Mathematics Commons^™

On Analysis Of Effectiveness Controlling Covid-19 With Quarantine And Vaccination Compartments In Indonesia, Prihantini Prihantini

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Model-Free Identification Of Relevant Variables From Response Data, Alan Veliz-Cuba, David Murrugarra

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

An Approach To The Gaussian Rbf Kernels Via Fock Spaces, Daniel Alpay, Fabrizio Colombo, Kamal Diki, Irene Sabadini

Mathematics, Physics, and Computer Science Faculty Articles and Research

We use methods from the Fock space and Segal–Bargmann theories to prove several results on the Gaussian RBF kernel in complex analysis. The latter is one of the most used kernels in modern machine learning kernel methods and in support vector machine classification algorithms. Complex analysis techniques allow us to consider several notions linked to the radial basis function (RBF) kernels, such as the feature space and the feature map, using the so-called Segal–Bargmann transform. We also show how the RBF kernels can be related to some of the most used operators in quantum mechanics and time frequency analysis; specifically, …

Functional Data Analysis Of Covid-19, Nichole L. Fluke

Mathematics & Statistics ETDs

This thesis deals with Functional Data Analysis (FDA) on COVID data. The Data involves counts for new COVID cases, hospitalized COVID patients, and new COVID deaths. The data used is for all the states and regions in the United States. The data starts in March 1^st, 2020 and goes through March 31^st, 2021. The FDA smooths the data and looks to see if there are similarities or differences between the states and regions in the data. The data also shows which states and regions stand out from the others and which ones are similar. Also shown …

A Comparison Of Cryptographic Methods, Christopher Gilmore

Senior Honors Theses

While elliptic curve cryptography and quantum cryptography are significantly different branches of cryptography, they provide a suitable reference point for comparison of the value of developing methods used in the present and investing in methods to be used in the future. Elliptic curve cryptography is quite common today, as it is generally secure and efficient. However, as the field of cryptography advances, the value of quantum cryptography’s inherent security from its basic properties should be considered, as a fully realized quantum cryptosystem has the potential to be quite powerful. Ultimately, it is of critical importance to determine the value of …

Minimizers Of Nonlocal Polyconvex Energies In Nonlocal Hyperelasticity, José C. Bellido, Javier Cueto, Carlos Mora-Corral

Department of Mathematics: Faculty Publications

We develop a theory of existence of minimizers of energy functionals in vectorial problems based on a nonlocal gradient under Dirichlet boundary conditions. The model shares many features with the peridynamics model and is also applicable to nonlocal solid mechanics, especially nonlinear elasticity. This nonlocal gradient was introduced in an earlier work, inspired by Riesz’ fractional gradient, but suitable for bounded domains. The main assumption on the integrand of the energy is polyconvexity. Thus, we adapt the corresponding results of the classical case to this nonlocal context, notably, Piola’s identity, the integration by parts of the determinant and the weak …

Music Genre Classification By Convolutional Neural Networks, Usame Suud

Mathematics & Statistics ETDs

In today’s world, deep learning models are widely used in a variety of fields. Audio

applications include speech recognition, audio classification, and music information

retrieval. In this paper, we will focus on the classification of music genres using an

artificial neural network. The development of audio machine learning techniques has

created an independence from traditional, more time-consuming signal processing

techniques. Starting with raw audio data, we will gain an understanding of what

audio is and its digital representation. Then, the focus will be on obtaining frequency

information from audio signals through the use of spectrograms. Transforming the

spectrograms into the …

Alternative Siar Models For Infectious Diseases And Applications In The Study Of Non-Compliance, Marcelo Bongarti, Luke Diego Galvan, Lawford Hatcher, Michael R. Lindstrom, Christian Parkinson, Chuntian Wang, Andrea L. Bertozzi

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we use modified versions of the SIAR model for epidemics to propose two ways of understanding and quantifying the effect of non-compliance to non-pharmaceutical intervention measures on the spread of an infectious disease. The SIAR model distinguishes between symptomatic infected (I) and asymptomatic infected (A) populations. One modification, which is simpler, assumes a known proportion of the population does not comply with government mandates such as quarantining and social-distancing. In a more sophisticated approach, the modified model treats non-compliant behavior as a social contagion. We theoretically explore different scenarios such as the occurrence …

One Iteration For The Second Boundary Condition For The Nonlinear One Dimensional Monge-Ampere Equation, Gerard Awanou

Mathematics Colloquium Series

The design of lenses and mirrors, in free form i.e. with no a priori symmetry assumption, has a long list of applications including materials processing, energy concentrators, medicine, antennas, computing lithography, laser weapons, optical data storage, imaging etc. The design process can be reduced to solving a generalized Monge-Ampere equation where the unknown is a function with a convexity property and subject to a constraint that a generalized gradient maps a given domain onto a prescribed one. The latter type of constraint is known as second boundary condition. The model one dimensional Monge-Ampere equation is nonlinear in the first order …

Fractal Like Snowflakes Generated By Non-Contractive Function Systems, William H. Kelly Iii

LSU Master's Theses

At the heart of this thesis is the examination of a non-contractive iterative function system T on the Hausdorff metric space of all compact subset of ℝ . Despite the absence of an 2 attracting fixed point, an examination reveals the appearance of fractal-like shapes (snowflakes) when applying the Barnsley’ random walk method to study the iterative sequence ��ⁿ(0) (�� ∈ ℕ) for �� = ��¹ ∪ ��² ∪ ��³, where ��₁(��) = ����, ��₂(��) = ���� + ��, and ��₃(��) = ���� - ��, and �� = …

Studying Extended Sets From Young Tableaux, Eric Nofziger

Rose-Hulman Undergraduate Mathematics Journal

Young tableaux are combinatorial objects related to the partitions of an integer and have various applications in representation theory. They are particularly useful in the study of the fibers arising from the Springer resolution. In recent work of Graham-Precup-Russell, an association has been made between a given row-strict tableau and three disjoint subsets of {1,2,...,n}. These subsets are then used in the study of extended Springer fibers, so we call them extended sets. In this project, we use combinatorial techniques to classify which of these extended sets correlate to a valid row-strict or standard tableau and give bounds on the …

On The Smallest Non-Trivial Action Of Saut(Fn) For Small N, Reemon Spector

Rose-Hulman Undergraduate Mathematics Journal

In this paper we investigate actions of SAut(F_n), the unique index 2 subgroup of Aut(F_n), on small sets, improving upon results by Baumeister--Kielak--Pierro for several small values of n. Using a computational approach for n ⩾ 5, we show that every action of SAut(F_n) on a set containing fewer than 20 elements is trivial.

Generalized Inverses Of Elements Of Rings And Matrices Over Rings, K. Manjunatha Prasad

Interdisciplinary Collection

It is well known that a square matrix with all its columns linearly independent has a unique inverse G satisfying AG=GA=I. However, if A is not square or if columns of A are not linearly independent, then such an inverse does not exist. Moore and Penrose independently generalized the notion of inverses to singular matrices. This led to the theory of generalized inverses. In the course of time different generalized inverses like group inverse, Drazin inverse, Core inverse etc., were introduced. The present author introduced Core-EP inverse in 2013. The author has also worked on the theory of generalized inverse …

Second-Order, Fully Decoupled, Linearized, And Unconditionally Stable Scalar Auxiliary Variable Schemes For Cahn–Hilliard–Darcy System, Yali Gao, Xiaoming He, Yufeng Nie

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we establish the fully decoupled numerical methods by utilizing scalar auxiliary variable approach for solving Cahn–Hilliard–Darcy system. We exploit the operator splitting technique to decouple the coupled system and Galerkin finite element method in space to construct the fully discrete formulation. The developed numerical methods have the features of second order accuracy, totally decoupling, linearization, and unconditional energy stability. The unconditionally stability of the two proposed decoupled numerical schemes are rigorously proved. Abundant numerical results are reported to verify the accuracy and effectiveness of proposed numerical methods.

How To Get The Most Accurate Measurement-Based Estimates, Salvador Robles, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we want to estimate a quantity y that is difficult -- or even impossible -- to measure directly. In such cases, often, there are easier-to-measure quantities x₁, ..., x_n that are related to y by a known dependence y = f(x₁,...,x_n). So, to estimate y, we can measure these quantities x_i and use the measurement results to estimate y. The two natural questions are: (1) within limited resources, what is the best accuracy with which we can estimate y, and (2) to reach a given accuracy, what amount …

Anomaly Detection In Crowdsourcing: Why Midpoints In Interval-Valued Approach, Alejandra De La Pena, Damian L. Gallegos Espinoza, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations -- e.g., when preparing examples for a machine learning algorithm -- we need to label a large number of images or speech recordings. One way to do it is to pay people around the world to perform this labeling; this is known as crowdsourcing. In many cases, crowd-workers generate not only answers, but also their degrees of confidence that the answer is correct. Some crowd-workers cheat: they produce almost random answers without bothering to spend time analyzing the corresponding image. Algorithms have been developed to detect such cheaters. The problem is that many crowd-workers cannot describe …

Dielectric Barrier Discharge (Dbd) Thrusters -- Aerospace Engines Of The Future: Invariance-Based Analysis, Alexis Lupo, Vladik Kreinovich

Departmental Technical Reports (CS)

One of the most prospective aerospace engines is a Dielectric Barrier Discharge (DBD) thruster -- an effective electric engine without moving parts. Originally designed by NASA for flights over other planets, it has been shown to be very promising for Earth-based flights as well. The efficiency of this engine depends on the proper selection of the corresponding electric field. To make this selection, we need to know, in particular, how its thrust depends on the atmospheric pressure. At present, for this dependence, we only know an approximate semi-empirical formula. In this paper, we use natural invariance requirements to come up …

Hunting Habits Of Predatory Birds: Theoretical Explanation Of An Empirical Formula, Adilene Alaniz, Jiovani Hernandez, Andres D. Munoz, Vladik Kreinovich

Departmental Technical Reports (CS)

Predatory birds play an important role in an ecosystem. It is therefore important to study their hunting behavior, in particular, the distribution of their waiting time. A recent empirical study showed that the waiting time is distributed according to the power law. In this paper, we use natural invariance ideas to come up with a theoretical explanation for this empirical dependence.

Aquatic Ecotoxicology: Theoretical Explanation Of Empirical Formulas, Demetrius R. Hernandez, George M. Molina Holguin, Francisco Parra, Vivian Sanchez, Vladik Kreinovich

Departmental Technical Reports (CS)

To analyze the effect of pollution on marine life, it is important to know how exactly the concentration of toxic substances decreases with time. There are several semi-empirical formulas that describe this decrease. In this paper, we provide a theoretical explanation for these empirical formulas.

Math 57: Applied Differential Equations I, John Mayberry

Pacific Open Texts

This book is designed for the fourth semester, “capstone” course in a calculus sequence with an emphasis on modeling with linear differential equations. Students will learn to translate verbal descriptions of physical problems into differential equation models, solve and visualize solutions to differential equations using MATLAB, calculate and investigate the behavior of analytic solutions to linear differential equations, discuss how solutions to differential equations depend on parameters, and interpret solutions to differential equations in the context of applications.

Conservative Unconditionally Stable Decoupled Numerical Schemes For The Cahn–Hilliard–Navier–Stokes–Darcy–Boussinesq System, Wenbin Chen, Daozhi Han, Xiaoming Wang, Yichao Zhang

Mathematics and Statistics Faculty Research & Creative Works

We propose two mass and heat energy conservative, unconditionally stable, decoupled numerical algorithms for solving the Cahn–Hilliard–Navier–Stokes–Darcy–Boussinesq system that models thermal convection of two-phase flows in superposed free flow and porous media. The schemes totally decouple the computation of the Cahn–Hilliard equation, the Darcy equations, the heat equation, the Navier–Stokes equations at each time step, and thus significantly reducing the computational cost. We rigorously show that the schemes are conservative and energy-law preserving. Numerical results are presented to demonstrate the accuracy and stability of the algorithms.

War And Money In Ngram Viewer, Robert H. Mcfadden, William Zywiak, Ronald P. Bobroff, Gao Niu

Finance Department Faculty Journal Articles

The second and fourth authors have been inviting Intro to Applied Analytics and Statistics 1 students to use the Ngram Database to explore historical topics of their choosing. This is the first article derived from this exercise. The first author examined the historical relationship between war and money from 1775 to 2005 in the American English corpus. This is followed by an examination of the 3-gram “cost of war” in the American English and British English corpora. Specific to the analyses presented here several military and economic events are discussed. More specifically, both economies and wars are somewhat unpredictable, with …

Resource Allocation For Multi-Tasking Optimization: Explanation Of An Empirical Formula, Alan Gamez, Antonio Aguirre, Christian Cordova, Alberto Miranda, Vladik Kreinovich

Departmental Technical Reports (CS)

For multi-tasking optimization problems, it has been empirically shown that the most effective resource allocation is attained when we assume that the gain of each task logarithmically depends on the computation time allocated to this task. In this paper, we provide a theoretical explanation for this empirical fact.

Why Color Optical Computing, Victor L. Timchenko, Yury P. Kondratenko, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we show that requirements that computations be fast and noise-resistant naturally lead to what we call color-based optical computing.

How To Reach A Joint Decision With The Smallest Need For Compromise, Sofia Holguin, Olga Kosheleva

Departmental Technical Reports (CS)

Usually, people's interests do not match perfectly. So when several people need to make a joint decision, they need to compromise. The more people one has to coordinate the decision with, the fewer chances that each person's preferences will be properly taken into account. Therefore, when a large group of people need to make a decision, it is desirable to make sure that this decision can be reached by dividing all the people into small-size groups so that this decision can reach a compromise between the members of each group. In this paper, we use a recent mathematical result to …

Word Representation: Theoretical Explanation Of An Empirical Fact, Leonel Escapita, Diana Licon, Madison Anderson, Diego Pedraza, Vladik Kreinovich

Departmental Technical Reports (CS)

There is a reasonably accurate empirical formula that predicts, for two words i and j, the number Xij of times when the word i will appear in the vicinity of the word j. The parameters of this formula are determined by using the weighted least square approach. Empirically, the predictions are the most accurate if we use the weights proportional to a power of Xij. In this paper, we provide a theoretical explanation for this empirical fact.

Need For Optimal Distributed Measurement Of Cumulative Quantities Explains The Ubiquity Of Absolute And Relative Error Components, Hector A. Reyes, Aaron D. Brown, Jeffrey Escamilla, Ethan D. Kish, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we need to measure the value of a cumulative quantity, i.e., a quantity that is obtained by adding measurement results corresponding to different spatial locations. How can we select the measuring instruments so that the resulting cumulative quantity can be determined with known accuracy -- and, to avoid unnecessary expenses, not more accurately than needed? It turns out that the only case where such an optimal arrangement is possible is when the required accuracy means selecting the upper bounds on absolute and relative error components. This results provides a possible explanation for the ubiquity of such …

Matrix Tree Theorem For The Net Laplacian Matrix Of A Signed Graph, Sudipta Mallik

Mathematics Faculty Research

For a simple signed graph G with the adjacency matrix A and net degree matrix D±, the net Laplacian matrix is L± = D±−A. We introduce a new oriented incidence matrix N± which can keep track of the sign as well as the orientation of each edge of G. Also L± = N±(N±)T. Using this decomposition, we find the number of both positive and negative spanning trees of G in terms of the principal minors of L± generalizing the Matrix Tree Theorem for an unsigned graph. …

Lstm-Sdm: An Integrated Framework Of Lstm Implementation For Sequential Data Modeling[Formula Presented], Hum Nath Bhandari, Binod Rimal, Nawa Raj Pokhrel, Ramchandra Rimal, Keshab R. Dahal

Arts & Sciences Faculty Publications

LSTM-SDM is a python-based integrated computational framework built on the top of Tensorflow/Keras and written in the Jupyter notebook. It provides several object-oriented functionalities for implementing single layer and multilayer LSTM models for sequential data modeling and time series forecasting. Multiple subroutines are blended to create a conducive user-friendly environment that facilitates data exploration and visualization, normalization and input preparation, hyperparameter tuning, performance evaluations, visualization of results, and statistical analysis. We utilized the LSTM-SDM framework in predicting the stock market index and observed impressive results. The framework can be generalized to solve several other real-world time series problems.

Multi-Scale Hybridized Topic Modeling: A Pipeline For Analyzing Unstructured Text Datasets Via Topic Modeling, Keyi Cheng, Stefan Inzer, Adrian Leung, Xiaoxian Shen, Michael Perlmutter, Michael Lindstrom, Joyce Chew, Todd Presner, Deanna Needell

School of Mathematical & Statistical Sciences Faculty Publications

We propose a multi-scale hybridized topic modeling method to find hidden topics from transcribed interviews more accurately and efficiently than traditional topic modeling methods. Our multi-scale hybridized topic modeling method (MSHTM) approaches data at different scales and performs topic modeling in a hierarchical way utilizing first a classical method, Nonnegative Matrix Factorization, and then a transformer-based method, BERTopic. It harnesses the strengths of both NMF and BERTopic. Our method can help researchers and the public better extract and interpret the interview information. Additionally, it provides insights for new indexing systems based on the topic level. We then deploy our method …