Physical Sciences and Mathematics Commons^™

Exploring Set-Theoretic Practices Of Youth Engagement In Connective Journalism: What We Lose In School-Mathematical Descriptions, Alexandra R. Aguilar, Emma C. Gargroetzi, Lynne M. Zummo, Emma P. Bene

Journal of Humanistic Mathematics

Analyzing youth video submissions regarding COVID-19 to KQED’s ‘Let’s Talk About the Election’ website, we explore the mathematics these youth engaged in through their submissions without creating any explicit connection to school mathematical concepts or standards. Our focus is the students’ construction of sets (e.g. sets of nurses, doctors, American workers), as a means of creating connection with voters and other media authors through Marchi and Clark’s (2021) construct of connective journalism. We observe these youth constructing sets of varying sizes and reflecting on how these sets are contextualized within a larger political dialogue. We also attempt to rewrite part …

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.

Communication In The Science-Policy Interface: Evidence From A Boundary Organization In Nebraska, Usa, Sechindra Vallury, Brian C. Chaffin, Samantha L. Hamlin, Craig R. Allen

School of Natural Resources: Faculty Publications

Boundary organizations have a crucial function in environmental governance by facilitating the processes through which scientists and decision-makers generate, exchange, evaluate, and utilize knowledge to identify societal problems, propose potential solutions, and make decisions on appropriate courses of action. This support for evidence-informed decision making is essential in addressing environmental challenges effectively. Despite the growing popularity of boundary organizations, there remains a significant challenge in designing information dissemination platforms to bridge the communication divide between scientific experts and non-experts. To address this gap, we used natural language processing tools to analyze the communication strategies of a specific boundary organization — …

Early Career Aquatic Scientists Forge New Connections At Eco-Das Xv, Olivia J. Graham, Alia Al-Haj, Eleanor C. Arrington, Emily R. Arsenault, Carolina C. Barbosa, Kadir Bice, Evie Brahmstedt, S. River D. Bryant, Xun Cai, Stacy Calhoun-Grosch, Joshua Culpepper, Katherine Dale, Derek J. Detweiler, Katlin D. Doughty, Kyle A. Emery, Kara Gadeken, Laura Griffiths, Atefeh Hosseini, Catriona Jones, Hadis Miraly, Alexander W. Mott, Karla Münzner, Igor Ogashawara, Carly R. Olson, Joseph S. Rabaey, Walter A. Rich, Phoenix A. Rogers, Meredith Evans Seeley, Lorena Selak, Qipei Shangguan, Kelsey J. Solomon, Xinyu Sun, Spencer J. Tassone, Audrey Thellman, John Tracey, Jilian Xiong, Tianfei Xue

School of Natural Resources: Faculty Publications

A sense of kuleana (personal responsibility) in caring for the land and sea. An appreciation for laulima (many hands cooperating). An understanding of aloha ’āina (love of the land). The University of Hawai’i at Manoa hosted the 2023 Ecological Dissertations in Aquatic Sciences (Eco-DAS) program, which fostered each of these intentions by bringing together a team of early career aquatic ecologists for a week of networking and collaborative, interdisciplinary project development (Fig. 1).

The Importance Of Contrast Sensitivity, Color Vision, And Electrophysiological Testing In Clinical And Occupational Settings, Frances Silva

Theses & Dissertations

Visual acuity (VA) is universally accepted as the gold standard metric for ocular vision and function. Contrast sensitivity (CS), color vision, and electrophysiological testing for clinical and occupational settings are warranted despite being deemed ancillary and minimally utilized by clinicians. These assessments provide essential information to subjectively and objectively quantify and obtain optimal functional vision. They are useful for baseline data and monitoring hereditary and progressive ocular conditions and cognitive function. The studies in this dissertation highlight the value of contrast sensitivity, color vision, and cone specific electrophysiological testing, as well as the novel metrics obtained with potential practical clinical …

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.

Design Of A Resonant Optical Cavity For Imaging Magneto-Optically Active Thin Film Samples, Cody Robert Brelage

Graduate Theses - Physics and Optical Engineering

This document describes the design and fabrication of an optical resonator system to investigate magneto-optic properties of thin film samples. This system uses an open-air optical resonator to enable photons to make multiple passes through each thin film and thus increase the magnitude of the Faraday rotation that each sample imposes onto the light that exits the system. This system promises many future experiments to study the magneto-optic properties of thin film and nano-particle samples. Using an optical resonator to enhance Faraday rotation should enable an improved signal-to-noise ratio in taking measurements and images with a photodetector.

A Computational Kinetics Model To Quantify Radiation Induced Chemical Products Of Atmospheric Gas Mixtures, Patrick Ables

Dissertations

This research is focused on the development of a computational model which will calculate the effects of radiation on the chemical composition of the atmosphere. The approach utilizes the open-source chemical kinetics toolkit Cantera to model the creation of radiation-induced reactant species within irradiated air mixtures. Chemical solutions are iteratively stepped toward chemical equilibrium within a ‘constantly stirred’ (homogeneous) reactor of fixed volume. Three different radiation chemistry models are implemented in several different pulsed and continuous radiation schemes. The first model includes the mechanisms and rates of a pulse radiation model from the literature to test the validity of the …

Causal Inference Methods For Estimation Of Survival And General Health Status Measures Of Alzheimer’S Disease Patients, Ehsan Yaghmaei

Computational and Data Sciences (PhD) Dissertations

Identifying optimal treatment options with respect to survival of Alzheimer's disease patients is crucially important and previously uninvestigated research question. Our objective was to estimate the causal effects of the most prevalent classes of Alzheimer’s disease drugs, Donepezil and Memantine, and their combined use on Survival and General Health Status Measures of Alzheimer's disease patients for the first five years after initial diagnosis. We carried out a thorough causal inference study using doubly robust estimators, nonparametric bootstrap confidence intervals, Bonferroni corrections for multiple comparisons and analyzing one of the largest high-quality medical databases containing millions of de-identified electronic health records …

Cybersecurity Safeguards: What Cybersecurity Safeguards Could Have Prevented The Intelligence/Data Breach By A Member Of The Air National Guard, Christopher Curtis Royal

Cyber Operations and Resilience Program Graduate Projects

Jack Teixeira, a 21-year-old IT specialist Air National Guard found himself on the wrong side of the US law after sharing what is considered classified and extremely sensitive information about USA's operations and role in Ukraine and Russia war. Like other previous cases of leakage of classified intelligence, the case of Teixeira raises concerns about the weaknesses and vulnerability of federal agencies' IT systems and security protocols governing accessibility to classified documents. Internal leakages of such classified documents hurt national security and can harm the country, especially when such secretive intelligence finds its way into the hands of enemies. Unauthorized …

Simulation And Analysis Of Self-Assembling Slat-Based Dna Ribbons, Lukas Vaughan, Hunter J. Fleming

Computer Science and Computer Engineering Undergraduate Honors Theses

Though still in its infancy, the design of DNA crisscross slats presents great potential in the algorithmic self-assembly of DNA. The provision for higher levels of cooperativity allows for fewer errors through the natural proofreading of slat placement, leading to more robust assembly. Highly accurate simulations of self-assembling DNA squares have been achieved by following the kinetic Tile Assembly Model. Building on that foundation, this study seeks to calibrate the system parameters of a kinetic simulator for self-assembling DNA slats to match experimental results and to use those ranges of parameters to perform exploratory simulations of systems not yet tested …

Arabic Dysarthric Speech Recognition Using Adversarial And Signal-Based Augmentation, Massa Baali, Ibrahim Almakky, Shady Shehata, Fakhri Karray

Machine Learning Faculty Publications

Despite major advancements in Automatic Speech Recognition (ASR), the state-of-the-art ASR systems struggle to deal with impaired speech even with high-resource languages. In Arabic, this challenge gets amplified, with added complexities in collecting data from dysarthric speakers. In this paper, we aim to improve the performance of Arabic dysarthric automatic speech recognition through a multi-stage augmentation approach. To this effect, we first propose a signal-based approach to generate dysarthric Arabic speech from healthy Arabic speech by modifying its speed and tempo. We also propose a second stage Parallel Wave Generative (PWG) adversarial model that is trained on an English dysarthric …

S2cd: Self-Heuristic Speaker Content Disentanglement For Any-To-Any Voice Conversion, Pengfei Wei, Xiang Yin, Chunfeng Wang, Zhonghao Li, Xinghua Qu, Zhiqiang Xu, Zejun Ma

Machine Learning Faculty Publications

In this paper, we propose a Self-heuristic Speaker Content Disentanglement (S2CD) model for any to any voice conversion without using any external resources, e.g., speaker labels or vectors, linguistic models, and transcriptions. S2CD is built on the disentanglement sequential variational autoencoder (DSVAE), but improves DSVAE structure at the model architecture level from three perspectives. Specifically, we develop different structures for speaker and content encoders based on their underlying static/dynamic property. We further propose a generative graph, modelled by S2CD, so as to make S2CD well mimic the multi-speaker speech generation process. Finally, we propose a self-heuristic way to introduce bias …

Fooctts: Generating Arabic Speech With Acoustic Environment For Football Commentator, Massa Baali, Ahmed Ali

Machine Learning Faculty Publications

This paper presents FOOCTTS, an automatic pipeline for a football commentator that generates speech with background crowd noise. The application gets the text from the user, applies text pre-processing such as vowelization, followed by the commentator's speech synthesizer. Our pipeline included Arabic automatic speech recognition for data labeling, CTC segmentation, transcription vowelization to match speech, and fine-tuning the TTS. Our system is capable of generating speech with its acoustic environment within limited 15 minutes of football commentator recording. Our prototype is generalizable and can be easily applied to different domains and languages.

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 …

Multi-Object Tracking: A Computer Vision Paradigm, Natalie Friede

Computer Science and Computer Engineering Undergraduate Honors Theses

This paper delves into advancements and hurdles encountered in multi-object tracking, a critical aspect of computer vision, with a special emphasis on 'referring understanding.' This technique integrates natural language queries into multi-object tracking tasks, thus broadening the scope for practical applications. The innovative referring multi-object tracking (RMOT) approach emerges as a promising solution in this regard. The effectiveness of RMOT was tested using the Refer-KITTI dataset, a dataset specializing in traffic scenes. The evaluation revealed RMOT's ability to handle a diverse range of referent objects, its robust temporal dynamics, and a high level of adaptability. While the paper acknowledges the …

A Tale Of Two Diagonalizations: Methods To Diagonalize A 1-D Piecewise Constant Indefinite Schrödinger Operator, Sarah Wright

Dissertations

We present two numerical methods for computing the solution of a partial differential equation (PDE) for modeling acoustic pressure, known as an extra-wide angle parabolic equation, that features the square root of a differential operator. The differential operator is the negative of an indefinite Schrödinger operator with a piecewise constant potential. This work primarily deals with the 3-piece case; however, a generalization is made to the case of an arbitrary number of pieces. In the first method, the Rayleigh-Secant Method, through restriction to a judiciously chosen lower-dimensional subspace, approximate eigenfunctions are used to obtain estimates for the eigenvalues of the …