Maker Math: Exploring Mathematics Through Digitally Fabricated Tools With K–12 In-Service Teachers,
2022
Kennesaw State University
Maker Math: Exploring Mathematics Through Digitally Fabricated Tools With K–12 In-Service Teachers, Jason R. Harron, Yi Jin, Amy F. Hillen, Lindsey Mason, Lauren Siegel
Open Access Publishing Fund Collection
This paper reports on nine elementary, middle, and high school in-service teachers who participated in a series of workshops aimed at exploring the wonder, joy, and beauty of mathematics through the creation and application of digitally fabricated tools (i.e., laser-cut and 3D printed). Using the Technological Pedagogical and Content Knowledge (TPACK) framework to investigate technological, pedagogical, contextual, and content knowledge, researchers applied qualitative methods to uncover the affordances and constraints of teaching and learning math concepts with digitally fabricated tools and examined how the workshops supported broadening participation in mathematics by focusing on the connections between mathematical inquiry, nature, and …
Duality For Asymptotic Invariants
Of Graded Families,
2022
University of South Alabama
Duality For Asymptotic Invariants Of Graded Families, Michael Dipasquale, Thái Thành Nguyễn, Alexandra Seceleanu
Department of Mathematics: Faculty Publications
The starting point of this paper is a duality for sequences of natural numbers which, under mild hypotheses, interchanges subadditive and superadditive sequences and inverts their asymptotic growth constants.
We are motivated to explore this sequence duality since it arises naturally in at least two important algebraic-geometric contexts. The first context is Macaulay- Matlis duality, where the sequence of initial degrees of the family of symbolic powers of a radical ideal is dual to the sequence of Castelnuovo-Mumford regularity values of a quotient by ideals generated by powers of linear forms. This philosophy is drawn from an influential paper of …
The Art Of Landslides: How Stochastic Mass Wasting Shapes Topography And Influences Landscape Dynamics,
2022
University of Colorado, Boulder
The Art Of Landslides: How Stochastic Mass Wasting Shapes Topography And Influences Landscape Dynamics, Benjamin Campforts, Charles Shobe, Irina Overeem, Gregory Tucker
Faculty & Staff Scholarship
Bedrock landslides shape topography and mobilize large volumes of sediment. Yet, interactions between landslide-produced sediment and fluvial systems that together govern large-scale landscape evolution are not well understood. To explain morphological patterns observed in steep, landslide-prone terrain, we explicitly model stochastic landsliding and associated sediment dynamics. The model accounts for several common landscape features such as slope frequency distributions, which include values in excess of regional stability limits, quasi-planar hillslopes decorated with straight, closely spaced channel-like features, and accumulation of sediment in valley networks rather than on hillslopes. Stochastic landsliding strongly affects the magnitude and timing of sediment supply to …
The Foundations Of Mathematics: Axiomatic Systems And Incredible Infinities,
2022
Bridgewater State University
The Foundations Of Mathematics: Axiomatic Systems And Incredible Infinities, Catherine Ferris
Honors Program Theses and Projects
Often, people who study mathematics learn theorems to prove results in and about the vast array of branches of mathematics (Algebra, Analysis, Topology, Geometry, Combinatorics, etc.). This helps them move forward in their understanding; but few ever question the basis for these theorems or whether those foundations are sucient or even secure. Theorems come from our foundations of mathematics, Axioms, Logic and Set Theory. In the early20th century, mathematicians set out to formalize the methods, operations and techniques people were assuming. In other words, they were formulating axioms. The most common axiomatic system is known as the Zermelo-Fraenkel axioms with …
The Role Of Surprise In Guessing Games,
2022
Bridgewater State University
The Role Of Surprise In Guessing Games, Justin Carpender
Honors Program Theses and Projects
In this thesis we will study the connection between game structure, surprise, and guessing strategies for these first two versions of a word guessing game. Our analysis will have three levels: one, a basic understanding of language and letter probabilities and the creation of programs that seek to use the structure of a game to efficiently guess words; two, an introduction of mathematical background and Information Theory; three, an analysis of the games and their corresponding guesses via a creative use of the key ideas of Information Theory, particularly, the concepts of surprise and entropy.
Vertex-Magic Graphs,
2022
Bridgewater State University
Vertex-Magic Graphs, Karissa Massud
Honors Program Theses and Projects
In this paper, we will study magic labelings. Magic labelings were first introduced by Sedláček in 1963 [3]. At this time, the labels on the graph were only assigned to the edges. In 1970, Kotzig and Rosa defined what are now known as edge-magic total labelings, where both the vertices and the edges of the graph are labeled. Following this in 1999, MacDougall, Miller, Slamin, and Wallis introduced the idea of vertex-magic total labelings. There are many different types of magic labelings. In this paper will focus on vertex-magictotal labelings.
Data Engineering Techniques And Designs With Music Generating Neural Networks,
2022
Bridgewater State University
Data Engineering Techniques And Designs With Music Generating Neural Networks, Noah Solomon
Honors Program Theses and Projects
The generation of music artificially is an interesting concept to many and has received a lot of attention in recent years. The advancement of neural networks has allowed for the creation of models that can seemingly generate music creatively to mimic a specific genre or composer. This project delved deep into the many ways to construct music generating neural networks and compared different model architectures and data engineering techniques. Three main types of models were implemented and the resulting generated music was evaluated with respect to the melody, note agreeableness, and rhythm. These models used the Bach Chorales corpus as …
Vertex-Magic Total Labeling On G-Sun Graphs,
2022
Bridgewater State University
Vertex-Magic Total Labeling On G-Sun Graphs, Melissa Mejia
Honors Program Theses and Projects
Graph labeling is an immense area of research in mathematics, specifically graph theory. There are many types of graph labelings such as harmonious, magic, and lucky labelings. This paper will focus on magic labelings. Graph theorists are particularly interested in magic labelings because of a simple problem regarding tree graphs introduced in the 1990’s. The problem is still unsolved after almost thirty years. Researchers have studied magic labelings on other graphs in addition to tree graphs. In this paper we will consider vertex-magic labelings on G-sun graphs. We will give vertex-magic total labelings for ladder sun graphs and complete bipartite …
Spectral Analysis Of Multiscale Cultural Traits On Twitter,
2022
MIT
Spectral Analysis Of Multiscale Cultural Traits On Twitter, Chandler Squires, Nikhil Kunapuli, Yaneer Bar-Yam, Alfredo Morales
Northeast Journal of Complex Systems (NEJCS)
Understanding and mapping the emergence and boundaries of cultural areas is a challenge for social sciences. In this paper, we present a method for analyzing the cultural composition of regions via Twitter hashtags. Cultures can be described as distinct combination of traits which we capture via principal component analysis (PCA). We investigate the top 8 PCA components of an area including France, Spain, and Portugal, in terms of the geographic distribution of their hashtag composition. We also discuss relationships between components and the insights those relationships can provide into the structure of a cultural space. Finally, we compare the spatial …
Mathematical Models Yield Insights Into Cnns: Applications In Natural Image Restoration And Population Genetics,
2022
Duquesne University
Mathematical Models Yield Insights Into Cnns: Applications In Natural Image Restoration And Population Genetics, Ryan Cecil
Electronic Theses and Dissertations
Due to a rise in computational power, machine learning (ML) methods have become the state-of-the-art in a variety of fields. Known to be black-box approaches, however, these methods are oftentimes not well understood. In this work, we utilize our understanding of model-based approaches to derive insights into Convolutional Neural Networks (CNNs). In the field of Natural Image Restoration, we focus on the image denoising problem. Recent work have demonstrated the potential of mathematically motivated CNN architectures that learn both `geometric' and nonlinear higher order features and corresponding regularizers. We extend this work by showing that not only can geometric features …
Lorentzian Polynomials, Higher Hessians, And The
Hodge-Riemann Property For Codimension Two Graded Artinian Gorenstein Algebras,
2022
Universidade de Evora
Lorentzian Polynomials, Higher Hessians, And The Hodge-Riemann Property For Codimension Two Graded Artinian Gorenstein Algebras, Pedro Macias-Marques, Chris Mcdaniel, Alexandra Seceleanu, Junzo Watanabe
Department of Mathematics: Faculty Publications
We study the Hodge-Riemann property (HRP) for graded Artinian Gorenstein (AG) algebras. We classify AG algebras in codimension two that have HRP in terms of higher Hessian matrices and positivity of Schur functions associated to certain rectangular partitions.
In this paper we introduce the Hodge Riemann property (HRP) on an arbitrary graded oriented Artinian Gorenstein (AG) algebra defined over R, and we give a criterion on the higher Hessian matrix of its Macaulay dual generator (Theorem 3.1). AG algebras can be regarded as algebraic analogues of cohomology rings (in even degrees) of complex manifolds, and the HRP is analogous to …
Polynomial Growth Of Betti Sequences
Over Local Rings,
2022
University of Nebraska-Lincoln
Polynomial Growth Of Betti Sequences Over Local Rings, Luchezar L. Avramov, Alexandra Seceleanu, Zheng Yang
Department of Mathematics: Faculty Publications
We study sequences of Betti numbers (βRi (M)) of finite modules M over a complete intersection local ring, R. It is known that for every M the subsequence with even, respectively, odd indices i is eventually given by some polynomial in i. We prove that these polynomials agree for all R-modules if the ideal I☐ generated by the quadratic relations of the associated graded ring of R satisfies height I☐ ≥ codim R − 1, and that the converse holds when R is homogeneous and when codim R ≤ 4. Avramov, …
Low-Gain Integral Control For A Class Of Discrete-Time Lur’E
Systems With Applications To Sampled-Data Control,
2022
Edinburgh Napier University
Low-Gain Integral Control For A Class Of Discrete-Time Lur’E Systems With Applications To Sampled-Data Control, Chris Guiver, Richard Rebarber, Stuart Townley
Department of Mathematics: Faculty Publications
We study low-gain (P)roportional (I)ntegral control of multivariate discrete-time, forced Lur’e systems to solve the output-tracking problem for constant reference signals. We formulate an incremental sector condition which is sufficient for a usual linear low-gain PI controller to achieve exponential disturbance-to-state and disturbance-to-tracking-error stability in closed-loop, for all sufficiently small integrator gains. Output tracking is achieved in the absence of exogenous disturbance (noise) terms. Our line of argument invokes a recent circle criterion for exponential incremental input-to-state stability. The discrete-time theory facilitates a similar result for a continuous-time forced Lur’e system in feedback with sampled-data low-gain integral control. The theory …
Debiasing Cyber Incidents – Correcting For Reporting Delays And Under-Reporting,
2022
Kennesaw State University
Debiasing Cyber Incidents – Correcting For Reporting Delays And Under-Reporting, Seema Sangari
Doctor of Data Science and Analytics Dissertations
This research addresses two key problems in the cyber insurance industry – reporting delays and under-reporting of cyber incidents. Both problems are important to understand the true picture of cyber incident rates. While reporting delays addresses the problem of delays in reporting due to delays in timely detection, under-reporting addresses the problem of cyber incidents frequently under-reported due to brand damage, reputation risk and eventual financial impacts.
The problem of reporting delays in cyber incidents is resolved by generating the distribution of reporting delays and fitting modeled parametric distributions on the given domain. The reporting delay distribution was found to …
Ocean Wave Prediction And Characterization For Intelligent Maritime Transportation,
2022
University of New Orlenas
Ocean Wave Prediction And Characterization For Intelligent Maritime Transportation, Pujan Pokhrel
LSU New Orleans Theses and Dissertations
The national Earth System Prediction (ESPC) initiative aims to develop the predictions
for the next generation predictions of atmosphere, ocean, and sea-ice interactions in the scale of days to decades. This dissertation seeks to demonstrate the methods we can use to improve the ESPC models, especially the ocean prediction model. In the application side of the weather forecasts, this dissertation explores imitation learning with constraints to solve combinatorial optimization problems, focusing on the weather routing of surface vessels. Prediction of ocean waves is essential for various purposes, including vessel routing, ocean energy harvesting, agriculture, etc. Since the machine learning approaches …
Stability And Differential Privacy Of Stochastic Gradient Methods,
2022
University at Albany, State University of New York
Stability And Differential Privacy Of Stochastic Gradient Methods, Zhenhuan Yang
Legacy Theses & Dissertations (2009 - 2024)
Recently there are a considerable amount of work devoted to the study of the algorithmic stability as well as differential privacy (DP) for stochastic gradient methods (SGM). However, most of the existing work focus on the empirical risk minimization (ERM) and the population risk minimization problems. In this paper, we study two types of optimization problems that enjoy wide applications in modern machine learning, namely the minimax problem and the pairwise learning problem.
Symbolic Power Containments In Singular Rings In Positive Characteristic,
2022
University of Nebraska-Lincoln
Symbolic Power Containments In Singular Rings In Positive Characteristic, Eloísa Grifo, Linquan Ma, Karl Schwede
Department of Mathematics: Faculty Publications
The containment problem for symbolic and ordinary powers of ideals asks for what values of a and b we have I(a)⊆Ib. Over a regular ring, a result by Ein-Lazarsfeld-Smith, Hochster-Huneke, and Ma-Schwede partially answers this question, but the containments it provides are not always best possible. In particular, a tighter containment conjectured by Harbourne has been shown to hold for interesting classes of ideals - although it does not hold in general. In this paper, we develop a Fedder (respectively, Glassbrenner) type criterion for F-purity (respectively, strong F-regularity) for ideals of finite projective dimension over F-finite Gorenstein rings and use …
Efficiency Of Homomorphic Encryption Schemes,
2022
Clemson University
Efficiency Of Homomorphic Encryption Schemes, Kyle Yates
All Theses
In 2009, Craig Gentry introduced the first fully homomorphic encryption scheme using bootstrapping. In the 13 years since, a large amount of research has gone into improving efficiency of homomorphic encryption schemes. This includes implementing leveled homomorphic encryption schemes for practical use, which are schemes that allow for some predetermined amount of additions and multiplications that can be performed on ciphertexts. These leveled schemes have been found to be very efficient in practice. In this thesis, we will discuss the efficiency of various homomorphic encryption schemes. In particular, we will see how to improve sizes of parameter choices in homomorphic …
Cohomology Of The Symmetric Group With Twisted Coefficients And Quotients Of The Braid Group,
2022
University of Arkansas, Fayetteville
Cohomology Of The Symmetric Group With Twisted Coefficients And Quotients Of The Braid Group, Trevor Nakamura
Graduate Theses and Dissertations
In 2014 Brendle and Margalit proved the level $4$ congruence subgroup of the braid group, $B_{n}[4]$, is the subgroup of the pure braid group generated by squares of all elements, $PB_{n}^{2}$. We define the mod $4$ braid group, $\Z_{n}$, to be the quotient of the braid group by the level 4 congruence subgroup, $B_{n}/B_{n}[4]$. In this dissertation we construct a group presentation for $\Z_{n}$ and determine a normal generating set for $B_{n}[4]$ as a subgroup of the braid group. Further work by Kordek and Margalit in 2019 proved $\Z_{n}$ is an extension of the symmetric group, $S_{n}$, by $\mathbb{Z}_{2}^{\binom{n}{2}}$. A …
Human Perception Of Exponentially Increasing Data Displayed On A Log Scale Evaluated Through Experimental Graphics Tasks,
2022
University of Nebraska-Lincoln
Human Perception Of Exponentially Increasing Data Displayed On A Log Scale Evaluated Through Experimental Graphics Tasks, Emily Robinson
Department of Statistics: Dissertations, Theses, and Student Research
Log scales are often used to display data over several orders of magnitude within one graph. We conducted a series of three graphical studies to evaluate the impact displaying data on the log scale has on human perception of exponentially increasing trends compared to displaying data on the linear scale. Each study was related to a different graphical task, each requiring a different level of interaction and cognitive use of the data being presented. The first experiment evaluated whether our ability to perceptually notice differences in exponentially increasing trends is impacted by the choice of scale. Participants were shown a …
