphene For Various Fabrication And Automation Techniques, Lance Yarbrough

Mechanical Engineering Undergraduate Honors Theses

Mechanical Exfoliation of Graphene is an often-overlooked portion of the fabrication of quantum devices, and to create more devices quickly, optimizing this process to generate better flakes is critical. In addition, it would be valuable to simulate test pulls quickly, to gain insight on flake quality of various materials and exfoliation conditions. Physical pulls of graphene at various temperatures, pull forces, and pull repetitions were analyzed and compared to the results of ANSYS simulations, solved for similar results. Using ANSYS’ ability to predict trends in exfoliations, flake thickness and coverage using stress and deflection analyses were investigated. Generally, both strongly …

Reducing Carbon Emissions With Returned Concrete, John M. Maxwell Jr.

Construction Management

The concrete industry is one of the most energy-intensive sectors of construction. Specifically, the cement production aspect is the most energy intensive, and produces the most carbon emissions. Concrete, a material ubiquitous with nearly every facet of construction; certain types of structures are composed of nearly all concrete. Production of cement is one of the biggest contributors to emissions within the industry. There have been initiatives to reduce or offset emissions from this process, through things like carbon capture, and the purchase of carbon or emissions credits. The objective of this paper was to investigate a new method of carbon …

An Edge Computing System With Amd Xilinx Fpga Ai Customer Platform For Advanced Driver Assistance System, Tsun Kuang Chi, Tsung Yi Chen, Yu Chen Lin, Ting Lan Lin, Jun Ting Zhang, Cheng Lin Lu, Shih Lun Chen, Kuo Chen Li, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

The convergence of edge computing systems with Field-Programmable Gate Array (FPGA) technology has shown considerable promise in enhancing real-time applications across various domains. This paper presents an innovative edge computing system design specifically tailored for pavement defect detection within the Advanced Driver-Assistance Systems (ADASs) domain. The system seamlessly integrates the AMD Xilinx AI platform into a customized circuit configuration, capitalizing on its capabilities. Utilizing cameras as input sensors to capture road scenes, the system employs a Deep Learning Processing Unit (DPU) to execute the YOLOv3 model, enabling the identification of three distinct types of pavement defects with high accuracy and …

Database And Machine Learning Model For Classifying Autism Spectrum Disorder From Smartphone Based Electroretinography, Rory Harris

Honors Scholar Theses

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that negatively affects a patient’s cognitive and communication aptitude and, therefore, can severely impact that patient’s quality of life. Because of this, early diagnosis is paramount. In recent studies, electroretinography (ERG), which is a measure of the retina’s electrical response to a brief flash of light into the eye, has shown promise in detecting ASD. Access to these scans can provide early diagnosis, improving well-being. Current ERG devices are very expensive due to their on board processing capabilities. This paper aims to create an ERG device using a smartphone as the main …

Bay Water Level Influences On Inundation And Morphological Changes Of A Semi-Connected Barrier Island During A Hurricane, Sydney D. Goodman

Graduate Theses and Dissertations (2019 - present)

This research aims to identify flooding and erosion changes along a semi-connected barrier island system due to varying bay water levels during storm conditions. The numerical model XBeach is used to simulate Hurricane Michael conditions and the resulting inundation and morphological change near Tyndall Air Force Base (Tyndall AFB). The installation is located 12 miles southeast of Panama City Beach along the panhandle of Florida and is vulnerable to flooding due to its proximity to the Gulf of Mexico (GoM), Saint Andrew Sound and Saint Andrew Bay. A land bridge connects the barrier island to the mainland of Tyndall AFB …

Improving Static Cold Storage Life Of The Human Heart Before Transplant, Juan Sebastian Rodriguez Paez

Theses and Dissertations

Organ storage and transportation are critical steps for the success of organ transplantation. Static cold storage (SCS) of hearts for heart transplantation (HTx) remains the standard approach. However, SCS may involve damage to the tissue resulting from extended hypothermic preservation, potentially affecting organ viability. More over, the temperature distribution on and within the heart is unknown during heart transplantation. Therefore, there is an interest to study different stages of the heart transplantation process towards determining the 3D temperature distribution on and within the heart. There could be a possibility of having a hypothermic injury in different parts of the heart …

Denoising Diffusion Probabilistic Models Based Accelerated Mri, Alexander Francis Bugielski

Theses and Dissertations

Magnetic Resonance Imaging (MRI) is a cornerstone in obtaining intricate visualizations of anatomy and physiological processes within the human body. However, its extensive scan duration not only causes patient discomfort but also increases the likelihood of motion-induced artifacts in the images. To address such a challenge, this study investigates deep neural network models for reconstructing high-resolution MRI images from noisy and significantly undersampled data in a supervised learning manner. Specifically, it compares three models: a conventional U-Net, a self-attentive U-Net, and an innovative probabilistic diffusion model that builds upon the self-attentive U-Net architecture. These models are evaluated on their ability …

Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger

Master's Theses

In this work, we study the use of modern portfolio theory in a cost-risk analysis of the Electric Reliability Council of Texas (ERCOT). Based upon the risk-return concepts of modern portfolio theory, we develop an n-asset minimization problem to create a risk-cost frontier of portfolios of technologies within the ERCOT electricity region. The levelized cost of electricity for each technology in the region is a step in evaluating the expected cost of the portfolio, and the historical data of cost factors estimate the variance of cost for each technology. In addition, there are several constraints in our minimization problem to …

Spin Disorder Control Of Topological Spin Texture, Hongrui Zhang, Yu-Tsun Shao, Xiang Chen, Binhua Zhang, Tianye Wang, Fanhao Meng, Kun Xu, Peter Meisenheimer, Xianzhe Chen, Xiaoxi Huang, Piush Behera, Sajid Husain, Tiancong Zhu, Hao Pan, Yanli Jia, Nick Settineri, Nathan Giles-Donovan, Zehao He, Andreas Scholl, Alpha N'Diaye, Padraic Shafer, Archana Raja, Changsong Xu, Lane W. Martin, Michael F. Crommie, Jie Yao, Ziqiang Qiu, Arun Majumdar, Laurent Bellaiche, David A. Muller, Robert J. Birgeneau, Ramamoorthy Ramesh

Physics Faculty Publications and Presentations

Stabilization of topological spin textures in layered magnets has the potential to drive the development of advanced low-dimensional spintronics devices. However, achieving reliable and flexible manipulation of the topological spin textures beyond skyrmion in a two-dimensional magnet system remains challenging. Here, we demonstrate the introduction of magnetic iron atoms between the van der Waals gap of a layered magnet, Fe₃GaTe₂, to modify local anisotropic magnetic interactions. Consequently, we present direct observations of the order-disorder skyrmion lattices transition. In addition, non-trivial topological solitons, such as skyrmioniums and skyrmion bags, are realized at room temperature. Our work highlights …

Modeling Vibration Stiffness: An Analytical Extension Of Hertzian Theory For Angular Contact Bearings With A Thin Viscoelastic Coating, Davis R. Burton

Honors Theses

This thesis considers the novel angular contact rolling-element bearings proposed by NASA’s Glenn Research Center, which are coated with a thin solid lubricant that exhibits viscoelastic behavior. Current analytical models for the dynamic stiffness matrix of angular contact bearings, critical for vibration analysis, lack the ability to model the effects of a solid coating, as well as the time dependencies inherent in viscoelastic theory. The author first presents an overview of the stiffness matrix derivation, followed by a treatment of the underlying Hertzian contact theory. An analytical extension of this theory is proposed which accounts for a thin elastic layer …

Algorithm-Based Linearly Graded Compositions Of Gesn On Gaas (001) Via Molecular Beam Epitaxy, Calbi Gunder, Mohammad Zamani-Alavijeh, Emmanuel Wangila, Fernando Maia De Oliveira, Aida Sheibani, Serhii Kryvyi, Paul C. Attwood, Yuriy I. Mazur, Shui-Qing Yu, Gregory J. Salamo

Physics Faculty Publications and Presentations

The growth of high-composition GeSn films in the future will likely be guided by algorithms. In this study, we show how a logarithmic-based algorithm can be used to obtain high-quality GeSn compositions up to 16% on GaAs (001) substrates via molecular beam epitaxy. Herein, we use composition targeting and logarithmic Sn cell temperature control to achieve linearly graded pseudomorph Ge_1−xSn_x compositions up to 10% before partial relaxation of the structure and a continued gradient up to 16% GeSn. In this report, we use X-ray diffraction, simulation, secondary ion mass spectrometry, and atomic force microscopy to analyze and …

Design And Application Of Smart Systems To Address Analytical Problems, Lucas B. Ayres

All Dissertations

This dissertation is a multidisciplinary effort that integrates low-cost analytical instrumentation, redox chemistry, and artificial intelligence to overcome existing limitations in the fields of wearable sensing technology, Deep Eutectic Solvents (DES), and antioxidant chemistry. The overall goal behind each implemented strategy is to enhance the accuracy, efficiency, and accessibility of analytical processes and technologies. A general overview of the thesis, along with the research outcomes is included in Chapter One. The theoretical framework of this dissertation is presented in Chapter Two. Chapter Three describes the development of a wearable platform (sensor and instrumentation) to rapidly detect (~20 minutes) S. aureus …

Geomagnetic Substorms Prediction Model Using Combined Physics-Based And Deep Learning Modeling Techniques, Ruthba Yasmin

Graduate Theses and Dissertations (2019 - present)

This thesis aims to develop a hybrid physics-incorporated neural network model (PINN) for classifying geomangnetic substorms in Earth's Magnetosphere. The model is trained using a comprehensive list of substorm onsets, ground magentometer data from a global network, and solar wind parameters from the Advanced Composition Explorer (ACE) satellite. Two different neural network architectures are used, and the physics model used for training is called WINDMI. The magnetic field components on the ground, which are a function of the ionospheric currents, are captured by the SML index. The methodology involves using 60-minute data segments preceding an event to train the hybrid …

Cloud Computing Integration Into Mixed-Reality: Physical To Abstraction, Yassine Chahid, Patrick Slattery

Publications and Research

This research evaluates the progression of cloud computing and mixed-reality technologies, and to identify how these technologies influence advancements in the latter. Both cloud computing and mixed reality have significantly impacted the IT field and the services available to the public and various institutions. Cloud computing provides a valuable way to process information or allocate computational resources on otherwise limited hardware. Augmented or virtual reality hardware would greatly benefit from this by offloading resource-intensive tasks to other machines. The research methodology involves analyzing essential components of both innovations, divided into multiple categories. These components range from physical, hardware-based elements to …

Modeling Sex-Specific Changes In Myocardial Fibrosis, Grace Martin

Chemical Engineering Undergraduate Honors Theses

Heart disease the leading cause of death for both men and women in the United States. Cardiac fibrosis, or accumulation of extracellular matrix proteins in the heart, can occur after a heart attack and increase the risk for further complications. Current treatments for heart disease do not include extracellular matrix regulators, partly due to the complicated signaling network responsible for the production of these proteins. By using a computational model of the signaling network in cardia fibroblasts, the relationship between particular molecules and downstream extracellular matrix production can be examined.

Biological sex is an important factor for cardiac health and …