Physical Sciences and Mathematics Commons^™

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 …

Optimizing Ai With Advanced Data Structuring: A Comparative Analysis Of K-Means And Gmm Clustering Techniques, Amir Alipour Yengejeh

Data Science and Data Mining

This study presents a detailed comparison of Kmeans and Gaussian Mixture Model (GMM) clustering algorithms, illustrating their unique capabilities and limitations across various synthetic datasets. By utilizing metrics such as the Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI), the research provides nuanced insights into how these algorithms handle datasets with varying structures and complexities. For instance, while both K-means and GMM show robust performance on well-separated clusters, GMM demonstrates a distinct advantage in scenarios with overlapping clusters or unbalanced data distributions. Conversely, K-means excels in identifying clear, distinct groupings, highlighting its utility in simpler clustering contexts. This study …

Machine Learning Approaches For Cyberbullying Detection, Roland Fiagbe

Data Science and Data Mining

Cyberbullying refers to the act of bullying using electronic means and the internet. In recent years, this act has been identifed to be a major problem among young people and even adults. It can negatively impact one’s emotions and lead to adverse outcomes like depression, anxiety, harassment, and suicide, among others. This has led to the need to employ machine learning techniques to automatically detect cyberbullying and prevent them on various social media platforms. In this study, we want to analyze the combination of some Natural Language Processing (NLP) algorithms (such as Bag-of-Words and TFIDF) with some popular machine learning …

Xgboost Hyperberd Model Using Steam Platform, Yuh-Haur Chen

Data Science and Data Mining

This project investigates game pricing strategies in the Steam market using an XGBoost model, drawing motivation from Professor Xie's lecture, and presenting findings through a density plot that delineates two primary pricing strategies. A free-to-play approach, indicated by a significant hot spot, is adopted by developers focusing on post-purchase revenues through DLC, aesthetic purchases, and in-game transactions. This sailing strategy includes community-centric developers aiming to distribute their games for player engagement rather than profit.

The project illustrates the effectiveness of advanced modeling techniques in handling complex datasets, with significant predictive accuracy reflected by a reduced MSE from 0.3472 to 0.1397. …

Predicting Road Accident Injury Severity For Drivers In Automobile Crashes In United States Using Machine Learning Models And Ai, Emil Agbemade, Benedict Kongyir

Data Science and Data Mining

This study analyzes data from the National Highway Trafc Safety Administration’s 2021 Crash Report Sampling System to identify key factors contributing to the severity of injuries in car accidents. By utilizing various machine learning algorithms and cross-validation techniques, we assessed metrics such as accuracy, sensitivity, precision, specifcity, and the area under the curve (AUC) to evaluate the efectiveness of predictive models. All data preprocessing and model building was done using KNIME Analytical software [9]. Our fndings reveal signifcant correlations between certain variables such as airbag injection, weather conditions, intoxication, vehicle state, driver distractions, and injury severity. These insights underscore the …

Dynamics And Inverse Problems For Nonlinear Schrödinger Equations, Christopher Hogan

Doctoral Dissertations

"The cubic nonlinear Schrödinger equation (NLS) is a model of interest in the study of physical problems including nonlinear optics and Bose-Einstein condensates. Of particular interest is the study of cubic NLS with inhomogeneities such as localizations of the nonlinearity or terms introducing potential barriers. We first address some preliminaries and techniques useful in the study of the cubic NLS and its variations. We then consider the cubic NLS with a localized nonlinearity in dimensions d ≥ 2. We show that solutions with data given by small-amplitude wave packets accrue a nonlinear phase that determines the X-ray transform of the …

High-Resolution Spectroscopy Of Interstellar Lines And Comets, Chemeda Tadese Ejeta

Doctoral Dissertations

"The study of interstellar molecules such as CO is crucial because interstellar ices in the core of a pre-solar molecular cloud provide the starting point for volatile evolution in the protoplanetary disk. A record of the initial volatile composition of the protoplanetary disk can be obtained from the study of the chemical composition of cometary nuclei. Because of their long residence in the Oort cloud and infrequent passage through the inner solar system, long-period comets are one of the most primitive bodies in our solar system that can tell us about the composition of the early solar system. High-resolution infrared …

Community Science And Coyote Stories: Capturing And Communicating Nature's Non-Material Values For Use In Decision-Making, Joshua Wright Morse

Graduate College Dissertations and Theses

The reasons and ways that nature matters underlie every part of environmental decision-making. Yet, there are disparities in how different kinds of benefits from and values about nature are represented in policy and practice. This dissertation explores how decision-makers and community members value nature broadly and also in the context of a specific human-wildlife interaction in Vermont, United States.

In my first chapter, I conduct semi-structured interviews with environmental sector practitioners in Vermont to learn about their awareness of non-material values from nature. I find that practitioners talk readily about both material and non-material ecosystem services as well as multiple …

Analysis Of Ultra-Wideband Voltage Pulse Propagation On Dispersive Absorptive Transmission Lines, Katherine Aho

Graduate College Dissertations and Theses

Electromagnetic transient waves are pulsed events that occur when there is an abruptchange in the typical steady-state conditions on a transmission line. Digital pulses on integrated circuits and a lightning strike on overhead power lines are some examples of transient voltage pulses. Although transients occur within a very short time duration, they can propagate over long distances; much farther than a slowly-varying envelope signal can propagate. Lingering effects of transients can be damaging to electrical equipment if they are not properly mitigated. Despite the negative effects of transients, certain designed transient pulses may be used to an advantage in remote …

Escape The Planet: Revolutionizing Game Design With Novel Oop Techniques, Qusai Kamal Fannoun

All Graduate Theses, Dissertations, and Other Capstone Projects

Mobile devices are continuously evolving and greater computing power and graphics capabilities are being introduced every year. As a result, there is an increasing demand for challenging and engaging mobile games that leverage these advanced features. This project explores best design practices using the development of Escape the Planet, which is an intricate maze game for mobile devices in which players navigate using a spaceship that is trapped in a hostile planet’s maze while avoiding obstacles and enemy attacks. The goal is to safely guide the spaceship out of the maze without colliding into walls or taking bullets from defensive …

Intelligent Traffic Management Systems, Mohammad Mazhar

All Graduate Theses, Dissertations, and Other Capstone Projects

With the increase in population and in particular urban population. The traffic and travel times in between cities and inside cities has increased due to more and more people using private means of transportation. Due to this need arose for tackling the increase in traffic by managing it using various means. For this we look towards The Intelligent Traffic Management System (ITMS). ITMS is an AI-powered solution designed to optimize traffic flow, reduce congestion, and improve overall road safety. The system will monitor real-time traffic data using a combination of cameras and sensors, identify traffic jams, and send alerts to …

Growing Up Sustainable? Politics Of Race And Youth In Urbanplan, Copenhagen, Max Ritts, Rebecca Rutt

Geography

This paper considers how racialized youth in Denmark negotiate sustainability amid contexts marked by intersecting forms of economic restructuring, progressive neoliberalism, white ethno-nationalism, and green urban planning. Urbanplan is a low-income, notoriously “troubled” Copenhagen neighborhood where we conducted fieldwork for 7 months (2019-2020) with fifteen male youth, aged 17-21. Using ethnography, policy reviews, and interviews with city social workers, we explore how intimate experiences of nature, group-identity, and place attachment here relate to and depart from the structural forces actively reshaping the neighborhood. Our analysis combines Cindi Katz's intersectional political economy approach with recent work on green gentrification, Critical Utopian …

Fault-Tolerant Consensus In Anonymous Dynamic Network, Qinzi Zhang, Lewis Tseng

Computer Science

This paper studies the feasibility of reaching consensus in an anonymous dynamic network. In our model, n anonymous nodes proceed in synchronous rounds. We adopt a hybrid fault model in which up to f nodes may suffer crash or Byzantine faults, and the dynamic message adversary chooses a communication graph for each round. We introduce a stability property of the dynamic network - (T, D)-dynaDegree for T ≥ 1 and n - 1 ≥ D ≥1 - which requires that for every T consecutive rounds, any fault-free node must have incoming directed links from at least D distinct neighbors. These …