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Full-Text Articles in Physical Sciences and Mathematics

Beyond Machine Learning: An Fmri Domain Adaptation Model For Multi-Study Integration, Lauryn Michelle Burleigh Mar 2023

Beyond Machine Learning: An Fmri Domain Adaptation Model For Multi-Study Integration, Lauryn Michelle Burleigh

LSU Doctoral Dissertations

Traditional machine learning analyses are challenging with functional magnetic
resonance imaging (fMRI) data, not only because of the amount of data that needs to be
collected, adding a particular challenge for human fMRI research, but also due to the change in
hypothesis being addressed with various analytical techniques. Domain adaptation is a type of
transfer learning, a step beyond machine learning which allows for multiple related, but not
identical, data to contribute to a model, can be beneficial to overcome the limitation of data
needed but may address different hypothesis questions than anticipated given the analysis
computation. This dissertation assesses …


Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu Dec 2022

Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu

LSU Doctoral Dissertations

In the oil and gas industry, distributed fiber optics sensing (DFOS) has the potential to revolutionize well and reservoir surveillance applications. Using fiber optic sensors is becoming increasingly common because of its chemically passive and non-magnetic interference properties, the possibility of flexible installations that could be behind the casing, on the tubing, or run on wireline, as well as the potential for densely distributed measurements along the entire length of the fiber. The main objectives of my research are to develop and demonstrate novel signal processing and machine learning computational techniques and workflows on DFOS data for a variety of …


Understanding Consumers' Use Experience On Electrically Heated Jacket: A Study On Online Review Using Topic Modeling, Md Nakib-Ul Hasan Aug 2022

Understanding Consumers' Use Experience On Electrically Heated Jacket: A Study On Online Review Using Topic Modeling, Md Nakib-Ul Hasan

LSU Doctoral Dissertations

The demand for heated jackets is anticipated to be fuelled by frequent temperature drops, severe winter weather, and increasing outdoor activities. Electrically heated jackets (EHJ) are primarily marketed through online distribution channels and expansion of online sales channels is expected to boost the global market. Consumers are increasingly relying on online reviews from other consumers to help them decide what to buy. Businesses also actively monitor and manage their online reviews to build trust in their brand and make it more likely that customers will buy. Traditional approaches for assessing customer behavior, such as market research surveys and focus groups, …


Impact Of Oil And A Tropical Cyclone On An Omnivore And Herbivore Population In Salt Marshes Of Louisiana, Hannah K. Gordon Jul 2022

Impact Of Oil And A Tropical Cyclone On An Omnivore And Herbivore Population In Salt Marshes Of Louisiana, Hannah K. Gordon

LSU Master's Theses

Terrestrial arthropods are the ideal ecological indicators for the health of a salt marsh. Salt marshes are under extreme continuous stressors including climate change, land loss, oil spills, and tropical cyclones. Such stressors impact trophic and species level interactions, food resources, dispersal and population size of insects. In the present study, we collected terrestrial arthropods from eleven sites around Barataria Bay, five sites were oiled and five sites were unoiled, to determine the impact of the redistribution of oil from the Deepwater Horizon oil spill. Site C6 was excluded from the oiled and unoiled data because it was in close …


Efficient Low Dimensional Representation Of Vector Gaussian Distributions, Md Mahmudul Hasan Apr 2022

Efficient Low Dimensional Representation Of Vector Gaussian Distributions, Md Mahmudul Hasan

LSU Doctoral Dissertations

This dissertation seeks to find optimal graphical tree model for low dimensional representation of vector Gaussian distributions. For a special case we assumed that the population co-variance matrix $\Sigma_x$ has an additional latent graphical constraint, namely, a latent star topology. We have found the Constrained Minimum Determinant Factor Analysis (CMDFA) and Constrained Minimum Trace Factor Analysis (CMTFA) decompositions of this special $\Sigma_x$ in connection with the operational meanings of the respective solutions. Characterizing the CMDFA solution of special $\Sigma_x$, according to the second interpretation of Wyner's common information, is equivalent to solving the source coding problem of finding the minimum …


Anticipating Stochastic Integrals And Related Linear Stochastic Differential Equations, Sudip Sinha Apr 2022

Anticipating Stochastic Integrals And Related Linear Stochastic Differential Equations, Sudip Sinha

LSU Doctoral Dissertations

Itô’s stochastic calculus revolutionized the field of stochastic analysis and has found numerous applications in a wide variety of disciplines. Itô’s theory, even though quite general, cannot handle anticipating stochastic processes as integrands. There have been considerable efforts within the mathematical community to extend Itô’s calculus to account for anticipation. The Ayed–Kuo integral — introduced in 2008 — is one of the most recent developments. It is arguably the most accessible among the theories extending Itô’s calculus — relying solely on probabilistic methods. In this dissertation, we look at the recent advances in this area, highlighting our contributions. First, we …


General Stochastic Calculus And Applications, Pujan Shrestha Apr 2022

General Stochastic Calculus And Applications, Pujan Shrestha

LSU Doctoral Dissertations

In 1942, K. Itô published his pioneering paper on stochastic integration with respect to Brownian motion. This work led to the framework for Itô calculus. Note that, Itô calculus is limited in working with knowledge from the future. There have been many generalizations of the stochastic integral in being able to do so. In 2008, W. Ayed and H.-H. Kuo introduced a new stochastic integral by splitting the integrand into the adaptive part and the counterpart called instantly independent. In this doctoral work, we conduct deeper research into the Ayed–Kuo stochastic integral and corresponding anticipating stochastic calculus.

We provide a …


Are Long-Period Exoplants Around Cool Stars More Common Than We Thought?, Emily Jane Safron Mar 2022

Are Long-Period Exoplants Around Cool Stars More Common Than We Thought?, Emily Jane Safron

LSU Doctoral Dissertations

The Kepler mission has been the catalyst for discovery of nearly 5,000 confirmed and candidate exoplanets. The majority of these candidates orbit Sun-like stars, and have orbital periods comparable to or shorter than that of the Earth, due to the selection bias inherent in the transit method and the limitations of automated transit search algorithms. We aim to develop a richer understanding of the population of exoplanets around the lowest-mass stars, the M spectral type. We are particularly interested in exoplanets with long orbital periods, which are difficult or impossible to find using standard transit search algorithms. In our study, …


Regional Expansion And Evaluation Of Potential Chemical Control For Invasive Apple Snails (Pomacea Maculata) In Southwest Louisiana, Julian M. Lucero Nov 2021

Regional Expansion And Evaluation Of Potential Chemical Control For Invasive Apple Snails (Pomacea Maculata) In Southwest Louisiana, Julian M. Lucero

LSU Master's Theses

The integration of monitoring and chemical control is an efficient strategy for managing invasive apple snails, Pomacea maculata, in the rice (Oryza sativa L.) and crawfish systems of southwest Louisiana. However, their current distribution, expansion rates, and susceptibility to chemical control methods in this area are not well known. This study evaluated the expansion of P. maculata in southwest Louisiana and assessed potential chemical control for P. maculata among toxicity assays using various application rates. The effects of potential chemical control were also assessed on a non-target species, the red swamp crawfish (Procambarus clarkii). P. maculata …


Applications Of Nonstandard Analysis In Probability And Measure Theory, Irfan Alam May 2021

Applications Of Nonstandard Analysis In Probability And Measure Theory, Irfan Alam

LSU Doctoral Dissertations

This dissertation broadly deals with two areas of probability theory and investigates how methods from nonstandard analysis may provide new perspectives in these topics. In particular, we use nonstandard analysis to prove new results in the topics of limiting spherical integrals and of exchangeability.

In the former area, our methods allow us to represent finite dimensional Gaussian measures in terms of marginals of measures on hyperfinite-dimensional spheres in a certain strong sense, thus generalizing some previously known results on Gaussian Radon transforms as limits of spherical integrals. This first area has roots in the kinetic theory of gases, which is …


Characterizing The Northern Hemisphere Circumpolar Vortex Through Space And Time, Nazla Bushra May 2021

Characterizing The Northern Hemisphere Circumpolar Vortex Through Space And Time, Nazla Bushra

LSU Doctoral Dissertations

This hemispheric-scale, steering atmospheric circulation represented by the circumpolar vortices (CPVs) are the middle- and upper-tropospheric wind belts circumnavigating the poles. Variability in the CPV area, shape, and position are important topics in geoenvironmental sciences because of the many links to environmental features. However, a means of characterizing the CPV has remained elusive. The goal of this research is to (i) identify the Northern Hemisphere CPV (NHCPV) and its morphometric characteristics, (ii) understand the daily characteristics of NHCPV area and circularity over time, (iii) identify and analyze spatiotemporal variability in the NHCPV’s centroid, and (iv) analyze how CPV features relate …


Stochastic Navier-Stokes Equations With Markov Switching, Po-Han Hsu Mar 2021

Stochastic Navier-Stokes Equations With Markov Switching, Po-Han Hsu

LSU Doctoral Dissertations

This dissertation is devoted to the study of three-dimensional (regularized) stochastic Navier-Stokes equations with Markov switching. A Markov chain is introduced into the noise term to capture the transitions from laminar to turbulent flow, and vice versa. The existence of the weak solution (in the sense of stochastic analysis) is shown by studying the martingale problem posed by it. This together with the pathwise uniqueness yields existence of the unique strong solution (in the sense of stochastic analysis). The existence and uniqueness of a stationary measure is established when the noise terms are additive and autonomous. Certain exit time estimates …


Predictive Modeling Of Asynchronous Event Sequence Data, Jin Shang May 2020

Predictive Modeling Of Asynchronous Event Sequence Data, Jin Shang

LSU Doctoral Dissertations

Large volumes of temporal event data, such as online check-ins and electronic records of hospital admissions, are becoming increasingly available in a wide variety of applications including healthcare analytics, smart cities, and social network analysis. Those temporal events are often asynchronous, interdependent, and exhibiting self-exciting properties. For example, in the patient's diagnosis events, the elevated risk exists for a patient that has been recently at risk. Machine learning that leverages event sequence data can improve the prediction accuracy of future events and provide valuable services. For example, in e-commerce and network traffic diagnosis, the analysis of user activities can be …


Habitat Associations And Reproduction Of Fishes On The Northwestern Gulf Of Mexico Shelf Edge, Elizabeth Marie Keller Nov 2019

Habitat Associations And Reproduction Of Fishes On The Northwestern Gulf Of Mexico Shelf Edge, Elizabeth Marie Keller

LSU Doctoral Dissertations

Several of the northwestern Gulf of Mexico (GOM) shelf-edge banks provide critical hard bottom habitat for coral and fish communities, supporting a wide diversity of ecologically and economically important species. These sites may be fish aggregation and spawning sites and provide important habitat for fish growth and reproduction. Already designated as habitat areas of particular concern, many of these banks are also under consideration for inclusion in the expansion of the Flower Garden Banks National Marine Sanctuary. This project aimed to gain a more comprehensive understanding of the communities and fish species on shelf-edge banks by way of gonad histology, …


Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga Jun 2019

Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga

LSU Master's Theses

Throughout the history of oil well drilling, service providers have been continuously striving to improve performance and reduce total drilling costs to operating companies. Despite constant improvement in tools, products, and processes, data science has not played a large part in oil well drilling. With the implementation of data science in the energy sector, companies have come to see significant value in efficiently processing the massive amounts of data produced by the multitude of internet of thing (IOT) sensors at the rig. The scope of this project is to combine academia and industry experience to analyze data from 13 different …


Assessment And Correction Of Lidar-Derived Dems In The Coastal Marshes Of Louisiana, William M. Lauve Mar 2019

Assessment And Correction Of Lidar-Derived Dems In The Coastal Marshes Of Louisiana, William M. Lauve

LSU Master's Theses

The onset of airborne light detection and ranging (lidar) has resulted in expansive, precise digital elevation models (DEMs). DEMs are essential for modeling complex systems, such as the coastal land margin of Louisiana. They are used for many applications (e.g. tide, storm surge, and ecological modeling) and by diverse groups (e.g. state and federal agencies, NGOs, and academia). However, in a marsh environment, it is difficult for airborne lidar to produce accurate bare-earth measurements and even accurate elevations are rarely verified by ground truth data. The accuracy of lidar in marshes is limited by the sensor’s resolution …


Vulnerability Of Industrial Facilities In The Lower Mississippi River Industrial Corridor To Relative Sea Level Rise And Tropical Cyclone Storm Surge, Joseph Blake Harris Mar 2019

Vulnerability Of Industrial Facilities In The Lower Mississippi River Industrial Corridor To Relative Sea Level Rise And Tropical Cyclone Storm Surge, Joseph Blake Harris

LSU Doctoral Dissertations

Relative sea level rise (RSLR) and tropical cyclone-induced storm surge are major threats to the Lower Mississippi River Industrial Corridor (LMRIC) which has approximately 120 industrial complexes located within the corridor. Spatial interpolation methods were applied to the 2004 National Oceanic and Atmospheric published Technical Report #50 subsidence dataset and cross-validation techniques were used to determine the accuracy of each method. Digital elevation models (DEMs) were created for the years 2025, 2050, and 2075, based on these predictive surface of subsidence rates. Future DEMs were utilized to model RSLR and determine the extent of storm surge on the LMRIC by …


Numerical Study Of Liquid Atomization And Breakup Using The Volume Of Fluid Method In Ansys Fluent, Sai Saran Kandati Oct 2018

Numerical Study Of Liquid Atomization And Breakup Using The Volume Of Fluid Method In Ansys Fluent, Sai Saran Kandati

LSU Master's Theses

The spherical metal particles produced from the centrifugal atomization process have been the topic of numerous theoretical, experimental and numerical studies from the past few years. This atomization process uses centrifugal force to break-up molten material into spherical droplets, which are quenched into solidified granules by the flow of cold air on the spherical droplets. In the present work, a transient three-dimensional multiphase CFD model is applied to three different materials: Molten slag, aqueous glycerol solution, and molten Ni-Nb to study the influence of the dimensionless parameters on the centrifugal atomization outcome.

Results from numerical experiments indicated that the droplet …


Identifying Key Factors Associated With High Risk Asthma Patients To Reduce The Cost Of Health Resources Utilization, Amani Ahmad Oct 2018

Identifying Key Factors Associated With High Risk Asthma Patients To Reduce The Cost Of Health Resources Utilization, Amani Ahmad

LSU Master's Theses

Asthma is associated with frequent use of primary health services and places a burden on the United States economy. Identifying key factors associated with increased cost of asthma is an essential step to improve practices of asthma management.

The aim of this study was to identify factors associated with over utilization of primary health services and increased cost via claims data and to explore the effectiveness of case management program in reducing overall asthma related cost.

Claims data analysis for Medicaid insured asthma patients in Louisiana was conducted. Asthma patients were identified using their ICD-9 and ICD-10 codes, forward variable …


Predicting River Stage Using Recurrent Neural Networks, Eric Rohli Jul 2018

Predicting River Stage Using Recurrent Neural Networks, Eric Rohli

LSU Master's Theses

River stage prediction is an important problem in the water transportation industry. Accurate river stage predictions provide crucial information to barge and tow boat operators, port terminal captains, and lock management officials. Shallow river levels caused by prolonged drought impact the loading capacity of barges and tow boats. High river levels caused by excessive rainfall or snowmelt allow for greater tow capacities but make downstream transportation and lock management risky. Current academic river height prediction systems utilize either time series statistical analysis or machine learning algorithms to forecast future river heights, but systems that combine these two areas often limit …


Development Of A Slab-Based Monte Carlo Proton Dose Algorithm With A Robust Material-Dependent Nuclear Halo Model, John Wesley Chapman Jr Jun 2018

Development Of A Slab-Based Monte Carlo Proton Dose Algorithm With A Robust Material-Dependent Nuclear Halo Model, John Wesley Chapman Jr

LSU Doctoral Dissertations

Pencil beam algorithms (PBAs) are often utilized for dose calculation in proton therapy treatment planning because they are fast and accurate under most conditions. However, as discussed in Chapman et al (2017), the accuracy of a PBA can be limited under certain conditions because of two major assumptions: (1) the central-axis semi-infinite slab approximation; and, (2) the lack of material dependence in the nuclear halo model. To address these limitations, we transported individual protons using a class II condensed history Monte Carlo and added a novel energy loss method that scaled the nuclear halo equation in water to arbitrary geometry. …


Waste Management By Waste: Removal Of Acid Dyes From Wastewaters Of Textile Coloration Using Fish Scales, S M Fijul Kabir Apr 2018

Waste Management By Waste: Removal Of Acid Dyes From Wastewaters Of Textile Coloration Using Fish Scales, S M Fijul Kabir

LSU Master's Theses

Removal of hazardous acid dyes by economical process using low-cost bio-sorbents from wool industry wastewaters is of a pressing need, since it causes skin and respiratory diseases and disrupts other environmental components. Fish scales (FS), a by-product of fish industry, a type of solid waste, are usually discarded carelessly resulting in pungent odor and environmental burden. In this research, the FS of black drum (Pogonias cromis) were used for the removal of acid dyes (acid red 1 (AR1), acid blue 45 (AB45) and acid yellow 127 (AY126)) from wool industry wastewaters by absorption process with a view to …


General Stochastic Integral And Itô Formula With Application To Stochastic Differential Equations And Mathematical Finance, Jiayu Zhai Mar 2018

General Stochastic Integral And Itô Formula With Application To Stochastic Differential Equations And Mathematical Finance, Jiayu Zhai

LSU Doctoral Dissertations

A general stochastic integration theory for adapted and instantly independent stochastic processes arises when we consider anticipative stochastic differential equations. In Part I of this thesis, we conduct a deeper research on the general stochastic integral introduced by W. Ayed and H.-H. Kuo in 2008. We provide a rigorous mathematical framework for the integral in Chapter 2, and prove that the integral is well-defined. Then a general Itô formula is given. In Chapter 3, we present an intrinsic property, near-martingale property, of the general stochastic integral, and Doob-Meyer's decomposition for near-submartigales. We apply the new stochastic integration theory to several …


An Enhanced Bridge Weigh-In-Motion Methodology And A Bayesian Framework For Predicting Extreme Traffic Load Effects Of Bridges, Yang Yu Nov 2017

An Enhanced Bridge Weigh-In-Motion Methodology And A Bayesian Framework For Predicting Extreme Traffic Load Effects Of Bridges, Yang Yu

LSU Doctoral Dissertations

In the past few decades, the rapid growth of traffic volume and weight, and the aging of transportation infrastructures have raised serious concerns over transportation safety. Under these circumstances, vehicle overweight enforcement and bridge condition assessment through structural health monitoring (SHM) have become critical to the protection of the safety of the public and transportation infrastructures. The main objectives of this dissertation are to: (1) develop an enhanced bridge weigh-in-motion (BWIM) methodology that can be integrated into the SHM system for overweight enforcement and monitoring traffic loading; (2) present a Bayesian framework to predict the extreme traffic load effects (LEs) …


Using Generalized Estimating Equations To Analyze Repeated Measures Binary Data From The Young Adolescent Crowd Study, Lauren Ashley Beacham Jan 2012

Using Generalized Estimating Equations To Analyze Repeated Measures Binary Data From The Young Adolescent Crowd Study, Lauren Ashley Beacham

LSU Master's Theses

The young adolescent crowd study (YACS) was conducted in order to look at the influence of various factors on use of controlled substances by middle school students. The contributing factors investigated were demographics (gender and race), self-esteem in different modalities such as school or athletic performance, and the peer group students belong to. Each student has a binary response for whether they have used alcohol, marijuana or cigarettes which was recorded in both seventh and eighth grade. Since the data has a binary repeated measures response, generalized estimating equations (GEE) in a logistic regression setting is a good way to …


Investigating The Ironwood Tree (Casuarina Equisetifolia) Decline On Guam Using Applied Multinomial Modeling, Karl Anthony Schlub Jan 2010

Investigating The Ironwood Tree (Casuarina Equisetifolia) Decline On Guam Using Applied Multinomial Modeling, Karl Anthony Schlub

LSU Master's Theses

The ironwood tree (Casuarina equisetifolia), a protector of coastlines of the sub-tropical and tropical Western Pacific, is in decline on the island of Guam where aggressive data collection and efforts to mitigate the problem are underway. For each sampled tree the level of decline was measured on an ordinal scale consisting of five categories ranging from healthy to near dead. Several predictors were also measured including tree diameter, fire damage, typhoon damage, presence or absence of termites, presence or absence of basidiocarps, and various geographical or cultural factors. The five decline response levels can be viewed as categories of a …


Two-Dimensional Penalized Signal Regression For Hand Written Digit Recognition, Qing Tang Jan 2006

Two-Dimensional Penalized Signal Regression For Hand Written Digit Recognition, Qing Tang

LSU Master's Theses

Many attempts have been made to achieve successful recognition of handwritten digits. We report our results of using statistical method on handwritten digit recognition. A digitized handwritten numeral can be represented by an image with grayscales. The image includes features that are mapped into two-dimensional space with row and column coordinates. Based on this structure, two-dimensional penalized signal logistic regression (PSR) is applied to the recognition of handwritten digits. The data set is taken from the USPS zip code database that contains 7219 training images and 2007 test images. All the images have been deslanted and normalized into 16 x …