Physical Sciences and Mathematics Commons^™

Phenanthrene Jamboree, Alexander D. Roth

Honors Theses

Using cyclopropanated and cyclobutanated phenanthrene precursors, our hero embarks on a mission to find as many reactive intermediates as possible. Fraught with danger, romance, and mangosteens, Anderson calls this work 'monstrous' and 'alarming.'

Stealthy Control Logic Attacks And Defense In Industrial Control Systems, Adeen Ayub

Theses and Dissertations

Industrial control systems (ICS) play a crucial role in monitoring and managing critical infrastructure, including nuclear plants, oil and gas pipelines, and power grid stations. Programmable logic controllers (PLCs) are a fundamental component of ICS, directly interfacing with physical processes and implementing control logic programs that govern operations. Due to their significance in controlling critical infrastructure, PLCs often become prime targets for attackers seeking to disrupt these systems. Exploitable vulnerabilities in PLCs render them susceptible to such attacks. While many attacks on PLCs leave a large footprint in network traffic and are detectable by intrusion detection systems (IDS), this dissertation …

Assessing Performance Optimization Strategies In Cloud-Native Environments Through Containerization And Orchestration Analysis, Daniel E. Ukene

Electronic Theses and Dissertations

This thesis comprises three distinct, yet interconnected studies addressing critical aspects of web infrastructure management. We begin by studying containerization via Docker and its impact on web server performance, focusing on Apache and Nginx hosted on virtualized environments. Through meticulous load testing and analysis, we provide insights into the comparative performance of these servers, adding users of this technology know which webservers to leverage when hosting their webservice along alongside the infrastructure to host it on. Next, we expand our focus to examine the performance of caching systems, namely Redis and Memcached, across traditional VMs and Docker containers. By comparing …

Characterization Of Carbon Nanotube/Polystyrene Composites Prepared Via Microwave-Induced Polymerization, Hubert Agamasu

Electronic Theses and Dissertations

Carbon nanotubes (CNTs), with their excellent mechanical properties, are well suited to the production of composites with good strength-to-weight ratio. However, the use of nanotubes as reinforcement is hampered by the lack of interaction between their inert surfaces and matrices. This, coupled with the van der Waal’s interactions between individual nanotubes, leads to agglomeration of CNTs in media. Functionalization is an efficient means to disperse nanotubes as well as increase their reactivity. The irradiation of CNTs with microwaves generates instantaneous, localized heating, being used in this work to trigger the rapid, thermal, free radical polymerization of styrene. Under microwaves, olefin-functionalized …

Machine Learning Based Three-Limb Core-Type Transformer Core Aspect Ratios Identification, Ananta Bijoy Bhadra

Electronic Theses and Dissertations

Power transformers are considered one of the key elements of electric grids. Transient studies include transformer transient analysis which is required for the continuous power supply. However, to perform the transient analysis, the details of the internal structure of the transformer are required which are unobtainable and considered as confidential information. Therefore, the application of topological-based transformer models is limited although the models can accurately represent the transformers. To address this concern, a novel approach utilizing Machine Learning (ML) to identify the core aspect ratios of the three-limb core-type transformer is introduced. The proposed approach, using only the voltage and …

Adaptive Multi-Label Classification On Drifting Data Streams, Martha Roseberry

Theses and Dissertations

Drifting data streams and multi-label data are both challenging problems. When multi-label data arrives as a stream, the challenges of both problems must be addressed along with additional challenges unique to the combined problem. Algorithms must be fast and flexible, able to match both the speed and evolving nature of the stream. We propose four methods for learning from multi-label drifting data streams. First, a multi-label k Nearest Neighbors with Self Adjusting Memory (ML-SAM-kNN) exploits short- and long-term memories to predict the current and evolving states of the data stream. Second, a punitive k nearest neighbors algorithm with a self-adjusting …

Optimizing Deep Inspiration Breath Hold Technique For Personalized Breast Cancer Radiotherapy, Srinidhi Rajagopalan

Theses and Dissertations

The purpose of this research is entrenched in advancing the practice of 3D Conformal Radiation Therapy (3D CRT) for breast cancer patients by meticulously evaluating the impact of different Deep Inspiration Breath Hold (DIBH) techniques on dosimetric parameters. This study aims to ascertain the quantitative benefits of varied breathing techniques, primarily focusing on the 'Ultimate DIBH' method's efficacy in sparing critical organs such as the heart and lungs.

The comprehensive analysis of different DIBH techniques in this research is not merely an academic exercise but is geared towards substantiating the hypothesized advantages of these techniques with empirical data. By generating …

On The Links Between Sea Level And Temperature Variations In The Chesapeake Bay And The Atlantic Meridional Overturning Circulation (Amoc), Tal Ezer, Teresa Updyke

CCPO Publications

Recent studies found that on long time scales there are often unexplained opposite trends in sea level variability between the upper and lower Chesapeake Bay (CB). Therefore, daily sea level and temperature records were analyzed in two locations, Norfolk in the southern CB and Baltimore in the northern CB; surface currents from Coastal Ocean Dynamics Application Radar (CODAR) near the mouth of CB were also analyzed to examine connections between the CB and the Atlantic Ocean. The observations in the bay were compared with daily Atlantic Meridional Overturning Circulation (AMOC) observations during 2005–2021. Empirical Mode Decomposition (EMD) analysis was used …

Special Issue Editorial: Business Innovation For The Sustainable Development Goals, Mohamed Saleem Nazmudeen, Fadzliwati Mohiddin, Stephen Singaraju, Seyed M Buhari

ASEAN Journal on Science and Technology for Development

Welcome to this special issue of the ASEAN Journal on Science and Technology for Development (AJSTD), focused on “Business Innovation for the Sustainable Development Goals (SDGs)." This collection features a robust ensemble of 30 papers that not only highlight innovative business practices across the ASEAN region but also align these innovations with the Sustainable Development Goals. These contributions span a diverse range of disciplines, grouped into five broad categories: Management and Strategy, Financial Innovations, Marketing and Consumer Behavior, Information Technology and Systems, and Environmental and Social Impact.

Smes’ Perspectives On The Benefits And Challenges Of Halal Certificate Application In Brunei Darussalam, Kamariah Ismail, Syahnur Farhana Haji Shahlehi, Vivi Nabilah Shaya

ASEAN Journal on Science and Technology for Development

The knowledge and research on SMEs and Halal-related studies in Brunei Darussalam are scant. Guided by the principles of Resource-Based View theory, this qualitative study aims to identify the benefits and challenges of Halal certificate application from the perspectives of Bruneian Halal food SMEs, as they obtain the Brunei’s Halal certificate and label. Based on the purposive and snowball sampling, four semi-structured interviews were conducted with business owners and managers in the Halal food industry. Government officials were also in-terviewed to enhance the findings. Thematic analysis, supplemented by secondary data, was employed for a comprehensive understanding. Four themes emerged, covering …

Fostering Corporate Resilience: Assessing Risk Management Committee Effectiveness In Malaysia’S Telecommunication And Media Sector Pre- And During The Covid-19, Flicia Rimin, Siti Rahayu Beli, Anastasiah Harbi, Imbarine Bujang, Jamaliah Said

ASEAN Journal on Science and Technology for Development

The COVID-19 pandemic has significantly impacted organizations, underscoring the critical role of financial factors in determining performance. Maintaining a healthy financial stance during crises necessitates effective risk management, prompting the exploration of a Risk Management Committee (RMC) as a focal point for addressing risk issues and managing internal controls. A study spanning 2017 to 2021 assessed 11 listed companies in the Telecommunication and Media Sector, revealing that a combined RMC did not enhance financial performance, indicating its ineffectiveness during the crisis. The study advocates for a separate risk management committee due to the audit committee’s limitations in performing both functions. …

Creation Of A Digital Storage System For Genome Sequencing Metadata, Jacquelin W. Olexa

Undergraduate Theses, Professional Papers, and Capstone Artifacts

As the field of computational genomics continues to expand in both potential and application, it is now more imperative than ever to ensure that massive genetic sequencing datasets are properly stored in an accessible manner. This project sought to establish a practical, user-friendly, secure system for a genomics research lab (the Good Lab; thegoodlab.org) at the University of Montana. A MySQL database and connected web application was ruled the best configuration to maximize utility and accessibility for the lab’s researchers. Building the logical framework for the database, creating the server, and sourcing data occurred over several months. The dataset ranged …

Front Matter, Konstantin Likharev

Essential Graduate Physics

Includes: Copyright and License; Preface; Disclaimer; Versions, Corrections, and Acknowledgments; Solution Request Templates; Notation; General Table of Contents

References, Appendices & All Parts Merged, Konstantin Likharev

Essential Graduate Physics

Includes: Appendix MA: Selected Mathematical Formulas; Appendix UCA: Selected Physical Units and Constants; References; EGP merged file (all parts, appendices, and references)

Swosu Research And Scholarly Activity Fair 2024, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the members of the University Research and Scholarly Activity Committee (USRAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University (SWOSU) - Welcome to the Thirty-Second SWOSU Research and Scholarly Activity Fair! There are 61 poster presentations and 10 oral presentations involving over 100 student and faculty researchers, writers, presenters, artists, collaborators, and faculty sponsors encompassing activities from the SWOSU Departments of Biological Sciences, Chemistry & Physics, Engineering Technology, Kinesiology, Language & Literature, Mathematics, Music, Parks and Recreation Management, Pharmacy, Psychology, and Social Sciences.

Water-Level And Recoverable Water In Storage Changes, High Plains Aquifer, Predevelopment To 2019 And 2017 To 2019, Virginia L. Mcguire, Kellan R. Strauch

United States Geological Survey: Water Reports and Publications

The High Plains aquifer underlies 111.8 million acres (about 175,000 square miles) in parts of eight States: Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming. Water-level declines began in parts of the High Plains aquifer soon after the beginning of substantial groundwater irrigation (about 1950). This report presents water-level changes and change in recoverable water in storage in the High Plains aquifer from predevelopment (about 1950) to 2019 and from 2017 to 2019.

Water-level changes from predevelopment to 2019, by well, ranged from a rise of 86 feet to a decline of 265 feet; the range for …

Factors That Influence Small Mammal Long Bone Morphology: An Analysis Of The Femora, Tibiae, And Humeri Of The Eastern Gray Squirrel (Sciurus Carolinensis), Tyler Everette Blake

Theses, Dissertations and Capstones

The goal of this study is to examine the effect of urbanization and latitude on bone morphology, specifically limb length and bone density among gray squirrels endemic to the eastern United States. This study’s hypotheses are as follows: gray squirrels occupying lower latitudes will have larger body sizes and longer limbs relative to body size than those at higher latitudes following Bergmann’s and Allen’s rules. Further, squirrels in urban habitats will have greater bone density than those in rural habitats. Results show moderate correlation between body mass and respective proxies and latitude following Bergmann’s rule. Weak correlations were found between …

The Comparison Of Different Wetland Fish Assemblages Over Time, Robert Edward Adelstein

Theses, Dissertations and Capstones

Wetlands provide essential ecosystem services. Historically, we have drained and filled 73% of wetlands for agricultural use throughout the United States from the 1780s to the 1980s (Dahl, 1990). A nationwide focus on restoring wetlands has since occurred. Literature on restored/mitigated wetlands is rife with examples that do and do not support the same ecosystem services as natural wetlands (Langston, 1997; Meil, 2014). Restoration of wetlands occurred at the Green Bottom Wildlife Management Area (GBWMA) over several decades. Various sections of the wetland were classified by age, water depth, and vegetation. One hypothesis was that differences in fish assemblage would …

An Analysis Of Corporate Social Responsibility And Real Earnings Management, Rachel Brassine

Theses, Dissertations and Capstones

Real earnings management (REM) is costly in the form of intense loan restrictions, increased interest expense, and public scrutiny. Nevertheless, companies still practice REM. Based on agency and stakeholder theories, this research predicts that as a company’s CSR score increases, REM will decrease, and this association will become more negative when a critical mass of females on the board of directors exists and when a board-level CSR committee is present. This study also predicts that when a company offers an executive incentive plan based on CSR metrics, REM will decrease, and the relationship will become more negative with a critical …

An Approach To Multidimensional Discrete Generating Series, Svetlana S. Akhtamova, Tom Cuchta, Alexander P. Lyapin

Mathematics Faculty Research

We extend existing functional relationships for the discrete generating series associated with a single-variable linear polynomial coefficient difference equation to the multivariable case.

Structured Invariant Subspace And Decomposition Of Systems With Time Delays And Uncertainties, Huan Phan-Van, Keqin Gu

SIUE Faculty Research, Scholarship, and Creative Activity

This article discusses invariant subspaces of a matrix with a given partition structure. The existence of a nontrivial structured invariant subspace is equivalent to the possibility of decomposing the associated system with multiple feedback blocks such that the feedback operators are subject to a given constraint. The formulation is especially useful in the stability analysis of time-delay systems using the Lyapunov-Krasovskii functional approach where computational efficiency is essential in order to achieve accuracy for large scale systems. The set of all structured invariant subspaces are obtained (thus all possible decompositions are obtained as a result) for the coupled differential-difference equations …

Language Models For Rare Disease Information Extraction: Empirical Insights And Model Comparisons, Shashank Gupta

Theses and Dissertations--Computer Science

End-to-end relation extraction (E2ERE) is a crucial task in natural language processing (NLP) that involves identifying and classifying semantic relationships between entities in text. This thesis compares three paradigms for end-to-end relation extraction (E2ERE) in biomedicine, focusing on rare diseases with discontinuous and nested entities. We evaluate Named Entity Recognition (NER) to Relation Extraction (RE) pipelines, sequence-to-sequence models, and generative pre-trained transformer (GPT) models using the RareDis information extraction dataset. Our findings indicate that pipeline models are the most effective, followed closely by sequence-to-sequence models. GPT models, despite having eight times as many parameters, perform worse than sequence-to-sequence models and …

The Performance Of Marginal Modeling Methods For Rare Events With Application To Opioid Overdose Mortality And Morbidity, Shawn Nigam

Theses and Dissertations--Epidemiology and Biostatistics

Opioid misuse is a nationwide epidemic, with Kentucky having one of the highest opioid overdose-related fatality rates across all US states. These rates have increased significantly over the past decade, with particularly large increases during the COVID-19 pandemic. This dissertation aims to study the behavior of these increases and the methods for the marginal modeling of count outcomes related to opioid overdose.

Opioid overdose-related fatality rates in Kentucky increased significantly during the COVID-19 pandemic. In this chapter, we characterize the changes in opioid overdose fatality rates in Kentucky and identify associations between potential factors and fatality rates. County-level opioid overdose …

Exponential Fusion Of Interpolated Frames Network (Efif-Net): Advancing Multi-Frame Image Super-Resolution With Convolutional Neural Networks, Hamed Elwarfalli, Dylan Flaute, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

Convolutional neural networks (CNNs) have become instrumental in advancing multi-frame image super-resolution (SR), a technique that merges multiple low-resolution images of the same scene into a high-resolution image. In this paper, a novel deep learning multi-frame SR algorithm is introduced. The proposed CNN model, named Exponential Fusion of Interpolated Frames Network (EFIF-Net), seamlessly integrates fusion and restoration within an end-to-end network. Key features of the new EFIF-Net include a custom exponentially weighted fusion (EWF) layer for image fusion and a modification of the Residual Channel Attention Network for restoration to deblur the fused image. Input frames are registered with subpixel …

A Competition Between The Economy And The Environment: An Analysis On The Impacts Of The Olympic Games For Host Countries, Phuong-Anh Ha

Undergraduate Research Awards

The Olympic Games have been known as the most celebrated international sporting event. However, the event has also faced countless criticisms regarding its environmental impact and the lack of benefits it brings to the host country’s economy. The paper analyzes the trade-offs between the environmental quality of a country and its economic growth that host countries make when deciding to host the Olympics. Specifically, this research seeks to explore how the Olympic Games influence the Gross Domestic Product (GDP) and carbon emissions of the host countries.

The Ownership Of Potato Boy: A Discussion On Ai And Copyright, James Thibeault

Library Publications

Surprisingly, the copyright status of generative AI works is pretty straight forward in the US: no one owns the copyright. According to the United States Copyright Office (2023), “copyright can protect only material that is the product of human creativity. Most fundamentally, the term ‘author,’ which is used in both the Constitution and the Copyright Act, excludes non-humans.” This concept is not new as previous court cases had already established this ruling. In the 1884 court case Burrow-Giles Lithographic Company v. Sarony, the defendant made copies of a photograph and claimed the author held no copyright since a machine, a …

Energy Consumption Optimization Of Uav-Assisted Traffic Monitoring Scheme With Tiny Reinforcement Learning, Xiangjie Kong, Chenhao Ni, Gaohui Duan, Guojiang Shen, Yao Yang, Sajal K. Das

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs) can capture pictures of road conditions in all directions and from different angles by carrying high-definition cameras, which helps gather relevant road data more effectively. However, due to their limited energy capacity, drones face challenges in performing related tasks for an extended period. Therefore, a crucial concern is how to plan the path of UAVs and minimize energy consumption. To address this problem, we propose a multi-agent deep deterministic policy gradient based (MADDPG) algorithm for UAV path planning (MAUP). Considering the energy consumption and memory usage of MAUP, we have conducted optimizations to reduce consumption on …

Promoting Thermal Conductivity Of Alumina-Based Composite Materials By Systematically Incorporating Modified Graphene Oxide, Nawon Lee, Jinsol Park, Nayeon Jang, Sehui Lee, Dayeon Kim, Sanggin Yun, Tae Woo Park, Jun-Hyun Kim, Hyun-Ho Park

Faculty Publications – Chemistry

Small amounts of thermally conductive graphene oxide (GO) and modified GO are systematically introduced as a second filler to thermal interface materials (TIMs) consisting of alumina (Al2O3) particles and polydimethylsiloxane (PDMS). The surface of GO is covalently linked with an organic moiety, octadecylamine (ODA), to significantly improve the miscibility and dispersity of GO across the TIM matrix. Subsequently, two series of PDMS-Al2O3 composite TIMs are manufactured as a function of GO and ODA-GO content (0.25 wt%–2.5 wt%) to understand the effect of these second additives. The incorporation of GO into the Al2O3-PDMS composite materials generally increases the thermal conductivity (TC), …

Combating Cyberbullying On Social Media: A Machine Learning Approach With Text Analysis On Twitter, Amir Alipour Yengejeh

Data Science and Data Mining

The popularity of the electronic mobile devices along with social media as well as networking websites have been tremendously increased in the recent year. Most people around the world daily engage in the variety of cyberspace additives. Even though the users can take most advantages of these system such as exchange the idea and information, being sociable, and enjoyments, they might be faced with such adverse behaviors such as toxicity, bullying, extremism, and cruelty. The recent statistics reports that such mentioned behaviors has been noticeably grown on the cyberspace such that can threaten the individuals and even any community. Thus, …

Diagnostic In Neuroimaging: A Comparative Study Of Deep Learning And Traditional Approaches, Amina Issoufou Anaroua

Data Science and Data Mining

In the realm of medical diagnostics, precise classification of brain tumors is pivotal. This study conducts a comprehensive comparative analysis of a Convolutional Neural Network (CNN) against traditional machine learning models, Logistic Regression (LR) and Support Vector Machines (SVM) on a dataset of MRI scans for multi-class brain tumor classification. The CNN, tailored for image recognition, is evaluated alongside LR and SVM, which have established benchmarks in classification tasks. The investigation reveals that the traditional models hold their ground in terms of precision and interpretability, with the SVM, in particular, achieving remarkable accuracy. However, the CNN distinguishes itself by demonstrating …