Digital Commons Network^™

Students’ Mathematical Learning During The Covid-19 Pandemic, Jessica Mean, Shilpa Dasgupta

Journal of Humanistic Mathematics

This paper discusses our new approach to assessing students’ learning. This approach includes the use of a final project rather than a final cumulative exam. We suggest that students taking a deep dive into one particular math concept and being able to make connections between that concept and the real world are educational achievements during this pandemic. We also argue that there is value in online learning because students who learn online choose to use library resources and develop their own interests by attending office hours, all of which benefit their learning.

No Simple Formula: Navigating Tensions In Teaching Postsecondary Social Justice Mathematics, Alexa W. C. Lee-Hassan

Journal of Humanistic Mathematics

Instructors of Social Justice Mathematics (SJM) have shared important insights into the powerful potential of connecting classroom mathematics with authentic data about social justice topics, but they have also warned about the harm such teaching can cause when done poorly. In this article, I consider what is necessary to teach SJM at the postsecondary level. I share research that has supported me in learning to teach SJM and highlight challenges that are particular to doing this work in postsecondary contexts. I then describe my experiences navigating the central tensions of this work while honoring its complexity.

Critical Co-Investigators Of Math Trails: Reflections From A Student And Teacher, Benjamin Dickman, Julia Feinberg

Journal of Humanistic Mathematics

In this article, a K-12 mathematics educator and a recent (2020) high school graduate discuss curricular work related to math trails, which are based around the idea of mathematizing potential discoveries along a physical walk. The intersection of math trails with the realities of schooling amid the COVID pandemic is described, along with ways in which math trail learning has ramified beyond classroom walls. This collaboration serves not only to draw attention to the under-researched topic of math trails, but also to exhibit how students and teachers can, in the language of Freire, work together as critical co-investigators.

Math And Democracy, Kimberly A. Roth, Erika L. Ward

Journal of Humanistic Mathematics

Math and Democracy is a math class containing topics such as voting theory, weighted voting, apportionment, and gerrymandering. It was first designed by Erika Ward for math master’s students, mostly educators, but then adapted separately by both Erika Ward and Kim Roth for a general audience of undergraduates. The course contains materials that can be explored in mathematics classes from those for non-majors through graduate students. As such, it serves students from all majors and allows for discussion of fairness, racial justice, and politics while exploring mathematics that non-major students might not otherwise encounter. This article serves as a guide …

Responsible Data Science For Genocide Prevention, Victor Piercey

Journal of Humanistic Mathematics

The term "genocide" emerged out of an effort to describe mass atrocities committed in the first half of the 20th century. Despite a convention of the United Nations outlawing genocide as a matter of international law, the problem persists. Some organizations (including the United Nations) are developing indicator frameworks and “early-warning” systems that leverage data science to produce risk assessments of countries where conflict is present. These tools raise questions about responsible data use, specifically regarding the data sources and social biases built into algorithms through their training data. This essay seeks to engage mathematicians in discussing these concerns.

#Disruptjmm: Online Social Justice Advocacy And Community Building In Mathematics, Rachel Roca, Carrie Diaz Eaton, Drew Lewis, Joseph Hibdon, Stefanie Marshall

Journal of Humanistic Mathematics

In 2019, \#DisruptJMM, a Twitter hashtag, began circulating after an Inclusion/Exclusion blog by Dr. Piper H pointing to the need to make commonplace conversations about human suffering in the Joint Mathematics Meetings (JMM). While the \#DisruptJMM hashtag has been used since 2019, the vast majority of use was in the JMM 2020 meetings. Twitter hashtags are used by activists to push forward conversations, join communities around a single idea, and create change. In this article, we draw on frameworks from community building seen in other equity and inclusion advocacy hashtags such as \#GirlsLikeUs [7] to qualitatively code and analyze tweets …

On Definitions Of "Mathematician", Ron Buckmire, Carrie Diaz Eaton, Joseph Hibdon, Katherine M. Kinnaird, Drew Lewis, Jessica Libertini, Omayra Ortega, Rachel Roca, Andrés R. Vindas Meléndez

Journal of Humanistic Mathematics

The definition of who is or what makes a “mathematician” is an important issue to be addressed in the mathematics community. Too often, a narrower definition of who is considered a mathematician (and what is considered mathematics) is used to exclude people from the discipline—both explicitly and implicitly. However, using a narrow definition of a mathematician allows us to highlight, examine, and challenge systemic barriers that exist in certain spaces of the community. This paper analyzes and illuminates tensions between narrow and broad definitions and how they can be used to promote both inclusion and exclusion simultaneously. In this article, …

Mathematics And Society: Towards Critical Mathematics Research And Education, Tian An Wong, Carrie Diaz Eaton, Rachel Roca, Nancy Rodriguez

Journal of Humanistic Mathematics

No abstract provided.

Mathematics And Society, Mark Huber, Gizem Karaali

Journal of Humanistic Mathematics

No abstract provided.

Front Matter

Journal of Humanistic Mathematics

No abstract provided.

Algebraic Product Is The Only "And-Like"-Operation For Which Normalized Intersection Is Associative: A Proof, Thierry Denœx, Vladik Kreinovich

Departmental Technical Reports (CS)

For normalized fuzzy sets, intersection is, in general, not normalized. So, if we want to limit ourselves to normalized fuzzy sets, we need to normalize the intersection. It is known that for algebraic product, the normalized intersection is associative, and that for many other "and"-operations (t-norms), normalized intersection is not associative. In this paper, we prove that algebraic product is the only "and"-operation (even the only "and-like" operation) for which normalized intersection is associative.

Why Unit Two-Variable-Per-Inequality (Utvpi) Constraints Are So Efficient To Handle: Intuitive Explanation, Saeid Tizpaz-Niari, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In general, integer linear programming is NP-hard. However, there exists a class of integer linear programming problems for which an efficient algorithm is possible: the class of so-called unit two-variable-per-inequality (UTVPI) constraints. In this paper, we provide an intuitive explanation for why an efficient algorithm turned out to be possible for this class. Namely, the smaller the class, the more probable it is that a feasible algorithm is possible for this class, and the UTVPI class is indeed the smallest -- in some reasonable sense described in this paper.

Industry-Academia Collaboration: Main Challenges And What Can We Do, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

How can we bridge the gap between industry and academia? How can we make them collaborate more effectively? In this essay, we try to come up with answers to these important questions.

Towards A Psychologically Natural Relation Between Colors And Fuzzy Degrees, Victor L. Timchenko, Yuriy P. Kondratenko, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

A natural way to speed up computations -- in particular, computations that involve processing fuzzy data -- is to use the fastest possible communication medium: light. Light consists of components of different color. So, if we use optical color computations to process fuzzy data, we need to associate fuzzy degrees with colors. One of the main features -- and of the main advantages -- of fuzzy technique is that the corresponding data has intuitive natural meaning: this data comes from words from natural language. It is desirable to preserve this naturalness as much as possible. In particular, it is desirable …

Why Attitudes Are Usually Mutual: A Possible Mathematical Explanation, Julio C. Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we provide a possible mathematical explanation of why people's attitude to each other is usually mutual: we usually have good attitude who those who have good feelings towards us, and we usually have negative attitudes towards those who have negative feelings towards, Several mathematical explanations of this mutuality have been proposed, but they are based on specific approximate mathematical models of human (and animal) interaction. It is desirable to have a solid mathematical explanation that would not depend on such approximate models. In this paper, we show that a recent mathematical result about relation algebras can lead …

How To Select A Model If We Know Probabilities With Interval Uncertainty, Vladik Kreinovich

Departmental Technical Reports (CS)

Purpose: When we know the probability of each model, a natural idea is to select the most probable model. However, in many practical situations, we do not know the exact values of these probabilities, we only know intervals that contain these values. In such situations, a natural idea is to select some probabilities from these intervals and to select a model with the largest selected probabilities. The purpose of this study is to decide how to most adequately select these probabilities.

Design/methodology/approach: We want the probability-selection method to preserve independence: If, according to the probability intervals, the two …

Stochastic Processes And Multi-Resolution Analysis: A Trigonometric Moment Problem Approach And An Analysis Of The Expenditure Trends For Diabetic Patients, Isaac Nwi-Mozu

Computational and Data Sciences (PhD) Dissertations

This dissertation is divided into two distinct parts. The main theme of the first part is to study stochastic processes (and related signal processing questions) using tools in wavelet analysis, functional analysis (we use in particular the trigonometric moment problem), the theory of realization of rational functions, and reproducing kernel Hilbert spaces. A novel form of multiresolution analysis is formulated in the discrete case that is used to study some stochastic processes. Using the trigonometric moment problem, we associate with a vector-valued wide-sense stationary process a multiresolution of a new kind. The notion of realization of rational functions was used …

Unilinear Residuated Lattices, Xiao Zhuang

Electronic Theses and Dissertations

We characterize all residuated lattices that have height equal to 3 and show that the variety they generate has continuum-many subvarieties. More generally, we study unilinear residuated lattices: their lattice is a union of disjoint incomparable chains, with bounds added. We give the characterization of all unilinear residuated lattices. By presenting the constructions and axiomatizations for different classes of unilinear residuated lattices, we conclude that the study of unilinear residuated lattices can be reduced to the study of the ⊤-unital ones. Using the classification of unilinear residuated lattices, the idempotent unilinear residuated lattices are studied and amalgamation property and strong …

If Everything Is A Matter Of Degree, Why Do Crisp Techniques Often Work Better?, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Numerous examples from different application domain confirm the statement of Lotfi Zadeh -- that everything is a matter of degree. Because of this, one would expect that in most -- if not all -- practical situations taking these degrees into account would lead to more effective control, more effective prediction, etc. In practice, while in many cases, this indeed happens, in many other cases, "crisp" methods -- methods that do not take these degrees into account -- work better. In this paper, we provide two possible explanations for this discrepancy: an objective one -- explaining that the optimal (best-fit) model …

A Novel Regularized Orthonormalized Partial Least Squares Model For Multi-View Learning, Ce Bian

Mathematics Dissertations - Archive

Over the past few years, the size of data dimensions or features has been increasing in various fields of science and engineering, owing to the rapid pace of data collection and the development of more advanced storage methods. However, to handle high-dimensional data, dimensionality reduction is essential before performing classification or regression tasks to eliminate noisy features. There are several numerical methods available for reducing data dimensionality, such as Canonical Correlation Analysis (CCA), Principal Component Analysis (PCA), and Linear Discriminant Analysis (LDA). While these methods offer valuable approaches to data dimensionality reduction, they do come with certain limitations. CCA, for …

A Machine Learning Approach To Constructing Ramsey Graphs Leads To The Trahtenbrot-Zykov Problem., Emily Hawboldt

Electronic Theses and Dissertations

Attempts at approaching the well-known and difficult problem of constructing Ramsey graphs via machine learning lead to another difficult problem posed by Zykov in 1963 (now commonly referred to as the Trahtenbrot-Zykov problem): For which graphs F does there exist some graph G such that the neighborhood of every vertex in G induces a subgraph isomorphic to F? Chapter 1 provides a brief introduction to graph theory. Chapter 2 introduces Ramsey theory for graphs. Chapter 3 details a reinforcement learning implementation for Ramsey graph construction. The implementation is based on board game software, specifically the AlphaZero program and its …

Stability Of Cauchy's Equation On Δ+., Holden Wells

Electronic Theses and Dissertations

The most famous functional equation f(x+y)=f(x)+f(y) known as Cauchy's equation due to its appearance in the seminal analysis text Cours d'Analyse (Cauchy 1821), was used to understand fundamental aspects of the real numbers and the importance of regularity assumptions in mathematical analysis. Since then, the equation has been abstracted and examined in many contexts. One such examination, introduced by Stanislaw Ulam and furthered by Donald Hyers, was that of stability. Hyers demonstrated that Cauchy's equation exhibited stability over Banach Spaces in the following sense: functions that approximately satisfy Cauchy's equation are approximated with the same level of error by functions …

Optimal Control Frameworks For Modeling Dynamics And Androgen Deprivation Therapies In Prostate Cancer, Hussein Ed Duweh

Mathematics Dissertations - Archive

In this work, we present an optimal control approach for the assessment of treatments in prostate cancer. For this purpose, we use two different approaches, based on differential equations, to model the dynamics of prostate cancer. For the first approach, we use a system of ordinary differential equations (ODE) that model androgen-dependent and independent prostate cancer cell mechanisms. Given some synthetic patient data, we then performed a parameter estimation process by formulating an optimization problem to obtain the coefficients in this model. A second optimal control problem was formulated to obtain optimal androgen suppression therapies. A theoretical analysis of both …

Probabilistic Modeling Of Social Media Networks, Distinguishing Phylogenetic Networks From Trees, And Fairness In Service Queues, Md Rashidul Hasan

Mathematics & Statistics ETDs

In this dissertation, three primary issues are explored. The first subject exposes who-saw-from-whom pathways in post-specific dissemination networks in social media platforms. We describe a network-based approach for temporal, textual, and post-diffusion network inference. The conditional point process method discovers the most probable diffusion network. The tool is capable of meaningful analysis of hundreds of post shares. Inferred diffusion networks demonstrate disparities in information distribution between user groups (confirmed versus unverified, conservative versus liberal) and local communities (political, entrepreneurial, etc.). A promising approach for quantifying post-impact, we observe discrepancies in inferred networks that indicate the disproportionate amount of automated bots. …

Algorithms For Computing Invariants Of Trisected Branched Covers, Patricia Cahn, Gordana Matic, Benjamin Ruppik

Mathematics Sciences: Faculty Publications

We give diagrammatic algorithms for computing the group trisection, homology groups, and intersection form of a closed, orientable, smooth 4-manifold, presented as a branched cover of a bridge-trisected surface in ��4. The algorithm takes as input a tri-plane diagram, labelled with permutations according to the Wirtinger relations. We apply our algorithm to several examples, including dihedral and cyclic covers of spun knots, cyclic covers of Suciu's ribbon knots with the trefoil knot group, and an infinite family of irregular covers of the Stevedore disk double. As an application, we give a fully automated algorithm for computing Kjuchukova's homotopy-ribbon obstruction for …

Association Of Lockdown Policies With Covid-19 Early Case Growth Rates In The United States, Anna Barefield

Boise State University Theses and Dissertations

The COVID-19 pandemic has impacted essentially the entire globe, infecting over 755 million people worldwide and resulting in over 6.8 million deaths to date. Different countries have had varying levels of success in managing the spread of the pandemic, and the success or lack thereof could be explained by the impact of government intervention, such as lockdown policies, mask mandates, and social distancing advisories. The United States responded particularly poorly to the early pandemic outbreak as compared to other similar countries, due to its lack of coordinated planning to implement effective policies, with large variations in action taken by each …

Large Eddy Simulation By Using Wang’S Liutex-Based Subgrid Model, Vishwa Shah

Mathematics Dissertations - Archive

Turbulent flows and vortex structures in fluid dynamics have been captivating researchers for decades, owing to their intrinsic complexity and significance in various industrial and natural processes. Despite their fundamental importance, the definition and identification of vortices in turbulent flows continue to pose challenges, and to date, no universally accepted approach exists. This pursuit dates to the pioneering work of Hermann von Helmholtz in the 19th century, when the concept of vortices was first introduced. In 2019, Liu et al. introduced a novel physical quantity termed "Liutex" in scalar, vector, and tensor forms, providing a promising avenue for understanding and …

Asymptotic Cones Of Quadratically Defined Sets And Their Applications To Qcqps, Alexander Joyce

All Dissertations

Quadratically constrained quadratic programs (QCQPs) are a set of optimization problems defined by a quadratic objective function and quadratic constraints. QCQPs cover a diverse set of problems, but the nonconvexity and unboundedness of quadratic constraints lead to difficulties in globally solving a QCQP. This thesis covers properties of unbounded quadratic constraints via a description of the asymptotic cone of a set defined by a single quadratic constraint. A description of the asymptotic cone is provided, including properties such as retractiveness and horizon directions.

Using the characterization of the asymptotic cone, we generalize existing results for bounded quadratically defined regions with …

A History Of The Hurwitz Problem Concerning Branched Coverings, James Alexander Byars

Boise State University Theses and Dissertations

From a d-sheeted branched covering f : M → N, where M and N are surfaces, one can read off the branch datum

D(f) = {M, N, d, (A₁, . . . , A_r)},

where A_i = [e_i1, . . . , e_{in_i}] is a partition of d. Furthermore, a relationship between the Euler characteristics between M and N is known, called the Riemann-Hurwitz formula

��(M) = d��(N) − v(D(f …

Matrix Completion Problems For The Positiveness And Contraction Through Graphs, Louis C. Christopher

Theses and Dissertations

In this work, we study contractive and positive real matrix completion problems which are motivated in part by studies on sparce (or dense) matrices for weighted sparse recovery problems and rating matrices with rating density in recommender systems. Matrix completions problems also have many applications in probability and statistics, chemistry, numerical analysis (e.g. optimization), electrical engineering, and geophysics. In this paper we seek to connect the contractive and positive completion property to a graph theoretic property. We then answer whether the graphs of real symmetric matrices having loops at every vertex have the contractive completion property if and only if …