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Articles 1 - 14 of 14
Full-Text Articles in Physical Sciences and Mathematics
Bivariate Markov Chain Model Of Irritable Bowel Syndrome (Ibs) Subtypes And Abdominal Pain, Ricardo Reyna Jr.
Bivariate Markov Chain Model Of Irritable Bowel Syndrome (Ibs) Subtypes And Abdominal Pain, Ricardo Reyna Jr.
Theses and Dissertations
Researchers use stochastic models like continuous-time Markov chains (CTMC) to model progression of morbidities of public health impact, like HIV and Hepatitis C. Most of the research in that area is done for a single disease. In this research, we use a bivariate continuous-time Markov chain (CTMC) to model progression of co-morbidities. In particular, we use a bivariate CTMC to model the joint progression of Irritable Bowel Syndrome (IBS) and abdominal pain. Symptoms of IBS are known to change throughout the duration of the disorder. Hence, patients are normally asked to make a journal of the stool type, symptoms, and …
Complete Integrability And Discretization Of Euler Top And Manakov Top, Austin Marstaller
Complete Integrability And Discretization Of Euler Top And Manakov Top, Austin Marstaller
Theses and Dissertations
The Euler top is a completely integrable system with physical system implications and the Manakov top is its four-dimensional extension. We are concerned about their complete integrability and the preservation of this property under a specific discretization known as the Hirota-Kimura Discretization. Surprisingly, it is not guaranteed that under any discretization the conserved quantities are preserved and therefore they must be discovered. In this work we construct the Poisson bracket and Lax pair for each system and provide the Lie algebra background needed to do such such constructions.
Dictionary-Based Data Generation For Fine-Tuning Bert For Adverbial Paraphrasing Tasks, Mark Anthony Carthon
Dictionary-Based Data Generation For Fine-Tuning Bert For Adverbial Paraphrasing Tasks, Mark Anthony Carthon
Theses and Dissertations
Recent advances in natural language processing technology have led to the emergence of
large and deep pre-trained neural networks. The use and focus of these networks are on transfer
learning. More specifically, retraining or fine-tuning such pre-trained networks to achieve state
of the art performance in a variety of challenging natural language processing/understanding
(NLP/NLU) tasks. In this thesis, we focus on identifying paraphrases at the sentence level using
the network Bidirectional Encoder Representations from Transformers (BERT). It is well
understood that in deep learning the volume and quality of training data is a determining factor
of performance. The objective of …
Numerical Simulation Of Low Reynolds Number Locomotion In Viscoelastic Media, Nesreen Abdulrahim Althobaiti
Numerical Simulation Of Low Reynolds Number Locomotion In Viscoelastic Media, Nesreen Abdulrahim Althobaiti
Theses and Dissertations
We use computational models to investigate 2D swimmers within various fluid media with low Reynolds Number. Extensions of the standard Immersed Boundary (IB) Method are proposed so that the fluid media may satisfy no slip, partial slip or free-slip conditions on the moving boundary. The fluid equations are solved through a Multigrid preconditioned GMRES solver. Our numerical results indicate that slip may lead to substantial speed enhancement for swimmers in a viscoelastic fluid, as well as in a viscoelastic two-fluid mixture. Under the slip conditions, the speed of locomotion is dependent in a nontrivial way on both the viscosity and …
Optimal Control Of Multiphase Free Boundary Problems For Nonlinear Parabolic Equations, Evan Cosgrove
Optimal Control Of Multiphase Free Boundary Problems For Nonlinear Parabolic Equations, Evan Cosgrove
Theses and Dissertations
Dissertation research is on the optimal control of systems with distributed parameters described by singular nonlinear partial differential equations (PDE) modeling multi-phase Stefan type second order parabolic free boundary problems. This type of free boundary problems arise in various applications, such as biomedical engineering problem on the laser ablation of biological tissues, aerospace engineering problem on the ice accretion in aircrafts mid-flight, biomedical problem on the growth of cancerous tumor, and many other phase transition processes in thermophysics and fluid mechanics. The aim of the optimal control of distributed free boundary systems is two fold: identification of functional parameters of …
An Investigation Of Gene Regulatory Network State Space Variability, Sara Faye Liesman
An Investigation Of Gene Regulatory Network State Space Variability, Sara Faye Liesman
Theses and Dissertations
Genes are segments of DNA that provide a blueprint for cells and organisms to effectively control processes and regulations within individuals. There have been many attempts to quantify these processes, as a greater understanding of how genes operate could have large impacts on both personalized and precision medicine. Gene interactions are of particular interest, however, current biological methods can not easily reveal the details of these interactions. Therefore, we infer networks of interactions from gene expression data which we call a gene regulatory network, or GRN. Due to the robust behavior of genes and the inherent variability within interactions, models …
A Study Of The Efficacy Of Machine Learning For Diagnosing Obstructive Coronary Artery Disease In Non-Diabetic Patients, Demond Larae Handley
A Study Of The Efficacy Of Machine Learning For Diagnosing Obstructive Coronary Artery Disease In Non-Diabetic Patients, Demond Larae Handley
Theses and Dissertations
According to the Centers for Disease Control and Prevention, about 18.2 million adults age 20 and older have Coronary Artery Disease in the United States. Early diagnosis is therefore of crucial importance to help prevent debilitating consequences, and principally death for many patients. In this study we use data containing gene expression values from peripheral blood samples in 198 non-diabetic patients, with the goal of developing an age and sex gene expression model for diagnosis of Coronary Artery Disease. We employ machine learning methods to obtain a classification based on genetic information, age and sex. Our implementation uses feed forward …
Critical Elliptic Boundary Value Problems With Singular Trudinger-Moser Nonlinearities, Shiqiu Fu
Critical Elliptic Boundary Value Problems With Singular Trudinger-Moser Nonlinearities, Shiqiu Fu
Theses and Dissertations
In this dissertation, we prove the existence of solutions for two classes of eliptic problems that are critical with respect to singular Trudinger-Moser embedding. The proofs are based on compactness and regularity arguments.
A Computational Investigation Of The Biomechanics For Platelets Aggregation, Ghadah Mohammed Alhawael
A Computational Investigation Of The Biomechanics For Platelets Aggregation, Ghadah Mohammed Alhawael
Theses and Dissertations
The proximal cause of most heart attacks and many strokes is the rapid formation of a blood clot (thrombus) in response to the rupture or erosion of an arterial atherosclerotic plaque. The formation of a thrombus in arteries is a very complex process whose workings are subjects of intense research. In this dissertation, we investigate the biomechanics of platelet aggregation in large arteries using a two-phase continuum computational model. The model tracks the number densities of various platelet populations, the concentration of one platelet-activating chemical, as well as the number densities of inter-platelet bonds. Through the formation of elastic bonds, …
Optimal Control Of Coefficients For The Second Order Parabolic Free Boundary Problems, Ali Hagverdiyev
Optimal Control Of Coefficients For The Second Order Parabolic Free Boundary Problems, Ali Hagverdiyev
Theses and Dissertations
Dissertation aims to analyze inverse Stefan type free boundary problem for the second order parabolic PDE with unknown parameters based on the additional information given in the form of the distribution of the solution of the PDE and the position of the free boundary at the final moment. This type of ill-posed inverse free boundary problems arise in many applications such as biomedical engineering problem about the laser ablation of biomedical tissues, in-flight ice accretion modeling in aerospace industry, and various phase transition processes in thermophysics and fluid mechanics. The set of unknown parameters include a space-time dependent diffusion, convection …
Modeling Nonlinear Heat Transfer For A Pin-On-Disc Sliding System, Brian A. Boardman
Modeling Nonlinear Heat Transfer For A Pin-On-Disc Sliding System, Brian A. Boardman
Theses and Dissertations
The objective of this research is to develop a numerical method to characterize heat transfer and wear rates for samples of Vascomax® 300, or Maraging 300, steel. A pin-on-disc experiment was conducted in which samples were exposed to a high-pressure, high-speed, sliding contact environment. This sliding contact generates frictional heating that influences the temperature distribution and wear characteristics of the test samples. A two-dimensional nonlinear heat transfer equation is discretized and solved via a second-order explicit finite difference scheme to predict the transient temperature distribution of the pin. This schematic is used to predict the removal of material from the …
The Analysis Of Neural Heterogeneity Through Mathematical And Statistical Methods, Kyle Wendling
The Analysis Of Neural Heterogeneity Through Mathematical And Statistical Methods, Kyle Wendling
Theses and Dissertations
Diversity of intrinsic neural attributes and network connections is known to exist in many areas of the brain and is thought to significantly affect neural coding. Recent theoretical and experimental work has argued that in uncoupled networks, coding is most accurate at intermediate levels of heterogeneity. I explore this phenomenon through two distinct approaches: a theoretical mathematical modeling approach and a data-driven statistical modeling approach.
Through the mathematical approach, I examine firing rate heterogeneity in a feedforward network of stochastic neural oscillators utilizing a high-dimensional model. The firing rate heterogeneity stems from two sources: intrinsic (different individual cells) and network …
Zero-Inflated Longitudinal Mixture Model For Stochastic Radiographic Lung Compositional Change Following Radiotherapy Of Lung Cancer, Viviana A. Rodríguez Romero
Zero-Inflated Longitudinal Mixture Model For Stochastic Radiographic Lung Compositional Change Following Radiotherapy Of Lung Cancer, Viviana A. Rodríguez Romero
Theses and Dissertations
Compositional data (CD) is mostly analyzed as relative data, using ratios of components, and log-ratio transformations to be able to use known multivariable statistical methods. Therefore, CD where some components equal zero represent a problem. Furthermore, when the data is measured longitudinally, observations are spatially related and appear to come from a mixture population, the analysis becomes highly complex. For this matter, a two-part model was proposed to deal with structural zeros in longitudinal CD using a mixed-effects model. Furthermore, the model has been extended to the case where the non-zero components of the vector might a two component mixture …
Modeling The Evolution Of Barrier Islands, Greg Robson
Modeling The Evolution Of Barrier Islands, Greg Robson
Theses and Dissertations
Barrier islands form off the shore of many coastal areas and serve as the first line of defense, protecting littoral communities against storms. To study the effects that climate change has on barrier islands, we use a cellular model of wind erosion, surface dynamics, beach dynamics, marsh dynamics, and vegetation development. We will show the inhibition of movement when vegetation is present.