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Articles 91 - 120 of 13243
Full-Text Articles in Physical Sciences and Mathematics
Differential Methylation Region Detection Via An Array-Adaptive Normalized Kernelweighted Model, Daniel Alhassan, Gayla R. Olbricht, Akim Adekpedjou
Differential Methylation Region Detection Via An Array-Adaptive Normalized Kernelweighted Model, Daniel Alhassan, Gayla R. Olbricht, Akim Adekpedjou
Mathematics and Statistics Faculty Research & Creative Works
A differentially methylated region (DMR) is a genomic region that has significantly different methylation patterns between biological conditions. Identifying DMRs between different biological conditions is critical for developing disease biomarkers. Although methods for detecting DMRs in microarray data have been introduced, developing methods with high precision, recall, and accuracy in determining the true length of DMRs remains a challenge. In this study, we propose a normalized kernel-weighted model to account for similar methylation profiles using the relative probe distance from "nearby" CpG sites. We also extend this model by proposing an array-adaptive version in attempt to account for the differences …
Causal Inference Using Bayesian Network For Search And Rescue, Amanda Belden
Causal Inference Using Bayesian Network For Search And Rescue, Amanda Belden
Master's Theses
People who are considered missing have much higher probabilities of being found dead compared to those who are not considered missing in terms of Search and Rescue (SAR) missions. Dementia patients are incredibly likely to be declared missing, and in fact after removing those with dementia the probability of the mission being regarded as missing person case is only about 10%. Additionally, those who go missing are much more likely to be on private land than on protected areas such as forests and parks. These and similar associations can be represented and investigated using a Bayesian network that has been …
Using Plankton Edna To Estimate Whale Abundances Off The California Coast: Data Integration And Statistical Modeling, Katherine Chan
Using Plankton Edna To Estimate Whale Abundances Off The California Coast: Data Integration And Statistical Modeling, Katherine Chan
Master's Theses
Understanding marine mammal populations and how they are affected by human activity and ocean conditions is vital, especially in tracking population declines and monitoring endangered species. However, tracking marine mammal populations and their distribution is challenging due to difficulties in observation and costs. Using surrounding plankton environmental DNA (eDNA) has the potential to provide an indirect measure of monitoring cetacean abundances based on ecological associations. This project aims to apply statistical methods to assess the relationship of visual abundances of common species of baleen whales with amplicon sequence variants (ASV) of plankton eDNA samples from the NOAA-CalCOFI Ocean Genomics (NCOG) …
Morphometric Analysis And Taxonomic Re-Evaluation Of Pepsis Cerberus Lucas And P. Elegans Lepeletier (Hymenoptera: Pompilidae: Pepsinae: Pepsini), Frank E. Kurczewski, Akira Shimizu, Diane H. Kiernan
Morphometric Analysis And Taxonomic Re-Evaluation Of Pepsis Cerberus Lucas And P. Elegans Lepeletier (Hymenoptera: Pompilidae: Pepsinae: Pepsini), Frank E. Kurczewski, Akira Shimizu, Diane H. Kiernan
Insecta Mundi
Hurd (1952) separated Pepsis cerberus Lucas from P. elegans Lepeletier (Hymenoptera: Pompilidae: Pepsinae: Pepsini) based on external morphology and biogeography. Vardy (2005) synonymized the familiar and historically well-documented P. cerberus and P. elegans, combining these Nearctic taxa with several Neotropical variants in an extremely broad definition of P. menechma Lepeletier. In doing so, Vardy (2005) breached the principle of nomenclatural stability. He ignored the prevailing usage and clearly violated articles 23.2, 23.3 and 23.9.1.2 of the ICZN (1999). Morphological differences, ecological divergence, and narrow sympatric geographic distribution of P. cerberus and P. elegans …
Mapping For Tracking Sexually Transmitted Infections By Subdistricts In Surabaya, Indonesia, Destri Susilaningrum, Brodjol Sutijo Suprih Ulama, Fausania Hibatullah, Diandra Soja Anjani
Mapping For Tracking Sexually Transmitted Infections By Subdistricts In Surabaya, Indonesia, Destri Susilaningrum, Brodjol Sutijo Suprih Ulama, Fausania Hibatullah, Diandra Soja Anjani
Kesmas
The 2014 shutdown localization of prostitution in Surabaya City, East Java Province, Indonesia, has given rise to an illegal prostitution industry, resulting in the spread of uncontrolled sexually transmitted infections (STIs). Mapping needs to be done to track the spread of the disease. This study used secondary data on STIs in 2020 from the Surabaya City Health Office. By using biplot analysis, this study sought to offer a detailed understanding of the distribution and dynamics of STI cases in different parts of Surabaya. The early-stage syphilis was found in Tegalsari and Krembangan Subdistricts; then, gonorrheal urethritis was found in Tandes, …
Spatial Durbin Model On The Utilization Of Delivery At Health Facilities: A 2017 Indonesian Demographic And Health Survey Analysis, Indah Sri Wahyuni, Ira Gustina, Martya Rahmaniati Makful, Tris Eryando
Spatial Durbin Model On The Utilization Of Delivery At Health Facilities: A 2017 Indonesian Demographic And Health Survey Analysis, Indah Sri Wahyuni, Ira Gustina, Martya Rahmaniati Makful, Tris Eryando
Kesmas
The utilization of delivery at health facilities is a major intervention in reducing 16 to 33% of deaths. This study aimed to determine the model of utilization of delivery at health facilities in Indonesia in 2017 and its influential factors. This study used secondary data from the 2017 Indonesian Demographic and Health Survey using a Spatial Durbin Model (SDM) approach. The population was mothers aged 15 – 49 years, spread across 34 provinces of Indonesia, and had 15,321 samples. The results showed that the Moran’s I value was positive (0.146) and significant at p-value = 0.007, indicating clustered regions with …
A Symbolic Approach To Nonlinear Time Series Analysis, Ranjan Karki, Nibhrat Lohia, Michael B. Schulte
A Symbolic Approach To Nonlinear Time Series Analysis, Ranjan Karki, Nibhrat Lohia, Michael B. Schulte
SMU Data Science Review
Current nonlinear time series methods such as neural networks forecast well. However, they act as a black box and are difficult to interpret, leaving the researchers and the audience with little insight into why the forecasts are the way they are. There is a need for a method that forecasts accurately while also being easy to interpret. This paper aims to develop a method to build an interpretable model for univariate and multivariate nonlinear time series data using wavelets and symbolic regression. The final method relies on multilayer perceptron (MLP) neural networks as a form of dimensionality reduction and the …
Reevaluating Texas Energy Market Forecasts In The Wake Of Recent Extreme Weather Events, Robert A. Derner, Richard W. Butler Ii, Alexandria Neff, Adam R. Ruthford
Reevaluating Texas Energy Market Forecasts In The Wake Of Recent Extreme Weather Events, Robert A. Derner, Richard W. Butler Ii, Alexandria Neff, Adam R. Ruthford
SMU Data Science Review
This paper provides updated forecasts of energy demand in Texas and recognizes the impact of sustainable energy. It is important that the forecasts of the adoption of sustainable energy are reexamined after Winter Storm Uri crippled the Texas power grid and left many without power. This storm highlighted the issues the Texas power grid had and has continued to struggle with in supplying the state with energy. This paper will offer an overview of the relevant literature on the adoption of sustainable energy and relevant events that have occurred in the state of Texas that will give the reader the …
Leveraging Transformer Models For Genre Classification, Andreea C. Craus, Ben Berger, Yves Hughes, Hayley Horn
Leveraging Transformer Models For Genre Classification, Andreea C. Craus, Ben Berger, Yves Hughes, Hayley Horn
SMU Data Science Review
As the digital music landscape continues to expand, the need for effective methods to understand and contextualize the diverse genres of lyrical content becomes increasingly critical. This research focuses on the application of transformer models in the domain of music analysis, specifically in the task of lyric genre classification. By leveraging the advanced capabilities of transformer architectures, this project aims to capture intricate linguistic nuances within song lyrics, thereby enhancing the accuracy and efficiency of genre classification. The relevance of this project lies in its potential to contribute to the development of automated systems for music recommendation and genre-based playlist …
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
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 …
Reports Of Autosomal Recessive Disease And Consanguineous Mating Within The Human Population, Johnathon L. Schluter
Reports Of Autosomal Recessive Disease And Consanguineous Mating Within The Human Population, Johnathon L. Schluter
Master's Theses
It is anecdotally evident when investigating published reports of autosomal recessive disease that a substantial number of cases are the result of related (consanguineous) mating. This research seeks to quantify the percent of manuscripts describing autosomal recessive diseases published between 2000 and 2020 in which consanguineous mating is indicated. We analyzed 602 peer-reviewed manuscripts to identify the percentage of cases presented in which consanguineous mating was indicated, the underlying genes (novel gene or new mutation) and geographical region. These papers were accessed through a specific set of parameters on the free access PubMed Central (PMC) database. A total of 552 …
Context Aware Music Recommendation And Playlist Generation, Elias Mann
Context Aware Music Recommendation And Playlist Generation, Elias Mann
SMU Journal of Undergraduate Research
There are many reasons people listen to music, and the type of music is largely determined by what the listener may be doing while they listen. For example, one may listen to one type of music while commuting, another while exercising, and yet another while relaxing. Without access to the physiological state of the user, current music recommendation methods rely on collaborative filtering - recommending music based on what other similar users listen to - and content based filtering - recommending songs based on their similarities to songs the user already prefers. With the rise in popularity of smart devices …
Towards A New Role Of Mitochondrial Hydrogen Peroxide In Synaptic Function, Cliyahnelle Z. Alexander
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 …
Time Scale Separation In Life-Long Ovarian Follicles Population Dynamics Model, Romain Yvinec, Frédérique Clément, Guillaume Ballif
Time Scale Separation In Life-Long Ovarian Follicles Population Dynamics Model, Romain Yvinec, Frédérique Clément, Guillaume Ballif
Biology and Medicine Through Mathematics Conference
No abstract provided.
Multi-Type Branching Processes In Time-Varying Environments, Arash Jamshidpey
Multi-Type Branching Processes In Time-Varying Environments, Arash Jamshidpey
Biology and Medicine Through Mathematics Conference
No abstract provided.
Exchangeability And A Model Of Biological Evolution, Renee Haddad
Exchangeability And A Model Of Biological Evolution, Renee Haddad
Honors Scholar Theses
A sequence of random variables (RVs) is exchangeable if its distribution is invariant under permutations. For example, every sequence of independent and identically distributed (IID) RVs is exchangeable. The main result on exchangeable sequences of random variables is de Finetti's theorem, which identifies exchangeable sequences as conditionally IID. In this thesis, we explore exchangeability, provide an elementary proof of de Finetti's theorem, and present two applications: the classical Polya's urn model and a toy model for biological evolution.
Modeling Human Temporal Eeg Responses To Vr Visual Stimuli, Richard R. Foster, Connor Delaney, Dean J. Krusienski, Cheng Ly
Modeling Human Temporal Eeg Responses To Vr Visual Stimuli, Richard R. Foster, Connor Delaney, Dean J. Krusienski, Cheng Ly
Biology and Medicine Through Mathematics Conference
No abstract provided.
Assessing Reproducibility Of Brain-Behavior Associations Using Bootstrap Aggregation Methods, Zhetao Chen
Assessing Reproducibility Of Brain-Behavior Associations Using Bootstrap Aggregation Methods, Zhetao Chen
Arts & Sciences Electronic Theses and Dissertations
在本论文中，随着越来越多地利用静息态功能连接 MRI (rs-fcMRI) 将神经活动与病理状况联系起来，我们面临着对此类数据可靠性的普遍担忧。我们的探索集中于提高人类连接组计划（HCP）数据集框架内大脑行为关联的可重复性。我们采用两种不同的引导聚合方法来研究功能连接可靠性的增强：使用循环块引导（CBB）的单独时间序列装袋和使用线性支持向量回归（LSVR）模型的主题级装袋。我们对 CBB 个体时间序列 bagging 的调查表明，这种方法并不能显着增强大脑行为关联的可重复性。这一发现指出了实现可靠的功能连接措施的复杂性以及某些聚合方法在克服这一挑战方面的局限性。相比之下，我们的学科水平考试 通过 LSVR 模型装袋呈现出更有希望的结果。这种方法显着增强了分析之间模型权重的可靠性，证明了其在提高数据稳健性和可重复性方面的功效。两种方法的这种不同影响强调了适当的分析策略在提高神经影像数据可靠性方面的关键作用。通过描述这两种方法的结果，本论文有助于对神经影像领域的数据可靠性进行更广泛的讨论。它强调了在不同数据集上持续进行方法创新和验证的必要性，以提高 rs-fcMRI 研究的可靠性和可解释性。
Robust Prediction Of Charpy Toughness Of Additively Manufactured Kovar Using Deep Convolutional Neural Networks, Nathan R. Bianco
Robust Prediction Of Charpy Toughness Of Additively Manufactured Kovar Using Deep Convolutional Neural Networks, Nathan R. Bianco
Mathematics & Statistics ETDs
Understanding the reason for mechanical failures of manufactured parts in their operating environments is critical to prevention of future failures. However, in-situ post-mortem evaluation of physical properties, such as fracture toughness, is time consuming and alters the condition of the material, leading to potentially misleading findings. In this study, additively manufactured test coupons were produced over a wide range of process conditions to test the impact toughness of a material. The Charpy V-Notch toughness was measured on over 200 samples alongside corresponding optical images of both sides of the fracture surface. Convolutional neural network models were trained to correlate fracture …
Statistical Approaches For The Early Detection Of Colorectal Cancer Using Longitudinal Biomarkers, Emily Berry
Statistical Approaches For The Early Detection Of Colorectal Cancer Using Longitudinal Biomarkers, Emily Berry
Statistical Science Theses and Dissertations
Colorectal cancer (CRC) is the third leading cause of cancer-related death in the United States [45]. CRC is believed to advance from adenomatous polyps creating a unique opportunity for both early detection and cancer prevention [4, 23]. Like other diseases, CRC screening reduces mortality by detecting cancer at earlier, more treatable stages; however, it can also reduce incidence through the removal of precancerous lesions [4]. As a result, screening is recommended for average-risk adults ≥ 45 years of age and includes a variety of tests [4, 12]. Despite alternate screening options, colonoscopy capacity is often cited as a barrier to …
The Performance Of Arima And Arfima In Modelling The Exchange Rate Of Nigeria Currency To Other Currencies, Adewole Ayoade I.
The Performance Of Arima And Arfima In Modelling The Exchange Rate Of Nigeria Currency To Other Currencies, Adewole Ayoade I.
Al-Bahir Journal for Engineering and Pure Sciences
Economic performance of a nation depends majorly on the stability of foreign exchange rate; the economic viability hangs on the exchange rate of local currencies against other currencies across the globe. Box – Jenkins Approach was employed to model the Naira exchange rate to other major currencies using Autoregressive Integrated Moving Average (ARIMA) and The autoregressive fractional integral moving average (ARFIMA) models. This studies aimed on measuring forecast ability of Autoregressive Integrated Moving Average (ARIMA) (p,d,q) and autoregressive fractional integral moving average (ARFIMA) (p, fd, q) models for stationary type series that exhibit features of Long memory properties. Results indicate …
Significant Predictors Of Suicide Rates In The United States: A Multiple Regression Analysis, Alexa L. Darak, Gary Popoli
Significant Predictors Of Suicide Rates In The United States: A Multiple Regression Analysis, Alexa L. Darak, Gary Popoli
Undergraduate Research Journal for the Human Sciences
Inspired by Stack's (2021) research, this study investigated the influence of 19 variables on suicide rates across all 50 United States. The variables included political party, gun ownership, registered guns, religion, alcohol consumption, state safety, depression, marriage, divorce, domestic violence, race, mean elevation, and region. Regression analyses revealed that gun ownership significantly impacts suicide rates, with stricter firearm laws correlating with lower suicide rates. Other crucial contributors to suicide risk were alcohol consumption, domestic violence, marital status, divorce, mean elevation, and political party affiliation. The five most statistically significant predictor variables were gun ownership, divorce rates, percentage of White individuals, …
Testing The Hypothesis That Tennis Points Are Independent And Identically Distributed Using Statistical Methods, Ernesto Ugona Santana
Testing The Hypothesis That Tennis Points Are Independent And Identically Distributed Using Statistical Methods, Ernesto Ugona Santana
Senior Honors Theses
Most research on the probability of winning a tennis match is based on the assumption that the points are independent and identically distributed, treating each point as a Bernoulli trial with fixed probability of success. This assumption, however, seems to contradict experience. Players' performance appears to fluctuate as the match progresses due to the psychological effect of past performance. To test this counterintuitive yet central assumption, previous research has attempted to test the independence hypothesis. However, there exists a research gap in evaluating the identicality-of-distribution hypothesis, a question of broader scope than that of independence. Hence, the purpose of this …
The Relationship Between Amygdala And Orbitofrontal Cortex Volume In The Context Of Oppositional Defiant Disorder, Rahul Alla
Honors Scholar Theses
Disobedient and rebellious attitude in children is on the rise and this type of behavior is categorized as Oppositional Defiant Disorder (ODD). ODD in children can be identified as a persistent pattern of angry or irritable mood, argumentative or defiant behavior or vindictiveness toward others according to the Diagnostic and Statistical Manual (DSM-5, Fifth Edition) of Mental Disorders.1 Children with ODD typically have difficulty regulating and processing their emotions. Issues with regulating emotions is defined as the process by which individuals “influence which emotions they have, when they have them, and how they experience and express them”.2 Dysregulation of emotions …
Calculations From On The Existence Of Periodic Traveling-Wave Solutions To Certain Systems Of Nonlinear, Dispersive Wave Equations, Jacob Daniels
Calculations From On The Existence Of Periodic Traveling-Wave Solutions To Certain Systems Of Nonlinear, Dispersive Wave Equations, Jacob Daniels
Mathematics and Statistics Student Research and Class Projects
In the field of nonlinear waves, particular interest is given to periodic traveling-wave solutions of nonlinear, dispersive wave equations. This thesis aims to determine the existence of periodic traveling-wave solutions for several systems of water wave equations. These systems are the Schr¨odinger KdV-KdV, Schr¨odinger BBM-BBM, Schr¨odinger KdV-BBM, and Schr¨odinger BBM-KdV systems, and the abcd-system. In particular, it is shown that periodic traveling-wave solutions exist and are explicitly given in terms of cnoidal, the Jacobi elliptic function. Certain solitary-wave solutions are also established as a limiting case of the periodic traveling-wave solutions, that is, as the elliptic modulus approaches one.
A Spatial Decision Support System For Rent Estimation Of Retail Spaces In Manhattan Using Geographically Weighted Regression And Spatial Regression, Andie M. Migden Miller
A Spatial Decision Support System For Rent Estimation Of Retail Spaces In Manhattan Using Geographically Weighted Regression And Spatial Regression, Andie M. Migden Miller
Theses and Dissertations
This report outlines an automated, three-phase Spatial Decision Support System that creates models to estimate rent of retail spaces across Manhattan. First, enrich data with predictors. Second, optimize spatially aware neighborhood-level models by combining GWR, spatial regression, and non-spatial regression. Finally, visualize results in an Esri-based WebApp.
Code For Care: Hypertension Prediction In Women Aged 18-39 Years, Kruti Sheth
Code For Care: Hypertension Prediction In Women Aged 18-39 Years, Kruti Sheth
Electronic Theses, Projects, and Dissertations
The longstanding prevalence of hypertension, often undiagnosed, poses significant risks of severe chronic and cardiovascular complications if left untreated. This study investigated the causes and underlying risks of hypertension in females aged between 18-39 years. The research questions were: (Q1.) What factors affect the occurrence of hypertension in females aged 18-39 years? (Q2.) What machine learning algorithms are suited for effectively predicting hypertension? (Q3.) How can SHAP values be leveraged to analyze the factors from model outputs? The findings are: (Q1.) Performing Feature selection using binary classification Logistic regression algorithm reveals an array of 30 most influential factors at an …
Markov Chain Model Of Three-Dimensional Daphnia Magna Movement, Helen L. Kafka
Markov Chain Model Of Three-Dimensional Daphnia Magna Movement, Helen L. Kafka
Theses and Dissertations
Daphnia magna make turns through an antennae-whipping action. This action occursevery few seconds, hence, during the intervening time, the animal either remains in place or continues movement roughly along its current course. We view their movement in three dimensions. We divide the movement in the three dimensions into the movement on a two-dimensional lattice and the movement between the different planes. For the movement on the lattice, we construct a second-order Markov chain model to make predictions about which region of the lattice the animal moves to based on where it was at the last two time points. The movement …
Utilizing Arma Models For Non-Independent Replications Of Point Processes, Lucas M. Fellmeth
Utilizing Arma Models For Non-Independent Replications Of Point Processes, Lucas M. Fellmeth
Theses and Dissertations
The use of a functional principal component analysis (FPCA) approach for estimatingintensity functions from prior work allows us to obtain component scores of replicated point processes under the assumption of independent replications. We show these component scores can be modeled using classical autoregressive moving average (ARMA) models, thus allowing us to also apply the FPCA model to non-independent replications. The Divvy bike-sharing system in the city of Chicago is showcased as an application.
Bayesian Change Point Detection In Segmented Multi-Group Autoregressive Moving-Average Data For The Study Of Covid-19 In Wisconsin, Russell Latterman
Bayesian Change Point Detection In Segmented Multi-Group Autoregressive Moving-Average Data For The Study Of Covid-19 In Wisconsin, Russell Latterman
Theses and Dissertations
Changepoint detection involves the discovery of abrupt fluctuations in population dynamics over time. We take a Bayesian approach to estimating points in time at which the parameters of an autoregressive moving average (ARMA) change, applying a Markov chain Monte Carlo method. We specifically assume that data may originate from one of two groups. We provide estimates of all multi-group parameters of a model of this form for both simulated and real-world data sets. We include a provision to resolve the problem of confounding ARMA parameter estimates and variance of segment data. We apply our model to identify points in time …