Recursive Marix Game Analysis: Optimal, Simplified, And Human Strategies In Brave Rats,
2024
California Polytechnic State University, San Luis Obispo
Recursive Marix Game Analysis: Optimal, Simplified, And Human Strategies In Brave Rats, William A. Medwid
Master's Theses
Brave Rats is a short game with simple rules, yet establishing a comprehensive strategy is very challenging without extensive computation. After explaining the rules, this paper begins by calculating the optimal strategy by recursively solving each turn’s Minimax strategy. It then provides summary statistics about the complex, branching Minimax solution. Next, we examine six other strategy models and evaluate their performance against each other. These models’ flaws highlight the key elements that contribute to the effectiveness of the Minimax strategy and offer insight into simpler strategies that human players could mimic. Finally, we analyze 123 games of human data collected …
Bagging Improves The Performance Of Deep Learning-Based
Semantic Segmentation With Limited Labeled Images: A Case
Study Of Crop Segmentation For High-Throughput
Plant Phenotyping,
2024
University of Nebraska-Lincoln
Bagging Improves The Performance Of Deep Learning-Based Semantic Segmentation With Limited Labeled Images: A Case Study Of Crop Segmentation For High-Throughput Plant Phenotyping, Yinglun Zhan, Yuzhen Zhou, Geng Bai, Yufeng Ge
Department of Statistics: Faculty Publications
Advancements in imaging, computer vision, and automation have revolutionized various fields, including field-based high-throughput plant phenotyping (FHTPP). This integration allows for the rapid and accurate measurement of plant traits. Deep Convolutional Neural Networks (DCNNs) have emerged as a powerful tool in FHTPP, particularly in crop segmentation—identifying crops from the background—crucial for trait analysis. However, the effectiveness of DCNNs often hinges on the availability of large, labeled datasets, which poses a challenge due to the high cost of labeling. In this study, a deep learning with bagging approach is introduced to enhance crop segmentation using high-resolution RGB images, tested on the …
Towards A New Role Of Mitochondrial Hydrogen Peroxide In Synaptic Function,
2024
CUNY Bernard M Baruch College
Towards A New Role Of Mitochondrial Hydrogen Peroxide In Synaptic Function, Cliyahnelle Z. Alexander
Student Theses and Dissertations
Aerobic metabolism is known to generate damaging ROS, particularly hydrogen peroxide. Reactive oxygen species (ROS) are highly reactive molecules containing oxygen that have the potential to cause damage to cells and tissues in the body. ROS are highly reactive atoms or molecules that rapidly interact with other molecules within a cell. Intracellular accumulation can result in oxidative damage, dysfunction, and cell death. Due to the limitations of H2O2 (hydrogen peroxide) detectors, other impacts of ROS exposure may have been missed. HyPer7, a genetically encoded sensor, measures hydrogen peroxide emissions precisely and sensitively, even at sublethal levels, during …
The Quantitative Analysis And Visualization Of Nfl Passing Routes,
2024
University of Arkansas, Fayetteville
The Quantitative Analysis And Visualization Of Nfl Passing Routes, Sandeep Chitturi
Computer Science and Computer Engineering Undergraduate Honors Theses
The strategic planning of offensive passing plays in the NFL incorporates numerous variables, including defensive coverages, player positioning, historical data, etc. This project develops an application using an analytical framework and an interactive model to simulate and visualize an NFL offense's passing strategy under varying conditions. Using R-programming and data management, the model dynamically represents potential passing routes in response to different defensive schemes. The system architecture integrates data from historical NFL league years to generate quantified route scores through designed mathematical equations. This allows for the prediction of potential passing routes for offensive skill players in response to the …
Selected Topics On Sequential Designs For Decision Making,
2024
Clemson University
Selected Topics On Sequential Designs For Decision Making, Caroline Kerfonta
All Dissertations
This dissertation is comprised of three parts. The first proposes a sequential approach to determine the experimental setting with the minimum variance (Kerfonta et al., 2024). Two acquisition functions are developed to assist developing the approach. Theoretical results along with a case study using data from crystallization experiments is conducted to show the ability of the proposed method to correctly select the experiment with the minimum variance. The second and third parts propose adaptations to the Bayesian optimization algorithm using transformed additive Gaussian processes (TAG) as the surrogate model. The goal of using the TAG framework is to decompose the …
Artificial Intelligence Could Probably Write This Essay Better Than Me,
2024
Augustana College, Rock Island Illinois
Artificial Intelligence Could Probably Write This Essay Better Than Me, Claire Martino
Augustana Center for the Study of Ethics Essay Contest
No abstract provided.
Phenomenological Inquiry Into Middle School Teachers’ Perception Of Creativity,
2024
University of Denver
Phenomenological Inquiry Into Middle School Teachers’ Perception Of Creativity, Katalin Grajzel
Electronic Theses and Dissertations
Researchers do agree that creativity is an ability that can be developed and should be fostered (Guilford, 1958; Parnes, 1961). Teachers play an important role in creativity development and often serve as gatekeepers to identify gifted and talented students (Bianco et al., 2011; Novak & Jones, 2021; Schack & Starko, 1990). However, teachers’ judgment of their students’ creativity often only correlates weakly with the results of creativity measures (Kettler et al., 2018; Torrance, 1963). Therefore, in this study I explored teachers’ perception of creativity and creative students as well as factors that support or hinder creativity. The findings revealed that …
Editorial: Ipps 2022 - Plant
Phenotyping For A
Sustainable Future,
2024
Wageningen University and Research
Editorial: Ipps 2022 - Plant Phenotyping For A Sustainable Future, Elias Kaiser, Philipp Von Gillhaussen, Jennifer Clarke, Ulrich Schurr
Department of Statistics: Faculty Publications
Plants are a venue for addressing the challenges facing humanity. The need for a reliable supply of food, feed, materials, chemicals and energy as well as ways to manage agroecology and climate change are among the challenges that we can address through the sustainable use of plants and plant ecosystems. The research community needs to integrate plant systems approaches, from molecular to organismal to applications in the field and ecosystems, to increase productivity sustainably while using fewer land, water, and nutrient resources. In the past two decades, plant phenotyping research has developed a highly valuable portfolio of technologies, processes and …
Discussion On “Spatial+: A Novel Approach To Spatial Confounding” By Dupont, Wood, And Augustin,
2024
North Carolina State University
Discussion On “Spatial+: A Novel Approach To Spatial Confounding” By Dupont, Wood, And Augustin, Brian J. Reich, Shu Yang, Yawen Guan
Department of Statistics: Faculty Publications
Congratulations to the authors for this thoughtful and timely contribution to the spatial confounding literature. The intuitive nature of the method and simplicity of the estimation procedure will surely make Spatial+ popular with practitioners, and the theoretical developments are a major advance for researchers in this area. There is much to discuss! We have formatted our discussion in two sections: in Section 2 we consider the assumptions and statistical properties of Spatial+, and in Section 3 we examine how Spatial+ fits in the wider literature on spatial causal inference.
Prebiotic Proanthocyanidins Inhibit
Bile Reflux–Induced Esophageal
Adenocarcinoma Through Reshaping The Gut
Microbiome And Esophageal Metabolome,
2024
University of Michigan, Ann Arbor
Prebiotic Proanthocyanidins Inhibit Bile Reflux–Induced Esophageal Adenocarcinoma Through Reshaping The Gut Microbiome And Esophageal Metabolome, Katherine M. Weh, Connor L. Howard, Yun Zhang, Bridget A. Tripp, Jennifer Clarke, Amy B. Howell, Joel H. Rubenstein, Julian A. Abrams, Maria Westerhoff, Laura A. Kresty
Department of Statistics: Faculty Publications
The gut and local esophageal microbiome progressively shift from healthy commensal bacteria to inflammation-linked pathogenic bacteria in patients with gastroesophageal reflux disease, Barrett’s esophagus, and esophageal adenocarcinoma (EAC). However, mechanisms by which microbial communities and metabolites contribute to reflux-driven EAC remain incompletely understood and challenging to target. Herein, we utilized a rat reflux-induced EAC model to investigate targeting the gut microbiome–esophageal metabolome axis with cranberry proanthocyanidins (C-PAC) to inhibit EAC progression. Sprague-Dawley rats, with or without reflux induction, received water or C-PAC ad libitum (700 μg/rat/day) for 25 or 40 weeks. C-PAC exerted prebiotic activity abrogating reflux-induced dysbiosis and mitigating …
Mapping Urban Form Into Local Climate Zones For The Continental Us From 1986–2020,
2024
Virginia Polytechnic Institute and State University
Mapping Urban Form Into Local Climate Zones For The Continental Us From 1986–2020, Meng Qi, Chunxue Xu, Wenwen Zhang, Matthias Demuzere, Perry Hystad, Tianjun Lu, Peter James, Benjamin Bechtel, Steve Hankey
Earth and Environmental Sciences Faculty Publications
Urbanization has altered land surface properties driving changes in micro-climates. Urban form influences people’s activities, environmental exposures, and health. Developing detailed and unified longitudinal measures of urban form is essential to quantify these relationships. Local Climate Zones [LCZ] are a culturally-neutral urban form classification scheme. To date, longitudinal LCZ maps at large scales (i.e., national, continental, or global) are not available. We developed an approach to map LCZs for the continental US from 1986 to 2020 at 100 m spatial resolution. We developed lightweight contextual random forest models using a hybrid model development pipeline that leveraged crowdsourced and expert labeling …
On The Transmuted Distributions; Properties And Application,
2024
Marshall University
On The Transmuted Distributions; Properties And Application, Jacob D. Kretzer
Theses, Dissertations and Capstones
The transmuted distributions first appeared in (2007) after Shaw and Buckley constructed a quadratic rank transmutation map (QRTM), G(u) = (1 + λ)u − λu2, as a transformation of a cumulative distribution function of a random variable X, to generate the transmuted-X distribution. In (2017), Jayakumar & Babu defined the T -transmuted-X family of distributions by incorporating a transmuted-X into a transformer-transformed class of distributions (Aljarrah et al., 2014). This thesis surveys the main properties of the transmuted-X distribution, such as density shapes, moments, and entropy. Detailed attention will be given …
Using Ai For Qualitative Labeling: Consistency And Comparisons,
2024
Rollins College
Using Ai For Qualitative Labeling: Consistency And Comparisons, James Mcintyre
Honors Program Theses
This paper details a research study evaluating AI's ability to perform qualitative deductive coding. Multiple AI models were utilized and compared against three human coders and one expert coder. A series of 107 statements were sourced from a group discussion for a qualitative impact assessment of an organization. The AI models were provided these statements and directed to code them using the Community Capitals Framework. Two generations of AI models were evaluated. Overall, the AI achieved a fair level of agreement with the human annotators, but the alignment was far from perfect. Newer AI models did not increase agreement with …
Examining Stigma In Rural Mental Health Care Settings: A Mixed Methods Approach,
2024
Murray State University
Examining Stigma In Rural Mental Health Care Settings: A Mixed Methods Approach, Lainie Krumenacker
Murray State Theses and Dissertations
More than half of Americans will be diagnosed with a mental illness in their lifetime (CDC, 2021), yet stigma towards mental health affects both patients and providers. Although programs exist to address stigma, improve cultural competency among providers, and educate families on the importance of support, facilities are often limited on programs they provide due to allocation of resources and funds. Without a shift in treatment and programing, stigma will continue to impact patient care and outcome.
This study explored stigma among mental health providers in rural communities, while exploring potential differences in treatment among patients due to race. Mental …
Last Passage Time And Excursion Theory For Solvable Diffusions With Applications In Mathematical Finance,
2024
Wilfrid Laurier University
Last Passage Time And Excursion Theory For Solvable Diffusions With Applications In Mathematical Finance, Yaode Sui
Theses and Dissertations (Comprehensive)
In this dissertation, we investigate the properties of last passage times and excursion theory in one-dimensional solvable diffusions, emphasizing their applications in financial modeling, particularly in option pricing. We derive closed-form formulas for the marginal distribution of last passage times and their joint distribution with process values, including the maximum and minimum of the process value. The focus is on time-homogeneous diffusions with various boundaries and imposed killing. Employing spectral expansion theory, we derive explicit formulas for distributions of last passage times in common processes such as Drifted Brownian Motion (BM), Squared Bessel (SQB), Ornstein-Uhlenbeck (OU), and Cox-Ingersoll-Ross (CIR) models. …
Imputation Strategies For Different Categories Of Missing Data,
2024
University of New Hampshire, Durham
Imputation Strategies For Different Categories Of Missing Data, Karthik Chalumuri
Honors Theses and Capstones
Addressing missing data in research is crucial for ensuring the reliability and validity of study findings, yet it remains a significant challenge. This study investigates the impact of missing data on research outcomes and explores the underutilization of existing tools for managing missingness, potentially leading to gaps in critical information with tangible implications for decision-making processes (Dziura et al.).
Focusing on the different categories of missing data—Missing Completely At Random (MCAR), Missing At Random (MAR), and Missing Not At Random (MNAR)—this research examines various imputation strategies tailored to each category. Specifically, we compare the efficacy of several model-based imputation methods, …
On Generative Models And Joint Architectures For Document-Level Relation Extraction,
2024
University of Kentucky
On Generative Models And Joint Architectures For Document-Level Relation Extraction, Aviv Brokman
Theses and Dissertations--Statistics
Biomedical text is being generated at a high rate in scientific literature publications and electronic health records. Within these documents lies a wealth of potentially useful information in biomedicine. Relation extraction (RE), the process of automating the identification of structured relationships between entities within text, represents a highly sought-after goal in biomedical informatics, offering the potential to unlock deeper insights and connections from this vast corpus of data. In this dissertation, we tackle this problem with a variety of approaches.
We review the recent history of the field of document-level RE. Several themes emerge. First, graph neural networks dominate the …
To Mean Or Not To Mean: An Investigation Of Regression To The Mean,
2024
The University of Akron
To Mean Or Not To Mean: An Investigation Of Regression To The Mean, Hunter Ellis
Williams Honors College, Honors Research Projects
Regression to the mean is a statistical phenomenon that can hide important characteristics of what is truly happening in a research study. Caused by statistical randomness, regression to the mean occurs when extreme values, high or low, are followed by less extreme values. To correctly deal with it, one must understand what it is and how to distinguish its effect on conclusions made from the data. This paper provides examples of regression to the mean in both a medical and academic performance study and explains simple identifiers one can observe. Those are then followed up by the introduction of the …
Disentangling Cyclic Causality: An Instance-Based Framework For Causal Discovery,
2024
Thayer School of Engineering
Disentangling Cyclic Causality: An Instance-Based Framework For Causal Discovery, Chase A. Yakaboski
Dartmouth College Ph.D Dissertations
Correlation does not imply causation" is one of the fundamental principles taught in science, emphasizing that associations between variables do not necessarily indicate causality. Yet, over the past three decades, extensive research has begun to challenge this perspective by developing sophisticated methods to differentiate causal from correlative relationships. This research suggests that correlations often involve a blend of confounded and causal interactions, which, given certain assumptions, can be disentangled to uncover actionable insights and deepen our understanding of physical, biological, and societal systems.
Accurately discovering causal relationships from data amidst cyclic dynamics remains a challenging open problem in causality research. …
Reducing Food Scarcity: The Benefits Of Urban Farming,
2023
Brigham Young University
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Journal of Nonprofit Innovation
Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.
Imagine Doris, who is …
