Physical Sciences and Mathematics Commons^™

The Mathematical And Historical Significance Of The Four-Color Theorem, Brock Bivens

Scholars Day Conference

Computers becoming more readily used in mathematics.

Accessing Advanced National Supercomputing And Storage Resources For Computational Research, Ramazan Aygun

All Things Open

This presentation will cover ACCESS (Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support), and Kennesaw State University's involvement in Open Science Data Federation program as a data origin to help researchers and educators with or without supporting grants to utilize the nation’s advanced computing systems and services. ACCESS, a program established and funded by the National Science Foundation, is an ecosystem with capabilities for new modes of research and further democratizing participation. The presentation covers how to apply for allocations on ACCESS. The last part of the presentation will briefly explain Open Science Data Federation and Kennesaw State University's involvement as …

Mechanistic Investigation Of C—C Bond Activation Of Phosphaalkynes With Pt(0) Complexes, Roberto M. Escobar, Abdurrahman C. Ateşin, Christian Müller, William D. Jones, Tülay Ateşin

Research Symposium

Carbon–carbon (C–C) bond activation has gained increased attention as a direct method for the synthesis of pharmaceuticals. Due to the thermodynamic stability and kinetic inaccessibility of the C–C bonds, however, activation of C–C bonds by homogeneous transition-metal catalysts under mild homogeneous conditions is still a challenge. Most of the systems in which the activation occurs either have aromatization or relief of ring strain as the primary driving force. The activation of unstrained C–C bonds of phosphaalkynes does not have this advantage. This study employs Density Functional Theory (DFT) calculations to elucidate Pt(0)-mediated C–CP bond activation mechanisms in phosphaalkynes. Investigating the …

The Propagation And Execution Of Malware In Images, Piper Hall

Cybersecurity Undergraduate Research Showcase

Malware has become increasingly prolific and severe in its consequences as information systems mature and users become more reliant on computing in their daily lives. As cybercrime becomes more complex in its strategies, an often-overlooked manner of propagation is through images. In recent years, several high-profile vulnerabilities in image libraries have opened the door for threat actors to steal money and information from unsuspecting users. This paper will explore the mechanisms by which these exploits function and how they can be avoided.

Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration, Alvan C. Arulandu, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Application Of Physics Informed Neural Networks For Predicting Disease Dynamics, Alonso Gabriel Ogueda, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

I-GUIDE Forum

Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …

Covid-19 In Casinos: Analysis Of Covid-19 Contamination And Spread With Economic Impact Assessment, Anastasia (Stasi) D. Baran, Jason D. Fiege

International Conference on Gambling & Risk Taking

Abstract:

The COVID-19 pandemic caused tremendous disruption for casinos, with the virus causing various lengths of shutdowns, capacity restrictions, and social distancing strategies such as machine removals or section closures. Although most of the world has now eased off these measures, it is important to review lessons learned to understand, and better prepare for similar circumstances in the future. We present Monte Carlo slot floor simulation software customized to simulate players spreading COVID-19 on the slot floor. We simulate the amount of touch surface contamination; the number of potential surface contact exposure events per day, and a proximity exposures statistic …

Statistical Methods To Generate Artificial Slot Floor Data For The Advancement Of Casino Related Research, Courtney Bonner, Anastasia (Stasi) D. Baran, Jason D. Fiege, Saman Muthukumarana

International Conference on Gambling & Risk Taking

Abstract:

A common difficulty when researching gambling topics is the availability of high-quality data sets for development and testing. Due to the high level of secrecy within the gambling industry, if data is obtained for research purposes it is often prohibitively obfuscated, incomplete, or aggregated. Although these data have allowed for advancement in academic work, it leaves both the researchers and readers left wondering about what would be possible if more detailed data sets were available. To mitigate the paucity of data available to researchers, we present a Markov chain-based statistical process for producing artificial event data for a simulated …

The Locals Casino As A Social Network – Can An Interconnected Community Of Players Detect Differences In Hold?, Jason D. Fiege, Anastasia (Stasi) D. Baran

International Conference on Gambling & Risk Taking

Abstract

It is difficult for individual players to detect differences in theoretical hold between slot machines without playing an unrealistically large number of games. This difficulty occurs because the fractional loss incurred by a player converges only slowly to the theoretical hold in the presence of volatility designed into slot pay tables. Nevertheless, many operators believe that players can detect changes in hold or differences compared to competition, especially in a locals casino market, and therefore resist increasing holds. Instead of investigating whether individual players can detect differences in hold, we ask whether a population of casino regulars who share …

Session 2: The Effect Of Boom Leveling On Spray Dispersion, Travis A. Burgers, Miguel Bustamante, Juan F. Vivanco

SDSU Data Science Symposium

Self-propelled sprayers are commonly used in agriculture to disperse agrichemicals. These sprayers commonly have two boom wings with dozens of nozzles that disperse the chemicals. Automatic boom height systems reduce the variability of agricultural sprayer boom height, which is important to reduce uneven spray dispersion if the boom is not at the target height.

A computational model was created to simulate the spray dispersion under the following conditions: a) one stationary nozzle based on the measured spray pattern from one nozzle, b) one stationary model due to an angled boom, c) superposition of multiple stationary nozzles due an angled boom, …

Hydrogen Bonding In Small Model Peptides; The Dft And Mp2 Study, Gracie Smith, Martina Kaledin

Symposium of Student Scholars

Formamide is a small model compound for the study of the peptide bond. The peptide bond links amino acids together, specifies rigidity to the protein backbone, and includes the essential docking sites for hydrogen-bond-mediated protein folding and protein aggregation, namely, the C=O acceptor and the N-H donor parts. Therefore, the infrared C=O (amide-I) and N-H (amide-A) vibrations provide sensitive and widely used probes into the structure of peptides. This computational chemistry work, we study hydrogen bonds in formamide dimer isomers. We evaluate the accuracy of the density functional theory (DFT) and many-body perturbation theory to the 2^nd order (MP2) …

Physics-Informed Neural Networks For Informed Vaccine Distribution In Heterogeneously Mixed Populations, Alvan Arulandu, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Kuramoto Model Approach To Predicting Chaotic Systems With Echo State Networks, Sophie Wu, Jackson Howe

Undergraduate Student Research Internships Conference

An Echo State Network (ESN) with an activation function based on the Kuramoto model (Kuramoto ESN) is implemented, which can successfully predict the logistic map for a non-trivial number of time steps. The reservoir in the prediction stage exhibits binary dynamics when a good prediction is made, but the oscillators in the reservoir display a larger variability in states as the ESN’s prediction becomes worse. Analytical approaches to quantify how the Kuramoto ESN’s dynamics relate to its prediction are explored, as well as how the dynamics of the Kuramoto ESN relate to another widely studied physical model, the Ising model.

Understanding The Influence Of Perceptual Noise On Visual Flanker Effects Through Bayesian Model Fitting, Jordan Deakin, Dietmar Heinke

MODVIS Workshop

No abstract provided.

Session 5: Equipment Finance Credit Risk Modeling - A Case Study In Creative Model Development & Nimble Data Engineering, Edward Krueger, Landon Thompson, Josh Moore

SDSU Data Science Symposium

This presentation will focus first on providing an overview of Channel and the Risk Analytics team that performed this case study. Given that context, we’ll then dive into our approach for building the modeling development data set, techniques and tools used to develop and implement the model into a production environment, and some of the challenges faced upon launch. Then, the presentation will pivot to the data engineering pipeline. During this portion, we will explore the application process and what happens to the data we collect. This will include how we extract & store the data along with how it …

Molecular Dynamics Simulations Of Vibrational Infrared And Raman Spectra Of H5o2+, Oluwaseun Omodemi, Ivonne Meares, Gabriella Garofalo, Martina Kaledin

Symposium of Student Scholars

We report infrared (IR) and Raman vibrational spectra of H₅O₂⁺ protonated water dimer using computational chemistry methods, the normal mode analysis (NMA), and molecular dynamics (MD) simulations. Various computational methods and basis sets were used. We also located the H₅O₂⁺ stationary points on the potential energy surface using the Gaussian 16 program. The H₅O₂⁺ Zundel complex serves as a benchmark system to study the proton transfer process. We also investigated IR and Raman intensities of other deuterated analogs, such as D₅O₂⁺, D_{4 …}

Probing Structure And Energetics Of Proton-Bound Complexes N2…Hco+ And N2h+…Oc Using Computational Chemistry Methods, Antonio Barrios, Dalton Boutwell, Onyi Okere, Monique Olocha, Oluwaseun Omodemi, Alexander Toledo, Antonio Barrios

Symposium of Student Scholars

N₂…HCO⁺ and N₂H⁺…OC are predicted to exist in interstellar clouds. These complexes involve HCO⁺ and N₂H⁺ fragments that are bound to N₂ and CO, respectively using hydrogen-bonded interaction. The reason these molecules are important is that the existence of nitrogen can be measured indirectly through ion-molecular complexes studied in this work. The measured vibrational spectra of molecules is an excellent way to characterize and detect molecules. We used B3LYP, MP2, and CCSD(T) computational methods to predict the structure and vibrational frequencies of N₂…HCO⁺ and N …

Theoretical Study On The Isomerization And Detection Of N2h+…Oc Complex In Interstellar Clouds, Dalton Boutwell, Martina Kaledin

Symposium of Student Scholars

In this study, we characterize N₂H⁺…OC linear complex using Driven Molecular Dynamics (DMD) and Vibrational Self-Consistent Field Theory (VSCF) methods due to its relevance in astrochemistry. A central challenge is the detection of the molecular complex in interstellar media (ISM). Computational chemistry approaches can predict vibrational spectra, hence facilitate prediction of its existence and stability in the ISM. N₂H⁺…OC involves the proton transfer process via hydrogen bonding interaction. Proton motion is highly anharmonic, therefore facing a significant challenge to characterize it accurately. Quantum mechanical variational methods are popular among many theoretical chemists …

Simulating 129-Xe Hyperpolarization, Jacob F. Abiad

Undergraduate Student Research Internships Conference

Hyperpolarized 129-Xe is an important resource in many fields of medical physics and MRI research. The physics of the efficient production of hyperpolarized 129-Xe is therefore equally worth investigation. The main process of hyperpolarizing 129-Xe is Spin Exchange Optical Pumping (SEOP) and is dependent on several physical factors that can be difficult to constantly change in a lab setting. Physical modelling of 129-Xe hyperpolarization allows for the more efficient testing of hyperpolarization physics in a wide array of experimental setups to better determine the optimal values for hyperpolarization. This research project attempted to create a working model for 129-Xe hyperpolarization …

Searching For New Relations Among The Eilenberg-Zilber Maps, Owen T. Abma

Undergraduate Student Research Internships Conference

The goal of this project was to write a computer program that would aid in the search for relations among the Eilenberg-Zilber maps, which relate to simplicial objects in algebraic topology. This presentation outlines the process of writing this program, the challenges faced along the way, and the final results of the project.

Numerical Simulation Of Adaptive Metabolic Response To Anti-Angiogenic Treatment In Renal Cell Carcinoma, Saranya Varakunan

Undergraduate Student Research Internships Conference

Renal cell carcinoma, a malignant kidney cancer, is often treated using anti-angiogenic drugs to prevent the growth of blood vessels within the tumour. Although tumours initially respond to this treatment, they eventually develop resistance. This resistance is hypothesized to be caused by a switch to a symbiotic metabolism that allows cells to survive even with a low blood supply.

This project seeks to computationally model the transport of oxygen, lactate, and glucose within a tumour in order to examine how cancer metabolism adapts to changes in blood vessels.

The Introduction Of Big Data In Cloud Computing, Austin Gruenberg

Student Academic Conference

One of the fastest-growing technologies that many people are unaware of is the world of cloud computing. Having started in 2006, it is a relatively new technological advancement in the computer industry. The major branch of cloud computing that I decided to focus on was big data. I decided to research this topic to better understand what its current uses are, to see what the future holds for Big Data and cloud computing and because it is a growing, significant piece of technology being used in our society today. Big data and cloud computing are very important industries and have …

Personalized Immunotherapy Treatment Strategies For A System Of Chronic Myelogenous Leukemia, Paul Valle

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Using Network Modeling To Understand The Relationship Between Sars-Cov-1 And Sars-Cov-2, Elizabeth Brooke Haywood, Nicole A. Bruce

Biology and Medicine Through Mathematics Conference

No abstract provided.

Modeling Gene Expression With Differential Equations, Madison Kuduk

Capstone Showcase

Gene expression is the process by which the information stored in DNA is convertedinto a functional gene product, such as protein. The two main functions that makeup the process of gene expression are transcription and translation. Transcriptionand translation are controlled by the number of mRNA and protein in the cell. Geneexpression can be represented as a system of first order differential equations for the rateof change of mRNA and proteins. These equations involve transcription, translation,degradation and feedback loops. In this paper, I investigate a system of first orderdifferential equations to model gene expression proposed by Hunt, Laplace, Miller andPham in …

An Extensible Geospatial Data Framework (Geoedf) For Fair Science, Carol Song, Rajesh Kalyanam, Lan Zhao

Purdue GIS Day

The growing urgency in dealing with the 21st century’s grand challenges associated with increasing population, food and water security, frequently occurring natural disasters, and changing climate demands innovative, collaborative, and multidisciplinary solutions for sustainability and resilience. However, scientific data, especially geospatial data, presents significant barriers to the effective access, use and sharing of data as they come in large volumes, from different sources, and with widely varying formats, resolutions, or annotation schemas that can differ among disciplines or even research groups. This presentation describes a recently funded NSF CSSI project to develop an open source, extensible geospatial data framework (GeoEDF), …

Integrating Mathematics And Biology In The Classroom: A Compendium Of Case Studies And Labs, Becky Sanft, Anne Walter

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Quantifying Pollen Traits To Build A Mathematical Model Of Pollen Competition - A Mathematician's Perspective, Montana Ferita, Julie Fucarino, Alex Capaldi, Charlotte Beckford

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Period Drift In A Neutrally Stable Stochastic Oscillator, Kevin Sanft

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.