Browsing The UTSA Journal of Undergraduate Research & Scholarly Work by Department "Management Science and Statistics"
Now showing items 1-15 of 15
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Application of the Cox Proportional Hazards Model for the Quantitative Analysis of LC-MS Proteomics Data
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 5The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 5, 2019)Along with quantitative, analytical genomics, proteomics continues to be a growing field for determining the gene and cellular functions at the protein level. As the liquid chromatography mass spectrometryphy (LC-MS) ... -
Can We Predict Big 5 Personality Traits from Demographic Characteristics?
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 8, 2022-12)Here we aim to predict the Big Five personality traits based on the demographic information using a generalized linear model. Data was obtained from openpsychometrics.org, pre-processed in MS Excel, and imported to R for ... -
Comparison of Gene Set Analysis with Various Score Transformations to Test the Significance of Sets of Genes
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 4, 2018)Microarray analysis can help identify changes in gene expression which are characteristic to human diseases. Although genomewide RNA expression analysis has become a common tool in biomedical research, it still remains a ... -
Comparison of Regression Methods to Identify Differential Expression in RNA-Sequencing Count Data from the Serial Analysis of Gene Expression
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 5, 2019)Comparative RNA-sequencing analysis for the Serial Analysis of Gene Expression (SAGE) can help identify changes in gene expression which are characteristic to human diseases. Since the RNA-sequencing experiment measures ... -
An expectation-maximization algorithm for estimating the parameters of the correlated binomial distribution
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 8, 2022-12)The correlated binomial (CB) distribution was proposed by Luceño (Computational Statistics & Data Analysis 20, 1995, 511–520) as an alternative to the binomial distribution for the analysis of the data in the presence of ... -
Meta-analysis of Odds Ratios from Heterogeneous Clinical Studies
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 8, 2022-12)Many systematic reviews of randomized clinical trials require meta-analyses of odds ratios. A conventional method estimates the overall odds ratios via weighted averages of the logarithm of individual odds ratios. However, ... -
Optimal Dynamic Treatment Regime by Reinforcement Learning in Clinical Medicine
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 7, 2020-12)Precision medicine allows personalized treatment regime for patients with distinct clinical history and characteristics. Dynamic treatment regime implements a reinforcement learning algorithm to produce the optimal ... -
Performance of Machine Learning Algorithms for Heart Disease Prediction: Logistic Regressions Regularized by Elastic Net, SVM, Random Forests, and Neural Networks
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 8, 2022-12)Heart disease, a medical condition caused by plaque buildup in the walls of the arteries, is the leading cause of death in the U.S. and worldwide. About 697,000 people suffer from this condition in the U.S. alone. This ... -
Policy-Guided Susceptible-Infected-Recovered Modeling of the COVID-19 Spread in Texas
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 8, 2022-12)The goal of this research was to create an SIR model for the Texas COVID-19 cases based on the state data from March of 2020 through October of 2020, and to investigate the impact of public policies on the transmission of ... -
Predicting the Expected Waiting Time of Popular Attractions in Walt Disney World
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 6, 2019)Waiting lines are inevitable consequence of imbalance in service operations at modern theme parks. Because of that, parks have introduced different approaches to reduce standard waiting time; some of which are at no extra ... -
Predicting the Next Big Impact: Modelling the Rate of Massive Meteorite Strikes
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 7, 2020-12)Meteorites are solid pieces of debris from an astronomical object such as a comet, asteroid, or meteoroid that originates in outer space and survives its passage through the atmosphere to reach the surface of a planet. ... -
Quantum Computation, Quantum Algorithms and Implications on Data Science
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 7, 2020-12)Quantum computing is a new revolutionary computing paradigm, first theorized in 1981. It is based on quantum physics and quantum mechanics, which are fundamentally stochastic in nature with inherent randomness and uncertainty. ... -
Statistical Perspectives in Teaching Deep Learning from Fundamentals to Applications
(The UTSA Journal of Undergraduate Research and Scholarly Work;, 2020-12)The use of Artificial Intelligence, machine learning and deep learning have gained a lot of attention and become increasingly popular in many areas of application. Historically machine learning and theory had strong ... -
Stochastic SIR-based Examination of the Policy Effects on the COVID-19 Spread in the U.S. States
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 7, 2020-12)Since the global outbreak of the novel COVID-19, many research groups have studied the epidemiology of the virus for short-term forecasts and to formulate the effective disease containment and mitigation strategies. The ... -
Strategic Analysis and Evaluation of Cheesecake Factory’s Supply Chain: Uncertainties, Challenges, and Remedies
(The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 6, 2019)In the business world, it is important to maintain a profitable balance between efficiency (cost) and responsiveness (to changes in the market, customer demand, etc.) We took the fundamentals of supply chain theory and ...