Pascal's Triangle, Pascal's Pyramid, And The Trinomial Triangle, 2019 California State University, San Bernardino
Pascal's Triangle, Pascal's Pyramid, And The Trinomial Triangle, Antonio Saucedo Jr.
Electronic Theses, Projects, and Dissertations
Many properties have been found hidden in Pascal's triangle. In this paper, we will present several known properties in Pascal's triangle as well as the properties that lift to different extensions of the triangle, namely Pascal's pyramid and the trinomial triangle. We will tailor our interest towards Fermat numbers and the hockey stick property. We will also show the importance of the hockey stick properties by using them to prove a property in the trinomial triangle.
The Martingale Approach To Financial Mathematics, 2019 California Polytechnic State University, San Luis Obispo
The Martingale Approach To Financial Mathematics, Jordan M. Rowley
Master's Theses and Project Reports
In this thesis, we will develop the fundamental properties of financial mathematics, with a focus on establishing meaningful connections between martingale theory, stochastic calculus, and measure-theoretic probability. We first consider a simple binomial model in discrete time, and assume the impossibility of earning a riskless profit, known as arbitrage. Under this no-arbitrage assumption alone, we stumble upon a strange new probability measure Q, according to which every risky asset is expected to grow as though it were a bond. As it turns out, this measure Q also gives the arbitrage-free pricing formula for every asset on our market. In considering ...
Pairwise Completely Positive Matrices And Conjugate Local Diagonal Unitary Invariant Quantum States, 2019 Mount Allison University
Pairwise Completely Positive Matrices And Conjugate Local Diagonal Unitary Invariant Quantum States, Nathaniel Johnston, Olivia Maclean
Electronic Journal of Linear Algebra
A generalization of the set of completely positive matrices called pairwise completely positive (PCP) matrices is introduced. These are pairs of matrices that share a joint decomposition so that one of them is necessarily positive semidefinite while the other one is necessarily entrywise non-negative. Basic properties of these matrix pairs are explored and several testable necessary and sufficient conditions are developed to help determine whether or not a pair is PCP. A connection with quantum entanglement is established by showing that determining whether or not a pair of matrices is pairwise completely positive is equivalent to determining whether or not ...
Analyzing The Structural Properties Of Pulmonary Arterial Networks, 2019 North Carolina State University at Raleigh
Analyzing The Structural Properties Of Pulmonary Arterial Networks, Megan J. Chambers
Biology and Medicine Through Mathematics Conference
No abstract provided.
Optimal Spraying Strategies For Controlling Re-Infestation By Chagas Disease Vectors, 2019 Virginia Commonwealth University
Optimal Spraying Strategies For Controlling Re-Infestation By Chagas Disease Vectors, Bismark Oduro, Winfried Just, Mario Grijalva
Biology and Medicine Through Mathematics Conference
No abstract provided.
Stokes, Gauss, And Bayes Walk Into A Bar..., 2019 University of Colorado, Boulder
Stokes, Gauss, And Bayes Walk Into A Bar..., Eric P. Kightley
Applied Mathematics Graduate Theses & Dissertations
This thesis consists of three distinct projects. The first is a study of microbial aggregate fragmentation, in which we develop a dynamical model of aggregate deformation and breakage and use it to obtain a post-fragmentation density function. The second and third projects deal with dimensionality reduction in machine learning problems. In the second project, we derive a one-pass sparsified Gaussian mixture model to perform clustering analysis on high-dimensional streaming data. The model estimates parameters in dense space while storing and performing computations in a compressed space. In the final project, we build an expert system classifier with a Bayesian network ...
Characterizing The Tails Of Degree Distributions In Real-World Networks, 2019 University of Colorado, Boulder
Characterizing The Tails Of Degree Distributions In Real-World Networks, Anna Broido
Applied Mathematics Graduate Theses & Dissertations
This is a thesis about how to characterize the statistical structure of the tails of degree distributions of real-world networks. The primary contribution is a statistical test of the prevalence of scale-free structure in real-world networks. A central claim in modern network science is that real-world networks are typically "scale free," meaning that the fraction of nodes with degree k follows a power law, decaying like k-a, often with 2 < a< 3. However, empirical evidence for this belief derives from a relatively small number of real-world networks. In the first section, we test the universality of scale-free structure by applying state-of-the-art statistical tools to a large corpus of nearly 1000 network data sets drawn from social, biological, technological, and informational sources. We fit the power-law model to each degree distribution, test its statistical plausibility, and compare it via a likelihood ratio test to alternative, non-scale-free models, e.g., the log-normal. Across domains, we find that scale-free networks are rare, with only 4% exhibiting the strongest-possible evidence of scale-free structure and 52% exhibiting the weakest-possible evidence. Furthermore, evidence of scale-free structure is not uniformly distributed across sources: social networks are at best weakly scale free, while a handful of technological and biological networks can be called strongly scale free. These results undermine the universality of scale-free networks and reveal that real-world networks exhibit a rich structural diversity that will likely require new ideas and mechanisms to explain. A core methodological component of addressing the ubiquity of scale-free structure in real-world networks is an ability to fit a power law to the degree distribution. In the second section, we numerically evaluate and compare, using both synthetic data with known structure and real-world data with unknown structure, two statistically principled methods for estimating the tail parameters for power-law distributions, showing that in practice, a method based on extreme value theory and a sophisticated bootstrap and the more commonly used method based an empirical minimization approach exhibit similar accuracy.
Proof Of A Conjecture Of Graham And Lovasz Concerning Unimodality Of Coefficients Of The Distance Characteristic Polynomial Of A Tree, Ghodratollah Aalipour, Aida Abiad, Zhanar Berikkyzy, Leslie Hogben, Franklin H.J. Kenter, Jephian C.-H. Lin, Michael Tait
The conjecture of Graham and Lov ́asz that the (normalized) coefficients of the distance characteristic polynomial of a tree are unimodal is proved; it is also shown that the (normalized) coefficients are log-concave. Upper and lower bounds on the location of the peak are established.
Combinatorial Optimization: Introductory Problems And Methods, 2019 University of Connecticut
Combinatorial Optimization: Introductory Problems And Methods, Erin Brownell
Honors Scholar Theses
This paper will cover some topics of combinatorial optimization, the study of ﬁnding the best possible arrangement of a set of discrete objects. These topics include the shortest path problem and network ﬂows, which can be extended to solve more complex problems. We will also brieﬂy cover some basics of graph theory and solving linear programming problems to give context to the reader.
Math Modeling Contest: Optimized Plan To Leave The Louvre, 2019 Carroll College
Math Modeling Contest: Optimized Plan To Leave The Louvre, Shirley Davidson, Terry Cox, Sabrina Crooks
Carroll College Student Undergraduate Research Festival
The distances between every section of the Louvre, exiting speeds dependent upon an individual's surroundings, time of day, total people, distribution of people, and stair dimensions are all factors utilized to establish a model for evacuating the Louvre. Our goal was to create an emergency protocol procedure that minimized the amount of time required to safely remove all guests from the Louvre. Using Dijkstra’s Algorithm to find the shortest path based on average distance between connecting nodes, three different piecewise difference equations were created to model the flow of guests out of the Louvre. With an average of ...
Vector Spaces Of Generalized Linearizations For Rectangular Matrix Polynomials, 2019 Indian Institute of Technology Guwahati
Vector Spaces Of Generalized Linearizations For Rectangular Matrix Polynomials, Biswajit Das, Shreemayee Bora
Electronic Journal of Linear Algebra
The complete eigenvalue problem associated with a rectangular matrix polynomial is typically solved via the technique of linearization. This work introduces the concept of generalized linearizations of rectangular matrix polynomials. For a given rectangular matrix polynomial, it also proposes vector spaces of rectangular matrix pencils with the property that almost every pencil is a generalized linearization of the matrix polynomial which can then be used to solve the complete eigenvalue problem associated with the polynomial. The properties of these vector spaces are similar to those introduced in the literature for square matrix polynomials and in fact coincide with them when ...
Describing Convex Polyhedral Growth, 2019 SUNY Geneseo
Describing Convex Polyhedral Growth, Bethanna Jones
Papers, Posters, and Recordings
We outline a method of describing convex polyhedra in computer graphics, using both algorithmic and mathematical models. Each polyhedron is described in our method with a unique set of planes that define the polyhedron’s faces. These planes thereby define the polyhedron’s shape, extent, and orientation. This definition allows for a computationally easy discrete growth process in which a polyhedron grows in directions perpendicular to some or all of its faces, preserving orientation and morphology. In future work, this method can potentially be applied to the realistic modeling of individual crystal growth and group aggregation on a substrate.
Generating Spectra Using Pca-Based Spectral Mixture Models, 2019 Olivet Nazarene University
Generating Spectra Using Pca-Based Spectral Mixture Models, Joseph S. Makarewicz, Heather D. Makarewicz
Scholar Week 2016 - present
PCA-based spectra mixture models have been created for several laboratory mixture data sets. This presentation provides examples of spectra that were generated using PCA-based spectra mixture models.
A More Powerful Unconditional Exact Test Of Homogeneity For 2 × C Contingency Table Analysis, 2019 Chapman University
A More Powerful Unconditional Exact Test Of Homogeneity For 2 × C Contingency Table Analysis, Louis Ehwerhemuepha, Heng Sok, Cyril Rakovski
Mathematics, Physics, and Computer Science Faculty Articles and Research
The classical unconditional exact p-value test can be used to compare two multinomial distributions with small samples. This general hypothesis requires parameter estimation under the null which makes the test severely conservative. Similar property has been observed for Fisher's exact test with Barnard and Boschloo providing distinct adjustments that produce more powerful testing approaches. In this study, we develop a novel adjustment for the conservativeness of the unconditional multinomial exact p-value test that produces nominal type I error rate and increased power in comparison to all alternative approaches. We used a large simulation study to empirically estimate ...
Algorithms For Bohemian Matrices, 2019 The University of Western Ontario
Algorithms For Bohemian Matrices, Steven E. Thornton
Electronic Thesis and Dissertation Repository
This thesis develops several algorithms for working with matrices whose entries are multivariate polynomials in a set of parameters. Such parametric linear systems often appear in biology and engineering applications where the parameters represent physical properties of the system. Some computations on parametric matrices, such as the rank and Jordan canonical form, are discontinuous in the parameter values. Understanding where these discontinuities occur provides a greater understanding of the underlying system.
Algorithms for computing a complete case discussion of the rank, Zigzag form, and the Jordan canonical form of parametric matrices are presented. These algorithms use the theory of regular ...
The Mathematical Modeling Of Ballet, 2019 Louisiana Tech University
The Mathematical Modeling Of Ballet, Kendall Gibson
Mathematics Senior Capstone Papers
This project aims to analyze the connections between ballet and mathematics. Specifically, this project focuses on analyzing the three-dimensional surfaces created as a dancer performs ballet choreography. The primary goal is to use a Vicon motion capture system in conjunction with MATLAB to model the three-dimensional lines and surfaces created by a dancer’s legs as she performs specific ballet movements. The movements used for this experiment were a pique turn and a rond de jambe. The data was collected using sensors to create objects in Vicon to record the position of the ankle, knee, and hip of the working ...
Optimal Conditional Expectation At The Video Poker Game Jacks Or Better, 2019 University of Utah
Optimal Conditional Expectation At The Video Poker Game Jacks Or Better, Stewart N. Ethier, John J. Kim, Jiyeon Lee
UNLV Gaming Research & Review Journal
There are 134,459 distinct initial hands at the video poker game Jacks or Better, taking suit exchangeability into account. A computer program can determine the optimal strategy (i.e., which cards to hold) for each such hand, but a complete list of these strategies would require a book-length manuscript. Instead, a hand-rank table, which fits on a single page and reproduces the optimal strategy perfectly, was found for Jacks or Better as early as the mid 1990s. Is there a systematic way to derive such a hand-rank table? We show that there is indeed, and it involves finding the ...
Neural Machine Translation, 2019 Loyola Marymount University
Neural Machine Translation, Quinn M. Lanners, Thomas Laurent
Neural Machine Translation is the primary algorithm used in industry to perform machine translation. This state-of-the-art algorithm is an application of deep learning in which massive datasets of translated sentences are used to train a model capable of translating between any two languages. The architecture behind neural machine translation is composed of two recurrent neural networks used together in tandem to create an Encoder Decoder structure. Attention mechanisms have recently been developed to further increase the accuracy of these models. In this senior thesis, the various parts of Neural Machine Translation are explored towards the eventual creation of a tutorial ...
Heterogeneous Boolean Networks With Two Totalistic Rules, 2019 University of Nebraska at Omaha
Heterogeneous Boolean Networks With Two Totalistic Rules, Katherine Toh
Student Research and Creative Activity Fair
Boolean Networks are being used to analyze models in biology, economics, social sciences, and many other areas. These models simplify the reality by assuming that each element in the network can take on only two possible values, such as ON and OFF. The node evolution is governed by its interaction with other nodes in its neighborhood, which is described mathematically by a Boolean function or rule. For simplicity reasons, many models assume that all nodes follow the same Boolean rule. However, real networks often use more than one Boolean rule and therefore are heterogeneous networks. Heterogeneous networks have not yet ...
Parametric Natura Morta, 2019 Independent researcher, Palermo, Italy
Parametric Natura Morta, Maria C. Mannone
The STEAM Journal
Parametric equations can also be used to draw fruits, shells, and a cornucopia of a mathematical still life. Simple mathematics allows the creation of a variety of shapes and visual artworks, and it can also constitute a pedagogical tool for students.