Physical Sciences and Mathematics Commons^™

Asymptotic Stability Of Solitary Waves For The 1d Nls With An Attractive Delta Potential, Satoshi Masaki, Jason Murphy, Jun Ichi Segata

Mathematics and Statistics Faculty Research & Creative Works

We Consider the One-Dimensional Nonlinear Schrödinger Equation with an Attractive Delta Potential and Mass-Supercritical Nonlinearity. This Equation Admits a One-Parameter Family of Solitary Wave Solutions in Both the Focusing and Defocusing Cases. We Establish Asymptotic Stability for All Solitary Waves Satisfying a Suitable Spectral Condition, Namely, that the Linearized Operator Around the Solitary Wave Has a Two-Dimensional Generalized Kernel and No Other Eigenvalues or Resonances. in Particular, We Extend Our Previous Result [35] Beyond the Regime of Small Solitary Waves and Extend the Results of [19, 29] from Orbital to Asymptotic Stability for a Suitable Family of Solitary Waves.

A Comparison Of Quaternion Neural Network Backpropagation Algorithms, Jeremiah Bill, Bruce A. Cox, Lance Champaign

Faculty Publications

This research paper focuses on quaternion neural networks (QNNs) - a type of neural network wherein the weights, biases, and input values are all represented as quaternion numbers. Previous studies have shown that QNNs outperform real-valued neural networks in basic tasks and have potential in high-dimensional problem spaces. However, research on QNNs has been fragmented, with contributions from different mathematical and engineering domains leading to unintentional overlap in QNN literature. This work aims to unify existing research by evaluating four distinct QNN backpropagation algorithms, including the novel GHR-calculus backpropagation algorithm, and providing concise, scalable implementations of each algorithm using a …

An Empirical Evaluation Of Neural Process Meta-Learners For Financial Forecasting, Kevin G. Patel

Master's Theses

Challenges of financial forecasting, such as a dearth of independent samples and non- stationary underlying process, limit the relevance of conventional machine learning towards financial forecasting. Meta-learning approaches alleviate some of these is- sues by allowing the model to generalize across unrelated or loosely related tasks with few observations per task. The neural process family achieves this by con- ditioning forecasts based on a supplied context set at test time. Despite promise, meta-learning approaches remain underutilized in finance. To our knowledge, ours is the first application of neural processes to realized volatility (RV) forecasting and financial forecasting in general.

We …

Nonparametric Tests For Replicated Latin Squares, Joseph Yang

Dissertations

Two classes of nonparametric procedures for a replicated Latin square design that test for both general and increasing alternatives are developed. The two classes of procedures are similar in the sense that both transform the data so that existing well-known tests for randomized complete block designs can be utilized. On the other hand, the two classes differ in the way that the data is transformed - one class essentially aggregates the data while the other class aligns the data. Within these contexts, the exact distributions and asymptotic distributions are discussed, when applicable. The exact distributions are easily computed using the …

Evaluating The Performance Of Estimators In Sem And Irt With Ordinal Variables, Bo Klauth

Dissertations

In conducting confirmatory factor analysis with ordered response items, the literature suggests that when the number of responses is five and item skewness (IS) is approximately normal, researchers can employ maximum likelihood with robust standard errors (MLR). However, MLR can yield biased factor loadings (FL) and FL standard errors (FLSE) when the variables are ordinal. Other estimators are available. Unweighted least squares and weighted least squares with adjusted mean and variance (ULSMV and WLSMV) are known as the estimators for CFA with ordinal variables (CFA-OV). Another estimator, marginal maximum likelihood (MML), is used in the item response theory (IRT), specifically …

Statistical And Biological Analyses Of Acoustic Signals In Estrildid Finches, Moises Rivera

Dissertations, Theses, and Capstone Projects

Acoustic communication is a process that involves auditory perception and signal processing. Discrimination and recognition further require cognitive processes and supporting mechanisms in order to successfully identify and appropriately respond to signal senders. Although acoustic communication is common across birds, classical research has largely disregarded the perceptual abilities of perinatal altricial taxa. Chapter 1 reviews the literature of perinatal acoustic stimulation in birds, highlighting the disproportionate focus on precocial birds (e.g., chickens, ducks, quails). The long-held belief that altricial birds were incapable of acoustic perception in ovo was only recently overturned, as researchers began to find behavioral and physiological evidence …

Characterization Of Boreal-Arctic Vegetation Growth Phases And Active Soil Layer Dynamics In The High-Latitudes Of North America: A Study Combining Multi-Year In Situ And Satellite-Based Observations, Michael G. Brown

Dissertations, Theses, and Capstone Projects

This dissertation examined the seasonal freeze/thaw activity in boreal-Arctic soils and vegetation physiology in Alaska, USA and Alberta, Canada, using in situ environmental measurements and passive microwave satellite observations. The boreal-Arctic high-latitudes have been experiencing ecosystem changes more rapidly in comparison to the rest of Earth due to the presently warming climatic conditions having a magnified effect over Polar Regions. Currently, the boreal-Arctic is a carbon sink; however, recent studies indicate a shift over the next century to become a carbon source. High-latitude vegetation and cold soil dynamics are influenced by climatic shifts and are largely responsible for the regions …

Learning Finite Mixture Of Ising Graphical Models, Chong Gu

Dissertations

The Ising model is valuable in examining complex interactions within a system, but its estimation is challenging. In this work, we proposed penalized likelihood procedures to infer conditional dependence structure when observed data come from heterogeneous resources in high-dimensional setting. The proposed method can be efficiently implemented by taking advantage of coordinate-ascent, minorization–maximization principles and EM algorithm. A BIC-type criterion will be utilized for the selection of the tuning parameter in the penalized likelihood approaches. The effectiveness of the proposed method is supported by simulation studies and a real-world example.

Dimensions Of Vaccination Attitudes In Nigeria: A Study Of The Impacts Of Covid-19 Vaccine Risk Perception And Acceptance, Abiodun Musbau Lawal, Babatola Dominic Olawa, Ikenna Maximillian Odoh, Ayodeji Olorunfemi Olawole, Olubukola Ajayi, Judith Chineye Azikiwe, Israel Oluwatosin Ayodele, Emmanuel Kolawole Odusina, Thomas Attah, Ezekiel Adeyemi Odedokun, Stephen Ishola Babatunde, Teslim Alabi Oladejo, Confidence Chioma Otoghile, Saheed Abiola Saka

Kesmas

Nigeria has been affected by the COVID-19 pandemic, and vaccination is a key strategy. However, the country faces vaccination hesitancy, poor risk perception, and low acceptance. This study aimed to assess the direct and interactive impacts of COVID-19 vaccine risk perception and acceptability on COVID-19 vaccination attitudes in the general Nigerian population. In a cross-sectional approach, participants completed a structured questionnaire including demographics, COVID-19 vaccine risk perception, acceptance, and vaccination attitude from April 2-30, 2021. The sample included 1,026 participants from different ethnicities across four regions (Southwest, South, Southeast, and North Central) in Nigeria, which were selected using the convenience …

Extremely Hot Ambient Temperature And Injury-Related Mortality, Mien T N Nguyen, Man V M Nguyen, Huong V T Le, Hoai Viet Nguyen, Vu Anh Nguyen, Ngoan Tran Le

Kesmas

This pilot study aimed to evaluate the effects of extremely hot ambient temperatures on the total number of fatal injuries. Data were collected from a population-based mortality registry of Thanh Hoa, a province in the North Central region of Vietnam. This study qualified the distributed lag non-linear model and calculated the RR and 95% CI adjusted for long-term trend and absolute humidity. For the entire study population with 3,949 registered deaths due to injuries collected during 2005-2007, after the onset of extremely hot ambient temperatures, an increased risk of death was observed on the 9th day RR (95% CI) = …

Effects Of Using An Application For Postpartum Contraceptive Use In Family Planning Counseling During Pregnancy, Lia Nurcahyani, Dyah Widiyastuti, Arief Tarmansyah Iman, Yanti Cahyati, Yeni Fitrianingsih

Kesmas

A decision-making tool for family planning flipchart is used for contraceptive counseling, but the use of this flipchart is suboptimal. In this study, primary study resulted in innovative decision-making tools for family planning applications. “Si KB Pintar” was also developed, a tool that women can use to discuss contraceptives with their husbands after family planning counseling. This study analyzed the effectiveness of family planning counseling during pregnancy by applying postpartum contraceptive use. Analytical quantitative quasi-experimental methods were used with a control group design. The sampling method was two-stage sampling. In the first stage, from 22 primary health care (PHC) in …

Assessment Of Rabies Control Attitudes During The Covid-19 Pandemic Through Partial Least Square-Structural Equation Modeling, Sang Gede Purnama, Ni Wayan Arya Utami, Made Subrata, Putu Erma Pradnyani, Karang Agustina, Ibn Swacita

Kesmas

The COVID-19 pandemic disrupts rabies control activities in the community. A new approach is needed to control rabies during the COVID-19 pandemic through digital health interventions by conducting digital surveillance and education. This study aimed to determine key attitude indicators in controlling rabies during the COVID-19 pandemic. A cross-sectional study on 166 participants in Denpasar City with a total of 31 indicators measuring five variables: perceptions of the benefits of rabies control (6 indicators), perceptions of rabies risk (6 indicators), perceptions of obstacles to rabies control (5 indicators), perceptions of the need for technology (7 indicators), and attitudes toward rabies …

A Survey On Online Matching And Ad Allocation, Ryan Lee

Theses

One of the classical problems in graph theory is matching. Given an undirected graph, find a matching which is a set of edges without common vertices. In 1990s, Richard Karp, Umesh Vazirani, and Vijay Vazirani would be the first computer scientists to use matchings for online algorithms [8]. In our domain, an online algorithm operates in the online setting where a bipartite graph is given. On one side of the graph there is a set of advertisers and on the other side we have a set of impressions. During the online phase, multiple impressions will arrive and the objective of …

Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan

Computer Science Senior Theses

We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …

Statistical Methods To Generate Artificial Slot Floor Data For The Advancement Of Casino Related Research, Courtney Bonner, Anastasia (Stasi) D. Baran, Jason D. Fiege, Saman Muthukumarana

International Conference on Gambling & Risk Taking

Abstract:

A common difficulty when researching gambling topics is the availability of high-quality data sets for development and testing. Due to the high level of secrecy within the gambling industry, if data is obtained for research purposes it is often prohibitively obfuscated, incomplete, or aggregated. Although these data have allowed for advancement in academic work, it leaves both the researchers and readers left wondering about what would be possible if more detailed data sets were available. To mitigate the paucity of data available to researchers, we present a Markov chain-based statistical process for producing artificial event data for a simulated …

Payments Data In Gambling Research, Kasra Ghaharian, Mana Azizsoltani

International Conference on Gambling & Risk Taking

A considerable body of gambling-related research has leveraged gamblers' behavioral tracking data to address a broad set of research questions. These data have typically comprised of gamblers' betting-related behaviors including, for example, the frequency and volume of betting. The analysis of gamblers' payment-related behavioral data is far less common, but provides a fruitful avenue gambling-related research.

In this presentation we discuss a selection of potential research opportunities that payments transaction data presents. We supplement this discussion with specific analyses that have been performed by our research group. We also discuss knowledge gaps and areas for future research.

A Game-Theoretic Analysis Of Baccara Chemin De Fer, Ii, Stewart N. Ethier, Jiyeon Lee

International Conference on Gambling & Risk Taking

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Testing For Dice Control Based On Observations Of The Length Of The Shooter's Hand, Stewart N. Ethier, Hokwon Cho

International Conference on Gambling & Risk Taking

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The Rocket: Analyzing Rtp (Return To Player), Payoff Distribution And Player Behavior In Crash Games, Mikhail M. Sher, Robert Haywood Scott Iii, Jonathan A. Daigle

International Conference on Gambling & Risk Taking

Abstract

Rocket is a crash game developed by DraftKings, an American publicly traded online casino, sports betting and fantasy sports company. DraftKings Rocket is a game played with a rising rocket. Players must exit the rocket at any point before the rocket crashes. In that case they receive the payoff in accordance to the multiplier of their exit point. If the rocket crashes before the player bails, player’s payoff is 0 (and they lose their bet).

The game boasts an unprecedented 97% RTP (Return to Player). For comparison, Atlantic City casino slots typically have a 91-92% RTP, while Vegas casino …

Tardys Quantifiers: Extracting Temporal And Reversible Dynamical Symmetries, Nhat Vu Minh Nguyen, Arjendu K. Pattanayak, Andres Aragoneses

2023 Symposium

One of the great challenges in complex and chaotic dynamics is to reveal the details of its underlying determinism. This can be manifest in the form of temporal correlations or structured patterns in the dynamics of a measurable variable. These temporal dynamical structures are sometimes a consequence of hidden global symmetries. Here we identify the temporal (approximate) symmetries of a semiconductor laser with external optical feedback, based on which we define the Temporal And Reversible DYnamical Symmetry (TARDYS) quantifiers to evaluate the relevance of specific temporal correlations in a time series. We show that these symmetries are also present in …

Interannual Variation Of Ichthyofaunal Utilization Of A Man-Made Salt Marsh Creek In Mission Bay, California, Maria Angst

Undergraduate Honors Theses

Marsh restoration and creation are increasingly being used to mitigate Southern California’s drastic decline in wetlands due to human activities. This study used minnow traps to resample the ichthyofauna of a created marsh (Crown Point Mitigation Site; CPMS) and an adjacent natural marsh (Kendall Frost) in Mission Bay, California, 26 years following the marsh creation. Data from this study were compared to data collected immediately after marsh creation from 1995-1998, and from 2021. Fishes captured included Fundulus parvipinnis, Gillichthys mirabilis, Acanthagobius flavimanus, Ctenogobius sagittula, and Mugil cephalus. Species richness and dominance measures were higher in the natural relative to the …

Stake Size And Wagering In A Professional Betting Environment – When Data Affects Decision Making, Anthony Bedford, Tristan Barnett

International Conference on Gambling & Risk Taking

In this work, we discuss the structure of a number of professional wagering organisations, and how they attempt to deal with the “Ender’s Game” effect – when knowledge of the true nature of the ‘war being wagered’ may have affected the process and choice of betting. We analyse the responses from professional wagering and betting organisations, whom operate predominately in Horseracing and sportsbetting, and they identify the importance of separation of decisions around choices to make and the stakes and size of wagers that are linked to the decisions. The proposed model, practically carried out by one company, is an …

Utilizing New Technologies To Measure Therapy Effectiveness For Mental And Physical Health, Jonathan Ossie

Dissertations

Mental health is quickly becoming a major policy concern, with recent data reporting increasing and disproportionately worse mental health outcomes, including anxiety, depression, increased substance abuse, and elevated suicidal ideation. One specific population that is especially high risk for these issues is the military community because military conflict, deployment stressors, and combat exposure contribute to the risk of mental health problems.

Although several pharmacological approaches have been employed to combat this epidemic, their efficacy is mixed at best, which has led to novel nonpharmacological approaches. One such approach is Operation Surf, a nonprofit that provides nature-based programs advocating the restorative …

Special Education: Inclusion And Exclusion In The K-12 U.S. Educational System, Erik Brault

Dissertations

The U.S. Department of Education defines students with disabilities as those having a physical or mental impairment that substantially limits one or more life activities. Previous research has found that students with disabilities placed in inclusive environments perform better academically and socially compared to students with disabilities who are placed in segregated environments. Yet, we know that inclusion in K-12 general education classrooms across the country is not consistently implemented.

The purpose of this study was to better understand the effects, if any, of general education high school teachers’ personal and professional experiences and knowledge on their attitudes toward educating …

Linear Regression With Regularization On The Genetic Architecture Of Maize Flowering Time, Roland Fiagbe

Data Science and Data Mining

Over a century, the maize crop has been one of the most important crop species that is targeted for genetic investigations and experiments. One of the major experiments that have been a topic of interest is crossing inbred lines to produce better offspring through a process called heterosis. Crossing the inbred lines create numerous SNP markers that determine the time to male flowering. This project seeks to explore the SNP markers to select the most relevant ones for predicting time to male flowering using linear regression with regularization methods due to the fact that p > n in our dataset. Various …

Analytical Approach For Monitoring The Behavior Of Patients With Pancreatic Adenocarcinoma At Different Stages As A Function Of Time, Aditya Chakaborty Dr, Chris P. Tsokos Dr

Biology and Medicine Through Mathematics Conference

No abstract provided.

A Novel Family Of Chain Binomial Models To Investigate Correlated Vaccination And Infection Rates In Sveirs Epidemic Dynamics, Divine Wanduku

Biology and Medicine Through Mathematics Conference

No abstract provided.

Predicting Dengue Incidence In Central Argentina Using Google Trends Data, Sahil Chindal, Elizabet Estallo, Yanjun Qian, Michael Robert

Biology and Medicine Through Mathematics Conference

No abstract provided.

Public Acceptance Of Guidance And Regulations For Space Flight Participation, Cory Trunkhill, Robert Joslin, Joseph Keebler

Journal of Aviation Technology and Engineering

Space flight participants are not professional astronauts and not subject to the rules and guidance covering space flight crewmembers. Ordinal logistic regression of survey data was utilized to explore public acceptance of current medical screening recommendations and regulations for safety risk and implied liability for civil space flight participation. Independent variables constituted participant demographic representations while dependent variables represented current Federal Aviation Administration guidance and regulations. Odds ratios were derived based on the demographic categories to interpret likelihood of acceptance for the criteria. Significant likely acceptance of guidance and regulations was found for five of twelve demographic variables influencing public …

Evaluating Models Of Scanpath Prediction, Matthias Kümmerer, Matthias Bethge

MODVIS Workshop

No abstract provided.