UMBC Mathematics and Statistics Department: Recent submissions
Now showing items 2140 of 398

SequenceBased Models for the Classification of Compton Camera Prompt Gamma Imaging Data for Proton Radiotherapy on the GPU Clusters Taki and Ada
(2022)Proton beam therapy is a unique form of radiotherapy that utilizes protons to treat cancer by irradiating cancerous tumors, while avoiding unnecessary radiation exposure to surrounding healthy tissues. Realtime imaging ... 
ON TOURNAMENTS AND NEGATIVE DEPENDENCE
(20220825)Negative dependence of sequences of random variables is often an interesting characteristic of their distribution, as well as a useful tool for studying various asymptotic results, including central limit theorems, Poisson ... 
The Mathematical Effects of Viscoelasticity in Quasistatic Biot Models
(20220824)We investigate and clarify the mathematical properties of linear poroelastic systems (quasistatic Biot) with the addition of classical viscoelasticity. We precisely demonstrate the timeregularization and dissipative effects ... 
Hyperbolic polynomials and majorization
(20211014)On a finite dimensional real vector space V, we consider a real homogeneous polynomial p of degree n that is hyperbolic relative to a vector e ∈ V. This means that p(e) 6= 0 and for any (fixed) x ∈ V, the roots of the ... 
Inference About a Common Mean Vector from Several Independent Multinormal Populations with Unequal and Unknown Dispersion Matrices
(United States Census Bureau, 20220822)In this paper we consider the problem of drawing inference about a common mean vector based on data from several independent multivariate normal populations with unknown and unequal dispersion matrices. An unbiased estimate ... 
Modeling and PDE Theory for The Large Deflections
(20220101)Flutter is defined as a selfexcitation of a thin structure where a surrounding flow destabilizes its natural elastic modes. Cantilevers are particularly prone to flutter, and it has been shown that this instability can ... 
A GROUP SEQUENTIAL MULTIPLE TESTING METHOD AND ITS APPLICATION TO GENOMIC DATA
(20220101)In this dissertation, we consider the simultaneous testing of groups and hypotheses within the groups which occurs in many scientific problems. A group is commonly judged to be significant if at least one hypothesis within ... 
Statistical Inference on High Dimensional Normal Mean Under Linear Inequality Constraints and Efficient Integration of Data in MetaAnalysis
(20220101)In this dissertation, we provide a framework for incorporating linear inequality parameter constraints in estimation and hypothesis testing involving high dimensional normal means. Modern statistical problems often involve ... 
Neural Networks for the Sanitization of Compton Camera Based Prompt Gamma Imaging Data for Proton Radiotherapy
(20220101)Proton beam radiotherapy is a method of cancer treatment that uses proton beamsto irradiate cancerous tissue, while simultaneously sparing doses to healthy tissue. In order to optimize radiation doses to the tumor and ... 
Statistical Modeling using Conditionally Specified Joint Distributions with Applications
(20210101)Often in practice, conditional distributions are easier to model and interpret while the joint distribution itself is either intractable or not available in closed form. When the observed response consists of both continuous ... 
METHODS IN LARGE SCALE MULTIPLE TESTING: MIXTURE NULL, SMALL SAMPLE REPLICATES, AND POWER BOOSTING
(20210101)In this dissertation, we study some methods in multiple testing. In the first topic, we consider the setting of gene expression experiments that use logfold change statistics where the null distribution is assumed to be a ... 
OPTIMIZATION ALGORITHMS FOR TRAINING DEEP NEURAL NETWORKS
(20210101)A formal representation of a deep neural network is constructed, andit is demonstrated that networks satisfying the representation can be trained via feed forward back propagation efficiently. Analysis of the formal ... 
Topics in Data Assimilation and Stochastic Partial Differential Equations
(20210101)In the first part of the thesis we consider data assimilation. We consider the nudging data assimilation algorithm applied to the 3D NavierStokes equations and we derive conditions, based entirely on the observations, ... 
Hidden Markov Models for High Dimensional Data with Geostatistical Applications
(20210101)Stochastic precipitation generators (SPGs) are a class of statistical models which generate synthetic data that can simulate dry and wet rainfall stretches for long durations. Generated precipitation time series data are ... 
Fully Distributed Algorithms for Densely Coupled Optimization Problems in Sparse Optimization and Transportation Applications
(20210101)Distributed algorithms are gaining increasing attention with broad applications indifferent areas such as multiagent network systems, big data, machine learning, and distributed control systems, among others. Most of the ... 
A Generalized Model of Flocking with Steering
(20210101)Flocking is a phenomenon in which selfpropelled agents use only simple rules based on information about the locations and velocities of other agents to move from an unordered motion to an ordered motion in the long run. ... 
Tornado Storm Data Synthesization Using Deep Convolutional Generative Adversarial Network
(Springer, 20211030)Predicting violent storms and dangerous weather conditions with current models can take a long time due to the immense complexity associated with weather simulation. Machine learning has the potential to classify tornadic ... 
Forecasting Sea Ice Concentrations using Attentionbased Ensemble LSTM (Papers Track)
Accurately forecasting Arctic sea ice from subseasonal to seasonal scales has been a major scientific effort with fundamental challenges at play. In addition to physicsbased earth system models, researchers have been ... 
Performance Benchmarking of Data Augmentation and GPU Count Variability for Deep Learning Tornado Predictions
(Elsevier, 20210715)Predicting violent storms and dangerous weather conditions with current mod els can take a long time due to the immense complexity associated with weather simulation. Machine learning has the potential to classify ... 
Positive and Negative Photoconductivity in Monolayer MoS₂ as a Function of Physisorbed Oxygen
(ACS, 20210416)We investigate the effect of molecular oxygen on the photoconductivity of monolayer MoS₂ via broadband timeresolved terahertz spectroscopy. We observe that the photoconductivity of monolayer MoS₂ transitions from ...