Discrete Math For Computer Science - Chapter 10: Definition Of Functions: Properties Of Functions,
2025
University of the Pacific
Discrete Math For Computer Science - Chapter 10: Definition Of Functions: Properties Of Functions, Houman Kamran Habibkhani
Pacific Open Videos
See this OER textbook full record by clicking here.
Discrete Math For Computer Science - Chapter 6: Proofs By Contradiction: Proofs By Cases,
2025
University of the Pacific
Discrete Math For Computer Science - Chapter 6: Proofs By Contradiction: Proofs By Cases, Houman Kamran Habibkhani
Pacific Open Videos
See this OER textbook full record by clicking here.
Discrete Math For Computer Science - Chapter 5: Direct Proofs: Proofs By Contrapositive,
2025
University of the Pacific
Discrete Math For Computer Science - Chapter 5: Direct Proofs: Proofs By Contrapositive, Houman Kamran Habibkhani
Pacific Open Videos
See this OER textbook full record by clicking here.
Discrete Math For Computer Science - Chapter 7: Sets And Subsets: Set Of Sets,
2025
University of the Pacific
Discrete Math For Computer Science - Chapter 7: Sets And Subsets: Set Of Sets, Houman Kamran Habibkhani
Pacific Open Videos
See this OER textbook full record by clicking here.
Book Vi Of The Mathematical Collection Of Pappus Of Alexandria, Translated By John B. Little,
2025
College of the Holy Cross
Book Vi Of The Mathematical Collection Of Pappus Of Alexandria, Translated By John B. Little, John B. Little, Pappus Of Alexandria
Holy Cross Bookshelf
Book VI of the Mathematical Collection is a collection of comments or notes about various points treated in parts of a collection of other texts sometimes known as the “Little Astronomy.” Pappus uses these works as sources and frequently quotes from them in this book. In the teaching of mathematical astronomy in late antiquity, and this would include the time of Pappus, the “Little Astronomy” is often understood to have been a follow-up to Euclid’s Elements and a preliminary to the study of the Almagest of Claudius Ptolemy (ca. 100–165 CE). The “Little Astronomy” included works by a group of …
Exploring The Potential Of Strongly Coupled Lagrangian Data Assimilation In An Ocean–Atmosphere System,
2025
University of Maryland at College Park
Exploring The Potential Of Strongly Coupled Lagrangian Data Assimilation In An Ocean–Atmosphere System, Luyu Sun, Amit Apte, Laura Slivinski, Elaine T. Spiller
Mathematical and Statistical Science Faculty Research and Publications
Precise measurements of ocean surface flow velocities are essential for refining forecasts in a coupled ocean–atmosphere system. While oceanic data are generally sparse, surface drifters present an opportunity by providing detailed and frequently observed sea surface currents, which are a critical component in the dynamics at air–sea interface. Such observations could potentially address the usual data gaps in a coupled ocean–atmosphere assimilation system. In this study, we investigate the implications of assimilating drifter data within a coupled system with intermediate complexity based on a quasigeostrophic model—Modular Arbitrary-Order Ocean–Atmosphere Model (MAOOAM)—using observing system simulation experiments (OSSEs). Two main strategies for assimilating …
Generation Of Patient Specific Cardiac Chamber Models Using Generative Neural Networks Under A Bayesian Framework For Electroanatomical Mapping,
2025
Marquette University
Generation Of Patient Specific Cardiac Chamber Models Using Generative Neural Networks Under A Bayesian Framework For Electroanatomical Mapping, Sunil Mathew, Jasbir Sra, Daniel B. Rowe
Mathematical and Statistical Science Faculty Research and Publications
Electroanatomical mapping is a technique used in cardiology to create a detailed 3D map of the electrical activity in the heart. It is useful for diagnosis, treatment planning and real time guidance in cardiac ablation procedures to treat arrhythmias like atrial fibrillation. A probabilistic machine learning model trained on a library of CT/MRI scans of the heart can be used during electroanatomical mapping to generate a patient-specific 3D model of the chamber being mapped. The use of probabilistic machine learning models under a Bayesian framework provides a way to quantify uncertainty in results and provide a natural framework of interpretability …
On Explicit Solutions For Coupled Reaction-Diffusion And Burgers-Type Equations With Variable Coefficients Through A Riccati System,
2025
The University of Texas Rio Grande Valley
On Explicit Solutions For Coupled Reaction-Diffusion And Burgers-Type Equations With Variable Coefficients Through A Riccati System, Jose M. Escorcia, Erwin Suazo
School of Mathematical & Statistical Sciences Faculty Publications
This work is concerned with the study of explicit solutions for generalized coupled reaction-diffusion and Burgers-type systems with variable coefficients. Including nonlinear models with variable coefficients such as the diffusive Lotka-Volterra model, the Gray-Scott model, the Burgers equations. The equations' integrability (via the explicit formulation of the solutions) is accomplished by using similarity transformations and requiring that the coefficients fulfill a Riccati system. We present traveling wave-type solutions as well as solutions with more complex dynamics and relevant features such as bending. A Mathematica file has been prepared as supplementary material, verifying the Riccati systems used in the construction of …
On Realizability Of Some Graphs,
2025
The University of Memphis
On Realizability Of Some Graphs, Runze Wang
Communications on Number Theory and Combinatorial Theory
A graph H is said to be realizable by a graph G if for any vertex v in G, the induced subgraph of G on the neighborhood of v is isomorphic to H. In this paper, we show that a complete multipartite graph is realizable if and only if each of its parts has the same size; characterize the graphs by which a complete multipartite graph with each part having the same size is realizable; show that all cluster graphs are realizable; prove that a wheel is realizable if and only if it has four vertices; prove that …
Ornstein-Uhlenbeck Type Operators Induced By Some Geometric Structures On Complex Domains,
2025
Laboratory of Stochastic Analysis and Applications, Faculty of Sciences of Tunis, University of Tunis El-Manar, 1060 Tunis, Tunisia
Ornstein-Uhlenbeck Type Operators Induced By Some Geometric Structures On Complex Domains, Souheyl Jendoubu
Journal of Stochastic Analysis
No abstract provided.
Hilbert’S 10th Problem Via Mordell Curves,
2025
The University of Texas Rio Grande Valley
Hilbert’S 10th Problem Via Mordell Curves, Somnath Jha, Debanjana Kundu, Dipramit Majumdar
School of Mathematical & Statistical Sciences Faculty Publications
We show that for 5 / 6 -th of all primes p, Hilbert’s 10th problem is unsolvable for the ring of integers of Q ( ζ 3 , 3 √ p ) . We also show that there is an infinite set S of square-free integers such that Hilbert’s 10th problem is unsolvable over the ring of integers of Q ( ζ 3 , √ D , 3 √ p ) for every D ∈ S and for every prime p ≡ 2 , 5 ( mod 9 ) . We use the CM elliptic curves y 2 = x …
Addressing Class Imbalance Problem In Health Data Classification: Practical Application From An Oversampling Viewpoint,
2025
The University of Texas Rio Grande Valley
Addressing Class Imbalance Problem In Health Data Classification: Practical Application From An Oversampling Viewpoint, Edmund F. Agyemang, Joseph A. Mensah, Eric Nyarko, Dennis Arku, Benedict Mbeah-Baiden, Enock Opoku, Ezekiel Nii Noye Nortey
School of Mathematical & Statistical Sciences Faculty Publications
While analyzing health data is important for improving health outcomes, class imbalance in datasets poses major challenges to machine learning classification models. This work, therefore, considers the class imbalance problem in stroke prediction using models such as K-nearest neighbors, support vector machine, logistic regression, random forest, and decision tree. This work balances the stroke dataset, thereby enhancing model performance, through various oversampling strategies: random oversampling (RO), ADASYN, SMOTE, and SMOTE–Tomek. Compared to the results of the imbalanced dataset, all applied oversampling techniques enhanced the correct classification of stroke events by the ML model. Among these, RO–SVM with RBF kernel was …
Analytical Method For Solving Systems Of Fractional Initial Value Problems Using The Modified Atangana-Baleanu Derivative,
2025
United Arab Emirates University
Analytical Method For Solving Systems Of Fractional Initial Value Problems Using The Modified Atangana-Baleanu Derivative, Lana Mohammad Aref
Thesis/ Dissertation Defenses
This thesis presents an analytical method to solve systems of fractional initial value problems using the Modified Atangana-Baleanu Fractional Derivative. The proposed approach leverages an improved operational matrix method, incorporating an iterative, direct computation technique to simplify the solution process and reduce computational costs. Foundational concepts in fractional calculus and block pulse functions are introduced, followed by the derivation of operational matrices tailored for fractional systems. Theoretical analysis establishes the existence and uniqueness of solutions, along with uniform convergence and error estimates. Practical examples and applications are presented that demonstrate the efficiency, accuracy, and versatility of the method in solving …
Quantum Extensions Of The Exotic Laplacians And Associated Quantum Heat Semigroups,
2025
Universitá di Roma Tor Vergata, Via di Torvergata, Roma, Italy
Quantum Extensions Of The Exotic Laplacians And Associated Quantum Heat Semigroups, Luigi Accardi, Un Cig Ji, Kimiaki Saito
Journal of Stochastic Analysis
No abstract provided.
Sobolev Regularity For The Bergman Projection On Relatively Compact Domains In Hermitian Manifolds,
2025
University of Arkansas, Fayetteville
Sobolev Regularity For The Bergman Projection On Relatively Compact Domains In Hermitian Manifolds, Philip Harrington
Mathematical Sciences Faculty Publications and Presentations
Generalizing a result of Berndtsson and Charpentier, we provide sufficient conditions for L2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L< ^>2$$\end{document} Sobolev regularity of the Bergman projection acting on L2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L< ^>2$$\end{document} sections of a holomorphic line bundle restricted to a relatively compact domain with Lipschitz boundary in a Hermitian manifold. We provide examples to show that our methods work for domains in Hopf manifolds endowed with a suitable Hermitian metric.
Preface,
2025
CIMA, Faculty of Exact Sciences and Engineering, University of Madeira, Campus da Penteada, 9020-105 Funchal, Madeira, Portugal
Preface, José Luis Da Silva, Un Cig Ji, Aurel Stan
Journal of Stochastic Analysis
No abstract provided.
Modeling Covid-19 Spread And Effects Of Non-Pharmaceutical Interventions On A College Campus,
2025
University of Washington - Seattle Campus
Modeling Covid-19 Spread And Effects Of Non-Pharmaceutical Interventions On A College Campus, Jakob Kotas, Priscilla Perey Ratonel
CODEE Journal
We consider an extension to the classical SIR compartmental model from mathematical epidemiology as applied to the spread of COVID-19 on a college campus. While the classical SIR model does not allow for recovered individuals to lose immunity, we alter the equations to allow for such (due to the rise of new variants), leading to a SIRS-type model. We study the system of ODEs analytically and through numerical simulation. Finally we discuss a quantitative approach for how college administrators can decide when to implement stricter non-pharmaceutical interventions (social distancing, mask mandates, quarantine, etc.) to eradicate the infection from the campus …
Semilinear Klein-Gordon Equation In Space-Time Of Black Hole Which Is Gaining Mass In The Universe With Accelerating Expansion,
2025
The University of Texas Rio Grande Valley
Semilinear Klein-Gordon Equation In Space-Time Of Black Hole Which Is Gaining Mass In The Universe With Accelerating Expansion, Karen Yagdjian, Anahit Galstyan
School of Mathematical & Statistical Sciences Faculty Publications
In this paper, we consider the propagation of waves in the space-time of a single black hole with a static Schwarzschild radius in the expanding universe, namely, the solutions of the linear and semilinear Klein-Gordon equations.
Modelling The Behavior Of Human Crowds As Coupled Active-Passive Dynamics Of Interacting Particle Systems,
2025
The University of Texas Rio Grande Valley
Modelling The Behavior Of Human Crowds As Coupled Active-Passive Dynamics Of Interacting Particle Systems, Thoa Thieu, Roderick Melnik
School of Mathematical & Statistical Sciences Faculty Publications
The modelling of human crowd behaviors offers many challenging questions to science in general. Specifically, the social human behavior consists of many physiological and psychological processes which are still largely unknown. To model reliably such human crowd systems with complex social interactions, stochastic tools play an important role for the setting of mathematical formulations of the problems. In this work, using the description based on an exclusion principle, we study a statistical-mechanics-based lattice gas model for active-passive population dynamics with an application to human crowd behaviors. We provide representative numerical examples for the evacuation dynamics of human crowds, where the …
Volatility Modelling In Garch Frameworks: A Comparative Analysis Of Non-Gaussian Error Distributions With Skewed Parameters.,
2025
Department of Statistics, Faculty of Science, Olabisi Onabanjo University, Ago-Iwoye, Ogun State, Nigeria.
Volatility Modelling In Garch Frameworks: A Comparative Analysis Of Non-Gaussian Error Distributions With Skewed Parameters., Olatunbosun Adewale Akanbi, Timothy Olabisi Olatayo, Abass Ishola Taiwo
Al-Bahir
Forecasting volatility in financial time series remains challenging due to their asymmetric nature and excess kurtosis. This study evaluates and compares the performance of four variant of GARCH models incorporating skewed non-Gaussian error innovation distribution. The performances of these GARCH family of models under the skewed error innovation distributions were evaluated for three different unique data sets to have a more robust assessment of the performance of these skewed error innovation distributions. This study leverage on daily closing prices of Bitcoin, Naira to Dollar Exchange rates and daily Nigeria All Share Index between January 1, 2015 and January 26, 2024. …
